Miracle-dz/UniFAR-FTUs huggingface dataset:
Have The European Union Guidelines been a Driving Force in the Inclusion of Children’s Rights into the German “Sachunterricht” Course Curriculum?

It is observed that efforts are made to benefit from the perspective of the Universal Convention on the Rights of the Child and to undertake the protection and promotion of children’s rights more effectively in countries that are members of the European Union/membership process with the European Union Agreement (Lisbon Treaty) which came into force in 2009. In this direction, the European Union Guidelines on the Promotion and Protection of Children’s Rights were published to guide the EU member countries and their countries in the process of membership in their work on children’s rights. So, the research purposed primarily to examine the status of children’s rights in the official Sachunterricht course curriculum used in the German education system in line with the EU Guidelines. In the research, a holistic multiple-state pattern was adopted from the qualitative research approach patterns. In the process of obtaining research data, the document review method was used. The official Sachunterricht course curriculum in sixteen states in the Federal Republic of Germany was examined in this scope. As a consequence of the research, it was concluded that the content included in the curriculum in most states is in line with the EU Guidelines. However, we saw just a few curricula have that there are statements of attainment and study examples regarding children’s right to protection and participation. At this point, studies can be put forward to make all education curricula more compatible with EU Guiding Principles. These studies should ensure that the teaching curricula that countries will use address children’s rights and related learning outcomes and teaching activities aimed at recognizing children’s rights, preventing discrimination against them, building a culture of universal peace, and preparing children for responsible lives in a free society.
Lipid Biosignatures From SO4‐Rich Hypersaline Lakes of the Cariboo Plateau

Modern and ancient hypersaline brines have been identified across the solar system, but the habitability of these environments remains unknown. Here, we evaluate organic matter (OM) production in MgSO4 and Na2CO3 rich hypersaline lakes whose chemistries resemble deposits on Mars such as those identified in Jezero crater. We focus our analysis on lipid biomarkers including fatty acids, alkanes, and ether‐bound lipids in modern brines, salt deposits, and surface sediments. We also report total organic carbon (TOC), carbon/nitrogen (C/N) ratios, and bulk OC (δ13C and δ15N) isotopes to contextualize the lipid biomarker data. In all lakes, the predominant biosignatures include midchain (12 < C < 23) fatty acids and alkanes suggesting microbial origin. Sediments also incorporate a greater diversity of lipids. Ether‐bound lipids derived from archaea and bacteria constitute a minor but measurable fraction of the lipids. This result contrasts with typical findings from other studies with NaCl brines which contain significant archeal biomass. TOC concentrations in all sediments are high, ranging from 0.7% to 12% with sulfate‐rich sediments having the highest concentrations. The isotopic and elemental compositions of TOC corroborate the biomarker results, showing δ13C values and C/N values indicative of aquatic microbial origin. This richness of organic matter and in situ microbial biosignatures differ from previously studied Cl‐dominated Mars‐analog sites which have shown limited OM production and preservation and acidic SO4‐rich hypersaline environments which were dominated by terrestrial inputs. Overall, our results suggest that MgSO4‐rich hypersaline environments are conducive for life and harbor a rich microbial biomarker landscape.
CLEF 2017 Dynamic Search Lab Overview And Evaluation

In this paper we provide an overview of the first edition of the CLEF Dynamic Search Lab. The CLEF Dynamic Search lab ran in the form of a workshop with the goal of approaching one key question: how can we evaluate dynamic search algorithms? Unlike static search algorithms, which essentially consider user request's independently, and which do not adapt the ranking w.r. t the user's sequence of interactions, dynamic search algorithms try to infer the user's intentions from their interactions and then adapt the ranking accordingly. Personalized session search, contextual search, and dialog systems often adopt such algorithms. This lab provides an opportunity for researchers to discuss the challenges faced when trying to measure and evaluate the performance of dynamic search algorithms, given the context of available corpora, simulations methods, and current evaluation metrics. To seed the discussion, a pilot task was run with the goal of producing search agents that could simulate the process of a user, interacting with a search system over the course of a search session. Herein, we describe the overall objectives of the CLEF 2017 Dynamic Search Lab, the resources created for the pilot task, the evaluation methodology adopted, and some preliminary evaluation results of the Pilot task.
A Literature Review of the Future of Oral Medicine and Radiology, Oral Pathology, and Oral Surgery in the Hands of Technology

In the realm of dentistry, a myriad of technological advancements, including teledentistry, virtual reality (VR), artificial intelligence (AI), and three-dimensional printing, have been extensively embraced and rigorously evaluated, consistently demonstrating their remarkable effectiveness. These innovations have ushered in a transformative era in dentistry, impacting every facet of the field. They encompass activities ranging from the diagnosis and exploration of oral health conditions to the formulation of treatment plans, execution of surgical procedures, fabrication of prosthetics, and even assistance in patient distraction, prognosis, and disease prevention. Despite the significant strides already taken, the relentless pursuit of new horizons fueled by human curiosity remains unabated. The future landscape of dentistry holds the promise of sweeping changes, notably characterized by enhanced accessibility to dental care and reduced treatment durations. In this comprehensive review article, we delve into the pivotal roles played by AI, VR, augmented reality, mixed reality, and extended reality within the realm of dentistry, with a particular emphasis on their applications in oral medicine, oral radiology, oral surgery, and oral pathology. These technologies represent just a fraction of the technological arsenal currently harnessed in the field of dentistry. A thorough comprehension of their advantages and limitations is imperative for informed decision-making in their utilization.
Data-Driven Remaining Useful Life Estimation of Discrete Power Electronic Devices

Robust and accurate prognostics models for estimation of remaining useful life (RUL) are becoming an increasingly important aspect of research in reliability and safety in modern electronic components and systems. In this work, a data driven approach to the prognostics problem is presented. In particular, machine learning models are trained to predict the RUL of wire-bonded silicon carbide (SiC) metal–oxide–semiconductor ﬁeld-effect transistors (MOSFETs) subjected to power cycling until failure. During such power cycling, ON-state voltage and various temperature measurements are continuously collected. As the data set contains full run-to-failure trajectories, the issue of estimating RUL is naturally formulated in terms of supervised learning. Three neural network architectures were trained, evaluated, and compared on the RUL problem: a temporal convolutional neural network (TCN), a long short-term memory neural network (LSTM) and a convolutional gated recurrent neural network (Conv-GRU). While the results show that all networks perform well on held out testing data if the testing samples are of similar aging acceleration as the samples in the training data set, performance on out-of-distribution data is signiﬁcantly lower. To this end, we discuss potential research directions to improve model performance in such scenarios.
Preserving Literacy and Education of Dong Pipa Cultural Heritage in Guizhou Province, China

Dong Pipa is a traditional string widely used in the daily life and folk music of the Dong people of Guizhou, Hunan, Guangxi, and other parts of China. The study’s objectives are to explore Dong Pipa literacy and education in the context of preserving Dong Pipa cultural heritage in Guizhou Province, China. Through the study of the site and the current research, the research shows that the Dong Pipa has become a musical instrument throughout the Dong community due to its simple structure and many relationships, such as entertainment, relationships, and lifestyle. The traditional music that Dong Pipa represents, however, is having significant issues due to the influence of global culture and a modern lifestyle. To meet this challenge, relevant government departments should increase the promotion of Dong Pipa culture to promote the interests of the Dong people, and schools should improve the outcomes of Dong Pipa education and heritage. Cultural institutions should organize more Dong Pipa performances and competitions to encourage Dong people to learn and preserve Dong cultural heritage. These efforts will help ensure Dong Pipa survives and thrives in today’s society.
Investigating the Impact of Perceived Social Support from Supervisors and Co-workers on Work Engagement Among Nurses in Private Healthcare Sector in Bangladesh: The Mediating Role of Affective Commitment

This study examined the role of workplace social support from supervisors and co-workers on work engagement of nurses in the private healthcare sector in Bangladesh through the mediating role of affective commitment. Data were collected from 271 nurses and analysed through structural equation modelling. The results reported that affective commitment partially mediated the relationship between supervisory support and work engagement, and fully mediated the relationship between co-worker support and work engagement. Healthcare organisations need to make sure that trained supervisors and co-workers are available in the workplace that can increase collaboration and cooperation among nurses. This study, grounded on job demand–resources theory and social exchange theory, contributes to extend the existing service research by studying the mediating mechanism of affective commitment integrating perceived supervisory support and perceived co-worker support to the work engagement of nurses.
Maisir Higgs Domino Chip Transactions Online for Millennials in Bengkalis Regency

The online Higgs domino maisir chip transaction among millennials in the Bengkalis region is the focus of this study. The purpose of this study was to determine how the millennial generation views online Higgs domino chip transactions and how they affect them. This kind of exploration is subjective examination. This kind of research uses descriptions and field conditions to develop concepts, understandings, and theories. Descriptive analysis is the method used in this study, which aims to accurately describe a person, disease, symptom, or group. The Interview is the method that is used to collect data. It is a form of verbal communication that aims to gather information. Written documents like diaries, magazines, documents, meeting minutes, and others are used to gather information on Islamic law and opinions about the Maisir Higgs domino chip transaction in the Bengkalis area for the millennial generation. The law of online Higgs domino maisir chip transactions, which includes the prohibitions of gharar, usury, and maisir from an Islamic economic perspective, are the findings of this study.
Heterogeneous Experience and Constant-Gain Learning

Recent evidence suggests that agents may base their forecasts for macroeconomic variables mainly on their personal life experiences. We connect this behavior to the concept of constant-gain learning (CGL) in macroeconomics. Our approach incorporates both heterogeneity in the life cycle via the perpetual youth model and learning from experience (LfE) into a linear expectations model where agents are born and die with some probability every period. For LfE, agents employ a decreasing-gain learning (DGL) model using data only from their own lifetimes. While agents are using DGL individually, we show that in the aggregate, expectations follow an approach related to CGL, where the gain is now tied to the probabilities of birth and death. We provide a precise characterization of the relationship between CGL and our model of perpetual youth learning (PYL) and show that PYL can well approximate CGL while pinning down the gain parameter with demographic data. Calibrating the model to U
Turkish Journal of Remote Sensing and GIS

Among many environmental problems, soil erosion poses a serious threat to the region known as Chittagong Hill Tracts (CHTs) in Bangladesh, comprising three districts, namely Bandarban, Rangamati, and Khagrachari. The annual soil erosion rate for this hilly terrain was calculated using the Revised Universal Soil Loss Equation (RUSLE) model integrated with Remote Sensing and Geographic Information System (GIS). The ranges of the estimated erosivity of rainfall, erodibility of the soil, slope length and slope steepness, crop management factor and conservation practices are 806.2 to 1513.2 MJ.mm. ha.h. yr (or an average of 1121.5 MJ.mm.ha.h.yr), 0 to 0.02 t.h. MJ mm, 0 to 78.8 (or average 0.41), 0 to 0.63 (or average 0.57) and 0.55 to 1 (or average 0.73), respectively. As per the findings, the study area is expected to lose 182621.5 tons of soil annually, with the estimated annual soil erosion rate of 15.18 t.ha. yr also predicted. The weighted overlay index approach was used to produce the probability zone map, which shows that the majority of the research region falls within the slight probability zone and that only a small percentage falls inside the high and very high probability zones. This study proves RS-GIS is useful for predicting erosion and can be used in soil conservation programs.
ObsPy – What can it do for data centers and observatories?

Data acquisition by seismic centers relies on real-time systems, like SeisComP3, Antelope and Earthworm. However, these are complex systems that are designed for fast and precisely defined standard real-time analyses. Therefore, it is not a simple task to access or modify internal routines, and to integrate them into custom-processing workflows or to perform in-depth data analyses. Often a library is necessary that provides convenient access to data and allows easy control over all of the operations that are to be performed on the data. ObsPy is such a library, which is designed to access and process seismological waveform data and metadata. We use short and simple examples here to demonstrate how effective it is to use Python for seismological data analysis. Then, we illustrate the general capabilities of ObsPy, and highlight some of its specific aspects that are relevant for seismological data centers and observatories, through presentation of real-world examples. Finally, we demonstrate how the ObsPy library can be used to develop custom graphical user interface applications.
Vitamin D, vitamin D supplementation and atrial fibrillation risk in the general population: updated systematic review and meta-analysis of prospective studies

Background Since the association of vitamin D with atrial fibrillation (AF) risk is still unclear, we conducted this updated meta-analysis of prospective studies to identify the relationship between vitamin D or vitamin D supplementation and AF in the general population. Methods We conducted a comprehensive search of multiple databases up to May 2023 for studies reporting vitamin D and AF. The hazard ratios (HRs) with 95% confidence intervals (CIs) were pooled by a random-effects model. Results A total of seven studies were included in this meta-analysis. Vitamin D deficiency (<20 ng/ml) was associated with increased AF incidence (HR: 1.12, 95% CI: 1.005–1.25). The HR was not significant with vitamin D insufficiency (20–30 ng/ml; HR: 1.09, 95% CI: 0.98–1.21). Each 10 ng/ml increase in serum vitamin D was associated with a significantly decreased AF incidence (HR: 0.95, 95% CI: 0.93–0.97). Two studies reported the effect of vitamin D supplements on AF incidence but reached inconsistent results. Conclusions Vitamin D deficiency or insufficiency was associated with an increased risk of AF in the general population. The role of vitamin D supplementation in AF prevention needs further investigation.
Quantifying the Impact of the Surface Roughness of Hexagonal Ice Crystals on Backscattering Properties for Lidar‐Based Remote Sensing Applications

Impacts of small‐scale surface irregularities, or surface roughness, of atmospheric ice crystals on lidar backscattering properties are quantified. Geometric ice crystal models with various degrees of surface roughness and state‐of‐the‐science light‐scattering computational capabilities are utilized to simulate the single‐scattering properties across the entire practical size parameter range. The simulated bulk lidar and depolarization ratios of polydisperse ice crystals at wavelength 532 nm are strongly sensitive to the degree of surface roughness. Comparisons of these quantities between the theoretical simulations and counterparts inferred from spaceborne lidar observations for cold cirrus clouds suggest a typical surface‐roughness‐degree range of 0.03–0.15 in the cases of compact hexagonal ice crystals, which is most consistent with direct measurements of scanning electron microscopic images. To properly interpret lidar backscattering observations of ice clouds, it is necessary to account for the degree of surface roughness in light‐scattering computations involving ice crystals.
On bicomplex Fourier-Wigner transforms

We consider the [Formula: see text]d and [Formula: see text]d bicomplex analogues of the classical Fourier–Wigner transform. Their basic properties, including Moyal’s identity and characterization of their ranges giving rise to new bicomplex–polyanalytic functional spaces are discussed. Details concerning a special window function are developed explicitly. An orthogonal basis for the space of bicomplex-valued square integrable functions on the bicomplex numbers is constructed by means of a specific class of bicomplex Hermite functions.
The 29 November 2004 M7.1 Kushiro-oki earthquake:An event between the on-going seismic quiescence area and the asperity ruptured by the 1973 Nemuro-oki earthquake

Title The 29 November 2004 M7.1 Kushiro-oki earthquake:An event between the on-going seismic quiescence area and the asperity ruptured by the 1973 Nemuro-oki earthquake Author(s) KATSUMATA, Kei; YAMANAKA, Yoshiko Citation 北海道大学地球物理学研究報告 = Geophysical bulletin of Hokkaido University, 69: 23-39 Issue Date 2006-03-15 DOI 10.14943/gbhu.69. 23 Doc URL http://hdl.handle. net/2115/21495 Type bulletin File Information 03.pdf
PEGylated therapeutics in the clinic

Abstract The covalent attachment of polyethylene glycol (PEG) to therapeutic agents, termed PEGylation, is a well‐established and clinically proven drug delivery approach to improve the pharmacokinetics and pharmacodynamics of drugs. Specifically, PEGylation can improve the parent drug's solubility, extend its circulation time, and reduce its immunogenicity, with minimal undesirable properties. PEGylation technology has been applied to various therapeutic modalities including small molecules, aptamers, peptides, and proteins, leading to over 30 PEGylated drugs currently used in the clinic and many investigational PEGylated agents under clinical trials. Here, we summarize the diverse types of PEGylation strategies, the key advantages of PEGylated therapeutics over their parent drugs, and the broad applications and impacts of PEGylation in clinical settings. A particular focus has been given to the size, topology, and functionalities of PEG molecules utilized in clinically used PEGylated drugs, as well as those under clinical trials. An additional section has been dedicated to analyzing some representative PEGylated drugs that were discontinued at different stages of clinical studies. Finally, we critically discuss the current challenges faced in the development and clinical translation of PEGylated agents.
MINIMIZATION OF RISK AND MAXIMIZATION OF PROFIT ON BEHALF OF BANK BY USING MACHINE LEARNING ALGORITHM

The main aim to develop a loan approval prediction model for a bank by utilizing machine learning algorithms. [Objective] The primary objective is to minimize the bank's loss by developing a decision rule for approving or rejecting a loan application based on an applicant's demographic and socio-economic profile. [Method] Three machine learning algorithms, namely Logistic Regression, Random Forest, and Decision Tree, were applied to a German credit dataset to achieve this objective. The data were preprocessed, including converting the target variable to binary, converting character variables to factors, and selecting only numeric variables. The accuracy, sensitivity, and precision of the models were evaluated using crossvalidation, and the results were compared. [Result] The Random Forest model showed the highest accuracy, with an average accuracy of 76.07%, followed by the Decision Tree model with an average accuracy of 71.99%, and Logistic Regression with an average accuracy of 71.62%. The sensitivity evaluation showed that the Decision Tree model had the highest sensitivity, with an average sensitivity of 70.88%, followed by the Logistic Regression model with an average sensitivity of 68.35%, and the Random Forest model with an average sensitivity of 65.86%. [Conclusion] In conclusion, the Random Forest model showed the highest accuracy, while the Decision Tree model had the highest sensitivity. However, all three models showed similar precision scores. Therefore, based on the objective of minimizing the bank's loss, the Decision Tree model may be more suitable as it has higher sensitivity, which means it has a lower chance of approving a loan for a potentially risky applicant. However, further research and testing are necessary before implementing these models in real-world applications.
Do private school girls marry rich?

This paper considers for the first time whether there is school-type homogamy, and whether for women there are significant advantages from private schooling as a consequence of school-type homogamy. Its focus is Britain, where a private education is associated with substantial labour market advantages and where access is socially exclusive. We find that privately educated women are 7 percentage points more likely than observably similar state-educated women to marry privately educated men. Privately educated married women have husbands who earn 15% higher pay, according to the BHPS-UKHLS panel (20% at age 42, according to the British Cohort Study). Causation is not established and considerable caution would be needed if interpreting these associations as reflecting causal effects from private schools. The findings nevertheless raise anew the issue of the negative association between Britain’s private schooling and social mobility.