bluuebunny/crossref_metadata_2025 huggingface dataset:
An Evaluation Model of Urban-Rural Exchange Teachers in Elementary School Based on Optimal Control Neural Network
Authors: Chen Ke
Published: September 2022

In this paper, an optimal control neural network algorithm is used to conduct an in-depth study and analysis of the evaluation of elementary school urban-rural exchange teachers, and an optimal control neural network evaluation model is designed and applied to the actual elementary school urban-rural exchange process. A tracking controller is designed to track the target trajectory for a typical second-order nonlinear system where the system model is partially unknown and the internal state of the system is unpredictable. The neural network observer is first designed using the input and output information of the system to approximate the drift dynamics of the system on the one hand and estimate the internal state information of the system on the other hand; then, based on the estimated system state, the sliding mode tracking controller is designed to achieve tracking of the established target trajectory. It is found that the policy implementation is not in place, teachers are not motivated to exchange and most of them aim at position promotion, their sense of responsibility is weak, and they cannot treat the matter of exchange seriously and correctly, thus cannot play their role in the exchange school. The ways to prevent and alleviate the conflict of interest among policy subjects are mainly divided into subjective and objective aspects: first, from the subjective level to arouse the value recognition of multiple interest subjects, including the government, should play the function of policy guidance and exhortation and clarify the value orientation of the policy; schools should cultivate the moral quality and professionalism of teachers and strengthen ideological mobilization; and teachers should improve their ideological awareness and consciously change their willingness to exchange. Establishing teachers’ status as civil servants, paying attention to teachers’ professional development and safeguarding the interests of rotating teachers to increase teachers’ motivation to exchange and rotate, creating a good social opinion environment, providing a good inflow school support environment for rotating teachers, and building a cloud platform for sharing high-quality educational resources create a good policy implementation environment to ensure that the teacher exchange and rotation policy is effectively implemented to achieve its goals of balancing teacher deployment. Although gradient-based methods can achieve high training accuracy, the performance of the backpropagation algorithm may be unsatisfactory when applied to test data, that is, if the size of the training data is not large enough.
Activation of PPARγ Protects Obese Mice from Acute Lung Injury by Inhibiting Endoplasmic Reticulum Stress and Promoting Mitochondrial Biogenesis
Authors: Tang Yin , Wei Ke , Liu Ling , Ma Jingyue , Wu Siqi , Tang Wenjing
Published: September 2022

Objective. Obesity-induced endoplasmic reticulum (ER) stress plays a role in increased susceptibility to acute lung injury (ALI)/acute respiratory distress syndrome (ARDS). The activation of peroxisome proliferator-activated receptor-γ (PPARγ) is associated with lung protection and is effective in ameliorating ER stress and mitochondrial dysfunction. The aim of this study was to investigate the expression of PPARγ in the lung tissues of obese mice and explore whether the PPARγ-dependent pathway could mediate decreased ALI/ARDS by regulating ER stress and mitochondrial biogenesis. Methods. We determined PPARγ expression in the lung tissues of normal and obese mice. ALI models of alveolar epithelial cells and of obese mice were used and treated with either PPARγ activator rosiglitazone (RSG) or PPARγ inhibitor GW9662. Lung tissue and cell samples were collected to assess lung inflammation and apoptosis, and ER stress and mitochondrial biogenesis were detected. Results. PPARγ expression was significantly decreased in the lung tissue of obese mice compared with that in normal mice. Both in vivo and in vitro studies have shown that activation of PPARγ leads to reduced expression of the ER stress marker proteins 78-kDa glucose-regulated protein (GRP78), C/EBP homologous protein (CHOP), and Caspase12. Conversely, expression of the mitochondrial biogenesis-related proteins peroxisome proliferator-activated receptor γ coactivator 1 (PGC-1α), nuclear respiratory factor-1 (NRF-1), and mitochondrial transcription factor A (TFAM) increased. Furthermore, activation of PPARγ is associated with decreased levels of lung inflammation and epithelial apoptosis and increased expression of adiponectin (APN) and mitofusin2 (MFN2). GW9662 bound to PPARγ and blocked its transcriptional activity and then diminished the protective effect of PPARγ on lung tissues. Conclusions. PPARγ activation exerts anti-inflammation effects in alveolar epithelia by alleviating ER stress and promoting mitochondrial biogenesis. Therefore, lower levels of PPARγ in the lung tissues of obese mice may lead to an increased susceptibility to ALI.
The Application of 3D Virtual Technology in the Teaching of Clinical Medicine
Authors: Zhang Haifeng , Kong Juan , Tong Yan , Gao Chunmei , Huang Wei
Published: September 2022

The booming development of 3D virtual technology provides the basis for the innovation of teaching mode of clinical medicine. Integrating 3D virtual technology into the clinical education teaching of medical students can help medical students learn clinical expertise more intuitively, enrich practical experience, improve hands-on ability, and make up for the shortcomings of traditional medical teaching. However, the traditional 3D modeling method has the problems of sparse and insufficient accuracy of output results, which greatly limits the specific application of 3D virtual technology in clinical teaching. Therefore, this paper addresses the shortcomings of previous 3D virtual technology in 3D modeling of organs, introduces deep learning, and then proposes a pyramidal shape perception network with the ability to generate samples on point clouds. Experimental results show that the proposed model not only has a large improvement in accuracy but also shows a high degree of confidence in providing real-time feedback of local image attributes.
Deep Federated Learning Based Convergence Analysis in Relaying-Aided MEC-IoT Networks
Authors: Liu Jun , Cui Tao , Zhang Lin , Zhang Yuwei , Wang Jing , Li Chao , Chen Kai , Huang Huang , Zhou Xuan , Zhou Wei , Li Sun , Feng Suili , Xie Dongqing , Li Yun , Xiang Haige , Dube Kaimeno , Muazu Abbarbas , Rono Nakilavai , Zhou Wen , Zhu Fusheng , Chen Liming , Deng Dan , Wang Zhao , Tang Yajuan
Published: September 2022

Recently, deep federated learning has attracted much attention from researchers in the fields of wireless communications, where the relaying technique has been shown as a powerful technology to assist the wireless signals and enhance the transmission quality, which is very important to the development of mobile edge computing (MEC) based Internet of Things (IoT) networks. In a relaying-aided MEC-IoT system, it is of vital importance to deeply investigate the system signal-to-noise ratio (SNR) at the receiver side, as it mainly determines the system performance metrics, such as capacity (or achievable data rate), outage probability, and bit-error-rate (BER). To this end, we first investigate the instantaneous convergence error, by deeply studying the relationship between the instantaneous two-hop relaying channels. We then investigate the statistical convergence error, by performing the statistical expectation with respect to the two-hop relaying channels. We finally present some results to show that the analysis of the convergence error is effective. The work in this paper can provide some theoretical foundation for deep federated learning and computing networks.
Comparative Analysis of the Performance of Complex Texture Clustering Driven by Computational Intelligence Methods Using Multiple Clustering Models
Authors: Zhou Jincheng , Wang Dan , Ling Lei , Li Mingjiang , Lai Khin-Wee
Published: September 2022

Traditional texture cluster algorithms are frequently used in engineering; however, despite their widespread application, these algorithms continue to suffer from drawbacks including excessive complexity and limited universality. This study will focus primarily on the analysis of the performance of a number of different texture clustering algorithms. In addition, the performance of traditional texture classification algorithms will be compared in terms of image size, clustering number, running time, and accuracy. Finally, the performance boundaries of various algorithms will be determined in order to determine where future improvements to these algorithms should be concentrated. In the experiment, some traditional clustering algorithms are used as comparative tools for performance analysis. The qualitative and quantitative data both show that there is a significant difference in performance between the different algorithms. It is only possible to achieve better performance by selecting the appropriate algorithm based on the characteristics of the texture image.
Application of Price Competition Model Based on Computational Neural Network in Risk Prediction of Transnational Investment
Authors: Chen Xiuxiu , Huang Xiaoxin
Published: September 2022

Aiming at the scenario where edge devices rely on cloud servers for collaborative computing, this paper proposes an efficient edge-cloud collaborative reasoning method. In order to meet the application’s specific requirements for delay or accuracy, an optimal division point selection algorithm is proposed. A kind of multichannel supply chain price game model is constructed, and nonlinear dynamics theory is introduced into the research of the multichannel supply chain market. According to the actual competition situation, the different business strategies of retailers are considered in the modeling, which makes the model closer to the actual competition situation. Taking the retailer’s profit as an indicator, the influence of the chaos phenomenon on the market performance is analyzed. Compared with the previous studies, this thesis uses nonlinear theory to better reveal the operating laws of the economic system. This paper selects company A in the financial industry to acquire company B in Sweden. It is concluded that company B is currently facing financial difficulties, but its brand and technical advantages are far superior to company A. The indirect financial risk index of company B, that is, the investment environment, is analyzed, and the final investment environment score of the country where company B is located is 90 points, which is an excellent grade by scoring the investment environment of the target enterprise. Combining the investment environment score and the alarm situation prediction score, it is concluded that the postmerger financial risk warning level of company A is in serious alarm.
Correlation between HPV PCNA, p16, and p21 Expression in Lung Cancer Patients
Authors: Marcos B. F. São , de Oliveira T. H. A. , Do Amaral C. M. M. , Muniz M. T. C. , Freitas A. C.
Published: September 2022

Purpose. Evaluate if human papillomavirus (HPV) infection in lung cancer patients might be helping cancer development by altering p16, p21, and PCNA, key human genes involved in cell proliferation and tumor development. Methods. 63 fresh-frozen (FF) and formalin-fixed paraffin-embedded (FFPE) samples from lung tumor patients were used to detect HPV by PCR, followed by genotype through sequencing. The host gene expressions of p21, p16, and PCNA were quantified by qPCR in both FF and FFPE samples, and the expression of viral oncogenes E5, E6, and E7 was also measured by qPCR in 19 FF samples. Results. 74.6% of samples were positive for HPV, 33/44 FFPE samples and 14/19 FF samples. HPV-16 and HPV-18 were detected in 31/33 and 7/33 FFPE, respectively, and HPV-16 was the only type in FF samples. E5, E6, and E7 were expressed in 10/19, 2/19, and 4/19 FF samples, respectively. The p16 RNAm expression was higher in FF HPV+ samples and FFPE+FF HPV+ samples, while p21 showed higher expression in all HPV- samples. In turn, the PCNA expression was higher in HPV+ FF samples; however, in FFPE and FFPE+FF samples, PCNA was higher in HPV- samples. In FF samples, PCNA, p16, and p21 showed a significant positive correlation as well as E5 and E7, and E5 was inversely correlated to p21. In FFPE, also, a positive correlation was observed between PCNA HPV+ and p21 HPV+ and PCNA HPV+ and p16 HPV. In FF+FFPE analysis, a direct correlation was found between PCNA HPV+ and p21 HPV+, p21 HPV+ and p16 HPV+, and PCNA HPV- and p16 HPV-, and an inverse correlation between PCNA HPV+ and p16 HPV+. Also, the p16 protein was positive in 10 HPV+ samples and 1 HPV-. Conclusions. Our data show that lung cancer patients from Northeast Brazil have a high prevalence of HPV, and the virus also expresses its oncogenes and correlates with key human genes involved in tumor development. This data could instigate the development of studies focused on preventive strategies, such as vaccination, used as a prognostic indicator and/or individualized therapy.
Leptin Levels in Serum or Semen and Its Association with Male Infertility: A Meta-Analysis with 1138 Cases
Authors: Mo Yi , Liang Fangfang , Mehmood Arshad , Niu Xiangli , Xie Ying , Shah Suleman , Lin Zhong , Sun Yan , Tan Daxian , Guo Yafen , Jiang Hesheng
Published: September 2022

Background. Leptin has an association with male infertility. However, only sporadic studies inconsistently reported the results. Aim and Objective. In this study, we aimed to perform a meta-analysis to investigate the relationship between leptin and male infertility. Methods. This study was performed based on published articles related to leptin and infertile males. PubMed, Web of Science, Google Scholar, Ovid + Cochrane Central Register of Controlled Trials, Wiley Online Library, Chinese CNKI, Chinese Chong Qing VIP, Chinese Wan Fang, and China Biology Medicine databases were searched to identify all relevant studies. All eligible works of literature were analyzed by the “meta” or “metan” command in STATA version 12.0 software. The standardized mean difference (SMD) of leptin concentration in serum or semen and 95% confidence intervals (CIs) were estimated for all studies. The heterogeneity was described with I2. The sources of heterogeneity were explored via metaregression, and stratified analyses, sensitivity analyses, and publication bias were performed. Results. Nineteen studies were included in the current meta-analysis, involving 1138 cases of infertile men and 756 controls. The SMD of leptin concentration in serum was 2.002 (95% CI: 1.086, 2.918), Z-test (z) z = 4.29;

p
<
0.001

, and I2 was 97.3%,

p
<
0.001

. The SMD of leptin concentration in semen was 3.274 (95% CI: 2.137, 4.411), z = 5.64;

p
<
0.001

, and I2 was 98.2%,

p
<
0.001

. Notably, serum follicle-stimulating hormone (FSH) was slightly higher in infertile men (SMD = 3.695, z = 2.33,

p
=
0.020

, I2 = 98.8%,

p
<
0.001

). Other hormones, such as luteinizing hormone (LH) and testosterone, were also slightly higher, but the results were not statistically significant. In addition, sperm count (SMD = −4.533, 95% CI: −6.565, −2.501) and sperm motility (SMD = −7.894, 95% CI: −10.616, −5.172) inversely correlated with leptin levels in infertile males. Sperm abnormal forms did not show a statistically significant SMD of −0.076 (95% CI: −3.410, 3.258). Conclusion. Leptin plays a potential role in association with male infertility. This study may effectively reveal the relationship between leptin together with other hormones and its association with male infertility. These results may also provide opinions on precautionary measures.
The Application of Multisensor Information Fusion Technology in Environmental Restoration
Authors: Yu Longsheng , Ye Youhua , Guo Wei , Chen Sanxiong , Zhang Hui
Published: September 2022

Multisensor information fusion technology is an advanced processing method that is different from classical data processing technology. Capability and operational accuracy, in order to make an effective comprehensive evaluation of environmental quality, the environmental monitoring system built by NB-IoT technology and sensor technology is used to conduct multisensor data fusion research on the collected environmental factors such as temperature, humidity, formaldehyde, PM2.5, and TVOC. At the same time, the two-level parallel fusion method is adopted to evaluate the environmental quality. Before data fusion, median filtering is used to eliminate abnormal data. Then, the Kalman filter algorithm is used to fuse multiple sets of similar sensors to obtain the best value of it. Finally, the fuzzy comprehensive evaluation method is used to fuse the different types of sensors at the decision-making level, in which the weight value is determined by the entropy method and the membership function is Gaussian. The different environment scenarios are tested by using the above algorithms, and the simulation results show that multisensor data fusion can obtain more abundant and effective environmental information, overcome the simplicity and limitation of single-factor sensor for environmental quality assessment, and improve the reliability and accuracy of the overall environmental quality assessment.
Design and Implementation of Group Animation Based on Multimedia Intelligent Algorithm
Authors: Li Qing
Published: September 2022

In order to improve the autonomy and intelligence of group animation behavior, this paper proposes a particle swarm optimization algorithm for automatic control of group animation behavior. After the user inputs the group animation behavior construction target, the individual path is planned according to the fixed behavior rules, and the particle swarm optimization algorithm and the improved artificial fish swarm optimization algorithm are used to select the optimal action for the individual in the group animation according to the top-down control process. The experimental results show that after the PSO converges to the global optimal solution, the evolution times of the PSO converge to the global optimal solution again when the surrounding environment changes 10 times. The population diversity of particle swarm optimization algorithm is obviously better than those of the other two algorithms in the process of automatically controlling the movement of individuals to the circle and to the stand in the crowd animation. Compared with the original algorithm AFSA, the improved artificial fish swarm algorithm proposed in this paper is easier to obtain the global optimal value, and the optimization speed is also improved. In conclusion, the example analysis verifies that the algorithm can effectively realize the automatic control of group animation behavior and has high convergence speed and high autonomy.
Efficacy and Safety of Bevacizumab in Pretreated Metastatic Breast Cancer: A Systematic Review and Meta-Analysis
Authors: Li Zhijun , Guo Fengzhu , Han Yiqun , Wang Jiayu , Xu Binghe
Published: September 2022

Background: The use of bevacizumab in patients with previously treated metastatic breast cancer (MBC) is controversial. This meta-analysis was carried out to evaluate the efficacy and safety of the regimen including bevacizumab among patients with pretreated MBC. Methods: We systematically searched PubMed, the Cochrane Library, Web of Science, and Embase databases for randomized controlled trials evaluating bevacizumab combined with chemotherapy for previously treated MBC patients. The primary endpoints were progression-free survival (PFS) and objective response rate (ORR). The secondary endpoints were overall survival (OS) and toxicity. The risk of bias was assessed by the Cochrane Collaboration’s tool. The pooled hazard ratio (HR) and risk ratio (RR) with 95% confidence intervals (CIs) were calculated for the identified studies. This study was performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist. Results: Four studies involving 1,640 individuals were included. Pooling results showed that the PFS of bevacizumab-containing groups (HR 0.82; 95% CI 0.73–0.93, p = 0.002) was significantly better than that of the control groups, especially when bevacizumab was administered as the second-line treatment for patients with human epidermal growth factor receptor 2 (HER2)-negative MBC (HR 0.77; 95% CI 0.66–0.88, p = 0.0002). The ORR in the bevacizumab-containing group was superior to that in the control group, both in the general (RR 1.45; 95% CI 1.18–1.78, p = 0.0004) and HER2-negative groups (RR 1.30; 95% CI 1.03–1.63, p = 0.03). However, no significant effect on OS was demonstrated for the addition of bevacizumab to the second-line treatment for HER2-negative MBC (HR 0.93; 95% CI 0.79–1.10, p = 0.39). Comparatively, proteinuria was more common in the bevacizumab-containing group. In addition, the application of bevacizumab tended to result in therapy discontinuation due to treatment-related toxicity. Conclusions: Bevacizumab-containing chemotherapy, in light of its favorable effects on clinical outcomes, could be a preferred therapeutic option for patients with MBC, for whom the disease must be rapidly relieved. Further studies are warranted for exploring the advantageous patients with the receipt of bevacizumab in multiline treatment.
Variance reduction technique in reliability evaluation for distribution system by using sequential Monte Carlo simulation
Authors: Rusyda Roslan Nur Nabihah , Farhanie Mohd Fauzi NoorFatin , Muhammad Ridzuan Mohd Ikhwan
Published: September 2022

This paper discusses the need for variance reduction in simulations in order to reduce the time required to compute a simulation. The large and complex network is commonly evaluated using a large-scale Monte Carlo simulation. Unfortunately, due to the different sizes of the network, it takes some time to complete a simulation. However, variance reduction techniques (VRT) can help to solve the issues. The effect of VRT changes the behaviors of a simulation, particularly the time required to run the simulation. To evaluate the reliability indices, two sequential Monte Carlo (SMC) methods are used. SMC with VRT and SMC without VRT are the two options. The presence of VRT in the simulation distinguishes the two simulations. Finally, reliability indices: system average interruption frequency index (SAIFI), system average interruption duration index (SAIDI), and customer average interruption duration index (CAIDI) will be calculated at the end of the simulation to determine the efficiency for the SMC with and without VRT. Overall, the SMC with VRT is more efficient because it is more convenient and saves time than the SMC without VRT.
Speed control of hybrid energy sources fed BLDC motor drive with FOPID controllerusing various optimization techniques
Authors: Kanagaraj Sushita , Nithaiyan Shanmugasundaram
Published: September 2022

This article suggests the control of current and speed approach to reduce the torque ripple in BLDC motor. Initially, the renewable energy hybrid power system (REHPS) is composed of a generation system of PV, fuel cell (FC), and the storage system of battery bank. This REHPS uses solar power as their main source of electricity during the day. It uses the fuel cell as a secondary source for maintenance at night or during periods of shaded conditions. The novelty of the proposed method is to achieve torque ripple minimization and to control the speed of the BLDC motor. The speed and error torque of the BLDC motor is optimized by mayfly optimization algorithm (MOA). The MOA provides gain parameters of the fractional order proportional–integral–derivative (FOPID) controller. The advantage of the proposed method is to improve the level of dependability and provide flexibility in solving the system error. The proposed model is implemented in MATLAB/Simulink and experimental setup. The results of the proposed method are compared with the existing research techniques such as particle swarm optimization (PSO) and moth flame algorithm (MFA).
Design and implementation reversible multiplexer using quantum-dot cellular automata approach
Authors: Sherif Noora H. , Ali Mohammed Hussien , Jazea Najim Abdallah
Published: September 2022

Rapid progress in the field of nanotechnology includes using quantum dot-cellular automata (QCA) as a replacement for conventional transistor-based complementary metal oxide semiconductor (CMOS) circuits in the construction of nano-circuits. Due to ultra low thermal dissipation, rapid clocking, and extremely high density, the QCA is a rapidly growing field in the nanotechnological field to inhibit the field effect transistor (FET)-based circuit. This paper discusses and evaluates two multiplexer (MUX) architectures: an innovative and effective 4×1 MUX structure and an 8×1 MUX structures using QCA technology. The suggested architectural designs are constructed using the Fredkin and controlled-NOT (CNOT) gates. These constructions were designed to simulate using tool QCA designer 2.0.3. The 591 and 1,615 cells would be used by the 4×1 and 8×1 QCA MUX architectures, respectively. The simulation results demonstrate that, when compared to the previous QCA MUX structures, the suggested QCA MUX designs have the best clock latency performance and use of different gate types.
Smarter dam based on cyber-physical system utilizing Raspberry Pi4 and NodeMCU ESP8266
Authors: Deab Mustafa Yassin , Croock Muayad Sadik
Published: September 2022

The majority of dams still use traditional technologies to manage water gates. These strategies have a number of limitations, including those related to human error. This study describes an automated method for controlling and managing dams based on the structure of a cyber-physical system (CPS) in order to reduce work hazards and human efforts. The suggested system design consists of four ESP8266 nodes, each connected to a water level sensor and distributed around the main dam and its feeder sections. These nodes are linked to a central server (Raspberry Pi4). The data is gathered and retransmitted through the message queuing telemetry transfer (MQTT) protocol to the (Raspberry Pi4) central server via wireless sensor nodes (WSNs) distributed on the dam's various sides to regulate the water levels in the dam's main reservoir and the areas it feeds. Furthermore, the Raspberry Pi4 transmits data to the cloud server using internet media. A cloud-based dashboard with numerous tabs for each node has been constructed. The results of the experiments reveal that the proposed technique is superior to the ones currently in use for dam management.
Long Noncoding RNA TPRG1-AS1 Suppresses Migration of Vascular Smooth Muscle Cells and Attenuates Atherogenesis via Interacting With MYH9 Protein
Authors: Ren Xiaoxiao , Zhu Huijuan , Deng Keyong , Ning Xiaotong , Li Lin , Liu Dan , Yang Bin , Shen Chenyang , Wang Xianqiang , Wu Naqiong , Chen Shufeng , Gu Dongfeng , Wang Laiyuan
Published: September 2022

Background:

Migration of human aortic smooth muscle cells (HASMCs) contributes to the pathogenesis of atherosclerosis. This study aims to functionally characterize long noncoding RNA TPRG1-AS1 (tumor protein p63 regulated 1, antisense 1) in HASMCs and reveal the underlying mechanism of TPRG1-AS1 in HASMCs migration, neointima formation, and subsequent atherosclerosis.

Methods:

The expression of TPRG1-AS1 in atherosclerotic plaques was verified a series of in silico analysis and quantitative real-time polymerase chain reaction analysis. Northern blot, rapid amplification of cDNA ends and Sanger sequencing were used to determine its full length. In vitro transcription-translation assay was used to investigate the protein-coding capacity of TPRG1-AS1. RNA fluorescent in situ hybridization was used to confirm its subcellular localization. Loss- and gain-of-function studies were used to investigate the function of TPRG1-AS1. Furthermore, the effect of TPRG1-AS1 on the pathological response was evaluated in carotid balloon injury model, wire injury model, and atherosclerosis model, respectively.

Results:

TPRG1-AS1 was significantly increased in atherosclerotic plaques. TPRG1-AS1 did not encode any proteins and its full length was 1279nt, which was
bona fide
a long noncoding RNA. TPRG1-AS1 was mainly localized in cytoplasmic and perinuclear regions in HASMCs. TPRG1-AS1 directly interacted with MYH9 (myosin heavy chain 9) protein in HASMCs, promoted MYH9 protein degradation through the proteasome pathway, hindered F-actin stress fiber formation, and finally inhibited HASMCs migration. Vascular smooth muscle cell-specific transgenic overexpression of TPRG1-AS1 significantly reduced neointima formation, and attenuated atherosclerosis in apolipoprotein E knockout (
Apoe
−/−
) mice.

Conclusions:

This study demonstrated that TPRG1-AS1 inhibited HASMCs migration through interacting with MYH9 protein and consequently suppressed neointima formation and atherosclerosis.
Regulation of VWF (Von Willebrand Factor) in Inflammatory Thrombosis
Authors: Manz Xue D. , Bogaard Harm Jan , Aman Jurjan
Published: September 2022

Increasing evidence indicates that inflammation promotes thrombosis via a VWF (von Willebrand factor)-mediated mechanism. VWF plays an essential role in maintaining the balance between blood coagulation and bleeding, and inflammation can lead to aberrant regulation. VWF is regulated on a transcriptional and (post-)translational level, and its secretion into the circulation captures platelets upon endothelial activation. The significant progress that has been made in understanding transcriptional and translational regulation of VWF is described in this review. First, we describe how VWF is regulated at the transcriptional and post-translational level with a specific focus on the influence of inflammatory and immune responses. Next, we describe how changes in regulation are linked with various cardiovascular diseases. Recent insights from clinical diseases provide evidence for direct molecular links between inflammation and thrombosis, including atherosclerosis, chronic thromboembolic pulmonary hypertension, and COVID-19. Finally, we will briefly describe clinical implications for antithrombotic treatment.
Racial and Ethnic Disparities in Financial Barriers Among Overweight and Obese Adults Eligible for Semaglutide in the United States
Authors: Lu Yuan , Liu Yuntian , Krumholz Harlan M.
Published: September 2022

Background

Semaglutide holds the promise for weight loss and risk reduction. Less is known about racial and ethnic disparities in financial barriers among the semaglutide‐eligible population.

Methods and Results

We conducted a cross‐sectional analysis of adults aged 18 years or older using data from the National Health and Nutrition Examination Survey 2015 to 2020. We analyzed adults eligible for semaglutide based on Food and Drug Administration labeling and assessed financial barriers and social determinants of health among the eligible population overall and by race and ethnicity. A total of 13 711 adults were included in the final analysis. In 2015 to 2020, 51.1% (48.3%–53.2%) of US adults (≈112.5 million) met the Food and Drug Administration eligibility criteria for semaglutide. The percentage of adults eligible for semaglutide was highest among Black adults (56.6% [54.2%–59.1%]), followed by Hispanic adults (55.0% [52.8%–57.3%]). Among adults eligible for semaglutide, 11.9% (10.1%–13.6%) were uninsured, 13.3% (12.1%–14.5%) lacked a usual source of care, 33.6% (30.2%–36.9%) had low family income, and 38.9% (36.5%–41.3%) lacked higher education. Compared with White individuals, significantly larger proportions of Black and Hispanic individuals were uninsured, lacked a usual source of care, had low family income, or lacked higher education (
P
<0.001 for all).

Conclusions

Many Americans who were eligible for semaglutide were likely to be unable to afford the medication. Among the eligible population, a larger proportion of Black and Hispanic adults had financial barriers than other subgroups.
Distribution Pattern Analysis of Cortical Brain Infarcts on Diffusion‐Weighted Magnetic Resonance Imaging: A Hypothesis‐Generating Approach to the Burden of Silent Embolic Stroke
Authors: Schaller‐Paule Martin A. , Fritz Daniel , Schaefer Jan Hendrik , Hattingen Elke , Foerch Christian , Seiler Alexander
Published: September 2022

Background

In patients with covert cerebrovascular disease or proximal source of embolism, embolic silent brain infarction may precede major stroke events. Therefore, characterization of particularly cortical silent brain infarction is essential for identifying affected patients and commencing adequate secondary prevention. This study aimed to investigate differences in the distribution pattern of cortical ischemic stroke lesions to assess potential predilection sites of cortical silent brain infarction.

Methods and Results

We prospectively included all consecutive patients with stroke presenting from January 1 to December 31, 2018. Diffusion‐weighted imaging lesions were used to generate voxel‐based lesion maps and assigned to atlas‐based cortical regions of interest in middle cerebral artery territories. Each region‐of‐interest lesion frequency was related to the respective region‐of‐interest volume to identify frequently affected and underrepresented cerebral cortex areas. Diffusion‐weighted imaging data for voxel‐based lesion maps were available in 334 out of 633 patients. Primary analysis revealed that small‐ (<0.24 cc) and medium‐sized (0.24–2640 cc) lesions distributed predominantly along regions associated with sensorimotor or language function. Detailed analysis within middle cerebral artery territories showed an approximated frequency of missed cortical stroke lesions of up to 67% in the right and 69% in the left hemisphere. In particular, the frontal, temporal, and occipital cortices were underrepresented. Larger lesion size and areas associated with higher cortical function led to hospital admission.

Conclusions

Cortical brain infarcts in hospitalized patients are not dispersed equally but are predominantly located in brain structures associated with motor control and sensory and language function. Matching underrepresented cerebral cortex regions to symptoms not yet associated with stroke warrants further exploration.
Association of Low‐Density Lipoprotein Cholesterol Levels During Statin Treatment With Cardiovascular and Renal Outcomes in Patients With Moderate Chronic Kidney Disease
Authors: Yen Chieh‐Li , Fan Pei‐Chun , Lee Cheng‐Chia , Chen Jia‐Jin , Kuo George , Tu Yi‐Ran , Chu Pao‐Hsien , Hsu Hsiang‐Hao , Tian Ya‐Chung , Chang Chih‐Hsiang
Published: September 2022

Background

The benefit of low‐density lipoprotein cholesterol (LDL‐C) levels in chronic kidney disease populations remains unclear. This study evaluated the cardiovascular and renal outcomes in patients with stage 3 chronic kidney disease with different LDL‐C levels during statin treatment.

Methods and Results

There were 8500 patients newly diagnosed as having stage 3 chronic kidney disease under statin treatment who were identified from the Chang Gung Research Database and divided into 3 groups according to their first LDL‐C level after the index date: <70 mg/dL, 70 to 100 mg/dL, and >100 mg/dL. Inverse probability of treatment weighting was performed to balance baseline characteristics. Compared with the LDL‐C ≥100 mg/dL group, the 70≤LDL‐C<100 mg/dL group exhibited significantly lower risks of major adverse cardiac and cerebrovascular events (6.8% versus 8.8%; subdistribution hazard ratio [SHR], 0.76 [95% CI, 0.64–0.91]), intracerebral hemorrhage (0.23% versus 0.51%; SHR, 0.44 [95% CI, 0.25–0.77]), and new‐onset end‐stage renal disease requiring chronic dialysis (7.6% versus 9.1%; SHR, 0.82 [95% CI, 0.73–0.91]). By contrast, the LDL‐C <70 mg/dL group exhibited a marginally lower risk of major adverse cardiac and cerebrovascular events (7.3% versus 8.8%; SHR, 0.82 [95% CI, 0.65–1.02]) and a significantly lower risk of new‐onset end‐stage renal disease requiring chronic dialysis (7.1% versus 9.1%; SHR, 0.76 [95% CI, 0.67–0.85]).

Conclusions

Among patients with stage 3 chronic kidney disease, statin users with 70≤LDL‐C<100 mg/dL and with LDL‐C <70 mg/dL had similar beneficial effect in the reduction of risks of major adverse cardiac and cerebrovascular events and new‐onset end‐stage renal disease compared with those with LDL‐C >100 mg/dL. Moreover, the 70≤LDL‐C<100 mg/dL group seemed to have a lowest risk of intracerebral hemorrhage, although the incidence was low.
On the Economic Consequences of Mass Shootings
Authors: Brodeur Abel , Yousaf Hasin
Published: September 2022

In this paper, we investigate the economic consequences of mass shootings. We find that shootings have negative effects on targeted counties’ economies. Estimates using three different comparison groups yield similar results. Examining the mechanisms, we find that residents of targeted areas: (i) develop pessimistic views of financial and local business conditions; and (ii) are more likely to report poor mental health, which hinders usual activities such as work, suggesting that shootings lead to decreases in productivity. Further, we find that greater national media coverage of shootings exacerbates their local economic consequences.
What Do Cross-Country Surveys Tell Us about Social Capital?
Authors: Tannenbaum David , Cohn Alain , Zünd Christian Lukas , Maréchal Michel André
Published: September 2022

We assess the predictive power of survey measures of social capital with a new behavioral data set that examines whether citizens report a lost wallet to its owner. Using data from more than 17,000 lost wallets across 40 countries, we find that survey measures of social capital—especially questions concerning generalized trust or generalized morality—are strongly and significantly correlated with country-level differences in wallet reporting rates. A second finding is that lost wallet reporting rates predict unique variation in the outputs of social capital, such as economic development and government effectiveness, not captured by existing measures.
Sex differences in pelvic and sacral size in wildcat from the Western Carpathians
Authors: Csanády Alexander , Krišovský Peter
Published: September 2022

Sexual differences in the wildcat were evaluated on 15 variables in 49 pelvic and 38 sacral bones in wildcat from the Western Carpathians. Our data confirmed a male-biased sexual size dimorphism (SSD) in the pelvic and sacral bones. The effect size was very large for two pelvic (SB, smallest width of the shaft of the ilium; and LAR, length of the acetabulum) and two sacral traits (GB, greatest width across the wings; and BFcr, greatest width of the cranial articular surface). Our different allometric patterns in pelvic and sacral measures in both sexes may also be important in mode of locomotion. These findings highlight the need for morphometric analysis of species at the regional as well global level.
Do You See What I See? How Media Choice and Visual Tornado Cues Influence Individual Storm Preparation
Authors: Armstrong Cory L. , Usery Anna Grace
Published: September 2022

When a tornado hits, there is little time to think through mental checklists for needed items. This study attempted to understand what information sources those in the path of tornados utilized for preparation and how those sources influence people to act. Results from the study indicate that television and radio are the top two information sources, and that some visual graphics—gauged via heat maps to understand higher levels of severe weather preparation—were reported as useful. Contrary to meteorological intentions, results showed that participants were less likely to prepare for impending weather when radar displayed tornado locations and intensity. In addition, those who identified as having more interest in weather-related information in the study were significantly more likely to prepare, along with those who fear future tornadoes. Each variable explored is underpinned by the theory of planned behavior and the risk information seeking and processing (RISP) model to better understand behavioral intentions and actions. This study offers two new concepts of general weather that have not previously been explored: interest and general versus specific storm preparation.

Significance Statement

The purpose of this work is to learn more about how individuals gather information and obtain weather warnings, primarily during tornado events. In particular, the study seeks to understand how individuals view and interpret visual graphics with information about the location and details about the event. Further, results suggest some differences between those who generally prepare for storm season versus those who only prepare for a specific event. Researchers may also be interested to know how weather enthusiasts may differ in their preparatory activities in comparison with nonweather enthusiasts. All of this information will help meteorologists and media professionals to better target their messages during severe weather.
Analysis of Nanostar Reshaping Kinetics for Optimal Substrate Fabrication
Authors: Vang Der , Strobbia Pietro
Published: September 2022

Gold nanostars (NS) are emerging as a versatile tool in surface-enhanced Raman scattering (SERS) applications because of their wide localized surface plasmon resonance (LSPR) tunability, simple synthesis procedure, and high SERS enhancement. These particles are commonly used in solutions with a stabilizing coating shell (e.g., thiolated molecules or silver shell). However, coatings cannot be used for the fabrication of SERS substrates as the NS have to interact with the substrate planar surface. Without coating, NS have been observed to change over time, leading to a hypochromic shift of the LSPR. To understand this shift, we synthesized surfactant-free gold NS with different spike morphologies and investigated their reshaping morphology and kinetics. Using TEM, the NS sharp spike features were observed to reshape over time. The kinetics of this process were analyzed and determined by monitoring the LSPR, which was observed to follow an exponential decay over time. We used an empirical fit for the LSPR-shift data as a function of time, which permits to predict the LSPR at a specific time based only on the initial LSPR (independently of the initial spike morphology). We show the effect of the LSPR on the SERS signal for the NS and how the SERS signal correlated to our prediction. Finally, we evaluated our approach by fabricating SERS substrates with immobilized NS and collecting the reflectance spectra. We were able to predict the substrate LSPR and aim for an optimal LSPR with an average 3% deviation. These new insights on NS reshaping can permit the fabrication of NS-based substrates with desirable optical/plasmonic properties.
Changing Parental Knowledge and Treatment Acceptance for ADHD: A Pilot Study
Authors: Dixon J. F. , Akins R. , Miller E. , Breslau J. , Gill S. , Bisi E. , Schweitzer J. B.
Published: September 2022

This pilot study assessed the feasibility and potential effectiveness of a single-session workshop in modifying parental beliefs/knowledge about attention-deficit/hyperactivity disorder (ADHD) in children and impact on treatment acceptance/utilization. Concerns raised by school professionals about lack of treatment follow-through after ADHD diagnosis and parental misinformation about medication usage catalyzed this project. A single-group pre-post quasi-experimental design was used. Sixty-eight parents completed ADHD knowledge/belief scales and stress inventories, and pre-ADHD and post-ADHD information workshop. Follow-up calls were made after the workshop to assess treatment utilization. Parents/caregivers experienced significant knowledge and belief changes regarding medication efficacy, willingness to accept physician treatment recommendations, and rejection of non-empirically based treatments. Follow-up data showed that 41% of contacted participants met with physicians to discuss medication utilization and behavioral treatments. Brief, one-session psycho-educational workshops were feasible and impacted parental beliefs and behaviors regarding scientifically supported interventions for ADHD.
A MEMS-INS assisted GNSS vector tracking loop for robust navigation based on cubature Kalman Filter
Authors: Liu Wei , Mou Minghui , Hu Yuan , Huang Hua , Shi Yihang , Wang Shengzheng
Published: September 2022

The occlusion of shade leads to the intermittent reception of satellite signals, which subsequently results in a decline of the positioning accuracy of Global Navigation Satellite System (GNSS). In order to improve the accuracy of positioning and ensure the continuity of navigation results in weak signal environment, a cubature Kalman Filter (CKF)-based micro-electro mechanical-system (MEMS) grade inertial navigation system (INS) assisted GNSS vector tracking (VT) loop is proposed in this paper. Combining effective GNSS measurements and INS information, attitude, velocity, and position results are predicted by CKF, and the pseudo-range results from navigation filter are fed back into the VT loop. The field tests show that the proposed CKF-based MEMS-INS assisted GNSS VT loop can run continuously and stably in weak signal environment with higher navigation accuracy.
Secure device control scheme with blockchain in a smart home
Authors: Park Junbeom , Chang Seongju
Published: September 2022

The Internet of Things (IoT) and blockchain technologies characterizing the era of the fourth industrial revolution have enabled smart home networks to support their various systems and services. In a blockchain-based smart-home network environment, all connected IoT devices must be controlled safely and efficiently. Nevertheless, existing block-chain-based smart-home IoT systems pose a delay issue due to the necessary block generation time. In addition, IoT devices installed in smart homes should be able to prevent forgery attacks such as spoofing because they are often directly associated with personal information. In this study, we proposed an enhanced method to control smart home devices safely and efficiently by applying the zero-knowledge proof combined with a blockchain-based IoT system to protect the public keys of home network devices and the communication among them. The proposed model was approximately 10 s faster than the block generation-based model when it communicated three times in rinkeby, which is one of the test networks of Ethereum.
Experiences of Turkish Paraprofessionals Who Support Students With Autism Spectrum Disorder
Authors: Güleç Aslan Yeşim
Published: September 2022

Paraprofessionals are important members of special education teams. In particular, the experiences of paraprofessionals who support students with autism spectrum disorder may provide valuable insights and thus merit qualitative research. In this narrative study, the relevant experiences of Turkish paraprofessionals are investigated. Findings reveal four themes, namely, working stories, issues experienced, motivational sources, and professional development needs. Moreover, the participants expressed professional and emotional satisfaction despite difficulties. The findings may direct further research efforts toward the formulation of strategies that can alleviate the challenges experienced by paraprofessionals.