bluuebunny/crossref_metadata_2025 huggingface dataset:
A RETROSPECTIVE STUDY OF INCIDENCE OF TEENAGE PREGNANCY IN TERTIARY CARE CENTER-MATERNAL AND FETAL OUTCOME
Authors: Umadevi P.S , Padmaja P. , Bindu C.
Published: March 2024

Teenage pregnancy is becoming a high risk to the health of mother and child due to its adverse outcomes to both mother and the child.it is common health problem around the world. It is one of the key issues concerning to the reproductive health of women not just in developing countries but also in developed countries. Pregnancy among teenagers is considered high risk due to its high incidence of adverse outcomes like LBW, prematurity, neonatal asphyxia, sepsis, jaundice, mortality, maternal anemia, preeclampsia(PE) , maternal mortality, etc. purpose of this article is to known the incidence of teenage pregnancy in tertiary care center, maternal and fetal outcome by which we can give awareness to public regarding the outcome come of teenage pregnancy, improve reproductive results , decrease the teenage pregnancy by ensuring female education, and enforcing marriage law.
The role of digital technologies in higher education institutions: The case of Kazakhstan
Authors: Nurtayeva Dana , Kredina Anna , Kireyeva Anel , Satybaldin Azimkhan , Ainakul Nazym
Published: March 2024

The ways of education development are changing, which is largely determined by the introduction of digital technologies and the desire to improve the efficiency of management of educational processes at universities. Therefore, this study aimed to identify the challenges and opportunities in universities related to the use of digital technologies (social media tools, digital online platforms, digital learning platforms) in higher education institutions in Kazakhstan. A sample included respondents (N = 69) from 16 educational institutions in Kazakhstan that combined teaching (conducting training courses or working with students) and administrative management (management or planning of the educational process). The data were obtained using an offline questionnaire and processed using SWOT methodology. Representatives from 16 public and private universities responded to the questionnaire: the rector (2%) and two vice-rectors (3%), deans of faculties (23%), directors, and heads of various departments of universities (71%) were interviewed (managers are engaged in teaching). As a result, six thematic outcomes demonstrated the opportunities for technology application in education: enhancing management quality, motivation, access to electronic resources and materials, transparency and objectivity in grading, the possibility of implementing distance learning, and simplification of routine tasks. It is also noteworthy to mention five thematic outcomes as challenges, which encompassed issues with security, technical errors, reduced communication, dependency, and complexities in grading.
AcknowledgmentsThe study was carried out within the framework of grant funding by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan “Modernization of the system of distribution relations and reduction of income inequality of the population of the Republic of Kazakhstan” BR21882165.
Temporal and spatial satellite data augmentation for deep learning-based rainfall nowcasting
Authors: Baydaroğlu Özlem , Demir Ibrahim
Published: March 2024

The significance of improving rainfall prediction methods has escalated due to climate change-induced flash floods and severe flooding. In this study, rainfall nowcasting has been studied utilizing NASA Giovanni satellite-derived precipitation products and the convolutional long short-term memory (ConvLSTM) approach. The goal of the study is to assess the impact of data augmentation on flood nowcasting. Due to data requirements of deep learning-based prediction methods, data augmentation is performed using eight different interpolation techniques. Spatial, temporal, and spatio-temporal interpolated rainfall data are used to conduct a comparative analysis of the results obtained through nowcasting rainfall. This research examines two catastrophic floods that transpired in Türkiye Marmara Region in 2009 and the Central Black Sea Region in 2021, which are selected as the focal case studies. The Marmara and Black Sea regions are prone to frequent flooding, which, due to the dense population, has devastating consequences. Furthermore, these regions exhibit distinct topographical characteristics and precipitation patterns, and the frontal systems that impact them are also dissimilar. The nowcast results for the two regions exhibit a significant difference. Although data augmentation significantly reduced the error values by 59% for one region, it did not yield the same effectiveness for the other region.
Anxiety and diet among elderly people suffering from diabetes mellitus in Banda Aceh, Indonesia: A correlational study
Authors:   Department Geriatric of Nursing, Faculty of Nursing, Universitas Syiah Kuala, Banda Aceh, Indonesia, Nurhasanah Nurhasanah , Juanita Juanita ,   Department Geriatric of Nursing, Faculty of Nursing, Universitas Syiah Kuala, Banda Aceh, Indonesia, Putra Ardia ,   Department Fundamental and Management of Nursing, Faculty of Nursing, Universitas Syiah Kuala, Banda Aceh, Indonesia
Published: March 2024

Successfully managing diabetes over a long period is challenging and requires close monitoring of one’s diet and lifestyle. However, mental health issues such as anxiety can make it difficult to manage diabetes effectively, especially in older people. This study aims to highlight the psychological challenges older people with diabetes face, emphasizing the importance of mental health in managing chronic illnesses. It explores how anxiety affects the eating habits of older individuals with diabetes. The study used a quantitative method and a descriptive correlational research design. It involved older people with diabetes mellitus, with about 300 participants selected through purposive sampling based on certain criteria. The study measured anxiety levels using the GAS questionnaire, which is highly reliable (0.93), and dietary patterns were assessed with the UK-DDQ, which has a reliability of 0.765. The findings show that most participants were female (62%), in their early elderly years (89.7%), and had finished high school (67.7%). Regarding income, 39.3% earned less than Rp. 1,500,000. Over half lived with a partner (51%) and felt sadness and depression (64%). A minority had no family history of diabetes (38.3%), and most were cared for by their children (54.3%). Most participants had been living with diabetes for 2-5 years (54.1%) and did not smoke (85%). In terms of treatment, the majority used metformin (73.7%), and just over half did not use traditional medicine (51.3%). The study found a significant link between anxiety and diet in older adults with diabetes mellitus, with a p-value of 0.006 (alpha = 0.05). It suggests that healthcare providers should consider the whole well-being of older adults with diabetes, recognizing that anxiety can hinder their ability to follow a diet plan. Therefore, it is crucial to understand a patient’s mental, emotional, and physical health for effective treatment.
Blood storage impacts on the hematological indices of healthy subjects and patients with iron-deficiency anemia and beta-thalassemia – A comparative study
Authors: M. Saeed Mudhafar Mohamed
Published: March 2024

Background: There are scientific evidence confirmed specific changes in blood cell counts, reducing the efficacy and feasibly the safeness of blood transmission when storing blood at 4°C for 5 weeks or more.Objectives: The study aimed to investigate the effects of stored blood obtained from healthy subjects and patients with anemia due to iron deficiency and beta-thalassemia, on hematological indices.Materials and Methods: A total of 37 participants, consisting of 14 healthy subjects, 13 patients with iron-deficiency anemia, and 10 patients with beta-thalassemia minor, were recruited from Hiwa Hospital between November 2021 and July 2022. Blood samples were obtained from the participants and stored at 4°C for 5 weeks. Hematological indices, including red cell distribution, platelet distribution width, and mean platelet volume, were determined using a hematology analyzer at weekly intervals.Results: Blood storage caused significantly increased mean values of hematological indices among healthy subjects as well as among patients with iron-deficiency anemia and beta-thalassemia, although the pattern of changes was differed.Conclusions: The storage of whole blood significantly increased hematological indices, showing variations in both healthy subjects and patients with iron-deficiency anemia and beta-thalassemia. The pattern of raise in these hematological indices is specific to iron-deficiency anemia and thalassemia when compared with healthy subjects.
Implementable Prediction of Pressure Injuries in Hospitalized Adults: Model Development and Validation
Authors: Reese Thomas J , Domenico Henry J , Hernandez Antonio , Byrne Daniel W , Moore Ryan P , Williams Jessica B , Douthit Brian J , Russo Elise , McCoy Allison B , Ivory Catherine H , Steitz Bryan D , Wright Adam
Published: March 2024

Background

Numerous pressure injury prediction models have been developed using electronic health record data, yet hospital-acquired pressure injuries (HAPIs) are increasing, which demonstrates the critical challenge of implementing these models in routine care.

Objective

To help bridge the gap between development and implementation, we sought to create a model that was feasible, broadly applicable, dynamic, actionable, and rigorously validated and then compare its performance to usual care (ie, the Braden scale).

Methods

We extracted electronic health record data from 197,991 adult hospital admissions with 51 candidate features. For risk prediction and feature selection, we used logistic regression with a least absolute shrinkage and selection operator (LASSO) approach. To compare the model with usual care, we used the area under the receiver operating curve (AUC), Brier score, slope, intercept, and integrated calibration index. The model was validated using a temporally staggered cohort.

Results

A total of 5458 HAPIs were identified between January 2018 and July 2022. We determined 22 features were necessary to achieve a parsimonious and highly accurate model. The top 5 features included tracheostomy, edema, central line, first albumin measure, and age. Our model achieved higher discrimination than the Braden scale (AUC 0.897, 95% CI 0.893-0.901 vs AUC 0.798, 95% CI 0.791-0.803).

Conclusions

We developed and validated an accurate prediction model for HAPIs that surpassed the standard-of-care risk assessment and fulfilled necessary elements for implementation. Future work includes a pragmatic randomized trial to assess whether our model improves patient outcomes.
Privacy Barriers in Health Monitoring: Scoping Review
Authors: Sun Luyi , Yang Bian , Kindt Els , Chu Jingyi
Published: March 2024

Background

Health monitoring technologies help patients and older adults live better and stay longer in their own homes. However, there are many factors influencing their adoption of these technologies. Privacy is one of them.

Objective

The aim of this study was to provide an overview of the privacy barriers in health monitoring from current research, analyze the factors that influence patients to adopt assisted living technologies, provide a social psychological explanation, and propose suggestions for mitigating these barriers in future research.

Methods

A scoping review was conducted, and web-based literature databases were searched for published studies to explore the available research on privacy barriers in a health monitoring environment.

Results

In total, 65 articles met the inclusion criteria and were selected and analyzed. Contradictory findings and results were found in some of the included articles. We analyzed the contradictory findings and provided possible explanations for current barriers, such as demographic differences, information asymmetry, researchers’ conceptual confusion, inducible experiment design and its psychological impacts on participants, researchers’ confirmation bias, and a lack of distinction among different user roles. We found that few exploratory studies have been conducted so far to collect privacy-related legal norms in a health monitoring environment. Four research questions related to privacy barriers were raised, and an attempt was made to provide answers.

Conclusions

This review highlights the problems of some research, summarizes patients’ privacy concerns and legal concerns from the studies conducted, and lists the factors that should be considered when gathering and analyzing people’s privacy attitudes.
Predictive Data Analytics in Telecare and Telehealth: Systematic Scoping Review (Preprint)
Authors: Anderson Euan , Lennon Marilyn , Kavanagh Kimberley , Weir Natalie , Kernaghan David , Roper Marc , Dunlop Emma , Lapp Linda
Published: March 2024

BACKGROUND

Telecare and telehealth are important care-at-home services used to support individuals to live more independently at home. Historically, these technologies have reactively responded to issues. However, there has been a recent drive to make better use of the data from these services to facilitate more proactive and predictive care.

OBJECTIVE

This review seeks to explore the ways in which predictive data analytics techniques have been applied in telecare and telehealth in at-home settings.

METHODS

The PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklist was adhered to alongside Arksey and O’Malley’s methodological framework. English language papers published in MEDLINE, Embase, and Social Science Premium Collection between 2012 and 2022 were considered and results were screened against inclusion or exclusion criteria.

RESULTS

In total, 86 papers were included in this review. The types of analytics featuring in this review can be categorized as anomaly detection (n=21), diagnosis (n=32), prediction (n=22), and activity recognition (n=11). The most common health conditions represented were Parkinson disease (n=12) and cardiovascular conditions (n=11). The main findings include: a lack of use of routinely collected data; a dominance of diagnostic tools; and barriers and opportunities that exist, such as including patient-reported outcomes, for future predictive analytics in telecare and telehealth.

CONCLUSIONS

All papers in this review were small-scale pilots and, as such, future research should seek to apply these predictive techniques into larger trials. Additionally, further integration of routinely collected care data and patient-reported outcomes into predictive models in telecare and telehealth offer significant opportunities to improve the analytics being performed and should be explored further. Data sets used must be of suitable size and diversity, ensuring that models are generalizable to a wider population and can be appropriately trained, validated, and tested.
Ensemble Method for Anomaly Detection On the Internet of Things
Authors: Kurniabudi Kurniabudi , Winanto Eko Arip , Astri Lola Yorita , Sharipuddin Sharipuddin
Published: March 2024

The internet of things generates various types of data traffic with a very large amount of data traffic which has an impact on security issues, one of which is an attack on the Internet of Things network. In the IoT data traffic flow, which contains various data, it turns out that the portion of attack data traffic is usually smaller than normal traffic. Therefore, the attack detection method must be able to recognize the type of attack on a very large data traffic flow and unbalanced data. High data dimensions and unbalanced data are one of the challenges in detecting attacks. To overcome the large data dimensions, Chi-square was chosen as a feature selection technique. In this study, the ensemble method is proposed to improve the ability to detect anomalies in unbalanced data. To produce an ideal detection method, a combination of several classification algorithms such as Bayes Network, Naive Bayes, REPtree and J48 is used. The CICIDS-2017 dataset is used as experimental data because it has a high data dimension which contains unbalanced data. The test results show that the proposed Ensemble method can improve the performance of anomaly detection for high-dimensional data containing unbalanced data
Comparison of lexical‐semantic processing in children with developmental language disorder and typically developing peers
Authors:   Faculty of Special Education and Rehabilitation University of Belgrade, Drljen Bojana , Vuković Mile ,   Faculty of Special Education and Rehabilitation University of Belgrade
Published: March 2024

Recent studies indicate that lexical and semantic deficits in children with developmental language disorder (DLD) are not caused only by reduced vocabulary and retrieval difficulties but also by sparse lexical-semantic network and deficits in semantic organization. This paper investigates qualitative differences in the lexical processing between children with DLD and typically developing peers, as well as developmental trends in the lexical-semantic processing in preschool and early school-age children with DLD. The sample consisted of 115 participants (5–8 yr.), 60 children with DLD and 55 typically developing (TD) children. The sample was also divided in two age groups, preschool (5 and 6 yr.) and school-aged groups (7 and 8 yr.). Word association task was used for the assessment of lexical-semantic processing. The responses were coded either as mature associations (paradigmatic and syntagmatic), immature associations (phonological, unrelated and echolalic) or omissions. The results show that DLD children have significantly less mature associations and more immature associations. Also, the performance of children with DLD was significantly poorer at early school age compared to their TD peers. Sparse lexical-semantic network and deficits of semantic organization in DLD children are caused by poor semantic fields and semantic categories, as well as difficulties in the activation of lexicon. However, developmental trends analysis showed that DLD children, although significantly delayed in lexical processing, have similar developmental pattern like TD children.
Od fonemske raščlambe i stapanja do premetanja – nedostaci u fonološkoj svjesnosti u djece s poremećajem čitanja u hrvatskome
Authors:   The SUVAG Polyclinic, Zagreb, Kelić Maja
Published: March 2024

Fonološka svjesnost podupire ovladavanje čitanjem, a nedostaci u fonološkoj svjesnosti smatraju se jednim od osnovnih pokazatelja poremećaja čitanja. Povezanost fonološke svjesnosti i vještine čitanja razlikuje se u različitim ortografijama. Cilj je ovog istraživanja bio usporediti čitatelje s poremećajem čitanja i njihove vršnjake urednog razvoja u različitim zadacima fonološke svjesnosti te provjeriti koliko uspješno ovi zadaci razlikuju skupine; mjereći točnost, brzinu rješavanja zadatka te analizirajući uporabljene čestice. Dobiveni rezultati pokazuju da površinska ortografija hrvatskog podupire razvoj fonološke svjesnosti te su u većini zadataka obje skupine sudionika postigle visoku razinu točnosti. No, unatoč dosljednosti hrvatske ortografije, zadaci fonološke svjesnosti načelno uspješno razlikuju čitatelje s poremećajem čitanja i uredne čitatelje. Analiza čestica provedena u ovom istraživanju pokazuje da je neophodno uzeti u obzir posebnosti ortografije, fonološku duljinu i složenost čestica te čestotnost kako bi se povećala njihova osjetljivost u prepoznavanju čitatelja s poremećajem čitanja.
Socioretorička analiza: događaj križa kao temelj kršćanskog mirotvorstva
Authors:   Adriatic Union College, Maruševec, Pirija Darko
Published: March 2024

Ovim se radom propituje odnos retorike i etike u svjetlu zahtjeva Schüssler Fiorenze za potpunim etičkim i epistemološkim obratom u socioretoričkoj analizi biblijskog teksta. Epistemološka ograničenja, tvrdi ona, proizišla iz metodološkog sužanjstva u okvirima empirijskog, pozitivističkog pristupa znanstvenom istraživanju i sociopolitičkih interesa znanstvenika, priječe ostvarenje emancipacijske uloge retoričke znanosti i stoga je potrebno tragati za komplementarnim potencijalom retoričke teorije i prakse i duhovne vizije u metodološkom prostoru transformacijske hermeneutike i političke teologije. Svrha je pokazati kako se socioretorička analiza ne treba baviti samo raščlambom strukture teksta i propitivanjem njegova značenja, već i načinom na koji on djeluje i otvara prostor za nove mogućnosti javnog dijaloga te pomiče granice primjenjivosti znanstvenog diskursa u službi društvenog pomirenja i cjelovitijeg suživota. Polazišna točka za kritičko vrednovanje Schüssler Fiorenzina prijedloga je pretpostavka da funkcija znanstvenog diskursa treba biti i izrazito kritička, prosvjetiteljska i preobraziteljska, a oslanja se na uvide Eagletona (1990, 1996), Gadamera (2012), Volfa (1998) i Westa (1985). U konačnici, etičnost u retoričkom čitanju temeljnoga kršćanskog teksta koja poštuje njegovu izvornu cjelovitost može doprinijeti mirotvorstvu i politici nenasilja čije je konačno ishodište u eshatološkom činu novog stvaranja (Volf, 1998) samo ako je istovremeno ukorijenjeno u konkretnom povijesnom životu pojedinca i kršćanske zajednice.
Varicose Veins: A Review and Management
Authors: Ali Insaf , Srivastava Sanjay
Published: March 2024

Abstract: Twisted, swollen veins that are commonly found on the lower limbs can be deformative and incapacitating. Varicose vein prevalence varies. At least one-third of people are thought to have lower leg varicose veins. Family history, obesity, advanced age, pregnancy, and prolonged standing are risk factors. The pathogenesis includes weakening vascular walls, defective valves, and genetic factors. Treatment options for varicose veins include surgery, interventional therapy, and conservative measures like diet, lifestyle modifications, and hydrotherapy—all of which depend heavily on patient compliance to be effective. The symptoms, patient preferences, cost, and possible risks all influence the therapeutic selection. This review looks at varicose vein risk factors, symptoms, management (surgery and conservative measures), and complication avoidance
Web-Ecosystem for Students with Special Needs
Authors: Singh Udit , Pandey Priyesh , Chaubey Sahil , Kumar Abhishek , Wati Suresh
Published: March 2024

Abstract: India faces a significant challenges for student, children with disabilities in minor or major forms for any of the physical organs or mentally unstable children are considered to be specially-abled ones educational ecosystem, the needs of such an environment need to be catered according to the category of ailments that exist in the students and provisions need to be made in order to make them feel special, and cared for and set the right mindset while they grow. educational ecosystem, the needs of such an environment need to be catered according to the category of ailments that exist in the students. The aim of this problem statement solution is also to produce innovative solutions which may use digital and physical mediums together to make sure disabled persons are able to access and run these applications. Students with special needs often face various challenges in educational settings. It is important to recognize that these challenges can vary widely depending on the type and severity of the disability. A web ecosystem for students with special needs involves designing a platform that is inclusive, accessible, and tailored to meet the diverse needs of students with disabilities.
Inventory Optimization Using an AI-Powered Holistic Model for Decision-Support System
Authors: Choudhary Shailesh
Published: March 2024

Abstract: This study presents a groundbreaking approach to inventory optimization through the implementation of an AIpowered holistic model within a decision-support system. Leveraging machine learning algorithms, specifically Logistic Regression (LR) and Decision Trees, the methodology explores historical sales data, supplier metrics, and market trends during an extensive Exploratory Data Analysis phase. The implementation of an AI-powered holistic model for inventory optimization in a decision-support system presents a transformative approach to managing and enhancing supply chain efficiency. The proposed methodology, integrating machine learning algorithms such as Logistic Regression and Decision Trees, has demonstrated its efficacy in achieving superior results compared to traditional models, as evidenced by higher accuracy, precision, recall, and F1 scores. The comprehensive exploration of historical sales data, supplier metrics, and market trends during the exploratory data analysis phase has facilitated a nuanced understanding of inventory dynamics. The seamless integration of the AI-powered model into the decision-support system has empowered organizations with timely and data-driven insights, fostering more agile and informed decision-making. The seamless integration of the AI-powered model into the decision-support system provides organizations with timely and data-driven insights, fostering agile and informed decisionmaking. Performance evaluation, including accuracy, precision, recall, and F1 scores, reveals that the proposed LR and Decision Tree models outperform the existing Support Vector Machine (SVM) model across all metrics. The LR model exhibits commendable precision, recall, and F1 score values of 0.95, 0.97, and 0.98, respectively, while the Decision Tree model demonstrates even higher values, with precision and recall at 0.96 and an exceptionally high F1 score of 0.99. These outcomes underscore the practical utility and robustness of the AI-powered holistic model in revolutionizing inventory management practices. While acknowledging challenges and limitations, this research signifies a crucial advancement in establishing responsive and intelligent decision-support systems for inventory optimization, paving the way for future innovations in supply chain management
Summarization of Video using Audio
Authors: Yadav Pratiksha , Rajgure Nimish , Thoke Rohan , Mandore Sahil , Bhaskre Prof. Pallavi
Published: March 2024

Abstract: Online education has emerged as a highly effective means of delivering quality education to students. Its popularity has increased due to the high-quality visual and graphical content, delivered by subject matter experts, and the convenience of learning anytime and anywhere. However, students may face time constraints that prevent them from fully engaging with the course content. To address this issue, video transcript summarizers have gained popularity. These tools extract the most important topics from a video, allowing students to understand the essence of the class without having to watch the entire video. Our system focuses on developing a module using txtai.pipeline with Python to summarize online class videos. We use Whisper, a general-purpose speech recognition model, to train our model on a large dataset of diverse audio. The model takes the URL of a video as input and uses two algorithms to summarize the content: TF-IDF and Gensim. The summarization process is subjective, and we have incorporated two prominent methods: cosine similarity and ROUGE score. The former does not require a human-generated summary for reference, while the latter does. Our results show that the efficiency obtained using cosine similarity is greater than 90% in both TF-IDF and Gensim cases. The efficiency obtained in the case of ROUGE score is between 40-50%.
Anomaly Detection in Crowd Surveillance using Edge Computing: A Comprehensive Survey
Authors: Juvekar Ayush , Bhadgaonkar Shrikant , Ghadge Ameya , Wakode Madhuri
Published: March 2024

Abstract: As urban environments continue to witness the proliferation of surveillance systems, ensuring public safety and security has become an increasingly challenging endeavor. Anomaly detection in crowded areas has emerged as a crucial task in these settings, aimed at identifying suspicious activities or potential threats. To meet the demands of real-time monitoring and analysis, edge computing has gained prominence as a critical technology. This survey paper provides a comprehensive overview of the state-of-the-art in anomaly detection, its use in crowd surviellance and the role played by edge computing in anomaly detection .The paper reviews an extensive body of literature encompassing various techniques and methodologies employed for anomaly detection in crowded scenes. It explores the evolution of traditional video-based approaches, such as motion analysis and object tracking, and the recent advancements leveraging deep learning, including various models in machine learning. These techniques are examined for their applicability in crowd surveillance scenarios.Various commonly used datasets to measure the quality of anomaly detection are also explored, along with their attributes and descriptions.The survey analyzes how edge computing solutions, such as edge AI accelerators and edge devices, enable faster and more context-aware processing of video data, while also addressing issues related to bandwidth constraints, privacy concerns, and scalability; paving way for a further research in harnessing the power of edge computing in crowd surveillance anomaly detection.
Data-Driven Agriculture: Empowering Farmers with IoT and Analytics
Authors: Neeraj  , Naveen S , Aranganathan Dr. A.
Published: March 2024

Abstract: The agriculture industry faces daunting challenges like climate change, water scarcity, and pest outbreaks, hindering farmers from meeting the demands of a growing population. To tackle these issues, this project proposes a smart farming platform integrating IoT devices, data analytics, and a user-friendly interface. It aims to optimize crop management, boost yields, and conserve resources. The platform includes sensor nodes and IoT devices gathering data on soil moisture, temperature, humidity, light intensity, and atmospheric conditions. It leverages predictive analytics for real-time insights on crop health, growth patterns, and potential threats like diseases and pests. Early detection mechanisms using image recognition and AI algorithms will be employed. Weather forecasting integration helps in decision-making for agricultural operations. Crop-specific recommendations based on local conditions are provided. The platform offers a dashboard interface for real-time monitoring, notifications, and remote control of automated systems. Historical data analysis aids in identifying patterns and trends for future crop cycles.
Low Power Design of Efficient Wireless Sensor Node
Authors: Uttarkar Vighneshkumar , G Poornima
Published: March 2024

Abstract: The escalating demand for rapid, efficient System on Chip (SoC) designs has intensified the need for low-power solutions, particularly in Wireless Sensor Nodes reliant on battery power. This research centers on leveraging clock gating to curtail dynamic power usage in an 8-bit Arithmetic and Logic Unit (ALU). Employing the Hans-Carlson Adder for addition and a 4x4 approximation multiplier, the ALU processes data from a humidity sensor module. Simulations using Xilinx Vivado reveal a substantial 65–73% reduction in power consumption at higher frequencies. This ALU, adept at minimizing power, emerges as a viable processing element for energy-sensitive sensor node applications, ensuring prolonged operational longevity.
Development of e-worksheet based on engineering design process for composition function material
Authors: Kurniawan Lutfi Cahya , Wahyuni Indah
Published: March 2024

Mathematics learning poses several challenges, making the utilization of technology, particularly e-worksheets, a promising solution to offer a more interactive learning experience and bolster student success. This research aims to describe the validity, practicality, and effectiveness of using Engineering Design Process (EDP)-based e-worksheets in composition function material in high school. The research subjects are 35 eleventh graders at SMAN 1 Tegaldlimo, Banyuwangi, East Java. The Research and Development (R&D) utilized the ADDIE model and collected data through observation, interviews, and tests. The results of expert validation approval obtained a score of 83.33%, which indicates valid or reasonable to use but requires slight updates. The practical results obtained from the analysis of student questionnaires were 76.69%. The pretest and post-test values are analyzed using the Wilcoxon Test with a significance value of < 0.05. The utilization of EDP-based e-worksheets significantly influences composition function material in high school. The N-Gain score shows the mean value was 70.09 %, which is categorized as high (quite effective). Developing e-worksheets based on feedback from teachers and students, as well as further studies on their long-term influence on student learning outcomes, is needed.
Cadena agroindustrial queso adobera de los Altos de Jalisco, impulsora del desarrollo local y regional
Authors: Cervantes-Escoto Fernando , Cesín Vargas Alfredo
Published: March 2024

El objetivo fue determinar, a través de un análisis de Fortalezas, Oportunidades, Debilidades y Amenazas (FODA), si la cadena agroindustrial del Queso Adobera de Los Altos de Jalisco, puede ser un polo de desarrollo local y regional. Se aplicaron encuestas estructuradas a 55 productores de leche, 13 queseros y 8 comercializadores; así como entrevistas abiertas a recolectores de leche y queso, representantes de las organizaciones de productores y a funcionarios de instituciones de apoyo. La información recabada, se organizó con base en el enfoque de cadena agroindustrial. Según la memoria colectiva de la región, el Queso Adobera de Los Altos de Jalisco se conoce con ese nombre, porque la cuajada se coloca en moldes de madera rectangulares, normalmente de madera de mezquite, resultando un queso con forma similar a un adobe de los utilizados en la construcción. Aunque es un queso valorado en la zona y existen estrategias que se pueden implementar para que la cadena agroindustrial sea un polo de desarrollo local y regional, primero, se debe resolver su principal debilidad, que es la poca disposición a organizarse por parte de los productores. Se concluye que es importante una buena gobernanza, con un capital social robusto, en la cadena para conseguirlo.
Pembentukan Kepemimpinan dalam Organisasi Keagamaan: Analisis Latihan Kader Utama Ikatan Pelajar Nahdlatul Ulama, Yogyakarta
Authors: Alghozali Ahmad Mirshad
Published: March 2024

This article aims to discuss how the Ikatan Pelajar Nahdlatul Ulama (IPNU) in Yogyakarta instills leadership qualities in its members through Primary Cadre Training. The study employs a qualitative method with a descriptive approach. Data were collected through observation, interviews, and content analysis conducted during the sessions of the Ikatan Pelajar Nahdlatul Ulama (IPNU) Primary Cadre Training. The study indicates that IPNU Primary Cadre Training emphasizes self-analysis, organizational understanding, and the development of ideology while instilling values of patriotism, nationalism, and Islamic ideology. The study concludes that leadership training in IPNU is grounded in Max Weber's theory of authority, emphasizing a combination of technical expertise and moral integrity. Although Primary Cadre Training does not guarantee charismatic authority, it serves as a crucial foundation for IPNU cadres to assume leadership responsibilities in the future.

Abstrak

Artikel ini bertujuan untuk mendiskusikan tentang bagaimana Ikatan Pelajar Nahdlatul Ulama (IPNU) di Daerah Istimewa Yogyakarta menanamkan kualitas kepemimpinan pada anggotanya melalui Latihan Kader Utama. Kajian ini menggunakan metode kualitatif dengan pendekatan deskriptif. Data dikumpulkan melalui observasi, wawancara, dan analisis konten selama sesi Latihan Kader Utama Ikatan Pelajar Nahdlatul Ulama (IPNU).  Kajian ini menunjukkan bahwa latihan Kader Utama IPNU menitikberatkan pada analisis diri, pemahaman organisasi, dan pengembangan ideologi, serta menanamkan nilai cinta tanah air, nasionalisme, dan ideologi keislaman. Kajian ini menyimpulkan bahwa latihan kepemimpinan di IPNU memiliki dasar pada teori otoritas Max Weber yang menekankan pada kombinasi keahlian teknis dan integritas moral. Meskipun Lakut tidak menjamin otoritas karismatik, tetapi sebagai tahap akhir pengkaderan Lakut memberikan landasan penting bagi kader IPNU untuk mengemban tanggung jawab kepemimpinan di masa depan.
Optimal Resource Allocation Strategy for ISAC Cellular Network with Multiple User Demands
Authors: Zhu Jia , Xie Yanxi , Jing Xiaojun , Mu Junsheng
Published: March 2024

Future communication networks are widely considered to be able to
provide both high-speed communication service and reliable sensing
service. Integrated sensing and communication (ISAC) has been a novel
trend due to its possible hardware gain and spectrum gain by the
integration of signal communication and sensing capabilities.
Appropriate resource allocation strategy is essential for ensuring the
quality of both communication and sensing services in terms of ISAC.
Existing ISAC-based resource allocation schemes mainly focus on the
coexistence of sensing and communication. However, in multi-user ISAC
networks, the services required by users are diverse, including
sensing-only, communication-only and dual-function cases. To this end,
we proposes a resource allocation strategy based on user quality of
service(QoS). Specifically, the sum rate of cellular network is
maximized via optimizing spectrum resource selection and transmit power,
while meeting the sensing QoS. We achieve the optimal solution to the
entire problem by first demonstrating that the communication rate in
this paper is a monotonically increasing function of sensing power,
allowing us to obtain the optimal power allocation scheme. Subsequently,
we employ a matching method to obtain the optimal spectrum sharing
scheme.
The impact of different dosages of vitamin E supplementation on oxidative stress, spatial learning, working memory, and the expression of aging-related genes in the heart and hippocampus of aged mice.
Authors: Zamanian Mohammad Yassin , Vasei Farnoosh Molavi , Golmohammadi Maryam , Mahmoodi Mehdi , Khademalhosseini Morteza , Tavakoli Tayyebeh , Esmaeili Ozra Sadat , Zarei Sadegh , Mirzaei Mohammad Reza , Hajizadeh Mohammad Reza
Published: March 2024

This study conducted an investigation into the impact of
different dosages of vitamin E supplementation on histopathological
alterations, cognitive behaviors, and the expression of age-associated
genes in the heart and hippocampus of aged mice. Mice at 12 months of
age received varying doses of vitamin E (100 mg/kg, 200 mg/kg, and 400
mg/kg) orally through gavage for 28 days. The results indicated that
vitamin E supplementation improved working memory and spatial learning,
reduced oxidative stress in the heart and brain tissues, and positively
influenced the expression of SIRT1, Nrf2, and Calstabin2 genes.
Interestingly, the efficacy of vitamin E was dose-dependent, with higher
doses demonstrating more beneficial effects. The study also examined the
influence of vitamin E on the activities of antioxidant enzymes, such as
SOD and GPX, as well as the levels of MDA, a marker of oxidative stress,
and found that vitamin E supplementation resulted in dose-related
changes in these parameters. The findings also indicate that higher
doses of vitamin E, particularly at 400 mg/kg, demonstrated more
beneficial effects. However, the study emphasizes the need for further
research to confirm these findings and to explore the potential clinical
applications of vitamin E supplementation in addressing age-related
conditions.
Divergent changes in microbial communities and nutrients upon forest floor humus layer of the sandy Pinus sylvestris var. mongolica plantation in Northeast of China
Authors: Wei Yawei , Wu Mengge , Cheng Zhiping , Jing Chunlin , Yan Lingyu , Meng Deling , Zhu Wenxu , Chen Zhenju
Published: March 2024

The sandy Pinus sylvestris var. mongolica plantation that
as the boundary part of the Three North Shelterbelt Project in Northeast
China has been well protected and prohibited disturbance more than ten
years, and thus bring about lots of forest floor litter and then humus
layer. While humus layer accumulation that could change the interface
between litter and soil, its effects on litter and soil, and especially
the interaction among them were still poorly understood. Hence, three
different treatments that included remove all forest floor litter and
humus, double forest floor litter and humus layer, and retain forest
floor litter and humus original (no treatment) were conducted, and the
physicochemistry properties and microbial communities were monitored.
Results showed that the humus layer increased forest floor litter
decomposition rate and its total carbon, total nitrogen and total
phosphorus significantly, while it changed soil pH and nutrients
differently and slightly. The abundances of bacterial groups at
different taxonomic levels increased and while its diversity indexes
decreased in litter when the humus layer existed, however, the fungi
community both in litter and soil varied insignificantly. The humus
layer not only increased remarkably the proportions of common OTUs
between humus and litter, humus and soil compared to litter and soil
both for fungi and bacteria, but also decreased the differences of the
number of fungal and bacterial taxa statistics between litter and soil.
It implied that the humus layer could act an important role in the
recover process of degraded forest ecosystem.
Targeting PPARα/γ by icariside Ⅱ to rescue acute liver injury via coactivating SIRT6
Authors: Gao Jianmei , Wei Jiajia , Yi Yang , Gong Miaoxian , Hou Fangqin , Wu Xiaoyu , Li Yiqi , Zhang Yuandong , Gong Qihai
Published: March 2024

Background and Purpose:: Peroxisome proliferator-activated receptor α
and-γ (PPARα/γ) are known to play crucial roles in acute liver injury
(ALI). Icariside Ⅱ (ICS Ⅱ), a natural flavonoid compound derived from
Herba Epimedii, confers neuroprotection with PPARα/γ induction potency.
This study was aimed to explore whether ICS Ⅱ has the capacity to
protect against ALI, and if so what are the role of PPARα/γ in the
beneficial effect of ICS Ⅱ on ALI. Experimental Approach: Mice
challenged by D-galactosamine (GalN)/lipopolysaccharide (LPS) and
Kupffer cells (KCs) upon LPS insult were used as ALI models in vivo and
in vitro. PPARα/γ-deficient mice and Sirt6-deficient mice were treated
with ICS Ⅱ to validate the potential targets of ICS Ⅱ on ALI. Key
results: ICS Ⅱ dose-dependently improved the survival rate and liver
histology, decreased ALT and AST in D-galactosamine
(GalN)/lipopolysaccharide (LPS)-treated mice. Furthermore, ICS Ⅱ
directly bound to PPARα/γ and increased their activities. The protective
properties of ICS Ⅱ were counteracted when PPARα/γ were knocked out in
GalN/LPS-induced mice and LPS-induced KCs, respectively.
Mechanistically, ICS Ⅱ restored mitochondrial function, reduced
oxidative stress and inflammation through activating PPARα/γ, which
interacted with Sirt6 and inhibited NF-κB nuclear translocation.
Intriguingly, ICS Ⅱ-evoked hepatoprotective effect and activation of
PPARα/γ were largely blunted in Sirt6-deficient mice. Conclusions and
implications: Our findings not only highlight PPARα/γ-SIRT6 signaling as
a vital therapeutic target to combat ALI, but also reveal ICS Ⅱ may
serve as a novel dual PPARα/γ agonist to safeguard ALI from the
oxidation-inflammation vicious circle by coactivating SIRT6.
The mass that should not be there: multi-modality imaging clarifies a diagnostic conundrum
Authors: Swinn Timothy , El-Medany Ahmed , L Gogola
Published: March 2024

We report a case of a 77-year-old male with an incidental finding of a
filling defect in his main pulmonary artery on computed tomography.
Pulmonary embolism was initially suspected however through serial
multimodality imaging the diagnosis became a main pulmonary artery
fibroelastoma, a very rare site for this tumour. The case highlights the
importance of marrying radiological findings with clinical examination
and demonstrates how complementary information was gained by each
modality. Furthermore, the case demonstrates how monitoring a lesion’s
behaviour over time can influence the differential diagnosis from a
common to a much rarer pathology.
Primordial symptoms and electrocardiogram among sudden cardiac death victims due to primary myocardial fibrosis
Authors: H Silvola , Pakanen Lasse , Holmström Lauri , Perkiömäki Juha , Huikuri Heikki , Junttila Juhani
Published: March 2024

Background. Sudden cardiac death (SCD) remains a major cause of
death despite progress in prevention and intervention of cardiac
diseases. The most common cause of non-ischemic SCD in young individuals
in Northern Finland is primary myocardial fibrosis (PMF).
Methods. Fingesture study consists of 5,869 systematically
autopsied subjects with SCD from Northern Finland collected from 1998 to
2017. Nonischemic etiology was the cause of SCD in 1477 (25%) subjects
out of which primary myocardial fibrosis was the cause of SCD in 184
(12%) subjects (65% men, median age 55±16 years). Medico-legal
autopsies in PMF subjects showed no other noncardiac organ changes or
prior diseases that could have caused myocardial fibrosis detected at
gross dissection and histological analyses. We examined the ante mortem
ECG and medical history of the subjects to discover preceding symptoms
and ECG changes. Results. Prior health care contact in
electronic health record system was found for 89 (48%) subjects and ECG
was available for 52 (28%) subjects; 20 subjects both medical history
and ECG were available. We observed that transient loss of consciousness
(TLOC) was the most common symptom recorded and was reported by
33 (37%) subjects. ECG was abnormal in 38 (73%) subjects. Fragmented
QRS (fQRS) complex was found in 26 (50%) subjects. Other ECG findings
were prolonged QTc (>450ms in men and >470ms
in women) in 10 (19%), T-inversions in 4 (8%), pathological Q-waves in
3 (6%), and prolonged QRS (> 110 ms) in 3 subjects. Vast
majority, 87% of subjects had either TLOC or abnormal ECG. Only 7
subjects with ECG or ERS history available had normal ECG and did not
have previous TLOC. Conclusions. Most subjects with PMF had
abnormal ECG or previous TLOC. The results suggest that the combination
should generate careful cardiovascular examination in order to detect
underlying myocardial disease and possibly prevent SCD.