bluuebunny/crossref_metadata_2025 huggingface dataset:
Linking Health Terminologies: A Unified Approach to the WHO Family of International Classifications
Authors: Tu Samson W. , Almborg Ann-Helene , Martinuzzi Andrea , Della Mea Vincenzo , Giannangelo Kathy , Chute Christopher G. , Linton Cassandra , Cornet Ronald , Celik Can , Jakob Robert
Published: August 2024

This paper presents an effort by the World Health Organization (WHO) to integrate the reference classifications of the Family of International Classifications (ICD, ICF, and ICHI) into a unified digital framework. The integration was accomplished via an expanded Content Model and a single Foundation that hosts all entities from these classifications, allowing the traditional use cases of individual classifications to be retained while enhancing their combined use. The harmonized WHO-FIC Content Model and the unified Foundation has streamlined the content management, enhanced the web-based tool functionalities, and provided opportunities for linkage with external terminologies and ontologies. This integration promises reduced maintenance cost, seamless joint application, complete representation of health-related concepts while enabling better interoperability with other informatics infrastructures.
UNICOM Test Lab: Implementation of ISO’s IDMP Standards Across the EU
Authors: Karanikas Haralampos , Gkogkidis Anargyros , Berler Alexander , Veggiotti Nicole , Diaco Simone , Spinozzi Giulio , Foglia Tommaso , Franconi Sofia , Teixeira José Costa , Ritz Derek , Stegwee Robert , Ishfaq Zain , Melgara Marcello , Garbarino Luca
Published: August 2024

The UNICOM Test Lab enhances patient safety and healthcare efficiency by implementing ISO’s IDMP standards across the EU. Funded by the EU’s HORIZON Programme, this initiative unites diverse stakeholders to enable the seamless exchange of medicinal product information. This paper details the interoperability challenges and methodologies employed, highlighting the UNICOM Test Lab’s role in validating and testing tools for IDMP standards implementation, aiming for semantic interoperability and a safe pharmaceutical supply chain within the EU.
From Syntactic to Semantic Interoperability Using a Hyperontology in the Oncology Domain
Authors: El Ghosh Mirna , Kalokyri Varvara , Sambres Mélanie , Vaterkowski Morgan , Duclos Catherine , Tannier Xavier , Tsakou Gianna , Tsiknakis Manolis , Daniel Christel , Dhombres Ferdinand
Published: August 2024

Interoperability is crucial to overcoming various challenges of data integration in the healthcare domain. While OMOP and FHIR data standards handle syntactic heterogeneity among heterogeneous data sources, ontologies support semantic interoperability to overcome the complexity and disparity of healthcare data. This study proposes an ontological approach in the context of the EUCAIM project to support semantic interoperability among distributed big data repositories that have applied heterogeneous cancer image data models using a semantically well-founded Hyperontology for the oncology domain.
HCE2RNFC: An Efficient Methodology for Reusing the EHR in the Spanish National Hip Fracture Registry
Authors: Rubio-Mayo Paula , Ojeda-Thies Cristina , Jiménez-Cerezo María Jesús , Garcia-Barrio Noelia , Cruz-Bermúdez Juan Luis , Pedrera-Jiménez Miguel
Published: August 2024

Hip fracture is a condition associated with ageing and frailty, with an associated prevalence of 7 per 10000 population in Spain. Evidence suggests that factors in the healthcare process can influence clinical outcomes, so the creation of a national registry is an opportunity to monitor and improve this process. In this regards, Electronic Health Record (EHR) can provide a large amount of data, that can be used to populate the Spanish National Hip Fracture Registry (RNFC, by its acronym in Spanish). However, this reuse of the EHR requires a prior effort in modelling and standardization to build the extraction, transformation, and loading (ETL) processes in a flexible, transparent, and scalable manner. In this work, a robust EHR reuse methodology is implemented to obtain EHR-derived data for the RNFC. The main result of this work was the design and implementation of an EHR data reuse methodology, which was able to load 1279 hip fracture cases and almost 68% of the required concepts from the RNFC.
Optimizing Integration with the Italian EHR: The Use of LOINC Codes
Authors: Murgia Ylenia , Cataldi Mauro , Illario Maddalena , Giacomini Mauro
Published: August 2024

According to the regulation “Decreto del Presidente del Consiglio dei Ministri” (DPCM) of September 29, 2015, n.178, the Logical Observation Identifiers Names and Codes (LOINC) system is included among the coding systems adopted in the Italian Electronic Health Record (EHR). As part of the Digital Health Solutions in Community Medicine (DHEAL-COM) project, one key goal is to categorize parameters using international classification systems. This enables the identification of appropriate Information and Communication Technology (ICT) solutions tailored to support people’s health needs. Our objective is to incorporate LOINC codes for parameter categorization, thus anticipating the future use of EHR.
Education Challenges Among Early Career Researchers in Medical Informatics
Authors: Rohani Narjes , Gallagher Michael , Gal Kobi , Manataki Areti
Published: August 2024

There is limited knowledge about early career researchers’ challenges when studying the interdisciplinary field of Medical Informatics (MI). We conducted a qualitative content analysis through semi-structured interviews with early career researchers in MI, including individuals pursuing Master’s, PhD, and postdoctoral research programmes, across two higher education institutions in the UK. We identified five challenges, including understanding biological jargon, interpreting biological data, interdisciplinary communication, understanding mathematical/statistical concepts, and programming difficulties. These insights and suggested actions to address those challenges can help to improve MI education.
Predicting Patient No-Shows: Situated Machine Learning with Imperfect Data
Authors: Gyldenkærne Christopher , Simonsen Jakob Grue , From Gustav , Hertzum Morten
Published: August 2024

Patients who do not show up for scheduled appointments are a considerable cost and concern in healthcare. In this study, we predict patient no-shows for outpatient surgery at the endoscopy ward of a hospital in Denmark. The predictions are made by training machine leaning (ML) models on available data, which have been recorded for purposes other than ML, and by doing situated work in the hospital setting to understand local data practices and fine-tune the models. The best performing model (XGBoost with oversampling) predicts no-shows at sensitivity = 0.97, specificity = 0.66, and accuracy = 0.95. Importantly, the situated work engaged local hospital staff in the design process and led to substantial quantitative improvements in the performance of the models. We consider the results promising but acknowledge that they are from a single ward. To transfer the no-show models to other wards and hospitals, the situated work must be redone.
Unsupervised Learning of Eye State Prototypes for Semantically Rich Blinking Detection
Authors: Xie Yuxuan , Büchner Tim , Schuhmann Lukas , Guntinas-Lichius Orlando , Denzler Joachim
Published: August 2024

Blinking contributes to the health and protection of the eye and also holds potential in the context of muscle or nerve disorder diagnosis. Traditional methods of classifying eye blinking as open or closed are insufficient, as they do not capture medical-relevant aspects like closure speed, duration, or percentage. The issue could be solved by reliably detecting blinking intervals in high-temporal recordings. Our research demonstrates the reliable detection of blinking events through data-driven analysis of the eye aspect ratio. In an unsupervised manner, we establish an eye state prototype to identify blink intervals and measure inter-eye synchronicity between moments of peak closure. Additionally, our research shows that manually defined prototypes yield comparable results. Our results demonstrate inter-eye synchronicity up to 4.16 ms. We anticipate that medical professionals could utilize our methods to identify or define disease-specific prototypes as potential diagnostic tools.
An LLM-Based Visualization and Analysis Aid for a Secondary Use Clinical Data Platform
Authors: Spiegel Sören , Wendt Thore , Gundler Christopher , Ückert Frank , Riemann Layla Tabea
Published: August 2024

This work introduces a novel approach to facilitate clinical research on secondary clinical data by integrating an LLM-based chatbot within a specialized platform called data hotel. The platform is designed to empower clinical researchers within our institution by enabling the generation of research hypotheses from secondary use patient data sources. Our focus in this work is on the deployment and functionality of the LLM-based chatbot within the data hotel ecosystem. The aim is to aid medical experts in visualizing and analyzing data sourced from the platform but also to enable the seamless storage of the generated code, enhancing the efficiency and reproducibility of the research process. This integration represents a significant advancement in leveraging LLM capabilities to enhance the utility and accessibility of clinical research platforms.
From Data Mining of Public Sources to Clinical Decision Support in Personalized Medicine
Authors: Vishnevskaya Valeriya , Sigle Stefan , Fegeler Christian
Published: August 2024

Personalized medicine enables precise tumor treatment for a patient’s molecular genetic profile. To devise optimal targeted treatment plans for patients in a molecular tumor board, physicians must consider alterations on gene- and proteins levels but also cancer cell phenotypes. Machine learning can uncover buried patterns, extract pivotal information, and unveil corresponding insights from available data. Publicly available datasets provide the amounts of data necessary. This work outlines the efficacy of various machine learning algorithms which could eventually serve as clinical decision support in a precision oncology setting. Leveraging algorithms including Random Forest, Decision tree, XGBoost, Logistic regression, Gaussian Naive Bayes, k nearest neighbor, and AdaBoost, we conducted two experiments for the breast invasive carcinoma dataset. Incorporated data includes patient-, molecular- and treatment data. The aim of the investigation was to predict medication treatment or type of treatment based on genetic profile. After preprocessing and application of ML algorithms, the first results were promising. Multiple factors challenge application in clinical care settings without carefully considering the limitations.
Leveraging FHIR in Federated Learning Environments: A Data Harmonization Framework for Cohort Studies
Authors: Cadavid Héctor , Arends Bauke
Published: August 2024

MyDigiTwin is a scientific initiative for the development of a platform for the early detection and prevention of cardiovascular diseases. This platform, which is supported by prediction models trained in a federated fashion to preserve data privacy, is expected to be hosted by the Dutch Personal Health Environments (PGOs). Consequently, one of the challenges for this federated learning architecture is ensuring consistency between the PGOs data and the reference datasets that will be part of it. This paper introduces a novel data harmonization framework that streamlines an efficient generation of FHIR-based representations of multiple cohort study data. Furthermore, its applicability in the integration of Lifelines’ cohort study data into the MiDigiTwin federated research infrastructure is discussed.
Harnessing the Power of Machine Learning and Electronic Health Records to Support Child Abuse and Neglect Identification in Emergency Department Settings
Authors: Landau Aviv Y. , Blanchard Ashley , Kulkarni Paritosh , Althobaiti Shahad , Idnay Betina , Patton Desmond U. , Cato Kenrick , Topaz Maxim
Published: August 2024

Emergency departments (EDs) are pivotal in detecting child abuse and neglect, but this task is often complex. Our study developed a machine learning model using structured and unstructured electronic health record (EHR) data to predict when children in EDs might need intervention from child protective services. We used a case-control study design, analyzing data from a pediatric ED. Clinical notes were processed with natural language processing (NLP) techniques to identify suspected cases and matched in a 1:9 ratio to ensure dataset balance. The features from these notes were combined with structured EHR data to construct a model using the XGBoost algorithm. The model achieved a precision of 0.95, recall of 0.88, and F1-score of 0.92, with improvements seen from integrating NLP-derived data. Key indicators for abuse included hospital admissions, extended ED stays, and specific clinical orders. The model’s accuracy and the utility of NLP suggest the potential for EDs to better identify at-risk children. Future work should validate the model further and explore additional features while considering ethical implications to aid healthcare providers in safeguarding children.
Automatic Extraction of Medication Data from Semi-Structured Prescriptions
Authors: Oehm Johannes Benedict , Wenning Oliver , Storck Michael , Jiang Xiaoyi , Varghese Julian
Published: August 2024

In many healthcare facilities, the prescription of drugs is done only in a semi-structured manner, using free-text fields where various information is often mixed. Therefore, automatic processing, especially for secondary use such as research purposes, is often challenging. This paper compares various approaches that identify and classify the various parts of these free-text fields in German language, namely simple Levenshtein-based, rule-based and CRF (conditional random field)-based approaches. Our results show that a F1-score >90% can be achieved with both the rule-based and the CRF-based approach, with the CRF-based approach even reaching nearly 95%.
From Affect Regulation to BMI: Unveiling Childhood Obesity Patterns Through Advanced Clustering Techniques
Authors: Feretzakis Georgios , Harokopou Athanasia , Fafoula Olga , Anastasiou Athanasios , Katoikou Efstathia , Balaska Athina , Koulountzou Antriana , Zagkavieros Georgios , Batzaki Stamatia , Morou Lida , Katsikogiannis Ioannis , Dalainas Ilias , Gkritzelas Georgios
Published: August 2024

This study explores the relationship between psychological factors and children’s BMI, using clustering methods like Gaussian Mixture Models and Spectral Clustering. Affinity Propagation was particularly effective, suggesting that tailored interventions based on psychological assessments could improve obesity management in children.
Continuous Monitoring by a Wearable Sensor Did Not Enhance Discharge Decision-Making in an Acute Admission Ward: Results of a Randomized Controlled Trial
Authors: Kant Niels , Garssen Sjoerd H. , Vernooij Carlijn A. , Mauritz Gert-Jan , Koning Mark V. , Bosch Frank H. , Doggen Carine J.M.
Published: August 2024

Adding continuous monitoring to usual care at an acute admission ward did not have an effect on the proportion of patients safely discharged. Implementation challenges of continuous monitoring may have contributed to the lack of effect observed.
A Decision Support Alert for Promoting Prophylactic Laxative Use with Clozapine
Authors: Sundermann Milan , Every-Palmer Susanna , Kl Chin Paul
Published: August 2024

We investigated the effectiveness of a decision support alert to improve prophylactic laxative use with clozapine in hospital. Prescribing data for first clozapine and laxative prescriptions were extracted and linked. Proportions of first clozapine prescriptions for which a laxative was co-prescribed within 24 hours was compared before and after alert implementation. The alert was associated with increased and earlier laxative co-prescribing.
User Experience Design for Intensive Care Alarm Management
Authors: Flint Anne Rike , Heeren Patrick , Klopfenstein Sophie A.I. , Poncette Akira-Sebastian
Published: August 2024

Alarm fatigue is a pressing issue in intensive care units. Based on user experience design, including clinical shadowings and feedback loops, we developed a prototype for a redesigned patient monitor: The prototype moves away from today’s threshold-based alarm systems. It combines a sleek design with machine learning driven clinical insights to mitigate alarm fatigue.
Collaborative Care Interventions for Patients with Multimorbidity: Protocol for a Systematic Review and Meta-Analysis with Preliminary Results
Authors: Knudsen Anne-Maj , Dunvald Ann-Cathrine D. , Hangaard Stine , Hejlesen Ole , Kronborg Thomas
Published: August 2024

Collaborative care interventions have been proposed as a promising strategy for the management of patients with multimorbidity. This systematic review and meta-analysis aims to assess the effectiveness of collaborative care interventions for adult patients with multimorbidity. Furthermore, a meta-regression analysis is planned to determine if certain participant or intervention characteristics can explain variance in effect.
PICO to PICOS: Weak Supervision to Extend Datasets with New Labels
Authors: Dhrangadhariya Anjani , Manzo Gaetano , Müller Henning
Published: August 2024

Hand-labelling clinical corpora can be costly and inflexible, requiring re-annotation every time new classes need to be extracted. PICO (Participant, Intervention, Comparator, Outcome) information extraction can expedite conducting systematic reviews to answer clinical questions. However, PICO frequently extends to other entities such as Study type and design, trial context, and timeframe, requiring manual re-annotation of existing corpora. In this paper, we adapt Snorkel’s weak supervision methodology to extend clinical corpora to new entities without extensive hand labelling. Specifically, we enrich the EBM-PICO corpus with new entities through an example of “Study type and design” extraction. Using weak supervision, we obtain programmatic labels on 4,081 EBM-PICO documents, achieving an F1-score of 85.02% on the test set.
Development of a Mental Health Apps Recommender Platform
Authors: Tapuria Archana , Alexander Jorge , Marchal Ariane , Cong Cen , Meinert Edward , Shankar Rohit , Ananthakrishnan Ananya , Lakey Ben
Published: August 2024

Introduction: The aim of the paper is to establish the requirements and methodology for the development and implementation of a recommender system for mental health apps to support patients in self-managing their mental health while awaiting formal treatment. Methods: The system was developed using an algorithm-based approach, including: (1) user needs assessment through literature review and interviews with various stakeholders, (2) software modelling and prototype creation, and (3) bench testing of the prototype with health experts and users. Results: Based on initial exploration of users’ requirements, relevant standards and regulations, a library of trusted mental health apps was compiled and a recommendation engine was built to generate accurate user profiles and deliver personalised health recommendations, which will be further tested to ensure quality. Conclusion: Developing a constructive mental health recommendation system requires the establishment of clear and comprehensive requirements, as well as a robust methodology adressing concerns related to data security, confidentiality, safety, and reliability. Subsequent research may compare various indicators of mental health outcomes at the start and end of patients’ waiting period to gain more insights into how the recommender system could be further improved to enhance user experience and their overall well-being.
Linking Maternal and Child Health Data to Enhance Public Health Surveillance and Implement Sustainable Interventions
Authors: Dixon Brian E. , Inderstrodt Jill , Riggins Daniel P. , Price John P. , Schlyer Titus K.L. , Grannis Shaun J.
Published: August 2024

Our initiative aims to enhance the public health informatics infrastructure for surveillance of maternal and child health (MCH) using data captured from electronic health records (EHRs), public health information systems, and administrative health data. Our work includes development, validation, and application of linkage algorithms across records for mothers and children; integration of data across myriad sources; design of routine surveillance reports; and design of longitudinal studies to examine determinants and outcomes in MCH populations. Our work is conducted in partnership with governmental public health agencies, health care providers, academic institutions, and community-based organizations. Future work will build on the enhanced informatics infrastructure to draw from additional public health data sources and/or expand surveillance efforts to include prioritized MCH outcomes. We will further translate knowledge gained from surveillance into action, working with our partners to improve and sustain better MCH equitably in our population.
Challenges in Daily Computerized Assessment of Cognitive Functions of Post-COVID Patients
Authors: Knak Ann-Kathrin , Roheger Mandy , Wulff Antje
Published: August 2024

While it would be quite helpful to learn more about the daily fluctuations of fatigue and cognitive impairments of post-COVID patients, their condition can make investigating these especially challenging. By discussing these issues with post-COVID patients and clinical practitioners, we identified six challenges that specifically apply to daily computerized assessment of cognitive functions of post-COVID patients. We proposed solutions for each of the challenges which can be summarized as offering a carefully planned and flexible study design to participants and monitoring their well-being throughout the assessments. We argue that when the proposed precautions are taken, it is feasible to conduct a study that will generate valuable insights into the trajectories of (cognitive) post-COVID symptoms.
Greek Tweets on Long COVID: Topic Modelling Following Sentiment Analysis and ChatGPT Interpretation
Authors: Katika Afroditi , Zoulias Emmanouil , Koufi Vassiliki , Malamateniou Flora
Published: August 2024

Long COVID is a disease that makes it hard for patients to get an official diagnosis while it impacts their quality of life. Many people are turning to social networks such as Facebook, WhatsApp, Twitter (now X) to express their opinions and feelings regarding Long COVID. In this paper, positive (or neutral) and negative text messages in the Greek language, posted on the Twitter platform in 2022, regarding Long COVID are analyzed and popular discussion topics are extracted. Analysis revealed that when topic modelling follows sentiment analysis more coherent topics are created. Furthermore, ChatGPT is used to assign a label to each topic that, in turn, is assessed by a human expert.
Deep Learning Models for Health-Driven Forecasting of Indoor Temperatures in Heat Waves in Canada: An Exploratory Study Using Smart Thermostats
Authors: Kaur Jasleen , Singh Gurjot , Oetomo Arlene , Kaur Navneet , Morita Plinio P.
Published: August 2024

In Canada, extreme heat occurrences present significant risks to public health, particularly for vulnerable groups like older individuals and those with pre-existing health conditions. Accurately predicting indoor temperatures during these events is crucial for informing public health strategies and mitigating the adverse impacts of extreme heat. While current systems rely on outdoor temperature data, incorporating real-time indoor temperature estimations can significantly enhance decision-making and strengthen overall health system responses. Sensor-based technologies, such as ecobee smart thermostats installed in homes, enable effortless collection of indoor temperature and humidity data. This study evaluates the efficacy of deep learning models in predicting indoor temperatures during heat waves using smart thermostat data, to enhance public health responses. Utilizing ecobee smart thermostats, we analyzed indoor temperature trends and developed forecasting models. Our findings indicate the potential of integrating IoT and deep learning into health warning systems, enabling proactive interventions, and improving sustainable health care practices in extreme heat scenarios. This approach highlights the role of digital health innovations in creating the resilient and sustainable healthcare systems against climate-related health adversities.
Training and Mentoring: Improving Pedagogical Competence of Catholic Religious Education Teachers
Authors: Sihotang Din Oloan , Lumbanbatu Johannes Sohirimon , Waruwu Ermina , Siregar Mariana , Tarigan Fransiskus
Published: August 2024

Improving the pedagogical competence of Catholic Religious Education teachers in Karo District's elementary schools is typically carried out through Teacher Working Groups (KKG) or workshops. Workshops for teachers usually focus on developing instructional materials. The implementation of Community Service (PkM) aims to enhance the pedagogical competence of teachers in planning and conducting lessons, organizing educational teaching methods, and utilizing information technology in teaching. The PkM activities consist of a two-day training session followed by two months of mentoring. The results show a significant improvement in the indicators of teachers' pedagogical competence, while partner satisfaction evaluations reflect the positive impact of these activities. It is expected that the Director General of Catholic Religious Affairs will ensure that each teacher competency improvement program includes concrete steps and a continuous monitoring and evaluation system to ensure the effective sustainability of pedagogical competence enhancement.
Pelancu Ecotourism Recovery Strategy in Ulak Pandan Village After the COVID-19 Pandemic
Authors: Syachroni Sasua Hustati , Helida Asvic , Mahni Imam
Published: August 2024

The pandemic conditions caused by Covid-19 have caused a quite drastic decline in the tourism sector in Indonesia, even though the tourism sector contributes as a source of income for the country. This research aims to increase the potential of Pelancu ecotourism by implementing a strategy to develop Pelancu ecotourism after the Covid-19 pandemic. This research was carried out in Ulak Pandan Village, West Merapi District, Lahat Regency, South Sumatra Province from September to November 2022. The research method used qualitative methods. Descriptive analysis, in collecting samples, descriptive data is produced in the form of words or verbally from several sources, namely the village government including the Village Head and BPD (Village Consultative Body), tourism managers, and the surrounding community as well as Pelancu Tourism tourists.  The research results show that the condition of Pelancu Tourism after the Covid-19 pandemic is well maintained, cool and beautiful. The arrangement of the Pelancu Tourism area is maintained, especially the cleanliness of the surrounding environment, which is the responsibility of the Pelancu Tourism object management. Some of the shortcomings found after the Covid pandemic were that the management did not pay enough attention to the infrastructure at Pelancu Tourism. The strategy for restoring Pelancu ecotourism in Ulak Pandan Village that the management will carry out is by adding several facilities such as the addition of children's park play equipment and infrastructure such as family food huts, photo-taking rides to attract the interest of tourists who come to Pelancu Tourism like before the Covid-19 pandemic. happen. Then by promoting it on social media, including Instagram, Facebook, etc. By updating posts on the Pelancu Tourism website and social media.
Golput Perspektif Undang-Undang Nomor 7 Tahun 2017 Tentang Pemilihan Umum dan Siyasah Dusturiyah
Authors: Habibah Habibah , Adan Hasanuddin Yusuf
Published: August 2024

Abstention is indirectly related to feelings of distrust towards potential leaders or contesting political parties. Golput is also often seen as a form of protest or dissatisfaction with the political system. This research examines the legal review of abstention from the perspective of the laws of the Republic of Indonesia and perspective of siyasah dusturiyah. The research method used is library research with a qualitative approach. The data source used is based on the results of a review of Law no. 39 of 1999 concerning human rights, Law no. 7 of 2017 concerning the holding of general elections, as well as the 2009 MUI Fatwa and opinions from contemporary ulama. The results of the research show that Indonesian legislation states that abstention is a constitutional right granted by the government to the people. so that the people have authority over voting rights and are allowed to exercise these rights or not. Meanwhile, from the siyasah dusturiyah perspective, choosing a leader is obligatory. If all Muslims in Indonesia abstain from voting then they are sinning, because the law requires fardu kifayah. Abstentions have the potential to give unqualified or unfit people the chance to become leaders. So it gives rise to mafsadat against Islamic law. However, in conditions where Muslims live in non-Muslim countries, abstention is recommended because it does not give loyalty or trust to the wrong people.
Pengembangan Strategi Komunikasi Yang Efektif Pada Badan Pengawas Pemilihan Umum Provinsi Jawa Barat
Authors: Hermawan Herry
Published: August 2024

Election is not only an indicator of democracy, but also an important part of democracy. In implementing this democratic process, the election supervisory institution (Badan Pengawas Pemilihan Umum - Bawaslu) develops a communication strategy as a preventive effort against potential violations in the election. So, the role of Bawaslu is to design messages to persuade and motivate the public so they  activelyparticipate to create clear and clean election. The aim of this program is, for participants, to understand effective communication strategies and to have effective communication skills. The participants were members of the Public Relations Division of Bawaslu in the area of West Java, totaling 40 people. The program was carried out from 17 November 2022 up to 18 November 2022 in Bogor City, and 15 December 2022 in Bandung District. The development of an effective communication strategy is carried out using lecture, practice and question and answer methods. Overall, these activities, both public relations development and writing press releases training, can be said to be successful. The benefit is they can know, understand and apply better communication techniques and these qualities can be used as points in assessing the quality of Bawaslu.
Strategi Meningkatkan Kesejahteraan Masyarakat Berbasis Masjid: Studi Pada Masjid-Masjid di Kota Tangerang Selatan
Authors: Rusmiati Elis Teti
Published: August 2024

Penelitian ini bertujuan untuk menganalisis strategi yang dapat digunakan untuk meningkatkan kesejahteraan masyarakat melalui peran masjid sebagai pusat kegiatan sosial dan spiritual. Kota Tangerang Selatan dipilih sebagai lokasi penelitian karena memiliki sejumlah masjid yang aktif dalam menyelenggarakan program dan kegiatan untuk masyarakat setempat. Penelitian ini menggunakan pendekatan kualitatif dengan teknik pengumpulan data melalui observasi, wawancara, dan studi dokumentasi. Kerangka teori melibatkan teori sosiologi masjid, teori pengembangan masyarakat berbasis masjid, dan konsep strategi meningkatkan kesejahteraan masyarakat. Analisis data dilakukan melalui analisis deskriptif, analisis korelasi antara kegiatan masjid dan kesejahteraan masyarakat, serta analisis faktor-faktor yang mempengaruhi kesejahteraan masyarakat. Temuan-temuan utama dalam penelitian ini menunjukkan bahwa agenda peningkatan kesejahteraan masyarakat menjadi agenda penting yang diprogramkan  pengurus masjid. Hanya saja berbeda dalam bentuk implementasinya serta dalampenyelenggaraannya. Kemampuan SDM pelaksana juga beragam sehingga dari kelima masjid yang diteliti menghasilkan output dan outcome yang bervariasi. Bentuk dari peningkatan kesejahteraan pada umumnya berupa peningkatan pendapatan, pengurangan pengeluaran konsumsi, bantuan akses pelayanan kesehatan, dan bantuan biaya pendidikan.
EFL STUDENTS' PERCEPTION ON THE TYPE OF TEACHER QUETIONS: A QUALITATIVE DESCRIPTIVE STUDY
Authors: Yahya Roza Auliya , Kaniadewi Nita
Published: August 2024

This study explores high school EFL students' perceptions of teacher questioning strategies, focusing on question types, their use, and effectiveness in enhancing engagement and comprehension. Questioning techniques are vital in EFL classrooms, promoting interaction, critical thinking, and understanding. This qualitative descriptive study involved ten first-year high school students from SMAN 58 Jakarta, using observations, semi-structured interviews, and documentation of student grades. The findings reveal that teachers frequently use open-ended questions at the beginning of lessons to review previous material and stimulate critical thinking, with students preferring these types of questions for fostering broader thinking and active participation. Teachers predominantly use Lower Order Thinking Skills (LOTS) questions initially, shifting to Higher Order Thinking Skills (HOTS) questions during exams. Students perceive that teacher questioning techniques significantly enhance their understanding and engagement, aligning with previous research indicating that effective questioning leads to better outcomes in EFL classrooms. The study underscores the importance of employing diverse questioning strategies to support language development and academic achievement, providing valuable insights into effective pedagogical practices for EFL teachers. This research highlights the need for strategic questioning to enhance student learning experiences, motivation, and comprehension.
An Analysis of Educational Policies Related to The Implementation of The Merdeka Curriculum in Madrasah
Authors: Putri Rahmi , Gunawan Rilla Gina , Ramadhani Yulia Rizki , Gistituati Nurhizrah , Rusdinal Rusdinal
Published: August 2024

The implementation of the Merdeka Curriculum in madrasahs, guided by the Ministry of Religious Affairs Regulation (KMA) Number 347 in 2022, offers both advantages and challenges. This policy empowers madrasahs in Indonesia to develop education unit-level curricula that cater to the specific needs and management of education. The advantages of implementing the Merdeka Curriculum lie in its ability to respect and enhance Islamic education. Madrasahs can emphasize religious understanding, Quranic studies, and character education, enabling students to deepen their religious knowledge and strengthen their religious identities. Moreover, the curriculum's flexibility allows madrasahs to tailor educational experiences to the needs, social contexts, and local cultures of their students, making learning more relevant and meaningful. By incorporating practical and contextual subjects, the Merdeka Curriculum facilitates the development of broader skills, equipping students with academic, social, and life skills essential for their holistic growth. However, challenges arise in implementing the Merdeka Curriculum. Educators need comprehensive training and professional development to effectively design and implement a flexible curriculum. Ensuring consistent education standards across madrasahs is also crucial, as the freedom to determine curricula may result in variations. Integration with the national curriculum is essential to ensure that fundamental subjects such as literacy, numeracy, and general knowledge are adequately covered.
Exploring the Impact of Artificial Intelligence on Student Creativity in Vietnamese Tertiary EFL Classrooms: Teacher Perspectives
Authors: Pham Trut Thuy , Le Thanh Thao
Published: August 2024

This qualitative study investigates the perceptions of Vietnamese tertiary English as a Foreign Language (EFL) teachers regarding the impact of artificial intelligence (AI) on student creativity in language learning. Amidst the rapid integration of AI in educational contexts, this research focuses on a relatively unexplored area: the intersection of AI technology and creative language pedagogy in the Vietnamese educational setting. Nine EFL teachers from two institutions in Vietnam, representing novice, mid-career, and near-end career stages, participated in semi-structured interviews. The study employed the Technology Acceptance Model (TAM) and the Creativity in Language Learning Framework (CLLF) as its theoretical basis. Thematic analysis of the interview data revealed four key themes: the perceived impact of AI on creative language practice, challenges in integrating AI with creative pedagogy, varied perceptions of AI’s role in developing student autonomy, and the impact of AI on traditional teaching methods and teacher roles. The findings indicated a spectrum of perspectives, from viewing AI as a beneficial tool for creative engagement to concerns over its potential to limit creative thinking and traditional pedagogical approaches. The study highlights the complexity of integrating AI into language learning and its influence on both teaching practices and student creativity.
Research on the construction of English "eco-classroom" in primary schools under the perspective of ecological linguistics
Authors: ZHENG Qiyun
Published: August 2024

Eco-linguistics is a new research field with the characteristics of interdisciplinary research. Its founder, Haugen, who compared the English teaching classroom to an ecological system composed of various ecological factors, thus coming to the term "eco-classroom". "Eco-classroom" is a dynamic and balanced ecosystem composed of teachers, students, classroom natural environment and classroom humanistic environment. Starting from the ecological linguistics horizon, this article explores the current primary school English ecological teaching system, and from the ecological classroom teaching concept, ecological factor interaction, the all-round development of English ability, this article puts forward the primary school English "eco-classroom" building countermeasures, in order to improve students' English language learning ability, application ability, and promote the deepening reform of English teaching mode.
An Analysis of the Structural Layout and Artistic Conception Creation of Contemporary Erhu Performance Art
Authors: Zhou Lian
Published: August 2024

Erhu, as the most representative traditional stringed instrument in China, is deeply loved by the audience for its unique timbre and rich expressive force. With the rapid development of China’s literary and artistic undertakings, contemporary Erhu performance art has not only formed a relatively standardized and complete structural model, but also created a beautiful artistic conception in the process of performance, fully reflecting the charm of contemporary Erhu performance art.
Exploration of graduate students' mental health education practice - based on the case analysis of a multi-causal psychological issue
Authors: REN Lijuan
Published: August 2024

Mental health education for graduate students is an important part of the training process in higher education institutions. Paying attention to the mental health status of graduate students, timely identification of issues, and provision of scientific psychological counseling are crucial tasks for graduate student advisors. In the process of addressing a case with multiple causal factors for a graduate student's psychological issues, a "three vertical and three horizontal" mechanism for investigating and tracking psychological problems was established. This method clarified a "1, 2, 3" approach to solving graduate students' mental health issues, contributing to the formation of a mental health education system for graduate students in higher education institutions, aiming to inspire advisors in carrying out mental health work with graduate students.
Research on the integration of campus running App into college public physical education curriculum
Authors: WANG Chunfang
Published: August 2024

This paper takes the current situation of the integration of campus running APP into public physical education courses in colleges and universities in Zhejiang Province as the research object, and understands the current situation of the integration of campus running APP into public physical education courses in colleges and universities through investigation and research, and points out the problems to be solved. At the same time, this paper puts forward a "two-in-one" campus running APP service model, which serves students' extracurricular physical exercise with high quality in schools and campuses, and provides effective countermeasures for further integrating campus running APP into public physical education courses in colleges and universities reasonably and efficiently.
Research on the deep integration and development of "artificial intelligence+cultural industry" in China
Authors: XIE Huiling
Published: August 2024

With the rapid development of technology, artificial intelligence (AI) has gradually integrated into every aspect of people's lives and has formed a deeper integration with various industries. Among them, as an important carrier of inheritance and innovation, the deep integration and development of the cultural industry and artificial intelligence have not only brought revolutionary changes to the cultural industry, but also endowed it with more profound significance. Based on this, this article briefly analyzes the significance of the deep integration of "artificial intelligence+cultural industry" in China, and conducts in-depth exploration of the current situation of the deep integration development of "artificial intelligence+cultural industry". It proposes effective strategies to promote the deep integration development of "artificial intelligence+cultural industry" in China for reference.
Innovative thinking and exploration of teaching evaluation in colleges under the background of intelligent education
Authors: ZHAO Liyan
Published: August 2024

Intelligent education is the advanced stage of the development of digital education and a new form of education in the digital era. The teaching evaluation of university teachers is an important link to ensure the quality of talent training and improve the level of education and teaching. The digital and intelligent transformation provides new ideas and methods for the teaching evaluation of university teachers. This paper analyzes the four innovative ideas of multi-dimensional evaluation, data-based, evidence-based evaluation and process orientation of teaching evaluation under the background of intelligent education, and expounds the realization path and practical significance of the four innovative teaching evaluation concepts respectively, in order to provide ideas for the innovative reform of teaching evaluation in universities under the background of digital education.
Research on specific implementation path of digital empowerment in college English teaching in local private universities
Authors: WANG Xiaosa
Published: August 2024

In the digital era, with the rapid development of information technology, digital technology has penetrated into all aspects of the field of education, bringing unprecedented changes to higher education. As an important part of the higher education system, how to seize the opportunity in the digital world and realize the innovation and development of college English teaching has become an urgent problem to be solved. College English, as a basic course of higher education, is of great significance in cultivating students' intercultural communication ability and international vision. However, due to various factors, college English teaching in local private universities generally faces some problems, such as insufficient teaching resources, single teaching methods and poor English application ability of students. The introduction of digital technology provides new ideas and methods to solve these problems.
Analyzing the "writing" in abstract expression oil painting
Authors: LIN Jin , SUN Shixin
Published: August 2024

In order to communicate with others and express their inner thoughts, human beings invented writing, and the term "writability" triggered by writing is not only used in calligraphy, but also in painting, which shows human beings' feelings and emotions towards the world when they are painting. In painting, "writing" also shows human's feelings and emotions towards the world when painting, which is a summary of the past, a record of the current experience, as well as the expectation and speculation of the future. This paper analyzes "writability" in abstract expression oil painting, firstly introduces "writability" briefly, then talks about the relationship between "writability" and abstract expression oil painting, and finally explains the relationship between "writability" and abstract expression oil painting. Finally, it elaborates on the embodiment of "writability" in abstract expression oil painting. In conclusion, it shows that "writability" can be an effective way to create a mood and express emotions in paintings, as well as a dynamic way to express the emotions that the works are experiencing and their responses to things.
Exploring German neo-expressionist painting
Authors: WANG Kexin , JIN Lian
Published: August 2024

In the 20th century, with the emergence of modernist and post-modernist art, artists opposed the traditional forms of art creation and began to wander between reality and illusion in a variety of styles, taking the mode of thinking and inner emotional cognition of art creation as the primary proposition. New concepts, materials and media began to break through the boundaries of painting. As a result, a variety of painting styles emerged, such as expressionism. Neo-expressionism is further developed from expressionism, and after decades of development, its influence on the contemporary oil painting style is getting bigger and bigger. Among the many contemporary oil painting artists, a considerable number of them are also influenced by neo-expressionism. They constantly combine this Western art with traditional Chinese local culture and art, and explore the development of local oil painting by themselves. This paper briefly analyzes some basic factors of neo-expressionism, so as to have a certain understanding of itself; then analyzes the factors in the process of its evolution, explaining the process of evolution; and finally analyzes its influence on the development of Chinese oil painting. All these can help to understand neo-expressionism better, and also understand the development trend of local oil painting.
A report on post-editing of machine translation of Climate Change 2023
Authors: LI Mengjun
Published: August 2024

The rapid progress of computer science has thrust machine translation (MT) into the limelight, praised for its speed and accessibility. Despite its widespread use, concerns persist about the quality of machine-translated content, leading to a reassessment of its effectiveness. Post-editing (PE) has emerged as a solution, blending the strengths of MT and human translation and becoming a mainstream practice in the language service industry. PE improves translation efficiency, reduces costs, and ensures the fidelity of translated text, especially in Chinese. This report focuses on MT combined with PE, examining the translation of Section 4.5 of Climate Change 2023, which explores recent mitigation and adaptation strategies for climate change across various sectors. Using SDL Trados Studio 2019 and DeepL, the author conducted PE to refine the translated content, addressing lexical, sentence, and discourse-level issues. Recommendations include establishing terminology databases and employing contextual disambiguation techniques to rectify errors and ensure coherence and formatting. The report emphasizes the importance of navigating translation theories and methodologies, alongside possessing critical analytical skills and a robust knowledge base. Ultimately, this translation aims to enhance discussions on translating climate-related literature, offering valuable insights for future endeavors in this field.