Congrats on choosing and making it into NUS Business School! I previously wrote here: https://www.reddit.com/SGExams/comments/118r7cg/all_about_studying_business_in_nussmuntu/ on what are some factors when considering between NUS, SMU and NTU business school. For better or worse, you'll be stuck here for the next 4 years so here's some broad advice on making the best out of it.
1. Put in effort to draft out your own Study Plan; Future you will thank you
What is a study plan? Essentially, it's an outline on what modules you'll be taking throughout your 4 years in University. Especially for a business student, a study plan should go beyond "what majospecialization/double majominor". Yes, figuring what major (or majors) that you want to eventually take is the first step. The next step is also considering whether you intend to take a gap semester (i.e. leave-of-absence) to do internships (which is becoming increasingly more common place; maybe not 1 gap sem but possibly even 2!). The unfortunate truth is that many biz student realize late in Year 2/3 that they might not be as competitive as their peers and usually then seek out LOA internships and end up delaying their graduation (whether its a good or bad thing is debatable). Besides gap semesters for internships, there are student who do credit bearing internships (which counts for some credits/MCs) or even do a part-time internship during the semester while studying (Do modules on Mon and Tues, FT work of Wed, Thurs, Fri). Not every student get's their desired summer internships, and often student have to compensate by applying for Off-Cycle LOA internships.
In your study plan, you would also have to take into consideration possibly going on overseas semester exchange or even the 6M to 1 Year long NOC program if you're interested! Overloading more modules earlier in your Uni (Y1 and Y2) gives you more flexibility to adapt to changes in the future. Of course, you need to gauge yourself whether you're able to cope with the workload. (Overloading in earlier sems, mean being more free in later sems to do internships/explore other modules or minors).
Additionally, most higher-level modules have pre-requisites (mostly ACC1701). If you delay taking these pre-requisite modules, your whole study plan can be delayed by a semester. My advice is to take ACC1701 (and consequently FIN2704) earlier rather than later, because these two mods open up the other majors/specializations available to you. You'll also figure out whether you'll want to to take the finance major after taking these two modules.

1. CCAs

There's a ton of CCAs available NUS-wide or Business School related. I strongly encourage you to take multiple CCAs (importantly taking into consideration what you can manage and your workload) so that you're able to meet new people and learn new skillsets. NUSC/RCs/Hall activities also count here. The unfortunately truth is that portfolio does matter in business school, and simply being good in academics (which can be competitive in itself) isn't enough. Your GPA/CAP allows you to have your foot in the door; your portfolio and experience allows you to enter it. Consulting CCAs in general are great an improving your eye for aesthetic and detail which I recommend. You'll be surprised that many biz kids are outright bad and atrocious at making PowerPoint slides even at Year 4... I would say that the CCAs you join do shape your uni experience in a large way.

1. Group Mates

Find good friends and group mates! Those in NUSC/RCs/Halls have an easier time for this. For most of your basic core 1k modules, you group is usually randomized and you have no say on who you're working with. It is during these randomized group that you'll figure out the pain of having poor group mates, and things get worse if you're taking higher level and tougher modules alone. On this note, try to find friends that will do various modules together with you! Having friends doing the module together with you is a huge advantage, from extra resources, dead line reminders, doing quizzes/tests together etc. 5 brains working on a problem set is always better than 1 brain by itself, these 5 ppl will often get a better grade than the one hardworking individual working alone. Implicitly, those who stay on campus have a huge edge over those who don't.

1. Business is ultimately not a technical degree

Controversial to some, but business school at the end of the day doesn't really teach you much. The only thing that it does teach is showmanship (and even then sometimes not taught well enough). Business School arguably teaches you how to carry yourself well, make fancy PowerPoints, use some excel, working with people (?) etc. Many of the more relevant things you learn, you learn them in your internship and your own experiences outside of the classroom e.g. CCAs. To me, doing well in Biz School is focusing on everything outside of academics (ensuring that you have some baseline CAP/GPA).
5. Figure out early whether you prefer Excel or Power Point.
The corporate world only runs on two applications, Excel and Power Point. Dabble in both, figure out early which application you prefer more and find a relevant internship/role/job that you enjoy decently that uses one over the other. Truly, Excel and PPT are the only takeaways when you leave the university. Great consultants are adept at handling PPT, navigating through them quickly with many templates in their desktops. Finance peeps do a little more excel work and have to do them well, fast and creatively. Even at the end of uni, there are still many students who can't use excel proficiently at a high level.
6. Internship Hell is real for those who care
Internship application period in itself can be a full-time commitment (for those that care). When internship applications open, you can be going through your own interview prep, doing several recorded interviews, applying to new internships etc. Many moving parts to juggle and a lot of ground work to be done. From preparing for interview questions, writing cover letters, tailoring your CV etc alot of the hell you experience in Biz school actually comes outside of academics contrary to popular belief (as Jean-Paul puts it, "hell is other people", bad group mates im looking at you). For those applying to more technical roles, you might also need to prep extra for technical questions e.g. IB 400 questions, consulting cases, market sizing brain teasers etc.
7. Not so much of an advice, but rather a plea from me to you
I really hope business students can be more code literate and savvy i.e. being able to read (and to a lesser extent implement) coding e.g. python or SQL. ~90% of the biz population are code illiterate (having only taken just 1 "coding module"). In a normal corporate workplace, you'll never have to code. But being able to think computationally, knowing the steps you can take to automate your task, time and workflow brings you more benefits than you can imagine when most corporate work that people do are typically administrative.
In conclusion, do your best in biz school. I think effort correlates strongly to how well you do here. You don't need to be smart (it makes life easier) but with enough forward thinking and future planning, you'll be able to grow through the next 4 years (and hopefully be worth it).
Feel free to ask any question in the comments, or for any seniors to elaborate and share their own experience! Left out a lot of controversial views not wanting to trigger anyone or NUS. Edit: I'm a graduating student from Biz, later they dont let me grad how? jk
Some extra links:

1. An event calendar regularly updated by NUS Careers, usually has lots of interesting and relevant events, competitions, webinars (if that's your thing): https://nus.edu.sg/cfg/events
2. Grading rubrics to apply for SEP, there is an actual rubrics to secure an SEP, please refer for those wanting to go: https://bba.nus.edu.sg/wp-content/uploads/sites/37/2019/07/SEP-Place-Allocation-Grading-System-2018-10.pdf

Abstract
The quantum consciousness theory, particularly the Orchestrated Objective Reduction (Orch-OR) model proposed by Roger Penrose and Stuart Hameroff, posits that consciousness arises from quantum processes within brain microtubules. This paper addresses the theoretical foundations, significant empirical challenges, and potential experimental approaches to validate this theory, specifically focusing on a consciousness wave function as described by a mathematical model. We propose a series of interdisciplinary studies designed to detect quantum coherence in neural structures, investigate the effects of anesthetics on quantum states, and explore the computational advantages of quantum neural networks. By advancing our understanding of quantum biology and integrating insights from physics, neuroscience, and cognitive science, this research seeks to provide a plausible framework for the quantum basis of consciousness.
Introduction
The nature of consciousness remains one of the most profound and elusive questions in science. Traditional neuroscience views consciousness as an emergent property of complex neural processes. However, the quantum consciousness theory, particularly the Orch-OR model, suggests that quantum mechanical phenomena play a crucial role in conscious experience. This theory proposes that consciousness arises from quantum computations within microtubules, which are key components of the cytoskeleton in neurons​ (Wikipedia)​​ (Center for Consciousness Studies)​.

Theoretical Background

The consciousness wave function, ΨΨ, as depicted in the attached image, is described by the equation:
see attached Image: A
https://preview.redd.it/rfcva5mn5d1d1.png?width=936&format=png&auto=webp&s=e25ed51268c38e0167a7f6f933a6d48ff5051704
This equation integrates exponential decay, trigonometric modulation, and sinusoidal perturbations to model the spatial and temporal distribution of consciousness.

Quantum Coherence in Biological Systems

Recent advancements in quantum biology have provided evidence that quantum coherence can exist in biological systems despite the challenges posed by thermal noise. Examples include the role of quantum coherence in avian navigation and photosynthesis, suggesting that biological systems can exploit quantum effects​ (Wikipedia)​​ (Center for Consciousness Studies)​.

but to a point that I feel that they've been present in my whole life.
I'm trying to discern if this is also a thing that NT people do but I realized that in my whole life I've been bothered by blanket statements, to an extent that it has lead to MANY heated arguments with my friends and family and people around me because I didn't care where they came politically... I couldn't stand blanket statements and stereotypes, they would just bothered me so much and made me feel anxious... even if they would came from opposite political views at the time (so my friends wouldn't understand why I would defend it). To an extent that I would hate any joke based on stereotypes. To an extent that I would spend hours and hours all day reading statistics for all the things and learnt statistics (and deep learning later because it's like regression but better) by my own (my very thing is computers and programming) because I loved understanding the correlation between the things, even between the smallest things. I have side projects related to statistics to see the correlation between keywords because how obssesed I was.
For years I was also obsessed trying to figure out the correlation using regression for stupid things that at the time I thought were useful, like the things my mother came home angry and we would end up having an argument, or between my coffee temperature and bitterness, or when I realized that my induction cooker would display energy consumed and I started collecting data points for boiling temperature, time and energy spent to find out the correlation.
I feel like I'm obsessed with the truth and connections behind everything, but in the last few years I gave it up because I realized I was arguing with everyone (family, friends, online...) and being very pedantic about stupid things. I argued with my best friend a lot, she isn't interested in statistics but I would send her walls of texts with data of the things we discussed and she was like why would you do that. I don't even know how she can stand me through these years.
I don't know, it's something I've realized recently that I've been doing all my life and wanted to share it. Is this a thing NT people do too?

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Looking for academic help? We provide a wide range of services to support your academic and professional needs. Our offerings include:

• Web Development
• Essay Writing
• Game Development
• Assistance with Online Classes
• Matlab Assignments
• Research Proposals
• Thesis Support
• Computer Science Projects
• Statistical Analysis using SPSS & RStudio

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Email: assighnmentdomain@gmail.com Discord: domain_ezo Telegram: @Zaer_ezo

I messed up. I messed up bad.
“Never get high on your own supply”. The human who sold me this data told me it was a saying from his world. But I had to be sure it was the real deal. After all, data drugs that worked on people without a brain interface installed? It was unheard of. But here I am [30 hours] later, and I no longer doubt. I feel utterly exhausted despite having barely moved. My every neuron feels fried. All 6 grasping appendages are sore from the repetitive motions, and my eyes are dry and unfocused from the long strain I have put them through. I feel intense pangs of hunger and thirst, as I haven’t eaten or drank since I started this test.
I still want more. But with a great effort of will I force myself away from the screen of my computing terminal and stumble to my pantry so I may attend to my body’s needs. As I gulp down nutrient drinks and chew some dried fruit, I reflect on the trance I’ve somehow barely managed to pull myself out of.
Simulations. A useful tool for engineers, scientists, and military strategists. We had never thought to teach storytellers or artists to use them. Humans had. And what they created was both miraculous and monstrous.
Humans decided to use simulation technology to create art and craft stories. It seemed that there was a human simulation… no, hundreds of human simulations, designed to invoke whatever feeling or emotion you could imagine. And possibly some you couldn’t.
I had started simple. A basic test of spatial reasoning, and later quick thinking, expressed through the medium of stacking colored blocks formed into geometric shapes. While comparable at first to a children's toy, as the speed and challenge increased I became increasingly hypnotized. The feeling of lining up and clearing four rows at once with the all too rare straight piece was intensely satisfying. Making a mistake, leaving a gap caused frustration and incompleteness like I had never felt before, and eventually fixing it gave a feeling of relief, of rightness. As the game sped up, I found myself more and more frantic to try and find places for every piece. The rush of success and agony of failure only increased as I prided and chided myself on my quick decisions.
Eventually, I could keep up no longer, leaving me only with a number. A score.
Could I push that score higher?
[4 hours] went by, and I barely noticed.
I should have stopped. I knew that what I had was genuine. But I wanted to know what else this data was capable of.
I navigated a colorful landscape, defying gravity with every action and finding joy in exploration and collection.
I slaughtered demons with a chaingun, turning the fear of being devoured into a rising sense of conquest and bloodlust.
I failed a single test of dexterity, sending me tumbling down a hole and erasing hours of progress, and I nearly knocked myself out from the shock of frustration.
I defeated a hulking warrior with a team of other adventurers, and the triumph of it was only amplified by the sting of failing several times before.
Freedom and entrapment.
Horror and domination.
Elation and sorrow.
Every new experience was an emotional high of a kind I’d never had before, and my hearts were racing with the myriad of feelings rushing through my mind. My imagination was going wild with the possibilities of all these new worlds of data and programming.
My self-reflection comes to a grinding halt. I need to stop. If I’m not careful I’ll get addicted and end up like one of those mindjackers, burning their brains out on data drugs. Supposedly these simulations can’t do that, but I wouldn’t have put it past the seller to lie about that kind of thing.
Well, one way or another, I’m gonna make a [alien animal that shares many traits with both giant squids and magpies]’s hoard selling these. Time to call my best clients…
[Time skip: approximately 25 solar years]
The Rise of the Galactic Game Industry: Fluke of the Black Market, or Human Marketing Genius? You Decide!
Dr’k-Nam, Head Investigative Critic for the Arts and Culture section of Twin Suns Newsgroup
Simulation games, also known as “video games”, have taken the galaxy by storm ever since their controversial introduction and subsequent series of bannings and legalizations across the galaxy. Simulation technology is nothing new of course, but galactic newcomers from the Sol system, Humans, used it in an extremely novel way: art and entertainment. According to their historical records, a significant amount of their entertainment industry is based around simulation games, and that portion has grown even further with their introduction to the galaxy at large.
At first, however, no one was interested. A simulation with little or no practical application, designed only to entertain? Most people preferred to stick with the entertainment they knew, or seek new experiences outside of sims. So what changed?
Simple: some anonymous human decided to sell them as data drugs instead of simulation games; data drugs usable by simply interacting with a computer program, rather than having to inject the data directly in through a neural interface. With this small, but completely false new branding, video games were ready to start spreading across virtual black markets like spoilers for the latest episode of Ace Flyer Kr’t-Kah on the galnet (side note: please have some courtesy to others and tag your spoilers).
Human governance and society at large had been reportedly as surprised to see a lack of simulation games from other species as they were that humans had them. But they were even more surprised when they started getting accused of pushing the latest data drug. This was an especially confusing accusation because neural interface technology was not widely adopted by humanity at the time, and only a fraction of a percent of their population even knew of the existence of data drugs in the first place. The revelation that most humans had video games of some sort on their PPDDs (personal portable data devices) threatened to cause an uproar in the galaxy, as paranoia around data drugs was at an all time high among many species.
After trying and failing to ignore the problem for long enough for it to go away, human governance, as well as human corporations producing video games, were forced to release statements, acknowledging that:

• Yes, video games were human productions.
• Yes, they could be addictive in the same way that any other pleasure-seeking activity could be addictive.
• Yes, there are games that even humans ban. Adult subject matter is restricted from youths, but additionally, games could be made manipulatively to exploit or develop gambling addictions, which is banned outright. Technically this ban isn’t even for games specifically, but instead falls under the purview of their laws against taking advantage of the mentally unstable.
• No, they did not “hack your brain” to cause neural impulses, unless you’re a a Syns-nah, who only partially exist in our dimension and are not used to any 3-dimensional sensory inputs, to the point where eating an unflavored [grain product resembling a cracker] can cause them vivid hallucinations.
• If other races want to ban them, go ahead, but humans can’t really stop data from spreading (their government has tried, believe me), and they’re not going to stop making or distributing them where it’s legal.

Ironically enough, the controversy made them much more popular, even in places that decided on banning them. The idea of a simulation that could act like a data drug without the risk of frying your mind like the real thing was enticing to many. The lack of side effects and ease with which the games could be distributed only increased both their spread and unregulatability. In short order, races throughout the galaxy were trying out a new pastime, and galnet connected multiplayer games were bridging the gaps between the stars. Now, several other races, including my own, are seeking advice from human developers in starting their own simulation game projects. Only time will tell what kind of games their unique perspectives will produce, but it’s unlikely that humans will lose their position as the most powerful and profitable storytellers through this new medium; they have generations of experience to draw upon, after all.
Rumors that the data drug sales pitch was a deliberate ploy by the human game industry (to drum up intergalactic sales) or by human governance (to spread human culture and influence) are still under investigation, but solid evidence for either has yet to emerge.
Edit: anyone posting untagged Ace Flyer Kr’t-Kah spoilers in the comments section of this article will receive an immediate, no-warning permaban.

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STATISTICS HELP (MY BEST SUBJECT):

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THE OBLIGATORY "IS THIS A SCAM?" QUESTION:
Considering the fact that you found my contact information online, it’s understandable to be skeptical regarding the legitimacy of my services. Therefore, I’m willing to do all of the following to help you feel more secure in trusting me with your academic needs:

• 1) Speak with you on the phone and answer any questions you may have so that you have the opportunity to assess and analyze my tone, articulation, accent, diction, dialect, regionalisms, pitch, vocabulary, word choice, intonations, and inflections.
• NOTE: I’m a New Jersey-born Irish/Italian-American, but I have been told that I speak in an erudite & articulate suburban American accent with a “professor style” voice somewhat resembling the voice of actor: Ben Stein.
• 2) Agree to do some homework questions of yours upfront with the work fully shown in real-time to prove my mastery of the course content.
• 3) Send you screenshots of at least five past scores I attained from completing exams & homework assignments for other students in the same type of class you need help with.
• 4) Send you full screenshots of written exam solutions I wrote up by hand for students in the past in the same course that you need help with so that you can see my neat handwriting.
• 5) Provide you with the contact information of students who have utilized my services in the past who would be more than willing to vouch for my skills.

MY REBUTTAL TO THE OBLIGATORY “IS THIS A SCAM?” QUESTION:
At the risk of sounding arrogant, I consider myself to be at least marginally more intelligent (both academically & socially) than the average person. Therefore, if I ever decided to suddenly risk prison time, risk my reputation, and risk enduring the wrath of modern-day “cancel culture” by scamming people out of their money:

• I certainly wouldn’t do it for such paltry amounts of money. (i.e., anything less than $1,000 per victim.)
• I certainly wouldn’t choose high school & college students as my “target audience” to scam, considering that most people without college degrees have abysmally low annual incomes. Why choose low-income victims when it would be much more profitable to target high-income, high-net-worth individuals earning at least six figures a year? I have knowledge in business consulting, and I promise you that a business owner would be a MUCH more lucrative mark than a low-income college student.
• I wouldn’t choose such a time & energy-draining method of scamming people. Also, communicating back and forth with potential clients is an absurdly long time sink since only less than 10% of all potential clients who reach out to me actually become paying clients of mine. This means that 90% of my time communicating with potential clients ultimately proves to be a colossal waste of my irretrievable time & energy.
• If you pay me to provide academic services and I don’t deliver, you can always dispute the payment with the payment app and easily get your money refunded. If I were in the habit of swindling money from people, then all of my payment accounts would have been investigated and be completely shut down by now. And I would have been permanently banned from opening new accounts. Therefore, the fact that all my payment apps have been fully active for years should be sufficient proof that I haven’t had people consistently disputing payments sent to me.

HOW TO CONTACT ME:
Paid Help from Hiraedu: If You're struggling to handle your Online Exams, Assignments or any other coursework, get help from Hiraedu and pay after the exam. Contact details for Hiraedu is: WhatsApp: +1 (213) 594-5657 OR Call: +1 727 456 9641

• I take my work as a tutor very seriously, and I always aim to do my best to help my students excel in school. I have a solid and sincere passion for academic achievement, and with my help, I am positive that I can help students obtain very high grades with minimal stress and effort.
• Please feel free to contact me if you're interested in my services and would like to learn more. I'm available 24/7 via phone call, email, and text. Again, thank you for taking the time to read my Reddit tutoring ad, and I hope to hear from you soon!

My contact details:
WhatsApp: +1 (213) 594-5657
Call: +1 727 456 9641
Website: hiraedu. com
Email: [info@hiraedu](mailto:info@hiraedu). com
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Looking for academic help? We provide a wide range of services to support your academic and professional needs. Our offerings include:

• Web Development
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ASSESSMENTS I CAN COMPLETE:

• Online Courses (1 - 20 Weeks Long)
• Homework Assignments
• Exams Quizzes Tests
• Excel Projects
• Discussion Forum Posts
• Research Papers Term Papers Essays
• Employment Assessments

MY MATH SUBJECTS OF EXPERTISE:
I am very knowledgeable and proficient in assisting students in a wide range of mathematics classes. I can help students complete their homework assignments and other projects get an A on quizzes, tests, and exams (including proctored assessments) answer online discussion posts write essays & papers in MLA APA Chicago format and provide general overall academic help in each math course listed below:

• Advanced Placement Honors High School Level Math
• AP Calculus AB A.P. Calculus BC
• AP Statistics
• Biostatistics Bio-Statistics
• College Algebra Intermediate Algebra
• Business Calculus
• Business Statistics
• Business Math
• Calculus I Calculus II Calculus III (Calc)
• Geometry
• International Baccalaureate (IB) Maths
• Liberal Arts Math
• Logic & Reasoning
• Multivariable Calculus Multi variable Calculus
• Precalculus Pre-calculus
• Probability & Statistics
• Psychology Statistics Psych Stats
• Quantitative Reasoning Quantitative Methods Quantitative Literacy (Quant)
• Statistics (Stats)
• Statistics for Social Sciences
• Trigonometry (Trig)

STATISTICS HELP (MY BEST SUBJECT):

• I have a master's degree in Applied Statistics from a university in New Jersey, USA. As a result, I am very proficient in helping students with various types of Statistics courses including Biostatistics Business Statistics Elementary Statistics Probability & Statistics Psychology Statistics.
• I have extensive knowledge and skill with helping students get through various statistical concepts including all of the following in alphabetical order:
• ANOVA Bar Graph, Boxplot, Dot Plot, Histogram, Pie Chart Bias Binomial, Exponential, Poisson, Gamma, Uniform Distribution Central Limit Theorem Chi-Square Test Coefficient of Determination (R^2) Conditional & Relative Probability Confidence Interval Correlation Coefficient (r) Critical Region Critical Value Descriptive & Inferential Statistics Effect Size Expected Value Experiment vs Observation Goodness of Fit Test Hypothesis Testing Interpolation & Extrapolation Interquartile Range (IQR) Kurtosis Left, Negative, Right, Positive Skewed Distribution Logistic Regression Mean, Median, Mode, Midrange Multiple Regression Nominal, Ordinal, Interval, Ratio I Population Parameter Normal, Symmetric & Bell Shaped Distribution Null & Alternate Hypothesis One & Two Sample T-Test One & Two Sample Z-Test Ordinary Least Squares Outliers P-Value Pooled Variance (Equal Variances) Proportion R^2 Range Regression Regression Line Reject & Fail to Reject Ho Relative & Cumulative Frequency Distributions Relativity & Reliability Right, Left, One, Two Tailed Tailed Hypothesis Test Sample Statistics Sampling Methods (Convenience, Stratified, Simple, Cluster, Systematic) Significance Level (1%, 5%, 10%) Skewness Standard Deviation& Variance T-Score Test Statistic Time Series Type I & Type II Errors Unbiased Estimators Z-Score

ALGEBRA HELP:

• I am well-versed in helping students do well in Algebra 1 & 2 College Algebra Intermediate Algebra Pre-Algebra and I am very knowledgeable and proficient in the following algebra topics in alphabetical order:
• Absolute Values Circle Equation Domain Exponents Graphing Horizontal & Vertical Asymptotes Inequalities, Equations & Functions Inverse Functions Linear, Exponential, Logarithmic, Quadratic Equations Logarithms Maximum & Minimum Values of a Graph Number Lines One-to-One Functions Parallel & Perpendicular Lines Plotting Points & Ordered Pairs Point-Slope Form Polynomial Division Polynomials Radicals Range Rational & Irrational Expressions Rational Functions Real Roots Real Zeros Relations & Functions Slope Slope-Intercept Form Square Roots Standard Form of a Line System of Equations System of Inequalities Variables X and Y Intercepts

CALCULUS HELP:

• I am well-versed in helping students do well in Calculus I, II & III, Calculus 1, 2 & 3, Business Calculus, Multivariable Calculus, Vector Calculus and I am very knowledgeable and proficient in the following calculus topics in alphabetical order:
• Absolute & Local Maximum and Minimum Antiderivative Area & Volume Chain Rule Concavity Continuity Convergence Test Critical Points Curvature Curve of Rotation Curve Sketching Derivatives Divergence Test First & Second Derivative Test Fourier Series Implicit Differentiation Increasing / Decreasing Functions Infinite Series Integrals Integration by Parts Jacobian Matrix Limits L’Hopital’s Rule Maclaurin Series Mean Value Theorem Partial Derivative Product & Quotient Rule Reiman Sum Related Rates Simpson’s Rule Solid of Revolution Substitution Rule Taylor Series

Paid Help from Hiraedu: If You're struggling to handle your Online Exams, Assignments or any other coursework, get help from Hiraedu and pay after the exam. Contact details for Hiraedu is: WhatsApp: +1 (213) 594-5657 OR Call: +1 727 456 9641
ATTRIBUTES THAT SET ME APART FROM OTHER TUTORS:

• I firmly believe that I have many attributes and skills that set me apart from other tutors. Below is a list of qualities that makes me an ideal fit to help you master your coursework:

I CAN AID STUDENTS TAKING PROCTORED ASSESSMENTS:

• Proficient in CollegeBoard AP Calculus AB, AP Calculus BC & AP Statistics exams.
• Skilled with International Baccalaureate Math Exams: IB Maths HL & IB Maths SL
• Can intentionally answer a few problems incorrectly at the student's request.
• Can text solutions to the student while they are taking a proctored exam.
• Upon request, can purposely obtain grades below an A (ex: B+, B, C+, C-).
• I can stretch out the time to a plausible length for timed exams and assignments before submitting them.
• Have reliable software that can change my IP address to match the closest major city near the student.
• I have exceptional multiple-choice exam-taking skills. I have mastered the various techniques to make calculated guesses for the correct option in standardized exams such as the SAT & GRE.

I CAN VERIFY MY ACADEMIC KNOWLEDGE & SKILLS:

• I have no problem with requests to solve sample problems upfront to prove my knowledge & proficiency of the course concepts.
• I can provide glowing references & strong examples of work done for past clients to verify my academic skills.
• I can also provide, upon request, complete detailed calculations with explanations for solutions to the problems worked on.
• I am quite skilled and adept in using multiple modernized educational platforms and software, including but not limited to: Brightspace MyStatLab D2L WebAssign Canvas MyMathLab Blackboard ALEKS
• Can format term papers and discussion posts in APA MLA Harvard Chicago Vancouver OSCOLA IEEE format.

I HAVE PAID ACCESS TO OVER 15 STUDY-HELP WEBSITES AND MATHEMATICAL SOFTWARE:

• I have multiple paid subscriptions to a wide range of academic tutoring resources, including Chegg, Quizlet, CourseHero, Brainly, Grammarly, Study. com, Bartleby, Slader, Transtutors, Slideshare, StudocU, Turnitin, Academia, SymboLab, WolframAlpha, and Scribd to help guide to solve exam & homework questions that I may not immediately know.
• However, I am smart enough not to blatantly plagiarize solutions online but instead write them in my own unique words, formatting, & mathematical terminology.
• I have access to a very sophisticated graphing calculator and various mathematical software that provides step-by-step solutions to complex mathematical problems within seconds, allowing me to provide exact solutions to the student in a timely manner.
• I have impeccable handwriting and a high-quality mobile scanner app that allows me to scan written solutions in very legible high-definition JPG, PNG, or PDF formats.

MY AVAILABILITY & RELIABILITY:

• Depending on my availability, I can accommodate immediate tutoring requests, 1-24 hour, and 1-30-day deadlines.
• I can schedule live real-time online sessions and meet deadlines in an impressively timely fashion.
• I can provide quick notifications and updates of progress made in the student's class via email text phone calls.
• I can also be available to tutor students for Fall 2021 Spring 2022 Summer 2022 semesters.

MY EDUCATIONAL SOFTWARE OF EXPERTISE:

• I am very knowledgeable and well-versed in a wide range of educational software to tutor students in including but not limited to: Acellus ALEKS APEX Learning Aplia Blackboard Brightspace Canvas Cengage CengageNow Connect ConnectMath Connexus CPM D2L Discord Edmentum Eviews Examity Excel Hawkes Learning Honorlock Khan Academy Knewton LimeSpring Lumen Maple MasteringChemistry MasteringPhysics MathXL (XL) MATLAB McGraw-Hill Microsoft Word Minitab Moodle MyAccountingLab MyEconLab MyITLab MyLab My Lab MyMathLab My Math Lab MyOpenMath MyPsychLab MySocLab MyStatLab My Stat Lab NCSS Open Source Software Pearson PERT PlatoWeb PowerPoint Prezi R Respondus Lockdown Browser with Webcam Sapling SPSS Stata StraighterLine Straighter Line WebAssign Web Assign Webex (Cisco) WebWork Wiley WileyPlus Wonderlic Zoom

SCHOOLS FROM WHICH I'VE HELPED STUDENTS IN :
As of 2021, I have tutored and helped students enrolled at the following U.S. universities community colleges county & city colleges schools for-profit institutions listed below in alphabetical order:

• A - C: American Public University System (APUS) Arizona State Ashford Brigham Young Brown Broward California State (Fullerton) Capella Chamberlain (Illinois) Colorado Technical Columbia Columbia Southern Cornell
• D - K: Dallas College Dartmouth DeVry Excelsior College Florida International Florida State Full Sail Georgia State Grand Canyon Harvard Houston Community College Ivy Tech Community College Kaplan Kennesaw State Kent State
• L - T: Liberty Lone Star College System Kaplan Miami Dade Michigan State CUNY State University of New York (SUNY) Northern Virginia Ohio State University of Phoenix (UOP) Penn State Princeton Purdue (Davenport) San Diego State San Francisco State San Jose State Southern New Hampshire Southern Nevada Stanford St. Petersburg Strayer Texas Tech
• UNIVERSITY OF: Alabama Arizona California (UC) Central Florida Chicago Cincinnati Florida Houston Illinois (Urbana-Champaign) Iowa Maryland Minnesota Michigan North Texas Pennsylvania Southern Florida Texas Toronto
• U - Z: UCLA Extension Utah State Utah Valley Valencia Walden U Wake Technical Western Governors Wilmington Yale

Paid Help from Hiraedu: If You're struggling to handle your Online Exams, Assignments or any other coursework, get help from Hiraedu and pay after the exam. Contact details for Hiraedu is: WhatsApp: +1 (213) 594-5657 OR Call: +1 727 456 9641
I OFFER FLEXIBLE PAYMENT PLANS:

• I offer several unique payment plans, including a weekly plan, a discounted monthly plan, a discounted half-now / half-later plan, and highly discounted up-front rates.
• I can accept the following payment methods for my services: PayPal Debit Cards Square Cash Credit Cards Cash App Venmo.
• Only people located in North America have access to Venmo Cash App Zelle.
• This is an excellent way to determine if the person you're dealing with is from the United States.
• Within reason, I offer a partial or full money-Back guarantee if the student is very unsatisfied with my academic services.

TUTORING AVAILABLE FOR OTHER SUBJECTS:

• For other subjects, you can reach out to me, and I can connect you with one of my tutoring partners who can provide general academic assistance for the following subjects:
• Art & Design: Art History Design Film Studies
• Business: Accounting (Acc) Biz Courses Business Administration (Biz Admn) Business Calculus Business Law Business Statistics Corporate Finance Economics (Econ) Finance (Fin) Financial Accounting Intermediate Accounting Intermediate Microeconomics (Micro) Macroeconomics (Macro) Management (Mgmt) Managerial Accounting Marketing MBA
• Computer Science: C C++ Computer Programming (Comp) Java Python R (Introduction & Intermediate Level Only)
• Humanities: Communications (Comm) English Literature Essay & Term Paper Writing, Editing, Proofreading Essays History Papers Philosophy (Phil) Religious Studies Theology (Theo)
• Mathematics: A.P. Calculus AB & BC Psychology Statistics AP Statistics Bio statistics Calculus I (1) Calculus II (2) Calculus III (3) College Algebra Differential Equations Discrete Math Finite Math Functions General Math Geometry Liberal Arts Math Linear Algebra Multi-variable Calculus Partial Differential Equations Precalculus Probability Quantitative Reasoning Real Analysis Statistics Trigonometry (Trig) Vector Calculus
• Science & Medicine: Anatomy & Physiology (A & P) Biochemistry Biology (Bio) Biostatistics Earth Science Environmental Science General Chemistry (Chem) Healthcare Medicine Nursing Nutrition Organic Chemistry Physics (Phys)
• Social Sciences: Anthropology Economics (Econ) Geology Law & Justice Liberal Arts Liberal Studies Political Science Psychology Sociology

THE OBLIGATORY "IS THIS A SCAM?" QUESTION:
Considering the fact that you found my contact information online, it’s understandable to be skeptical regarding the legitimacy of my services. Therefore, I’m willing to do all of the following to help you feel more secure in trusting me with your academic needs:

• 1) Speak with you on the phone and answer any questions you may have so that you have the opportunity to assess and analyze my tone, articulation, accent, diction, dialect, regionalisms, pitch, vocabulary, word choice, intonations, and inflections.
• NOTE: I’m a New Jersey-born Irish/Italian-American, but I have been told that I speak in an erudite & articulate suburban American accent with a “professor style” voice somewhat resembling the voice of actor: Ben Stein.
• 2) Agree to do some homework questions of yours upfront with the work fully shown in real-time to prove my mastery of the course content.
• 3) Send you screenshots of at least five past scores I attained from completing exams & homework assignments for other students in the same type of class you need help with.
• 4) Send you full screenshots of written exam solutions I wrote up by hand for students in the past in the same course that you need help with so that you can see my neat handwriting.
• 5) Provide you with the contact information of students who have utilized my services in the past who would be more than willing to vouch for my skills.

MY REBUTTAL TO THE OBLIGATORY “IS THIS A SCAM?” QUESTION:
At the risk of sounding arrogant, I consider myself to be at least marginally more intelligent (both academically & socially) than the average person. Therefore, if I ever decided to suddenly risk prison time, risk my reputation, and risk enduring the wrath of modern-day “cancel culture” by scamming people out of their money:

• I certainly wouldn’t do it for such paltry amounts of money. (i.e., anything less than $1,000 per victim.)
• I certainly wouldn’t choose high school & college students as my “target audience” to scam, considering that most people without college degrees have abysmally low annual incomes. Why choose low-income victims when it would be much more profitable to target high-income, high-net-worth individuals earning at least six figures a year? I have knowledge in business consulting, and I promise you that a business owner would be a MUCH more lucrative mark than a low-income college student.
• I wouldn’t choose such a time & energy-draining method of scamming people. Also, communicating back and forth with potential clients is an absurdly long time sink since only less than 10% of all potential clients who reach out to me actually become paying clients of mine. This means that 90% of my time communicating with potential clients ultimately proves to be a colossal waste of my irretrievable time & energy.
• If you pay me to provide academic services and I don’t deliver, you can always dispute the payment with the payment app and easily get your money refunded. If I were in the habit of swindling money from people, then all of my payment accounts would have been investigated and be completely shut down by now. And I would have been permanently banned from opening new accounts. Therefore, the fact that all my payment apps have been fully active for years should be sufficient proof that I haven’t had people consistently disputing payments sent to me.

HOW TO CONTACT ME:
Paid Help from Hiraedu: If You're struggling to handle your Online Exams, Assignments or any other coursework, get help from Hiraedu and pay after the exam. Contact details for Hiraedu is: WhatsApp: +1 (213) 594-5657 OR Call: +1 727 456 9641

• I take my work as a tutor very seriously, and I always aim to do my best to help my students excel in school. I have a solid and sincere passion for academic achievement, and with my help, I am positive that I can help students obtain very high grades with minimal stress and effort.
• Please feel free to contact me if you're interested in my services and would like to learn more. I'm available 24/7 via phone call, email, and text. Again, thank you for taking the time to read my Reddit tutoring ad, and I hope to hear from you soon!

My contact details:
WhatsApp: +1 (213) 594-5657
Call: +1 727 456 9641
Website: hiraedu. com
Email: [info@hiraedu](mailto:info@hiraedu). com
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In today’s evolving and competitive landscape, the value of innovation is shifting from the traditional closed systems approach to a more open, decentralized, and community-driven approach. Paul Lalovich and Tesha Teshanovich from Agile Dynamics outline what is driving the trend, its implications for organizations, and how leaders can successfully operate at the forefront of the shift.
Innovation transcends the mere conceptualization of fresh ideas; it is the actionable process of enhancing existing products or conjuring entirely new offerings. While there is a strong correlation between R&D and innovation – with the former serving as a wellspring for pioneering thoughts – the journey from groundbreaking research to practical utility can be intricate and protracted.
However, it’s worth noting that innovation isn't solely tethered to structured R&D. It can spontaneously arise from sheer curiosity, a spark of inspiration, or even the simple act of refining or tweaking existing methodologies.
Firms might invest in R&D to catalyze innovation, but they can also harness external advancements – referred to as ‘spillovers’. After all, groundbreaking knowledge isn't always the exclusive domain of its creators, making external inspirations invaluable.
Emerging from a robust foundation of innovation, soft power presents tangible advantages. Leaders in technology often establish benchmarks that others deem beneficial to adopt. As a result, global standards lean favorably toward those pioneers. Moreover, countries recognized for their innovative acumen become prime territories for patent filings. These innovation hubs magnetize not just domestic but international investments and capital.
Perhaps the most profound testament to their soft power is the allure they hold for top-tier talents. For instance, Silicon Valley has evolved into a global nexus, drawing in exceptional minds from the realms of information, communication, and digital technologies. Such concentrations of talent can significantly influence a nation’s trade dynamics.

Tech monopolies slow down innovation

In the arena of global economic dominance, competition emerges as the cornerstone, propelling nations to the forefront of innovation and growth. While Chinese strategies appear to have adapted, embracing the dynamism of competitive markets, the United States stands at a crossroads. Some of its tech behemoths promote their size and market leadership as pivotal for cutting-edge innovation.
Yet, it is crucial to discern the nature of this innovation and whose interests it truly serves. Does it prioritize shareholder returns, or is there a broader, national interest at play? As smaller, agile firms emerge, emphasizing true boundary-pushing innovation, one must ponder: Is the spirit of unbridled competition – a force that once fueled the American economy – being overshadowed by the looming giants?
In the nuanced interplay between governmental oversight and market forces, recent actions within China's technology sector provide a captivating study of regulatory boundaries. This phenomenon, aptly termed ‘de-tycoonification’, captures a deliberate effort to harmonize enterprise innovation with centralized checks.
A leading digital commerce platform in China encountered regulatory attention. The swift determination that its practices were anti-competitive, accompanied by a significant financial penalty, symbolizes a broader intent to redefine market paradigms. Prompt official communique following these events conveys a clear perspective: monopolistic behaviours can inhibit the holistic evolution of a market-based economy.
This stance also emphasizes that thoughtful regulations, rather than restricting growth, might actually serve as pillars to stabilize and nurture it. The regulatory web further ensnared another major digital entity in China, underscoring the principle that technological ingenuity should operate within established ethical and legal frameworks. Such internal checks within China challenge certain dominant narratives in global tech centres.
The notion that maintaining a robust market stature acts as a shield against global tech adversaries comes under scrutiny. The introspective regulatory steps within China necessitate a broader re-evaluation of such assumptions.
The tech landscape today is unmistakably marked by the towering presence of Big Tech, but what underlies this dominance might point towards a concerning reduction in competitive intensity. For two decades, the profits raked in by American tech behemoths have remained unparalleled, with market valuations suggesting this trend is expected to continue, if not amplify, in the coming years.
Such sustained, sky-high profitability isn't typical in a genuinely competitive market. In such a setting, rivals and newcomers usually exert downward pressures, ensuring no single entity retains an overwhelming edge for extended periods. The tech industry's trajectory further points towards a rising penchant for consolidation. This is evidenced by the substantial acquisitions of budding companies by the tech titans.
Data sourced from Mergermarket underscores an uptick in acquisition activity by these colossal tech firms, particularly post-2010. The symbiotic relationship between persistent high profits and a trend toward industry concentration suggests that the tech market might be veering away from the vibrant competitive arena it once was.

Cardwell’s law

The tech landscape’s evolution, in its relationship with innovation, is witnessing a palpable shift in entrepreneurial motivation and vision. Historically, the fervour of pioneering something transformative, encapsulated in the ‘moonshot thinking’, drove entrepreneurs. This audacious spirit envisioned groundbreaking entities akin to the tech luminaries of the late 20th and early 21st century. Yet, today’s entrepreneurial aspirations seem more tempered.
Instead of fostering ambitions of building the next revolutionary tech empire, there’s a growing inclination towards securing an acquisition by an existing tech colossus. This shift in sentiment dims the likelihood of a new tech juggernaut rising to challenge the incumbent titans. Post the era of computer-centric, web-driven, and smartphone-related innovations, a cloud of uncertainty looms over the emergence of new tech powerhouses.
Notably, the promising technological domains of the upcoming decade – be it autonomous vehicles with their exorbitant R&D costs, virtual or augmented reality's significant development expenditures, the data intensity of artificial intelligence, or drones and the Internet of Things with their challenging profit margins – present formidable entry barriers.
These hurdles, combined with a changing entrepreneurial landscape, cast a shadow on the future dynamism of tech innovation. Cardwell's elucidation on the patterns of technological evolution offers a poignant lens through which to view the current landscape dominated by Big Tech.
Donald Stephen Lowell Cardwell’s seminal work from 1972 suggests that technological vigor within societies is not an enduring flame, but a fleeting burst of brilliance. Within the European context, as one nation's innovative energy began to wane, another would rise, ensuring a consistent relay of progress across the continent.
Visualize this relay of innovation as a torch, brilliant yet intense. Historically, regions such as Northern Italy, Southern Germany, Spain, and Portugal, and later Holland, Britain, the United States, and Germany, took turns in holding this torch, leading the march of innovation. Yet, no single society clung to this leadership for extended durations. The relay ensured that as one nation's innovation diminished, another took up the mantle, propelling the collective forward.
This phenomenon, coined as ‘Cardwell’s Law’ by Joel Mokyr, posits that when left in isolation, a society’s technological creativity is but a brief spark. Over time, conservatism’s stifling grip, intent on preserving existing structures of power and privilege, often curtails this innovative drive.
This is where the analogy becomes particularly relevant for the Big Tech landscape. In today’s digital age, a few colossal entities dominate, much like the leading nations of old Europe. Yet, as these tech giants solidify their positions, they risk becoming victims of the very conservatism Mokyr speaks of.
Instead of being conduits for continual innovation, their sheer dominance and entrenched positions could lead to a stagnation in technological creativity. As they grow in size and influence, there is an increasing tendency to preserve the status quo, which inadvertently suppresses the innovative spark found in smaller, more agile entities.

Decentralization and open innovation

In the contemporary milieu characterized by the overwhelming dominance of Big Tech monopolies, the paradigms of decentralized innovation and open innovation emerge as potentially transformative alternatives.
The concept of distributed strategy borrows from nature, suggesting that in the same manner that organisms such as trees maximize their efficiency by creating multiple self-similar structures like leaves instead of solely relying on a single core trunk, businesses too need to shift their focus from purely scaling their core processes to nurturing multiple iterative strategies at the organizational peripheries. This can be encapsulated in the mantra of ‘Think Local, Act Global’.
In essence, companies must attune to the nuanced demands and opportunities of each local market, while simultaneously integrating these learnings into a broader global strategy. This is particularly evident in industries undergoing rapid transformation; for instance, the automotive industry's evolution from merely selling cars to offering comprehensive mobility solutions, a shift that is predicted to significantly alter its revenue structure by 2035.
In parallel, in our data-driven age, there is an increasing realization that the sheer volume of data is less crucial than its meaningful interpretation. Organizations need to pivot from prioritizing data accumulation to developing advanced algorithms capable of drawing insights from fragmented, patchy datasets. In the rapidly shifting landscape of today's global business environment, numerous established multinational corporations find themselves at a perplexing crossroads.
The crux of their predicament stems from a foundational dilemma: how to juxtapose traditional scale-driven strategies with the emergent imperative of Distributed strategies. To dissect this conundrum, one must appreciate the inherently divergent organizational philosophies underpinning scale and distributed strategies. Transitioning from a scale-centric model to a distributed-oriented one is not merely about implementing a series of organizational modifications, no matter how profound.
The shift demands a comprehensive reimagining of the organizational ethos and operational mechanics. Moreover, it is a fallacy to view these strategies as mutually exclusive. In actuality, they exist on a continuum, each holding its unique value. The challenge for modern enterprises lies in striking an optimal balance between harnessing the benefits of scale and the agility of Distributed strategies. Regrettably, the journey to this equilibrium is riddled with pitfalls, and many companies, even with their vast resources and global reach, have faltered in this endeavor.
Contrary to scale-centric entities that depend on static assets, with streamlined yet inherently slower supply chains, Distributed organizations harness networks characterized by adaptability and continuous transformation. These networks are primed for swiftly addressing specific local requirements and seizing niche market prospects.
Such frameworks incorporate a blend of proprietary micro-production facilities, possibly utilizing innovations like 3D printing; leasing assets from providers offering asset-on-demand services; and coordinating flexible ecosystems of regional digital collaborators. The overarching aim is twofold: continuously devise innovative solutions tailored for local clientele and escalate them to various markets with optimal speed.
Distributed-oriented organizations prioritize decentralization, contrasting with the top-down hierarchies commonly seen in scale-driven entities. Within these structures, decision-making isn't confined to a centralized corporate core. Instead, considerable authority is delegated to customer-centric teams positioned away from the primary headquarters. This design fosters agility, allowing for a rapid response to localized demands and new opportunities.
Some multinational corporations have observed marked improvements in their performance metrics after such decentralization. They empowered regional leaders with financial oversight, decision-making rights, streamlined communication channels to the central office, and enhanced access to market analytics.
Another trend, seen in the case of an appliance industry giant, involves an even more radical shift. This entity introduced a unique organizational framework aimed at minimizing the distance between the enterprise and its customer base. In a bold move, an entire level of middle management was eliminated, redistributing power to numerous newly-formed, semi-independent, customer-aligned business segments. These units operate in synergy, linked by a unified digital platform.
Further reading: Knowledge and venture capital as a driver of innovation.
Meanwhile, ‘Open Innovation’ offers a complementary model, championing a departure from insular corporate research and development approaches. Instead, it advocates for the amalgamation of external insights, be they from academia, startups, or independent innovators, into the innovation process. This synergistic approach addresses the often-criticized inertia inherent in large tech monopolies, promoting a more dynamic and collaborative innovation ecosystem.
Both these paradigms, however, necessitate a significant cultural shift within organizations, demanding a more flexible, adaptive, and outward-looking ethos to truly harness their potential in countering the inertia often associated with tech giants.
The rise of open innovation, propelled by reduced communication costs and advancements in memory and computation capabilities, has ushered in significant changes in market dynamics and societal interactions. Unlike the traditionally centralized, firm-driven innovation models, open innovation champions a decentralized, peer-based approach that emphasizes intrinsic motivation and societal benefits.
Indeed, the literature has delved into the nature of these peer innovation communities, understanding their social structures and intricacies.
However, the repercussions of this shift towards open innovation on established and emerging firms remain inadequately explored. Current organizational and strategic theories don't fully encapsulate the nuances of community-driven innovation. Despite the transformative potential of open innovation, its influence on mainstream organizational and strategic discourses has been somewhat muted.
As we progress, it becomes imperative to develop a more comprehensive understanding of firms in this new context, addressing the interaction between traditional organizational structures and emerging community-based innovation paradigms.

Conclusion

In an evolving landscape where tasks are increasingly modular and knowledge about solutions becomes more widespread, the traditional closed systems of innovation shift towards open, community-driven models. The implications are profound: we can no longer rely solely on conventional understandings of innovation rooted in cost efficiency, control mechanisms, and external incentives.
As innovation gets embedded in a spectrum ranging from strictly internal processes to open community collaborations, our conceptualization of firms and their boundaries need revisiting. This doesn’t negate the value of traditional models, but it requires a hybrid approach where both internal and open strategies coexist.
A pivotal question arises: under what circumstances should firms toggle between these different modes of innovation? The answer, it appears, lies in understanding the nature of the product and the distribution of problem-solving knowledge.
For products that are inherently integrated and where specialized knowledge is centralized, the conventional in-house R&D model, bolstered by a strong innovation-centric culture, remains relevant. Here, innovation is typically cocooned within the firm's boundaries, spanning from distinct functional divisions to intricate, ambidextrous designs.
However, when a product can be broken down into modular components and the requisite knowledge is dispersed, the limitations of a closed innovation system become evident. In these contexts, the power dynamics of innovation are reshaped by the principles of openness, collaborative sharing, intrinsic motivation, and community engagement.
The challenge, then, for modern enterprises is to discern when to internalize and when to externalize, ensuring that they harness the best of both worlds while navigating the complex terrain of innovation.In today’s evolving and competitive landscape, the value of innovation is shifting from the traditional closed systems approach to a more open, decentralized, and community-driven approach. Paul Lalovich and Tesha Teshanovich from Agile Dynamics outline what is driving the trend, its implications for organizations, and how leaders can successfully operate at the forefront of the shift. Innovation transcends the mere conceptualization of fresh ideas; it is the actionable process of enhancing existing products or conjuring entirely new offerings. While there is a strong correlation between R&D and innovation – with the former serving as a wellspring for pioneering thoughts – the journey from groundbreaking research to practical utility can be intricate and protracted. However, it’s worth noting that innovation isn't solely tethered to structured R&D. It can spontaneously arise from sheer curiosity, a spark of inspiration, or even the simple act of refining or tweaking existing methodologies.
Firms might invest in R&D to catalyze innovation, but they can also harness external advancements – referred to as ‘spillovers’. After all, groundbreaking knowledge isn't always the exclusive domain of its creators, making external inspirations invaluable. Emerging from a robust foundation of innovation, soft power presents tangible advantages. Leaders in technology often establish benchmarks that others deem beneficial to adopt. As a result, global standards lean favorably toward those pioneers. Moreover, countries recognized for their innovative acumen become prime territories for patent filings. These innovation hubs magnetize not just domestic but international investments and capital. Perhaps the most profound testament to their soft power is the allure they hold for top-tier talents. For instance, Silicon Valley has evolved into a global nexus, drawing in exceptional minds from the realms of information, communication, and digital technologies. Such concentrations of talent can significantly influence a nation’s trade dynamics. Tech monopolies slow down innovation In the arena of global economic dominance, competition emerges as the cornerstone, propelling nations to the forefront of innovation and growth. While Chinese strategies appear to have adapted, embracing the dynamism of competitive markets, the United States stands at a crossroads. Some of its tech behemoths promote their size and market leadership as pivotal for cutting-edge innovation. Yet, it is crucial to discern the nature of this innovation and whose interests it truly serves. Does it prioritize shareholder returns, or is there a broader, national interest at play? As smaller, agile firms emerge, emphasizing true boundary-pushing innovation, one must ponder: Is the spirit of unbridled competition – a force that once fueled the American economy – being overshadowed by the looming giants? In the nuanced interplay between governmental oversight and market forces, recent actions within China's technology sector provide a captivating study of regulatory boundaries. This phenomenon, aptly termed ‘de-tycoonification’, captures a deliberate effort to harmonize enterprise innovation with centralized checks. A leading digital commerce platform in China encountered regulatory attention. The swift determination that its practices were anti-competitive, accompanied by a significant financial penalty, symbolizes a broader intent to redefine market paradigms. Prompt official communique following these events conveys a clear perspective: monopolistic behaviours can inhibit the holistic evolution of a market-based economy. This stance also emphasizes that thoughtful regulations, rather than restricting growth, might actually serve as pillars to stabilize and nurture it. The regulatory web further ensnared another major digital entity in China, underscoring the principle that technological ingenuity should operate within established ethical and legal frameworks. Such internal checks within China challenge certain dominant narratives in global tech centres. The notion that maintaining a robust market stature acts as a shield against global tech adversaries comes under scrutiny. The introspective regulatory steps within China necessitate a broader re-evaluation of such assumptions. The tech landscape today is unmistakably marked by the towering presence of Big Tech, but what underlies this dominance might point towards a concerning reduction in competitive intensity. For two decades, the profits raked in by American tech behemoths have remained unparalleled, with market valuations suggesting this trend is expected to continue, if not amplify, in the coming years. Such sustained, sky-high profitability isn't typical in a genuinely competitive market. In such a setting, rivals and newcomers usually exert downward pressures, ensuring no single entity retains an overwhelming edge for extended periods. The tech industry's trajectory further points towards a rising penchant for consolidation. This is evidenced by the substantial acquisitions of budding companies by the tech titans. Data sourced from Mergermarket underscores an uptick in acquisition activity by these colossal tech firms, particularly post-2010. The symbiotic relationship between persistent high profits and a trend toward industry concentration suggests that the tech market might be veering away from the vibrant competitive arena it once was. Cardwell’s law The tech landscape’s evolution, in its relationship with innovation, is witnessing a palpable shift in entrepreneurial motivation and vision. Historically, the fervour of pioneering something transformative, encapsulated in the ‘moonshot thinking’, drove entrepreneurs. This audacious spirit envisioned groundbreaking entities akin to the tech luminaries of the late 20th and early 21st century. Yet, today’s entrepreneurial aspirations seem more tempered. Instead of fostering ambitions of building the next revolutionary tech empire, there’s a growing inclination towards securing an acquisition by an existing tech colossus. This shift in sentiment dims the likelihood of a new tech juggernaut rising to challenge the incumbent titans. Post the era of computer-centric, web-driven, and smartphone-related innovations, a cloud of uncertainty looms over the emergence of new tech powerhouses. Notably, the promising technological domains of the upcoming decade – be it autonomous vehicles with their exorbitant R&D costs, virtual or augmented reality's significant development expenditures, the data intensity of artificial intelligence, or drones and the Internet of Things with their challenging profit margins – present formidable entry barriers. These hurdles, combined with a changing entrepreneurial landscape, cast a shadow on the future dynamism of tech innovation. Cardwell's elucidation on the patterns of technological evolution offers a poignant lens through which to view the current landscape dominated by Big Tech. Donald Stephen Lowell Cardwell’s seminal work from 1972 suggests that technological vigor within societies is not an enduring flame, but a fleeting burst of brilliance. Within the European context, as one nation's innovative energy began to wane, another would rise, ensuring a consistent relay of progress across the continent. Visualize this relay of innovation as a torch, brilliant yet intense. Historically, regions such as Northern Italy, Southern Germany, Spain, and Portugal, and later Holland, Britain, the United States, and Germany, took turns in holding this torch, leading the march of innovation. Yet, no single society clung to this leadership for extended durations. The relay ensured that as one nation's innovation diminished, another took up the mantle, propelling the collective forward. This phenomenon, coined as ‘Cardwell’s Law’ by Joel Mokyr, posits that when left in isolation, a society’s technological creativity is but a brief spark. Over time, conservatism’s stifling grip, intent on preserving existing structures of power and privilege, often curtails this innovative drive. This is where the analogy becomes particularly relevant for the Big Tech landscape. In today’s digital age, a few colossal entities dominate, much like the leading nations of old Europe. Yet, as these tech giants solidify their positions, they risk becoming victims of the very conservatism Mokyr speaks of. Instead of being conduits for continual innovation, their sheer dominance and entrenched positions could lead to a stagnation in technological creativity. As they grow in size and influence, there is an increasing tendency to preserve the status quo, which inadvertently suppresses the innovative spark found in smaller, more agile entities. Decentralization and open innovation In the contemporary milieu characterized by the overwhelming dominance of Big Tech monopolies, the paradigms of decentralized innovation and open innovation emerge as potentially transformative alternatives. The concept of distributed strategy borrows from nature, suggesting that in the same manner that organisms such as trees maximize their efficiency by creating multiple self-similar structures like leaves instead of solely relying on a single core trunk, businesses too need to shift their focus from purely scaling their core processes to nurturing multiple iterative strategies at the organizational peripheries. This can be encapsulated in the mantra of ‘Think Local, Act Global’. In essence, companies must attune to the nuanced demands and opportunities of each local market, while simultaneously integrating these learnings into a broader global strategy. This is particularly evident in industries undergoing rapid transformation; for instance, the automotive industry's evolution from merely selling cars to offering comprehensive mobility solutions, a shift that is predicted to significantly alter its revenue structure by 2035. In parallel, in our data-driven age, there is an increasing realization that the sheer volume of data is less crucial than its meaningful interpretation. Organizations need to pivot from prioritizing data accumulation to developing advanced algorithms capable of drawing insights from fragmented, patchy datasets. In the rapidly shifting landscape of today's global business environment, numerous established multinational corporations find themselves at a perplexing crossroads. The crux of their predicament stems from a foundational dilemma: how to juxtapose traditional scale-driven strategies with the emergent imperative of Distributed strategies. To dissect this conundrum, one must appreciate the inherently divergent organizational philosophies underpinning scale and distributed strategies. Transitioning from a scale-centric model to a distributed-oriented one is not merely about implementing a series of organizational modifications, no matter how profound. The shift demands a comprehensive reimagining of the organizational ethos and operational mechanics. Moreover, it is a fallacy to view these strategies as mutually exclusive. In actuality, they exist on a continuum, each holding its unique value. The challenge for modern enterprises lies in striking an optimal balance between harnessing the benefits of scale and the agility of Distributed strategies. Regrettably, the journey to this equilibrium is riddled with pitfalls, and many companies, even with their vast resources and global reach, have faltered in this endeavor. Contrary to scale-centric entities that depend on static assets, with streamlined yet inherently slower supply chains, Distributed organizations harness networks characterized by adaptability and continuous transformation. These networks are primed for swiftly addressing specific local requirements and seizing niche market prospects. Such frameworks incorporate a blend of proprietary micro-production facilities, possibly utilizing innovations like 3D printing; leasing assets from providers offering asset-on-demand services; and coordinating flexible ecosystems of regional digital collaborators. The overarching aim is twofold: continuously devise innovative solutions tailored for local clientele and escalate them to various markets with optimal speed. Distributed-oriented organizations prioritize decentralization, contrasting with the top-down hierarchies commonly seen in scale-driven entities. Within these structures, decision-making isn't confined to a centralized corporate core. Instead, considerable authority is delegated to customer-centric teams positioned away from the primary headquarters. This design fosters agility, allowing for a rapid response to localized demands and new opportunities. Some multinational corporations have observed marked improvements in their performance metrics after such decentralization. They empowered regional leaders with financial oversight, decision-making rights, streamlined communication channels to the central office, and enhanced access to market analytics. Another trend, seen in the case of an appliance industry giant, involves an even more radical shift. This entity introduced a unique organizational framework aimed at minimizing the distance between the enterprise and its customer base. In a bold move, an entire level of middle management was eliminated, redistributing power to numerous newly-formed, semi-independent, customer-aligned business segments. These units operate in synergy, linked by a unified digital platform. Further reading: Knowledge and venture capital as a driver of innovation. Meanwhile, ‘Open Innovation’ offers a complementary model, championing a departure from insular corporate research and development approaches. Instead, it advocates for the amalgamation of external insights, be they from academia, startups, or independent innovators, into the innovation process. This synergistic approach addresses the often-criticized inertia inherent in large tech monopolies, promoting a more dynamic and collaborative innovation ecosystem. Both these paradigms, however, necessitate a significant cultural shift within organizations, demanding a more flexible, adaptive, and outward-looking ethos to truly harness their potential in countering the inertia often associated with tech giants. The rise of open innovation, propelled by reduced communication costs and advancements in memory and computation capabilities, has ushered in significant changes in market dynamics and societal interactions. Unlike the traditionally centralized, firm-driven innovation models, open innovation champions a decentralized, peer-based approach that emphasizes intrinsic motivation and societal benefits. Indeed, the literature has delved into the nature of these peer innovation communities, understanding their social structures and intricacies. However, the repercussions of this shift towards open innovation on established and emerging firms remain inadequately explored. Current organizational and strategic theories don't fully encapsulate the nuances of community-driven innovation. Despite the transformative potential of open innovation, its influence on mainstream organizational and strategic discourses has been somewhat muted. As we progress, it becomes imperative to develop a more comprehensive understanding of firms in this new context, addressing the interaction between traditional organizational structures and emerging community-based innovation paradigms. Conclusion In an evolving landscape where tasks are increasingly modular and knowledge about solutions becomes more widespread, the traditional closed systems of innovation shift towards open, community-driven models. The implications are profound: we can no longer rely solely on conventional understandings of innovation rooted in cost efficiency, control mechanisms, and external incentives. As innovation gets embedded in a spectrum ranging from strictly internal processes to open community collaborations, our conceptualization of firms and their boundaries need revisiting. This doesn’t negate the value of traditional models, but it requires a hybrid approach where both internal and open strategies coexist. A pivotal question arises: under what circumstances should firms toggle between these different modes of innovation? The answer, it appears, lies in understanding the nature of the product and the distribution of problem-solving knowledge. For products that are inherently integrated and where specialized knowledge is centralized, the conventional in-house R&D model, bolstered by a strong innovation-centric culture, remains relevant. Here, innovation is typically cocooned within the firm's boundaries, spanning from distinct functional divisions to intricate, ambidextrous designs. However, when a product can be broken down into modular components and the requisite knowledge is dispersed, the limitations of a closed innovation system become evident. In these contexts, the power dynamics of innovation are reshaped by the principles of openness, collaborative sharing, intrinsic motivation, and community engagement. The challenge, then, for modern enterprises is to discern when to internalize and when to externalize, ensuring that they harness the best of both worlds while navigating the complex terrain of innovation.

One of the most fascinating and transformative developments in AI over the next 10-20 years is its integration with quantum computing. While AI has already revolutionized numerous industries with its advanced data processing and learning capabilities, the advent of quantum computing promises to take these capabilities to unprecedented levels. This synergy between AI and quantum computing is poised to solve some of the most complex problems in science, technology, and society.

Understanding Quantum Computing

Quantum computing is based on the principles of quantum mechanics, utilizing quantum bits or qubits. Unlike classical bits, which represent data as either 0 or 1, qubits can represent both 0 and 1 simultaneously thanks to a property known as superposition. Additionally, quantum entanglement allows qubits that are entangled to be instantaneously correlated with each other, regardless of distance. These properties enable quantum computers to process vast amounts of data simultaneously and solve complex problems much faster than classical computers.

The Synergy Between AI and Quantum Computing

1. Accelerating Machine Learning:
   • Enhanced Algorithms: Quantum computing can significantly speed up the training of machine learning models. Quantum algorithms like the Quantum Approximate Optimization Algorithm (QAOA) and the Variational Quantum Eigensolver (VQE) can solve optimization problems more efficiently than classical algorithms.
   • Improved Data Processing: Quantum computers can process large datasets much faster, enabling AI systems to analyze and learn from data at unprecedented speeds. This acceleration can lead to breakthroughs in fields that require massive data analysis, such as genomics, climate modeling, and financial forecasting.
2. Advancing AI Capabilities:
   • Complex Simulations: Quantum computing can handle the complexity of simulating quantum systems, which classical computers struggle with. This capability is crucial for advancing AI in fields like materials science and drug discovery, where understanding molecular interactions at a quantum level can lead to significant innovations.
   • Enhanced Predictive Models: Quantum-enhanced AI models can provide more accurate predictions in various domains, from weather forecasting to stock market analysis, by processing and learning from complex patterns that classical computers cannot efficiently handle.
3. Revolutionizing Cryptography and Security:
   • Quantum Encryption: Quantum computing can create virtually unbreakable encryption methods using quantum key distribution (QKD). This level of security is essential for protecting sensitive information in an increasingly digital world.
   • Breaking Classical Encryption: Conversely, quantum computers have the potential to break current encryption algorithms, such as RSA and ECC, which rely on the difficulty of factoring large numbers. This threat necessitates the development of quantum-resistant cryptographic methods, where AI can play a crucial role in devising and testing these new algorithms.

Real-World Applications and Impact

1. Healthcare and Drug Discovery: Quantum computing combined with AI can revolutionize healthcare by accelerating drug discovery and personalized medicine. AI can identify potential drug candidates, while quantum simulations can predict their interactions with biological systems at an atomic level, significantly reducing the time and cost of bringing new drugs to market.
2. Climate Change and Environmental Science: The ability to process vast datasets and run complex simulations makes quantum-enhanced AI a powerful tool in climate modeling. These models can provide more accurate predictions of climate change impacts and help develop effective mitigation strategies.
3. Optimization Problems in Logistics and Supply Chain: AI and quantum computing can solve complex optimization problems in logistics, such as route planning, inventory management, and supply chain optimization, leading to more efficient and sustainable operations.
4. Financial Services: In finance, quantum-enhanced AI can improve risk modeling, fraud detection, and algorithmic trading, providing more robust financial analysis and decision-making tools.

Ethical and Societal Considerations

1. Access and Inequality: Ensuring equitable access to quantum computing resources and preventing a technological divide between those who can afford it and those who cannot is crucial.
2. Security and Privacy: As quantum computing can break current encryption, developing quantum-resistant cryptographic methods and ensuring data privacy are paramount.
3. Regulation and Governance: Establishing regulations and governance frameworks to manage the development and use of quantum-enhanced AI responsibly will be essential to mitigate risks and ensure ethical use.

Conclusion

The intersection of AI and quantum computing represents one of the most exciting frontiers in technology. Over the next 10-20 years, this synergy is poised to revolutionize numerous fields by solving problems that are currently intractable for classical computers. From healthcare and climate science to cryptography and financial services, the combined power of AI and quantum computing will drive unprecedented advancements and transform our world in profound ways. As we navigate this future, it will be crucial to address ethical and societal challenges to harness this transformative potential responsibly.
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We have a few space satellites that measure global temperature independently of ground stations.
My basic understanding is that they measure incoming (from earth) radiation level (irradiance).
Then with some maths, they derive the temperature from the received light spectrum.
Some satellites measure incoming infrared radiation, but the most popular ones measure incoming microwave radiation.
My main question is related to the use of thermometers on board of those satellites, their purposes.
Let's take for example the famous UAH satellite, its founder, Roy Spencer, says the following:
> Contrary to some reports, the satellite measurements are not calibrated in any way with the global surface-based thermometer records of temperature. They instead use their own on-board precision redundant platinum resistance thermometers (PRTs) calibrated to a laboratory reference standard before launch.
platinum thermometers are simply a more accurate version of thermometers versus mercury based ones.
He says the satellite has onboard (redundant (2)) thermometers. Why and at which step in the temperature calculus pipeline are those thermometers used in the satellite?
The satellites are in near space (very cold) and their face that is solar exposed could be very hot. In both ways (space cold and heat) seems highly unrelated to measuring earth surface temperature.
If so, then what are the purpose of those thermometers onboard? How do they relate with the spectroscopic measure of incoming radiation?
Here is my tentative understanding:
I was able to find this UAH paper that says:
> the spacecraft experience a slight E-W drift during the course of their operational life.
> the (microwave) instrument is exposed to more direct sunlight and warms as a result. This warming is evidenced in the on-board platinum resistance thermometer which is embedded in the hot-target plate. Christy et al. 2000 discovered the dependency of variations in the hot-target plate temperature (HTPT) and errors in the atmospheric temperature reported by the instrument. The instrument error was eliminated by determining a linear coefficient which when multiplied by the HTPT anomaly would account for much of the error.
from https://ams.confex.com/ams/pdfpapers/68728.pdf
The paper they cite is most likely:
https://journals.ametsoc.org/view/journals/atot/17/9/1520-0426_2000_017_1153_mttdca_2_0_co_2.xml?tab_body=abstract-display
> As mentioned in Christy et al. (1998), we discovered a spurious influence on the calculation of Tb due to the temperature of the instrument itself
According to this, it seems that the two thermometers, which are near the sun exposed part (plate) and the radiometer, are used to algorithmically correct the bias/drift effect of satellite temperature variation on the accuracy of the radiometer that measure microwaves.
Besides this correction, that was added in the 2000s, my question is, did the two themometers had, and still have another role in the earth temperature calculus? Do the radiometer needs them, independently of aforementioned drift.
> The determination of earth-viewed Tb from the ob-served digital counts is based on an interpolation scheme between two temperature anchor points: cold space and the onboard warm target plate T W . The MSU reports the intensity of microwave radiation as digital counts for the 11 earth views and for cold space and the warm target. The temperature for cold space is known (2.7 K) and that of the warm target is monitored by the two PRTs. Thus a relationship is then computed between counts and Tb given the digital counts and temperatures of the anchor points (Spencer et al. 1990).
If "earth viewed Tb" means earth calculated temperature (?) then it seems the radiometer alone cannot work (?) and needs to do the difference between the cold and hot zone of the satellite.
It seems to not be the same thing as aforementioned bias drift correction but the difference to me is unclear. The argument for this role of the thermometer being different is that it was described in 1990, before the drift was known (it seems but not sure).
note that they mention errors corrections can be non linear.
> In general, as the instrument heats (T W increases) the calculated earth-viewed temperature based on laboratory nonlinear calibration coefficients becomes too warm.
Meaning that the warmer the radiometer is, the warmer (non linearly) the earth calculated temperature is.
anyone knows what the "cold target counts" terminology actually means in regards to the radiometer?
note that the idea of using coorbiting satellites thermometer data for increased redundancy is promising.
Anyway here is my discovery, that is in fact known but it seems nobody had connected the dots before.
Christy discovered that the temperature variation of the radiometer affects the earth temperature calculus (non linearly).
They also measured that past similar satellites had anomalous drifts/temperature records because (among other things like orbital decay, instrument gain and diurnal bias) they were not correcting for their discovered bias.
HOWEVER, it seems no one has considered that there is a meta-drift, a drift over the drift since the 2 thermometers that are used to correct the radiometer bias, have themselves an intrinsic temperature drift over time that is an artificial warming effect.
It is known that thermometers (mercury, alcohol) artificially gain 0.7 degree per century.
for platinum thermometers, the temperature drift is between 2-10 millikelvin per year hence up to 1 degree of warming per century....
but in an environment like space (extreme cold, extreme heat when sun aligned, and lower gravity (could affect thermal expansion/accuracy) the effect could be bigger or faster especially with solar radiation.
source: https://ui.adsabs.harvard.edu/abs/2015SPIE.9258E..1AD/abstract
Of course, here even if the thermometers were to have their temperature artificially increase by 1 degree (or more via accellerated space aging), the effect would not directly translate to an artificial increase of earth calculated temperature by 1 degree.
According to Christy's paper, the average UAH satellite monthly temperature was 280 degree at the time. So it would shift to an artificial 281 monthly temperature.
It appears there was a drift of 2 degree between 1979 to 97 for a similar satellite (see figure 5) albeit data is not clean at the end, and also, it might be natural space temperature variance (or via orbital decay/change) (no idea) instead of accelerated thermometer aging.
For N-6 (assuming it is representative..) the monthly mean hot plate variance was of 4 degree hence a thermal drift of 1-2 degree could affect the monthly variance by 25 to 50% which is huge but unclear to me how much the algo is sensitive to the variance versus the absolute temperature. Also daily variance is probably much larger.
The actual effect on earth calculated temperature could be calculated from figure 6, but I am too much of a noob to do the maths sadly.. If anyone could answer how much an artificial gain in thermometer temperature of say 1 degree would do on earth temperature that would be great.
For reference, when the bias was not corrected they observed ~0.8 degree of earth calculated temperature variance bias.
Note that this could have two effects as according to my partial understanding, the thermometer is used two times, 1) for the radiometer to work (related to "counts") they need to know the difference between the cold (fixed temp) and hot plate. and 2) for correcting the non linear bias of radiometer temperature. 1 and 2 might be the same thing but IMO they are not.
Note that independently of thermometer drift and temperature effect on radiometer, the radiometer could itself have also an age drift independent of temperature cf paper aforementioned instrument gain.
While the magnitude of the thermometer drift on earth temperature is unknown (to me) but can be calculated, it could be significant and falsify the satellite temperature record to an extent, and it should worsen in the following decades (especially if aging is non linear also there will be considerably more cosmic rays radiations during the incoming maunder like minimum (maybe arround 2030) which is predicted to reduce (temporarilly) the sun magnetosphere by something like 40% IIRC.
Most importantly this bias can be corrected, via analyzing coorbiting satellites with the UAH (or RSS) that are more recent, e.g. if a spacex satellite came with a thermometer and is nearby, then it could be cross correlated and used to assess how much the UAH thermometers have drifted empirically.

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Hi so I am an undergradute student and the only thing left for me to do is to finish my thesis, and I'm hoping to get some advise/help with it. So to begin with, my thesis is regarding the study of condensed matter physics specifically about metamaterials; specifically, I am trying to optimize and study the response of the metamaterial when you apply an EM field to it. To be precise, I am interested in studying the respose (specifically, Absorption) of a metamaterial when it interacts with an EM wave in the NIR to Visible regime.
The problem I have is that I need to find a simulation software in order to run my simulations where the metamaterial interacts with an EM wave. I tried studying it and creating my own simulation program by using the FDTD method in Matlab. The book I am using for reference is, The Finite-Difference Time-Domain Method For Electromagnetics with MATLAB Simulations - Atef Z. Elsherbeni, Veysel Demir. But I am having a problem following the book and figuring out how exactly do I simulate an EM field interacting with my metamaterial.
I got desparete and thought to myself I should just look for software that has already been created to do such simulations. So far I have found 2 simulation tools,
1). CST studio suite - I found this being used from one of the research articles I was reading, I looked it up and it seemed perfect indeed. The problem with this is that I need to buy a license, this poses a problem with me because for starters it is not available to be bought in my country and on top of that when I tried looking up the price, I saw that it could reach as high as 3000EUR for students! Which is just too expensive for me as a student!
2). openEMS - This one I found as an open source simulation tool because I figured there was no way in hell I could affort CST studio suite, I was hopeful at first so I looked around and saw that this simulation tool is actually not suitable for my case since its not optimized for frequencies higher than 6.0 GHz.
So I guess now I am just desperate in trying to figure out any other alternatives that I can use to simulate my desired metamaterial. I have been trying to look online for alternatives but all the others I found are either not available anymore or seems sketchy and requires a vast knowledge in programming which I wholeheartedly admit right now I really dont have at all.
So to sum it up, here are my concerns and hopefully someone here could possibly help me or give me some guidance as to what I can do to find an answer to my problem of finding a good simulation tool for the purpose I need:
1). Are there any other simulation software you guys know of that I can look at which suites the kind of simulation I need (metamaterials interacting with light in the NIR to Visible wavelength and being able to extract properties such as the absorption, dispersion, response to both TE and TM polarization, etc.)?
2). Can anyone help me to find other possible and easier to understand sources/materials that I can study in order to implement the FDTD method for creating my own simulation if needed, for use in metamaterials.
3). Any advise regarding studying of metamaterials and how to study it properly?
Sorry for the long post but I really am desperate and I am having a hard time asking for help because as far as I know I am the only one focusing on metamaterials as a topic for my thesis in my schools Physics program and my Thesis adviser (Condensed Matter) is also new to metamaterials so I couldnt go to them for advise as to progression the experimental/computational part of my thesis.
Thank you very much if you have gotten this far, and any advise or tips regarding my questions are greatly appreciated!!

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• Computer Science & Programming: Android AWS Azure Blockchain Cryptocurrency Smart Contracts C C# C++ Cloud Computer Organization and Assembly Languages CSS Data Science Data Structures and Algorithms Deep Learning Design Patterns Game Design and Development iOS Java Javascript Machine Learning MATLAB MySQL Networking NoSQL Object Oriented Programming Operating Systems PHP Principles of Computer Science Programming for Virtual Reality Programming Languages Python R Robotics Ruby Software Engineering SQL Swift Web Development

MY EDUCATIONAL SOFTWARE OF EXPERTISE:

• Acellus ALEKS Aplia APEX Learning Badgr Blackboard Blink Learning Brightspace / D2L Canvas Cengage CengageNow Childsmath Cisco ConnectMath Connexus CPM Crowdmark EViews Edmentum Examity Excel Garch Google Classroom Google Education Gradescope Hawkes Learning Honorlock iClicker InQuizitive (Norton) Java Kaltura Khan Academy Knewton Kryterion LaunchPad MATLAB Maple MasteringChemistry MasteringPhysics MathXL Mathematica McGraw-Hill Connect MegaStat Microsoft Teams Microsoft Access, Word, Excel, PowerPoint Mindtap Minitab MonitorEDU Moodle MyAccountingLab MyEconLab MyFinanceLab MyITLab MyMathLab MyOpenMath MyPsychLab MySocLab MyStatLab NCSS Outlier Pearson MyLab and Mastering Piazza PlatoWeb Prezi Proctor360 Proctorio Proctortrack Python R Respondus Lockdown Browser with Webcam SAM Sapling SAS SPSS Socrative Stata StraighterLine Turnitin VoiceThread WebAssign WebEx WebWork Wiley WileyPlus Zoom

TOP 20 REASONS WHY I'M THE MOST LEGIT EXAM, HW, ONLINE CLASS TUTOR ON REDDIT:

1. Team of U.S. Academic Experts: I and my team of dedicated academic experts complete all types of academic coursework for students in most math, English, science, business, humanities, social Sciences, computer programming, and foreign language classes on a 24/7/365 full-time round-the-clock basis. This is not some part-time gig for me. It’s literally my primary source of income. I can regularly make myself available to help students with last-minute & same-day academic requests.
2. Essay Writing Skills: I can write essays & research papers in native U.S. American English and fluent Canadian English using APA MLA Harvard Chicago Vancouver OSCOLA IEEE formatting & citations.
3. 75+ Types of Academic Software: I am highly skilled & experienced in using over 75+ types of academic software and educational platforms including the following: ALEKS, Blackboard, Brightspace, Canvas, Cengage, WebAssign, ConnectMath, Crowdmark, D2L, Moodle, Pearson MyLab and Mastering, MyMathLab, MyStatLab, MyOpenMath, StraighterLine, WebWork, and Wiley.
4. Can Change IP Address: I have multiple reliable VPN software including: NordVPN, SurfShark & ExpressVPN that allows me to successfully change my computer’s original New Jersey IP address to any major city in the U.S. & Canada to avoid raising red flags with students’ online class software.
5. Proctored Exam Help: I have developed multiple highly effective methods of helping students with exams, tests, and quizzes that are proctored by software like: Respondus Lockdown Browser with Webcam, Honorlock, Examity, Proctorio, Proctor360, Proctortrack, and ProProctor using 3 highly effective proven methods. Option 1 - WhatsApp: I use WhatsApp to have the student discreetly text me photos of the exam questions outside of the webcam’s view and I text them the correct solutions to the exam questions. Option 2 - Screen Share: Using screen share software like Zoom to see the student’s screen displaying the exam questions and I text the correct solutions. Option 3 - Remote PC Access & Control: Using remote computer access software like to control the student’s mouse and keyboard from my own computer.
6. Study Help Apps: I have over 15+ paid subscriptions to a wide range of study help apps, software, websites, and programs to help me solve exam & homework questions faster and more efficiently. Some of these resources include: Brainly, Chegg, CourseHero, Quizlet, SymboLab & WolframAlpha.
7. Calculators & Math Software: I have access to a very sophisticated graphing calculator and various mathematical software that provides step-by-step solutions to complex mathematical problems within seconds, allowing me to provide exact solutions to the student in a timely manner.
8. Test Taking Techniques: I have developed highly effective methods to determine the correct answers to questions that I’m not already familiar with including process of elimination, working backwards, quickly searching for similar questions online, and utilizing standardized test taking techniques taught only in elite standardized test prep tutoring programs.
9. Handwriting & Scanning Apps: I have impeccable handwriting and a high-quality mobile scanner app that allows me to scan written solutions in very legible high-definition JPG, PNG, and PDF formats.
10. Live Exam Help Videos: I am the only verified U.S.-based online exam hw online class help tutor with a highly successful YouTube Channel where I regularly upload live unedited videos of me actually completing exams, quizzes & homework assignments for other students and clearly explain my entire thought process and display on-screen all the steps, apps, websites, and software I use to compute the correct answers.
11. Flexible Payment Methods: I offer negotiable rates, multiple payment methods (PayPal, Venmo, Cash App, Zelle, anonymous credit & debit card payments via online invoice), and flexible payment plans: weekly (most expensive), monthly, half-now / half-later, and all-up-front (least expensive).
12. Money Back Guarantee: I have won multiple academic awards for my exceptional skills & expertise in math. I guarantee overall A & B grades for all coursework completed. Plus. I also offer a 50% refund for C+, C, and C- scores, and a full 100% refund for D+, D, D-, and F scores.

HOW I CALCULATE FINAL RATES:

• Exams & Quizzes: Final rates for exams and quizzes depend on various factors including: whether or not there is proctoring, how many hours the exam is, total number of questions including sub-parts, preferred method of me delivering solutions, whether it's show all work or just the answer only, and whether the assessment has a flexible window of time to complete or a fixed & rigid start and end time.
• Full Courses: Final rates for full class help depend all the foregoing plus: total number of hw, quizzes, exams, discussion posts, and other academic tasks left that need to be completed, total number of weeks or modules left in the class to complete, and whether there is required multi factor authentication for logging in like Duo Push or text passcode.
• Essays Papers Discussion Posts: Final rates for writing tasks depend on the required number of words or pages. topic of interest, type of citations, required number and type of sources & bibliography style , level of research required, and type of additional software required to complete the essay like: Excel, R, or Minitab.

Paid Help from Hiraedu: If You're struggling to handle your comptia or any other WGU Exam or any other coursework, get help from Hiraedu and pay after the exam. Contact details for Hiraedu is: WhatsApp: +1 (213) 594-5657 OR Call: +1 727 456 9641
ABOUT MY RATES & PAYMENT OPTIONS:

• Rationale for My Rates: I sincerely believe my rates are more than fair considering my education, skills, native born U.S. resident status, legitimacy, and the substantial amount of value, stress relief, and saved time & energy I’d be providing you in exchange for my valuable, irretrievable time, energy, and effort.
• Disclaimer About Rates: Completing someone else's exam, essay, or homework assignment is obviously NOT something you can just freely ask anyone to do, especially on the internet. Therefore, such help should be well-compensated. Services that are reliable and deliver high-quality results are difficult to find and are very high in demand. Thus, I expect to be compensated fairly for all the value, stress relief, and saved time & energy my services provide. However, I may be willing to negotiate rates if necessary.
• Payment Methods: I accept PayPal (required for all Canadian students), Venmo, Zelle, Cash App, and anonymous credit & debit card payments via online invoice.
• Payment Plans: I offer the following payment plans for my services: weekly (most expensive), monthly, half-now / half-later, and all upfront (least expensive).
• Money Back Guarantee: I guarantee the following grades for coursework completed: A+. A, A-, B+, B. and B-. However, I offer a 50% refund for C+, C, and C- grades, and a full 100% refund for D+, D, D-, and F grades.

CURRENT RATES -- AS OF SUMMER / FALL 2022 -- SUBJECT TO CHANGE:

• Full Class Help Rates: $595 – $2495 USD
• Exam & Test Help Rates: $150 – $350 USD
• Quiz Help Rates: $60 – $180 USD
• HW Assignment Help Rates: $60 – $420 USD
• Essay & Paper Writing Help Rates: $19 – $29 USD per 300 words

THE OBLIGATORY "IS THIS A SCAM?" QUESTION:
Considering the fact that you found my contact information online, it’s understandable to be skeptical regarding the legitimacy of my services. Therefore, I’m willing to do all of the following to help you feel more secure in trusting me with your academic needs:

• Engage in a Telephone interview: Speak with you on the phone and answer any questions you may have so that you have the opportunity to assess and analyze my tone, articulation, and accent. I’m a New Jersey-born Irish/Italian-American, but I have been told that I speak in an erudite & articulate suburban American accent with a “professor style” voice somewhat resembling the voice of actor: Ben Stein.
• Provide Telephone References: Provide you with the contact information of students who have utilized my services in the past who would be more than willing to vouch for my skills.

MY REBUTTAL TO THE OBLIGATORY “IS THIS A SCAM?” QUESTION:
At the risk of sounding arrogant, I consider myself to be at least marginally more intelligent (both academically & socially) than the average person. Therefore, if I ever decided to suddenly risk prison time, risk my reputation, and risk enduring the wrath of modern-day “cancel culture” by scamming people out of their money:

• Not Worth the Money: I certainly wouldn’t do it for such paltry amounts of money. (i.e., anything less than $1,000 per victim.)
• Most Students are Broke: I certainly wouldn’t choose high school & college students as my “target audience” to scam, considering that most people without college degrees have abysmally low annual incomes.
• Waste of Time & Energy: Communicating back and forth with potential clients is an absurdly long time sink since only less than 10% of all potential clients who reach out to me actually become paying clients of mine.
• All My Payment Apps are Still Active: If you pay me to provide academic services and I don’t deliver, you can always dispute the payment with the payment app and easily get your money refunded. If I were in the habit of swindling money from people, then all of my payment accounts would have been investigated and be completely shut down by now.
• My Mission: Thank you for taking the time to read my Reddit post. I take what I do very seriously and I always strive to get the highest possible grades for all students who entrust me with their coursework.
• Closing Words: Please feel free to reach out to me if you're sincerely interested in having help you with your school work. I am available via text, email, and call almost 24/7/365.

Paid Help from Hiraedu: If You're struggling to handle your comptia or any other WGU Exam or any other coursework, get help from Hiraedu and pay after the exam. Contact details for Hiraedu is: WhatsApp: +1 (213) 594-5657 OR Call: +1 727 456 9641
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