bluuebunny/crossref_metadata_2025 huggingface dataset:
Bağımlılıkla Mücadelede Siyasi Partilerin Politika Önerileri: 2023 Seçimlerine Yönelik İnceleme
Authors: Yolcu Tuğba
Published: February 2025

Çalışma, seçim sürecinde siyasi partilerin bağımlılığa yönelik politika önerilerini ortaya çıkarmayı amaçlamaktadır. Siyaset, toplumsal sorunların ele alınması ve toplumun şekillenmesi üzerinde doğrudan etkiye sahiptir. Toplumun karşı karşıya kaldığı sorunların ele alınması, siyasetin temel işlevlerinden biridir. Bu nedenle çalışma siyasetin bu işlev çerçevesinde bağımlılık konusuna yaklaşımının yeterli düzeyde olup olmadığına dikkat çekmeyi amaçlamaktadır. Çalışmada siyasi partilerin seçim beyannameleri çerçevesinde bağımlılığa yönelik politika önerileri içerik analizi yöntemi ile incelenmiştir. Çalışmanın temel veri kaynağı siyasi partilerin seçim beyannameleridir. Bu beyannameler ‘bağımlılık’ anahtar kelimesi kullanılarak içerik analizine tabi tutulmuştur. Çalışmanın örneklemini 2023 genel seçimleri içinde ittifak içinde yer alan siyasi partilerin seçim beyannameleri ile mutabakat metinleri oluşturmaktadır. Çalışmada incelemeye alınan sekiz metinden beş tanesinde bağımlılık konusu işlenmiştir. Bu metinler içinde de bağımlılık aile, sağlık, uyuşturucu ile mücadele, gençlik ve hukuk kategorilerinde ele alınmıştır. Metinler içinde yer alan siyasi partilerden konuya en fazla yer veren Adalet ve Kalkınma Partisi ile İyi Parti olmuştur. Bağımlılık ana temasında ise metinler içinde en fazla madde bağımlılığı ön plana çıkmıştır.
Iran’s Defensive Policy in Assad’s Syria: Proxy War
Authors: Taşdemir Kaderli Damla , İşyar Ömer Göksel
Published: February 2025

After the Arab Spring that started in the Middle East in 2011, a civil war broke out in Syria. Syria has become a proxy war zone due to many global and regional actors intervened in the crisis. The most important regional actor supporting the Bashar al-Assad regime against the opposition in Syria is Iran. Syria, ruled by Bashar al-Assad was Iran's only ally in the region. For this reason, the most important router of the proxy war in Syria has been Iran. The purpose of this article is to explain the reasons why Iran, which supports the reflections of the Arab Spring and changes of authority in other countries, changed its stance after the protests spread to Syria and implemented a proxy war policy in order to protect the Bashar al-Assad regime. The dynamics that enabled Iran-Syria relations to continue at an almost smooth level from 1979 until the end of the Assad regime in December 2024 are included in the article. In this regard, the proxy war implemented by Iran in Syria has been explained. Iran's proxy war policy in Syria has been analyzed based on the arguments of defensive realism.
Game-Based Learning for Mathematics Lesson on 3rd Grade Elementary School
Authors: Tanudidjaja Miquel Jan , Pranata Caraka Aji , . Bernadhed
Published: February 2025

Integrating cutting-edge strategies to improve students' learning experiences has become increasingly important in the ever-changing world of education. This study investigates how third-grade students at SD Pius Purbalingga can benefit from using game-based learning as an instructional strategy to improve their mathematical education. The study focuses on how to hold children' attention and improve their knowledge of mathematics. The main subject of this study is the effectiveness of educational games in enhancing elementary school student's understanding of mathematics. A mathematics game was created to solve this problem by actively involving pupils and reiterating key mathematical ideas. This game-based strategy aimed to create an engaged and enjoyable learning experience for third-grade pupils with acceptable cognitive capacities. The findings suggest that students who played the math game significantly increased their involvement, comprehension, and memorization of mathematical ideas. This study adds to the growing evidence supporting using educational games as useful tools in mathematics instruction. The study's findings revealed increased academic performance among students, with male students experiencing a rise of 2.4% in their overall scores. In contrast, female students demonstrated a significantly higher increase of 8.5%, indicating a more pronounced advancement in their academic performance.
Evaluation of Telecommunication Customer Churn Classification with SMOTE Using Random Forest and XGBoost Algorithms
Authors: Wakhidah Lisa Nusrotul , Zyen Akhmad Khanif , Wahono Buang Budi
Published: February 2025

Competition in the telecommunications industry, particularly among Internet Service Providers (ISPs), significantly influences customer churn, which negatively impacts revenue, profitability, and business sustainability. An effective approach to mitigate churn involves identifying potential churners early, enabling companies to implement strategic retention measures. However, predicting churn can be challenging due to the limited data available on churned customers. This study aims to predict customers likely to terminate or discontinue their subscriptions, focusing on addressing data imbalance using the Synthetic Minority Over-Sampling Technique (SMOTE). The dataset, sourced from Kaggle, comprises 21 attributes and 7,034 entries. The pre-processing phase includes data cleaning, feature encoding, and the implementation of Random Forest and XGBoost algorithms after data balancing with SMOTE. The findings reveal that the XGBoost algorithm achieves a prediction accuracy of 82%, outperforming Random Forest with 81%. Key factors influencing churn include Contract, TotalCharges, and tenure. The study concludes by emphasizing the significance of contract flexibility and the need to prioritize customers with high total costs or extended subscription periods to reduce churn rates. Future research is encouraged to investigate alternative methods for handling data imbalance and to explore advanced machine learning algorithms to further enhance prediction accuracy and the effectiveness of customer retention strategies.
Development of Virtual Lab on Collision Dynamics Learning Object with Collision Algorithm Integration
Authors: Yusupa Ade , Tarigan Victor , Sengkey Daniel F.
Published: February 2025

The objective of this study is to evaluate the efficacy of a Virtual Lab employing a collision algorithm in enhancing students' conceptual comprehension of collision dynamics, in comparison to traditional pedagogical approaches, within the context of physics education.The methodology employed in this study is as follows: The study employed an experimental approach, comprising a comparison between two groups: an experimental class that used the Virtual Lab, and a control class that utilised traditional teaching methods. Both groups were subjected to pre-tests to ascertain their existing level of understanding, after which post-tests were conducted to evaluate their knowledge after the instruction period. An independent t-test was employed to analyse the differences in post-test outcomes between the two groups.The results are as follows: The findings indicated a significant improvement in the experimental class's understanding, with an average increase from the pre-test to the post-test of 33.89%, in comparison to a 30.74% improvement in the control class. The results of the t-test demonstrated a statistically significant difference (t = 4.32, p < 0.05), indicating that the Virtual Lab was more effective in enhancing conceptual comprehension. In conclusion, the Virtual Lab, based on the collision algorithm, has been demonstrated to be an effective tool for teaching collision dynamics, offering a more interactive and engaging experience than traditional methods. This study highlights the potential of technology-based learning tools to enhance physics education and recommends further development of Virtual Labs with interactive features to increase accessibility and understanding in diverse educational environments.
Energy Efficiency and Time Management through IoT-Based Automated Electrical Control System and Digital Prayer Schedule Integration
Authors: Syaputra Muhammad Adie , Sutomo Budi , Saprudin Usep , Putra Muhammad Aqida
Published: February 2025

This study aims to develop an Internet of Things (IoT)-based automated electrical control system integrated with a digital prayer schedule to enhance energy efficiency and time management in mosques. Using IoT devices, electronic equipment such as air conditioners, lights, and loudspeakers can be automatically controlled according to prayer times, reducing energy waste and minimizing fire risks due to negligence in operating electrical devices. The study employs a prototyping method, where a system prototype is tested to evaluate its performance and effectiveness. A machine-to-machine bridge communication model is implemented to integrate the digital prayer schedule with mosque electrical devices. The research results are expected to provide an environmentally friendly technological solution while improving mosque operational efficiency. However, technical challenges, such as integrating the system with older electrical infrastructure, limited internet connectivity, and user readiness to operate new technology, must be addressed. Thus, this study contributes not only to energy efficiency but also to improving mosque management quality through digital technology.
Utilization of Machine Learning for Predicting Corrosion Inhibition by Quinoxaline Compounds
Authors: Fadil Muhamad , Akrom Muhamad , Herowati Wise
Published: February 2025

Corrosion is a significant issue in both industrial and academic sectors, with widespread negative impacts on various aspects, including economics and safety. To address this problem, the use of corrosion inhibitors has proven effective. This study explores the application of Machine Learning (ML) methods based on Quantitative Structure-Properties Relationship (QSPR) to develop a predictive model for the efficiency of quinoxaline compounds as corrosion inhibitors. By conducting a comparative analysis among three algorithms: AdaBoost Regressor (ADB), Gradient Boosting Regressor (GBR), and Extreme Gradient Boosting Regressor (XGBR), and optimizing parameters through hyperparameter tuning using Grid Search and Random Search, this research demonstrates that the XGBR model yields the most superior prediction results. The XGBR optimized with hyperparameter tuning using Grid Search achieved the highest RÂ² value of 0.970 and showed the lowest RMSE, MSE, MAD, and MAPE values of 0.368, 0.135, 0.119, and 0.273, respectively, indicating high predictive accuracy. These results are expected to contribute to the development of more effective methods for identifying corrosion inhibitor candidates.
Plant Performance and Storability Tomato (Solanum lycopersicum L.) Fruit With theApplication of Calsium Chloride (CaCl2)
Authors: Faradilla Nisa , Kurniadinata Odit Ferry
Published: February 2025

This study was conducted to determine the interaction of CaCl2 concentration and application technique on the tomato plant
performance and storability of tomatoes. The CaCl2 concentration (K) consisting of k0 (0 mL L
-1
), k1 (0.5 mL L
-1
), k2 (1.0 mL L
-1
), k3
(1.5 mL L
-1
), k4 (2.0 mL L
-1
) and application technique (T) consisting of t1 (sprayed on the plant) and t2 ( watered into the growing
media). The results shows that k2t2 combination obtained the maximum number of flowers with an average 24.33 florets and obtained
height of tomato plant. The maximum number of fruits was obtained by k3t2 combination (11.33 florets), followed by k4t2 combination
(11.00 florets). The minimum number of flowers fall off was obtained by k0t2 combination (1.00 florets) and the maximum number of
flowers fall off was obtained by k3t1 combination (4.67 florets). The combination of k4t1 and k4t2 gave the best results on blossom endrot diseases (zero diseases) and storability of tomatoes (up to 30 days).
Key words: tomato, calcium chloride (CaCl2), performance, storability
EVALUATION OF THE COMMUNITY DEVELOPMENT AND EMPOWERMENT PROGRAM (PROBEBAYA) IN RT.43 SEMPAJA TIMUR DISTRICT, NORTH SAMARINDA DISTRICT, SAMARINDA CITY
Authors: Debbya Larasati  , Zulkifli Abdullah
Published: February 2025

Penelitian ini bertujuan untuk mengetahui, mengevaluasi, dan mendeskripsikan pelaksanaan Program Pembangunan dan Pemberdayaan Masyarakat (Pro-Bebaya) di RT.43 Kelurahan Sempaja Timur dengan model evaluasi CIPP (Context, Input, Process, dan Product) beserta indikator yang berkaitan dengan aspek CIPP, tujuan dan prinsip Pro-Bebaya. Penelitian ini menggunakan metode deskriptif kualitatif dengan pendekatan model evaluasi CIPP. Sumber data meliputi data primer dan sekunder. Data dikumpulkan dengan menggunakan teknik observasi, wawancara, dan dokumentasi yang dianalisis dengan menggunakan teknik reduksi data, penyajian data, dan penarikan kesimpulan. Hasil penelitian menunjukkan bahwa pada pelaksanaan pro-bebaya di RT.43 Kelurahan Sempaja Timur terdapat perubahan kepengurusan RT pada tahun 2022 serta adanya permasalahan terkait pokmas yang tidak terlibat secara aktif di tahun 2021-2022 namun telah dievaluasi oleh pihak kelurahan dan ditemukan beberapa hambatan terkait anggaran dan pengelolaan waktu oleh RT. Penyusunan dan perencanaan program dilakukan secara transparan dan partisipatif oleh RT, kelurahan, dan masyarakat dan pada hasil program ditemukan hasil evaluasi yang mencerminkan terwujudnya tujuan dan prinsip pro-bebaya yang mencakup program di bidang infrastruktur, ekonomi, kesehatan, pendidikan, sosial budaya, dan kepemudaan serta memberikan dampak yang berkelanjutan dan respon positif dari masyarakat.
APPLICATION OF CLIMATE SMART AGRICULTURE IN THE IMPLEMENTATION OF THE PRIMADONA PROGRAM (SUSTAINABLE INNOVATIVE INDEPENDENT MANGO FARMING)
Authors: Adinda Aulia Nur Afifah  , Riezqi Fajar  , Arfianto Trisnawan
Published: February 2025

Perubahan iklim berpengaruh terhadap pergeseran musim menjadi salah satu faktor menurunnya produktivitas pertanian mangga. Artikel ini bertujuan untuk mengetahui implementasi Program PRIMADONA (Pertanian Mangga Mandiri Inovatif Berkelanjutan) binaan PT Pertamina Patra Niaga Integrated Terminal Balongan melalui pendekatan Climate Smart Agriculture. Program PRIMADONA merupakan program Corporate Social Responsibility (CSR) PT Pertamina Patra Niaga Integrated Terminal Balongan dalam bidang pemberdayaan petani mangga di Desa Sliyeg Lor, Indramayu dengan fokus kegiatan pengembahan pertanian mangga tahan iklim. Artikel ini menggunakan pendekatan kualitatif deskriptif. Adapun data yang dipakai menggunakan data primer dan sekunder yang bersumber dari wawancara dan studi literatur. Hasil penelitian ini menunjukkan bahwa implementasi Program PRIMADONA telah menerapkan prinsip pendekatan Climate Smart Agriculture yakni 1) meningkatkan produktivitas pertanian; 2) adaptasi untuk membangun ketahanan terhadap perubahan iklim; 3) mengurangi gas rumah kaca (GRK). PT Pertamina Patra Niaga Integrated Terminal Balongan berupaya meningkatkan produktivitas pertanian melalui metode tumpangsari, budidaya mangga di dalam greenhouse serta pengelolaan pasca panen melalui pengolahan produk turunan mangga. Upaya adaptasi dan mitigasi untuk membangun ketahanan perubahan iklim dalam Program PRIMADONA diimplementasikan melalui pengembangan smart greenhouse berbasis Internet of Things (IoT). Pengurangan sumbangan gas rumah kaca dilakukan dengan penggunaan pupuk organik dalam budidaya mangga serta penerapan zero waste dalam pengelolaan limbah pertanian.  Keterlibatan kelompok sosial masyarakat, pelibatan wanita, lansia dan petani milenial turut menjadi elemen penting dalam pelaksanaan skema kegiatan Program PRIMADONA.
OPEN DATA USAGE AND DIGITAL LITERACY LEVEL OF PEOPLES IN TANGERANG REGENCY
Authors: Ahmad Khumaeni Zhakaria  , Ray Septianis Kartika  , Nurkholish Majid
Published: February 2025

The era of digitalization requires an innovative and accountable government. Tangerang Regency has a variety of applications that are realized to accelerate services and good governance as a whole. One of them is through open government data, which is easily accessible by any party to achieve a goal, namely transparency and disclosure of information. The purpose of this study is to determine the level of digital literacy of the community and the extent of their use of the open data portal. This research uses a mixed method with quantitative analysis using a Likert scale.  The population and sample of the study were the people of Tangerang district aged between 18 and 60 years old, domiciled in Tangerang, and had used the district's open data portal. The results of this study indicate that although most people in Tangerang district have relatively high digital literacy skills, they still do not fully utilize this tool in the context of using the open data portal. This is due to several factors such as lack of public awareness, socialization from the government, and features that are not fully optimized.
IMPLEMENTATION OF FAMILY FUNCTIONS IN SINGLE FATHERS IN KAMPAR, RIAU PROVINCE
Authors: Anna Zahirah  , Kadarisman Yoskar
Published: February 2025

This research aims to show how single fathers are carrying out family functions from five existing family functions. This research was conducted in Kota Baru Village, Tapung Hilir District, Kampar Regency in Riau Province with a focus on the implementation of family functions in a single area. In this study, the method used is qualitative descriptive, where data is collected through documentation and in-depth interviews. From the results of the research conducted, it was found that in the implementation of family functions, they (single fathers) can carry out these functions even though they are not optimal due to various obstacles they face. The obstacles they experience are obstacles in managing working time with time taking care of the household, multitasking obstacles where single fathers are somewhat minimal related to these skills, obstacles in skills in taking care of children, especially related to the needs of girls. From the results of this study, It can be concluded that in the implementation of family functions carried out by single fathers in Kota Baru Village, especially by five (5) subjects/informants with five (5) family functions, they are all carried out or carried out by each of them in a different way even though it is not optimal due to various existing obstacles. Except for the economic function which is one of the decisive aspects in carrying out other functions, although they carry it out, the way they carry it out depends on their economic conditions.
ECOSYSTEM MANAGEMENT AND IMPACT OF JATIGEDE RESERVOIR CONSTRUCTION ACTIVITIES IN THE POLITICAL ECOLOGY PERSPECTIVE
Authors: Haryanti Rinrin , Kurniawan Kunkun Kobul
Published: February 2025

Jatigede Reservoir construction activities in Sumedang Regency have an impact on various aspects. The purpose of this research is to reveal the impact of Jatigeda reservoir development on ecological and community socio-economic aspects. The research method is descriptive with a qualitative approach through observation and in-depth interviews. The results of the research show that significant changes occurred in the conversion of agricultural land and settlements to stagnant water flows. Meanwhile, changes in society lives have been identified as changes in livelihoods, shifts in living habits and cultural customs, as well as psychological impacts. This especially happens to directly affected communities. So that management can be carried out through a political ecology perspective approach, namely with an integrated collaborative pattern between the central government, regional governments and affected communities. The political ecology approach used in this research focuses on environmental political aspects with ecological and social impacts.
AVALIAÇÃO E TRATAMENTO DE LESÃO POR PRESSÃO EM PESSOAS IDOSAS HOSPITALIZADAS: REVISÃO DE ESCOPO
Authors: OLIVEIRA DE ALBUQUERQUE FERNANDA KELLY , Rodrigues Lopes de Oliveira Fabiana Maria , Batista Cabral João Victor , Ferreira Galindo Júnior José Uilson , Monteiro Gomes Andressa , Ferreira de Andrade Sílvia Cláudia , De Arruda Silva Rodrigues Maria das Graças , Fernandes Barbosa Keylla Talitha
Published: February 2025

Objetivo: Mapear as intervenções de enfermagem realizadas para avaliação e tratamento de lesão por pressão em pessoas idosas hospitalizadas. Método: Scoping review, com buscas entre março e abril de 2024, realizadas na cidade de João Pessoa/ Paraíba/ Brasil, conforme o método definido pelo The Joanna Briggs Institute, nas bases de dados: Medline/ PubMed, Embase, LILACS, CINAHL, Scopus, Cochrane, Web of Science, BDENF, ProQuest Dissertations & Theses Global e Google Scholar, sem restrição de idioma e sem limite de tempo. Abusca ocorreu de de março a abril de 2024. Resultados: Foram selecionados 18 estudos publicados entre 1995 e 2023. As evidências primordiais envolveram intervenções, avaliação, sistemas de gerenciamento de enfermagem e produtos/tecnologias no tratamento de lesões por pressão. Conclusão: As intervenções mapeadas demonstraram bons resultados e boa relação custo-benefício, porém, constatou-se a falta de uniformização dos critérios avaliativos. As evidências reforçam a necessidade de um cuidado de enfermagem pautado na Prática Baseada em Evidências.
Palavras-chave: Lesão por pressão; Idoso; Enfermagem.
GA-LDA Approach for Topic Modeling in Turkish Accounting and Finance Articles: Performance Optimization in Text Classification
Authors:   Department of International Trade and Logisctics, Faculty of Economics and Administrative Sciences, Kilis 7 Aralik University, Kilis, Turkey, Ozcalci Mehmet , Kilic Meltem ,   Department of International Trade and Logisctics, Faculty of Economics and Administrative Sciences, Kahramanmaras Sutcu Imam University, Kahramanmaras, Turkey
Published: February 2025

The volume of research in the social sciences is expanding rapidly, creating significant challenges in extracting meaningful insights from unstructured text, particularly from articles lacking a classification system. Analyzing these high-volume texts offers numerous advantages, including the ability to automatically identify topic relevance and track thematic trends over time. Such insights are valuable for journal management and enable researchers to access detailed information about evolving areas of study. Latent Dirichlet Allocation (LDA) is a widely used method for topic modeling, effectively extracting topics from textual data. However, its performance can be further enhanced through optimization techniques such as Genetic Algorithms (GA). This study introduces an intelligent GA-LDA framework designed to optimize word subsets for LDA, thereby improving its predictive capabilities. The proposed system is applied to a dataset of 928 abstracts from a Turkish-language academic journal specializing in accounting and finance, covering publications from 2005 to 2020. The genetic algorithm selects optimal word subsets for LDA analysis, with perplexity scores serving as the fitness function to guide the optimization process. Experimental results demonstrate that the GA-enhanced LDA significantly improves classification accuracy and topic modeling performance. This study not only underscores the potential of GA-LDA in handling unstructured text but also provides a robust tool for advancing automated content analysis in Turkish academic literature.
LangChain v0.3
Authors: Mavroudis Vasilios
Published: February 2025

LangChain is a rapidly emerging framework that offers a versatile and modular approach to developing applications powered by large language models (LLMs). By leveraging LangChain, developers can simplify complex stages of the application lifecycle—such as development, productionization, and deployment—making it easier to build scalable, stateful, and contextually aware applications. It provides tools for handling chat models, integrating retrieval-augmented generation (RAG), and offering secure API interactions. With LangChain, rapid deployment of sophisticated LLM solutions across diverse domains becomes feasible. However, despite its strengths, LangChain's emphasis on modularity and integration introduces complexities and potential security concerns that warrant critical examination. This paper provides an in-depth analysis of LangChain's architecture and core components, including LangGraph, LangServe, and LangSmith. We explore how the framework facilitates the development of LLM applications, discuss its applications across multiple domains, and critically evaluate its limitations in terms of usability, security, and scalability. By offering valuable insights into both the capabilities and challenges of LangChain, this paper serves as a key resource for developers and researchers interested in leveraging LangChain for innovative and secure LLM-powered applications.
AI 学習のための哲学的推論
Authors: Kanazashi Rikito
Published: February 2025

本研究は、AI が「二つの概念の比較」を通じて哲学的推論(帰納・演繹・ア ブダクション)を行うことが可能であるかを検証する。既存の AI は統計的手法 に依存しており、概念の自発的形成が困難である。しかし、人間の知的成長には 異なる概念の関連付けが不可欠であり、本研究ではこのプロセスを AI に組み込 む方法を探る。具体的には、無作為に選ばれた二つの概念を AI に与え、比較に よって新たな知識を得ることが可能かを分析する。これにより、既存の AI モデ ルの限界を補強し、専門的学習の必要性を示すとともに、AI の知識体系の拡張 と思考の一般化を促すことを目的とする。This study examines whether AI can perform philosophical reasoning (induction, deduction, and abduction) through the comparison of two concepts. Existing AI models rely on statistical methods, making it difficult for them to autonomously form new concepts. However, human intellectual growth depends on associating different concepts. This research explores a method to integrate this process into AI. Specifically, we analyze whether AI can derive new knowledge by comparing two randomly selected concepts. By doing so, this study aims to reinforce the limitations of existing AI models, demonstrate the necessity of specialized learning, and promote the expansion of AI's knowledge system and the generalization of thought.
Greener Pastures? A Labor Market Theory of Climate Governance
Authors: Zucker Noah , Singh Simran , Thrall Calvin
Published: February 2025

Climate governance requires access to climate experts: individuals with specialized knowledge of decarbonization and climate science. Here we model climate governance as the function of a competition between the state and private sector for a scarce pool of climate experts. Governments seek experts to develop and implement climate policies. Firms seek experts to affect policy choice, skirt enforcement, and measure climate risks to commercial interests. As firm interest in climate grows, the government’s ability to attract experts declines, making it more reliant on the private sector for climate governance. To support this argument, we measure private sector demand for experts with unique data on U.S. job postings, paired with administrative data on government bureaucrats and procurement. Our findings offer a novel labor-based account of climate politics, contributing to the study of labor markets in political science, the sources of bureaucratic expertise, and the net effects of corporate social responsibility.
Preconception predictors of next generation early relational health: A living review of prospective cohort studies
Authors: Macdonald Jacqui A , Mansour Kayla , Evans-Whipp Tracy Jean , Spry Elizabeth , Letcher Primrose , Ritland Lisa , Misuraca Gessica , Mallawaarachchi Sumudu , Cobden Annalee , Green Melissa , Hutchinson Delyse , Thomson Kimberly , Greenwood Christopher , Kretschmer Tina , Hancox Robert , Olsson Craig
Published: February 2025

Intergenerational studies suggest that the developmental foundations of children’s early relationalhealth are seeded well before conception. Here, we present studies that report on associationsbetween factors in the parental preconception life course (across childhood, adolescence, and youngadulthood), and indicators of the child’s early relational ecology (e.g., infant-to-parent attachment,parent-to-infant bonds). We searched MEDLINE, PsycINFO and Embase databases for peer-reviewedarticles, published in English, that reported on prospectively assessed factors at any stage of aparent’s life course prior to conception, and associations with offspring relational health fromconception to end of age 3 years. No date restrictions were imposed. The search yielded 11,337articles of which 23 met inclusion criteria, reporting data from 15 separate cohorts. Child relationalhealth was assesses using both coded observations and parent reports. Most studies focused on themother-child relationship (65%). Most preconception predictors were within the family microsystem(70%) and measured during adolescence (70%). Few studies assessed other microsystems or broaderecological systems, with no studies investigating workplaces, online interactions, or cultural beliefsystems as predictors of next generation relational health. We conclude that longitudinal cohortsthat track individuals into parenthood can provide critical insights into the preconception origins ofearly relational health; however, the existing body of prospective studies is heterogeneous andreflects a nascent field of enquiry. We present five recommendations for future investment in publichealth approaches that promote early relational health.
Daubert and Omics: Exploring the Use of Complex Scientific Evidence in Court
Authors: Chighine Alberto , Locci Emanuela
Published: February 2025

The integration of omics sciences, such as genomics, transcriptomics, proteomics, lipidomics, and metabolomics, into forensic practice holds substantial promise for advancing personalized forensic medicine. This short communication aims to elucidate the complexities associated with implementing these advanced methodologies within forensic contexts, particularly in relation to legal admissibility under the standards established by the landmark U.S. Supreme Court case, Daubert v. Merrell Dow Pharmaceuticals. Omics technologies generate vast, intricate datasets that necessitate sophisticated statistical analyses to unravel relevant insights, thereby posing unique challenges in meeting legal criteria for scientific evidence. This short communication delves into how omics approaches can meet Daubert standards, focusing on aspects like testability, known or potential error rates, and general acceptance within the scientific community. It highlights the design of increasingly rigorous experimental protocols in omics research, which include multiple sample replicates, controlled environments, and robust validation processes to ensure reproducibility. However, despite this methodological rigor, several hurdles persist. There is a significant need for specialized, interdisciplinary expertise during peer review, as reviewers must be conversant in both advanced statistical methods and forensic science. Furthermore, the gap between research on animal models and its direct applicability to human forensic cases, the challenges of intra- and interlaboratory reproducibility, especially in less mature omics fields like proteomics and metabolomics, are examined. The legal system's increasing reliance on scientific evidence has also pushed for greater scrutiny on the error rates of omics methods, requiring forensic scientists to refine their approaches to account for biological variability and environmental factors, particularly in post-mortem settings. While genomics has seen notable acceptance in forensic DNA profiling due to decades of practice and validation, other omics disciplines are gradually gaining ground. However, their practical use in court is still limited, primarily because the depth and breadth of omics data are not yet fully exploited for straightforward forensic interpretations. While omics offer transformative potential, their full judicial integration necessitates further research, standardization, and community acceptance to bridge the gap between theoretical capabilities and practical forensic application.
Bridging the Mental Health Gap: Evaluating the Psychometric Properties of the Strengths and Difficulties Questionnaire for Nigerian Adolescents
Authors: Katus Laura , Olalekan Bukola Deborah , Oyekola Adebunmi Oyebisi
Published: February 2025

Adolescence is a critical period for the development of mental health disorders, making early identification during this time essential for enabling targeted interventions and preventing long-term adverse consequences. Globally, one in seven adolescents experiences poor mental health, including depression and anxiety, yet many countries, especially in sub-Saharan Africa, face a scarcity of mental healthcare provisions. Tools like the Strengths and Difficulties Questionnaire (SDQ), which assesses emotional and behavioural problems in children and adolescents, offer a potential solution for identifying issues early. However, its applicability in non-Western, sub-Saharan African contexts, requires further scrutiny. This study assesses the psychometric properties of the SDQ in a representative sample of N=2,178 (n=1,366 female, age 10-19, mean age = 14.758, SD=1.902) in Oyo state, Nigeria, specifically examining the measure’s factor structure and measurement invariance across demographic groups such as sex, age, parental education, and marital status. Our results demonstrate that the original 5-factor model of the SDQ did not fit well for the Nigerian sample, consistent with previous studies in sub-Saharan Africa. Interestingly, a 3-factor model previously proposed for Nigerian contexts (Apka et al., 2016) also did not achieve good model fit, necessitating further psychometric probing. We found that a slightly modified 5-factor model (releasing items of Q02 ‘I am restless’, Q05 ‘I get very angry’ and Q06 ‘I am usually on my own’) showed excellent fit, but some overlap between emotional symptoms, conduct problems, and peer issues suggests that the SDQ’s constructs may need further adaptation for cultural specificity. We also established that the SDQ exhibited full scalar invariance across sex and age groups, supporting its utility in diverse demographic groups. However, partial scalar invariance across parental marital status indicates that family dynamics may influence responses to certain items. These findings underscore the importance of refining the SDQ for use in sub-Saharan Africa, highlighting the need for culturally appropriate tools to address adolescent mental health challenges in diverse settings.
Development and Evaluation of CirQA: A Parametric Tool for Circularity Quick Assessment and Lifecycle Impact in Early-Stage Building Design
Authors: Pibal Sophia Silvia , Rezk Karim , Kovacic Iva
Published: February 2025

The construction sector, which is responsible for nearly 40% of emissions and almost third of all waste generated, is under increasing pressure to integrate sustainability principles, particularly in the early design stage, where key decisions influencing a building’s lifecycle are made. This study presents the development and evaluation of the Circularity Quick Assessment tool (CirQA), aiming at accessibility to a broad range of users, including those with varying levels of expertise. CirQA employs parametric design methods and data repositories to generate digital building models with the corresponding environmental impact. A user study was conducted with professionals from various backgrounds to assess the tool's usability, design, relevance and decision-making impact. Both quantitative and qualitative data were collected, with qualitative data analyzed through thematic coding and SWOT analysis. Results indicated that CirQA was generally perceived as user-friendly and effective for early-stage sustainability assessments. Also, areas for refinement were identified, including improving the clarity of data presentation, enhancing the interface, and providing more detailed guidance on circularity metrics. The SWOT analysis identified strengths in the tool’s ease of use and comprehensive functionality, weaknesses in its interface usability and data interpretation, opportunities for broader integration and customization, and threats related to increasing complexity. The study concludes that CirQA holds significant potential to advance circular and life cycle-oriented building practices, with future efforts focused on optimizing user experience, expanding lifecycle metrics, and ensuring regulatory adaptability to enhance informed decision-making.
The Self-Computing Universe Hypothesis (SCUH): Consciousness as the Selector of Reality
Authors: Slettenhaar Wouter
Published: February 2025

This paper proposes the Self-Computing Universe Hypothesis (SCUH), a novel theoretical framework that integrates quantum mechanics, the philosophy of time, and the role of consciousness. Unlike traditional interpretations where consciousness is seen as a passive observer, SCUH posits that consciousness actively selects reality from a field of quantum possibilities within a dynamic, multidirectional temporal structure. We argue that what appears as randomness in quantum mechanics is a manifestation of deeper computational dynamics, and that time itself is not linear but a fluid medium navigated by conscious agency.
Setting the Stage for the Inner Journey: Unraveling the Interplay of Contextual Factors and the Intensity of Psychedelic-induced Ego Dissolution
Authors: Adamczyk Stanisław , Paczyńska Małgorzata , Ruban Anastasia , Szczypiński Jan , Bola Michał , Orlowski Paweł
Published: February 2025

Psychedelics have the potential to induce profound alterations in cognition, emotionality, and sensory perception. The quality and intensity of these subjective effects exhibit high intra- and inter-individual variability, which can potentially be accounted for by the variability in contexts in which psychedelics are used. Therefore, the aim of the present cross-sectional study was to investigate how internal and external contextual factors are related to the subjective intensity of psychedelic-induced ego dissolution experiences. Participants completed an online survey in which they reported their motivations for past use of psychedelic substances, and the frequency of use in different environments and social contexts. Additionally participants completed the Ego Dissolution Inventory to evaluate the intensity of past ego dissolution experiences. Robust linear regression analysis was performed on data from 862 psychedelics users (701 had used LSD and 553 had used psilocybin mushrooms); this revealed that participants consuming psychedelics for spiritual or self-healing purposes reported more intense, while those motivated by curiosity reported less intense ego dissolution experiences. However, the social context and physical environment did not exhibit robust associations with the reported ego dissolution. Therefore, our study enhances understanding of how set and setting factors relate to psychedelic-induced ego dissolution experiences in naturalistic contexts.
Strontium isotope mapping of elephant enamel supports a micro-sampling and modeling workflow to reconstruct past migrations
Authors: Yang Deming , Podkovyroff Katya , Uno Kevin , Bowen Gabriel , Fernandez Diego P. , Cerling Thure E.
Published: February 2025

Strontium isotope ratios (87Sr/86Sr) of incrementally grown tissues have been used to study animal movement/migration. Despite growing interest in this tool, questions remain regarding how different dental tissues preserve the same 87Sr/86Sr input signal, and how different biological processes and sampling methods influence measured enamel 87Sr/86Sr. We collected 87Sr/86Sr data from tusk dentine and molar enamel of Misha, a zoo elephant with known movement history, using in situ laser ablation (LA-ICP-MS) mapping, conventional drilling, and micromilling techniques. We compared 87Sr/86Sr data from different substrates to evaluate the influence of turnover, tissue type, and sampling methods. Our LA-ICP-MS analysis showed a remarkable 87Sr/86Sr geometry consistent with enamel apposition. Enamel maturation affects 87Sr/86Sr primarily in the outer enamel. Conventional drilling and micromilling produced attenuated 87Sr/86Sr records due to enamel maturation and sample averaging. Caution should be taken when interpreting 87Sr/86Sr data from conventionally drilled enamel, which may bias reconstructions of movement/migration. Our results show that LA-ICP-MS of the innermost enamel with associated dental growth measurements can best recover the primary 87Sr/86Sr turnover history. However, biological turnover of 87Sr/86Sr is still the primary source of input signal attenuation and should be accounted for. We recommend a micro-sampling and inverse modeling workflow which we demonstrate using Misha’s tusk and enamel data. While a broader application of this approach would benefit from more experiments, it can facilitate quantitative interpretations of movement/migration histories and help answer questions of individual life history such as human/animal seasonal subsistence and reproductive patterns.
First empirical assessment of ice content from Himalayan rock glaciers.
Authors: Harrison Stephan , Peacey Matthew , Irvine-Fynn Tristram , Hu Yan , Anderson Karen , Leng Ruolin , Sun Shangyu , Liu Lin
Published: February 2025

Climate warming in the Himalaya threatens glaciers and permafrost, with severe implications for the future sustainability of the region’s natural ‘water towers’ and connected ecological systems and human infrastructure. Recent work in high mountain environments has highlighted how rock glaciers are prevalent and contain globally valuable water supplies. Yet, over the Himalaya, information regarding their number, spatial distribution, morphometric characteristics and water content are scarce. Here, we present the first measured assessment of ice content in any Himalayan rock glacier. We use InSAR and Ground Penetrating Radar (GPR) surveys, respectively, to assess the current movement and ice content of a large rock glacier at Gokyo, central Nepal. This landform is situated at over 4700 m elevation and we show that parts of it are currently moving downslope at 75-100 cm per year; a figure in line with other rock glacier velocities in high arid mountains. This suggests that the rock glacier contains solid buried ice, and this is confirmed by our GPR surveys. We demonstrate the presence of massive ice units up to 250 m in length and 28 m in thickness underlies the rock glacier surface, representing an estimated total of up to 3.01 ×105 m3 of freshwater equivalent. We have recently reported that there are over 25,000 rock glaciers in the Himalayas. If the Gokyo rock glacier is representative for the region, then these landforms are likely to contain significant amounts of ice, and therefore will be of great hydrological value to downstream regions as climate change progresses and the buried ice slowly melts.
Beyond Single Hazard Framework: Multi-Hazard Worst Case Scenarios from Ensemble Tropical Cyclone Forecasts
Authors: Islam Md. , Oizumi Tsutao , Duc Le , Ota Takuma , Kawabata Takuya , Sawada Yohei
Published: February 2025

Ensemble forecasting is a powerful tool for supporting informed decision-making in managing multi-hazard risks associated with tropical cyclones (TCs). Although TC ensemble forecasts are widely used in operational numerical weather prediction systems, their potential for disaster prediction and management has not been fully exploited. Here we propose a novel, efficient, and practical method to extract meaningful Multi-Hazard Worst Case Scenarios (MHWCS) from a large ensemble TC forecast of 1000-members. We performed the ensemble atmospheric forecasting of TC Hagibis (2019) using the Japan Meteorological Agency's (JMA) nonhydrostatic model. The simulated atmospheric predictions were serving as inputs for the JMA’s operational flood forecast model, as well as statistical storm surge and gust wind models. These models estimate river flooding, storm surge, and wind hazard intensities in Tokyo. By accounting for uncertainties in ensemble multi-hazard forecasts, we objectively demonstrate that Pareto-optimal solutions can effectively identify the meaningful MHWCS. These solutions illustrate complex trade-offs among competing hazard components across various forecast locations. While some identified MHWCS pose severe risks for a single hazard type or location, others present moderately high risks across multiple hazards and locations. This diversity in potential scenarios requires risk managers to prepare multiple response strategies for both imminent risks and post-disaster management. Our findings further underscore the importance of evaluating Pareto-optimal solutions to assist forecasters and risk managers in understanding how combinations of TC meteorological variables—such as track, translation speed, size, intensity, and rainfall—shape worst-case scenarios.
Senescence driven solubilization of biomass is the main source of kelp-derived dissolved organic carbon to the coastal ocean
Authors: English Chance , Bell Tom , Opalk Keri , Siegel David , Carlson Craig
Published: February 2025

Kelp forests form some of the most productive areas on earth and are proposed to sequester carbon in the ocean, largely in the form of released dissolved organic carbon (DOC). Here we investigate the role of environmental, seasonal and age-related physiological gradients on the partitioning of net primary production (NPP) into DOC by the canopy forming giant kelp (Macrocystis pyrifera). Rates of DOC production were strongly influenced by an age-related decline in physiological condition (i.e. senescence). During the mature stage of giant kelp development, DOC production was a small and constant fraction of NPP regardless of tissue nitrogen content or light intensity. When giant kelp entered its senescent phase, DOC production increased substantially and was uncoupled from NPP and light intensity. Compositional analysis of giant kelp-derived DOC showed that elevated DOC production during senescence was due to the solubilization of biomass carbon, rather than by direct exudation. We coupled our incubation and physiological experiments to a novel satellite-derived 20-year time series of giant kelp canopy biomass and physiology. Annual DOC production by giant kelp varied due to differences in standing biomass between years, but on average, 74% of the annual DOC production by giant kelp was due to senescence. This study suggests DOC may be a more important fate of macroalgal NPP than previously recognized.
Towards a global deep learning model for daily soil CO2 efflux
Authors: Smykalov Valerie , Li Li , Vargas Rodrigo , Bond-Lamberty Ben
Published: February 2025

Soil CO2 efflux, the largest flux of CO2 to the atmosphere, is expected to rise globally under climate change. Its magnitude and temporal variability are highly uncertain, and daily-scale models capturing rapid changes to environmental drivers remain rare. We used a global database of soil CO2 efflux (total observations = 7,797,535 from 2002-2020) to train a deep learning model (Long Short-Term Memory, LSTM) to predict daily soil CO2 efflux in 82 sites across gradients of climate, soil type, and land cover. The model achieved a median train and test Nash Sutcliffe Efficiency (NSE) of 0.54 and 0.02, respectively, and Kling Gupta Efficiency (KGE) of 0.67 and 0.30, respectively. The model performed well (NSE > 0.5 and KGE > 0.3) at about one-third of sites, mainly in temperate mesic ecosystems (where most training sites were located) with cyclical data patterns driven by temperature. The model performed poorly at sites with little data and noncyclical temporal patterns, mostly at extreme climates including arid, Arctic/boreal, and tropical ecosystems. The model struggled to capture soil CO2 efflux pulses and peaks/troughs, highlighting the challenges of modeling extremes in time series. Our results demonstrate that LSTM models can leverage existing data to generate synthetic daily datasets, particularly for temperate mesic regions, but also underscore the challenges of learning relationships from a spatially biased dataset. To improve model performance, future data collection should prioritize 1) historically underrepresented ecosystems with variable temperature relationships; 2) conditions under extreme weather events that may become disproportionally impactful in a warming climate.