Miracle-dz/UniFAR-FTUs huggingface dataset:
, Halley ( 2019 ) Internet Gaming Disorder : compensating as a Draenei in World of Warcraft

The diagnosis of Gaming Disorder (GD) has been recently proposed in the beta draft of the eleventh revision of the International Classification of Diseases (ICD-11) by the World Health Organization (WHO). This follows the inclusion of Internet Gaming Disorder (IGD), as a condition requiring additional research in the Diagnostic Statistical Manual for Mental Disorders (DSM-5), issued by the American Psychiatric Association (APA). Further research has been recommended to enhance understanding of excessive gaming, especially in the context of user-avatar (in-game figure representing the gamer) relationships. The association between selecting the Draenei race, compensation of real-life deficits through gaming and the gamer’s gender were investigated as IGD risk factors among players of the online game, World of Warcraft (WoW). A normative online sample of WoW gamers (N = 404 Mage = 25.56; 13-75; Males = 299; 74%) completed the Internet Gaming Disorder Scale–Short-Form (IGDS9-SF) and the compensation subscale of the User-Avatar Questionnaire. Regression, mediation and moderated mediation analyses were conducted. Overall, players with higher levels of compensation exhibited greater levels of IGD symptoms. Interestingly, choosing the Draenei race was associated with increased compensatory behavior, which in turn linked to higher IGD risk. These associations were mildly stronger among females. Findings suggest that virtual demographics, such as the Draenei race, and their interplay with compensatory behaviors should be carefully considered when creating prevention and intervention policies targeting excessive gaming, especially when it involves the use of avatars.
Gånggriftstidens boplatsnivåer i Södertörn

Abstract In 15 neolithic shore sites in the district of Sodertorn, dating from the period of passage graves, the downward extension of the habitation was determined analyzing the soil for phosphate. The levels thus found showed an even distribution between 29.5 and 24 m. above sea level, indicating an even transition between the different stages belonging to the Sater group. Elevations were reduced to the isobase latitude of Vasterhaninge. Probable errors and approximations resorted to are discussed.
Detection of pyrethroids resistance alleles in goat biting louse Bovicola caprae (Phthiraptera: Trichodectidae) in west and northwest of Iran

Pyrethroid insecticides target voltage-gated sodium channels (VGSCs) that are essential for electrical signaling in the nervous system of insects. Three-point mutations at the corresponding amino acid sequence positions M815I, T917I, and L920F located in domain II conferring the knockdown resistance (kdr) are the most important mutations in pyrethroid-resistant lice worldwide. In addition, six new mutations have been reported in the extracellular loops IIS1-2 (H813P) and IIS5 (I927F, L928A, R929V, L930M, L932M) in the α- subunit of the sodium channel in lice. The aim of this study was to detect alleles resistant to pyrethroids in the domain II (S5-S6) of the VGSC gene in goat biting louse. Goat biting lice were collected from five provinces in the west and northwest of Iran. Genomic DNA was extracted from goat biting lice and Bovicola (Damalinia) caprae species was confirmed by amplifying the cytochrome oxidase subunit I (COXI) gene. A fragment in the domain II (S5-S6) of the VGSC gene was amplified using the specific primers and the resultant polymerase chain reaction products were sequenced. Substitutions T917I, L920F, I927F, L928A, R929V and L930M were identified in the examined sequences. The results showed that all the examined lice had at least one mutation in their VGSC gene associated with pyrethroid resistance or new mutations. The presence of these mutated alleles in the VGSC gene may be due to the long-term and multiple use of pyrethroids against arthropods. Thus, the molecular detection of resistance to pyrethroid insecticides in goat chewing lice can help plot a kdr frequency map to enact effective policies to control caprine pediculosis.
Women’s and health professionals’ perceptions, beliefs and barriers to cervical cancer screening uptake in Southern Ethiopia: a qualitative study

Abstract Cervical cancer remains a public health problem worldwide. Screening for cervical cancer is poorly implemented in resource-limited settings. In Ethiopia, evidence from the community and health professionals regarding implementation of the screening programme is lacking. The objective of this study was to explore women’s and health professionals’ perceptions, beliefs, and barriers in relation to cervical screening in Southern Ethiopia. Five focus group discussions among women and six key informant interviews with health professionals were conducted from June to July 2022 to gather the required data from a total of 42 participants. The participants were purposively selected from a diverse group to ensure varied viewpoints. Data were collected through group discussions and face-to-face interviews using a semi-structured interview guide. The interview sessions were tape-recorded. The data were analysed using a thematic approach. Women demonstrated a low level of awareness and perceived risk. Also, the perceived benefit of screening for cervical cancer during healthy periods was low. Individual and system-level barriers to screening include low awareness, stigma, poor perceptions towards health screening and causes of cervical cancer, low risk perception and competing domestic priorities, shortage of trained human and other resources, human resource turnover, low implementation and lack of close follow-up of screening programmes. In summary, lack of awareness, misconceptions, and poor perceptions were common. Screening implementation and uptake were low due to individual, psychosocial, and system-related barriers. Therefore, behavioural change communication and system-strengthening efforts need to be in place to effectively tackle the observed gaps.
Constructing accurate maps of atmospheric water vapor by combining interferometric synthetic aperture radar and GNSS observations

Over the past 20years, repeat‐pass spaceborne interferometric synthetic aperture radar (InSAR) has been widely used as a geodetic technique to generate maps of the Earth's topography and to measure the Earth's surface deformation. In this paper, we present a new approach to exploit microwave data from InSAR, particularly Persistent Scatterer InSAR (PSI), and Global Navigation Satellite Systems (GNSS) to derive maps of the absolute water vapor content in the Earth's atmosphere. Atmospheric water vapor results in a phase shift in the InSAR interferogram, which if successfully separated from other phase components provides valuable information about its distribution. PSI produces precipitable water vapor (PWV) difference maps of a high spatial density, which can be inverted using the least squares method to retrieve PWV maps at each SAR acquisition time. These maps do not contain the absolute (total) PWV along the signal path but only a part of it. The components eliminated by forming interferograms or phase filtering during PSI data processing are reconstructed using GNSS phase observations. The approach is applied to build maps of absolute PWV by combining data from InSAR and GNSS over the region of Upper Rhine Graben in Germany and France. For validation, we compared the derived PWV maps with PWV maps measured by the optical sensor MEdium‐Resolution Imaging Spectrometer. The results show strong spatial correlation with values of uncertainty of less than 1.5mm. Continuous grids of PWV are then produced by applying the kriging geostatistical interpolation technique that exploits the spatial correlations between the PWV observations.
Development of an Okinawa panel for biogeographic inference of Okinawans

Abstract Background The Precision ID Ancestry Panel with 165 SNP markers was unable to differentiate between mainland Japanese and Okinawa Japanese or to distinguish either of them from other East Asian populations. Aim An Okinawa panel was developed with the aim of further separating Okinawa Japanese individuals from mainland Japanese and other Asian groups. Seventy-five SNPs were selected using the most informative markers from the literature. Further, 22 SNPs were selected to separate Okinawa Japanese at minimum SNPs. Subjects and methods Samples were collected from 48 unrelated individuals from mainland Japan and 46 unrelated residents of the Okinawa prefecture. Data were evaluated by STRUCTURE, principal component, and GenoGeographer analyses. Results The 22 SNP set had similar levels of differentiation in STRUCTURE and PCA analyses as the 75 SNP set. GenoGeographer analysis showed that, out of the 46 Okinawa Japanese individuals, the 75 SNP and 22 SNP sets correctly assigned the Okinawan population as the most likely population of origin for 32 and 31 individuals, respectively. Conclusion Neither SNP set could completely differentiate between Okinawa Japanese and other Asian groups, however, these sets should be useful for crime investigation, when the sample, cost and time are limited.
Climate change effects on the distribution of yellow‐breasted capuchin monkey (Sapajus xanthosternos (Wied‐Neuwied, 1826))

The magnitude of recent climatic changes has no historical precedent and impacts biodiversity. Climatic changes may displace suitable habitats (areas with suitable climates), leading to global biodiversity decline. Primates are among the most affected groups. Most primates depend on forests and contribute to their maintenance. We evaluated the potential effects of climatic change on the distribution of Sapajus xanthosternos, a critically endangered primate whose geographical range encompasses three Brazilian biomes. We evaluated changes between baseline (1970–2000) and future (2081–2100) climates using multivariate analysis. Then, we compared current and future (2100) climatic suitability projections for the species. The climatic changes predicted throughout the S. xanthosternos range differed mostly longitudinally, with higher temperature increases in the west and higher precipitation reductions in the east. Climatic suitability for S. xanthosternos is predicted to decline in the future. Areas with highest current climatic suitability occur as a narrow strip in the eastern part of the geographic range throughout the latitudinal range. In the future, areas with highest values are projected to be located as an even narrower strip in the eastern part of the geographical range. A small portion of forest remnants larger than 150 ha located in the east has larger current and future suitability values. At this large scale, the spatial heterogeneity of the climate effects reinforce the importance of maintenance of current populations in different areas of the range. The possibility that phenotypic plasticity helps primates cope with reduced climatic suitability may be mediated by habitat availability, quality, and connectivity.
Salinity Management for Sustainable Irrigation: Integrating Science, Environment, and Economics

Is irrigation sustainable, and if so, how and under what conditions? That is the question that has impelled the writing of this report. This report examine the nature of salinity, its effects on crop production, its effects on irrigation water, the effects of watrlogging and drainage, efforts to control salinity, the use of early warning systems, and social and institutional issues posed by salinity to conclude that irrigated agriculture will not only survive but indeed thrive in the proper circumstances and with appropriate measures. However, this statement is conditional: in some specific locations, inherently inefficient, self-destructive, and environmentally damaging operations will be forced to terminate. On the whole, however, irrigated agriculture should be able to adapt to the long-term requirements of sustainability, and to continue to feed humanity in the even more than in the past.
An Examination of the Thermodynamic Impacts of Western North Pacific Tropical Cyclones on Their Tropical Tropospheric Environment

AbstractThe present study examines the tropospheric thermodynamic anomalies induced by western North Pacific tropical cyclone (TC) passage using storm-relative composites. Negative moist static energy (MSE) anomalies containing embedded westward-propagating anomalies generally occur only following larger TCs for two months following TC passage in a region extending from the domain center to ~3000 km to its west. Larger TCs force negative MSE anomalies likely because of feedbacks from stronger, broader TC-induced negative sea surface temperature (SST) anomalies and the excitation of TC-induced Rossby waves to the southeast of the TC. The negative MSE anomalies are composed of lower- and midtropospheric negative latent energy anomalies with smaller contributions from boundary layer and upper-tropospheric negative sensible heat anomalies. The lower- and midtropospheric negative MSE anomalies are forced by the TC, whereas the upper-tropospheric negative MSE anomalies are forced by the Madden–Julian oscillatio.
Inference and forecasting phase shift regime of COVID-19 sub-lineages with a Markov-switching model

ABSTRACT The occurrences and domination of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants are still crucial factors for determining the coronavirus disease 19 (COVID-19) policies. We collected weekly Phylogenetic Assignment of Named Global Outbreak sub-lineages, naming genetically distinct lineages of SARS-CoV-2, including variants of concern, in the United Kingdom, South Africa, South Korea, Denmark, Germany, the United States, and worldwide. This study included 12,296,756 samples of the max share of the sub-lineages from the 33rd week of 2020 to the 40th week of 2022. This study conducted a two-state Markov-switching model to estimate the probability of the phase shift state and predicted the probability of each regime with the Hamilton filter and Kim’s smoothing algorithm. We discovered different weekly patterns based on dominant SARS-CoV-2 variants in target area. Due to differences in containment policies and outbreak waves, we observed a time lag in dominant variants in these countries. Using the inferred probability of the phase shift regime for forecasting, it showed significant probabilities that the stable phase will still be stable in the next week. It also showed significant probabilities that the unstable phase will still be unstable in the next week. Our findings present the probability of observing the phase shift regime each week. Until a new SARS-CoV-2 variant occurs, the regime tended to stay with a low probability of phase shift regime. When a new SARS-CoV-2 variant would occur, the regime would immediately react and change the probability. We propose the Markov-switching model to determine COVID-19 policies and predict SARS-CoV-2 variants. IMPORTANCE Using regime-switching models, we attempted to determine whether there is a link between changes in severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) variants and infection waves, as well as forecasting new SARS-Cov-2 variants. We believe that our study makes a significant contribution to the field because it proposes a new approach for forecasting the ongoing pandemic, and the spread of other infectious diseases, using a statistical model which incorporates unpredictable factors such as human behavior, political factors, and cultural beliefs. Using regime-switching models, we attempted to determine whether there is a link between changes in severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) variants and infection waves, as well as forecasting new SARS-Cov-2 variants. We believe that our study makes a significant contribution to the field because it proposes a new approach for forecasting the ongoing pandemic, and the spread of other infectious diseases, using a statistical model which incorporates unpredictable factors such as human behavior, political factors, and cultural beliefs.
Differential skin immune responses in mice intradermally infected with Candida auris and Candida albicans

ABSTRACT Candida auris, an emerging multi-drug-resistant fungal pathogen, uniquely colonizes the human skin long term, leading to subsequent development of life-threatening invasive infections in humans. The factors regulating skin colonization of C. auris are not well understood. In this study, we established an intradermal mouse model of C. auris infection to define the innate and adaptive immune response to this emerging pathogen and compare it to Candida albicans. Our results indicate that compared to C. albicans-infected mice, C. auris-infected mouse skin tissue had significantly higher fungal load after 3 and 14 days post-infection. C. auris infection was associated with a significantly decreased accumulation of CD11b+ Ly6G+ neutrophils and increased numbers of CD11b+ Ly6 Chi inflammatory monocytes and CD11b+ CD207+ Langerhans cells at the site of infection. Furthermore, a significant decrease in the absolute numbers of type 3 innate lymphoid cells and Th17 cells was observed in C. auris-infected skin tissue. Taken together, our findings indicate that the skin immune responses are different between C. auris- and C. albicans-infected mice. The increased fungal load observed in C. auris-infected mouse skin tissue is associated with less potent innate and adaptive immune responses induced by this emerging pathogen relative to C. albicans. IMPORTANCE Candida auris is a globally emerging fungal pathogen that transmits among individuals in hospitals and nursing home residents. Unlike other Candida species, C. auris predominantly colonizes and persists in skin tissue, resulting in outbreaks of nosocomial infections. Understanding the factors that regulate C. auris skin colonization is critical to develop novel preventive and therapeutic approaches against this emerging pathogen. We established a model of intradermal C. auris inoculation in mice and found that mice infected with C. auris elicit less potent innate and adaptive immune responses in the infected skin compared to C. albicans. These findings help explain the clinical observation of persistent C. auris colonization in skin tissue. Candida auris is a globally emerging fungal pathogen that transmits among individuals in hospitals and nursing home residents. Unlike other Candida species, C. auris predominantly colonizes and persists in skin tissue, resulting in outbreaks of nosocomial infections. Understanding the factors that regulate C. auris skin colonization is critical to develop novel preventive and therapeutic approaches against this emerging pathogen. We established a model of intradermal C. auris inoculation in mice and found that mice infected with C. auris elicit less potent innate and adaptive immune responses in the infected skin compared to C. albicans. These findings help explain the clinical observation of persistent C. auris colonization in skin tissue.
A multimodality therapeutic application on Toxoplasma gondii encephalitis utilizing Spiramycin and ‘de novo’ Ferula asafetida in immunodeficient mice

This study investigated a ‘de Novo’ medicinal herb, Ferula asafetida (FA), against toxoplasma encephalitis either alone or combined with spiramycin (SP). Female Swiss‐Webster mice (n = 72) were divided into three batches. Batch‐I received no DMS to serve as an immunocompetent control, batch‐II was immune‐suppressed with the DMS (0.25 mg/g/day) for 14 days pre‐infection, whilst batch‐III was immune‐suppressed with the DMS on the same day of infection. All experimental mice were inoculated with Toxoplasma gondii ME49 cysts (n = 75). Each batch was split into four subgroups: Mono‐SP, mono‐FA, combined drug (SP + FA), or neither. Therapies were administered on day zero of infection in batches (I and II) and 35 days post‐infection in batch (III). Treatments lasted for 14 days, and mice were sacrificed 60 days post‐infection. Histopathological changes, cysts load, and CD4 and CD8 T‐cells were counted in brain tissues. The cyst‐load count in mice receiving SP + FA was significantly (p < .0001) the least compared to the mono treatments in all protocols. Interestingly, the combined therapy demolished the T‐cell subsets to zero in immunocompetent and immunocompromised infected mice. In conclusion, F. asafetida might be a powerfully natural, safe vehicle of SP in the digestive system and/or across the brain–blood barrier to control toxoplasmosis even through immunodeficient conditions.
Predicting synergistic anticancer drug combination based on low-rank global attention mechanism and bilinear predictor

Abstract Motivation Drug combination therapy has exhibited remarkable therapeutic efficacy and has gradually become a promising clinical treatment strategy of complex diseases such as cancers. As the related databases keep expanding, computational methods based on deep learning model have become powerful tools to predict synergistic drug combinations. However, predicting effective synergistic drug combinations is still a challenge due to the high complexity of drug combinations, the lack of biological interpretability, and the large discrepancy in the response of drug combinations in vivo and in vitro biological systems. Results Here, we propose DGSSynADR, a new deep learning method based on global structured features of drugs and targets for predicting synergistic anticancer drug combinations. DGSSynADR constructs a heterogeneous graph by integrating the drug–drug, drug–target, protein–protein interactions and multi-omics data, utilizes a low-rank global attention (LRGA) model to perform global weighted aggregation of graph nodes and learn the global structured features of drugs and targets, and then feeds the embedded features into a bilinear predictor to predict the synergy scores of drug combinations in different cancer cell lines. Specifically, LRGA network brings better model generalization ability, and effectively reduces the complexity of graph computation. The bilinear predictor facilitates the dimension transformation of the features and fuses the feature representation of the two drugs to improve the prediction performance. The loss function Smooth L1 effectively avoids gradient explosion, contributing to better model convergence. To validate the performance of DGSSynADR, we compare it with seven competitive methods. The comparison results demonstrate that DGSSynADR achieves better performance. Meanwhile, the prediction of DGSSynADR is validated by previous findings in case studies. Furthermore, detailed ablation studies indicate that the one-hot coding drug feature, LRGA model and bilinear predictor play a key role in improving the prediction performance. Availability and implementation DGSSynADR is implemented in Python using the Pytorch machine-learning library, and it is freely available at https://github.com/DHUDBlab/DGSSynADR.