bluuebunny/crossref_metadata_2025_split huggingface dataset:
Fault diagnosis of wind turbine with few-shot learning based on acoustic signal
Authors: Yang Shuai , Xu Hanfeng , Wang Yu , Chen Junhong , Li Chuan 
Published: January 2025

Abstract
Due to the harsh working conditions of wind turbines, it is difficult to obtain sufficient fault data from the gearbox. To address this issue, this study proposes a graph neural network model based on few-shot learning (GNN-FSL) for the fault diagnosis on planetary gears of wind turbine gearbox with acoustic signals. The short-time Fourier transform (STFT) is chosen for preprocessing of acoustic signals as input data, which converts the raw data into two-dimensional data. Then, convolutional neural networks (CNN) are used to extract data features. Finally, the extracted features are input for the graph neural network for fault classification. The experimental results show that the model performs well in fault classification on small sample datasets, providing an effective method for fault diagnosis of planetary gears in wind turbines. By comparing EfficientNet-b0, ResNet-50, Densenet121, Mobilenet_v2 and DiffKendall models, it is verified that the proposed method is effective in planetary gear fault classification, and its performance is superior to all these networks.
Electro-osmotic flow in channel: effects of superhydrophobic surface structures sizing
Authors: Jing Mei , Yu Kok Hwa , Aziz Mohd Sharizal Abdul , Chang Wei Shyang 
Published: January 2025

Abstract
Numerical study on electro-osmotic flow over superhydrophobic transverse grooves and ribs have been explored. With uncharged liquid-gas interface, smaller electro-osmotic axial flow is attained. The electro-osmotic axial flow is found to be significantly influenced by the gas area fraction and the normalized groove-rib spacing. In the presence of the liquid-gas interfaces, slip flows are observed over these interfaces, consistent with that reported in pressure-driven flow. As the flow is permitted in the vicinity of the liquid-gas interface, flow redistribution is observed along the channel. Higher bulk flow with reducing flow magnitude is observed close to the wall when solid wall is present, and vice versa. Despite the alteration of the axial flow, conservation of flow along axial direction is attained. To estimate the normalized electro-osmotic axial flow for this flow condition, a new correlation formulation is proposed to accurately predict the averaged axial flow magnitude for different values of gas area fraction and normalized groove-rib spacing in the range between 0.1 and 4.
3D Breast Scanning in Plastic Surgery Utilizing Free iPhone LiDAR Application: Evaluation, Potential, and Limitations
Authors: Kyriazidis Ioannis , Berner Juan Enrique , Waked Karl , Hamdi Moustapha 
Published: January 2025

Abstract

Background
Three-dimensional (3D) imaging enhances surgical planning and documentation in plastic surgery, but high costs limit accessibility. Mobile light detection and ranging (LiDAR) technology offers a potential cost-effective alternative.

Objectives
The objective of this research was to evaluate the accuracy and clinical utility of iPhone-based LiDAR scanning for breast measurements compared to traditional methods, and to establish standardized protocols for clinical implementation.

Methods
In this prospective validation study, 25 consecutive patients (mean age: 44 years; range: 32-64 years; mean BMI: 23.2 kg/m2) undergoing breast procedures were evaluated with the “3D Scanner App” on the iPhone 15 Pro (Apple Inc., Cupertino, CA). Three standardized measurements (sternal notch-to-nipple, nipple-to-midline, nipple-to-inframammary fold) of LiDAR and manual techniques were compared. Technical error of measurement (TEM) and relative TEM (rTEM) were calculated. Interrater reliability, learning curve assessment, and cost-effectiveness analysis were performed.

Results
LiDAR measurements showed very good accuracy for sternal notch-to-nipple (rTEM 1.43%, 95% CI: 1.21-1.65) and nipple-to-midline (rTEM 2.83%, 95% CI: 3.12-3.78) distances. Nipple-to-inframammary fold measurements showed poor accuracy (rTEM 13.05%, 95% CI: 8.21-9.39). Interrater reliability was excellent (ICC = 0.92). Learning curve analysis demonstrated measurement stability after 5 cases. Cost analysis revealed 97.8% reduction in initial investment compared to commercial 3D imaging systems.

Conclusions
Mobile LiDAR offers a cost-effective tool for breast surgery planning and documentation. While measurements like sternum-to-nipple and nipple-to-midline are highly accurate, the relatively poor accuracy of nipple-to-IMF highlights limitations with complex curves. As this technology continues to evolve, further improvements in accuracy are anticipated, expanding its role in clinical use.

Level of Evidence: 4 (Therapeutic)
KPRR: a novel machine learning approach for effectively capturing nonadditive effects in genomic prediction
Authors: Li Mianyan , Hall Thomas , MacHugh David E , Chen Liang , Garrick Dorian , Wang Lixian , Zhao Fuping 
Published: January 2025

Abstract
Nonadditive genetic effects pose significant challenges to traditional genomic selection methods for quantitative traits. Machine learning approaches, particularly kernel-based methods, offer promising solutions to overcome these limitations. In this study, we developed a novel machine learning method, KPRR, which integrated a polynomial kernel into ridge regression to effectively capture nonadditive genetic effects. The predictive performance and computational efficiency of KPRR were evaluated using six datasets from various species, encompassing a total of 18 traits. All the traits were known to be influenced by additive, dominance, or epistatic genetic effects. We compared the performance of KPRR against six other genomic prediction methods: SPVR, BayesB, GBLUP, GEBLUP, GDBLUP, and DeepGS. For datasets dominated by additive effects, KPRR achieved superior prediction accuracies in the wheat dataset and comparable performance in the cattle dataset when compared to GBLUP. For datasets influenced by dominance effects, KPRR matched GDBLUP in accuracies in the pig dataset and outperformed GDBLUP in the sheep dataset. For datasets exhibiting epistatic effects, KPRR outperformed other methods in some traits, while BayesB showed superior performance in others. Incorporating nonadditive effects into a GBLUP model led to overall improvements in prediction accuracy. Regarding computational efficiency, KPRR was consistently the fastest, while BayesB was the slowest. Our findings demonstrated that KPRR provided significant advantages over traditional genomic prediction methods in capturing nonadditive effects.
A transformer-based deep learning survival prediction model and an explainable XGBoost anti-PD-1/PD-L1 outcome prediction model based on the cGAS-STING-centered pathways in hepatocellular carcinoma
Authors: Wang Ren , Liu Qiumei , You Wenhua , Wang Huiyu , Chen Yun 
Published: January 2025

Abstract
Recent studies suggest cGAS-STING pathway may play a crucial role in the genesis and development of hepatocellular carcinoma (HCC), closely associated with classical pathways and tumor immunity. We aimed to develop models predicting survival and anti-PD-1/PD-L1 outcomes centered on the cGAS-STING pathway in HCC. We identified classical pathways highly correlated with cGAS-STING pathway and constructed transformer survival model preserving raw structure of pathways. We also developed explainable XGBoost model for predicting anti-PD-1/PD-L1 outcomes using SHAP algorithm. We trained and validated transformer survival model on pan-cancer cohort and tested it on three independent HCC cohorts. Using 0.5 as threshold across cohorts, we divided each HCC cohort into two groups and calculated P values with log-rank test. TCGA-LIHC: C-index = 0.750, P = 1.52e−11; ICGC-LIRI-JP: C-index = 0.741, P = .00138; GSE144269: C-index = 0.647, P = .0233. We trained and validated [area under the receiver operating characteristic curve (AUC) = 0.777] XGBoost model on immunotherapy datasets and tested it on GSE78220 (AUC = 0.789); we also tested XGBoost model on HCC anti-PD-L1 cohort (AUC = 0.719). Our deep learning model and XGBoost model demonstrate potential in predicting survival risks and anti-PD-1/PD-L1 outcomes in HCC. We deployed these two prediction models to the GitHub repository and provided detailed instructions for their usage: deep learning survival model, https://github.com/mlwalker123/CSP_survival_model; XGBoost immunotherapy model, https://github.com/mlwalker123/CSP_immunotherapy_model.
Hydrogen supply pipeline leakage diffusion and safety assessment for fuel cell patrol vehicle
Authors: Liu Shuai , Hao Liutao , Jia Hekun , Zhang Qiushi , Du Pengzhu 
Published: January 2025

Abstract
This study aims to reveal the hydrogen leakage and diffusion characteristics of the hydrogen supply pipeline in a fuel cell patrol vehicle and to evaluate the damage distance following an explosion. Through numerical analysis, the impact of the position, diameter, shape, and direction of leakage holes, as well as ambient wind, on hydrogen diffusion was discussed. The results show that different leakage positions are affected by surrounding objects and the height above the ground, altering the volume and diffusion distance of the flammable hydrogen cloud (FHC). An increase in leakage aperture leads to a significant rise in hydrogen leakage, the volume of the FHC, and the damage range after an explosion. The shape of the leakage hole affects the velocity distribution of hydrogen upon impacting a wall, resulting in a different distribution of the FHC. When the leakage direction is 180°, the volume of the FHC decreases by 79.2%. Environmental winds significantly influence hydrogen diffusion, with lateral winds reducing the volume of the FHC by 74%. The maximum hazard radius of hydrogen leakage is 4.09 m, the maximum distance for multiple fatalities caused by a hydrogen explosion is 1.48 m, and the maximum distance for minor injuries is 6.04 m.
Investigation of consistency and uniformity for commercial-size proton-exchange membrane fuel cell stack based on multipoint impedance measurement
Authors: Zhou Julong , Zhou Yuhan , Li Ruitao , Yao Naiyuan , Lin Weikang , Ma Tiancai 
Published: January 2025

Abstract
The proton-exchange membrane fuel cell is a highly attractive clean energy technology for the future. However, differences in the consistency and uniformity of commercial-size fuel cell stacks significantly impact their health status and lifespan. This study is based on a commercial-size 10-cell stack. First, the characteristic frequency was determined by multipoint voltage and impedance sweeping experiments. Subsequently, the consistency and uniformity of the output characteristics of the stack at various loads under standard operating conditions were comprehensively analyzed using fixed-frequency multipoint impedance. Finally, a sensitivity analysis was conducted to quantitatively assess the effects of key parameters, including the air stoichiometry ratio and operating temperature, on the consistency and uniformity of voltage and high-frequency resistance. The inconsistency is more pronounced at high current densities, especially at the cathode inlet side compared to the outlet side. At low-current-density operation, the high-frequency resistance is greater at the cathode inlet side compared to the outlet side due to uneven gas distribution and more severe membrane drying at the inlet side. Increasing the air stoichiometry ratio enhances the consistency and uniformity of the stack. The effect of temperature on stack consistency is not significant in the appropriate temperature interval, but higher temperatures can reduce cell uniformity differences. The analytical approach in this study can provide guidance for stack consistency and uniformity studies.
Early left ventricular unloading after venoarterial extracorporeal membrane oxygenation: 1-year outcomes of the EARLY-UNLOAD randomized clinical trial
Authors: Lim Yongwhan , Kim Min Chul , Lee Seung Hun , Park Seongho , Ahn Joon Ho , Hyun Dae Young , Cho Kyung Hoon , Jung Yong Hun , Jeong In-Seok , Ahn Youngkeun 
Published: January 2025

Abstract

Aims
The long-term effects of early left ventricular (LV) unloading after venoarterial extracorporeal membrane oxygenation (VA-ECMO) remain unclear.

Methods and results
The EARLY-UNLOAD trial was a single-centre, investigator-initiated, open-label, randomized clinical trial involving 116 patients with cardiogenic shock (CS) undergoing VA-ECMO. The patients were randomly assigned to undergo either early routine LV unloading by transseptal left atrial cannulation within 12 h after randomization or the conventional approach, which permitted rescue transseptal cannulation in case of an increased LV afterload. The pre-specified secondary endpoints at 1 year included all-cause mortality, cardiac mortality, non-cardiac mortality, rehospitalization for heart failure (HF), and the composite of all-cause mortality or rehospitalization for HF. At 1 year, data for 114 of 116 patients (98.3%) were available for analysis. All-cause death had occurred in 33 of 58 patients (56.9%) in early group and 32 of 56 patients (57.1%) in conventional group {hazard ratio [HR], 0.97 [95% confidence interval (CI), 0.60 to 1.58], P = 0.887}. There was no significant difference in cardiac or non-cardiac mortality. Among 61 survivors at 30 days, the incidence of rehospitalization for HF at 1 year was comparable between two groups [HR, 1.17 (95% CI 0.43 to 3.24), P = 0.758]. The incidence of the composite outcome of all-cause mortality or rehospitalization for HF also did not differ between the groups [HR, 1.01 (95% CI 0.69 to 1.76), P = 0.692].

Conclusion
Among patients with CS undergoing VA-ECMO, early routine LV unloading did not improve clinical outcomes at 1 year of follow-up.

Registration
ClinicalTrials.gov: NCT04775472
Patients perspectives on integrating eHealth in regular care pathways for atrial fibrillation: evaluating photoplethysmography for remote self-assessment
Authors: van Mourik Manouk J W , Keijsers Lotte , van der Velden Rachel M J , Vorstermans Bianca , Crijns Harry J G M , Muris Jean W M , Linz Dominik K , Gidding-Slok Annerika 
Published: January 2025

Abstract

Aims
Smartphone applications for heart rate and rhythm assessment are increasingly used for the management of atrial fibrillation (AF). Although the use of a photoplethysmography (PPG)-based smartphone application with subsequent (tele)consultations for AF management has been proven feasible in the TeleCheck-AF project, specific needs, and expectations of patients with AF are unclear. The aim of this study is to evaluate patients’ perspectives on the use of remote PPG-based electronical health (eHealth) integrated in regular care pathways for AF.

Methods and results
A qualitative study was conducted among patients with known AF, who have used a PPG-based smartphone application around scheduled (tele)consultations. Semi-structured interviews were audio-recorded and transcribed verbatim. Data were analysed according to conventional content analysis.
In total, 14 patients were interviewed. Five main themes were defined after analysis, i.e. smartphone application usability, requirements for eHealth implementation, remote self-assessment, patient engagement, and blended care (i.e. combining digital and face-to-face care). Overall, the participants were positive about the use of the PPG-based smartphone application and subsequent (tele)consultation. Using this application made the participants feel involved and led to active participation. In addition, the healthcare provider-patient relationship appeared an important aspect for adequate implementation. Particularly, timely consultation was found important, to discuss the results with their healthcare provider.

Conclusion
The results of this study emphasize the importance of blended care for the implementation of remote PPG-based eHealth in AF management. The use of a PPG-based smartphone application in regular care can support patient engagement and subsequently the process of shared decision making.
Challenges and strategies for effective recruitment and retention of participants in clinical research studies
Authors: Klompstra Leonie , Strömberg Anna , Jaarsma Tiny , Hendriks Jeroen M 
Published: January 2025

Abstract
Effective recruitment and retention of participants in clinical research studies are critical to be able to draw meaningful and valid conclusions in research studies. However, there are multiple challenges related to communication, generalizability, and logistics. Researchers must address and overcome these challenges to ensure robust research outcomes. Effective strategies include honest and clear communication, awareness of reasons for (non)-participation, incentivization, and reimbursements of expenses as well as co-designing interventions and research protocols. This paper outlines common issues in participant recruitment and retention and provides practical strategies to overcome challenges.
Swarming bacteria exhibit developmental phase transitions to establish scattered colonies in new regions
Authors: Zdimal Amanda M , Di Dio Giacomo , Liu Wanxiang , Aftab Tanya , Collins Taryn , Colin Remy , Shrivastava Abhishek 
Published: January 2025

Abstract
The collective surface motility and swarming behavior of microbes play a crucial role in the formation of polymicrobial communities, shaping ecosystems as diverse as animal and human microbiota, plant rhizospheres, and various aquatic environments. In the human oral microbiota, T9SS-driven gliding bacteria transport non-motile microbes and bacteriophages as cargo, thereby influencing the spatial organization and structural complexity of these polymicrobial communities. However, the physical rules governing the dispersal of T9SS-driven bacterial swarms are barely understood. Here, we collected time-lapse images, under anaerobic conditions, of developing swarms of a T9SS-driven microbe common to the human oral microbiota. Tracking of swarms revealed that small peripheral flares emerging from a colony develop structures that resemble fireworks displaying a chrysanthemum effect and flower-like patterns that convert to wave-like patterns and which further evolve into scattered microcolonies. Particle-image velocimetry showed density-dependent phase transitions and initial vorticity within these emerging patterns. Numerical simulations demonstrate that these patterns arise due to changes in swarm speed and alignment strength. Our data reveal a strategy used by an anaerobic swarming bacterium to control swarm behavior, resulting in scattered microcolonies distant from the mother colony, thus reducing competition for resources among colony members. This might ensure species survival even if conditions change drastically in one location of the human oral cavity.
Electronic Health Record Design Impacts Clinician Ordering Behavior: An Interrupted Time Series Analysis
Authors: Wilber Eli P , Burd Eileen M , Fitts Eric C , Jacob Jesse T , Suchindran Sujit 
Published: January 2025

Abstract

Background
Diagnostic stewardship is the science of improving diagnostic test use. Whether electronic health record (EHR) design influences clinician diagnostic testing behavior and electronic medical record interventions can improve diagnostic stewardship outcomes are key questions. We leveraged the natural experiment of a recent change in EHR platforms to investigate if changing how 2 commonly misused tests, blood cultures for acid-fast bacilli (AFB) and fungi, are displayed affected their use.

Methods
We performed a retrospective chart review of all AFB and fungal blood cultures at 4 hospitals with a shared EHR. The preintervention and postintervention periods were 52 and 26 weeks, respectively. The culture rate was standardized per 1000 patient-days and segmented into 2-week periods. Pre- and postintervention median rates were compared with the Wilcoxon rank sum test and further analyzed with an interrupted time series (ITS) analysis using a quasi-Poisson regression model.

Results
The biweekly median AFB blood culture rate decreased by 41.6% in the postintervention period (0.46/1000 patient-days vs 0.79/1000 patient-days, P &lt; 0.001). The median rate of fungal blood cultures decreased by 54.3% in the postintervention period (0.42/1000 patient-days vs 0.92/1000 patient-days, P &lt; 0.001). In ITS analysis, the EHR change was associated with a level change in AFB (−31.8%, 95% CI: −54.6% to +2.6%) and fungal (−44.6%, 95% CI: −59.3% to −24.7%) blood culture use.

Conclusions
An electronic medical record design change resulted in decreased use of 2 commonly misused diagnostic tests. This highlights the impact of EHR design on clinician behavior and diagnostic stewardship programs’ potential to reduce waste.
The Role of the Clinical Laboratory in Diagnostic Stewardship and Population Health
Authors: Crawford James M , Shotorbani Khosrow , Swanson Kathleen 
Published: January 2025

Abstract

Background
As healthcare identifies new opportunities to provide patient services and moves from volume to value payment models, the clinical laboratory is in an ideal position to serve as a catalyst for these changes. In 2017, the Project Santa Fe Foundation (PSFF) was founded to support the clinical laboratory’s role to promote the objectives of population health and value-based healthcare. The initiative, known as Clinical Lab 2.0, uses longitudinal laboratory data to create actionable insights that can lead to improved patient and population outcomes, optimize the total cost of care, and reduce financial risk for stakeholders.

Content
The Clinical Lab 2.0 model was developed by a coalition of laboratory leaders to support clinical laboratories in the implementation of this new paradigm that moves beyond the provision of high-specificity and high-accuracy transactional test results and promotes “well care” and population health.
To provide leadership for Clinical Lab 2.0 across healthcare, promote dissemination of these concepts to clinical laboratories, and create evidence of laboratory’s value; the Foundation has several ongoing initiatives. The first initiative is the conduct of both single-site and multisite demonstration projects at PSFF member sites. The second ongoing initiative for the Foundation is the provision of guidance documents to support clinical laboratories in the implementation of Clinical Lab 2.0 and promote policy development. PSFF has developed 2 types of guidance document tools: Position Statements and Laboratory-Driven Care Models.

Summary
This review summarizes the history, background, and initiatives for Clinical Lab 2.0 supported by the Project Santa Fe Foundation.