bluuebunny/crossref_metadata_2025 huggingface dataset:
End‐to‐End Semantic Leaf Segmentation Framework for Plants Disease Classification
Authors: Khan Khalil , Khan Rehan Ullah , Albattah Waleed , Qamar Ali Mustafa
Published: May 2022

Pernicious insects and plant diseases threaten the food science and agriculture sector. Therefore, diagnosis and detection of such diseases are essential. Plant disease detection and classification is a much‐developed research area due to enormous development in machine learning (ML). Over the last ten years, computer vision researchers proposed different algorithms for plant disease identification using ML. This paper proposes an end‐to‐end semantic leaf segmentation model for plant disease identification. Our model uses a deep convolutional neural network based on semantic segmentation (SS). The proposed algorithm highlights diseased and healthy parts and allows the classification of ten different diseases affecting a specific plant leaf. The model successfully highlights the foreground (leaf) and background (nonleaf) regions through SS, identifying regions as healthy and diseased parts. As the semantic label is provided by the proposed method for each pixel, the information about how much area of a specific leaf is affected due to a disease is also estimated. We use tomato plant leaves as a test case in our work. We test the proposed CNN‐based model on the publicly available database, PlantVillage. Along with PlantVillage, we also collected a dataset of twenty thousand images and tested our framework on it. Our proposed model obtained an average accuracy of 97.6%, which shows substantial improvement in performance on the same dataset compared to previous results.
Implementation of Artificial Neural Network to Predict Diabetes with High-Quality Health System
Authors: E. P. Prakash , K. Srihari , Karthik S. , M. V. Kamal , P. Dileep , Reddy S. Bharath , M. A. Mukunthan , K. Somasundaram , R. Jaikumar , N. Gayathri , Sahile Kibebe
Published: May 2022

Patients with diabetes who are closely monitored have a higher overall quality of life than those who are not. Costs associated with healthcare can be decreased by utilising the Internet of Things (IoT), thanks to technological advancements. To satisfy the expectations of e-health applications, it is required for the development of the intelligent systems as well as increases the number of applications that are connected to the network. As a result, in order to achieve these goals, the cellular network should be capable of supporting intelligent healthcare applications that require high energy efficiency. In this paper, we model a neural network-based ensemble voting classifier to predict accurately the diabetes in the patients via online monitoring. The study consists of Internet of Things (IoT) devices to monitor the instances of the patients. While monitoring, the data are transferred from IoT devices to smartphones and then to the cloud, where the process of classification takes place. The simulation is conducted on the collected samples using the python tool. The results of the simulation show that the proposed method achieves a higher accuracy rate, higher precision, recall, and f-measure than existing state-of-art ensemble models.
A Rare Occurrence of Bilateral Single-Rooted Mandibular First Molar
Authors: Ujariya Urvashi , Bharatiya Rajendra , Kothari Anjali , Shah Viraj , Parikh Mishri , Pandey Kruti , Mehta Dhara , Amin Nishi
Published: May 2022

It is essential to have an in-depth knowledge of root and root canal anatomy to prevent any iatrogenic errors. Many studies and case reports are present in the literature related to the anatomy of mandibular first molars, but most of them are on an extra number of roots and root canals. There are few studies related to a lower number of roots and root canals, but the occurrence of bilateral mandibular first and second molars with the presence of root fusion resulting in a single root is very rare. This case report presents the nonsurgical endodontic management of the left and right mandibular first molars with the presence of a single root confirmed using a CBCT and treated by placing an apical MTA plug followed by backfill using thermoplasticised gutta percha.
Effects of Coarse and Fine Crushed Clay Brick Content on the Compressive Strength of Recycled Aggregate Concrete and the Microscopic Mechanism
Authors: Chang Jin , Luo Shi-lin , Ailifeila Aierken , Chong Lin-lin , Jiang Jian-qing
Published: May 2022

The objective of this study is to investigate the compressive strength and microstructural evolution of recycled aggregate concrete (RAC) containing coarse and fine clay brick aggregates. The compressive strength tests, scanning electron microscopy (SEM) observations, and X-ray diffraction (XRD) tests were performed on RAC and natural aggregate concrete (NAC) containing different coarse and fine crushed clay brick contents. The results showed that the compressive strength of NAC and RAC decreased with the increase of crushed clay brick content, and the growth rate of their compressive strength slowed down with the increase of age. At the same age and replacement rate, fine crushed clay bricks had less effect on the compressive strength of RAC than coarsely crushed clay bricks. The compressive strength of RAC aged 60 days, mixed with 60% fine brick slag and mixed with 60% coarse brick slag, is 10.49% and 14.75% lower than that of RAC aged 60 days and mixed with 0% fine brick slag, respectively. Compared with RAC, the compressive strength of NAC was more significantly affected by grading. The interfacial transition zones inside RAC had loose crystals and high porosity, with a weak adhesion between the crushed clay bricks and mortar interfaces. The crushed clay bricks did not affect the types of concrete hydration products, and Calcium-Silicate-Hydrate (C-S-H) and Ca(OH)2 crystals remained the early hydration products in RAC with crushed clay bricks. Nevertheless, the crushed clay bricks inhibited the hydration reaction of the concrete, resulting in decreasing hydration products in NAC, RAC, and RAC with crushed clay bricks.
A Multifeature Fusion Short-Term Traffic Flow Prediction Model Based on Deep Learnings
Authors: Chai Chunxu , Ren Chuanxiang , Yin Changchang , Xu Hui , Meng Qiu , Teng Juan , Gao Ge
Published: May 2022

Short-term traffic flow prediction is an important component of intelligent transportation systems, which can support traffic trip planning and traffic management. Although existing predicting methods have been applied in the field of traffic flow prediction, they cannot capture the complex multifeatures of traffic flows resulting in unsatisfactory short-term traffic flow prediction results. In this paper, a multifeature fusion model based on deep learning methods is proposed, which consists of three modules, namely, a CNN-Bidirectional GRU module with an attention mechanism (CNN-BiGRU-attention) and two Bidirectional GRU modules with an attention mechanism (BiGRU-attention). The CNN-BiGRU-attention module is used to extract local trend features and long-term dependent features of the traffic flow, and the two BiGRU-attention modules are used to extract daily and weekly periodic features of the traffic flow. Moreover, a feature fusion layer in the model is used to fuse the features extracted by each module. And then, the number of neurons in the model, the loss function, and other parameters such as the optimization algorithm are discussed and set up through simulation experiments. Finally, the multifeature fusion model is trained and tested based on the training and test sets from the data collected from the field. And the results indicate that the proposed model can better achieve traffic flow prediction and has good robustness. Furthermore, the multifeature fusion model is compared and analyzed against the baseline models with the same dataset, and the experimental results show that the multifeature fusion model has superior predictive performance compared to the baseline models.
Analysis of Rainfall Erosion and Protective Measures for the Aeolian Sand Subgrade Slope of the Wuma Expressway
Authors: Yin Wenhua , Wang Fang , Liu Weizheng , Wu Yongxiang , Wang Xu
Published: May 2022

It is difficult to build roads in the desert areas with wind-blown sands because the prevailing harsh environment and the characteristics of the aeolian sands inhibit strategies and measures for road damage prevention and control that are typically effective in other settings. Typically, the rainfall period in aeolian sand areas worldwide is concentrated and the rainfall volume is relatively large, which combined with small and unstable nature and the aeolian sand particles means roads built in these areas can be easily washed away and are vulnerable to water damage. Given geological conditions, topographic features and hydrometeorological conditions differ depending on the region, basic research into water damage in highway roadbed slopes in aeolian sand areas is necessary to formulate treatment measures that are versatile and applicable in different regions. Towards that end, this study strengthens the evaluation of roadbed and pavement drainage and protective measures given aeolian sand erosion caused by rainwater infiltration in certain longitudinal length sections of the Expressway K165 + 250 mileage pile section, and includes verification of the design scheme. The effects of rainwater drainage, storage, and subgrade reinforcement on the seepage and stability of drainage in a long longitudinal slope in the desert hinterland were quantitatively analyzed using numerical analysis. Additionally taking into account the regional climate environment characteristics that locally prevail, the necessity and applicability of geotechnical reinforcement in practical engineering applications is demonstrated. The research found the stability of the subgrade slope given potential for rainfall erosion due to concentrated-rainfall periods in an aeolian sand region is promoted through measures including slope drainage on the highway combined with side ditch drainage, strengthening of the box culvert under embankment ditches, and local protection by laying geogrid in the embankment to produce a significant lateral diffusion effect.
The Reform of Journalism Education Driven by Digital Technology in the Era of Media Integration
Authors: Zhang Fuyin
Published: May 2022

Multimedia industry is a combination of economic industry and cultural industry and is a powerful tool to promote national cultural revival. In the process of multimedia integration, the multimedia industry has developed rapidly, and there is a huge demand for talents in this field. However, every year, the graduates of media majors have the status quo that they cannot find a suitable job or leave the original profession. The emergence of this status quo is due to the rapid development of the media industry. We should also see the other side that there is a clear contradiction between the news education of universities and the needs of the industry. In China’s journalism major education, there are contradictions between the barriers between colleges and the media industry and the “fine” and “all” dilemmas in the cultivation of talents. The purpose of this paper is to study the reform of journalism major professional education driven by the era of digital media technology. This paper sets up a control experiment to demonstrate that the integration of the concept of media integration into teaching can enable students to achieve greater progress. Through the literature research method, it summarizes the shortcomings of journalism major education at this stage and collects educational reforms from previous students through a questionnaire survey. It is recommended that 79% recommend adding practice links in the teaching process, 45% suggest that network coverage in the classroom is convenient for students to access materials at any time, 73% suggest that practitioners can be invited to participate in teaching, and 63% recommend imitation media. In teaching, 39% suggested that students should be taught according to their individual characteristics. 55% suggested using general education in teaching, and 39% suggested setting up more related competitions.
A Perspective Review on Thermal Conductivity of Hybrid Nanofluids and Their Application in Automobile Radiator Cooling
Authors: Ukueje Wisdom Etabiese , Abam Fidelis Ibiang , Obi Anthony
Published: May 2022

Hybrid nanofluids developed with the fusion or suspension of two or more different nanoparticles in a mixture as a novel heat transfer fluid are currently of interest to researchers due to their proven better measured thermal conductivities. Several reviewed articles exist on the thermal conductivity of hybrid nanofluids, a vital property for which the heat transfer rate is directly dependent. This review aims to understand the current developments in hybrid nanofluids and their applications. An extensive literature survey was carried out of heuristic-based articles published in the last 15 years. The review reiterates topical research on the preparation methods and ways to improve the stability of readied fluid, thermophysical properties of mixture nanofluids, and some empirical correlations developed for estimating thermal conductivity. Hybrid nanofluid studies on heat transfer performance in automobile radiator cooling systems were also obtained and discussed. The review’s significant findings include the following: (1) hybrid nanofluids produce a noticeable thermal conductivity enhancement and a relatively higher heat transfer coefficient than mono nanofluids and regular liquids. Furthermore, through the uniform dispersion and stable suspension of nanoparticles in the host liquids, the maximum possible thermal augmentation can be obtained at the lowest possible concentrations (by <0.1% by volume). (2) An automobile radiator’s overall heat transfer accomplishment can thus be boosted by using a mixture of nanofluids as conventional coolants. Up-to-date literature results on the thermal conductivity enhancement of mixture fluids are also presented in this study. Nonetheless, some of the barriers and challenges acknowledged in this work must be addressed for its complete deployment in modern applications.
CCgen: Injecting Covert Channels into Network Traffic
Authors: Iglesias Félix , Meghdouri Fares , Annessi Robert , Zseby Tanja
Published: May 2022

Covert channels are methods to convey information clandestinely by exploiting the inherent capabilities of common communication protocols. They can be used to hide malware communication as part of cyber attacks. Here, we present CCgen, a framework for injecting covert channels into network traffic that includes modules for common covert channels at the network and transport layer and allows a smooth integration of novel covert channel techniques. Our tool—openly available and implemented in Python—enables the operation on-the-fly in live communications as well as the manipulation of network traffic packet captures. We evaluate a first prototype by generating a varied assortment of covert channels based on state-of-the-art techniques and check their detectability with Suricata, a popular, open-source intrusion prevention and detection system. The injected covert channels remain mostly undetected. Our proposal fills a gap within the diversity of openly available tools for cybersecurity research and education. It builds a flexible environment for experts to test analysis algorithms, thus also enabling advanced training in applied network steganography.
Library Personalized Service System Based on Computer Network Technology
Authors: Song Zhixiang , Dang Lingwei
Published: May 2022

In order to solve the library’s demand for computer network technology, a research on the library’s personal system service is proposed. A library-based self-service model was originally designed and developed. The system is developed from six aspects: resource association analysis and mining, reading interest analysis, data collection, personal service, personal service scheduling, and data warehouse. Secondly, it shows that this study has done some research on library application itself and completed some research. Finally, libraries can accomplish personal services in a variety of ways, such as distributing modifications, smart administrators, vertical portals, pushers, and more. In foreign libraries and universities represented by North Carolina State University and the Data and Information Center of the Chinese Academy of Sciences, the construction of personal data in digital libraries has become an important part of future development. According to the law, 57.9% and 65.0% of users ranked search engines as second only to e-mail in the China Internet Improvement Data released by the China Internet Network Information Center in 2000 and 2005, respectively.
An Automated Approach for the Prediction of the Severity Level of Bug Reports Using GPT-2
Authors: kamal Mohsin , Ali Sikandar , Nasir Anam , Samad Ali , Basser Samad , Irshad Azeem
Published: May 2022

Manual investigation is warranted in traditional approaches for estimating the bug severity level, which adds to the effort and time required. For bug severity report prediction, numerous automated strategies have been proposed in addition to manual ones. However, the current bug report predictors by facing several issues, such as overfitting and weight computation, and therefore, their efficiency for specific levels of data noise needs to improve. As a result, a bug report predictor is required to solve these concerns (e.g., overfitting and avoiding weight calculation, which increases computing complexity) and perform better in the situation of data noise. We use GPT-2’s features (limiting overfitting and supplying sequential predictors rather than weight computation) to develop a new approach for predicting the severity level of bug reports in this study. The proposed approach is divided into four stages. First, the bug reports are subjected to text preprocessing. Second, we assess each bug report’s emotional score. Third, each report is presented in vector format. Finally, an emotion score is assigned to each bug report, and a vector of each bug report is produced and sent to GPT-2. We employ statistical indicators like recall, precision, and F1-score to evaluate the suggested method’s effectiveness and efficacy. A comparison was also made using state-of-the-art bug report predictors such as Random Forest (RF), Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM) Network, Support Vector Machine (SVM), XGBoost, and Naive Bayes Multinomial (NBM). The proposed method’s promising result indicates its efficacy in bug information retrieval.
Value of Magnetic Resonance Images and Magnetic Resonance Spectroscopy in Diagnosis of Brain Tumors under Fuzzy C‐Means Algorithm
Authors: Liu Huaiqin , Zhang Qi , Niu Shujun , Liu Hao
Published: May 2022

This study was aimed to explore the diagnostic value of magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS) in brain tumors under the fuzzy C‐means (FCM) algorithm. The two‐dimensional FCM hybrid algorithm was improved to be three‐dimensional. The MRI images and MRS spectra of 127 patients with brain tumors (low‐grade glioma group) and 54 healthy people (healthy group) were analyzed. The results suggested that the membership matrix of the improved algorithm had lower ambiguity, higher segmentation accuracy, closer relationship of intrapixels, and stronger irrelevance of interclass pixels. Through the analysis of gray matter volume, it was found that, compared with the healthy group, the gray matter and white matter volumes in the brain of high‐grade glioma were higher, and those of low‐grade glioma group were lower. The improved FCM algorithm could obtain a higher accuracy of 88.64% in segmenting images. It had a higher sensitivity to gray matter changes in brain tumors, reaching 92.72%; its specificity was not much different from that of traditional FCM, which were 83.61% and 88.06%, respectively. In the diagnostic value, the area under the curve of mean kurtosis was the largest, which was 0.962 (P < 0.001). The best critical value was 0.4096, which had a greater reference significance for clinical treatment and prognosis. The ratio of choline/N‐acetyl‐aspartate and the ratio of choline/creatine also showed significant differences in high‐ and low‐grade gliomas (P < 0.05), but the specificity and sensitivity were slightly lower. It also had guiding significance for the grading of gliomas. Overall, the improved FCM algorithm had obvious advantages in the segmentation process of MRI images, which provided help for the clinical diagnosis of brain tumors.
Primary Hypothyroidism with Pituitary Hyperplasia in an Omani Girl
Authors: Abdallah Fadle Wafa , Al Reesi Ali , Al-Shabibi Saud , Khamis Al-Badi Maryam
Published: May 2022

Pituitary hyperplasia secondary to primary hypothyroidism (PHPH) is uncommon in children and is reversible with thyroxine therapy. We report an Omani girl who presented at the age of 13 years and 6 months with profound primary hypothyroidism due to Hashimoto’s thyroiditis and secondary pituitary hyperplasia and hyperprolactinemia. Pituitary magnetic resonance imaging confirmed the presence of pituitary hyperplasia which regressed during follow-up after the administration of thyroxine therapy. The diagnosis of PHPH is very important in both children and adults in order to avoid unnecessary brain surgery or medical treatment for a presumed pituitary mass or adenoma. To our knowledge, this patient represents the first case of an Omani child presenting with PHPH.
[Retracted] Effects of Cardiac Rehabilitation on Cardiac Function and Quality of Life in Patients with Ischemic Nonobstructive Coronary Artery Disease and Diabetes Mellitus
Authors: Wen Yuan , Zhang Xiaoli , Lan Weiqun , Zhao Shimin , Qi Qiuhuan , Yang Li
Published: May 2022

Objective. To investigate the effect of cardiac rehabilitation on the quality of life in patients with ischemic and nonobstructive coronary artery disease complicated with diabetes mellitus. Methods. From January 2020 to June 2021, 100 patients with ischemic nonobstructive coronary heart disease complicated with diabetes were randomly divided into the control group (n = 50). The routine drug therapy observation group (50 cases) was treated with routine drugs combined with cardiac rehabilitation at 6 months for 1 course. The curative effect, cardiac function, 6 min walking distance (6MWD), cardiopulmonary exercise test (CPFT) index, SF‐36 Health Status Survey Scale, and quality of life score were compared between the two groups. Results. The total effective rate of the observation group was significantly higher than that of the control group (P < 0.05). After treatment, there was no significant change in cardiac function and 6MWD in the control group. The left ventricular ejection fraction and 6MWD in the observation group were significantly higher/longer than those before treatment and the control group (all P < 0.05). After treatment, the indexes of CPET in the two groups were improved in varying degrees. The forced vital capacity and oxygen uptake of anaerobic valve in the observation group were significantly higher than those in the control group (all P < 0.05). After treatment, the scores of the SF‐36 in both groups were improved in varying degrees. The physiological function, general health, energy, mental health, and total scores of the observation group were significantly higher than those of the control group (all P < 0.05). Conclusion. Cardiac rehabilitation can significantly improve the cardiorespiratory function, exercise ability, and quality of life in patients with ischemic and nonobstructive coronary artery disease complicated with diabetes mellitus.
Developing Warrants for Designing Continuous Flow Intersection
Authors: Almoshaogeh Meshal , Abou-Senna Hatem , Radwan Essam , Kamal Tarek Lotfy , Alharbi Fawaz , Alfawzan Mohammed , Haider Husnain
Published: May 2022

The increase in the left‐turn demand is the main cause of congestion at conventional intersections, and the traditional countermeasures are inadequate to solve this congestion due to the high changes in demand. This paper looks at the justifying threshold to redesign a signalized intersection from a conventional intersection (CI) to a continuous flow intersection (CFI) and create performance guidelines for decision‐makers and professionals deciding to consider the alternative. A performance comparison between the CI and CFI was conducted to define the main parameters affecting the operational performance. To accomplish the paper’s objective, candidate locations that have already implemented the CFI were identified, and the location with sufficient data for analysis was selected. After the consideration of different evaluation tools, microsimulation (VISSIM 8) was utilized to model the before and after conditions of the location. Using the field data, signal optimization and driving behavior parameter sensitivity analysis were performed to calibrate the models to replicate real‐life conditions. Afterwards, an experiment was designed to examine the different factors that affect the efficiency of each design. The experiment involved 72 different configurations of CFI and CI with 5 different volume levels and used two measures of effectiveness, average vehicle delay, and capacity to assess the results. The results were used to develop guidelines that will help the decision‐makers to decide which design should be considered, which will result in developing a decision support system that will accelerate finding which design is superior to others.
Heart Block Initiated by Candlenut Ingestion
Authors: Lawani Osayi , Winter Mark
Published: May 2022

The candlenut tree is a tropical plant that has a vast number of uses which include fertilizer, dye, ink for tattooing, and fuel. The inner seed of the nut is the most utilized portion of the plant and is often sold as a food additive, natural laxative, or a weight loss supplement. Unfortunately, the seed itself is very toxic when consumed whole and in its raw state. Typical symptoms of toxicity include abdominal pain, vomiting, and diarrhea. Rarely, it can cause cardiac dysrhythmias, most commonly bradycardia and atrioventricular heart block. We present a case of a young adult female with no significant past medical history who developed typical symptoms of toxicity, as well as atrioventricular heart block following ingestion of a candlenut. Most documented cases describe complete resolution of gastrointestinal and cardiac symptoms about one week following ingestion; however, treatment while inpatient can consist of inotropes or vasopressor support, intravenous fluid hydration, electrolyte replacement, and antiemetics. Although the mechanism of action remains unclear, this report provides physicians with an understanding of the risks of ingestion and the knowledge of typical management of the toxic effects of the candlenut.
Numerical Investigation of the Landslide and Its Surge: A Case Study of the Gongjiafang Landslide in the Three Gorges Reservoir Area
Authors: Fan Yunyun , Ma Dongyang , Sun Xu
Published: May 2022

Once the slope in the near bank area enters the state of failure, a geological disaster chain caused by landslide and its generated surge occurs very likely. In this study, a two-layer depth-averaged model was used to describe the disaster chain. The HLL (Harten-Lax-van Leer) finite volume method was used for numerical simulation and analysis. Meanwhile, the linear interpolation technique was employed to obtain second-order accuracy. The numerical results of the analytical examples reflect the movement characteristics of the two-layer fluid and verify the correctness of the numerical model. On the basis of numerical verification, the Gongjiafang landslide and its surge were simulated and analyzed. In the early stage, the deformation of the underwater geomaterials disturbed the water, forming the prototype of the surge, and then the landslide movement promoted the rapid development of the surge. After the landslide was deposited, the surge continued to travel forward and formed the largest form near the opposite bank. The numerical simulation is applicable to complex terrain and reveals some mechanisms and characteristics of the disaster chain. Compared with empirical methods, the numerical model adopted could reproduce the process of disasters chain more accurately and effectively and then improve the understanding of the disaster chain. It is feasible that the proposed numerical model can be applied under approximate plane strain conditions but is no longer applicable under 3D conditions. This work can provide reference for further research on disaster chain caused by landslide.
Identification of an Autophagy-Related Signature Based on Whole Bone Marrow Sequencing for the Prognosis and Immune Microenvironment Characterization of Multiple Myeloma
Authors: Li Licheng , Chen Ting , Wang Jishi , Li Mengxing , Li Qinshan
Published: May 2022

Myeloma (MM) is a malignant plasma cell disorder, which is incurable owing to its drug resistance. Autophagy performs an integral function in homeostasis, survival, and drug resistance in multiple myeloma (MM). Therefore, the purpose of the present research was to identify potential autophagy-related genes (ARGs) in patients with MM. We downloaded the transcriptomic data (GSE136400) of patients with MM, as well as the corresponding clinical data from the Gene Expression Omnibus (GEO); the patients were classified at random into two groups in a ratio of 6: 4, with 212 samples in the training dataset and 142 samples in the test dataset. Both multivariate and univariate Cox regression analyses were performed to identify autophagy-related genes. The univariate Cox regression analysis demonstrated that 26 ARGs had a significant correlation with overall survival (OS). We constructed an autophagy-related risk prognostic model based on six ARGs: EIF2AK2 (ENSG00000055332), KIF5B (ENSG00000170759), MYC (ENSG00000136997), NRG2 (ENSG00000158458), PINK1 (ENSG00000158828), and VEGFA (ENSG00000112715) using LASSO-Cox regression analysis to predict risk outcomes, which revealed substantially shortened OS duration in the high-risk cohort in contrast with that in the low-risk cohort. Therefore, the ARG-based model significantly predicted the MM patients’ prognoses and was verified in an internal test set. Differentially expressed genes were found to be predominantly enriched in pathways associated with inflammation and immune regulation. Immune infiltration of tumor cells resulted in the formation of a strong immunosuppressive microenvironment in high-risk patients. The potential therapeutic targets of ARGs were subsequently analyzed via protein–drug network analysis. Therefore, a prognostic model for MM was established via a comprehensive analysis of ARGs, through using the clinical models; we have further revealed the molecular landscape features of multiple myeloma.
Effects of Osteocyte Shape on Fluid Flow and Fluid Shear Stress of the Loaded Bone
Authors: Yang Fengjian , Yu Weilun , Huo Xuyang , Li Hongliang , Qi Qiuju , Yang Xiaohang , Shi Nianqiu , Wu Xiaogang , Chen Weiyi
Published: May 2022

This study was conducted to better understand the specific behavior of the intraosseous fluid flow. We calculated the number and distribution of bone canaliculi around the osteocytes based on the varying shapes of osteocytes. We then used these calculated parameters and other bone microstructure data to estimate the anisotropy permeability of the lacunar‐canalicular network. Poroelastic finite element models of the osteon were established, and the influence of the osteocyte shape on the fluid flow properties of osteons under an axial displacement load was analyzed. Two types of boundary conditions (BC) that might occur in physiological environments were considered on the cement line of the osteon. BC1 allows free fluid passage from the outer elastic restraint boundary, and BC2 is impermeable and allows no free fluid passage from outer displacement constrained boundary. They both have the same inner boundary conditions that allow fluid to pass through. Changes in the osteocyte shape altered the maximum value of pressure gradient (PG), pore pressure (PP), fluid velocity (FV), and fluid shear stress (FSS) relative to the reference model (spherical osteocytes). The maximum PG, PP, FV, and FSS in BC2 were nearly 100% larger than those in BC1, respectively. It is found that the BC1 was closer to the real physiological environment. The fluid flow along different directions in the elongated osteocyte model was more evident than that in other models, which may have been due to the large difference in permeability along different directions. Changes in osteocyte shape significantly affect the degrees of anisotropy of fluid flow and porous media of the osteon. The model presented in this study can accurately quantify fluid flow in the lacunar‐canalicular network.
Cardiac Fibroblasts Promote Ferroptosis in Atrial Fibrillation by Secreting Exo-miR-23a-3p Targeting SLC7A11
Authors: Liu Dishiwen , Yang Mei , Yao Yajun , He Shanqing , Wang Youcheng , Cao Zhen , Chen Huiyu , Fu Yuntao , Liu Huafen , Zhao Qingyan
Published: May 2022

The exact mechanism of atrial fibrillation (AF) has been not well elucidated. Ferroptosis is an iron-dependent cell death due to excessive accumulation of peroxidized polyunsaturated fatty acids. However, the molecular mechanism underlying AF and ferroptosis has never been reported. Here, we established the rapid pacing model in vivo and vitro to investigate the relationship between AF and ferroptosis. In canine model of rapid atrial pacing, the content of malondialdehyde and total ions in the atrial tissue of the Pacing group was significantly increased and the exosome inhibitor GW4869 reduced ferroptosis, fibrosis, and inflammation and improved histological and electrophysiological remodeling. In rapid pacing h9c2 cells, the expression of antioxidative stress genes associated with ferroptosis presented sequential changes and proteins involved in ferroptosis such as FTH1, SLC7A11, and GPX4 were gradually depleted. Furthermore, pacing cardiac fibroblast-derived exosomes (CF-exos) exacerbated ferroptosis in h9c2 cells and pretreated pacing-CF-exos with GW4869 alleviated injury to h9c2 cells. In mechanism, our results demonstrated that pacing-CF-exos highly expressed miR-23a-3p by informatics analysis and experimental verification. Inhibitor-miR-23a-3p protected h9c2 cells from ferroptosis accompanying with upregulation of SLC7A11. In addition, SLC7A11 was shown to be the target gene of miR-23a-3p. In conclusion, our results suggest that CF-exos-miR-23a-3p may promote ferroptosis. The development of AF in a persistent direction could be prevented by intervening with exosomal miRNAs to reduce oxidative stress injury and ferroptosis.
An Empirical Study on the High-Quality Development of “Specified, Refined, Characterized, and Innovative” Small- and Medium-Sized Enterprises under the Background of “Dual Circulation”: A Case Study of Wuxi City, Jiangsu Province
Authors: Liu ShiYu , Zhou ZhiWei
Published: May 2022

China attaches importance to the development of “specified, refined, characterized, innovative (SRCI)” small- and medium-sized enterprises (SMEs) under the background of the major strategic adjustment of the new pattern of “dual circulation.” This study studies the willingness and influencing factors of SMEs through questionnaire survey, interview, and data mining of 147 technology-based SMEs, 20 “SRCI” small giant enterprises, and 146 NEEQ-listed enterprises by descriptive statistics and inference statistics. To promote “SRCI” quality development of SMEs, the policy suggestions are guided to consummate the related industry, the established companies’ cultivation library are improved, the public service platform of SMEs is established and improved, enterprises are guided to enhance independent innovation ability by “patent” to strengthen the innovative service supportability, and SMEs are guided to strengthen the echelon construction of talent team with the standard of high-quality development. Suggestions on strengthening the support for the listing of high-quality enterprises can provide a reference for the management of decision-making and enterprise practice of government departments.
An Infrared Stripe Noise Removal Method Based on Multi-Scale Wavelet Transform and Multinomial Sparse Representation
Authors: Li Mingxuan , Nong Shenkai , Nie Ting , Han Chengshan , Huang Liang
Published: May 2022

The non-uniformity present in the infrared detector and readout circuit leads to significant stripe noises in the infrared images. The effect of these stripe noises on infrared images brings trouble to the subsequent research. The currently available algorithms for removing infrared streak noises cannot effectively protect the non-stripe information while removing the stripe noise. Compared with these algorithms, our algorithm uses a multi-scale wavelet transform to concentrate the streak noise by frequency into vertical components of different scale levels. Then, our algorithm analyzes the unique properties of the streak noise compared to the ideal vertical component. The denoising model of the vertical component at each level is established with its multinomial sparsity, and the streak noise is removed by the alternating direction method of multipliers (ADMM) algorithm for optimal calculation. To prove the usefulness of our algorithm, we carried out a large series of real experiments, comparing it with the most advanced algorithms in terms of both subjective determination and objective indices. The experimental results fully demonstrate the superiority and effectiveness of our algorithm.
The Efficacy of Orthodontics plus Implant Anchorage in Orthodontic Treatment: A Randomized Controlled Study
Authors: Zhang Yuying , Li Keyue , Li Nan
Published: May 2022

Objective. To investigate the efficacy of orthodontics plus implant anchorage in orthodontic treatment. Methods. This randomized controlled study was conducted on 90 patients who had orthodontic treatment in our hospital between October 2019 and October 2020, and they were assigned to either a control group (n = 45) or an observation group (n = 45) via the random number table method. Patients in the control group received orthodontics while those in the observation group underwent orthodontics plus implant anchorage. The two groups were compared in terms of clinical indexes, efficacy, orthodontic state, adverse reaction rate, quality of life, and satisfaction. Results. After treatment, orthodontics plus implant anchorage led to lower gingival attachment level, gingival bleeding index, plaque index, and periodontal probing depth versus orthodontics alone (

P
<
0.05

); orthodontics plus implant anchorage contributed to a higher efficacy versus orthodontics alone (91.11% vs. 73.33%,

P
<
0.05

); orthodontics plus implant anchorage resulted in smaller molar displacement, larger protrusion distance of the upper central incisor, and larger inclination angle of the upper central incisor (

P
<
0.05

); orthodontics plus implant anchorage was associated with fewer adverse reactions (4.44% vs. 26.67%,

P
<
0.05

) and a higher quality of life scores versus orthodontics alone (

P
<
0.05

); orthodontics plus implant anchorage yielded a higher satisfaction level versus orthodontics alone (95.56% vs. 66.67%,

P
<
0.05

). Conclusion. The orthodontics plus implant anchorage offers a promising solution in orthodontic treatment. It is conducive to restoring dental indicators and improving quality of life and satisfaction. It is therefore worthy of application.
Expression and Clinical Trends of Pct Combined with Lactate Clearance in Sepsis
Authors: Li Shigang , Chen Zhe , Yan Weifeng
Published: May 2022

Objective. To study the expression and clinical trend of procalcitonin (Pct) + lactate clearance in sepsis. Methods. A total of 63 septic shock patients enrolled in our hospital from March 2018 to March 2021 were recruited as group A, and the 87 septic patients admitted during the same period were recruited as group B. The Pct, lactic acid, and lactate clearance were compared between the two groups. Results. The Pct and lactic acid in group A were higher than those in group B at the time of diagnosis, 1 d, 2 d, and 3 d after treatment, but the lactate clearance rate at 1 d, 2 d, and 3 d after treatment was lower than that in group B (

P
<
0.05

). The Pct and lactate at the time of diagnosis, 1 d, 2 d, and 3 d after treatment in the good prognosis group were lower than those in the poor prognosis group, but the lactate clearance rate at 1 d, 2 d, and 3 d after treatment was higher than that in the poor prognosis group (

P
<
0.05

). Disease severity and prognosis were positively correlated with Pct and lactate, but negatively correlated with lactate clearance rate (

P
<
0.05

). Conclusions. Pct and lactate clearance rate might serve as accurate predictors of the severity of sepsis and prognosis. It merits promotion in clinical setting.
Traumatic Brain Magnetic Resonance Imaging Feature Extraction Based on Variable Model Algorithm in Stroke Examination
Authors: Wu Zhenghong , Wu Dongqiu , Yang Weiwei , Wan Bing , Liu Sibin
Published: May 2022

The purpose of this study was to explore the diagnostic value of different sequence scanning of nonparametric variable model‐based cranial magnetic resonance imaging (MRI) for ischemic stroke. A histogram analysis‐based nonparametric variable model was proposed first, which was compared with the parametric deformation (PD) model and geometric deformation (GD) model. Then, 116 patients with acute ischemic stroke were selected as the research subjects. Routine MRI (T2WI, T1WI, FLAIR, DWI, SWI, and 3D TOF MRA) and MR SCALE‐PWI were performed. The results showed that the nonparametric variable model algorithm was relatively complete in the actual segmentation results of MRI images, and the display clarity of lesions was better than PD and GD algorithms. The diagnostic sensitivity, specificity, and overall performance of the variable model algorithm were significantly higher than those of the other two algorithms (P < 0.05). According to ROC curve analysis, the AUC areas of DWI, SWI, 3D TOF MRA, and MR SCALE‐PWI for the diagnosis of ischemic penumbra were 0.793, 0.825, 0.871, and 0.933, respectively. In summary, the segmentation results of MRI images by the nonparametric variable model based on histogram analysis were relatively complete, and the clarity of lesions was better than that of the traditional model. MRI images can effectively identify the occurrence of ischemic stroke. Moreover, MR SCALE‐PWI had a good early identification effect on ischemic penumbra, which can reduce unnecessary treatment for patients.
Common Fixed Point Theorems on Tricomplex Valued Metric Space
Authors: Mani Gunaseelan , Gnanaprakasam Arul Joseph , Haq Absar Ul , Baloch Imran Abbas , Jarad Fahd
Published: May 2022

In this paper, we introduce the notion of tricomplex valued metric space and prove some common fixed point theorems. The presented results generalize and expand some of the literature well-known results. We also explore some applications of our key results.
Multifunctional Core‐Shell NiFe2O4 Shield with TiO2/rGO Nanostructures for Biomedical and Environmental Applications
Authors: Esther Nimshi R. , Judith Vijaya J. , Al-Najar B. , Hazeem L. , Bououdina M. , John Kennedy L. , Kombaiah K. , Bellucci S.
Published: May 2022

Multifunctional core@shell nanoparticles have been synthesized in this paper through 3 stages: NiFe2O4 nanoparticles by microwave irradiation using Pedalium murex leaf extract as a fuel, core@shell NiFe2O4@TiO2 nanoparticles by sol‐gel, and NiFe2O4@TiO2@rGO by sol‐gel using preprepared reduced graphene oxide obtained by modified Hummer’s method. XRD analysis confirmed the presence of both cubic NiFe2O4 spinel and tetragonal TiO2 rutile phases, while Raman spectroscopy analysis displays both D and G bands (ID/IG = 1.04) associated with rGO. Morphological observations by HRTEM reveal a core‐shell nanostructure formed by NiFe2O4 core as confirmed by SAED with subsequent thin layers of TiO2 and rGO. Magnetic measurements show a ferromagnetic behavior, where the saturation magnetization drops drastically from 45 emu/g for NiFe2O4 to 15 emu/g after TiO2 and rGO nonmagnetic bilayers coating. The as‐fabricated multifunctional core@shell nanostructures demonstrate tunable self‐heating characteristics: rise of temperature and specific absorption rate in the range of ΔT = 3–10°C and SAR = 3–58 W/g, respectively. This effectiveness is much close to the threshold temperature of hyperthermia (45°C), and the zones of inhibition show the better effective antibacterial activity of NTG against various Gram‐positive and Gram‐negative bacterial strains besides simultaneous good efficient, stable, and removable sonophotocatalyst toward the TC degradation.
Analysis of the Impact Mechanism of Occupational Identity on Occupational Well-Being Based on Big Data
Authors: Wang Yuefen , Yang Dianyi
Published: May 2022

Occupational identity is an individual’s view, recognition, and approval of his long-term occupation, and its importance to every professional is self-evident. Only when a professional person agrees with the profession he is engaged in from the bottom of his heart can he devote himself wholeheartedly to it and unreservedly exert his greatest potential. On the basis of sorting out and analyzing the prevailing theoretical and empirical research results, this paper deliberates the empirical research on the influence mechanism between employees’ occupational identity and occupational well-being. In this study, through big data analysis, literature search, questionnaire survey, and other methods, this paper obtained the professional identity data of employees in different companies and used a method of big data analysis, namely, BP neural network (BPNN) to design in this paper to verify the data, and finally obtain an effective theoretical model of the influence mechanism of occupational identity and occupational well-being. The main work of this paper is as follows: (1) it introduces the interpretation of the concept of “professional identity” by different scholars at home and abroad and makes a brief review of the researches on professional identity and professional well-being made by foreign scholars in recent years. (2) The basic knowledge and algorithm process of artificial neural network (ANN) are introduced, and the design of the evaluation model of the influence mechanism of occupational identity on occupational well-being based on BPNN is proposed. (3) The simulation software validates the neural network (NN) assessment system developed in this paper. Experiments reveal that the BPNN system is a reasonable and feasible evaluation approach for analyzing the impact of occupational identity on occupational well-being.