bluuebunny/crossref_metadata_2025_split huggingface dataset:
Learning Fast Diffeomorphic Registration for Cardiac Motion Estimation in 3D Echocardiography
Authors: Ghadim Yalda Zafari , Azarnoush Hamed 
Published: September 2023

Abstract
Echocardiography is a well-established technique for diagnosing and monitoring cardiovascular diseases. Myocardial regional motion analysis has the potential to offer a comprehensive understanding of cardiac health. Accurate and efficient quantification of cardiac motion is crucial for clinical tasks related to cardiac diagnosis and prognosis. Although various methods have been proposed for cardiac motion tracking, they often suffer from long inference times or require numerous adjustable parameters. In this study, we propose a diffeomorphic registration network (DRN) to take advantage of deep neural networks’ capability for registration purposes: their ability to learn complex representations and predict the desired output in a single step. Diffeomorphic image registration offers distinct advantages, such as generating invertible and topology-preserving deformation fields, which are key attributes in the context of cardiac motion. This approach enhances the accuracy and realism of deformation field estimation. The DRN framework employs a neural network to estimate a stationary velocity field, from which the deformation field is derived through the Scaling and Squaring method. Evaluation of methods on a synthetic echocardiography dataset with ground truth displacement vectors demonstrates the superiority of our approach in terms of accuracy. Importantly, it maintains a practical inference time of 316.63 ms per frame, making it suitable for clinical applications. Notably, DRN trained with segmentation labels achieves the best results, with a mean error of 0.81 mm for global tracking error.
The relationship between Axial Length and anterior segment biometry in Highly axial Myopic Children and Adolescents Aged 7 to 18 Years
Authors: Zhang Zengrui , Mu Jingyu , Wei Jing , Geng Haoming , Duan Jun guo 
Published: September 2023

Abstract
Background
The purpose of this study was to investigate the relationship between axial length(AL) and anterior segment biometry in highly axial myopic children and adolescents.
Methods
A cross-sectional study was conducted involving 366,278 students aged 7 to 18. The SUOER Ophthalmic Optical Biometer (SW-9000) was utilized for Ocular Biometric Measurements. A multivariate linear regression model was employed to explore the correlation with AL.
Results
Among the participants, 28,877 exhibited highly axial myopia (AL≥26mm), and 995 had super highly axial myopia (AL≥28mm). The average keratometry (K) and lens thickness (LT) of highly axialmyopic students were both smaller than those of the control group (AL<26mm),while corneal astigmatism (CA), central corneal thickness (CCT), and anterior chamber depth (ACD) were greater in the highly axial myopic students. With increasing AL, CA, CCT, and ACD demonstrated an increasing trend, while K showed a decreasing trend. When AL was<27 mm, LT exhibited a trend of thinning with increasing AL, while after AL exceeded 27 mm, LT showed a slow thickening trend with increasing AL. Multivariate linear regression analysis indicated that CA (β=0.206), K (β=-0.273), CCT (β=0.001), ACD (β=1.598), and LT (β=-0.58) were all correlated with AL (all P<0.001). When AL was <27 mm, AL was negatively correlated with LT, while after AL exceeded 27 mm, there was no linear correlation between AL and LT (P>0.05).
Conclusion
In the children and adolescent, highly axial myopia was associated with lower K, higher CA, thicker CCT, deeper ACD, and thinner LT. When AL is <27 mm, the thinning of the LT may play a role in myopia compensation, but as AL exceeds 27 mm, this crystalline lens compensatory effect gradually diminishes.
Myocardial MRI enhancement patterns in patients with left ventricular noncompaction hypertrabeculation cardiac morphology and thromboembolic events
Authors: SIEGEL YOEL , Maggart Michael 
Published: September 2023

Abstract
Left ventricular noncompaction cardiomyopathy (LVNC) is an idiopathic non-ischemic cardiomyopathy with subendocardial hypertrabeculation morphology. LVNC is associated with thromboembolic events which are thought to originate from trabeculae and associated recesses. The standard therapy for thromboembolic disease is anticoagulation, however, the timing of treatment initiation is controversial. The aim of the study is to examine the association between thromboembolic events and patterns of cardiac MRI delayed enhancement.
Patients with MRI criteria for non-compaction cardiomyopathy were included. The patients were screened for ischemic coronary disease. Images from cardiac MRI were reviewed for delayed enhancing. Cardiac function was also recorded. Medical records were searched for evidence of thrombotic or thromboembolic events. Statistical analysis was performed to investigate the association between delayed myocardial enhancement patterns and thromboembolic events.
Results
Fifty-two patients were included in the study. Thirty one patients had delayed enhancement of the myocardium. Of these 12 had an ischemic pattern of enhancement. Eleven patients had thromboembolic events and of these 6 had ischemic pattern of enhancement. Of the various parameters examined ischemic pattern of enhancement was associated with these events.
Conclusion:
An association between ischemic pattern of enhancement and distal thromboembolic events was found in patients with hypertrabeculated myocardium that meet MRI ratio criteria for non compaction cardiomyopathy. The etiology of this association is unclear, however, may be attributed to auto-infarction, whereby thrombi from the myocardium embolize to coronary arteries. This association can potentially guide therapeutic approach of anticoagulation in patients with LVNC.
Microcrack monitoring and fracture evolution of coal and rock using integrated acoustic emission and digital image correlation techniques
Authors: Zhao Zhihui , Yang Jinhu , Kang Yueming , Xiao Yong 
Published: September 2023

Abstract
The mechanical properties of a coal–rock body were examined through uniaxial compression tests, and the rupture process of the coal–rock body was monitored in real time using a combined acoustic emission (AE) monitoring system and a digital image correlation (DIC) full-field strain measurement system. From a comparison of the mechanical properties of coal and sandstone, clear differences are apparent regarding the uniaxial compressive strength, deformation characteristics, and damage mode; the brittle failure characteristics of the coal samples are also more evident. The change in AE energy reflects the accumulation and release of elastic energy during the rupture process, and the evolution of AE localization points under different stress levels can effectively reflect rupture propagation. Further, the DIC full-field strain measurement method can quantitatively monitor the evolution of the displacement and strain fields at the marking point and surface simultaneously, thereby overcoming the limitations of traditional empirical and qualitative rupture processes. During monitoring, the AE focuses on the internal rupture of the specimen and the DIC focuses on the surface deformation. These complement each other and reflect the rupture process more comprehensively.
Research on target detection method of coal gangue based on improved Yolov5s model
Authors: YUAN Xinpeng , FU Zhibo , ZHANG Bowen , XIE Zhengkun , GAN Rui 
Published: September 2023

Abstract
In order to solve the problems of slow detection speed, large number of parameters and large computational volume of deep learning based gangue target detection method, we propose an improved algorithm for gangue target detection based on Yolov5s. First, the lightweight network EfficientVIT is used as the backbone network to increase the target detection speed. Second, C3_Faster replaces the C3 part in the HEAD module, which reduces the model complexity. once again, the 20×20 feature map branch in the Neck region is deleted, which reduces the model complexity; thirdly, the CIOU loss function is replaced by the Mpdiou loss function. The introduction of the SE attention mechanism makes the model pay more attention to critical features to improve detection performance. Experimental results show that the improved model size of the coal gang detection algorithm reduces the compression by 77.8 percent, the number of parameters by 78.3 percent, the computational cost is reduced by 77.8 percent and the number of frames is reduced by 30.6 percent, which can be used as a reference for intelligent coal gangue classification.
Evaluation and comparison of SSR, ISSR, and retrotransposon molecular markers in the study of genetic diversity of Aegilops tauschii as wild ancestor of wheat
Authors: Falaknaz Mehran , Aalami Ali , Mehrabi Aliashraf , Kahrizi Danial , Sabouri Atefeh 
Published: September 2023

Abstract
Wheat is an annual plant from the cereal family, this plant is the most important agricultural plant used in the human food chain. In plant breeding programs, identifying genes resistant to biotic and non-biotic stresses is of particular importance to transfer them to crop species to increase production. The most important goal in breeding programs is the existence or creation of diversity to select superior plants. One of the ways to enrich genetic resources is to know the level of diversity in germplasm and genetic treasures, which is one of the important sources of diversity and identification of useful genes in wild relatives. In this research, the genetic diversity of 125 Aegilops tauschii genotypes was investigated using SSR, ISSR, and retrotransposon markers. In this research, based on the presented results and the changes in ΔK and its maximum curve at K = 7, the number of 125 studied Aegilops tauschii genotypes were divided into 7 subpopulations with a probability of more than 70%. In general, the results obtained from this study showed that retrotransposon markers were better markers than SSR and ISSR in terms of useful indicators. However, the average PIC index in the other two systems was higher than retrotransposon, but they did not differ much from each other. Among the three marker systems, retrotransposons and SSRs were able to show a high level of intraspecies diversity.
Towards a Model for Predicting Traffic Flow for Optimizing Resource Allocation and Usage in a Cloud Computing Systems
Authors: Sekwatlakwatla Sello Prince , Malele Vusumuzi 
Published: September 2023

Abstract
Short-term traffic flow prediction is one of the most important tools for the organisation to manage traffic and properly allocate system resources. Cloud computing requires concentrated computational resources and predictive tools to monitor traffic and integrate innovations such as artificial intelligence and machine learning. This paper uses compares a stepwise linear regression, linear support vector machine, and Gaussian process regression for tools for predicting traffic flow. The results show that stepwise linear regression performs better than other models in predicting traffic flow in Organisational Cloud Computing Systems. The use of a combination of machine learning models with hourly monitoring and resource allocation will be considered for future studies.
Impact of food price inflation on malnutrition in under five aged children in Bangladesh
Authors: Sadikeen Sheikh Sifat , Haque Nazmul , Hossain Md Miraj , Uddin Md Jamal 
Published: September 2023

Abstract
Background
Currently, food price inflation is a widespread issue in Bangladesh as well as the rest of the world. Malnutrition is a common issue among children that can have long-lasting effects on their development and overall health. We aimed to determine the relationship between food price inflation and malnutrition in children under five years of age in Bangladesh.
Method
The study utilized food price data from the World Food Programme database and malnutrition (stunting) information from the 2014 and 2017-18 Bangladesh Demographic Health Surveys. Food prices were linked to the BDHS dataset using each child's birth month. For each child, the average food prices from 9 months prior to 5 months post-birth, including their birth month, were recorded to calculate month-to-month inflation. This inflation was computed for rice (coarse), oil, wheat flour, and lentils by comparing the price sum of each item from one month to the previous month and dividing by the total price of the preceding month. A generalized linear regression model was used to assess the relationship between food price inflation and stunting, with stunting as the dependent variable. Other explanatory variables included wealth index, child's gender, height, weight, mother's education, respondent's current pregnancy, and breastfeeding status.
Results
Our study has revealed that food price inflation has a significant negative impact on stunting, with a coefficient of -0.127 (p < 0.001). Furthermore, we have identified several other factors that have significant associations with malnutrition, including the wealth index (p < 0.001), mother's education level (p < 0.001), mother's pregnancy status (p < 0.001), breastfeeding (p < 0.001), child's age (p < 0.001), and child's weight (p < 0.001). However, we did not find any significant differences in malnutrition between boys and girls.
Conclusion
The findings of this study suggest that food price inflation has a significant negative impact on child malnutrition, and its impact must be considered alongside other contributing factors. Indeed, our results underscore the importance of recognizing food price inflation as a crucial determinant of malnutrition, along with various other factors.
Dynamic Soft Tissue Artifacts during Impulsive Loads: Tuning Measurement Errors with Wearable Inertial Measurement Unit Sensor Design
Authors: Rong Roxanne , Kuo Calvin 
Published: September 2023

Abstract

Purpose
As inertial measurement unit (IMU) sensors become more ubiquitous to measure human motion in real-world environments, it is important to understand the errors that arise when using these sensors. We characterized measurement errors due to transient dynamic soft tissue artifacts that are excited by impulsive loads to the body, such as foot strikes during running and jumping.
Methods
We instrumented 10 participants (5 female, 5 male) with IMUs on the dominant leg. An ankle IMU measured ground truth vertical accelerations during impulsive loads and was cross-validated against a force plate. These were compared against measurements from two IMUs on the posterior shank and anterior shank to characterize errors caused by dynamic soft tissue artifacts. The shank sensors’ masses were varied to explore their effect on dynamic soft tissue artifacts.
Results
Both the posterior IMU and anterior IMU overestimated peak vertical accelerations during the impulsive load (gain of 2.18 ± 0.63 and 1.55 ± 0.35 respectively) and exhibited post-impulsive load oscillations lasting 326 ± 75ms and 151 ± 50ms respectively with a natural frequency of 9.79 ± 2.68Hz and 18.22 ± 12.10Hz respectively. The oscillation duration and natural frequency varied with sensor mass in accordance with an underdamped second-order system. Low-pass filtering reduced overestimation of peak vertical accelerations, but also attenuated the ground truth signal.
Conclusion
Our study suggests dynamic soft tissue artifacts result in transient, but substantial measurement errors that may not be appropriately mitigated through low-pass filtering alone. However, the measurement errors predictably varied with sensor mass, allowing for optimization in specific applications for improved kinematics measurement.
Propagation behavior of a new generalized laser beam through marine environment
Authors: Saad Faroq , Benzehoua Halima , Belafhal Abdelmajid 
Published: September 2023

Abstract
Based on the extended Huygens-Fresnel principal, we investigate the propagation behavior of Generalized Hermite cosh-Gaussian (GHCG) beam through new random medium namely maritime atmospheric turbulence. The analytical formula of the GHCG beam propagating in the considered turbulent medium is derived. The impacts of the maritime turbulence parameters and the source beam parameters on the propagation characteristics of the GHCG beam are analyzed using numerical calculations. The results show that the evolution process of average intensity for a GHCG beam through maritime turbulence will gradually lose its properties and its resistance to fluctuations and then evolve faster into Gaussian distribution in the far field as the turbulent constant structure increases and as the inner scale size of the turbulence decreases. The obtained results can be significantly contributed to the practical application for free-space optical communication and remote sensing.
One-Step Graph-Based Incomplete Multi-View Clustering
Authors: Zhou Baishun , Ji Jintian , Zhou Zihao , Ding Gangyi , Feng Songhe 
Published: September 2023

Abstract
Existing graph-based incomplete multi-view clustering methods mainly adopt the three-step strategy, i.e., graph completion, graph fusion (consensus representation learning) and subsequent $k$-means clustering. Such three-step schemes inevitably seek sub-optimal clustering results due to information loss. Besides, existing methods for incomplete multi-view clustering tasks focus on inferring the missing instances by using global complementary information without considering the local structure of data. And their weight allocation strategies for views are mostly static, the model cannot adaptively select the informative views during the process of training. To solve these issues, we propose a novel One-step Graph-based Incomplete Multi-view Clustering (OGIMC) method, which introduces the strategy of local structure preservation and adaptive weights into the model. Furthermore, a rank constraint imposed on the Laplacian matrix of the fused graph integrates the separate objectives into a unified training framework. Extensive experimental results demonstrated that OGIMC outperforms state-of-the-art baselines remarkably.
Reducing the Carbon Footprint of China’s Health Sector through Clinical Pathway Modification and Disease Management, Based on Dialysis Cases
Authors: Ma Junxiong , Bi Shuhong , Du Runming , Jiao Wangteng , Liang Zhisheng , Zhou Qinfeng , Zhou Shuduo , Pan Yuhang , Tang Wen , Zhang Haibin , Zheng Zhijie , Xu Ming , Wang Tao , Liu Gordon , Zhang Zhenyu 
Published: September 2023

Abstract
Background
The healthcare sector is a significant contributor to greenhouse gas emissions. Reducing the carbon footprint by adjusting the medical disease management structure is important for China.
Methods
We conducted a case study, estimated the annual carbon footprint of both haemodialysis and peritoneal dialysis patients and compared demographic characteristics and carbon consumption in each category between haemodialysis (HD) and peritoneal dialysis (PD). Linear regression was used to explore factors potentially influencing the carbon footprint.
Findings
271 dialysis patients (143 HD and 128 PD) were included in study. The carbon footprints of HD and PD were 3150.3 and 471.3 kgCO2-eq. The most consumed parts of HD are dialysis equipment (42%) and medical consumables (22%), and of PD are discharge medication (45%) and medical supplies (45%). The carbon footprints of HD and PD did not change significantly with the extension of dialysis time and remained stable at 2500–3500 and 200–800 kgCO2-eq. The influencing factors of them were different; some had opposite effects due to the different treatment modalities.
Conclusions
Our study demonstrated the feasibility of clinical pathway modification to reduce the carbon footprint. Our findings suggest that promoting peritoneal dialysis could effectively reduce the healthcare system's carbon footprint and promote sustainability.
Facile preparation of CuS microspheres based superhydrophobic paper with self-cleaning, high chemical stability, and photothermal effect enhanced separation of oil/water mixtures and emulsions
Authors: Cao Lele , Guo Zhibiao , Gao Xianming , He Zhiwei 
Published: September 2023

Abstract
Frequent oil spill accidents and the discharge of oily wastewaters cause significant threats to the marine ecological systems and human health. Herein, a CuS microspheres based superhydrophobic paper (CuS SP) has been prepared with the photothermal property for efficient oil/water separation and emulsions. To increase the durability, polydopamine is introduced to cellulosic fibers of the filter paper via self-assembly of dopamine. The CuS SP exhibits a water contact angle of 150.5° and an oil contact angle of ~ 0°, displaying excellent superhydrophobicity and superoleophilicity. Also, the CuS SP possesses excellent chemical resistance, thermal stability, mechanical durability and self-cleaning property. More importantly, the surface temperature of the CuS SP can reach about 48 ℃ after 100 s under one sunlight irradiation (1.0 kW·m-2). The separation flux of CCl4 can be increased about 14.3% under one sunlight irradiation by using the CuS SP when compared with that without sunlight irradiation. Although the photothermal effect has no obvious influence on the separation efficiency, the CuS SP still shows a high separation efficiency (> 99%) for CCl4 under 15 cyclic separation tests with/without sunlight irradiation. Besides, in situ experimental observations for the separation of oil-in-water emulsions have been investigated with the CuS SP by using an optical microscopy, and the possible mechanisms for the separation of oil-in-water emulsions are discussed. Thus, the as-prepared CuS SP shows great potentials in the practical applications of self-cleaning, and the separation of oil/water mixtures and emulsions.
Cost and Reliability Aware Scheduling of Workflows Across Multiple Clouds with Security Constraints
Authors: Banerjee Suman , Tekawade Atharva 
Published: September 2023

Abstract
Many real-world scientific workflows can be represented by a Directed Acyclic Graph (DAG), where each node represents a task and a directed edge signifies a dependency between two tasks. Due to the increasing computational resource requirements of these workflows, they are deployed on multi-cloud systems for execution. In this paper, we propose a complete framework for scheduling workflows in a multi-cloud system. In particular, we focus on minimizing the total execution time, and cost, and maximizing the reliability subject to security constraints. First, we use a Gravitational Search Algorithm (GSA) based approach to assign resources to tasks. Next, for a given task-resource mapping, we propose a cipher assignment algorithm that assigns security services to edges responsible for transferring data in a time-optimal manner subject to given security constraints. The proposed algorithms have been analyzed to understand their time and space requirements. We implement the algorithms and experiment with many real-world scientific workflows of varying sizes. We compare the performance of the proposed method with the state-of-art methods. We observe that our method outperforms the others in terms of cost and reliability, and is inferior in terms of makespan in some cases.