Miracle-dz/UniFAR-FTUs huggingface dataset:
Emotion Regulation and Psychological Capital of Chinese University Students during the COVID-19 Pandemic: The Serial Mediation Effect of Learning Satisfaction and Learning Engagement

The mediating mechanism between the emotion regulation and psychological capital of university students is currently unclear. This study analyzed the serial mediation of learning satisfaction and learning engagement on the relationship between the emotion regulation and psychological capital of university students during the coronavirus disease 2019 (COVID-19) pandemic. A total of 328 undergraduates and postgraduates from universities in different regions of China were surveyed through an online questionnaire. The tools used in the study were the emotion regulation questionnaire, university student learning satisfaction questionnaire, learning engagement questionnaire, and psychological capital questionnaire. The analysis revealed both direct and indirect mediation effects. It was found that emotion regulation can positively predict psychological capital. Further, learning satisfaction and learning engagement can act as mediating variables between emotion regulation and psychological capital, respectively. Learning satisfaction and learning engagement can also have a serial mediation effect between emotion regulation and psychological capital. The results show that learning support should be strengthened to improve the learning satisfaction and learning engagement of students and, consequently, enhance their psychological capital.
What Is Solastalgia and How Is It Measured? SOS, a Validated Scale in Population Exposed to Drought and Forest Fires

Solastalgia is a recent concept that refers to disruptive psychological responses in people exposed to environmental degradation. The aim of this study was to determine the number of dimensions solastalgia has using a sample of people exposed to the effects of climate change in the coastal dry land of Maule region, Chile. In order to achieve this, a Scale Of Solastalgia (SOS) was designed and then validated, by means of applying it to 223 inhabitants at the municipalities of Pencahue (n = 105) and Curepto (n = 118), who were also evaluated by the Short Post-traumatic Stress Disorder Rating Interview (SPRINT-E). Using robust validation methods (Parallel factor analysis and Omega), two dimensions were obtained for solastalgia: solace and algia. Both correlate with the SPRINT-E scale (r = 0.150, p < 0.01 and r = 0.359, p < 0.01, respectively) and have 58% sensitivity and 67% specificity to detect cases of post-traumatic stress disorder (PTSD). Like PTSD, solastalgia is related to psychopathologies expected after disasters and also presents a spatial pattern where the concentration of positive cases occurs in places of greater exposure to environmental change or degradation.
Evolving Einstein's Field Equations with Matter: The ``Hydro without Hydro'' Test

We include matter sources in Einstein's field equations and show that our recently proposed 3+1 evolution scheme can stably evolve strong-field solutions. We insert in our code known matter solutions, namely the Oppenheimer-Volkoff solution for a static star and the Oppenheimer-Snyder solution for homogeneous dust sphere collapse to a black hole, and evolve the gravitational field equations. We find that we can evolve stably static, strong-field stars for arbitrarily long times and can follow dust sphere collapse accurately well past black hole formation. These tests are useful diagnostics for fully self-consistent, stable hydrodynamical simulations in 3+1 general relativity. Moreover, they suggest a successive approximation scheme for determining gravitational waveforms from strong-field sources dominated by longitudinal fields, like binary neutron stars: approximate quasi-equilibrium models can serve as sources for the transverse field equations, which can be evolved without having to re-solve the hydrodynamical equations (``hydro without hydro'').
Partitioning the Effects of Soil Legacy and Pathogen Exposure Determining Soil Suppressiveness via Induced Systemic Resistance

Beneficial host-associated bacteria can assist plant protection against pathogens. In particular, specific microbes are able to induce plant systemic resistance. However, it remains largely elusive which specific microbial taxa and functions trigger plant immune responses associated with disease suppression. Here, we experimentally studied this by setting up two independent microcosm experiments that differed in the time at which plants were exposed to the pathogen and the soil legacy (i.e., soils with historically suppressive or conducive). Overall, we found soil legacy effects to have a major influence on disease suppression irrespective of the time prior to pathogen exposure. Rhizosphere bacterial communities of tomato plants were significantly different between the two soils, with potential beneficial strains occurring at higher relative abundances in the suppressive soil. Root transcriptome analysis revealed the soil legacy to induce differences in gene expression, most importantly, genes involved in the pathway of phenylpropanoid biosynthesis. Last, we found genes in the phenylpropanoid biosynthesis pathway to correlate with specific microbial taxa, including Gp6, Actinomarinicola, Niastella, Phaeodactylibacter, Longimicrobium, Bythopirellula, Brevundimonas, Ferruginivarius, Kushneria, Methylomarinovum, Pseudolabrys, Sphingobium, Sphingomonas, and Alterococcus. Taken together, our study points to the potential regulation of plant systemic resistance by specific microbial taxa, and the importance of soil legacy on disease incidence and eliciting plant-defense mechanisms.
Weber’s Law for Timing and Time Perception: Reconciling the Poisson Clock with Scalar Expectancy Theory (SET)

The pacemaker-counter model is the most prominent psychological account of timing and time perception. It has been often assumed that an internal pacemaker generates pulses according to a Poisson process and that these pulses are accumulated over time. According to Scalar Expectancy Theory (SET), the number of accumulated pulses represents the elapsed duration to be timed. Although the Poisson process provides a plausible cognitive and physiological mechanism for timing and time perception, its implementation into the framework of SET remains a theoretical challenge. The present contribution shows that a merger of Creelman’s (1962) and Treisman’s (1963) counting models enables such an implementation, which can account for Weber’s law and scalar timing. We demonstrate this for the fundamental principles of counting and timing, as well as for a temporal bisection task.
Effect of Size and Concentration of Copper Nanoparticles on the Antimicrobial Activity in Escherichia coli through Multiple Mechanisms

Metal and metal oxide nanoparticles, including copper nanoparticles (CuNPs), display antimicrobial activities and are regarded as promising microorganism inhibitors. Here, we explored the antimicrobial activity of CuNPs in Escherichia coli (E. coli) using two particle sizes (20 and 60 nm) and five concentrations (1, 5, 10, 50 and 100 μg/mL). The result showed a concentration-dependent trend of bactericidal activities for both size groups, with 20 nm particles more effective than 60 nm particles at low concentrations. The membrane disruption caused by CuNPs was confirmed by electron microscopy, PI staining and protein leaking analysis. However, the results of reactive oxygen species generation and genomic DNA damage revealed that the size and concentration of CuNPs were factors affecting the induction of multiple bactericidal mechanisms simultaneously on different scales. Further results of annexin V-PI staining supported this hypothesis by showing the shifting composition of the early-, late- and non-apoptotic dead cells across the CuNP groups. Many CuNP treatment groups were rescued when four mammalian modulators—wortmannin, necrosulfonamide, Z-VAD-FMK, and SBI-0206965—were applied separately. The results suggest the possible existence of bacterial programmed cell death pathways in E. coli which could be triggered by CuNP treatments.
Parametric empirical Bayes model selection---some theory, methods and simulation

For nested models within the PEB framework of george and Foster (Biometrika,2000), we study the performance of AIC, BIC and several relatively new PEB rules under 0-1 and prediction loss, through asymptotics and simulation. By way of optimality we introduce a new notion of consistency for 0-1 loss and an oracle or lower bound for prediction loss.The BIC does badly , AIC does well for the prediction problem with least squares estimates. The structure and performance of PEB rules depend on the loss function. Properly chosen they rend to outperform other rules.
An Investigation of How Firm Size Affects Firm Value through Corporate Reputation

This study proves that firm size is an antecedent of corporate reputation in increasing firm value. Research model is constructed based on Resource-Based Theory. The populations used are manufacturing companies listed on the Indonesia Stock Exchange (IDX) during the 2015-2018 period. The study uses purposive sampling method and documentary data from annual report and the Corporate Image Index score. Path analysis was used to analyze the data and the mediation hypothesis testing was carried out using Sobel test. The results show that the firm size has a significantly positive effect on corporate reputation, but insignificantly effect on firm value. Further testing shows that corporate reputation has a significantly positive effect on firm value. The Sobel test also proves that corporate reputation mediates the relationship between firm size and firm value. This research contributes to previous research studies related to corporate reputation, which tend to be examined partially what prompted the creation of corporate reputation and other parts of the partial ratings as well.
Molecular Targeting of the Most Functionally Complex Gene in Precision Oncology: p53

Simple Summary Precision medicine is a powerful treatment modality for controlling tumor growth. However, given the substantial variability between cancer patients, identifying suitable targets is no easy task. Tumor protein p53 represents one of the most promising anti-cancer drug targets due to its high mutation rate and critical role in tumorigenesis. Despite this, current treatment strategies targeting p53 signaling have only seen modest clinical success presumably due to the complex signaling network surrounding p53 enabling cancer cells to have the ability to adapt to each treatment strategy. This review will focus on the multiple approaches to target p53 and will touch on some of the limitations that may be hindering their clinical success. Abstract While chemotherapy is a key treatment strategy for many solid tumors, it is rarely curative, and most tumor cells eventually become resistant. Because of this, there is an unmet need to develop systemic treatments that capitalize on the unique mutational landscape of each patient’s tumor. The most frequently mutated protein in cancer, p53, has a role in nearly all cancer subtypes and tumorigenesis stages and therefore is one of the most promising molecular targets for cancer treatment. Unfortunately, drugs targeting p53 have seen little clinical success despite promising preclinical data. Most of these drug compounds target specific aspects of p53 inactivation, such as through inhibiting negative regulation by the mouse double minute (MDM) family of proteins. These treatment strategies fail to address cancer cells’ adaptation mechanisms and ignore the impact that p53 loss has on the entire p53 network. However, recent gene therapy successes show that targeting the p53 network and cellular dysfunction caused by p53 inactivation is now possible and may soon translate into successful clinical responses. In this review, we discuss p53 signaling complexities in cancer that have hindered the development and use of p53-targeted drugs. We also describe several current therapeutics reporting promising preclinical and clinical results.
First non‐amber Mesozoic pseudoscorpion from Upper Triassic deposits of eastern Europe, with a description of two new fossil subfamilies (Arachnida, Pseudoscorpiones, Feaellidae)

Pseudoscorpiones is one of the oldest arachnid orders, known in the palaeontological record since the Middle Devonian (c. 390 Ma). The following reliable indications of fossil pseudoscorpions occur in Early Cretaceous amber: Lebanese amber (c. 135–125 Ma), Spanish Álava amber (c. 113–100 Ma), Archingeay amber (c. 100 Ma) and Burmese amber (c. 99 Ma). Thus, there is a gap of at least 255–265 myr in the palaeontological record of pseudoscorpions. Therefore, the fossil feaellid pseudoscorpion Archaeofeaella henderickxi gen. et sp. nov., described herein from Triassic deposits of Ukraine (c. 227 Ma) is of exceptional interest. Based on the analysis of previously unknown morphological features for the family Feaellidae, we place A. henderickxi in Archaeofeaellinae subfam. nov. The previously described species Protofeaella peetersae from Burmese amber is placed in Protofeaellinae subfam. nov., based on comparisons with A. henderickxi as more ancient and closer to the basal group, as well with Recent representatives of this family. Based on this new data, we show that the family Feaellidae survived the Triassic break‐up of Pangaea, and its earliest find is associated not with Gondwana, but with Laurasia; thus, the current ‘Gondwanan distribution’ of the family on the continents of the southern hemisphere is a relic of a wider (probably pancontinental) distribution.
Direct Chaotic Communication in Microwave Band

We discuss the concept of Direct Chaotic Communication (DCC). The scheme is based on the following ideas: (1) the chaotic source generates chaotic oscillations directly in the specified microwave band; (2) information component is input by means of formation of the appropriate stream of chaotic radio pulses; (3) envelope detection is used. The principle of communication scheme is confirmed experimentally in microwave band. The transmission rates of 3.34, 10.0 and up to 70.0 Mbps are demonstrated. his only looks like the abstract.
The velocity ellipsoid in the Galactic disc using Gaia DR1

The stellar velocity ellipsoid of the solar neighbour is re-examined using intermediate-old mono-abundances stellar groups with high quality chemistry data together with parallaxes and proper motions from Gaia DR1. We find the average velocity dispersion values for the three space velocity components for the thin and thick disc of (\sigma_{U},\sigma_{V},\sigma_{W})_{thin} = (33 \pm 4, 28 \pm 2, 23 \pm 2) and (\sigma_{U},\sigma_{V},\sigma_{W})_{thick} = (57 \pm 6, 38 \pm 5, 37 \pm 4) km s^{-1}, respectively. The mean values of the ratio between the semi-axes of the velocity ellipsoid for the thin disc are found to be, \sigma_{V}/\sigma_{U} = 0.70 \pm 0.13 and \sigma_{W}/\sigma_{U} is 0.64 \pm 0.08, while for the thick disc \sigma_{V}/\sigma_{U} = 0.67 \pm 0.11 and \sigma_{W}/\sigma_{U} is 0.66 \pm 0.11. Inputting these dispersions into the linear Str\"omberg relation for the thin disc groups, we find the Sun's velocity with respect to the LSR in Galactic rotation to be V_{\sun} = 13.9 \pm 3.4 km s^{-1}. A relation is found between the vertex deviation and the chemical abundances for the thin disc, ranging from -5 to +40^{\circ} as iron-abundance increases. For the thick disc we find a vertex deviation of l_{uv} \sim -15^{\circ}. The tilt angle (l_{uw}) in the U-W plane for the thin disc groups ranges from -10 to +15^\circ, but there is no evident relation between l_{uw} and the mean abundances. However we find a weak relation for l_{uw} as a function of iron abundances and \alpha-elements for most of the groups in the thick disc, where the tilt angle decreases from -5 to -20^\circ when [Fe/H] decreases and [\alpha/Fe] increases. The velocity anisotropy parameter is independent of the chemical group abundances and its value is nearly constant for both discs (\beta \sim 0.5), suggesting that the combined disc is dynamically relaxed.
Anomaly Detection in Industrial IoT Using Distributional Reinforcement Learning and Generative Adversarial Networks

Anomaly detection is one of the biggest issues of security in the Industrial Internet of Things (IIoT) due to the increase in cyber attack dangers for distributed devices and critical infrastructure networks. To face these challenges, the Intrusion Detection System (IDS) is suggested as a robust mechanism to protect and monitor malicious activities in IIoT networks. In this work, we suggest a new mechanism to improve the efficiency and robustness of the IDS system using Distributional Reinforcement Learning (DRL) and the Generative Adversarial Network (GAN). We aim to develop realistic and equilibrated distribution for a given feature set using artificial data in order to overcome the issue of data imbalance. We show how the GAN can efficiently assist the distributional RL-based-IDS in enhancing the detection of minority attacks. To assess the taxonomy of our approach, we verified the effectiveness of our algorithm by using the Distributed Smart Space Orchestration System (DS2OS) dataset. The performance of the normal DRL and DRL-GAN models in binary and multiclass classifications was evaluated based on anomaly detection datasets. The proposed models outperformed the normal DRL in the standard metrics of accuracy, precision, recall, and F1 score. We demonstrated that the GAN introduced in the training process of DRL with the aim of improving the detection of a specific class of data achieves the best results.
Ab initio study of the phase diagram of epitaxial BaTiO 3

Using a combination of first-principles and effective-Hamiltonian approaches, we map out the structure of ${\text{BaTiO}}_{3}$ under epitaxial constraints applicable to growth on perovskite substrates. We obtain a phase diagram in temperature and misfit strain that is qualitatively different from that reported by Pertsev, Zembilgotov, and Tagantsev [Phys. Rev. Lett. 80, 1988 (1998)], who based their results on an empirical thermodynamic potential with parameters fitted at temperatures in the vicinity of the bulk phase transitions. In particular, we find a region of ``$r$ phase'' at low temperature where Pertsev et al. have reported an ``$ac$ phase. '' We expect our results to be relevant to thin epitaxial films of ${\text{BaTiO}}_{3}$ at low temperatures and experimentally achievable strains.
A Review of Compensation Topologies and Control Techniques of Bidirectional Wireless Power Transfer Systems for Electric Vehicle Applications

Owing to the constantly rising energy demand, Internal Combustion Engine (ICE)-equipped vehicles are being replaced by Electric Vehicles (EVs). The other advantage of using EVs is that the batteries can be utilised as an energy storage device to increase the penetration of renewable energy sources. Integrating EVs with the grid is one of the recent advancements in EVs using Vehicle-to-Grid (V2G) technology. A bidirectional technique enables power transfer between the grid and the EV batteries. Moreover, the Bidirectional Wireless Power Transfer (BWPT) method can support consumers in automating the power transfer process without human intervention. However, an effective BWPT requires a proper vehicle and grid coordination with reasonable control and compensation networks. Various compensation techniques have been proposed in the literature, both on the transmitter and receiver sides. Selecting suitable compensation techniques is a critical task affecting the various design parameters. In this study, the basic compensation topologies of the Series–Series (SS), Series–Parallel (SP), Parallel–Parallel (PP), Parallel–Series (SP), and hybrid compensation topology design requirements are investigated. In addition, the typical control techniques for bidirectional converters, such as Proportional–Integral–Derivative (PID), sliding mode, fuzzy logic control, model predictive, and digital control, are discussed. In addition, different switching modulation schemes, including Pulse-Width Modulation (PWM) control, PWM + Phase Shift control, Single-Phase Shift, Dual-Phase Shift, and Triple-Phase Shift methods, are discussed. The characteristics and control strategies of each are presented, concerning the typical applications. Based on the review analysis, the low-power (Level 1/Level 2) charging applications demand a simple SS compensation topology with a PID controller and a Single-Phase Shift switching method. However, for the medium- or high-power applications (Level 3/Level 4), the dual-side LCC compensation with an advanced controller and a Dual-Side Phase-Shift switching pattern is recommended.
Individualized Decision Making in Transperineal Prostate Biopsy: Should All Men Undergo an Additional Systematic Biopsy?

Simple Summary In the last few years, multiparametric magnetic resonance imaging (mpMRI) has been implemented in the diagnostic prostate cancer pathway for the identification of cancerous lesions, and consecutively, targeted fusion biopsy was implemented. In some cases, aggressive prostate cancer is missed by a targeted biopsy. To address this imperfection, additional systematic biopsy is recommended but may be harmful in terms of the additional diagnosis of indolent cancer, and the higher frequency of adverse events and resource expenditures. This study investigates whether all men should undergo an additional systematic biopsy within this clinically relevant trade-off. As a key finding, men with an mpMRI-lesion classified as PI-RADS 5 may obviate additional systematic biopsy. This was confirmed when we analyzed histopathological reclassification rates between biopsy and a subsequent radical prostatectomy. Abstract Background: In prostate cancer (PC) diagnosis, additional systematic biopsy (SB) is recommended to complement MRI-targeted biopsy (TB) to address the limited sensitivity of TB alone. The combination of TB+SB is beneficial for diagnosing additional significant PC (sPC) but harmful in terms of the additional diagnosis of indolent PC (iPC), morbidity, and resource expenditures. We aimed to investigate the benefit of additional SB and to identify predictors for this outcome. Methods: We analyzed the frequency of upgrading to sPC by additional SB in a retrospective single-center cohort of 1043 men. Regression analysis (RA) was performed to identify predictors for this outcome. Reclassification rates of ISUP grade groups between prostate biopsy and a subsequent radical prostatectomy were assessed. Results: Additional SB led to upgrading to sPC in 98/1043 men (9.4%) and to the additional diagnosis of iPC in 71/1043 (6.8%). In RA, men harboring a PI-RADS 2-4 lesion were more likely to have TB results upgraded by SB (p < 0.01) compared to PI-RADS 5 men. When analyzing reclassification rates, additional SB reduced the upgrading to sPC from 43/214 (20.1%) to 8/214 (3.7%). In the PI-RADS 5 subgroup, this difference decreased: 4/87 (4.7%) with TB only vs. 1/87 (1.2%) with TB+SB. Conclusion: Men with a PI-RADS 5 lesion may obviate additional SB.