Miracle-dz/UniFAR-FTUs huggingface dataset:
Development and nutrition of Prodenia litura on four food plants.

The effects of four food plants(castor,cowpea,papaya,and banana) on the development and nutriention of Prodenia litura were studied under 28.1℃ of laboratory temperature and 84.0% of relative humidity.The results showed that there were significant differences in developmental duration of larvae,pupa weight and nutrient function of the P.litura when fed on the four food plants.Among them,the larvae fed with the castor has the shortest developmental duration(9.93 d) and heaviest pupa weight(377.8 mg),while the larvae fed with the banana has the longest developmental duration(15.84 d) and the lightest pupa weiht(245.6 mg);the survival rate of the larvae was 98% when fed with the castor,while 66.0% when fed with banana;the consumption index,approximate digestibility,and relative growth rates of P.litura were the highest(5.458,68.492,0.531) when fed with castor,and those with banana were the lowest(0.860,16.300,0.255). The castor is a more sutible food plant to P.litura than bnana.
Upgraded GMRT Observations of the Coma Cluster of Galaxies: The Observations

We have used the upgraded Giant Metrewave Radio Telescope to map the Coma cluster of galaxies at 250–500 MHz and 1050–1450 MHz bands. These 6. ″26 and 2. ″18 resolutions observations allow detailed radio structures to be determined of all detected radio sources that show both discrete pointlike and extended morphologies. We present images of a subset of 32 brightest (Sν ≳ 30 mJy) and dominant sources, and several sources show discrete pointlike radio morphologies. We find the steepening of the spectra consistent with synchrotron cooling in the majority of sources and the median for spectral indices is −0.78, suggesting that ∼59% sources have steep spectra. The nature and the statistical properties of the radio sources in the Coma cluster will be discussed in subsequent papers.
First-Order Methods for Wasserstein Distributionally Robust MDP

Markov Decision Processes (MDPs) are known to be sensitive to parameter specification. Distributionally robust MDPs alleviate this issue by allowing for ambiguity sets which give a set of possible distributions over parameter sets. The goal is to find an optimal policy with respect to the worst-case parameter distribution. We propose a first-order methods framework for solving Distributionally robust MDPs, and instantiate it for several types of Wasserstein ambiguity sets. By developing efficient proximal updates, our algorithms achieve a convergence rate of $O(NA^{2.5}S^{3.5}\log(S)\log(\epsilon^{-1})\epsilon^{-1.5})$ for the number of kernels $N$ in the support of the nominal distribution, states $S$, and actions $A$ (this rate varies slightly based on the Wasserstein setup). Our dependence on $N$, $A$ and $S$ is significantly better than existing methods; compared to Value Iteration, it is better by a factor of $O(N^{2.5}A S)$. Numerical experiments on random instances and instances inspired from a machine replacement example show that our algorithm is significantly more scalable than state-of-the-art approaches.
Achieving Real-Time Execution of Transformer-based Large-scale Models on Mobile with Compiler-aware Neural Architecture Optimization

Pre-trained large-scale language models have increasingly demonstrated high accuracy on many natural language processing (NLP) tasks. However, the limited weight storage and computational speed on hardware platforms have impeded the popularity of pre-trained models, especially in the era of edge computing. In this paper, we seek to find the best model structure of BERT for a given computation size to match specific devices. We propose the first compiler-aware neural architecture optimization framework (called CANAO). CANAO can guarantee the identified model to meet both resource and real-time specifications of mobile devices, thus achieving real-time execution of large transformer-based models like BERT variants. We evaluate our model on several NLP tasks, achieving competitive results on well-known benchmarks with lower latency on mobile devices. Specifically, our model is 5.2x faster on CPU and 4.1x faster on GPU with 0.5-2% accuracy loss compared with BERT-base. Our overall framework achieves up to 7.8x speedup compared with TensorFlow-Lite with only minor accuracy loss.
Collaborative Distillation in the Parameter and Spectrum Domains for Video Action Recognition

Recent years have witnessed the significant progress of action recognition task with deep networks. However, most of current video networks require large memory and computational resources, which hinders their applications in practice. Existing knowledge distillation methods are limited to the image-level spatial domain, ignoring the temporal and frequency information which provide structural knowledge and are important for video analysis. This paper explores how to train small and efficient networks for action recognition. Specifically, we propose two distillation strategies in the frequency domain, namely the feature spectrum and parameter distribution distillations respectively. Our insight is that appealing performance of action recognition requires \textit{explicitly} modeling the temporal frequency spectrum of video features. Therefore, we introduce a spectrum loss that enforces the student network to mimic the temporal frequency spectrum from the teacher network, instead of \textit{implicitly} distilling features as many previous works. Second, the parameter frequency distribution is further adopted to guide the student network to learn the appearance modeling process from the teacher. Besides, a collaborative learning strategy is presented to optimize the training process from a probabilistic view. Extensive experiments are conducted on several action recognition benchmarks, such as Kinetics, Something-Something, and Jester, which consistently verify effectiveness of our approach, and demonstrate that our method can achieve higher performance than state-of-the-art methods with the same backbone.
Open Cluster Chemical Homogeneity throughout the Milky Way

The chemical homogeneity of surviving stellar clusters contains important clues about interstellar medium (ISM) mixing efficiency, star formation, and the enrichment history of the Galaxy. Existing measurements in a handful of open clusters suggest homogeneity in several elements at the 0.03 dex level. Here we present (i) a new cluster member catalog based only on APOGEE radial velocities and Gaia-DR2 proper motions, (ii) improved abundance uncertainties for APOGEE cluster members, and (iii) the dependence of cluster homogeneity on Galactic and cluster properties, using abundances of eight elements from the APOGEE survey for 10 high-quality clusters. We find that cluster homogeneity is uncorrelated with Galactocentric distance, , age, and metallicity. However, velocity dispersion, which is a proxy for cluster mass, is positively correlated with intrinsic scatter at relatively high levels of significance for [Ca/Fe] and [Mg/Fe]. We also see a possible positive correlation at a low level of significance for [Ni/Fe], [Si/Fe], [Al/Fe], and [Fe/H], while [Cr/Fe] and [Mn/Fe] are uncorrelated. The elements that show a correlation with velocity dispersion are those that are predominantly produced by core-collapse supernovae (CCSNe). However, the small sample size and relatively low correlation significance highlight the need for follow-up studies. If borne out by future studies, these findings would suggest a quantitative difference between the correlation lengths of elements produced predominantly by Type Ia SNe versus CCSNe, which would have implications for Galactic chemical evolution models and the feasibility of chemical tagging.
Deep Learning Based Vulnerability Detection: Are We There Yet?

Automated detection of software vulnerabilities is a fundamental problem in software security. Existing program analysis techniques either suffer from high false positives or false negatives. Recent progress in Deep Learning (DL) has resulted in a surge of interest in applying DL for automated vulnerability detection. Several recent studies have demonstrated promising results achieving an accuracy of up to 95 percent at detecting vulnerabilities. In this paper, we ask, “how well do the state-of-the-art DL-based techniques perform in a real-world vulnerability prediction scenario? ” To our surprise, we find that their performance drops by more than 50 percent. A systematic investigation of what causes such precipitous performance drop reveals that existing DL-based vulnerability prediction approaches suffer from challenges with the training data (e.g., data duplication, unrealistic distribution of vulnerable classes, etc.) and with the model choices (e.g., simple token-based models). As a result, these approaches often do not learn features related to the actual cause of the vulnerabilities. Instead, they learn unrelated artifacts from the dataset (e.g., specific variable/function names, etc.). Leveraging these empirical findings, we demonstrate how a more principled approach to data collection and model design, based on realistic settings of vulnerability prediction, can lead to better solutions. The resulting tools perform significantly better than the studied baseline—up to 33.57 percent boost in precision and 128.38 percent boost in recall compared to the best performing model in the literature. Overall, this paper elucidates existing DL-based vulnerability prediction systems’ potential issues and draws a roadmap for future DL-based vulnerability prediction research.
Implications of BREEAM Sustainability Assessment on the Design of Hotels

This original research paper analyses the actual and important topic of the implications of BREEAM sustainability assessment on the design of hotels and it is a personal response to “The Agenda 2030 for Sustainable Development” and its influence on the Tourism and Hospitality Industry. The paper aims to examine the influence of the sustainable assessment method BREEAM on the design of hotels by using seven case studies and studying the changes that were implemented in order to achieve their targets. Qualitative data were obtained by conducting in-depth interviews and analyzing the supplied documentation. The authors notice that the results revealed that a BREEAM approach might limit the design of the hotels but, including the right measures at the early design stage of the project, the target can be easily achieved.
Enrichment of genotyping panels for the genomic selection of special traits in broiler chicken

Enrichment of genotyping panels for the genomic selection of special traits in broiler chicken Traditional animal breeding programs have considerably modified chicken production in Brazil. However, the intensive selection process over the years brought negative consequences in poultry production, such as increased of the abdominal fat deposition, resulting in difficulties in the industrial processing and depreciation of the final product. In recent years, technological advances in molecular genetics and bioinformatics fields have made genomic selection (GS), using molecular markers (Single Nucleotide Polymorphisms SNP), and more recently the whole-genome sequencing (WGS), an important tool to increase the genetic gain in animal breeding, especially for complex traits and traits which are difficult to measure. The aims of this work were to estimate the genetic values and compare the genomic predictions using a high-density SNP panel (HD 600K) and whole-genome sequencing (WGS) dataset through different marker densities. Organs (heart, liver, gizzard and lungs) and carcass (breast, thigh, drumstick) information of 2,000 animals derived from a TT broiler line belonging to the Animal Breeding Program from Embrapa Swine and Poultry were used in further analysis. Subsequently, genomic predictions were performed using pedigreebased BLUP (PBLUP), single-step genomic BLUP (ssGBLUP) and BayesC models using various densities of SNP and variants imputed from whole-genome sequence. Genomic predictions were better when the genomic information was added in the analyses. However, our results showed no benefit of using WGS data compared to HD array data when ssGBLUP or BayesC approaches were applied. Besides that, the use of array data with lower densities (~74,000 SNPs) can provide significant results at a low cost.
On the global homotopy theory of symmetric monoidal categories

Parsummable categories were defined by Schwede as the input for his global algebraic $K$-theory construction. We prove that their whole homotopy theory with respect to the so-called global equivalences can already be modelled by the more mundane symmetric monoidal categories. In another direction, we show that the resulting homotopy theory is also equivalent to the homotopy theory of a certain simplicial analogue of parsummable categories, that we call parsummable simplicial sets. These form a bridge to several concepts of `globally coherently commutative monoids' like global $\Gamma$-spaces and ultracommutative monoids that will be explored in forthcoming work.
Protein Requirement of Yearling White-Tailed Deer

In each of 2 experiments, 6 different yearling white-tailed deer (Odocoileus virginianus) were fed 6 equicaloric concentrate diets with varying crude protein content. Maintenance requirement for protein was computed to be met by a diet containing 5.8 ? 2.0% crude protein (moisture-free basis). Each additional unit of dietary nitrogen resulted in 0.23 ? 0.01 units increase in retained body nitrogen and 0.66 ? 0.03 units increase in urinary nitrogen loss. Metabolic fecal nitrogen component was estimated to be 0.53 g/100 g dry matter consumed. J. WILDL. MANAGE. 43(4):872-879 The white-tailed deer is valued for aesthetics and hunting; this species can live satisfactorily on land not well adapted to agriculture. Urban development and other encroachments often threaten the deer's habitat. For this reason, among many others, more intensive management is needed. Knowledge of the nutritional requirements of various age-classes of deer and the value of natural foods in meeting these requirements is essential. Smith et al. (1975) reported that fawns require 3.05 g digestible nitrogen per kilogram of metabolic weight (Wo.75) per day for maximum growth. This is equivalent to a dietary concentration of 25% crude protein (CP) on a moisture-free basis when the diet is offered ad libitum. Ullrey et al. (1967) found greater body weight gain in male fawns fed a complete pelleted diet with 22% CP than when the diet contained 14% CP (dry matter [DM] basis). Female fawns gained more weight with 14 than with 8.6% CP in the ration; response was not greater when 22% CP was in the diet. Older deer exhibited lower productivity and suboptimum physical development when fed diets containing about 7.8% CP (DM basis) than when protein content was higher (Murphy and Coates 1966). The work of French et al. (1955) and Magruder et al. (1957) suggests that diet DM for deer older than 1 year of age sh uld have about 7 to 8% CP for body weight maintenance and about 14 to 18% CP for "optimum" body weight gain. McEwan and Whitehead (1970) found maintenance digestible nitrogen requirement in reindeer and caribou to be 0.46 g/kgW0.75 Change in gross body weight is not closely correlated with changes in body retention of energy or nitrogen (Holter et al. 1977). Changes in water retention, gut fill, and skeletal mass also affect body weight. Deer may simultaneously gain body protein and lose body fat or vice versa (Thompson et al. 1973, Holter et al. 1977). The objective of these experiments was to study the dietary protein needs of yearling deer in relation to body retention of nitrogen and energy. We gratefully acknowledge the technical support of H. A. Davis, B. Mueller, and T. Kenna, and the statistical advice of W. E. Urban, Jr.
Adverse Childhood Experiences and Risk Behaviours Later in Life: Evidence from SHARE Countries

In this paper we investigate whether exposure to adverse experiences during childhood such as physical and emotional abuse affects the likelihood of unhealthy habits and separately the insurgency of chronic diseases and disabilities later in life. The novelty of our approach consists in exploiting the recently published data on adverse childhood experiences for 19 SHARE countries, which enables us to account for country-specific heterogeneity and investigate the long-run effects of exposure to adverse early-life circumstances on risk behaviour such as smoking, drinking, overweight and obesity. Our results highlight a significant positive effect of exposure to adverse childhood experiences (ACEs) on the probability of unhealthy lifestyles as well as on the insurgency of chronic diseases and disabilities in the long run.
Cognitive-behavioral therapy for hyperphagia in an adult with Prader-Willi Syndrome: pitfalls and challenges Terapia Cognitivo-Conductual para hiperfagia en un adulto con Síndrome de Prader-Willi: obstáculos y retos

Hyperphagia is a typical characteristic in Prader-Willi Syndrome and a clinical problem when not managed appropriately. There is scarce evidence of its treatment. The actual literature targets interventions in well-developed countries, thus leaving a gap for clinical professionals to treat PWS in developing countries where the cultural and socioeconomic conditions are extremely different. The aim of the present study was to assess the effect of cognitive behavioral therapy for hyperphagia within an interdisciplinary treatment conformed by behavioral, pharmacological, dietary and exercise interventions in a 31-year-old Mexican male with Prader-Willi Syndrome and morbid obesity in a developing country context. The main results were the weight of the patient that remained relatively constant, there was a downward trend relevant to his glucose levels, a reduction of his arterial pressure levels, and behavioral changes in regard to exercise that did not maintain overtime. There are considerable limitations inherent to developing country contexts that affect the validity of treatments applied in these settings.
SLANT LIGHTLIKE SUBMANIFOLDS OF AN INDEFINITE SASAKIAN MANIFOLD

We study half lightlike submanifolds of an indefinite Sasakian manifold. The aim of this paper is to prove the following result: If a locally symmetric half lightlike submanifold of an indefinite Sasakian manifold is totally umbilical, then it is of constant positive curvature 1. In addition to this result, we prove three characterization theorems for such a half lightlike submanifold.
MORPHOLOGICAL STUDY OF KIDNEY IN CADAVERS OF WESTERN MAHARASHTRA REGION

Corresponding Author: Dr. Shweta B Shambharkar, Plot No.43/B, Dhadiwal Layout, Suyog Nagar Square, Post: Parwati Nagar, Nagpur, Maharashtra-440027, India. Phone: 9960810368 E-Mail: shambharkar.shweta4@gmail.com The Kidneys are the most important organs responsible for removing excess water, salts and waste products from the blood and for maintenance of blood pH. Dimensions of kidney vary in a large interval from birth to adulthood. Changes in kidney length, parenchymal width (PW), cortex width (CW) or volume can be associated with atherosclerotic renal diseases, arterial hypertension, atherosclerotic renovascular disease, or diabetes mellitus or to be indicative of these. The renal dimensions can also be an indicator for unilateral glomerular filtration rate. The coronal section study of kidney provides good knowledge in cases of chronic renal diseases and renal transplantation. The purpose of this study was to determine the anatomical parameters of the kidney in adults. Weight, length, breadth, maximum anteroposterior thickness, cortical width, parenchymal widths were studied in 100 adult cadaveric kidneys. The data was statistically analysed. No statistical significance was seen with respect to the difference in right and left side. But the differences which are frequently seen i.e. length of left kidney greater than the right was also found in the present study, resulting in greater breadth and thickness on the right side. Males had slightly higher values than females, though not statistically significant. The mean values provided in the study could be of use to surgeons, radiologists and nephrologists.
Dutch University Spin-Offs and the probability to receive governmental funding: a study of entrepreneurial orientation and human capital key determinants

This dissertation analyses the relationship between academic entrepreneurship and the funding of Dutch based University Spin-offs (USO’s) by utilizing a sample of 111 business proposals submitted to a Dutch governmental funding programme. By using the theoretical concepts of entrepreneurial orientation and human capital derived from the prior studies, I develop six hypotheses that relate entrepreneurial orientation and human capital to the likelihood of receiving funding. Binary logistic regressions indicate that USO’s with extensive dynamic capabilities and USO’s that define their project risks and uncertainties are more likely to receive funding. Contrary to my hypothesis the regression analysis also indicate that, USO’s that are non-internationalized and USO’s that show reactive market behaviour, are more likely to receive governmental funding. Graduation Committee Members: Igors Skute, PhD candidate Prof. Dr. Petra de Weerd-Nederhof
Rate of Convergence for Distributed Optimization with Uncertain Communications

We consider the distributed optimization problem for the sum of convex functions where the underlying communications network connecting agents at each time is drawn at random from a collection of directed graphs. Building on an earlier work [15], where a modified version of the subgradient-push algorithm is shown to be almost surely convergent to an optimizer on sequences of random directed graphs, we find an upper bound of the order of $\sim O(\frac{1}{\sqrt{t}})$ on the convergence rate of our proposed algorithm, establishing the first convergence bound in such random settings.