Miracle-dz/UniFAR-FTUs huggingface dataset:
Fear of COVID-19 Impact on Professional Quality of Life among Mental Health Workers

Several studies have examined the impact of the COVID-19 pandemic on healthcare workers’ mental health, but only a few have investigated its detrimental effect on the mental well-being of mental health workers (MHWs). Background: The current study aimed to explore the effect of the fear of COVID-19 (FCV-19) on professional quality of life dimensions, namely compassion satisfaction (CS), burnout (BO), and secondary traumatic stress (STS) in MHWs above and beyond sociodemographic and professional factors. Methods: Hierarchical linear regression models were employed to examine the relationship of extreme FCV-19 with CS, BO, and STS in MHWs (n = 224), after considering sociodemographic variables as potential confounding factors. Extreme FCV-19 was operationalized as a binary variable with a cut-off score of ≥16.5 considered as extreme fear. Results: We found that extreme FCV-19 in MHWs is linked with increased compassion fatigue (BO and STS), and this relationship is exacerbated by younger age in regard to BO and by female gender concerning STS. CS remains unaffected by severe FCV-19, and it is higher in older participants. Conclusion: Organizational support is required to protect MHWs’ mental well-being and ensure the quality of care they provide during prolonged crises, such as the COVID-19 pandemic. Measures that intensify a sense of safety, protection, and control against COVID-19 infections in mental health services should be included in the recommendations that may reduce BO and STS among MHWs.
Profiling of the Candidate Interacting Proteins of SELF-PRUNING 6A (SP6A) in Solanum tuberosum

SELF-PRUNING 6A (SP6A), a homolog of FLOWERING LOCUS T (FT), has been identified as tuberigen in potato. StSP6A is a mobile signal synthesized in leaves and transmitted to the stolon through phloem, and plays multiple roles in the growth and development of potato. However, the global StSP6A protein interaction network in potato remains poorly understood. In this study, BK-StSP6A was firstly used as the bait to investigate the StSP6A interaction network by screening the yeast two-hybrid (Y2H) library of potato, resulting in the selection of 200 independent positive clones and identification of 77 interacting proteins. Then, the interaction between StSP6A and its interactors was further confirmed by the Y2H and BiFC assays, and three interactors were selected for further expression analysis. Finally, the expression pattern of Flowering Promoting Factor 1.1 (StFPF1.1), No Flowering in Short Days 1 and 2 (StNFL1 and StNFL2) was studied. The three genes were highly expressed in flowers or flower buds. StFPF1.1 exhibited an expression pattern similar to that of StSP6A at the stolon swelling stages. StPHYF-silenced plants showed up-regulated expression of StFPF1.1 and StSP6A, while expression of StNFL1 and StNFL2 was down-regulated in the stolon. The identification of these interacting proteins lays a solid foundation for further functional studies of StSP6A.
Bridging Ecology and Agronomy to Foster Diverse Pastures and Healthy Soils

Renovating pastures to increase forage species diversity is a burgeoning practice among producers. Over a century of grassland and small-plot research suggests that increasing plant diversity can lead to improved pasture productivity, resilience, and soil health. However, it remains hard to decipher how these benefits translate to grazed production systems given the limited experimentation in realistic grazing systems. There is a disconnect between ecological and agronomic research regarding what qualifies as a “diverse” grassland or pasture. This review aims to examine the current state of research regarding plant diversity and its potential benefits for soil health in pasture systems, and outlines how we can improve our understanding and implementation of this practice in production systems.
Learning a hierarchy of specialized pairwise models for coreference resolution (Apprentissage d’une hiérarchie de modèles à paires spécialisés pour la résolution de la coréférence) [in French]

Learning a hierarchy of specialized pairwise models for coreference resolution This paper proposes a new method for significantly improving the performance of pairwise coreference models. Given a set of indicators, our method learns how to best separate types of mention pairs into equivalence classes for which we construct distinct classification models. In effect, our approach finds the best feature space (derived from a base feature set and indicator set) for discriminating coreferential mention pairs. Although our approach explores a very large space of possible features spaces, it remains tractable by exploiting the structure of the hierarchies built from the indicators. Our experiments on the CoNLL-2012 shared task English datasets indicate that our method is robust to different clustering strategies and evaluation metrics, showing large and consistent improvements over a single pairwise model using the same base features. Our best system obtains 67.2 of average F1 over MUC, B 3 , and CEAF which, despite its simplicity,
An exact slope for AdS/CFT

We present a conjecture for the small spin limit of the minimal scaling dimension of Wilson operators in the sl(2) sector of the planar N=4 Super-Yang-Mills theory. The expression is given in closed form as a function of the 't Hooft coupling and twist of the operator. The formula should stand as a prediction of the Asymptotic Bethe Ansatz equations for the spectrum of scaling dimensions and evidence is given at both weak and strong coupling that it should be exact. In particular, agreement is found with established one-loop spectroscopy of string energies at strong coupling.
Advantages of and Barriers to Crafting New Technology in Healthcare Organizations: A Qualitative Study in the COVID-19 Context

Nursing professionals are constantly required to adapt to technological changes, and especially so in the wake of COVID-19, which has prompted the development of new digital tools. A new and specific form of job crafting in relation to new technology has recently emerged in the literature; that is, adoption job crafting. However, little is known about this specific form of job crafting, especially within the pandemic context. We aim, in this study, to explore the advantages of and barriers to adoption job crafting. We used NVivo software to analyze 42 semi-structured interviews conducted during COVID-19. Our findings revealed that nurses had proactive and positive attitudes toward new technology (adoption job crafting) to enhance efficiency, sustainability, well-being, virtual teamwork, communication, and knowledge sharing. We also identified many barriers to adoption job crafting due to several organizational obstacles, such as the lack of human resource management practices, especially training, and the characteristics of the technology used. We contribute to the literature by documenting innovative cases of and barriers to adoption job crafting, which have not been explored before. These findings stress the necessity to adopt human resources practices, especially training, to foster positive job crafting among nurses and safeguard their adaptive expertise.
AI-Based Soft Module for Safe Human–Robot Interaction towards 4D Printing

Soft robotic modules have potential use for therapeutic and educational purposes. To do so, they need to be safe, soft, smart, and customizable to serve individuals’ different preferences and personalities. A safe modular robotic product made of soft materials, particularly silicon, programmed by artificial intelligence algorithms and developed via additive manufacturing would be promising. This study focuses on the safe tactile interaction between humans and robots by means of soft material characteristics for translating physical communication to auditory. The embedded vibratory sensors used to stimulate touch senses transmitted through soft materials are presented. The soft module was developed and verified successfully to react to three different patterns of human–robot contact, particularly users’ touches, and then communicate the type of contact with sound. The study develops and verifies a model that can classify different tactile gestures via machine learning algorithms for safe human–robot physical interaction. The system accurately recognizes the gestures and shapes of three-dimensional (3D) printed soft modules. The gestures used for the experiment are the three most common, including slapping, squeezing, and tickling. The model builds on the concept of how safe human–robot physical interactions could help with cognitive and behavioral communication. In this context, the ability to measure, classify, and reflect the behavior of soft materials in robotic modules represents a prerequisite for endowing robotic materials in additive manufacturing for safe interaction with humans.
Distance-Based Phylogenetic Placement with Statistical Support

Simple Summary Phylogenetic placement seeks to find the optimal position for a new query species on an existing backbone tree. Fast and accurate distance-based phylogenetic placement methods lack the crucial feature of estimating the support values for various placements of a query sequence. This study presents both parametric and nonparametric methods for measuring the support values of distance-based phylogenetic placements. Abstract Phylogenetic identification of unknown sequences by placing them on a tree is routinely attempted in modern ecological studies. Such placements are often obtained from incomplete and noisy data, making it essential to augment the results with some notion of uncertainty. While the standard likelihood-based methods designed for placement naturally provide such measures of uncertainty, the newer and more scalable distance-based methods lack this crucial feature. Here, we adopt several parametric and nonparametric sampling methods for measuring the support of phylogenetic placements that have been obtained with the use of distances. Comparing the alternative strategies, we conclude that nonparametric bootstrapping is more accurate than the alternatives. We go on to show how bootstrapping can be performed efficiently using a linear algebraic formulation that makes it up to 30 times faster and implement this optimized version as part of the distance-based placement software APPLES. By examining a wide range of applications, we show that the relative accuracy of maximum likelihood (ML) support values as compared to distance-based methods depends on the application and the dataset. ML is advantageous for fragmentary queries, while distance-based support values are more accurate for full-length and multi-gene datasets. With the quantification of uncertainty, our work fills a crucial gap that prevents the broader adoption of distance-based placement tools.
Atrial Fibrillation as a Prognostic Indicator in Patients With Orthostatic Hypotension: Nationwide Inpatient Sample Analysis

Background Orthostatic hypotension and atrial fibrillation have common etiology and a bidirectional relationship with several cardiovascular conditions. Despite both conditions being highly prevalent in hospitalized patients, prior research has primarily evaluated adverse outcomes due to orthostatic hypotension and atrial fibrillation independent of each other. In this study, we aim to assess if the presence of atrial fibrillation exacerbates in-hospital outcomes of patients with orthostatic hypotension. Methods Adult patients hospitalized in 2019 with a primary diagnosis of orthostatic hypotension with or without pre-existing atrial fibrillation were identified using the International Classification of Diseases, Tenth Revision (ICD-10) code. The primary outcome of interest was in-patient mortality and cardiac arrest. Secondary outcomes of interest were the length of stay and total hospital charges. Adjusted and unadjusted analysis was performed on appropriate variables of interest. Results Among 10,630 hospitalizations with orthostatic hypotension, 2,987 (median (interquartile range (IQR)) age: 78.5 (68.5 - 88.5) years; 1,197 women (40.1%)) comprised the atrial fibrillation cohort. Mean Charlson comorbidity index was noted to be significantly higher in orthostatic hypotension and atrial fibrillation patients (mean (standard deviation (SD)): 3.1 (2.1) vs. 2.5 (2.1), P < 0.001). Compared to orthostatic hypotension patients without atrial fibrillation, the prevalence of congestive heart failure (1,263 (42.3%) vs. 1,367 (17.9%)), coronary artery disease (1,432 (47.9%) vs. 2,481 (32.5%)), history of percutaneous coronary intervention or graft (443 (14.83%) vs. 860 (11.3%)), chronic obstructive pulmonary disease (644 (21.6%) vs. 1,131 (14.8%)) , chronic kidney disease (1,182 (39.6%) vs. 2,216 (29.0%)), and hyperlipidemia (1,828 (61.2%) vs. 4,087 (53.5%); all P < 0.05), were significantly higher in orthostatic hypotension patients with atrial fibrillation. Following multivariable analysis of orthostatic hypotension patients, atrial fibrillation was associated with 5.0 times greater odds for cardiac arrest (adjusted odds ratio (aOR) = 5.0 (95% confidence interval (CI): 1.4 - 18.2), P = 0.014), without increased risk of in-hospital mortality (aOR = 2.1 (95% CI: 0.9 - 5.0), P = 0.090). Conclusions Atrial fibrillation is an independent predictor for cardiac arrest but not in-hospital mortality in patients with orthostatic hypotension. The short- and long-term prognostic value of atrial fibrillation in orthostatic hypotension patients must be confirmed in future prospective trials to improve patient outcomes.
Spatio-textual search on Spark

The amount of spatially aware data is growing at a rapid rate, and challenges both processing and organizing such data is in focus in the scientific world and the industry. But spatial data seldom exists alone, usually accompanied by some form of textual property. The challenges increase as we attempt to process the spatio-textual documents that are created, and the usage of Big Data platforms become a necessity. This paper provides an insight into different approaches on how to meet the spatial challenges on Big Data platforms, and provides a way to extend a solution to a spatio-textual index on top of Apache Spark. The approach is evaluated to show good results on very large datasets.
Power-Hardware-in-the-Loop Emulation of the Low-Frequency Oscillation Phenomenon in AC Railway Networks

Dynamic interactions among the AC railway traction network and power electronics converters feeding the trains have been reported to cause low-frequency oscillations (LFO) of the catenary voltage and current. This can result in railway system instability, eventually leading to a power outage and the shutdown of the train traffic. To avoid LFO, control of train power electronic converters must be properly designed and tuned. Experimental verification of control performance regarding the LFO phenomenon in the railway traction network is not easy. Alternatively, the railway traction network can be emulated using a power electronic converter, which would feed the train power converter under test. This paper addresses the design of a network emulator able to reproduce the dynamic behavior of the actual network at low frequencies, including LFO. Three different options will be considered for the network emulator. Their performance will be studied first by means of simulations. Finally, the selected solution will be verified on a downscale test bench.
Ovo Like Zinc Finger 2 (OVOL2) Suppresses Breast Cancer Stem Cell Traits and Correlates with Immune Cells Infiltration

Background Breast cancer stem cells (BCSCs) are associated with tumor initiation, invasion, metastasis and drug resistance. It is known that many proteins and signaling pathways are involved in the regulation of BCSCs, however, much more efforts are needed to understand BCSCs comprehensively. Tumor-infiltrating immune cells are important in cancer treatment efficacy and patient prognosis. We tried to identify potential suppressor of BCSCs and analyze its correlation with various immune cells infiltration by bioinformatic and experimental methods. Methods Expression level and methylation state of OVOL2 were analyzed by tools from bc-GenExMiner v4.8 and UALCAN databases. The Kaplan–Meier plotter was applied to evaluate the prognostic values of OVOL2. Gene expression datasets (GSE7515, GSE15192) were selected to analyze differentially expressed genes (DEGs) related to BCSCs. GO and KEGG pathway analyses of DEGs were conducted. MCODE app plugin of Cytoscape was used to screen modules in PPI network of downregulated DEGs. Correlation of OVOL2 expression with infiltrating immune cells was evaluated by TIMER 2.0. Experiments were conducted to verify whether OVOL2 could inhibit stemness traits of breast cancer cell MDA-MB-231. Results The expression level of OVOL2 in basal/TNBC was significantly lower than that of other subtypes. Survival analyses indicated that high expression of OVOL2 was associated with favorable prognosis. GO and KEGG pathway analyses for upregulated and downregulated DEGs were conducted. The top three clusters of downregulated DEGs showed that tight junction and chemokines may play important roles in BCSCs. OVOL2 is one module of clusters. OVOL2 expression is correlated with various immune cells infiltration. Experiments showed that OVOL2 suppresses CD44+/CD24− ratio and mammospheres formation of MDA-MB-231. Conclusion OVOL2 may play an important role in the regulation of breast cancer stemness and immune cell infiltration, and is likely to be a target for the treatment of breast cancer.
On 3D Reconstruction Using RGB-D Cameras

The representation of the physical world is an issue that concerns the scientific community studying computer vision, more and more. Recently, research has focused on modern techniques and methods of photogrammetry and stereoscopy with the aim of reconstructing three-dimensional realistic models with high accuracy and metric information in a short time. In order to obtain data at a relatively low cost, various tools have been developed, such as depth cameras. RGB-D cameras are novel sensing systems that capture RGB images along with per-pixel depth information. This survey aims to describe RGB-D camera technology. We discuss the hardware and data acquisition process, in both static and dynamic environments. Depth map sensing techniques are described, focusing on their features, pros, cons, and limitations; emerging challenges and open issues to investigate are analyzed; and some countermeasures are described. In addition, the advantages, disadvantages, and limitations of RGB-D cameras in all aspects are also described critically. This survey will be useful for researchers who want to acquire, process, and analyze the data collected.
Lamin-A/C Is Modulated by the Involvement of Histamine-Mediated Calcium/Calmodulin-Dependent Kinase II in Lung Cancer Cells

Lamins are nuclear envelope proteins involved in various cellular functions, such as DNA modulation, cellular differentiation, and development. In this study, we investigate the role of histamine in lung cancer biology. Since it is known that lamin-A/C is negatively regulated in lung cancer, we hypothesize that histamine signaling is related to nuclear lamin-A/C regulation and cancer progression. Our findings reveal that histamine stimulation enhances lamin-A/C expression in lung cancer cells. Lamin-A/C expression is dependent on histamine-mediated intracellular calcium signaling and subsequent calcium/calmodulin-dependent kinase II (Ca/CaMKII) activation. The nuclear protein nestin, which stabilizes lamin-A/C expression, is also modulated by Ca/CaMKII. However, histamine-mediated lamin-A/C expression is independent of Akt/focal adhesion kinase or autophagy signaling. Histamine stimulation attenuates lung cancer motility in the presence of enhanced lamin-A/C expression. In conclusion, we propose a regulatory mechanism that accounts for the modulation of lamin-A/C levels through the involvement of Ca/CaMKII in cancer cells and provides molecular evidence of histamine signaling in lamin-A/C biology.
Assessment of Psychosocial Effect and Quality of Life in Breast Cancer Patients

Psychological factors and quality of life influence the breast cancer patient (Khan et al., 2010). The aim of this retrospective study is to evaluate the breast cancer patients’ self-esteem, perceived social support, and quality of life. Sixty patients were taken in this, whose age was between twenty to sixty years. A self-esteem scale, social support questionnaire, and EORTC quality of life questionnaires were used to assess breast cancer patients. All statistical analyzes were completed via SPSS 16.0. The majority of the patients (93%) had high self-esteem and social support (90%). There was a significant association was found between self-esteem and social support (.001). Global health status and functional scores were high. Patients had increased complaints of fatigue, systemic therapy side-effect, and arm symptoms. Participants had suffered increased financial difficulties. It was observed that the sexual activity and sexual enjoyment of the participants had decreased. Breast cancer patients’ self-esteem and social support were high. The overall quality of life in breast cancer patients appeared to be good. The participants had felt more tired, difficulty lifting their arms. Therefore, Higher Self- esteem and social support were strongly associated with a good overall quality of life.
Linoleic Acid-Based Transferosomes for Topical Ocular Delivery of Cyclosporine A

Delivering high-molecular-weight hydrophobic peptides, such as cyclosporine A, across the corneal epithelium remains a challenge that is complicated by other physio-anatomical ocular structures that limit the ocular bioavailability of such peptides. Transferosomes have previously been used to improve transdermal permeability, and have the potential for improving the ocular corneal permeability of applicable drugs. In this study, transferosomes for the potential ocular delivery of cyclosporine A were investigated. Linoleic acid was evaluated for its effect on the stability of the transferosomes and was substituted for a portion of the cholesterol in the vesicles. Additionally, Span® 80 and Tween® 80 were evaluated for their effect on transferosome flexibility and toxicity to ocular cells as edge activators. Attenuated Total Reflectance–Fourier Transform Infrared spectroscopy (ATF-FTIR), differential scanning calorimetry (DSC), and dynamic light scattering (DLS) were used to evaluate the physicochemical parameters of the blank and the cyclosporine A-loaded transferosomes. Cyclosporine A release and corneal permeability were studied in vitro and in a New Zealand albino rabbit corneal model, respectively. The linoleic acid contributed to improved stability and the nano-size of the transferosomes. The Tween®-based formulation was preferred on the basis of a more favorable toxicity profile, as the difference in their corneal permeability was not significant. There was an initial burst release of cyclosporine A in the first 24 h that plateaued over one week. The Tween®-based formulation had a flux of 0.78 µg/cm2/h. The prepared transferosomes demonstrated biocompatibility in the ocular cell line, adequately encapsulated cyclosporine A, ensured the corneal permeability of the enclosed drug, and were stable over the period of investigation of 4 months at −20 °C.