Impact of socio-demographic structure of the deaf people communities in prevalence of hereditary hearing loss by O. L. Posukh, M. S. Bady-Khoo, M. V. Zytsar, V. Yu. Mikhalskaia, S. A. Lashin, N. A. Barashkov, G. P. Romanov

“…The start for these events was the breakdown of the deep social isolation of deaf people, which occurred about 300 years ago in Europe, and later in the US, when special schools for the deaf with learning sign language as a common tool for communication were established (linguistic homogamy). …”
Get full text

Keterlibatan Stakeholder Pada Strategi TI; Studi Pemetaan Sistematis by Hidayatul Aini Puteri, Apol Pribadi Subriadi

“…Abstract Studying stakeholders aims to explain how companies treat their stakeholders and the impact of their choices on the company's overall performance. Learning stakeholder strategies has been carried out in various fields. …”
Get full text

Clinical code usage in UK general practice: a cohort study exploring 18 conditions over 14 years by Christos Grigoroglou, Darren M Ashcroft, Evangelos Kontopantelis, David Reeves, Salwa S Zghebi, Rosa Parisi, Brian McMillan

“…Objective To assess the diagnostic Read code usage for 18 conditions by examining their frequency and diversity in UK primary care between 2000 and 2013.Design Population-based cohort studySetting 684 UK general practices contributing data to the Clinical Practice Research Datalink (CPRD) GOLD.Participants Patients with clinical codes for at least one of asthma, chronic obstructive pulmonary disease, diabetes, hypertension (HT), coronary heart disease, atrial fibrillation (AF), heart failure, stroke, hypothyroidism, chronic kidney disease, learning disability (LD), depression, dementia, epilepsy, severe mental illness (SMI), osteoarthritis, osteoporosis and cancer.Primary and secondary outcome measures For the frequency ranking of clinical codes, canonical correlation analysis was applied to correlations of clinical code usage of 1, 3 and 5 years. …”
Get full text

Integrating Infant Safe Sleep and Breastfeeding Education Into an App in a Novel Approach to Reaching High-Risk Populations: Prospective Observational Study by Tamar Krishnamurti, Rachel Moon, Rudolph Richichi, Rachel Berger

“…The primary outcome was engagement, defined as watching at least 1 video either in response to a push notification or directly from the app’s learning center. ResultsA total of 7572 pregnant persons were enrolled in the TodaysBaby Program—3308 with push notifications and 4264 without. …”
Get full text

Investigating Maps of Science Using Contextual Proximity of Citations Based on Deep Contextualized Word Representation by Muhammad Roman, Abdul Shahid, Shafiullah Khan, Lisu Yu, Muhammad Asif, Yazeed Yasin Ghadi

“…For automated classification, we need to train deep learning models, which take the citation context as input and provides the reason for citing a paper. …”
Get full text

Hot and cold exposure triggers distinct transcriptional and behavioral responses in laboratory-inbred pond snails by Veronica Rivi, Anuradha Batabyal, Cristina Benatti, Fabio Tascedda, Johanna Maria Catharina Blom, Ken Lukowiak

“…., 4 ​°C and 30 ​°C), particularly in the context of learning and memory formation. We found that while short-term (1 ​h) cold exposure transiently upregulated the expression levels of HSP70 and HSP40 in the snail's central ring ganglia, prolonged cold exposure (24 ​h) resulted in a significant downregulation of LymMIPII and an upregulation of LymMIPR. …”
Get full text

Tropical Cyclone Size Prediction and Development of An Error Correction Method by Guo Ruichen, Xu Jing, Wang Yuqing

“…Based on this relationship, a machine learning model, XGBoost, is used to develop an R17 size correction scheme that incorporate initial and forecast intensity, inner-core and outer-core sizes, and initial errors as predictors to estimate and correct model-predicted size errors. …”
Get full text

Identification and validation of a prognostic risk model based on radiosensitivity-related genes in nasopharyngeal carcinoma by Yi Li, Xinyi Hong, Wenqian Xu, Jinhong Guo, Yongyuan Su, Haolan Li, Yingjie Xie, Xing Chen, Xiong Zheng, Sufang Qiu

“…Differentially expressed genes (DEGs) were identified between radiotherapy-sensitive and resistant samples. Machine learning algorithms and Cox regression were used to construct a prognostic risk model, validated in the GSE102349 dataset. …”
Get full text

Methodology for adapting a co-created early childhood development intervention and implementation strategies for use by frontline workers in India and Guatemala: a systematic appli... by Amruta Bandal, Sara Hernández, Revan Mustafa, Karyn Choy, Namrata Edwards, Magdalena Guarchaj, Marinés Mejía Alvarez, Anushree Sane, Scott Tschida, Chetna Maliye, Ann Miller, Abhishek Raut, Roopa Srinivasan, Morgan Turner, Bradley H. Wagenaar, Ilgi Ertem, Maria del Pilar Grazioso, Subodh S. Gupta, Vibha Krishnamurthy, Peter Rohloff

“…Final adaptations included: refining training techniques to match skill levels and learning styles of frontline workers; tailoring all visual materials to local languages and contexts; design of job aids for providing developmental support messages; modification of referral and triage processes for children in need of enhanced support and speciality referral; and creation of post-training support procedures. …”
Get full text

Exploring Magnetic Fields in Molecular Clouds through Denoising Diffusion Probabilistic Models by Duo Xu, Jenna Karcheski, Chi-Yan Law, Ye Zhu, Chia-Jung Hsu, Jonathan C. Tan

“…We present a machine learning approach using denoising diffusion probabilistic models (DDPMs) to estimate magnetic field strength from synthetic observables such as column density, orientation angles of the dust continuum polarization vector, and line-of-sight (LOS) nonthermal velocity dispersion. …”
Get full text

Diagnostic impact of DNA methylation classification in adult and pediatric CNS tumors by Laetitia Lebrun, Nathalie Gilis, Manon Dausort, Chloé Gillard, Stefan Rusu, Karim Slimani, Olivier De Witte, Fabienne Escande, Florence Lefranc, Nicky D’Haene, Claude Alain Maurage, Isabelle Salmon

“…DNA methylation classification has emerged as a powerful machine learning approach for clinical decision-making in CNS tumors. …”
Get full text

Inhibition of tumour necrosis factor alpha by Etanercept attenuates Shiga toxin-induced brain pathology by Robin Christ, Devon Siemes, Shuo Zhao, Lars Widera, Philippa Spangenberg, Julia Lill, Stephanie Thiebes, Jenny Bottek, Lars Borgards, Andreia G. Pinho, Nuno A. Silva, Susana Monteiro, Selina K. Jorch, Matthias Gunzer, Bente Siebels, Hannah Voss, Hartmut Schlüter, Olga Shevchuk, Jianxu Chen, Daniel R. Engel

“…Analysis of microglial populations using a novel human-in-the-loop deep learning algorithm for the segmentation of microscopic imaging data indicated specific morphological changes, which were reduced to healthy condition after inhibition of TNF-α. …”
Get full text

Intelligent Electrochemical Sensing: A New Frontier in On-the-Fly Coffee Quality Assessment by Simone Grasso, Maria Vittoria Di Loreto, Alessandro Zompanti, Davide Ciarrocchi, Laura De Gara, Giorgio Pennazza, Luca Vollero, Marco Santonico

“…A specific experimental setup has been designed, and the data has been analyzed using machine learning techniques. The results obtained from Principal Component Analysis (PCA) and Partial Least Square Discriminant Analysis (PLS-DA) show the sensor’s capability to distinguish between samples of different quality, with a percentage of correct classification of 86.6%. …”
Get full text

In Vivo Plasticity at Hippocampal Schaffer Collateral-CA1 Synapses: Replicability of the LTP Response and Pharmacology in the Long-Evans Rat by A. Ahnaou, E. White, R. Biermans, N. V. Manyakov, W. H. I. M. Drinkenburg

“…Synaptic plasticity, encompassing long-term potentiation (LTP), is believed to underlie mechanisms of learning and memory. The present study was undertaken in Long-Evans (LE) rats, a strain of rat commonly used in cognitive behavioral tests, to (1) compare three LTP tetanisation protocols, namely, the high-frequency stimulation (HFS), the theta-burst stimulation (TBS), and the paired-pulse facilitation (PPF) at the Schaffer collateral-CA1 stratum radiatum synapse and to (2) assess sensitivity to acute pharmacology. …”
Get full text

Neural network based classification of rock properties and seismic vulnerability by U. Muksin, E. Riana, A. Rudiyanto, K. Bauer, A.V.H. Simanjuntak, M. Weber

“…Neural network was then applied to adaptively cluster and map the geophysical parameters. Four learning model clusters were developed from the three input seismic parameters: shear wave velocity, peak amplitude, and dominant frequency.FINDINGS: Generally, the values of the horizontal to vertical spectral ratios in the west of the study area were low (less than 5) compared with those in the southeastern part. …”
Get full text

A Method for Quantifying Mung Bean Field Planting Layouts Using UAV Images and an Improved YOLOv8-obb Model by Kun Yang, Xiaohua Sun, Ruofan Li, Zhenxue He, Xinxin Wang, Chao Wang, Bin Wang, Fushun Wang, Hongquan Liu

“…Traditional information extraction methods are often hindered by engineering workloads, time consumption, and labor costs. Applying deep-learning technologies for information extraction reduces these burdens and yields precise and reliable results, enabling a visual analysis of seedling distribution. …”
Get full text

Neuroanatomical and functional substrates of the short video addiction and its association with brain transcriptomic and cellular architecture by Yuanyuan Gao, Ying Hu, Jinlian Wang, Chang Liu, Hohjin Im, Weipeng Jin, Wenwei Zhu, Wei Ge, Guang Zhao, Qiong Yao, Pinchun Wang, Manman Zhang, Xin Niu, Qinghua He, Qiang Wang

Get full text

Possible Usefulness of Gadolinium-Enhanced Brain MRI for Evaluating Risk of Perioperative Hemorrhage: A Case of Infective Endocarditis by Chikahiko Koeda, Atsushi Tashiro, Tomohiro Takahashi, Masanobu Niiyama, Ryohei Sakamoto, Takumi Kimura, Yoshihiro Morino, Katsutoshi Terui, Ryoichi Tanaka, Kunihiro Yoshioka, Hajime Kin, Hitoshi Okabayashi, Motoyuki Nakamura

“…This case suggests that disappearance of the contrast media enhancement effect around the black dots may be a useful marker for optimal timing of surgery to minimize the risk of perioperative cerebral hemorrhage in patients with IE. Learning Objective. The MRI T2* weighted images including those with Gd contrast medium enhancement effect may be useful for evaluating the risk of perioperative intracranial hemorrhage in IE.…”
Get full text

A novel multi-source data-driven energy consumption prediction model for Venlo-type greenhouses in China by Yangda Chen, Aiqun Bao, Yapeng Li, Yingfeng Xiang, Wanlong Cai, Zhaoqiang Xia, Jialei Li, Mingyang Ning, Jing Sun, Haixi Zhang, Xianpeng Sun, Xiaoming Wei

“…To overcome the challenges concerning heterogeneity, redundancy, and interdependence among different data sources, this paper proposed a novel energy consumption method that integrates multi-source data through feature engineering and machine learning techniques, which significantly enhances the efficiency of data utilization and improves prediction accuracy. …”
Get full text

Modified sutureless and glue-free method versus conventional sutures for conjunctival autograft fixation in primary pterygium surgery: a systematic review and meta-analysis by Faisal Aljahdali, Waleed Khayyat, Abdulelah T BinYamin, Sultan A Al-Qahtani, Mohammed D Alghamdi, Ali Saleh Alsudais, Husain A Alalgum, Halah Bin Helayel, Mohammed AlMutlak

“…However, CS is linked to a higher likelihood of experiencing foreign body sensations. Understanding the learning curve and surgeon familiarity with novel techniques is crucial for optimising patient care and surgical outcomes, while individualised decision-making is necessary considering the advantages and disadvantages of each approach. …”
Get full text