bluuebunny/crossref_metadata_2025 huggingface dataset:
Implementasi Metode AHP dan Multi-Objective Optimization by Ratio (MOORA) dalam Pemilihan Motor Listrik
Authors: Sembiring Kristian Eykman , Purnomo A Sidiq
Published: July 2024

The mode of transportation is very widely used because it is an access to take one place to another and is also used as a tool to transport an object. There are many types of transportation in Indonesia, one of which is a motorcycle. The increasing number of motorcycle users who consume fuel oil (BBM), raises concerns about climate change and air pollution. With these concerns, it can increase public awareness of the importance of protecting the environment. Efforts can be made to protect the environment in using transportation equipment, namely by using fuel from electrical energy. The number of electric motorbikes on the market with various types, makes it difficult for ordinary people to determine the choice of electric motorbikes that match their wishes and on average ordinary people determine the choice of motorbikes only from brands, selling prices, and do not understand the specifications of each of the criteria on electric motorbikes. From this problem, the researcher presents a decision support system to support lay people in determining the desired electric motorbike, using the AHP method to determine the weight and continued with the MOORA method to get the recommended electric motorbike. Electric motors that have affordable prices with good specifications get the highest rank in ranking with a value of 0.0718. The purpose of this research is to increase understanding of the factors that are important in the selection of electric motors, this method has never been used before for the selection of electric motors so it is hoped that the results of this research can develop new methods for selecting electric motors, and this research can provide recommendations for the best electric motors for prospective buyers so as to facilitate prospective buyers in making decisions in selecting electric motors.
Perbandingan Algoritma K-Nearest Neighbor dan Support Vector Machine Pada Pengenalan Pola Tulisan Tangan
Authors: Widiyanti Adella , Megawaty Dyah Ayu
Published: July 2024

Handwriting is a biometric characteristic because each person has a unique handwriting pattern. This uniqueness can be utilized as a biometric identity. Handwriting pattern recognition is one of the important fields in document analysis to biometric authentication. This research explores the implementation of K-Nearest Neighbors (K-NN) and Support Vector Machine (SVM) algorithms in the context of handwriting pattern recognition. In addition, this research incorporates digital image processing technology by utilizing feature extraction using Gray-Level Co-occurrence Matrix (GLCM). This process involves taking handwriting samples, digitizing them into digital images, and utilizing GLCM to extract texture features. These features play an important role in capturing the unique characteristics of each handwriting pattern. This research was conducted because handwriting has a wide implementation in various fields. In the field of data security, handwriting recognition can be used for data verification in financial transactions and official documents. A comparison of the K-NN and SVM algorithms was conducted to determine the most effective and efficient algorithm in handwriting pattern recognition. These two algorithms are very popular and often used in classification. By comparing these two algorithms, this research aims to evaluate and compare the performance of two classification algorithms in handwriting pattern recognition so as to provide recommendations for implementation in handwriting pattern recognition. The main focus of this research is to investigate the effectiveness and accuracy of the K-NN and SVM algorithms in recognizing and classifying handwriting. K-NN algorithm produces the highest accuracy value of 82.11%, while the SVM algorithm produces the highest accuracy value of 83.87%, so that the SVM algorithm becomes the best algorithm in the classification of handwriting pattern recognition.
Alat Pendeteksi Dini Titik Api Kebakaran Hutan Menggunakan Komunikasi LoRa (Long Range)
Authors: Rizky Muhammad , Zarory Hilman , Ullah Aulia , Faizal Ahmad
Published: July 2024

Forests play an important role in maintaining environmental balance. Forests provide oxygen, host a variety of animals, protect soil, regulate water, and provide cultural, recreational and livelihood resources for humans. Despite their important role, forests are often threatened by fires caused by natural and human factors. Forest fires can cause economic losses, environmental damage, and adverse effects on human health. This research aims to create a tool that can detect forest fires early, monitor the condition of the forest environment in real time, stores data in the databas, and send early warnings via WhatsApp application. In this research, the tool uses sensors such as MQ-2, DHT22, and Soil Humidity Moisture which are connected to the ESP32 microcontroller, as well as LoRa communication technology to send data. This system can work well even in remote areas without a network. The test results show that this tool can provide accurate information about environmental conditions such as air temperature, humidity, and CO2 levels. This research makes an important contribution by providing an effective solution to monitor and prevent forest fires early, especially in remote areas that are difficult to reach by networks. With this tool, it is expected to reduce the negative impact of forest fires on the environment, economy, and human health. This system is expected to be an effective tool in monitoring and preventing forest fires early
Analyzing the Sentiment of the 2024 Election Sirekap Application Using Naïvee Bayes Algorithm
Authors: Muhammad Isa Ali , Rakhmawati Desty , Wijaya Anugerah Bagus
Published: July 2024

One of the most recent types of elections is the 2024 election, which includes the election of the president as well as legislative members. Along with the development of technology, an application called Sirekap emerged which is used to recapitulate the results of the vote. Although the app only has a one-star rating on the Play Store, reading all the user reviews to know the quality takes quite a while. Therefore, sentiment analysis can be an alternative to get an overview of user reviews so that it can help in making better decisions then, the method that will be used in conducting sentiment analysis in this study is the naïve Bayes algorithm. This research aims to identify and categorize user sentiment, as well as evaluate the quality of the app based on reviews provided on the Playstore. This research contributes by providing an efficient method to analyze user reviews of the Sirekap app, which can assist app developers and other stakeholders in making better decisions regarding app development and improvement. In addition, the results of this study confirm that the app's one-star rating is accurate, with evaluation metrics such as precision, memory, and f1 score reaching 1.00 each.
Implementasi Algoritma Backpropagation Untuk Prediksi Jumlah Siswa SMA
Authors: Salis Rahmi , Windarto Agus Perdana , Suhendro Dedi
Published: July 2024

Senior High School (SMA) is one form of formal education unit that organizes general education at the secondary education level as a continuation of Junior High School (SMP). The number of high school students in Pematangsiantar City has decreased and increased from year to year. The factors causing the decrease and increase in the number of students are economic factors, population growth rate, distance from home, age, low quality of schools, lack of teachers and teaching media. This is because the number of students is very influential in determining when additional teachers, classrooms, textbooks and teaching media are needed to support the learning process. This study aims to predict the number of high school students in Pematangsiantar City. The dataset used is a dataset of the number of high school students in Pematangsiantar City in 2019-2023 obtained from the Ministry of Education, Culture, Research and Technology (Dapodik) website https://dapo.kemdikbud.go.id/pd/2/076300. The dataset is then divided into 2 parts, namely training and testing datasets. The algorithm used in the research is the Backpropagation algorithm with 6 architectural models, namely 4-15-1, 4-25-1, 4-45-1, 4-55-1, 4-75-1, and 4-85-1. The results of this study obtained the best architectural model, namely 4-25-1 with an accuracy level of 87.5%, Epoch 65, MSE Training 0.000967055, and MSE Testing 0.001440343. Based on this best architecture model will be used to predict the number of high school students in Pematangsiantar City for 2024.
Optimizing Sentiment Analysis of Working Hours Impact on Generation Z’s Mental Health Using Backpropagation
Authors: Farsya Nabila Zibriza , Luthfiarta Ardytha , Maharani Zahra Nabila , Ganiswari Syuhra Putri
Published: July 2024

The topic of working hours' impact, Generation Z, and mental health are discussions that are often found on social media such as X (used to be Twitter). The sentiment analysis addressing these topics is needed to find out people’s opinions regarding these topics. It could also be helpful as a consideration for the decision-making process for related topics research. Therefore, this research aims to improve the accuracy of the model generated by the previous sentiment analysis research regarding the working hours’ impact on Gen Z’s mental health. The contribution of this research is by building a robust Backpropagation Neural Network model and utilizing SMOTETomek to achieve higher accuracy. This research compared two oversampling techniques for data balancing: SMOTE and SMOTETomek. The result shows that this research has successfully outperformed the baseline research with the best accuracy of 91% using SVM by generating the best accuracy of 93.01% with SMOTETomek. For comparison, SMOTETomek has outperformed SMOTE by generating the best accuracy of 93.01%, while the best accuracy generated with SMOTE is 92.26%. It indicates that in the case of Indonesian text sentiment analysis of this research, SMOTETomek has a better effect compared to SMOTE.
Meningkatkan Akurasi Deteksi Berita Palsu dengan Pendekatan Berbasis Lexicon dan LSTM melalui Text Preprocessing dan Model Training
Authors: Prastyo Edwin Hari Agus , Faisal M
Published: July 2024

Hoax news is an issue that is troubling the global community, including Indonesia. The spread of hoax news can cause various negative impacts, such as social division, public unrest, and can even endanger life safety. Hoaxes have become an epidemic in Indonesia, with 11,357 hoax issues identified by the Ministry of Communication and Information from August 2018 to March 2023. The combined approach of Lexicon-Based and LSTM results in improved accuracy in detecting hoax news. The combination of lexicon filters and pre-trained LSTM enables the model to identify hoax keywords and classify news with an accurate final score. Experimental results show that the use of Adam's optimizer produces high accuracy, achieving precision =1.0, recall=1.0, F1-score =1.0, and accuracy of 0.99. The model is able to perfectly distinguish between hoax and non-hoax news, demonstrating the effectiveness of using combined techniques and the right optimizer. However, there are some drawbacks that need to be considered, such as the reliance on a lexicon that may be incomplete and the potential for overfitting of the LSTM model. The results of this study provide insight into the importance of combined techniques in fake news detection, as well as the need for parameter adjustments and optimization strategies to minimize the drawbacks.
Optimization of Sentiment Analysis Classification of ChatGPT on Big Data Twitter in Indonesia using BERT
Authors: Sinaga Frans Mikael , Purba Ronsen , Pipin Sio Jurnalis , Lestari Wulan Sri , Winardi Sunaryo
Published: July 2024

This research is grounded in the emergence of ChatGPT technology, supported by prior and similar studies. The urgency of the issue is highlighted by previous research indicating non-convergent classification outcomes in LSTM (Long Short-Term Memory) methods due to suboptimal hyperparameter settings and limitations in understanding text data within Big Data. The presence of ChatGPT technology brings both benefits and potential misuse, such as copyright infringement, unauthorized news extraction, and violations of accountability principles. Understanding public sentiment towards the presence of ChatGPT technology is crucial. The research aims to implement the BERT (Bidirectional Encoder Representations from Transformers) method to achieve accurate and convergent sentiment analysis classification. This study involves data preprocessing stages using Natural Language Processing (NLP) techniques. Text data, already vectorized, is classified using BERT to determine public sentiment (positive, negative, neutral) towards ChatGPT technology, ensuring greater accuracy, convergence, and contextual relevance. Performance testing of the BERT model is conducted using a Confusion Matrix. With parameters set to Max Sequence Length = 128 and Batch Size = 16, the highest classification accuracy achieved is 93.4%.
Implementation of User Sentiment with Naïve Bayes Algorithm to Analyze LinkedIn Application Regarding Job Vacancies in the Play Store
Authors: Al Ghozi Dhiyauddin , Hasan Firman Noor
Published: July 2024

Mobile applications have become an important part, one of which is the LinkedIn application which is a mobile application that focuses on the recruitment process, job search and as a professional networking platform which is now increasingly relevant, especially in Indonesia. The methodology involves data collection, data preprocessing, data labeling, and application of the Naïve Bayes algorithm. Sentiment analysis can be used as a reference to improve the quality of an application and the level of user satisfaction as well as knowing the number of positive and negative sentiments in user feedback. The 999 data obtained were then divided into 60% training data and 40% test data. In this analysis, negative sentiment outweighs positive sentiment, with a total of 539 negative reviews and 460 positive reviews. Based on evaluation using the confusion matrix, accuracy results were 95.74%, precision was 100%, and recall was 91.46%. This research aims to provide insight into the communication and interaction patterns of LinkedIn users in relation to job opportunities and overall sentiment towards the platform.
Pengembalian Data Yang Hilang Pada Dataset Dengan Menggunakan Algoritma K-Nearest Neighbor Imputation Data Mining
Authors: Bangun Budianto , Karim Abdul Karim
Published: July 2024

One of the things that is really hoped for when collecting data is to produce complete data. In research, incomplete data will affect the results obtained. because the process carried out in the research was not optimal. A dataset is a collection of information that is stored for a long time and becomes a large pile of data. Missing values in the dataset will be an important problem and must be handled in research. Therefore, data recovery is needed. Data mining is a process carried out in computer research. Where data mining will process data that has been collected first, either data collected by yourself (primary data) or data that has been collected in a dataset (secondary data). Recovery is the process of recovering data that is lost or cannot be found. The K-Nearest Neighbor Imputation algorithm is a system that uses a supervised learning algorithm and aims to discover new data patterns by connecting existing data patterns with new data. KNNI is an approach used to identify objects based on certain information, namely the closest distance to the object
EDUCAÇÃO PERMANENTE EM SAÚDE DOS PROFISSIONAIS DA ESTRATÉGIA SAÚDE DA FAMÍLIA NA PANDEMIA DA COVID-19
Authors: Moreno Yara Rayany de Aquino , Araujo Janieiry Lima de , Pereira Andrezza Karine Araújo de Medeiros , Gois Palmyra Sayonara de , Marinho Patrícia Raquel Gurgel Leite , Lima Maria Valéria Chaves de
Published: July 2024

Objetivo: Investigar o processo de Educação Permanente em Saúde dos profissionais da Estratégia Saúde da Família no município de Pau dos Ferros/RN para atuação na pandemia Covid-19. Métodos: O estudo teve como participantes os profissionais atuantes nas equipes da Estratégia de Saúde da Família. Teve como critério de inclusão: atuar como médico, enfermeiro e/ou técnico de enfermagem nas equipes da Estratégia de Saúde da Família na pandemia Covid19 em Pau dos Ferros/RN. Critérios de Exclusão: Estar em licença de qualquer natureza por ocasião da coleta de dados e profissional que tenha tempo de atuação na Estratégia de Saúde da Família inferior a 120 dias. A coleta de dados ocorreu mediante a realização de entrevista semiestruturada. Resultados: Não houve ações de Educação Permanente em Saúde disponibilizadas pela gestão. Demonstrou-se esforço voluntário dos profissionais de saúde no ajuste a infodemia que a mídia tradicional e especializada repercutia, incessantemente, sobre o SARS-CoV-2 e a Covid-19; e ainda a todo aparato de diretrizes, protocolos e recomendações emitidos pela Organização Mundial da Saúde, Ministério e Secretárias de Saúde. Considerações Finais: Nota-se que houve frágil direcionamento de ações, por parte da gestão local, não se mostrou presente apenas no sentido da articulação da Atenção Primária a Saúde, com os demais níveis assistenciais, o que acarretou limitação da atuação dos profissionais no enfrentamento da pandemia.
Dually Noted: Examining the Implications of Dual Enrollment Course Structure for Students’ Course and College Enrollment Outcomes
Authors: Ryu Wonsun , Schudde Lauren , Pack-Cosme Kimberly
Published: July 2024

Dual enrollment (DE)—where students earn college credits during high school—is expanding rapidly. To facilitate DE, institutional actors across K-12 schools and colleges must build or repurpose structures across separate organizations to determine course offerings, assignments, modality, and composition. Yet the organization and implications of those structures remain a black box. Using statewide administrative data from Texas, we describe DE coursetaking and course characteristics for traditional Texas public high school students and examine how DE course characteristics predict students’ course performance and subsequent college enrollment. Our descriptive analyses illuminate striking differences between academic and career and technical education DE, both in students’ backgrounds and course structures. Our regression analyses illustrate how several malleable DE course characteristics predict student outcomes.
Healthcare Organizations' Readiness for Potential System Transformation to Value-Based Care
Authors: Özdere Nazife Bahar , Tarım Mehveş
Published: July 2024

Aim: This study aimed to determine the readiness of healthcare organizations for a potential systemic shift to value-based healthcare. Meanwhile, it also sought to understand healthcare professionals' awareness and attitudes toward value-based healthcare, their views on the need for system change, and on what is needed to achieve system change.
Methods: The basic qualitative analysis design was used in the study. Interviews using a semi-structured questionnaire were conducted with 14 clinical and non-clinical health professionals. The data obtained were evaluated by content analysis and MAXQDA 2024 program was used in the analysis.
Results: It’s stated that there are deficiencies and failures in the current health system (n=14) and that value-based system can be realized in the long term, provided that some changes are made (n=9). Care delivery and human resources aspects of the current health system are the most problematic and these are the priority areas that will ensure the harmonization of organizations with the value-based system through regulation. Evaluations in terms of care delivery process, financial strength, clinical and operational informatics, and provider network comprehensiveness were particularly positive about technology and informatics (n=27). The areas with the most negative evaluations were provider network comprehensiveness (n=23) and financial strength (n=26).
Conclusion: Healthcare professionals' demands on the system are aligned with the promises of value-based healthcare. Many processes, especially in private and city hospitals, are running parallel to value-based healthcare, even if they are not labeled as “value-based”. Private hospitals are better prepared than public hospitals for the potential transition to value. If implemented with the necessary changes, value-based healthcare can be a suitable reform for the Turkish health system and an ideal method to meet the needs.
A Summarized Version of The Internet Model of the Theory of Everything (iTOE): A New Approach to Developing the Theory of Everything (TOE) in Consciousness Science
Authors: TIJANI M. A. , Olubanjo Kehinde , Quadri Tijani , Fiyinfoluwa OYESANMI , Olalekan OLAYIWOLA Toheeb , Habeeb ALIU Opeyemi , Akolawole IBIROGBA Damilola , Daniel Obe , Nkechi EMMANUEL Blessing , Glory SIMON Ojoma , Ejitu IHEANACHO Blessing , Dazeen DANJUMA Ibrahim , Adeleke OLAOLUWA John , Rachael OJO Ige , Malik MALIK O.
Published: July 2024

**New Version uploaded July 27, 2024, with updates made to the authors and contributions of each author to the summarized version of the iTOE paper** This paper presents a meta-model of the Theory of Everything (TOE), melding science, art, mathematics, engineering, social science, and other seemingly disparate areas of study together into a single theoretical framework, a clear departure from the common approaches of developing the TOE using solely physical and mathematical methods in Physics. In the Internet Model of the Theory of Everything (iTOE), the TOE is proposed as a new discipline of study for developing Fundamental Theory (Standard Model) for any field/discipline. The iTOE Model simply states that Consciousness-Energy (CEN) is everything that really exists, meaning all things (whether living or non-living), including all fields and disciplines, are all manifestations (states or forms) of a single entity/matrix: Consciousness-Energy (CEN). The iTOE uses a set of interdisciplinary, intradisciplinary, transdisciplinary, multidisciplinary, and crossdisciplinary approaches to building the TOE in Consciousness Science and is the first of its kind in existence. It is a network theory — a new approach to the TOE, which entails internetworking and interconnecting all fields and disciplines modelled as networks or webs using CEN. The TOE is built based on Eight Axioms, the Axioms of Everything (AxioE), as its core, with a new algebra, Temic algebra, the Algebra of Everything (AlgebroE), and new numbers, Temic numbers, the Numbers for Everything (NumoE), harmonizing, unifying, and standardizing all fields and disciplines using CEN as the Universal Language — the Language for Everything (LoE). The Model has potential applications across all spheres of life and will spur new technologies and breakthroughs in all fields and disciplines.
Probabilistic normative maps of the corticospinal and cortico-reticulospinal tracts in streamline and volumetric formats
Authors: Boyne Pierce , Williamson Brady , Buclez Josephine , Cramer Steven C. , Lin David
Published: July 2024

Background. Normative maps of brain tracts are key tools for assessing the extent of tract injury and plasticity after brain lesions such as stroke. The conventional procedure for tract mapping reduces diffusion tractography streamlines to a volumetric image before warping them to a standard coordinate space. Unfortunately, this volumetric reduction discards information about tract connectivity across voxels, complicating estimation of tract injury from the resulting map. This issue could be addressed by using a streamline-based tract map, but prior efforts to do so using group-based tractography have not accounted for individual variability, and thus are at risk of underestimating tract extent. New Method. Direct streamline normalization (DSN) directly warps individual tractography streamlines to a standard coordinate space, which can be pooled across individuals to account for individual variability. Here, DSN was used to create normative tract maps for the first time.Results. Novel probabilistic maps of the corticospinal tract (CST) and cortico-reticulospinal tract (CRST) were generated in streamline format using DSN. Comparison with Existing Methods. Compared with group-based tractography, tract maps generated with DSN had 3.2-5.5 times greater volume, 1.0-1.5 times greater mean diameter and 9.7-17.7 times greater cortical origin area.Conclusions. DSN produces tract maps with more accurate representation of axonal geometry than the conventional procedure and greater incorporation of individual variability than group-based tractography, likely resulting in larger maps. Future studies can use the CST and CRST maps generated here to optimize tract injury and plasticity measurements, which may provide an improved understanding of motor impairment and recovery.
The Wasserstein Bipolarization Index: A New Measure of Public Opinion Polarization, with an Application to Cross-Country Attitudes toward COVID-19 Vaccination Mandates.
Authors: Lee Hane , Sobel Michael
Published: July 2024

Although the topic of opinion polarization receives much attention from the media, public opinion researchers and political scientists, the phenomenon itself has not been adequately characterized in either the lay or academic literature. To study opinion polarization among the public, researchers compare the distributions of respondents to survey questions or track the distribution of responses to a question over time using ad-hoc methods and measures such as visual comparisons, variances, and bimodality coefficients. To remedy this situation, we build on the axiomatic approach in the economics literature on income bipolarization, specifying key properties a measure of bipolarization should satisfy: in particular, it should increase as the distribution spreads away from a center toward the poles and/or as clustering below or above this center increases. We then show that measures of bipolarization used in public opinion research fail to satisfy one or more of these axioms. Next, we propose a p-Wasserstein polarization index that satisfies the axioms we set forth. Our index measures the dissimilarity between an observed distribution and a distribution with all the mass clustered on the lower and upper endpoints of the scale. We use our index to examine bipolarization in attitudes toward governmental COVID-19 vaccine mandates across 11 countries, finding the U.S and U.K are most polarized, China, France and India the least polarized, while the others (Brazil, Australia, Colombia, Canada, Italy, Spain) occupy an intermediate position.
Implementing An Automated Socratic Method to Reduce Hallucinations in Large Language Models
Authors: Underwood Hugo , Fenwick Zoe
Published: July 2024

The increasing reliance on AI-driven applications necessitates robust methods to ensure the accuracy and reliability of the information generated by these systems. The integration of the Socratic method within AI models represents a novel approach to addressing the critical issue of hallucinations, where models produce factually incorrect or logically inconsistent outputs. This research presents an innovative methodology that leverages structured questioning, self-critique mechanisms, iterative training processes, and automated evaluation metrics to systematically enhance the quality of responses generated by the Llama model. The results demonstrate significant improvements in coherence, factual accuracy, relevance, and logical consistency, thereby reducing the incidence of hallucinations. The study's findings have important implications for the deployment of AI in high-stakes applications, suggesting that the Socratic method can be effectively scaled and adapted across various domains to develop more reliable and trustworthy AI systems. Future work may explore further refinements of the questioning algorithms and expand the evaluation metrics to achieve even greater enhancements in model performance, paving the way for advancements in AI safety and robustness.
Visual Attention Biases in Creativity and Aberrant salience
Authors: Iosifyan Marina
Published: July 2024

Both studies on creativity and psychosis have identified a tendency to connect remotely related concepts. Yet, it is unclear whether they share similar perceptual mechanisms. This study investigated how aberrant salience and creativity are related to visual attention allocation in a meaningfulness judgment task. Participants observed objects which were perceptually, semantically, symbolically related and unrelated to the target object. They also observed words which were phonologically, semantically, figuratively related and unrelated to the target word. Individual differences in aberrant salience and creativity were measured. In a non-clinical sample, individuals with aberrant salience exhibited less bias towards longer fixations on semantically related objects versus symbolically related ones. Creative individuals showed less bias towards longer fixations on perceptually similar objects versus unrelated ones. The application of these findings to the creativity-mental illness debate is discussed.
How bilingualism shapes (or does not) the socio-cognitive skills of autistic and neurotypical adults
Authors: Digard Bérengère Galadriel , Stanfield Andrew , Fletcher-Watson Sue
Published: July 2024

Background: Research finds a positive influence of bilingualism on socio-cognitive skills for autistic and non-autistic children. However, findings in adulthood are inconsistent in neurotypical people and absent for autistic people. This study aims to chart the influence of bilingualism on cognitive and affective perspective-taking skills in autistic and neurotypical adults.Methods:We recruited 31 autistic (42% female, mean age = 33.2 years) and 95 neurotypical (72% female, mean age = 28.5 years) adults with a range of language exposures, who completed an executive attention task, and a socio-cognitive test battery. Stepwise multiple linear regressions were conducted to identify the influence of language exposures, proficiency and usage while controlling for age, attention, and non-verbal IQ variables.Results:Age of acquisition of the 2nd language negatively predicted cognitive (b = -0.020, p = 0.0012) and General (b = -0.020, p = 0.0036) perspective-taking scores above and beyond the other control variables for a range of tested socio-cognitive outcomes, but not Affective perspective-taking scores.Conclusions: This study describes a long-lasting developmental stimulating influence of early bilingualism on key sociocognitive processes in autistic and neurotypical adults alike, above and beyond the role of other individual differences such as non-verbal IQ or executive skills.
The dynamic association between physical activity and psychological symptoms in young people with major depressive disorder: an active and passive sensing longitudinal cohort study
Authors: Baynham Rosalind , Carmago Andres , D'Alfonso Simon , Zhang Tianyi , Munoz Zamantha , Davies Pemma , Alvarez-Jimenez Mario , van Berkel Niels , Kostakos Vassilis , Schmaal Lianne , Tagliaferri Scott
Published: July 2024

Purpose: Physical activity could be associated with psychological symptoms in young people with major depressive disorder (MDD). Using actigraphy and ecological momentary assessment (EMA), we investigated the associations between physical activity and stress, anxiety, and positive and negative affect in a young people with MDD. Methods: Actigraphy and EMA were collected daily in 40 young participants (aged 16-25 years) with MDD over 8 weeks. Multi-level linear mixed models were used to examine within- and between-person dynamic associations between physical activity and symptoms of stress, depression, and positive and negative affect. Results: Participants with at least 14 days of complete data were included in analysis (n participants=22; total days=598). Typical (defined as average across assessment period) vigorous physical activity was significantly associated with lower daily stress (β[95%CI]= 0.152 [ 0.298, 0.007], p=0.041) and higher daily positive affect (0.526 [0.061, 0.992], p=0.028). Variability in daily light (0.004 [0.001, 0.006], p=0.010) and moderate physical activity (0.004 [0.001, 0.007], p=0.009) were positively associated with daily stress. Variability in daily light (0.003 [0.001, 0.006], p=0.018) and moderate physical activity (0.004 [0.001, 0.007], p=0.011) were positively associated with daily anxiety.Conclusions: Various intensities of physical activities were dynamically associated with symptoms of stress, anxiety, and positive affect in young people with MDD. Future research should continue to define the causal and dynamic associations between physical activity and psychological symptoms to promote evidence based behavioural strategies to improve psychological symptoms in young people with MDD.
Alteration processes of mantle peridotite in the Samail ophiolite inferred from independent component analysis of rock physical properties
Authors: Akamatsu Yuya , Kuwatani Tatsu , Oyanagi Ryosuke
Published: July 2024

To quantify the alteration processes of mantle from geophysical data, an understanding of the relationship between alteration and the physical properties of mantle peridotite is essential. In this study, we employed independent component analysis (ICA) to evaluate variations in the physical properties of altered peridotites collected by the Oman Drilling Project, to understand the alteration processes of mantle peridotite in the Samail ophiolite. We analyzed multivariate physical properties (density, porosity, P-wave velocity, electrical resistivity, permeability, magnetic susceptibility, and color reflectance) that had been measured on core samples. The ICA results show that the observed variations in physical properties can be explained broadly by four independent components. Through their relationships with physical properties and comparisons with petrological and geochemical data from previous studies, we infer the four independent components to represent distinct alteration processes: the early and late stages of serpentinization, magnetite formation, and near-surface carbonation. These processes develop differently during the overall process of alteration, and they influenced each physical property in different ways. Our results demonstrate that ICA can separate the effects of multiple processes of alteration on various physical properties of the altered peridotites, which previously had been difficult to quantify.
A red button does it all: An adaptive notification badge to nudge students to close their knowledge gaps in intelligent tutoring systems
Authors: Spitzer Markus , Moeller Korbinian , Richter Eileen , Frede Luisa , Bardach Lisa
Published: July 2024

Background: Intelligent tutoring systems (ITSs) often adaptively provide students with additional learning materials to close knowledge gaps recognized automatically by the system. In addition, students may be nudged with adaptive notification badges to close their knowledge gaps. Aim: This study evaluated the effectiveness of implementing an adaptive notification badge (small red button) reminding students to close their knowledge gaps. We also investigated the association between closing knowledge gaps and students’ overall performance, while controlling for other relevant factors (e.g., students’ usage behavior, system features, and teachers’ assignment types).Sample: We considered 105,081 students (in 6,668 classes working on ~25 million problems) who used an ITS for learning mathematics.Methods: We employed hierarchical linear regression analysis to evaluate whether students were more likely to close their knowledge gaps in a period in which notification badges were implemented in the ITS, as compared to a period without notification badges. Moreover, we used psychological network analysis to evaluate whether closing knowledge gaps was associated with students’ performance relative to other relevant factors.Results: Students closed 28% of their knowledge gaps when the adaptive red button notification badge nudged them but only closed 5% when there was no red button. Closing knowledge gaps predicted better student performance and was a more important predictor than students’ usage behavior, other system features, and teachers’ assignment types.Conclusions: Our study highlights the relevance of adaptive nudges within ITS for closing knowledge gaps and shows that closing knowledge gaps is linked to students’ performance.
In control but uninspired: Displays of artist self-control undermine perceptions of creativity
Authors: Kokkoris Michail , Stavrova Olga
Published: July 2024

Previous research highlighted the interpersonal benefits of self-control in professional contexts: People prefer high self-control individuals as work or study partners and expect them to perform better than low self-control individuals. We show that these benefits of self-control reverse in the artistic domain. Results of one pilot study and five preregistered online experiments (N = 1,644) reveal that artists with high (vs. low) self-control are perceived as less creative. This effect replicates across various artistic domains (visual art, music, poetry, screenwriting), holds for both male and female artists, and can be explained by perceptions of lower experiential processing, which is considered indispensable for creativity. However, art created by high (vs. low) self-control artists is ascribed higher market value due to stronger attributions of productivity. These findings provide novel insights into the social perception of self-control and contribute to the understudied topic of the downsides of self-control as well as to the literature on lay theories of creativity.
Computational Mechanisms of Self-enhancement During Social Comparison and their Relationship to Internalizing Symptoms
Authors: Stendel Moriah , Clithero John A. , Chavez Robert
Published: July 2024

Internalizing disorders like anxiety and depression commonly feature cognitive biases in self-evaluation, particularly in the context of social comparison. Despite the role of such biases in the severity and prognosis of internalizing conditions, limited work has identified computational mechanisms underlying self- evaluative biases in social contexts. In a sample of N = 292 participants, the present study applied hierarchical Bayesian computational modeling to a trait-evaluation task where individuals choose whether positive and negative traits better describe themselves or a close friend. We found that individuals generally engage in self-enhancement, more efficiently processing information that supports positive self-schema. However this effect flips as individuals report more symptoms, such that it becomes more difficult to integrate evidence in support of a pos- itive self-concept. These findings suggest that altered process- ing of both positive and negative self-referential information is a transdiagnostic mechanism driving aberrant self-evaluation in internalizing disorders.
On the role of life expectations in a feedback control model of subjective wellbeing. A case study with Romanian students
Authors: Susnea Ioan , Pecheanu Emilia , Cocu Adina , Simona Susnea
Published: July 2024

Contrary to the long-time dominant theories, which argue that subjective wellbeing (SWB) tends to return to a genetically determined “set point” regardless of positive or negative life events, recent research shows that lasting changes in SWB are possible.In this paper, we suggest that the stability and variability of SWB are better explained if SWB is viewed as a “feedback-controlled process” and propose a model of SWB inspired by the control theory in engineering. In this model, the target value of the SWB control process includes, besides the genetically determined components, a variable component that can be influenced by the system's output through a feedback loop. We suggest that a measure of future life expectations (FLE) is a good candidate for this variable component of the reference value in SWB regulation, and preliminary data collected using a sample of 98 Romanian students seem to support this hypothesis.
Replication Value in the Courtroom; a Commentary on Isager, van 't Veer & Lakens
Authors: Beerdsen Edith
Published: July 2024

Isager, van ‘t Veer, and Lakens (2021) propose a sensible and simple approach to help determine which claims to prioritize for replication studies, based primarily on citation counts (as a measure of value) and sample sizes (as a measure of uncertainty). When it comes to using citation counts as a measure of value, the authors acknowledge that clinical, political, and educational impact and other sources of value are unlikely to be captured fully by citation counts (Isager et al., 2021, pp. 10-12). In this Commentary, I focus on the impact that original research can have in a legal context. I argue that citation counts represent a promising start for evaluating the value of a claim, but that it is important to try to capture nonscientific impact as part of assessing value, even if doing so will be more complex than assessing scientific impact. A full accounting for nonscientific impact will likely require significant follow-up work, but I believe that a beginning can be made within Isager et al.’s proposed framework.
Sense of Agency during Group Control
Authors: Galang Carl Michael Orquiola , Cracco Emiel , Chirkov Valerii , Obhi Sukhvinder S. , Brass Marcel
Published: July 2024

Previous work has shown that the sense of agency increases when commanding other people. However, such work has primarily been limited to dyads, and little is known about how the sense of agency changes when the number of followers increases. Furthermore, it is unclear if commanding social agents vs. mere physical events changes one's sense of agency. Three experiments, involving making virtual agents clap their hands and/or streetlamps turning on, explore this topic. All three experiments reveal a robust linear increase in explicit agency judgments with follower count. Interestingly, experiments 2 and 3 show that this effect is amplified with human-like avatars (relative to streetlamps), suggesting that there may be something special about commanding a group of human-like social agents. This research provides further insight to our understanding of the sense of agency in group dynamics.
Vermögensungleichheit und ökonomische Eliten
Authors: Waitkus Nora , Butt Asif
Published: July 2024

Vermögen ist zu einer zentralen Dimension sozialer Ungleichheit und der Sozialstrukturanalyse avanciert. Dieses Kapitel zielt darauf ab, eine umfassende Einführung in die Forschung zur Vermögensungleichheit zu bieten. Zuerst werden grundlegende Begriffe definiert, um darauf aufbauend die komplexen Aspekte der Vermögensmessung und -verteilung zu erörtern. Danach wird ein Überblick über den aktuellen Forschungsstand zur sozialstrukturellen Verteilung von Vermögen gegeben, bevor der Fokus auf das obere Ende der Verteilung gerichtet wird: die ökonomische Elite und deren Erforschung. Bislang wurden die Superreichen weder als sozialstrukturelle Kategorie noch in der Elitensoziologie ausreichend untersucht. Das Kapitel schließt mit einem Ausblick auf potenzielle zukünftige Forschungsbereiche für Sozialstrukturanalytiker*innen, die sich mit der Vermögensungleichheit befassen
A new Trachyscelis Latreille, 1809 from Cape Verde Islands (Coleoptera Tenebrionidae)
Authors: Lo Cascio Pietro , Leo Piero
Published: July 2024

A new species of Trachyscelis Latreille, 1809 (Coleoptera Tenebrionidae) endemic to some islands of the Cape Verde archipelago is described. It differs from the widely distributed T. aphodioides Latreille, 1809 for the testaceous teguments, the incomplete set of elytral striae where only 1-3 are entirely visible, the smaller eyes with 50 ommatidia and the reduced wings.
Mindfulness y competencia emocional en Educación Primaria: un Estudio de Caso
Authors: Benesh Fernández-Miranda Nicolás
Published: July 2024

La práctica de mindfulness en los centros educativos ha tenido un notable auge en los últimos años. Por ello, se presenta un estudio de caso donde se contrasta la competencia emocional de estudiantes de 5º de Educación Primaria en su estado inicial y la evolución a lo largo del curso académico. Se realiza a través de una metodología cualitativa que desea conocer las atribuciones que el alumnado realiza a su mejora en competencia emocional a través de la práctica de mindfulness. Aparecen resultados reveladores sobre la importancia que los estudiantes dan a la práctica de mindfulness y momentos de encuentro consigo mismos. Estos están en consonancia con otros estudios analizados en contextos similares. Por tanto, se aporta un estudio longitudinal que engloba un curso académico completo, posibilitando tener una mayor perspectiva de estudio. Las conclusiones invitan a reflexionar sobre la necesidad de dotar a la escuela de momentos de introspección y desarrollo personal interior, a la vez que se continúan trabajando contenidos curriculares básicos para el desarrollo de los estudiantes.
Analysis of Opportunities for the Development of Electromobility of urban Transport on the Territory of Pila District
Authors: Gorzelańczyk Piotr , Warnke Filip
Published: July 2024

In the transportation industry, electromobility has become an indisputable trend that is not going to go away any time soon. According to analyses of the industry’s growth, all signs point to an increase in the number of electric automobiles, which will eventually supplant conventional combustion vehicles. One electric vehicle is now sold every 1,000 people in Poland, where they make up roughly 4.5% of total automobile sales. 20,253 units were sold in 2021, a 93% increase from the previous year (Elektromobilność…, 2022). The continued efforts of the world’s leading economies to cut greenhouse gas emissions, which are hastening climate change, are unquestionably a significant element supporting this course.
The aim of this article is to analyse the potential for the development of electromobility in the urban transport sector in Piła County. However, the success of this analysis will be possible during a period of transition in a number of important spheres. On the basis of the analysis, it can be concluded that such a possibility exists, as cars and other vehicles powered by electricity are becoming an alternative to traditional combustion vehicles, also reducing emissions of pollutants harmful to the environment. On the other hand, however, there are public concerns about this possibility, due to fires in electric cars, among other things.
Kategoria bezpieczeństwa mikro-mobilności w zrównoważonych miastach
Authors: Kędzior-Laskowska Małgorzata
Published: July 2024

Celem artykułu było wprowadzenie kategorii bezpieczeństwa w ogólny kontekst rozwoju mikro-mobilności we współczesnych miastach. Artykuł ma charakter teoretyczny. Uwagę skoncentrowano na relatywnie młodym i atrakcyjnym rynku w kontekście ekologizacji życia i rozwoju społeczno-gospodarczego.
Rynek mikro-mobilności cieszy się coraz większym zainteresowaniem zarówno mieszkańców, jak i urbanistów. Kategoria bezpieczeństwa została określona przez: a) techniczne standardy pojazdów, b) wypadki drogowe użytkowników mikro-mobilności, c) infrastrukturę transportowa miast i d) dane osobowe użytkowników mikro-mobilności. Wykazano, że bezpieczeństwo jest interdyscyplinarną kategorią istotną planowaniu transportu i rozwoju miast. Mikro-mobilność ma duże znaczenie w promowaniu zrównoważonego rozwoju. Dlatego konieczne jest jej włączenie do planów zrównoważonej mobilności miejskiej i zachęcanie osób do zmiany wzorców mobilności. Rynek jest dość dynamiczny i pojawia się coraz więcej pojazdów, także dla osób starszych i z niepełnosprawnościami ruchowymi. Pojawienie się nowych technologii może sprzyjać rozwojowi miast, bezpiecznych dla mieszkańców i środowiska.