bluuebunny/crossref_metadata_2025 huggingface dataset:
Smart Water Management Framework for Irrigation
Authors: Bhardwaj Akashdeep
Published: October 2024

The demand for and pressure on natural resources worldwide is rising,
placing more emphasis on the availability of clean, safe drinking water. Modern
technologies like cloud computing, embedded systems, and smart sensors can provide
safe and effective control of the supply of drinking water for agriculture and consumer
usage. By combining proactive alerting, monitoring, and real-time data collection with
proactive management measures, problems are avoided before they arise. This study
offers a clever and safe foundation for future research aimed at improving the current
irrigation system. This is a low-cost irrigation strategy that uses smart device sensors
and cloud connectivity to give automated management and needs according to the
environment and season. In order to address the operational failures, this also provides
alerting scenarios for device and component failures as well as water leaks by
immediately switching to an alternate mode and delivering alert messages about the
problems.
Multinomial Naïve Bayesian Classifier Framework for Systematic Analysis of Smart IoT Devices
Authors: Bhardwaj Akashdeep
Published: October 2024

Machine learning and artificial intelligence-based sentiment analysis are
crucial for companies to automatically predict whether the customers are happy with
their products. In this paper, a deep learning model is built to analyze thousands of
reviews of Amazon Alexa to predict customer sentiment. The proposed model can be
directly applied to any company that has an online presence to automatically detect
customer sentiment from their reviews. The objective of this research work is to
propose a suitable method for analyzing the users’ reviews of Amazon Echo and
categorizing them into positive or negative reviews. In this research work, a dataset
containing reviews of 3150 users has been used. Initially, a word cloud of positive and
negative reviews has been plotted that gave a lot of insight from the text data. After that,
a deep learning model using a multinomial naïve Bayesian classifier has been built and
trained by using 80% of the dataset, and then the remaining 20% of the dataset has
been used for testing the model. The proposed model gives 93% accuracy. The
proposed model has also been compared with four models used in the same domain,
and it outperformed three of them.
Comparison of IoT Communication Protocols Using Anomaly Detection with Security Assessments of Smart Devices
Authors: Bhardwaj Akashdeep
Published: October 2024

The authors implemented an attack scenario simulating attacks to
compromise node and sensor data. This research proposes a framework with algorithms
that generate automated malicious commands, which conform to device protocol
standards and bypass compromise detection. The authors performed attack detection
testing with three different home setup simulations and referred to accuracy of
detection, ease of precision, and attack recall, with F1-score as the parameters. The
results obtained for anomaly detection of IoT logs and messages used K-nearest
neighbor, multi-layer perceptron, logistic regression, random forest, and linear support
vector classifier models. The attack results presented false-positive responses with and
without the proposed framework and false-negative responses for different models.
This research calculated precision, accuracy, F1-score, and recall as attack detection
performance models. Finally, the authors evaluated the performance of the proposed
IoT communication protocol attack framework by evaluating a range of anomalies and
compared them with the maliciously generated log messages. IoT Home #1 in which
the model involved IP Camera and NAS device traffic displayed 97.7% Accuracy,
96.54% Precision, 97.29% Recall, and 96.88% F-1 Score. This demonstrated the model
classified the Home #1 dataset consistently.
Smart Home and Industrial IoT Devices: Critical Perspectives on Cyberthreats, Frameworks and Protocols
Authors: Bhardwaj Akashdeep
Published: October 2024

Smart Home and Industrial IoT Devices: Critical Perspectives on Cyber Threats, Frameworks and Protocols provides an in-depth examination of the Internet of Things (IoT) and its profound impact on smart homes and industrial systems. The book begins by exploring the significance of IoT in smart homes, followed by an analysis of emerging cyber threats targeting smart homes and cyber-physical systems. It presents AI and machine learning-based frameworks for monitoring water quality and managing irrigation in agriculture, highlighting their role in IoT ecosystems. The text also discusses a framework to mitigate cyber-attacks on robotic systems and introduces a multinomial naive Bayesian classifier for analyzing smart IoT devices. Dataflow analysis and modeling experiments are detailed, along with a comparison of IoT communication protocols using anomaly detection and security assessment. The book concludes with a discussion on efficient, lightweight intrusion detection systems and a unique taxonomy for IoT frameworks. This book is ideal for students, researchers, and professionals seeking to understand and secure IoT environments.
ANALISIS PENGARUH UTANG DOMESTIK DAN UTANG LUAR NEGERI TERHADAP PERTUMBUHAN EKONOMI DI INDONESIA PADA TAHUN 2014 - 2023
Authors: Pratomo Athar Gherin , Fadjar Nurman Setiawan
Published: October 2024

During the period of 2014-2023, Indonesia government set a target for average economic growth of 5.2% for 2014-2020 and 6% for 2020-2025. In order to achieve that, the fiscal policy adopted by the government is by utilizing debt. Based on Keynesian view, the government can incur debt to finance government budget deficits and stimulate economic growth. This research employs the ordinary least squares (OLS) method because it seeks to analyze the relationship between the variables of quarterly increase of GDP, quarterly increase of domestic debt growth, and quarterly foreign debt. Based on the estimation results of the model conducted in the research,  the result show that the variables of quarterly domestic debt growth and quarterly foreign debt growth can only explain a 14.49% increase in quarterly GDP value. Simultaneously, domestic debt and foreign debt do not affect economic growth. Partially, an increase per quarter in domestic debt has a significant negative effect on the increase in quarterly GDP value, while an increase per quarter in foreign debt has a positive but not significant effect on the increase of quarterly GDP value.
Entre os fluxos da natureza: diálogos entre o design, a arte e o meio ambiente
Authors: Arantes Priscila , Prado Gilbertto
Published: October 2024

Neste texto, discutimos as relações entre o design, a arte e o meio ambiente a partir de uma perspectiva transdisciplinar. Para tanto, o artigo divide-se em três partes: na primeira, fazemos uma breve discussão enfocando os debates decoloniais no campo do design, através de autores como Walter Mignolo e Arturo Escobar. Na segunda, trazemos como estudos de caso práticas artísticas e produções que dialogam com o campo do design, da arte e da tecnologia e que colocam em debate questões relacionadas ao meio ambiente e à natureza, indicando-nos caminhos férteis para pensarmos e imaginarmos outros modos de ser e viver no mundo contemporâneo. No último tópico, voltamos nosso olhar para os projetos Desertesejo (2000/2014), Amoreiras (2010) e Encontros (2012), do artista Gilbertto Prado e/ou com o grupo Poéticas Digitais.
Vraag & Antwoord
Authors: Vermeersch A.-S. , Opsomer G.
Published: October 2024

Udder cleft-dermatitis
Analysing the Factors Determining the Acceptance of Blockchain Technology within the Mauritian Tourism Industry - Use of an Extended UTAUT Model
Authors: Ramphul N. , Sunecher Y. , Amelot L. , Puchooa K.
Published: October 2024

The aim of this study will be on the investigation of the behavioural intention to accept Blockchain Technology within the tourism industry in the Mauritian context. Partial Least Square-Structural Equation Modelling (PLS-SEM) has been employed for investigation and analysis.The research found that the most important predictors to affect the behavioural intention towards Blockchain Technology acceptance was that of Trust Transparency and Hedonic Motivation. In the same line, Performance Expectancy, Social Influence and Effort Expectancy, Security, Facilitating Conditions and Cost of Innovations had positive significance with the behavioural intention. Organisational Size was used as a moderator and was found that indirect specific effects were significant with Facilitating Conditions and Hedonic Motivation on the Behavioural Intention towards Blockchain Technology. Organisational culture has been investigated to be key emerging conditions since the concept of resistance to change, as emanated from findings, is ingrained in the culture of organisation. Attitudes and beliefs of employees may align with resistance, thus influencing how they perceive and respond to change initiatives. The study is one of the first study that has investigated the adoption of blockchain within the tourism industry in Mauritius thus contributing to new findings to the existing literature.
ANT COLONY OPTIMISATION COUPLED WITH CHAOTIC DATA MINING FOR ENHANCED WEATHER PREDICTION ANALYSIS
Authors:   Sri Krishna Adithya College of Arts and Science, India, J Santhosh , Balde Govind Hanmantrao ,   NTVS G.T. Patil Arts, Commerce and Science College, India, A Rajesh Kumar ,   N.S.N. College of Engineering and Technology, India, Akana Chandra Mouli Venkata Srinivas ,   Bonam Venkata Chalamayya Engineering College, India
Published: October 2024

Meteorological predictions play a pivotal role in various sectors, from agriculture to disaster management. While traditional weather prediction models exhibit proficiency, challenges persist in accurately capturing the complex and dynamic nature of atmospheric phenomena. Conventional weather prediction models often struggle to adapt to the intricacies of climate patterns, leading to suboptimal forecasting accuracy. The need for more robust methodologies that can effectively extract patterns from vast datasets and optimize model parameters is evident. Existing literature lacks comprehensive studies that seamlessly integrate ACO and Data Mining for weather prediction. This research bridges the gap by proposing a novel framework that leverages ACO optimization capabilities to refine Data Mining models, thereby improving the precision of weather forecasts. The proposed method involves utilizing ACO to optimize the parameters of Data Mining algorithms, such as decision trees and neural networks. ACO ability to find optimal solutions is harnessed to fine-tune the model parameters, enhancing its capability to extract meaningful patterns from historical weather data. Experiments demonstrate promising results, with a significant improvement in the accuracy of weather predictions compared to traditional models. The integrated approach shows particular efficacy in handling non-linear relationships and abrupt changes in weather patterns.
Leveraging Machine Learning to Identify Subgroups of Misclassified Patients in the Emergency Department: Multicenter Proof-of-Concept Study
Authors: Wyatt Sage , Lunde Markussen Dagfinn , Haizoune Mounir , Vestbø Anders Strand , Sima Yeneabeba Tilahun , Sandboe Maria Ilene , Landschulze Marcus , Bartsch Hauke , Sauer Christopher Martin
Published: October 2024

Background

Hospitals use triage systems to prioritize the needs of patients within available resources. Misclassification of a patient can lead to either adverse outcomes in a patient who did not receive appropriate care in the case of undertriage or a waste of hospital resources in the case of overtriage. Recent advances in machine learning algorithms allow for the quantification of variables important to under- and overtriage.

Objective

This study aimed to identify clinical features most strongly associated with triage misclassification using a machine learning classification model to capture nonlinear relationships.

Methods

Multicenter retrospective cohort data from 2 big regional hospitals in Norway were extracted. The South African Triage System is used at Bergen University Hospital, and the Rapid Emergency Triage and Treatment System is used at Trondheim University Hospital. Variables included triage score, age, sex, arrival time, subject area affiliation, reason for emergency department contact, discharge location, level of care, and time of death were retrieved. Random forest classification models were used to identify features with the strongest association with overtriage and undertriage in clinical practice in Bergen and Trondheim. We reported variable importance as SHAP (SHapley Additive exPlanations)-values.

Results

We collected data on 205,488 patient records from Bergen University Hospital and 304,997 patient records from Trondheim University Hospital. Overall, overtriage was very uncommon at both hospitals (all <0.1%), with undertriage differing between both locations, with 0.8% at Bergen and 0.2% at Trondheim University Hospital. Demographics were similar for both hospitals. However, the percentage given a high-priority triage score (red or orange) was higher in Bergen (24%) compared with 9% in Trondheim. The clinical referral department was found to be the variable with the strongest association with undertriage (mean SHAP +0.62 and +0.37 for Bergen and Trondheim, respectively).

Conclusions

We identified subgroups of patients consistently undertriaged using 2 common triage systems. While the importance of clinical patient characteristics to triage misclassification varies by triage system and location, we found consistent evidence between the two locations that the clinical referral department is the most important variable associated with triage misclassification. Replication of this approach at other centers could help to further improve triage scoring systems and improve patient care worldwide.
The Impact of International Classification of Disease–Triggered Prescription Support on Telemedicine: Observational Analysis of Efficiency and Guideline Adherence
Authors: Accorsi Tarso Augusto Duenhas , Eduardo Anderson Aires , Baptista Carlos Guilherme , Moreira Flavio Tocci , Morbeck Renata Albaladejo , Köhler Karen Francine , Lima Karine de Amicis , Pedrotti Carlos Henrique Sartorato
Published: October 2024

Background

Integrating decision support systems into telemedicine may optimize consultation efficiency and adherence to clinical guidelines; however, the extent of such effects remains underexplored.

Objective

This study aims to evaluate the use of ICD (International Classification of Disease)-coded prescription decision support systems (PDSSs) and the effects of these systems on consultation duration and guideline adherence during telemedicine encounters.

Methods

In this retrospective, single-center, observational study conducted from October 2021 to March 2022, adult patients who sought urgent digital care via direct-to-consumer video consultations were included. Physicians had access to current guidelines and could use an ICD-triggered PDSS (which was introduced in January 2022 after a preliminary test in the preceding month) for 26 guideline-based conditions. This study analyzed the impact of implementing automated prescription systems and compared these systems to manual prescription processes in terms of consultation duration and guideline adherence.

Results

This study included 10,485 telemedicine encounters involving 9644 patients, with 12,346 prescriptions issued by 290 physicians. Automated prescriptions were used in 5022 (40.67%) of the consultations following system integration. Before introducing decision support, 4497 (36.42%) prescriptions were issued, which increased to 7849 (63.57%) postimplementation. The physician’s average consultation time decreased significantly to 9.5 (SD 5.5) minutes from 11.2 (SD 5.9) minutes after PDSS implementation (P<.001). Of the 12,346 prescriptions, 8683 (70.34%) were aligned with disease-specific international guidelines tailored for telemedicine encounters. Primary medication adherence in accordance with existing guidelines was significantly greater in the decision support group than in the manual group (n=4697, 93.53% vs n=1389, 49.14%; P<.001).

Conclusions

Most of the physicians adopted the PDSS, and the results demonstrated the use of the ICD-code system in reducing consultation times and increasing guideline adherence. These systems appear to be valuable for enhancing the efficiency and quality of telemedicine consultations by supporting evidence-based clinical decision-making.
Feasibility of a Mobile App–Based Cognitive-Behavioral Perinatal Skills Program: Protocol for Nonrandomized Pilot Trial
Authors: Temkin-Yu Andrea B , Ayaz Aliza , Blicker Ella , Liu Michael X , Oh Ace , Siegel Isabelle E , Seewald Meredith J , Hermann Alison D , Givrad Soudebah , Baez Lara M , Osborne Lauren M , Green Cori M , Schier Maddy M , Davis Alexandra M , Zhu Shasha , Falk Avital , Bennett Shannon M
Published: October 2024

Background

Mental illness is one of the top causes of preventable pregnancy-related deaths in the United States. There are many barriers that interfere with the ability of perinatal individuals to access traditional mental health care. Digital health interventions, including app-based programs, have the potential to increase access to useful tools for these individuals. Although numerous mental health apps exist, there is little research on developing programs to address the unique needs of perinatal individuals. In an effort to fill this gap, a multidisciplinary team of experts in psychology, psychiatry, obstetrics, and pediatric primary care collaborated to develop the novel Perinatal Skills Program within Maya, a flexible and customizable cognitive-behavioral skills app. Maya-Perinatal Skills Program (M-PSP) uses evidence-based strategies to help individuals manage their mood and anxiety symptoms during pregnancy and post partum.

Objective

This pilot study aims to assess the feasibility, acceptability, and usability of M-PSP and explore links between program use and symptoms of anxiety and low mood.

Methods

This single-arm trial will recruit 50 pregnant or postpartum individuals with mild-to-moderate anxiety or mood symptoms. Participants will be recruited from a variety of public and private insurance-based psychiatry, obstetrics, and primary care clinics at a large academic medical center located in New York City. Participants will complete all sessions of M-PSP and provide feedback. Outcome measures will include qualitative and quantitative assessments of feasibility, acceptability, and usability, passively collected program usage data, and symptom measures assessing mood, anxiety, and trauma. Planned data analysis includes the use of the grounded theory approach to identify common themes in qualitative feedback, as well as an exploration of possible associations between quantitative data regarding program use and symptoms.

Results

The recruitment began on August 2023. As of October 2024, a total of 32 participants have been enrolled. The recruitment will continue until 50 participants have been enrolled.

Conclusions

Digital health interventions, like M-PSP, have the potential to create new pathways to reach individuals struggling with their mental health. The results of this study will be the groundwork for future iterations of M-PSP in the hopes of providing an accessible and helpful tool for pregnant and postpartum individuals.

Trial Registration

ClinicalTrials.gov NCT05897619; https://classic.clinicaltrials.gov/ct2/show/NCT05897619

International Registered Report Identifier (IRRID)

PRR1-10.2196/59461
Development of an Educational Website for Patients With Cancer and Preexisting Autoimmune Diseases Considering Immune Checkpoint Blockers: Usability and Acceptability Study (Preprint)
Authors: Lopez-Olivo Maria A , Suarez-Almazor Maria E , Duhon Gabrielle F , Cherry McKenna , Lu Huifang , Calabrese Cassandra , Altan Mehmet , Tawbi Hussain , Meara Alexa , Bingham Clifton O , Diab Adi , Leal Viola B , Volk Robert J
Published: October 2024

BACKGROUND

Patients with cancer and an underlying autoimmune disease who are considering immune checkpoint blockers (ICBs) need to know about the benefits and risks of severe immune-related adverse events and flares of the autoimmune condition.

OBJECTIVE

This study aims to develop and alpha test an educational website for patients with cancer.

METHODS

Learning topics, images, and website architecture (including flow and requirements) were developed and iteratively reviewed by members of a community scientist program, a patient advisory group, and content experts. Alpha testing was performed, measuring the site’s usability using the Suitability Assessment of Materials and its acceptability using the Ottawa Acceptability Measure.

RESULTS

The website included a home page; general information about ICBs; comprehensive modules on the benefits and risks of ICBs for patients with cancer and preexisting autoimmune diseases; general wellness information; and features such as a quiz, additional resources, and a glossary. For the alpha testing, 9 users assessed the newly developed website. Patient reviewers (n=5) had rheumatoid arthritis, Crohn disease, Sjogren syndrome, or vasculitis. Health care provider reviewers (n=4) were medical oncologists or rheumatologists. The median Suitability Assessment of Materials rating was 75 (IQR 70-79; range 0-100) for patients versus 66 (IQR 57-72; range 0-100) for providers (scores ≥70 indicate no substantial changes needed). Recommendations for improvement, mostly involving navigation and accessibility, were addressed. All participants expressed that the website was acceptable and balanced in terms of discussion of benefits and harms. Because half (2/4, 50%) of the providers suggested we increase the amount of information, we extended the content on the impact of having an autoimmune disease when considering ICB treatment, the probability of flares, and the management of flares in this context.

CONCLUSIONS

The feedback led to minor revisions to enhance readability, navigation, and accessibility, ensuring the website’s suitability as a decision-making aid. The newly developed website could become a supporting tool to facilitate patient-physician discussion regarding ICBs.

CLINICALTRIAL
Acoustic Features for Identifying Suicide Risk in Crisis Hotline Callers: A Machine Learning Approach (Preprint)
Authors: Su Zhengyuan , Jiang Huadong , Yang Ying , Hou Xiangqing , Su Yanli , Yang Li
Published: October 2024

BACKGROUND

Crisis hotlines serve as a crucial avenue for early identification of suicide risk, which is of paramount importance for suicide prevention and intervention. However, assessing the risk of callers in crisis hotline context is constrained by factors such as lack of non-verbal communication cues, anonymity, time limitations, and single-occasion intervention. Therefore, it is necessary to develop approaches including acoustic features for identifying suicide risk among hotline callers early and quickly. Given the complicated features of the sound, adopting artificial intelligence models to analyze callers’ acoustic features is promising.

OBJECTIVE

In this study, we investigated the feasibility of using acoustic features to predict suicide risk in crisis hotline callers. We also adopted a machine learning approach to analyze the complex acoustic features of hotline callers, with the aim of developing suicide risk prediction models.

METHODS

We collected audio data from crisis hotline calls, and extracted various acoustic features, including basic acoustic features and high-level statistical function features (HSFs). The performance of prediction models based on basic acoustic features was compared with those utilizing HSFs.

RESULTS

The development of machine learning models utilizing HSF acoustic features has been demonstrated to enhance recognition performance compared to models based solely on basic acoustic features. The random forest classifier, developed with HSFs, achieved the best performance in detecting suicide risk among the models evaluated(Accuracy = 0.75, F1-score = 0.70, Recall = 0.76, False Negative Rate = 0.24).

CONCLUSIONS

These results demonstrated the potential of developing AI-based early warning systems using acoustic features in identifying suicide risk among crisis hotline callers. Our work also has implications for employing acoustic features to identify suicide risk in voice salient contexts.

CLINICALTRIAL

The present study has been approved by the Institutional Review Board of Tianjin University (2024-453). The researchers confirm that all stages of this study were conducted in accordance with the ethical standards set forth by the Helsinki Declaration, as revised in 1989. Prior to being connected with a hotline operator, callers were informed via an automated message that their calls would be recorded and that any data obtained from these calls would be treated in accordance with the tenets of confidentiality and analyzed in an anonymized manner.
A Culturally Tailored mHealth Intervention to Promote Physical Activity in African American Men: A Protocol for a Comparative Effectiveness Trial of MobileMen (Preprint)
Authors: Nuss Kayla , Brice Amanda , Hebert Callie , Nauta Phillip , Stull April J. , Swift Damon L. , Griffith Derek , Buller David B. , Newton Jr Robert L.
Published: October 2024

BACKGROUND

African American men are at a higher risk for serious health conditions like cardiovascular disease, diabetes, and stroke compared to non-Hispanic White men. Physical activity (PA) is a modifiable health behavior that has been shown to decrease chronic disease risk, yet PA engagement is alarmingly low in African American men. Interventions to improve PA engagement are effective in a number of populations; very few have been tailored to the unique needs of African American men. Even fewer have leveraged mobile health applications (apps), despite African American men’s interest in and willingness to use such technologies for health improvement.

OBJECTIVE

This comparative effectiveness trial aims to evaluate MobileMen, a PA promotion app tailored to the needs and preferences of African American men. The trial will compare MobileMen to a commercially available PA promotion app with similar features but lacks culturally tailored components.

METHODS

We will recruit a sample of “low active” (accumulating < 7,500 steps per day) African American men (n=100) aged > 30 years from Baton Rouge, Louisiana and surrounding communities. All participants will be given a Fitbit Charge 6 wearable activity tracker to assess daily PA and steps, and will be randomized to either the intervention app, MobileMen), or the comparator app, a commercially available PA tracking app called Stridekick. Stridekick has similar features to MobileMen but was not intentionally designed for African American men. The intervention period is 6 months during which participants will interact with their assigned mobile app. MobileMen includes features such as digital badges earned for PA, tangible prizes like exercise equipment, challenges among participants, goal setting, and nutrition, PA, and behavior change educational information in text, audio, and video formats. Participants will complete assessments at baseline and 6-months post-randomization. Assessments include objective measurements of daily steps and minutes of moderate to vigorous PA, quality of life, dietary measures, self-efficacy for fruit and vegetable consumption and PA, and autonomous motivation for PA.

RESULTS

This trial is in the start-up phase. MobileMen development and usability testing was completed in August 2024. Recruitment efforts began in October 2024. The trial and associated data analyses and interpretation are planned to be completed by Fall 2025.

CONCLUSIONS

Mobile apps are a widely accessible means to disseminate culturally tailored PA promotion interventions to various populations, including African American men. MobileMen has the potential to impact PA engagement in African American men, which would dramatically improve the overall health and chronic disease risk in this underrepresented group.

CLINICALTRIAL
Persepsi Sakit, Pengobatan, dan Kepuasan Peserta JKN Terhadap Pelayanan Kesehatan di Fasilitas Kesehatan Tingkat Pertama
Authors: Sukanto Anung Khoiri , Endarti Dwi , Widayanti Anna Wahyuni
Published: October 2024

Salah satu faktor yang mendorong peserta JKN untuk mengunjungi fasilitas kesehatan adalah persepsinya terhadap sakit, pengobatan, dan kepuasan peserta tersebut terhadap pelayanan kesehatan, khususnya di fasilitas kesehatan tingkat pertama. Kepuasan pasien merupakan salah satu indikator keberhasilan dalam pemberian pelayanan kesehatan. untuk mengetahui gambaran persepsi sakit, pengobatan, dan kepuasan peserta JKN terhadap pelayanan kesehatan di fasilitas kesehatan tingkat pertama dan mengetahui hubungan antara karakter sosiodemografi dengan ketiga varibael tersebut. Penelitian ini merupakan penelitian observasional analitik dengan pengumpulan data secara cross-sectional. Pengambilan data dengan teknik convenience sampling.. Metode pengumpulan data menggunakan metode kuesioner berbasis online. Minimal jumlah sampel pada penelitian ini sebanyak 385 responden peserta JKN untuk memperoleh 95% Confidence Interval (CI) dan margin error 0,05. Hasil dari penelitian terdapat 390 responden yang masuk kedalam kriteria inklusi. Pada persepsi sakit, persepsi terhadap pengobatan, dan kepuasan sebagian besar responden memiliki persepsi positif yaitu sejumlah 373 responden (95,6%), 374 responden (95,8%), dan 363 responden (93%). Variabel yang berhubungan adalah jumlah penghasilan keluarga dan jumlah tanggungan dalam keluarga dengan persepsi sakit, dengan p-value 0,043 (<0,05). Mayoritas responden memiliki persepsi positif tentang sakit dan pengobatan. Sebagian responden juga merasa puas terhadap pelayanan kesehatan di Fasilitas Pelayanan Kesehatan Tingkat Pertama.
Drug Interaction Study of Antihypertension in Geriatric Patients Diagnosed Hypertension at Puskesmas Mauponggo, Nusa Tenggara Timur
Authors: Virginia Dita Maria , Jago Uko Maria Anjeline
Published: October 2024

Hypertension is one of the main causes of mortality and morbidity in Indonesia. Treatment of hypertension in geriatric patients has the potential to increase the risk of drug-drug interactions because geriatric patients tend to experience polypharmacy. This study aims to analyze differences in mean blood pressure based on the interaction of antihypertensive drugs with other therapies in geriatric patients who suffer from hypertension at the Mauponggo Health Center, Nagekeo, East Nusa Tenggara. This research is a type of analytic observational research using a research design cross sectional. Data collection was carried out retrospectively. Data was collected using medical records collected from January to December 2021. In this study, a sample of 101 patients was obtained who met the predetermined inclusion and exclusion criteria. Data analysis using unpaired T test to analyze the difference of mean blood pressure based on the presence of antihypertensive drug interactions in geriatric patients, regarding on a significance level of p<0.05. The results showed that drug interactions had no effect on the mean systolic (p-value 0.063), or average diastolic (pvalue 0.392) in geriatric patients suffering from hypertension at the Mauponggo Health Center, Nagekeo, East Nusa Tenggara. Antihypertensive drug interactions did not affect the average blood pressure in geriatric patients in this study. Further research is required to classify the types of antihypertensive drugs that significantly impact blood pressure.
Analyzing the Potential of Herbal Plant Research for Alzheimer's Disease in Diabetes: A Bibliometric Approach
Authors: Marzuki Ahmad , Rahmayani Almira , Khafi Muhammad , Hertiani Triana , Murwanti Retno
Published: October 2024

Alzheimer’s disease is a progressive neurologic dementia disorder and the fifth leading cause of death among elderly individuals. Its pathogenesis is closely linked to diabetes-induced brain insulin resistance, which accelerates beta-amyloid accumulation, exacerbating disease severity. This condition significantly impacts quality of life and healthcare costs, necessitating effective treatment strategies. Medicinal plants offer a promising avenue, with bibliometric analysis identifying trending active compounds for potential development as therapies for diabetic Alzheimer’s. This study analyzed 200 articles from the Scopus database, employing Scopus and VOSviewer 1.6.20 to visualize bibliometric trends by publication, country/territory, subject area, and keyword co-occurrence. Results indicate a recent decline in research activity, with China leading in publications across pharmacology, medicine, and biochemistry. Notably, flavonoids like “quercetin,” “kaempferol,” and “gallic acid” emerged as prominent topics.Keywords: Alzheimer’s diabetes, Bibliometrics, Herbal medicine, Extracts
A Review of the Research on Teachers’ Motivating Style
Authors: Qin Xia
Published: October 2024

With the deepening and development of the application of self-determination theory, the research enthusiasm for teachers’ motivating style is increasing at home and abroad. Teachers’ motivating style refers to the way that teachers motivate students. This paper starts with the theory of self-determination, and on the basis of in-depth elaboration of the connotation and measurement of teachers’ motivating style, reviews the relevant research on teachers’ motivating style at home and abroad. The results show that there are many factors influencing the formation of teachers’ different motivating styles. Meanwhile, different motivating styles also affect students’ learning motivation and learning engagement.
Comparative Analysis of Nutritional Composition and Antimicrobial Properties of Organically and Chemically Cultivated Garlic (Allium sativum)
Authors: Phate Mayank , Yadav Anil Kumar , Choudhary Vikas
Published: October 2024

Garlic (Allium sativum) is renowned for its culinary uses and medicinal properties, attributed to its bioactive compounds such as allicin and protein. Organic farming practices have been increasingly recognized for producing crops with higher nutrient content and lower environmental impact compared to conventional methods. This study aimed to compare the nutritional composition and antimicrobial properties of organically and chemically grown garlic. Nutritional analysis revealed that organic garlic had significantly higher levels of bioactive elements compared to chemically grown garlic. Specifically, organic garlic contained 161,879.31 mg/kg of protein and 13.64% allicin content, whereas chemically grown garlic had 123,047.28 mg/kg of protein and 11.25% allicin content. Statistical analysis showed significant differences between the mean values of sodium (organic: 9,455.54 ppm, chemical: 5,486.90 ppm), protein (organic: 161,879.31 mg/kg, chemical: 123,047.28 mg/kg), and allicin (organic: 13.64%, chemical: 11.25%). The antimicrobial study demonstrated that organic garlic juice exhibited greater antimicrobial activity against both Salmonella typhi (p < 0.001) and Staphylococcus aureus (p < 0.01) compared to chemical garlic juice. Organic cultivation significantly enhances the nutritional and antimicrobial properties of garlic, making it a healthier and more environmentally friendly choice. These findings underscore the importance of organic farming practices for improving food quality and safety.
Can the Story of Eve (Genesis 2-3) be Interpreted as Feminist
Authors: Roberts Lily
Published: October 2024

This essay will argue that Eve in Genesis 2-3 cannot be interpreted as feminist as her story, tied to Adam, is inherently patriarchal. I will argue against three points that form the basis of a feminist re-interpretation of Genesis 2-3: that Adam is ungendered, that Eve is made from Adam’s side rather than his rib, and, that Eve is Adam’s suitable helper rather than his subordinate. I argue that feminist and traditional interpretations of Eve define her existence in relation to Adam’s prior existence. In this way, Eve consistently represents the Other, as she is defined only in reference to the Subject Adam, a man (De Beauvoir, 1949, 26). Eve is incidental while Adam is essential, and for a representation to be truly feminist it must show the woman as the Subject.
Who is the Blame for the Russia-Ukraine war? Feminist and Postcolonial Perspectives on 'Real Politics'
Authors: Yeroshkina Liza
Published: October 2024

The 2022 Russian invasion of Ukraine has widely been narrated as having epochal significance with far-reaching implications. For leading historians of Eastern Europe, such as Timothy Snyder (2022) and Serhii Plokhy (2015), what we are seeing is an existential threat to democratic norms.
While discussing phenomena of the political world, drawing on a variety of lenses is advantageous; in the case of the Russian-Ukrainian war it is a necessity. This article engages with a combination of lenses provided by feminist and postcolonial theories to critically reflect on the logic, as articulated by Russia's political elites, behind the invasion of Ukraine. It focuses on the role of gender and racialisation in normalising one’s place in the social hierarchy and its ‘appropriate’ behaviour, excusing occupational, violent and genocidal policies under the abstract term of ‘real politics’.
This article attempts to trace the way social structures empower gendered and racialised politics, allowing invasions to be justified. Russia-led wars in Ukraine will be discussed as an example of the consequences of such a structure and ideology. This article will firstly underline a feminist and postcolonial approach that addresses the necessity of social hierarchy analysis to reveal the causes of war. Further sections will focus on unpacking Russia’s claims of the legitimacy of its colonial/great-power state project to incorporate Ukraine. I will conclude with a reflection on how the notion of the nation-state, rooted in the ideologies of social hierarchy and colonial domination, can be seen as having fuelled the ongoing war.
Girlcore: the Right Way to be Female? Examining the Effect of Choice Feminism on What it Means to be a 'Woman' through the Language and Trends of Tiktok
Authors: Scott Ruby
Published: October 2024

Since the beginning of the 2010s and the advent of what many call the fourth wave of feminism, “choice feminism” has accounted for an increasingly large segment of people who call themselves “feminists”. This movement can widely be observed through commentary on femininity on social media such as TikTok and women choose to use the platform. Since the rise of TikTok in 2020 many different trends and debates have appeared in relation to what it means to be a “girl” or “woman”, and these instances can be observed and analysed to ask a larger question of what being female and identifying as such means in the modern era and years to come. In a world more and more defined by our online presence and the use of social media, there is a landscape in which there is increasing desire to market oneself. In using micro-labels, micro-labels here referring to the hyper-specific aesthetic or identity related categories that have risen in popularity over the last couple years on social media (Sojit Pejcha, 2023), we transform ourselves from human beings to concepts. This process seems to be specifically taken up by women who exercise their “choice” to objectify themselves in a radical new way; something that I argue is much more comfortable than having to deal with the true acceptance of the human experience and what it means to be a woman.
“Wha would ha’e thoucht it, Stockings would ha’e boucht it?”
Authors: Rees Ieuan
Published: October 2024

Scottish history, Folklore, Ethnology, Horology, Women’s History, Stockings, Popular Culture, Scottish poetry, Material Culture, Archaeology, Bannockburn, Longcase clocks, Material Culture, Narratology, Local studies, St Ninian’s, Time
A worldwide bibliometric analysis on euthanasia
Authors: Güdük Özden
Published: October 2024

Introduction: Euthanasia, which allows individuals with an incurable disease to end their lives in an honourable way, is a long-debated practice. It is related to various issues such as culture, philosophy, religion, ethics, public value, and efficient use of health resources. While some advocate for the right of individuals to choose euthanasia, others criticize it on ethical, legal, and religious grounds.
Methods: In this study bibliometric analysis was used and the data were obtained from the Web of Science Core Collection database on July 26, 2024. Only English publications and articles were included using keywords such as "euthanasia," "end-of-life decisions," "medical assistance in dying," "physician-assisted death," and "physician-assisted suicide" without time restrictions. VOSviewer software was used to create network and density graphs, and SciMAT software was used to create strategic diagrams.
Results: A total of 2,230 studies published between 1980 and 2024 were analyzed. The author with the most publications is Deliens, L, with 86 studies. The majority of studies were published in the USA, Netherlands, and Canada (692, 336, 225 respectively). The most frequently used keywords are euthanasia, palliative care, and ethics. The highest number of publications (149) was in the year 2021. In the strategic diagram for the first period (between 1980 and 2001), the themes of care and ethics were prominent, while for the second period (between 2002 and 2024), the clusters of nurse and shared decision-making were notable.
Conclusion: After its legalization in the Netherlands, euthanasia has been accepted and implemented in some countries over the years, with variations in scope. Some countries, like the Netherlands and Belgium, also accept health problems related to old age and mental illness as euthanasia requests. The discussion around euthanasia often revolves around the principles of medical ethics, including autonomy, beneficence, non-maleficence, and justice. Studies have focused on the role of physicians and nurses in the process, as well as end-of-life decision-making by patients. Recently, Canada defined the role of nurses in the euthanasia process, marking a significant development.
Libertad testamentaria en Roma. Una aproximación a propósito de la cuestión en el Código Civil y Comercial de la Nación de 2015
Authors: Estrada Susana Isabel
Published: October 2024

El interrogante acerca de si el sucesor continúa la persona del causante o simplemente lo sucede en sus bienes ha generado una larga controversia en la doctrina, desarrollándose dos corrientes con el propósito de fundamentar el origen de la herencia romana. Por una parte, la idea de una ficción que hacía sobrevivir la personalidad del causante, que expresada o a través de sus parientes próximos continuaba rigiendo el destino de sus bienes. Otro criterio se sustentaba en que tenía como finalidad la continuidad del culto familiar y el ejercicio de las potestades del paterfamilias, pero no la sucesión en los bienes, porque ellos estaban destinados al sustento del grupo familiar. La primera regulación en materia sucesoria aparece en el sistema del derecho quiritario que giraba en torno de la voluntad absoluta del pater, no existiendo restricción alguna a ese poder soberano. Surgieron dos interpretaciones, que serán objeto de análisis, acerca del ejercicio de la libertad testamentaria. El trabajo analiza la evolución de la libertad testamentaria en las fuentes romanas desde el derecho primitivo, su evolución en la República, su presencia en el Corpus Iuris Civilis y la suerte que tuvo su proyección al Código Civil y Comercial de 2015.
Vestigios de la institución del divorcio romano en la legislación mexicana
Authors: Munive García Grecia Sofía
Published: October 2024

Una de las instituciones sociales de mayor importancia en la antigüedad romana fue el matrimonio. A pesar del gran valor de esta institución dentro de la sociedad romana, los antiguos legisladores comprendieron que, en determinadas situaciones, era mejor terminar el matrimonio que continuar con un vínculo que ya no era conveniente, útil ni beneficioso para ninguna de las partes. Por lo anterior se incluyó dentro de la legislación la disolución del matrimonio a través del divorcio, ya fuera por iniciativa de uno o de ambos cónyuges.
La disolución del vínculo matrimonial por divorcio no sólo fue importante en la civilización romana, sino también en aquellas que han sido herederas de su magnánima herencia en el ámbito jurídico. En el derecho positivo mexicano, en el cual es posible constatar la recepción del derecho romano en diversas áreas -sobre todo en el derecho civil-, encontramos la institución del divorcio en la cual aún es posible vislumbrar la esencia de la institución plasmada en los ordenamientos jurídicos de la antigua Roma.
Impact of 4D Seismic Data Assimilation in the Production Forecasting of a Heavy Oil Turbidite Sandstone Field Offshore Brazil
Authors: Silva Felipe Bruno Mesquita , Davolio Alessandra , Schiozer Denis José
Published: October 2024

The incorporation of 4D seismic data can be done at model characterization and data assimilation steps, the latter applying the observed data to update the model properties. In this work, we evaluate the impact of 4DS data in the production forecasting results investigating the influence on these distinct steps. We employ a prior model set generated without 4DS data and another prior set with 4DS in the characterisation. We perform, then, the DA in three different ways: (1) using only well history data with a prior set without 4DS; (2) using well history and 4DS data with this same prior set; and (3) using well history and 4DS data with the prior set generated with 4DS data. We employ the Ensemble Smoother with Multiple Data Assimilation method for data assimilation and implement a procedure to adjust the well productivities and injectivities after DA. This work assesses the differences among the three DA cases in terms of field oil production forecasting, model attributes and model misfits, the latter evaluated in terms of the assimilated data set and of a different data set for validation purposes only. We apply the work to a real heavy oil turbiditic field located offshore Brazil. The case application demonstrates a successful data assimilation study on a real field integrating well history and 4DS data. The results show that the utilisation of 4DS in both model characterisation and DA steps brought value to the final uncertainty reduction results. The posterior model ensemble with 4DS data in model characterization and DA provided the lowest model misfits overall to the full data set, being the best choice for application in field production forecasting studies. The case without 4DS data provided significantly more pessimistic field oil production than the cases with 4DS, making very evident the importance of employing 4DS at uncertainty reduction workflows.