Miracle-dz/UniFAR-FTUs huggingface dataset:
Ganzheitliches Metadatenmanagement im Data Lake: Anforderungen, IT-Werkzeuge und Herausforderungen in der Praxis

Data Lakes haben sich in der industriellen Praxis als Plattformen für die Speicherung und Analyse aller Arten von (Roh-)daten etabliert. Erweiterte Anforderungen hinsichtlich Governance und Self-Service machen das Metadatenmanagement im Data Lake zum kritischen Erfolgsfaktor. Bisher gibt es dazu jedoch nur wenige wissenschaftliche Arbeiten, es mangelt insbesondere an einer ganzheitlichen Betrachtung zur Konzeption und Realisierung des Metadatenmanagements im Data Lake. Diese Arbeit adressiert das Thema und basiert auf praktischen Erfahrungen aus einem Industriekonzern beim Aufbau eines unternehmensweiten Data Lake. Es werden praktische Anforderungen und Anwendungsbeispiele für das Metadatenmanagement im Data Lake diskutiert und die unterschiedlichen Arten von Metadaten anhand des Praxisbeispiels analysiert. Zur Umsetzung des Metadatenmanagements werden anschießend unterschiedliche IT-Werkzeuge anhand definierter Kriterien analysiert. Das Analyseergebnis zeigt, dass Datenkataloge grundsätzlich die geeignete Werkzeugart darstellen, wobei noch technische Unzulänglichkeiten existieren. Abschließend werden die in der Praxis bestehenden Herausforderungen für ein ganzheitliches Metadatenmanagement im Data Lake zusammengefasst und zukünftige Forschungsbedarfe aufgezeigt.
Forecasting the response of a recovered pinniped population to sustainable harvest strategies that reduce their impact as predators

The recovery of marine mammal populations has led to increased predation on commercially valuable prey species, creating conflicts with fisheries and calls for predator control. Grey seals are important predators of Atlantic Cod and Winter Skate in the southern Gulf of St. Lawrence (sGSL), and both species are likely to be extirpated unless grey seal presence in that ecosystem is strongly reduced. We aimed to identify harvest strategies that reduced grey seal presence in the sGSL to levels that favour fish recovery while maintaining grey seal conservation goals. We fit an integrated population model to grey seal abundance, reproductive and mark-recapture data, and projected future presence in the sGSL while varying the magnitude and age-composition of the annual commercial quota. We found that both removal and conservation targets could be met with annual quotas of 6000 seals if 50% of hunted seals were young of the year (YOY), though small amounts of overhunting reduced seal abundance below limit reference levels. Harvest strategies that targeted higher proportions of YOY were less likely to trigger conservation concerns, though these strategies required much larger quotas to achieve removal targets.
WiC: the Word-in-Context Dataset for Evaluating Context-Sensitive Meaning Representations

By design, word embeddings are unable to model the dynamic nature of words’ semantics, i.e., the property of words to correspond to potentially different meanings. To address this limitation, dozens of specialized meaning representation techniques such as sense or contextualized embeddings have been proposed. However, despite the popularity of research on this topic, very few evaluation benchmarks exist that specifically focus on the dynamic semantics of words. In this paper we show that existing models have surpassed the performance ceiling of the standard evaluation dataset for the purpose, i.e., Stanford Contextual Word Similarity, and highlight its shortcomings. To address the lack of a suitable benchmark, we put forward a large-scale Word in Context dataset, called WiC, based on annotations curated by experts, for generic evaluation of context-sensitive representations. WiC is released in https://pilehvar.github. io/wic/.
Student religious attitudes and global citizenship antecedents, identification, and outcomes in a Filipino sample

ABSTRACT In the present study, we investigated the influence of religious attitudes on a model of antecedents, identification, and outcomes of global citizenship using predictive quantitative tools. A total of 2,694 university students were recruited from two campuses of a large state university in southern Philippines and completed measures regarding religious attitudes and antecedents and outcomes of global citizenship identification. Data were analysed using correlations and structural equation modelling. Results showed that among three religious attitude dimensions, the religious behavioural dimension (religiosity) predicted antecedents, identification, and outcomes of global citizenship attitudes of university students. Implications of the results were analysed with respect to religious attitudes, university extension programmes and global citizenship education.
L’INTERCOMPRÉHENSION POUR LA PROMOTION DE LA LANGUE FRANÇAISE DANS L’INTERNATIONALISATION DES UNIVERSITÉS BRÉSILIENNES

RÉSUMÉ Cette étude vise à examiner l'approche d'intercompréhension (AI) comme une occasion de promouvoir la langue française dans le contexte de l'internationalisation des universités brésiliennes, compte tenu des réformes récentes en matière d'éducation (en général) et d'enseignement des langues (en particulier) qui entravent l'enseignement, l'apprentissage et l'utilisation de langues autres que l'anglais au Brésil. À cette fin, l'auteur a effectué une recherche bibliographique pour identifier les rapports entre les études de langues étrangères et internationalisation, ainsi qu'une recherche documentaire pour identifier les textes relatifs aux réformes éducatives et politiques linguistiques au Brésil qui affectent l'utilisation du français. Il est conclu que des approches innovantes telles que l'AI sont nécessaires pour promouvoir l'enseignement du français (et d'autres langues) en milieu universitaire, avec le support des technologies de l'information et de la communication (TICs), en faveur d'un enseignement supérieur plus diversifié et multilingue.
Incidence and Predictors of Secondary Upper Tract Urothelial Cancer in Patients with High-Risk Non-Muscle Invasive Urinary Bladder Cancer and its Impact on Imaging Surveillance: A Retrospective Analysis with 1501 Patients

Objectives: We aimed to study the incidence and predictors of upper tract urothelial cancer (UTUC) in patients with high-risk non-muscle invasive bladder cancer (HR-NMIBC). Methods: Patients who had HR-NMIBC were reviewed to identify those who subsequently developed UTUC. Complete transurethral resection was performed, and biopsies were collected for histopathology followed by intravesical chemoimmunotherapy. Patients were screened annually by computed tomography (CT) for UTUC. Results: Data for 1501 patients were reviewed. UTUC developed in 59 (4%) after a median of 20 months after HR-NMIBC. Most patients were symptomatic, but UTUC was discovered on routine follow-up imaging in 28%. On bivariate analysis, only multiple bladder tumors and the number of bladder recurrences were predictors for UTUC (P = 0.01 and P = 0.008, respectively). Multiple bladder tumors and ≥ 3 bladder recurrences remained significant on multivariable analysis. Conclusion: UTUC after HR-NMIBC is uncommon (4%). Despite routine follow-up CT imaging, recurrence was detected due to symptoms in most patients, and based on imaging only in 28%. Imaging surveillance can be prioritized in patients with multiple bladder tumors and those with ≥ 3 bladder recurrences. For the other patients, the benefit of imaging surveillance has to be weighed against the risks.
Unsupervised Learning of Eye Gaze Representation from the Web

Automatic eye gaze estimation has interested researchers for a while now. In this paper, we propose an unsupervised learning based method for estimating the eye gaze region. To train the proposed network "Ize-Net" in self-supervised manner, we collect a large ‘in the wild’ dataset containing 1,54,251 images from the web. For the images in the database, we divide the gaze into three regions based on an automatic technique based on pupil-centers localization and then use a feature-based technique to determine the gaze region. The performance is evaluated on the Tablet Gaze and CAVE datasets by fine-tuning results of Ize-Net for the task of eye gaze estimation. The feature representation learned is also used to train traditional machine learning algorithms for eye gaze estimation. The results demonstrate that the proposed method learns a rich data representation, which can be efficiently finetuned for any eye gaze estimation dataset.
Evaluating Methodologies for Business Process Architecture Design - A Pilot Study

A pilot user study was conducted for evaluating methodologies for business process architecture design. We adapted the Method Evaluation Model for assessing these kind of methodologies in terms of perceived and actual usefulness and ease of use, as well as intention to use. The study allowed to compare two methodologies and evaluate them individually. Also, we found that usefulness was the most relevant aspect when predicting their use in practice.
Toward Wafer‐Scale Production of 2D Transition Metal Chalcogenides

2D transition metal chalcogenides (TMCs) have attracted tremendous interest from both the scientific and technological communities due to their variety of properties and superior tunability through layer number, composition, and interface engineering. Wafer‐scale production of 2D TMCs is critical to the industrial applications of these materials. Extensive efforts have been bestowed to the large‐area growth of 2D TMCs through various approaches. In this review, recent advances in obtaining large‐area 2D TMCs by different methods such as chemical vapor deposition (CVD), metal–organic CVD, and physical vapor deposition are first highlighted and their advantages and disadvantages are also evaluated. Then, strategies for the control of the grains, morphology, layer number, and phase to achieve controllable and uniform thicknesses and large crystal domains for 2D TMCs are discussed. Applications of large‐area 2D TMCs in electronics, optoelectronics, spintronics, etc., are also introduced. Finally, ideas and prospects for the future developments of wafer‐scale 2D TMCs are provided.
Ebastine, a Mast Cell Blocker Improves Sperm Motility in Asthenospermic Infertile Men

Introduction: The right treatment of male infertility is relatively costly procedure. So we should sincerer about the treatment procedure to evaluate the role of mast cell blocker ebastin in male infertility for the sake of the wellbeing of our people. The study aims to observe and evaluate the effect of Mast cell (MC) blocker Ebastin in the improvement of sperm motility in asthenospermic infertile male. Methods: This was a longitudinal clinical trial study and was conducted in the Infertility Unit outdoor, Department of obstetrics and gynecology, Bangabandhu Sheikh Mujib Medical University, Dhaka. Bangladesh during the period from January 2015 to December 2015. This study was conducted among the male patients and followed Purposive sampling technique. Finally, 334 cases were enrolled in this study. Among the male with abnormal semen parameter 168 patients were Asthenozospermic and 60 patients were combined Oligo-asthenozospermic. Statistical analysis was carried out by using the SPSS 16.0 & MS-Excel2016. Result: From 334 study people we found in group I, mean sperm total mortality was 24.86±12.02% in pretreatment and 34.29±9.35% in post treatment. The difference was statistically significant (p 0.05). Improved sperm motility was 75.4% of asthenozospermic male in ebastin group and 19.3% in placebo group. Which was statistically significant (p 0.05). Conclusion: that sperm motility and rapid progress had significantly improved after three months’ treatment period with Ebastin than Placebo. Therefore, this study suggested that mast cell blocker ebastin can be helpful than placebo to improve the patients’ sperm motility with asthenozoospermia.
Variational Bayesian Dropout With a Hierarchical Prior

Variational dropout (VD) is a generalization of Gaussian dropout, which aims at inferring the posterior of network weights based on a log-uniform prior on them to learn these weights as well as dropout rate simultaneously. The log-uniform prior not only interprets the regularization capacity of Gaussian dropout in network training, but also underpins the inference of such posterior. However, the log-uniform prior is an improper prior (i.e., its integral is infinite), which causes the inference of posterior to be ill-posed, thus restricting the regularization performance of VD. To address this problem, we present a new generalization of Gaussian dropout, termed variational Bayesian dropout (VBD), which turns to exploit a hierarchical prior on the network weights and infer a new joint posterior. Specifically, we implement the hierarchical prior as a zero-mean Gaussian distribution with variance sampled from a uniform hyper-prior. Then, we incorporate such a prior into inferring the joint posterior over network weights and the variance in the hierarchical prior, with which both the network training and dropout rate estimation can be cast into a joint optimization problem. More importantly, the hierarchical prior is a proper prior which enables the inference of posterior to be well-posed. In addition, we further show that the proposed VBD can be seamlessly applied to network compression. Experiments on classification and network compression demonstrate the superior performance of the proposed VBD in regularizing network training.
PANIC - Plugging Data Leak Detection into the Camunda Modeler (short paper)

We present PANIC, a certified data leak detection tool, implemented as a plugin for the Camunda Modeler. With the help of our tool, process designers can detect data leaks instantaneously and interactively. The current prototype supports arbitrary BPMN processes with data logic implemented as inline scripts of a Groovy subset.
Time Dependent Mathematical Model of Thermoregulation in Human Dermal Parts During Sarcopenia

Sarcopenia is an illness characterized by the loss of skeletal muscle mass, and its strength occurs in aging after 50 years. Muscle mass plays a vital role in body weight and metabolism. The loses in body weight impact reducing the basal metabolic rate (BMR). The BMR affects the human body temperature due to lower metabolic heat production during sarcopenia. The present study deals with time dependent temperature variation in human dermal parts during sarcopenia. The finite element method is used to solve a one-dimensional bioheat equation. In this model, the thickness of the epidermis, dermis layers, and the BMR of different aging, are estimated. The results show the nodal temperature of the epidermis and dermis layers increases due to reducing the thickness. Further, the subcutaneous nodal temperature slightly decreases due to the cause of BMR.
Qualitative analysis of healthy eating attitudes among self-sufficient shelter residents

ABSTRACT Access and feasibility are strong barriers to healthy eating and prevalent among individuals in the lowest income bracket. While studies have addressed ways policymakers can alleviate these issues, more qualitative research is needed to understand food access in these populations. To assess nutrition beliefs and behaviors, this study recruited 31 self-sufficient shelter residents (individuals within 3 months of a stable life situation) to complete a brief survey on food attitudes, stage of change, and participate in focus groups. The sample was predominantly Black (48.4%, n = 15), male (48.4%, n = 15), and employed (53.3%, n = 16). We examined survey responses and used NVivo to identify themes from the focus groups. Qualitative analysis revealed participants distrusted food companies/government, lacked specific knowledge for healthy eating, felt little control to be healthier, yet desired to acquire the knowledge and resources to be healthier. Future qualitative research should probe health theory components, specifically how distrust and health willingness influence healthy-eating behavior with larger samples of individuals with low income.
Pharmacological, medicinal and toxicological properties of lavender essential oil: A review

The natural products extracted from plants are part of traditional medicine and are also therapeutic possibilities for treating many diseases. Recently, its use in the development of new drugs has shown much visibility for its efficiency and few adverse effects. Essential oils extracted from medicinal plants are indicated to treat numerous diseases due to their antimicrobial, antiviral, antimutagenic, anticancer, antioxidant, anti-inflammatory, immunomodulatory, and antiprotozoal properties. Among essential oils, lavender essential oil stands out for having several important pharmacological properties. This review detailed the main studies on essential oils from different species of lavender and obtained a valuable collection on all their pharmacological, medicinal and toxicological potential. In this context, we evaluated lavender essential oil as a promising substance that can help treat several diseases. We provide some evidence and an overview of the potential therapeutic effect of lavender essential oil to guide new research.
Three-Color Bipartite Ramsey Number for Graphs with Small Bandwidth

We estimate the $3$-colour bipartite Ramsey number for balanced bipartite graphs $H$ with small bandwidth and bounded maximum degree. More precisely, we show that the minimum value of $N$ such that in any $3$-edge colouring of $K_{N,N}$ there is a monochromatic copy of $H$ is at most $\big(3/2+o(1)\big)|V(H)|$. In particular, we determine asymptotically the $3$-colour bipartite Ramsey number for balanced grid graphs.
Influence of Mechanical and Intelligent Robotic Weed Control Methods on Energy Efficiency and Environment in Organic Sugar Beet Production

Rapidly warming climate, tightening environmental requirements, an aging society, rising wages, and demand for organic products are forcing farming to be more efficient and sustainable. The main aim of this study was to perform an analytical analysis and to determine the energy use and GHG emissions of organic sugar beet production using different weed control methods. Seven different methods of non-chemical weed control were compared. Mechanical inter-row loosening, inter-row cutting and mulching with weeds, weed smothering with catch crops, and thermal inter-row steaming were performed in field experiments at the Experimental Station of Vytautas Magnus University (Lithuania, 2015–2017). The other three, namely, automated mechanical inter-row loosening with cameras for row-tracking, inter-row loosening with a diesel-powered robot, and inter-row loosening with an electric robot were calculated analytically. The results showed that the average total energy use of organic sugar beet production was 27,844 MJ ha−1, of which manure costs accounted for 48–53% and diesel fuel for 29–35%. An average energy efficiency ratio was 7.18, while energy productivity was 1.83 kg MJ ha−1. Analysis of GHG emissions showed that the total average GHG emissions to the environment from organic sugar beet production amounted to 4552 kg CO2eq ha−1, and the average GHG emissions ratio was 4.47. The most sustainable organic sugar beet production was achieved by using mechanical inter-row loosening with a diesel-powered robot for weed control.
Gold Nanoparticles from Plant Materials: Green Extraction, Biological Synthesis and Its Beneficials Properties for Cosmeceutical Applications

Green technologies have become trends among researchers and it is developing as the current demand is increased towards products that are processed through green technologies. In this regard, green extraction and green synthesis of gold nanoparticles (GNPs) from plants are presented and discussed. Rapid development in green extraction makes the researchers are competing in providing the best extraction techniques which will use safe extracting solvent, low energy consumption, and did not release hazardous materials as residues of the processes. The same thing goes for the green synthesis of GNPs, plant extracts are used as reducing agent and it does not release any hazardous residues as compared to chemical synthesized GNPs. The application of the GNPs in this paper is reviewed on their properties that are beneficial for cosmeceutical applications. Even though the application of GNPs in the cosmeceutical application in research papers is relatively unexplored, but it has a high potential to be studied since there is existing research that recognizes the properties played by GNPs. The properties that are mostly studied by researchers are an antioxidant, anti-inflammatory, and antibacterial activity that is found to be advantageous in the production of cosmeceutical products.
Reality and the Probability Wave

Effects associated in quantum mechanics with a divisible probability wave are explained as physically real consequences of the equal but opposite reaction of the apparatus as a particle is measured. Taking as illustration a Mach-Zehnder interferometer operating by refraction, it is shown that this reaction must comprise a fluctuation in the reradiation field of complementary effect to the changes occurring in the photon as it is projected into one or other path. The evolution of this fluctuation through the experiment will explain the alternative states of the particle discerned in self interference, while the maintenance of equilibrium in the face of such fluctuations becomes the source of the Born probabilities. In this scheme, the probability wave is a mathematical artifact, epistemic rather than ontic, and akin in this respect to the simplifying constructions of geometrical optics.
IoT-based panel for real time traffic data monitoring in Smart Cities: A case study in the Guadalajara Metropolitan Zone

The objective of the present article is to show the implementation of a smart panel to be placed all around Guadalajara Metropolitan Zone, that will be equipped with an informative screen, a camera, and internet access. It will be in charge of requesting the traffic information from the surrounding zone using web services, taking pictures of its vision field to be later uploaded, showing traffic information of different road segments (estimated traveling time) and download pictures of other nearby panels to be also shown on its informative screen. The system has been implemented in an embedded system, capable of running the web services client, and computer vision processing.
The Turán Number of Berge K_4 in Triple Systems

A Berge-K_4 in a triple system is a configuration with four vertices $v_1,v_2,v_3,v_4$ and six distinct triples $\{e_{ij}: 1\le i< j \le 4\}$ such that $\{v_i,v_j\}\subset e_{ij}$ for every $1\le i.