Miracle-dz/UniFAR-FTUs huggingface dataset:
Numerical Properties of Spherical and Cubical Representative Volume Elements with Different Boundary Conditions

It has been found that, due to the smaller surface to volume ratio, the spherical representative volume elements (RVE) converge faster to the effective properties than cubical RVEs, in terms of the RVE volume (Gl ̈ ge et al., 2012). It remains to discuss whether one can actually draw a numerical advantage from this in the finite element calculations, since there are also some drawbacks, for example the necessarily irregular meshing. It has been demonstrated that the boundary conditions, in conjunction with different solution strategies for the linear system that emerges in the FEM, can significantly influence the numerical expense (Fritzen and B öhlke, 2010a). In the light of these results, we examine the numerical properties of spherical and cubical RVEs with linear displacement and periodic (resp. antipodic) boundary conditions.
A Multidimensional Dataset Based on Crowdsourcing for Analyzing and Detecting News Bias

The automatic detection of bias in news articles can have a high impact on society because undiscovered news bias may influence the political opinions, social views, and emotional feelings of readers. While various analyses and approaches to news bias detection have been proposed, large data sets with rich bias annotations on a fine-grained level are still missing. In this paper, we firstly aggregate the aspects of news bias in related works by proposing a new annotation schema for labeling news bias. This schema covers the overall bias, as well as the bias dimensions (1) hidden assumptions, (2) subjectivity, and (3) representation tendencies. Secondly, we propose a methodology based on crowdsourcing for obtaining a large data set for news bias analysis and identification. We then use our methodology to create a dataset consisting of more than 2,000 sentences annotated with 43,000 bias and bias dimension labels. Thirdly, we perform an in-depth analysis of the collected data. We show that the annotation task is difficult with respect to bias and specific bias dimensions. While crowdworkers' labels of representation tendencies correlate with experts' bias labels for articles, subjectivity and hidden assumptions do not correlate with experts' bias labels and, thus, seem to be less relevant when creating data sets with crowdworkers. The experts' article labels better match the inferred crowdworkers' article labels than the crowdworkers' sentence labels. The crowdworkers' countries of origin seem to affect their judgements. In our study, non-Western crowdworkers tend to annotate more bias either directly or in the form of bias dimensions (e.g., subjectivity) than Western crowdworkers do.
Training Deep Learning Recommendation Model with Quantized Collective Communications

Deep Learning Recommendation Model (DLRM) captures our representative model architectures developed for click-through-rate (CTR) prediction based on high-dimensional sparse categorical data. Collective communications can account for a significant fraction of time in synchronous training of DLRM at scale. In this work, we explore using fine-grain integer quantization to reduce the communication volumn of alltoall and allreduce collectives. We emulate quantized alltoall and allreduce , the latter using ring or recursive-doubling and each with optional carried-forward error compensation. We benchmark accuracy loss of quantized alltoall and allreduce with a representative DLRM model and Kaggle 7D dataset. We show that alltoall forward and backward passes, and dense allreduce can be quantized to 4 bits without accuracy loss compared to full-precision training.
African buffalo diet in a woodland and bush-dominated biome as determined by stable isotope analysis : short communication

We examined the importance of browse and grazing in the diet of 28 African buffalo Syncerus cafferl/Ig from Chobe National Park, Botswana, through analysis of stable isotope ratios of tooth collagen. Carbon isotope levels indicated that the assimilated diet was wholly dominated by grasses. Variations in nitrogen isotope values were consistent with variation in individual <SPAN lang=AF style="FONT-FAMILY: Symbol; mso-ascii-font-family: 'Times New Roman'; mso-hansi-font-family: 'Times New Roman'; mso-char-type: symbol; mso-symbol-font-family: Symbol"><SPAN style="mso-char-type: symbol; mso-symbol-font: Symbol">d 13 C values being due to variations in the small proportion of non-grasses in the diet. There were no significant sex differences in diet.
Security Enhancement in Personalized Web Search

: For clients with individual data objectives, web personalization is utilized to enhance look up quality by altering query items, in view of the individual information of client shared to the web search tool. Clients are not happy with uncovering private inclination data to web crawlers, yet in the event that there is gain in search quality or productivity then protection can be traded off. Accordingly, there ought to be a harmony between the inquiry quality and security assurance. Security assurance can be achieved by using hierarchical client profile model in PWS applications. A PWS framework called UPS that can adaptively generalize profiles by queries when the client specifies privacy requirements. Runtime generalization aims at striking a harmony between predictive metrics that evaluate the average precision of information and the privacy risk of exposing the generalized profile. Offline generalization and online generalization algorithm are used for static and runtime generalization. Online prediction mechanism is used for deciding personalizing a query is beneficial. Discriminating power is used for the prediction of generalization decision. It also considers the preferences of interest mentioned in user profile and sensitivity of information defined by user while generalizing the user Profile. Session attacks like hijacking, eavesdrops, injections are controlled.
Bug Triaging Mechanism for Non-Reproducible Bugs

—Programming organizations spend more than 45 percent of cost in managing programming bugs. An unavoidable stride of settling bugs is bug triage, which means to effectively appoint a designer to another bug. To diminish the time cost in manual work, content order procedures are connected to lead programmed bug triage. In this paper, we address the issue of information decrease for bug triage, i.e., how to lessen the scale and enhance the nature of bug information. We consolidate occurrence determination with include choice to at the same time diminish information scale on the bug measurement and the word measurement. To decide the request of applying case choice and highlight determination, we separate characteristics from recorded bug informational collections and construct a prescient model for another bug informational collection. We observationally research the execution of information lessening on absolutely 600,000 bug reports of two huge open source ventures, in particular Eclipse and Mozilla. The outcomes demonstrate that our information decrease can adequately diminish the information scale and enhance the precision of bug triage.
Genetic Panels in Breast Cancer: Current Guidelines

The breast is the most frequent site of cancer among women in both developed and in developing countries [1]. Breast cancer is the most frequent cause of cancer death in women from less developed countries and second most frequent (after lung cancer) among women in developed countries [1]. It is increasing in incidence in the developing world due to increased life expectancy, increased urbanization and the adoption of western lifestyles [2]. According to the World Health Organization (WHO), “Early detection in order to improve breast cancer outcome and survival remains the cornerstone of breast cancer control” [2]. Breast cancer staging also takes into account cancer's grade; the presence of tumor markers, such as receptors for estrogen, progesterone and HER2; and proliferation factors.Standard screening for new and recurrent breast cancer involves clinical breast exam and breast imaging. Given the recognized differences in breast cancer incidence, subtypes, and prognosis among women , it is important to evaluate potential biomarkers in the landscape of breast cancer subtypes ranging from DCIS to triple-negative breast cancer (TNBC) to determine if a simple blood test can enhance the diagnosis of this disease and knowing about stage of disease, and helping in proper treatment. In this review we tried to discuss role of genetic panels in breast cancer management.
Real Exchange Rate and Export Diversification: How do Financial Crises shape the Causation?

Diversification in export has become of growing interest in the recent literature. When a correlation between the real exchange rate and export diversification is established, most studies focus on the causal link from the former to the latter. Surprisingly, the reverse causal direction is usually ignored. This paper proposes a panel Granger causality test between real exchange rate and export diversification in the middle-income countries of Asia and Latin America over the period 1995-2015. We also examine the effects of two financial crises on the causal relationship, namely the East Asian financial crisis of 1997 and the global crisis of 2008. Looking at the whole sample, our study finds a bidirectional causality between the two variables. A causal link running from real exchange rate to export diversification is consistent with the conventional literature. However, our empirical findings provide evidence of a reverse causality, which is a novel contribution to previous studies. Our results are confirmed when the data are investigated by region: the causality results are consistent with those for the full sample of middle-income countries at the optimal lag length. While most countries were unaffected by the financial crises, the link running from export diversification to real exchange rate was disturbed by the crises in almost eight individual countries. JEL Codes: F14, F41, 011, O24, O53, 057
The effects of temperature on hemoglobin in Capitella teleta

Annelid hemoglobin represents an impressive diversity in structure and function that has been highly influential in developing the current understanding of how this large class of protein works. Unique to the annelids are giant extracellular pigments of two main varieties: the 3600 kDa erythrocruorins and the 400 kDa hexagonalbilayer hemoglobins. The marine polychaete Capitella teleta has served as a model organism for numerous biological studies, yet very little work has been dedicated to understanding the types and properties of respiratory pigments utilized by this worm. As a temperate opportunist, this species is ideal for studying the effects laboratory induced changes in temperature and oxygen saturation on the structure and functionality of hemoglobin. The goal of this work was to determine what type of extracellular hemoglobin is normally present in C. teleta, and to determine the effects of warm versus cold acclimation on the concentration and subunit composition of this hemoprotein. It was observed that cold-acclimation induces two major changes in the morphology of C. teleta: an increase in body size and a change in red pigmentation. Using the pyridine hemochrome assay in conjunction with a heme activity assay, it was determined that the difference in pigmentation was due to a combination of effects. The 21C worms had a greater concentration of hemoglobin than the 4C worms, but less heme b. It has been suggested that this was due to a difference in the functional status of the heme b, as well as a minor difference in hemoglobin stability. Using size exclusion chromatography and native gel electrophoresis, the major extracellular hemoglobin in both warmand cold-acclimated C. teleta was determined to be a 333kDa hexagonal-bilayer hemoglobin composed of three major and up to three minor polypeptide chains that covalently bind to form disulfide-linked dimers
CENTRUM Católica’s Working Paper Series

This research studied the relationships among the consensus, the cohesion, the conflict and the potency of the top management teams in a textile and apparel sector. In order to achieve its goal, this study used four validated scales: (a) Strategic Orientation of Business Enterprises Scale for measuring consensus, (b) Perceived Cohesion Scale for measuring cohesion, (c) Interpersonal Conflict Scale for measuring conflict, and (d) Guzzo, Yost, and Campbell Scale for measuring potency. The conclusions were the following: (a) by well managing cohesion, consensus and conflict, the top management team can acquire potency, (b) the used scales with small changes are appropriate for evaluating the constructs, and (c) the proposed model was validated, with the precision that the influence of cohesion by itself seems not too important. Finally, some topics were suggested for future researches.
Forecasting stress, mood, and health from daytime physiology in office workers and students

We examine the problem of forecasting tomorrow morning’s three self-reported levels (on scales from 0 to 100) of stressed-calm, sad-happy, and sick-healthy based on physiological data (skin conductance, skin temperature, and acceleration) from a sensor worn on the wrist from 10am-5pm today. We train automated forecasting regression algorithms using Random Forests and compare their performance over two sets of data: "workers" consisting of 490 days of weekday data from 39 employees at a high-tech company in Japan and "students" consisting of 3,841 days of weekday data from 201 New England USA college students. Mean absolute errors on held-out test data achieved 10.8, 13.5, and 14.4 for the estimated levels of mood, stress, and health respectively of office workers, and 17.8, 20.3, and 20.4 for the mood, stress, and health respectively of students. Overall the two groups reported comparable stress and mood scores, while employees reported slightly poorer health, and engaged in significantly lower levels of physical activity as measured by accelerometers. We further examine differences in population features and how systems trained on each population performed when tested on the other.
A Phase I/ II Feasibility Study of Intravenous Cetuximab in Combination with 5 days Weekly Oral Capecitabine and Preoperative Radiotherapy in Rectal Cancer (XERXES)

Background Preoperative Long-course chemoradiation (LCCRT) is the standard-of-care in locally advanced rectal cancer (LARC). This phase I/II trial in two sequential studies aimed to evaluate the activity and safety of the anti-epidermal growth factor receptor (EGFR) monoclonal antibody cetuximab administered weekly-prior to, and following LCCRT. Patients and Methods All patients had magnetic resonance imaging (MRI) defined cT3/cT4 or node-positive rectal adenocarcinoma and treatment with LCCRT (capecitabine 825 mg/m2 bid on Monday-Friday for 5 weeks during radiotherapy [45Gy in 25 daily fractions] followed by total mesorectal excision (TME). In Phase I patients received weekly induction cetuximab 400mg/m2 loading, then 250mg/m2 once weekly for 4 weeks prior to standard LCCRT. In phase II 10 patients were randomised to receive: arm A standard LCCRT alone or arm B (sandwich) LCCRT with additional induction cetuximab 250mg/m2 weekly prior to LCCRT and consolidation for 5 weeks following. Results In Phase I all 12 patients proceeded to surgery with a single pCR (8%) reported. This pCR rate together with acceptable compliance (100%) and toxicity (4 Grade 3 toxicities, 2 skin rash, 1 pain and 1 pulmonary embolus) and the absence of severe surgical complications allowed continuation to phase II. In Phase II, 10 patients were recruited and five patients were randomly assigned to each treatment arm. One additional patient allocated cetuximab/CRT chose to withdraw from the trial and received no treatment. In Arm B 4/5 patients proceeded to surgery with one pCR compared to three of five patients proceeding to surgery with two achieving pCR in Arm A. The Trial closed after studies in metastatic disease reported efficacy depended on selection according to K-RAS/NRAs mutational status. Conclusions: In unselected patients without enrichment according to KRAS/NRAS/BRAF status, the addition of induction and consolidation cetuximab to pre-operative LCCRT provided modest efficacy with good compliance and manageable toxicity.
Optimal design and suitable media for e-learning effectiveness: A student-driven choice

— The advances in information technologies over the last decade have been significant, especially in terms of multimedia content management. e-learning is at the heart of research interest. Designing and developing e-learning programmes is a complex process and their deployment combines various educational considerations, questions of usability and learning environments. This study focuses on the usability and selection of the most appropriate presentation media for the content of e-learning programmes, with an aim to enhance learning effectiveness. It also focuses on the students intention to use such e-learning systems or learning information systems. The research model and the research data described in this article explain how different versions of e-learning applications are highly dependent on their intended use and the selection of media to present the multimedia material.
Optimized Machine Learning based Classifications of Staging in Gynecological Cancers using Feature Subset through Fused Feature Selection Process

After diagnosing the cancer, the next step is to identify the staging of the cancer to start with the appropriate treatment plans. There are different kinds of gynaecological cancers and this research lays emphasis on cervical and ovarian cancer types with their staging classifications. The cervical and ovarian cancers data from SEER registry are used in this work. This work intends to propose an optimized classification method for staging prediction in gynaecological cancers through fused feature selection process that aimed to provide an optimal feature subset. The fused feature selection process includes the hybridization of relief filter approach with wrapper method of genetic algorithm to produce revised feature subset of data as an outcome. Accordingly, this work attained an improved feature subset through fused feature selection process for precise classification of cervical and ovarian cancer stages by identifying their significant features. The predictive models are established with 10-fold cross validation using major classification algorithms like C5.0, Random Forest and KNN. The classification results are attained for the respective types of cervical, ovarian cancer stages and the stage-wise classification based on patients age also obtained through this proposed method. The results portrayed that the women in the age group of 45 and above are more critical with the incidence of cervical and ovarian cancer types. Random Forest method has shown progressive accuracy rate with progressive percentage of other performance outcomes. Also, this work recognized that the best and optimal feature subset selection could condense the complexity of the predictive model.
Research on Key Technologies of Urban Road Safety under the condition of Big Data

— To solve the urban road safety, congestion, pollution and efficiency, we need grasp accurate real-time traffic conditions of the city. Intelligent Traffic need to discover rules and provides various services through processing, analysis and mining massive real-time and historical data. Big Data technology is an effective way to achieve this purpose. Based on the analysis and comparison of the current popular processing platforms and technologies of the big data, this paper designs a new framework for processing traffic big data that is fit for both batch processing and real-time processing at the same time, and then to achieve data collection, storage, correlation, semantic processing and analysis of the traffic big data through this new framework. The experimental results show that the framework can real-time, fast and accurate processing and calculating traffic big data.
A preliminary study on artificial rearing of the pink stem borer,Sesamia inferens

An artificial diet for rearing the pink stem borer, Sesamia inferens(Walker), was formulated with soybean powder, corn powder, wheat germ powder and freshwater bamboo as the major components. A rearing technique for the mass and repeated production of S. inferens was developed using freshwater bamboo (a natural food source) for young larvae (neonates to 2rd instar) and the artificial diet for older larvae (3rd instar and above). The performance of S. inferens reared on this fresh water bamboo/artificial diet regimen was evaluated over 3 consecutive generations by comparison with individuals fed only on freshwater bamboo for an entire generation. The fitness indicators of larval duration, pupal weight, larval survival rate, pupation rate, eclosion rate and number of eggs laid per female were similar between these two diet regimens. However, the fresh water bamboo/artificial diet combination reduced costs by saving a considerable amount of labor and time, and by significantly reducing the rate of insecticidal pathogen contaminations. The new diet and rearing technique are suitable for mass and repeated production of the pink stem borer.
Microleakage Evaluation in Teeth Restored with Experimental Dental Nanocomposite

Introduction: The aim of this study was to evaluate the experimental nanocomposite (Kelfil) against microleakage when bonded with two different types of bonding systems. Methods: Sixty sound extracted human permanent incisors were divided into six groups randomly. Each tooth was prepared with standardised Class III cavity on each proximal surface. The teeth were immersed in Rhodamin B dye for ten hours and sectioned to analyse the depth of dye penetration. The depth of the dye penetration was measured in micrometres by using confocal laser scanning microscope (CLSM). Results: The depth of the dye penetration in the groups was compared by ANOVA test. The results showed comparable microleakage between different types of composites. Conclusion: The experimental nanocomposite (Kelfil) in comparison to the commercially available nanocomposite and micro-hybrid composite has comparable microleakage when bonded using self-etching and total-etched adhesive systems.
Update on Contact Lens Treatment of Keratoconus

Keratoconus (KC) is a progressive disease that leads to major losses of visual quality and related quality of life. Contact lens (CL) application has a primary place and importance in the correction of the optic problems due to the disease. The corneal changes and increased irregular astigmatism that occur with KC progression necessitate special CL designs and fitting methods. In addition to disease stage, the patient’s lens tolerance also plays a role in the application of CLs in KC patients. With recent advances in materials and design technology, the CLs used in the treatment of KC have developed considerably and there are various types available. In this review, we discuss the wide range of CLs, including rigid and soft lenses, hybrid and scleral lenses, and even custom lens designs, in light of recent scientific advances.