Miracle-dz/UniFAR-FTUs huggingface dataset:
Research on Information Avoidance Behavior of College Students — Take WeChat Public Account As an Example

—In order to research the information evasion behavior of college students in WeChat public account, inquiry the characteristics of college students, and provide some theoretical guidance for college students' information services. The semi-structured interview method was used to collect the data evasion behavior data of 20 college students. Combined with relevant report data and literature analysis, the user's information evasion behavior was described. The influence factors were summarized by referring to the Wilson information behavior model. Personal factors directly affect the information evasion behavior of college students, and information factors have an indirect influence.
The full-information best-choice problem with uniform or gamma horizons

A decision-maker has to choose one from among a Poisson stream of i.i. d. bids, with no recall. The stream stops at a random time with a uniform (in the first case) or Erlang (in the second case) distribution. We solve the problem explicitly for maximal expected gain for bids that may take on any finite number of values. A fast procedure to solve the problem for fixed horizon is presented as well.
Optimal Control for Multi-agent Systems Using Off-Policy Reinforcement Learning

To achieve the consensus for discrete-time multi-agent systems, an optimal control policy is designed based on off-policy reinforcement learning. By utilizing centralized learning and decentralized execution, we first define a centralized and shared value function. Then, a value iteration adaptive dynamic programming method is proposed to approach the solution of the Bellman optimality equation with convergence analysis. Furthermore, the actor-critic structure is given for the implementation purpose, where one single-critic network is given to approach the optimal centralized value function, and multi-actor networks are decentralized based on the local observation from the neighbors to obtain the optimal policy for each agent. Finally, the proposed algorithm is verified in a leader-follower consensus case.
Magnesium-doped lithium niobate for higher optical power applications

Compositions of lithium niobate containing 4.5 at. % or more MgO have the ability to transmit, without distortion, light 100 times as intense as undopecl compositions. Holographic diffraction measurements of photorefraction have demonstrated that the improved performance is due to a hundredfold increase in the photoconductivity, rather than to a decrease in the Glass current. The damage-resistant compositions are also distinguished by a thermal activation energy of 0.1 eV for the diffraction efficiency, an OH-stretch vibration at 2.83 Am, a lattice phonon absorption at 21.2 Am, an electron spin resonance signal for Fe impurities at 1500 G, and, after reduction by heating in a vacuum, an optical absorption band at 1.2 um. (The corresponding values for undopedl LiNbO3 are 0.5 eV, 2.87 um, 21.8 um, 790 G, and 0.5 um, respectively.) The high photoconductivity is thus related to a distinctive electronic environment for impurities in the damage-resistant crystals. The photoconductivity strongly affects the impedance and time constants of signal processing devices made of LiNbO3.
Microbiota-derived metabolites in regulating the development and physiology of Caenorhabditis elegans

Microbiota consist of microorganisms that provide essential health benefits and contribute to the animal’s physiological homeostasis. Microbiota-derived metabolites are crucial mediators in regulating host development, system homeostasis, and overall fitness. In this review, by focusing on the animal model Caenorhabditis elegans, we summarize key microbial metabolites and their molecular mechanisms that affect animal development. We also provide, from a bacterial perspective, an overview of host-microbiota interaction networks used for maintaining host physiological homeostasis. Moreover, we discuss applicable methodologies for profiling new bacterial metabolites that modulate host developmental signaling pathways. Microbiota-derived metabolites have the potential to be diagnostic biomarkers for diseases, as well as promising targets for engineering therapeutic interventions against animal developmental or health-related defects.
On a numerical solution of the supersonic panel flutter eigenproblem

An automated digital computer procedure is presented in this paper which enables efficient solution of the eigenvalue problem associated with the supersonic panel flutter phenomena. The step-by-step incremental solution procedure is based on an inverse iteration technique which effectively utilizes solution results from the previous step in determining such results during the current solution step. Also, the computations are limited to the determination of a few specific roots only, which are expected to contain the flutter mode, and this is achieved at each step without having to compute any other root. The structural discretization achieved by the finite element method yields highly banded stiffness, mass, and aerodynamic matrices; the aerodynamic matrix evaluated by the linearized piston theory is real but unsymmetric in nature. The solution algorithm presented in this paper fully exploits the banded form of the associated matrices, and the resulting computer program written in FORTRAN V for the JPL UNIVAC 1108 computer proves to be most efficient and economical when compared to existing procedures of such analysis. Numerical results are presented for a two-dimensional panel flutter problem.
A High Performance Wheat Disease Detection Based on Position Information

Protecting wheat yield is a top priority in agricultural production, and one of the important measures to preserve yield is the control of wheat diseases. With the maturity of computer vision technology, more possibilities have been provided to achieve plant disease detection. In this study, we propose the position attention block, which can effectively extract the position information from the feature map and construct the attention map to improve the feature extraction ability of the model for the region of interest. For training, we use transfer learning to improve the training speed of the model. In the experiment, ResNet built on positional attention blocks achieves 96.4% accuracy, which is much higher compared to other comparable models. Afterward, we optimized the undesirable detection class and validated its generalization performance on an open-source dataset.
Numerical Experiments for Nuclear Flashes toward Superbursts in an Accreting Neutron Star

We show that the superburst would be originated from thermonuclear burning ignited by accumulated fuels in the deep layers compared to normal X-ray bursts. Two cases are investigated for models related to superbursts by following thermal evolution of a realistic neutron star: helium flash and carbon flash accompanied with many normal bursts. For a helium flash, the burst shows the long duration when the accretion rate is low compared with the observation. The flash could become a superburst if the burning develops to the deflagration and/or detonation. For a carbon flash accompanied with many normal bursts, after successive 2786 normal bursts during 1.81 × 109 s, the temperature reaches the deflagration temperature. This is due to the produced carbon which amount reaches to ≈0.1 in the mass fraction. The flash will develop to dynamical phenomena of the deflagration and/or detonation, which may lead to a superburst.
More GP Consultations by Violence Victims: Results from the Representative German DEGS1 Study

Violence is a growing public health problem influencing physical and mental health. Victims tend to contact medical care in the first place, yet a discrepancy between patients’ violence experiences (VE) and general practitioners’ (GP) awareness is reported. The number of GP visits by victims is of interest. Using data of the nationally representative German Health Interview and Examination Survey for Adults (DEGS1), associations between the prevalence of ≥1 recent VE (last 12 months) and the number of GP contacts were analyzed with respect to age, gender, socio-economic status, and health conditions. The DEGS1 dataset comprised persons aged 18 to 64 years (n = 5938). The prevalence of a recent VE was 20.7%. Compared to non-victims, VE victims visited their GP significantly more often in the preceding 12 months (3.47 vs. 2.87, p < 0.001), which increased markedly in those who were strongly impaired by a recent physical VE (3.55 GP visits) or psychological VE (4.24). The high frequency of GP contacts in VE victims constitutes opportunities to professionally support this vulnerable patient group and underlines the necessity for GPs to integrate VE as a bio-psycho-social problem in a holistic treatment approach.
The effects of simulated duathlon on multisegment running external and internal load in well-trained triathletes

ABSTRACT Duathlon is a rapidly promoting sport, so it is necessary to identify the factors that influence performance. This study aimed to analyse internal and external loads and the interactions between them during running legs before and after cycling in duathlon. Twenty-three male and female athletes participated in a simulated duathlon (5k-20k-5k). Internal workload was assessed using the rate of perceived exertion (RPE) and heart rate (maximum: HRMAX; average: HRAVG; R-R interval), whereas external workload was assessed using inertial sensors (Player Load by RealTrack, PLRT) attached to six body locations. The results showed that both running legs presented an increasing trend in RPE, HRMAX, and HRAVG throughout the kilometres, while the R–R interval decreased. The PLRT of the upper and lower back, knee, and ankle increased throughout the first running leg but not in the second. The PLRT was greater in the lower body than in the upper body because of energy absorption. RPE was higher in the second running leg than in the first leg. In conclusion, the cycling leg affects the internal and external load between running legs in duathlon. Load monitoring can help coaches understand duathletes’ performance and design specific training strategies to reduce fatigue during competition.
Numerical investigation of separated nozzle flows

A numerical study of axisymmetric overexpanded nozzle flows is presented. The flow structures of the startup and throttle-down processes are examined. During the impulsive startup process, observed flow features include the Mach disk, separation shock, Mach stem, vortex core, contact surface, slip stream, initial shock front, and shocklet. Also the movement of the Mach disk is not monotonical in the downstream direction. For a range of pressure ratios, hysteresis phenomenon occurs; different solutions were obtained depending on different processes. Three types of flow structures were observed. The location of separation point and the lower end turning point of hysteresis are closely predicted. A high peak of pressure is associated with the nozzle flow reattachment. The reversed vortical structure trapped behind the Mach disk appears to be key to causing the differences in the flow structures and affects engine performance.
Second order SM approach to SISO time-delay system output tracking

A fully linearizable SISO relative degree n system with an output time delay is considered in this paper. Using the approach of Pade approximation, system centre approach and second order sliding mode (in short SM) control, we have obtained good output tracking results. Smith Predictor is used to compensate the difference between the actual delayed output and its approximation. A second order super-twisting SM observer is used to observed the disturbance in the plant.
Trench Gate Nanosheet FET to Suppress Leakage Current From Substrate Parasitic Channel

Recently, nanosheet FETs (NS FETs) have been introduced as promising candidates for beyond 3-nm node technology. However, difficulties remain for mass production of the NS FETs. One of the concerns is increased OFF-state current (<inline-formula> <tex-math notation="LaTeX">${I}_{ \mathrm{OFF}}$ </tex-math></inline-formula>) due to leakage current from the substrate parasitic channel. Since the NS FET includes a 2-D parasitic FET on the bottom substrate, increased leakage current through the bottom is inevitable. The traditional methodology to suppress the leakage current from the parasitic channel is to use a punchthrough stopper (PTS). However, the PTS requires both ion implantation and an annealing process, which are detrimental to device yield. In this context, the trench gate (TG) NS FET is proposed as a new device architecture. The TG structure increases the effective gate length (<inline-formula> <tex-math notation="LaTeX">${L}_{G\text {,EFF}}$ </tex-math></inline-formula>) of the parasitic FET, reducing the leakage current through the bottom. Moreover, the fabrication process for the TG NS FET is fully compatible with conventional processes.
Human EGFRvIII chimeric antigen receptor T cells demonstrate favorable safety profile and curative responses in orthotopic glioblastoma

Glioblastoma is a highly aggressive and fatal brain malignancy, and effective targeted therapies are required. The combination of standard treatments including surgery, chemotherapy and radiotherapy is not curative. Chimeric antigen receptor (CAR) T cells are known to cross the blood–brain barrier, mediating antitumor responses. A tumor‐expressed deletion mutant of the epidermal growth factor receptor (EGFRvIII) is a robust CAR T cell target in glioblastoma. Here, we show our de novo generated, high‐affinity EGFRvIII‐specific CAR; GCT02, demonstrating curative efficacy in human orthotopic glioblastoma models.
Shaping Heterogeneity of Naive CD8+ T Cell Pools

Immune diversification helps protect the host against a myriad of pathogens. CD8+ T cells are essential adaptive immune cells that inhibit the spread of pathogens by inducing apoptosis in infected host cells, ultimately ensuring complete elimination of infectious pathogens and suppressing disease development. Accordingly, numerous studies have been conducted to elucidate the mechanisms underlying CD8+ T cell activation, proliferation, and differentiation into effector and memory cells, and to identify various intrinsic and extrinsic factors regulating these processes. The current knowledge accumulated through these studies has led to a huge breakthrough in understanding the existence of heterogeneity in CD8+ T cell populations during immune response and the principles underlying this heterogeneity. As the heterogeneity in effector/memory phases has been extensively reviewed elsewhere, in the current review, we focus on CD8+ T cells in a “naïve” state, introducing recent studies dealing with the heterogeneity of naive CD8+ T cells and discussing the factors that contribute to such heterogeneity. We also discuss how this heterogeneity contributes to establishing the immense complexity of antigen-specific CD8+ T cell response.
A Hierarchical Bayesian Model With Correlated Residuals for Investigating Stability and Change in Intensive Longitudinal Data Settings

The present paper’s focus is the modeling of interindividual and intraindividual variability in longitudinal data. We propose a hierarchical Bayesian model with correlated residuals, employing an autoregressive parameter AR(1) for focusing on intraindividual variability. The hierarchical model possesses four individual random effects: intercept, slope, variability, and autocorrelation. The performance of the proposed Bayesian estimation is investigated in simulated longitudinal data with three different sample sizes (N = 100, 200, 500) and three different numbers of measurement points (T = 10, 20, 40). The initial simulation values are selected according to the results of the first 20 measurement occasions from a longitudinal study on working memory capacity in 9th graders. Within this simulation study, we investigate the root mean square error (RMSE), bias, relative percentage bias, and the 90% coverage probability of parameter estimates. Results indicate that more accurate estimates are associated with .
One Health—Key to Adequate Intervention Measures against Zoonotic Risks

Zoonotic diseases are a heterogenous group of infections transmittable between humans and vertebrate animal species. Globally, endemic and emerging zoonoses are responsible for high social and economic costs. Due to the particular positioning of zoonoses at the human-animal-environment interface, zoonotic disease control is an integral part of One Health, which recognizes the close link between human, animal and ecosystem health. During recent years, the validity of the One Health approach has been recognized by academia and policy makers. However, gaps are still evident, particularly in the implementation of the concept as a unifying, integrated approach for different sectors and disciplines for the control of zoonoses. For example, while cooperation between human and veterinary medicine has made significant progress, networking with environmental sciences leaves room for improvement. Examination of individual intervention measures can help to gain valuable insights for future projects, and help to identify existing gaps. This is also a task for the One Health High-Level Expert Panel, which was established by WHO, OIE, FAO and UNEP to give science-based strategic advice on One Health measures. Overall, we should aim to learn from current situations, and to identify the best practice examples available, to continuously develop and improve One Health concepts for the control of zoonoses.
Atmospheric opacity: A study of visibility observations in the British Isles

A station may be classified as to visibility by using visibility frequencies to evaluate the atmospheric opacity, which is directly proportional to the extinction coefficient. Mean values of the atmospheric opacity in clear conditions and in foggy conditions at various stations in the British Isles are utilised to infer the contribution of the various types of nuclei and particles to the opacity, and in particular to infer the relative efficiency of each type as a fog-producer. It is concluded that sea-salt nuclei are much larger than combustion nuclei and play a leading part in the determination of visibility. The effect of combustion nuclei is negligible unless they are extremely numerous, but the concomitant smoke particles contribute largely to impairment of visibility and when plentiful may even produce thick fog. Water fogs are due to sea-salt nuclei and if supersaturation is attained the fogs may thicken considerably owing to the deposition of water on the sea-salt nuclei which consequently become very much larger. Such deposition does not occur on the combustion nuclei if sea-salt nuclei are present. The variation in opacity with relative humidity is calculated theoretically and the calculations are applied to observations of nuclei, particles, and relative humidity at Kew Observatory in the afternoon. Fair agreement is found between the calculated values of opacity and those which correspond to the visibility observed. In one appendix to the paper factors are evaluated by which the visibility of reflecting objects viewed against sky or terrestrial backgrounds may be compared with the visibility of a black object silhouetted against the sky. In a second appendix the increase in opacity during precipitation is calculated.
Organization of the bacterial nucleoid by DNA-bridging proteins and globular crowders

The genomic DNA of bacteria occupies only a fraction of the cell called the nucleoid, although it is not bounded by any membrane and would occupy a volume hundreds of times larger than the cell in the absence of constraints. The two most important contributions to the compaction of the DNA coil are the cross-linking of the DNA by nucleoid proteins (like H-NS and StpA) and the demixing of DNA and other abundant globular macromolecules which do not bind to the DNA (like ribosomes). The present work deals with the interplay of DNA-bridging proteins and globular macromolecular crowders, with the goal of determining the extent to which they collaborate in organizing the nucleoid. In order to answer this question, a coarse-grained model was developed and its properties were investigated through Brownian dynamics simulations. These simulations reveal that the radius of gyration of the DNA coil decreases linearly with the effective volume ratio of globular crowders and the number of DNA bridges formed by nucleoid proteins in the whole range of physiological values. Moreover, simulations highlight the fact that the number of DNA bridges formed by nucleoid proteins depends crucially on their ability to self-associate (oligomerize). An explanation for this result is proposed in terms of the mean distance between DNA segments and the capacity of proteins to maintain DNA–bridging in spite of the thermal fluctuations of the DNA network. Finally, simulations indicate that non-associating proteins preserve a high mobility inside the nucleoid while contributing to its compaction, leading to a DNA/protein complex which looks like a liquid droplet. In contrast, self-associating proteins form a little deformable network which cross-links the DNA chain, with the consequence that the DNA/protein complex looks more like a gel.
CBFF-Net: A New Framework for Efficient and Accurate Hyperspectral Object Tracking

Visual object tracking is a fundamental task in computer vision and thrived in recent decades. With the development of snapshot hyperspectral (HS) sensors, efforts have been made to exploit tracking the object with HS videos to overcome the inherent limitation of red–green–blue (RGB) images. Existing HS tracking algorithms extract the deep features from image data separately, which break the interaction information between bands. Therefore, the discrimination ability of HS trackers is limited and the efficiency of the existing HS algorithms is low. In this article, a novel algorithm [cross-band feature fusion network (CBFF-Net)] is proposed for HS object tracking to improve the discrimination ability and reduce the computational complexity. Specifically, the backbone and head network are implemented with modules of a transferred RGB object tracking network to carry out the HS target tracking task while maintaining the discrimination ability learned from RGB data. Moreover, a bidirectional multiple deep feature fusion (BMDFF) module is proposed to fuse the features extracted from different bands of the HS images, and a cross-band group attention (CBGA) module is introduced to learn interaction information across bands of the HS images. Experiments results indicate the superiority in performance of CBFF-Net, and it runs at 24 frames/s (FPS).