Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of dietary supplementation of Neem (Azadirachta indica) leaf powder on the performance of commercial broiler chicken

The present experiment was conducted to study the effect of supplementation of Neem (Azadirachta indica) leaf powder (NLP) on the performance of commercial broiler chicken. A total of 144 day-old commercial broiler chicks (Cobb 400) were randomly divided into four groups viz. T0 (only basal diet as control), T1 (basal diet +0.1 % NLP), T2 (basal diet +0.2 % NLP) and T3 (basal diet +0.3 % NLP) consisting of 36 birds per group and further subdivided into 3 replicates of 12 chicks each. Supplementation of 0.3% Neem leaf powder improved the total feed consumption, significantly (P<0.05) improved final body weight and body weight gain. The final body weight per broiler was highest in T3 group (2048.61 ± 24.27 g) followed by T2 group (1939.64 ± 20.63 g), T1 (1744.12 ± 45.71 g) and T0 (1710.29 ± 38.32 g). At the end of the experimental period best FCR (1.75), highest BPEI (117.06) and higher gross profit was obtained in T3 group among the different experimental groups.
Almost sure convergence rates for Stochastic Gradient Descent and Stochastic Heavy Ball

We study stochastic gradient descent (SGD) and the stochastic heavy ball method (SHB, otherwise known as the momentum method) for the general stochastic approximation problem. For SGD, in the convex and smooth setting, we provide the first almost sure asymptotic convergence rates for a weighted average of the iterates . More precisely, we show that the convergence rate of the function values is arbitrarily close to o(1/ √ k), and is exactly o(1/k) in the so-called overparametrized case. We show that these results still hold when using stochastic line search and stochastic Polyak stepsizes, thereby giving the first proof of convergence of these methods in the non-overparametrized regime. Using a substantially different analysis, we show that these rates hold for SHB as well, but at the last iterate. This distinction is important because it is the last iterate of SGD and SHB which is used in practice. We also show that the last iterate of SHB converges to a minimizer almost surely. Additionally, we prove that the function values of the deterministic HB converge at a o(1/k) rate, which is faster than the previously known O(1/k). Finally, in the nonconvex setting, we prove similar rates on the lowest gradient norm along the trajectory of SGD.
AWARD NUMBER: W81XWH-16-1-0400 TITLE: Powering Up Mitochondrial Functions to Treat Mitochondrial Disease PRINCIPAL INVESTIGATOR:

Growth differentiation factor 15 (GDF15) is a secreted protein with pleotropic functions from the transforming growth factor (TGF) family. GDF15 is synthesized as a precursor and undergoes proteolytic cleavage to generate mature GDF15. The strong appetite-suppressing effect of mature GDF15 makes it an attractive therapeutic agent/target for diseases such as obesity and cachexia. In addition, clinical studies indicate that circulating, mature GDF15 is an independent biomarker for heart failure. We recently found that GDF15 functions as a heart-derived hormone that inhibits liver growth hormone signaling and postnatal body growth in the pediatric period. However, little is known about the mechanism of GDF15 maturation, in particular the enzymes that mediate GDF15 precursor cleavage. We investigated which candidate proteases can cleave GDF15 precursor and generate mature GDF15 in cardiomyocytes in vitro and mouse hearts in vivo. We discovered that three members of the proprotein convertase, subtilisin/kexin-type (PCSK) family, namely, PCSK3, PCSK5, and PCSK6, can efficiently cleave GDF15 precursor, therefore licensing its maturation both in vitro and in vivo. Our studies suggest that PCSK3, -5, and -6 mediate a crucial step of GDF15 maturation through proteolytic cleavage of the precursor. These results also reveal new targets for therapeutic application of GDF15 in treating obesity and cachexia.
In vitro Antagonistic Potential of Endophytic Fungi of Soybean (Glycine Max (L.) Merril) Against Macrophomina phaseolina

Utilization of indigenous endophytes is considered as an environmentally-friendly and ecologically efficient strategy. A total 14 endophytic fungi belonging Alternaria alternata, Aspergillus niger, Aspergillus sp. , Curvularia lunata, Cladosporium cladosporioides, Chaetomium sp. , Phomopsis sp.1, Macrophomina phaseolina, Nigrospora sphaerica, Penicillium sp. , Paecilomyces lilacinus, Fusarium oxysporum, Phomopsis sp. 2 and Rhizoctonia sp. were isolated from soybean (Glycine max (L.) Merril) and were screened in vitro for the antagonistic activity against charcoal rot of soybean caused by M. phaseolina. In this fungal endophytic antagonists tested, Paecilomyces lilacinus was found most effective with highest mycelial growth inhibition (61.11%), followed by Aspergillus niger and Penicillium sp. with of 53.87% and 51.48% mycelial inhibition. These endophytes thus; could be efficient biological control agent in sustainable crop production and offer unique opportunity for crop protection and biological control.
Aluminum to titanium laser welding-brazing in V-shaped groove

Laser assisted joining of AA5754 aluminum alloy to T40 titanium with use of Al-Si filler wires was carried out. Continuous Yb:YAG laser beam was shaped into double spot tandem and defocalized to cover larger interaction zone in V shaped groove. Experimental design method was applied to study the influence of operational parameters on the tensile properties of the joints. Microstructure examination and fractography study were carried out to understand the relation between local phase content and fracture mode. Within defined window of operational parameters, statistically important factors that influenced the strength of T40 to AA5754 joints in V groove configuration were Si content in the filler metal and groove opening angle on T40 side. The best quality joint showed joint coefficient of 90% (or 200 MPa of apparent UTS). Tensile strength of the joints was found to be determined by the proportion between well-developed and under-developed reaction zones of T40/melted zone interface. The formation of 2–25 m thick Si-rich interlayers composed by Ti5Si3 and 2 proved to enhance the strength of brazed interface. The creation of very thin (<0.5 m) Si-rich layers at the bottom of the groove was found not sufficient to establish mechanical continuity of the joint and thus should be avoided.
Arabinogalactan proteins_ Distribution during the development of male and female gametophytes

Arabinogalactan proteins (AGPs), i.e. a subfamily of hydroxyproline-rich proteins (HRGPs), are widely distributed in the plant kingdom. For many years, AGPs have been connected with the multiple phases of plant reproduction and developmental processes. Currently, extensive knowledge is available about their various functions, i.e. involvement in pollen grain formation, initiation of pollen grain germination, pollen tube guidance in the transmission tissue of pistil and ovule nucellus, and function as a signaling molecule during cell-cell communication. Although many studies have been performed, the mechanism of action, the heterogeneous molecule structure, and the connection with other extracellular matrix components have not been sufficiently explained. The aim of this work was to gather and describe the most important information on the distribution of AGPs in gametophyte development. The present review provides a summary of the first reports about AGPs and the most recent knowledge about their functions during male and female gametophyte formation.
A PRELIMINARY STUDY ON LARVICIDAL EFFICACY OF Piper nigrum L. (PIPERACEAE) EXTRACTS AGAINST DENGUE VECTOR, Aedes albopictus (DIPTERA: CULICIDAE)

Botanical insecticides have become an alternative biocontrol tool in controlling mosquito population worldwide. Hence, the current study was conducted to determine the efficacy of Sarawak Piper nigrum ethanolic extracts as larvicidal potential on its morphological abnormalities against larvae and pupae of Aedes albopictus. Plant samples of P. nigrum were extracted in 95% ethanol, evaporated and analysed using standard qualitative method. Phytochemical screening revealed the presence of alkaloid, flavonoid, tannin, triterpenes and steroid in the fruit and leaf extracts, while saponins was only found in the leaf extract. Larval bioassays were conducted using the crude extracts following WHO standard for larval susceptibility test. After 24 hours of exposure, the total mortality of larvae was achieved at 10.5 ppm and 450 ppm for P. nigrum fruit and leaf extracts, respectively. Fruit extract has shown a more remarkable larvicidal potential with lower LC50 (5.07ppm) and LC90 (7.85ppm) as compared to the leaf extract which required higher LC50 (108.893ppm) and LC90 (213.796ppm). Analysis of variance (ANOVA) demonstrated a significant difference in the mean mortality of larvae between each concentration of fruit extract (F=121.202, df=6, p<0.05) and leaf extract (F=452.875, df=6, p<0.05) as compared to the control groups. It was observed that both P. nigrum extracts induced several morphological abnormalities at larval and pupal stage that finally led to the individual mortality. Various phytochemical constituents detected in P. nigrum extracts may possess the mosquito larvicidal properties and cause the morphological abnormalities in mosquitoes. Hence, the ethanolic extracts of P. nigrum from Sarawak may pave the way for the development of an environmentally safe mosquito biopesticide.
From Neural Responses to Population Behavior: Neural Focus Group Predicts Population-Level Media E$ects

Can neural responses of a small group of individuals predict the behavior of large-scale populations? In this investigation, brain activations were recorded while smokers viewed three diFerent television campaigns promoting the National Cancer Institute’s telephone hotline to help smokers quit (1-800-QUIT-NOW). He smokers also provided self-report predictions of the campaigns’ relative eFectiveness. Population measures of the success of each campaign were computed by comparing call volume to 1-800-QUIT-NOW in the month before and the month aJer the launch of each campaign. His approach allowed us to directly compare the predictive value of self-reports with neural predictors of message eFectiveness. Neural activity in a medial prefrontal region of interest, previously associated with individual behavior change, predicted the population response, whereas self-report judgments did not. His Inding suggests a novel way of connecting neural signals to population responses that has not been previously demonstrated and provides information that may be diGcult to obtain otherwise
Physical fitness and nutritional anthropometric status of children from disadvantaged communities in the Nelson Mandela Bay region

Background Information about the relationships between physical fitness, body composition and nutrition has increased in recent years; however, little is known about physical fitness and the coexistence of under-/overnutrition among children living in disadvantaged areas. Objectives To determine the physical fitness status and its association with body composition, growth and selected socio-demographics in primary schoolchildren from disadvantaged communities in the Nelson Mandela Bay region. Methods Nine hundred and sixty-five children (49% girls, M=9.5 years) participated in this cross-sectional study. Height and weight were measured to establish body mass index, and height-for-age z-scores. Physical fitness was assessed using tests from the Eurofit Physical Fitness test battery (flexibility, upper/lower body muscular strength and cardiorespiratory fitness). Between-group differences and cross-sectional associations were examined with univariate (Chi2-tests, analyses of variance) and multivariate methods (mixed linear/logistic regression). Results Most children had normal weight (76.7%), while 4.5% were underweight and 18.7% were overweight/obese. Underweight children and children with stunted growth (11.5%) had lower average upper body strength (p<0.001). Overweight/obese children had lower scores in weight-bearing activities (p<0.001). Children with higher socio-economic status were more likely to be overweight and obese (p<0.001). In the multivariate analyses, sex, age, body mass index, and stunting were associated with children’s physical fitness. Conclusion Fitness assessments seem to be a relevant measure of the current health status of children in disadvantaged settings. Compared to international norms, the children in this study had relatively low scores for both upper- and lower body muscular strength. Therefore, effective school-based intervention programmes should be developed to improve children’s physical fitness in disadvantaged schools.
OPTIMAL ONLINE DATA-DRIVEN OPTIMIZATION WITH MULTIPLE TIME-VARYING NON-CONVEX OBJECTIVES

ABSTRACT This report presents the development of optimization research methods and concepts for time-varying, real-world situations, which include: factoring in more realistic assumptions on the dynamical systems underlying the objective functions and constraints, nonconvexity of objectives, reasonability of currently existing performance measures, time-varying constraints, and situations where the true objective function is unknown. Two scenarios were considered for training of statistical models for optimization: 1. ) where changes in the objective function were smooth, and 2. ) where the dynamical system of objective functions was adversarial (non-predictable). The problems considered in the body of work span a large number of subfields of optimization and are summarized in the remainder of the report
Effect of nitrogen and phosphorus on growth and flowering of calendula

A field experiment was conducted at Horticulture section, College of Agriculture, Nagpur (Maharashtra), India during Rabi season of the year 2018-2019 to know the response of nitrogen and phosphorus on growth and flowering of calendula. The experiment was laid out in Factorial Randomized Block Design with three replication and sixteen treatment combinations, which comprised of four levels of nitrogen (0, 75, 100 and 125 kg ha) and phosphorus (0, 25, 50 and 75 kg ha). The results revealed that nitrogen and phosphorus levels significantly influenced the growth and flowering of calendula. Growth parameters viz., plant height (62.33 cm), stem diameter (0.76 cm), leaves plant (177.36), leaf area (73.66 cm), branches plant (37.60) and plant spread at 50 % flowering (45.56 cm) were recorded significantly maximum with nitrogen 100 kg and phosphorus 50 kg ha. As regards flowering parameters viz., minimum days for first flower bud initiation, days for opening of first flower, days for 50 per cent flowering and flowering span were recorded with individual application of nitrogen 100 kg and phosphorus 50 kg ha.
Metformin as an Antidepressant in Type 2 Diabetes Mellitus Patients

Depression and diabetes are diseases that share similar mechanisms with the aging process, specifically inflammation and oxidative stress. Metformin is an approved drug to treat diabetes but appears to several aging-related mechanisms. It currently targets multiple pathways of aging that involves the AMPK pathway, mTOR pathway, and IGF-1 signaling pathway. Thus, for its aging-related mechanism, glucose metabolism may not be the most important one. This study reviews 12 types of research related to the use of metformin to treat depression. This study used online research engines such as PubMed and Google Scholar to review the current finding of metformin and depressionrelated issues. We found that metformin targets age-related diseases, such as neurocognitive functions other than to regulate blood glucose levels through multiple biological pathways. And the final result of how metformin can be deployed against the aging process might help other researchers and clinicians to determine how to best use this drug.
Speech-to-Speech Translation without Text

The common system requires effort to construct several components, including automatic speech recognition (ASR), machine translation (MT), and text-to-speech (TTS) synthesis, all of which are trained and tuned independently. Given speech input, ASR processes and transforms speech into text in the source language, MT transforms the source language text to corresponding text in the target language, and finally TTS generates speech from the text in the target language. Significant progress has been made and various commercial speech translation systems are already available for several language pairs. However, more than 6000 languages, spoken by 350 million people, have not been covered yet. At the moment, it is difficult to scale-up the existing approach to unknown languages without written forms or transcription data available. In this paper, we take a step beyond the current framework and propose a method for training speech to speech translation tasks without any transcription or linguistic supervision. Instead of only discovering subword units and synthesizing them within a certain language, our approach discovers subword units that are directly translated to another language. Our proposed method consists of two steps: (1) we train and generate discrete representation with unsupervised term discovery, which is also based on vector quantized variational autoencoder (VQ-VAE) [4]; (2) we train a sequence-to-sequence model to directly map the source language speech to the target language discrete representation. Our proposed method can directly generate target speech without any auxiliary or pre-training steps with source or target transcription. To the best of our knowledge, this is the first work that performed pure speech-to-speech translation between untranscribed unknown languages.
Balanced COPA: Countering Superﬁcial Cues in Causal Reasoning

Pretrained language models such as ELMo [15], BERT [1], RoBERTa [12] and ALBERT [9] have led to improved performance in benchmarks of natural language understanding, in tasks such as natural language inference [NLI, 11], argumentation [14], and commonsense reasoning [10, 18]. However, recent work has identified superficial cues in benchmark datasets which are predictive of the correct answer, such as unbalanced token distributions and lexical overlap. Once these cues are neutralized, models perform poorly, suggesting that their good performance is an instance of the Clever Hans effect1 [16]: Models trained on datasets with superficial cues learn heuristics for exploiting these cues, but do not develop any deeper understanding of the task. While superficial cues have been identified in, among others, datasets for NLI [5, 13], machine reading comprehension [20], and argumentation [14], one of the main benchmarks for commonsense reasoning, namely the Choice of Plausible Alternatives [COPA, 17], has not been analyzed so far. Here we present an analysis of superficial cues in COPA. Given a premise, such as The man broke his toe, COPA requires choosing the more plausible, causally related alternative, in this case either: because He got a hole in his sock (wrong) or because He dropped a hammer on his foot (correct). Our analysis reveals that COPA contains superfcial cues (§2) and that finetuned BERT [1] performs well (83.9 percent accuracy) on easy instances containing superficial cues, but worse (71.9 percent) on hard instances without such simple cues (§4.3). To prevent models from exploiting superficial cues in COPA, we introduce Balanced COPA (B-COPA). BCOPA contains one additional, mirrored instance for each original training instance. This mirrored instance uses the same alternatives as the corresponding original instance,
THE EFFECT OF DIFFERENT LIGHT CONDITIONS ON THE GROWTH AND DEVELOPMENT OF CHLOROPHYTUM AMANIENSE ENGL. ‘FIRE FLASH’

Chlorophytum amaniense Engl. is a foliage plant, member of the family Liliaceae, originates from the rainforests of East Africa. ‘Fire Flash’, the only cultivar of this species, known by several common names including Fire Glory, Mandarin Plant and Tangerine, present unique decorative characteristics. C. amaniense‚ ʻFire Flash’ do not support the direct action of the sun's rays and the placement in bright exposures. Given the claims of C. amaniense versus light and insufficient information in the literature, the objective of this research was to study the reaction of ‘Fire Flash’ under different lighting conditions. Plants attained the greatest leaf size and petioles when ‚ʻFire flash’ were grown in low and medium light intensity while plants exposed to high light showed lowest values of growth parameters. In addition, high light intensity produced chlorosiss and leaf burn and plants have become unmarketable after a 3 months period. The best size and quality of ‘Fire Flesh’ plants, occurred when plants were grown at a medium light levels of 80 μmol m s.
Macroscopic Cross-Section Generation for Nodal Code RAST-K Using Artificial Neural Network

Artificial Neural Networks (ANN) proved their effectiveness in solving various complex problems in numerous fields of knowledge, including nuclear reactor design and analysis. One of the most popular ways to use ANN in nuclear field is to replace numerically accurate reactor design computer codes with surrogate models that are capable of predicting target output parameters at a much faster speed. The trade-off of using ANN in this case is the uncertainty in the trained model that introduces an error in the final result. However, in some cases the accuracy requirement is not as strict as the requirement to obtain a result quickly. For example, a new reactor design requires many hundreds of human hours in order to find an optimal or nearly optimal fuel design and fuel loading pattern (LP) configuration. An optimal LP search involves numerous trials of possible LP configurations using computationally intensive and time-consuming reactor design codes. Some of those LPs could have been filtered out using ANN prior to running a more accurate computer code. In our previous writings [1], we discussed the applicability of a convolutional neural network (CNN) to prediction of various core design parameters. Though this approach is quite efficient for predicting various safety and design-related parameters, the trained ANN model is not versatile, i.e. it cannot be used for a different reactor type with a different number of fuel assemblies (FA) or different fuel configuration. To solve this problem, we can use a hybrid approach, which is based on the idea of finding the most computationally demanding parts and replacing them with an ANN model. In this study, we are working with our in-house nodal diffusion code RAST-K [2]. As explained in the reference, this code is part of a two-step computation system. The first step is to generate macroscopic crosssections (XS) using some lattice physics code. The second step is to solve a nodal diffusion equation implemented in RAST-K using those XS. The most computationally intensive component in this system is the first – XS generation – part of the process. In addition to that, the core geometry is being specified in the RAST-K part of the two-step code system, which means that we can replace the lattice code with a surrogate ANN model and predict the XS set required for solving a nodal diffusion equation regardless of the target core geometry. 2. Model description