bluuebunny/crossref_metadata_2025_split huggingface dataset:
Investigation of the effect of the alignment of the eye and the virtual image of virtual reality on fatigue in viewing VR device
Authors: Hong Hyungki , Kang Hyungoo 
Published: September 2024

AbstractCybersickness is a major problem hindering the use of fully immersive virtual reality (VR) systems. A mismatch between the interpupillary distance (IPD) and the inter‐optical system distance (IOSD) can cause discomfort when using VR devices. To solve this, the IOSD must be aligned according to the user's IPD. Herein, we investigated the effects of the optimum alignment of IPD and IOSD on eye fatigue when using VR systems. A method was used such that the IPD and IOSD for each participant were initially aligned under the condition that binocular fusion did not occur by displaying different left and right images. Fifteen university students aged 20–26 years were included. In the alignment and misalignment states, a symptom questionnaire was used to evaluate changes in the symptoms of participants after viewing a short movie using the VR device. We found that the obtained results in the eye strain category were statistically improved in the aligned state compared with those in the misaligned state. However, there were no significant differences in the general discomfort, nausea, focusing difficulty, or headache categories. Consequently, we confirmed that the alignment of the VR device using the proposed method can reduce eye fatigue when viewing VR content.
ChatGPT and Tourist Decision‐Making: An Accessibility–Diagnosticity Theory Perspective
Authors: Stergiou Dimitrios P. , Nella Athina 
Published: September 2024

ABSTRACTThis paper investigates the role of ChatGPT in informing tourist decision‐making across different destination contexts, focusing particularly on the accessibility and diagnosticity of its recommendations. Specifically, we inform our analysis with the tenets of the Accessibility–Diagnosticity Theory (ADT), to draw insights into ChatGPT's capabilities to produce contextually relevant and personalised travel content. Our findings reveal a sophisticated and multi‐dimensional advisory approach characterised by three themes: ‘Tailored Engagement and Accessibility’, ‘Diagnosticity of Information’ and ‘Contextual Variation in Criteria Prioritisation.’ These themes and their intersections highlight ChatGPT's potential to improve tourist decision‐making by offering comprehensive and user‐centric guidance. Based on these findings, we develop a model of ChatGPT's advisory dynamics in tourism decision‐making, which illustrates how ChatGPT integrates personalised insights, diagnostic relevance and contextual adaptation, offering a blueprint for leveraging artificial intelligence in enhancing the travel experience. We conclude with a discussion of the theoretical and practical contributions of the study.
Context‐driven implementation strategies: Exploring three approaches to implement a lean capability framework within a global production company
Authors: Linderson Sara 
Published: September 2024

AbstractThis paper explores global implementation of capability building projects as part of an corporate lean programme. The aim is to identify the core parameters in global implementation of complex knowledge in various contexts within the corporation. The empirical research investigates the global implementation of a lean capability project in three regional clusters within a large pharmaceutical multinational production company. The findings indicate that contextual situations in regional clusters, for example, maturity levels, national culture, and previous experiences, influence the design of the implementation approaches embedding knowledge management principles in various ways. Three types of implementation approaches (horizontal, parallel, and delegated) are identified, which highlights the strategically different pathways to realise new frameworks for knowledge management. This study shows how adjustments to contextual situations influence the implementation process and identifies various hallenges with various approaches that may hinder the execution of lean strategy. This paper puts forward five identified implementation parameters that could guide future research and knowledge management practitioners in opex, HR, and learning and development functions.
Partial weight‐bearing and range of motion limitation significantly reduce the loads at medial meniscus posterior root repair sutures in a cadaveric biomechanical model
Authors: Sukopp Matthias , Schwab Nina , Schwer Jonas , Frey Julian , Metzger Jonas Walter , Ignatius Anita , Perl Mario , Salami Firooz , Vogele Daniel , Kappe Thomas , Seitz Andreas Martin 
Published: September 2024

AbstractPurposeThe aim of this study was to investigate the influence of medial meniscus posterior root avulsion (MMPRA) before and after surgical treatment on the biomechanics of the knee joint, including suture repair forces during daily and crutch‐assisted gait movements.MethodsMMPRA were investigated in eight human cadaver knee joint specimens by a dynamic knee joint simulator with daily (normal gait, gait with additional rotational movement, standing up, sitting down) and rehabilitation‐associated movements (crutch‐assisted gait with limited flexion range of motion [30°] and 30% [toe‐touch weight‐bearing, TTWB] and 50% of body weight [partial weight‐bearing, PWB]) with simulated physiologic muscle forces. Each specimen was tested in intact, torn and repaired (transtibial suture) state. The biomechanical parameters were: medial mean contact pressure and area, knee joint kinematics, medial displacement of the posterior meniscus horn and loading on the anchoring suture.ResultsSignificant reduction of the contact area due to the avulsion was observed in all movements except for PWB and sitting down. MMPRA repair significantly increased the contact areas during all movements, bringing them to levels statistically indistinguishable from the initial state. MMPRA resulted in a medial displacement up to 12.8 mm (sitting down) and could be reattached with a residual displacement ranging from 0.7 mm (PWB) to 5.7 mm (standing up), all significantly (p < 0.001) reduced compared to the torn state. The mean peak anchoring suture load increased from TTWB (77 N), PWB (91 N) to normal gait (194 N), gait rotation (207 N), sitting (201 N; p < 0.01) and to standing up (232 N; p = 0.03).ConclusionSurgical treatment of MMPRA allows restoration of physiological knee joint biomechanics. Crutch‐assisted movements reduce the loading of the repair suture, thus likewise the risk for failure. From a biomechanical point of view, crutch‐assisted movements are recommended for the early rehabilitation phase after MMPRA repair.Level of EvidenceLevel V.
Harmonic‐Assisted Super‐Resolution Rotational Measurement
Authors: Guo Zhenyu , Wang Jiawei , Zhao Weihua , Gao Hong , Chang Zehong , Wang Yunlong , Zhang Pei 
Published: September 2024

AbstractEnhancing rotational measurement resolution and broadening the detectable spectral range are two critical and unresolved matters within the realm of motion perception. The rotational Doppler effect (RDE) is combined with the harmonic generation process to create a rotational measurement scheme that offers flexible detection wavelength conversion, exponential improvement of measurement resolution, and real‐time display of detection results. In the experiments, a cascaded second harmonic generation process is employed to attain a fourfold enhancement in rotational resolution and demonstrate how low‐cost silicon‐based detectors can be used for real‐time detection of infrared objects. This scheme employs a Gaussian beam within the nonlinear process to achieve high conversion efficiency, thereby enabling potential for subsequent cascade amplification. Additionally, it is fully compatible with existing RDE schemes, allowing for co‐amplification of rotational resolution at both the front‐end and back‐end. This research could offer a more precise and cost‐effective method for remote sensing detection.
High serum magnesium level is associated with increased mortality in patients with sepsis: an international, multicenter retrospective study
Authors: Li Le , Li Li , Zhao Qiuyue , Liu Xiao , Liu Yaohui , Guo Kailin , Zhang Dongsu , Hu Chang , Hu Bo 
Published: September 2024

AbstractMagnesium imbalances commonly exist in septic patients. However, the association of serum magnesium levels with mortality in septic patients remains uncertain. Herein, we elucidated the association between serum magnesium and all‐cause mortality in septic patients from American and Chinese cohorts by analyzing data from 9099 patients in the Medical Information Mart for Intensive Care‐IV (MIMIC‐IV) database and 1727 patients from a university‐affiliated hospital’ intensive care unit in China. Patients in both cohorts were categorized into five groups based on serum magnesium quintiles from the MIMIC‐IV dataset. Patients with higher serum magnesium levels exhibited an increased risk of 28‐day mortality in both cohorts. The restricted cubic spline (RCS) curves revealed a progressively elevated risk of 28‐day mortality with increasing serum magnesium in MIMIC‐IV cohort, while a J‐shaped correlation was observed in institutional cohort. Our findings have validated the association between high serum magnesium and high mortality in sepsis across different races and medical conditions. Serum magnesium levels might be useful in identifying septic patients at higher mortality risk.
Copper homeostasis and cuproptosis in health and disease
Authors: Yang Yunuo , Wu Jiaxuan , Wang Lisheng , Ji Guang , Dang Yanqi 
Published: September 2024

AbstractCopper is a vital trace element in human physiology, essential for the synthesis of numerous crucial metabolic enzymes and facilitation of various biological processes. Regulation of copper levels within a narrow range is imperative for maintaining metabolic homeostasis. Numerous studies have demonstrated the significant roles of copper homeostasis and cuproptosis in health and disease pathogenesis. However, a comprehensive and up‐to‐date systematic review in this domain remains absent. This review aims to consolidate recent advancements in understanding the roles of cuproptosis and copper homeostasis in health and disease, focusing on the underlying mechanisms and potential therapeutic interventions. Dysregulation of copper homeostasis, manifesting as either copper excess or deficiency, is implicated in the etiology of various diseases. Cuproptosis, a recently identified form of cell death, is characterized by intracellular copper overload. This phenomenon mediates a diverse array of evolutionary processes in organisms, spanning from health to disease, and is implicated in genetic disorders, liver diseases, neurodegenerative disorders, and various cancers. This review provides a comprehensive summary of the pathogenic mechanisms underlying cuproptosis and copper homeostasis, along with associated targeted therapeutic agents. Furthermore, it explores future research directions with the potential to yield significant advancements in disease treatment, health management, and disease prevention.
Benchmarking deep learning‐based low‐dose CT image denoising algorithms
Authors: Eulig Elias , Ommer Björn , Kachelrieß Marc 
Published: September 2024

AbstractBackgroundLong‐lasting efforts have been made to reduce radiation dose and thus the potential radiation risk to the patient for computed tomography (CT) acquisitions without severe deterioration of image quality. To this end, various techniques have been employed over the years including iterative reconstruction methods and noise reduction algorithms.PurposeRecently, deep learning‐based methods for noise reduction became increasingly popular and a multitude of papers claim ever improving performance both quantitatively and qualitatively. However, the lack of a standardized benchmark setup and inconsistencies in experimental design across studies hinder the verifiability and reproducibility of reported results.MethodsIn this study, we propose a benchmark setup to overcome those flaws and improve reproducibility and verifiability of experimental results in the field. We perform a comprehensive and fair evaluation of several state‐of‐the‐art methods using this standardized setup.ResultsOur evaluation reveals that most deep learning‐based methods show statistically similar performance, and improvements over the past years have been marginal at best.ConclusionsThis study highlights the need for a more rigorous and fair evaluation of novel deep learning‐based methods for low‐dose CT image denoising. Our benchmark setup is a first and important step towards this direction and can be used by future researchers to evaluate their algorithms.
Structural tensor and frequency guided semi‐supervised segmentation for medical images
Authors: Leng Xuesong , Wang Xiaxia , Yue Wenbo , Jin Jianxiu , Xu Guoping 
Published: September 2024

AbstractBackgroundThe method of semi‐supervised semantic segmentation entails training with a limited number of labeled samples alongside many unlabeled samples, aiming to reduce dependence on pixel‐level annotations. Most semi‐supervised semantic segmentation methods primarily focus on sample augmentation in spatial dimensions to reduce the shortage of labeled samples. These methods tend to ignore the structural information of objects. In addition, frequency‐domain information also supplies another perspective to evaluate information from images, which includes different properties compared to the spatial domain.PurposeIn this study, we attempt to answer these two questions: (1) is it helpful to provide structural information of objects in semi‐supervised semantic segmentation tasks for medical images? (2) is it more effective to evaluate the segmentation performance in the frequency domain compared to the spatial domain for semi‐supervised medical image segmentation? Therefore, we seek to introduce structural and frequency information to improve the performance of semi‐supervised semantic segmentation for medical images.MethodsWe present a novel structural tensor loss (STL) to guide feature learning on the spatial domain for semi‐supervised semantic segmentation. Specifically, STL utilizes the structural information encoded in the tensors to enforce the consistency of objects across spatial regions, thereby promoting more robust and accurate feature extraction. Additionally, we proposed a frequency‐domain alignment loss (FAL) to enable the neural networks to learn frequency‐domain information across different augmented samples. It leverages the inherent patterns present in frequency‐domain representations to guide the network in capturing and aligning features across diverse augmentation variations, thereby enhancing the model's robustness for the inputting variations.ResultsWe conduct our experiments on three benchmark datasets, which include MRI (ACDC) for cardiac, CT (Synapse) for abdomen organs, and ultrasound image (BUSI) for breast lesion segmentation. The experimental results demonstrate that our method outperforms state‐of‐the‐art semi‐supervised approaches regarding the Dice similarity coefficient.ConclusionsWe find the proposed approach could improve the final performance of the semi‐supervised medical image segmentation task. It will help reduce the need for medical image labels. Our code will are available at https://github.com/apple1986/STLFAL.
Biophysical modeling of low‐energy ion irradiations with NanOx
Authors: Alcocer‐Ávila Mario , Levrague Victor , Delorme Rachel , Testa Étienne , Beuve Michaël 
Published: September 2024

AbstractBackgroundTargeted radiotherapies with low‐energy ions show interesting possibilities for the selective irradiation of tumor cells, a strategy particularly appropriate for the treatment of disseminated cancer. Two promising examples are boron neutron capture therapy (BNCT) and targeted radionuclide therapy with ‐particle emitters (TAT). The successful clinical translation of these radiotherapies requires the implementation of accurate radiation dosimetry approaches able to take into account the impact on treatments of the biological effectiveness of ions and the heterogeneity in the therapeutic agent distribution inside the tumor cells. To this end, biophysical models can be applied to translate the interactions of radiations with matter into biological endpoints, such as cell survival.PurposeThe NanOx model was initially developed for predicting the cell survival fractions resulting from irradiations with the high‐energy ion beams encountered in hadrontherapy. We present in this work a new implementation of the model that extends its application to irradiations with low‐energy ions, as the ones found in TAT and BNCT.MethodsThe NanOx model was adapted to consider the energy loss of primary ions within the sensitive volume (i.e., the cell nucleus). Additional assumptions were introduced to simplify the practical implementation of the model and reduce computation time. In particular, for low‐energy ions the narrow‐track approximation allowed to neglect the energy deposited by secondary electrons outside the sensitive volume, increasing significantly the performance of simulations. Calculations were performed to compare the original hadrontherapy implementation of the NanOx model with the present one in terms of the inactivation cross sections of human salivary gland cells as a function of the kinetic energy of incident ‐particles.ResultsThe predictions of the previous and current versions of NanOx agreed for incident energies higher than 1 MeV/n. For lower energies, the new NanOx implementation predicted a decrease in the inactivation cross sections that depended on the length of the sensitive volume.ConclusionsWe reported in this work an extension of the NanOx biophysical model to consider irradiations with low‐energy ions, such as the ones found in TAT and BNCT. The excellent agreement observed at intermediate and high energies between the original hadrontherapy implementation and the present one showed that NanOx offers a consistent, self‐integrated framework for describing the biological effects induced by ion irradiations. Future work will focus on the application of the latest version of NanOx to cases closer to the clinical setting.
Retrospective motion correction for cardiac multi‐parametric mapping with dictionary matching‐based image synthesis and a low‐rank constraint
Authors: Chen Haiyang , Emu Yixin , Gao Juan , Chen Zhuo , Aburas Ahmed , Hu Chenxi 
Published: September 2024

AbstractPurposeTo develop a model‐based motion correction (MoCo) method that does not need an analytical signal model to improve the quality of cardiac multi‐parametric mapping.MethodsThe proposed method constructs a hybrid loss that includes a dictionary‐matching loss and a signal low‐rankness loss, where the former registers the multi‐contrast original images to a set of motion‐free synthetic images and the latter forces the deformed images to be spatiotemporally coherent. We compared the proposed method with non‐MoCo, a pairwise registration method (Pairwise‐MI), and a groupwise registration method (pTVreg) via a free‐breathing Multimapping dataset of 15 healthy subjects, both quantitatively and qualitatively.ResultsThe proposed method achieved the lowest contour tracking errors (epicardium: 2.00 ± 0.39 mm vs 4.93 ± 2.29 mm, 3.50 ± 1.26 mm, and 2.61 ± 1.00 mm, and endocardium: 1.84 ± 0.34 mm vs 4.93 ± 2.40 mm, 3.43 ± 1.27 mm, and 2.55 ± 1.09 mm for the proposed method, non‐MoCo, Pairwise‐MI, and pTVreg, respectively; all p < 0.01) and the lowest dictionary matching errors among all methods. The proposed method also achieved the highest scores on the visual quality of mapping (T1: 4.74 ± 0.33 vs 2.91 ± 0.82, 3.58 ± 0.87, and 3.97 ± 1.05, and T2: 4.48 ± 0.56 vs 2.59 ± 0.81, 3.56 ± 0.93, and 4.14 ± 0.80 for the proposed method, non‐MoCo, Pairwise‐MI, and pTVreg, respectively; all p < 0.01). Finally, the proposed method had similar T1 and T2 mean values and SDs relative to the breath‐hold reference in nearly all myocardial segments, whereas all other methods led to significantly different T1 and T2 measures and increases of SDs in multiple segments.ConclusionThe proposed method significantly improves the motion correction accuracy and mapping quality compared with non‐MoCo and alternative image‐based methods.
Comparison of 3D UTE free‐breathing lung MRI with hyperpolarized 129Xe MRI in pediatric cystic fibrosis
Authors: Munidasa Samal , Zanette Brandon , Dumas Marie‐Pier , Wee Wallace , Braganza Sharon , Li Daniel , Ratjen Felix , Santyr Giles 
Published: September 2024

AbstractPurposeTo compare phase‐resolved functional lung (PREFUL) regional ventilation derived from a free breathing 3D UTE radial MRI acquisition to hyperpolarized 129Xe‐MRI (Xe‐MRI), conventional 2D multi‐slice PREFUL MRI, and pulmonary function tests in pediatric cystic fibrosis (CF) lung disease.MethodsFree‐breathing 3D UTE and 2D multi‐slice 1H MRI as well as Xe‐MRI were acquired in 12 stable pediatric CF patients. Using PREFUL, regional ventilation (RVent) maps were calculated from the free‐breathing data. Ventilation defect percentage (VDP) was determined from 3D and 2D RVent maps (2D VDPRVent and 3D VDPRVent, respectively) and Xe‐MRI ventilation (VDPXe). VDP was calculated for the whole lung and for eight regions based on left/right, anterior/posterior, and superior/inferior divisions of the lung. Global and regional VDP was compared between the three methods using Bland–Altman analysis, linear mixed model‐based correlation, and one‐way analysis of variance and multiple comparisons tests.ResultsGlobal 3D VDPRVent, VDPXe, and 2D VDPRVent were all strongly correlated (all R2 > 0.62, p < 0.0001) and showed minimal, non‐significant bias (all <2%, p > 0.05). Three dimensional and 2D VDPRVent significantly correlated to VDPXe in most of the separate lung regions (R2 = 0.18–0.74, p < 0.04), but showed lower inter‐agreement. The superior/anterior lung regions showed the least agreement between all three methods (all p > 0.12).ConclusionAbsolute VDP assessed by 3D UTE PREFUL MRI showed good global agreement with Xe‐MRI and 2D multi‐slice PREFUL MRI in pediatric CF lung disease. Therefore, 3D UTE PREFUL MRI offers a sensitive and potentially more accessible alternative to Xe‐MRI for regional volumetric evaluation of ventilation.
Investigation on the Instability Mechanism of Expansive Soil Slope With Weak Interlayer Based on Strain Softening
Authors: Xu Shuai , Jiang Hanjing , Xu Yongfu , Wang Aoxun , Qi Shunchao 
Published: September 2024

ABSTRACTExpansive soils are widespread in the world and coincide with areas of high human activity. The main cause of deep instability of expansive soil slopes is due to their softening caused by excavation and seepage. By developing a comprehensive numerical model based on the theory of unsaturated soil, this study examines the characteristics of stress and displacement distribution of expansive soil slopes through hydraulic‐mechanical coupled numerical simulation. This study analyzes the evolution patterns of slopes with excavation unloading and seepage of water storage to reveal the mechanisms of deep‐seated instability of expansive soil slopes. The findings demonstrate that: The instability of expansive soil slopes begins at the foot of the slope and propagates along the interlayer, affecting the entire slope. Excavation leads to the softening of the expansive soil interlayer and the transfer of shear stress. During water storage, the weakening of the soil strength results in slope instability along the weak interlayer slip. Softening of the expansive soil interlayer facilitates the redistribution of shear forces in the slope and alters the distribution law of the plastic zone in the deep layer. Overly slowing down the slope leads to significant excavation unloading, which is detrimental to the slope's stability.