bluuebunny/crossref_metadata_2025 huggingface dataset:
Genome-wide profiling of the epigenetic landscape of histone variant TH2B in murine oocytes and pre-implantation embryos
Authors: Singh Isha , Parte Priyanka
Published: October 2024

In brief

This study investigates the role of TH2B in pre-implantation embryos and found that TH2B deposition varies between gametes but rapidly redistributes in two-cell embryos after fertilization. Our ultra-low-input native chromatin immunoprecipitation and sequencing (ULI-NChIP-seq) revealed that TH2B is enriched in early chromatin but decreases after the two-cell stage, with strong correlations to key regulatory regions, histone modifications and transposable elements (TEs), indicating its critical role in zygotic genome activation and early developmental processes.

The histone variant TH2B, enriched in oocytes, sperm and early embryos, decreases as embryos differentiate into pre-gastrula stages. Despite its presence, the role of TH2B in epigenetic reprogramming during early embryonic development remains largely under-researched. Our study employed ULI-NChIP-seq to analyze the genome-wide distribution of TH2B in metaphase II (MII) oocytes and early embryos. We found that TH2B is enriched in the chromatin of oocytes and two-cell stage embryos but becomes less prevalent after the two-cell stage. Correlation analysis revealed that the TH2B chromatin patterns in sperm and pre-implantation embryos are more similar to each other than to those in MII oocytes. Gene ontology (GO) analysis of TH2B-occupied loci linked them to various developmental processes including oogenesis, fertilization, chromatin modification and transcription regulation. The study also identified a strong association of TH2B with specific TEs, particularly long terminal repeats, which are known to regulate pre-implantation development. Additionally, early embryos showed H3K9me3 marks at TH2B-bound loci. TH2B exhibited strong correlations with H2A.Z and H3.3 in the two-cell and eight-cell stages, a positive association with H3K27Ac and H3K4me3 and a negative correlation with H3K27me3. Allelic reprogramming analysis of TH2B in embryos from C57BL/6J and DBA/2J crosses revealed differential dynamics between maternal and paternal alleles, with a notable paternal bias at the promoter in two-cell embryos. Thus, TH2B’s enrichment in early embryonic stages and its association with key regulatory regions and histone modifications underscore its importance in zygotic genome activation and subsequent developmental processes.
Adaptation and Validation of a Scale of Self-Regulation of Learning in Mathematical Problem Solving
Authors: Landa Josune , Berciano Ainhoa , Marbán José M
Published: October 2024

[Objective] This work aims to adapt and validate a scale that measures the level of self-regulation in mathematical problem-solving contexts of teachers in initial training in primary education. [Methodology] For sample selection, non-probabilistic convenience or incidental sampling was used. A total of 269 first-year primary education undergraduate degree students at the University of the Basque Country (UPV/EHU) in the 2020–2021 academic year participated in the validation process of the adapted scale. The type of research conducted is descriptive. Data were analyzed using the SPSS statistical software. [Results] The Cronbach's alpha coefficient value of 0.884 revealed a consistent internal reliability. Likewise, to test the factor structure of the scale, an exploratory factor analysis was conducted, obtaining a Kaiser-Meyer-Olkin (KMO) index of 0.836 > 0.7 and a p= 0.000<0.05 in the Bartlett test of sphericity. It also indicated a seven-factor structure: students' perceptions of their ability and how these perceptions influence self-regulation of the resolution process; ethics, problem-solving and personal growth; attitude towards the statement; negative self-efficacy beliefs; external causal attribution; problem-solving methods; and the social environment. [Conclusions] The latent structure provided by the exploratory factor analysis agrees with the classification of items established a priori and allows for the orientation of the confirmatory factor analysis that provides continuity to the research.
PRIMER REGISTRO DE Disocactus speciosus (Cav.) Barthlott subsp. speciosus (Cactaceae: Cactoideae) EN NAYARIT, MÉXICO.
Authors: Salomon Montijo Bladimir , Díaz J. S , Márquez-Salazar G. , Gámez-Duarte E. A
Published: October 2024

En mayo de 2022 durante una exploración de una semana en la Sierra de Álica, municipio de La Yesca, Nayarit, se colectaron algunas cactáceas. Se registró Disocactus speciosus subsp. speciosus, no reportada previamente para la flora nayarita. Los especímenes fueron determinados en la Facultad de Biología de la Universidad Autónoma de Sinaloa. La especie es rupícola, péndula, tallos de tres costillas, espinas agudas, cortas en aréolas, flores polipétalas rojas, estambres numerosos, estigma plumoso color crema.  El registro complementa la distribución de la especie en una entidad ubicada entre dos estados que ya la tienen inventariada en su flora.
İsrail-Filistin Savaşında Siyasi Liderlerin X (Twitter) İçeriklerinin Analizi
Authors: Koca Gözde , Eğilmez Özüm , Ankara Yeşim
Published: October 2024

Günümüzde teknolojinin gelişmesiyle birlikte sosyal medya araçlarının çeşitliliği de önemli ölçüde artmaktadır. Bireyler sosyal medya araçları ile kendi fikir ve düşüncelerini paylaşabilme bu sayede görünür olma ve diğer insanları etkileyebilme fırsatı yakalamaktadırlar. X (Twitter) ise bu sosyal medya araçları içerisinde anlık ileti gönderme ve yüksek sayıda kitlelere hitap etmesiyle dikkat çekmektedir. Bu çalışmada 07 Ekim 2023 tarihinde Hamas’ ın Güney İsrail sınırlarından girerek saldırıda bulunması ile başlayan Hamas-İsrail çatışmaları ile ilgili siyasi liderlerin tweetleri nitel araştırma yöntemlerinden olan içerik analizi tekniği ile incelenmiş ve dünya siyasi liderlerinin bu savaş hakkındaki tutumlarını ortaya koymak amaçlanmıştır. Bu bağlamda çatışmaların ilk dönemi olan 07 Ekim - 07 Kasım 2023 tarihleri arasındaki tweetler incelemeye alınmıştır. Amerika Birleşik Devletleri Başkanı Joe Biden’ ın 73, Fransa Cumhurbaşkanı Emmanuel Macron’ un 29, Almanya Şansölyesi Olaf Scholz’ ın 24, Birleşik Krallık Başbakanı Rishi Sunak’ ın 38, Türkiye Cumhuriyeti Cumhurbaşkanı Recep Tayyip Erdoğan’ın 18 ve Katar Emiri Temim Bin Hamed Es-Sani’nin 5 olmak üzere toplam 187 tweet her biri kendi içerisinde ayrılarak analiz edilmiştir. Analiz için MAXQDA 2020 paket programı kullanılmış ve sonuç olarak siyasi liderlerin savaşın ilk dönemlerinde mevcut iş birlikleri ve siyasi stratejileri gereği tweetleri olduğu gözlenirken zaman içerisinde barış yanlısı tutumlar sergiledikleri tespit edilmiştir. Bununla birlikte Hamas’ ın tüm Filistin halkını temsil etmediği ve savaşın her iki taraf içinde yıkıcı sonuçları olduğu ve sivillerin bu durumdan zarar görmemesi gerektiği konusunda hemfikir olunduğu, insani yardım konusunda tüm liderlerin gayretli çalışmalar yürüttüğü tespit edilmiştir. Çalışmanın siyasi liderlerin ilgili çatışmalar hakkındaki tweetlerinin içerik analizini çıkararak alana katkı sağlayacağı düşünülmektedir.
Back-testing the iconic Polyfytos balanced-cantilever bridge to enhance condition assessment
Authors: Moutsianos Sokratis , Stefanidou Sotiria P. , Papanikolaou Vassilis K. , Mitoulis Stergios A.
Published: October 2024

This paper introduces a comprehensive framework for reliable damage assessment and decision making for bridge intervention planning. By utilising historical data and three-dimensional unmanned aerial vehicle (3D-UAV) photogrammetry, a detailed 3D numerical model is created, incorporating advanced modelling and scenario-based approaches. The methodology is applied to the Polyfytos bridge in Greece, which faces significant vertical deck deflections that disrupt traffic and have an impact on local communities. This approach offers a reliable, cost-effective, and efficient process, allowing stakeholders to make informed decisions with minimal physical interaction with the bridge. The integration of advanced modelling with in situ measurements and expert judgement is emphasised. For the Polyfytos bridge, the framework helps prioritise retrofits and assess the deck’s remaining strength under various loads, providing estimates of its overstrength. This aids in evaluating the bridge’s ability to handle additional vertical loads through pushdown analysis. Overall, the framework is valuable for rapid infrastructure assessment, identifying damage patterns, severity and the urgency of interventions related to structural strength.
AI-Based Smart Proxy Models for Accurate Oil Rate Prediction and Efficient Pipeline Monitoring
Authors: Ali Sajedian , Shahab Mohaghegh , Sasidharan Adiyodi Kenoth , Maryam Dashtbayaz , Iman Oraki Kohshour , Yasir Alkalby , Afeez Shittu
Published: October 2024

This research develops an advanced AI-based smart proxy model to significantly enhance the prediction of oil rates and the monitoring of crucial operational parameters such as temperature and pressure in oil field pipeline management. By integrating real-time data from Multiphase Flow Meters (MPFM) with sophisticated simulation outputs, the study introduces a dual-model approach that overcomes the limitations of traditional methods, improving both efficiency and cost-effectiveness. Model 1 employs high-precision real-time MPFM data to provide accurate oil rate predictions. By focusing on critical control points within expansive pipeline networks, this model strategically reduces dependency on extensive MPFM deployment, achieving substantial cost reductions while maintaining rigorous measurement standards. The incorporation of real-time data ensures immediate responsiveness to operational changes, facilitating accurate and reliable insights essential for effective pipeline management. Model 2 utilizes an AI-driven smart proxy to refine the outputs of conventional flow simulators such as OLGA. This model addresses computational challenges including high runtime and numerical convergence issues by selecting the most reliable and accurate simulation outputs. It provides rapid and dependable insights into flow dynamics, supporting timely operational decisions and proactive management that enhance the safety and efficiency of pipeline networks. The integration of Model 1 and Model 2 ensures localized precision and extends analytical capabilities across the entire pipeline network, significantly enhancing predictive accuracy. This harmonized approach not only sets new standards for flow assurance and pipeline management but also illustrates the transformative impact of AI on operational strategies in the hydrocarbon sector.
The effect of climate change on lactating mammalian milk: asystematic review protocol v1
Authors: Nogueira de São José Artur , Reis Zilma , Cândida Ferrarez Bouzada Maria , Gomes Penido Machado Márcia , do Carmo Resende Ursula , de Oliveira Mota Hilton , Ferreira da Rocha Adson , Lopes Pereira Júnior Marcelo , de Jesus Hartmann Nader Paulo
Published: October 2024

The search will be carried out in the following databases: MEDLINE (PubMed), Cochrane Library, Embase-Elsevier, Scopus-Elsevier, Web of Science, LILACS-BVS, IEEE. To define the search strategies, we will have support from the library of the Faculty of Medicine of the Univesidade Federal de Minas Gerais (one of the institutions that are part of this project). Furthermore, we will use the software StaRt‱ to manage all the bibliographical references and to centralize all information necessary to build a database for this systematic review. References retrieved from search strategies will be exported to the software StaRt‱, and duplicates will be removed. After this procedure, two independent reviewers will select potential titles and abstracts, assessed for the inclusion criteria outlined above. Potentially relevant studies will have their full-text versions then independently assessed by two reviewers to determine if they meet the inclusion criteria. Discrepancies will be resolved by a third investigator. Excluded articles will be documented along with the reasons for exclusion. A total of nine reviewers is involved in this process. The final selection of included studies will be carried out for qualitative and quantitative analysis. Subsequently, data will be extracted, and the characteristics of the included studies will be detailed.
Comparative efficacy and safety of cardio-renoprotective pharmacological interventions in chronic kidney disease: an umbrella review of network meta-analyses and a multicriteria decision analysis v1
Authors: Bellos Ioannis , Benetou Vassiliki
Published: October 2024

This umbrella review aims to evaluate the available network meta-analyses in order to provide pooled estimates comparing the effects of sodium-glucose co-transporter 2 inhibitors (SGLT2i), glucagon-like peptide-1 receptor agonists (GLP1a) and non-steroidal mineralocorticoid receptor antagonists (ns-MRA) in chronic kidney disease. A multicriteria decision analysis will be implemented to generate rankings of the above interventions evaluating multiple potentially conflicting endpoints at the same time.
Human scRNA-seq Alignment Pipeline Version 1.0 v1
Authors: Morley Michael
Published: October 2024

The Morrisey and Basil Labs at the University of Pennsylvania use a specific protocol for scRNA-seq (single-cell RNA sequencing) alignment that involves the STARsolo tool (version 2.9.7a) to generate outputs comparable to those produced by the 10x Genomics Cell Ranger v3.0 pipeline. Alignment with STARsolo (version 2.9.7a):The STARsolo algorithm is used as a fast, memory-efficient alternative to 10x Genomics CellRanger.STARsolo directly aligns raw sequencing reads from scRNA-seq data to the human reference genome. Like CellRanger, STARsolo performs: Barcode and UMI (Unique Molecular Identifier) extraction: Identifies cell barcodes and UMIs from the raw sequencing reads.Read alignment: Reads are aligned to the genome using STAR.Transcript quantification: Assigns reads to genes based on the alignment to compute gene expression per cell.Gene-cell matrix generation: Produces a matrix similar to CellRanger's output, containing gene expression counts across cells. Achieving CellRanger v3.0 Output:To match the output of CellRanger v3.0, specific parameters are set within the STARsolo command, particularly: --soloType CB_UMI_Simple: Defines the type of input for the barcodes and UMIs.--soloCBwhitelist: Uses the 10x Genomics whitelist to ensure correct identification of valid barcodes.--soloUMIdedup: UMI deduplication is set to handle potential PCR artifacts by counting each transcript only once per UMI.--soloFeatures: This is set to generate gene expression matrices, capturing standard features like gene and transcript annotations. --soloCellFilter EmptyDrops_CRPost-Processing:Once the alignment and quantification are completed, the resulting gene-cell matrix is further processed using SoupX to remove ambient RNAs
Plate Streaking v2
Authors: Carlos Goller Carlos , Sjogren Carly
Published: October 2024

Overview and Goals Streaking bacteria on agar plates allows scientists to obtain isolated colonies of bacteria. An isolated colony provides up to 10^8 bacteria cells that are genetically identical. This is why we call them clones or refer to them as colonies. The medium we chose to streak out bacteria must provide the nutrients required for prolific organismal growth, and not all bacteria require the same nutrients. There are a variety of types of media and we will use Tryptic Soy Agar (TSA) plates to grow your bacteria, which may or may not support your bacterium's growth. After completing this lab you will gain the following lab skills: Lab safety and proper personal protective equipment (PPE) Proper use of equipment: bacterial cell culture incubator Bacterial plate streaking Bacterial plate incubation
The VVBlue assay: a plate-readable, dye exclusion-based cell viability assay for the toxicological testing of chemicals v1
Authors: Vitipon Marianne
Published: October 2024

A viability test for in vitro cultures, based on the intake of the textile dye Alphazurine A by dead cells and its exclusion by viable cells, is described. This test uses the affinity of Alphazurine A for proteins, so that the dye is retained in dead cells even after rinsing, while its anionic character prevents it from entering live cells. This feature makes this dye exclusion test amenable to a reading in a plate format. The Alphazurine viability test provides an indicator of the absolute number of dead cells present in the culture well. To reach a cell viability index, a “dead cells” control (e.g. cells killed with ethanol) must be added. We also describe a double viability test, which first uses the Alphazurine assay to provide the number of dead cells then a crystal violet assay to provide an index of the number of cells present in the plate. This double test provides a complete appraisal of the situation in the cell culture wells, and has been compared to other viability tests such as propidium iodide exclusion or tetrazolium reduction. Its performances to study the toxicity of substances such as pigments are also established.
RNA Extraction CTAB Protocol v1
Authors: Joly Simon
Published: October 2024

Protocol used and fine-tuned in the Joly laboratory Reference Gambino G., Perrone I., Gribaudo I. 2008. A rapid and effective method for RNA extraction from different tissues of grapevine and other woody plants. Phytochemical Analysis. 19:520–525.
Data-Driven Campaigning in Data-Dense Small Multiparty Systems: A Party-Level Analysis
Authors: Segesten Anamaria Dutceac , Sandberg Linn
Published: October 2024

This study examines data-driven campaign (DDC) practices in Sweden. We explore the extent of data-driven practices adopted in Swedish political campaigns, and parties’ motivations to adopt them. Since this is a comparison of domestic parties, we test the importance of four party-level factors—resources, structure, attitudes toward data use, and ideology—using extensive interviews with key campaign managers in Sweden during the 2022 election year. Our results show that the differences among the eight parties studied are rather small, and that systemic factors are more important than party variables to explain the adoption of data-driven approaches. Zooming in on these finer differences we distinguish between top DDC adopters (Social Democrats, Center, and Conservatives) and a lower tier with lower levels of DDC implementation. To explain the differences between the two tiers, we find that economic resources are important, with richer parties being more advanced in DDC use. Party structure, attitudes to data, and ideology do not affect the likelihood of a Swedish party using data analytics in their strategic decision-making. Instead, we suggest party type (catch-all vs. niche) is a potentially more useful party-level factor in explaining variation.
Data-Driven Maintaining: The Role of the Party and Data Maintenance in the US Context
Authors: Baldwin-Philippi Jessica
Published: October 2024

Political campaigning in the US is unique in the global context for its lack of attention to the role of the party, largely due to the centrality and power of campaigns. In the US context, successful data-driven campaigning (DDC) has often been covered by the press and analyzed by US scholars as an innovative campaign creating new tools and new tactics (and earning more media coverage for them). This research investigates the oft-ignored role of party organizations in DDC in the US, and in doing so, highlights the invisible work of data maintenance that is their purview. Methodologically, it brings together interviews with staffers from both party organizations and campaigns with thematic analysis of news coverage to answer questions about how the data-driven practices of parties versus campaigns differ, how parties’ data work is (and is not) covered, and what, in staffers’ views, contributes to such coverage. Ultimately, this research highlights how a lack of attention to party organizations’ work has gone hand in hand with a lack of attention to maintenance work in both academic and public discussions of DDC.
Floristics and land use mapping of Parque Ecológico Sucupira, Planaltina, DF, Brazil
Authors: Pacheco Iara Camargo Vecchi , Noronha Sergio Eustáquio , Cavalcanti Taciana Barbosa
Published: October 2024

The Parque Ecológico Sucupira (SEP) is a Sustainable Use Conservation Unit covering 31.09 hectares, located in the Planaltina Administrative Region, Distrito Federal its flora is typical of the cerrado sensu stricto. The study aimed to make available knowledge of the native species and the conservation status of SEP to support management and conservation programs. Collections were made over a period of 12 months through random walking. Two to three samples of each woody plant individual with floral buds, flowers, and/or fruits were collected, as well as 3-4 individuals of herbaceous or small-sized plants. The collected specimens were deposited at Herbarium CEN and UB. Up to the present, 258 species have been sampled, represented by 180 genera and 63 families. The five most representative families were Fabaceae, Poaceae, Asteraceae, Malpighiaceae, and Myrtaceae. The proportion of species from herbaceous-shrub habit compared to arboreal was 6:1 highlighting greater floristic richness in the herbaceous-shrub stratum. Furthermore, it was found that only one species occurring in SEP, Anemopaegma arvense, is classified as endangered. Approximately 40% of SEP's flora is endemic to the country. However, several factors threaten the integrity and compromise the biodiversity of the Park, such as land tenure, pressure from surrounding occupation, and invasion by exotic species.
Face Expression Recognition via transformer-based classification models
Authors: Arslanoğlu Muhammed Cihad , Acar Hüseyin , Albayrak Abdülkadir
Published: October 2024

Facial Expression Recognition (FER) tasks have widely studied in the literature since it has many applications. Fast development of technology in deep learning computer vision algorithms, especially, transformer-based classification models, makes it hard to select most appropriate models. Using complex model may increase accuracy performance but decreasing inference time which is a crucial in near real-time applications. On the other hand, small models may not give desired results. In this study, we aimed to examine performance of 5 different relatively small transformer-based image classification algorithms for FER tasks. We used vanilla ViT, PiT, Swin, DeiT, and CrossViT with considering their trainable parameter size and architectures. Each model has 20-30M trainable parameters which means relatively small. Moreover, each model has different architectures. As an illustration, CrossViT focuses on image using multi-scale patches and PiT model introduces convolution layers and pooling techniques to vanilla ViT model. We obtained all results for widely used FER datasets: CK+ and KDEF. We observed that, PiT model achieves the best accuracy scores 0.9513 and 0.9090 for CK+ and KDEF datasets, respectively
Average Wind Speed Prediction in Giresun-Kümbet Plateau Region with Artificial Neural Networks
Authors: Özbilgin Ferdi , Çalık Hüseyin , Dikbaş Mehmet Cem
Published: October 2024

In order to estimate the electricity generation capacity and schedule the supply for vendor needs, wind speed prediction is crucial for wind power plant frameworks. Prior to the installation of the wind power plants, a reliable wind behaviour model is neccesary. To have such a model, wind data is recorded periodically. In this study, hourly recorded meteorological data of actual pressure, relative humidity, temperature, wind direction and average wind speed for the year 2023 were obtained from the General Directorate of Meteorology for the Kümbet plateau region of Giresun province. The data is used to accurately predict the future wind speed for the region. Matlab Artificial Neural Networks (ANN) is utilized. Actual pressure, relative humidity, temperature and wind direction parameters are defined as input in the prediction process. 85% of the data set is used as training data and remainin 15% data set is used for testing data. An optimization process is applied to determine the number of hidden layers to have the prediction value with the smallest error. Bayesian Regularization training process was performed by seeing that the hidden layer has the lowest error at 90 neurons. Performance evaluations are performed with Mean Square Error (MSE), Mean Absolute Error (MAE), Root Mean Square Error (RMSE) and Pearson Correlation Coefficient (R) metrics. The values of the metrics for the test data are 26.7137, 5.1685, 3.5055 and 0.7457 respectively. The results show that, ANN based model is useful for the wind speed prediction over the region.
Grid Integration Strategies for Optimizing Renewable Energy Deployment and Grid Resilience
Authors: Aykut Ercan , Alshuraida Ihsan
Published: October 2024

This study explores the integration of renewable energy sources, namely, solar and wind, focusing on strategies to optimize their deployment into the electrical grid, and increasing the resiliency of the grid. Using four-year comprehensive data from Spain, including energy consumption, generation, pricing, and the condition of the weather, advanced statistical analysis, regression models, and optimization methods have been employed. Based on the results, it is clear that solar energy is seasonal, and wind energy is variable, with the weather playing a considerable role in the energy output. The optimization analysis showed that when the renewable capacity was increased to include 30 MW of solar and 120 MW of wind, the energy demand would be met at a significantly lower total system cost of $12.60 per unit. The costs related to operation and emissions would also decrease notably. However, with the regression models giving modest values of R² equal to 0.19 for solar and R² equal to 0.21 for wind, the extent of these developments and prediction can be fairly modest. Still, these results provide a strong backbone for the prediction of energy generation and show that modernization of the grid and adaptive management are of crucial importance. The results of the study could provide a guideline for policymakers and energy managers on how these goals can be achieved.
Artificial intelligence systems for predicting chronic ischemic heart disease outcomes in cardiac surgery patients based on presence of anemia: a literature review
Authors: Kalyuta Tatyana Y. , Emelyanova Irina P. , Suvorov Valeriy V. , Fedonnikov Alexander S.
Published: October 2024

BACKGROUND: In Russia, the number of people undergoing heart surgery exceeds 600 thousand annually. These include anemia in 30–70% of patients with a 4-fold increased risk of one-year death, a 5-fold increased risk of stent thrombosis, a 1.3-fold increased risk of recurrent acute coronary events, and a 2-fold increased risk of bleeding. However, among the prognostic systems developed using artificial intelligence (AI) technologies, few take the presence of anemia into account. Existing digital platforms are not designed to support clinical decision making.
AIM: The review aimed to evaluate existing AI platforms for predicting the course of ischemic heart disease (IHD) and systems that take into account the presence of anemia.
MATERIALS AND METHOD: The PubMed and Russian Science Citation Index databases from 2000 to January 2024 were analyzed. Using Keywords of “artificial intelligence”, “anemia”, “coronary heart disease”, “hemoglobin”, and “cardiac surgery”, 906 articles were found, of which 38 met the inclusion criteria for analysis.
RESULTS: In some countries, AI platforms have been created to predict the course of IHD. This review analyzes published data on the development and use of AI-based digital products for the management of patients with IHD, including those that take into account key hemodynamic parameters.
CONCLUSION: Analysis of existing developments revealed a focus on solving prognostic problems. However, in our opinion, the range of parameters analyzed is not wide enough. For example, anemia, which plays a key role in modifying the risk of adverse outcomes in IHD, has not been considered as a factor.
Exploiting Graphical Structures of Data and Neural Network Architectures
Authors:   , McDonald Andrew , Shokoufandeh Ali
Published: October 2024

The goal of this dissertation is to demonstrate the computational advantages gained by exploiting the graphical structures implicit in data, as well as the graph-theoretical underpinnings of computational architectures such as neural networks. A new computational architecture, Ortus, that uses a graph-based model to process structured data is introduced, which can be thought of as an approximation to a biologically-grounded Boltzmann machine. Next, sparse super-regular networks are developed to show the applicability of using sparse architectural network design toward solving real-world problems. Then, probabilistic hybrid graph convolutional networks show the practical applications of leveraging the inherent structural interdependencies within data by using hybrid neural network architectures. Within these networks, subnetworks are geared to extract particular types of relationships, similar to how Ortus routes specific types of information through predetermined channels. Finally, the benefits of merging structural sparsity with structured information processing are demonstrated by substituting super-regular network layers in place of fully-connected layers within the probabilistic hybrid architectures.
Effectiveness of cocoa bean extract mouthwash against gingivitis in pregnant women in Aceh Besar
Authors: Nuraskin Cut Aja , Reca  , Mardiah Ainun , Rahmayani Liana
Published: October 2024

Background: Gingivitis and periodontitis are the most common dental support tissue problems in dentistry. Gingivitis is an inflammation of the gingiva due to the body's response to the accumulation of dental plaque bacteria in the form of Streptococcus mutans, Streptococcus sanguis, Actinomyces, and Spirochaeta on the surface of the teeth. Gingivitis and nutritional status in pregnant women are related to the risk of 8.75 times the birth of low-birth-weight babies (BBLR) and premature babies. Prevention of gingivitis can be done chemically through gargling with antibacterial mouthwash. Therefore, herbal ingredients are needed that can prevent plaque and control gingivitis. This study aims to determine the effectiveness of mouthwash of cocoa bean extract against gingivitis.
Methods: This study used the post-test only control group design method. The study was conducted on pregnant women in Bayu Aceh Besar village with a total of 30 samples. The sample was divided into 3 groups that received different treatments. Group 1 was instructed to do a mouthwash with cocoa extract mouthwash while Group 2 with chlorhexidine, group 3 with mineral water. Each pregnant woman gargles for 30 seconds (20 ml) for 3 days.
Results: Analysis of the gingival index before and after using cocoa seed extract mouthwash showed that this mouthwash was more effective in reducing the gingival index with a value of p=0.012 (p<0.05).
Conclusions: Gargling with cocoa bean extract is more effective in reducing gingivitis. We recommend further studies to investigate the potential of cocoa bean extract for use in mouthwashes.
Drug utilization study of antidepressant drugs in psychiatric outdoor patients at a tertiary care hospital in Southern Rajasthan
Authors: Tanwar Arvind Singh , Singh Harcharan , Bhandari Aditi , Brahmbhatt Harshkumar K. , Garg Dharmendra , Jani Chetan , Damor Rahul , Ramkiran Nelliyottu Veettil
Published: October 2024

Background: The World Health Organization (WHO) defines “Drug Utilization” as the marketing, distribution, prescription, and use of drugs in a society, with special emphasis on the resulting medical, social, and economic consequences. Antidepressants are used to treat depressive illnesses and anxiety disorders. However, these are also employed in the pharmacotherapy of several psychiatric disorders. Very few studies were found regarding the pattern of prescription of antidepressants in outdoor patients in southern Rajasthan. So, this study has been planned to learn about the prescription pattern of antidepressant drugs as per WHO Core Drugs Prescribing indicators at a tertiary care hospital in southern Rajasthan.
Methods: A cross-sectional observational study was conducted among 375 patients by convenient sampling over one year duration, in the outdoor Department of Psychiatry at RNT Medical College, Udaipur, Rajasthan. Patient’s prescriptions were analyzed for drug utilisation pattern in OPD after relevant consent. All data was compiled in MS Excel and analyzed using statistical methods.
Results: Out of 375 prescriptions analyzed, 48.8% were males and 51.2% were females. Most commonly, patients had a diagnosis of depressive disorder (42.93%), followed by bipolar affective disorder (14.4%). The most common drug class prescribed was SSRI (88.86%). Escitalopram (41.65%) was the most prescribed drug, followed by Sertraline (30.51%).
Conclusions: Among the prescribed antidepressants SSRIs were the most common class of drug followed by TCA. Escitalopram was the most common drug to be prescribed followed by sertraline. More than half of the patients receiving antidepressants suffered from non-depressive disorders. Monotherapy was preferred over combination therapy. All patients were prescribed generic drugs.
Assessment of knowledge, attitude and practice of over-the-counter drugs and dietary supplements among non-healthcare college students in Chitradurga
Authors: Varghese Annu Merin , V. Srinivas , N. Hema , R. Yogananda , S. Vaishnavi
Published: October 2024

Background: The market for OTC drugs and dietary supplements is rapidly growing. However, there exists a lack of adequate awareness among the general public regarding the advantages and potential drawbacks associated with these products, particularly among the younger generation, who heavily rely on the internet for information. Therefore, this study sought to assess the knowledge, attitude and practice of college students regarding OTC drugs and dietary supplements, including prevalence and associated factors.
Methods: A prospective interventional study with 306 participants was conducted. Data were collected using a self-designed and pre-validated questionnaire and analysed using Statistical Package for the Social Sciences (SPSS) version 28. Descriptive and inferential (T-test) statistics were use.
Results: The prevalence of usage of OTC drugs and DSs was found to be 98.4% and 61.4% respectively. Easy accessibility (42.2%), safe and well tolerable (32.5%) were the main factors that influenced them to turn to SM with OTC drugs. The respondent’s preference for DSs was primarily driven by their desire to maintain good health (33.6%). Internet (22.2%) and healthcare professionals (21.9%) were the two most reported sources that students relied on to obtain information about DSs. The result revealed poor knowledge and a positive attitude towards OTC drugs and DSs among all participants.
Conclusions: A high prevalence of self-medication with OTC drugs and dietary supplements use was highlighted. Notable issues and improper practices were recognized. The findings indicate a need for education to enhance knowledge about OTC drugs and DSs and to encourage safe practices.
Formulation and evaluation of herbal gel containing ethanolic extract of Momordica charantia against socransky’s periodontal pathogens of the oral cavity-an in vitro study
Authors: Karvekar Shruti , Thakker Jasleen , Pattar Vilas , Krishna Vinita , Dhaleria Ritashna Kaur
Published: October 2024

Background: Periodontitis is a multifaceted disease initiated by periodontal pathogens which when left untreated results in inflammation of the supporting tissues of the teeth, resorption of alveolar bone, loss of the periodontal ligament attachment, periodontal pocket formation and/or recession of the gingiva. Hence, the current study aimed at evaluating the efficacy of Momordica charantia leaves extract on Socransky’s periodontal pathogens and formulating a herbal gel for subgingival local drug delivery for the potential treatment of moderate periodontitis.
Methods: M. charantia leaves were authenticated from a recognized taxonomist. They were coarsely powdered following which an ethanol-based extract preparation was done. The extract obtained was then assessed for minimum inhibitory concentration, minimum bactericidal concentration followed by gel formulation which was then subjected to time kill assay and zone of inhibition on periodontal pathogens, the efficacy of which was comparatively evaluated against 0.12% chlorhexidine (CHX) gluconate. Kruskal-Wallis Test was employed with the statistical significance set at p≤0.05.
Results: The concentration of M. charantia ethanolic extract against periodontal pathogens was determined to be 1 gm/100 ml and a statistically significant difference was found in the effectiveness between the gel so formulated and CHX.
Conclusion: The antibacterial activity was evident in the ethanolic extract of M. charantia which when used to formulate a herbal gel against anaerobic periodontal pathogens demonstrated efficacy comparable to that of CHX.
Exploring the effect of peppermint oil massage on pulmonary function in patients with bronchial asthma: insights from a case series
Authors: Chidambaram Yogapriya , Prabathas Reeves Justilind Dhas Reginald , Palanisamy Karthikeyan , Balasubramaniam Sushanthikaa , Kuppusamy Maheshkumar
Published: October 2024

Bronchial asthma (BA) is a chronic inflammatory disorder characterized by airway hyperresponsiveness and obstruction, leading to symptoms such as coughing, wheezing, and shortness of breath. Management typically involves inhaled corticosteroids, but their adverse effects necessitate exploring alternative therapies. Aromatherapy massage, particularly using peppermint oil, may offer therapeutic benefits due to its anti-inflammatory and broncho dilatory properties. This study investigates the impact of upper back massage with peppermint oil on pulmonary function in BA patients. Three female patients with a history of poorly controlled BA participated in this case series. Each patient received a 20-minute upper back massage with peppermint oil daily for 10 days. Pulmonary function tests (PFTs) were conducted before and after the intervention, measuring forced vital capacity (FVC), forced expiratory volume in the first second (FEV1), the FEV1/FVC ratio, peak expiratory flow rate (PEFR), and forced expiratory flow (FEF 25-75%). All patients showed improvement in pulmonary function post-intervention. Case 1: FVC increased from 80% to 97%, FEV1 from 67% to 82%, and PEFR from 72% to 93%. Case 2: FVC improved from 69% to 81%, FEV1 from 64% to 76%, and FEF 25-75% from 40% to 50%. Case 3: FVC rose from 74% to 78%, FEV1 from 55% to 60%, and PEFR from 56% to 63%. Upper back massage using peppermint oil appears to enhance pulmonary function in individuals with bronchial asthma.
An expert consensus on managing cough in Indian pediatric practice: airway disease education and expertise 2.0 (2024)
Authors: Ganapathy Sridhar , Mathur Ashish , Chakarvarty Ashok , Joshi Devesh K. , Gala Monil , Muchhala Snehal S. , Kotak Bhavesh P.
Published: October 2024

Cough in children is one of the most frequent presenting symptoms in health care settings. Coughing can significantly affect a child's sleep and level of activity, which often causes parents’ distress. Promptly addressing chronic cough may enhance the quality of life in children and reduce the considerable stress on parents. In 2017, airway disease education and expertise (ADEX) NEXT recommendations for diagnosis, management, and follow-up of persistent (chronic) cough were published. For the present work 27 modified Delphi consensus statements were prepared, and a survey was undertaken involving 30 expert pediatricians from across India. The opinions of the expert panel on the updates related to pediatric chronic cough awareness, diagnosis, and management were collected. Consensus was predetermined to be obtained if more than 75% of the participants agreed or remained neutral for the statement. All the statements were supported by the latest data from the literature search. All the statements reached consensus after an agreement of more than 75%. Consequently, all the opinions from experts were consolidated and expert recommendations were framed. Children presenting with cough should be treated in accordance with child-specific guidelines. The present expert recommendations can be utilized by pediatricians to make well-informed decisions when treating pediatric patients with cough. The management of cough in children should be determined by the underlying cause, where a prompt and efficient therapy can result in early resolution.
Patrones actitudinales de pacientes con diabetes en Venezuela
Authors: Velásquez Enmanuel , Hernandez Pablo
Published: October 2024

Introducción: las actitudes son predisposiciones para actuar de una manera determinada a partir de respuestas de carácter afectivo, cognitivo y conductual. Objetivo: distinguir los patrones actitudinales sobre su enfermedad en las personas con diabetes mellitus tipo 1 y 2 de Venezuela. Métodos: estudio descriptivo transversal en el que se valoró la actitud sobre la diabetes de 100 sujetos a través de la Diabetes Attitude Scale (DAS-3sp), la cual fue traducida al castellano y validada para Venezuela de forma previa. Se aplicó un análisis de componentes principales a las cinco dimensiones de dicha escala, seguido de un procedimiento de conglomerado jerárquico, lo que permitió determinar los patrones actitudinales de los pacientes. Resultados: las dimensiones con mayor puntaje promedio fueron Necesidad de entrenamiento especial (3,61 ± 0,38), Valoración del control estricto (3,17 ± 0,44) y Autonomía del paciente (3,08 ± 0,39), mientras que la Valoración del impacto psicosocial (2,32 ± 0,45) registró el menor puntaje. Se encontraron tres patrones actitudinales: el primero representa al 40 % de la muestra y obtuvo puntuaciones elevadas en las cinco dimensiones; el segundo agrupa al 21 % de los pacientes y se distingue por una muy baja puntuación en las dimensiones Percepción de la gravedad, Valoración del control estricto e impacto psicosocial; el tercero representa al 39 % de la muestra y valores significativamente menores en las dimensiones Necesidad de entrenamiento especial y Autonomía del paciente. Conclusión: los tres patrones actitudinales se diferenciaron por el componente emocional y se asociaron al grupo etario y nivel educativo de los pacientes.
The Development and Application of a MCPS (Motivation and Creative Problem Solving) Instructional Model in Computing Liberal Arts for Non-Majors
Authors: Park Hee Jung , Jeon Yong Ju
Published: October 2024

The purpose of this study is to develop and validate a learning motivation and creative problem-solving MCPS instructional model for non-majors in a computing liberal arts course. This study aimed to propose a specific method for conducting a computing liberal arts class tailored for non-majors. The research was divided into two phases: model development and model application studies. In the model development study, we formulated the MCPS instructional model and lesson design by integrating Papert's constructionism learning principles, addressing the challenges in computing education for non-majors, and incorporating various teaching methods identified from related research. In addition, to improve the completeness of the instructional model, we developed an evaluation rubric that considered both content and evaluation aspects through expert review. In the model application study, we validated the effectiveness of this instructional model by implementing it in a university class. We employed various research analysis methods to derive further insights and implications. Research suggests that the traits of Papert's constructionism learning theory can enhance learner engagement and foster creative problem-solving in computing education when utilizing the MCPS instructional model. This model, as proposed in the study, can effectively serve as a pedagogical approach for delivering semester-long or more extensive computing liberal arts courses tailored for non-majors in college. We anticipate that the outcomes of this study will contribute to the establishment of robust computing education programs in universities, particularly at a time when the demand for computing education among non-majors is increasing, and its significance is growing.
Deep Learning and Statistical Process Control Approach to Improve Quality in Immigration Services
Authors: Pontiselly  , Ahsan Muhammad , Lee Muhammad Hisyam
Published: October 2024

Technological advancements have profoundly influenced various sectors, including tourism, by simplifying international travel and increasing the demand for passports. In this context, public feedback on the Surabaya Immigration Office's services, gathered from Google Maps reviews, presents an invaluable dataset for analysis. This study introduces a novel approach to quality management systems in immigration services by applying the Convolutional Long Short-Term Memory (Co-LSTM) for sentiment analysis of public reviews and p-attribute control charts for statistical process control. Focusing on the Surabaya Immigration Office, we analyze public feedback from Google Maps to assess service quality. Our methodology preprocesses and classifies opinion data into sentiment classes, employing Co-LSTM for its superior accuracy over traditional models. The sentiment analysis reveals a predominance of positive over negative reviews, with classification accuracy demonstrating Area Under Curve (AUC) values of 98.61% for training and 85.66% for testing data. Furthermore, the p-attribute control charts are utilized to monitor service defects, identifying areas of uncontrolled variability and suggesting the necessity for service improvement interventions. The study uncovers that the primary public grievance relates to the perceived lack of friendliness and politeness from office staff. By integrating sentiment analysis with statistical process control, this research offers a comprehensive approach for immigration service providers to enhance service quality, respond proactively to public sentiment, and ensure customer satisfaction.
Digital Transformation in the Music Industry: Session Musicians Matchmaking Platform Effectiveness Analysis
Authors: Fernando  , Yohannis Alfa Ryano
Published: October 2024

The music industry has been through a significant digital transformation in recent years, with one interesting development being the rise of matchmaking platforms for session musicians. Despite their potential benefits, the effectiveness and impact of these platforms on the music industry are not well studied. Therefore, this study aims to analyze the effectiveness of session musician matchmaking platforms and their implications for the music industry. Leveraging the architecture capabilities of The Open Group Architecture Framework (TOGAF), specifically the Architecture Development Method (ADM), all the participants with their current processes and pain points are identified. The identified pain points are then validated using the empathy map method through an online questionnaire. From the identified pain points, values are developed as the main targets for pain relievers in the current situation, which are later evaluated against existing platforms of a similar nature. After comprehensive research and data analysis, several key insights emerged. First, the findings reveal that, under the current traditional model, the collaboration process between session musicians and music entertainment continues to function effectively. Second, there is enthusiasm among participants for platforms that offer solutions to common challenges faced in collaboration processes. However, the research data shows low levels of adoption and utilization among participants. This suggests there is a huge opportunity for the development and promotion of matchmaking platforms designed specifically for session musicians and music entertainment to enhance collaboration and improve the music industry.