bluuebunny/crossref_metadata_2025 huggingface dataset:
Case Identification of Depression in Inpatient Electronic Medical Records: Scoping Review
Authors: Grothman Allison , Ma William J , Tickner Kendra G , Martin Elliot A , Southern Danielle A , Quan Hude
Published: July 2024

Background

Electronic medical records (EMRs) contain large amounts of detailed clinical information. Using medical record review to identify conditions within large quantities of EMRs can be time-consuming and inefficient. EMR-based phenotyping using machine learning and natural language processing algorithms is a continually developing area of study that holds potential for numerous mental health disorders.

Objective

This review evaluates the current state of EMR-based case identification for depression and provides guidance on using current algorithms and constructing new ones.

Methods

A scoping review of EMR-based algorithms for phenotyping depression was completed. This research encompassed studies published from January 2000 to May 2023. The search involved 3 databases: Embase, MEDLINE, and APA PsycInfo. This was carried out using selected keywords that fell into 3 categories: terms connected with EMRs, terms connected to case identification, and terms pertaining to depression. This study adhered to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines.

Results

A total of 20 papers were assessed and summarized in the review. Most of these studies were undertaken in the United States, accounting for 75% (15/20). The United Kingdom and Spain followed this, accounting for 15% (3/20) and 10% (2/20) of the studies, respectively. Both data-driven and clinical rule-based methodologies were identified. The development of EMR-based phenotypes and algorithms indicates the data accessibility permitted by each health system, which led to varying performance levels among different algorithms.

Conclusions

Better use of structured and unstructured EMR components through techniques such as machine learning and natural language processing has the potential to improve depression phenotyping. However, more validation must be carried out to have confidence in depression case identification algorithms in general.
Identifying Marijuana Use Behaviors Among Youth Experiencing Homelessness Using a Machine Learning–Based Framework: Development and Evaluation Study
Authors: Deng Tianjie , Urbaczewski Andrew , Lee Young Jin , Barman-Adhikari Anamika , Dewri Rinku
Published: July 2024

Background

Youth experiencing homelessness face substance use problems disproportionately compared to other youth. A study found that 69% of youth experiencing homelessness meet the criteria for dependence on at least 1 substance, compared to 1.8% for all US adolescents. In addition, they experience major structural and social inequalities, which further undermine their ability to receive the care they need.

Objective

The goal of this study was to develop a machine learning–based framework that uses the social media content (posts and interactions) of youth experiencing homelessness to predict their substance use behaviors (ie, the probability of using marijuana). With this framework, social workers and care providers can identify and reach out to youth experiencing homelessness who are at a higher risk of substance use.

Methods

We recruited 133 young people experiencing homelessness at a nonprofit organization located in a city in the western United States. After obtaining their consent, we collected the participants’ social media conversations for the past year before they were recruited, and we asked the participants to complete a survey on their demographic information, health conditions, sexual behaviors, and substance use behaviors. Building on the social sharing of emotions theory and social support theory, we identified important features that can potentially predict substance use. Then, we used natural language processing techniques to extract such features from social media conversations and reactions and built a series of machine learning models to predict participants’ marijuana use.

Results

We evaluated our models based on their predictive performance as well as their conformity with measures of fairness. Without predictive features from survey information, which may introduce sex and racial biases, our machine learning models can reach an area under the curve of 0.72 and an accuracy of 0.81 using only social media data when predicting marijuana use. We also evaluated the false-positive rate for each sex and age segment.

Conclusions

We showed that textual interactions among youth experiencing homelessness and their friends on social media can serve as a powerful resource to predict their substance use. The framework we developed allows care providers to allocate resources efficiently to youth experiencing homelessness in the greatest need while costing minimal overhead. It can be extended to analyze and predict other health-related behaviors and conditions observed in this vulnerable community.
Added Value of Medical Subject Headings Terms in Search Strategies of Systematic Reviews: Comparative Study
Authors: Leblanc Victor , Hamroun Aghiles , Bentegeac Raphaël , Le Guellec Bastien , Lenain Rémi , Chazard Emmanuel
Published: July 2024

Background

The massive increase in the number of published scientific articles enhances knowledge but makes it more complicated to summarize results. The Medical Subject Headings (MeSH) thesaurus was created in the mid-20th century with the aim of systematizing article indexing and facilitating their retrieval. Despite the advent of search engines, few studies have questioned the relevance of the MeSH thesaurus, and none have done so systematically.

Objective

The objective of this study was to estimate the added value of using MeSH terms in PubMed queries for systematic reviews (SRs).

Methods

SRs published in 4 high-impact medical journals in general medicine over the past 10 years were selected. Only SRs for which a PubMed query was provided were included. Each query was transformed to obtain 3 versions: the original query (V1), the query with free-text terms only (V2), and the query with MeSH terms only (V3). These 3 queries were compared with each other based on their sensitivity and positive predictive values.

Results

In total, 59 SRs were included. The suppression of MeSH terms had an impact on the number of relevant articles retrieved for 24 (41%) out of 59 SRs. The median (IQR) sensitivities of queries V1 and V2 were 77.8% (62.1%-95.2%) and 71.4% (42.6%-90%), respectively. V1 queries provided an average of 2.62 additional relevant papers per SR compared with V2 queries. However, an additional 820.29 papers had to be screened. The cost of screening an additional collected paper was therefore 313.09, which was slightly more than triple the mean reading cost associated with V2 queries (88.67).

Conclusions

Our results revealed that removing MeSH terms from a query decreases sensitivity while slightly increasing the positive predictive value. Queries containing both MeSH and free-text terms yielded more relevant articles but required screening many additional papers. Despite this additional workload, MeSH terms remain indispensable for SRs.
Evaluating the Usability and Quality of a Clinical Mobile App for Assisting Physicians in Head Computed Tomography Scan Ordering: Mixed Methods Study
Authors: Meidani Zahra , Omidvar Aydine , Akbari Hossein , Asghari Fatemeh , Khajouei Reza , Nazemi Zahra , Nabovati Ehsan , Holl Felix
Published: July 2024

Background

Among the numerous factors contributing to health care providers’ engagement with mobile apps, including user characteristics (eg, dexterity, anatomy, and attitude) and mobile features (eg, screen and button size), usability and quality of apps have been introduced as the most influential factors.

Objective

This study aims to investigate the usability and quality of the Head Computed Tomography Scan Appropriateness Criteria (HAC) mobile app for physicians’ computed tomography scan ordering.

Methods

Our study design was primarily based on methodological triangulation by using mixed methods research involving quantitative and qualitative think-aloud usability testing, quantitative analysis of the Mobile Apps Rating Scale (MARS) for quality assessment, and debriefing across 3 phases. In total, 16 medical interns participated in quality assessment and testing usability characteristics, including efficiency, effectiveness, learnability, errors, and satisfaction with the HAC app.

Results

The efficiency and effectiveness of the HAC app were deemed satisfactory, with ratings of 97.8% and 96.9%, respectively. MARS assessment scale indicated the overall favorable quality score of the HAC app (82 out of 100). Scoring 4 MARS subscales, Information (73.37 out of 100) and Engagement (73.48 out of 100) had the lowest scores, while Aesthetics had the highest score (87.86 out of 100). Analysis of the items in each MARS subscale revealed that in the Engagement subscale, the lowest score of the HAC app was “customization” (63.6 out of 100). In the Functionality subscale, the HAC app’s lowest value was “performance” (67.4 out of 100). Qualitative think-aloud usability testing of the HAC app found notable usability issues grouped into 8 main categories: lack of finger-friendly touch targets, poor search capabilities, input problems, inefficient data presentation and information control, unclear control and confirmation, lack of predictive capabilities, poor assistance and support, and unclear navigation logic.

Conclusions

Evaluating the quality and usability of mobile apps using a mixed methods approach provides valuable information about their functionality and disadvantages. It is highly recommended to embrace a more holistic and mixed methods strategy when evaluating mobile apps, because results from a single method imperfectly reflect trustworthy and reliable information regarding the usability and quality of apps.
Visualizing Patient Pathways and Identifying Data Repositories in a UK Neurosciences Center: Exploratory Study
Authors: Knight Jo , Chandrabalan Vishnu Vardhan , Emsley Hedley C A
Published: July 2024

Background

Health and clinical activity data are a vital resource for research, improving patient care and service efficiency. Health care data are inherently complex, and their acquisition, storage, retrieval, and subsequent analysis require a thorough understanding of the clinical pathways underpinning such data. Better use of health care data could lead to improvements in patient care and service delivery. However, this depends on the identification of relevant datasets.

Objective

We aimed to demonstrate the application of business process modeling notation (BPMN) to represent clinical pathways at a UK neurosciences center and map the clinical activity to corresponding data flows into electronic health records and other nonstandard data repositories.

Methods

We used BPMN to map and visualize a patient journey and the subsequent movement and storage of patient data. After identifying several datasets that were being held outside of the standard applications, we collected information about these datasets using a questionnaire.

Results

We identified 13 standard applications where neurology clinical activity was captured as part of the patient’s electronic health record including applications and databases for managing referrals, outpatient activity, laboratory data, imaging data, and clinic letters. We also identified 22 distinct datasets not within standard applications that were created and managed within the neurosciences department, either by individuals or teams. These were being used to deliver direct patient care and included datasets for tracking patient blood results, recording home visits, and tracking triage status.

Conclusions

Mapping patient data flows and repositories allowed us to identify areas wherein the current electronic health record does not fulfill the needs of day-to-day patient care. Data that are being stored outside of standard applications represent a potential duplication in the effort and risks being overlooked. Future work should identify unmet data needs to inform correct data capture and centralization within appropriate data architectures.
Ethical Considerations and Fundamental Principles of Large Language Models in Medical Education: Viewpoint
Authors: Zhui Li , Fenghe Li , Xuehu Wang , Qining Fu , Wei Ren
Published: July 2024

This viewpoint article first explores the ethical challenges associated with the future application of large language models (LLMs) in the context of medical education. These challenges include not only ethical concerns related to the development of LLMs, such as artificial intelligence (AI) hallucinations, information bias, privacy and data risks, and deficiencies in terms of transparency and interpretability but also issues concerning the application of LLMs, including deficiencies in emotional intelligence, educational inequities, problems with academic integrity, and questions of responsibility and copyright ownership. This paper then analyzes existing AI-related legal and ethical frameworks and highlights their limitations with regard to the application of LLMs in the context of medical education. To ensure that LLMs are integrated in a responsible and safe manner, the authors recommend the development of a unified ethical framework that is specifically tailored for LLMs in this field. This framework should be based on 8 fundamental principles: quality control and supervision mechanisms; privacy and data protection; transparency and interpretability; fairness and equal treatment; academic integrity and moral norms; accountability and traceability; protection and respect for intellectual property; and the promotion of educational research and innovation. The authors further discuss specific measures that can be taken to implement these principles, thereby laying a solid foundation for the development of a comprehensive and actionable ethical framework. Such a unified ethical framework based on these 8 fundamental principles can provide clear guidance and support for the application of LLMs in the context of medical education. This approach can help establish a balance between technological advancement and ethical safeguards, thereby ensuring that medical education can progress without compromising the principles of fairness, justice, or patient safety and establishing a more equitable, safer, and more efficient environment for medical education.
Social Media Perceptions and Insights During the COVID-19 Pandemic in the United Kingdom (Preprint)
Authors: Araghi Marzieh , Sahota Arron , Czachorowski Maciej , Naicker Kevin , Bohm Natalie , Phillipps Katie , Gaddum James , Cook Erica Jane
Published: July 2024

BACKGROUND

Social media listening can be leveraged to obtain authentic perceptions about events, their impact, guidelines and policies. There has been to date no research that has examined COVID-19 patients’ experiences from diagnosis to treatment using social media listening in the United Kingdom.

OBJECTIVE

This study aimed to assess public perceptions, insights, and sentiments throughout the patient journey from diagnosis to treatment during the coronavirus disease 2019 (COVID-19) pandemic.

METHODS

A comprehensive search query was designed to retrieve social media data that refer to COVID-19 and treatment. The search was conducted using the social media monitoring tool, Synthesio (Ipsos). Data were retrospectively collected for the period covering September 2019 to September 2022 from Twitter/X, Facebook, Instagram, and YouTube as well as 126 public forums (including Health Unlocked, Mums Net, The Student Room and Patient Forums UK). Available data in the UK expressed in the English language were collected and filtered generating a final dataset consisting of 31,319 posts. Complimentary Google trend analyses of Google search terms mentioning COVID-19 treatments were also performed.

RESULTS

Overall, the trend observed from social media posts relating to COVID-19 treatment extracted in Synthesio was largely congruent with the trend of COVID-19 searches on Google. We observed that the public had a good understanding of COVID-19 symptoms with many expressing concerns relating to severe symptoms. Negative attitude was associated with lack of testing and delay in diagnosis in the early part of the pandemic. Finally, the public displayed a high desire to access information regarding COVID-19 treatment.

CONCLUSIONS

Findings from this study have the potential to inform decision-making regarding public health interventions, communication strategies, and healthcare policies in the UK during future public health emergencies.
Structural and Functional Usages of Lexical Bundle in Native and Non-Native English Sociology Academic Writings: A Comparative Study Based on MICUSP
Authors: Long Bingren , Shao Shaohui , Yao Juan , Zhang Junchen
Published: July 2024

Framed within Biber’s structural classification and Hyland’s functional classification, this study investigates the structural and functional uses of four-word lexical bundles in sociology academic writings by native (NS) and non-native speakers (NNS) of English by using the Michigan Corpus of Upper-level Student Papers (MICUSP) and tools such as AntConc and Xu Jiajin’s Log-Likelihood Ratio Test Calculator. The statistical findings reveal that both NS and NNS predominantly use noun phrase-based bundles, reflecting their critical role in sociology academic discourse. However, NNS exhibit a significantly higher usage of prepositional phrase-based bundles, indicating a strategy to enhance clarity and coherence. Functionally, while both groups rely heavily on research-oriented bundles, NNS employ text-oriented bundles more frequently, suggesting a heightened focus on ensuring textual coherence as a compensatory strategy for managing discourse. Conversely, NS more frequently use participant-oriented bundles, indicating greater rhetorical sophistication and personal engagement with the reader. The study contributes to linguistic theories by elucidating how lexical bundles function within the context of sociology and offering practical implications for English for Academic Purposes (EAP) instruction in sociology, emphasizing the need for targeted support in both the structural and functional aspects of lexical bundles and in improving academic writing skills.
Road Sense: Intelligent Road Monitoring System
Authors: Nimisha Naina , Pandey Subrat , Priyadarshi Siddhant , Preetham Dr. Anusha
Published: July 2024

Abstract: This project proposes a system for detecting traffic signals, lane layouts, and speed bumps in road infrastructure using video footage through machine learning. Lane detection is performed through region of interest selection and edge detection. Lane lines are extracted based on specific characteristics. A deep learning model is trained to detect lane boundaries and road curvature. The system provides real-time alerts and recommendations to enhance road safety and driving experiences.
Calculating the Volume of the Sediment Wedge in Retention Check Dams by Using Most Appropriate Models in Jammu and Kashmir\'s Budgam District
Authors: Pandit Dr. Bashir Ahmad
Published: July 2024

Abstract: Though their efficacy is currently under question, check dams are crucial for sediment retention globally. To estimate the retained sediment fast, readily, and with a suitable degree of approximation, 10 geometric models are proposed in this study together with their field technique and equations. The models were used to calculate the volume of trapped silt and compare them with other commonly used techniques on a sample of check dams in the Budgam district of Jammu and Kashmir based on the valley's form. Compared to topographic methods, our geometric method produced lesser volumes, but it produced larger volumes than basic methods. As a result, this approach minimizes fieldwork, computations, and expense when used as a preliminary approximation to estimate the sediment trapped by check dams and tiny silted dams. Additionally, compared to the outdated, basic procedures, it enables the selection of a higher precision and better match to the sediment wedge shape.
Intelligent Farming Systems in Future Using Machine Learning: A Focus on India
Authors: Pradhan Kajal Saran
Published: July 2024

Abstract: The integration of machine learning (ML) into Indian agriculture holds transformative potential for addressing critical challenges such as climate variability, water scarcity, soil degradation, and market fluctuations. This paper explores the current state of ML applications in Indian agriculture, highlighting successful case studies and initiatives led by government, private sector, and academic institutions. It discusses the technological integration of ML with the Internet of Things (IoT), remote sensing, and blockchain to enhance precision farming practices. Key barriers to widespread adoption, including data quality, infrastructure, and farmer awareness, are identified, along with strategies to overcome them. Future directions emphasize the importance of robust data infrastructure, localized ML models, collaborative research, sustainable practices, and supportive policy frameworks. By leveraging ML, Indian agriculture can achieve significant improvements in productivity, sustainability, and profitability.
Harvesting Knowledge: Data Science and Machine Learning Techniques for Evaluating Pesticide Impact in Vegetable Organic Farming
Authors: Chavan Aditi
Published: July 2024

Abstract: The integration of data science and machine learning is revolutionizing the assessment of pesticide impact in organic vegetable farming. This review explores methodologies, applications, and research examples showcasing the transformative potential of data-driven approaches. Remote sensing, including satellite imagery and drones, is essential for monitoring crop health and detecting pesticide impacts on vegetable crops like tomatoes, lettuce, and red peppers. By synthesizing research and trends, the review underscores technology's significance in informed decision-making for sustainable vegetable organic farming practices. Spectral analysis and vegetation indices quantify changes in crop health, informing pesticide efficacy and environmental impact. Sensor networks and IoT devices allow real-time monitoring of environmental conditions and pesticide dynamics, optimizing application practices to minimize contamination while maximizing yield. Machine learning, particularly decision tree-based models like random forests, predicts and mitigates pesticide impacts by analyzing complex datasets. Incorporating variables such as soil type and climate, these models accurately forecast pesticide fate, aiding in targeted mitigation strategies. Deep learning, such as convolutional neural networks (CNNs), identifies pesticide stress symptoms from digital images of vegetable leaves, facilitating rapid intervention. Challenges like data integration and model interpretability persist, yet ongoing research addresses these through data fusion and explainable AI. This review emphasizes the progress in leveraging data science and machine learning for pesticide impact evaluation in organic vegetable farming. By synthesizing research and trends, it offers insights for future sustainable agriculture applications.
Review Paper on Diffierent Types of Solar Dryer
Authors: Gautam Jitendra Kumar , Verma Pankaj
Published: July 2024

Abstract: One of the most appealing and economical uses of solar energy is drying agricultural goods. With differing degrees of technical performance, a multitude of solar dryer types have been devised and developed across the globe. In general, solar dryers come in four different varieties: (1) direct solar dryers, (2) indirect solar dryers, (3) mixed-mode dryers, and (4) hybrid solar dryers. The product being dried, as well as technical and financial concerns, are reviewed in this paper together with other solar dryer kinds. Technically speaking, integrated storage, high efficiency, compact collector design, and long-life drying systems are the main focuses in the development of solar-assisted drying systems for vegetables. There exist alternative systems to air-based solar collectors. By using a water-to-air heat exchanger, water-based collectors are another option. A water-to-air heat exchanger can be used to push hot air used for drying agricultural products to pass through it. As part of the solar drying system, the hot water tank stores heat
A Study on Cashless Payments in Retail Businesses in Rural Areas of Kurnool District of Andhra Pradesh
Authors: Ramanjaneyulu Dr. Kamma , Rachapudi Ravi
Published: July 2024

Abstract: In India post demonetization, cashless transactions have emerged as a significant trend in the Indian economy. They are touted for their convenience, simplicity, and enhanced safety compared to cash transactions. This shift is notably affecting the spending habits of rural residents in Kurnool district, Andhra Pradesh. The purpose of this article is to explore rural attitudes towards cashless transactions. A study conducted among 100 respondents revealed that 65% of rural residents engage in cashless transactions, particularly those with higher education levels. However, 35% of respondents still do not use cashless methods. These findings underscore the need for education and awareness programs aimed at rural communities to promote cashless transactions. Such initiatives could play a crucial role in fostering economic development and transforming spending patterns in these areas.
The relationship between psychological capital and career commitment in teachers
Authors: Awaliah Rizka , Ingarianti Tri Muji
Published: July 2024

When teachers have a high level of psychological capital, it can motivate them to be more proactive, exhibit higher confidence, and achieve better performance. This positive impact, in turn, can lead to strong commitment to their work, career, and the organization they belong to, resulting in the formation of high-quality teaching staff. This research aims to examine the relationship between psychological capital and career commitment among teachers. The participants in this study were 336 teachers. The research utilized a quantitative research model with a correlational method employing the simple linear regression assumption test. The instruments used in this study were the Psychological Capital Questionnaire (PCQ) and Career Commitment Measure (CCM). The results of this study indicate a correlation between two psychological capital dimensions (efficacy and optimism) and three dimensions of career commitment. There is also a relationship between the hope dimension and the identity dimension of career commitment, while the other two dimensions do not have a connection with career commitment dimensions. Additionally, the resilience dimension is also associated with career planning.
Supportive Community of Elementary School Children’s for Sports and Physical Activity
Authors: Bilagi Jayaprakash
Published: July 2024

The adults can supportive community and physical challenge by providing fun physical challenges that are appropriate for children's abilities, by giving children choices over how they move and play, and by providing opportunities for children to practice self-regulation through physical games an education that is organized with the aim of facilitating the growth and development of children as a whole that emphasizes the development of all aspects of the child's personality. Involve your child in physical activities around the home such as gardening, washing the car or house cleaning. Walk is the short distances instead of taking the car. Encourage and support walking and cycling to school. Take your child for regular walks around the neighborhood. Every child has a number of potentials, whether physical, biological, cognitive, or emotionally social (Desmita, 2009). Early childhood education should provide various activities that can develop various aspects of development including cognitive, language, social, and emotional aspects for development and socialization in children become a very important part in shaping behavior in children. One form of game that can be used to improve the social and emotional skill of early childhood is the traditional game. Students Behaviors that represent children's emotional growth and their ability to successfully navigate their world through interactions with adults and parents since these skills are develop together, this area of development is referred to as social-emotional development. We analyze the mechanics in these games and compare these mechanics against existing videogames to show what makes traditional games unique. Our student’s analysis has helped us to interpret the playability issues that we can observed in our exploratory studies, and informed the design of a new videogame that rural children found to be more intuitive and engaging.
Husband's Rejection To Children's Lineage After Divorce
Authors: Hanapi Agustin , Achyar Gamal , Zulhamidi Nur Nadhila Syafini Binti
Published: July 2024

The religious scholars have different opinions in determining the maximum period of pregnancy for a woman. Fiqh scholars stated that lineage is one of the strong foundations in building a family life that can bind a person's personality based on blood unity. Islam has laid down guidelines in terms of the conviction of lineage according to Shariah law. This research uses a type of normative research, namely the approach of legal principles, legal theory, court decisions and uses the case approach method. The results of the research show that the husband's rejection of the child's lineage after divorce can be considered by the judge in convicting the child's lineage by examining all aspects and evidence of statements whether oral or written so that it is in line with syariah law and the Islamic Family Law (Kedah). As for if a pillar and condition of marriage is not fulfilled in line with the Sharia, then a wording of the marriage contract is invalid so that it can make the marriage broken (fasid) or the occurrence of dubious intercourse. In line with that, then the status of a child will be doubted by the parties about the legitimacy of his lineage.
Irritation Test and Effectiveness of Facial Humidity Skin from Peel Off Gel Mask Based of Date Palm Seeds Powder (Phoenix dactylifera)
Authors: Lestari Uce , Farid Faizar , Yuliawati Yuliawati , Pratama Septa
Published: July 2024

Dry skin is the main problem of skin damage such as scaly, peeling, cracked and itchy skin, this is because the skin loses fluids due to weather changes and as we age we experience a decrease in the amount of oil and water on the skin. Facial skin care is done, one of which is by using a peel off gel mask of dates palm powder. The fat content is useful as a facial skin moisturizer. This study aims to determine the formula of the peel off gel mask which has determine its safety and effectiveness in moisturizing facial skin. The peel off gel mask was made into 3 formulas with the concentration of date palm seeds powder 1% (FI), 2% (FII) and 3% (FIII). Â Procedures in this study include irritation test, hedonic test and facial skin moisture test using a skin analyzer compared before and after use. Peel off gel mask choco milk as a positive control. The results showed that FII ( 2%) corresponding the requirements of no irritation occurs compared to other formulas. Testing the effectiveness of facial skin moisture showed that FII (2%) was able to increase the water content after use and the water content was higher than the positive control. Results it can be concluded that the FII has safe for use and effective in moisturizing facial skin.
Sanitary Hygiene and Analysis of Escherichia Coli Bacteria Content in Lalapan Kol at Pecel Lele Trader
Authors: Safitri Anita , Novita Lidya
Published: July 2024

The presence of Eschericia coli (E.Coli) bacteria is one indicator of food contamination that can cause food-borne diseases. Fresh vegetables have nutritional advantages because they are consumed raw so that the nutrients contained in them are not denatured or changed. Types of vegetables that are usually consumed fresh have the potential to be detrimental to health because they are susceptible to microbial contamination. This study aims to review the sanitation hygiene of traders and determine the content of E.Coli bacteria in cabbage vegetables from fried catfish traders in one of the sub-districts in the city of Pekanbaru. The type of research used is survey and laboratory analysis. Technique sampling in this study is total sampling technique with a sample of 10 fried catfish traders. The results showed that hygiene and sanitation were still low in all traders. All traders do not use running water for washing vegetables and cutlery, and vegetables are not stored in closed containers. The results of bacterial analysis, it was found that 6 samples of fresh vegetables cabbage fried catfish contained E.Coli and the rest did not contain E.Coli bacteria. It can be concluded that the application of food sanitation hygiene by food handlers at several fried catfish traders in Pekanbaru City is in the poor category, because from 10 samples of cabbage vegetables, E.coli was found in 6 samples of cabbage vegetables.
Toxicity Test of Inggu (Ruta angustifolia (L)) Ethanol Leaves Extract to Male White Mice (Mus musculus)
Authors: Hidayat Vikri , Elisma Elisma , Lestari Intan
Published: July 2024

Inggu leaf (Ruta angustifolia (L.) is one of the medicinal plants that is widely used by Indonesian people as traditional medicine for various diseases. One of the properties of the inggu plant can be used to treat fever, toothache, heartburn and ulcers. Toxicity testing ethanol extract of guinea leaf using a completely randomized design (CRD) with 7 treatments with stratified doses of 500, 1000, 2000, 4000, 8000, 16,000 mg/kg BW and control. Parameters observed after administration of the extract were diarrhea, changes in breathing, changes in aggressive behavior and decreased movement activity. Liver and kidney organs were taken to determine the organ weight ratio. The results showed that the ethanol extract of inggu leaves with graded doses up to a dose of 16,000 mg/kg BW in experimental animals did not cause death, which was included in the practically non-toxic category. Administration of ethanol extract of guinea leaves at a dose of 500 mg/kg BW to 16,000 mg/kg BW caused a decrease in locomotion activity in experimental animals during the 4-hour observation time. The ratio of organ weight of mice from the test results of the ratio of liver, right kidney and left kidney of mice was not different from that of control animals.
The Effect of Starch Concentration on the Characteristics of Modified Purple Yam Starch Using the Precipitation Method
Authors: Parera Yogi , Ulyarti Ulyarti , Gusriani Ika
Published: July 2024

Purple yam starch-based edible film experienced high water vapor transmission rate. The use of composite starch using addition of modified starch of smaller size particles may decrease the rate. This study aimed to obtain starch concentrations that produced smallest size of modified starch, to produce composite starch for edible films and to determine the characteristics of edible films made out of native starch and edible films from composite starch (mixture of native starch and modified starch with the smallest size). This research was conducted in 2 stages: modification of purple yam starch by precipitation method and production of edible films from native starch and composite starch. This study was designed to produce modified starch using 5 levels of starch concentration (0,2%, 0,4%, 0,6%, 0,8%, and 1%) and 2 repetitions. The results showed that the treatment of 0,8% starch concentration produced the smallest particle size of starch (3,211 x 10,340 Âµm) up to (20,876 x 25,437 Âµm) with starch yield of 76,25%. Edible films made out composite starch have different characteristics than native starch alone. Edible films from composite starch produced higher thickness values â€‹â€‹of 0.161 Â± 0.007 mm, lower solubility 32,080 Â± 4,671%, lower transparency of 10.644 Â± 0.357% / mm and lower water vapor transmission rate (WVTR) of 24,701 Â± 7,05 g / m2. hour and higher compressive strength 356,87 Â± 7,38 gF than native starch edible films.
PENGARUH KEDALAMAN TERHADAP PERKEMBANGAN RUMPUT LAUT KOTONI (Kappaphycus alvarezii) HASIL KULTUR JARINGAN
Authors: Runtuboy Nico , Riyadi Slamet
Published: July 2024

Penelitian ini bertujuan untuk mengetahui  kedalaman terbaik terhadap perkembangan bibit rumput laut hasil kultur jaringan. Uji coba dilakukan selama VI minggu dengan menggunakan berat awal bibit yang sama yaitu 75 gram pada 3 tingkatan kedalaman perairan berbeda : 10 cm, 30 dan 50 cm. Parameter yang diamati meliputi, perkembangan tanaman, dan sintasan. Hasil pengamatan perkembangan tanaman pada kedalaman 10 cm dari minggu pertama sampai minggu ke VI berat awal 75 gr, 115,80 gr, 157,40 gr, 216,00 gr,303,00 gr, 341,00 gr dan 375,00 gr. Kedalaman 30 cm berat awal 75 gr, 118,60 gr,139,80 gr, 199,00 gr, 254 gr 293 gr dan 304 gr. Kadalaman 50 cm : berat awal 75 gr, 96,6 gr, 122,4 gr, 159 gr,207 gr, 250 gr dan 260,8 gr. Sintasan (SR) pada kedalaman 10 cm dari minggu pertama hingga minggu keempat 100 % dan pada minggu ke lima dan keenam masing-masing 98 %. SR pada kedalaman 30 cm dari minggu pertama hingga keempat 100 % dan minggu kelima dan keenam 96 %. Dan SR pada kedalaman 50 cm dari minggu pertama hingga minggu ke empat 100 % dan pada minggu ke lima 94 % dan 92 %. Berdasarkan hasil perhitungan, perkembangan tanaman pada kadalaman 10 sampai 30 cm, relatif sama dan memberikan hasil lebih baik dibanding  pada kedalaman 50 cm.  Hal ini berarti dalam melakukan kegiatan produksi dapat melakukan penanaman pada kedalaman antara 10 hingga 30 cm.
DETEKSI KRISTAL PROTEIN PADA ISOLAT BACILLUS SP. DENGAN PEWARNAAN COOMASSIE BRILLIANT BLUE
Authors: Siallagan Maria Denada , Ekowati Christina Nugroho , Sumardi Sumardi , Rosa Emantis
Published: July 2024

Bacillus merupakan salah satu marga bakteri yang memiliki potensi untuk dikembangkan dalam bidang bioteknologi. Bacillus mampu menghasilkan kristal protein selama fase stasioner dalam siklus hidupnya. Kristal protein ini merupakan protoksin yang dalam keadaan aktif akan bersifat patogenik pada serangga. Pada penelitian ini, dilakukan pewarnaan kristal protein menggunakan pewarna coomassie brilliant blue pada isolat Bacillus sp. dengan kode isolat B1, B2, dan B3. Ketiga isolat tersebut dibiakkan pada media Nutrient Broth (NB) dengan pH 5, pH 7, dan pH 9, selama 72 jam. Hasil penelitian menunjukkan ketiga isolat tersebut terdeteksi meghasilkan kristal protein. Kristal protein isolat Bacillus sp. pada media dengan pH 5 dan pH 7 terletak di bagian ujung spora, sementara kristal protein isolat Bacillus sp. pada media dengan pH 9 terletak pada bagian luar spora.
Hungary’s AI Strategy: Lessons for Indonesia’s AI Legal Framework Enhancement
Authors: Saputra Beny , Hartati Hartati , Bene Olivér
Published: July 2024

This study analyses Hungary's approach to regulating artificial intelligence (AI) by analyzing their AI Strategy (2020-2030) and provides insights for improving Indonesia's legal framework. In Hungary, although there is no dedicated legislation for artificial intelligence (AI), the country places a high importance on adhering to current regulations to regulate AI technologies. This paper does a comparative analysis to evaluate the influence of Hungary's approach on the advancement of artificial intelligence (AI), the methods used to enforce regulations, the ethical principles followed, the safeguarding of data, and the extent of international partnerships. This research seeks to offer practical insights for enhancing Indonesia's legal infrastructure in the field of AI governance and technology regulation by comparing Hungary's regulatory landscape with Indonesia's current framework. The purpose of the research is to provide guidance to policymakers and stakeholders in Indonesia regarding effective tactics and best practices based on Hungary's experience. This will assist in enhancing Indonesia's regulatory framework for AI and technology
ANHA DOTHRAK CHEK ASSHEKH: THE RENDERING OPERATION OF THE INVENTED LANGUAGE DOTHRAKI INTO BAHASA INDONESIA IN GAME OF THRONES SEASON 6
Authors: Isnaini Anisa Wahyu
Published: July 2024

This research is conducted to observe the rendering operation of L3 translation applied of Game of Thrones series Season 6, specifically focusing on two objectives: identifying the types of rendering operations used and explaining why these operations are chosen. The research adopts a descriptive qualitative approach. Corrius and Zabalbeascoa's theory on L3 translation rendering operations serves as the framework for addressing the research questions. Data analysis employs Spradley’s componential analysis method, and the researcher verified the findings with an expert. The study identified 175 instances of Dothraki language in Game of Thrones Season 6, leading to the discovery of three distinct types of L3 translation rendering operations. There are 6 Delete L3ST (3,5%) in which the L3 in ST is omitted in TT, 16 Substitute L3ST → L2 (9,1%), which is divided into 2 conditions. There are condensation and inappropriate translation. The last is 153 Substitute L3ST (87,4%) which is divided into two conditions, defining the plot and emphasizing the characters, identity and story. The data shows that the most dominant rendering operation of L3 translation applied by the subtitler is Substitute L3ST because it is considered to be the most suitable operation that can be used as a solution in translating invented language. It is also because the subtitler accurately translated the third language into the target language, as evidenced by the consistency with the dictionary, dialogues, and scene narratives. The second finding of this research shows that there are 2 kinds of nature and degree of L3 presence. In this research, the researcher found 22 data (12,6%) of Lost which is divided into 6 causes, i.e: lack of duration, no full translation, accidental error, incorrect translation, unnecessary scene and unclear words. Also 153 data (87,4%) of Kept which is divided into 4 conditions; to define Khaleesi, define Dothraki, define Game of Thrones and define the context of the story. This means that the subtitler still wants to retain the meaning and the style of the third language.
THE INTERTEXTUALITY OF CULTURAL REPRESENTATIONS AS SEEN FROM SPIDERMAN ACROSS THE SPIDER-VERSE (2023) AND MS MARVEL (2022)
Authors: Sekarini Siska Ayu Diaz , Khadija Albar Hanafi  , Isna Shofiyani Fathoni
Published: July 2024

This study aims to reveal the intertextual of cultural diversity of Spiderman Across the Spider-Verse (2023) and Ms. Marvel (2022). This study focuses on Spiderman characters: Miles Morales and Pavitr Prabhakar and also Ms. Marvel named Kamala in Ms. Marvel, social life and their surroundings. This study uses the theory from Kristeva (1989) to examine the intertextuality between the two films and representative theory from Stuart Hall(1997) to analyze the cultural representation of Spiderman Miles Morales, Spiderman Pavitr Prabhakar, and Kamala Khan. The researchers used qualitative research methods. Research results show that cultural representation in movies appears beyond superficial markers, incorporating meaning, signs and symbols that are relevant to the characters' backgrounds in society. Both films depict elements such as food, stereotypes, and religious norms that represent a specific culture or religion. However, both films clearly reflect traditional fashion symbols, musical instruments, language, traditions, decorations, and religious rituals. This intertextual exploration enriches the story and offers a more inclusive depiction of superheroes in a globalized worldThis study is expected to provide insightful and nuanced understandings of cultural representation in this modern era of globalization through the eyes of Spiderman Across the Spider-Verse (2023) and Ms. Marvel (2022).
Audit committee ownership, firm size, and audit delay: Empirical evidence from Indonesia
Authors: Wibowo Raden Arief , Barros Agapito
Published: July 2024

Research on audit committee ownership is still very limited, making it highly worthy of further investigation. Investors and regulators acknowledge the significance of having audited financial information that is released in a timely manner. Audit delay conducted by the auditor creates high information uncertainty for investors. This study aims to analyze the effect of audit committee ownership and firm size on audit delay mediated by the quality of financial reporting with a sample of 75 non-financial companies listed on the IDX in 2016-2020 with the sampling technique used is purposive sampling. This study uses path analysis with Eviews software version 9. The results of this study indicate that company share ownership and Firm Size have no effect on audit delay, financial reporting quality does not mediate the effect of company share ownership on audit delay, while financial reporting quality mediates the effect of size company against audit delay. This research contributes theoretically by enriching the literature on audit committee ownership.
Cybersocialism and the Future of the Socialist Calculation Debate
Authors: Dapprich Jan Philipp , Greenwood Dan
Published: July 2024

In the long running debate about the desirability and feasibility of a planned socialist economy, Austrian economists proclaim victory. Drawing from Mises and Hayek, they stress that the problem of deciding the most economic methods for producing goods and services is not simply, as some early socialist responses suggested, a ‘computational’ one but is rather epistemological. Hence, they reject recent ‘cybersocialist’ claims that developments in computational technology offer potential for addressing the ‘socialist calculation problem’ famously formulated by Mises, long before the advent of computer technology. Yet this theoretical claim by Austrians hinges more than is recognised upon the capacity of rapidly evolving computational technologies and their potential applications. We highlight the need to re-appraise Austrian conclusions, attending closely to the distinction offered by Mises between supply and demand-side calculation. Recent cybersocialist proposals should be viewed as opening up several different avenues of research relating to different aspects of the long-running socialist calculation debate, including the inter-relationships between economic calculation, incentives and innovation.