A Bibliometric Analysis of Macrophage Research Associated with Periodontitis Over the Past Two Decades by Yu Qiu, Zhenzhen Ding, Deqin Yang

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Tackling Heterogeneous Light Detection and Ranging-Camera Alignment Challenges in Dynamic Environments: A Review for Object Detection by Yujing Wang, Abdul Hadi Abd Rahman, Fadilla ’Atyka Nor Rashid, Mohamad Khairulamirin Md Razali

“…These sensors produce heterogeneous data due to differences in data format, spatial resolution, and environmental responsiveness. …”
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Pseudonymization tools for medical research: a systematic review by Hammam Abu Attieh, Armin Müller, Felix Nikolaus Wirth, Fabian Prasser

“…Abstract Background Pseudonymization is an important technique for the secure and compliant use of medical data in research. At its core, pseudonymization is a process in which directly identifying information is separated from medical research data. …”
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Near‐Surface Air Temperature Profile in Maritime Antarctica (2006–2023) by Miguel Angel dePablo

“…Raw data in American Standard Code for Information Interchange (ASCII) format, without filtering or preprocessing, are made available to ensure flexibility for diverse research needs, allowing users to apply tailored cleaning and analysis protocols. …”
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Study of Multivariate Background Error Characteristics of Convective System on Plateau Slope and Typhoon System Based on Convective-Scale Ensemble Samples by Wanli ZHANG, Yuanbing WANG, Rou LI, Yaodeng CHEN, Deming MENG, Xinyao QIAN, Xili JIN

“…The effective assimilation of observation data in the slope areas of the Qinghai-Xizang （Tibetan） Plateau and typhoon systems has a significant impact on the capabilities of weather forecasting in China， with background error being a key factor affecting the performance of data assimilation.The purpose of this study is to gain a deeper understanding of the characteristics of background errors in conventional control variables and hydrometeor control variables within convective systems on the slopes of the Qinghai-Xizang （Tibetan） Plateau and typhoon systems， so as to develop the data assimilation scheme which is applicable to the convective systems on the slopes of the Qinghai-Xizang （Tibetan） Plateau and typhoon systems.This study employs the Ensemble Transform Kalman Filter （ETKF） and the hybrid Ensemble-Variational data assimilation method to update the ensemble perturbation and the ensemble mean respectively to produce convective-scale ensemble forecast samples with 80 ensemble members and 4-kilometers resolution.This study focuses on cases of convective weather from the northeast slope of the Qinghai-Xizang （Tibetan） Plateau in mid-August 2022 and Typhoon "Meihua"， the 12th typhoon of 2022.Multivariate background error covariances， including those for multiphase hydrometeor and vertical velocity， were computed through physical transformation， vertical transformation， and horizontal transformation.Analyses of the spatial error characteristics， including the eigenvalues， eigenvectors， and characteristic length scales were conducted， and the results of the analyses indicate that background errors are more pronounced in the case of convective system on the slope of the Qinghai-Xizang （Tibetan） Plateau in comparison to the typhoon system.At the same time， the simulation of hydrometeor variables and vertical velocity is less precise in the case of convective system on the slope of the Qinghai-Xizang （Tibetan） Plateau compared to the typhoon system.In the context of data assimilation for these comparable convective systems， the analysis tends to be more aligned with observations and less so with the background， this feature highlights the necessity for high-quality and comprehensive observations in the slope areas of the Qinghai-Xizang （Tibetan） Plateau.In addition， the atmospheric characteristics and the horizontal scale of hydrometeor variables and vertical velocity in the case of convective system on the slope of the Qinghai-Xizang （Tibetan） Plateau display smaller and more localized features compared with those observed in the typhoon system.Moreover， hydrometeor control variables and the vertical velocity exhibit smaller horizontal scales and more pronounced localized characteristics compared to conventional control variables， therefore potentially leading to the influence range of observations and information related to hydrometeor control variables in the slope areas of the Qinghai-Xizang （Tibetan） Plateau relatively limited in the context of the subsequent assimilation analysis.…”
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GA4RF: An Effective Fall Detection System Through Optimizing Random Forest Hyperparameters Using Genetic Algorithm With Mobile Sensor Data by Ha-Nam Nguyen, Hong-Lam Le, Ngo-Thi-Thu-Trang, Duc-Nhan Nguyen

“…These results indicate that GA4RF is a promising approach for improving FDS, especially when dealing with highly imbalanced data and meeting performance requirements in real-world applications.…”
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Intelligent Functional Clustering and Spatial Interactions of Urban Freight System: A Data-Driven Framework for Decoding Heavy-Duty Truck Behavioral Heterogeneity by Ruixu Pan, Quan Yuan, Chen Liu, Jiaming Cao, Xingyu Liang

“…Against this backdrop, this study develops a data-driven framework to analyze HDT behavioral heterogeneity and its spatial interactions with a freight functional zone in Shanghai. …”
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Advancing automatic speech recognition for low-resource ghanaian languages: Audio datasets for Akan, Ewe, Dagbani, Dagaare, and IkposoScience Data Bank by Isaac Wiafe, Jamal-Deen Abdulai, Akon Obu Ekpezu, Raynard Dodzi Helegah, Elikem Doe Atsakpo, Charles Nutrokpor, Fiifi Baffoe Payin Winful, Kafui Kwashie Solaga

“…Ethical guidelines were strictly followed throughout the data collection process and participants were given incentives for lending their voices to this study.…”
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Crop classification in Google Earth Engine: leveraging Sentinel-1, Sentinel-2, European CAP data, and object-based machine-learning approaches by Marco Vizzari, Giacomo Lesti, Siham Acharki

“…This methodology employed spectral bands, spectral indices (Normalized Difference Vegetation Index and Modified Radar Vegetation Index), and textural information (Gray-Level Co-occurrence Matrix) derived from Sentinel-2 L2A (S2) and Sentinel-1 GRD (S1) data within the GEE platform. Moreover, European Common Agricultural Policy (CAP) data associated with cadastral parcels were employed and served as ground information during the training and validation stages. …”
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Distributions of Ion Density Irregularities and Their Gradients Inside Low‐Latitude Ionospheric Plasma Bubbles Based on C/NOFS Planar Langmuir Probe Data by Emanoel Costa, Patrick A. Roddy, John O. Ballenthin

“…Abstract Data from the planar Langmuir probe onboard the Communication/Navigation Outage Forecasting System has been processed, with focus on the: (1) identification of Equatorial Plasma Bubbles located within the eclipse sections of the satellite orbits; (2) subdivision of each Equatorial Plasma Bubble into three sections (West Wall, Center, and East Wall); and (3) statistical analyses of the standard deviations and gradients of ion density data for each section. …”
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Determining factors affecting the accuracy of SEM-EDX data-based quantitative chemical analysis for identifying naturally occurring individual carcinogenic erionite fibers by Wenxia Wendy Fan, Alessandro F. Gualtieri, Ayrton Hamilton, Janki P. Patel, Jennifer A. Salmond

“…SEM-EDXA results were compared with previously acquired EPMA reference data from the bulk sample to assess analytical accuracy. …”
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Predicting Cervical Lymph Node Metastasis Using Preoperative Multiparameter Data Based on Imaging, Serology, and Clinical Features in Unifocal Papillary Thyroid Carcinoma by Junlin HE, Wenjing CHEN, Lili HU, Yongsheng WANG, Jing CHEN, Ming WU

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Changing practice in cystic fibrosis: Implementing objective medication adherence data at every consultation, a learning health system and quality improvement collaborative by Carla Girling, India Davids, Nikki Totton, Madelynne A. Arden, Daniel Hind, Martin J. Wildman

“…An online application (CFHealthHub) has been designed to deliver these data to people with CF and their clinical team. …”
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Ligand-receptor dynamics in heterophily-aware graph neural networks for enhanced cell type prediction from single-cell RNA-seq data by Lian Duan, Mahshad Hashemi, Alioune Ngom, Luis Rueda

“…In this context, Our work explores the application of GNNs to single-cell RNA sequencing (scRNA-seq) data, a domain characterized by complex and heterogeneous relationships. …”
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High-Precision Permeability Evaluation of Complex Carbonate Reservoirs in Marine Environments: Integration of Gaussian Distribution and Thomeer Model Using NMR Logging Data by Hengyang Lv, Jianhong Guo, Baoxiang Gu, Yuhan Liu, Li Wang, Long Wang, Zuomin Zhu, Zhansong Zhang

“…Among the available techniques, permeability assessment based on nuclear magnetic resonance (NMR) logging data is one of the most widely used and precise methods. …”
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Three-dimensional visual technique based on CT lymphography data combined with methylene blue in endoscopic sentinel lymph node biopsy for breast cancer by Baiye Wang, Caifeng Ou, Jingang Yu, Jianping Ye, Yunfeng Luo, Yu Wang, Pusheng Zhang

“…Abstract Background The combined application of blue dye and radioisotopes is currently the primary mapping technique used for sentinel lymph node biopsy (SLNB) in breast cancer patients. …”
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Detection of the stem-boring damage by pine shoot beetle (Tomicus spp.) to Yunan pine (Pinus yunnanensis Franch.) using UAV hyperspectral data by Meng-Ying Liu, Guang-Yun Li, Lei Shi, Ya-Ying Li, Huai Liu

“…However, there is a lack of studies investigating the application and accuracy of UAV hyperspectral data for detecting PSB stem-boring damage.MethodsIn this study, we compared the differences in spectral features of healthy pines (H level), three levels of shoot-feeding damage (E, M and S levels), and the stem-boring damage (T level), and then used the Random Forest (RF) algorithm for detecting stem-boring damage by PSB.ResultsThe specific canopy spectral features, including red edge (such as Dr, SDr, and D711), blue edge (such as Db and SDb), and chlorophyll-related spectral indices (e.g., MCARI) were sensitive to PSB stem-boring damage. …”
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Assessing the temporal transferability of machine learning models for predicting processing pea yield and quality using Sentinel-2 and ERA5-land data by Michele Croci, Manuele Ragazzi, Alessandro Grassi, Giorgio Impollonia, Stefano Amaducci

“…It is recommended that future work focus on more robust approaches, such as models designed for temporal data (e.g., RNNs, Transformers) and higher-resolution data, to bridge the gap towards reliable real-world application.…”
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Improving the Transparency of Data Access Conditions in the SSH Domain: Recommendations based on a small-scale analysis of the conditions applied to restricted access datasets by Deborah Thorpe, Ricarda Braukmann, Angelica Maineri

“…Decisions are said to require an evaluation of the quality of the application, yet the evaluation criteria seem to be rarely specified and explicitly communicated at the time of data deposit. …”
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Melt Density Monitoring of Extruder Extrusion Process Based on Multi-source Data Fusion and Convolutional Long Short-term Memory Neural Network by Binbin ZHANG, Zhuyun CHEN, Fei ZHANG, Gang JIN

“…The proposed model effectively learns the intricate mapping relationship between sensory data and melt density by amalgamating these multi-source sensory inputs and using the feature extraction capabilities of convolutional neural networks and the temporal dependencies modeling capabilities of LSTM networks.Results and Discussions The application of the proposed method demonstrates significant efficiency in real-time monitoring of polymer melt density by monitoring the melt density during the PC/ABS blending extrusion process. …”
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