bluuebunny/crossref_metadata_2025 huggingface dataset:
Cleaner Production Standards and Increased Technical Complexity for Textile Exporters
Authors: Ju Xiaoying , Ge Xiaoli , Yao Peng
Published: September 2022

An important prerequisite for promoting sustainable development and value chain climbing of textile enterprises is to achieve a win-win situation between environmental protection and export technical complexity. Thus, based on Chinese enterprises’ microdata, this paper investigates the impact of cleaner production standards implementation on the export technical complexity of Chinese textile enterprises using a double difference method. The results show that the implementation of cleaner production standards significantly increases the export technical complexity of Chinese textile enterprises. The results of the mechanism test indicate that cleaner production standards increase export technical complexity by enhancing capital and labor inputs of textile enterprises, as well as by promoting enterprise innovation and increasing productivity. Heterogeneity analysis shows that cleaner production standards have a significant role in increasing the export technical complexity of textile enterprises in the eastern region and larger scale; it is not significant in increasing the export technical complexity of textile enterprises in the central and western regions and smaller scale; in terms of enterprise ownership attributes, it has the greatest role in increasing the export technical complexity of state-owned textile enterprises, followed by foreign and private textile enterprises. The results of this paper show that cleaner production standards, as an environmental regulation policy, can achieve a win-win situation for environmental protection and export technical complexity increase.
Dynamic Equilibrium Strategy of Power Battery Closed-Loop Supply Chain Based on Stochastic Differential Game
Authors: Guan Yue , Xu Xiangdong , Jia Haixiang
Published: September 2022

The industrialization of new energy vehicles has accelerated, and the recycling industry driven by a large number of retired power batteries has exploded rapidly. How to control and deal with decommissioned batteries and balance economic and environmental benefits has become an urgent problem to be solved. Considering the influence of uncertain interference factors, the dynamic equilibrium strategy of power battery closed-loop supply chain members composed of leading manufacturer, recycler, and cascade utilization enterprise was studied. (1) This paper describes the stochastic evolution process of cascade utilization effort level by using Ito process and constructs a stochastic differential game model of closed-loop supply chain dynamic system combined with cost-sharing coordination mechanism. (2) Based on the stochastic differential game theory, the optimal profit function of the participants is given, and the dynamic equilibrium strategy of each participant is obtained. (3) In order to grasp the statistical characteristics of cascade utilization effort level, the random evolution characteristics of cascade utilization effort level are revealed. (4) Combined with numerical example, the influence of relevant parameters on the dynamic system of power battery closed-loop supply chain is analyzed. The results found that with the increase of the proportion of manufacturer sharing the innovation cost of cascade utilization enterprise, the cascade utilization effort level will improve, the profits of cascade utilization enterprise and recycler will increase significantly, the profits of manufacturer will decrease slightly, and the overall profits of the supply chain will increase. The cost-sharing coordination mechanism is conducive to ensuring the steady development of the industry and effectively improving the utilization efficiency of industrial resources.
A Comprehensive Review on Smart Health Care: Applications, Paradigms, and Challenges with Case Studies
Authors: Saba Raoof Syed , Durai M. A. Saleem
Published: September 2022

Growth and advancement of the Deep Learning (DL) and the Internet of Things (IoT) are figuring out their way over the modern contemporary world through integrating various technologies in distinct fields viz, agriculture, manufacturing, energy, transportation, supply chains, cities, healthcare, and so on. Researchers had identified the feasibility of integrating deep learning, cloud, and IoT to enhance the overall automation, where IoT may prolong its application area through utilizing cloud services and the cloud can even prolong its applications through data acquired by IoT devices like sensors and deep learning for disease detection and diagnosis. This study explains a summary of various techniques utilized in smart healthcare, i.e., deep learning, cloud‐based‐IoT applications in smart healthcare, fog computing in smart healthcare, and challenges and issues faced by smart healthcare and it presents a wider scope as it is not intended for a particular application such aspatient monitoring, disease detection, and diagnosing and the technologies used for developing this smart systems are outlined. Smart health bestows the quality of life. Convenient and comfortable living is made possible by the services provided by smart healthcare systems (SHSs). Since healthcare is a massive area with enormous data and a broad spectrum of diseases associated with different organs, immense research can be done to overcome the drawbacks of traditional healthcare methods. Deep learning with IoT can effectively be applied in the healthcare sector to automate the diagnosing and treatment process even in rural areas remotely. Applications may include disease prevention and diagnosis, fitness and patient monitoring, food monitoring, mobile health, telemedicine, emergency systems, assisted living, self‐management of chronic diseases, and so on.
Prevalence and Antimicrobial Resistance of Campylobacter coli and Campylobacter jejuni Isolated from Pig Guts, Pig Feces, and Surface Swabs from the Cutting Tables at Slaughterhouse and Taverns in Southern Benin
Authors: Agbankpe Alidehou Jerrold , Kougblenou Sylvain D. , Dougnon Tamegnon Victorien , Oussou Alida , Gbotche Elodie , Koudokpon Charles Hornel , Legba Brice Boris , Baba-Moussa Lamine , Bankole Honore Sourou
Published: September 2022

Campylobacter food-borne infections are a serious public health problem. In Benin, there is a proliferation of pork consumption in several forms. This study aims to determine the prevalence and the antimicrobial resistance of Campylobacter coli and Campylobacter jejuni strains isolated from pig guts, pig feces, and surface swabs from the cutting tables in southern Benin. For this purpose, 200 samples of pig guts, 40 samples of swabs from the cutting table surface, and 8 samples of pig feces were collected and subjected to bacteriological examination. The method used for the identification of bacteria was microbiological culture combined with molecular identification by PCR. The identified strains were then subjected to antibiotic susceptibility testing according to the methodology recommended by the EUCAST. Antibiotic profiles were compared between strains isolated from pig guts, pig feces, and cutting table surfaces on the one hand and among the different sampling sites on the other hand. The results obtained show that 47.6% of the samples analyzed were contaminated by Campylobacter spp. Molecular identification revealed 34.7% of Campylobacter coli and 9.3% of Campylobacter jejuni. The study of antimicrobial susceptibility showed resistance to ciprofloxacin, 44% to ampicillin, 23.9% to erythromycin, 11% to gentamicin, and 10.1% to amoxicillin + clavulanic acid. In total, 90.8% of the isolated Campylobacter strains were multidrug resistant. The use of antimicrobials in livestock production systems has increased considerably, which could explain, at least partially, the prevalence of Campylobacter and the resistance of strains to antibiotics. To limit the risk of Campylobacter food-borne infections, it is therefore important to include Campylobacter in the list of pathogens to be tested during sanitary quality control of meat and meat products in Benin.
The Development of Tourism Towns with Characteristic Ancient Buildings Based on Partial Differential Model of Competitive Resource Optimization
Authors: Jiang Jing
Published: September 2022

In this paper, a deep learning-based method for solving high-dimensional nonlinear partial differential equations is proposed, that is, the deep backward stochastic differential equation method. The solution function of the high-dimensional partial differential equation is represented by the corresponding solution function of the backward stochastic differential equation. The substantive carrier of ancient town tourism is the ancient town itself. The essence of resources and the ancient town are highly unified, resource occupiers (suppliers) and tourism participants are highly unified, and tourists need to be highly coupled with the essence of tourism products. The art of ancient architecture is not only an important material basis for the sustainable development of the local tourism industry but also an important experience reference for the traditional architectural design of the creation of artistic architecture in the new era. To create a tourist destination of ancient architecture in a characteristic town, it will contribute to the sustainable development of the local economy and society. Taking the policy support related to tourism of ancient buildings as the starting point, and the internal cultural heritage as the basis for development, we explore the characteristic activities and products, integrate natural tourism resources and modern tourism resources in the whole region, to help ancient buildings become an important driving force to promote the development of the tourism industry.
[Retracted] System Construction of Athlete Health Information Protection Based on Machine Learning Algorithm
Authors: Liu Long , Fan Xiaodong
Published: September 2022

The exercise volume and exercise level can be quantitatively assessed by measuring and collecting athletes’ health and exercise data. The protection of athletes’ health information has lately become an important research topic due to a rise in sports activities. However, due to the nature of the data and the limits of protection models, protecting athlete health data is a complex undertaking. Machine learning and blockchain have caused worldwide technological innovation, and it is bound to bring deep modifications to the sports industry. The main purpose of blockchain is security, decentralization, traceability, and credibility of the athlete’s health data protection and gathering system. To progress and increase the sports industry and methodically assess the physical fitness of sportspersons’ health information, this study concentrates on the Machine Learning and Blockchain‐based Athlete Health Information Protection System (MLB‐AHIPS) proposed in the sports industry. The ML technique is utilized to clean and handle the information to comprehend the recognition and secure managing of the sportsperson’s fitness information. The system uses attribute‐based access control, which permits dynamic and fine‐grained access to athlete health data, and then stores the health data in the blockchain, which can be secured and tamper‐proof by expressing the respective smart contracts. The simulation outcomes illustrate that the suggested MLB‐AHIPS attains a high accuracy ratio of 97.8%, security ratio of 98.3%, an efficiency ratio of 97.1%, scalability ratio of 98.9%, and data access rate of 97.2% compared to other existing approach.
[Retracted] Computational Biology Predicts the Efficacy of Tumor Immune Checkpoint Blockade
Authors: Kang Wenyi , Tong Yao , Zhang Weijia , Jian Mengru , Zhang Anqi , Ren Guoqing , Fan Hao , Yang Jiyuan
Published: September 2022

Tumor immunotherapy is considered as one of the most promising methods in cancer treatment in recent years. Immune checkpoint blockade (ICB) can activate immune cells to destroy tumors by relieving the inhibitory pathway of tumor cells to immune cells. In silico prediction of the ICB response is an important step toward achieving effective and personalized cancer immunotherapy. Although immune checkpoint inhibitors have shown exciting clinical effects in the treatment of many types of tumors, there are still some clinical problems in practical application, such as low response rate and large individualized differences. How to predict the efficacy of effective individualized immune checkpoint inhibitors for tumor patients based on specific biomarkers and computational models is one of the key issues in the immunotherapy of this kind of tumor. In our work, from the five levels of genome level, transcription level, epigenetic level, microbial taxonomy level, and the immune cell infiltration profile level, the biomarkers and in silico calculation methods that affect the efficacy of tumor immune checkpoint inhibitors are comprehensively summarized.
Indistinguishable Element-Pair Attribute Reduction and Its Incremental Approach
Authors: Liang Baohua , Zhang Haiqi , Lu Zhengyu , Zhang Zhengjin
Published: September 2022

Attribute reduction is a popular approach of preprocessing data. Discernibility matrix is a typical method that focuses on attribute reduction. Faced with the processing of modern information systems with large amounts of data and rapid changes, the traditional static discernibility matrix reduction model is powerless. To overcome this shortcoming, this paper first proposes an indistinguishable element pair method that does not need to store discernibility information, which retains the advantages of institution and easy-to-understand, and at the same time effectively solves the problem of space consumption. In order to make the model adapt to the processing of dynamic data sets, we further study the incremental mechanism and design a set of dynamic reduction models, which can adjust the reduction set in time according to the changes of objects. Theoretical analysis and experimental results indicate that the proposed algorithm is obviously superior to the discernibility matrix model, and can effectively deal with the reduction of dynamic data sets.
Performance Evaluation and Estimation of Energy Measures of Grid-Connected PV Module
Authors: Srimathi R. , Meenakshi J. , Vijayabhasker R. , Belay Semagn Shifere
Published: September 2022

In this paper, the effectiveness of two grid-connected photovoltaic (PV) techniques up of copper indium selenium (CIS) and monocrystalline silicon (m-Si) arrays has been examined. In order to determine whether the technology is suitable for the actual winter and summer climatic conditions in Thoothukudi, Tamil Nadu, the observed and calculated performances have been compared. The final yield, photovoltaic (PV) effectiveness, array yield, performance ratio, and capacity utilisation factor seem to be the variables used to evaluate performance. Using recorded meteorological data at the selected location, PVsyst software predicts both PV systems’ year-round performances. These predictions are then contrasted to the outcomes of the actual measurements. The outcome showed that with a maximal observed performance ratio, both PV systems function marginally better in the winters than those in the summers. The performance indicators of the PV mechanisms are contrary with those of other PV systems with comparable capacities that are located in different places.
Recent Advances in Methods for Synthesis of Carbon Nanotubes and Carbon Nanocomposite and their Emerging Applications: A Descriptive Review
Authors: Gacem Amel , Modi Shreya , Yadav Virendra Kumar , Islam Saiful , Patel Aradhna , Dawane Vinars , Jameel Mohammed , Inwati Gajendra Kumar , Piplode Satish , Solanki Vijendra Singh , Basnet Anup
Published: September 2022

Nanomaterials have gained huge applications ever since their discoveries, especially in the field of electronics, medicine, research, and environmental cleanup. Nanomaterials have a high surface area‐to‐volume ratio along with high surface energies making them suitable for such wide applications. Carbon nanotubes (CNTs) and carbon nanocomposite (CNC) materials are remarkable nanomaterials that have become the backbone of most industries these days. Both materials have gained huge attention in the last decade by the scientific community. CNTs come in two variants, i.e., single‐walled CNTs (SW‐CNTS) and multiwalled CNTs (MW‐CNTs). Due to their wider applications, CNT synthesis is currently emerging with the advancement in technology. Currently, CNTs are being synthesized by chemical as well as physical approaches. The current review article focuses on the vital research and application for the synthesis of CNTs depending on the quality of the nanotube materials. Controlled routes to their organization and assembly are also discussed in detail over here. The aim is to provide recent advances in the synthesis methods, of CNTs, their current applications, future applications, and the potential of agrowaste and industrial waste for the synthesis of CNTs and nanomaterials.
Methane Extraction and Resource Utilization Based on Multisource Data Fusion
Authors: Chen Wensheng , Lu Zhongliang
Published: September 2022

Gas clusters can reprove the sewage ability of flame-permeability char joint, but the interaction motion between proposed vapor molecules and gasoline-confine charcoal during the wind enema advance is still unclear. For this consideration, supported by the surface assimilation figure of qualifier-enclose char, the magnificent orthodox whole Monte Carlo (GCMC) manner was interesting to ponder the elution conduct of CH4 in the wind-confine charcoal configuration after the farding bag of N2/CO2 under distinct enema stamp. The clockwork of N2/C advances the elution of CH4 in charcoal. The examination ensues showed the following: (1) Compared with the enema of N2, the gasoline-restrain charcoal has more familiar CH4 molecules after CO2 enema, and the constituting force of the CH4-CO2 system is everywhere more humble than that of the CH4-N2 system, the former is more fix. (2) In the same enema pattern, obtained with the CH4-N2 system, the CH4 grout indicated more regular distribution in the CH4-CO2 system. CH4 heptane is more active, the expansion cooperation of CH4 in the CH4-CO2 system is more, and the effect of CO2 in promoting the elution of CH4 is better. (3) After CO2/N2 is interjected into the fart-hold charcoal construction, as the enema compression extension, the referring concentrations of CO2, N2, and CH4 in the coping wax, the opposite to major of CH4 in the CH4-CO2 system is the zenith everywhere. In the CH4—N2 system, the opposite to major of CO2 in the CH4 and CH4—CO2 system is in the centric, and the opposite to major of N2 in the CH4—N2 system is the lowermost. (4) The reasonably enema affliction for N2 to raise CH4 elution is between 2 and 4 MPa, and CO2 is honest to advance CH4 elution. The enema urgency is between 3 and 4 MPa. Based on this data, methane extraction and resource utilization can be improved to a certain extent. The result has shown that the inquiry effect can condition speculative uphold for the research studies of char cicatrix petrol enema irritation technology.
Exploring the Spatially Heterogeneous Effects of the Built Environment on Bike-Sharing Usage during the COVID-19 Pandemic
Authors: Yang Hongtai , Guo Zishuo , Zhai Guocong , Yang Linchuan , Huo Jinghai
Published: September 2022

Bike-sharing holds promise for available and healthy mobility services during COVID-19 where bike sharing users can make trips with lower health concerns due to social distancing compared to the restricted transportation modes such as public transit and ridesharing services. Leveraging the trip data of the Divvy bike-sharing system in Chicago, this study exploresspatially heterogeneous effects of built environment on bike-sharing usage under the pandemic. Results show that the average weekly ridership declined by 52.04%. To account for the spatially heterogeneous relationship between the built environment and the ridership, the geographically weighted regression (GWR) model and the semiparametric GWR (S-GWR) model are constructed. We find that the S-GWR model outperforms the GWR and the multiple linear regression models. The results of the S-GWR model indicate that education employment density, distance to subway, COVID-19 cases, and ridership before COVID-19 are global variables. The effects between ridership and the built environment factros (i.e., household density, office employment density, and the ridership) vary across space. The results of this study could provide a useful reference to transportation planners and bike-sharing operators to determine the high bike-sharing demand area under the pandemic,thus adjusting station locations, capacity, and rebalancing schemes accordingly.
Flow-Mediated Dilatation in the Assessment of Coronary Heart Disease: A Meta-Analysis
Authors: Xiao Xiaoyong , Li Xiang , Xiao Xiaohua , Wang Jingjing , Liu Dehong , Deng Zhe
Published: September 2022

Endothelial dysfunction may contribute to the increased morbidity and mortality associated with coronary heart disease (CHD). Flow-mediated dilatation (FMD) is the most popular noninvasive method for vascular endothelial function evaluation. This meta-analysis aimed to investigate the association between FMD and CHD. We searched the publications listed in the PubMed, Web of Science, Scopus, and Embase databases. Stata 14 software was used to analyze the data. Standardized mean difference (SMD) was used to calculate FMD levels, and the effect sizes were expressed with a 95% confidence interval (CI). I2 statistics were used to evaluate statistical heterogeneity. In this meta-analysis, 9 studies enrolled a total number of 943 participants, including 534 (56.63%) patients with CHD and 409 controls (43.37%). We found that patients with CHD showed a significantly lower FMD than the controls (SMD −0.706%; 95% CI: −0.985, −0.427;P=0.001) with high heterogeneity. In addition, funnel plot analysis suggested asymmetry that could be evidence of publication bias. But sensitivity analyses show that there were no influential studies. This meta-analysis provides evidence that patients with CHD show a significantly lower FMD than controls and highlights the literature on FMD as a hallmark in CHD diseases.
An Integrative Multi-Omics Analysis Based on Nomogram for Predicting Prostate Cancer Bone Metastasis Incidence
Authors: Zhao Jun , Wang Rui , Sun Xiaoxin , Huang Kai , Jin Jiacheng , Lan Lan , Jian Yuli , Xu Zhongyang , Wu Haotian , Wang Shujing , Wang Jianbo
Published: September 2022

Background. The most common site of prostate cancer metastasis is bone tissue with many recent studies having conducted genomic and clinical research regarding bone metastatic prostate cancer. However, further work is needed to better define those patients that are at an elevated risk of such metastasis. Methods. SEER and TCGA databases were searched to develop a nomogram for predicting prostate cancer bone metastasis. Results. Herein, we leveraged the Surveillance, Epidemiology, and End Results (SEER) database to construct a predictive nomogram capable of readily and accurately predicted the odds of bone metastasis in prostate cancer patients. This nomogram was utilized to assign patients with prostate cancer included in The Cancer Genome Atlas (TCGA) to cohorts at a high or low risk of bone metastasis (HRBM and LRBM, respectively). Comparisons of these LRBM and HRBM cohorts revealed marked differences in mutational landscapes between these patient cohorts, with increased frequencies of gene fusions, somatic copy number variations (CNVs), and single nucleotide variations (SNVs), particularly in the P53 gene, being evident in the HRBM cohort. We additionally identified lncRNAs, miRNAs, and mRNAs that were differentially expressed between these two patient cohorts and used them to construct a competing endogenous RNA (ceRNA) network. Moreover, three weighted gene co-expression network analysis (WGCNA) modules were constructed from the results of these analyses, with KIF14, MYH7, and COL10A1 being identified as hub genes within these modules. We further found immune response activity levels in the HRBM cohort to be elevated relative to that in the LRBM cohort, with single sample gene enrichment analysis (ssGSEA) scores for the immune checkpoint signature being increased in HRBM patient samples relative to those from LRBM patients. Conclusion. We successfully developed a nomogram capable of readily detecting patients with prostate cancer at an elevated risk of bone metastasis.
A Rare Case of Cardiac Recovery after Acute Myocarditis from West Nile Virus Infection: A Review of the Current Literature
Authors: Lei KaChon , Ji Wilbur , Bhaya Bhavana , Ahsan Chowdhury
Published: September 2022

West Nile Virus (WNV) myocarditis is nearly fatal, according to the current medical literature. We report a previously healthy 37-year-old Caucasian male who presented to our facility with two days of progressive lower extremity weakness, fever, edema, and shortness of breath found to have left ventricular global hypokinesis with an ejection fraction of less than 25%, consistent with acute viral myocarditis. He also has concomitant WNV meningoencephalitis due to his altered mentation. He was found to have a positive serum WNV IgM suggestive of a diagnosis of WNV myocarditis. He was intubated and was placed on vasoactive pressors for supportive care due to evidence of mixed cardiogenic and septic shock. After two weeks of hemodynamic support, we discovered a near-complete cardiac recovery, as shown on a repeat transthoracic echocardiography (TTE) and a normalized mean arterial blood pressure. This is a unique case report because near fatality is often associated with WNV myocarditis secondary to tachyarrhythmia, and there are currently no documented cases that are suggestive of cardiac recovery from the current literature.
Analytical Approximation of Brusselator Model via LADM
Authors: Muhammad Khan Faiz , Ali Amjad , Abdullah  , Shah Kamal , Khan Aziz , Mahariq Ibrahim
Published: September 2022

In this paper, we have investigated the fractional-order Brusselator model for the approximate analytical solution. The concerned coupled system of nonlinear fractional-order partial differential equations (PDEs) has been considered in many research articles to describe various real-world problems. Nonlinear dynamical systems are increasingly used in autocatalytic chemical reactions. These types of autocatalytic chemical reaction models have a variety of applications in several physical systems. The Brusselator model is one of the intensively used autocatalytic models. We have obtained the approximate solution of the considered fractional nonlinear Brusselator model in the Caputo sense by using the Laplace–Adomian decomposition method (LADM). We have established a general scheme for the solution to the proposed model by applying the LADM. We then testified two examples to demonstrate our analysis. The results we have obtained ensure the accuracy and effectiveness of the proposed technique. The said technique does not require any kind of prior discretization or collocation. Also, with the help of Matlab, we have presented 2D and 3D plots for the approximate solution.
Echoing Mechanism of Juvenile Delinquency Prevention and Occupational Therapy Education Guidance Based on Artificial Intelligence
Authors: Hou Fang
Published: September 2022

In this paper, in-depth research and analysis of juvenile delinquency prevention and occupational therapy education guidance using artificial intelligence are conducted, and its response mechanism is designed in this way. Two crime type prediction algorithms based on time-crime type count vectorization and dense neural network and crime type prediction based on the fusion of dense neural network and long- and short-term memory neural network are proposed. The outputs of both are fed into a new neural network for training to achieve the fusion of the two neural networks. Among them, the use of the dense neural network can effectively fit the relationship between the constructed features and crime types. The behavioral manifestations and causes of the formation of deviant behavior in adolescents are discussed. They can only read numerical data, but there is a lot of information in the textual data that is closely related to the training effect. When experimenting, it is necessary to extract knowledge and build applications. The practical work with adolescents with deviant behaviors is again carried out from group work and casework, respectively, with problem diagnosis, needs assessment, and service plan development for specific clients, to carry out relevant practical service work. The causes of juvenile delinquency in the Internet culture are discussed in terms of the Internet environment, juvenile use of the Internet, Internet supervision, and crime prevention education, respectively. The fourth chapter focuses on the analysis of the prevention and control measures for juvenile delinquency in cyberculture. In response to the above-mentioned causes of juvenile delinquency in cyberculture, the prevention and control measures are discussed in four aspects, namely, strengthening the construction of cyberculture and building a healthy cyber environment, strengthening the capacity building of guiding juveniles to use cyber correctly, building a prevention and supervision system to promote the improvement of the legal system, and improving and innovating the crime prevention education in the cyber era.
A Comparison of the Ligation Torque Expression of a Ribbonwise Bracket–Archwire Combination and a Conventional Combination: A Primary Study
Authors: Lin Bin , Jiang Feifei , Chen Jie , Liang Jiaxing
Published: September 2022

Objective. To assess the effect of the third-order mechanics of a new ribbonwise bracket–archwire combination using an orthodontic torque simulator. Material and Methods. An orthodontic torque simulator was used to measure the third-order moment of a maxillary central incisor as it changed from a neutral position to a 40° rotation in 1° increment. A new ribbonwise bracket (Xinya, China) was compared with a conventional ligation bracket (American Orthodontic, U.S.A.). The effects of different archwire sizes (i.e., 0.017″ × 0.025″ and 0.019″ × 0.025″) and materials (i.e., nickel-titanium, titanium-molybdenum alloy, and stainless steel) were analyzed. Paired sample t-tests were conducted to compare the moments between the two bracket types corresponding to each of the archwires. The effects of the stiffness of the bracket–archwire complexes were also assessed. Results. Statistically significant differences (

P
=
0.05

) between the moments from the two brackets were found. The ribbonwise bracket–archwire complex generated larger moments when the rotation angle was lower than 30°. The ribbonwise brackets produced moments that could reach a threshold of 5 Nmm more quickly as the angle was increased. The higher the stiffness of the complex, the larger the moment. Conclusion. The ribbonwise bracket–archwire complex reached the moment threshold limits earlier than the conventional complex. When the rotation angle is less than 30°, the ribbonwise bracket–archwire complex generated a greater torque moment in comparison with the conventional complex.
FD2Foremer: Thinking Face Forgery Detection in Midfrequency Geometry Details
Authors: Li Wentao , Shen Zhidong
Published: September 2022

Face forgery by DeepFake has caused widespread concern in community because of the synthesized media’s risks to the society. However, advances in recent years have been able to produce synthetic images indistinguishable from real images in the RGB space. Extracting midfrequency facial geometry details, including person-specific details and dynamic expression-dependent ones on facial geometry surfaces, is a promising way to highlight forgery clues during face forgery detection. In this paper, we use 3D face reconstruction to generate the displacement map from a single input face image, which is able to represent middle and fine scale details by indicating signed distance from the point in UV space. The cropped face images can also provide eyes and mouse information, so we use face image and its displacement map to extract the image features. Besides, we save the computation cost and maintain competitive performance using a universal transformer architecture and introduce a manifold distillation strategy to train our model from a more complex transformer backbone. Extensive experiments on various public DeepFake datasets indicate the effectiveness of the extracted facial geometry details, and proposed method achieves competitive performance.
Coefficient Inequalities for a Subclass of Symmetric q ‐Starlike Functions Involving Certain Conic Domains
Authors: Khan Mohammad Faisal , Khan Nazar , Araci Serkan , Khan Shahid , Khan Bilal
Published: September 2022

In this paper, we make use of a certain Ruscheweyh‐type q ‐differential operator to introduce and study a new subclass of q ‐starlike symmetric functions, which are associated with conic domains and the well‐known celebrated Janowski functions in . We then investigate many properties for the newly defined functions class, including for example coefficients inequalities, the Fekete–Szegö Problems, and a sufficient condition. There are also relevant connections between the results provided in this study and those in a number of other published articles on this subject.
The Influence of Brand Visual Communication on Consumer Psychology Based on Deep Learning
Authors: Wang Hui
Published: September 2022

In order to solve the problem that there are few methods of users’ consumption psychology, the author proposes a research on the influence of brand visual communication on consumer psychology based on deep learning. First, establish the mapping relationship between experience level-product features-aspect words and then use aspect word extraction technology, mining users’ attention to different experience levels from user comments and dividing users into three types: instinctive preference, behavioral preference, and reflective preference; finally, the deep learning-based aspect sentiment analysis technology is used to calculate the user’s preference for the product and further analyze the characteristics of different types of users. Experimental results show that based on the application analysis of more than 900,000 JD.com mobile phone review data, three types of consumer preference user groups were obtained, of which instinctive preference users accounted for 41.6%; it is higher than behavioral preference users (33.01%) and reflection preference users (25.39%), and the consumption characteristics of the three types of users are analyzed from the aspects of mobile phone brand and price. It is proved that the author’s user portrait method can better express the consumption preferences of different types of users.
The Effective Analysis for Blue Honeysuckle Extract in the Treatment of Hepatocellular Carcinoma
Authors: Zhang Chun-Peng , Li Wei-Hua , Liu Jia-Ren , Li Guo-Dong , Zhang Hao-Peng , Wei Jiu-Feng , Chen Hong-Sheng , Zhao Jin-Lu , Wang Yun-Feng , Lv Qiang , Liu Ming
Published: September 2022

To further determine how BHE affected the growth of HCC cells, the proportion of each cell cycle phase was explored in HCC cells by flow cytometry. Blue honeysuckle (Lonicera caerulea L.) is a species of bush that grows in eastern Russia. Blue honeysuckle extract (BHE) is rich in bioactive phytochemicals which can inhibit the proliferation of tumor cells. The mechanism underlying the anticancer activity of BHE in primary liver cancer is poorly understood. The purpose of this study was to evaluate the growth inhibition mechanism of bioactive substances from blue honeysuckle on hepatocellular carcinoma (HCC) cells and to explore its protein and gene targets. The compounds in BHE were determined by high-performance liquid chromatography (HPLC) and liquid chromatography-mass spectrometry (LC-MS). Cell counting kit-8 (CCK8) assay was used to evaluate the effects of BHE on HCC cell proliferation, and flow cytometry assay (FCA) was used to determine how BHE arrested the proportion of each cell cycle phase in HCC cells. Western blot (WB) was performed to determine the expression of cell cycle-related proteins in HCC cells treated with different concentrations of BHE. The xenograft tumor animal models were established by HCC cell implantation. The results showed that cyanidin-3-o-glucoside and cyanidin-3-o-sophoroside which are the main biologically active components were detected in BHE. BHE is highly effective in inhibiting the proliferation of HCC cells by arresting the HCC cell cycle in the G2/M phase. BHE also downregulated the expression of conventional or classical dendritic cells-2 (cDC2) and cyclin B1 by promoting the expression of myelin transcription factor 1 (MyT1) in HCC cells. The weight and volume of xenografts were significantly decreased in the BHE treated groups when compared to the control group. BHE increased the expression of MyT1 in xenograft tissues. These findings showed that blue honeysuckle extract inhibits proliferation in vivo and in vitro by downregulating the expression of cDC2 and cyclin B1 and upregulating the expression of MyT1 in HCC cells.
Role of Chemoradiation in the Adjuvant Treatment of Radically Resected Pancreatic Cancer Patients: A Mono-Institutional Retrospective Analysis
Authors: Mattiucci Gian Carlo , Salvatore Lisa , D’Aviero Andrea , Bagalà Cinzia , Bensi Maria , Castronovo Francesco Mosè , Cellini Francesco , De Franco Paola , Di Stefano Brunella , Macchia Gabriella , Masiello Valeria , Menghi Roberta , Quero Giuseppe , Reina Sara , Morganti Alessio Giuseppe , Alfieri Sergio , Tortora Giampaolo , Valentini Vincenzo
Published: September 2022

Introduction: Pancreatic cancer (PC) represents an unfavorable prognosis condition, even in patients with resectable disease. The aim of this series was to investigate the role of treatment intensification with adjuvant chemoradiation (CRT) in radically resected PC patients. Methods: Data from PC patients who underwent radical surgery, adjuvant chemotherapy (CT), and CRT throughout a 20-year period were retrospectively collected. Actuarial local control (LC) and the overall survival (OS) were the primary endpoints, with disease-free survival and metastasis-free survival (MFS) representing secondary endpoints. Results: The analysis included 108 PC patients treated with adjuvant CRT and CT from January 2000 to August 2019. Median age was 66 years (range: 40–83), and all patients underwent radical surgical resection with adjuvant CT (88, 81.5%) plus concomitant CRT (101, 93.5%) or radiotherapy alone (7, 6.5%). The median dose delivered to the tumor bed was 50.4 Gy (range: 45–50.6 Gy), while median dose to regional lymphatic drainage stations was 39.6 Gy (range 39.6–45 Gy). Concomitant CT was a gemcitabine-based regimen in the vast majority of patients (87, 80.6%). Median follow-up time was 21 months; the 2- and 5-year LC rates were 75.8% and 59.1%, respectively. Perineural invasion at pathological assessment was found significantly associated with LC (p = 0.028). Median OS was 40 months with 2- and 5-year OS rates of 73.9% and 41.6%, respectively. Conclusions: The outcomes of this series suggest to investigate the possible impact of adding adjuvant CRT to CT in PC patients. Timing and combination of modern CRT with new systemic therapies need to be further investigated to personalize therapy and optimize clinical advantages.
Investigating the Link between Later-Life Brain Volume and Cardiorespiratory Fitness after Mild Traumatic Brain Injury Exposure
Authors: Markovic Shaun J. , Hellewell Sarah C. , Doré Vincent , Xia Ying , Scott Brendan R. , Peiffer Jeremiah J. , Fitzgerald Melinda , Brown Belinda M.
Published: September 2022

Introduction: Evidence suggests that maintaining a higher level of cardiorespiratory fitness (CRF) later in life can offer some protection against brain volume loss as we age. By contrast, mild traumatic brain injury (mTBI) could accelerate age-related cortical atrophy. The current study sought to examine whether variations in the CRF level modified the association between mTBI history and brain volumetric measures in a sample of older adults. Methods: Seventy-nine community-dwelling older adults (mean age 68.7 ± 4.3 years, 54.4% female) were assessed for their mTBI history: 25 participants (32%) reported sustaining at least one lifetime mTBI. Participants also underwent a CRF assessment and magnetic resonance imaging (MRI) to obtain global and region-of-interest volumes. Results: Analysis of covariance, controlling for age, sex, education, and apolipoprotein (APOE) ε4 allele carriage, revealed that participants with a history of mTBI had a significantly larger total mean grey matter volume (582.21 ± 12.46 cm3) in comparison to participants with no mTBI history (571.08 ± 17.21 cm3, p = 0.01 after correction for multiple comparisons). However, no differences between groups based on mTBI history were found for total white matter volume or in any other cortical or subcortical structures examined. A subsequent moderation analysis found that CRF was predominantly non-influential on the association between mTBI history and the MRI-quantified measures of brain volume. Conclusion: While unexpected, the findings suggest that a history of mTBI can lead to grey matter alterations in the ageing brain. However, concurrent variations in the CRF level did not influence the differences in brain volume found based on mTBI exposure status.
Ex Vivo Study Using Diffusion Tensor Imaging to Identify Biomarkers of Atherosclerotic Disease in Human Cadaveric Carotid Arteries
Authors: Tornifoglio Brooke , Stone Alan J. , Kerskens Christian , Lally Caitríona
Published: September 2022

Background:

This study aims to address the potential of ex vivo diffusion tensor imaging to provide insight into the microstructural composition and morphological arrangement of aged human atherosclerotic carotid arteries.

Methods:

In this study, whole human carotid arteries were investigated both anatomically and by comparing healthy and diseased regions. Nonrigid image registration was used with unsupervised segmentation to investigate the influence of elastin, collagen, cell density, glycosaminoglycans, and calcium on diffusion tensor imaging derived metrics (fractional anisotropy and mean diffusivity). Early stage atherosclerotic features were also investigated in terms of microstructural components and diffusion tensor imaging metrics.

Results:

All vessels displayed a dramatic decrease in fractional anisotropy compared with healthy animal arterial tissue, while the mean diffusivity was sensitive to regions of advanced disease. Elastin content strongly correlated with both fractional anisotropy (r>0.7,
P
<0.001) and mean diffusivity (r>−0.79,
P
<0.0002), and the thickened intima was also distinguishable from arterial media by these metrics.

Conclusions:

These different investigations point to the potential of diffusion tensor imaging to identify characteristics of arterial disease progression, at early and late-stage lesion development.
Implementing the National Heart, Lung, and Blood Institute’s Strategic Vision in the Division of Cardiovascular Sciences—2022 Update
Authors: Grant Meagan G. , Pratt Charlotte , Wong Renee P. , Addou Ebyan , Desvigne-Nickens Patrice , Campo Rebecca A. , Donze Laurie Friedman , Barnes Vanessa I. , Schopfer David W. , Jaquish Cashell E. , Fleg Jerome , Galis Zorina S. , Fenton Kathleen , Oh Young S. , Hong Yuling , Chen Jue , Wang Wayne , Fine Lawrence , Goff David C.
Published: September 2022

Spurred by the 2016 release of the National Heart, Lung, and Blood Institute’s Strategic Vision, the Division of Cardiovascular Sciences developed its Strategic Vision Implementation Plan—a blueprint for reigniting the decline in cardiovascular disease (CVD) mortality rates, improving health equity, and accelerating translation of scientific discoveries into better cardiovascular health (CVH). The 6 scientific focus areas of the Strategic Vision Implementation Plan reflect the multifactorial nature of CVD and include (1) addressing social determinants of CVH and health inequities, (2) enhancing resilience, (3) promoting CVH and preventing CVD across the lifespan, (4) eliminating hypertension-related CVD, (5) reducing the burden of heart failure, and (6) preventing vascular dementia. This article presents an update of strategic vision implementation activities within Division of Cardiovascular Sciences. Overarching and cross-cutting themes include training the scientific workforce and engaging the extramural scientific community to stimulate transformative research in cardiovascular sciences. In partnership with other NIH Institutes, Federal agencies, industry, and the extramural research community, Division of Cardiovascular Sciences strategic vision implementation has stimulated development of numerous workshops and research funding opportunities. Strategic Vision Implementation Plan activities highlight innovative intervention modalities, interdisciplinary systems approaches to CVD reduction, a life course framework for CVH promotion and CVD prevention, and multi-pronged research strategies for combatting COVID-19. As new knowledge, technologies, and areas of scientific research emerge, Division of Cardiovascular Sciences will continue its thoughtful approach to strategic vision implementation, remaining poised to seize emerging opportunities and catalyze breakthroughs in cardiovascular sciences.
Disruption of Sarcoplasmic Reticulum‐Mitochondrial Contacts Underlies Contractile Dysfunction in Experimental and Human Atrial Fibrillation: A Key Role of Mitofusin 2
Authors: Li Jin , Qi Xi , Ramos Kennedy S. , Lanters Eva , Keijer Jaap , de Groot Natasja , Brundel Bianca , Zhang Deli
Published: September 2022

Background

Atrial fibrillation (AF) is the most common and progressive tachyarrhythmia. Diabetes is a common risk factor for AF. Recent research findings revealed that microtubule network disruption underlies AF. The microtubule network mediates the contact between sarcoplasmic reticulum and mitochondria, 2 essential organelles for normal cardiomyocyte function. Therefore, disruption of the microtubule network may impair sarcoplasmic reticulum and mitochondrial contacts (SRMCs) and subsequently cardiomyocyte function. The current study aims to determine whether microtubule‐mediated SRMCs disruption underlies diabetes‐associated AF.

Methods and Results

Tachypacing (mimicking AF) and high glucose (mimicking diabetes) significantly impaired contractile function in HL‐1 cardiomyocytes (loss of calcium transient) and
Drosophila
(reduced heart rate and increased arrhythmia), both of which were prevented by microtubule stabilizers. Furthermore, both tachypacing and high glucose significantly reduced SRMCs and the key SRMC tether protein mitofusin 2 (MFN2) and resulted in consequent mitochondrial dysfunction, all of which were prevented by microtubule stabilizers. In line with pharmacological interventions with microtubule stabilizers, cardiac‐specific knockdown of MFN2 induced arrhythmia in
Drosophila
and overexpression of MFN2 prevented tachypacing‐ and high glucose–induced contractile dysfunction in HL‐1 cardiomyocytes and/or
Drosophila
. Consistently, SRMCs/MFN2 levels were significantly reduced in right atrial appendages of patients with persistent AF compared with control patients, which was aggravated in patients with diabetes.

Conclusions

SRMCs may play a critical role in clinical AF, especially diabetes‐related AF. Furthermore, SRMCs can be regulated by microtubules and MFN2, which represent novel potential therapeutic targets for AF.