Miracle-dz/UniFAR-FTUs huggingface dataset:
Dealing With the COVID-19 Infodemic: Distress by Information, Information Avoidance, and Compliance With Preventive Measures

In the ongoing coronavirus disease 2019 (COVID-19) pandemic, media reports have caused anxiety and distress in many. In some individuals, feeling distressed by information may lead to avoidance of information, which has been shown to undermine compliance with preventive health behaviors in many health domains (e.g., cancer screenings). We set out to examine whether feeling distressed by information predicts higher avoidance of information about COVID-19 (avoidance hypothesis), and whether this, in turn, predicts worse compliance with measures intended to prevent the spread of COVID-19 (compliance hypothesis). Thus, we conducted an online survey with a convenience sample (N = 1,059, 79.4% female) and assessed distress by information, information avoidance, and compliance with preventive measures. Furthermore, we inquired about participants’ information seeking behavior and media usage, their trust in information sources, and level of eHealth literacy, as well as generalized anxiety. We conducted multiple linear regression analyses to predict distress by information, information avoidance, and compliance with preventive measures. Overall, distress by information was associated with better compliance. However, distress was also linked with an increased tendency to avoid information (avoidance hypothesis), and this reduced compliance with preventive measures (compliance hypothesis). Thus, distress may generally induce adaptive behavior in support of crisis management, unless individuals respond to it by avoiding information. These findings provide insights into the consequences of distress by information and avoidance of information during a global health crisis. These results underscore that avoiding information is a maladaptive response to distress by information, which may ultimately interfere with effective crisis management. Consequently, we emphasize the need to develop measures to counteract information avoidance.
Minimal Number of Required Inputs for Temporally Precise Action Potential Generation in Auditory Brainstem Nuclei

The auditory system relies on temporal precise information transfer, requiring an interplay of synchronously activated inputs and rapid postsynaptic integration. During late postnatal development synaptic, biophysical, and morphological features change to enable mature auditory neurons to perform their appropriate function. How the number of minimal required input fibers and the relevant EPSC time course integrated for action potential generation changes during late postnatal development is unclear. To answer these questions, we used in vitro electrophysiology in auditory brainstem structures from pre-hearing onset and mature Mongolian gerbils of either sex. Synaptic and biophysical parameters changed distinctively during development in the medial nucleus of the trapezoid body (MNTB), the medial superior olive (MSO), and the ventral and dorsal nucleus of the lateral lemniscus (VNLL and DNLL). Despite a reduction in input resistance in most cell types, all required fewer inputs in the mature stage to drive action potentials. Moreover, the EPSC decay time constant is a good predictor of the EPSC time used for action potential generation in all nuclei but the VNLL. Only in MSO neurons, the full EPSC time course is integrated by the neuron’s resistive element, while otherwise, the relevant EPSC time matches only 5–10% of the membrane time constant, indicating membrane charging as a dominant role for output generation. We conclude, that distinct developmental programs lead to a general increase in temporal precision and integration accuracy matched to the information relaying properties of the investigated nuclei.
User Modeling and Churn Prediction in Over-the-top Media Services

We address the problem of customer retention ( churn ) in applications installed on over the top (OTT) streaming devices. In the first part of our work, we analyze various behavioral characteristics of users that drive application usage. By examining a variety of statistical measures, we answer the following questions: (1) how do users allocate time across various applications? , (2) how consistently do users engage with their devices? and (3) how likely are dormant users liable to becoming active again? In the second part, we leverage these insights to design interpretable churn prediction models that learn the latent characteristics of users by prioritizing the specifications of the users. Specifically, we propose the following models: (1) Attention LSTM (ALSTM), where churn prediction is done using a single level of attention by weighting on individual time frames (temporal-level attention) and (2) Neural Churn Prediction Model (NCPM), a more comprehensive model that uses two levels of attentions, one for measuring the temporality of each feature and another to measure the influence across features (feature-level attention). Using a series of experiments, we show that our models provide good churn prediction accuracy with interpretable reasoning. We believe that the data analysis, feature engineering and modeling techniques presented in this work can help organizations better understand the reason behind user churn on OTT devices.
COVID-19 Knowledge Test: An Assessment Tool for Health Educators During the COVID-19 Pandemic

Background: As of August 11, 2020, Coronavirus disease 2019 (COVID-19) has infected 19,936,210 persons and led to 732,499 deaths worldwide. The impact has been immense, and with no vaccine currently available, the best way to protect our communities is health education. We developed a brief COVID-19 knowledge test for health educators that can be used to assess deficits in clients' understanding of the disease. Methods: COVID-19 Knowledge Test items were developed by the research team and administered to participants. An alternate-choice item format was selected for the knowledge test, and data analysis was based on an American sample of 273 respondents. A detailed analysis of the data was conducted with classical test theory and Rasch analysis. Findings: The final instrument was found to be a unidimensional measure of COVID-19 knowledge. Results provided evidence for absolute model fit and model fit for individual items. All items included on the scale were monotonically increasing and split-half reliability was considered acceptable. Total test information revealed that the test is suitable for individuals with low to average knowledge of COVID-19. Interpretation: Rasch analysis provides support for the COVID-19 Knowledge Test to be used as an assessment tool for health educators. The final version of the test consists of 34 high-quality test items that can be administered in <10 min. Normative data and suggested cutoff scores are also provided.
A Review of C4 Plants in Southwest Asia: An Ecological, Geographical and Taxonomical Analysis of a Region With High Diversity of C4 Eudicots

Southwest Asia is climatically and topographically a highly diverse region in the xeric belt of the Old World. Its diversity of arid habitats and climatic conditions acted as an important area for the evolution and diversification of up to 20 (of 38 known) independent Eudicot C4 origins. Some of these lineages present unique evolutionary strategies like single-cell functioning C4 and C3–C4 switching mechanisms. The high diversity of C4 taxa in Southwest (SW) Asia is also related to the presence of seven phytogeographic zones including the Irano-Turanian region as a center of diversification of many Caryophyllales lineages and the Somali-Masai region (Southern Oman and Yemen) as a center of diversification for C4 Monocots. Nevertheless, the C4 flora of SW Asia has not received detailed attention. This paper presents a comprehensive review of all known C4 species in the area based on a literature survey, own floristic observations, as well as taxonomic, phylogenetic and herbarium data, and δ13C-isotope ratio analysis. The resulting checklist includes a total number of 923 (861 native, of which 141 endemic, and 62 introduced) C4 species, composed of 350 Eudicots and 509 Monocots, most of which are therophytic and hemicryptophytic xerophytes with pluriregional and Irano-Turanian distribution. Two hundred thirty-nine new δ13C-isotope ratios of C4 and C3 plants, as well as some taxonomic changes are presented. An analysis of the distribution of the three main C4 plant families (Chenopodiaceae, Poaceae, and Cyperaceae) in the region in relation to climatic variables indicates that the increase of C4 species follows more or less a latitudinal gradient similar to global patterns, while separate taxonomic groups seem to depend on specific factors as continentality (Chenopodiaceae), average annual temperature (Cyperaceae), and the presence of summer precipitation (Poaceae). An increase of C4 Eudicots in W-E direction even in similar longitudinal belts is explained by a combination of edaphic and climatic conditions. The provided data should encourage a deeper interest in the evolution of C4 lineages in SW Asia and their adaptation to ecological and climatical conditions and awaken interest in the importance of local C4 crops, the conservation of threatened C4 taxa, and awareness of human impacts on the rapid environmental changes in the region.
Polymorphisms in TLR4 Gene Associated With Somatic Cell Score in Water Buffaloes (Bubalus bubalis)

Considering the importance of the diseases affecting the productive performance of animals in the dairy industry worldwide, it is necessary to implement tools that help to control and limit the occurrence of such diseases. As the increased somatic cell counts (SCC) are a direct expression of the inflammatory process, they are candidates to become the usual parameter for assessing udder health regarding milk quality and for monitoring mastitis incidences. Toll-Like Receptors are membrane proteins that play a key role in immunity, recognizing pathogens and, subsequently, activating immune responses. The present study was conducted to identify single nucleotide polymorphisms in the TLR4 gene of buffaloes and to analyze its associations with somatic cell counts. DNA samples of 120 Murrah buffaloes were used. The whole coding region of the TLR4 gene was amplified by polymerase chain reaction reactions and sequenced for polymorphism scanning. A total of 13 polymorphisms were identified for the sequenced regions of the TLR4, most of which are in the coding region. The association with the somatic cell score was highly significant (p < 0.001) for all identified polymorphisms of TLR4 gene (g.54621T>A, g.54429G>T, g.54407T>A, g.46616C>A, g.46613T>G, g.46612A>G, g.46611C>A, g.46609T>G, g.46541C>G, g.46526C>A, g.46516T>C, g.46376C>T, g.46372T>C). Therefore, it is suggested that the markers of the TLR4 gene can be used as molecular markers for mastitis resistance in buffaloes, due to their association with somatic cell counts.
Functional Status Is Associated With Prefrontal Cortex Activation in Gait in Subacute Stroke Patients: A Functional Near-Infrared Spectroscopy Study

Increasing cerebral oxygenation, more precisely the overactivation of the prefrontal cortex (PFC), reflects cortical control of gait in stroke disease. Studies about the relationship between brain activation and the functional status in stroke patients remain scarce. The aim of this study was to compare brain activation, gait parameters, and cognitive performances in single and dual tasks according to the functional status in subacute stroke patients. Twenty-one subacute stroke patients were divided in two groups according to Barthel Index (“low Barthel” and “high Barthel”) and randomly performed ordered walking, cognitive task (n-back task), and dual tasks (walking + n-back task). We assessed gait performances (speed, variability) using an electronic walkway system and cerebral oxygenation (ΔO2Hb) by functional near-infrared spectroscopy. Patients with better functional status (high Barthel) showed a lower PFC activation (ΔO2Hb) and better gait parameters in single and dual tasks compared to low-Barthel patients, who exhibited decreased gait performances despite a higher PFC activation, especially in the unaffected side (P < 0.001). PFC overactivation in less functional subacute stroke patients may be due to the loss of stepping automaticity. Our results underline the interest of proposing rehabilitation programs focused on walking, especially for patients with low functional capacity.
Correction

ENVIRONMENTAL SCIENCES Correction for “Genetic diversity and population structure of the endangered marsupial Sarcophilus harrisii (Tasmanian devil),” by Webb Miller, Vanessa M. Hayes, Aakrosh Ratan, Desiree C. Petersen, Nicola E. Wittekindt, Jason Miller, Brian Walenz, James Knight, Ji Qi, Fangqing Zhao, Qingyu Wang, Oscar C. Bedoya-Reina, Neerja Katiyar, Lynn P. Tomsho, Lindsay McClellan Kasson, Rae-Anne Hardie, Paula Woodbridge, Elizabeth A. Tindall, Mads Frost Bertelsen, Dale Dixon, Stephen Pyecroft, Kristofer M. Helgen, Arthur M. Lesk, Thomas H. Pringle, Nick Patterson, Yu Zhang, Alexandre Kreiss, Gregory M. Woods, Menna E. Jones, and Stephan C. Schuster, which appeared in issue 30, July 26, 2011, of Proc Natl Acad Sci USA (108:12348–12353; first published June 27, 2011; 10.1073/ pnas.1102838108). The authors note that additional GenBank accession numbers for all the mitochondrial sequences reported in their paper are JX475454–JX475467.
Betulinic Acid Exerts Cytoprotective Activity on Zika Virus-Infected Neural Progenitor Cells

Zika virus (ZIKV), a member of the Flaviviridae family, was brought into the spotlight due to its widespread and increased pathogenicity, including Guillain-Barré syndrome and microcephaly. Neural progenitor cells (NPCs), which are multipotent cells capable of differentiating into the major neural phenotypes, are very susceptible to ZIKV infection. Given the complications of ZIKV infection and potential harm to public health, effective treatment options are urgently needed. Betulinic acid (BA), an abundant terpenoid of the lupane group, displays several biological activities, including neuroprotective effects. Here we demonstrate that Sox2+ NPCs, which are highly susceptible to ZIKV when compared to their neuronal counterparts, are protected against ZIKV-induced cell death when treated with BA. Similarly, the population of Sox2+ and Casp3+ NPCs found in ZIKV-infected cerebral organoids was significantly higher in the presence of BA than in untreated controls. Moreover, well-preserved structures were found in BA-treated organoids in contrast to ZIKV-infected controls. Bioinformatics analysis indicated Akt pathway activation by BA treatment. This was confirmed by phosphorylated Akt analysis, both in BA-treated NPCs and brain organoids, as shown by immunoblotting and immunofluorescence analyses, respectively. Taken together, these data suggest a neuroprotective role of BA in ZIKV-infected NPCs.
BLE Indoor Positioning System Using RSSI-based Trilateration

Systems for outdoor positioning such as Global Positioning System (GPS), Global Navigation Satellite System (GLONASS) or Galileo are commonly used in our everyday lives through smartphones or in-car devices to establish our current position outdoors and/or to navigate to a speciﬁed destination. There is, however, no standard solution to establish our position indoors, where satellite signals do not reach. In this paper we present a system for indoor positioning that uses Bluetooth Low Energy (BLE) beacons as transmitting nodes with known positions and the Received Signal Strength Indicator (RSSI) designating the strength of the signal emitted by the nodes with the help of trilateration to establish user’s position in a building with a mobile application. Due to the signal’s instability we propose enhancements that improve positioning precision. We report results of the conducted tests performed in both static and dynamic scenarios, whose precision is acceptable in most of the typical indoor positioning schemes.
Multi-Enzymatic Systems for Cleaning-up Synthetic Dyes from the Environment

Synthetic dyes are xenobiotic compounds widely used in several industries from textile, paper, pharmaceutical and food, to leather or cosmetics. During the dyeing processes in the textile industry, millions of tons of dyes are discharged in industrial effluents causing serious environmental and health hazards. The current physico-chemical methods used in the treatment of dyecontaining wastewaters are not cost-effective and may result in the formation of hazardous by-products. Therefore, there is an urgent need in the development of efficient and environmentally friendly technologies for the treatment of dye-containing wastewaters. Enzymatic processes can offer several advantages such as specificity to attack the dye molecules while keeping intact dyeing additives or fibers, water recycling, easiness of engineering to improve their robustness, environmentally friendly nature and non-production of sludge. Azoreductases, laccases and peroxidases are among the few enzymes reported in the literature with the ability to degrade synthetic dyes. Hence, the purpose of this thesis was to study the enzymatic properties, mechanisms and toxicity of dye-degradation products of different bacterial enzymes to set-up multi-enzymatic systems for cleaning synthetic dyes from the environment. A new bacterial strain, Pseudomonas putida MET94, was selected among 48 bacterial strains for its ability to decolourise at high extent structurally different synthetic azo dyes. P. putida is an ubiquitous bacterium engaged in important metabolic activities in the environment, including element cycling and degradation of biogenic and xenobiotic pollutants. Therefore, the physiology of synthetic dyes decolourisation processes in growing and resting cells of P. putida MET94 was addressed. Whole-cell systems were tested and optimized not only towards the reduction of single dye molecules but also in the decolourisation of model dye baths with high ionic strengths that mimic effluents produced during cotton and wool dyeing processes. We
Label-Free Oligonucleotide-Based SPR Biosensor for the Detection of the Gene Mutation Causing Prothrombin-Related Thrombophilia

Prothrombin-related thrombophilia is a genetic disorder produced by a substitution of a single DNA base pair, replacing guanine with adenine, and is detected mainly by polymerase chain reaction (PCR). A suitable alternative that could detect the single point mutation without requiring sample amplification is the surface plasmon resonance (SPR) technique. SPR biosensors are of great interest: they offer a platform to monitor biomolecular interactions, are highly selective, and enable rapid analysis in real time. Oligonucleotide-based SPR biosensors can be used to differentiate complementary sequences from partially complementary or noncomplementary strands. In this work, a glass chip covered with an ultrathin (50 nm) gold film was modified with oligonucleotide strands complementary to the mutated or normal (nonmutated) DNA responsible for prothrombin-related thrombophilia, forming two detection platforms called mutated thrombophilia (MT) biosensor and normal thrombophilia (NT) biosensor. The results show that the hybridization response is obtained in 30 min, label free and with high reproducibility. The sensitivity obtained in both systems was approximately 4 ΔμRIU/nM. The dissociation constant and limits of detection calculated were 12.2 nM and 20 pM (3 fmol), respectively, for the MT biosensor, and 8.5 nM and 30 pM (4.5 fmol) for the NT biosensor. The two biosensors selectively recognize their complementary strand (mutated or normal) in buffer solution. In addition, each platform can be reused up to 24 times when the surface is regenerated with HCl. This work contributes to the design of the first SPR biosensor for the detection of prothrombin-related thrombophilia based on oligonucleotides with single point mutations, label-free and without the need to apply an amplification method.
The Relocation Problem of Field Calibrated Low-Cost Sensor Systems in Air Quality Monitoring: A Sampling Bias

This publication revises the deteriorated performance of field calibrated low-cost sensor systems after spatial and temporal relocation, which is often reported for air quality monitoring devices that use machine learning models as part of their software to compensate for cross-sensitivities or interferences with environmental parameters. The cause of this relocation problem and its relationship to the chosen algorithm is elucidated using published experimental data in combination with techniques from data science. Thus, the origin is traced back to insufficient sampling of data that is used for calibration followed by the incorporation of bias into models. Biases often stem from non-representative data and are a common problem in machine learning, and more generally in artificial intelligence, and as such a rising concern. Finally, bias is believed to be partly reducible in this specific application by using balanced data sets generated in well-controlled laboratory experiments, although not trivial due to the need for infrastructure and professional competence.
Local tissue reaction and histopathological characteristics of three different bulking agents: a rabbit model

ABSTRACT Purpose: We assessed the efficacy and safety of a single injection of three bulking agents over the short- and long-term follow-ups in rabbits. Dermal and preputial matrices were compared with Deflux (DxHA) injection. Material and methods: Twenty-four rabbits were divided into three groups. Group I (n=8) underwent the injection of a lyophilized dermal matrix (LDM) beneath the seromuscular layer of the bladder wall. Rabbits in group II (n=8) were injected with lyophilized preputial matrix (LPM). Rabbits of group III (n=8) were injected with DxHA as the control group. They were followed up for 1 and 6 months after the injection. Subcutaneous injection of all bulking agents was also performed in nude mice. Biopsies were stained with LCA (leukocyte common antibody), CD68, CD31, and CD34. Scanning electron microscopy (SEM) and MTT assay were also performed. Results: Immunohistochemistry staining with CD68 and LCA revealed higher inflammation grade in LDM as compared with LPM and DxHA. Fibrosis grade was also higher in LDM both in short- and long-term follow-ups. However, no significant difference was detected in CD31 and CD34 staining between control and experimental groups. SEM analysis showed that the particle size of LPM was more similar to DxHA. MTT assay revealed that cell proliferation was similar in DxHA, LDM, and LPM. In-vivo assay in nude mice model showed more promising results in LPM as compared with LDM. Conclusion: The long-term results demonstrated that LPM was more similar to Deflux with the least local tissue reaction, inflammation, and fibrosis grade.