Miracle-dz/UniFAR-FTUs huggingface dataset:
The CA model based on data assimilation

This paper presents a new method for calibrating urban cellular automata(CA) using ensemble Kalman filter(EnKF) of data assimilation.In CA modeling,the key issue is defining transition rules,which usually consist of many variables and parameters.There are many uncertainties in determining parameter values and the transition rules are deterministic and unchanged during the modeling process.As a result,the model errors would accumulate continuously in the simulation.The paper introduces the ensemble Kalman filter of data assimilation into CA model,and a data assimilation CA model based on ensemble Kalman filter was established.After using the model,the paper can derive analyzed values by merging information from remotely sensed observations with CA model predictions,and modify the simulated results closer to actual situation based on the analysis values.The proposed model has been tested in Dongguan,a city in the Pearl River Delta of Southern China.Experiments indicate that the method can reduce the model error in the simulation and help to generate more reliable simulation results by comparing variance,accuracy and kappa coefficient.
More is Not Always Better: Examining the Cumulative Effects of School Safety Policies on Perceptions of School Safety for Youth of Color

ABSTRACT In response to fears regarding high-profiled school shootings and firearm violence, schools transformed dramatically, implementing school safety measures such as school police, armed security, metal detectors, and active shooter drills. This study used nationally representative data to assess the relationship between school safety policies and student perceptions of school safety for Youth of Color in comparison to non-Hispanic, White youth. Results show that an increase in the total number of school safety policies – as well as specific types of school safety policies (i.e. armed security personnel and student search practices) – are associated with lower perceptions of school safety for Youth of Color relative to White youth. Findings may inform school administrators’ decisions regarding implementation of school safety policies to prevent school violence, including school-level decisions around firearm injury prevention efforts.
Null-Free Wireless Power Transfer System Based on a Coil Array to Compensate for 2-D Misalignment

In this study, a coil array technology is proposed to compensate for 2-D misalignment between coils, regardless of its direction, in a wireless power transfer (WPT) system at 6.78 MHz. The primary coil is printed on one side of the substrate, while the assistant coil is printed on the other side in a <inline-formula> <tex-math notation="LaTeX">$2\times2$ </tex-math></inline-formula> array configuration. Depending on the degree of misalignment, the coil pair with the best alignment can be switched on. Thus, high efficiency can be maintained without increasing the size of the coils. Experimental results for a <inline-formula> <tex-math notation="LaTeX">$47\times47$ </tex-math></inline-formula> mm<sup>2</sup>-sized coil system demonstrate null-free operation that maintains transfer efficiency of more than 80% with diagonal misalignment of up to 98% relative to the largest coil dimension. Regardless of the direction of the misalignment, its efficiency is 80% or higher with up to 72% misalignment, and 50.5% or higher with extremely high misalignment (up to 120%). The results indicate that the proposed coil array technology successfully addresses the notorious misalignment issue in a near-field WPT system, regardless of the direction of the misalignment, without increasing the coil size. Furthermore, the results for an asymmetric system in which the coil array technology is adopted only on the Tx side reveal the feasibility of the proposed method for practical applications.
Novel Schemes of No-Slip Boundary Conditions for the Discrete Unified Gas Kinetic Scheme Based on the Moment Constraints

The boundary conditions are crucial for numerical methods. This study aims to contribute to this growing area of research by exploring boundary conditions for the discrete unified gas kinetic scheme (DUGKS). The importance and originality of this study are that it assesses and validates the novel schemes of the bounce back (BB), non-equilibrium bounce back (NEBB), and Moment-based boundary conditions for the DUGKS, which translate boundary conditions into constraints on the transformed distribution functions at a half time step based on the moment constraints. A theoretical assessment shows that both present NEBB and Moment-based schemes for the DUGKS can implement a no-slip condition at the wall boundary without slip error. The present schemes are validated by numerical simulations of Couette flow, Poiseuille flow, Lid-driven cavity flow, dipole–wall collision, and Rayleigh–Taylor instability. The present schemes of second-order accuracy are more accurate than the original schemes. Both present NEBB and Moment-based schemes are more accurate than the present BB scheme in most cases and have higher computational efficiency than the present BB scheme in the simulation of Couette flow at high Re. The present Moment-based scheme is more accurate than the present BB, NEBB schemes, and reference schemes in the simulation of Poiseuille flow and dipole–wall collision, compared to the analytical solution and reference data. Good agreement with reference data in the numerical simulation of Rayleigh–Taylor instability shows that they are also of use to the multiphase flow. The present Moment-based scheme is more competitive in boundary conditions for the DUGKS.
Deep reinforcement learning for IRS-assisted UAV covert communications

Covert communications can hide the existence of a transmission from the transmitter to receiver. This paper considers an intelligent reflecting surface (IRS) assisted unmanned aerial vehicle (UAV) covert communication system. It was inspired by the high-dimensional data processing and decision-making capabilities of the deep reinforcement learning (DRL) algorithm. In order to improve the covert communication performance, an UAV 3D trajectory and IRS phase optimization algorithm based on double deep Q network (TAP-DDQN) is proposed. The simulations show that TAP-DDQN can significantly improve the covert performance of the IRS-assisted UAV covert communication system, compared with benchmark solutions.
Chaos and its control in the libration motion of a non-rigid spacecraft with viscous drag in circular orbit

We study the libration motion dynamics of an asymmetric spacecraft in circular orbit under the influence of a gravity gradient torque. The spacecraft is perturbed by a small aerodynamic drag torque proportional to the angular velocity of the body about its mass center. We also suppose that one of the moments of inertia of the spacecraft is a periodic function of time. Under both perturbations, we show that the system exhibits a transient chaotic behavior by means of the Melnikov method. This method gives us an analytical criterion for heteroclinic chaos in terms of the system parameters. This criterion is numerically contrasted. We show also show that some periodic orbits survive for perturbation small enough. Finally, we apply some feedback methods of chaos control to initially-irregular libration motions in order to remove their chaotic behaviors and obtain periodic motions.
Ecology and Diversity of Aphids: A Review

Plant lices are tiny, soft-bodied arthropod insects which feed on sap of plants. Aphids are another name for these insects. They are members of the Aphidinae subfamily. Aphids fall into 60 genera and have roughly 400 species globally. In India, there are 25 genera with 125 species of aphids, while Uttarakhand (plains to very high altitudes) has 4 genera with 125 species of aphids. There are 65 different types of aphids, with the genus Aphidius having the most species overall. Aphids are greatly harming horticulture fruits and vegetables as well as agricultural crops. Temperature, humidity, and other environmental conditions affect its outbreak. Aphids are tiny, soft-bodied, viviparous, parasitic insects that lack wings and have wax secreting tubes on their abdomens. They can stunt plant growth, create plant galls, spread viral diseases to plants, and deform leaves, buds, and flowers. They have an impact on both plants, such as roses, lilies, and marigolds, as well as fruits and vegetables including mustard, cabbage, peas, potatoes, and beans. The mountainous area lacks data on the variety, ecology, and inventory of aphids. So an effort has been made to review the aphids diversity in India.
Association between polycystic ovarian morphology and insulin resistance in women with polycystic ovary syndrome

Objective The aim of the present study was to determine whether polycystic ovarian morphology (PCOM) is related to insulin resistance in women with polycystic ovary syndrome (PCOS). Methods A total of 147 Korean women aged 18 to 35 years and diagnosed with PCOS were included in this study. Fasting blood tests and standard 2-hour 75-g oral glucose tolerance tests were performed for all participants. PCOM-related parameters including total antral follicle count (TFC) and total ovarian volume (TOV) were assessed using transvaginal or transrectal ultrasonography. Correlation analysis was conducted to assess the relationships of TFC and TOV with insulin resistance-related clinical and biochemical parameters using Spearman rank correlation coefficients and linear regression analysis, with partial correlations used to control for the effects of confounding covariates. Results Fasting insulin levels, low-density lipoprotein levels, and insulin sensitivity assessment indices (ISAIs) were significantly correlated with TFC, but neither postprandial blood glucose levels nor insulin levels were significantly associated with TFC. No insulin resistance-related parameter was significantly correlated with TOV. These results did not change after adjustments for other anthropometric covariates. Fasting insulin and some ISAIs differed significantly between groups categorized by the median TFC value (TFC ≤54 and TFC >54). Conclusion TFC, but not TOV, was found to be related to fasting insulin resistance-related parameters in women with PCOS.
Influences of preconditioning on the mutual coherence and the restricted isometry property of Gaussian/Bernoulli measurement matrices

This article discusses the influence of preconditioning on the mutual coherence and the restricted isometry property of Gaussian or Bernoulli measurement matrices. The mutual coherence can be reduced by preconditioning, although it is fairly small due to the probability estimate of the event that it is less than any given number in (0, 1). This can be extended to a set that contains either of the two types of matrices with a high probability but a subset with Lebesgue measure zero. The numerical results illustrate the reduction in the mutual coherence of Gaussian or Bernoulli measurement matrices. However, the first property can be true after preconditioning for a large type of measurement matrices having the property of s-order restricted isometry and being full row rank. This leads to a better estimate of the condition number of the corresponding submatrices and a more accurate error estimate of the conjugate gradient methods for the least squares problems typically used in greedy-like recovery algorithms.
Adaptive Density Spatial Clustering Method Fusing Chameleon Swarm Algorithm

The density-based spatial clustering of application with noise (DBSCAN) algorithm is able to cluster arbitrarily structured datasets. However, the clustering result of this algorithm is exceptionally sensitive to the neighborhood radius (Eps) and noise points, and it is hard to obtain the best result quickly and accurately with it. To solve the above problems, we propose an adaptive DBSCAN method based on the chameleon swarm algorithm (CSA-DBSCAN). First, we take the clustering evaluation index of the DBSCNA algorithm as the objective function and use the chameleon swarm algorithm (CSA) to iteratively optimize the evaluation index value of the DBSCAN algorithm to obtain the best Eps value and clustering result. Then, we introduce the theory of deviation in the data point spatial distance of the nearest neighbor search mechanism to assign the identified noise points, which solves the problem of over-identification of the algorithm noise points. Finally, we construct color image superpixel information to improve the CSA-DBSCAN algorithm’s performance regarding image segmentation. The simulation results of synthetic datasets, real-world datasets, and color images show that the CSA-DBSCAN algorithm can quickly find accurate clustering results and segment color images effectively. The CSA-DBSCAN algorithm has certain clustering effectiveness and practicality.
Synergistic effects of canopy chemistry and autogenic soil biota on a global invader

Soil biota have strong effects on plants, but we have a poor understanding of how plant chemistry might modify these effects. We examined the effect of soil biota associated with an exotic invasive tree, Prosopis juliflora, versus that associated with native species, from seven sites across India on conspecifics and two other plant species. We then measured changes in species‐specific soil biota effects (identified as plant–soil feedbacks, PSFs) when leaf leachate from P. juliflora or from native plant species was added to soil containing respective live and sterile soil inoculum. We quantified the amino acid L‐tryptophan from leaf leachate of P. juliflora, Leucaena leucocephala (another invader), and two native species. We also tested effects of P. juliflora or native species soil inoculum amendment of tryptophan on P. juliflora, P. cineraria and L. leucocephala across seven sites. We then quantified the microbially metabolized derivatives of tryptophan, phytohormone indole‐3‐acetic acid (IAA) and intermediates after adding tryptophan into P. juliflora and native soils. Soil biota associated with P. juliflora generated positive effects on conspecifics and L. leucocephala, but negative effects on the native congener P. cineraria. When P. juliflora leaf leachate was added to soil with live P. juliflora inoculum, PSFs became more positive for P. juliflora and other species, compared to leaf leachate amended with sterile soil inoculum. Native leaf leachate interacted weakly with soil biota to impact biomass of conspecifics and heterospecifics. There was roughly 10× more tryptophan in the leaf leachate of P. juliflora than in the leaf leachate of other species. Tryptophan generally increased positive PSFs associated with P. juliflora relative to soil biota associated with other plant species. When tryptophan was added to live P. juliflora soil, IAA and its intermediates were produced at five of seven sites, and at four of these sites soil biota from P. juliflora had positive PSFs. Synthesis. These results provide the first experimental evidence that a chemical leached from the leaves of an invader regulates PSFs. Our results indicate that canopy effects and PSFs, which are usually studied independently, can interact in ways that strongly affect conspecifics and neighbouring species.
THE H-EIGEN ENERGY FORMATION NUMBER OF H-DECOMPOSABLE CLASSES OF GRAPHS-FORMATION RATIOS, ASYMPTOTES AND POWER

The study of graph decomposition is well known, so is the energy of graphs in terms of its eigenvalues. The union of these two ideas has been presented recently where the idea of the energy used in forming a "graphical molecule" from its decomposed parts was muted. In this paper, we inherit the idea of the Hückel de-localization or deformation energy, which correlates with the experimental heat of combustion associated with a molecule, to introduce the idea of the formation energy of a H-decomposable class of graphs. We consider the average formation energy (as a ratio) and discuss classes of graphs which have asymptotic convergence. The idea of the formation power of a class of graphs is developed using the Riemann integral of the formation energy, which allowed for the investigation of classes of graphs on a large number of vertices whose formation powers converge in a constant "reciprocal" manner.
Glauber Modeling in Heavy Ion Collisions

With increasing search of critical point at RHIC fluctuations in flow, Glauber model provides a baseline over which effects of fluctuations start gaining importance. Glauber model is used to have a quantitative idea of the geometrical configuration of nuclei, when nuclei collide at ultra relativistic energies, and treats the collision as a sequence of nucleon-nucleon collision. This method is able to calculate the number of participating nucleons and the number of binary collisions analytically, for a given impact parameter and centre of mass energy. To compare the results to real experimental data, the nuclear density profile and inelastic nucleon-nucleon cross-section is given as an input to the model. Glauber model comes into two variants-The Optical Glauber model, which assumes smooth matter density described by Fermi distribution function, and The Monte Carlo Glauber model which analyses the quantities mentioned, by considering individual nucleons as distributed stochastically event by event. This analytical study of the flow mechanism of heavy ion collisions with the help of Glauber model is highly significant for the study of high energy collisions. This work will also help scientific society for the search of parameters yet not explored at high energy.
Bayes and Empirical Bayes approaches to addressing stock structure questions using mtDNA data, with an illustrative application to North Pacific minke whales

Bayesian methods using mtDNA data are developed to compare single- and multiple-stock hypotheses. The likelihood of the data is assumed to be multinomial and the multivariate prior for the probability of an individual having a particular haplotype is assumed to be of the Dirichlet-b form. The values for the parameters of this prior are either determined using an Empirical Bayes approach or assumed to be distributed according to a log-normal hyper-prior (the ‘Full Bayes’ approach). The Empirical and Full Bayes methods are examined using simulation. The performance of the Empirical Bayes method is found to be much worse than that of the Full Bayes method. Illustrative comparisons for North Pacific minke whales based on the latter method confirm previous results that sub-areas 6 and 7 contain different stocks. Results of the application of this method to the mtDNA data for the sub-areas to the east of Japan, although generally uninformative, are nevertheless consistent with analyses based on hypothesis testing using allozymes and mtDNA. The results from this method should, however, be used for management purposes with some caution. This is because, although some testing of the Full Bayes method has been completed and suggests that when applied to data for two stocks that differ substantially in haplotype frequency, or when sample sizes are large and there is only one stock, performance is adequate, in common with most other methods for analysing genetics data, its performance has yet to be fully evaluated.
Diabetes Mellitus and Tuberculosis Treatment Outcomes: Interaction Assessment Between Hyperglycemia and Human Immunodeficiency Virus in the State of Georgia, 2015–2020

Abstract Background Diabetes mellitus and human immunodeficiency virus (HIV) are independent risk factors for poor outcomes among people with tuberculosis (TB). To date, information on the joint impact of diabetes and HIV on TB outcomes is limited. We aimed to estimate (1) the association between hyperglycemia and mortality and (2) the effect of joint exposure to diabetes and HIV on mortality. Methods We conducted a retrospective cohort study among people with TB in the state of Georgia between 2015 and 2020. Eligible participants were 16 or older, did not have a previous TB diagnosis, and were microbiologically confirmed or clinical cases. Participants were followed during TB treatment. Robust Poisson regression was used to estimate risk ratios for all-cause mortality. Interaction between diabetes and HIV was assessed on the additive scale using the attributable proportion and on the multiplicative scale with product terms in regression models. Results Of 1109 participants, 318 (28.7%) had diabetes, 92 (8.3%) were HIV positive, and 15 (1.4%) had diabetes and HIV. Overall, 9.8% died during TB treatment. Diabetes was associated with an increased risk of death among people with TB (adjusted risk ratio [aRR] = 2.59; 95% confidence interval [CI], 1.62–4.13). We estimated that 26% (95% CI, −43.4% to 95.0%) of deaths among participants with diabetes mellitus and HIV were due to biologic interaction. Conclusions Diabetes alone and co-occurring diabetes and HIV were associated with an increased risk of all-cause mortality during TB treatment. These data suggest a potential synergistic effect between diabetes and HIV.
Tossing a Fair Coin

Responses 1 and 2 are essentially the probability model for a single toss of a fair coin. Response 3, with a bit about limits and rigor, is the "relative frequency" definition of probability. So, 1, 2, and 3 are essentially equivalent. What about response 4? The common belief is that it is equivalent to the others. That is, after many tosses of a fair coin the number of heads tossed is practically equal to the mlmber of tails, and the more times the coin is tossed the more nearly equal are the number of heads and the number of tails. Some reflection on this statement indicates that it might be equivalent to the belief that a coin has a memory. But response 4 is a more subtle way of saying that, and it is certainly the belief that guides bets of amateur gamblers. (It is interesting to note that Bertrand Russell may have had this mistaken notion. See Lo Bello [4].)We will see that response 4 fails in perhaps the worst possible way: The difference between the number of heads and tails grows larger as the number of tosses increases. We will study this phenomenon by using the Central Limit Theorem, a major tool in all probability and statistics courses from elementary to advanced, and computer simulation. The simulation and further use of the Central Limit Theorem will lead us to a surprise "proof" of Wallis's formula. It is easy to see arithmetically that response 4 might not be correct. The following table shows why.
Performance Evaluation of State-of-the-Art High-Resolution Time-of-Flight Cameras

It has been about 20 years since the disruptive appearance of the first time-of-flight (ToF) cameras. Since then, ToF imaging has progressively evolved. Nowadays, ToF sensors have broken the barrier of the 1-megapixel resolution, and a significant number of high-resolution ToF cameras have appeared in the market. To provide a better understanding of their performance and applications, we experimentally evaluate three state-of-the-art high-resolution ToF cameras such as Azure Kinect, Helios2, and S100D, together with the solid-state LiDAR L515. We perform various experiments to examine some key parameters, such as warm-up times, accuracy, precision, lateral and axial resolutions, edge noise, unsteady scenes, and modulated waveform and optical power. Our evaluation draws various conclusions: S100D shows fluctuations within 1 mm after being powered up while the others require warm-up times. Azure Kinect, Helios2, and L515 can achieve precision within 2 mm in a measuring range of 0.5–3 m. Helios2 and S100D are more severely affected by dynamic scenes. Finally, the point clouds (PCs) generated for a white panel at a distance of 1.5 m show that flying pixels are present in all cameras, being this problem less acute for the L515.