Effects of a Smartphone-Based Breastfeeding Coparenting Intervention Program on Breastfeeding-Related Outcomes in Couples During First Pregnancy: Randomized Controlled Trial by Yi-Yan Huang, Rong Wang, Wei-Peng Huang, Tian Wu, Shi-Yun Wang, Sharon R. Redding, Yan-Qiong Ouyang

“…Data on exclusive breastfeeding rate and exclusive breastfeeding duration were analyzed using the chi-square, Fisher exact, or Mann-Whitney U tests; coparenting relationships and the infant’s BMI were analyzed using an independent samples t test; and breastfeeding knowledge, parenting sense of competence, and depressive symptoms were analyzed using a generalized estimation equation. …”
Get full text

Efficacy of a Mobile Health–Based Behavioral Treatment for Lifestyle Modification in Type 2 Diabetes Self-Management: Greenhabit Randomized Controlled Trial by Ana Maria Ruiz-Leon, Rosa Casas, Sara Castro-Barquero, Sofia Alfaro-González, Petia Radeva, Emilio Sacanella, Francesc Casanovas-Garriga, Ainhoa Pérez-Gesalí, Ramon Estruch

“…Data on nutrition, anthropometrics, and blood and urine samples were collected at baseline, 6 weeks, and 12 weeks. …”
Get full text

Exploring the efficacy and safety of Yu-Ping-Feng powder with variation against allergic rhinitis: a randomized, double-blind, placebo-controlled trial by Zhi-Xiu Lin, Tin Muk Ho, Yan-Fang Xian, Kam Leung Chan, Qing-Qing Xu, Cho Wing Lo, Justin Che Yuen Wu, Kam Lun Hon, Sin Bond Leung, Chon Pin Chia, Chi Him Sum, Tak Yee Chow, Pui Kuan Cheong, Jessica Yuet Ling Ching, Hongwei Zhang, Ka Chun Leung, Wai Ling Lin

“…Purpose To evaluate the efficacy and safety of YPV on AR patients with the lung and spleen Qi deficiency type using a randomized, double-blind, placebo-controlled clinical trial (RCT). …”
Get full text

Migraine triggers, phases, and classification using machine learning models by Anusha Reddy, Ajit Reddy

“…The precision and accuracy obtained by the support vector machine and artificial neural network are 91% compared to logistic regression (90%) and random forest (87%). These models are run with the dataset without optimal tuning across the entire dataset for different migraine types; which is further improved with selective sampling and optimal tuning. …”
Get full text

A prospective single center non randomized clinical trial of autologous skin cells with platelet rich plasma for diabetic ulcer and trauma injuries patients by Nur Hakimin Bin Md Noorpi, Mohd Yazid Bin Bajuri, Norliyana Binti Mazli, Ruszymah Binti Hj Idrus, Angela Ng Min Hwei, Jia Xian Law

“…The study enrolled total of 7 participants, 2 with traumatic wounds and 5 with diabetic ulcers, using random sampling. After obtaining informed consent, a 1 cm2 skin biopsy was harvested from a concealed area. …”
Get full text

Community re-entry program on global functioning and medication adherence among bipolar affective disorder patients- A randomized controlled trial pilot study by Jaishri, Sreevani Rentala, Preethy Kathiresan, Mukesh Swami

“…The present study was done at the in-patient department of the tertiary care academic institute, Jodhpur. Samples N = 50 (25 + 25) were selected through consecutive sampling techniques and randomly assigned to intervention and control groups. …”
Get full text

Accurately Estimating Correlations Between Demographic Parameters: A Response to Riecke Et al. (2024) by Cody E. Deane, Lindsay G. Carlson, Curry J. Cunningham, Pat Doak, Knut Kielland, Greg A. Breed

“…Deane et al. (2023) evaluated the bias and certainty of correlation parameters between recovery and survival probabilities estimated as random effects drawn from bivariate normal distributions relative to different prior distributions and sample size combinations. …”
Get full text

Path Planning of Intelligent Mobile Robots with an Improved RRT Algorithm by Wenliang Zhu, Guanming Qiu

“…Addressing issues such as pronounced randomness, low search efficiency, inefficient utilization of effective points, suboptimal path smoothness, and potential deviations from the optimal path in the RRT algorithm based on random sampling, we proposed an optimization algorithm that integrates Kalman filtering to eliminate redundant points along the path. …”
Get full text

Heart Rate Variability (HRV) as a Marker of Improved Autonomic Function in PMS: A Homeopathy Intervention-Based Single Blind Randomized Control Study by Nayana P. Barde, Pradip B. Barde, Ajay O. Dahad, Tripathi Shatrugan, Anagha Kulkarni, Tapas K. Kundu

Get full text

How Representative Are Uncrewed Aircraft System Measurements of the Convective Boundary Layer? by Brian R. Greene, Leia M. Otterstatter, Scott T. Salesky

“…Errors are on the order of 2–6 m s−1 for wind speed, 15–60° for wind direction, 0.2–3 K for potential temperature, and 0.1–1 g kg−1 for specific humidity, with errors in turbulent fluxes on the order of 50%–100%. Sampling strategies that mitigate random errors are discussed in light of our results.…”
Get full text

Non-Immersive Virtual Reality Exercise Can Increase Exercise in Older Adults Living in the Community and in Long-Term Care: A Randomized Controlled Trial by Sheehy L, Bharadwaj L, Nissen KA, Estey JL

“…Lisa Sheehy,1 Lalita Bharadwaj,2 Kelsey Annie Nissen,2 Justine L Estey2 1Bruyère Health Research Institute, Ottawa, Ontario, Canada; 2Centre for Innovation and Research in Aging, Fredericton, New Brunswick, CanadaCorrespondence: Lisa Sheehy, Bruyère Health Research Institute, 43 Bruyère St, Ottawa, ON, K1N 5C8, Canada, Tel +01 613 562 6262 ext. 1593, Email lsheehy@bruyere.orgPurpose: To assess the impact of an 8-week non-immersive virtual reality exercise program for older adults on 1) balance, physical function, community integration and quality of life; 2) falls, emergency room visits, hospital and long-term care admissions; 3) quantity of exercise performed; and 4) acceptance of non-immersive virtual reality.Patients and Methods: This prospective, assessor-blinded, randomized controlled trial was carried out on two separate samples of older adults: those living in their own homes (“home-based”) and those living in long-term care (“facility-based”). …”
Get full text

Determinants and risk prediction models for frailty among community-living older adults in eastern China by Lin Qi, Lin Qi, Jianyu Liu, Xuhui Song, Xinle Wang, Mengmeng Yang, Xinyi Cao, Yan He

“…Predictive models were constructed using decision trees, random forests, and XGBoost algorithms, implemented in R software (version 4.4.2). …”
Get full text

Layered Soil Moisture Retrieval and Agricultural Application Based on Multi-Source Remote Sensing and Vegetation Suppression Technology: A Case Study of Youyi Farm, China by Zhonghe Zhao, Yuyang Li, Kun Liu, Chunsheng Wu, Bowei Yu, Gaohuan Liu, Youxiao Wang

“…This study proposes a multi-modal remote sensing collaborative retrieval framework that integrates UAV-based multispectral imagery, Sentinel-1 radar data, and in situ ground sampling. By incorporating a vegetation suppression technique, a random-forest-based quantitative soil moisture model was constructed to specifically address the interference caused by dense vegetation during crop growing seasons. …”
Get full text

Investment Portfolio Allocation and Insurance Solvency: New Evidence from Insurance Groups in the Era of Solvency II by Thomas Poufinas, Evangelia Siopi

Get full text

NeuAFG: Neural Network-Based Analog Function Generator for Inference in CIM by Pengcheng Feng, Yihao Chen, Jinke Yu, Zhelong Jiang, Junjia Su, Qian Zhou, Hao Yue, Zhigang Li, Haifang Jian, Huaxiang Lu, Wan'Ang Xiao, Gang Chen

“…Resistive Random-Access Memory (RRAM)-based Compute-in-Memory (CIM) architectures offer promising solutions for energy-efficient deep neural network (DNN) inference. …”
Get full text

Support Vector Machines and Model Selection for Control Chart Pattern Recognition by Chih-Jen Su, I-Fei Chen, Tzong-Ru Tsai, Tzu-Hsuan Wang, Yuhlong Lio

“…The three CCPR approaches can save sample resources in the initial process monitoring, improve the weak learner’s ability to recognize non-normal data, and include normality as a special case. …”
Get full text

Forecasting Ultrafine Dust Concentrations in Seoul: A Machine Learning Approach by Sophia Park, Myeong Jun Kim

“…This study applied various machine learning techniques, including shrinkage methods, XGBoost, CSR, and random forest, to forecast ultrafine particulate matter (PM2.5) concentrations in Seoul, South Korea. …”
Get full text

Discrimination of Customers Decision-Making in a Like/Dislike Shopping Activity Based on Genders: A Neuromarketing Study by Atefe Hassani, Amin Hekmatmanesh, Ali Motie Nasrabadi

“…In addition, the most distinctive features for males were sample and approximate entropy, as well as the Higuchi fractal dimension that with the RF classifier produced an accuracy rate of 71.33± 14.07%. …”
Get full text

Enhanced Subspace Iteration Technique for Probabilistic Modal Analysis of Statically Indeterminate Structures by Hongfei Cao, Xi Peng, Bin Xu, Fengjiang Qin, Qiuwei Yang

“…When the complete analysis is applied to calculate the vibration modes for each sample of the stochastic finite element model, a substantial computational expense is incurred. …”
Get full text

Prediction of the strength characteristics of basalt fibre reinforced concrete using explainable machine learning models by B. Y. Wickramasuriya, Yasitha Alahakoon, B. R. G. A. Krishantha, Janaka Alawatugoda, I. U. Ekanayake

“…Three datasets, each with 267 samples, were used for model development. Each sample included 10 features: cement, fly ash, silica ash, coarse aggregate, fine aggregate, water, superplasticiser, fibre diameter, fibre length, and fibre content. …”
Get full text