Miracle-dz/UniFAR-FTUs huggingface dataset:
Day-ofthe-Week Effect on Stock Market Return and Volatility : Evidence from Indian Stock Market

The present paper tries to investigate the presence of the significant Day-of-the-Week effect in Indian Stock Market for the period covering from January 2000 to December 2015 using daily closing prices. The Dayof-the-Week effect assumes significance particularly because of the integration of the Indian financial market to the global market since the mid-1990s. The BSE Sensex and the NSE Nifty are mostly the representatives for looking at the behavior of the Indian financial market in a macroeconomic setup and hence they are included for analysis. In order to fulfill the objectives the paper has incorporated the GARCH model specifications where a conditional variance term is included to eliminate the problem of heteroscadasticity of the residual term. The empirical results suggest that there exists no Day-of-the-Week effect on the stock return of Sensex and Nifty indexes. However, the volatility on Tuesday is statistically significant to explain the variation in the expected stock return.
How does promoting the minority fraction affect generalization? A theoretical study of one-hidden-layer neural network on group imbalance

Group imbalance has been a known problem in empirical risk minimization (ERM), where the achieved high average accuracy is accompanied by low accuracy in a minority group. Despite algorithmic efforts to improve the minority group accuracy, a theoretical generalization analysis of ERM on individual groups remains elusive. By formulating the group imbalance problem with the Gaussian Mixture Model, this paper quantifies the impact of individual groups on the sample complexity, the convergence rate, and the average and group-level testing performance. Although our theoretical framework is centered on binary classification using a one-hidden-layer neural network, to the best of our knowledge, we provide the first theoretical analysis of the group-level generalization of ERM in addition to the commonly studied average generalization performance. Sample insights of our theoretical results include that when all group-level co-variance is in the medium regime and all mean are close to zero, the learning performance is most desirable in the sense of a small sample complexity, a fast training rate, and a high average and group-level testing accuracy. Moreover, we show that increasing the fraction of the minority group in the training data does not necessarily improve the generalization performance of the minority group. Our theoretical results are validated on both synthetic and empirical datasets, such as CelebA and CIFAR-10 in image classification.
Examining the Interplay between the Cognitive and Emotional Aspects of Gender Differences in Spatial Processing

Women reliably perform worse than men on measures of spatial ability, particularly those involving mental rotation. At the same time, females also report higher levels of spatial anxiety than males. What remains unclear, however, is whether and in what ways gender differences in these cognitive and affective aspects of spatial processing may be interrelated. Here, we tested for robust gender differences across six different datasets in spatial ability and spatial anxiety (N = 1257, 830 females). Further, we tested for bidirectional mediation effects. We identified indirect relations between gender and spatial skills through spatial anxiety, as well as between gender and spatial anxiety through spatial skills. In the gender → spatial anxiety → spatial ability direction, spatial anxiety explained an average of 22.4% of gender differences in spatial ability. In the gender → spatial ability → spatial anxiety direction, spatial ability explained an average of 25.9% of gender differences in spatial anxiety. Broadly, these results support a strong relation between cognitive and affective factors when explaining gender differences in the spatial domain. However, the nature of this relation may be more complex than has been assumed in previous literature. On a practical level, the results of this study caution the development of interventions to address gender differences in spatial processing which focus primarily on either spatial anxiety or spatial ability until such further research can be conducted. Our results also speak to the need for future longitudinal work to determine the precise mechanisms linking cognitive and affective factors in spatial processing.
Effect of Intermittent Thoracic Paravertebral Block on Postoperative Nausea and Vomiting Following Thoracoscopic Radical Resection of the Lung Cancer: A Prospective Randomized Trial

Purpose To explore the benefits of ultrasound-guided intermittent thoracic paravertebral block (TPVB) combined with intravenous analgesia (PCIA) in alleviating postoperative nausea and vomiting (PONV) during video-assisted thoracic surgery (VATS). Patients and Methods 120 patients with lung carcinoma undergoing VATS were included and divided into three groups: group S (single TPVB+PCIA), group I (intermittent TPVB+PCIA), and group P (PCIA). The patients’ NRS scores, postoperative hydromorphone hydrochloride consumption, and intramuscular injection of bucinnazine hydrochloride were recorded. The incidence of PONV and complications were documented. Results Compared with the group P, both group I and group S had significantly lower static NRS scores from 1–48 hours after the operation (P <0.05), and the dynamic NRS score of group I at the 1–48 hours after the operation were significantly decreased (P <0.05). Compared with the group P, the proportion of patients with PONV in group I was significantly lower (P <0.05), while there was no significant difference in group S. Moreover, the hospitalization period of patients in group I was significantly reduced compared with the other two groups (P <0.01), and the patient satisfaction was significantly increased compared with the group P (P <0.05). Conclusion Intermittent TPVB combined with PCIA can reduce the postoperative pain and the occurrence of PONV.
The Rotation Model in Blended Learning

: The COVID-19 pandemic has led to an increase in the use of blended learning globally, but there is a lack of understanding of the various types of blended learning models. This literature review study focuses on the blended learning models and the rotation blended learning model. The study gathered data through document analysis and used content analysis to analyze it. The findings suggest that blended learning can be delivered through different models, including the models based on class instruction. Therefore, when developing a blended learning activity, course, or program, it is important to consider all available models. This study emphasizes the importance of the rotation model and its sub-models in blended learning and offers suggestions for future research and practitioners. The results of this study can be used to create effective blended learning environments.
Long-Term Survivability of Tardigrade Paramacrobiotus experimentalis (Eutardigrada) at Increased Magnesium Perchlorate Levels: Implications for Astrobiological Research

Perchlorate salts, including magnesium perchlorate, are highly toxic compounds that occur on Mars at levels far surpassing those on Earth and pose a significant challenge to the survival of life on this planet. Tardigrades are commonly known for their extraordinary resistance to extreme environmental conditions and are considered model organisms for space and astrobiological research. However, their long-term tolerance to perchlorate salts has not been the subject of any previous studies. Therefore, the present study aimed to assess whether the tardigrade species Paramacrobiotus experimentalis can survive and grow in an environment contaminated with high levels of magnesium perchlorates (0.25–1.0%, 1.5–6.0 mM ClO4− ions). The survival rate of tardigrades decreased with an increase in the concentration of the perchlorate solutions and varied from 83.3% (0.10% concentration) to 20.8% (0.25% concentration) over the course of 56 days of exposure. Tardigrades exposed to 0.15–0.25% magnesium perchlorate revealed significantly decreased body length. Our study indicates that tardigrades can survive and grow in relatively high concentrations of magnesium perchlorates, largely exceeding perchlorate levels observed naturally on Earth, indicating their potential use in Martian experiments.
Spatial and Temporal Changes in Taenia solium Cysticercosis Seroprevalence among Pigs in the Southern Highlands of Tanzania

Taenia solium remains among the major causes of epilepsy in sub-Saharan Africa. Understanding the geospatial distribution of the parasite is important to inform control strategies. This study assessed spatiotemporal changes in the T. solium infection among pigs from a rural area in southwestern Tanzania. Secondary data from a previous repeated cross-sectional study in the Mbeya and Mbozi districts were used, involving sixteen villages, eight from each of the two districts. Serum samples were collected from 482, 460, and 421 pigs in 221, 196, and 139 households, respectively, at seven-month intervals. Ag-ELISA was used to analyse the samples for circulating antigens. Geographic coordinates of the pig corrals adjacent to the households were also recorded using a hand-held GPS device. SatScan v9.7 software was used to perform purely spatial scan analysis, based on the Bernoulli distribution model. Spatial clustering was assumed based on the relative risk of T. solium seropositivity. Statistical significance (set at 0.05) of the cluster was determined by comparing the log-likelihood ratio with the null distribution derived by Monte Carlo simulations. The window with the highest log-likelihood ratio was regarded as a primary cluster. Results showed significant clustering of T. solium cases with the presence of a single primary cluster during each phase. The relative risk of T. solium infection among pigs within the primary cluster areas ranged from 3.0 to 6.7. The radii of the clusters expanded from 1.83 to 27.7 km before shrinking to 1.5 km, and cluster location drifted from north to central and then to the southern part of the study area. These findings suggest that with restricted resources, control measures in the area could be focused on pockets of high transmission. However, changes in the size and location of clusters suggest that to be effective, interventions should be instituted soon after clusters are identified.
Revolutionizing Healthcare: The Crucial Impact of Relational Marketing Strategies

: Purpose: This article focuses on non-medical benefits for the patient, which may influence their choices. The authors intend to identify the directions and actions of the healthcare entity, ensuring improvement of the quality of services provided and, as a result, increased patient satisfaction and loyalty. The analyses aim to understand how patients make decisions regarding the choice of a medical facility and what their priorities and expectations are concerning the organization of work, communication and image of the medical centre. Design/Methodology/Approach: Authors apply methods of multivariate statistical analysis - the Mann-Whitney test was used to verify the significance of differences in respondents' evaluations. The following research hypotheses are formulated: (H1) recommendations positively impact the satisfaction related mainly to the organisation of the clinic’s activity and providing necessary information (availability of services, waiting times, registration, website); (H2) satisfaction with the treatment process is primarily related to positive experiences. Calculations were made in Statistica. Findings: The main conclusion of the research is the assumption that an effective marketing approach in health services should include a systematic study of patients' needs and expectations, the identification of latent preferences and the offering of new services in line with the expectations of potential as well as existing health consumers. Originality/Value: The results suggest that the elements related to the treatment process are more important than on the opinions of other people in this area.
Evaluating Temperature Effects on Bluetongue Virus Serotype 10 and 17 Coinfection in Culicoides sonorensis

Bluetongue virus (BTV) is a segmented, double-stranded RNA virus transmitted by Culicoides midges that infects ruminants. As global temperatures increase and geographical ranges of midges expand, there is increased potential for BTV outbreaks from incursions of novel serotypes into endemic regions. However, an understanding of the effect of temperature on reassortment is lacking. The objectives of this study were to compare how temperature affected Culicoides survival, virogenesis, and reassortment in Culicoides sonorensis coinfected with two BTV serotypes. Midges were fed blood meals containing BTV-10, BTV-17, or BTV serotype 10 and 17 and maintained at 20 °C, 25 °C, or 30 °C. Midge survival was assessed, and pools of midges were collected every other day to evaluate virogenesis of BTV via qRT-PCR. Additional pools of coinfected midges were collected for BTV plaque isolation. The genotypes of plaques were determined using next-generation sequencing. Warmer temperatures impacted traits related to vector competence in offsetting ways: BTV replicated faster in midges at warmer temperatures, but midges did not survive as long. Overall, plaques with BTV-17 genotype dominated, but BTV-10 was detected in some plaques, suggesting parental strain fitness may play a role in reassortment outcomes. Temperature adds an important dimension to host–pathogen interactions with implications for transmission and evolution.
Climatology of snow phenology over the Tibetan plateau for the period 2001–2014 using multisource data

Seasonal snow cover over the Tibetan plateau (TP) has unique features in terms of global snow cover distribution because of the high mountains and vital surface water storage functions in non‐humid regions of Southwest China and surrounding Asian countries. Limited by the complex topography and relatively low spatial resolution of satellite observations, the characteristics of snow phenology and the factors for snow phenology changes remain still unclear. Using multisource data for the period 2001–2014, this study quantifies the climatology of snow phenology and explores its attribution factors. The results show that the snow onset date (Do) and snow end date (De) were 4.9 (±7.7) and 108.1 (±5.9) in day of year (DOY), respectively, and the snow duration days (Dd) were 103.2 (±13.4) over the TP during the study period. The characteristics of satellite observed Dd was similar to subzero temperature days derived from ground observations. The 14‐year anomalies in snow phenology features regional disparity over the TP, with increased Dd in the central TP and shortened Dd in the Tarim River, endorheic drainage basins, and upper reaches of the Brahmaputra River. In contrast to previous findings in northern mid‐latitudes, changes in Dd over the TP during 2001–2014 were mainly induced by anomalies in Do, which can be further attributed to the declines in accumulation season temperature over the TP.
Diversity-Infused Network for Unsupervised Few-Shot Remote Sensing Scene Classification

Few-shot remote sensing scene classification (RSSC) confronts challenges due to its dependence on extensive labeled datasets. Addressing this, we propose the diversity-infused network (DIN), an unsupervised paradigm for few-shot RSSC, utilizing unlabeled data in training and adapting to novel classes with limited labeled samples. Within an augmentation-based framework, DIN includes a random augmentation sampling (RAS) strategy for task diversity in the meta-training stage, and a channel-driven metric learning (CDML) module to decode complex channel interactions, enhancing information diversity. Additionally, DIN presents a multimutual information (Multi-MI) objective function to balance the architecture and reduce the unreliability and potential biases from pseudotraining. Experimental results demonstrate that DIN surpasses other unsupervised approaches by over 11% in one-shot and nearly 9% in five-shot settings on WHU-RS19, and closely approaches supervised methods, with less than 1% difference in both settings.
Planned Socio-Spatial Fragmentation: The Normalisation of Gated Communities in Two Mexican Metropolises

Mexican metropolises, like many others in Latin America, are facing complex challenges connected to rapid urbanisation and population growth. Local governments struggle to provide the necessary infrastructure, housing, security, and basic services in a highly divided—socially and spatially—urban realm. Socio-spatial fragmentation in cities like Guadalajara and Puebla has existed since their foundations in the 16th century, as planning guidelines in the Laws of the Indies established differentiated rules for Spaniards and indigenous people. However, in recent decades, neoliberal planning and housing policy reforms, the consolidation of the real estate market, growing crime and violence, and socioeconomic disparities have contributed to more tangible forms of planned socio-spatial fragmentation, such as gated communities. This work discusses how policies and social practices have led to the normalisation of these fortified enclaves in the metropolises of Guadalajara and Puebla, whose capital cities are preparing to celebrate their 500th anniversaries in a context of conflict, loss of shared space, insecurity, and social inequalities. The work is based on a comprehensive review of national and local planning and housing policies, a historical and cartographic analysis of neighbourhood development, and qualitative research in Puebla over a decade, along with similar work in Guadalajara in the last couple of years. The relevance of this work lies in identifying the role of planning in the production of fragmented urban structures and visualising the possibilities for more inclusive solutions.
Knowledge, attitude of medical students regarding biomedical waste management

Objective: The present study was undertaken to assess the knowledge, attitude and practices of nurses regarding biomedical waste management. Methods: A total of 60 final year Medical students were randomly selected by simple random sampling using random numbers generated by computer. A survey was conducted with the help of questionnaire to assess the knowledge and attitude of medical students regarding biomedical waste management. Results: The medical students at Andhra Medical College have very good knowledge about the variables associated with waste management. Students have high positive attitude regarding all variables of biomedical waste management. Conclusion: From this study, we are able to identify the knowledge and attitude of medical students towards biomedical waste management. We recommend all institutes to conduct similar studies and educate the staff and students for pollution free world for betterment of all in general.
The United Nations Convention to Combat Desertification

The international community has long recognized that desertification is a major economic, social and environmental problem of concern to many countries in all regions of the world. In 1977, the United Nations Conference on Desertification (UNCOD) adopted a Plan of Action to Combat Desertification (PACD). Unfortunately, despite this and other efforts, the United Nations Environment Programme concluded in 1991 that the problem of land degradation in arid, semi-arid and dry sub-humid areas has intensified, although there were “local examples of success”.
Phylogenetic relationships of the Mangrove Hummingbird, “Amazilia” boucardi (Apodiformes: Trochilidae) of Costa Rica

Introduction: A recent revision of the generic classification of the Trochilidae based on DNA sequences revealed many inconsistencies with the current generic classification, largely based on plumage characters subject to homoplasy, especially in the Trochilini, the largest tribe. A thorough generic reorganization brought the classification into accord with the phylogeny, but due to lack of genetic data, two species remained unclassified. One of these was the Mangrove Hummingbird, “Amazilia” boucardi, endemic to Costa Rica and included in the IUCN red list of threatened species. Objective: To obtain molecular evidence to clarify the generic relationships of “A. ” boucardi. Methods: We isolated DNA from tissues of this species and amplified 4 nuclear and 4 mitochondrial fragments and compared these with homologous fragments from 56 species in the Trochilini, constructing phylogenetic trees with maximum likelihood and Bayesian methods. Results: Our phylogenetic analyses confirmed the placement of boucardi in the Trochilini and definitely excluded it from Amazilia but placed it with high confidence in the genus Chrysuronia Bonaparte, 1850, within which its closest relative is C. coeruleogularis, which also inhabits mangroves. Conclusions: Our genetic data based on nuclear and mitochondrial regions clearly indicate the relationship of A. boucardi and L. coeruleogularis. Moreover, it is also support by their habitat distribution in the mangroves of the Pacific coast of Costa Rica and Western Panama. Therefore, we suggested to exclude A. boucardi as "incertae sedis".
Analysis of the uncertainty of fuel model parameters in wildland fire modelling of a boreal forest in north-east China

Fire propagation is inevitably affected by fuel-model parameters during wildfire simulations and the uncertainty of the fuel-model parameters makes forecasting accurate fire behaviour very difficult. In this study, three different methods (Morris screening, first-order analysis and the Monte Carlo method) were used to analyse the uncertainty of fuel-model parameters with FARSITE model. The results of the uncertainty analysis showed that only a few fuel-model parameters markedly influenced the uncertainty of the model outputs, and many of the fuel-model parameters had little or no effect. The fire-spread rate is the driving force behind the uncertainty of other fire behaviours. Thus, the highly uncertain fuel-model parameters associated with spread rate should be used cautiously in wildfire simulations. Monte Carlo results indicated that the relationship between model input and output was non-linear and neglecting fuel-model parameter uncertainty of the model would magnify fire behaviours. Additionally, fuel-model parameters have high input uncertainty. Therefore, fuel-model parameters must be calibrated against actual fires. The highly uncertain fuel-model parameters with high spatial-temporal variability consisted of fuel-bed depth, live-shrub loading and 1-h time-lag loading are preferentially chosen as parameters to calibrate several wildfires.