Miracle-dz/UniFAR-FTUs huggingface dataset:
Role of spin-orbit coupling and evolution of the electronic structure of WTe 2 under an external magnetic field

Here, we present a detailed study on the temperature and angular dependence of the Shubnikovde-Haas (SdH) effect in the semi-metal WTe2. This compound was recently shown to display a very large non-saturating magnetoresistance which was attributed to nearly perfectly compensated densities of electrons and holes. We observe four fundamental SdH frequencies and attribute them to spin-orbit split, electron- and hole-like, Fermi surface (FS) cross-sectional areas. Their angular dependence is mildly consistent with ellipsoidal FSs with volumes implying an excess of � 7 % in the density of electrons with respect to that of the holes. Nevertheless, we show that density functional theory (DFT) calculations can reasonably describe the experimentally determined electron FSs but fail to accurately describe the hole FSs. When their cross-sectional areas are adjusted to reflect the experimental data, the resulting volumes of the electron/hole FSs obtained from the DFT would imply a strong imbalance between the densities of electrons and holes. We observe a severe fieldinduced renormalization of the effective masses suggesting that the electronic structure of WTe2 is particularly sensitive to the Zeeman-effect. By combining the results of our DFT calculations with our analysis of the experimental results we conclude that WTe2 is unlikely to remain compensated under an external field.
Linear, Generalized Linear, and Nonlinear Mixed Effects Models

2. General Principles of Programming: Computer and Statistical 25 Sastry S. Isukapalli and Amit Roy 3. Validation of Software for Pharmacometric Analysis 53 Gary L. Wolk 4. Linear, Generalized Linear, and Nonlinear Mixed Effects Models 103 Farkad Ezzet and José C. Pinheiro 5. Bayesian Hierarchical Modeling with Markov Chain Monte Carlo Methods 137 Stephen B. Duffull, Lena E. Friberg, and Chantaratsamon Dansirikul 6. Estimating the Dynamics of Drug Regimen Compliance 165 Ene I. Ette and Alaa Ahmad 7. Graphical Displays for Modeling Population Data 183 E. Niclas Jonsson, Mats O. Karlsson, and Peter A. Milligan 8. The Epistemology of Pharmacometrics 223 Paul J. Williams, Yong Ho Kim, and Ene I. Ette 9. Data Imputation 245 Ene I. Ette, Hui-May Chu, and Alaa Ahmad
Toeplitz lemma, complete convergence, and complete moment convergence

ABSTRACT In this paper, we study the Toeplitz lemma, the Cesàro mean convergence theorem, and the Kronecker lemma. At first, we study “complete convergence” versions of the Toeplitz lemma, the Cesàro mean convergence theorem, and the Kronecker lemma. Two counterexamples show that they can fail in general and some sufficient conditions for “complete convergence” version of the Cesàro mean convergence theorem are given. Second, we introduce two classes of complete moment convergence, which are stronger versions of mean convergence and consider the Toeplitz lemma, the Cesàro mean convergence theorem, and the Kronecker lemma under these two classes of complete moment convergence.
Free-Living Amoebas in Extreme Environments: The True Survival in our Planet

Free-living amoebas (FLAs) are microorganisms, unicellular protozoa widely distributed in nature and present in different environments, such as water or soil; they are maintained in ecosystems and play a fundamental role in the biological control of bacteria, other protozoa, and mushrooms. In particular circumstances, some can reach humans or animals, promoting several health complications. Notably, FLAs are characterized by a robust capacity to survive in extreme environments. However, currently, there is no updated information on the existence and distribution of this protozoan in inhospitable places. Undoubtedly, the cellular physiology of these protozoan microorganisms is very particular. They can resist and live in extreme environments due to their encysting capacity and tolerance to different osmolarities, temperatures, and other environmental factors, which give them excellent adaptative resistance. In this review, we summarized the most relevant evidence related to FLAs and the possible mechanism, which could explain their adaptative capacity to several extreme environments.
One‐way Quantum Computation

The circuit model of quantum computation [1, 2, 3] has been a powerful tool for the development of quantum computation, acting both as a framework for theoretical investigations and as a guide for experiment. In the circuit model (also called the network model), unitary operations are represented by a network of elementary quantum gates such as the CNOT gate and single-qubit rotations. Many proposals for the implementation of quantum computation are designed around this model, including physical prescriptions for implementing the elementary gates. By formulating quantum computation in a different way, one can gain both a new framework for experiments and new theoretical insights. One-way quantum computation [4] has achieved both of these. Measurements on entangled states play a key role in many quantum information protocols, such as quantum teleportation and entanglement-based quantum key distribution. In these applications an entangled state is required, which must be generated beforehand. Then, during the protocol, measurements are made which convert the quantum correlations into, for example, a secret key. To repeat the protocol a fresh entangled state must be prepared. In this sense, the entangled state, or the quantum correlations embodied by the state, can be considered a resource which is “used up” in the protocol. In one-way quantum computation, the quantum correlations in an entangled state called a cluster state [6] or graph state [7] are exploited to allow universal quantum computation through single-qubit measurements alone. The quantum algorithm is specified in the choice of bases for these measurements and the “structure” of the entanglement (as explained below) of the resource state. The name “one-way” reflects the resource nature of the graph state. The state can be used only once, and (irreversible) projective measurements drive the computation forward, in contrast to the reversibility of every gate in the standard network model. In this chapter, we will provide an introduction to one-way quantum computation, and several of the techniques one can use to describe it. In this section we will introduce graph and cluster states and develop a notation for general single-qubit measurements. In section 2 we will introduce the key concepts of one-way quantum computation with some simple examples. After this, in section 3, we shall investigate how one-way quantum computation can
Oil slicks in the Gulf of Guinea – 10 years of Envisat Advanced Synthetic Aperture Radar observations

Abstract. The Gulf of Guinea is a very active area with respect to maritime traffic as well as oil and gas exploitation. Due to the failure of some actors to comply with environmental standards, this region has been subject to a large number of oil pollution episodes. This anthropogenic oil pollution is in addition to natural oil seepage from the ocean floor. This study aims to detect oil slicks in the Gulf of Guinea and to analyse their spatial distribution using synthetic-aperture radar (SAR) images. Previous works have already locally mapped oil slicks in this area; however, to our knowledge, this study is the first to achieve a global statistical analysis based on 10 years of radar images covering 17 exclusive economic zones (EEZs) in the Gulf of Guinea. The present study is based on a database of 3644 SAR images collected between 2002 and 2012 by the Advanced Synthetic Aperture Radar (ASAR) sensor onboard the European Spatial Agency (ESA) Envisat mission, and these images allowed the identification of 18 063 oil slicks. The spatial distribution of these oil slicks is available from Zenodo: https://doi.org/10.5281/zenodo.6470470 (Najoui, 2022b). The oil slicks detected in this work encompass both oil spills of anthropogenic origin and oil seeps of natural origin (natural oil reservoir leaks). A set of 100 georeferenced oil spills is also available from Zenodo: https://doi.org/10.5281/zenodo.6907743 (Najoui, 2022a).
Using a Two‐Level Structure to Manage the Point Location Problem in Explicit Model Predictive Control

The problem of determining the state region in which the current state point lies is referred to as the point location problem in the explicit model predictive control. In this paper, a two‐level structure to store the state regions is proposed and two efficient methods for solving the point‐location problem are developed; these are the two‐level grid (TLG) method and the grid‐BST method. The TLG method uses a tow‐level hash table. Before building the two‐level structure, the synonymy partitions are merged to reduce the memory storage demand. By setting each parameter in a triplet, the two‐level hash table can reach its optimal state and balance the complexity among the memory storage, reprocessing (offline computation) and the online computation. The grid‐BST method uses hash table as the first‐level structure and builds the binary search tree in the hash grid in which there are many partitions. This two‐level structure reduces reprocessing time significantly especially when the state partitions and the piecewise affine control laws (PWA control laws) are in a large number. Using the hyperplane (HP) as the node (not leaf node) of the tree, the method only stores all the different PWA control laws instead of the state partitions. The two proposed methods overcome the quick complexity growth when the number of polyhedral partitions increases and 2 numerical examples show the advantages of the proposed two methods.
A Study of Interlinkages among Exchange Rate and Stock Price for India

This paper is an attempt to examine the empirical relation between exchange rate and Indian stock price using the monthly time series data over the period 2011-2021. Johansen’s cointegration test has been applied to test the long run relationship between exchange rate and stock price. Both the trace and Maximum Eigenvalue test statistic are less than the 0.05 critical values. Thus, the null hypothesis of no cointegration is accepted and no long run stable equilibrium relation was found to exist between exchange rate and stock price. The analysis further reveals the prevalence of unidirectional causal relationship from stock price to exchange rate by employing the Granger causality test. Thus, the study is found to support the Stock oriented model. So, regulators can predict the trends in exchange rate from the past values of stock prices which can induce profitable trading in the currency market. This study would be of immense importance for various stakeholders like investors, practitioners and policy makers to reduce the information symmetry owing to the volatile nature of the two variables.
A Hybrid Model for Temperature Prediction in a Sheep House

Simple Summary In intensive sheep farming, the temperature is an important indicator of the healthy growth of sheep. The key to ensuring the healthy growth of sheep in a stress-free environment is to grasp the changing trend in the sheep-house temperature in time and adjust in advance. In order to solve this problem, we use machine learning technology to establish a combined prediction model to accurately predict the temperature of the sheep barn. The result shows that the combined prediction model has good stability and high accuracy. Additionally, it can be extended to the prediction research of other environmental parameters of other animal houses, such as pig houses and cow houses, in the future. Abstract Too high or too low temperature in the sheep house will directly threaten the healthy growth of sheep. Prediction and early warning of temperature changes is an important measure to ensure the healthy growth of sheep. Aiming at the randomness and empirical problem of parameter selection of the traditional single Extreme Gradient Boosting (XGBoost) model, this paper proposes an optimization method based on Principal Component Analysis (PCA) and Particle Swarm Optimization (PSO). Then, using the proposed PCA-PSO-XGBoost to predict the temperature in the sheep house. First, PCA is used to screen the key influencing factors of the sheep house temperature. The dimension of the input vector of the model is reduced; PSO-XGBoost is used to build a temperature prediction model, and the PSO optimization algorithm selects the main hyperparameters of XGBoost. We carried out a global search and determined the optimal hyperparameters of the XGBoost model through iterative calculation. Using the data of the Xinjiang Manas intensive sheep breeding base to conduct a simulation experiment, the results show that it is different from the existing ones. Compared with the temperature prediction model, the evaluation indicators of the PCA-PSO-XGBoost model proposed in this paper are root mean square error (RMSE), mean square error (MSE), coefficient of determination (R2), mean absolute error (MAE) , which are 0.0433, 0.0019, 0.9995, 0.0065, respectively. RMSE, MSE, and MAE are improved by 68, 90, and 94% compared with the traditional XGBoost model. The experimental results show that the model established in this paper has higher accuracy and better stability, can effectively provide guiding suggestions for monitoring and regulating temperature changes in intensive housing and can be extended to the prediction research of other environmental parameters of other animal houses such as pig houses and cow houses in the future.
Verification of the Regulatory Effect of Individual Personality in the Relationship between the Characteristics of Short-Form Beauty Contents and Behavioral Intention: With a Focus on the Generation MZ

Purpose: In this study, the purpose is to, by analyzing the MZ subjects to verify the regulatory effect of individual personality in terms of the relationship between the characteristics of short-form beauty contents and the behavioral intention, and by studying how individual personality affects short-form characteristics of beauty contents and the behavioral intention, present the basic data for the effective digital scalability that provides an optimal experience to Generation MZ and a strategy to induce the users to consume beauty contents while feeling the curiosity and interest of users about planning, producing and sharing form beauty contents. Method: The subjects of this study were analyzed by using the SPSS 25.0, AMOS 22.0 program for 406 online questionnaires in Seoul, Gyeonggi, Incheon metropolitan area and non-metropolitan area to verify the research problem targeting Generation MZ who used short-form beauty contents at least once. The exploratory factor analysis and reliability analysis were performed to secure the validity and reliability of the scale, and the Pearson correlation analysis was performed to confirm the correlation between the major variables. To verify the regulatory effect, the hierarchical regulation regression analysis was performed, and the test was confirmed with a simple slope graph according to the significant interaction effect. Results: As a result of the analysis performed, significant results were confirmed with a focus on the three stages in which all variables were input together. In the first stage, the characteristics of short-form beauty contents of the independent variables were static, all in playfulness, information, reliability, creativity, and interactivity. As the influence of individual personality on the behavioral intention in the second stage, it was confirmed that extroversion, affinity, and neurosis were significant. It was verified that the interaction variables that can confirm the regulatory effect in the third stage were the interaction between playfulness and sincerity(=.114, p<.05), the interaction between playfulness and neurosis(=.091, p<.05), reliability and the interaction of affinity(=.096, p<.05) was positively significant, and the interaction of information and affinity was negatively significant(=-.156, p<.01). Conclusion: Based on the results of this study, it was possible to learn that, playfulness and reliability reinforce the behavioral intention in the characteristics of short-form beauty contents. Behavioral intention increases as individual personality integrity, neurosis, and evolution are regulated, whereas informationality deteriorates as the evolutionary nature increases, and it was also found that a strategy of creating and planning useful information that may be enjoyed or shared is necessary to provide an optimal experience of content, considering the characteristics and individual personalities of Generation MZ users
Cellular PSMB4 Protein Suppresses Influenza A Virus Replication through Targeting NS1 Protein

The nonstructural protein 1 (NS1) of influenza A virus (IAV) possesses multiple functions, such as the inhibition of the host antiviral immune responses, to facilitate viral infection. To search for cellular proteins interacting with the IAV NS1 protein, the yeast two-hybrid system was adopted. Proteasome family member PSMB4 (proteasome subunit beta type 4) was found to interact with the NS1 protein in this screening experiment. The binding domains of these two proteins were also determined using this system. The physical interactions between the NS1 and cellular PSMB4 proteins were further confirmed by co-immunoprecipitation assay and confocal microscopy in mammalian cells. Neither transiently nor stably expressed NS1 protein affected the PSMB4 expression in cells. In contrast, PSMB4 reduced the NS1 protein expression level, especially in the presence of MG132. As expected, the functions of the NS1 protein, such as inhibition of interferon activity and enhancement of transient gene expression, were suppressed by PSMB4. PSMB4 knockdown enhances IAV replication, while its overexpression attenuates IAV replication. Thus, the results of this study suggest that the cellular PSMB4 protein interacts with and possibly facilitates the degradation of the NS1 protein, which in turn suppresses IAV replication.
Reciprocal bark exchange helps to disentangle tree species‐dependent bark and wood trait effects on invertebrate diversity

Previous studies showed that bark cover at early‐decay stage had profound control on the invertebrate assemblages of bark and wood, with possible consequence for the decomposition process. However, previous experimental designs could not disentangle how bark versus wood traits affect the invertebrate assemblage process in bark and/or wood separately because wood traits of different tree species may vary independently from bark traits. Furthermore, we do not know whether such tree species‐specific bark trait effects are still influential at mid‐decay stage. To unravel whether and how bark and wood traits influence invertebrate communities in tree logs at mid‐decay stage, we introduce reciprocal bark transplantation within pairs of different tree species as a new method. We applied this method to two pairs of phylogenetically contrasting species of gymnosperms (pair I: Araucaria araucana and Cryptomeria japonica, pair II: Picea abies and Thuja plicata) and another gymnosperm (Chamaecyparis lawsoniana) set as disturbance control to test for potential bark manipulation artefacts on invertebrate community composition. Our bark exchange experiment revealed that both bark and wood host abundant and divergent subsets of invertebrates on mid‐decay logs of different tree species. We further documented that the invertebrate community composition was predominantly shaped by the traits of host tissue per se, while also being significantly but less strongly affected by the traits of the other tissue, that is, the adjacent bark or wood. Our results indicated that bark trait effects faded with time and how long bark trait effects persist greatly depends on bark thickness. Synthesis. Our study suggests that maintaining deadwood heterogeneity related to variation between tree species and bark versus wood, is important for nursing a large biodiversity of invertebrates. Combined with bark removal methodology, our bark exchange method can be further extended to more decay stages and more forest biomes to track bark trait effects and bark induced priority effects on deadwood decomposition, and its associated invertebrate and microbial communities.
Portable and Non-Intrusive Fill-State Detection for Liquid-Freight Containers Based on Vibration Signals

Remote, automated querying of fill-states of liquid-freight containers can significantly boost the operational efficiency of rail- and storage-yards. Most existing methods for fill-state detection are intrusive, or require sophisticated instrumentation and specific testing conditions, making them unsuitable here, due to the noisy and changeable surroundings and restricted access to the interior. We present a non-intrusive system that exploits the influence of the fill-state on the container’s response to an external excitation. Using a solenoid and accelerometer mounted on the exterior wall of the container, to generate pulsed excitation and to measure the container response, the fill-state can be detected. The decision can be either a binary (empty/non-empty) label or a (quantised) prediction of the liquid level. We also investigate the choice of the signal features for the detection/classification, and the placement of the sensor and actuator. Experiments conducted in real settings validate the algorithms and the prototypes. Results show that the placement of the sensor and actuator along the base of the container is the best in terms of detection accuracy. In terms of signal features, linear predictive cepstral coefficients possess sufficient discriminative information. The prediction accuracy is 100% for binary classification and exceeds 80% for quantised level prediction.
Aerosols in Northern Morocco-2: Chemical Characterization and PMF Source Apportionment of Ambient PM2.5

Insufficient data on the chemical composition of PM2.5 and its emission sources in the southwestern (SW) Mediterranean area has been identified. Ambient PM2.5 samples were collected in an urban area of Tetouan city, northern Morocco. Chemical mass closure calculations and positive matrix factorization were performed for the comprehensive dataset of PM2.5 chemical analyses. Mass closure improved when multipliers (1.2 and 0.23, respectively) were used for the conversion of organic carbon (OC) and calcium ion (Ca2+) into particulate organic matter (POM) and mineral dust masses, respectively. The mass closure model performed well in this SW Mediterranean region, with a significant correlation (r2 = 0.97) obtained between gravimetrically measured and chemically determined PM2.5 mass. The one-year average concentration of PM2.5 was 17.96 μg/m3, and the major chemical components were POM (34%), secondary inorganic aerosol (SIA) (28%), and black carbon (18%), while unidentified mass was 4%. The mass concentration and most of the chemical components of PM2.5 showed clear seasonal variations, with a summer-high and winter-low pattern for SIA, dust, and BC. In the winter months, POM was the dominant component. Source apportionment analysis revealed that PM2.5 emission sources, regarding their typical tracers, were ammonium sulfate (SO42−, NH4+, K+, NO3−), road traffic and biomass burning emissions (OC, BC), fresh sea salt (Cl−, K+, NO3−), aged sea salt (Mg2+, Na+, Ca2+), and oxalate-rich (oxalate, NO3−) factors. Further, it is hoped that these findings help to improve the scientific understanding of SW Mediterranean aerosols.