bluuebunny/crossref_metadata_2025_split huggingface dataset:
Advances in molecular diagnostics for cardiovascular diseases: Techniques and applications
Authors: Herve Mwewa Kibwe  
Published: October 2024

This review explores the cutting-edge advancements in molecular diagnostics for cardiovascular diseases (CVDs), emphasizing the transformative potential of genomic, proteomic, transcriptomic, and metabolomic technologies. The study highlights how these molecular diagnostics offer unprecedented precision in the early detection, risk assessment, and treatment personalization for complex cardiovascular conditions, such as coronary artery disease and heart failure. By utilizing advanced diagnostic tools like next-generation sequencing (NGS), artificial intelligence (AI), and multi-omics approaches, this paper reveals the potential of molecular diagnostics in reshaping cardiovascular healthcare. The key findings demonstrate that molecular diagnostics enable the identification of specific biomarkers and genetic mutations that drive CVD pathogenesis, leading to earlier and more accurate diagnoses. The review also acknowledges significant challenges, including the high cost of these technologies, the complexity of data interpretation, and ethical concerns regarding genetic privacy. Despite these barriers, the future of molecular diagnostics in CVD care is promising, with ongoing advancements in AI integration, real-time monitoring, and liquid biopsies providing exciting prospects for enhanced precision medicine. The study concludes by recommending increased research investments, clinical trials for tool validation, and the development of standardized protocols. It also suggests educational programs for clinicians to bridge the gap between diagnostics and practical clinical application, advocating for the comprehensive integration of molecular diagnostics into routine care to optimize cardiovascular health outcomes.
Keywords: Molecular Diagnostics, Cardiovascular Diseases, Genomics, Multi-omics, Artificial Intelligence, Precision Medicine.
El Niño enhances snow-line rise and ice loss on the Quelccaya Ice Cap, Peru
Authors: Lamantia Kara A. , Larocca Laura J. , Thompson Lonnie G. , Mark Bryan G. 
Published: October 2024

Abstract. Tropical glaciers in the central Andes are vital water resources and crucial climate indicators, currently undergoing rapid retreat. However, understanding their vulnerability to the combined effects of persistent warming, the El Niño and La Niña climate phenomena, and interannual fluctuations remains limited. Here, we automate the mapping of key mass balance parameters on the Quelccaya Ice Cap (QIC) in Peru, one of the largest tropical ice caps. Using Landsat's near-infrared (NIR) band, we analyze snow cover area (SCA) and total area (TA) and calculate the accumulation area ratio (AAR) and equilibrium-line altitude (ELA) over nearly 40 years (1985–2023). Between 1985 and 2022, the QIC lost ∼58 % and ∼37 % of its SCA and TA, respectively. We show that the QIC's reduction in SCA and rise in ELA are exacerbated by El Niño events, which are strongly correlated with the preceding wet season's Oceanic Niño Index (ONI). Further, expansion in the QIC's SCA is observed during all La Niña years, except during the 2021–2022 La Niña. Although this is a singular event, it could indicate a weakened ability for SCA recovery and an accelerated decline in the future, primarily driven by anthropogenic warming.
Charging Station Power System Data Prediction Model Based on Deep Learning
Authors: Hu Houpeng , Xiao Yanhong , Ou Jiaxiang , Chen Zerui , He Peilin , Deng Yuedan , Yang Shang 
Published: October 2024

The increase growth and adoption of electric vehicles (EVs) are playing a crucial role in advanced transportation system, helping to minimizing the emissions of harmful greenhouse gases and enhancing environmental sustainability. The need for EVs to be charged immediately has gained significant attention due to the rise in EVs sales over the last years. As a result of this, need for electric car charging is important to reducing the impact of electric network and providing minimum charging fares. In order to calculate the demand for charging EVs, a novel Deep Learning (DL)-based Long-Short Term Memory (LSTM) recurrent neural network predictor model is attempted to be developed in this research study. The Modified Aquilla Optimizer Algorithm (MAOA) is used to optimizing the parameter of the new Deep LSTM (DLSTM) neural predictor models and Independent Component Analysis (ICA) is utilized to solve the input time series data while conserving its properties. In this research, a novel ICA—AOA—DLSTM neural predictor model was developed to addressed the challenges of vanishing and exploding gradient in basic recurrent neural learnings. The predictor model was tested on the EV charging dataset from Georgia Tech, Atlanta, USA, indicating its performance. During simulation, the predictor achieved a prediction accuracies of 96.24% with a mean absolute errors of 0.1083 and a RMSE errors of 3.0629 × 10^-5, outperforming previous techniques. Additionally, the mean absolute error was found to be 0.2083, with a mean square error of 3.25516 × 10^-10. These results highlight the effectiveness of the novel deep learning LSTM neural predictor for this dataset compared to existing techniques.
Effect of soy flour and flour improvers on nutritional value, texture, colour and sensory characteristics of wafer biscuits
Authors: Alkhalalieh Nazieh , Frehat Ghadeer 
Published: October 2024

Biscuits are a popular and desirable snack food by consumers. Still, the quality of these products decreases during the storage process, so this study focuses on improving the wafer's quality and nutritional value and reducing their fragility by partially replacing wheat flour with soybean flour in the following proportions: 5% (T1), 10% (T2), 15% (T3), 20% (T4), and adding ammonium carbonate in different quantities. The sensory evaluation showed that the best wafer treatment was supported with 15% soy flour and 150 g of ammonium carbonate. At the same time, the mean for sensory evaluation is 8.80. Also, the results of the chemical analysis (protein, moisture, fat, carbohydrate, ash, fibre) texture and colour after direct manufacturing and after three months of storage. The result showed a significant increase in the percentage of protein and fat from 6.56±0.30 to 12.19 ± 0.35, 11.56±0.10 to 19.64±0.55, respectively the moisture content was higher in the control was 3.88±0.02 for wafer sample 2.47±0.13, while fibre was 1.93±0.15. The carbohydrates in the control sample were higher than in other treatments. Texture and colour were improved compared with the control. Commercial-batter biscuits with high nutritional value content and high-quality properties can be prepared by replacing wheat flour with 15% soy flour and adding 150 g of ammonium carbonate.
Static Analysis of Single Shaft Hub Wheel Cover to Determine The Strength Level of The Cover
Authors: Kurnia Ishak Rizaldy Eka , Muttaqin Benazir Imam Arif , Huki Chandra  
Published: October 2024

The cover on the wheel hub serves to protect the most important components and support the weight coming from the body, so it must be designed as well as possible to support the existing weight. The cover on the wheel hub also functions as a balance when driving so that the cover is made with strong material and is not easy to corrode because the part is often subjected to mechanical pressures. The problems that occur in the Nusantara Energy Manufacturing company (MEN) make researchers want to develop a cover design on a single shaft wheel hub to increase the strength of the cover in receiving pressure from vehicles, drivers, and passengers. In this research, a simulation study is carried out to design the cover and perform static simulations to determine the value of deformation and stress that occurs in the single shaft wheel hub cover. The material used in the cover design is Aluminum Alloy 6061 with a load value of 2177 N and 2912 N. The maximum deformation value on the MEN cover is 0.272 mm, a strain value of 0.007, and a stress value of 730.805 N/m2 with a load of 2177 N. At 2912 N loading, the maximum deformation value is 0.111 mm, a strain value of 0.003, and a stress of 307.538 N/m2. It can be concluded that the MEN cover has a higher static value than the YMMotorcover. There are several factors such as the thickness of the cover on the parts used as supportpoints.
Impact des perturbations scolaires au cours des années 2020-2021 sur les apprentissages en lecture en 4e année du primaire
Authors: Côté Sylvana , Haeck Catherine , Collet Ophélie , Sauve William , Larose Simon 
Published: October 2024

La Covid-19 et les mesures mises en place ont affecté les enseignements. Les épreuves standardisées ayant été annulées au Canada, nous avons peu d’informations sur l’ampleur des pertes d’apprentissage. Les apprentissages en lecture ont été évalué auprès de 10 880 élèves de 9-10 ans lors d’une épreuve ministérielle de 2019, réutilisée en juin 2021. On observe une baisse de 8,3 points de pourcentage en lecture entre juin 2019 et juin 2021. La taille de l’écart varie en fonction de la performance à l’épreuve: la différence est maximale pour le décile inférieur, modérée pour les déciles intermédiaires et nulle pour les déciles supérieurs. Les garçons ont subi une baisse plus importante relativement aux filles. Les perturbations pandémiques ont entrainé une baisse des performances en lecture pour les enfants, en particulier pour les plus vulnérables. Un suivi de l’évolution de la performance permettra de réduire les écarts causés par les perturbations.
Diagnosis and evaluating the urgent CT KUB at king Fahad specialist hospital, Buraydah, Saudi Arabia 2022.
Authors: Altasan Abdulaziz , Alrabeah Shuruq , Alfawzan Ohud 
Published: October 2024

PURPOSE: The aim of this research was to evaluate the diagnostic yield of urgent CT KUBs and assess the appropriateness of their use in the investigation of acute renal colic at King Fahad specialist hospital , Buraydah, Saudi Arabia 2022.

METHODS: All data were collected retrospectively from patient’s records including all patients who presented to the emergency and inpatients undergo unenhanced CT KUB to rule out urinary tract stones . Follow-up requests of known urolithiasis and any scan done for other clinical indications were excluded ,representing 3.7% .

RESULTS:
This study reviewed 1671 patients, 24.9% were aged between 31 and 40 years old, with nearly 60% being males. Most patients were admitted to ER (98%) and referred by non-urology physicians (99%). The prevalence of patients who were diagnosed with renal stones was 38.7%. Among patients who were presented with acute renal colic and CT scan revealed no urolithiasis, there was 11% with incidental and other alternative diagnosis. The most common finding was genitourinary diseases (48.9%), followed by gastrointestinal diseases (27.2%).

CONCLUSION:
The significant percentage of negative CT KUB of the examined patients reflects the physicians misapplication with this technique with a subsequent reduction in the rate of renal calculi detection with unnecessary radiation exposure as well as increased the alternative/incidental of extraordinary findings, which may indicate further emergency abdominal CT studies. Therefore, urology opinion before CT-KUB requested for patients with atypical presentation is highly advised. Additionally , departmental ultrasound is suggested mainly for the young females prior to CT scan to rule out any gynecological conditions that can mimic renal stones.
COMPARISON OF VECTOR AUTOREGRESSIVE (VAR) AND VECTOR ERROR CORRECTION MODELS (VECM) FOR THE COMPOSITE STOCK PRICE INDEX (JCI) IN INDONESIA
Authors: Arafat. A Lathif , Meta Williya , Meilisa Meilisa 
Published: October 2024

The capital market has a major role for economic development which is able to encourage capital formation and sustain economic growth. Financial liberalisation between countries in the world will make capital markets in each country interconnected. If there is a large movement in the global stock index, it will also have an impact on the JCI in Indonesia. In addition to global indices, macroeconomics is also seen as capable of influencing capital markets. Inflation and interest rates are macroeconomic components that can be used. The purpose of this research is to be able to see the relationship between one variable and another, namely the Composite Stock Price Index (JCI), Dow Jones Industrial Average (DJIA), inflation rate, interest rate. The VAR/VECM analysis approach was used in this study. Data was taken from 2017 to 2023. The data used for modelling is 84 observations. Based on the results, Inflation and DJIA have a long-term influence on the increase of JCI, while interest rates have no long term influence on JCI in Indonesia. With the model projection for the next 10 years. The projection results state that the variability of JCI in Indonesia is most dominantly explained by the JCI variable itself with a proportion of 95.21619%, while inflation contributes 0.193202%, interest rates 0.249170%, and DJIA index 4.341438%. The results of this analysis can be used as a consideration of strategies in increasing the JCI in Indonesia to maintain the health and stability of the economy.
Performance of advanced-deep learning algorithm for modeling and prediction of rain height over some selected locations in the tropics and sub-tropics zone for radio propagation applications
Authors: Lawal Yusuf Babatunde , Owolawi Pius Adewale , Tu Chunling , Wyk Etienne Van , Ojo Joseph Sunday 
Published: October 2024

As demand for high-frequency broadband communication services keeps rising, rain-induced attenuation remains the predominant threat to radiowave propagation. Accurate prediction of attenuation requires continuous measurement and monitoring of rain-induced meteorological parameters, specifically rain rate and rain height, due to their spatio-temporal variations. Rain height is an upper dataset mostly computed from Zero- degree Isotherm Heights (ZDIH) measured by radar. This research proposes a novel approach for predicting rain height from earth surface data such as surface temperature, pressure, total cloud cover, dew point temperature, surface solar radiation, water vapor amount in the air, and humidity. This research investigates the relationship between meteorological surface data and rain height. Subsequently, six machine learning models were employed for predicting rain height using the ten years surface data as input variables. The models were applied to six sub-tropical (Polokwane, Pretoria. and Cape Town) and tropical (Sokoto, Akure, and Port Harcourt (PH)) stations in South Africa and Nigeria, respectively. Analysis of the results shows that the Gradient Boosting Algorithm (GBA) performed best with determination coefficients greater than 0.80 and RMSE less than 350 in all three stations in South Africa. However, all the models failed to produce good result for the Nigeria stations. The Random Forest model has the fairest performance metrics with r2 of 0.40, 0.46 and 0.46 in Sokoto, Akure and PH. respectively. GBA is recommended for predicting rain height in South Africa. The research outcome would assist radio engineers in improving the prediction of rain-induced attenuation and determining appropriate fade mitigation techniques.
A Study of digital literacy among the marginalizes in Thailand: Issues, challenges for implementation and the way forward
Authors: Intraratat Kamolrat , Lomchavakarn Piyachat , Boonsiri Karn , Ng Khar Thoe , Intaratat Duangkamol 
Published: October 2024

The concerns about digital literacy in Thailand especially relevant to fake news, disinformation, and misinformation keep increasing and creating a multifaceted challenges to various sectors of Thai society i.e. financial, commercial, politics, society, and health-related. Among the areas identified include digital contents creation, dissemination, and social media enabling various information with complex challenges such as the proliferation of fake news, disinformation, and misinformation affected more kinds of negative effects currently. This study employs mixed-research method quantitative (survey questionnaire) and qualitative (Focus group discussion, observation, interview) data collection and analysis. A total of 315 samples and key informants were involved as well as grouped under 5 categories: marginal youths, elderly, community leaders, teachers, also government workers focusing on digital literacy knowledge and skills relevant to fake news. It also highlights the relevant contexts i.e. regulatory frameworks and mechanisms driven by key agencies in Thailand. Two main results were revealed that reflected the objectives of the study accordingly: The first objective is (1) overview of digital literacy and how to achieve it. The findings summarized from survey questionnaire include 1.1) even regulations exist found inadequate enforcement and low public awareness call for more effective and collaborative communication from all partners starting from the government agencies; 1.2) urgent need for public awareness communication campaigns emphasizing all the marginalized groups. Youths expressed in the interviews about their contribution to help reduce all kinds of fake news; 1.3) support more friendly ICT context provision such as availability, affordability, accessibility, usability, and useful information. The second objective is (2) mechanism for digital skills empowerment. The feedback from key informants include: 2.1) strengthening digital literacy skills among all marginalized groups to be a smart citizen then can help protecting themselves, their families and their communities; 2.2) all agencies from policy to local i.e. community leaders, educational institutions, private sectors, social media companies, civil society, and others must synergized more contributions; 2.3) educational institutions must design digital literacy academy with digital new-skills for the marginalizes, ensuring them for their safety and future job demands; 2.4) private sectors should support and co-designing digital products and services that address all current needs; 2.5) local government, and all partners should take an active collaboration and enforcement. The study concluded with implications and suggestions for future research in line with SDGs.
Perkembangan Bahasa Pada Anak Sindrom Down : Tinjauan Pustaka Sistematis
Authors: Lusiana Vilya Chalisyah  , Nisrina Raudhah  , Rhypsalida Zarra Vinasty  , Risa Risa  , Siti Hamidah  
Published: October 2024

Down syndrome is a common disorder. In Indonesia, cases of Down syndrome tend to increase every year. Down syndrome is a genetic disorder that causes children to have low cognitive and physical differences. One of the differences owned by down syndrome children is their language development. Therefore, this article was prepared to find out how language development in down syndrome children. This article was prepared using the systematic literature review (SLR) method, which contains how language development in children with Down syndrome, factors that affect language development in children with Down syndrome, and efforts that can be made to develop language skills in children with Down syndrome. This article explains that some Down syndrome children experience language delays, which are caused by genetic abnormalities and physical conditions such as a mouth cavity that is too narrow, a short palate, weak speech muscles and many more. To overcome language development in children with Down syndrome, several efforts can be made such as conducting speech and language therapy, and using the PECS method which has been proven effective in efforts to develop language in children with Down syndrome.
Analisis Penyebaran Hoax Di Media Sosial Dan Dampaknya Terhadap Masyarakat
Authors: Yopita Desriana Butar  
Published: October 2024

The spread of hoaxes on social media has become a serious problem in society. This research aims to analyze the factors that cause the spread of hoaxes, the characteristics of hoax content, a well as their impact on society. The research method used is the study of literature and content analysis from various online news sources. The results showed that the main factors of the spread of hoaxes were lack of digital literacy., economic motivation, and political polarization. Hoax content generally spreads quickly, has sensational titles, and contains inaccurate information. The impact of hoaxes on society includes confusion, social conflict, and a decline in public trust. This research concludes that comprehensive efforts from the government, media, and the public are needed to overcome the hoax problem. This research aims to analyze the causes, patterns of spread, and the impact of hoaxes on social media on the community. The research methods used are literature studies and content analysis from various trusted sources. Patterns of spreading hoaxes generally utilize sicial media algorithms to achieve a wide reach quickly. The negative impact of hoaxes on society is very diverse, ranging from triggering social confilcts, affecting public opinion, to threatening political stability and national security. This shows the urgency of handing hoaxes comprehensively, involving the role of government, social media platforms, and the public.
Meningkatkan Hasil Belajar Pendidikan Agama Katolik dan Budi Pekerti Metode Problem Based Learning Berbantuan Media Audio Visual Fase E Kelas X SMK Negeri IV SPP-SPMA Singkawang
Authors: Giovani Rikho  , Y L Sukestiyarno  , Martina Murlani  
Published: October 2024

The purpose of this study was to improve the learning outcomes of Catholic students in Catholic Religion lessons in class X with the Problem Based Learning model assisted by audio visual. The type of research used is Classroom Action Research which is carried out in two learning cycles. The research subjects were 15 Catholic students in class X DKV SMK Negeri IV SPP-SPMA Singkawang. To determine the achievement of student learning outcomes, researchers used written tests as a measuring tool. Meanwhile, to determine the learning outcomes of Pancasila students' profile in the dimension of critical reasoning, observation techniques were used. The results showed an increase in student learning outcomes by using problem-based learning, both cognitive and affective. Data on student cognitive learning outcomes, in cycle I the average value was 74%. Experienced an increase in cycle II to 83%. Data from the observation of the Pancasila learner profile of the critical reasoning dimension in cycles I and II showed an increase. Where in cycle I the average value was only 71%, it increased in cycle II by 82%. So, it can be concluded that the application of the Problem based learning model assisted by audio visual can improve student learning outcomes.