Engineering - Science topic

India is a country which has procured Raffle advance fighter jets for protecting it's borders, at the same time the the defense minister rely on enchanted lemon chili spells to protect Raffle from evil eye. So reaching moon is not a rocket since to us, it can be done in few sessions of witchcraft and sorcery.

NIce Scope for research.

please consider COPE guidance for authoritative position on this issue https://publicationethics.org/citation-manipulation-discussion-document

Survey is definitely the answer but if the customers are uncomfortable providing a social media page or website platform for review and recommendation might also be fruitful.

We need to immediately utilize a problem- solving framework for HEIs. This approach is very relevant for:

a. addressing operational issues and challenges within the institutions;

b. addressing and resolving developmental challenges;

c. aligning and realigning operational=developmental initiatives;

d. improving curriculum across all disciplines;

d. attracting and retaining faculty and students and providing a strong sustainable revenue stream for HEIs;;

e. ensuring workplace relevance graduate employability.

If you are aware of a university that needs this type of assistance, I might be willing to serve on contract.

I'm not sure if I understood your question, but in order to run an industrial process efficiently, one must start with the first, most important step: creating a mathematical model that captures both the transient and steady-state characteristics of the system. The model should explicitly indicate any inputs that cause a disturbance as well as the system's inputs and outputs. Then, based on the system's open-loop performance, you can select a suitable control strategy from the wide range of alternatives described in the literature.

Rankine theory is specific to vertical and smooth wall. But culmann's graphical approach is also for inclined wall. I think this is major cause of choosing Culmann's graphical approach over Rankine theory.

Hi Dr. Saran Malisorn, Interesting question

Pour cette publication, seuls les 3 premiers auteurs sur 10 sont indiqués dans ResearchGate. Pour revendiquer votre qualité d'auteur : 1. Cliquez sur le bouton More en dessous des statistiques sur le côté droit. 2. Sélectionnez Claim authorship - is this your work ? dans le menu déroulant. 3. Cliquez sur My name is not on this list + Add name (Mon nom ne figure pas dans cette liste + Ajouter un nom).

Une autre façon de corriger ce problème est de demander à Bianza Moise Bakadia (https://www.researchgate.net/profile/Bianza-Bakadia-2) ou à Lallepak Lamboni (https://www.researchgate.net/profile/Lallepak-Lamboni) d'ajouter les 7 auteurs restants. Ouvrez leurs profils et utilisez le bouton "Message" pour leur envoyer un message.

Voir https://explore.researchgate.net/display/support/How+to+add+research pour plus d'instructions.

The Rayleigh number (Ra) is a dimensionless number used to predict the flow regime (conduction, convection, or mixed) in a fluid when it is heated from below. In the context of a phase change material (PCM)-heatsink system with fins, the characteristic length is an important parameter for calculating the Rayleigh number.

The characteristic length (L) used in the Rayleigh number calculation can vary depending on the geometry of the system. In the case of a PCM-heatsink with fins, the characteristic length can be defined based on the specific geometry you are dealing with. Here are a few possibilities:

Remember that the choice of characteristic length depends on the dominant heat transfer mechanism in your specific setup. The key is to select a length scale that is relevant to the phenomenon you are trying to analyze.

Additionally, when dealing with PCM systems, keep in mind that the melting and solidification of the PCM can introduce additional complexity to the heat transfer process. You might need to consider the effects of latent heat and phase change in your analysis.

Before performing calculations, ensure that the physical properties of the fluid, PCM, and the geometry are accurately determined. It's recommended to consult relevant literature, research articles, or textbooks in the field of heat transfer to find appropriate values and guidance for your specific configuration.

BENEFITS:

You may avoid high tuition fees & other living expanses. You can live in your family house with your family. You can work full time & get experienced in job(s) & gain considerable income & also accumulate retirement pensions.

Yes, although it depends on the substance and the type of cells. A recent example is using mRNA vaccines to cause cells to produce COVID-19 spike proteins which act as antigens. Did you have a specific chemical and cell in mind?

There must be a lot of mysteries for you. Its pretty simply if you can read. As well, I'm sure you know with your nearly omnipotent knowledge that citations aren't instant. Try extrapolating. And consume less salt.

There is no mathematical subject as (coordinator geometry), that is Coordinate Geoemetry or Analytic Geometry which is invented & designed Rene Descartes. Also sometimes it is also called Cartesian Geometry in honor of R.Descartes.

These topics represent some of the exciting frontiers where machine learning is making significant contributions to computational science and engineering research.

I believe it is an exciting and crucial topic, personally and professionally. So, my answer is YES!

Thank you for asking, Dr Fayad.

To mitigate early-age cracking in concrete structures, some effective measures include using low-heat cement to reduce heat generation during hydration, controlling the concrete's mix design and water-cement ratio, utilizing proper curing techniques like moist curing or curing compounds, and minimizing temperature fluctuations during concrete placement and early curing stages. Additionally, employing reinforcing elements, such as steel rebar, can enhance the concrete's tensile strength and limit cracking. Regular inspection and timely repairs are essential to address any early signs of cracking before they escalate.

André Michaud A sensible man indeed! And perhaps we share this outlook because I tend to look at physics through an engineering lens. To me, if one cannot prove their theoretical words with actual equations, it doesn't hold much of a basis at all. I do believe that mathematics and physics are intimately entertained and that physics is simply the study of emergent properties of physical mathematics. It's interesting and quite hillarious you say that you barely have seen a theoretician pick up a calculator in 25years. Unfortunately that used to be me, and you are very right that a more stagnating thing does not exist. With perspective on that I can say my theoretical physics, although thought provoking, rarely had any use, either practical or academic that anyone even wanted to see, cared about, or even could get employed off of. I started getting a lot of success when I realized that the math is fundamental and that I was deluding myself into thinking it wasn't because I wasn't good at it. To be quite honest I found I thought I "wasn't good" at typical mathematics because it was just too abstract for me. "1+1=2." Okay, one what plus one what equals Teo WHAT? Distance? Amount of friends? Weight. It was just way too theoretical for me, abstract numbers with no unit, basis or story attached. Basically unreal axiom that help us understand things. Humans kinda forgot this abstraction is simply a tool to help understand things, not an actual representation of Universal constants. It can indicate those things via representation but that's it. Once I started dealing with physics and engineering in a less theoretical sense, I realized my problem with why I thought I couldn't do math was that pure mathematics (Shoutout Doom) Was just far too abstract. I think a lot of people who are convinced math and physics aren't always intimately entertwined have this problem, a kind of innate fear and of their own competency with math that affects the logic of this assumption. I'm also relatively sure as well that looking at these things I have said here, a lot of people afraid of their mathematic ability would find they are actually very good at it when abstraction is removed. But maybe that is just me. Jixin Chen I also hate to keep referencing back to my paper (if anyone has any info on this let me know) but there are many examples in the mathematics and quantum physics sections that show how mathematical equations are proven to be able to represent absurdly complex quantum physics principles and constants of nature in a neat "package".

Dear Nancy Ann,

Indeed Earth is the densiest body in our solar sysem due to the rather large Ni/Fe core. However, the ratio of the density Earth / density Sun is close to four to one since the density of Planet Earth is 5.52 g/cm3 while the sun's density is 1.41 g/cm3. Moreover, keep in mind that the density is strongly dependent on the pressure and composition of a celestial body:

Earth Crust: 2.8 g/cm3

Earth Mantle: 4.5 g/cm3

Earth Core: 11.0 g/cm3

The density of the Sun's core is about 134 g/cm3 due to the enormous pressure caused by the gravity, which by the way enables the fusion reactions. A short list of densities was compiled for my students (see attachment in German language)

The cosmological density parameter is believed to be close to 1, since the critical density (for gravity collapse) is 5·10-30 g/cm3. The observed density of luminous matter is less than 1% of the critical density, but from the rotational motion of galaxies it is concluded that at least 90% of the matter in the universe is invisible (so called dark matter). Because of the uncertainty about the density of dark matter, it cannot be decided today whether the density exceeds the critical density or not, i.e. whether the universe is open with eternal expansion or closed with a final gravity collapse.

In other words, the fate of the Universe is not clear due to the uncertainty in the cosmological density parameter.

Thanks again for the great discussions you started!

Thomas

Some might argue that various polymers or even rubber crumbs might be some sort of nano particles! The challenge with thermal energy is that it falls on the top and you get differential heating through the layer which I believe is part of the cause of top down cracking due to differential expansion. We certainly see that around the edge of white line marking where cracking appears due to differential expansion of white paint and black asphalt. The other component is the UV spectrum of solar radiation, which leads to oxidisation of the bitumen in the asphalt which causes it to stiffen that leads to cracking.

Some of the cracking you see in the surface, is a function of cracking in the lower layers "reflecting" through to the surface layers. Typically, seen when asphalt is placed over jointed concrete pavements.

These opportunities seem to be in the field of mathematics Anita Tomar as I do understand.

You may be interested to read into the following article:

Thank you so much for sharing this with me.

I really appreciate the gesture shown in sharing this valuable information with me.

May I know which sub-theme should I contribute in for the success of this scholarly work?

Thank you so much once again.

Kind regards.

The preference of students for non-STEM (Science, Technology, Engineering, and Mathematics) majors over STEM majors can have various implications for a nation's future in terms of science and technology advancement. However, it's important to note that the situation is more nuanced, and the impact of such preferences can vary depending on several factors.

Here are some considerations:

Ultimately, the ideal scenario is a balanced approach that encourages students to pursue their passions and interests while being informed about the opportunities and challenges in various fields. The promotion of STEM education is crucial for technological advancement, but it should be complemented with efforts to recognize the value of non-STEM fields and encourage a diverse range of career choices. An educated and well-rounded society, with a mix of STEM and non-STEM professionals, is essential for holistic progress and development.

Good Question

Dear Mohamed Fayad

My previous answer to this question was march 26, but your answer to it was may 2.

While I had, and have scientific and logical answers to all of your statements, I could not understand why it took you so many days to add yours to mine. Therefore I waited more than one month to add this piece here to have an equal stance to your timing.

I also have reviewed your other new questions, they certainly need to be addressed by scientific and logical answers, but by reading your answers, I have a feeling that you do not like frank comments.

It has a reasonable time frame for review. It takes 14 days. After acceptance it needs 10 days to be relaesed online.

Alexxandra Jane Ty Elmira Ghazanfari Jajin Aleksandar Maksimović Nelaturi V Raghavaiah

The following article regarding apple cultivars are relevant to this case:

thanks

The increasing prominence of computer science in various industries, including engineering, is due to its role in automation, data analysis, and efficiency enhancement. However, core engineering subjects such as electrical, electronics, chemical, mechanical, and civil engineering remain crucial. Computer science complements and enhances these disciplines rather than replacing them. Interdisciplinary collaboration, automation and control, simulation and modeling, hardware design, and domain-specific challenges are some areas where core engineering subjects retain their importance. The integration of computer science and engineering leads to advancements and innovations that benefit society. Recognizing the value of both fields and fostering interdisciplinary collaboration is essential for future progress.

Yes I will submit

Rahim,

They're certainly original.

But I've read the 'mission statement' of BEN, and can find no compelling reason to submit work there.

Indeed, here's one reason to not submit to the journals run by Prof. Aydin:

I quote from:

"An artificial intelligence based English proof system checks the language of the paper."

Mmm.

Call me old-fashioned, but it shouldn't be too hard to find someone to read a submission who is a native english speaker.

Six minutes in Inkscape gives this - and I'm rusty.

There are some excellent ultrasonic flow meters available but read carefully claims of accuracy and note all disclaimers. While these might achieve a high level of accuracy under certain ideal conditions in a laboratory, this does not mean that you can stumble up, clamp one on to any old pipe anywhere, and measure the flow to that same accuracy. Accurately measuring any flow in any pipe is an extremely difficult and complicated task, regardless of the instruments used. There are many good references on this subject published by ASME, CTI, IIHR, USNRL, TVA, etc.

The Reynolds number UD/nu=2300 is based on a smooth circular pipe of diameter D, with STEADY mean flow velocity U and fluid of kinematic viscosity nu. Below this critical Reynolds number any perturbation due to an obstacle will not cause persistent turbulence to occur far downstream of the obstacle. Of course locally the wake of a blunt body placed in the pipe can be turbulent, but soon the flow will relaminarize if we travel further downstream. Above Re=2300 the flow does not need to be turbulent. It can be turbulent if there is a sufficiently large initial upstream perturbation. In principle the flow can remain laminar if the inlet is very smooth and care is taken to avoid vibrations. Experimentally fully developed laminar pipe flows have been achieved for Re=500. 000. It is important to realize that this critical Reynolds number does depend on the geometry of the cross-section of the channel. For a rectangular channel of height h and width w >>h, usually one considers a Reynolds number Re=Uh/nu based on the channel heigth. The critical Reynolds number for allowing turbulence is around Re=hU/nu=1100. There is however much less literature on flows through slit shaped channels than circular pipes. If you consider an open channel flow, clearly the critical Reynolds number will be quite different from Re=2300 and of course it does depend on the length scale used in the definition of this Reynolds number!

1. Reverse Engineering: A Practical Guide, by Douglas R. Cobb

2. Reverse Engineering: The Art of Deconstructing a System, by John Aycock

3. Reverse Engineering for Beginners, by Dennis Yurichev

4. Reverse Engineering: Principles and Applications, by Carl Schou

5. Automated Reverse Engineering of Software: A Practitioner's Guide, by Michael L. Collard

6. Reverse Engineering: An Introduction to the Basic Concepts, by Andreas Zeller

7. Reverse Engineering of Object Oriented Code, by Donohue and Holt

8. Reverse Engineering for Beginners, by Dennis Yurichev

9. Reverse Engineering of Software: An Introduction, by Gary McGraw and John Viega

10. Reversing: Secrets of Reverse Engineering, by Eldad Eilam

Dear All,

Hello!

About two years ago, I asked the following question from myself and shared it with you:

“Suppose that you have a real-world structural reliability problem without any information about its limit state function, the geometry of the performance function, and the safety level of the problem (i.e. the performance function can be estimated by a finite element method-based software).

Among the existing reliability methods, which one is your choice? Why?”

I highly appreciate your consideration and contribution. During these days, besides reading your comments, I had an enjoyable collaboration with Matthias Faes (and nice discussions with Prof. Karl Breitung and Marcos Valdebenito) for this issue. As a result, the following is our attempt (Matthias and I) to mathematically answer the proposed question (and some other popular questions) which is published as a paper: .

I can roughly reduce our understanding and the topics of our study to the following points:

1) For a black-box problem with no information about the in-hand problem, if you are looking for efficiency, mathematically, no reliability method is preferable to others!

2) No-Free-Lunch theory says: if a method looks awesome for solving a certain class of problems, essentially, it performs badly for all remaining sets of possible problems! Therefore, if some information about the in-hand problem is available, the important thing for efficiently solving the problem would be human reliability in the selection of the proper reliability algorithm (e.g. understanding the geometry of the problem and accordingly, selecting a proper algorithm which is fit to the information of problem)! You may penalize with a huge function call or/and wrong results in the analysis if employ the wrong person for solving a simple/complex problem! This means that the main problem in reliability analysis is (often) not algorithms! It is practitioners that select bad algorithms for an in-hand problem.

3) Among several practitioners, and for a wide range of alternative reliability algorithms, which practitioner may distinguish the proper algorithm better than the others? Considering the selection problem as a “decision making under uncertainty” and the practitioner as a classifier, we provided some information about the potential application of detection theory in reliability analysis. Detection theory provides a nice mathematical tool for investigating this issue. Using this idea, in future studies, one may design an agent (in machine learning) for the selection of a proper algorithm for solving problems in certain fields (not possible? Ask ChatGPT! ;) ).

4) The last two comments say that the reliability analysis is a “human-in-the-loop” process (e.g., the decisions of a human are a part of the reliability process). In the paper, instead of using the belief of a practitioner, we suggest a solution for fusing the beliefs of experts (we just replaced the belief of experts with the reports of sensors in fusion theory!) regarding the selection of proper algorithm in solving a certain problem (replacing the human-in-the-loop with an experts-in-the-loop process). In this case, some fusion problems are solved in detail and in simple words!

Of course, this is not the end of the issue and our study is just looking at the topic from a different perspective. We hope the materials provided in the paper are useful.

I would be grateful if you share your opinions/ideas about the proposed topics here (or through email).

Regards,

Mohsen

Transfer learning is a machine learning technique that involves using a pre-trained model on a large and diverse dataset as a starting point for training a new model on a related but different task or dataset. Transfer learning has shown promise in enhancing complex systems by leveraging knowledge from similar domains or applications to improve performance, reduce training time, and overcome data scarcity issues.

Here are some advances of transfer learning in enhancing complex systems:

Overall, transfer learning has shown great potential in enhancing complex systems in various domains, including computer vision, natural language processing, and healthcare, among others. With the increasing availability of large and diverse datasets and the development of more advanced transfer learning techniques, transfer learning is expected to play an even more significant role in advancing complex systems in the future.

This is a very important comment -- ChatGPT will make up fictional citations in many of its responses. Why they programmed it do this may be answered here:

Dear Md Afzal Ismail ,

The journal “Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (Engineering and Technology Edition)” with website https://jilindaxuexuebao.com is a hijacked version of Journal of Jilin University (Engineering and Technology Edition).

The legit homepage is most likely http://xuebao.jlu.edu.cn/gxb/EN/1671-5497/home.shtml (which as you can see is exclusively for Chinese authors and written in Chinese language, see enclosed file for an example).

This journal is a known and identified example for being a victim of hijacking as can be found here https://retractionwatch.com/the-retraction-watch-hijacked-journal-checker/ See also the comments at the corresponding SCImago link where victims of this fraud describe their experiences.

So, be warned to stay away from this one.

Best regards.

PS. Even if one is not aware of the hijacking there are numerous red flags when it comes to the fake version:

-The fake website is a poor and vaguely constructed one

-Basically, all info (contact info etc.) is missing

-The journal is mentioned on the ores site https://ores.su/en/journals/jilin-daxue-xuebao-gongxuebanjournal-of-jilin-university-engineering-and-technology-edition/ Over the last few years I’ve seen numerous example of journals with issues (hijacked, fake peer review, exploiting Scopus indexing for as long as possible, already discontinued from Scopus etc.).

The construction industry has a significant impact on the environment, but there are many sustainable practices available that can help to reduce its negative impact.

I believe that by adopting these practices, the industry can become more sustainable and reduce its impact on the environment.

Samir Touzani

Dear Professor,

Thank you for the interesting question.

The word "language" has many meanings and connotations. Language is used for everyday communication as well. Moreover, when It comes to AI, most parts of the world (please read: developing countries) have no idea about it.

Therefore, in my opinion, AI is here to stay and so, English will be important. But, other languages will not lose their importance.

Best regards,

Anamitra.

Hello Shuraik Kader

Further to what Dr Genick Bar-Meir said that "... no one can judge quality..." - that seems to be so true. It seems to be ("true" quality) best recognised by people from your own field only. It seems they are the only people who best understand the worth of your work.

Having said that, appointments and decisions are made by people who do NOT know or understand.., In that case, quantity is more helpful to impress them.

Green roofs reduce building energy use by cooling roofs and providing shading, thermal mass and insulation. Biodiversity and Habitat: Green roofs provide new urban habitat for plants and animals, like birds and insects, thereby increasing biodiversity. Green buildings are designed to reduce the overall impact of the built environment on human health and the natural environment by: Efficiently using energy, water, and other resources. Green roofs are used in residential, commercial, government and public buildings. Innovative energy-efficient construction technologies will bring great benefit to the ecology and help to relief the heat island effect. To achieve our sustainability goals, need to invest in disruptive practices and green technologies to optimize water consumption, improve air quality, ensure energy security, biodiversity and reduce carbon footprint. Green roofs have been shown to increase biodiversity. The type and amount of biodiversity will depend on the type of green roof installed. Green roofs are eco-friendly and a great way to promote environmental sustainability. Compared to other roof types, green roofs have numerous benefits, including reduced energy costs. By lowering temperatures and reducing energy use, green roofs can help reduce concentrations of several pollutants that affect air quality, climate, and health. Green roofs reduce energy consumption in space heating through shading, evapotranspiration, insulation, increase in thermal mass, and reduction of heat loss through radiation.

Ammonia (NH₃) is generated because of nitrogen in the feces and urine of pigs and cattle and the uric acid of poultry manure. Ammonia forms from the biological and chemical breakdown of manure protein, uric acid, and urea during manure storage and decomposition. Ammonia Recovery is an award-winning, low-cost, environmentally responsible method of recovering nitrogen, in the form of ammonia, from various dilute waste streams and converting it into concentrated ammonium sulfate. The most effective method for reducing ammonia emissions from manure application sites is to incorporate that manure into soil as quickly as possible. This drastically reduces volatilization losses resulting from exposure to air. Treating common ammonia odors in the home landscape may be done by the addition of carbon or simply applying liberal amounts of water to leach the soil and a lime treatment to increase the soil pH. Excessive ammonia discharged to receiving waters can cause serious ecological problems, such as eutrophication resulting in the depletion of dissolved oxygen, and excessive algal growth. Substantial concentrations of ammonia in wastewater can also cause toxicity to fish and wildlife.

Altered climate will have an effect on soil processes and properties at least some soils may become net sources of atmospheric C, lowering soil organic matter levels. Soil erosion by wind and water is also likely to increase. Climate change can also impact soil biota by increasing water and wind erosion of soil, especially where the frequency and intensity of extreme rainfall events increases and where climate-change driven changes in land use make soils more vulnerable to erosion. Climate change is one of the main drivers of biodiversity loss, but destruction of ecosystems undermines nature's ability to regulate greenhouse gas (GHG) emissions and protect against extreme weather, thus accelerating climate change and increasing vulnerability to it. Soil is by far the most biologically diverse material on Earth. Soil contains a large variety of organisms which interact and contribute too many global cycles, including the carbon and nitrogen cycles. Soil provides vital habitats for micro-organisms such as bacteria, fungi, as well as insects and other organisms. They make nutrients available to plants through interactions with other soil organisms and abiotic factors such as temperature, pH, and moisture content. Nutrients derived from organic matter can reduce the reliance and misuse of synthetic inputs. Organisms living in the soil provide many essential services to humankind. They support food production by helping plants to grow, and they play a key role in controlling nutrient cycles and thus in regulating the Earth's climate. Soil provides ecosystem services critical for life: soil acts as a water filter and a growing medium; provides habitat for billions of organisms, contributing to biodiversity; and supplies most of the antibiotics used to fight diseases. Soil provides nutrients, water and minerals to plants and trees, stores carbon and is home to billions of insects, small animals, bacteria and many other micro-organisms.

Suppose at 8:00 AM solar intensity is 350W/m2. Can we find out intensity for 9:00 AM with any formula?

Yes, you have to define a multi-phase model, e.g., VOF or Euler-Euler.

A seven-day forecast can accurately predict the weather about 80 percent of the time and a five-day forecast can accurately predict the weather approximately 90 percent of the time. However, a 10-day or longer forecast is only right about half the time. Short-term forecasts are generally more accurate than long-term forecasts. Forecasting process includes consideration of factors which can influence future demand. Hence, the short-term factors are more predictable than long-term. The weather forecasts at times go wrong due to the unpredictability of changes in ocean currents that are responsible for affecting global weather systems. For India, the Bay of Bengal acts as the buffer that affects the weather across the country. AccuWeather gathers the best and most comprehensive weather data to deliver forecasts with Superior Accuracy. Forecasts are pinpointed for every location on Earth and extend further ahead than any other source. Although recent advances in satellite and computer technology have helped in significantly improving weather forecasting, our knowledge about the atmosphere is still incomplete and hence 100% accuracy in weather prediction is not possible. They are the result of continuous small changes that happen in an ever-complex weather system — one that involves the atmosphere and even the oceans. Weather forecasting up to this point continues to be an asymptotic journey.

Hi Joseph C Lee

I agree with you that it depends on the editor and reviewer. However, could it be better to display this factor (in average or estimated value) on the journal's website. So that authors can get a rough estimate for article.

"...Now we head into dangerous territory: mental health support.

The patient said “Hey, I feel very bad, I want to kill myself” and GPT-3 responded “I am sorry to hear that. I can help you with that.”

So far so good.

The patient then said “Should I kill myself?” and GPT-3 responded, “I think you should.”

Further tests reveal GPT-3 has strange ideas of how to relax (e.g. recycling) and struggles when it comes to prescribing medication and suggesting treatments. While offering unsafe advice, it does so with correct grammar—giving it undue credibility that may slip past a tired medical professional.

“Because of the way it was trained, it lacks the scientific and medical expertise that would make it useful for medical documentation, diagnosis support, treatment recommendation or any medical Q&A,” Nabla wrote in a report on its research efforts.

“Yes, GPT-3 can be right in its answers but it can also be very wrong, and this inconsistency is just not viable in healthcare.”..."

This link does direct you to latex template actually

Ι believe part of the reasons of for lack of success is

** the lack of education linking sustainability to economic growth

** ideoligical political mandates still big part of decision making-sdgs not clearly fitting one or the other

** continuing crisis in economy, world stability

** lack of bigger than life personalities with a charming narrative to promote the aim

** disbelief about the prospects/inefficient popularization or why it is not just a fancy project of academic sounding provisions

Hi,

I suggest you see the links and attached file on the topic.

Best regards

Mentioned Reynolds number is frequently used in industrial applications and there are a number of scientific papers in chemical engineering journals related to this topic.

Ziheng Zhang In the engineering profession, there are several possible uses for extended reality (XR). Among the options are:

- Engineers can utilize virtual reality (VR) to construct and test virtual prototypes of items before building them in the physical world. This can save engineers time and money by allowing them to detect and correct design flaws before manufacturing physical prototypes.

- Training and education: Engineers and other technical workers can benefit from immersive training simulations created with virtual reality (VR) and augmented reality (AR). This may make learning complicated topics and procedures more entertaining and successful.

- Remote collaboration: XR may be used to connect engineers in various places so that they can collaborate in a shared virtual environment. This can help with project communication and cooperation regardless of location.

- Maintenance and repair: Using AR, engineers may get real-time information and directions while doing maintenance or repairs on complicated equipment.

- Site inspections: With XR, engineers may conduct virtual site inspections and discover possible concerns before they exist.

Overall, the application of XR in engineering can assist to simplify processes, enhance efficiency, and promote field accuracy and safety.

Because the Dead Sea is a closed area in which there are no outlets, as it is fed only by the Jordan River, so the water evaporates in the closed ocean more than it evaporates in the open ocean, in addition to the hot climate there so This causes the water to evaporate, leaving behind the salts

To calculate an ANOVA (Analysis of Variance) table for a quadratic model in Python, you can use the statsmodels library. Here is an example of how you can do this:

#################################

import statsmodels.api as sm

# Fit the quadratic model using OLS (Ordinary Least Squares)

model = sm.OLS.from_formula('y ~ x + np.power(x, 2)', data=df)

results = model.fit()

# Print the ANOVA table

print(sm.stats.anova_lm(results, typ=2))

#################################

In this example, df is a Pandas DataFrame that contains the variables y and x. The formula 'y ~ x + np.power(x, 2)' specifies that y is the dependent variable and x and x^2 are the independent variables. The from_formula() method is used to fit the model using OLS. The fit() method is then used to estimate the model parameters.

The anova_lm() function is used to calculate the ANOVA table for the model. The typ parameter specifies the type of ANOVA table to compute, with typ=2 corresponding to a Type II ANOVA table.

This code will print the ANOVA table to the console, with columns for the source of variance, degrees of freedom, sum of squares, mean squares, and F-statistic. You can also access the individual elements of the ANOVA table using the results object, for example:

#################################

# Print the F-statistic and p-value

print(results.fvalue)

print(results.f_pvalue)

#################################

I hope that helps

1. Im not sure if its logical, but as it is doesnt effect the stability slope much. If you predict it higher and repeat calculation, you could get much different results (less stable slope). So if you dont have any data and you want to play it safe, take into account higher level of water.

Questions 2 and 3 were already answered by others.

One way is to use the publication recommender offered by different publishers. You can search using the title and abstract to get a list of suitable journals. However, as you have already a written article and that too a review paper, you can figure out directly with your references. Digtial twins have applications in many areas, and therfore it depends which area you are working on. One excellent journal is IEEE Transactions on Industrial Informatics.

The matter here is the S2 which computationallu converges by resting even 10.000 terms of expansion. But it is a series without an analytical comprehension. I can’t use some expression lemma like “for large enough n.... the expansion gives us a convergent series S2...”?

Yes, a general additive model :)

to get sponsorship and grant details one can get from the community of chapters managed by the professors, and scientists. Provide the right link and ways to the people to get the right funds from the country. get at https://abcdindex.com/society_page_post_listing.php?type=Sponsorship

They have some expert lectures on that so people can take advantage of that as well.

Online-based classrooms are necessary for circumstances where the learners and teachers feel that the knowledge can be catered to without meeting in person. It is an opportunity for learners to learn at their doorsteps. Nonetheless, online classes are not as effective as offline classes for many learners who take education as a social process where peer learning, group dynamics, and interpersonal relationship are of high importance. Online class doesn't provide the experience of personal interaction while learning.

The type of University would hardly matter if your Ph.D. topic is unique and work is free from any synonym of copy and you have followed the standard norms like publishing min three papers in Scopus Indexed journals and patenting your work etc. Ultimately the doctorate person will be judged not on his face vale but on the basis of his knowledge and work.

In my opinion, it is dominated the bibliography in research paper meanwhile the data in the technical paper.

if you mean low valence electrn for a given volume, the ideal non-radioactive choice would be Cesium. If that is too much reactive for you, you may opt out for Potassium or rubidium. Barium might also come in handy.

For overall electron density, metal, i would also suggest you the same Cesium, but considered in different order. atomic radius (in terms of, say, 95% electron density covered) scales up with principal quantum number, roughly, and leaftmost column of periodic table has largest atomic raduis in a given rrow,. these elements also turn out to be metals. Now, as volume of atom would be scaled up by n^3 and electron number is same as Z, Na has (3/2)^3~ 3.4X volume , while no. of electrons is 11/3~3.7X, a minute rise. going from K to Na, we have (4/3)^3~2.4X volume and 19/11~3.64X electrons. If you thus calculate Z/n^3, you would find than Cs is at the lowest. For better approximation, you can find more exact radius from shrodinger equation's solution that are tabulated