bluuebunny/crossref_metadata_2025_split huggingface dataset:
lncRNA CDKN2B-AS1 regulates collagen expression
Authors: Shi Weiwei , Song Jiahui , Weiner January , Chopra Avneesh , Dommisch Henrik , Beule Dieter , Schaefer Arne S 
Published: December 2023

Abstract
Background
The long noncoding RNA CDKN2B-AS1 harbors a major coronary artery disease risk haplotype, which is also associated with progressive forms of the oral inflammatory disease periodontitis as well as myocardial infarction (MI). Despite extensive research, there is currently no broad consensus on the function of CDKN2B-AS1 that would explain a common molecular role of this lncRNA in these diseases.Our aim was to investigate the role of CDKN2B-AS1 in gingival cells to better understand the molecular mechanisms underlying the increased risk of progressive periodontitis.
Methods
We downregulated CDKN2B-AS1 transcript levels in primary gingival fibroblasts with LNA GapmeRs. Following RNA-sequencing, we performed differential expression, gene set enrichment analyses and Western Blotting. Putative causal alleles were searched by analyzing associated DNA sequence variants for changes of predicted transcription factor binding sites. We functionally characterized putative functional alleles using luciferase-reporter and antibody electrophoretic mobility shift assays in gingival fibroblasts and HeLa cells.
Results
Of all gene sets analysed, collagen biosynthesis was most significantly upregulated (Padj=9.7x10− 5 (AUC > 0.65) with the CAD and MI risk gene COL4A1 showing strongest upregulation of the enriched gene sets (Fold change = 12.13, Padj = 4.9 x 10− 25). The inflammatory “TNFA signaling via NFKB” gene set was downregulated the most (Padj=1x10− 5 (AUC = 0.60). On the single gene level, CAPNS2, involved in extracellular matrix organization, was the top upregulated protein coding gene (Fold change = 48.5, P < 9x10− 24). The risk variant rs10757278 altered a binding site of the pathogen responsive transcription factor STAT1 (P = 5.8x10− 6). rs10757278-G allele reduced STAT1 binding 14.4% and rs10757278-A decreased luciferase activity in gingival fibroblasts 41.2% (P = 0.0056), corresponding with GTEx data.
Conclusion
CDKN2B-AS1 represses collagen gene expression in gingival fibroblasts. Dysregulated collagen biosynthesis through allele-specific CDKN2B-AS1 expression in response to inflammatory factors may affect collagen synthesis, and in consequence tissue barrier and atherosclerotic plaque stability.
Implementing Formative Assessment in Human Anatomy Practical Sessions: Medical Students’ Perception and Effect on Final Exam Performance
Authors: Atwa Hani Salem , Potu Bhagath Kumar , Fadel Raouf Abdelrahman , Deifalla Abdelhalim Salem , Fatima Ayesha , Othman Manal Ahmed , Sarwani Nasir Abdul Latif , El-Din Wael Amin Nasr 
Published: December 2023

Abstract

Background
Formative assessment with feedback is part of the assessment program in medical education to improve students' learning. Limited research has focused on its application and impact on practical anatomy education.
Method
This study aimed to examine medical students' perceptions of formative assessment conducted after practical anatomy sessions of integrated body systems-based educational units and explore its influence on their final practical exam performance. A descriptive, cross-sectional study was conducted. Data was collected from Year 2 medical students through an author-made survey that addressed their perception of the process and importance of formative assessment and feedback during practical anatomy sessions. The survey employed a 5-point Likert scale. Two additional open-ended questions were appended at the end of the survey. Students’ performance in Unit 3 (where formative assessment was conducted) was compared to their performance in Unit 2 (where no formative assessment was conducted) and with the performance of the previous academic year’s students in Unit 3 (where no formative assessment was conducted). Descriptive statistics were used, and the level of statistical significance was set at a p-value < 0.05. Responses to open-ended questions (qualitative data) were counted, categorized as themes, and presented as frequencies and percentages.
Results
The survey showed high internal consistency and its validity was established through exploratory factor analysis that yielded a single factor. The results showed that the mean mark for the unit with formative assessment and feedback was significantly higher than for the units without formative assessment and feedback. The students had a positive perception of formative assessment and feedback conducted after practical anatomy sessions. The students reported useful insights regarding the benefits they gained from formative assessment and feedback as well as constructive suggestions for improvements for the future.
Conclusions
The study findings indicate that the students positively perceived formative assessment and feedback sessions after practical anatomy sessions. The findings also refer to a possible positive effect of such formative assessment on students’ performance in summative practical assessment in anatomy.
CHAPTER: Gravitational Field Data Modeling and Interpretation
Authors: Taha Abdelhafiz Gadelmula , Muhammed Hussein 
Published: December 2023

Abstract
In order to interpret observed earth gravitational field, it is assumed that the surface is homogenous and the gravity fluctuation occurs only underground. A number of corrections of the data is applied to compensate for these fluctuations before modelling is performed. Gravity data in the form of Bouguer anomaly is obtained by correcting the measured gravity for the effects of latitude and topography and other minor corrections that allows for a clearer view of subsurface density. Variations in Bouguer Anomalies provide crucial information about the variations in earths subsurface rock distributions. Gravitational-field interpretation involve the qualitative and quantitative analysis of gravity data to derive reasonable and acceptable models that provide valuable insights into Earth's subsurface which in turn supports geological exploration results and resource assessment. The Bouguer gravity is analysed and modelled to estimate density-depth distribution. Examples of applications in geotechnical, petroleum, groundwater, regional crustal and tectonic models using different 2D and3D soft wares were provided here.
Blind Color Image Watermarking using Deep Artificial Neural Network using statistical features
Authors: Pandey Manoj Kumar , Jaiswal Sushma 
Published: December 2023

Abstract
With increasing digital content over the internet it is very important to secure the digital contents in such a way that the identity and integrity of data is preserved in some way. The healthcare data is also a digital content which is important and this paper presents a methodology for copyright protection and authorship. In order to achieve a balance between imperceptibility and robustness a robust watermarking scheme is proposed using deep artificial neural network (DNN) and lifting wavelet transform. YIQ color model is utilized for image watermarking and statistical features have been obtained for creating training and testing set. Here watermark extraction is done as a binary classification technique and PCA is utilized for reducing the feature set. Ten standard images have been used for image watermarking and for threshold value 0.3 it shows the average imperceptibility of 51.08 dB and shows good robustness under various image attacks.
Data-driven Approach to Age Prediction on Patients Diabetes and Cardiovascular Diseases Using Machine Learning: National Health and Nutrition Health Survey (Nhanes)
Authors: Abbas Irfan 
Published: December 2023

Abstract
Background
Diabetes and cardiovascular disease are two of the main causes of death in the United States. Identifying and predicting these diseases in patients is the first step towards stopping their progression. We evaluate the capabilities of machine learning models in detecting at-risk patients using survey data (and laboratory results), and identify key variables within the data contributing to these diseases among the patients.
Methods
Our research explores data-driven approaches which utilize supervised machine learning models to identify patients with such diseases. Using the National Health and Nutrition Examination Survey (NHANES) dataset, we conduct an exhaustive search of all available feature variables within the data to develop models for cardiovascular, prediabetes, and diabetes detection. Using different time-frames and feature sets for the data (based on laboratory data), multiple machine learning models (Support vector machines and adaptive boosting) were evaluated on their classification performance. The models were then combined to develop a weighted ensemble model, capable of leveraging the performance of the disparate models to improve detection accuracy. Information gain of tree-based models was used to identify the key variables within the patient data that contributed to the detection of at-risk patients in each of the diseases classes by the data-learned models.
Results
Diabetes and cardiovascular disease (CVD) are two of the leading causes of death in the United States. Detecting and predicting these diseases in patients is the first step to halting their progression. In this study, it was used Adaptive Boosting (AdaBoost) and Support Vector Machines (SVM) together as prediction. The purpose of this study was to knowing whether AdaBoost SVM could produce good accuracy. Tests were conducted using 50% data training and 50% data testing. Dot kernel were used to SVM. The highest accuracy value of AdaBoost SVM was accuracy 98.54%. Therefore it could be that AdaBoost can improve the performance of SVM in prediction of CVD desease severity
Conclusion
We conclude machine learned models based on survey questionnaire can provide an automated identification mechanism for patients at risk of diabetes and cardiovascular diseases. We also identify key contributors to the prediction, which can be further explored for their implications on electronic health records.
An assessment of nutrition information on front of pack labels and healthiness of Cereals and products in Vanuatu retail market
Authors: Shadrack Ronick , Kotra Krishna K , Livu Leyanni , Tari Daniel , Tabi Hancy 
Published: December 2023

Abstract

Nutrient profiling of front of pack labels is described as the science of ranking foods based on their nutrient content. It is fast becoming the basis for regulating nutrition labels, health claims, and marketing and advertising, especially for child and medicinal products. Survey of imported food nutritional facts is a primary monitoring tool for product quality evaluation prior to facts finding laboratory testing. Vanuatu, a South Pacific Island country depend on imports for its cereals needs, however there has been longstanding concerns over low quality and non-nutrient products with misleading labels. To evaluate this, a survey on nutritional quality on the food labels was conducted on cereals and products sold in retail market in Port Vila to qualitatively assess the nutrient profile. The survey aims to capture the availability of nutrient information on product, most common nutrient information on facts sheets and to qualify food based on the criteria of Food and Drugs Administration of the United States. Front-of pack labels on each cereal product were taken by a tablet device and manually entered into a database. The data was treated in a two-way randomized block design to evaluate presence of each nutrient, most common nutrient, and content of each nutrient on front of pack labels. Results revealed six significant and most common nutrient on cereals and products such as Energy, Protein, Fats, Carbohydrate, Sugar, Sodium and Saturated Fats compared to mineral, vitamins and other factors (P < 0.05). Over 70% of cereals and products having sugar, sodium and saturated fats (14.40 ± 15.65 g, 371.67 ± 278.75 mg and 6.61 ± 5.76 g respectively) beyond the FDA maximum limits of 2.5 g, 230 mg and 1 g. In light of these findings, authorities may require including and strengthening food quality monitoring programs to ensure supplies are within safe limits. Further research into developing a healthy food criteria model is recommended.
Unexpected contribution of cloud seeding to NPP increase during drought
Authors: Lee Munseok , Yoo Chulsang , Chang Ki-Ho 
Published: December 2023

Abstract
Cloud seeding is generally used to secure additional water resources, which is not an easy goal to achieve, as the spatial variability of rainfall is high. Instead, the increased rain may moisten the neighboring forest. This study focuses on this situation and estimates the possible increase in the net primary production (NPP) due to cloud seeding. This study considers the Boryeong Dam basin in Korea as a study area and uses the Carnegie–Ames–Stanford Approach (CASA) model to estimate the NPP at 8-day intervals. As a result, first, the increase of the current 8-day NPP is greater when the rainfall amount during the last 16-day period is 50 mm or more. The mean increase of the 8-day NPP is estimated at about 1.873 g/m2 of carbon. Second, the increase of the NPP with the target 16-day rainfall of 50 mm is estimated at about 3%, which is about 4% with the target 16-day rainfall of 100 mm. Simply extrapolating the derived result to the entire forest in Korea, the increased carbon accumulation can be extended to about 0.6 and 0.8% of the total carbon emission in 2018, respectively. These amounts correspond to about 1.2 and 1.5% of the target amount of carbon reduction by 2030 in Korea.
Impact of climate change on irrigation water requirements for coffee plants in the fruit development stage: a case study of Dak Lak and Gia Lai provinces in the Central Highlands of Vietnam
Authors: Tran Lap Quoc 
Published: December 2023

Abstract
This research investigates the impact of climate change on the irrigation water requirements for coffee plants in the fruit development stage in Gia Lai and Dak Lak provinces, Vietnam. Observation data were collected from four meteorological stations, namely, An Khe, Pleiku, Buon Ma Thuot, and Buon Ho. To simulate future scenarios, five CMIP6 models (BBC-CSM2-MR, CanESM5, GFDL-ESM4, MIROC6, and MPIESM1.2-HR) were used with the SSP24.5 scenario for the years 2030-2049 and 20802099. The irrigation water requirements were calculated by the Cropwat model version 8.0. For 2030-2049, the simulation results of BCC-CSM2-MR at An Khe showed the highest increase of approximately 90 mm, while CanESM5 displayed only a 4 mm rise. On the other hand, both MIROC6 and MPI-ESM1.2-HR indicated a slight reduction, ranging from 4 to 10 mm at all stations. For 20802099, the BBC-CSM2-MR model at An Khe recorded the highest increase of 100 mm, whereas the GFDL-ESM4 model showed a decline of 90 mm at Buon Ho. Other models showed a fluctuation increase from 40 to 60 mm. This means that climate change has a significant impact on the irrigation water requirements for coffee plants in the Central Highlands of Vietnam.
Research on optimal allocation of flow and head in cascade pumping stations based on Harris hawks optimization
Authors: Hou Xiaopeng , Zhang Leike , Liu Xiaolian , Wang Xueni , Tian Yu , Deng Xianyu , Ye Chen 
Published: December 2023

Abstract

To address the problems of massive energy consumption and low operating efficiency in cascade pumping stations (CPSs), an optimized scheduling model for CPSs with water flow and head constraints was constructed in this study. The Harris hawks optimization (HHO) algorithm was employed to solve this model owing to its excellent performance in the field of engineering majorization. Based on this model, an optimal scheduling method for CPSs was proposed and applied to the three-stage pumping station system. The results demonstrate that the optimization schemes based on the HHO algorithm can improve the operational efficiency and annual cost savings under three different pumping flow conditions by 0.16, 0.55, and 0.56%, reducing the annual operating cost by ¥22,703, ¥74,581, and ¥75,356, respectively, relative to the currently used schemes. These results are better than those obtained by the particle swarm optimization (PSO) algorithm and genetic algorithm (GA). Furthermore, in terms of computational time, the optimization method with the HHO algorithm can show an improvement of 8.94–29.74% compared with those of PSO and GA, verifying the feasibility and efficiency of the HHO algorithm in the optimal scheduling for CPSs. Therefore, the proposed method is effective at solving the scheduling problem of CPSs.
Variability of factors influencing coffee export performance in Indonesia.
Authors: Yanuarti Rizky , Widjaya Dani 
Published: December 2023

Abstract
Empirical evidence is lacking on the nexus between coffee commodity output and commodity price volatility of developing countries especially during pandemic era. The most visible impact from an economic perspective is the change of price expectation on people's basic needs which are in line with the decline of economic growth in Indonesia. This has significant implications, particularly considering the important role of coffee in supporting the country's economy. The aim of this study is to examine the factors that influence the performance of coffee exports in Indonesia. The novelty of this study lay on the used national dataset within the range of 20 years (2000-2020) and including the pandemic effect on coffee sector performance. We examines the relationship between variables and coffee exports in Indonesia using unit root tests, cointegration analysis, and an Error Correction Model (ECM). The results show that coffee exports, total area, coffee production, coffee price, gross national income, and coffee imports have significant influences on coffee exports. The variables of total area and coffee production impact coffee exports negatively in the long term, while coffee price, gross national income, and coffee imports have mixed effects. In the short term, total area and coffee production significantly affect coffee exports, while coffee prices and gross national income show no significant impact. Coffee imports have a significant negative influence on coffee exports in the short term. These findings contribute to understanding the dynamics of the coffee industry in Indonesia.
Time in Tight Glucose Range in Type 1 Diabetes: Predictive Factors and Achievable Targets in Real-World Users of the MiniMed 780G System
Authors: Castañeda Javier , Arrieta Arcelia , van den Heuvel Tim , Battelino Tadej , Cohen Ohad 
Published: December 2023

OBJECTIVE
We studied time in tight range (TITR) (70–140 mg/dL) in real-world users of the MiniMed 780G system (MM780G).

RESEARCH DESIGN AND METHODS
CareLink Personal data were extracted (August 2020 to December 2022) to examine TITR and its relationship with time in range (TIR; 70–180 mg/dL), factors predicting higher TITR, and which TITR target is a reasonable treatment goal.

RESULTS
The 13,461 users (3,762 age ≤15 years and 9,699 age &gt;15 years) showed an average TITR of 48.9% in those age ≤15 years and 48.8% in the older group (vs. TIR 71.2% and 73.9%, respectively). Consistent use of a glucose target (GT) of 100 mg/dL and active insulin time (AIT) of 2 h were the most relevant factors predicting higher TITR (P &lt; 0.0001). In users consistently applying these optimal settings, TITR was 56.7% in those age ≤15 years and 57.0% in the older group, and the relative impact of these settings on TITR was 60% and 86% greater than that on TIR, respectively. TITRs of ∼45% (age ≤15 years 46.3% and older group 45.4%), ∼50% (50.7% and 50.7%) and ∼55% (56.4% and 58.0%) were best associated with glucose management indicators &lt;7.0%, &lt;6.8%, and &lt;6.5%, respectively. TITRs of &gt;45%, &gt;50%, and &gt;55% were achieved in 91%, 74%, and 55% of those age ≤15 years and 93%, 81%, and 57% of older group users, respectively, at optimal settings.

CONCLUSIONS
This study demonstrates that 1) mean TIR is high with a high mean TITR in MM780G users (&gt;48%), 2) consistent use of optimal GT/AIT improves TITR (&gt;56%), 3) the impact of these settings on TITR is larger than on TIR, and 4) a TITR target &gt;50% is our suggested treatment goal.
Pengaruh Moralitas Individu, Kesesuaian Kompensasi, Proteksi Awig-Awig Desa Adat dan Asimetri Informasi terhadap Kecendrungan Kecurangan (Fraud) pada Lembaga Perkreditan Desa (LPD) di Kabupaten Buleleng
Authors: Cahyaningsih Ni Ketut , Atmadja Anantawikrama Tungga 
Published: December 2023

Abstract
This study aims to examine the effect of individual morality variables, compensation suitability, traditional village awig-awig protection and information asymmetry on the tendency of fraud at the Village Credit Institution (LDP) in Buleleng Regency. This study uses a quantitative approach. The research sample consisted of 64 respondents consisting of the Chair and staff of the LPD finance or bookkeeping department from 32 LPD samples in Buleleng Regency, which were determined by the Purposive Sampling method. The type of data used is a questionnaire distributed directly to the respondents. Technical analysis of the data used is multiple linear regression analysis and data presentation assisted by SPSS 26.0 for windows program. The results of this study indicate that individual morality has a negative and significant effect on the tendency of fraud at the Village Credit Institution (LPD), the suitability of compensation has a negative and significant effect on the tendency of fraud at the Village Credit Institution (LPD) for the protection of traditional village awig-awig. has a negative and significant effect on the tendency of fraud at the Village Credit Institution and information asymmetry has a positive and significant effect on the tendency of fraud at the Village Credit Institution (LPD) in Buleleng Regency.

Keywords : individual morality, compensation suitability, protection of traditional village awig-awig, information asymmetry, tendency to fraud
Pengaruh Pengetahuan, Kemudahan Penggunaan, dan Kredibilitas Terhadap Minat Penggunaan Quick Response Code Indonesian Standard (QRIS) (Studi Pada Generasi Z di Provinsi Bali)
Authors: Komang Erlita Agustina  , Lucy Sri Musmini  
Published: December 2023

Penelitian ini bertujuan untuk mengetahui pengaruh pengetahuan, kemudahan penggunaan dan kredibilitas terhadap minat penggunaan QRIS. Penelitian ini merupakan jenis penelitian kuantitatif dengan jumlah responden sebanyak 400 generasi Z di Provinsi Bali yang pernah menggunakan QRIS melalui aplikasi E-Wallet sebagai metode untuk transaksi pembayaran. Data diperoleh dengan menyebarkan kuesioner menggunakan media google form. Sampel dipilih menggunakan kriteria dengan teknik purposive sampling kemudian dihitung dengan rumus Slovin. Data yang digunakan adalah data primer berupa jawaban responden dan diolah menggunakan SPSS versi 26. Alat Uji data yang digunakan dalam penelitian ini adalah dengan uji kualitas data yang terdiri dari uji validitas dan uji reliabilitas. Setelah itu menggunakan pengujian asumsi klasik yang terdiri dari uji normalitas, uji multikolinearitas dan uji heteroskedastisitas. Pengujian hipotesis yang digunakan adalah uji T dan koefisien determinasi. Data dianalisis dengan metode analisis regresi linear berganda. Hasil penelitian ini menunjukkan bahwa pengetahuan, kemudahan penggunaan, dan kredibilitas secara parsial berpengaruh positif dan signifikan terhadap minat penggunaan QRIS.
Kata kunci: pengetahuan, kemudahan penggunaan, kredibilitas, minat penggunaan QRIS