bluuebunny/crossref_metadata_2025 huggingface dataset:
Mediatory Effect of Inflammatory Markers (IL-1β and PAI-1) on Association of Dietary Total Antioxidant Capacity and Body Composition in Overweight and Obese Women: A Cross-Sectional Study
Authors: Radkhah Parisa , Mirzababaei Atieh , Shiraseb Farideh , Hosseininasab Dorsa , Clark Cain C. T. , Mirzaei Khadijeh
Published: May 2022

Background. Obesity is considered a state of chronic low-grade inflammation. Different components of the diet, like antioxidants, can have anti-inflammatory effects or cause chronic inflammation. This study investigated the dietary TAC and inflammatory markers and body composition in obese and overweight women. Methods. This cross-sectional study was conducted on 259 women with overweight and obesity. Dietary intake was assessed by using an FFQ with 147 items, and DTAC was used to evaluate the antioxidant capacity of the diet. The anthropometric measurements, body composition, and biochemical assessments were measured by standard protocols. Results. We observed a significant positive association between DTAC and consumption of fruits (P = 0.021), vegetable oils (P < 0.001), potassium (P = 0.006), manganese (P = 0.003), and caffeine (P < 0.001), after adjusting confounders. After adjusting for age, energy intake, and physical activity, there was a significant correlation between DTAC and fat-free mass (FFM) (P:0.054), fat-free mass index (FFMI) (P:0.012), waist circumference (WC) (P:0.002), and visceral fat level (VFL) (P:0.063). FFM, FFMI, waist circumference (WC), and visceral fat area (VFA) were mediated by IL-1β. FFM, VFL, VFA, and WC were mediated by PAI-1. Conclusion. Some anthropometric indices were associated with DTAC, mediated by augmenting serum levels of IL-1β and PAI-1. Intake of foods rich in antioxidants could represent a protective strategy against chronic diseases, such as cardiovascular disease.
Autoantibodies to Zinc Transporter 8 and SLC30A8 Genotype in Type 1 Diabetes Childhood: A Pioneering Study in North Africa
Authors: Fakhfakh Raouia , Kmiha Sana , Tahri Safa , Feki Sawsan , Zouidi Ferjeni , Abida Olfa , Hachicha Mongia , Kammoun Thouraya , Masmoudi Hatem
Published: May 2022

Background. Type 1 diabetes (T1D) occurs as a result of insulin deficiency due to destructive lesions of pancreatic β cells. In addition to classical autoantibodies (Abs) to islet cell antigens, antizinc transporter 8 Abs (ZnT8-Ab) have been recently described in T1D. Objective. As no data on ZnT8-Ab in Tunisian patients has been reported, we aim to evaluate the relationships between ZnT8-Ab, ZnT8 coding gene (SLC30A8) promoter polymorphism, and T1D risk in newly diagnosed children. Methods. ZnT8-Ab were measured in the serum of T1D newly affected children (

n
=
156

) who were admitted to the pediatric department of the Hedi Chaker University Hospital of Sfax. Rs13266634 was genotyped in T1D children and 79 of their first-degree parents. The SPSS software was used to analyze the serological data. Allelic association analysis was conducted with family-based association tests implemented in the FBAT program v1.5.1. Results. ZnT8-Ab was detected in 66/156 (42.3%) of T1D newly diagnosed children. Among them, 6 (9%) presented ZnT8-Ab as the only humoral marker. The inclusion of ZnT8-Ab increased the number of Ab-positive patients to 90% and reduced the negative ones by 27%. There was no evidence of any overtransmission of any allele of the rs13266634 C/T polymorphism from parents to affected T1D children, nor of any correlation with any clinical or serological parameter. After the T1D disease onset age adjustment, a significant association was observed with the C allele suggesting that it could have a susceptibility role. Conclusion. ZnT8-Ab appears as a relevant diagnostic marker for T1D in Tunisian children, especially at the onset of the disease as teenagers.
Fixed Point Results for Single and Multivalued Maps on Partial Extended
b
-Metric Spaces
Authors: Aydi Hassen , Batul Samina , Aslam Muhammad , Sagheer Dur-e-Shehwar , Ameer Eskandar
Published: May 2022

This article is based on the concept of partial extended

b

-metric spaces, which is inspired by the notions of new extended

b

-metric spaces and partial metric spaces. Fixed point results for single and multivalued mappings on such spaces are also presented. Few examples are also provided to elaborate the concepts.
Artificial Intelligence Limb Rehabilitation System on Account of Virtual Reality Technology on Long-Term Health Management of Stroke Patients in the Context of the Internet
Authors: Bai Yu , Liu Fang , Zhang Hua
Published: May 2022

This study was aimed at discussing artificial intelligence (AI) limb rehabilitation system on account of virtual reality (VR) on long-term health management of stroke patients. In the study, AI limb rehabilitation system on account of VR technology was compared with traditional drug therapy, and effects of the two therapies on long-term health management of stroke patients were compared. Fifty patients with stroke in the hospital were randomly divided into experimental group and control group with 25 patients in each group. Patients in experimental group were treated with AI limb rehabilitation system on account of VR technology, and those in control group were treated with traditional drug therapy. To compare and judge the recovery of patients’ physical ability, patients in the two groups were compared in physical movement ability and daily living activity ability after 10-week treatment. After 10-week treatment, Fugl-Meyer assessment-upper extremity (FMA-UE), Fugl-Meyer assessment-lower extremity (FMA-LE), the Hong Kong version of functional test for the hemiplegic upper extremity (FTHUE-HK), Barthel index (BI) daily living (ADL) activities, and Berg balance scale (BBS) in control group were lower than those in experimental group, but the score of MWS was higher than that of experimental group (

P
<
0.05

). AI limb rehabilitation system on account of VR technology could effectively recover the daily health management of stroke patients, and its effect was significantly higher than that of traditional drug therapy. This method could be popularized in clinic.
The Time-Dependent Reliability Analysis of Brake Piston Special-Shaped Seal of the Caliper Disc Brake
Authors: Sun Meng , Lu Liqun , Bai Xin , Ni Huiting , Shi Leilei
Published: May 2022

To solve the brake caliper disc brake piston sealing ring in the high temperature, pressure, and changeful, complex working environments, such as vibration failure cause brake short service life, low reliability, in the original brake piston O seal ring and cross section, the research, based on the standard of sealing ring, such as special-shaped seal structure is put forward in order to improve the reliability of the caliper disc brake piston sealing performance. Based on the basic concept of time-varying reliability and the theoretical basis of stress-strength interference model, the time-varying reliability model of the plum blossom seal ring of the brake piston under shear stress failure and leakage failure modes was established. The reliability of the plum blossom seal ring under single failure mode and multiple failure modes is obtained. The results show that under the same conditions, the reliability of the plum blossom seal ring is greater than that of the O seal ring, and its sealing performance is better than that of the O seal ring.
Mixed Interlaminar Fracture Toughness and Durability of Composites under Humid and Hot Conditions
Authors: Li Mingyong , Meng Xia , Zhang Qingyi
Published: May 2022

Composite material is a new material prepared by several raw materials with different forms or properties through new processing methods. The composite not only maintains the advantages of the properties of each component but also can obtain the comprehensive properties that cannot be achieved by a single component through the complementarity and correlation of the properties of each component. The purpose of this paper is to study the effect of wet and hot conditions on the interlaminar fracture toughness and durability of composites. In this paper, the interlaminar fracture toughness and durability are studied, and the prediction and analysis method under wet and hot conditions is carried out. The effects of hot and humid conditions on interlaminar fracture toughness and durability were analyzed. The experimental results show that the longitudinal compressive strength of the unidirectional composite at 120°C and 1.00% moisture absorption is 29.53% lower than that at 20°C and 0.50% moisture absorption. Due to the high moisture absorption of aramid fiber, the longitudinal compressive strength of unidirectional aramid composite fiber will be significantly reduced in the humid and warm environment.
Analysis on Total Factor Productivity and Differences of Industrial Internet Concept Companies
Authors: Hu Yuanning , Xu Hongyi
Published: May 2022

Based on the Malmquist-DEA model and the DEA-BCC model, using the data of 53 industrial Internet-listed companies, the total factor productivity (TFP), technological progress (TC), and technical efficiency changes of the industrial Internet industry were measured from static and dynamic perspectives (EC), and used the coefficient of variation to further analyze the variance variables that measure the differences between enterprises in various subsectors in the industrial Internet industry. The study pointed out that the overall productivity level of the industrial Internet industry in 2015 to 2019 was low, and the fluctuation range was large, especially the sharp drop in productivity in 2016 to 2017, which had a serious impact on the entire industry. At the same time, changes in technical efficiency are the main reason for the decline in total factor productivity after 2015. Among various industries, the Malmquist indices of manufacturing and information transmission, software, and information technology services are all less than 1, and there is little difference in production efficiency and changes between the two. This study provides a reference for the productivity measurement of the industrial Internet industry based on the Malmquist-DEA model and provides practical inspiration for future management activities.
First Reported Case of Reverse Pott’s Disease
Authors: Ramachandran Lintu , Lyu David , Baloch Luqman , Affinati Mario
Published: May 2022

Tuberculosis, while rare, is a disease that can have several extrapulmonary manifestations. One such known extrapulmonary manifestation of disseminated TB is vertebral osteomyelitis, often referred to as “Pott’s Disease.” We present the case of a patient who underwent back surgery with allogenic bone graft who developed vertebral osteomyelitis and subsequently had disseminated tuberculosis, from an infected bone graft. We review current guidelines for allograft tissue screening and discuss the possible need for standardizing tuberculosis screening for bone allografts.
[Retracted] Dynamic Alterations and the Affecting Attributes of the Unbalanced Economic Development in the Basin of the Yellow River: Analysis Utilizing Population‐Weighted Coefficient of Variation
Authors: Zhao Ziqiang
Published: May 2022

This paper employs a method called the population‐weighted coefficient of variation (PWCV) to investigate the dynamic changes related to the imbalanced economic progression in the Yellow River Basin (YRB) between 2010 and 2020, and also analyzes the affecting attributes that are related to industry‐specific and the spatial property of this change through the double decomposition of the PWCV method. The imbalanced economic progression in the YRB that tends to decline generally was found. The basin of the Yellow River, with three constituent regions, namely upper, middle, and lower streams of it, experiencing an imbalanced development has roots in the condition of the imbalanced economic progression in the YRB. However, since 2018, the imbalance ratio between regions has expanded. When the industrial decomposition is under consideration, the YRB experiences imbalanced economic development due to the dissimilarity between the industrial implementations, called the secondary and tertiary. Before 2018, the imbalance caused by the difference in the secondary industry accounted for more than 50%, while the imbalance led by the difference in the tertiary industry exceeded the imbalance caused by the secondary industry after 2018.
Magnetic Field Effect on Heat and Momentum of Fractional Maxwell Nanofluid within a Channel by Power Law Kernel Using Finite Difference Method
Authors: Lashin Maha M. A. , Usman Muhammad , Asjad Muhammad Imran , Ali Arfan , Jarad Fahd , Muhammad Taseer
Published: May 2022

The mathematical model of physical problems interprets physical phenomena closely. This research work is focused on numerical solution of a nonlinear mathematical model of fractional Maxwell nanofluid with the finite difference element method. Addition of nanoparticles in base fluids such as water, sodium alginate, kerosene oil, and engine oil is observed, and velocity profile and heat transfer energy profile of solutions are investigated. The finite difference method involving the discretization of time and distance parameters is applied for numerical results by using the Caputo time fractional operator. These results are plotted against different physical parameters under the effects of magnetic field. These results depicts that a slight decrease occurs for velocity for a high value of Reynolds number, while a small value of Re provides more dominant effects on velocity and temperature profile. It is observed that fractional parameters α and β show inverse behavior against u(y, t) and θ(y, t). An increase in volumetric fraction of nanoparticles in base fluids decreases the temperature profile of fractional Maxwell nanofluids. Using mathematical software of MAPLE, codes are developed and executed to obtain these results.
Security and Makespan Trade-Off Strategy in Fog-Enabled IoT Networks
Authors: Wang Xiaoli , Veeravalli Bharadwaj , Tan Yulong , Tong Zhihao
Published: May 2022

Fog computing relieves the Internet of Things (IoT) from a heavy burden of workload computation, consequently minimizes workload makespan, and reduces the considerable energy consumption of IoT devices. However, the fog-enabled IoT poses a risk to data security due to the intrinsic open and distributed structure of the fog. Hence, it is imperative to search for an optimal scheduling strategy on fog nodes to minimize workload makespan, while guaranteeing high data security. In this study, we investigate the trade-off between security and makespan and propose a multiobjective optimization model to optimize them simultaneously. To achieve this goal, we design an evolutionary algorithm together with two effective measures to handle large-scale partitionable workloads: a conflict-free multi-installment scheduling (ConfMIS) strategy as well as a security criterion based on Eigenvector centrality measure. Experimental results show that the proposed algorithm can generate a set of widely spread and uniformly distributed solutions in the decision space. Among these representative solutions, system designers/decision-makers can choose their favorite one based on specific IoT application demands.
[Retracted] A Composite Particle Swarm Optimization Algorithm for Hospital Equipment Management Risk Control Optimization and Prediction
Authors: Li Jinghui , Zhang Li , Gu Xiangmin
Published: May 2022

Aiming at the problem that particles cannot realize multidimensional analysis and poor global search ability, a composite particle swarm optimization algorithm is proposed, improving the accuracy of particle swarm optimization. Firstly, k‐clustering is used to cluster risk management particle swarm optimization. The advantages of particle swarm optimization have to be given full play, and the risk of hospital equipment management from various aspects has to be controlled. Then, the multidimensional particle swarm is segmented to obtain an ordered multidimensional risk particle swarm set, which provides a basis for later risk prediction. Finally, through the fusion function of multidimensional risk particle swarm, the risk particle swarm set based on the clustering degree is constructed, and the optimal extreme value is obtained, so as to improve the accuracy of management risk calculation results. Through MATLAB simulation analysis, it can be seen that the composite particle swarm optimization algorithm is better than particle swarm optimization algorithm in global search accuracy and search time. Moreover, the calculation time and accuracy are better. Therefore, the composite particle swarm optimization algorithm can be used to analyze the risk of hospital equipment and effectively control the risk of hospital equipment management.
Experimental and Numerical Studies of Supercritical Water Flooding for Offshore Heavy Oil Recovery
Authors: Zhang Yanyu , Li Xiaoyu , Sun Xiaofei , Zheng Wei , Tan Xianhong , Cai Jiaming
Published: May 2022

Supercritical water (SCW) is a novel thermal agent that has been recently utilized for the production of heavy oil. However, a lack of knowledge about its recovery mechanisms limits the application of SCW. In this study, pyrolysis and sandpack flooding experiments were performed to investigate the mechanisms and viability of SCW flooding. Then an innovative simulation model was developed for SCW flooding. Finally, sensitivity studies on SCW flooding were conducted by the developed model. The results showed that SCW flooding yielded a 13.99% increase in oil recovery in comparison to steam flooding, indicating that SCW flooding is technically applicable to offshore heavy oil reservoirs. Heavy oil upgrading in SCW can suppress coke formation and plays an important role in oil recovery. A novel numerical model for SCW flooding was established based on a history match of experiments. The simulation results suggested that during SCW flooding, SCW could induce heavy oil upgrading to increase oil mobility, and long-term injection of SCW may cause the formation of coke deposits. Higher injection temperatures and pressures would benefit the production performance of SCW flooding. However, an unlimited increase in temperature would damage formations by significant coke deposits.
Segmentation for Multimodal Brain Tumor Images Using Dual-Tree Complex Wavelet Transform and Deep Reinforcement Learning
Authors: Liu Gang , Li Xiaofeng , Cai Yingjie
Published: May 2022

Image segmentation is an effective tool for computer-aided medical treatment, to retain the detailed features and edges of the segmented image and improve the segmentation accuracy. Therefore, a segmentation algorithm using deep reinforcement learning (DRL) and dual-tree complex wavelet transform (DTCWT) for multimodal brain tumor images is proposed. First, the bivariate concept in DTCWT is used to determine whether the image noise points belong to the real or imaginary region, and the noise probability is checked after calculation; second, the wavelet coefficients corresponding to the region where the noise is located are selected to transform the noise into normal pixel points by bivariate; then, the conditional probability of occurrence of marker points in the edge and center regions of the image is calculated with the target points, and the initial segmentation of the image is achieved by the known wavelet coefficients; finally, the segmentation framework is constructed using DRL, and the network is trained by loss function to optimize the segmentation results and achieve accurate image segmentation. The experiment was evaluated on BraTS2018 dataset, CQ500 dataset, and a hospital brain tumor dataset. The results show that the algorithm in this paper can effectively remove multimodal brain tumor image noise, and the segmented image has good retention of detail features and edges, and the segmented image has high similarity with the original image. The highest information loss index of the segmentation results is only 0.18, the image boundary error is only about 0.3, and F-value is high, which indicates that the proposed algorithm is accurate and can operate efficiently, and has practical applicability.
Provable Cloud Data Transfer with Efficient Integrity Auditing for Cloud Computing
Authors: Yang Changsong , Xiao Jun , Liu Yueling , Liu Yang
Published: May 2022

Due to the promising market prospects, more and more enterprises invest cloud storage and offer on-demand data storage services, which are characterized by distinct quality; thus, users would dynamically change the cloud service providers and transfer their outsourced data. However, the original cloud server might not honestly transfer the outsourced data for saving overhead, and the outsourced data might be polluted during the transfer process. Therefore, how to achieve secure outsourced data transfer has become a primary concern of users. To solve this issue, we put forward a solution for the issue of provable cloud data transfer, which can also simultaneously realize efficient data integrity auditing. By taking the advantages of Merkle sum hash tree (MSHT), our presented scheme can satisfy verifiability without dependency on a third party auditor (TPA). Meanwhile, the formal security proof can demonstrate that our presented scheme meets all of the expected security requirements. Finally, we implement our presented scheme and offer the precise performance evaluation, which can intuitively show the high-efficiency and practicality of our presented scheme in the real-world applications.
Note on Precise Asymptotics in the Law of the Iterated Logarithm under Sublinear Expectations
Authors: Xu Mingzhou , Cheng Kun
Published: May 2022

By using Lebesgue bounded convergence theorem, we prove precise asymptotics in the law of the iterated logarithm for independent and identically distributed random variables under sublinear expectation.
Urbanization Detection Using LiDAR-Based Remote Sensing Images of Azad Kashmir Using Novel 3D CNNs
Authors: Hameed Mazhar , Yang Fengbao , Bazai Sibghat Ullah , Ghafoor Muhammad Imran , Alshehri Ali , Khan Ilyas , Baryalai Mehmood , Andualem Mulugeta , Jaskani Fawwad Hassan
Published: May 2022

An important measurable indicator of urbanization and its environmental implications has been identified as the urban impervious surface. It presents a strategy based on three-dimensional convolutional neural networks (3D CNNs) for extracting urbanization from the LiDAR datasets using deep learning technology. Various 3D CNN parameters are tested to see how they affect impervious surface extraction. For urban impervious surface delineation, this study investigates the synergistic integration of multiple remote sensing datasets of Azad Kashmir, State of Pakistan, to alleviate the restrictions imposed by single sensor data. Overall accuracy was greater than 95% and overall kappa value was greater than 90% in our suggested 3D CNN approach, which shows tremendous promise for impervious surface extraction. Because it uses multiscale convolutional processes to combine spatial and spectral information and texture and feature maps, we discovered that our proposed 3D CNN approach makes better use of urbanization than the commonly utilized pixel-based support vector machine classifier. In the fast-growing big data era, image analysis presents significant obstacles, yet our proposed 3D CNNs will effectively extract more urban impervious surfaces.
Linear Stability of Magneto Viscoelastic Walter’s

B

′

Type with Heat and Mass Transfer
Authors: Mostafa D. M.
Published: May 2022

In this paper, the couple influence of axial magnetic field and the heat and mass transfer on two rotating cylinders of Walter’s

B

′

viscoelastic fluids by using the potential flow theory of viscoelastic fluid has been investigated. The normal mode method is used to compute the growth rate of disturbance. The influence of gravity is ignored at the interface, while the effect of surface tension is present in the analysis. The effect of the parameters on the stability is studied. It is found that the rotation of the inner cylinder induces stability. Furthermore, the viscoelastic ratio of fluids has a stabilizing influence. The heat and mass transfer, magnetic permeability ratio, and Ohnesorge number have a stabilized influence, while viscosity ratio of fluids, density ratio of fluids, and axial magnetic field have destabilizing influence on the considered system.
Current-Volt Biosensing “Cystatin C” on Carbon Nanowired Interdigitated Electrode Surface: A Clinical Marker Analysis for Bulged Aorta
Authors: Chen Xi , Kang Jie , Sun Qiu , Liu Cheng , Wang Hongling , Wang Chen , Gopinath Subash C. B.
Published: May 2022

A carbon nanowire-modified surface with interdigitated electrode (IDE) sensing system was introduced to identify abdominal aortic aneurysm biomarker “papain,” also known as cysteine protease, used as the capture probe to identify Cystatin C. Papain was immobilized through the covalent integration of amine group on papain and the carboxyl group with carbon nanowire. This papain-modified electrode surface was utilized to detect the different concentrations of Cystatin C (100 pg/mL to 3.2 ng/mL). The interaction between papain and Cystatin C was monitored using a picoammeter, and the response curves were compared. With increasing Cystatin C concentrations, the total current levels were gradually increased with a linear range from 200 pg/mL to 3.2 ng/mL, and the current differences were plotted and the detection limit of Cystatin C was calculated as 200 pg/mL. The averaging of three independent experiments (n = 3) was made with 3δ estimation, and the determination coefficient was y = 1.8477 × 0.7303 and R2 = 0.9878. Furthermore, control experiments with creatinine and gliadin failed to bind the immobilized papain, indicating the specific detection of Cystatin C.
Identification of Potential Biomarkers for Ryanodine Receptor 1 (RYR1) Mutation-Associated Myopathies Using Bioinformatics Approach
Authors: Wang Xi , Kong Chang , Liu Pan , Geng Wujun , Tang Hongli
Published: May 2022

Background. Myopathies related to Ryanodine receptor 1 (RYR1) mutation are the most common nondystrophy muscle disorder in humans. Early detection and diagnosis of RYR1 mutation-associated myopathies may lead to more timely treatment of patients, which contributes to the management and preparation for malignant hyperthermia. However, diagnosis of RYR1 mutation-associated myopathies is delayed and challenging. The absence of diagnostic morphological features in muscle biopsy does not rule out the possibility of pathogenic variations in RYR1. Accordingly, it is helpful to seek biomarkers to diagnose RYR1 mutation-associated myopathies. Methods. Skeletal muscle tissue microarray datasets of RYR1 mutation-associated myopathies or healthy persons were built in accordance with the gene expression synthesis (GEO) database. Differentially expressed genes (DEGs) were identified on the basis of R software. Genes specific to tissue/organ were identified through BioGPS. An enrichment analysis of DEGs was conducted in accordance with the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO). We also built protein-protein interaction (PPI) networks to explore the function and enrichment pathway of DEGs and the identification of hub genes. Lastly, the ROC curve was drawn for hub genes achieving specific expressions within skeletal muscle. Moreover, the area under the curve (AUC) was obtained to calculate the predictive value of key genes. The transcription factors of hub genes achieving specific expressions within skeletal muscle were predicted with the use of the iRegulon plugin. Results. We identified 170 DEGs among 11 muscle biopsy samples of healthy subjects and 17 muscle biopsy samples of RYR1 mutation-associated myopathy patients in the dataset. Among the above DEGs, 30 genes achieving specific expressions within tissues/organs were found. GO and KEGG enrichment analysis of DEGs mainly focused on muscle contraction, actin-mediated cell contraction, actin filament-based movement, and muscular sliding. 12 hub genes were identified with the use of Cytoscape. Four hub genes were specifically expressed in skeletal muscle tissue, including MYH1 (AUC: 0.856), TNNT3 (AUC: 0.840), MYLPF (AUC: 0.786), and ATP2A1 (AUC: 0.765). The iRegulon predicted results suggested that the transcription factor MYF6 was found with the highest reliability. Conclusions. Four skeletal muscle tissue-specific genes were identified, including MYH1, TNNT3, MYLPF, and ATP2A1, as the potential biomarkers for diagnosing and treating RYR1 mutation-associated myopathies, which provided insights into the transcriptome-level development mechanism. The transcription factor MYF6 may be a vital upstream regulator of the above biomarkers.
Application of the VR Sensor Image Combined with Sports Games in the Treatment of Autistic Children
Authors: Wang Li
Published: May 2022

In order to study the application of the VR sensor image combined with sports games in the treatment of autistic children, this study mainly takes qualitative research as the main research method and uses physical intervention based on sensory integration training to study autistic children aged 6-9. Three children, A, B, and C, are mainly selected in order to promote the improvement of children’s physical function and motor skills and further have a positive impact on behavior and psychology. By analyzing the effects measured before and after the experiment, this paper explores the impact of sports intervention based on sensory integration training on the motor ability of autistic children over the age of 6, as well as its impact on their sensory integration function, daily behavior, and psychological activities, so as to enrich the empirical research on the content, principles, implementation methods, and specific implementation process of sensory integration training, to provide reference and enlightenment for schools, institutions, and children’s parents engaged in educational intervention for autistic children.
Proteome Analysis of Pancreatic Tumors Implicates Extracellular Matrix in Patient Outcome
Authors: Silwal-Pandit Laxmi , Stålberg Stina M. , Johansson Henrik J. , Mermelekas Georgios , Lothe Inger Marie B. , Skrede Martina L. , Dalsgaard Astrid Marie , Nebdal Daniel J. H. , Helland Åslaug , Lingjærde Ole Christian , Labori Knut Jørgen , Skålhegg Bjørn S. , Lehtiö Janne , Kure Elin H.
Published: May 2022

Pancreatic cancer remains a disease with unmet clinical needs and inadequate diagnostic, prognostic, and predictive biomarkers. In-depth characterization of the disease proteome is limited. This study thus aims to define and describe protein networks underlying pancreatic cancer and identify protein centric subtypes with clinical relevance. Mass spectrometry–based proteomics was used to identify and quantify the proteome in tumor tissue, tumor-adjacent tissue, and patient-derived xenografts (PDX)-derived cell lines from patients with pancreatic cancer, and tissues from patients with chronic pancreatitis. We identified, quantified, and characterized 11,634 proteins from 72 pancreatic tissue samples. Network focused analysis of the proteomics data led to identification of a tumor epithelium–specific module and an extracellular matrix (ECM)-associated module that discriminated pancreatic tumor tissue from both tumor adjacent tissue and pancreatitis tissue. On the basis of the ECM module, we defined an ECM-high and an ECM-low subgroup, where the ECM-high subgroup was associated with poor prognosis (median survival months: 15.3 vs. 22.9 months; log-rank test, P = 0.02). The ECM-high tumors were characterized by elevated epithelial–mesenchymal transition and glycolytic activities, and low oxidative phosphorylation, E2F, and DNA repair pathway activities. This study offers novel insights into the protein network underlying pancreatic cancer opening up for proteome precision medicine development.

Significance:

Pancreatic cancer lacks reliable biomarkers for prognostication and treatment of patients. We analyzed the proteome of pancreatic tumors, nonmalignant tissues of the pancreas and PDX-derived cell lines, and identified proteins that discriminate between patients with good and poor survival. The proteomics data also unraveled potential novel drug targets.
Neuromuscular Aging: A Case for the Neuroprotective Effects of Dancing
Authors: Franchi Martino V. , Badiali Francesca , Sarto Fabio , Müller Patrick , Müller Notger G. , Rehfeld Kathrin , Monti Elena , Rankin Debbie , Longo Stefano , Lund Jon , Hökelmann Anita , Narici Marco
Published: May 2022

Aim: We planned a cross-sectional investigation (study 1) and a longitudinal training intervention (study 2) to investigate whether recreational dancing affords greater neuroprotective effects against age-related neuromuscular junction (NMJ) degeneration compared to general fitness exercise training. Methods: In study 1, we recruited 19 older volunteers regularly practising dancing (older dancers [OD]) and 15 recreationally physically active older individuals (OA) and physical performance, muscle morphology, muscle function, and NMJ stability (from serum C-terminal agrin fragment [CAF] concentration) were assessed. In study 2, employing a longitudinal study design in a different cohort (composed of 37 older adults), we aimed to study whether a 6-month dancing intervention decreased CAF concentration compared to general fitness exercise training in older adults. Results: Our findings show that OD had a lower CAF concentration (suggesting an increased NMJ stability) compared to OA. This result was accompanied by superior functional performance despite no differences in muscle size. In study 2, we observed a reduction in CAF concentration only in the dancing group. Conclusion: Overall, these findings suggest that dancing is an effective training modality to promote neuroprotection and increase muscle function in healthy older individuals.
Ethical Justification for Deferral of Consent in the AcT Trial for Acute Ischemic Stroke
Authors: Faris Hannah , Dewar Brian , Dowlatshahi Dar , Ramji Alnar , Kenney Carol , Page Stacey , Buck Brian , Hill Michael D. , Coutts Shelagh B. , Almekhlafi Mohammed , Sajobi Tolulope , Singh Nishita , Sehgal Arshia , Swartz Richard H. , Menon Bijoy K. , Shamy Michel
Published: May 2022

The AcT trial (Alteplase Compared to Tenecteplase) compares alteplase or tenecteplase for patients with acute ischemic stroke. All eligible patients are enrolled by deferral of consent. Although the use of deferral of consent in the AcT trial meets the requirements of Canadian policy, we sought to provide a more explicit and rigorous approach to the justification of deferral of consent organized around 3 questions. Ultimately, the approach we outline here could become the foundation for a general justification for deferral of consent.
Planning the Potential Future during Multi-item Visual Working Memory
Authors: Nasrawi Rose , van Ede Freek
Published: May 2022

Working memory allows us to retain visual information to guide upcoming future behavior. In line with this future-oriented purpose of working memory, recent studies have shown that action planning occurs during encoding and retention of a single visual item, for which the upcoming action is certain. We asked whether and how this extends to multi-item visual working memory, when visual representations serve the potential future. Human participants performed a visual working-memory task with a memory-load manipulation (one/two/four items) and a delayed orientation-reproduction report (of one item). We measured EEG to track 15- to 25-Hz beta activity in electrodes contralateral to the required response hand—a canonical marker of action planning. We show an attenuation of beta activity, not only in Load 1 (with one certain future action) but also in Load 2 (with two potential future actions), compared with Load 4 (with low prospective-action certainty). Moreover, in Load 2, potential action planning occurs regardless whether both visual items afford similar or dissimilar manual responses, and it predicts the speed of ensuing memory-guided behavior. This shows that potential action planning occurs during multi-item visual working memory and brings the perspective that working memory helps us prepare for the potential future.
Activation in Right Dorsolateral Prefrontal Cortex Underlies Stuttering Anticipation
Authors: Jackson Eric S. , Dravida Swethasri , Zhang Xian , Noah J. Adam , Gracco Vincent , Hirsch Joy
Published: May 2022

People who stutter learn to anticipate many of their overt stuttering events. Despite the critical role of anticipation, particularly how responses to anticipation shape stuttering behaviors, the neural bases associated with anticipation are unknown. We used a novel approach to identify anticipated and unanticipated words, which were produced by 22 adult stutterers in a delayed-response task while hemodynamic activity was measured using functional near infrared spectroscopy (fNIRS). Twenty-two control participants were included such that each individualized set of anticipated and unanticipated words was produced by one stutterer and one control participant. We conducted an analysis on the right dorsolateral prefrontal cortex (R-DLPFC) based on converging lines of evidence from the stuttering and cognitive control literatures. We also assessed connectivity between the R-DLPFC and right supramarginal gyrus (R-SMG), two key nodes of the frontoparietal network (FPN), to assess the role of cognitive control, and particularly error-likelihood monitoring, in stuttering anticipation. All analyses focused on the five-second anticipation phase preceding the go signal to produce speech. The results indicate that anticipated words are associated with elevated activation in the R-DLPFC, and that compared to non-stutterers, stutterers exhibit greater activity in the R-DLPFC, irrespective of anticipation. Further, anticipated words are associated with reduced connectivity between the R-DLPFC and R-SMG. These findings highlight the potential roles of the R-DLPFC and the greater FPN as a neural substrate of stuttering anticipation. The results also support previous accounts of error-likelihood monitoring and action-stopping in stuttering anticipation. Overall, this work offers numerous directions for future research with clinical implications for targeted neuromodulation.
Collective Program Social Justice Identity and Perceived Norms on Promoting Student Advocacy
Authors: Keum Brian TaeHyuk , Kase Colleen A. , Sharma Rajni , Yee Stephanie E. , O’Connor Seini , Bansal Priya , Yang NaYeon
Published: May 2022

A growing body of research suggests that graduate psychology training programs with a stronger collective social justice identity are likely to provide more support for students’ advocacy engagements than those with discrepant views among members. We conducted response surface analyses ( N = 178 PhD students; across 16 counseling psychology programs) to examine whether the degree of congruence and discrepancy in social justice attitudes and perceptions of training program norms (perceived social justice norms among students and faculty) between the individual student and other students in their program would be associated with students’ social justice advocacy intentions and behaviors. Higher congruence in attitudes and perceived norms (among students and faculty) were significantly associated with advocacy intentions. For advocacy behaviors, only congruently higher perceptions of faculty were significantly associated. Discrepant attitudes and perceived norms were not significantly related to students’ advocacy intentions and behaviors. Recommendations for training and research are discussed.
Men in Women Industrial Space: Male Hairdressers of Ibadan, Nigeria
Authors: Ademuson Adefolake , Rebecca Ayinde Omolara , Akanle Olayinka
Published: May 2022

A definitive element of labor market is gender-based occupational segregation. Most previous studies on the subject of gender and labor have concentrated on gender mainstreaming and glass ceiling in formal economy with little attention to gender and informal economy. Hence, there has been very little attention to men venturing into female areas of traditional informal economy of Africa. This article, therefore, contributes fresh insights and interesting new knowledge on the emerging gender dynamics in contexts of Africa’s informal economy usually dominated by women. This article investigates men’s involvement in hairdressing, an area commonly considered as women’s jobs, the factors that led men to engage in hairdressing, the unique challenges male hairdressers face as a result of working in a female-dominated field, and their coping mechanisms. Qualitative and quantitative data gathered were analyzed through Content analysis (qualitative data) and Statistical Package for the Social Sciences (SPSS; quantitative data). Quantitative data were analyzed at univariate and bivariate levels. The results show that a large percentage of the customers prefer Male Hairdressers as they believe male hairdressers are good at the profession. Findings suggest the country’s high unemployment rate is, largely accountable, for men’s venturing into the Hairdressing Industry as an adaptive mechanism in complicated and precarious socioeconomic context and tidal system of social change.
Incompetence or Ingenuity? Why Did Nazi Germany Not Seek Closer Wartime Economic Cooperation with Italy?
Authors: Scherner Jonas
Published: May 2022

This article sheds light on why there was, and why Nazi Germany pursued, only comparatively little economic cooperation between the two most important axis partners, Italy and Germany, during the Second World War. In particular, the article looks more closely at the two countries’ cooperation in terms of raw materials, crucial to the war economy: why did Germany not deliver more raw materials to Italy and why did an underutilized Italian industry not export more manufactures to the Reich? Based on comparisons with other axis partners and occupied nations, the article argues that this was primarily the case because Italy could resist German economic pressure and, in contrast to many other countries in wartime Europe, maintained its sovereignty. Unlike Italy, these other countries readily (if not always voluntarily) financed larger bilateral German balance of payments deficits at favourable conditions and could not prevent Germany from implementing and monitoring a rigid raw material regime in their factories. Under these circumstances, greater economic cooperation with Italy seemed too costly to German officials and economic experts. Ironically, economic cooperation between the two Axis partners was so limited precisely because they were allies.
Fatigue life prediction of brake discs for high-speed trains via thermal stress
Authors: Luo Jiao , Liu Jiazhi , You Ziyun , Liu Xintian
Published: May 2022

As one of the essential components of the braking system, the high-speed train brake disc is an integral part of ensuring the safety of the train. The main objective of this study is to conduct thermal analysis and reliable life prediction on brake discs. The research was conducted by developing a programmer spectrum of brake discs with high-speed train brake discs. According to the results of numerical analysis and the S-N curve of the material, the temperature distribution on the surface of the brake disc is determined, and the fatigue life of the brake disc is predicted. The comparison with the service life of the brake disc verifies the rationality of the calculation results. In addition, a fatigue damage probability model of brake discs is established based on the theory of fatigue cumulative damage. Through the relationship between the reliability of mechanical parts and the number of load cycles, the reliable life of the brake disc under different working conditions is predicted. This work establishes a method of reliable life analysis for brake discs of high-speed trains based on the load spectrum, which could analyze the life and reliability of brake discs more systematically.
Threats and Responses in Organizational Research
Authors: Connelly Brian L. , Shi Wei
Published: May 2022

In recent years, executives and their employees have faced a wide range of threats to, and within, their organization. We put forward a framework that organizational scholars can use to position their ideas within the literature on threats and responses. We delineate different types of threats that firms often face. We also develop a set of constructs that, taken together, can be useful for describing how managers assess threats and how they might react to them. In addition, we identify several theories that explain organizational threats and responses, including two (protection motivation theory and integrated threat theory) that have proven useful in other disciplines but have yet to take hold in management studies. Lastly, we offer examples of how to expand extant theories to the domain of organizational threats and conclude with a call for research on threats and responses in organizational research.
Trifecta versus Perimount Magna Ease aortic valves: Failure mechanisms
Authors: Suzuki Ryo , Ito Toshiro , Suzuki Masato , Ohori Shunsuke , Takayanagi Ryo , Miura Shiro
Published: May 2022

Background

There are increasing reports of early externally mounted pericardial Trifecta bioprosthesis failure. We compared the hemodynamic performance of Trifecta and Carpentier–Edwards Perimount Magna Ease valves to determine the failure mechanism.

Methods

We retrospectively included 270 consecutive patients (age: 73.4 ± 8.2 years; 57.5% male; mean follow-up: 48.0 ± 20.3 months) who underwent aortic valve replacement from 2014 to 2021 at a single center and compared the Trifecta ( N = 137) and Carpentier–Edwards Perimount Magna Ease valve ( N = 133) patients.

Results

The prosthetic valve major aortic regurgitation incidence was higher for the Trifecta than that for the Carpentier–Edwards Perimount Magna Ease valve (6.3% vs. 0%, P < 0.009). Among the Trifecta failures, 33% developed structural valve deterioration, but all requiring redo aortic valve replacement developed major prosthetic valve aortic regurgitation. Freedom at 5 years from redo aortic valve replacement due to structural valve deterioration was significantly lower for Trifecta (89.4% vs. 100%, P = 0.003). The reoperation hazards were determined for Trifecta (vs. Carpentier–Edwards Perimount Magna Ease): 11.6 (1.47–90.9; P = 0.02), prosthetic valve aortic regurgitation: 2.38 (1.70–3.32; P < 0.01), structural valve deterioration: 20.82 (4.08–106.2; P < 0.01), 5-year mean transprosthetic pressure gradient: 1.14 per 1-point increase (1.03–1.24; P = 0.007), and urgent surgery: 10.1 (2.59–39.0; P = 0.001). The Cox regression analysis identified that prosthetic valve aortic regurgitation solely contributed to redo aortic valve replacement (hazard ratio: 2.38; confidence intervals: 1.70–3.32).

Conclusions

Significantly, more early failures occurred with the Trifecta valve than the Carpentier–Edwards Perimount Magna Ease valve but the Trifecta showed reasonable mean transprosthetic pressure gradient over time. Prosthetic valve aortic regurgitation and calcific structural valve deterioration synergistically contributed to Trifecta valve failure alternatively.