Miracle-dz/UniFAR-FTUs huggingface dataset:
Contribution of Exogenous Proline to Abiotic Stresses Tolerance in Plants: A Review

Abiotic stresses are the major environmental factors that play a significant role in decreasing plant yield and production potential by influencing physiological, biochemical, and molecular processes. Abiotic stresses and global population growth have prompted scientists to use beneficial strategies to ensure food security. The use of organic compounds to improve tolerance to abiotic stresses has been considered for many years. For example, the application of potential external osmotic protective compounds such as proline is one of the approaches to counteract the adverse effects of abiotic stresses on plants. Proline level increases in plants in response to environmental stress. Proline accumulation is not just a signal of tension. Rather, according to research discussed in this article, this biomolecule improves plant resistance to abiotic stress by rising photosynthesis, enzymatic and non-enzymatic antioxidant activity, regulating osmolyte concentration, and sodium and potassium homeostasis. In this review, we discuss the biosynthesis, sensing, signaling, and transport of proline and its role in the development of various plant tissues, including seeds, floral components, and vegetative tissues. Further, the impacts of exogenous proline utilization under various non-living stresses such as drought, salinity, high and low temperatures, and heavy metals have been extensively studied. Numerous various studies have shown that exogenous proline can improve plant growth, yield, and stress tolerance under adverse environmental factors.
Evolution of Neuroimaging Findings in Severe COVID-19 Patients with Initial Neurological Impairment: An Observational Study

Background and Objectives: Cerebral complications related to the COVID-19 were documented by brain MRIs during the acute phase. The purpose of the present study was to describe the evolution of these neuroimaging findings (MRI and FDG-PET/CT) and describe the neurocognitive outcomes of these patients. Methods: During the first wave of the COVID-19 outbreak between 1 March and 31 May 2020, 112 consecutive COVID-19 patients with neurologic manifestations underwent a brain MRI at Strasbourg University hospitals. After recovery, during follow-up, of these 112 patients, 31 (initially hospitalized in intensive care units) underwent additional imaging studies (at least one brain MRI). Results: Twenty-three men (74%) and eight women (26%) with a mean age of 61 years (range: 18–79) were included. Leptomeningeal enhancement, diffuse brain microhemorrhages, acute ischemic strokes, suspicion of cerebral vasculitis, and acute inflammatory demyelinating lesions were described on the initial brain MRIs. During follow-up, the evolution of the leptomeningeal enhancement was discordant, and the cerebral microhemorrhages were stable. We observed normalization of the vessel walls in all patients suspected of cerebral vasculitis. Four patients (13%) demonstrated new complications during follow-up (ischemic strokes, hypoglossal neuritis, marked increase in the white matter FLAIR hyperintensities with presumed vascular origin, and one suspected case of cerebral vasculitis). Concerning the grey matter volumetry, we observed a loss of volume of 3.2% during an average period of approximately five months. During follow-up, the more frequent FDG-PET/CT findings were hypometabolism in temporal and insular regions. Conclusion: A minority of initially severe COVID-19 patients demonstrated new complications on their brain MRIs during follow-up after recovery.
Differentiating between direct and indirect hate crime: Results from Poland

Inspired by individual-level research on direct and indirect as well as reactive and proactive aggression, this article proposes to differentiate direct and indirect types of hate crime. We use the largest hate crime database in Poland (N = 3,153 incidents) to analyze: (1) temporal trends in the relative prevalence of two types of hate crime; (2) the involvement of hate group-affiliated and non-hate group-affiliated perpetrators; and (3) the targeting of victims that are perceived to pose more of a symbolic (vs. more of a realistic threat) to the majority group. Results indicate that direct hate crime was more likely than indirect hate crime to be perpetrated by members and affiliates of hate groups, was more likely to target outgroups seen as posing symbolic rather than realistic threat to the majority group, and was also positively related to societal levels of negative intergroup attitudes and negatively related to unemployment. The findings also show that the two types of hate crime are differently predicted by factors indicative of the social and political climate of the country (e.g., unemployment, political preferences, xenophobia). Although the results were only obtained in one cultural context and will benefit from further validation, they provide very promising initial evidence for the predictive utility of distinguishing direct and indirect hate-crime.
Influence of Core-Stability Exercises Guided by a Telerehabilitation App on Trunk Performance, Balance and Gait Performance in Chronic Stroke Survivors: A Preliminary Randomized Controlled Trial

Stroke is one of the main causes of disability. Telerehabilitation could face the growing demand and a good strategy for post-stroke rehabilitation. The aim of this study is to examine the possible effects of therapeutic exercises performed by an App on trunk control, balance, and gait in stroke survivors. A preliminary 12-week randomized controlled trial was developed. Thirty chronic stroke survivors were randomly allocated into two groups. Both groups performed conventional physiotherapy, in addition to, the experimental group (EG) had access to a telerehabilitation App to guide home-based core-stability exercises (CSE). Trunk performance was measured with the Spanish-Trunk Impairment Scale (S-TIS 2.0) and Spanish-Function in Sitting Test. Balance and gait were measured with Spanish-Postural Assessment Scale for Stroke patient, Berg Balance Scale and an accelerometer system. In EG was observed an improvement of 2.76 points in S-TIS 2.0 (p = 0.001). Small differences were observed in balance and gait. Adherence to the use of the App was low. CSE guided by a telerehabilitation App, combined with conventional physiotherapy, seem to improve trunk function and sitting balance in chronic post-stroke. Active participation in the rehabilitation process should be increased among stroke survivors. Further confirmatory studies are necessary with a large sample size.
SOCIAL WORKERS' EXPERIENCES OF WORKING WITH CHILDREN AND YOUTHS AT CHILD AND YOUTH CARE CENTRES IN DURBAN

Social workers employed in Child and Youth Care Centres (CYCCs) play a critical role in offering therapeutic services for children and youths in need of care. This article explores social workers' experiences working in seven different CYCCs in Durban. It is based on qualitative research using an exploratory, descriptive research design with a sample of eleven social workers. Social workers in CYCCs faced challenges including role overload and overlap, lack of adequate resources, safety and security concerns and limited support, which caused strain and compromised social workers' core role in CYCCs. The article offers practical solutions and recommendations for addressing these challenges.
Web-Based Psychological Interventions for People Living With and Beyond Cancer: Meta-Review of What Works and What Does Not for Maximizing Recruitment, Engagement, and Efficacy

Background Despite high levels of psychological distress experienced by many patients with cancer, previous research has identified several barriers to accessing traditional face-to-face psychological support. Web-based psychosocial interventions have emerged as a promising alternative. Objective This meta-review aimed to synthesize evidence on recruitment challenges and enablers, factors that promote engagement and adherence to web-based intervention content, and factors that promote the efficacy of web-based psychosocial interventions for patients with cancer and cancer survivors. Methods We conducted a systematic search of previous reviews that investigated the recruitment, engagement, and efficacy of web-based and app-based psychosocial interventions in adult patients with cancer and cancer survivors. We searched PubMed, CINAHL, PsycINFO, and the Cochrane Library database for relevant literature. The search terms focused on a combination of topics pertaining to neoplasms and telemedicine. Two independent authors conducted abstract screening, full text screening, and data extraction for each identified article. Results A total of 20 articles met eligibility criteria. There was inconsistency in the reporting of uptake and engagement data; however, anxiety about technology and perceived time burden were identified as 2 key barriers. Web-based psychosocial oncology interventions demonstrated efficacy in reducing depression and stress but reported weak to mixed findings for distress, anxiety, quality of life, and well-being. Although no factors consistently moderated intervention efficacy, preliminary evidence indicated that multicomponent interventions and greater communication with a health care professional were preferred by participants and were associated with superior effects. Conclusions Several consistently cited barriers to intervention uptake and recruitment have emerged, which we recommend future intervention studies address. Preliminary evidence also supports the superior efficacy of multicomponent interventions and interventions that facilitate communication with a health care professional. However, a greater number of appropriately powered clinical trials, including randomized trials with head-to-head comparisons, are needed to enable more confident conclusions regarding which web-based psychosocial oncology interventions work best and for whom. Trial Registration PROSPERO CRD42020202633; https://www.crd. york.ac. uk/prospero/display_record. php? RecordID=202633
Internet Gaming Disorder: Evidence for a Risk and Resilience Approach

Although previous research has noted a range of factors that predict developing Problematic Video Game Use (PVGU) and Internet Gaming Disorder (IGD), few studies have looked at risk and protective factors together, and there is scant empirical evidence examining whether risk for PVGU or IGD increases or decreases as risk or protective factors accumulate in the individual. The aim of the current study was to examine both issues using predictors from three demonstrated PVGU and IGD risk categories: executive dysfunction, unmet needs in everyday life, and unhelpful family environment. In a survey of N = 866 12–17-year-old school students, the risk/protective factors that most strongly predicted severity of IGD symptomology and meeting IGD diagnostic criteria were self-control and social exclusion. Other significant predictors included impulsivity, self-esteem, mastery, control of one’s external environment, and better parent-child attachment quality. Trend analyses revealed a linear increase in the risk of PVGU as risk and net-risk factors accumulated, and a decrease as protective and net-protective factors accumulated. Thus, a net accumulation of issues around impulse control and unmet needs in everyday life may predispose adolescents to PVGU or IGD. Results support a ‘risk and resilience’ approach to adolescent screen-based disorders and suggest potential benefits to a risk factor focus in treatment.
Image space branch-reduction-bound algorithm for globally minimizing a class of multiplicative problems

This paper presents an image space branch-reduction-bound algorithm for solving a class of multiplicative problems (MP). First of all, by introducing auxiliary variables and taking the logarithm of the objective function, an equivalent problem (EP) of the problem (MP) is obtained. Next, by using a new linear relaxation technique, the parametric linear relaxation programming (PLRP) of the equivalence problem (EP) can be established for acquiring the lower bound of the optimal value to the problem (EP). Based on the characteristics of the objective function of the equivalent problem and the structure of the branch-and-bound algorithm, some region reduction techniques are constructed for improving the convergence speed of the algorithm. Finally, the global convergence of the algorithm is proved and its computational complexity is estimated, and numerical experiments are reported to indicate the higher computational performance of the algorithm.
VIBRATION REDUCTION OF A STRUCTURE USING VISCOELASTIC DAMPERS INSTALLED BY CABLES

In this study new installation scheme for passive dampers was proposed using cables installed in such a way that relative displacement equal to story displacement occurs between the cable and the structure when the structure is subjected to lateral load. The cables can be installed continuously or discretely between base and top story of the structure. To verify the validity of the proposed method nonlinear dynamic analysis of model structures with viscoelastic dampers installed using the proposed configuration scheme was carried out using three earthquake records and two sinusoidal forces. According to the analysis results the proposed method resulted in significant reduction in the size of dampers compared with the conventional installation methods.
Reviews of Computer-Aided Technologies for Jewelry Design and Casting

The paper reviews the existing and state-of-the-art computer-aided technologies and computational techniques, which can be applied to jewelry design and casting. A broad array of techniques are selected and ordered into three key parts: design; model-making; and casting, that outline the core of computer-aided jewelry design and casting. Computer-aided design and haptic technologies are surveyed in the purposes of supporting the design of jewelry and shape modeling. Rapid prototyping and computer numerical controlled machines are reviewed in the functions of fabricating physical jewelry models and developing the direct tools. Computer-aided engineering technologies are investigated in the rationales of simulating lost-wax casting process and optimizing process parameters. Artificial intelligence techniques are reviewed in intentions of developing algorithmic designs, and assisting hard computations and parameter optimizations in designing and casting. With those computer advanced technologies, major challenges and solutions are systematically discussed and commented to address new developments for jewelry industry.
Distributed fault detection and isolation in time‐varying formation tracking UAV multi‐agent systems

The problem of distributed fault detection and isolation (DFDI) in conjunction with time‐varying formation control of unmanned aerial vehicle (UAV) multi‐agent systems with multiple‐leader leader–follower structure is studied, in this paper. It is assumed that the communication data of the agents are noisy, and faults may occur in either leaders or followers. The followers are not aware of the main trajectory and just follow the leaders. The first step in this paper is to reduce the communication noise. Besides, if a fault occurs in one of the leaders causing to exit the leader from the main trajectory, the followers should be able to detect the fault, isolate the leader, use the other leaders' data, and keep the main trajectory. Tracking the trajectory by followers in such a case is the second step of this paper. Preserving the time‐varying formation despite a fault occurring in one of the followers is the next step. To reach these goals, a distributed array of Kalman filters is used for noise cancellation and data extraction. Next, the combination of state vector data fusion and some type of χ2 test are employed for DFDI, in agents. Besides, a controller is implemented in each agent for formation tracking. In this controller, estimated relative position and velocity vectors of the agents are employed to keep the time varying formation while tracking the leaders. The closed‐loop stability is studied via Lyapunov stability theorem, and various simulations are carried out to demonstrate the capability of the proposed strategy.
Homogenization and Trends Analysis of Monthly Precipitation Series in the Fez-Meknes Region, Morocco

High quality and long-term precipitation data are required to study the variability and trends of rainfall and the impact of climate change. In developing countries like Morocco, the quality of climate data collected from various weather stations faces numerous obstacles. This paper presents methods for collecting, correcting, reconstructing, and homogenizing precipitation series of Morocco’s Fez-Meknes region from 1961 to 2019. Data collected from national specialized agencies based on 83 rain gauge stations was processed through an algorithm specially designed for the homogenization of climatic data (Climatol). We applied the Mann-Kendall test and Sen’s slope estimator to raw and homogenized data to calculate rainfall trend magnitudes and significance. The homogenization process allows for the detection of a larger number of stations with statistically significant negative trends with 95% and 90% confidence levels, particularly in the mountain ranges, that threatens the main sources of water in the largest watershed in the country. The regionalization of our rain gauge stations is highlighted and compared to previous studies. The monthly and annual means of raw and homogenized data show minor differences over the three main climate zones of the region.
Quality and Price of Spruce Logs, Determined Conventionally and by Dendrochronological and NDE Techniques

We examined valuable log assortments of Norway spruce (Picea abies) from a traditional auction in Slovenia where spruce growth on many sites is affected by climate change. From 6620 logs, we selected 817 that obtained the highest prices. Factors including log dimensions and geometry, tree-ring characteristics, quality grades according to the standard, properties measured by NDE stress wave testing, and their combined effect on price were modelled. The results showed that half of the auctioned logs were of highest quality (Q1, Q2), with diameters over 60 cm. These logs were more expensive than the thinner logs of lower quality (Q3, Q4). The quality class of the logs, determined by their external features and geometry, was associated with tree-ring and acoustic characteristics. The artificial neural network model (ANN) with feed-forward backpropagation using tree-ring data, longitudinal stress wave velocity, and damping showed that more than 75% of the logs could be accurately classified into quality classes. On the other hand, tree-ring data and acoustic characteristics could not adequately explain the price offered at auction, which probably also depends on unidentified individual requirements and the needs of the buyer.
Microfluidic Applications of Artificial Cilia: Recent Progress, Demonstration, and Future Perspectives

Artificial cilia-based microfluidics is a promising alternative in lab-on-a-chip applications which provides an efficient way to manipulate fluid flow in a microfluidic environment with high precision. Additionally, it can induce favorable local flows toward practical biomedical applications. The endowment of artificial cilia with their anatomy and capabilities such as mixing, pumping, transporting, and sensing lead to advance next-generation applications including precision medicine, digital nanofluidics, and lab-on-chip systems. This review summarizes the importance and significance of the artificial cilia, delineates the recent progress in artificial cilia-based microfluidics toward microfluidic application, and provides future perspectives. The presented knowledge and insights are envisaged to pave the way for innovative advances for the research communities in miniaturization.
Prediction of in-hospital mortality: An adaptive severity-of-illness score for a tertiary ICU in South Africa

Background A scoring system based on physiological conditions was developed in 1984 to assess the severity of illness. This version, and subsequent versions, were labelled Simplified Acute Physiology Scores (SAPS). Each extension addressed limitations in the earlier version, with the SAPS III model using a data-driven approach. However, the SAPS III model did not include data collected from the African continent, thereby limiting the generalisation of the results. Objectives To propose a scoring system for assessing severity of illness at intensive care unit (ICU) admission and a model for prediction of in-hospital mortality, based on the severity of illness score. Methods This is a prospective cohort study which included patients who were admitted to an ICU in a South African tertiary hospital in 2017. Logistic regression modelling was used to develop the proposed scoring system, and the proposed mortality prediction model. Results The study included 829 patients. Less than a quarter of patients (21.35%; n=177) died during the study period. The proposed model exhibited good calibration and excellent discrimination. Conclusion The proposed scoring system is able to assess severity of illness at ICU admission, while the proposed statistical model may be used in the prediction of in-hospital mortality. Contributions of the study This study is the first to develop a model similar to the SAPS III model, based on data collected in South Africa. In addition, this study provides a potential starting point for the development of a model that can be used nationally.
Controllable Swarm Animation using Deep Reinforcement Learning with a Rule-based Action Generator

The swarm behavior in nature is a fascinating and complex phenomenon that has been studied extensively for decades. Visually natural swarm animation can be produced by the state-of-the-art rule-based method; however, it still suffers from the drawbacks of low control accuracy and instability in swarm behavior quality when controlled by the user. In this study, we propose a deep reinforcement learning (DRL) based approach to generate swarm animation that reacts to real-time user control with high quality. A rule-based action generator (RAG) adapted to the actor-critic DRL method is presented to enhance DRL’s action exploration strategy. Various practical dynamic reward functions are also designed for DRL to train agents by rewarding swarm behaviors and penalizing misbehavior. The user controls the swarm by interacting with the swarm’s leader agent, for example by directly changing its speed or orientation, or by specifying a path consisting of waypoints. The second aim of this study is to improve the scalability of the trained policy. We introduce a new state observation quantity of DRL called the embedded features of swarm (EFS) as a state observation of DRL, allowing the trained policy scaling to a more extensive system than it has been trained on. In the experiments, four different scenarios have been designed to evaluate the control accuracy and quality of the generated swarm behavior by metrics and visualization. Additionally, the experiment has compared the performance of the proposed dynamic reward functions with fixed reward functions. Experimental results show that the proposed approach outperforms state-of-the-art methods in terms of swarm behavior quality and control accuracy. Moreover, the proposed dynamic reward functions are more effective than the existing reward functions.