bluuebunny/crossref_metadata_2025 huggingface dataset:
Mycogenic Synthesis of gold nanoparticles mediated by the endophytic fungi Colletotrichum gloeosporioides, with special reference to In Vitro and In Silico studies
Authors: Rajasekar Arvindganth , Govindarajan Kathiravan , Deivasigamani Priyadharsini
Published: September 2023

The Mycogenic prospects of gold nanoparticles (AuNPs) using endophytic fungi C. gloeosporioides was evaluated. The AuNPs were confirmed and characterized by using UV –Vis spectroscopy with the shape and size of the nanoparticles ranging from 0.5 to 1 nm, depending on Scanning and Transmission microscopy. In addition, spot the capping factor responsible for the reduction of gold ions and the stabilization of nanoparticles prepared FTIR. The X-ray diffraction corresponds to the intense peaks at 2θ values recorded. The GCMS analysis studies showed the presence of active compounds Heptadecanoic acid, 16-methyl,-methyl ester AuNPs exhibited. In vitro anticancer activity against breast cancer cell line
MCF-7 with different concentrations such as 100, 50, 25, 12.5, 6.25, 3, 3.125, 1.562 and 0.781 μg/ml were treated. The cell viability in the percentage of the respective concentration was about 15.33 to 77.90. The synthesize synthesized mycogenic associated nanoparticles derived active major compound Heptadecanoic acid, 16-methyl,-methyl ester ligand was indicate good activity against BRCA 1 and HER 2 breast cancer cell line protein receptor. The present investigation reports it gives a clear role in the therapeutic and biocatalytic contribution of synthesized mycogenic gold nanoparticles.
Trends in visits to a 24-hour walk-in crisis mental health centre during the COVID-19 pandemic
Authors: Lemoine Jocelyne , Jiang Depeng , Vakil Tanvi , Bolton James , Hensel Jennifer
Published: September 2023

Objective:Visit rates were examined at a 24-hour mental health crisis centre in Manitoba, Canada that offered in-person and virtual crisis assessments in a stepped care model during the COVID-19 pandemic.
Methods: All visits from the three years prior to the pandemic until September 28, 2022 were retrieved from the electronic patient record. Mean weekly visits had the pandemic not occurred were predicted with an autoregressive integrated moving average model and compared with observed rates.
Results: Visit rates remained lower than predicted throughout the observation period, with the total number of visits reduced by an average of 34.1 per week (p <.001) at the onset of the pandemic (first wave), and that gap narrowing to an average of 18.9 visits per week (p=0.001) during the fourth wave. Thirteen percent of pandemic visits were virtual; highest during the first wave of the pandemic (average of 34.1% of visits per week) and decreased to an average of 5.6% of visits per week during the last measured period.
Conclusion: Further investigation is necessary to better understand this sustained pattern of reduced service utilization as we move beyond the pandemic.
Right Ventricular Dyssynchrony for the Prediction of Prognosis in Patients with Systemic Lupus Erythematosus-Aaociated Pulmonary Arterial Hypertension: A Study with Two-Dimensional Speckle Tracking
Authors: Tan Xiao-Lan , Deng Yan , Lan Wei-Fang , Dai Ping , Hu Jie , Lan Jing
Published: September 2023

Purpose
Pulmonary arterial hypertension (PAH) is a common complication of systemic lupus erythematosus (SLE), and PAH can cause right ventricle (RV) remodel and dyssynchrony. The aim of this study was to explore the value of RV dyssynchrony in predicting adverse clinical events in patients with systemic lupus erythematosus-aaociated pulmonary arterial hypertension (SLE-PAH) using two-dimensional speckle tracking echocardiography (2D-STE).
Methods
A total of 53 patients with SLE-PAH were assigned to an adverse clinical event group and a non-adverse clinical event group. The dyssynchrony of the RV (RV-SD6) was evaluated by 2D-STE. The clinical data of all participants were collected, and routine cardiac function parameters were measured by two-dimensional echocardiography, and analyzed for their correlation with RV-SD6. The predictive value of RV-SD6 in clinical adverse event was evaluated.
Results
RV-SD6 was negatively correlated with RV-FLS, RV-FAC, and TAPSE (r=-0.788, r=-0.363 and r=-0.325, respectively, all P < 0.01), while the correlation with RV-FLS was the strongest. linear regression analysis showed that RV-FLS was an independent risk factor for RV-SD6 (β=-1.40, 95% CI -1.65 ~ -1.14, P < 0.001). Cox regression analysis showed that RV-SD6 was independently associated with clinical adverse events (HR = 1.03, 95% CI 1 ~ 1.06, P < 0.05). RV-SD6 was highly discriminative in predicting clinical adverse events (AUC = 0.764), at a cutoff of 51.10 ms with a sensitivity of 83.3% and specificity of 68.3%.
Conclusion
RV-FLS was negatively correlated with RV-SD6 and was an independent risk factor for it. RV-SD6 can serve as an indicator for predicting the occurrence of adverse clinical events in SLE-PAH patients, with high sensitivity and specificity.
Is India’s reluctance to join the Belt and Road Initiative a missing opportunity? Synthetic Control Method Analysis.
Authors: Elish Eman , Ahmed Hossam Eldien
Published: September 2023

Eight years have passed since the launch of the Belt and Road Initiative (BRI) in 2013 which was put into action in 2014. Since then, a series of research papers have categorized their findings in relation to the initiative’s aims, targets, and estimations of possible outcomes. This research intends to measure the impact of India’s resilience to join this initiative on its net foreign direct investment by comparing its trajectory to the trajectory of the same outcome for a counterfactual unit of comparison from countries that have joined the initiative. The method that will be employed is the Synthetic control method (SCM) for a panel of 27 countries between 1990 to 2021. The empirical results show that the net Foreign Direct Investment FDI trajectory for India during the eight years from 2014 to 2021 has fallen compared to synthetic India constructed from BRI member countries. This research study is distinctive from other empirical contributions by using an inventive technique of SCM, which is a new experimental method to assess actual outcomes rather than predicting them, as in other conventional regression models. Moreover, the economic aspect of accessing the BRI has rarely been investigated, since most studies have qualitatively focused on the political aspect of the initiative. The results can assist in decision-making for India and other countries considering membership in this millennium initiative.
A Walk on Entrepreneurial Path: A Journey of Young Entrepreneurs
Authors: Sait Sofia Ahmed , Kasmir Mrs Lekha
Published: September 2023

The study "A Walk on the Entrepreneurial Path: A Study Showcasing Young Entrepreneurs" looks at the factors that affect young entrepreneurs' motivation. The study found that financial gain and professional autonomy are the two most significant motivators, followed by creativity, hardest work, and making a beneficial impact. Important internal management problems, such as a lack of expertise and knowledge, time management, marketing and sales, burnout and stress, and external environmental problems, such as financial, competitive, legal, and regulatory challenges, were also noted by the study. The study emphasizes the significance of access to capital, mentorship and networks, as well as recognition and assistance for young entrepreneurs, in order to overcome these difficulties. Furthermore, the report contends that adaptability and creativity, accessibility to tools and resources, and assistance from governments and policies may all help young entrepreneurs succeed and have a beneficial impact in the cutthroat economic environment. Overall, the study emphasizes the chances young entrepreneurs have to overcome obstacles and be successful in their business endeavors.
Parameters estimation and curves analysis for faults evaluation of a degraded photovoltaic module
Authors: AYANG ALBERT , Goron Deli , Mbakop Fabrice Kwefeu , . Yaouba , Saad Mohamad
Published: September 2023

In the present work, a fault evaluation method for photovoltaic arrays based on fault parameters identification and curves analysis is proposed for diagnosing the state of photovoltaic generators. An overview of the components, the modelling of the photovoltaic generator and the meaning of the parameters is established for relating parameters to photovoltaic components and environmental conditions. The analysis and investigation of the relationship between the maximum power points and the parameters variations are performed. Investigation on how degradations and failure on photovoltaic systems can affect parameters, is established. In this context, the methodology for diagnosing and monitoring defects based on photovoltaic estimated parameters is developed; the optimization technique maximum likelihood, is used for extracting health and faults parameters from the measured curves of the photovoltaic array. From residual vectors, the parameters which vary more are the series resistance, the shunt resistor, and the current of photon. The maximum power also changes and decreases from its reference value. The validation results prove deviations on parameters, which means that there are degradations and failures on the ARCO Solar M75 array after 20 years of outdoors operation. So, at the end of this analysis, it is recommended to act on the PV system through junction box, cell edges, wiring, busbars, and connectors.
A human cadaveric model for venous air embolism tool development
Authors: Robinson Nathaniel L. , Marcellino Chris , Johnston Matt , Abcejo Arnoley S.
Published: September 2023

Purpose
A human cadaveric model combining standard lung protective mechanical ventilation and modified cardiac bypass techniques was developed to allow investigation into automated modes of detection of venous air emboli (VAE) prior to in vivo human or animal investigations.
Methods
In this study, in order to create an artificial cardiopulmonary circuit in a cadaver that could mimic VAE physiology, the direction of flow was reversed from conventional cardiac bypass. Saline was circulated in isolation through the heart and lungs as opposed to the peripheral organs by placing the venous cannula into the aorta and the arterial cannula into the inferior vena cava with selective ligation of other vessels.
Results
Mechanical ventilation and this reversed cardiac bypass scheme allowed preliminary detection of VAE independently but not in concert in our current simulation scheme due to pulmonary edema in the cadaver. A limited dissection approach was used initially followed by a radical exposure of the great vessels, and both proved feasible in terms of air signal detection. We used electrical impendence as a preliminary tool to validate detection in this cadaveric model however we theorize that it would work for echocardiographic, intravenous ultrasound or other novel modalities as well.
Conclusion
A cadaveric model allows monitoring technology development with reduced use of animal and conventional human testing.
A Lightweight Log-Monitoring-Based Mitigation Tool Against WLAN Attacks
Authors: Saifan Ramzi , Radi Mohammad , Al-Dabbagh Hamsa , Mansour Badr
Published: September 2023

Wireless network attacks are some of the most common network security threats dealt with on a daily basis. Their ease of execution and effectiveness make them commonplace within most public networks. The goal of this paper is to develop a tool which provides defenses against these attacks, one which can also generate the attacks to test its own effectiveness in defending against them. The research involved the design, testing, and implementation of an attack/defense tool, one which benefits from a user-friendly user interface that greatly simplifies the testing process. The attacks were generated using existing tools, linked to one central interface. The defense methodology was script-based and created entirely from scratch. It was also linked to a single interface which continuously monitored logs. The results showed that the proposed defenses to the studied wireless attacks were effective at mitigation, or outright prevention. They were also more lightweight than existing solutions, making them more appealing for less powerful hardware.
Middle East Nurses Turnover Intention and Its Correlates Amid the Covid-19 Pandemic; A Systematic Review
Authors: Kunjavara Jibin , Alomari Albara Mohammad Ali , Mannethodi Kamaruddeen , Hassan Nesiya , Singh Kalpana , Joy George Vellaramcheril , Lenjawi Badriya Al
Published: September 2023

Global nursing scarcity was more evident during COVID-19. This study investigated the rates and contributing factors of turnover intention in the middle east through meta-analysis. Medline EMCARE, Cochrane, CINAHL, EMBASE, Ovid, Psych Info, PubMed, Science Direct, Scopus, and Web of Science databases searched, Protocol PROSPERO Registration Number was CRD42022337686. The turnover intention rate was 42.3% [CI:40%, 44.6%]. Working environment, stress, deployment to Covid, fear of infection, long working hours, shift duties, and lack of social support were the major contributing factors.
WITHDRAWN: Multi-omics predicts risk factors for kidney disease associated with RNA modification
Authors: Liu Xinran , Zhu Sai , Liu Xueqi , Luo Xiaomei , Wang Yikai , Chen Chaoyi , Jiang Ling , Wu Yonggui
Published: September 2023

Background
More and more evidence suggests that RNA modification play significant roles in kidney and may be ideal targets of kidney diseases. However, the specific mechanisms of RNA modification in the pathogenesis of kidney diseases remain unclear. Genome-wide association study (GWAS) have identified lots of genetic loci for kidney function and RNA modification. The identification and exploration of the functions of kidney function associated with RNAm-SNPs can help us to explore comprehensive understanding of the underlying mechanism of kidney disease and find potential therapeutic targets.
Methods
First, we examined the association of RNAm-SNPs with kidney function. Secondly, we performed eQTL and pQTL analyses to explore the function of these identified RNAm-SNPs. Finally, we evaluated the causality between RNAm-SNPs associated gene expression and circulating protein and kidney function by using mendelian randomization analysis and Bayesian colocalization test (coloc).
Results
370 RNAm-SNPs related to m6A, m1A, A-to-I, m5C, m7G and m5U modifications were identified. All of them was significantly associated with kidney function. Most of these RNAm-SNPs (60.27%) showed cis-eQTL effects in kidney tissues or in blood cells, while 78 RNAm-SNPs (21.08%) showed cis-pQTL effects in plasma. In addition, we demonstrate a causal association of some RNAm-SNPs associated gene expression and circulating protein with the risk for kidney function. Notably, we demonstrate a causal association of the gene expression in blood and plasma protein of ITIH4 with the risk for kidney function.
Conclusions
The study found the associations between RNAm-SNPs and kidney function. These SNPs can regulate gene expression and protein levels by RNA modification, eventually leading to kidney dysfunction. Our study provided direct evidences that connect the genetic risk of kidney disease to RNA modification and the new idea for potential therapeutic targets of prevention and treatment of kidney disease.
Learning Fast Diffeomorphic Registration for Cardiac Motion Estimation in 3D Echocardiography
Authors: Ghadim Yalda Zafari , Azarnoush Hamed
Published: September 2023

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

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

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

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

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

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

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

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

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

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

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

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

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

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.
Prevalence and correlates of depression in early childhood home visitors serving rural Colombian families
Authors: Pérez Catalina , Bernal Raquel , Macias Mariafernanda , Barrueco Sandra
Published: September 2023

Purpose Limited information is available on early childhood provider depression, particularly in lower and middle-income (LMIC) countries, yet evidence from diverse fields indicates that depression negatively affects work functioning. Given extensive investment worldwide in early childhood home visiting programs, understanding home visitor mental health may help improve services for families. The current investigation examined the prevalence and correlates of depression in early childhood home visitors working in rural Colombia.Methods Three hundred and forty-one home visitors (N = 341) completed the Spanish versions of the Center for Epidemiological Studies Depression Scale (CES-D) and the Knowledge of Infant Development Inventory, and self-reported socio-demographic and job-related information. Cross-sectional, clustered statistical analyses were employed in STATA Software.Results Thirteen percent of home visitors met the cut off score for depression. Higher home visitor depression was related to maternal depression among beneficiaries. Additionally, depression was higher among home visitors who were older and those who identified their marital status as separated. Depression was lower among home visitors who completed more home visits and those with higher educational attainment.Conclusions Early childhood providers experienced interconnections in their depression with those whom they served. In addition, social environmental factors related to home visitor depression were identified. The results from this study speak to the importance of considering providers’ mental health as part of the effort of disseminating high quality early childhood home visiting programs. Program and clinical implications are further discussed.
Effects of dietary phytol supplementation on growth performance, immunological parameters, intestinal bacteria, and prevention of oxidative stress following transportation of Nile tilapia, Oreochromis niloticus
Authors: Ahani Saman , Ahani Sara , Yousefi Morteza , Mirghaed Ali Taheri , Rahman Afaf N. Abdel
Published: September 2023

In this study, Nile tilapia, Oreochromis niloticus, fingerlings (2.00 ± 0.02) were fed diets (crude protein 345 g/kg; crude lipid 86.8 g/kg) containing 0 (CTL), 75 (PH-75), 150 (PH-150), and 300 (PH-300) mg/kg phytol for 60 days, at 4% of biomass. The fish were reared in sixteen 70-L tanks (n = 4, each with 40 fish). After 60 days rearing, the fish were subjected to 6-h transportation to monitor the hepatic antioxidant parameters. The results showed that dietary 75 mg/kg phytol significantly improved fish growth (P < 0.001) and feed efficiency (P = 0.015). Plasma lysozyme (P = 0.004) alternative complement (P = 0.006), alkaline phosphatase (P = 0.014) significantly increased in PH-75, 75PH/150PH, and PH-75/PH-300 treatments, respectively. All phytol-treatments led to significant (P = 0.001) increase in the blood neutrophil count. The PH-300 treatment resulted in significantly higher blood WBC (P = 0.008), monocyte (P = 0.010), and eosinophil (P < 0.001) counts, compared to CTL. Phytol also modulated intestinal microbiota by reducing the number of total viable bacteria in PH-75 and PH-150 (P = 0.027) and increasing lactic acid bacteria in PH-75 (P = 0.017). PH-75 and PH-150 had highest survival, antioxidant enzymes, reduced glutathione levels, lowest lipid peroxidation, before and/or after the transportation. PH-300 treatment showed an elevation lipid peroxidation, after the transportation. These findings suggest that dietary phytol may be a good supplement for improving the health and growth performance of Nile tilapia, and the recommended level is 75 mg/kg.
Activation patterns in male and female forebrain circuitries during food consumption under novelty
Authors: Greiner Eliza M. , Witt Mary E. , Moran Stephanie J. , Petrovich Gorica D.
Published: September 2023

The influence of novelty on feeding behavior is significant and can override both homeostatic and hedonic drives due to the uncertainty of potential danger. Previous work found that novel food hypophagia is enhanced in a novel environment and that males habituate faster than females. The current study’s aim was to identify the neural substrates of separate effects of food and context novelty. Adult male and female rats were tested for consumption of a novel or family food in either a familiar or in a novel context. Test-induced Fos expression was measured in the amygdalar, thalamic, striatal, and prefrontal cortex regions that are important for appetitive responding, contextual processing, and reward motivation. Food and context novelty induced strikingly different activation patterns. Novel context induced Fos robustly in almost every region analyzed, including the central (CEA) and basolateral complex nuclei of the amygdala, the thalamic paraventricular (PVT) and reuniens nuclei, the nucleus accumbens (ACB), the medial prefrontal cortex prelimbic and infralimbic areas, and the dorsal agranular insular cortex (AI). Novel food induced Fos in a few select regions: the CEA, anterior basomedial nucleus of the amygdala, anterior PVT, and posterior AI. There were also sex differences in activation patterns. The capsular and lateral CEA had greater activation for male groups and the anterior PVT, ACB ventral core and shell had greater activation for female groups. These activation patterns and correlations between regions, suggest that distinct functional circuitries control feeding behavior when food is novel and when eating occurs in a novel environment.
Characterizing industry payments to ophthalmologists before and after onset of the COVID-19 pandemic
Authors: Choudhry Hassaam S , Choudhry Hannaan S , Burton Carter , Patel Aman M , Patel Riya , Li Ximin , Berkowitz Sean , Kaleem Mona A
Published: September 2023

Purpose
The COVID-19 pandemic had profound effects on many different aspects of our healthcare system and the relationship between industry and physicians was no exception. The present database study evaluates industry payments to ophthalmologists in order to identify whether there are significant differences in industry payments to ophthalmologists before and after onset of the pandemic.
Methods
The Centers for Medicare & Medicaid Services Open Payments Database was queried for all ophthalmologists who received industry payments between 2018 and 2021. Pre-Covid was defined as 2018–2019 while post-Covid was defined as 2020–2021. Payment date, value, type, company making payment, and state of recipient were recorded. The top ten companies and states in terms of payment value were included in analysis. Generalized Estimating Equations (GEE) modeling was used to assess significance.
Results
There were 729,263 industry payments to 20,832 ophthalmologists totaling $817,892,867.54 included for analysis in this study. We found that there was a significant increase in the mean value of research payments and a significant decrease in the mean value of general payments after the onset of the pandemic (both p < 0.001). We also report significant changes in industry payments to ophthalmologists based on the company making the payment and the state in which the ophthalmologist practices.
Conclusions
Our results suggest that significant differences exist in industry payment patterns to ophthalmologists following onset of the COVID-19 pandemic. Understanding underlying reasons for the observed differences may improve our understanding of the relationship between industry and clinical ophthalmology.
Portability profiled power analysis based on deep domain adaptation
Authors: Li Xiang , Yang Ning , Liu Weifeng , Zeng Lu , Chen Aidong
Published: September 2023

The security of password information is essential to protect personal privacy and sensitive data. In recent years, deep learning-based side-channel profiled analysis has been more in-depth research. However, the differences between devices caused by circuit design, process parameters and other hardware characteristics have not been well solved, and the generalization ability of pre-trained models on new devices is poor, and the prediction performance is low. Therefore, this paper proposes a new method, Portability Profiled Power Analysis (PPPA) strategy, which combines domain adaptive and deep learning technology to model and calibrate the domain difference between the profiling device and the target device. Improve model adaptability in different device environments. Experiments show that the proposed method can recover the key information of different devices and effectively reduce the influence of domain differences caused by different devices.