Miracle-dz/UniFAR-FTUs huggingface dataset:
The Synthesis of Some Imine Derivatives via Condensation Reactions between Some Aromatic Phenylhydroxylamine Derivatives with Glyoxylic Acid and the Study of their biological activity

This study investigated the condensation reactions between N-(3,4-dimethoxybenzyl)hydroxylamine and N-(4-methylbenzyl)hydroxylamine with glyoxalic acid. The objective was to obtain imine derivatives as the desired target products. FT-IR, 1H-NMR, and 13C-NMR spectroscopic techniques were used to identify the structures of the produced compounds. Different conditions were considered for these reactions and only N-(3,4-dimethoxybenzyl)hydroxylamine could be converted to the desired nitrone. Finally, the antimicrobial efficacy was assessed in terms of its action against the bacteria Escherichia coli (E.coli) as Gram-negative bacteria, Staphylococcus aureus (S.aureus) as Gram-positive bacteria and fungus (Candida albicans). The activity data proved that this nitrone showed significant antimicrobial activity compared to standard drugs.
Evaluation of drought tolerance indices and their relationship with grain yield of lentil lines in drought-stressed and irrigated environments.

In order to study genetic diversity of lentil lines, screening drought tolerance three indices and lines, eighteen genotypes were evaluated in a randomized complete block design with 3 replications under both stress and non-stress conditions in the Research Farm of Zabol University in 2009. Based on yields of non-stress (Yp) and stress (Ys) conditions, several quantitative drought tolerance indices, such as mean productivity, geometric mean productivity, harmonic mean, tolerance index, yield index, yield stability index, stress susceptibility index and stress tolerance index were used to evaluate the drought responses of these genotypes. GMP, HM and STI were considered as the best indices for selection of lentil lines under drought stress. Based on these indices values, TN1084 could be considered as superlative line, followed by KC210034. TN2464 was the weakest line in respect to drought tolerance. Principal component analysis revealed that the first PCA explained 66.82% of the total variation and named as the yield potential and drought tolerance dimension. The second PCA explained 32.48% of the total variability and named as a stress-tolerant dimension. Distribution of the genotypes in the PCA biplot space indicated the presence of genetic diversity among the lines for drought stress. TN1084 genotype with high PC1 was more suitable for stress and non-stress conditions. KC210034 genotype with high PC2 was more suitable for non-stress than for stress environment. Biplot based on grain yield of lines under stress and non-stress conditions revealed the results of principal component analysis and showed the possibility of diversifying the legumepredominant farming systems in Sistan. Based on cluster analysis TN1084 and KC210034 group had high yield under stress and non-stress conditions and ranked as the best group. TN2464 group had low yield positional under stress and non-stress conditions and ranked as the worst group. All in all, TN1084 and KC210034, respectively, were best line for stress and non-stress conditions and can be recommended for cultivation and parental material for breeding efforts to develop higher yielding varieties.
A SHARI’AH ANALYSIS OF THE NATIONAL HIGHER EDUCATION LOAN SCHEME IN THE MALDIVES

This study conducts a thorough Shari’ah analysis of the National Higher Education Loan Scheme (NSLS) in the Maldives, aiming to assess its adherence to Islamic financial principles. Employing a qualitative desk review research method, it systematically collects and analyzes existing literature, documents, reports, and academic publications related to the NSLS, offering insights into its financing structure, service charges, and contractual obligations. The research reveals critical findings, including concerns about the 1% service charge, the absence of formal Shari’ah oversight, and varying scholarly opinions regarding its Islamic compliance. Importantly, it provides recommendations to enhance the NSLS's alignment with Shari’ah principles, potentially serving as a blueprint for ethically sound higher education funding. This study's originality lies in its pioneering exploration of a relatively uncharted area and its potential to inspire future research and innovative Shari’ah-compliant financing models in higher education, not only in the Maldives but also in broader Islamic contexts.
Plumbagin's molecular docking studies as a possible target for the SARS-CoV-2 spike receptor protein

Around the end of 2019, reports of unusual cases of pneumonia with specific symptoms started to arrive in Wuhan, China. Within a few weeks, the atypical pneumonia spread throughout China, and a few months after that, it became a global pandemic. The etiological agent of that pandemic, which is officially known as COVID-19, is Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). In an attempt to find an efficient therapy to either fight the spread of COVID-19 or to cure infected people from its tissue damage, researchers around the world have been studying several plants, herbs, and natural products. Abundant studies have revealed that organic compounds can be very operative in averting virus-mediated infection. The purpose of this study was to accomplish molecular docking studies among plant-derived naphthoquinone (Plumbagin) and spike receptor (THR304) proteins of coronavirus. MGL virtual screening tool and Biovia Discovery Studio were utilized in the current molecular docking investigations. Outcomes of docking studies exposed that selected organic compounds have interacted with targeted spike receptor protein with binding energies in the range of -4.0 to -9.5 kcal, which means the binding energy of the target and ligand is -5.78. In summary, plumbagin seems to be a more effective primary protease inhibitor than the other chosen ligands for deactivating the SARS-Coronavirus.
Sophisticated face mask dataset: a novel dataset for effective coronavirus disease surveillance

Efficient and accurate coronavirus disease (COVID-19) surveillance necessitates robust identification of individuals wearing face masks. This research introduces the sophisticated face mask dataset (SFMD), a comprehensive compilation of high-quality face mask images enriched with detailed annotations on mask types, fits, and usage patterns. Leveraging cutting-edge deep learning models—EfficientNet-B2, ResNet50, and MobileNet-V2—, we compare SFMD against two established benchmarks: the real-world masked face dataset (RMFD) and the masked face recognition dataset (MFRD). Across all models, SFMD consistently outperforms RMFD and MFRD in key metrics, including accuracy, precision, recall, and F1 score. Additionally, our study demonstrates the dataset's capability to cultivate robust models resilient to intricate scenarios like low-light conditions and facial occlusions due to accessories or facial hair.
The Effect of Feeding a Total Mixed Ration with an ad libitum or Restricted Pelleted Starter on Growth Performance, Rumination Behavior, Blood Metabolites, and Rumen Fermentation in Weaning Holstein Dairy Calves

Simple Summary Preweaning nutrition plays a crucial role in the growth of dairy calves, determining their future productivity and overall health. Researchers are still studying the most appropriate dietary strategies in the preweaning and early post-weaning periods. In particular, the effect of different levels of forage inclusion in the diet of young cattle is not yet clear. Our study evaluated the effects of starter restriction and ad libitum inclusion of the total mixed ration on intake, growth performance, rumination time, and health status of Holstein dairy calves during preweaning and in the immediate post-weaning period. The results obtained from the present study indicate that providing TMR (high fiber content, with or without concentrate restriction) does not impair growth performance and health of calves, and at the same time it leads to a greater time spent for ruminating when calves are weaned. The latter indicates a better rumen development and likely a better rumen fermentation efficiency in post-weaning. Abstract The aim of the current study was to evaluate the effect of the starter restriction and of the ad libitum TMR (total mixed ration) inclusion on intake, growth performance, rumination time (RT), and health condition of Holstein dairy calves during weaning. We randomly assigned thirty female Holstein calves (with an average weight of 38.5 ± 1.96 kg at birth) to one of three treatments. From 21 days of age, the calves were fed one of three treatments as follows: a control diet (CTR) with an ad libitum calf starter but without TMR; Treatment 1 diet (TRT1) with both an ad libitum calf starter and ad libitum TMR; Treatment 2 diet (TRT2) with ad libitum TMR and a restricted amount of a calf starter (50% of the intake recorder in the control group day by day). Calves in the TRT2 group, between 56 and 63 days of age, had a lower body weight (80.1; 79.5; 75.6 kg for the CTR, TRT1, and TRT2 groups, respectively) compared with CTR and TRT1 calves. This outcome is ascribed to the average daily gain (0.759; 0.913; 0.508 kg/day for the CTR, TRT1, and TRT2 groups, respectively), resulting also in TRT2 being lower than CTR or TRT1 calves. The inclusion of ad libitum TMR increased the rumination time, especially after weaning (15.28 min/h, 18.38 min/h, and 18.95 min/h for the CTR, TRT1, and TRT2 groups, respectively). Concerning the rumen metabolism and inflammometabolic response, overall, no differences were observed between the three dietary treatments. In conclusion, the results indicated that a TMR could partially replace a calf starter in weaning dairy calves, since neither growth performance nor health status were impaired. In addition, providing TMR (with or without concentrate restriction) led to a better rumen development and likely a better rumen fermentation efficiency in post-weaning.
Plankton Biomass Models Based on GIS and Remote Sensing Technique for Predicting Marine Megafauna Hotspots in the Solor Waters

Geographic information system and remote sensing techniques can be used to assist with distribution modelling; a useful tool that helps with strategic design and management plans for MPAs. This study built a pilot model of plankton biomass and distribution in the waters off Solor and Lembata, and is the first study to identify marine megafauna foraging areas in the region. Forty-three samples of zooplankton were collected every 4 km according to the range time and station of aqua MODIS. Generalized additive model (GAM) we used to modelling zooplankton biomass response from environmental properties.Thirty one samples were used to build a model of inverse distance weighting (IDW) (cell size 0.01°) and 12 samples were used as a control to verify the models accuracy. Furthermore, Getis-Ord Gi was used to identify the significance of the hotspot and cold-spot for foraging area. The GAM models was explain 88.1% response of zooplankton biomass and percent to full moon, phytopankton biomassbeing strong predictors. The sampling design was essential in order to build highly accurate models. Our models 96% accurate for phytoplankton and 88% accurate for zooplankton. The foraging behaviour was significantly related to plankton biomass hotspots, which were two times higher compared to plankton cold-spots. In addition, extremely steep slopes of the Lamakera strait support strong upwelling with highly productive waters that affect the presence of marine megafauna. This study detects that the Lamakera strait provides the planktonic requirements for marine megafauna foraging, helping to explain why this region supports such high diversity and abundance of marine megafauna.
Expression of Rice Glutelin Gene GluA-2 in Wheat Endosperm

Rice (Oryza sativa L.) glutelin accounts for about 80% of total seed storage protein. Glutelin can be easily digested by human and contains high concentrations of lysine and other essential amino acids. To improve the nutritional quality of wheat (Triticum aestivum L.), the cDNA sequence of rice glutelin gene GluA-2 was introduced into common wheat through biolistic bombardment. Six hundreds of immature embryos from wheat cultivar Bobwhite (T. aestivum cv. Bobwhite) were bombarded. Four transgenic plants carrying GluA-2 gene were confirmed by PCR and Southern blotting analyses. Gene GluA-2 was translated in three of the transgenic plants and their progeny, as indicated by SDS-PAGE analyses. The expression of GluA-2 gene was not detected in one transgenic plant and the endogenous wheat high molecular weight glutenin subunits Bx7 and By9 contents decreased greatly in both T0 and T1 generations.
Chemotherapy and Radiotherapy Long-Term Adverse Effects on Oral Health of Childhood Cancer Survivors: A Systematic Review and Meta-Analysis

Simple Summary The survival rate for pediatric cancer has increased over the past few decades, short- and long-term complications have been detected and studied, and oral complications have emerged as an important topic of research. Here, we aimed to highlight the importance of oral manifestations that may only become apparent years or even decades after cancer treatment. Childhood cancer survivors presented a higher risk of having dental alterations than control counterparts. Additional analyses reveal possible sex-based differences that should be explored in future studies. These results collectively highlight the importance of oral healthcare and the prevention of disease in childhood cancer survivors. Abstract The survival rate for pediatric cancer has increased over the past few decades, short- and long-term complications have been detected and studied, and oral complications have emerged as an important topic of research. Here, we aimed to highlight the importance of oral manifestations that may only become apparent years or even decades after cancer treatment. This systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis. We searched articles using PubMed via the MEDLINE, Web of Science, and LILACS databases until October 2023. Overall, 35 observational studies were included, and the results estimated a pooled prevalence of the following dental anomalies: discoloration, 53%; crown-root malformations and agenesis, 36%; enamel hypoplasia, 32%; root development alterations, 29%; unerupted teeth, 24%; microdontia, 16%; hypodontia, 13%; and macrodontia, 7%. Most childhood cancer survivors have at least one dental sequela. Childhood cancer survivors presented a higher risk of having dental alterations than control counterparts. Additional analyses reveal possible sex-based differences that should be explored in future studies. These results collectively highlight the importance of oral healthcare and the prevention of disease in childhood cancer survivors.
Preparation and Characterization of Boza Enriched with Nonfat Dry Milk and Its Impact on the Fermentation Process

Boza is an indigenous, traditional, low-alcohol and highly viscous beverage prepared by fermenting cereals. Its thick and gel-like consistency make it suitable for consumption via spoon. Although boza is a nutritious beverage, its protein content is very low (<2%). A new type of boza was developed by incorporating nonfat dry milk (NFDM) to elevate the protein content of the beverage. Different NFDM amounts (10 to 40% w/v) were added to determine the best concentration and fermentation time based on the refractive index and pH values at room temperature (0–48 h). The best sample was further characterized by rheological analyses and Fourier transform infrared (FTIR) spectroscopy. The sample with 10% NFDM was the best, as fermentation was successfully performed, and further addition of NFDM increased the initial pH. The refractive index and pH decreased from 21.9 ± 0.1 to 11.8 ± 0.1 and 5.77± 0.50 to 4.09 ± 0.35 during fermentation, respectively. The samples exhibited shear-thinning, solid-like behavior, and a gel-like structure. FTIR analysis by independent modeling of class analogy (SIMCA) demonstrated that unfermented slurry and the fermented product could be effectively differentiated. With the addition of 10% NFDM, the increase in the protein content of the boza medium became significant.
The early evolution and diversification of holothurians (Echinozoa)

The early evolution and diversification of the sea cucumbers have shortly been reviewed and reinterpreted, including new records of Ordovician, Silurian, and Devonian material. Holothuroids have a Phanerozoic history extending back more than 464 Ma, ranging from the early Middle Ordovician to the present time. The maximum level of morphological diversification was apparently reached in the Mesozoic, in all likelihood due to a lack of research in other strata. A revised hypothesis of Early Palaeozoic higher-level relationships within the Holothuroidea is presented.
The Moderating Role of Cortisol and Negative Emotionality in the Effects of Classroom Size and Window View on Young Children’s Executive Functions

This study probed how baseline cortisol (BC), negative emotionality (NE), and environmental facets—classroom size and window view—interact to affect executive function (EF) in preschoolers using virtual reality (VR). In a cohort of 144 children aged 61–85 months, BC levels were measured by saliva assays and NE by parental surveys. Participants completed computerized EF assessments both pre- and post-exposure to one of four VR conditions, which varied by classroom size (large vs. small) and window view (natural vs. built). Due to missing data and outlier responses, three children were removed from the analyses. Regression analyses, accounting for initial EFs, revealed that higher BC was significantly associated with better Digit-span task scores in the nature view, while lower BC correlated with improved performance in the built view. With regard to classroom size, children with varying levels of NE benefitted from the large classroom environment, as evidenced by marginally significant improvements on the Corsi block task. However, higher NE children outperformed their lower NE peers in the large classroom, while a trend inverted in the small classroom context. The findings illuminate how the physical components of preschool environments may interact with children’s physiological reactivity, potentially influencing the development of working memory.
Understanding Adversarial Atmospheric Features Interpretation, Analysis, and Standardization for Tackling the Computer Vision Problems in Videos

In real-world situations, the performance of vision-based systems in indoor environments has been observed to provide noticeable results. However, in the case of the outdoor environment, the proper functioning of vision-based systems is often disrupted due to the occurrence of atmospheric/weather effects. To ensure the functional operation of all vision-based devices in any weather condition, a reliable classification/recognition system is needed to identify the weather pertinent to the scenes for effective removal. Consequently, a trustworthy classification/recognition system is required to recognize the weather pertinent to the outdoor scenes for its effective removal to guarantee the efficient functioning of all vision-based systems in any weather situation. For this, this work investigated and analyzed the performance of conventional handcrafted features extracted from outdoor scenes to solve the problem of atmospheric/weather classification tasks in real-world outdoor scenes. Recently, convolutional neural network (CNN)-based architectures have been used by research communities for solving many vision-based problems. Motivated by the enormous success of CNNs, in the present scope of this article, the perception capability of deep CNN features is also investigated for effective analysis and discrimination of atmospheric/weather-degraded scenes. To achieve the precise necessities of the objectives, several experiments were conducted. The analysis and experiments were carried out using the created Extended Tripura University Video Dataset (E-TUVD), which consists of a diverse set of atmospheric/weather-degraded outdoor scenes. The experiment results reveal that effectively selecting the discriminative features, thereby describing the weather properties, can improve classification accuracy and provide an accurate weather type classification using machine learning classifiers.
Spatial Variability of Rainfall and Classification of Peninsular Indian Catchments

The strength and success of hydrological analysis depend upon the quantity and quality of observed data. In the recent past, the availability of advanced computing facilities and measurement techniques had a great impact on the field of hydrology, especially in hydrologic analysis and hydrologic modeling. In spite of such growth, the present hydrologic modeling has certain challenges: complexity (involving a large number of parameters), applicability to a specific region (difficult to generalize for other regions), and lack of understanding of the connection between model theories and the actual system. The general solution of simplifying the models in terms of developing a classification framework has been discussed and focused on in the present study. It will greatly help to overcome the hydrologic modeling challenges and provides a better understanding of the hydrologic process. In general, classification is a way of grouping entities which has similar characteristics. The importance of applying nonlinear dynamics and chaos methods for classification has been realized in the recent past; since such studies provide exclusive information on hidden characteristics such as complexity, nonlinearity, dimensionality, etc. Of hydrological processes. The hydrologic processes are complex. In this study, information regarding the complexity is extracted by statistical analysis and linear methods such as Autocorrelation Function, and Average Mutual Information. 367 gridded rainfall stations over Peninsular Indian basins are used to investigate the applicability of different methods used in the study.
Recent Advances in Efficient Photocatalytic Degradation Approaches for Azo Dyes

In recent decades, the textile industry has contributed to continuous pollution in the environment. Synthetic dyes which are commonly found in waste water are azo, sulfur, anthraquinone, triphenylmethyl, indigoid, and phthalocyanine derivatives. These pollutants block the light penetration in water bodies and prevent photosynthesis activity, thereby affecting aquatic life. As an environmental crisis, several technologies have been explored to control pollution. Among all the techniques, the photocatalysis process is considered as a green, simple, and economical process. To improve the photocatalytic activity, researchers worldwide have investigated various photocatalysts such as metal oxides, metal ferrites, and heterostructured nanocomposites. The major goal of this review article is to propose a high-performing, cost-effective hybrid photocatalyst reported to date for prospective azo dye pollutant remediation. This review article also aimed to highlight the challenges and uncertainties associated with dye degradation in the photocatalytic process.