Miracle-dz/UniFAR-FTUs huggingface dataset:
Dengue and chikungunya virus loads in the mosquito Aedes aegypti are determined by distinct genetic architectures

Aedes aegypti is the primary vector of the arboviruses dengue (DENV) and chikungunya (CHIKV). These viruses exhibit key differences in their vector interactions, the latter moving more quicky through the mosquito and triggering fewer standard antiviral pathways. As the global footprint of CHIKV continues to expand, we seek to better understand the mosquito’s natural response to CHIKV—both to compare it to DENV:vector coevolutionary history and to identify potential targets in the mosquito for genetic modification. We used a modified full-sibling design to estimate the contribution of mosquito genetic variation to viral loads of both DENV and CHIKV. Heritabilities were significant, but higher for DENV (40%) than CHIKV (18%). Interestingly, there was no genetic correlation between DENV and CHIKV loads between siblings. These data suggest Ae. aegypti mosquitoes respond to the two viruses using distinct genetic mechanisms. We also examined genome-wide patterns of gene expression between High and Low CHIKV families representing the phenotypic extremes of viral load. Using RNAseq, we identified only two loci that consistently differentiated High and Low families: a long non-coding RNA that has been identified in mosquito screens post-infection and a distant member of a family of Salivary Gland Specific (SGS) genes. Interestingly, the latter gene is also associated with horizontal gene transfer between mosquitoes and the endosymbiotic bacterium Wolbachia. This work is the first to link the SGS gene to a mosquito phenotype. Understanding the molecular details of how this gene contributes to viral control in mosquitoes may, therefore, also shed light on its role in Wolbachia.
Baricitinib as the first systemic treatment for severe alopecia areata

ABSTRACT Introduction Alopecia areata is a heterogenous, immune-mediated hair loss disorder that can affect any hair-bearing site on the body. Despite being one of the most prevalent autoimmune skin diseases, treatments have historically been limited to off-label medications that have demonstrated limited efficacy, especially in more severe forms of disease. Thus, there has long been an unmet need for rigorously studied therapeutics in alopecia areata. Areas covered Janus kinase inhibitors have proven to be an effective class of drugs for treating several inflammatory disorders. One such drug, baricitinib, has recently demonstrated significant hair regrowth in phase 2 and 3 alopecia areata trials. It has since become the first systemic therapy approved for treating severe alopecia areata. This review examines the role of Janus kinase pathways in alopecia areata’s pathogenesis and the safety and efficacy of baricitinib for treating severe alopecia areata. Expert opinion The approval of baricitinib for treating severe alopecia areata marks a major milestone in the disease’s history. While baricitinib has proven to be efficacious for this indication and has demonstrated an overall good safety profile, patients’ individual risk factors for serious adverse events should be assessed during shared decision-making with patients before initiating treatment.
Associations between post-traumatic stress symptoms and sleep/circadian parameters: Exploring the effect of chronotype as a moderator variable

ABSTRACT The present study aimed at evaluating how post-traumatic stress symptoms (PTSS) are associated with rest-activity circadian and sleep-related parameters, assessed both subjectively (via questionnaires) and objectively (via actigraphy). Specifically, we explored whether chronotype could moderate the association between sleep/circadian parameters and PTSS. Participants (n = 120 adults; mean age 35.6 ± 14; 48 male) were assessed through the Trauma and Loss Spectrum Self Report (TALS-SR) for lifetime PTSS, the reduced version of the Morningness-Eveningness Questionnaire (rMEQ) for chronotype, the Pittsburgh Sleep Quality Index (PSQI) for self-reported sleep quality, and wrist actigraphy for sleep and circadian parameters. Eveningness, poor self-reported sleep quality, lower sleep efficiency (SE), lower interdaily stability (IS), and higher intradaily variability (IV) were correlated with higher TALS-SR scores. Regression analyses showed that IV, SE, and PSQI remained associated with TALS symptomatic domains after adjusting for potentially confounding factors (age and gender). Moderation analysis showed that only the PSQI remained significantly associated with TALS symptomatic domains; however, the interaction with chronotype was not significant. Targeting self-reported sleep disturbances and rest-activity rhythms fragmentation could mitigate PTSS. Although the effect of chronotype as a moderator of the associations between sleep/circadian parameters and PTSS was not significant, eveningness was associated with higher TALS scores, thus confirming the vulnerability of evening types to worse stress reactions.
COMPARISON AND ANALYSIS OF STRATIFIED RANDOMIZED RESPONSE MODELS

Introduction Surveys are a means by which responses to questions concerning certain topics may be obtained from a sample of individuals selected in some manner from a population of interest. Results from surveys are affected by two main sources of error. The first is sampling error that results from taking a sample instead of enumerating the whole population. The second type of error is non-sampling error that cannot be attributed to sample-to-sample variability. Nonsampling error has two different errors which are random error and nonrandom error. Random error, which results from a reduction in the reliability of measurements, can be minimized over repeated measurements. However, nonrandom error, which is bias in the survey data, is difficult to cancel out over repeated measurements. Deming (1960) and Cochran (1977) have discussed the sources of non-sampling error and its effects on sampling estimates. The main sources of non-sampling error in any survey are non-response bias and response bias. Non-response bias arises from subjects’ refusal to respond and response bias arises from giving incorrect responses. When open or direct surveys are about sensitive matters (e.g., gambling habits, addiction to drugs and other intoxicants, alcoholism, proneness to tax evasion, induced abortions, drunken driving, history of past involvement in crimes, and homosexuality), nonresponse bias and response bias become serious problems because people oftentimes do not wish to give correct information. In order to reduce non-response and response bias, a survey technique different from open or direct surveys was needed that made people comfortable and encouraged truthful answers. Warner (1965) developed such an alternative survey technique that is called randomized response (RR) technique. Warner’s RR survey technique is designed to eliminate evasive answer bias and keep the respondents’ confidentiality. Since Warner presented the RR technique, many variants of the Warner model have been presented in the literature to further improve the technique, especially in regard to increasing the cooperation of the respondents and decreasing the variances of the RR estimators (i.e., improving model efficiency). This paper briefly introduces three of these: stratified random sampling using optimal allocation versions of Warner’s RR model, the unrelated question RR model, and the two-stage RR model. These models are compared with their respective counterparts that use simple random sampling. Furthermore, the proposed models are compared to each other in terms of relative efficiency. It is shown that stratified random sampling using optimal allocation further minimizes the variability in the estimate of the proportion of people with the sensitive trait under question, resulting in a survey with more precise results.
Interindividual differences in crop foraging behavior of chimpanzees (Pan troglodytes schweinfurthii) at a forest–agriculture interface

The expansion of agriculture in equatorial areas is fragmenting and reducing wildlife habitats. For primates, it also increases opportunities to consume crops as high-energy resources, exacerbates conflicts with farmers, and increases exposure to diseases and agrochemicals at the edge of protected areas. In species with sex differences in ranging behavior, individual exposure to such opportunities and threats may vary by sex. Chimpanzees show a great feeding flexibility and are territorial species with varied ranging patterns according to site, sex, or individuals. Within a community whose territory is crossed by a high-traffic road and partially bordered by maize gardens, we tested hypotheses of interindividual differences in access to crops based on age, sex, ranging behavior, and kinship. By analyzing the presence of Sebitoli chimpanzees (Pan troglodytes schweinfurthii, Kibale National Park, Uganda) on video clips from 16 camera traps, we estimated the individual dispersion range across the community's territory and the crop foraging frequency along maize gardens over 16 months. While all age and sex classes were represented at the forest–garden interface, large intrasex differences were observed: some mature males and females were not observed to participate. The crop foraging frequency of adult females in maize gardens was significantly correlated with the location of their ranging areas. Related individuals revealed similar range patterns within the forest territory without sharing crop foraging habits. However, social learning and energy and risks–benefits trade-offs as potential drivers of crop consumption are not excluded.
Global Error for Generalized Complementarity Problems based on Generalized Fisher-Burmeister Function

In this paper, we provide global error bounds generalized co mplementarity problem, denoted by GCP( f ,g) based on the generalized Fisher-Burmeister function and its generaliz ations under certain conditions. These error bounds can be v iewed not only as extensions of previously known results the existing but als o new results for the nonlinear/generalized complementari ty p oblems.
Easy and efficient spike-based Machine Learning with mlGeNN

Intuitive and easy to use application programming interfaces such as Keras have played a large part in the rapid acceleration of machine learning with artificial neural networks. Building on our recent works translating ANNs to SNNs and directly training classifiers with e-prop, we here present the mlGeNN interface as an easy way to define, train and test spiking neural networks on our efficient GPU based GeNN framework. We illustrate the use of mlGeNN by investigating the performance of a number of one and two layer recurrent spiking neural networks trained to recognise hand gestures from the DVS gesture dataset with the e-prop learning rule. We find that not only is mlGeNN vastly more convenient to use than the lower level PyGeNN interface, the new freedom to effortlessly and rapidly prototype different network architectures also gave us an unprecedented overview over how e-prop compares to other recently published results on the DVS gesture dataset across architectural details.
Talking Turtles With Tourists: Evaluating the Relative Conservation Impacts of Different Types of Sea Turtle Education Programs at Jekyll Island, GA, USA

We used a pre-post survey approach to compare learning and conservation-focused behavioral outcomes for tourists participating in two different types of field-based wildlife education programs at the Jekyll Island Authority Georgia Sea Turtle Center (GSTC) on Jekyll Island, GA, USA: a low-interaction program (n = 59) led by education guides that featured minimal direct contact between visitors and sea turtles, and a high-interaction program (n = 42) led by turtle biologists that featured more intimate interactions between visitors and turtles. Both programs revealed comparable positive effects on participants’ knowledge of sea turtles and intent to engage in turtle advocacy behaviors, but neither type of program had a major influence on pro-turtle attitudes or participation in turtle-friendly beach behaviors (partly because scores for these variables were high entering the program). Results suggest managers and educators at wildlife tourism destinations could employ different program delivery methods while still achieving similar education and conservation goals.
The Impact of Message Framing on Wildlife Approach During Ungulate Viewing Experiences in the Greater Yellowstone Ecosystem

Every year, millions of people visit parks and protected areas to view wildlife. Conflict between people and ungulates is prominent, and many incidents occur when people approach ungulates at proximities less than the National Park Service regulation of 25 yards. The purpose of this study was to test how wildlife viewing communication messages impact park visitors’ approach behavior. A survey and walking exercise were conducted with life-sized ungulate cutouts on a 100-yard transect in Grand Teton and Yellowstone National Parks to test the influence of three message frames (i.e., current NPS messaging, resource protection messaging, and a visitor experience message) on visitors’ approach behaviors. Park visitors overestimated proximity when given current park messaging. Additionally, the resource protection- and the visitor experience-framed messages led to more conservative wildlife approach compared to current park messaging. These results have practical applications for influencing visitors’ behaviors and reducing human-wildlife conflict through education and interpretation.
Objective stepwise Bayes weights in survey sampling

Although weights are widely used in survey sampling their ultimate justification from the design perspective is often problematical. Here we will argue for a stepwise Bayes justification for weights that does not depend explicitly on the sampling design. This approach will make use of the standard kind of information present in auxiliary variables however it will not assume a model relating the auxiliary variables to the characteristic of interest. The resulting weight for a unit in the sample can be given the usual interpretation as the number of units in the population which it represents.
Syndemic of factors that shape the early lives of women who enter into sex work: a qualitative methods study from Nairobi, Kenya

Objective To explore the structural and social co-factors that shape the early lives of women who enter sex work in Nairobi, Kenya. Design Thematic analysis of qualitative data collected as part of the Maisha Fiti study among female sex workers (FSWs) in Nairobi. Participants and measures FSWs aged 18–45 years were randomly selected from seven Sex Workers Outreach Programme clinics in Nairobi and participated in baseline behavioural–biological surveys. Participants in this qualitative study were randomly selected from the Maisha Fiti study cohort and were interviewed between October 2019 and July 2020. Women described their lives from childhood, covering topics including sex work, violence and financial management. Results 48 out of 1003 Maisha Fiti participants participated in the in-depth qualitative interviews. FSWs described how physical and sexual violence, poverty and incomplete education in their childhood and adolescence intertwined with early pregnancy, marriage, intimate partner violence and relationship breakdown in their adolescence and early adulthood. The data analysis found clear syndemic relationships between these risk factors, particularly childhood violence, poverty and incomplete education and highlighted pathways leading to financial desperation and caring for dependents, and subsequent entry into sex work. Women perceived sex work as risky and most would prefer alternative work if possible, but it provided them with some financial independence and agency. Conclusions This is the first study in Kenya to qualitatively explore the early lives of sex workers from a syndemic perspective. This method identified the pivotal points of (1) leaving school early due to poverty or pregnancy, (2) breakdown of early intimate relationships and (3) women caring for dependents on their own. Complex, multi-component structural interventions before these points could help increase school retention, reduce teenage pregnancy, tackle violence, support young mothers and reduce entry into sex work and the risk that it entails by expanding livelihood options.
Further results on the independent Roman domination number of graphs

Abstract Let f : V (G) → {0, 1, 2} be a function on a graph G with vertex set V (G). Let Vi = {v ∈ V (G) : f (v) = i} for every i ∈ {0, 1, 2}. The function f is said to be an independent Roman dominating function on G if V 1 ∪ V 2 is an independent set and for every υ 2 V 0. The minimum weight among all independent Roman dominating functions f on G is the independent Roman domination number of G, and is denoted by iR (G). In this paper we continue with the study of this parameter. In particular, we provide new bounds on iR (G) in terms of other domination invariants. Some of our results are tight bounds that improve some well-known results. Finally, we compute the independent Roman domination number of some product graphs, and we provide an alternative proof to show that the problem of computing iR (G) is NP-hard.
The Rheology Handbook: For users of rotational and oscillatory rheometers

Official Full-Text Publication: Rheological characterization of gel-in-oil-in-gel type low amplitude oscillatory shear rheology and creep recovery measurements. with the effects of rheology, the science of deformation and flow behavior. Rheology Handbook: For Users of Rotational and Oscillatory Rheometers PDF. Rotational (oscillatory) rheometers (referred to in road engineering as Dynamic Rheometers – DSR) are complex devices designed to characterize rheological.
Body size affects specialization and modularity in the global resin foraging meta-network of stingless bees

Bees are in global decline and specialized species might be the most vulnerable to extinctions. Bee conservation can be studied using interaction networks, whose relative importance of nodes might correlate with morphological traits. Specifically, body size could affect flying range and thus influence the set of plant-bee interactions. Although several studies have reported botanical sources of resins in stingless bees, resin foraging networks were rarely assembled. Here we aim to describe the global resin-foraging meta-network of stingless bees, identify the most specialized species, and test how body size influences modularity and specialization. We found a modular and nested structure, in which some modules exhibit significant differences in body size and specialization. Melipona beecheii is the most specialized stingless bee in collecting resins. Body size is positively correlated with specialization, in which larger bees are more specialized to collect resins from a subset of plants, possibly because larger bees with broader flying ranges avoid competition by collecting less disputed resources. Our results demonstrate how resin collection can be analyzed in a meta-network framework to test ecological hypotheses and identify specialized species as candidate priorities for the conservation of stingless bees.
Fault Detection of Multi-mode Process Using Segmented PCA Based on Differential Transform

Fault detection for multi-mode process is a complicated problem,as the fault detection for both steady mode and transition mode should be taken into consideration. Different modes are needed for different steady modes because different relations of variables are contained in each mode model. Transition mode is a dynamic process occurring when production changes operating mode. The dynamic characteristic refiects not only the changing variables but also the changing relation of variables. The relative change information can be obtained by differential transform of transition data. Principle components can be extracted by analyzing correlation of differential variables using principal component analysis (PCA). At last,segmented modeling with PCA method is used to monitor multi-mode process of continuous annealing line. The algorithm reflects transition process well and is proved to be efficient.
Asymptotic properties of the complex valued non-linear regression model

The non-linear regression model, when the parameters are complex valued is considered here. Jennrich(1969) considered the non-linear regression model when the parameters are real valued. He first rigorously proved the existence of the least square estimator and showed its consistency properties and asymptotic normality. In this paper we generalise the idea for the com-plex parameters case. Large sample properties of the proposed estimator has been studied.
How individual P. aeruginosa cells with diverse stator distributions collectively form a heterogeneous macroscopic swarming population

Swarming is a macroscopic phenomenon in which surface bacteria organize into a motile population. The flagellar motor that drives swarming in Pseudomonas aeruginosa is powered by stators MotAB and MotCD. Deletion of the MotCD stator eliminates swarming, whereas deletion of the MotAB stator enhances swarming. Interestingly, we measured a strongly asymmetric stator availability in the WT strain, with MotAB stators produced ∼40-fold more than MotCD stators. However, recruitment of MotCD stators in free swimming cells requires higher liquid viscosities, while MotAB stators are readily recruited at low viscosities. Importantly, we find that cells with MotCD stators are ∼10x more likely to have an active motor compared to cells without, so wild-type, WT, populations are intrinsically heterogeneous and not reducible to MotAB-dominant or MotCD-dominant behavior. The spectrum of motility intermittency can either cooperatively shut down or promote flagellum motility in WT populations. In P. aeruginosa, transition from a static solid-like biofilm to a dynamic liquid-like swarm is not achieved at a single critical value of flagellum torque or stator fraction but is collectively controlled by diverse combinations of flagellum activities and motor intermittencies via dynamic stator recruitment. Experimental and computational results indicate that the initiation or arrest of flagellum-driven swarming motility does not occur from individual fitness or motility performance but rather related to concepts from the ‘jamming transition’ in active granular matter. Importance After extensive study, it is now known that there exist multifactorial influences on swarming motility in P. aeruginosa, but it is not clear precisely why stator selection in the flagellum motor is so important or how this process is collectively initiated or arrested. Here, we show that for P. aeruginosa PA14, MotAB stators are produced ∼40-fold more than MotCD stators, but recruitment of MotCD over MotAB stators requires higher liquid viscosities. Moreover, we find the unanticipated result that the two motor configurations have significantly different motor intermittencies, the fraction of flagellum-active cells in a population on average, with MotCD active ∼10x more often than MotAB. What emerges from this complex landscape of stator recruitment and resultant motor output is an intrinsically heterogeneous population of motile cells. We show how consequences of stator recruitment led to swarming motility, and how they potentially relate to surface sensing circuitry.