Miracle-dz/UniFAR-FTUs huggingface dataset:
Nutritional analysis of some common avian edible eggs of district Anantnag (Jammu and Kashmir)

It is a well-established fact that apart from topography, there are some other variables (e.g., Size and weight) which determine the nutritional values of an egg. It is an established and well proven fact that, the age of a hen is directly proportional to the increase in the size of eggs. Furthermore, the size of an egg is inversely proportional to the amount of yolk present in an egg i.e. smaller the size of an egg larger the amount of yolk and larger the size of an egg, smaller the amount of yolk. With increase in age of hens, there is subsequent decrease in the egg shape index. With interaction of breed with age, the traits of egg shell may be affected. Materials and Methods: Different types of avian edible eggs as unfertile, white double yolked, desi and organic eggs were obtained from local poultry farm from District Anantnag Jammu and Kashmir. These eggs were subjected to different types of analyses and experimentation. Invitro digestion was done and then they were freeze dried at -70°C till further experimentation. Protein estimation was done by Hatree Lowry method (1951), Cholesterol test was done by Liebermann-Burchard method, sodium and potassium were determined by flame photometer, Free radical scavenging activity was determined by DPPH based on the method given by Brand Williams 1995 and ABTS by Re et.al.,1999. Zinc (Zn) Iron (Fe) and Calcium (Ca) were determined by Atomic Ab sorption Spectroscopy (AAS). Results: After lab. Experimentation it was proven that, double yolked eggs have highest weight of average 68.02 gms followed by organic eggs 60.58 gms, desi eggs, 60.30 gms and Unfertilized eggs 55.05gms respectively. Double yolked egg was found with highest protein content of 10.5 mg/ml followed by organic Eggs with 8.05mg/ml, unfertilised eggs with 7.87mg/ml and desi eggs with 7.67 mg/ml respectively. Highest amount of cholesterol was found in double yolked eggs with 8.01 ± 0.005 mg/ ml. Highest amount of zinc and calcium 0.17 mg/l and 3.03mg/l respectively was found in unfertilised eggs. Strong antioxidant activity and scavenging activity was found in desi eggs with 13. 09μmol/l and 62. 11μmol/l respectively. Conclusion: After our experimentation it can be concluded that eggs are rich in nutrients, Minerals and are loaded with high scavenging and antioxidant properties. Eggs can be used as supplement food stuffs, Therapative foods and can be used by different food industries in different aspects to explore many more things.
Communicative Behavior and Speech Perception of Social Media Actors: A Neural Network Approach

The paper concerns the analysis of the residents’ attitude towards the construction of the chord ring in Moscow, as well as the identification of digital conflictogenic zones and predictive analytics. The material for the study was network data collected during the period from 1.07. 2019 00:00 to 31.12. 2019 23:59. To interpret the data, neural network text analysis, analysis of lexical associations, content analysis and sentiment analysis were used. As a result, digital conflictogenic zones were identified; users’ perception of each facility was characterized; the risks of protests in the virtual and real space during the project implementation were assessed.
IMPACT OF DIVIDEND PAYOUT ON THE FIRM VALUE: A STUDY OF FIRMS LISTED ON NATIONAL STOCK EXCHANGE

-----------------------------------ABSTRACT----------------------------------Maximization of firm value or shareholders wealth maximization is the prime objective of a firm. As the dividend payout decision is one of the important decisions, its impact on the firm value has been widely studied and researched topic in the area of corporate finance. In the present study the impact of dividend payout on the value of the firm has been examined on the sample of Nifty-100 index firms. Along with the Dividend Payout(DPR), Current year’s profit(CPR), Size(SIZE), Leverage(LEV), Growth Opportunities(GWOP), Market risk(Beta), PriceEarnings(PE) ratio and Age(AGE) have been considered in the model as independent variables. The result shows that, dividend payout positively related but not significantly influence on the value of the firm. Whereas, The Current year’s profit (CPR), Size (SIZE), Growth Opportunities (GWOP) and Price-Earnings (PE) are the variables significantly influence on the value of the firm.
Fe3O4@SiO2@TiO2@Pt Hierarchical Core-Shell Microspheres: Controlled Synthesis, Enhanced Degradation System, and Rapid Magnetic Separation to Recycle

Magnetic composite microspheres consisting of a SiO2-coated Fe3O4 core, an ordered TiO2 hierarchically structured shell, and a Pt nanoparticle layer dispersed on the surface of the TiO2 nanoplatelets have been successfully synthesized using a facile and efficient method. The shells of TiO2 hierarchical microspheres were assembled from nanoplatelets, which exposed the high-energy {001} facets, and the Pt nanoparticles were evenly deposited on the surface of the TiO2 nanoplatelets, with a concentration of ∼1 wt %. The resulting composite microspheres exhibited flower-like hierarchical structures with a 202.42 m2 g–1 surface area and possessed superparamagnetic properties with a high saturation magnetization of 31.5 emu g–1. These features endow the obtained composite microspheres with a high adsorption capacity and strong magnetic responsivity that could be easily separated by an external magnetic field. The high photocatalytic activity toward Rhodamine B (RhB) degradation may be caused by the hierarchicall.
The kinetics, thermodynamics and equilibrium study of nickel and lead uptake using corn residues as adsorbent

Agricultural residues rich in lignocellulosic biomass are low-cost and sustainable adsorbents widely used in water treatment. In the present research, thermodynamics, kinetics, and equilibrium of nickel(II) and lead(II) ion biosorption were studied using a corncob (Zea mays). The experiments were performed in a batch system evaluating the effect of temperature and dose of adsorbent. Langmuir and Freundlich isotherms were used to study the equilibrium. Thermodynamic and kinetic parameters were determined using kinetic models (pseudo-first order, pseudo-second order, Elovich). Biosorbent characteristics were studied by Fourier-transform infrared spectroscopy, Scanning Electron Microscopy and Energydispersive X-ray spectroscopy. It was found that the hydroxyl, carboxyl, and phenolic groups are the major contributors to the removal process. Besides, Pb(II) ions form micro-complexes on the surface of the biomaterial while Ni(II) ions form bonds with active centers. It was found that the highest Ni(II) removal yields were achieved at 0.02 g of adsorbent and 70°C, while the highest Pb(II) removal yields were achieved at 0.003 g and 55°C. A maximum Ni(II) adsorption capacity of 3.52 mg∙g (86%) and 13.32 mg∙g (94.3%) for Pb(II) was obtained in 250 and 330 min, respectively. Pseudo-first order and pseudo-second order models best fit experimental data, and Langmuir and Freundlich models well describe the isotherm of the process. Thermodynamic parameters (∆H0, ∆G0, ∆S0) suggest that the adsorption process of both cations is exothermic, irreversible, and not spontaneous.
Pathomorphology In Subclinical Brucellosis

Brucellosis is an acute and chronic infectious disease of many animal species and humans.The variety of forms and brucellosis course still amaze researchers studying the problems of this disease. Changing conditions for keeping animals in the intensification direction and concentrated keeping, feeding animals with feed treated with various chemical and bacterial preparations, changes in the ecological atmosphere conditions lead to a change in the resistance and many other properties of pathogenic microorganisms causative agents of infectious animal diseases, and, accordingly, the clinical manifestation of the disease and its consequences can also change.
Substantial Differences in SARS-CoV-2 Antibody Responses Elicited by Natural Infection and mRNA Vaccination

: We analyzed data from two ongoing serologic surveys, a longitudinal cohort of health care workers (HCW) from the University of California Irvine Medical Center (Orange County, CA, USA), collected from May and December 2020 through March 2021, and a cross sectional county-wide study in July 2020 (actOC; Orange County, CA) and a more focused community study in the city of Santa Ana (Santa Ana Cares; Orange County, CA, USA), collected in December 2020 - in order to compare the antibody responses to SARS-CoV-2 natural infection and vaccination. In addition, we serially tested 9 volunteers at multiple time points to analyze the time course of vaccine-induced antibody response in more detail. In May 2020, 1060 HCW were enrolled and had finger stick samples collected. Finger stick samples were again collected in December 2020, before vaccination, as well as January, February and March 2021 during vaccination campaign. A total of 8,729 finger stick blood specimens were probed and analyzed for IgG and IgM antibodies using a coronavirus antigen microarray (COVAM). The microarray contained 10 SARS-CoV-2 antigens including nucleocapid protein (NP) and several varying fragments of the spike protein, as well as 4 SARS, not present in the vaccine and can be used as a biomarker of past exposure. The results show that naturally-exposed individuals mount a stronger anti-spike response upon vaccination than individuals that were not previously exposed. Longitudinal specimens taken at approximately weekly intervals from 9 individuals show variation in the response to the mRNA vaccine, with some showing a vigorous response to the first dose (prime) and others requiring a subsequent dose (boost) to reach high anti-SARS-CoV-2 levels. Antibody titers determined by serial dilution of the specimens were used to accurately compare antibody levels in these samples. mRNA vaccinees after the boost have higher Ab titers (up to 10 times higher) than convalescent plasmas from donors who recovered from natural infection. The results of this study exemplify the time course and outcomes expected from similar mRNA mass vaccination campaigns conducted in other institutions.
The superconformal index of theories of class S

We review different aspects of the superconformal index ofN = 2 superconformal theories of class S. In particular we discuss the relation of the index of class S theories to topological QFTs and integrable models, and review how this relation can be harnessed to completely determine the index. This is part of a combined review on 2d-4d relations, edited by J. Teschner.
SQL Generation from Natural Language: A Sequence-to-Sequence Model Powered by the Transformers Architecture and Association Rules

: Using Natural Language (NL) to interacting with relational databases allows users from any background to easily query and analyze large amounts of data. This requires a system that understands user questions and automatically converts them into structured query language such as SQL. The best performing Text-to-SQL systems use supervised learning (usually formulated as a classification problem) by approaching this task as a sketch-based slot-filling problem, or by first converting questions into an Intermediate Logical Form (ILF) then convert it to the corresponding SQL query. However, non-supervised modeling that directly converts questions to SQL queries has proven more difficult. In this sense, we propose an approach to directly translate NL questions into SQL statements. In this study, we present a Sequence-to-Sequence (Seq2Seq) parsing model for the NL to SQL task, powered by the Transformers Architecture exploring the two Language Models (LM): Text-To-Text Transfer Transformer (T5) and the Multilingual pre-trained Text-To-Text Transformer (mT5). Besides, we adopt the transformation-based learning algorithm to update the aggregation predictions based on association rules. The resulting model achieves a new state-of-the-art on the WikiSQL DataSet, for the weakly supervised SQL generation.
The Agile Success Model

Organizations are increasingly adopting Agile frameworks for their internal software development. Cost reduction, rapid deployment, requirements and mental model alignment are typical reasons for an Agile transformation. This article presents an in-depth field study of a large-scale Agile transformation in a mission-critical environment, where stakeholders’ commitment was a critical success factor. The goal of such a transformation was to implement mission-oriented features, reducing costs and time to operate in critical scenarios. The project lasted several years and involved over 40 professionals. We report how a hierarchical and plan-driven organization exploited Agile methods to develop a Command & Control (C2) system. Accordingly, we first abstract our experience, inducing a success model of general use for other comparable organizations by performing a post-mortem study. The goal of the inductive research process was to identify critical success factors and their relations. Finally, we validated and generalized our model through Partial Least Squares - Structural Equation Modelling, surveying 200 software engineers involved in similar projects. We conclude the article with data-driven recommendations concerning the management of Agile projects.
Food Ingredients Identification from Dish Images by Deep Learning

Diet plays an important role in people’s daily life with its strong correlation to health and chronic diseases. Meanwhile, deep based food computing emerges to provide lots of works which including food recognition, food retrieval, and food recommendation, and so on. This work focuses on the food recognition, specially, the ingredients identification from food images. The paper proposes two types of ways for ingredient identification. Type1 method involves the combination of salient ingredients classifier with salient ingredient identifiers. Type 2 method introduces the segment-based classifier. Furthermore, this work chooses 35 kinds of ingredients in the daily life as identification categories, and constructs three kinds of novel datasets for establishing the ingredient identification models. All of the classifiers and identifiers are trained on Resnet50 by transfer learning. Many experiments are conducted to analyze the effectiveness of proposed methods. As the results, Salient ingredients classifier predict one ingredient and achieves 91.97% on test set of salient ingredients dataset and 82.48% on test dish image dataset. Salient ingredients identifiers predict remained ingredients and achieve mean accuracy of 85.96% on test dish image dataset. Furthermore, Segment-based classifier achieves 94.81% on test set of segment-based ingredients dataset.
New Statistical Learning Methods for Personalized Medical Decision Making

Xuan Zhou: New Statistical Learning Methods for Personalized Medical Decision Making (Under the direction of Donglin Zeng and Yuanjia Wang) This research focuses on developing new and computationally efficient statistical learning methods for multicategory classification and personalized medical decision making. Motivated by the challenge of multicategory classification problems, and the computational efficiency and theoretical properties of support vector machines (SVM), a novel learning algorithm is proposed. The method is then adapted to estimating multicategory individualized treatment rules by connecting with outcome weighted learning (Zhao et al., 2012). At last, an application to Electronic Health Record data is explored. The proposed algorithm, forward-backward SVM (FB-SVM) is based on a sequential binary classification algorithm and relies on support vector machines for each binary classification and utilizes only feasible data in each step. Therefore, the method guarantees convergence and entails light computational burden. More importantly, we prove the theoretical property of Fisher consistency of the classification rule derived from the FB-SVM, which is not guaranteed by existing algorithms. We also obtain the risk bound for the predicted misclassification rate. We conduct extensive simulation and application studies, using popular benchmarking data and data from a newly completed realworld study, to demonstrate that the proposed method has superior performance, in terms of low misclassification rates and significantly improved computational speed when compared to existing methods. Furthermore, we generalize the proposed FB-SVM with outcome weighted learning to estimate optimal individualized treatment rule (ITR) with multiple options of treatment, namely sequential outcome-weighted learning (SOM). Specifically, we solve a multicategory treatment selection problem via sequential weighted support vector machines. Theoretically, we show that the resulting ITR is Fisher consistent. We demonstrate the performance of proposed method with extensive simulations.
Interacting with virtual instructors: The effect of gender and years of study on the perception of in‐game instructors

Previous research has shown that student‐instructor interaction is vital to motivating students to learn a second language. However, it is unclear whether learners' demographics affect in‐game immersion and interactions with virtual instructors. This study's purpose is to investigate whether the number of years learning Japanese (foreign language familiarity) influences students' immersion levels in serious games and their interactions with virtual instructors. We developed a 3D animated Japanese roleplaying game with a virtual in‐game instructor. Eighty‐four college students enrolled in 200‐ and 300‐level Japanese language courses voluntarily participated in the study. Participants played the game and then answered a questionnaire concerning virtual character appearance, attentiveness to the instructor, and immersion in the game. The findings indicated that gender and the number of years studying Japanese significantly impact multiple measurements.
Weighted Random Sampling – Alias Tables on the GPU

An alias table is a data structure that allows for efficiently drawing weighted random samples in time in O(1). The PSA algorithm by Hübschle-Schneider and Sanders is able to construct alias tables in parallel on the CPU. In this thesis, we develop a construction algorithm for GPUs that is based on the idea of PSA. Our algorithm specifically fits the architectural properties of GPUs. It achieves a speedup of 34 on a GPU in comparison to the 4-threaded PSA method on a consumer grade CPU. Our implementation of the PSA+ method achieves an additional speedup of up to 1.4 to our PSA implementation. Being faster than the CPU method even when including memory transfers to the GPU and back, our method can be used to offload the construction efficiently. For sampling, we achieve an up to 56 times higher throughput on a consumer GPU than Hübschle-Schneider and Sanders on the CPU.
UniK-QA: Unified Representations of Structured and Unstructured Knowledge for Open-Domain Question Answering

We study open-domain question answering with structured, unstructured and semi-structured knowledge sources, including text, tables, lists and knowledge bases. Departing from prior work, we propose a unifying approach that homogenizes all sources by reducing them to text and applies the retriever-reader model which has so far been limited to text sources only. Our approach greatly improves the results on knowledge-base QA tasks by 11 points, compared to latest graph-based methods. More importantly, we demonstrate that our unified knowledge (UniK-QA) model is a simple and yet effective way to combine heterogeneous sources of knowledge, advancing the state-of-the-art results on two popular question answering benchmarks, NaturalQuestions and WebQuestions, by 3.5 and 2.6 points, respectively. The code of UniK-QA is available at: https://github.com/facebookresearch/UniK-QA.
Mobile Payment Adoption And Customer‟s Attitude

This research aimed to investigate the relationship between customer’s attitude and mobile payment among Malaysian customers. There are three research objectives. First to identify the consumers’ related issues which effect the mobile payments among Malaysian Customer. Second objective is to investigate the relationships between, payment culture, ease of use, usefulness and security. finally, to identify the main consumers’ concern that influencing the mobile payment feasibility in Malaysia. In this research, the researcher carried out a survey among the young public to access the performance of mobile payment services available in Malaysia. Besides, the direct opinion from the consumers is able to enhance the insight of the service providers. In conclusion, mobile payment feasibility is important to realize Bank Negara Malaysia (BNM) strategy which is Malaysia becomes a cashless society by 2050.
Sampling-based Motion Planning for Uncertain Nonlinear Systems via Funnel Control

—We integrate sampling-based planning techniques with funnel-based feedback control to develop KDF, a new framework for solving the kinodynamic motion-planning problem via funnel control. The considered systems evolve subject to complex, nonlinear, and uncertain dynamics (aka differential constraints). Firstly, we use a geometric planner to obtain a high-level safe path in a user-deﬁned extended free space. Secondly, we develop a low-level funnel control algorithm that guarantees safe tracking of the path by the system. Neither the planner nor the control algorithm use information of the underlying dynamics of the system, which makes the proposed scheme easily distributable to a large variety of different systems and scenarios. Intuitively, the funnel control module is able to implicitly accommodate the dynamics of the system, allowing hence the deployment of purely geometrical motion planners. Extensive computer simulations and experimental results with a 6 -DOF robotic arm validate the proposed approach.
CSR-HRM Nexus: Defining the Role Engagement of the Human Resources Professionals

The study explores the nexus between CSR and HRM and defines the role engagement of the HR professionals in CSR initiatives. Literature reviewed reveals that CSR is a triple bottom line (economic, social and environmental) performance and essentially a top-management driven activity, devoid of employees’ participation. The latter characteristic of CSR is classical and tends to impede implementation process. However, a new dawn of CSR is now advocated to reposition HR professionals as strategic business partners to enhance the successful packaging and execution of CSR programs. The paper defines the role engagement of the HR professionals vis a vis CSR activities to include among others, leading and educating employees on the value of CSR, developing responsible and sustainable practices, communicating CSR activities to employees and other stakeholders, and providing direction, control and action plans for implementing the program in the organization. Finally, the study affirms the existence of the nexus between the two concepts and charges management to see the nexus as a strategic business decisions to unlock the human capital of an