bluuebunny/crossref_metadata_2025 huggingface dataset:
Implementation of Interoperable Healthcare Standards for Community Healthcare
Authors: Bae Ye Seul , Park Yeju , Lee Seung Min , You Hahyun , Park Yujin , Lee Hyeonji , Yoon Hyung-Jin
Published: May 2023

Building an integrated data model that includes not only clinical data but also personal health records has become increasingly important. We aimed to build a big data healthcare platform by developing a common data model that can be utilized in the healthcare field. To this end, we acquired health data from various communities to establish community care digital healthcare service models. Further, to improve personal health data interoperability, we ensured conformance to international standards, namely, the Systemized Nomenclature of Medicine Clinical Terms (SNOMED-CT) and transmission standards, namely, Health Level 7 Fast Healthcare Interoperability Resource (HL7 FHIR). Furthermore, FHIR resource profiling was designed to transmit and receive data, following the HL7 FHIR R4 guidelines.
Use of Digital Games for Educational Purposes Among Medical and Paramedical Sciences Students, Mashhad, Iran
Authors: Sarbaz Masoumeh , Banaye Yazdipour Alireza , Mousavi Baigi Seyyedeh Fatemeh , Darroudi Ali , Kimiafar Khalil
Published: May 2023

This study aimed to investigate the use of digital games for educational purposes among medical and paramedical sciences students at Mashhad University of Medical Sciences (Northeast of Iran). This cross-sectional study was conducted from July 2018 to January 2019. The research population was all students of the school of medicine and school of paramedical sciences at Mashhad University of Medical Sciences (n = 496). The research tool was a researcher-made questionnaire based on a literature review. The validity of the questionnaire was confirmed by its content validity, and the reliability of the questionnaire was evaluated based on the test-retest method (r = 0.82). In this examination of medical and paramedical sciences students’ attitudes and perspectives, some novel preliminary insights into the applications, advantages, disadvantages, and features of digital games in education emerge. Overall, the findings showed that the use of interactive digital games can increase students’ motivation for learning and make the learning process more attractive for students. This study was approved by the ethical committee of MUMS (approval number IR.MUMS.REC.1397.151).
First Contact, First Learnings – Nursing Staff Approaching Robotics in Health Care
Authors: Krückeberg Jörn , Beume Daniel Peter , Klawunn Ronny , Müller Jens , Griga Leif , Winkelhake Lena , Eich Lukas , Kempe Nina , Albayrak Esma
Published: May 2023

Systems for service and assistance robotics become relevant in nursing care. Workshops with target user groups can support the reflection and identification of scenarios for the use of robotic systems.
Exploring Obese Adults’ Preferences for a Physical Activity Chatbot: Qualitative Study
Authors: Larbi Dillys , Wynn Rolf , Årsand Eirik , Denecke Kerstin , Zanaboni Paolo , Gabarron Elia
Published: May 2023

Social media chatbots could help increase obese adults’ physical activity behaviour. The study aims to explore obese adults’ preferences for a physical activity chatbot. Individual- and focus group interviews will be conducted in 2023. Identified preferences will inform the development of a chatbot that motivates obese adults to increase their physical activity. The interview guide was tested in a pilot interview.
E-learning as Part of Residency Education
Authors: Abovarda Adam , Vallo Hult Helena , Master Östlund Christian , Pålsson Paul
Published: May 2023

Through a literature review in combination with qualitative analysis of course evaluations, this study examines aspects that contribute to enhancing e-learning for physicians in a residency education program. The literature review and the qualitative analysis outline three main factors (pedagogical, technological, and organizational), highlighting the importance of a holistic approach that includes learning and technology in context when integrating e-learning strategies in adult learning programs. The findings contribute insights and practical guidance for education organizers on how to conduct e-learning during and after the pandemic.
Interdisciplinary Teams in Health Informatics: Using FHIR Standards to Share Computable Knowledge
Authors: Andrikopoulou Elisavet , Schreiweis Björn , Anywar Michael
Published: May 2023

The use and shareability of Clinical Quality Language (CQL) artefacts is an important aspect in enabling the exchange and interoperability of clinical data to support both clinical decisions and research in the medical informatics field. This paper, while basing on use cases and synthetic data, developed purposeful CQL reusable libraries to showcase the possibilities of multidisciplinary teams and how CQLs could be best used to support clinical decision making.
Interdisciplinary Human-Centered AI for Hospital Readmission Prediction of Heart Failure Patients
Authors: Soliman Amira , Nair Monika , Petersson Marcus , Lundgren Lina , Dryselius Petra , Fogelberg Ebba , Hamed Omar , Etminani Kobra , Nygren Jens
Published: May 2023

The evolution of clinical decision support (CDS) tools has been improved by usage of new technologies, yet there is an increased need to develop user-friendly, evidence-based, and expert-curated CDS solutions. In this paper, we show with a use-case how interdisciplinary expertise can be combined to develop CDS tool for hospital readmission prediction of heart failure patients. We also discuss how to make the tool integrated in clinical workflow by understanding end-user needs and have clinicians-in-the-loop during the different development stages.
Feature Selection Based on a Genetic Algorithm for Optimizing Weaning Success
Authors: Rosati Samanta , Scotto Andrea , Fanelli Vito , Balestra Gabriella
Published: May 2023

Finding the right time for weaning from ventilator is a difficult clinical decision. Several systems based on machine or deep learning are reported in literature. However, the results of these applications are not completely satisfactory and may be improved. An important aspect is represented by the features used as input of these systems. In this paper we present the results of the application of genetic algorithms to perform feature selection on a dataset containing 13688 patients under mechanical ventilation characterizing by 58 variables, extracted from the MIMIC III database. The results show that all features are important, but four of them are essential: ‘Sedation_days’, ‘Mean_Airway_Pressure’, ‘PaO2’, and ‘Chloride’. This is only the initial step to obtain a tool to be added to the other clinical indices for minimize the risk of extubation failure.
First Steps Towards a Risk of Bias Corpus of Randomized Controlled Trials
Authors: Dhrangadhariya Anjani , Hilfiker Roger , Sattelmayer Martin , Giacomino Katia , Caliesch Rahel , Elsig Simone , Naderi Nona , Müller Henning
Published: May 2023

Risk of bias (RoB) assessment of randomized clinical trials (RCTs) is vital to conducting systematic reviews. Manual RoB assessment for hundreds of RCTs is a cognitively demanding, lengthy process and is prone to subjective judgment. Supervised machine learning (ML) can help to accelerate this process but requires a hand-labelled corpus. There are currently no RoB annotation guidelines for randomized clinical trials or annotated corpora. In this pilot project, we test the practicality of directly using the revised Cochrane RoB 2.0 guidelines for developing an RoB annotated corpus using a novel multi-level annotation scheme. We report inter-annotator agreement among four annotators who used Cochrane RoB 2.0 guidelines. The agreement ranges between 0% for some bias classes and 76% for others. Finally, we discuss the shortcomings of this direct translation of annotation guidelines and scheme and suggest approaches to improve them to obtain an RoB annotated corpus suitable for ML.
Modeling Clinical Guidelines for an Epilepsy-CDSS: The EDiTh Project
Authors: Pérez Garriga Ariadna , Wolking Stefan , Fortmann Jonas , Majeed Raphael W. , Stockem Christian , Niekrenz Lukas , Bosselmann Christian , Weber Yvonne , Röhrig Rainer , Lipprandt Myriam
Published: May 2023

The knowledge transformation process involves the guideline for the diagnosis and therapy of epilepsy to an executable and computable knowledge base that serves as the basis for a decision-support system. We present a transparent knowledge representation model which facilitates technical implementation and verification. Knowledge is represented in a plain table, used in the frontend code of the software where simple reasoning is performed. The simple structure is sufficient and comprehensible also for non-technical persons (i.e., clinicians).
Me-to-We Design: A Blueprint for Enriching Welfare Technologies
Authors: Hertzum Morten , Yasuoka Mika
Published: May 2023

Current technologies for ambient assisted living leave underexploited that social interaction is key to human wellbeing. Me-to-we design provides a blueprint for enriching such welfare technologies with social interaction. We present the five stages of me-to-we design, illustrate how it may transform a common class of welfare technologies, and discuss the distinguishing features of me-to-we design. These features include scaffolding social interaction around an activity and supporting transitions among the five stages. In contrast, most current welfare technologies support only some of the five stages and, thereby, either bypass social interaction or presuppose that social relations already exist. Me-to-we design offers a blueprint for building social relations stage by stage if they do not exist up front. It is for future work to validate whether the blueprint in practice delivers welfare technologies that are enriched by its profoundly sociotechnical approach.
Definition, Composition, and Harmonization of Core Datasets Within the German Center for Lung Research
Authors: Stöhr Mark R. , Günther Andreas , Majeed Raphael W.
Published: May 2023

Core datasets are the composition of essential data items for a certain research scope. As they state commonalities between heterogeneous data collections, they serve as a basis for cross-site and cross-disease research. Therefore, researchers at the national and international levels have addressed the problem of missing core datasets. The German Center for Lung Research (DZL) comprises five sites and eight disease areas and aims to gain further scientific knowledge by continuously promoting collaborations. In this study, we elaborated a methodology for defining core datasets in the field of lung health science. Additionally, through support of domain experts, we have utilized our method and compiled core datasets for each DZL disease area and a general core dataset for lung research. All included data items were annotated with metadata and where possible they were assigned references to international classification systems. Our findings will support future scientific collaborations and meaningful data collections.
Fitness for Use of Anatomical Therapeutic Chemical Classification for Real World Data Research
Authors: Reinecke Ines , Henke Elisa , Peng Yuan , Sedlmayr Martin , Bathelt Franziska
Published: May 2023

Introduction: Real-world data (RWD) is gaining importance in research. For instance, the European Medicines Agency (EMA) is currently in the process of establishing a cross-national research network that utilizes RWD for research. However, data harmonization across countries must be carefully considered to avoid misclassification and bias. Objectives: This paper aims to investigate the extent to which a correct assignment of RxNorm ingredients is possible for medication orders that include only ATC codes. Methods: In this study, we analyzed 1,506,059 medication orders from the University Hospital Dresden (UKD) and merged them with the ATC vocabulary in the Observational Medical Outcomes Partnership (OMOP) including relevant relationship mappings to RxNorm. Results: We identified 70.25% of all medication orders were single ingredients with direct mapping to RxNorm. However, we also identified a significant complexity in mappings for the other medication orders that was visualized in an interactive scatterplot. Discussion: The majority of medication orders under observation (70.25%) are single ingredients and can be standardized to RxNorm, combination drugs pose a challenge due to the different approaches of ingredient assignments in ATC and RxNorm. The provided visualization can help research teams gain a better understanding of problematic data and further investigate identified issues.
Exploring Use Cases for CovidGraph
Authors: Gütebier Lea , Henkel Ron , Niklas Christian , Waltemath Dagmar
Published: May 2023

HealthECCO is the driving force behind the COVID-19 knowledge graph spanning multiple biomedical data domains. One way to access CovidGraph is SemSpect, an interface designed for data exploration in graphs. To showcase the possibilities that arise from integrating a variety of COVID-19 related data sources over the last three years, we present three use cases from the (bio-)medical domain. Availability: The project is open source and freely available from: https://healthecco.org/covidgraph/. The source code and documentation are available on GitHub: https://github.com/covidgraph.
Evaluating the Portability of Rheumatoid Arthritis Phenotyping Algorithms: A Case Study on French EHRs
Authors: Fabacher Thibaut , Sauleau Erik-André , Leclerc Du Sablon Noémie , Bergier Hugo , Gottenberg Jacques-Eric , Coulet Adrien , Névéol Aurélie
Published: May 2023

Previous work has successfully used machine learning and natural language processing for the phenotyping of Rheumatoid Arthritis (RA) patients in hospitals within the United States and France. Our goal is to evaluate the adaptability of RA phenotyping algorithms to a new hospital, both at the patient and encounter levels. Two algorithms are adapted and evaluated with a newly developed RA gold standard corpus, including annotations at the encounter level. The adapted algorithms offer comparably good performance for patient-level phenotyping on the new corpus (F1 0.68 to 0.82), but lower performance for encounter-level (F1 0.54). Regarding adaptation feasibility and cost, the first algorithm incurred a heavier adaptation burden because it required manual feature engineering. However, it is less computationally intensive than the second, semi-supervised, algorithm.
Secondary Use of Clinical Problem List Entries for Neural Network-Based Disease Code Assignment
Authors: Kreuzthaler Markus , Pfeifer Bastian , Kramer Diether , Schulz Stefan
Published: May 2023

Clinical information systems have become large repositories for semi-structured and partly annotated electronic health record data, which have reached a critical mass that makes them interesting for supervised data-driven neural network approaches. We explored automated coding of 50 character long clinical problem list entries using the International Classification of Diseases (ICD-10) and evaluated three different types of network architectures on the top 100 ICD-10 three-digit codes. A fastText baseline reached a macro-averaged F1-score of 0.83, followed by a character-level LSTM with a macro-averaged F1-score of 0.84. The top performing approach used a downstreamed RoBERTa model with a custom language model, yielding a macro-averaged F1-score of 0.88. A neural network activation analysis together with an investigation of the false positives and false negatives unveiled inconsistent manual coding as a main limiting factor.
Classification of Clinical Notes from a Heart Failure Telehealth Network
Authors: Wiesmüller Fabian , Lauschenski Aaron , Baumgartner Martin , Hayn Dieter , Kreiner Karl , Fetz Bettina , Brunelli Luca , Pölzl Gerhard , Pfeifer Bernhard , Neururer Sabrina , Schreier Günter
Published: May 2023

Heart failure is a common chronic disease which is associated with high re-hospitalization and mortality rates. Within the telemedicine-assisted transitional care disease management program HerzMobil, monitoring data such as daily measured vital parameters and various other heart failure related data are collected in a structured way. Additionally, involved healthcare professionals communicate with one another via the system using free-text clinical notes. Since manual annotation of such notes is too time-consuming for routine care applications, an automated analysis process is needed. In the present study, we established a ground truth classification of 636 randomly selected clinical notes from HerzMobil based on annotations of 9 experts with different professional background (2 physicians, 4 nurses, and 3 engineers). We analyzed the influence of the professional background on the inter annotator reliability and compared the results with the accuracy of an automated classification algorithm. We found significant differences depending on the profession and on the category. These results indicate that different professional backgrounds should be considered when selecting annotators in such scenarios.
Predicting Depression Risk in Patients with Cancer Using Multimodal Data
Authors: de Hond Anne , van Buchem Marieke , Fanconi Claudio , Roy Mohana , Blayney Douglas , Kant Ilse , Steyerberg Ewout , Hernandez-Boussard Tina
Published: May 2023

When patients with cancer develop depression, it is often left untreated. We developed a prediction model for depression risk within the first month after starting cancer treatment using machine learning and Natural Language Processing (NLP) models. The LASSO logistic regression model based on structured data performed well, whereas the NLP model based on only clinician notes did poorly. After further validation, prediction models for depression risk could lead to earlier identification and treatment of vulnerable patients, ultimately improving cancer care and treatment adherence.
Prognostic Factors for Covid-19 on Admission Profile and Air Pollutants
Authors: Sato Kikue , Furukawa Taiki , Yamashita Satoshi , Kobayashi Daisuke , Oyama Shintaro , Shiratori Yoshimune
Published: May 2023

It has been reported that the severity and lethality of Covid-19 are associated with coexisting underlying diseases (hypertension, diabetes, etc.) and cardiovascular diseases (coronary artery disease, atrial fibrillation, heart failure, etc.) that increase with age, but environmental exposure such as air pollutants may also be a risk factor for mortality. In this study, we investigated patient characteristics at admission and prognostic factors of air pollutants in Covid-19 patients using a machine learning (random forest) prediction model. Age, Photochemical oxidant concentration one month prior to admission, and level of care required were shown to be highly important for the characteristics, while the cumulative concentrations of air pollutants SPM, NO2, and PM2.5 one year prior to admission were the most important characteristics for patients aged 65 years and older, suggesting the influence of long-term exposure.
Towards Automated COVID-19 Presence and Severity Classification
Authors: Mueller Dominik , Mertes Silvan , Schroeter Niklas , Hellmann Fabio , Elia Miriam , Bauer Bernhard , Reif Wolfgang , André Elisabeth , Kramer Frank
Published: May 2023

COVID-19 presence classification and severity prediction via (3D) thorax computed tomography scans have become important tasks in recent times. Especially for capacity planning of intensive care units, predicting the future severity of a COVID-19 patient is crucial. The presented approach follows state-of-theart techniques to aid medical professionals in these situations. It comprises an ensemble learning strategy via 5-fold cross-validation that includes transfer learning and combines pre-trained 3D-versions of ResNet34 and DenseNet121 for COVID19 classification and severity prediction respectively. Further, domain-specific preprocessing was applied to optimize model performance. In addition, medical information like the infection-lung-ratio, patient age, and sex were included. The presented model achieves an AUC of 79.0% to predict COVID-19 severity, and 83.7% AUC to classify the presence of an infection, which is comparable with other currently popular methods. This approach is implemented using the AUCMEDI framework and relies on well-known network architectures to ensure robustness and reproducibility.
The Future of Online Video Consultations in Primary Care: A Qualitative Study
Authors: Hägglund Maria , Davoody Nadia , Kristensson Ekwall Anna , Farrokhnia Nasim
Published: May 2023

The COVID-19 pandemic has significantly increased the use of remote services such as video consultations (VCs). In Sweden, private healthcare providers offering VCs have grown substantially since 2016 and have been controversial. Few studies have focused on physicians’ experiences of providing care in this context. Our overall aim was to study physicians’ experiences of VCs, here focusing on their suggestions for future improvements. Twenty-two semi-structured interviews were performed with physicians working for an online healthcare provider in Sweden, and analyzed through inductive content analysis. Two themes emerged related to desired future improvements of VCs; blended care and technical innovation.
Benchmarking the Impact of Noise on Deep Learning-Based Classification of Atrial Fibrillation in 12-Lead ECG
Authors: Bender Theresa , Gemke Philip , Idrobo-Avila Ennio , Dathe Henning , Krefting Dagmar , Spicher Nicolai
Published: May 2023

Electrocardiography analysis is widely used in various clinical applications and Deep Learning models for classification tasks are currently in the focus of research. Due to their data-driven character, they bear the potential to handle signal noise efficiently, but its influence on the accuracy of these methods is still unclear. Therefore, we benchmark the influence of four types of noise on the accuracy of a Deep Learning-based method for atrial fibrillation detection in 12-lead electrocardiograms. We use a subset of a publicly available dataset (PTB-XL) and use the metadata provided by human experts regarding noise for assigning a signal quality to each electrocardiogram. Furthermore, we compute a quantitative signal-to-noise ratio for each electrocardiogram. We analyze the accuracy of the Deep Learning model with respect to both metrics and observe that the method can robustly identify atrial fibrillation, even in cases signals are labelled by human experts as being noisy on multiple leads. False positive and false negative rates are slightly worse for data being labelled as noisy. Interestingly, data annotated as showing baseline drift noise results in an accuracy very similar to data without. We conclude that the issue of processing noisy electrocardiography data can be addressed successfully by Deep Learning methods that might not need preprocessing as many conventional methods do.
Implementing Remote Patient Monitoring for Patients During Systemic Cancer Therapy
Authors: Kohn Lara , Mueller Anita , Scheble Veit , Storz Philip , Borlinghaus Hanna , Ulas Selcan Behiye , Malek Nisar , Thies Christian
Published: May 2023

Mobile monitoring of outpatients during cancer therapy becomes possible through technological advancements. This study leveraged a new remote patient monitoring app for in-between systemic therapy sessions. Patients’ evaluation showed that the handling is feasible. Clinical implementation must consider an adaptive development cycle for reliable operations.
Voxel-Wise Medical Imaging Transformation and Adaption Based on CycleGAN and Score-Based Diffusion
Authors: Li Feifei , Schöneck Mirjam , Beyan Oya , Caldeira Liliana Lourenco
Published: May 2023

Supervised methods, such as those utilized in classification, prediction, and segmentation tasks for medical images, experience a decline in performance when the training and testing datasets violate the i.i.d (independent and identically distributed) assumption. Hence we adopted the CycleGAN(Generative Adversarial Networks) method to cycle training the CT(Computer Tomography) data from different terminals/manufacturers, which aims to eliminate the distribution shift from diverse data terminals. But due to the model collapse problem of the GAN-based model, the images we generated suffer serious radiology artifacts. To eliminate the boundary marks and artifacts, we adopted a score-based generative model to refine the images voxel-wisely. This novel combination of two generative models makes the transformation between diverse data providers to a higher fidelity level without sacrificing any significant features. In future works, we will evaluate the original datasets and generative datasets by experimenting with a broader range of supervised methods.
Differential Gene Expression Data Analysis of ASD Using Random Forest
Authors: Pragya  , Govarthan Praveen Kumar , Sinha Kshitij , Mukherjee Sudip , Agastinose Ronickom Jac Fredo
Published: May 2023

Autism spectrum disorder (ASD) is a developmental disability caused by differences in the brain regions. Analysis of differential expression (DE) of transcriptomic data allows for genome-wide analysis of gene expression changes related to ASD. De-novo mutations may play a vital role in ASD, but the list of genes involved is still far from complete. Differentially expressed genes (DEGs) are treated as candidate biomarkers and a small set of DEGs might be identified as biomarkers using either biological knowledge or data-driven approaches like machine learning and statistical analysis. In this study, we employed a machine learning-based approach to identify the differential gene expression between ASD and Typical Development (TD). The gene expression data of 15 ASD and 15 TD were obtained from the NCBI GEO database. Initially, we extracted the data and used a standard pipeline to pre-process the data. Further, Random Forest (RF) was used to discriminate genes between ASD and TD. We identified the top 10 prominent differential genes and compared them with the statistical test results. Our results show that the proposed RF model yields 5-fold cross-validation accuracy, sensitivity and specificity of 96.67%. Further, we obtained precision and F-measure scores of 97.5% and 96.57%, respectively. Moreover, we found 34 unique DEG chromosomal locations having influential contributions in identifying ASD from TD. We have also identified chr3:113322718-113322659 as the most significant contributing chromosomal location in discriminating ASD and TD. Our machine learning-based method of refining DE analysis is promising for finding biomarkers from gene expression profiles and prioritizing DEGs. Moreover, our study reported top 10 gene signatures for ASD may facilitate the development of reliable diagnosis and prognosis biomarkers for screening ASD.
A Reliable and Secure Method for Sharing Genomic Data
Authors: Cruz Dinis. B. , Almeida João R. , Silva Jorge M. , Oliveira José L.
Published: May 2023

Genomics has significantly impacted the field of medicine, with advances in DNA sequencing leading to personalized medicine and a deeper understanding of the genomic basis of various diseases. The ability to share genomic data is crucial for advancing this field and developing new approaches to understanding the genome. However, the sensitive nature of this data requires secure methods for protecting it during storage and transfer. In this paper, we present a new tool for the secure encryption and decryption of FASTA files without sharing a common secret and with a reduced number of shared keys between the pairs. Our proposal combines symmetric and asymmetric encryption techniques, including the AES (Advanced Encryption Standard) cypher and RSA (Rivest–Shamir–Adleman). The tool is fast, reliable, and secure, outperforming existing tools in terms of security and ease of use. This makes it a valuable solution for the secure sharing and use of sensitive genomic data, representing a significant advancement in the field of genomics.
Shrewdness, coup d’œil, and genius: the cognitive attributes of the consummate general (Greek antiquity, Byzantine era, modern times)
Authors: Rapin Ami-Jacques
Published: May 2023

Everett Wheeler's hypothesis that the Greek concept of _ankhínoia_ finds its equivalent in eighteenth-century military writers' notion of the _coup d'oeil_ is tested by comparing treatises on the art of war written in the two periods. After highlighting the different meanings of the _coup d’oeil_ in 18th century military terminology, Clausewitz's approach is examined in the light of his concept of the genius for war.
Pelatihan Program Microsoft Office dalam Rangka Meningkatkan Teknologi Adaptif pada Remaja RT. 01/RW. 03 Desa Iwul Kecamatan Parung Kabupaten Bogor
Authors: Masriah Imas , Yuangga Kharisma Danang , Wahyudi Yuli
Published: May 2023

Mitra dalam program ini adalah Pada Remaja RT. 01/RW. 03 Desa Iwul Kecamatan Parung. Masalah utama yang dihadapi oleh mitra adalah remaja harus dipersiapkan sebaik mungkin dalam menghadapai tantangan jaman. Microsoft Office merupakan keahlian yang penting dikuasai oleh remaja RT. 01/RW. 03 Desa Iwul Kecamatan Parung karena bidang tersebut dapat dikembangkan secara profesional, bahkan sebelum lulus dari jenjang sekolah. Microsoft office merupakan sebuah paket perangkat lunak yang diciptakan atau dikembangkan oleh perusahaan Microsoft itu sendiri. Didalam paket software tersebut, terdapat software-software yang mendukung aktivitas sehari hari khususnya dalam dunia kerja. Microsoft Office terdiri dari Microsoft Word, Microsoft Excel dan Microsoft Power Poin. Dengan memiliki kemampuan dasar sebagai penunjang kerja di masa depan. Akan menjadi pengetahuan teknologi adaptif bagi para remaja. Sehingga para remaja bisa mulai dari sejak dini di asah kemampuannya maupun mind set nya untuk meningkatkan kemampuan standar yang akan mendukung minat dan bakat potensial nya kedepan.
MACROECONOMIC EFFECTS ON SYSTEMATIC RISK IN EUROPE. THE CASE OF CYCLICAL V. NON-CYCLICAL COMPANIES
Authors:   University of Piraeus., Artikis Panagiotis , Diamantopoulou Lydia ,   University of Piraeus., Kampouris Christos ,   University of Piraeus.
Published: May 2023

This study explores macroeconomic and industry-level effects on corporate systematic risk (or beta) for European cyclical and noncyclical companies. We document the extent to which stock market betas fluctuate over time for both industry groups. In addition, we analyze the fundamental determinants of systematic risk. We find evidence that, although noncyclical industries market betas have a lower magnitude, after controlling for firms fundamental strength, macroeconomic conditions and different institutional environments, both types of industries are affected in the same manner by the variables incorporated in our study.
STUDY OF THE DOMESTIC EXPERIENCE OF IMPLEMENTING THE IMPACT OF THE REGULATORY SYSTEM ON THE CLINICAL TRIALS MANAGEMENT
Authors:   ational University ", Yashchenko Mariia ,   Kyiv-Mohyla Academy"
Published: May 2023

The article deals with the general analysis of the domestic experience of implementing the impact of the regulatory system on the clinical examinations management. It has been determined that in all the developed countries the state continues playing the key role in regulating the sphere of scientific investigations and innovations, in particular, the pharmaceutical field. Despite the current normative and legal regulation, during inspections of the activities of enterprises conducting clinical examinations of medicines within the framework of state control, specialists of control and supervisory structures identify cases of non-compliance with mandatory requirements. It has been stated that nowadays conducting the clinical examinations is related to a number of risks: a significant pressure on the pharmaceutical companies in the aspect of quick development of new effective medicines with a low price; a huge number of standards and requirements that need to be met; increasing the complexity of clinical research (increase in the number of endpoints during the last 10 years, increase in the number of adaptive examinations), etc. It has been resumed that the development of additional tools to improve the quality of the informed consent procedure as the main stage of informing subjects about the benefits of participation, limitations on the time of the clinical examinations, risks that may arise from participation, etc., is currently relevant. Analysis of the influence of regulatory system of Ukraine on the problem of clinical examinations management gave an opportunity to assume that the list of potentially viable variants for solving the outlined issue through the implementation of state policy include: increasing the attractiveness of the clinical examinations market of Ukraine for domestic and foreign investors; creating the conditions for infrastructure formation and development in Ukraine, which is necessary for conducting modern biomedical studies; implementing the effective mechanisms of involving doctors to the clinical examinations, etc. It has been generalized that state regulation in the field of conducting clinical examinations is continuously modified and has a tendency to develop a stable legal base and comprehensive harmonization of the Ukrainian legislation with international requirements of basic principles regarding clinical examinations based on the achievements of modern science and new medical technologies.
СОЦІАЛЬНІ ПРОЄКТИ НА РІВНІ ПІДПРИЄМСТВА В СУЧАСНИХ УМОВАХ
Authors: Сазонова Тетяна , Шарлай Максим
Published: May 2023

Стаття присвячена актуальним питанням визначення доцільності ініціювання та реалізації соціальних проєктів на рівні підприємства, організації в сучасних вітчизняних умовах. Проаналізовані підходи щодо визначення змісту понять «соціальний проєкт», «соціальне проєктування». Розглянуті види соціального проєктування на рівні підприємства, організації. Досліджені етапи соціального проєктування та зміст етапу ініціювання соціальних проєктів; принципи соціального проєктування. Проаналізовані умови успішності соціального проєктування. За результатами досліджень, наведені популярні напрями соціального проєктування, що реалізовувалися та реалізуються вітчизняними підприємствами, організаціями в 2022-2023 рр. Окреслені особливості соціального проєктування в сучасних вітчизняних умовах та доведена необхідність ініціювання та реалізації соціальних проєктів на мікрорівні в сучасних реаліях.
КОМУНІКАЦІЙНІ СТРАТЕГІЇ ПРОПАГАНДИСТСЬКОГО ДОКУМЕНТАЛЬНОГО КОНТЕНТУ ЯК ІНСТРУМЕНТ НАРАТИВНОГО РЕГУЛЮВАННЯ
Authors: Kovpak V. , Troino M.
Published: May 2023

The purpose of the study is to analyze the communication strategies of propaganda documentary content as an instrument of narrative regulation in the information space.

Research methodology. The following methods were used in the study: classification (types of communication strategies), discourse analysis (content analysis taking into account historical, political, and social circumstances), systematic approach (taking into account the peculiarities of the media landscape of the Russian propaganda information space), and synchronous method (focusing on the conditions of Russia’s full-scale invasion of Ukraine).

Results. The article characterizes the concepts of «narrative strategies», «communication strategies», «narrative bias», and «narrative regulation» in social communications. Despite the different platforms and target audiences, the narrative strategies of documentary content on the RT TV channel (on the example of the documentary «Maidan: Turn to War» (March 5, 2022)) and on the author’s YouTube channel «Stas wow how simple» (the documentary «Donbas Diary. How I was in the war») are absolutely identical. The Kremlin narratives are wrapped in blatant manipulation of human emotions, lack of facts, and are promoted by communication strategies of framing, priming, «agenda-setting», destructive multiplicity of narratives, as well as audiovisual tools of film narration, which help to regulate the narrative of the hostile information space.

The scientific novelty lies in the revealed mechanics of the use of communication strategies in the documentary content of the state television channel Russia Today (RT) and the author’s YouTube channel «Stas wow how simple» on the example of documentaries on the Revolution of Dignity and the Russian-Ukrainian war of 2014 for the narrative regulation of this issue in the information space.

Practical meaning. The practical significance of the study and the prospects of researching the narrative practices of the Russian-Ukrainian war are evidenced by the analyzed trends in the applied communication strategies of propaganda documentary content as a tool for narrative regulation in the information space, since the revealed narrativization allows us to trace grand narratives and sub-narratives, to identify concepts, means of their presentation – narrative strategies, communication strategies for their implementation, and the role of the so-called narrators-regulators who determine the narrative.

Key words: narrative bias, narrative regulation, dominant narratives, sub-narratives, communication strategies, documentary content.
Identifikasi Cemaran Mikroplastik pada Sungai Inlet Rawa Pening dan Biotanya
Authors: Puspita Dhanang , Nugroho Pulung , Palimbong Sarlina , Wijaya Rasya Pandhu
Published: May 2023

Danau Rawa Pening memiliki kandungan TSS (total padatan terlalut) yang tinggi, sehingga kualitas airnya berada di kelas 3 dan 4. TTS tersebut berasal dari 9 Sub DAS yang menjadi inletnya Rawa Pening. Sumber TSS berasal cari cemaran limbah padat, dan salah satunya adalah mikroplastik. Adanya mikroplastik juga menjadi ancaman keamanan pangan bila masuk dalam tubuh biota dan dikonsumsi manusia. Tujuan dari penelitian ini adalah untuk mengetahui cemaran mikroplastik pada ikan yang ada di Sub DAS Rawa Pening. Metode yang dilakukan adalah survey dan analisis laboratorium dengan tahapan; pengambilan sampel, preparasi sampel, dan analisi mikroplastik. Hasil penenilitian menujukan 4 aliran sungai yakni; sungai Sraten, Muncul, Rawa Sari dan Rawa Boni terkontaminasi mikroplastik, begitu juga dengan biotanya yakni ikan sapu-sapu, louhan, lele, nila, gabus, dan moluska keong terdapat kandungan mikroplastik pada saluran pencernaannya. Adanya mikroplastik ini kemungkina berasal dari limbah domestik dan industri, dimana 4 sungai tersebut terdapat permukiman penduduk dan industri. Dapat disimpulkan, 4 sungai di Rawa Pening sudah tercemar mikroplastik, begitu juga dengan biotanya.
Kajian Paparan Medan Listrik pada Pertumbuhan Tanaman Pare (Momordica charantia L.)
Authors: Ko'u Setiwani , Wiguna Gede Arya , Welsiliana Welsiliana
Published: May 2023

Pare (Momordica charantia L.) dalam bahasa daerah Timor disebut paria adalah tumbuhan herba merambat termasuk dalam famili Cucurbitaceae yang banyak dimanfaatkan sebagai sayuran. Selain sebagai sayuran pare banyak dimanfaatkan sebagai obat seperti antidiabetes, antipiretik dan antiinflamasi. Budidaya tanaman pare memiliki prospek yang baik, oleh karenanya perlu dilakukan kajian peningkatkan produktivitas tanaman pare, diantaranya yaitu menggunakan paparan medan listrik. Penelitian ini bertujuan untuk mengetahui pengaruh paparan medan litrik terhadap pertumbuhan tanaman pare. Penelitian ini menggunakan rancangan acak lengkap (RAL) dengan dua faktorial dengan tiga kali ulangan dengan variabel bebas paparan medan listrik dan waktu paparan. Variabel terikatnya adalah laju pertumbuhan tanaman serta laju pertumbuhan jumlah daun. Perlakuan penelitian terdiri dari 6 perlakuan dengan satu kontrol dan paparan medan listrik yang masing-masing adalah  1,28 kV/m, 1,55 kV/m, 1,80 kV/m, 2,12 kV/m, dan 2,45 kV/m. Waktu paparan yang diberikan yaitu 15 menit dan 30 menit. Hasil data yang diperoleh selanjutnya dilakukan analisis menggunakan Statistical Package for the Social Sciences. Apabila hasil sidik ragam menunjukkan pengaruh nyata dari perlakuan, maka dilakukan uji lanjut Duncan Mean Range Test (DMRT). Hasil yang diperoleh menunjukkan bahwa paparan medan listrik pada pare berpengaruh terdahap pertumbuhan tanaman baik pertumbuhan tinggi dan juga jumlah daun. Pertumbuhan optimum tanaman pare yaitu pada perlakuan paparan medan listrik 1,28 kV/m selama 30 menit, dengan hasil laju pertumbuhan 14,2 ± 0,5 cm/minggu dan laju jumlah daun 13,8 ± 0,5 helai/minggu.
Analisis Pembatasan Garam pada Pasien Hipertensi dan Faktor-Faktor Determinannya di Desa Perapat Nunggul Kecamatan Lawe Alas Kabupaten Aceh Tenggara
Authors: Handayani Sri
Published: May 2023

ABSTRACT Hypertension is a cardiovascular disease that is the main cause of death worldwide. behavior that is often done and causes hypertension such as consuming processed foods, not caring about the salt content in food, adding salt to the table, and not buying low-sodium salt. Salt restriction in hypertensive patients is related to knowledge, family support, and support from health workers. This study aims to analyze salt restriction in hypertensive patients and its determinant factors in Perapat Nunggul Village, Lawe Alas District, and Southeast Aceh District. This research is a correlational analytic descriptive study with a cross-sectional approach. The population is all hypertension sufferers totaling 63 people with a sampling technique in the form of total sampling. The results showed that there was a significant relationship between knowledge, family support, and health worker support with salt restriction in hypertensive patients, with p-values for each variable, namely knowledge (p = 0.000), family support (p = 0.004) and support from health workers (p = 0.011). Based on the results of this study, it is hoped that the Puskesmas will support health workers in home care activities and families can provide support in the form of assessments, awards, and instrumental and emotional. Keywords: Hypertension, salt restriction, knowledge, family, health workers. ABSTRAK Hipertensi merupakan salah satu penyakit kardiovaskular yang menjadi penyebab utama kematian di seluruh dunia. perilaku yang sering dilakukan dan menjadi penyebab hipertensi seperti mengonsumsi makanan olahan, tidak mempedulikan kadar garam dalam makanan, menambahkan garam di atas meja dan tidak membeli garam rendah sodium. Pembatasan garam pada penderita hipertensi berkaitan dengan pengetahuan, dukungan keluarga dan dukungan tenaga kesehatan. Penelitian ini bertujuan menganalisis pembatasan garam pada pasien hipertensi dan faktor-faktor determinannya di Desa Perapat Nunggul Kecamatan Lawe Alas Kabupaten Aceh Tenggara. Penelitian ini merupakan penelitian deskriptif analitik korelasional dengan pendekatan cross sectional. Populasi yaitu seluruh penderita hipertensi berjumlah 63 orang dengan teknik pengambilan sampel berupa total sampling. Hasil penelitian menunjukkan ada hubungan yang signifikan antara pengetahuan, dukungan keluarga, dan dukungan tenaga kesehatan dengan pembatasan garam pada penderita hipertensi, dengan nilai p-value untuk masing-masing variabel yaitu pengetahuan (p = 0,000), dukungan keluarga (p = 0,004) dan dukungan tenaga kesehatan (p = 0,011). Berdasarkan hasil penelitian ini, diharapkan puskesmas mendukung tenaga kesehatan dalam kegiatan home care dan keluarga dapat memberikan dukungan berupa penilaian, penghargaan, instrumental dan emosional. Kata Kunci: Hipertensi, Pembatasan Garam, Pengetahuan, Keluarga, Tenaga Kesehatan.
Analisis Intervensi Optimalisasi Kemampuan untuk Meningkatkan Harga Diri Pada Klien Stroke
Authors: Herdalisa Wiwie , Iksan Ricky Riyanto , Putri Rima Berlian , Yeni Roza Indra , Batubara Salamah Thomasita , Permatasari Putri
Published: May 2023

ABSTRACT Stroke is a condition that occurs when blood flow to a part of the brain is suddenly disrupted. This condition can have psychological effects including hopelessness and low self-esteem. The purpose of this research is to identify ability optimization, which is a person's ability to move his body until there is independence for a person. This research method is descriptive and case study. The interventions carried out are teaching ROM and motivating patients to use their body parts so that the patient's self-esteem can increase. The results of this study are optimization in stroke patients. The conclusion is that increasing the ability and self-esteem of clients who have had a stroke really needs to be done in stroke patients and other patients. Keywords: Low Self-Esteem, Stroke, Bibliography Optimization  ABSTRAK Stroke yaitu suatu kondisi yang terjadi ketika aliran darah ke bagian otak secara tiba- tiba sehingga dapat mengalami gangguan. Kondisi ini dapat menimbulkan dampak psikologi termasuk keputusasaan dan harga diri rendah. Tujuan penelitian adalah mengidentifikasi Optimalisasi kemampuan adalah kemampuan seseorang dalam pergerakan tubuhnya sampai adanya kemandirian bagi seseorang. Metode Penelitian ini bersifat deskritif dan studi kasus. Intervensi yang dilakukan adalah mengajarkan ROM dan memotivasi pasien untuk menggunakan bagian tubuhnya sehingga harga diri pasien dapat meningkat.  Hasil Penelitian ini optimalisasi pada pasien stroke. Kesimpulan adanya  peningkatan kemampuan dan harga diri pada klien yang terkena stroke ini sangat perlu dilakukan pada pasien stroke dan pasien lain. Kata Kunci: Harga Diri Rendah, Stroke, Optimalisasi Daftar Pustaka
Gambaran Proses Adaptasi Mahasiswa Baru STIKES di Surabaya
Authors: Lestarina Ni Nyoman Wahyu , Purwantini Dwi
Published: May 2023

ABSTRACT New students are faced with different situations when entering lectures at tertiary institutions. This makes the adaptation process for new students more difficult. At the time of entering college, new students are faced with being able to improve their ability to adapt and be able to adapt to the environment in college. Good adaptation helps students to cope with educational and academic demands.This study’s aim is to see an overview of adaptation in tertiary institutions, especially for new students. The research design used is descriptive. The population of this study was new STIKES students in Surabaya with a total sample of 68 people who were taken by purposive sampling technique. The measuring tool used is the Student Adaptation College Questionnaire (SACQ). The research was conducted in February 2022. The research results obtained from the four aspects of student adaptation found that 54.4% had low academic adjustment aspects, 63.2% had low social adjustment aspects, 63.2% had high personal-emotional adjustment aspects, and 54.4% had low institutional attachment aspects. New STIKES students in Surabaya have low scores on the aspects of academic adjustment, social adjustment, and institutional adjustment. There needs to be intensive guidance for new students through a mentoring program by both supervisors and student organizations. Keywords: Adaptation, New Student  ABSTRAK Mahasiswa baru dihadapkan pada situasi yang berbeda saat memasuki perkuliahan di perguruan tinggi. Hal ini membuat membuat proses adaptasi mahasiswa baru menjadi lebih sulit. Pada saat memasuki perguruan tinggi, mahasiswa baru dihadapkan untuk dapat meningkatkan kemampuan dalam penyesuaian diri dan mampu beradaptasi dengan lingkungan di perguruan tinggi. Adaptasi yang baik membantu mahasiswa untuk mengatasi tuntutan pendidikan dan akademik. Tujuan penelitian ini adalah untuk melihat gambaran adaptasi di perguruan tinggi terutama bagi mahasiswa baru. Desain penelitian yang digunakan adalah deskriptif. Populasi penelitian ini adalah mahasiswa baru STIKES di Surabaya dengan jumlah sampel 68 orang yang diambil dengan teknik sampling purposive sampling. Alat ukur yang digunakan adalah Student Adaptation College Questionnaire (SACQ). Penelitian dilakukan pada bulan Februari 2022. Hasil penelitian didapatkan dari keempat aspek pada adaptasi mahasiswa didapatkan bahwa 54,4% mahasiswa memiliki aspek academic adjustment yang rendah, 63,2% mahasiswa memiliki aspek social adjustment yang rendah, 63,2% mahasiswa memiliki aspek personal- emotional adjustment tinggi dan 54,4% mahasiswa memiliki aspek institutional attachment yang rendah. Mahasiswa baru STIKES di Surabaya memiliki nilai rendah pada aspek academic adjustment, social adjustment dan institutional adjustment. Perlu adanya bimbingan intensif pada mahasiswa baru melalui program bimbingan baik oleh dosen pembimbing maupun organisasi mahasiswa. Kata Kunci: Adaptasi, Mahasiswa Baru