bluuebunny/crossref_metadata_2025_split huggingface dataset:
Validation of a software‐based torsional measurement method of the lower limb: A retrospective study
Authors: Grünwald Leonard , Nejima Shuntaro , Histing Tina , Schröter Steffen , Hagedorn Peter 
Published: October 2024

AbstractPurposeThe aim of this study was to evaluate a software‐based measurement tool of computed tomography imaging to assess torsional alignment of the lower limb—usually used for patients with posttraumatic deformities and patellofemoral issues—and compare these measurements with manual measurements of two experienced raters.MethodsThis study was a retrospective analysis of 58 lower limbs (47 patients, 20 men and 27 women) aged between 19 and 97 years. Inclusion criteria were the clinical indication for torsion measurement of the lower limb. Legs with incomplete imaging and age less than 18 years were excluded. Femoral and tibial torsion were measured separately. Torsional alignment was assessed software‐based at two time points by two raters. Rater one additionally assessed manual‐based measurement at two time points. The software used was mediCAD 3D Knee Version 2.5.33 (Hectec). Subsequently, intra‐ and inter‐rater reliability was calculated using the intraclass correlation coefficient (ICC). Validity testing was performed by means of precision, concordance correlation coefficient according to Lin (ccc) and Pearson correlation coefficient.ResultsHigh intra‐rater reliability for software‐based as well as manual‐based evaluation of torsional alignment was found for the tibia as well as the femur (ICC ranging between 0.870 and 0.993). Inter‐rater reliability also showed highly significant results of both manual and software‐based measurements (ICC ranging between 0.851 and 0.993). For almost all comparisons (except the tibia left), software‐based measurements showed higher ICC scores above 0.9, and, therefore, classified as ‘excellent reliability’. For validity testing, correlation coefficients and precision showed very good correspondence of the measurements (all values > 0.9), without systematic deviations.ConclusionsSoftware‐based measurement of torsional alignment according to the measurement method developed by H.‐A. Waidelich proved to be a reliable and valid technique. Especially for inexperienced surgeons, software‐based measurement, therefore, might improve confidence in reliable medical decisions in diagnostics and treatment.Level of EvidenceLevel III.
Cultivated Land Quality Assessment and Obstacle Factors Diagnosis in Changtu County, Northeast China
Authors: Qian Fengkui , Jiao Siyu , Yu Yuanjun , Wang Xiangguo , Shao Tianyi 
Published: October 2024

ABSTRACTEffective evaluation of cultivated land quality is crucial for sustainable agricultural management. Existing research often focuses on regional scales and lacks sufficient detailed analysis of spatial distribution and limiting factors at localized scales. This study aims to select the key indicators to evaluate cultivated land quality and analyze their influence on cultivated land quality at the county level. Taking Changtu County as the research area, principal component analysis (PCA) was employed to identify the most effective Minimum Data Set (MDS) for evaluation, including cultivated layer thickness, soil organic matter (SOM), pH, bulk density (BD), and cultivated layer texture. Additionally, an obstacle degree model was used to analyze restricting factors and their degrees of impact. Results showed that the constructed MDS could replace all indicators for cultivated land quality evaluation. Quality was higher in central areas and lower in eastern and western regions. SOM content decreases with the decrease of quality grade, significantly affecting the quality distribution, and pH in the medium category (Grades III and VI) cultivated lands were lower compared to other categories. Low organic matter content and low pH levels were the main obstacles affecting cultivated land quality, with average obstacle degrees of 43.5% and 29.3%, respectively. Low SOM content significantly affected land quality, particularly in the western region, whereas acidic soils in the eastern region influenced quality grade distribution. Thus, strategies for pH control and SOM enhancement are essential for improving cultivated land quality. This study provides valuable insights into sustainable agriculture.
Multiple Circular Polarizations Coexisting with Bound States in the Continuum Without Breaking Symmetry
Authors: Zhang Xiao , Xu JiPeng , Zhu ZhiHong 
Published: October 2024

AbstractBound states in the continuum (BICs) have been engineered in periodic photonic systems to achieve diverse polarization behavior in momentum space. By breaking C2z symmetry of photonic crystal slabs (PhCS), purely circular polarization, which hold significant potential for applications in topological physics and chiral optics, can be achieved near the BICs. In this study, the intriguing phenomenon of BICs on the degenerate band of PhCS with a triangular lattice featuring cylindrical holes are investigated. Unlike previous studies that mainly focused on BICs on non‐degenerate photonic bands, this research reveals a sophisticated interplay between BICs and Dirac points on the more intricate degenerate photonic band. This interaction gives birth to two pairs of purely circular polarizations with opposite chirality, even without breaking any symmetry of the PhCS. Additionally, It is find that by further breaking the σz mirror symmetry of the PhCS, these purely circular polarization states can be significantly amplified. This findings not only enrich the polarization responses of high‐Q photonic devices but also enables the modulation of chiral light, laying the groundwork for the creation of high‐quality optical devices with precisely engineered polarization properties.
On the Use of Reflection Polarized Optical Microscopy for Rapid Comparison of Crystallinity and Phase Segregation of P3HT:PCBM Thin Films
Authors: Alzahrani Rawan A. , Alshehri Nisreen , Alessa Alaa A. , Amer Doha A. , Matiash Oleksandr , De Castro Catherine S. P. , Alam Shahidul , Jurado José P. , Gorenflot Julien , Laquai Frédéric , Petoukhoff Christopher E. 
Published: October 2024

AbstractRapid, nondestructive characterization techniques for evaluating the degree of crystallinity and phase segregation of organic semiconductor blend thin films are highly desired for in‐line, automated optoelectronic device fabrication facilities. Here, it is demonstrated that reflection polarized optical microscopy (POM), a simple technique capable of imaging local anisotropy of materials, is capable of determining the relative degree of crystallinity and phase segregation of thin films of polymer:fullerene blends. While previous works on POM of organic semiconductors have largely employed the transmission geometry, it is demonstrated that reflection POM provides 3× greater contrast. The optimal configuration is described to maximize contrast from POM images of polymer:fullerene films, which requires Köhler illumination and slightly uncrossed polarizers, with an uncrossing angle of ±3°. It is quantitatively demonstrated that contrast in POM images directly correlates with 1) the degree of polymer crystallinity and 2) the degree of phase segregation between polymer and fullerene domains. The origin of the bright and dark domains in POM is identified as arising from symmetry‐broken liquid crystalline phases (i.e., dark conglomerates), and it is proven that they have no correlation with surface topography. The use of reflection POM as a rapid diagnostic tool for automated device fabrication facilities is discussed.
Structural insights into the mechanotransducing mechanism of FtsEX in cell division
Authors: Chen Yuejia , Guo Du , Wang Xin , Zhang Changbin , Chen Yatian , Luo Qinghua , Chen Yujiao , Yang Lili , Zhang Zhibo , Hong Tian , Zhang Zhengyu , Dong Haohao , Chang Shenghai , Hu Jianping , Tang Xiaodi 
Published: October 2024

AbstractThe filamentous temperature‐sensitive (Fts) protein FtsEX plays a pivotal role in Escherichia coli (E. coli) cell division by facilitating the activation of peptidoglycan hydrolysis through the adaptor EnvC. FtsEX belongs to the type VII ATP‐binding cassette (ABC) transporter superfamily, which harnesses ATP energy to induce mechanical force, triggering a cascade of conformational changes that activate the pathway. However, the precise mechanism by which FtsEX initiates mechanotransmission remains elusive. Due to the inherent instability of this type of ABC transporter protein in vitro, the conformation of FtsEX has solely been determined in the stabilized ATP‐bound state. To elucidate the dynamics of FtsEX, we characterized FtsEX and EnvC of various functional structures through cryo‐electron microscopy (cryo‐EM) and homology modeling. We validated the structures by molecular dynamics simulations. By site‐directed mutagenesis and phenotype screening, we also identified the functional residues involved in allosteric communication between FtsE and FtsX as well as FtsX and EnvC. Additionally, we discovered a potential role of phospholipids in stabilizing the complex conformation during mechanotransmission. This comprehensive exploration significantly enhances our understanding of the intricate mechanisms governing bacterial cell division and unveils potential molecular targets for developing innovative antimicrobial drugs to combat antibiotic resistance.
Prospective Connectomic‐Based Deep Brain Stimulation Programming for Parkinson's Disease
Authors: Hines Kevin , Noecker Angela M. , Frankemolle‐Gilbert Anneke M. , Liang Tsao‐Wei , Ratliff Jeffrey , Heiry Melissa , McIntyre Cameron C. , Wu Chengyuan 
Published: October 2024

AbstractBackgroundEfficacy of deep brain stimulation (DBS) relies on accurate lead placement as well as optimization of the stimulation parameters. Although clinical software tools are now available, programming still largely relies on a monopolar review, a tedious process for both patients and programmers.ObjectiveThis study investigates the safety and feasibility of prospective automated connectomic DBS programming (automated connectomic programming [ACP]), focusing on the recruitment of specific white matter pathways.MethodsAfter DBS implantation, a detailed connectomic DBS model in patient‐specific space was developed for each study participant. A driving‐force model was used to quantify pathway recruitment across 2400 different DBS settings. Optimization algorithms maximized recruitment of therapeutic pathways while minimizing recruitment of side‐effect pathways. Thirteen subjects were enrolled in two study phases that compared DBS settings derived from ACP to standard clinical DBS settings.ResultsNine patients underwent reprogramming with ACP (5 globus pallidus interna [GPi], 4 subthalamic nucleus [STN]). Four patients underwent initial programming with ACP (3 GPi, 1 STN). All patients tolerated ACP without persistent side effects. In the reprogramming cohort, 3 patients preferred their ACP program, and 1 patient felt it was comparable to their clinical program. Unified Parkinson's Disease Rating Scale, Part III, scores for the initial ACP cohort (3 GPi, 1 STN) improved by an average of 43.5% (40.4–52.6 ± 5.6%).ConclusionsACP appeared clinically safe and feasible. It provided reasonable motor improvement, which can be further optimized with subsequent clinical adjustment. Additional investigation is required to refine the optimization algorithm and to quantify the clinical benefit of ACP in a larger cohort. © 2024 International Parkinson and Movement Disorder Society.
Bridging gaps at key intersections: Strategies to improve early intervention and treatment access for eating disorders
Authors: Kennett Juliane , Stelfox Henry T. 
Published: October 2024

ABSTRACTMental health is at the forefront of discussions in healthcare, education, and social settings, yet eating disorders remain poorly understood and inadequately treated. This paper presents evidence on risk factors for insufficient recognition and intervention for eating disorders across clinical and community healthcare settings and proposes actionable strategies to improve awareness and early intervention for eating disorders. Specifically, gaps in eating disorder awareness and treatment access are exacerbated at two key intersections within health and social systems. First, eating disorders manifest themselves at the intersection of mental and physical categories of health, which places them at risk of being misunderstood, poorly diagnosed, and insufficiently intervened upon. Second, the peak onset of eating disorders falls at the intersection of adolescence and young adulthood, which is a period of rapid developmental, social change, and transitions in care. This analysis highlights how systemic issues within existing social and health systems underlie these intersections and contribute to the continued stigmatization and inadequate treatment access for eating disorders. Given their increased incidence and severity, there is an urgent need to address both the individual and societal burden of these disorders. Healthcare systems must prioritize coordination between physical and mental health practices and improve transitions in care from pediatric and adult healthcare services. Identifying gaps at intersections provides the opportunity to make concrete progress toward improving awareness and treatment.
A weakly supervised model for incomplete multimodal MRI synthesis with tumor‐aware approach
Authors: Chang Can , Yao Li , Zhao Xiaojie 
Published: October 2024

AbstractBackgroundMagnetic resonance images (MRIs) are a valuable tool in the study of brain tumors, and multimodal sequences provide unique insights into different aspects of brain tumors. However, in clinical practice, missing modalities are often encountered due to various factors. This makes it difficult to obtain comprehensive and reliable information related to brain tumors.PurposeThe purpose of this work is to develop an algorithm for the synthesis of missing MRI modality with high precision, and to center on generating accurate tumor‐related information to offer more data for clinical diagnosis.MethodsA novel weakly supervised MRI synthesis model named TAM‐DAM‐GAN has been proposed, which integrates tumor‐aware and detail adjustment mechanisms to enhance the quality of tumor generation. The tumor‐aware mechanism leverages weak label information to guide the network to classify images based on crucial information in local structures, thereby compelling the generative network to identify and highlight the learning of local tumor regions. The detail adjustment mechanism utilizes a discriminator to create attention maps at the pixel level in real‐time. These maps are then used to modify the loss weight, which in turn adjusts the details that are generated.ResultsGeneration quality of four tasks (T1‐to‐T2, T2‐to‐T1, T1‐to‐FLAIR, and FLAIR‐to‐T1) was evaluated. Experiments on the BRATS2015 dataset show that the proposed approach is superior in both qualitative and quantitative measures. Taking FLAIR‐to‐T1 as an example, TAM‐DAM‐GAN improves PSNR of tumor region from 18.556 to 20.576 compared to baseline. Also, using real FLAIR data with generated T1 data boosts tumor segmentation accuracy by 10% compared to using only real FLAIR data.ConclusionThis finding will be conducive to enhancing the accuracy of cross‐modality synthesis in incomplete multimodal MRI, especially for tumor regions, thereby providing more dependable and comprehensive data for clinical diagnosis and scientific research.
Motion and anatomy dual aware lung ventilation imaging by integrating Jacobian map and average CT image using dual path fusion network
Authors: Ma Pei , Chen Zhi , Huang Yu‐Hua , Zhao Mayang , Li Wen , Li Haojiang , Cao Di , Jiang Yi‐Quan , Zhou Ta , Cai Jing , Ren Ge 
Published: October 2024

AbstractBackgroundDeep learning‐based computed tomography (CT) ventilation imaging (CTVI) is a promising technique for guiding functional lung avoidance radiotherapy (FLART). However, conventional approaches, which rely on anatomical CT data, may overlook important ventilation features due to the lack of motion data integration.PurposeThis study aims to develop a novel dual‐aware CTVI method that integrates both anatomical information from CT images and motional information from Jacobian maps to generate more accurate ventilation images for FLART.MethodsA dataset of 66 patients with four‐dimensional CT (4DCT) images and reference ventilation images (RefVI) was utilized to develop the dual‐path fusion network (DPFN) for synthesizing ventilation images (CTVIDual). The DPFN model was specifically designed to integrate motion data from 4DCT‐generated Jacobian maps with anatomical data from average 4DCT images. The DPFN utilized two specialized feature extraction pathways, along with encoders and decoders, designed to handle both 3D average CT images and Jacobian map data. This dual‐processing approach enabled the comprehensive extraction of lung ventilation‐related features. The performance of DPFN was assessed by comparing CTVIDual to RefVI using various metrics, including Spearman's correlation coefficients (R), Dice similarity coefficients of high‐functional region (DSCh), and low‐functional region (DSCl). Additionally, CTVIDual was benchmarked against other CTVI methods, including a dual‐phase CT‐based deep learning method (CTVIDLCT), a radiomics‐based method (CTVIFM), a super voxel‐based method (CTVISVD), a Unet‐based method (CTVIUnet), and two deformable registration‐based methods (CTVIJac and CTVIHU).ResultsIn the test group, the mean R between CTVIDual and RefVI was 0.70, significantly outperforming CTVIDLCT (0.68), CTVIFM (0.58), CTVISVD (0.62), and CTVIUnet (0.66), with p < 0.05. Furthermore, the DSCh and DSCl values of CTVIDual were 0.64 and 0.80, respectively, outperforming CTVISVD (0.63; 0.73) and CTVIUnet (0.62; 0.77). The performance of CTVIDual was also significantly better than that of CTVIJac and CTVIHU.ConclusionsA novel dual‐aware CTVI model that integrates anatomical and motion information was developed to synthesize lung ventilation images. It was shown that the accuracy of lung ventilation estimation could be significantly enhanced by incorporating motional information, particularly in patients with tumor‐induced blockages. This approach has the potential to improve the accuracy of CTVI, enabling more effective FLART.
Identification of Disc Cutter Wear via Operation Parameters Combined With Vibration Data: A Case Study
Authors: Wang Yan‐Ning , Chen Han , Min Xin‐Hao , Zhao Lin‐Shuang 
Published: October 2024

ABSTRACTThis paper proposed an approach to estimate disc cutter wear utilizing a combination of multiple operational parameters and vibration data collected during shield tunneling operations. The incorporation of vibration signals, notably those originating from acceleration sensors mounted on the back plate of the soil chamber, has markedly enhanced the accuracy of the model. Time‐frequency domain features were extracted through analysis methods such as Fast Fourier Transform (FFT), Short‐Time Fourier Transform (STFT), and Continuous Wavelet Transform (CWT). A predictive model utilizing vibration and shield operation parameters was developed using the XGBoost algorithm, and a deep GoogLeNet Convolutional Neural Network (CNN) was trained on time‐frequency graphs from the CWT. In addition, this study also investigated the impact of signal duration on wavelet image information and model accuracy. In the Huang‐Shang Intercity Railway Project, the approach effectively assessed disc cutter wear during tunneling operations and dynamically optimized the operational parameters of the shield tunnel machine through predictive analysis.
Blood‐based biomarkers of Alzheimer's disease: Standardization and comprehensiveness
Authors: Liu Ying , Guo Yu , Yu Jintai 
Published: October 2024

AbstractPopulation aging is sweeping across the globe, resulting in a striking prevalence of Alzheimer's disease (AD) and dementia and a heavy economic burden. Given the time window of 10–20 years from pathological initiation to clinically detected cognitive impairment, early detection can significantly impact the prevention and control of AD. The invasiveness and high cost of cerebrospinal fluid biomarkers and positron emission tomography‐computed tomography imaging limit large‐scale disease screening. However, blood‐based biomarkers (BBMs) lack these disadvantages, shedding light on their usefulness in the large‐scale identification and prevention of AD. Prominent advancement has recently been made regarding BBMs of AD co‐pathology (amyloid β, tau protein, neurofilament light polypeptide, and glial fibrillary acidic protein) to improve their accuracy as clinical diagnostics of AD to a level comparable to that of canonical methods, facilitating the large‐scale clinical implementation of diagnostic tests with higher precision. To briefly summarize, the prospects of AD BBMs rely on standardization and comprehensiveness. Calibrating the sample collection procedure and clarifying the boundaries for indices and abnormalities are beneficial for constructing a canonical diagnostic assay. The comprehensive assembly of heterogeneous clinical evidence guarantees the accuracy of diagnosis and improves the workflow for early identification.
Multigrid Reduction‐In‐Time Convergence for Advection Problems: A Fourier Analysis Perspective
Authors: De Sterck H. , Friedhoff S. , Krzysik O. A. , MacLachlan S. P. 
Published: October 2024

ABSTRACTA long‐standing issue in the parallel‐in‐time community is the poor convergence of standard iterative parallel‐in‐time methods for hyperbolic partial differential equations (PDEs), and for advection‐dominated PDEs more broadly. Here, a local Fourier analysis (LFA) convergence theory is derived for the two‐level variant of the iterative parallel‐in‐time method of multigrid reduction‐in‐time (MGRIT). This closed‐form theory allows for new insights into the poor convergence of MGRIT for advection‐dominated PDEs when using the standard approach of rediscretizing the fine‐grid problem on the coarse grid. Specifically, we show that this poor convergence arises, at least in part, from inadequate coarse‐grid correction of certain smooth Fourier modes known as characteristic components, which was previously identified as causing poor convergence of classical spatial multigrid on steady‐state advection‐dominated PDEs. We apply this convergence theory to show that, for certain semi‐Lagrangian discretizations of advection problems, MGRIT convergence using rediscretized coarse‐grid operators cannot be robust with respect to CFL number or coarsening factor. A consequence of this analysis is that techniques developed for improving convergence in the spatial multigrid context can be re‐purposed in the MGRIT context to develop more robust parallel‐in‐time solvers. This strategy has been used in recent work to great effect; here, we provide further theoretical evidence supporting the effectiveness of this approach.