bluuebunny/crossref_metadata_2025_split huggingface dataset:
(Per)cursos tecnológicos na sala de aula de línguas: entre possibilidades e intersecções
Authors: Lopes Lucas Rodrigues 
Published: August 2024

RESUMO O presente trabalho visa trazer reflexões sobre possíveis percursos do uso de tecnologias em sala de aula de línguas a partir de diversos autores. Desse modo, na busca por interlocução, no terreno tecnológico, articularemos, entre outros teóricos, o pensamento de Edgar Morin. O primeiro para nos auxiliar a entender a sala de aula e seus infindáveis desdobramentos e o segundo por ter desenvolvido teorias discursivas que discutem aspectos que entrelaçados ao viés da complexidade e podem nos ajudar a (re)pensar o uso de ferramentas tecnológicas, como, por exemplo o YouTube; fator extremamente relevante para a inovação das práticas escolares no tenso terreno da modernidade líquida. Palavras-chave: Professor de línguas. Tecnologia. YouTube. Língua-cultura. ABSTRACT This paper aims at reflecting upon possible technological pathways when using technologies inside a language classroom from different authors’ perspectives. This way, we search for interlocution, under technological lens; we are to articulate, among others, Edgar Morin’s theories and Mikhail Bakhtin’s. The first one helps us out into understanding classroom and its endless continuities and the second one for having developed discursive theories which discuss aspects which relate to complexity theory and can help us to (re)think technological tools use, for instance, YouTube; such a relevant factor for school practices innovation under liquid modernity lens. Keywords: Language teachers. Technology. YouTube. Language-culture. RESUMEN El presente trabajo pretende aportar reflexiones sobre posibles cursos para el uso de las tecnologías en el aula de idiomas desde la perspectiva de varios autores. Por lo tanto, en la búsqueda de interlocución en materia tecnológica, articularemos, entre otros teóricos, el pensamiento de Edgar Morin. El primero que nos ayudará a entender la clase y sus interminables desdoblamientos, y el segundo por haber desarrollado las teorías discursivas que discuten aspectos que entrelazados en el sesgo de la complejidad y pueden ayudarnos a (re)pensar el uso de las herramientas tecnológicas, tales como, por ejemplo, los videos de YouTube. Factor muy relevante para la innovación de las prácticas escolares en el tenso terreno de la modernidad líquida. Palabras-clave: Profesor de lenguas. Tecnología. YouTube. Lengua-cultura.
Efektivitas Media Tumbuh Maggot (Hermetia illucens) Berbasis Limbah Pertanian Sebagai Bahan Pakan Sumber Protein
Authors: Nur'aini  , Ulina Hutasuhut  
Published: August 2024

Penelitian ini bertujuan untuk mengetahui media pertumbuhan maggot (Hermetia Illucens) yang tebaik meliputi kondisi media, suhu dan pH media, susut media melalui pemanfaatan limbah pertanian. Penelitian ini menggunakan Rancangan Acak Lengkap (RAL) Non Faktorial dengan 5 perlakuan dan 3 ulangan. Perlakuan yang diberikan pada penelitian ini adalah : P0A = dedak 100 %; P0b = limbah sayuran dan buah 100 %; P1 = dedak 75 % + limbah sayuran dan buah 25 %; P2 = dedak 50 % + limbah sayuran dan buah 50 %; P3 = dedak 25 % + limbah sayuran dan buah 75 %. Hasil penelitian menunjukkan media tumbuh maggot dari pencampuran dedak 50% dengan limbah sayur dan buah 50% (P2) merupakan media tumbuh yang terbaik dan sesuai untuk maggot baik dari segi kondisi media, suhu dan pH media, sehingga pemanfaatan media tumbuh sebagai pakan bagi maggot lebih maksimal dan efektif yang ditunjukkan dengan nilai susut media yang tinggi. Adapun kondisi media tumbuh dari P2 berwarna cokelat, cukup halus, lembab dan tidak berjamur dengan pH 5 - 6,03 dan suhu media 23,27 – 26,73 OC dengan susut media 1.540 g. Disimpulkan bahwa media tumbuh maggot dengan perbandingan yang sama dari pencampuran limbah pertanian dedak dengan limbah sayuran dan buah dapat menghasilkan susut media yang tinggi dengan kondisi, suhu dan pH media tumbuh yang sesuai untuk kebutuhan hidup maggot
Topical issues of rheumatological service in Kazakhstan
Authors: Тогизбаев Г.А. 
Published: August 2024

Системные аутоиммунные и иммуновоспалительные болезни занимают одно из ведущих мест в структуре заболеваемости населения республики и в значительной мере определяют уровень его временной и стойкой утраты трудоспособности. Их значительная распространенность, поражение людей преимущественно молодого возраста, приведение к тяжелой инвалидности делают эту проблему социально значимой. В этой связи такие болезни, как ревматизм, системные поражения соединительной ткани и орфанные (редкие) заболевания включены в Перечень социально значимых (Приказ Министра здравоохранения Республики Казахстан от 23 сентября 2020 года № ҚР ДСМ-108/2020).
Systemic autoimmune and immune-inflammatory diseases occupy one of the leading places in the structure of morbidity of the population of the republic and largely determine the level of its temporary and permanent disability. Their significant prevalence, affection of mostly young people, leading to severe disability make this problem socially significant. In this regard, diseases such as rheumatism, systemic lesions of connective tissue and orphan (rare) diseases are included in the List of socially significant diseases (Order of the Minister of Health of the Republic of Kazakhstan dated September 23, 2020 No. ҚР DSM-108/2020).
An Immense Approach of High Order Fuzzy Time Series Forecasting of Household Consumption Expenditures with High Precision
Authors: Burney Syed Muhammad Aqil , Khan Muhammad Shahbaz , Alim Affan , Efendi Riswan 
Published: August 2024

Abstract
Fuzzy Time Series (Fts) models are experiencing an increase in popularity due to their effectiveness in forecasting and modelling diverse and intricate time series data sets. Essentially these models use membership functions and fuzzy logic relation functions to produce predicted outputs through a defuzzification process. In this study, we suggested using a Second Order Type-1 fts (S-O T-1 F-T-S) forecasting model for the analysis of time series data sets. The suggested method was compared to the state-of-theart First Order Type 1 Fts method. The suggested approach demonstrated superior performance compared to the First Order Type 1 Fts method when applied to household consumption data from the Magene Regency in Indonesia, as measured by absolute percentage error rate (APER).
ANN Approach for SCARA Robot Inverse Kinematics Solutions with Diverse Datasets and Optimisers
Authors: Bouzid Rania , Gritli Hassène , Narayan Jyotindra 
Published: August 2024

Abstract
In the pursuit of enhancing the efficiency of the inverse kinematics of SCARA robots with four degrees of freedom (4-DoF), this research delves into an approach centered on the application of Artificial Neural Networks (ANNs) to optimise and, hence, solve the inverse kinematics problem. While analytical methods hold considerable importance, tackling the inverse kinematics for manipulator robots, like the SCARA robots, can pose challenges due to their inherent complexity and computational intensity. The main goal of the present paper is to develop efficient ANN-based solutions of the inverse kinematics that minimise the Mean Squared Error (MSE) in the 4-DoF SCARA robot inverse kinematics. Employing three distinct training algorithms – Levenberg-Marquardt (LM), Bayesian Regularization (BR), and Scaled Conjugate Gradient (SCG) – and three generated datasets, we fine-tune the ANN performance. Utilising diverse datasets featuring fixed step size, random step size, and sinusoidal trajectories allows for a comprehensive evaluation of the ANN adaptability to various operational scenarios during the training process. The utilisation of ANNs to optimise inverse kinematics offers notable advantages, such as heightened computational efficiency and precision, rendering them a compelling choice for real-time control and planning tasks. Through a comparative analysis of different training algorithms and datasets, our study yields valuable insights into the selection of the most effective training configurations for the optimisation of the inverse kinematics of the SCARA robot. Our research outcomes underscore the potential of ANNs as a viable means to enhance the efficiency of SCARA robot control systems, particularly when conventional analytical methods encounter limitations.
A Comparative Study of Various Machine Learning Techniques for Diagnosing Clinical Depression
Authors: Adegboyega Adegboye , Imianvan Anthony Agboizebeta 
Published: August 2024

Abstract
One of the major areas of machine learning application is in medical diagnosis. Machine learning algorithms can detect patterns in patients’ data and generates a diagnosis based on those patterns. There are several machine learning classification algorithms each having different strengths and weaknesses, and this makes it difficult to determine the best one for classification problems. In this paper, machine learning techniques used to classify the clinical depression dataset are Fuzzy Logic, Neural Network, Neuro-Fuzzy System, and Genetic Neuro-Fuzzy System. A total of 134 clinical diagnosis first report depression datasets were used in arriving at prediction. The outcome of the experiment showed that the Genetic Neuro-Fuzzy model generated the best result with a prediction accuracy of 95 %, and cross-validation of 83.2 %. This shows that the model is robust and can make accurate prediction on new, unseen data. This research work will guide future researchers and practitioners to identify new directions for advanced development opportunities in using machine learning in depression diagnosis. It will help policymakers in the area of depression to make informed decisions, especially in the area of best machine learning technique for classification problem related to depression diagnosis. The research is limited to clinical depression diagnosis; future work could be expanded to compute the severity ranks of other depression-connected dysfunctions similar to diabetes, lungs, and cancer diseases.
Alzheimer’s Disease Detection: A Comparative Study of Machine Learning Models and Multilayer Perceptron
Authors: Jha Shambhu Kumar , Vats Shambhavi , Kaushik Rajni Sehgal 
Published: August 2024

Abstract
The intersection of Artificial Intelligence (AI) and medical science has shown great promise in recent years for addressing complex medical challenges, including the early detection of Alzheimer’s disease (AD). Alzheimer’s disease presents a significant challenge in healthcare, and despite advancements in medical science, a cure has yet to be found. Early detection and accurate prediction of AD progression are crucial for improving patient outcomes. This study comprehensively evaluates four Machine Learning (ML) models and one Perceptron Model for early detection of AD using the Open Access Series of Imaging Studies (OASIS) dataset. The evaluated models include Logistic Regression, Random Forest, XGBoost, CatBoost, and a Multi-layer Perceptron (MLP). This study assesses the performance of each model, on metrics like accuracy, precision, recall, and AUC ROC. The MLP model emerges as the top performer, achieving an impressive accuracy of 95 %, highlighting its efficacy in accurately predicting AD status based on biomarker indicators. While other models, such as Logistic Regression (85 %), Random Forest (87 %), XGBoost (83 %), and CatBoost (89 %), demonstrate considerable accuracy, they are outperformed by the MLP model.
The Healthcare Study Examines the Humoral Anti-S1 Antibody Response Following mRNA Vaccination, Comparing Individuals with and without Prior SARS-CoV-2 Infection
Authors: Staruszkiewicz Małgorzata , Pituch-Noworolska Anna , Skayne Mohamad , Matthias Torsten , Skoczen Szymon 
Published: August 2024

Abstract
Vaccines targeting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been pivotal in curtailing the spread of infection. Health care workers, as frontline responders, were among the first to receive vaccination to mitigate coronavirus disease in 2019 (COVID-19) transmission. This study aimed to assess the humoral response elicited by mRNA vaccines, specifically measuring antibodies against the spike S1 protein, a marker of immune response. A cohort of 649 health care workers received three doses of mRNA vaccine, with antibody levels evaluated before and after each dose within a 2- to 3-week interval. Participants were stratified into groups based on prior exposure to the virus: those without prior contact (440 individuals) and those with a history of infection (209 individuals). Among the latter, cases of SARS-CoV-2 infection ranged from asymptomatic (92 individuals) to mild symptomatic (117 individuals). Participants with a history of infection exhibited elevated levels of IgG antibodies against the S1 protein prior to vaccination. Notably, both immunoglobulin IgA class (IgA) and immunoglobulin IgG class (IgG) antibody responses increased significantly post-vaccination, peaking after the second dose for IgG and after the third dose for IgA. Interestingly, the immune response to the vaccine did not vary significantly based on the symptomatic or asymptomatic nature of prior infection. Furthermore, the study findings indicate that completion of the vaccination regimen led to sustained antibody production lasting between 6 months and 9 months. This study underscores the robust and enduring humoral response elicited by mRNA vaccines, particularly among health care workers, irrespective of prior SARS-CoV-2 exposure.
Bridging Borders with Books: The Rise of Romanian Diaspora Libraries
Authors: Hrib Bogdan , Zbuchea Alexandra 
Published: August 2024

Abstract
The Romanian migration of the last decades has generated in the world, but especially in Europe, a significant population of Romanian origin, but far from the cultural sources in Romania. The appearance of activities that would bring together the Romanian community appeared inevitable; among them, the initiatives of some Romanian libraries were born naturally, in various forms, sometimes structured on local public libraries or just as personal initiatives. The present article maps and evaluates several European cases of Romanian libraries: three in the Kingdom of the Netherlands and one in Prague, which already has countless branches, especially in the European Union. The investigation shows a strong connection between the Romanian libraries and their communities, especially with the parents of minor children, and a strong appreciation of these libraries' educational and social impact.
Bridging Culture and Communities: A Bibliometric Analysis of Collaboration Practices of Museums, Libraries, and Theaters
Authors: Zbuchea Alexandra , Iordan Iulia , Michailov Mihaela 
Published: August 2024

Abstract
The study encompasses a bibliometric analysis of the classical cultural organizations (museums, libraries and theaters), considering the mainstream academic research documenting the relationships between these organizations and their communities. The first part discusses how these organizations’ focus and commitments have shifted from passive cultural aims, observing a social and educational turn towards communities. We observe a redefinition of their core purposes, becoming dynamic community and social spaces that promote sustainable development, social enrichment and wellbeing. They are no longer temples of culture, but complex hubs, spaces for engagement. Mainstream academic research gives more attention to the transformations in the library sector. Nevertheless, overall, it captures the transformations in all cultural organizations investigated, highlighting the importance of technology, community engagement and interdisciplinary approaches, as well as their growing significance in community development and wellbeing.
How Does Fintech Development Affect Financing Constraints of Smes? Evidence From China
Authors: Yang Jian , Zhang Yawen , Gong Jinguo , Liu Tong 
Published: August 2024

Abstract
Small and medium-sized enterprises (SMEs) play an indispensable role in China’s economy through making huge contributions to GDP, national employment, financial innovation and government taxation. However, SMEs in China have long faced financing constraints due to their inherent problems, such as financial information asymmetry, immature governance mechanisms, and lack of collateral under the traditional financial system, which have hindered their long-term development. In recent years, financial technology (Fintech) has entered a rapid development track, especially in China, providing new ideas and methods for solving the financing difficulties of SMEs from a technical perspective. In order to examine this, this paper measures the degree of financing constraints through the cash flow sensitivity of cash model and explores how the Fintech development affects financing constraints of SMEs in China and how this impact further communicated to the performance and the risks of SMEs by adopting two-way fixed effects models. The results show that Fintech could alleviate the financing constraints of SMEs. Furthermore, the mediating role of ownership is identified, presenting a better mitigating effect of Fintech on the financing constraints for private SMEs. In addition, both the performance and the risks of SMEs showed the upward single-sided U-shaped relationship with the increase of the Fintech development index, which indicates that Fintech could amplify performance while magnifying the risks of SMEs. The findings of this paper offer an important implication for China that regulatory authorities should consider and balance the financing constraint mitigation effect and risk amplification effect of Fintech.
Functional evaluation of different soil hydraulic parametrizations in hydrological simulations reveals different model efficiency for soil moisture and water budget
Authors: Kozma Zsolt , Decsi Bence , Ács Tamás , Jolánkai Zsolt , Manninger Miklós , Móricz Norbert , Illés Gábor , Barna Gyöngyi , Makó András , Szabó Brigitta 
Published: August 2024

Abstract
Novel soil datasets and the application of pedotransfer functions provide soil hydraulic input data for modelling hydrological processes at different scales. We aimed to evaluate the reliability of soil hydraulic parameters derived by indirect methods in simulation of soil moisture time series and water budgets at profile level of three sites (Forest, Orchard and Grassland) from a Central European catchment (Lake Balaton, Hungary). Five soil-vegetation-atmosphere model variants were set up with the Hydrus-1D model for each site, differing only in the parametrization of input soil data: i) a calibrated reference, ii) measured values, iii) values predicted from measured basic soil properties, iv) values predicted from national soil map information, v) values derived from the 3D soil hydraulic dataset of Europe. Calibrated soil parameters led to Nash-Sutcliffe efficiency 0.50, 0.54 and 0.71 for the Forest, Orchard and Grassland Site respectively. The outcomes for model efficiency of soil moisture underline the superiority of local databases over regional ones and the need for more detailed vertical discretization during modelling. The model performance according to soil moisture and water budget accuracy led to different rank order of model variants. Water budget comparisons indicated moderate differences between the hydrologic fluxes simulated by the different model variants, emphasizing the uncertainties associated with soil hydraulic parametrization either at local or at watershed scale.
Channel deformation around non-submerged spur dikes with different alignment angles under ice cover
Authors: Jafari Rahim , Sui Jueyi 
Published: August 2024

Abstract
This study explores how the ice cover on water surfaces affects the deformation of the channel bed around non-submerged spur dikes. Laboratory experiments have been conducted by using two types of model ice cover with different roughness coefficients and three sands with different median grain sizes. The effects of various layout angles of non-submerged spur dikes on the maximum scour depth and scour patterns around spur dikes have been evaluated. Results showed that the dike orientation angle is the critical factor influencing the maximum scour depth. The presence of an ice cover and its roughness coefficient dramatically affect the channel bed deformation around spur dikes. The combined effect of the dike orientation angle, ice cover roughness, and flow Froude number resulted in different scour patterns. For instance, the upstream length of scour holes decreases by approximately 60% when the dike angle changes from 90º to 60º, while an increase in flow rate by about 50% leads to a 20% increase in the downstream length of scour holes. Equations have been derived to determine the maximum scour depth around spur dikes, considering the effects of ice cover, bed material and the dike layout angles.
Bildungspolitik ist Arbeitsmarktpolitik
Authors: Isphording Ingo E. , Zorn Dirk 
Published: August 2024

Abstract
Based on empirical evidence, we argue that recent declines in the basic skills of German pupils are highly concerning from a labour market policy perspective. High-quality schooling is crucial for meeting the demands of a changing labour market, as it provides new cohorts of workers with basic and self-productive skills and facilitates the acquisition of more complex skills and lifelong meta-competences. Therefore, education policy must be seen as an integral part of labour market policy. However, there is a distinct lack of communication and coordination between labour and education policy in Germany, due to misaligned incentives and fragmented responsibilities. Recent reforms provide hope that the necessary capacity building can be achieved.
Migration ist kein Nullsummenspiel –ein Interview
Authors: Dustmann Christian 
Published: August 2024

Abstract
In this interview, Christian Dustmann discusses current opportunities and challenges for the German labour market. The interview covers a wide range of topics such as the differences between labour migration and refugee migration, the flexibilisation of working conditions to attract and retain more people in the labour force, the role of free collective bargaining and continuous training, and ends with remarks on the quality and availability of data for labour market economics and contributions to economic policy.
Verteilungswirkungen und Fallstricke des Faktorverfahrens bei der Lohnsteuer
Authors: Herrmann Judith , Teuber Martin , Calahorrano Lena 
Published: August 2024

Abstract
The German coalition agreement (2021) intends to transform withholding tax class combination III/V for married couples to the symmetric tax class combination IV/IV with a factor, to strengthen economic independence and fairness. The taxation with a factor could eliminate possible disadvantages of tax class combination III/V, particularly the high marginal tax burden in tax class V. The planned reform is associated with several pitfalls. We present the expected reform effects on tax revenues and income distribution, which we calculate using a microsimulation model. We then discuss possible difficulties associated with the reform’s implementation, in particular those concerning individuals employed less than 12 months and sole earners.