Miracle-dz/UniFAR-FTUs huggingface dataset:
PERSONALITY DYNAMICS OF BOARDERS AND DAY SCHOLARS WHO BELONG TO MADRASSAH AND PUBLIC SCHOOL

The major objective of the present study was to assess and compare the personality dynamics of boarders and day scholars who belongs to Madrassah and Public schools. Population of the present included all female and male students studying in Public school and Madrassah in Hazara division. For the present study six Public schools and six Madrassahs were randomly selected from four cities Haripur, Havelian, Abbottabad and Mansehra of Hazara division. Simple random sampling technique was used to select the sample of 168 students with age ranged from 15 years to 30 years out of which 84 male and female students were taken from Madrassah and same number of male and female students from Public schools respectively. Urdu version of NEO-PI (Goldberg, 1999) was used to collect data. t-test was used to analyze the data. Gender wise analysis indicated that Madrassah female students exhibited high vulnerability for Anxiety and Depression than Public school students, while male students from Public schools exhibited inclination towards Neuroticism and Extraversion as compares to Madrassah students. On the other hand both type of students manifested same level of Conscientiousness, Agreeableness, and Openness. Key word: Personality Dynamics, Madrassah students, Public school students, Boarders, DayScholars. Copyright © 2011 SAVAP International www.savap.org.pk www.journals. savap.org.pk 157
L G ] 1 1 O ct 2 01 9 A General Scoring Rule for Randomized Kernel Approximation with Application to Canonical Correlation Analysis

Random features has been widely used for kernel approximation in large-scale machine learning. A number of recent studies have explored data-dependent sampling of features, modifying the stochastic oracle from which random features are sampled. While proposed techniques in this realm improve the approximation, their application is limited to a specific learning task. In this paper, we propose a general scoring rule for sampling random features, which can be employed for various applications with some adjustments. We first observe that our method can recover a number of datadependent sampling methods (e.g., leverage scores and energy-based sampling). Then, we restrict our attention to a ubiquitous problem in statistics and machine learning, namely Canonical Correlation Analysis (CCA). We provide a principled guide for finding the distribution maximizing the canonical correlations, resulting in a novel data-dependent method for sampling features. Numerical experiments verify that our algorithm consistently outperforms other sampling techniques in the CCA task.
Language Identity and the Other Gender

There is small amount of research conducted on “gay focused linguistic scholarship” and its counterpart in Arabic-gay-sociolinguistics is virtually non-existent. The present paper raises the issue of the existence of gay community in the Arab world. On the basis of empirical investigations, field-direct and indirect observations, interviews as well as random questionnaire, we hypothesize that there exists a gay speech community in (at least in the studied countries) the Arab world for we investigate and determine its social and linguistic dimensions. This lead us to find out the discursive criteria which characterize modes of gay-speak that are part of their identity. After comparing them to women’s talk, we assume, however, that in spite of this high rate of assimilation in language behavior at the phonological, lexical, and even gestural ones, gays cannot be defined as “women” nor can they be classified as a separate gender or third sex (as other studies claim).
The effect of atmospheric conditions on sound propagation and its impact on the outdoor sound field control

The performance of active sound field control solutions is directly dependent on the knowledge of the acoustic transfer functions between the control loudspeakers and control areas. Outdoors, the propagation of sound and thus these transfer functions are affected by atmospheric conditions and their variation. In this work we experimentally investigate the effect of wind and temperature changes on transfer functions. We present the results of a measurement campaign, where transfer functions and weather data were gathered every 30 minutes for a time period of a week. The results show the impact of wind (up to 8 m/s) and temperature (−2◦C to 6◦C) variations on the sound propagation over distances of around 300 m. We discuss the results in relation to the outdoor control of sound.
Biologically-Inspired Computational Neural Mechanism for Human Action/activity Recognition: A Review

Theoretical neuroscience investigation shows valuable information on the mechanism for recognizing the biological movements in the mammalian visual system. This involves many different fields of researches such as psychological, neurophysiology, neuro-psychological, computer vision, and artificial intelligence (AI). The research on these areas provided massive information and plausible computational models. Here, a review on this subject is presented. This paper describes different perspective to look at this task including action perception, computational and knowledge based modeling, psychological, and neuroscience approaches.
Synthesis of Silver Nanoparticles Mediated by Fungi: A Review

The use of fungi as reducing and stabilizing agents in the biogenic synthesis of silver nanoparticles is attractive due to the production of large quantities of proteins, high yields, easy handling, and low toxicity of the residues. Furthermore, this synthesis process coats the nanoparticles with biomolecules derived from the fungus, which can improve stability and may confer biological activity. The aim of this review is to describe studies in which silver nanoparticles were synthesized using fungi as reducing agents, discussing the mechanisms and optimization of the synthesis, as well as the applications. The literature shows that various species of fungus have potential for use in biogenic synthesis, enabling the production of nanoparticles with different characteristics, considering aspects such as their size, surface charge, and morphology. The synthesis mechanisms have not yet been fully elucidated, although it is believed that fungal biomolecules are mainly responsible for the process. The synthesis can be optimized by adjusting parameters such as temperature, pH, silver precursor concentration, biomass amount, and fungus cultivation time. Silver nanoparticles synthesized using fungi enable the control of pathogens, with low toxicity and good biocompatibility. These findings open perspectives for future investigations concerning the use of these nanoparticles as antimicrobials in the areas of health and agriculture.
Antidiabetic, Antihyperlipidemic, Antioxidant, Anti-inflammatory Activities of Ethanolic Seed Extract of Annona reticulata L. in Streptozotocin Induced Diabetic Rats

Annona reticulata L. (Bullock's heart) is a pantropic tree commonly known as custard apple, which is used therapeutically for a variety of maladies. The present research was carried out to evaluate the possible protective effects of Annona reticulata L. (A. reticulata) ethanolic seed extract on an experimentally induced type 2 diabetes rat model. Male Albino Wistar rats were randomly divided into five groups with six animals in each group viz., control rats in group I, diabetic rats in group II, diabetic rats with 50 and 100 mg/kg/bw of ethanolic seed extract of A. reticulata in groups III and IV, respectively, and diabetic rats with metformin in group V. Treatment was given for 42 consecutive days through oral route by oro-gastric gavage. Administration of A. reticulata seed extract to diabetes rats significantly restored the alterations in the levels of body weight, food and water intake, fasting blood glucose (FBG), insulin levels, insulin sensitivity, HbA1c, HOMA-IR, islet area and insulin positive cells. Furthermore, A. reticulata significantly decreased the levels of triglycerides, cholesterol, LDL, and significantly increased the HDL in diabetic rats. A. reticulata effectively ameliorated the enzymatic (ALT, AST, ALP, GGT) and modification of histopathological changes in diabetic rats. The serum levels of the BUN, creatinine levels, uric acid, urine volume, and urinary protein were significantly declined with a significant elevation in CCr in diabetic rats treated with A. reticulata. MDA and NO levels were significantly reduced with an enhancement in SOD, CAT, and GPx antioxidant enzyme activities in the kidney, liver, and pancreas of diabetic rats treated with A. reticulata. Diabetic rats treated with A. reticulata have shown up-regulation in mRNA expression levels of nuclear factor erythroid 2-related factor 2 (Nrf2), NAD(P)H:quinone oxidoreductase 1 (NQO1), Heme oxygenase-1 (HO-1) and protein expression level of Nrf2 with diminution in Keap1 mRNA expression level in pancreas, kidney, and liver. From the outcome of the current results, it can be inferred that seed extract of A. reticulata exhibits a protective effect in diabetic rats through its anti-diabetic, anti-hyperlipidemic, antioxidant and anti-inflammatory effects and could be considered as a promising treatment therapy in the treatment of diabetes mellitus.
Fluocell for Ratiometric and High-Throughput Live-Cell Image Visualization and Quantitation

Spatiotemporal regulation of molecular activities dictates cellular function and fate. Investigation of dynamic molecular activities in live cells often requires the visualization and quantitation of fluorescent ratio image sequences with subcellular resolution and in high throughput. Hence, there is a great need for convenient software tools specifically designed with these capabilities. Here we describe a well-characterized open-source software package, Fluocell, customized to visualize pixelwise ratiometric images and calculate ratio time courses with subcellular resolution and in high throughput. Fluocell also provides group statistics and kinetic analysis functions for the quantified time courses, as well as 3D structure and function visualization for ratio images. The application of Fluocell is demonstrated by the ratiometric analysis of intensity images for several single-chain Förster (or fluorescence) resonance energy transfer (FRET)-based biosensors, allowing efficient quantification of dynamic molecular activities in a heterogeneous population of single live cells. Our analysis revealed distinct activation kinetics of Fyn kinase in the cytosolic and membrane compartments, and visualized a 4D spatiotemporal distribution of epigenetic signals in mitotic cells. Therefore, Fluocell provides an integrated environment for ratiometric live-cell image visualization and analysis, which generates high-quality single-cell dynamic data and allows the quantitative machine-learning of biophysical and biochemical computational models for molecular regulations in cells and tissues.
Orexin-A Excites Airway Vagal Preganglionic Neurons via Activation of Orexin Receptor Type 1 and Type 2 in Rats

Airway vagal nerves play a predominant role in the neural control of the airway, and augmented airway vagal activity is known to play important roles in the pathogenesis of some chronic inflammatory airway diseases. Several lines of evidence indicate that dysfunctional central orexinergic system is closely related to the severity of airway diseases, however, whether orexins affect airway vagal activity is unknown. This study investigates whether and how orexin-A regulates the activity of medullary airway vagal preganglionic neurons (AVPNs). The expression of orexin receptor type 1 (OX1R) and type 2 (OX2R) was examined using immunofluorescent staining. The effects of orexin-A on functionally identified inspiratory-activated AVPNs (IA-AVPNs), which are critical in the control of airway smooth muscle, were examined using patch-clamp in medullary slices of neonatal rats. Airway vagal response to injection of orexin-A into the magna cisterna was examined using plethysmography in juvenile rats. The results show that retrogradely labeled AVPNs were immunoreactive to anti-OX1R antibody and anti-OX2R antibody. Orexin-A dose-dependently depolarized IA-AVPNs and increased their firing rate. In synaptically isolated IA-AVPNs, the depolarization induced by orexin-A was blocked partially by OX1R antagonist SB-334867 or OX2R antagonist TCS OX2 29 alone, and completely by co-application of both antagonists. The orexin-A-induced depolarization was also mostly blocked by Na+/Ca2+ exchanger inhibitor KB-R7943. Orexin-A facilitated the glutamatergic, glycinergic and GABAergic inputs to IA-AVPNs, and the facilitation of each type of input was blocked partially by SB-334867 or TCS OX2 29 alone, and completely by co-application of both antagonists. Injection of orexin-A into the magna cisterna of juvenile rats significantly increased the inspiratory and expiratory resistance of the airway and consequently decreased the dynamic compliance of the lungs, all of which were prevented by atropine sulfate or bilateral vagotomy. These results demonstrate that orexin-A excites IA-AVPNs via activation of both OX1R and OX2R, and suggest that increased central synthesis/release of orexins might participate in the pathogenesis of airway diseases via over-activation of AVPNs.
The Impact of Pre-operative Nutritional Status on Outcomes Following Congenital Heart Surgery

Aims and Objectives: Malnutrition is common in children with congenital heart disease and may contribute to adverse outcomes. This study evaluates the impact of pre-operative nutritional status on outcomes after congenital heart surgery. Methods: We conducted a retrospective cohort study enrolling children under 10 years old who underwent congenital heart surgery at a tertiary children's hospital from 2012 to 2016. Patients who had patent ductus arteriosus ligation only, genetic syndromes, or global developmental delay were excluded. Outcome measures included 30-day mortality, intensive care unit (ICU) length of stay (LOS), hospital LOS, duration of mechanical ventilation, and number of inotropes used post-operatively. We performed univariate/multivariable logistic regression analysis, adjusting for age, cyanotic cardiac lesion, co-morbidity, and Risk Adjustment for Congenital Heart Surgery (RACHS-1) score. Results: Three hundred two children of median age 16.2 [interquartile range (IQR) 3.1, 51.4)] months were included. The most common cardiac lesions were ventricular septal defect (27.8%), atrial septal defect (17.9%), and Tetralogy of Fallot (16.6%). Median weight-for-age z-score (WAZ) was −1.46 (IQR −2.29, −0.61), height-for-age z-score (HAZ) was −0.94 (IQR −2.10, −0.10), and body mass index (BMI)-for-age z-score (BAZ) was −1.11 (IQR −2.19, −0.30). In multivariable analysis, there was an increased risk of 30-day mortality for WAZ ≤−2 vs. WAZ >−2 [adjusted odds ratio (aOR): 4.01, 95% CI: 1.22, 13.13; p = 0.022]. For HAZ ≤-2 vs. HAZ > −2, there was increased risk of hospital LOS ≥ 7 days (aOR: 2.08, 95% CI: 1.12, 3.89; p = 0.021), mechanical ventilation ≥48 h (aOR: 2.63, 95% CI: 1.32, 5.24; p = 0.006) and of requiring ≥3 inotropes post-operatively (aOR: 3.00, 95% CI: 1.37, 6.59; p = 0.006). Conclusion: In children undergoing congenital heart surgery, WAZ ≤ −2 is associated with higher 30-day mortality, while HAZ ≤ −2 is associated with longer durations of hospital LOS and mechanical ventilation, and increased risk of use of 3 or more inotropes post-operatively. Future studies are necessary to develop safe and efficacious peri-operative nutritional interventions, particularly in patients with WAZ and HAZ ≤ −2.
Well-Being as a Cognitive Load Reducing Agent: A Review of the Literature

Cognitive Load Theory is an evolutionary based theory of learning centered upon the cognitive architecture of the brain, which outlines a series of empirically based instructional effects that ensure efficient and effective learning. While the research upon which Cognitive Load Theory is based has generally aimed at controlling the impacts of the surrounding environment, the impact of individual psycho-social factors such as a student’s level of wellbeing have not, as yet, been fully explored. This review was conducted using the Scopus database focusing on the Cognitive Load Theory Instructional Effects literature. The review proposes that wellbeing may act as a cognitive load reducing agent for students and offers evidence from the broader literature on mechanisms through which wellbeing reduces the cognitive load placed upon a student’s working memory. The proposed mechanisms of reducing extraneous load and increasing germane load are proposed through; the presence of positive emotions, the absence of painful emotions, high levels of academic buoyancy and cognitive regulation.
Synthesis and Characterization of Covalent Triazine Framework CTF-1@Polysulfone Mixed Matrix Membranes and Their Gas Separation Studies

Covalent triazine framework CTF-1 and polysulfone (PSF) are used to form mixed-matrix membranes (MMMs) with 8, 16, and 24 wt% of the porous filler material CTF-1. Studies on permeability and selectivity are carried out concerning the gases O2, N2, CO2, and CH4. CO2 permeability of the synthesized MMMs increases by 5.4 Barrer in comparison to the pure PSF membrane. The selectivity remains unchanged for O2/N2 and CO2/CH4 but was found to be increased for CO2/N2. Further, comparisons to theoretical models for permeability prediction yield a permeability for CTF-1 which is about six times higher than the permeability of PSF. The inverse of the sum of the free fractional volumes (FFV) of the polymer and the filler correlate linearly to the logarithm of the permeabilities of the gases which conversely indicates that the porosity of the filler contributes to the gas transport through the membrane.
Structural Imaging of Native Cryo-Preserved Secondary Cell Walls Reveals the Presence of Macrofibrils and Their Formation Requires Normal Cellulose, Lignin and Xylan Biosynthesis

The woody secondary cell walls of plants are the largest repository of renewable carbon biopolymers on the planet. These walls are made principally from cellulose and hemicelluloses and are impregnated with lignin. Despite their importance as the main load bearing structure for plant growth, as well as their industrial importance as both a material and energy source, the precise arrangement of these constituents within the cell wall is not yet fully understood. We have adapted low temperature scanning electron microscopy (cryo-SEM) for imaging the nanoscale architecture of angiosperm and gymnosperm cell walls in their native hydrated state. Our work confirms that cell wall macrofibrils, cylindrical structures with a diameter exceeding 10 nm, are a common feature of the native hardwood and softwood samples. We have observed these same structures in Arabidopsis thaliana secondary cell walls, enabling macrofibrils to be compared between mutant lines that are perturbed in cellulose, hemicellulose, and lignin formation. Our analysis indicates that the macrofibrils in Arabidopsis cell walls are dependent upon the proper biosynthesis, or composed, of cellulose, xylan, and lignin. This study establishes that cryo-SEM is a useful additional approach for investigating the native nanoscale architecture and composition of hardwood and softwood secondary cell walls and demonstrates the applicability of Arabidopsis genetic resources to relate fibril structure with wall composition and biosynthesis.
Spatio-Temporal Distribution of Monarch Butterflies Along Their Migratory Route

Efforts to conserve the migratory phenomenon of monarch butterflies in eastern North America have increased since a 2013-2014 monitoring report documenting a historical population low at the Monarch Butterfly Biosphere Reserve in Mexico. Surprisingly, there have been few systematic attempts to develop predictive models of monarch butterfly distributions along their migratory route between Mexico and the United States and Canada. Here we produced monthly habitat suitability models for monarch butterflies along their migratory route to identify potential areas for resting, feeding, and reproduction of the population. We compiled a point occurrence database of monarch butterflies for Mexico, USA, and Canada, including georeferenced records from GBIF, the Naturalista platform in Mexico, Correo Real initiative, and the Mexican governmental monitoring network for the monarch butterfly. We produced monthly habitat suitability models (HSM), using the R language and environment for statistical computing, abiotic (WorldClim), edaphic, and topographic variables. A total of 95 HSM were produced for each month. June to September, corresponding to the reproduction months in North America showed the highest geographic extent with suitable habitats; April, corresponding to the reproduction of the first post-migration generation, showed the smallest area. September, October and November, correspond to the movement of the monarch butterflies southwards, showed typical recognized distribution of the phenomenon and the overwintering months. December to February showed the smallest geographic extent in habitat suitability. Edaphic variables ranked high in importance in HSM for 11 of 12 months, indicating the relevance of vegetation and floral resources in the monarch butterfly migration route. Identifying such regions contribute to establish concrete conservation programs accordingly, as reduction of the use of pesticides and herbicides, decrease in the speed of cars in roads, and planting species with high nectary value, among others. Our study provides a first predictive spatio-temporal approximation of the monarch butterfly migratory route annual cycle.
Teaching an Old Dog New Tricks: Strategies That Improve Early Recognition in Similarity-Based Virtual Screening

High throughput screening (HTS) is an important component of lead discovery, with virtual screening playing an increasingly important role. Both methods typically suffer from lack of sensitivity and specificity against their true biological targets. With ever-increasing screening libraries and virtual compound collections, it is now feasible to conduct follow-up experimental testing on only a small fraction of hits. In this context, advances in virtual screening that achieve enrichment of true actives among top-ranked compounds (“early recognition”) and, hence, reduce the number of hits to test, are highly desirable. The standard ligand-based virtual screening method for large compound libraries uses a molecular similarity search method that ranks the likelihood of a compound to be active against a drug target by its highest Tanimoto similarity to known active compounds. This approach assumes that the distributions of Tanimoto similarity values to all active compounds are identical (i.e., same mean and standard deviation)—an assumption shown to be invalid (Baldi and Nasr, 2010). Here, we introduce two methods that improve early recognition of actives by exploiting similarity information of all molecules. The first method ranks a compound by its highest z-score instead of its highest Tanimoto similarity, and the second by an aggregated score calculated from its Tanimoto similarity values to all known actives and inactives (or a large number of structurally diverse molecules when information on inactives is unavailable). Our evaluations, which use datasets of over 20 HTS campaigns downloaded from PubChem, indicate that compared to the conventional approach, both methods achieve a ~10% higher Boltzmann-enhanced discrimination of receiver operating characteristic (BEDROC) score—a metric of early recognition. Given the increasing use of virtual screening in early lead discovery, these methods provide straightforward means to enhance early recognition.