Miracle-dz/UniFAR-FTUs huggingface dataset:
Automatic Structured Abstract for Research Papers Supported by Tabular Format using NLP

The abstract is an extensive summary of a scientific paper that supports making a quick decision about reading it. The employment of a structured abstract is useful to represent the major components of the paper. This, in turn, enhances extracting information about the study. Regardless of the importance of the structured abstract, many computer science research papers do not apply it. This may lead to weak abstracts. This paper aims at implementing the natural language processing (NLP) techniques and machine learning on conventional abstracts to automatically generate structured abstracts that are formatted using the IMRaD (Introduction, Methods, Results, and Discussion) format which is considered as a predominant in medical, scientific writing. The effectiveness of such sentence classiﬁcation, which is the capability of a method to produce an expected outcome of classifying unstructured abstracts in computer science research papers into IMRAD sections, depends on both feature selection and classiﬁcation algorithm. This can be achieved via IMRaD Classifier by measuring the similarity of sentences between the structured and the unstructured abstracts of different research papers. After that, it can be classified the sentences into one of the IMRaD format tags based on the measured similarity value. Finally, the IMRaD Classifier is evaluated by applying Naive Bayes (NB) and Support Vector Machine (SVM) classiﬁers on the same dataset. To conduct this work, we use dataset contains 250 conventional Computer Science abstracts for periods 2015 to 2018. This dataset is collected from two main websites: DBLP and IOS Press content library. In this paper, 200 xml based files are used for training, and 50 xml based files are used for testing. Thus, the dataset is 4x250 files where each file contains a set of sentences that belong to different abstracts but belong to the same IMRaD sections. The experimental results show that Naive Bayes (NB) can predict better outcomes for each class (Introduction, method, results, Discussion and Conclusion) than Support Vector Machine (SVM). Furthermore, the performance of the classifier depends on an appropriate number of the representative feature selected from the text.
Web of Causation between Dietary Patterns and Childhood Obesity: Applying Hill's Criteria

Abstract Since their publication in 1965, the Bradford Hill criteria for causality have been largely used as a framework for causal inference in epidemiology. We aim at employing this classical approach to shed new light onto the web of causation of childhood obesity. Although the fundamental cause of obesity is the long-term imbalance between energetic need and intake, this medical condition is multifactorial in its origin, influenced by genetic, behavioral, socioeconomic, and environmental factors. This imbalance leads to accumulation of excessive adipose tissue. Observational studies tend to mostly quantify association between dietary factors and accumulation of adipose tissue. On the other hand, multivariate analysis proved some of these associations to be spurious, therefore prospective trials are needed to demonstrate causality. Short term experimental studies have been conducted to identify unique dietary pattern changes on specific outcomes, but long term, community-based studies would offer more comprehensive answers on dietary pattern effects. We conducted a literature review on PubMed, Scopus, Web of Science, and Google Scholar. From a total of 323 papers identified at first stage, we further discuss the applicability of Bradford Hill criteria for 31 articles, by examples of dietary patterns and accumulation of excess body fat as exposure-response associations. We also put forward and analyzed the evidence prospective studies would bring, as foundation for future interventions.
Complicated SPG4 presenting with recurrent urinary tract infection

ABSTRACT We present a 62-year-old woman who developed recurrent urinary tract infections in her early fifties and, after an evaluation by an infectious disease physician, was referred for a neurological consultation. Her history and neurological examination were consistent with spastic paraparesis and there was significant family history of a variety of neurological diagnoses suggesting a genetic disorder. Whole exome genetic testing revealed a novel change, a c.508 C > T variant in the SPAST gene. Our genetic and protein modeling analysis suggest that this is a disease-producing mutation confirming the diagnosis of hereditary spastic paraplegia type 4 (SPG4). This patient expands the spectrum of mutations that can cause this disorder and demonstrate the importance of recognizing the role of neurological disorders in causing neurogenic bladder and recurrent urinary tract infections.
Bioactive multifunctional hopeite coatings on new generation SS254 steel by laser rapid manufacturing for bone implant applications

ABSTRACT Overall long-term success of metallic bone implant is mainly governed by the two key factors osseointegration and antibacterial function. Bioceramic hopeite coatings have been proven effective for getting strong osseointegration and antibacterial character. However, deterioration of hopeite coatings during the implantation period can adversely affect their overall biological performance. To overcome this issue, the present research work recommends an innovative process route of laser rapid manufacturing (LRM) for depositing hopeite coatings with good metallurgical bonding. Microstructure, phase composition, microhardness, antibacterial efficacy, and bioactivity were evaluated through Scanning Electron Microscopy (SEM), X-ray diffraction (XRD), a Vickers microhardness tester, Fluorescence-Activated Cell Sorting (FACS) technique, and a Simulated Body Fluid (SBF) immersion test respectively. The promising results obtained from these characterisations and testing establishes the new process route LRM as an effective alternative to deposit multifunctional hopeite coatings on metallic prosthetic-orthopaedic implants.
DEAL – ‘Deep Ensemble ALgorithm’ Framework for Credit Card Fraud Detection in Real-Time Data Stream with Google TensorFlow

ABSTRACT The state-of-the-art Credit Card Fraud Detection (CCFD) systems utilize supervised rule-based schemes to identify fraudulent behaviors in static data. Designing an efficient framework for CCFD is particularly challenging due to the imbalanced distribution of positive and negative classes in data. Conventional works overlook hidden transaction patterns and the performance evaluation methods of algorithm or system. The early models have also been criticized for over-fitting, i.e. models having less prediction accuracy than training or classification accuracy. However, the categorical accuracy is more important than overall accuracy for extremely imbalanced data; most of the previous works do not evaluate their model on the basis of categorical accuracy. In this work, we propose a predictive framework (DEAL) based on novel Deep Ensemble Learning for detecting fraudulent transaction in real-time data stream. The proposed framework is adaptive against data imbalance and robust against latent transaction patterns such as spending behavior. To build the model and predict the fraud, the transactions from real data from a major bank are passed as tensors to ensemble of Deep Learning Network. The adaptive optimization is suggested to minimize the objective function and improve fraud prediction. All Experiments are conducted in Python using scikit-learn, Google TensorFlow, and Keras Deep Learning libraries. The results demonstrate its superiority over state-of-the-art methods in catching frauds. Graphical abstract
The aerobactin iron uptake system in enteropathogenic Escherichia coli: evidence for an extinct transposon

Some enteroinvasive and enteropathogenic (but not enterotoxigenic) strains of Escherichia coli secrete the hydroxamate siderophore aerobactin. The genetic determinants of the aerobactin system in these strains is associated either with plasmids or with the chromosome. Comparative restriction mapping revealed conservation of restriction sites within the aerobactin gene cluster itself but significant divergence in the flanking regions, suggesting mutational loss of a putative transposable element.
Phytase in rations of growing pigs: performance, blood parameters and bone mineral content

Objetivou-se, com o presente trabalho, verificar o efeito da fitase sobre o desempenho, mineralizacao ossea e teor de ureia no plasma de suinos. Foram utilizados 80 animais com 30 ± (3,1 kg), mesticos (LD x LW), machos e femeas, distribuidos em um delineamento em blocos casualisados (DBC) com quatro tratamentos e cinco repeticoes. Os tratamentos consistiram de uma racao a base de milho, farelo de soja e farelo de arroz desengordurado (FAD), suplementada com quatro niveis de fitase (0, 400, 800 e 1200 FTU/kg). A racao foi formulada para atender as exigencias de suinos em crescimento, exceto para calcio e fosforo disponiveis, cujos niveis foram 0,64 e 0,25 %, respectivamente. A enzima fitase utilizada foi a Natuphos 5000. Durante o periodo experimental, a cada sete dias, foi coletado sangue de dois animais por bloco, por meio de uma puncao no sinus orbital, para determinar o teor de ureia no plasma. Ao final do periodo experimental, foram abatidos dois animais por parcela para coleta do osso metacarpo, objetivando verificar o teor de minerais. As variaveis analisadas foram: ganho de peso medio diario (GPMD), consumo de racao medio diario (CRMD), conversao alimentar (CA), teor de ureia no plasma e teor de cinzas, calcio, fosforo no osso. Os niveis de fitase proporcionaram uma melhoria linear (P<0,05) da conversao alimentar e um efeito quadratico sobre o teor de ureia no plasma dos suinos. A fitase promoveu aumento linear (P<0,05) no teor de calcio e fosforo no osso metacarpo dos suinos. O nivel de 750 FTU/kg proporcionou o menor teor de ureia no plasma. Conclui-se que a utilizacao da enzima fitase em racoes para suinos em crescimento melhorou a conversao alimentar, diminuiu o teor de ureia no plasma e aumentou os teores de calcio e fosforo no osso.
Effects of CO2-driven acidification on the ostracod Cypridopsis vidua: what are its likely environmental consequences?

Abstract If anthropogenic CO2 emissions are maintained at the current rate, the pH of freshwater ecosystems will drop by 0.2–0.3 pH units by the year 2100, which will have great effects on aquatic biota. The impact of acidification on the ostracod species Cypridopsis vidua as a model organism has been studied. To provide the best rearing conditions, a preliminary experiment with different food concentrations was performed. Cypridopsis vidua reached higher survival under the established experimental conditions when reared with 1.5 × 106 cells of Scenedesmus obliquus per ostracod. Two CO2-driven acidification experiments were designed: the first, an acute experiment (96 hours) pH 6.0, 6.5, 7.0 and 8.3 showed that at low pH the survival rate decreased by more than 90%. The second was a chronic experiment (21 days) pH 7.3, 7.8 and 8.3 with a sharp decrease (60%) in reproduction rate and effects on phototactic behaviour at low pH. Abbreviations: CCAP: culture collection of algae and protozoa (in the Scottish Association for Marine Science); CR1: chronic test at medium pH (7.78 ± 0.11); CR2: chronic test at low pH (7.30 ± 0.16); GLM: generalized linear model; IPCC: intergovernmental panel on climate change; LT: lethal time; TA: total alkalinity; pCO2: partial pressure of carbon dioxide; PI: phototactic index; R0: treatment in starvation (no food); R1: low food concentration treatment (7.5 × 105 cell per individual); R2: optimal food concentration treatment (1.5 × 106 cell per individual); R3: high food concentration treatment (3.0 × 106 cell per individual); UTM: universal transverse mercator (coordinate system); YSI: yellow spring instruments
Diet effect on nitrogen partitioning and isotopic fractionation (δ15N) in ruminants

II ACKNOWDLEGEMENTS V TABLE OF CONTENTS . VI LIST OF TABLES . IX LIST OF FIGURES XI LST OF COMMONLY USED TERMS XII CHAPTER 1: INTRODUCTION 1 CHAPTER 2: LITERATURE REVIW 3 2.1. The importance of studying nitrogen metabolism and partitioning in ruminants 3 2.1. 1. Nitrogen metabolism in the rumen 3 2.1. 2. Nitrogen metabolism and partitioning in ruminant body 5 2.1. 3. Major factors influencing nitrogen partitioning 8 2.2. Current methods for measuring and predicting nitrogen partitioning 12 2.2.1. Nitrogen balance 12 2.2.2. Urea nitrogen 13 2.2.3. Prediction of urinary nitrogen output 15 2.3. Use of nitrogen isotopic fractionation to indicate nitrogen partitioning 16 2.3. 1. The principle of nitrogen isotopic fractionation 16 2.3. 2. Nitrogen isotopic fractionation in animal body 17 2.3. 3. Nitrogen isotopic fractionation in ruminant body 18 2.3. 4. Nitrogen isotopic fractionation in relation to nitrogen partitioning 19
Redefining sad music: Music’s structure suggests at least two sad states

Many researchers have noted inconsistencies between descriptions and effects of nominally sad music. The current study addresses whether traditional music-related sadness can be broken down into more than one category. Melancholic and grieving musical passages were collected in three stages. Participants with superior aural skills rated 18 structural parameters of these musical passages on 7-point unipolar scales. The results are consistent with the idea that musical parameters differ in melancholic and grieving states and that what has been previously defined as sad music may, in fact, be conflating more than one emotional state.
THE DEVELOPMENT OF ROOT HAIRS BY ELODEA CANADENSIS

IT is characteristic of a number of water plants that they produce roots which are hairless in water but develop hairs when they penetrate the mud. Although this phenomenon has given rise to much speculation in the past no satisfactory reason has as yet been advanced to explain the hairless condition of the roots in water. In the present investigation an experimental and microchemical attack on this problem has been undertaken. Elodea canadensis was chosen as the experimental material not only because it has been studied to some extent in the past but because it is of common occurrence and produces abundant roots under normal conditions. Preliminary studies established the fact that the roots are perfectly hairless in water but that once they penetrate the mud hairs are abundantly produced. Figs. I-3 represent strips of epidermis removed from various roots after warming with dilute ammonia, and illustrate the occurrence of special preformed hair-producing cells scattered haphazardly over the surface of the root. They are shorter than the neighbouring epidermal cells, and are distinguishable also by the greater density of their protoplasm. Fig. i, from the meristematic region of a root growing in the soil, illustrates clearly the difference between the two types of cell. Fig. 2 is from the mature region of the same root, the circles representing the bases of root hairs. Fig. 3 is from the mature region of a root growing free in water. Such roots were always hairless, and their short cells are generally much longer than the haired cells of the soil roots. Though hairless they are clearly distinguishable from neighbouring long cells in the same region. In the older regions of the root they are not so easily recognized. Such cells were first reported on Elodea roots by Schwarz (I883) and Sauvageau (I889). The former failed to produce root hairs by
Mass spectrometry-based metabolomics in biomarker-assisted drug discovery and oxidative stress research

Biomarker-assisted drug discovery is a major step in identification of drug efficacy and disease proliferation of both communicable and noncommunicable diseases. Biomarker-assisted drug discovery using metabolomics approach is now a reliable “path of opportunity” in drug discovery, as it offers precise insight into the efficacy of tested drug in the biological setup. With the advent of recent advances in instrumentation, accuracy and specificity of biomarker-based drug discovery program is improved. A key challenge in biomarker discovery is the choice of detection method, as diverse metabolites present in the physiological system pose varying levels of detection response with different instrumentation platforms. In biomarker-assisted early diagnosis, mass spectrometry-based metabolomics has a major advantage due to its capability of wide metabolite range coverage with great specificity. This review also discusses the advantage of biomarker-assisted discovery using metabolome analysis.
An E-Learning based Recommendation System for Semantic Web: A Survey

: The recommender systems are the technique of processing and evaluation of user behavioral data in order to suggest the resources according to user needs. In e-learning system, it is actually used to suggest resources and relevant contents to learners. Thus e-Learning recommender system is a technique to identify requirements of learner to provide relevant learning content. In this paper current state-of-art for the e-learning recommendation system is reviewed. In addition of that recent research work in the direction of enhancing the user’s experience in online learning is also reported.
Complications of leadless vs conventional (lead) artificial pacemakers – a retrospective review

ABSTRACT Background: Leadless pacemakers (LPM) are introduced in cardiovascular market with a goal to avoid lead- and pocket-associated complications due to conventional artificial pacemakers (CPM). The comparison of LPM and CPM complications is not well studied at a case by case level. Methods: Comprehensive literature was searched on multiple databases performed from inception to December 2019 and revealed 204 cases that received LPM with a comparison of CPM. The data of complications were extracted, screened by independent authors and analyzed using IBM SPSS Statistics for Windows, Version 22.0 (Armonk, NY: IBM Corp.). Results: The complications of CPM were high in comparison to LPM in terms of electrode dislodgement (56% vs 7% of cases, p-value < .0001), pocket site infection rate (16% vs 3.4%, p-value = 0.02), and a lead fracture rate (8% vs 0%, p-value = 0.04). LPMs had a statistically non-significant two-times high risk of pericardial effusion (8%) compared to CPMs (4%) with a p-value = 0.8. Conclusion: LPMs appear to have a better safety profile than CPMs. There was a low pocket site and lead-related infections in LPM as compared to CPM. However, LPM can have twice the risk of pericardial effusion than CPMs, but this was not statistically significant.
Wireless and Computing Resource Allocation for Selfish Computation Offloading in Edge Computing

We consider the problem of allocating wireless and computing resources to a set of autonomous wireless devices in an edge computing system. Devices in the system can decide whether or not to use edge computing resources for offloading computing tasks so as to minimize their completion time, while the edge cloud operator can allocate wireless and computing resources to the devices. We model the interaction between devices and the operator as a Stackelberg game, prove the existence of Stackelberg equilibria, and propose an efficient decentralized algorithm for computing equilibria. We provide a bound on the price of anarchy of the game, which also serves as an approximation ratio bound for the proposed algorithm. Our simulation results show that the joint allocation of wireless and computing resources by the operator can halve the completion times compared to a system with static resource allocation. At the same time, the convergence time of the proposed algorithm is approximately linear in the number of devices, and thus it could be effectively implemented for edge computing resource management.
Editorial

The study of purchase intentions is a critical issue for marketing practitioners (Akturan & Bozbay, 2018). Analyzing market trends is crucial to understand customer preferences, and it can determine a business’s strategic orientation and performance (Cacciolatti & Lee, 2016). Regarding the massive importance of marketing for firms, there is a new approach that encourages a kind of product promotion that is more sensitive to the environment, namely cause-related or social marketing (Srivastava, 2019). However, whatever the marketing strategy, like the corporate strategy, the ultimate goal is to achieve good performance and grow the business (Akturan & Bozbay, 2018). Marketing has traditionally been studied within the field of psychology. The psychology literature uses different theories to try to explain customer behavior, but one of the most widely agreed views is that of self-regulation (Higgins, 1997). This view proposes two different forms of customer orientation: promotion focus and prevention focus. Promotion is the orientation of customers who look for positive outcomes. In contrast, prevention is the orientation of customers who look to avoid negative outcomes (Fazeli, Shukla, & Perks, 2020). Thus, in the search for promotion objectives, firms try to become international or global brands because they are linked to quality and prestige (Johansson & Ronkainen, 2005). This is one reason why entrepreneurs usually aspire to grow, and this aspiration is enhanced by the acquisition of new and non-redundant knowledge (Estrin, Korosteleva, & Mickiewicz, 2019). The current special issue focuses on consumer attitudes, that is, the strategies undertaken by ventures to promote their products, taking special consideration of consumer perceptions and the impact that business decisions have not just on customers in general but also on specific groups of customers. The selection of papers in this special issue is based on a study and review of the papers presented at the 2019 conference “Knowledge, Business, and Innovation. Economies and sustainability of future growth,” which was held in Verona (Italy). Below, a short description of each paper is given.