Miracle-dz/UniFAR-FTUs huggingface dataset:
Zika Virus Replicates in the Vagina of Mice with Intact Interferon Signaling

Zika virus (ZIKV) is transmitted by mosquitoes, similar to other flaviviruses. However, ZIKV is unusual among flaviviruses in its ability also to spread through sexual transmission. ABSTRACT Zika virus (ZIKV) is unusual among flaviviruses in its ability to spread between humans through sexual contact, as well as by mosquitoes. Sexual transmission has the potential to change the epidemiology and geographic range of ZIKV compared to mosquito-borne transmission and potentially could produce distinct clinical manifestations, so it is important to understand the host mechanisms that control susceptibility to sexually transmitted ZIKV. ZIKV replicates poorly in wild-type mice following subcutaneous inoculation, so most ZIKV pathogenesis studies use mice lacking type I interferon (IFN-αβ) signaling (e.g., Ifnar1−/−). We found that wild-type mice support ZIKV replication following intravaginal infection, consistent with prior studies, although the infection remained localized to the lower female reproductive tract. Vaginal ZIKV infection required a high-progesterone state (pregnancy or pretreatment with depot medroxyprogesterone acetate [DMPA]) even in Ifnar1−/− mice that otherwise are highly susceptible to ZIKV infection. Progesterone-mediated susceptibility did not appear to result from a compromised epithelial barrier, blunted antiviral gene induction, or changes in vaginal leukocyte populations, leaving open the mechanism by which progesterone confers susceptibility to vaginal ZIKV infection. DMPA treatment is a key component of mouse vaginal infection models for herpes simplex virus and Chlamydia, but the mechanisms by which DMPA increases susceptibility to those pathogens also remain poorly defined. Understanding how progesterone mediates susceptibility to ZIKV vaginal infection may provide insights into host mechanisms influencing susceptibility to diverse sexually transmitted pathogens. IMPORTANCE Zika virus (ZIKV) is transmitted by mosquitoes, similar to other flaviviruses. However, ZIKV is unusual among flaviviruses in its ability also to spread through sexual transmission. We found that ZIKV was able to replicate in the vaginas of wild-type mice, even though these mice do not support ZIKV replication by other routes, suggesting that the vagina is particularly susceptible to ZIKV infection. Vaginal susceptibility was dependent on a high-progesterone state, which is a common feature of mouse vaginal infection models for other pathogens, through mechanisms that have remained poorly defined. Understanding how progesterone mediates susceptibility to ZIKV vaginal infection may provide insights into host mechanisms that influence susceptibility to diverse sexually transmitted pathogens.
The Passenger Satisfaction Evaluation for Urban Rail Traffic Based on Bayesian Network

This articles by studying urban rail transit operating system and starting from the passenger satisfaction,it established the urban rail transport passenger satisfaction index model and determined the urban rail traffic passenger satisfaction evaluation index architecture and established the urban rail transit passengers' satisfaction Bayesian network model and determined each node of the conditional probability table Bayesian network.Finally,it using the application of Bayesian network calculated and analyzed the example of Chongqing rail transit's service system and proposed a few points to improve rail service improvements.
The Role of Natural Polymorphic Variants of DNA Polymerase β in DNA Repair

DNA polymerase β (Polβ) is considered the main repair DNA polymerase involved in the base excision repair (BER) pathway, which plays an important part in the repair of damaged DNA bases usually resulting from alkylation or oxidation. In general, BER involves consecutive actions of DNA glycosylases, AP endonucleases, DNA polymerases, and DNA ligases. It is known that protein–protein interactions of Polβ with enzymes from the BER pathway increase the efficiency of damaged base repair in DNA. However natural single-nucleotide polymorphisms can lead to a substitution of functionally significant amino acid residues and therefore affect the catalytic activity of the enzyme and the accuracy of Polβ action. Up-to-date databases contain information about more than 8000 SNPs in the gene of Polβ. This review summarizes data on the in silico prediction of the effects of Polβ SNPs on DNA repair efficacy; available data on cancers associated with SNPs of Polβ; and experimentally tested variants of Polβ. Analysis of the literature indicates that amino acid substitutions could be important for the maintenance of the native structure of Polβ and contacts with DNA; others affect the catalytic activity of the enzyme or play a part in the precise and correct attachment of the required nucleotide triphosphate. Moreover, the amino acid substitutions in Polβ can disturb interactions with enzymes involved in BER, while the enzymatic activity of the polymorphic variant may not differ significantly from that of the wild-type enzyme. Therefore, investigation regarding the effect of Polβ natural variants occurring in the human population on enzymatic activity and protein–protein interactions is an urgent scientific task.
Satisfaction with Organizational Career Management and the Turnover Intention of Social Workers in Guangdong Province, China

Abstract High social worker turnover is a serious challenge to the social work organizations in Guangdong Province in Mainland China. Little is understood about the relationship between the social workers’ satisfaction with organizational career management (OCM) and their turnover intentions. A quantitative survey was undertaken to gather information from 212 registered social workers employed by 43 social work organizations in eleven cities in Guangdong Province. This study reveals that social workers’ satisfaction with OCM had significant influence on turnover intentions. Implications of the study are discussed and further research can explore social workers’ career aspirations and its relation to participation in OCM practices.
Using FaceReader to explore the potential for harnessing emotional reactions to motivate hand hygiene

Background Handwashing is a key strategy for reducing the spread of infection but hand hygiene practises are often poor. Pre-testing messages prior to a campaign is expensive and time consuming. Objective This study investigates (1) emotional reactions to handwashing messages based on four different theoretical constructs (Knowledge of Risk, Comfort, Disgust and Social Norms), (2) how images may influence emotional reactions and (3) the influence of emotion, images and theoretical construct on handwashing motivation. Methods A novel methodology was employed whereby FaceReader, software that automatically analyses emotions, was used to identify reactions to handwashing messages. Thirty-one participants from The University of Sheffield were recruited for this laboratory study. Results Most participants did not react strongly to any message and emotional reactions were similar for messages from different theoretical constructs. Adding images to text messages intensified some emotional reactions, particularly Happy and Disgusted for the two messages from the Disgust theoretical perspective. Moreover, participants thought that messages that used images were 1.8 times more likely to encourage handwashing. Knowledge of Risk messages (most encouraging) were 2.9 times more likely to be selected as encouraging handwashing than Comfort messages (least encouraging). An increase in the Disgusted emotion was also associated with an increase in encouragement. Discussion This study suggests that handwashing messages should be designed to exploit emotional reactions but more research is needed to understand how to design messages for these reactions. Whether disgust is as important post Covid-19 requires future investigation. FaceReader can be usefully and inexpensively employed to pre-test handwashing messages.
THE UNEMPLOYMENT-INFLATION TRADE-OFF REVISITED: THE PHILLIPS CURVE IN COVID TIMES

We estimate the natural rate of unemployment, often referred to as u*, in the United States using data on labor market flows, short-term and long-term inflation expectations and a forward-looking New-Keynesian Phillips curve for the 1960-2021 period. The natural rate of unemployment was at around 4.5% before the onset of the pandemic and increased to 5.9% by the end of 2021. This pronounced rise was primarily informed by strong wage growth rather than changes in inflation expectations. Despite the rise in the natural rate of unemployment, the secular trend of unemployment continued to fall and stands at around 4.2% reflecting ongoing secular developments which have been pushing down the unemployment rate over the last 30 years. Our model forecasts strong wage growth to moderate only sluggishly continuing to put upward pressure on inflation in the medium-run. We project underlying inflation to remain 0.5 percentage points above its long-run trend by the end of 2023 even if long-run inflation expectations remain well anchored. Given the importance of wage growth for the inflation outlook, we examine detailed micro data on job-filling rates, posted wages for vacant positions, and workers' reservation wages. In particular, we construct a composition-bias free measure of wage growth at the employer-job level using Burning Glass Technologies data and document strong wage growth for both teleworkable and non-teleworkable jobs. Moreover, we find that workers' reservation wages increased substantially after the pandemic. Our empirical analysis suggests that the strong wage growth is likely not a one-time adjustment of additional compensation for jobs that pose health risks to workers but rather reflects a tight labor market accompanied with a changing work-leisure trade-off.
Advanced control in factory automation: a survey

This paper provides a survey of the main advanced control techniques currently adopted in factory automation. In particular, it focuses on five classes of control approaches, namely: model-based control, control based on computational intelligence, adaptive control, discrete event systems-based control and finally event-triggered and self-triggered control. A particular focus is put on the most significant and recent contributions in these areas with attention to their application in the factory automation domain. Finally, open issues, challenges and the requirements of further research efforts for each class are pointed out.
Mapping of Urban Vegetation with High-Resolution Remote Sensing: A Review

Green space is increasingly recognized as an important component of the urban environment. Adequate management and planning of urban green space is crucial to maximize its benefits for urban inhabitants and for the urban ecosystem in general. Inventorying urban vegetation is a costly and time-consuming process. The development of new remote sensing techniques to map and monitor vegetation has therefore become an important topic of interest to many scholars. Based on a comprehensive survey of the literature, this review article provides an overview of the main approaches proposed to map urban vegetation from high-resolution remotely sensed data. Studies are reviewed from three perspectives: (a) the vegetation typology, (b) the remote sensing data used and (c) the mapping approach applied. With regard to vegetation typology, a distinction is made between studies focusing on the mapping of functional vegetation types and studies performing mapping of lower-level taxonomic ranks, with the latter mainly focusing on urban trees. A wide variety of high-resolution imagery has been used by researchers for both types of mapping. The fusion of various types of remote sensing data, as well as the inclusion of phenological information through the use of multi-temporal imagery, prove to be the most promising avenues to improve mapping accuracy. With regard to mapping approaches, the use of deep learning is becoming more established, mostly for the mapping of tree species. Through this survey, several research gaps could be identified. Interest in the mapping of non-tree species in urban environments is still limited. The same holds for the mapping of understory species. Most studies focus on the mapping of public green spaces, while interest in the mapping of private green space is less common. The use of imagery with a high spatial and temporal resolution, enabling the retrieval of phenological information for mapping and monitoring vegetation at the species level, still proves to be limited in urban contexts. Hence, mapping approaches specifically tailored towards time-series analysis and the use of new data sources seem to hold great promise for advancing the field. Finally, unsupervised learning techniques and active learning, so far rarely applied in urban vegetation mapping, are also areas where significant progress can be expected.
Comprehensive Phytochemical Profiling of Polyherbal Divya-Kayakalp-Vati and Divya-Kayakalp-Oil and Their Combined Efficacy in Mouse Model of Atopic Dermatitis-Like Inflammation Through Regulation of Cytokines

Purpose Atopic dermatitis (AD) is a chronic inflammatory disease that varies in signs and symptoms in different individuals. General symptoms include dryness of the skin, itching, and development of red to brownish-gray patches. Divya-Kayakalp-Vati (DKV) and -Oil (DKO) are Indian polyherbal compositions prescribed for treating inflammatory skin diseases. In the present study, we evaluated the anti-inflammatory efficacy of DKV and DKO co-treatment (DKV-O) in ameliorating Oxazolone (OXA)-stimulated AD-like inflammation and pro-inflammatory cytokine release in a Swiss albino mouse model. Methods Phytochemical profiling of the DKV and DKO were done using Liquid Chromatography-Mass Spectroscopy (LC-MS) QToF. Swiss albino mice were sensitized for 7 days and treated with OXA in their ear region. Stimulated and control animals were orally treated with DKV and topically with DKO. Anti-inflammatory efficacy of DKV-O was determined in OXA-treated animals through physiological, histopathological, and biochemical parameter analysis. Results DKV and DKO formulations individually contained 39 and 59 phytochemicals, respectively. Many of the phytochemicals have been reported to have anti-inflammatory activities. In the OXA-sensitized Swiss albino mice, combined treatment with DKV-O, and separately with Dexamethasone (positive control) significantly reduced the OXA-stimulated ear edema, biopsy weight, and epidermal thickness. DKV-O further reduced OXA-stimulated induction of inflammatory lesions, neutrophil influx, and release of Interleukin (IL)-1β, IL-6, tumor necrosis factor-α, and myeloperoxidase. Conclusion Finally, DKV-O co-treatment showed good pharmacological effects in ameliorating AD-like inflammation through the modulation of inflammatory cell influx and release of soluble mediators. Therefore, DKV-O treatment can be used as a suitable polyherbal therapeutic against AD-like inflammatory diseases.
Eliminating Noise at the Box-fitting Spectrum

Abstract Non gaussian sources of erros need to be taken into consideration when searching for planetary transits. Such phenomena are mostly caused by the impact of high energetic particles on the detector (Pinheiro da Silva et al. 2008). The detection efficiency of transits, therefor, depend significantly on the data quality and the algorithms utilized to deal with these errors sources. In this work we show that a modified detrend algorithm CDA (CoRoT Detrend Algorithm; Mislis et al. 2010) using a robust statistics and an empirical fit, instead of a polynomial one, can eliminate more efficiently gaps in the data and other long-term trends from the light-curve. Using this algorithm enables us to obtain a reconstructed light-curve with better signal-to-noise ratio that allows to improve the detection of exoplanet transits, although long term signals are destroyed. The results show that these modifications lead to an improved BLS (Box-fitting Least Squares; Kovács, Zucker & Mazeh 2002) algorithm spectrum. At the end we have compared our planetary search results with CoRoT (Convection, Rotation and planetary Transits) satellite chromatic light-curves available in the literature.
Response dynamics of spiking network models to incoming seizure-like perturbation

Epilepsies are characterized by electrophysiological crises in the brain, 2 which were first observed thanks to electroencephalograms. However, it is 3 known that seizures originating from one or more specific regions may or 4 may not spread to the rest of the brain, while the exact mechanisms are 5 unclear. We propose three computational models at the neural network 6 scale to study the underlying dynamics of seizure propagation, understand 7 which specific features play a role, and relate them to clinical or exper- 8 imental observations. We consider both network features, such as the 9 internal connectivity structure and single neuron model, and input prop- 10 erties in our characterization. We show that a paroxysmal input leads to 11 a dynamical heterogeneity inside the network, non-trivially related with 12 its architecture, which may or may not entrain it into a seizure. Although 13 hard to anticipate because of the intricate nature of the instability in- 14 volved, the seizure propagation might be circumvented upon acting on 15 the network during a specific time window. As we deal with a complex 16 system, which seems to depend non trivially on various parameters, we 17 propose a probabilistic approach to the propagative/non-propagative sce- 18 narios, which may serve as a guide to control the seizure by using appro- 19 priate stimuli. 20 21 Significance: Our computational study shows the specific role that the 22 inhibitory population can have and the possible dynamics regarding the propa- 23 gation of seizure-like behavior in three different neuronal networks. The study 24 conducts in this paper results from the combination of structural aspects and 25 time-continuous measures, which helps us unravel the internal dynamics of the 26 network. We show the existence of a specific time window favorable to the 27 reversal of the seizure propagation. 28
Studies on the effect of H+ carrier toward ionic conduction properties in alginate-ammonium sulfate complexes–based polymer electrolytes system

The present work highlights the contribution of ammonium sulfate (NH4)2SO4 as H+ carriers in alginate-based solid polymer electrolytes (SPEs) that were successfully prepared via a solution casting technique. The Fourier transform infrared analysis revealed that molecular interactions between the host polymer and the ionic dopant complexes occurred at the wavenumbers 3700–2500 cm−1, 1800–1500 cm−1, and 1200–900 cm−1. These regions corresponded to the O-H stretching, COO− and C-O-C, moieties of alginate, respectively, which coordinated with the H+ carrier from (NH4)2SO4. At ambient temperature, the optimum ionic conductivity was obtained at 3.01 × 10−5 S cm−1 for the sample containing 10 wt. % of (NH4)2SO4. The IR-deconvolution approach shows that the ionic conduction enhancement is governed by the ionic mobility and the diffusion coefficient of H+ carriers, and the findings show that the present biopolymer, which is an alginate-based SPEs system, has an excellent possibility to be used as electrolytes for application in electrochemical devices.
Determination of Control Characteristic for Detecting the Aircraft Pilot Coupling

This paper presents the real-time algorithm of recursive Fourier transform for preprocessing aircraft control/response signals and extracting methodology of aircraft control oscillation characteristic for fuzzy APC/PIO online detection. Through extracting from flight test data of the aircraft pilot coupling, the control oscillation characteristic parameters were analyzed to be reasonable and effectiveness. Finally, some suggestions were put forward to further research.
Distributed Feeder Automation Based on Automatic Recognition of Real-time Feeder Topology

The existing feeder automation(FA)mostly designs the algorithm based on the fixed network topology and tie switch position.The algorithm of FA system needs to be reconfigured if the feeder topology changes.Tie switches can be recognized and the algorithm can be adjusted automatically by detecting the voltages of switches with potential transformers installed on both sides.The smart terminal unit(STU)can recognize the feeder topology and the position of tie switches byrelay inquiry. STUs of adjacent switches locate and isolate the faults by exchanging fault current information.STU monitoring tie switch restores maximum power supply according to the real-time feeder topology and the capacity of backup source.The static simulation test and field application proves that the proposed method can automatically adapt to the change of feeder topology,quickly isolate the fault and restore the power supply.
Oryza nivara allele of a major effect QTL qFLA1.1 increases flag leaf area in rice

A stable back cross introgression line IL65 (IET22161) (Swarna/O. nivara-BC2F6) of rice was used to map flag leaf related traits in F2 and F3. A total of 12 QTLs were mapped for flag leaf related traits on two chromosomes with each QTL explaining 3 to 21% phenotypic variance (PV). Interestingly, a novel 12Mb QTL cluster (RM8094 - RM9) that controls 7 traits was identified on long arm of chromosome 1 where QTLs qSPAD1.2, qSPAD1.3 for SPAD, qFLL1.1, qFLL1.2 for flag leaf length, qFLW1.1, qFLW1.2 for flag leaf width, qFLA1.1, qFLA1.2 for flag leaf area, qPH1.1, qPH1.2 for plant height, qDTF1.2, qDTF1.3 for days to flowering and qHI1.2, qHI1.3 for harvest index were co-located. Among these, one major effect QTL qFLA1.1 for flag leaf area was identified in a 9Mb region between RM8094 and RM5638. There was an adjacent minor effect QTL qFLA1.2 in a 3Mb region between RM5638 and RM9. Together these two QTLs and with leaf area increasing QTL allele from O. nivara explained 19.7% PV. The QTL for flag leaf related traits can be fine mapped and considered for breeding rice varieties with higher flag leaf area, photosynthetic rate and grain yield.
Understanding the Potential of Mental Health Apps to Address Mental Health Needs of the Deaf and Hard of Hearing Community: Mixed Methods Study

Background Mental health concerns are a significant issue among the deaf and hard of hearing (D/HH) community, but community members can face several unique challenges to accessing appropriate resources. Objective The aim of this study was to investigate the mental health needs of the D/HH community and how mental health apps may be able to support these needs. Methods A total of 10 members of the D/HH community participated in a focus group and survey to provide their perspectives and experiences. Participants were members of the Center on Deafness Inland Empire team, which comprises people with lived experience as members of and advocates for the D/HH community. Results Findings identified a spectrum of needs for mental health apps, including offering American Sign Language and English support, increased education of mental health to reduce stigma around mental health, direct communication with a Deaf worker, and apps that are accessible to a range of community members in terms of culture, resources required, and location. Conclusions These findings can inform the development of digital mental health resources and outreach strategies that are appropriate for the D/HH community.