Representation - Science topic

Sorry, I don't have any idea.

Explore databases like JSTOR, PubMed, ScienceDirect, and ProQuest. Use similar keywords to conduct searches and journals might include "Cultural Anthropology," "American Anthropologist," or journals focusing on media and technology studies

You are indeed addressing an issue that is not formally codified in empirical qualitative social research.

David L. Morgan rightly points out the important argument: If 'n' (number of subjects in the survay) is very small, an indication of the number or percentage suggests an empirical and/or statistical representation that is not considered scientifically valid compared to the corresponding population. Do not be so impressed by the positions of your reviewers - they seem to disagree on this point as well. From this point of view, deal with the issue offensively: Explain how you proceed and why. And then you can use terms like 'one', 'half' or 'almost all'.

When discussing numbers and percentages, we should not ignore the essential underlying meaning of qualitative methods. Especially in the course of explorative research, qualitative methods are used to identify possible casual references in the first place and to initiate a process of theory building. In this way, theoretical approaches and empirical findings can later be coordinated and aggregated at a higher level. Only on such a basis does it make sense to use quantitative methods and to report formal numbers and percentages.

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According to the Treccani Dictionary (the most authoritative Italian dictionary) rappresentazione is "Il processo mediante il quale un contenuto di percezioni, immaginazioni, giudizi e concetti, si presenta alla coscienza, e quanto viene così rappresentato". Accordingly, 'representation' may apply both to the past and to the future and the re- prefix is no longer bound to its original Lat. meaning "back" --though even in Latin re- did not mean just "back". You may have a mental representation ( immaginazione, Vorstellung) of what will be the situation in Israel next month.

On the other hand, rappresentazione can have a more concrete, physical meaning, exactly as Vorstellung: La rappresentazione alla Scala dello Zauberfluete di Mozart. I do not know whether Engl. representation can have this meaning: I do not think so. As for French, représentation may refer, among many other meanings, to 'Action de donner un spectacle devant un public, en particulier au théâtre' and also to 'Perception, image mentale, etc., dont le contenu se rapporte à un objet, à une situation, à une scène, etc., du monde dans lequel vit le sujet'.

V is the volumen of your sample

@1%

I am a gerontologoist and aging expert. Memory LOSS is not normal at any age. The question is flawed because the premise is flawed. Cognitive slowing is normal with advancing age but that is not the same as memory loss. Think of the brain as a computer. An older computer chugs along because it has a slower operating speed. The memory in the computer is not lost, it is slowed. Besides, the older brain has more files than a younger one, right?

Hello. Unfortunately, my scientific interest is connected with another field of research. I can't help you. Have a nice day.

If you are looking at the relationship between the data points in two variables, then there are no points in the empty set, it is irrelevant.

Before cluster analysis, reducing variables is crucial. Correlation Analysis can eliminate redundant variables, while Principal Component Analysis (PCA) captures significant data variance in fewer components. Using Domain Knowledge or determining Feature Importance with Tree-based Models can also guide variable selection. Post-reduction validation ensures meaningful clustering remains.

Thank you Wanjing Lai. I think the number of arm entry is also low.

Business for community development

Thank you

Greater soil biodiversity is essential for maintaining important ecosystem functions, such as the processes that drive our plant and crop production. Soil biodiversity plays an important role in supporting the sustainable productivity of ecosystems and regulating multiple other ecosystem services, including nutrient cycling, organic matter decomposition, pollutant degradation, and pathogen control in terrestrial ecosystems. Soils are a key reservoir of global biodiversity which ranged from microorganisms to flora and fauna. The biodiversity has a fundamental role in supporting soil functions and, therefore, ecosystem goods and services associated with soils. The level of abundance and diversity varies from soil to soil, depending on factors such as organic matter content, soil texture, pH and soil management practices. In fact, did you know that soil comprises 25% of the world's biodiversity? If you want to know more about these overlooked organisms, keep on reading. In this article, we will explore their importance and the threats they face. The soil ecosystem is complex and heterogeneous because it comprises inorganic and organic components, water, gases, and various flora and fauna. After cropping, the residual recalcitrant crop wastes from crop plants, trees, and woody plants are dumped in soil. Soils are a complex system which involves biotic and abiotic elements, such as nutrients, minerals, organic matter and living organisms. This system is one of the main reservoirs of biodiversity on the planet. In fact, it is estimated that a teaspoon of soil contains approximately 50 billion microbes. Several factors contribute to species diversity, including habitat diversity, competition among species, and genetic diversity. Genetic diversity within a species not only is necessary to maintain diversity among species,but also contributes to the diversity of food, fiber, and medicines available from nature.

I believe it's more about how you use the tool rather than which tool. But Matplotlib can do quite well for many common requests. They have a library of examples where you can learn how to create more complex plots: https://matplotlib.org/stable/gallery/index.

There's seaborn (developed based on Matplotlib) as well, if you want something to be done real quick, try that. I'd suggest you start with Matplotlib first, understand their principles, and then move on to seaborn, where customization requires you to add more Matplotlib parameters. See the gallery here: https://seaborn.pydata.org/examples/index.html.

There's also plotly (https://plotly.com/examples/), suitable for developing interactive apps. It looks really potential, but is an independent platform from Matplotlib, so will take you a while to learn.

Pyramid ecosystem modeling can also be used to show energy flow through the trophic levels. Pyramids of energy are always upright, since energy is lost at each trophic level; an ecosystem without sufficient primary productivity cannot be supported. Pyramids of energy show relative amounts of energy available at different trophic levels. Pyramids of biomass show the total amount of living tissue at each trophic level. A pyramid of numbers shows the relative numbers of organisms at different trophic levels. Inverted pyramids of biomass can occur when the primary producer has a high turnover rate. Pyramids of energy are usually upright and are the best representation of energy flow and ecosystem structure. The pyramid of productivity or energy is the most efficient in describing the ecosystem. This pyramid shows how the energy passes from one level to another. Thus, it is widely used in describing the organisms of different kinds; namely producers, herbivores, carnivores, secondary carnivores and predators. Energy pyramids are used to show how much energy is available in each of the different trophic levels. Because the amount of energy is proportional to the amount of matter in an ecosystem, these pyramids can also show how much matter or biomass is available in each trophic level. Animals use energy for growth, movement and keeping a constant body temperature. This means that less biomass is passed on to the next trophic level. When animals egest , biomass is lost so less biomass and energy is passed on to the next trophic level. The ecological pyramids show the energy flow in the system. A biomass pyramid is the representation of total living biomass or organic matter present at different trophic levels in an ecosystem. Biomass is calculated as the mass of living organisms present at each trophic level in a given sample size. At the base of the pyramid are the producers, who use photosynthesis or chemosynthesis to make their own food. Herbivores or primary consumers, make up the second level. Secondary and tertiary consumers, omnivores and carnivores, follow in the subsequent sections of the pyramid.

Biomass is the dry mass of living organisms in an area at a particular time. A pyramid of biomass represents the mass of organisms at each trophic level. A pyramid of biomass is always shaped like a pyramid because the biomass always goes down from one trophic level to the next. As you pass along a food chain, the number of individual animals decreases at each trophic level. If you arrange these numbers on top of each other, they form a pyramid shape. Here's an example from a woodland food chain: All food chains form this shape. It is a pyramid of numbers. An energy pyramid, also known as a trophic or ecological pyramid, is a graphical representation of the energy found within the trophic levels of an ecosystem. The bottom and largest level of the pyramid is the producers and contains the largest amount of energy. Pyramid of numbers represents the number of individual organisms at each trophic level. Pyramid of biomass represents the biomass present at each trophic level while pyramid of energy shows the energy available at each trophic level. All three types of pyramids are useful for characterizing ecosystem structure. The pyramid of energy shows the rate of energy flow and/or productivity at successive trophic levels. The pyramid of numbers shows the relationship between producers and consumers at successive trophic levels in terms of their number. Energy pyramids are used to show how much energy is available in each of the different trophic levels. Because the amount of energy is proportional to the amount of matter in an ecosystem, these pyramids can also show how much matter or biomass is available in each trophic level. An energy pyramid shows the flow of energy at each trophic level in an ecosystem. A pyramid shape is used because energy is lost at each trophic level when organisms use it up. Pyramid of biomass shows the amount of biomass at each trophic level in an ecosystem while pyramid of energy shows the flow of energy from one trophic level to the next in an ecosystem. This is the key difference between pyramid of biomass and pyramid of energy. The importance of ecological pyramid can be explained in the following points: They show the feeding of different organisms in different ecosystems. It shows the efficiency of energy transfer. The condition of the ecosystem can be monitored, and any further damage can be prevented.

The pyramid of energy shows the rate of energy flow and/or productivity at successive trophic levels. The pyramid of numbers shows the relationship between producers and consumers at successive trophic levels in terms of their number. In this pyramid energy in each trophic level is considered as a level in the pyramid. Biomass pyramids show the relative amount of biomass in each of the trophic levels of an ecosystem. Biomass is simply the mass of living things in a particular trophic level. Terrestrial ecosystems usually have much more biomass in plants, such as trees and grass, and less biomass as you move up in trophic levels. A pyramid of energy shows the relative amount of energy available at each trophic level of a food chain or web. On average, about 10 percent of the energy available within one trophic level is transferred to the next level. A biomass pyramid is the representation of total living biomass or organic matter present at different trophic levels in an ecosystem. Biomass is calculated as the mass of living organisms present at each trophic level in a given sample size. It can be represented as dry weight in grams or calories per unit area.Describe why the pyramid shape is used to represent energy, biomass, and numbers pyramids. The pyramid is used because it can represent energy available at every trophic level, and at each level everything gets smaller as you go up the pyramid. An ecological pyramid is a graphical representation showing the relationship between different organisms in an ecosystem. It shows the flow of energy at different trophic levels in an ecosystem. Pyramid of number is an ecological / Eltonian pyramid. It is a graphical representation of a number of individuals at each trophic level. It puts organisms sequence-wise, with producers at the base and various consumers at successively higher levels.

A population pyramid can be used to compare differences between male and female populations of an area. They also show the number of dependents and general structure of the population at any given moment. The shape of a pyramid allows weight to be distributed evenly throughout the structure. Most of the weight in a pyramid is on the bottom and it decreases the higher you go. A pyramid is a three-dimensional shape. A pyramid has a polygonal base and flat triangular faces, which join at a common point called the apex. A pyramid is formed by connecting the bases to an apex. The shape of the energy pyramid shows that there is enough biomass energy contained in the primary producers at the bottom to support the predators at the top, even though energy is lost at each level. Ecological pyramids show the relative amounts of matter or energy in different trophic levels of an ecosystem. In most ecosystems, only about 10% of the total energy available at a given trophic level is transferred to the next level.The shape of the energy pyramid shows that there is enough biomass energy contained in the primary producers at the bottom to support the predators at the top, even though energy is lost at each level. A pyramid of energy represents how much energy, initially from the sun, is retained or stored in the form of new biomass at each trophic level in an ecosystem. Typically, about 10% of the energy is transferred from one trophic level to the next, thus preventing a large number of trophic levels. Energy pyramids are used to show how much energy is available in each of the different trophic levels. Because the amount of energy is proportional to the amount of matter in an ecosystem, these pyramids can also show how much matter or biomass is available in each trophic level.

Energy transfer between trophic levels is not 100% efficient. Organisms at each trophic level utilize some of the energy they consume for their own needs, leaving less energy available for the next trophic level. This contributes to a decrease in biomass as you move up the pyramid. Only approximately 10 % of the biomass from each trophic level is transferred to the level above it. This is why the pyramid of biomass gets smaller, as there are less organisms as we go higher up the trophic levels. Biomass shrinks with each trophic level. That is because between 80% and 90% of an organism's energy, or biomass, is lost as heat or waste. A predator consumes only the remaining biomass. Organisms tend to be larger in size at higher trophic levels, but their smaller numbers result in less biomass. Biomass is the total mass of organisms at a trophic level. In an ecological pyramid, what happens to energy, biomass and of species as you move up. They all decrease because energy is lost as it moves up each trophic level. Each trophic level requires more energy to sustain it, increasing competition for resources and causing number of organisms to drop.The amount of energy at each trophic level decreases as it moves through an ecosystem. As little as 10 percent of the energy at any trophic level is transferred to the next level; the rest is lost largely through metabolic processes as heat. An energy pyramid shows the flow of energy at each trophic level in an ecosystem. A pyramid shape is used because energy is lost at each trophic level when organisms use it up. An energy pyramid is a diagram that shows the transfer of energy in an ecosystem. An energy pyramid shows which levels in the ecosystem have more energy by locating them lower, and thus with larger levels, on the pyramid. An ecosystem is all of the living and non-living things in an area. A food chain describes the passage of energy between trophic levels. A food web is a set of interconnected and overlapping food chains. Food webs are interconnected, such as nearby land and marine food webs

Christian Lorenz

Aha,

p366, the Selene team shows their working!

"The solar irradiance is a solar spectrum resampled from MODTRAN4"

It seems that people are quite happy to use the raw solar spectrum as modelled by some tool (here, MODTRAN4). That ought to convince a revierwer.

In reallity this image is a Pauli representation from this web:

Dear Jean-Paul,

Qamar Ul Islam Thank you for your prompt and helpful response. I appreciate your insights and suggestions on how to resolve the discrepancy. I will follow your advice and check my code, numerical method, and solver parameters. I hope to get a better result with your guidance. Thank you again for your time and expertise.

Thanks a lot. I shall try this solution.

The more accurate representation of the actual feeding relationships in the ecosystem is the food web because it emphasizes the different possibilities of energy flow and interaction of the ecosystem. Energy transfer between trophic levels is not very efficient. Only about 10% of the net productivity of one level ends up as net productivity at the next level. Ecological pyramids are visual representations of energy flow, biomass accumulation, and number of individuals at different trophic levels.

I offer pure Platonism. The name of any finite entity is a hypostasis (literally - the lower state, and, perhaps, not of the first rank) of the corresponding primary archetype - which, in turn, is one of the hypostases of the Absolute. Accordingly, the name sets the trend for the development of the essence in the direction of the archetype. But only trend - the less pronounced, the higher the rank of the name as an incarnation.

Peter Breuer Thank you for your comment, he clarified, he pointed out the precise idea that I had in mind when I asked the question; This general theoretical question arose from a practical problem: the completion of (knowledge) graphs and the need to create an ontology, based on a set of axioms, to admit or reject new links (arcs) and objects (nodes). In fact, we are talking about a monotonic extension of the given original set.

In fact, the original set of statements is implicitly assumed to be consistent (nothing to say otherwise). But here's a small detail: speaking of "consistency" could be interpreted as assuming the existence of some kind of formal system. Probably the problem should be posed as emerging from a situation in which, there being some relation (binary, for simplicity), written (of course) in some formalized language (hence w.f.f.), representing a set of non-contradictory statements (here, not contradictory means the absence of a statement and its -semantically understood- negation).

And yes, the set of all statements is a (trivial) system of axioms.

As for the assumption of the presence of some kind of logic, it is not assumed. Here, significantly, it is relevant to take into account what is meant by logic; As far as I know, despite their historical and genetic relationships (in the sense of genesis), they are not synonymous, logic (syntactic approach) is (mainly) a kind of formal system.

Well, here I end my ramblings. Thanks for the comment.

Thank you, Ahmed Khalid Ahmed Asinger, for the explanation.

Hi Ruben,

I was also inspired by the research to add some clusters to my visualized lda model but I did not succeed although I tried different ways of visualizing by LDAvis or pyLDAvis.

I wonder if you found a way that could share with me?

Thank you!

Reactive power control by direct axis and quadratic axis components of field currents…..

Dear, there are two types of samples: random samples and random samples, and this depends on the size of the sample and other conditions. my regards .

I know this feed is old, but I'm working with CDK and trying to discern FP37 with a similar issue and cannot seem to find any resources on the matter.

Have you found a suitable reference since posting this?

Thanks in advance!

Dear Mohammed

Sometimes, if you install another program, it may change the Ansys server license settings. You may need to make the settings from the beginning again in the license manager. Have you recently installed a new program? Or VPNs may also make unwanted changes.

When estimating the molecular weight of DNA bands on an agarose gel, there are several factors that can affect the accuracy of the estimation, including:

Given these factors, it's difficult to say with certainty whether the bands observed on the gel are representative of the desired 511 bp fragment. However, the fact that the observed bands are within 10-20 bp of the expected size suggests that they may be representative of the gene of interest. It's also possible that the differences in size could be due to experimental error, such as slight variations in loading or migration. If accuracy is critical, it may be worth repeating the experiment and optimizing the gel conditions to improve resolution and accuracy.

These video playlists might be helpful to you:

Tensor space-time (TST) is a mathematical framework that extends the conventional MIMO (multiple-input multiple-output) systems to the space-time domain, allowing for the exploitation of the spatial, temporal, and frequency diversities in communication systems.

In satellite communication analysis, TST can be used to model the channel characteristics and design signal processing algorithms for optimal transmission and reception. One of the key advantages of using TST in satellite communication analysis is that it allows for the modeling of the channel as a spatiotemporal entity, which can capture the complex interactions between the satellite and the ground station, as well as the multipath effects, fading, and interference. TST can also be used to design advanced signal processing techniques such as space-time coding, beamforming, and interference cancellation, which can improve the communication performance in terms of data rate, reliability, and spectral efficiency.

Regarding the correlation between AI and tensor in communication systems, it is important to note that AI techniques such as deep learning and neural networks can be used to analyze and process large-scale tensor data, which can be generated by TST-based communication systems. By leveraging the computational power of AI, it is possible to optimize the signal processing algorithms, adaptively adjust the transmission parameters, and even predict the channel characteristics based on historical data.

I want to apologize cause I could not edit my previous posts Pls choose a more accurate representation and leave your commenrs Thanks

Sure, here you are:

Potato virus A (C4H4NO2I)n

The virus is a nanoscale object, I guess also with n molecules N-iodo succinimide (NiS) bound to it.

you mean like a dynamic diagram in audio editor? Never mind :) Not really my field. These were not the droids I was looking for. I will move along.

If want to know about the big things that are the sum how many things act, you need to know how many things act. Following is just a few concepts that need changing and my proofs of the changes:

The proofs that 4 constants ae changed by relativistic velocities as a PDF file will pop up when the following link is Left clicked: -------------------------------------------------------------------- https://drive.google.com/file/d/1e1ExWG-VyTR8PAPxU5OnfSzd86uj59nh/view?usp=share_link --------------------------------------------------------------------- A link to prerequisite proofs that all Doppler shifts change time and distance (axial, gravitational and transverse not just the transverse). -------------------------------------------------------------------- https://drive.google.com/file/d/1vGRBH1AgUOCP8_zp7fKxBTMPg-YP_-uh/view?usp=share_link -------------------------------------------------------------------- A link to: Proof of a version of the Schrodinger equation for relativistic velocities: ------------------------------------------------------------------ https://drive.google.com/file/d/1kh2d4fYFOd8rbS6tgyUbTA5zDZW-aUNH/view?usp=share_link-------------------------------------------------------------------------------------------- I hope you can make use of the above. Samuel Lewis Reich (sLrch53@gmail.com)

Thank you so much, Saad! I found your response so helpful and will go ahead to experiment with both encoding types.

Rafiq Issam Rafiq, In general, The energy gap between HOMO and LUMO indicates the molecular chemical stability. Red indicates the negative charge and green a positive charge. For more details and numerous articles please to a search using "What do green and red mean in HOMO and LUMO orbitals" in Google and/or Google Scholar

S ve p polarizasyonlarını temsil etmenin en iyi yolu onları x ve y eksenlerinde göstermektir. Bunlar için x ve y herhangi birini seçmek önemli olmayabilir. Ama en iyi yol s için x eksenini p için y ekseni seçilmeli ve Frekans ve açı değerleri buna göre ölçülmelidir. Dolayısıyla FDTD 'deki yapımın s ve p 'deki Polarizasyonu farklı değerlere ve ölçülere sahiptir. Ayrıca Frekans ve açıdan başka değişkenlere de sahiptirler.

Good evening, Ali Chebaiki,

This is Pedro Eduardo Ribeiro. I am PhD student and a PhD fellow at a research centre. I usually deal with Social Semiotics and Kress and van Leeuwen's approach. Hence, I think I can help you in some way.

First of all, I recommend you to read the book to understand their standpoints. Social Semiotics is very concerned with the context, more than Semiology. So that, they recommend many frameworks all over the book.

Usually, I make use of the representational, interactional, and compositional meanings to understand which meanings and discourses images produce. It depends on your focus. Mine is usually this one, as it goes along with some other works by Portuguese scholars, such as Silvana Mota-Ribeiro and Zara Pinto-Coelho. They have really interesting exploratory studies and very well explained notes on their methodological approaches.

Explaining in a more pragmatic way, to understand the sign-making is complex and there are many frameworks at your availability. In my case, I aim to explore those three meanings and I make use of Critical Discourse Analysis as well as intersectional approaches. For example, when analysing a magazine cover, what can we understand from this visual structure? Representational meanings: body appearance, scenary, age, gender, facial feedback, clothing,... Interactional meanings: gaze, modulation - as it gets higher, it means the image is less real -,... Compositional meanings: informative value - for example, 'centre' and 'margins' -, salience,...

Well, there are many ways of proceeding to a social semiotics analysis, but I believe the one I came up with is very useful if you want to explore in depth certain structures - images or not. Multimodality is a concept to bear in mind: the several modes of meaning production, such as graphic images or written text, are combined in one structure that produces meanings. Also, taking into account that communicative events are texts, which means they comprise textuality, can offer you a better and clearer understanding of what is a semiotic whole. In my view, it is inserted in a discourse, which is something larger than a semiotic whole.

If you want to go further, you can make use of Discourse (Critical) Studies. However, in my opinion, Social Semiotics is a good start for you. I should have started exploring Semiotics earlier, in my master's, to be honest. Better later than never, right? You can do it! Let me know if you need some help.

Cheers,

Pedro Eduardo Ribeiro

A mixed combined vaccine is given in form of Diphtheria and Tetanus Toxoid given together as Td in adults for protections against Diphtheria and Tetanus .for more detailed check the attached ref:

ncbi.nlm.nih.gov>NB...

Thank you for your answer,

But I've read the manual several times and it presents only six formats that Haploview can accept. The manual doesn't talk about what to do if you have DNA sequences aligned in fasta format.

When I import the sequences I have saved in phased format with the DnaSP software it gives me an error.

Osinachi Ekeagwu

Dear Dr. Ekeagwu,

I am sorry for my delayed reply.

Thank you for spending your worth time on feedback, which not only assisted me in reaching acceptable answers but also made me look at the issue from a different perspective. However, I do not agree with your points 2 and 5 so much.

In general, I think it is true that due to significant heterogeneity, the pooled prevalence or incidence may not be considered too correct and logical; however, sometimes the policymaker wants to make a series of comparisons between countries on a broad level or make decisions supposedly for the provision of medicine based on the results from pooled means. Therefore, pooled prevalence or incidence can maybe be useful in this regard.

Best,

When you group data in SQL, when you see the number “-9999”, you understand that this is an error in the data or they were not recorded. I immediately realized this when I worked with data on cotton and guayule(Matthew and Bronson).

The HIL setups allow us to test a real piece of hardware (hence the name - hardware-in-the-loop) with its pertaining features and operational modes.

Specifically, in a controller-hardware-in-the-loop (C-HIL, just one type of HIL setup) setup we can test how the controller with an embedded code is going to behave once deployed in an actual device. What is hard to model or do in e.g. MATLAB in this regard is the following:

- Controller capacities utilization - in various forms! (memory overrun, interrupts execution, etc.),

- Coordination and execution of different control layers (especially if they are executed on different controllers/control platforms),

- Communication devices and systems, overlaying the power electronics system (how are you going to model dynamics associated with the CAN communication protocol, for example, used to exchange the references between the controllers?),

- Integration with other real-time executed tools (for example, flight simulator for testing more electric airplanes),

- etc.

So to abstract things - Doing tests on a certain piece of hardware in real-time allows us to connect these devices to other devices and processes that are also executed in real-time (and sometimes can not be easily executed in non-real-time context) and to examine many features that are simply hard to model, or sometimes meaningless, in an offline simulation.

On the other hand, and more broadly speaking, unlike MATLAB, the HIL setups allow us to model and test:

- Medium/large complexity and size systems (for example, microgrids are extremely hard to model in detail since the model runtime tends to increase exponentially),

- High-power/high-voltage devices (in a power-hardware-in-the-loop, P-HIL, setup we can test the behavior of the real protection device in various network situations, such as short-circuits, loss of phase, etc. - this is next to impossible to do in offline simulation),

- etc.

This all being said, the offline simulation tools (constituting model-in-the-loop, MIL, setup) are here to stay. They are still great for initial tests, to put it in simple terms, and simulation tool providers are constantly adding new useful features, but the HIL setups have closed the serious gap that existed between the offline simulations and the tests on actual devices (prototypes or commercially available devices). It is safer than the real hardware, but faster and 'more precise' (again serious simplification) than the models executed in offline simulations.

You can check the following two documents for further details if you wish.

Write a caption for the plot that reports what test you did, what value you got, and the p-value you want to report. The asterisk convention is simply a shorthand that some find convenient, but isn't really a part of the display. But all statistical graphics should have captions that provide enough information to understand them.

For instance, you can structure x''=ax'+bx+c being a second order differential equation to system of linear equations as follows:

Let x=x_1

x'=(x_1)'=x_2

x''=(x_1)''=(x_2)'

Thus, the system of first order differential equation is given by:

(x_1)'=x_2

(x_2)'=-ax_2-bx_1-c

The finite difference relation that you obtain for equation 1 should be like this

-c [ { u(x_i+1,y_j) -2 u(x_i,y_j)+u(x_i-1,y_j)}/dx^2 + { u(x_i,y_j+1) -2 u(x_i,y_j)+u(x_i,y_j_1)}/dy^2}] + beta u(x_i,y_j) = f(x_i,y_j) for i = 2,...n and for j = 1,2,...,m

The Dirichlet boundary condition becomes u(x_1,y_j) = 0 for j=1,...,m

The Neumann boundary condition [u(x_i+1,y_j) -u(x_j-1,j_j)]/2*dx = C u(x_n,y__j) for j = 1,2,...m

You have it all now. You just need to connect the dots.

Cheers.

I am not sure I have enough information to answer your question. Here are some questions for you that would help me respond. What, exactly are your two independent variables--diet and P/L? What is your dependent variable? Is it continuous? Is it univariate? How large a sample do you expect to collect? What is your sampling plan? It is possible that your research questions would reveal the answers to my questions if I had them.

This paper may do what you want, please have a look.

Agglomeration of nanoparticles is a major concern and pose many challenges in different applications. But to avoid such problem one can either use a compatible capping agent such as any functionalized material or chemical moiety which enhances the stability of the nanoparticles and keep it bonded which further enables its reusability and reproducibility. Most basic and widely used example of such a process is the development of citrate-capped gold/silver nanoparticles. But again these chemical compounds does not provide much stability and leads to exposure of nanoparticles (Au/Ag) into the environment causing many problems thus, due to this, a suitable polymeric material might prove to be a great alternative.

Hope this might provide you a rough idea about how to find a suitable material for enhancing the stability of your nanoparticles(any) based on the field of interest of your application.

Dear Ravichandhran Gobi, one strategy is surface modification against NPs association by any mechanism, and to impart long-term dispersion stability. My Regards

Hi,

Yes: I guess that is a way to start.

Did you acquire MS/MS data too? If so, you can check which precursors show fragment ions that are similar to those obtained for vitamin D. At the same time, fragmentation spectra can also point towards how the additional compounds differ (chemically) from vitamin D.

I do not know if that is exactly what you are looking for, but there is a seminal paper on that matter: "A Differential Equation for Modeling Nesterov's Accelerated Gradient Method: Theory and Insights", by Su, Boyd and Candès. There, they study the accelerated gradient method by analyzing the associated differential equation.

If you want to program it yourself use something based CoolProp or pyromat, TESPy would offer a solution for building your cycles with predefined components. For plotting I created fluprodia which is based on CoolProp but has some nice visuals for different fluid property diagrams.

Depends on where you are publishing it. For example, APA (psych) journals specify p < .001 (without the lead zero that Sal Mangiafico uses for values that can't go above 1), but in areas like discoveries in physics the 5 sigma rule is used, which would require more digits for small ps.

A ratio can becom huge when the denominator is close to zero.

Don't look only on the point estimate. Always consider the entire confidence interval. If when the point estimate is huge, the lower limit of the confidence interval may still be quite close to 1. This case is not uncommon and would indicate that your data does not provide much information about the odds ratio (as the data are compatible with odds ratios of any size, from almost 1 to almost infinity). Sometimes the confidence intervan even inclused values lower than one. In this case your data does not even provedie enough information to make a claim if the treament is beneficial or hazardous. In combination with a large confidence interval this is then a quite useless result (a result from which no useful conclusions can be drawn - because there is too little useful information in the sample data).

You need to do using Dem, slope and distance to road inputs with the Ca-Markov using IDIRISI's, There is no option in MOLUSCE plugin. You can get some more ideas from the given research article. Kindly used the reference journals too.

Dear Anna Diem ,

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Shafagat

This is out of my field

Not rally.

Many things happen at nitrogen starvation and this depends on the nitrogen source...

A switchback is defined not only in terms of the radial component of the magnetic field, B_R. The Sun has magnetic sectors, with magnetic field "away" from or "toward" the Sun, and such magnetic field orientation is carried out with the solar wind. From one of Maxwell's equations, a sudden change in magnetic field B implies a current sheet at the boundary. This is called the heliospheric current sheet (HCS). But a change in B_R due to a changing sector, or an HCS crossing, is *not* termed a switchback. In Parker Solar Probe's 8th encounter, there were several HCS crossings but actually very few switchbacks.

So how can you tell whether B_R is reversing as an HCS crossing or a switchback? Ideally you would use another type of data. Heat flux electrons, a.k.a. suprathermal or strahl electrons in the solar wind, are found to stream away from the Sun along the local B line. So if you see the pitch angle distribution of such electrons *not* changing, which B_R reverses, that is a switchback. Before/after an HCS crossing, the dominant pitch angle would reverse. Similarly, the cross-helicity of magnetic and velocity fluctuations is generally characteristic of outward-moving Alfven modes, so that behaves like the strahl electron pitch angle: it reverses before/after an HCS crossing but not during a switchback. Or a very simple but not physically rigorous way to identify a switchback is as a very temporary reversal of B_R, with the same sign before and after the switchback.

Finally, given that electron strahl and cross helicity are not reversing, many people define a switchback as B_R changing sign. However, a more general definition is rotation of the B vector beyond some angle, with the threshold angle as a variable parameter (see Dudok de Wit et al. 2020).

the results are converted as mg/100 mL (expressed as dry weight soluble solids fraction by 100 ml in the vol of sample used.

, Carlo Ruzzo , Arun Patil