Miracle-dz/UniFAR-FTUs huggingface dataset:
Role of degradation concepts for adsorbing contaminants in context of wastewater irrigation

Marginal water, like treated effluent or other types of wastewater, induces contaminant accumulation in different environmental compartments such as soil and groundwater. With a root zone model and daily rainfall data as input, accumulation in the case of two different degradation concepts was modeled: (I) the solute degrades only in the solution phase, and (II) the solute degrades in both the solution and the adsorption phase. For linear adsorption, both degradation concepts not only yield similar results, but adsorption does not affect the long‐term concentration. This can be readily explained with the governing equations. For nonlinear adsorption, the degradation concept does affect the concentration and fluxes. When the first concept is valid, the long‐term concentration is not affected by adsorption, whereas the short‐term and fluctuations are. For the second degradation concept, the long‐term average concentration and fluxes are also affected by adsorption. A correction factor was derived to correct the analytical solution of the time‐dependent concentration of nonlinearly adsorbing solutes. For all scenarios, reasonable estimates of the long‐term concentration could be obtained with analytical models for most parameter combinations, which can be used to identify contaminant species that should be prioritized for further research.
The Impact of Implementing Talent Management Practices on Sustainable Organizational Performance

As organizations operate in an inexorable marketplace, there are always new and unpredictable difficulties that make managerial roles harder and the achievement of organizational goals and objectives more critical. Recently, the implementation of talent management practices in achieving sustainable organizational performance that will match the firms’ operational and strategic goals have been the concern of both academics and practitioners, but the issue has not been exhaustively investigated. Thus, the aim of this study is to investigate the effect of talent management practices on the sustainable organizational performance in real estate companies located in the United Arab Emirates. This paper seeks to make contributions through an empirical evaluation of talent management in the United Arab Emirates. A structured questionnaire was distributed to collect data from a study sample of 306 managers working in real estate companies. The proposed hypotheses were verified by structural equation modeling (SEM). The results of this study show that talent attraction and talent retention had no impact on the sustainable organizational performance, whereas learning and development and career management were found to have significantly positive impacts. The study suggests that learning and development, and employee career management, should be leveraged on by the management by concentrating on the coaching and training programs and job rotation so that the firm can achieve sustainable organizational performance.
POINTER: Constrained Progressive Text Generation via Insertion-based Generative Pre-training

Large-scale pre-trained language models, such as BERT and GPT-2, have achieved excellent performance in language representation learning and free-form text generation. However, these models cannot be directly employed to generate text under specified lexical constraints. To address this challenge, we present POINTER (PrOgressive INsertion-based TransformER), a simple yet novel insertion-based approach for hard-constrained text generation. The proposed method operates by progressively inserting new tokens between existing tokens in a parallel manner. This procedure is recursively applied until a sequence is completed. The resulting coarse-to-fine hierarchy makes the generation process intuitive and interpretable. We pre-train our model with the proposed progressive insertion-based objective on a 12GB Wikipedia dataset, and fine-tune it on downstream hard-constrained generation tasks. Non-autoregressive decoding yields an empirically logarithmic time complexity during inference time. Experimental results on both News and Yelp datasets demonstrate that POINTER achieves state-of-the-art performance on constrained text generation. We released the pre-trained models and the source code to facilitate future research (this https URL).
Safety Assessment of Dairy Microorganisms, Streptococcus thermophilus and Lactobacillus bulgaricus, Isolated from Traditional Yoghurt Cultures

The traditional fermented food consumption has become very popular because of the increasing public concern about food additives. Lactic Acid Bacteria (LAB) species have traditionally been used as starter cultures in the production of fermented food. LAB can acquire antibiotic resistance from other bacteria in the natural environment and different resistant mechanisms via mutation. The resistance of bacteria to antibiotics is an increasingly important public health problem worldwide. In this study, antibiotic resistance of 115 Streptocoocus thermophilus and 35 Lactobacillus bulgaricus isolates obtained from traditional Turkish yogurts were tested against kanamycin, chloramphenicol, erythromycin, ampicillin, rifampicin, tetracycline, vancomycin and gentamicin using disc diffusion method. Study results showed that most strains were susceptible to all the antibiotics tested while a few of them were determined to be resistant only to kanamycin, ampicillin, erythromycin, and tetracycline. When contacted in a human body, resistant strains might transfer the related genes to the pathogenic species, which may result in devastating consequences.
A Coupled-Inductor-Based Bidirectional Circuit Breaker for DC Microgrid

DC microgrids have attracted more and more attention with its universality, high efficiency, and potential application market. However, dc fault protection is still a challenge to the development of dc microgrids. In this article, a novel bidirectional dc solid-state circuit breaker based on coupled inductor is introduced. It can realize bidirectional energy flow and bidirectional isolation and interruption of short-circuit faults with fewer components. The working principle of the topology and the working process under different conditions are described, and some properties of the novel circuit breaker are explored, including minimum fault current ramp rate and load step analysis, which provide a reference for the selection of component parameters. Finally, the feasibility and performance of the novel bidirectional circuit breaker is evaluated by simulations and experiments.
A simple chromogenic whole-cell arsenic biosensor based on Bacillus subtilis

Arsenic contaminated ground water is a serious public health issue, and recent estimates place 150 million people worldwide at risk. Current chemical field test kits do not reliably detect arsenic at the lower end of the relevant range, and may generate toxic intermediates and waste. Whole-cell biosensors potentially provide an inexpensive, robust and analyte-specific solution to this problem. The second generation of a Bacillus subtilis-based arsenic biosensor, designated Bacillosensor-II, was constructed using the native chromosomal ars promoter, arsR and the reporter gene xylE encoding catechol-2,3-dioxygenase. Within four hours, Bacillosensor-II can detect arsenic in the form of arsenate AsO43- at levels more than one order of magnitude below the recommended safe limit for drinking water suggested by the World Health Organisation (10 µg/L). Detection is reported by the enzymatic conversion of the inexpensive substrate catechol to 2-hydroxy-cis,cis-muconic semialdehyde, a bright yellow product visible by eye. We hope that this work will aid in developing a simple inexpensive field test kit for screening of drinking water for arsenic contamination.
A Novel Greedy FluidSpread Algorithm With Equilibrium Temperature for Influence Diffusion in Social Networks

Maximizing positive influenced users (MPIU) is one of the most important and classic problems in social networks. In this article, we propose an effective solution to the problem of MPIU with positive top-$k$ influence, namely, Greedy FluidSpread Algorithm with Equilibrium Temperature (GFAET). In this article, the behavior of the users, such as the interactions and relationships of each user, and the content of a topic are modeled to the user interest vector and the topic distribution vector, respectively, to calculate the information acceptance probability. The influence diffusion process in social network is modeled as a fluid dynamics system and the attitude of the user is modeled as the fluid temperature. Newton's law of cooling and fluid dynamics theory is utilized to obtain a more accurate value of equilibrium temperature. Important users are then greedily selected in this system. Extensive experiments demonstrate that our GFAET significantly outperforms other traditional methods in terms of positive influence spread on both artificially generated and real-trace network datasets.
Attention-Based Deep Reinforcement Learning for Virtual Cinematography of 360$^{\circ}$ Videos

Virtual cinematography refers to automatically selecting a natural-looking normal field-of-view (NFOV) from an entire 360<inline-formula><tex-math notation="LaTeX">$^{\circ}$</tex-math></inline-formula> video. In fact, virtual cinematography can be modeled as a deep reinforcement learning (DRL) problem, in which an agent makes actions related to NFOV selection according to the environment of 360<inline-formula><tex-math notation="LaTeX">$^{\circ}$</tex-math></inline-formula> video frames. More importantly, we find from our data analysis that the selected NFOVs attract significantly more attention than other regions, i.e., the NFOVs have high saliency. Therefore, in this paper, we propose an attention-based DRL (A-DRL) approach for virtual cinematography in 360<inline-formula><tex-math notation="LaTeX">$^{\circ}$</tex-math></inline-formula> video. Specifically, we develop a new DRL framework for automatic NFOV selection with the input of both the content, and saliency map of each 360<inline-formula><tex-math notation="LaTeX">$^{\circ}$</tex-math></inline-formula> frame. Then, we propose a new reward function for the DRL framework in our approach, which considers the saliency values, ground-truth, and smooth transition for NFOV selection. Subsequently, a simplified DenseNet (called Mini-DenseNet) is designed to learn the optimal policy via maximizing the reward. Based on the learned policy, the actions of NFOV can be made in our A-DRL approach for virtual cinematography of 360<inline-formula><tex-math notation="LaTeX">$^{\circ}$</tex-math></inline-formula> video. Extensive experiments show that our A-DRL approach outperforms other state-of-the-art virtual cinematography methods, over the datasets of Sports-360 video, and Pano2Vid.
The role of social support in contributing to posttraumatic growth in persons with vision impairment

background Some individuals report transformational growth understood as lasting positive changes following adverse experiences. Recently psychological research has attempted to understand the complex relationship between adversity and subsequent growth. In 1995 Tedeschi and Calhoun coined the term “posttraumatic growth” (PTG), which is also termed “adversarial growth” by Linley and Joseph. PTG has become a leading area of research, striving for a balanced positive psychology that integrates the complexity between the negatives and positives to optimise positive outcomes. Therefore, the purpose of this study was to elucidate the role of social support in contributing to PTG in three study cases.
Fetal Origins – A Life Cycle Model of Health and Aging from Conception to Death

The fetal origins hypothesis suggests that health and nutrition shocks in utero are causally related to health deficits in old age. It has received considerable empirical support, both within epidemiology and economics but so far it has not been integrated into a life cycle theory of human aging and longevity. The present study shows that the health deficit model, based on the frailty index developed in gerontology, generates shock amplification consistent with the hypothesis. In order to discuss human health over the life cycle from conception to death, we develop a theory of ontogenetic growth and health in utero and during childhood, unify it with the health deficit model of adult aging, and discuss the transmission of early-life shocks to late-life health deficit accumulation.
Power and Subcarrier Allocation in 5G NOMA-FD Systems

In this article, we study the problem of power and channel allocation for multicarrier non-orthogonal multiple access (NOMA) full duplex (FD) systems. In such a system there are multiple interfering users transmitting over the same channel and the allocation task is a non-convex and extremely challenging problem. Following a block coordinated descent approach, we propose two algorithms based on the decomposition of the original allocation problem in lower-complexity sub-problems, which can be solved in the Lagrangian dual domain with a great reduction of the computational load. Numerical results show the effectiveness of the proposed approach, which outperforms other schemes designed to address NOMA-FD allocation and attains performance similar to the optimal solution with much lower complexity.
Is Covid-19 "The Great Leveler"? The Critical Role of Social Identity in Lockdown-induced Job Losses

Using nationally representative panel data for 21,799 individuals between May 2018 and April 2020, this paper investigates whether the Covid-19 pandemic was indeed a Great Leveller in the sense that it imposed similar and equivalent labour market shocks on different caste groups. We find that while all caste groups lost jobs in the first month of the lockdown, the job losses for lowest-ranked castes are greater by a factor of three. The data shows that the disproportionate effects stem from lower levels of human capital and over-representation in vulnerable jobs for the lowest-ranked caste groups in the country.
Sistematização dos procedimentos para a implementação da comunicação alternativa e ampliada em uma UTI geral

Objetivo: Descrever os procedimentos que antecederam a intervencao da terapia ocupacional em pacientes com dificuldades comunicativas internados em uma Unidade de Terapia Intensiva (UTI). Metodo: Pesquisa-acao realizada em uma UTI de um hospital de referencia na cidade do Rio de Janeiro, no periodo de junho a dezembro de 2018, com pacientes com restricao de comunicacao verbal, profissionais de saude e familiares. Os instrumentos utilizados foram: 1) avaliacao da condicao clinica e a biografia do paciente; 2) registro sobre informacoes basicas a beira do leito; 3) protocolo de avaliacao de habilidades comunicativas; 4) avaliacao do perfil ocupacional do sujeito apoiada em um conjunto de pranchas de Comunicacao Alternativa e Ampliada (CAA); e 5) escala de satisfacao do paciente aplicada antes e apos a intervencao. Resultados: Dentre os procedimentos, destacaram-se as acoes que antecederam a entrada do profissional na unidade e o delineamento de etapas que foram iniciadas com a busca ativa; a preparacao do material e os cuidados necessarios; o uso do protocolo de avaliacao e as habilidades comunicativas; a avaliacao do perfil ocupacional; a oferta e o treino do kit basico de pranchas de CAA; a avaliacao da satisfacao do paciente em relacao a sua habilidade comunicativa; o registro no prontuario e a orientacao aos familiares e profissionais de saude. Conclusao: Os dados mostraram que ha uma serie de procedimentos que antecedem a introducao da CAA e que devem ser consideradas e valorizadas pelo terapeuta ocupacional no favorecimento do gerenciamento da comunicacao do paciente com restricao verbal em UTI.
A comparative study on simulating flow-induced fracture deformation in subsurface media by means of extended FEM and FVM

Accurate and efficient simulation on the fluid flow and deformation in porous media is of increasing importance in a diverse range of engineering fields. At present, there are only several methods can be used to simulate the deformation of fractured porous media. It is very important to know their application scopes, advantages, and disadvantages for solving the practical problems correctly. Therefore, in this paper, we compared two numerical simulation methods for flow-induced fracture deformation in porous media. One is the Extended Finite Element Method (XFEM), which is based on the classical finite element method and can simulate strong or weak discontinuous problems. The other is developed within the finite-volume framework, termed Extended Finite Volume Method (XFVM). We designed three test cases, including single fracture, cross fractures and eight discrete fractures, to investigate the accuracy and efficiency of XFEM and XFVM. The reference solutions were provided by the commercial software, COMSOL, where the standard finite element method is implemented. The research findings showed that the accuracy of the XFEM was slightly higher than that of the XFVM, but the latter was more efficient. These results are likely to be useful in decision making regarding choice of solving methods for the multi-field coupling problem in fractured porous media.
The complete chloroplast genome of the Chinese Abelia Lineae chinensis (R.Br.) A.Braun & Vatke (Caprifoliaceae)

Abstract Linnaea chinensis (Caprifoliaceae), which inhabits in China and Japan, is commonly cultivated as an ornamental shrub. The complete chloroplast genome of L. chinensis was newly assembled in this study based on Illumina pair-end sequencing data. The full length of L. chinensis plastome is 155,813 bp. In total, 124 genes were identified, including 75 protein-coding genes, 8 rRNA genes, and 42 tRNA genes. The overall GC content of this genome was 38.4%. A further phylogenomic analysis including16 species from Adoxaceae and Caprifoliaceae was constructed.
Synthetic Aperture Radar Image Statistical Modeling: Part One-Single-Pixel Statistical Models

With the rapid development of spaceborne synthetic aperture radar (SAR) technology and the acquisition of a large volume of SAR images, SAR image interpretation has become an urgent and difficult research topic. SAR image statistical modeling is one of the theoretical foundations for SAR image interpretation. It is of great value for the in-depth analysis of SAR images. This article reviews the major developments of SAR image statistical modeling since its beginning, including more than 20 statistical distributions of eight statistical models, and gives their derivations and expressions, which can be used as a basic reference for the statistical modeling of SAR images (see "Notations and Definitions").
Understanding Decisions in Collective Risk Social Dilemma Games Using Reinforcement Learning

Prior research has used reinforcement-learning models to investigate human decisions in choice games. However, research has not investigated how reinforcement-learning models expectancy valence learning (EVL) and prospect valence learning (PVL) would explain human decisions in applied judgment games where people face a collective risk social dilemma (CRSD) against societal problems such as climate change. In CRSD game, a group of players invested some part of their private incomes to a public fund over several rounds with the goal of collectively reaching a climate target, failing which climate change would occur with a certain probability making players lose their remaining incomes. In this article, we propose EVL and PVL models in the CRSD game and calibrate model parameters to aggregate and individual human decisions across four between-subjects information conditions, where half of the players in each condition possessed lesser wealth (poor) compared to the other half (rich). Results showed that model calibration to individual decisions provided a more accurate account compared to the calibration to aggregate decisions and the EVL model was better fit compared to the PVL model across most conditions. Both models outperformed the symmetric Nash model across all conditions. Overall, moderate recency, loss aversion, and exploration drove people’s decisions. We present the implications of our model results for situations involving a CRSD.
Splice variants of DOMINO control Drosophila circadian behavior and pacemaker neuron maintenance

Circadian clocks control daily rhythms in behavior and physiology. In Drosophila, the small ventral lateral neurons (sLNvs) expressing PIGMENT DISPERSING FACTOR (PDF) are the master pacemaker neurons generating locomotor rhythms. Despite the importance of sLNvs and PDF in circadian behavior, little is known about factors that control sLNvs maintenance and PDF accumulation. Here, we identify the Drosophila SWI2/SNF2 protein DOMINO (DOM) as a key regulator of circadian behavior. Depletion of DOM in circadian neurons eliminates morning anticipatory activity under light dark cycle and impairs behavioral rhythmicity in constant darkness. Interestingly, the two major splice variants of DOM, DOM-A and DOM-B have distinct circadian functions. DOM-A depletion mainly leads to arrhythmic behavior, while DOM-B knockdown lengthens circadian period without affecting the circadian rhythmicity. Both DOM-A and DOM-B bind to the promoter regions of key pacemaker genes period and timeless, and regulate their protein expression. However, we identify that only DOM-A is required for the maintenance of sLNvs and transcription of pdf. Lastly, constitutive activation of PDF-receptor signaling rescued the arrhythmia and period lengthening of DOM downregulation. Taken together, our findings reveal that two splice variants of DOM play distinct roles in circadian rhythms through regulating abundance of pacemaker proteins and sLNvs maintenance.
Maternal immune activation specifically increases diagonal domain volume in the rat brain during early postnatal development

Maternal immune activation (MIA) is consistently associated with elevated risk for multiple psychiatric and neurological disorders in the affected offspring. Converging lines of evidence from humans and animal models suggest a link between MIA and early entry into an atypical neurodevelopmental trajectory characterised by time- and sex-dependent abnormalities in brain structure and function. However to date, no such studies have investigated the brain-wide impact of MIA in the early post-weaning period, a critical and dynamic window of brain development. To address this, we acquired high-resolution ex vivo structural and diffusion tensor imaging (DTI) images from Wistar rat brains on postnatal day (PD) 21 following exposure to the viral mimetic poly (I:C) or sterile saline on gestational day (GD) 15 using a recently validated protocol. Using a combination of atlas-based segmentation and tensor based morphometry analysis we observed that MIA resulted in a significant increase in the relative volume of the diagonal domain (FDR q<0.1). Additional trend-level volume increases (p<0.05 uncorrected) were also found for the olfactory structures and preoptic area. Although not significant after FDR correction, we found trend-level evidence (p<0.05 uncorrected) for MIA x sex interactions in the volume of the diagonal domain, nucleus accumbens, pineal gland and anterior commissure. In contrast to volume, we found no evidence for microstructural alterations in our DTI dataset at PD21. These data provide new insights into the specific effects of MIA early in development, highlighting in particular, the diagonal domain as a target for future studies.
Boletus himalayensis (Basidiomycota; Boletales), a new porcini species from Pakistan

Samina SARWAR*, Sana JABEEN, Ishtiaq AHMAD, Bryn M. DENTINGER, Abdul Nasir KHALID Department of Botany, Lahore College for Women University, Lahore, Pakistan Department of Botany, Division of Science and Technology, University of Education, Township, Lahore, Pakistan 3Centre of Plant Biodiversity, University of Peshawar, Peshawar, Pakistan Natural History Museum of Utah, University of Utah, Salt Lake City, UT, USA Department of Botany, University of the Punjab, Lahore, Pakistan