Digital Economy, Consumption Upgrading and Domestic Demand Level: An Empirical Analysis of PVAR Based on Provincial Panel Data by Jianhong Fan, Jiaxuan Zhang, Huichao Wu, Chen Liang

“…This study selects provincial panel data from 2008 to 2019 and constructs a panel vector autoregressive (PVAR) model to explore the bidirectional interactive relationship between digital economy, consumption upgrading and domestic demand level through the Granger causality test, the analysis of impulse response function and variance decomposition. …”
Get full text

Examining Nasdaq Market Data and Presenting an Optimized Model by Extreme Gradient Boosting Regression and Artificial Bee Colony by Ali Ahmadpour

“…Stock price prediction is a critical task in the financial sector due to its profound implications for traders and investors. This paper presents a comparative analysis of machine learning models applied to stock price prediction using historical data from the Nasdaq stock index spanning the years 2015 to 2023. …”
Get full text

Nature, sector, and GVC participation of firms: empirical insights from firm-level data in selected SSA countries by Alhassan Abdul-Wakeel Karakara, Camara Kwasi Obeng, Mark Kojo Armah, Jacob Nunoo

“…We employ the logit model and the Enterprise Survey data for four sub-Saharan African countries, namely Gambia, Kenya, Rwanda, and Zambia. …”
Get full text

Tactics and strategy analysis in professional badminton: insights from match data and performance metrics- a systematic review by Eval Edmizal, Dally Rahman, Eri Barlian, Donie Donie, Alnedral Alnedral

“…This study uses match data and performance metrics as the primary evaluation tools. …”
Get full text

Optimization of Lecturers' Understanding of OBE Curriculum and 4 Literacies (Human, Language, Data, Digital) at State University of Medan by Abil Mansyur, Fajar Apollo Sinaga, Muliawan Firdaus, Maya Octora, Marlan Marlan, Tiur Malasari Siregar

“…In the modern era of education, the implementation of the Outcome-Based Education (OBE) Curriculum and the mastery of four key literacies, human, language, data, and digital literacy are urgent needs for educators in higher education institutions. …”
Get full text

High global consumption of potentially inappropriate fixed dose combination antibiotics: Analysis of data from 75 countries. by Barbara Bortone, Charlotte Jackson, Yingfen Hsia, Julia Bielicki, Nicola Magrini, Mike Sharland

“…However, high use of potentially inappropriate FDCs has been reported, with implications for antimicrobial resistance (AMR) and toxicity. …”
Get full text

A Distributed Privacy Preserved Federated Learning Approach for Revolutionizing Pneumonia Detection in Isolated Heterogenous Data Silos by Shagun Sharma, Kalpna Guleria

“…The misdiagnosis results in increased healthcare costs, worsened medical conditions, and legal implications. Centralized deep learning enhances the feature extraction process and optimally improves the prediction outcomes; however, these models have data privacy concerns due to centralized storage systems. …”
Get full text

Private sensors and crowdsourced rainfall data: Accuracy and potential for modelling pluvial flooding in urban areas of Oslo, Norway by Kay Khaing Kyaw, Emma Baietti, Cristian Lussana, Valerio Luzzi, Paolo Mazzoli, Stefano Bagli, Attilio Castellarin

“…Cloudbursts and extreme rainstorms pose a growing threat to urban areas. Accurate rainfall data is essential for predicting inundations and urban flooding. …”
Get full text

Assessing Driving Risk Level: Harnessing Deep Learning Hybrid Model With Intercity Bus Naturalistic Driving Data by Wei-Hsun Lee, Che-Yu Chang

“…By collecting naturalistic driving data from intercity buses, the model is trained on an extensive dataset featuring 27,057 journey-based instances, incorporating dynamic GPS data and static journey background information from over 300 drivers. …”
Get full text

Data stochasticity and model parametrisation impact the performance of species distribution models: insights from a simulation study by Lambert, Charlotte, Virgili, Auriane

“…SDM can be implemented with a wide array of data types (presence-only, presence-absence, count...), which can either be point- or areal-based, and use a wide array of environmental conditions as predictor variables. …”
Get full text

Sharing individual participant data from clinical trials: an opinion survey regarding the establishment of a central repository. by Catrin Tudur Smith, Kerry Dwan, Douglas G Altman, Mike Clarke, Richard Riley, Paula R Williamson

“…The main concerns were gaining permission from trial data owners, uncertainty about the purpose of the repository, potential resource implications, and increased workload for IPD reviewers. …”
Get full text

An explainable machine learning framework for railway predictive maintenance using data streams from the metro operator of Portugal by Silvia García-Méndez, Francisco de Arriba-Pérez, Fátima Leal, Bruno Veloso, Benedita Malheiro, Juan Carlos Burguillo-Rial

“…This work contributes to a real-time data-driven predictive maintenance solution for Intelligent Transportation Systems. …”
Get full text

The Corona Warning App of the German Federal Government – How perceived data protection issues hindered any effectiveness by Robert MÜLLER-TÖRÖK, Alexander PROSSER

“…Approach We use statistical methods to show that, (i) even in the very best case with a perfectly working app the coverage would have been roughly half of all relevant encounters (ii) and that the voluntary usage of this app as well as the free decision of the infected individual to publish its (anonymized) data to warn others in fact reduces any effectiveness considerably. …”
Get full text

Variant calling from RNA-Seq data reveals allele-specific differential expression of pathogenic cancer variants by Audrey Bollas, Jeffrey Gaither, Kathleen M. Schieffer, Peter White, Elaine R. Mardis

“…Strikingly, this phenomenon is prevalent in cancer-driving genes, where VarRNA analysis of the RNA-Seq data reveals the variant allele expression as much higher than expected based on the exome sequencing data. …”
Get full text

Relation of cytokine profile and antibody values to post-translational protein modifications in patients with rheumatoid arthritis (preliminary data) by D. А. Dibrov, А. S. Avdeeva, М. Е. Diatroptov, V. V. Rybakova, Е. L. Nasonov

“…In anti-Carp(–) patients (n=73) higher values of IL-17 were recorded. Conclusion. Our data support the concept of RA heterogeneity, characterised by the existence of different clinical and immunological subtypes, which may have implications for improving personalised therapy.…”
Get full text

A Computational Framework for Revealing Competitive Travel Times with Low-Carbon Modes Based on Smartphone Data Collection by Mehrdad Bagheri, Milos N. Mladenovic, Iisakki Kosonen, Jukka K. Nurminen, Claudio Roncoli, Antti Ylä-Jääski

“…In particular, having more thorough data from large number of participants could provide implications for transportation researchers and planners to identify groups or areas for promoting mode shift. …”
Get full text

The Impact of WHO-2023 Malnutrition Criteria on Caseload of Infants Aged Under Six Months: Secondary Data Analysis by Ayenew Negesse, Tsinuel Girma, Beruk Berhanu Desalegn, Melkamu Berhane, Marko Kerac

“…Methods: We conducted a secondary analysis of data from 1048 Ethiopian infants u6m using STATA software version 17. …”
Get full text

The job performance and job burnout relationship: a panel data comparison of four groups of academics’ job performance by Miao Lei, Miao Lei, Gazi Mahabubul Alam, Karima Bashir, Karima Bashir

“…Provided here are applicable strategies aimed at preventing and maximizing job burnout crises before the job is taken and during its execution.MethodologyTo answer the research questions quantitatively, group regression analysis utilizing panel data from 2020 to 2023 was employed. The instruments include the KPI and mental health records to evaluate the level of job performance and job burnout. …”
Get full text

Diagnosis of Chronic Kidney Disease Using Retinal Imaging and Urine Dipstick Data: Multimodal Deep Learning Approach by Youngmin Bhak, Yu Ho Lee, Joonhyung Kim, Kiwon Lee, Daehwan Lee, Eun Chan Jang, Eunjeong Jang, Christopher Seungkyu Lee, Eun Seok Kang, Sehee Park, Hyun Wook Han, Sang Min Nam

“…MethodsThe 3 models were developed and validated: eGFR-RIDL (estimated glomerular filtration rate–retinal image deep learning), eGFR-UDLR (logistic regression using urine dipstick data), and eGFR-MMDL (multimodal deep learning combining retinal images and urine dipstick data). …”
Get full text

The Impact of Pose Alignment Errors on a Classical Late Infrastructure-Vehicle Collaboration Framework Using Experimental Data by Roshan George, Dara Molloy, Tim Brophy, William O'Grady, Darragh Mullins, Edward Jones, Brian Deegan, Martin Glavin

Get full text