bluuebunny/crossref_metadata_2025 huggingface dataset:
Computerized-Assisted Scoliosis Diagnosis Based on Faster R-CNN and ResNet for the Classification of Spine X-Ray Images
Authors: Chen Peiji , Zhou Zhangnan , Yu Haixia , Chen Kun , Yang Yun
Published: June 2022

In order to reduce the subjectivity of preoperative diagnosis and achieve accurate and rapid classification of idiopathic scoliosis and thereby improving the standardization and automation of spinal surgery diagnosis, we implement the Faster R-CNN and ResNet to classify patient spine images. In this paper, the images are based on spine X-ray imaging obtained by our radiology department. We compared the results with the orthopedic surgeon’s measurement results for verification and analysis and finally presented the grading results for performance evaluation. The final experimental results can meet the clinical needs, and a fast and robust deep learning-based scoliosis diagnosis algorithm for scoliosis can be achieved without manual intervention using the X-ray scans. This can give rise to a computerized-assisted scoliosis diagnosis based on X-ray imaging, which has strong potential in clinical utility applied to the field of orthopedics.
Work Emotion Intervention and Guidance Training Method for Enterprise Employees Based on Virtual Reality
Authors: Zhu Lixun
Published: June 2022

Objective. Improper management of employees’ emotions has a great impact on work status and work efficiency, and emotional management has increasingly become a very important part of corporate human resource management. How to adjust the various emotions of employees, so that employees can work in a fuller and more passionate attitude, is a problem that enterprise managers need to consider. From the perspective of employees themselves, a good mood will also bring happiness and satisfaction to life and work. Only in this way can the company and the employees be satisfied with each other and continue to maintain the good development momentum of the company. Method. This paper proposes a new method of using virtual reality scenes to induce human emotions. Based on computer science and psychological cognitive science, a scene library of “virtual reality emotion induction system” is constructed. Emotion induction based on virtual reality scenes has better interactivity and generalization, as well as stronger immersion and user operability. Its emotional arousal is high, the data is reliable, and the interference of environmental factors in the induction process is weakened, and relatively objective emotional data can be obtained. The factors affecting the emotional management of the enterprise are investigated by means of a questionnaire survey, statistics and problems are found, and the objective problems existing in the emotional management work of the company are determined. According to the analysis, the problems are summarized, and it is believed that the company still has certain room for improvement and improvement potential in terms of corporate culture construction, emotional counseling system construction, and human resource career planning. In the research of this paper, through the combination of theory and practice, the enterprise’s emotional management work has been comprehensively analyzed, and the practical problems existing in its emotional management work have been found through questionnaires. Results/Discussion. In the field of enterprise human resource management, emotion management is always an eternal topic worthy of our attention. But unfortunately, emotional management has not been given enough attention by managers. Most companies often think that emotions are their own business. Employees should self-regulate, control, and tolerate themselves. They should not bring personal emotions to work and even think that emotional work is unprofessional. This kind of misunderstanding has led to the fact that emotional management has not received due attention and affirmation in many enterprises.
Comparison of the Efficacy and Safety of Neuroendoscopic Endonasal Transsphenoidal Surgeries and Intracranial Endoscopic Pterional Approach in Resection of Tuberculum Sellae Meningiomas
Authors: Lin Zhenrong , Wu Ziyue , Wang Yuzhe , Wang Weiwei , Zheng Weixin , Lin Ruisheng , Guo Aishun
Published: June 2022

Objective. To compare of the efficacy and safety of neuroendoscopic endonasal transsphenoidal surgeries and intracranial endoscopic pterional approach in resection of tuberculum sellae meningioma. Methods. From January 2014 to June 2021, 60 patients with tuberculum sellae meningioma diagnosed and treated in our hospital were enrolled and randomly divided into study group and control group. The tuberculum sellae meningioma was removed by neuroendoscopic endonasal transsphenoidal surgeries in the study group, while the intracranial endoscopic pterional approach was used in the control group. The chi-square test was used to compare the differences of tumor complete resection rate, visual acuity improvement rate, total effective rate at 3 months after operation, and adverse reactions between the two groups. Results. The clinical characteristics of the two groups were comparable (

P
>
0.05

). After surgical treatment, the complete resection rate in the study group was higher than that in the control group (93.3% vs 70.0%), and the difference was statistically significant (

P
=
0.020

). After treatment, the visual acuity improvement rate of the study group was 83.3% (25/30), which was significantly higher than that of the control group (60.0%, 18/30), and the difference was statistically significant (χ2 = 4.022,

P
=
0.045

). After surgical treatment, the total effective rate at 3 months after operation was higher in the study group than in the control group (96.7% vs 83.3%), with statistical significance (

P
=
0.041

). There was no significant difference in postoperative adverse reactions between the study group and control group (33.3% vs 30.0%,

P
=
0.781

). Conclusion. The neuroendoscopic endonasal transsphenoidal surgeries has significant efficacy and can significantly improve the visual acuity of patients without increasing adverse reactions, which is worthy of clinical promotion.
[Retracted] Time Intervals between Double Primary Breast and Ovarian Cancers and Survival Outcomes of Patients with Both Cancers: A SEER Database Analysis
Authors: He Xin-Qin , Gao Yu-Tao , Zhang Xia , Jiang Hong
Published: June 2022

Background. The time interval rules and survival outcomes of individuals with synchronous and metachronous breast cancer (BC) and ovarian cancer (OC) were examined in this retrospective population‐based investigation. Methods. The National Cancer Institute’s Surveillance, Epidemiology, and End Results database was used to create a cohort of people diagnosed with BC and OC between 1973 and 2015. Patients were separated into three groups: those with main BC followed by primary OC (group 1), those with synchronous primary breast and ovarian cancer (group 2), and those with OC prior to BC (group 3). The Kaplan‐Meier technique was used to assess overall survival (OS) and cancer‐specific survival (CSS). Results. A total of 4,975 patients were identified: 2,929 patients in group 1, 680 patients in group 2, and 1,366 patients in group 3. The average duration between these tumors was 60 months (range 0–499). Approximately 50% of second primary cancer cases occurred during the first 60 months of the first primary cancer diagnosis, and more than 70% occurred within the first 120 months. The median survival time for 4,975 individuals was 140 months. Group 2 had the smallest median OS (35 months), whereas group 3 had the longest (45 months) (239 months). Conclusions. The majority of second primary cancer cases occurred during the first 120 months following the diagnosis of the first original malignancy. Individuals who had primary OC prior to BC had better prognoses, whereas patients who had synchronous BC and OC had worse prognoses.
Hydraulic Lifting and Rotating System Lifting Machinery Transmission Control Design
Authors: Chen Linlin
Published: June 2022

With the continuous improvement of the level of intelligence in the construction machinery industry, as one of the core technologies in the hydraulic lifting and rotating system, the lifting transmission control system has become a key factor in determining the performance of the elevator. As a hydraulic lifting machine with high protection level and powerful functions, the mechanical transmission controller has been recognized by the market. This study is based on the design of lifting machinery transmission control of hydraulic lifting and rotating system and studies the lifting mechanism transmission system in the hydraulic lifting and rotating system required for engineering operation. According to the functional characteristics of the transmission controller of the lifting mechanism, the control system scheme is designed. On this basis, the system design of the lift machinery transmission control and, according to this design, the functions of driving speed control and transmission mode switching are studied. Starting from the movement mechanism of hydraulic continuous lifting technology, this research carried out the principle design of mechanical transmission control, related calculations, selection of hydraulic components, corresponding simulations, structural design of mechanical transmission, and tests of hydraulic power systems. Finally, the control system was verified through simulation experiments, and technical difficulties such as the liquid supply mode of the large-flow system, the selection of standby working conditions, and the reliability and safety design were solved. It can be seen from the simulation results that, as the displacement ratio increases, the system efficiency increases, reaching more than 70%. When the valve opening reaches 20° when the valve port is closed, the efficiency of the power control valve reaches 95%. It can be seen that the control system established in this study has more advantages in power and economy. The transmission control system of hoisting machinery designed in this study can give greater play to its transmission efficiency and significantly reduce the working time and intensity of the operator.
Hybrid Approach Named HUAPO Technique to Guide the Lander Based on the Landing Trajectory Generation for Unmanned Lunar Mission
Authors: Latif Shaikh Abdul , Mehedi Ibrahim M. , Iskanderani Ahmed I. M. , Vellingiri Mahendiran T. , Jannat Rahtul
Published: June 2022

This manuscript proposes a hybrid method for landing trajectory generation of unmanned lunar mission. The proposed hybrid control scheme is the joint execution of the human urbanization algorithm (HUA) and political optimizer (PO) with radial basis functional neural network (RBFNN); hence it is named as HUA-PORFNN method. The HUA is a metaheuristic method, and it is used to solve several optimization issues and several nature-inspired methods to enhance the convergence speed with quality. On the other hand, multiple-phased political processes inspire the PO. The work aims to guide the lander with minimal fuel consumption from the initial to the final stage, thus minimizing the lunar soft landing issues based on the given cost of operation. Here, the HUAPO method is implemented to overcome thrust discontinuities, checkpoint constraints are suggested for connecting multi-landing phases, angular attitude rate is modeled to obtain radical change rid, and safeguards are enforced to deflect collision along with obstacles. Moreover, first, the issues have been resolved according to the proposed HUAPO method. Here, energy trajectories with 3 terminal processes are deemed. Additionally, the proposed HUAPO method is executed on MATLAB/Simulink site, and the performance of the proposed method is compared with other methods.
Influence of Imperfect Faraday Rotation Mirror on All-Fiber Optic Current Sensor
Authors: Wu Jianhua , Zhang Xiaofeng , Chen Liang
Published: June 2022

The effects of the Faraday rotation mirror on the all-fiber optic current sensor (AFOCS) are studied in this paper. The reflectivity degradation of FRM with the long-term operation, the misalignment of the optical axis between FRM and the sensing fiber, and the influence of temperature fluctuation on FRM are modeled and simulated in this paper. The effect of temperature is the biggest obstacle to the application of the Faraday rotation mirror, while other factors can be easy to overcome by the data processing method. The experiments are designed and realized for verification. The temperature fluctuation range is related to the measured electric current to satisfy the required accuracy for IEC 60044-8 class 0.2S.
Effects of Soil Properties and Slope Angle on Deformation and Stability of Cut Slopes
Authors: Habtemariam Behailu G. , Shirago Kelifa B. , Dirate Democracy D.
Published: June 2022

The impact of soil parameters and slope angle on the deformation and stability of cut slopes is critical for defining road project safety measurement. This study investigates the effect of soil properties and slope angle on the deformation and stability of cut slopes in general and the specific Arba Minch‐Chencha upgrading road project. Forty‐eight (48) analyses were carried out both in Slope/W and Plaxis 2D software for six cut slopes and analyzed for four different slope angles. Twenty‐four (24) dataset samples were collected from six different cut‐slope sites. These dataset samples were categorized in two situations, i.e., before and after water saturation for each cut slope. The limit equilibrium method (LEM) comparison clearly showed that the Spencer, Bishop, and Morgenstern‐Price methods produced similar FOS. The Ordinary and Janbu approaches, on the other hand, underestimate the FOS. Most LEMs except Ordinary and Janbu methods that estimated higher FOS than finite element method (FEM) analysis. It is observed that the main reasons for the cut‐slope instability were the provision of steep cut‐slope angles, the existence of a high proportion of fine soil, and moisture content, which was observed in both Plaxis 2D (FEM) and Slope/W (LEM). It was concluded that the slope is more stable for the soil having few fine‐grained fractions. Moreover, flattening the slope stabilizes the cut slopes based on the results obtained from both Plaxis 2D and Slope/W.
Internal Economic Management and Performance Evaluation Method of Enterprise Based on Balanced Scorecard
Authors: Liu Shuangshuang
Published: June 2022

In order to evaluate the performance management level of the enterprise, it is necessary to use the Balanced Scorecard to establish the performance evaluation system of the enterprise. On the basis of pointing out the specific problems and deficiencies existing in the enterprise, suggestions for improving the performance level of the enterprise are put forward. Then, a detailed analysis of the performance evaluation of Company A is carried out. Through the analysis of various aspects of Company A’s performance, the problems and deficiencies in its performance evaluation are found. According to the specific problems of Company A, a performance evaluation system is designed based on the balanced scorecard. The Balanced Scorecard is a management tool for measuring performance in multiple dimensions. Starting from multiple aspects, scientifically combining strategic objectives with multiple dimensions, this management method not only is suitable for the current market environment, but also improves the company’s internal management system. Through the investigation of the company’s performance management, it is found that there is a problem in the company’s performance management. In view of the existing problems, the Balanced Scorecard of management accounting is used as a management tool to design a feasible performance appraisal plan for the company from the four dimensions of finance, customer, internal process, and learning and growth. Recommendations for full participation can be made for its implementation. The results show that the comprehensive score of Company A’s performance in 2022 is 70 points. It can be seen from the evaluation results that the financial performance evaluation level of the company is average. The company’s customer performance levels are average as well. The internal operation level of the enterprise is at a high level. The level of learning and growth performance of the business is very good. At the same time, according to the reliability test standard, the reliability coefficient of the questionnaire is 0.866, indicating that the reliability is acceptable.
Privacy Protection of Medical Service Data Based on Blockchain and Artificial Intelligence in the Era of Smart Medical Care
Authors: Wu Bo , Pi Yong , Chen Jinhong
Published: June 2022

Smart medical care will realize the self-management, selection, and optimization of related things with more thorough induction, more comprehensive interconnection, and more intelligent insight, so that people can get an increasingly personalized medical and health service experience. 5G-enabled Internet of Things and AI (artificial intelligence) will continue to drive innovative applications in the medical industry. Access control and sharing of medical data is of great significance to the development of smart medical care, but the security problems in medical data sharing cannot be ignored. In this paper, a privacy protection scheme of medical service data based on blockchain and AI is proposed. The user chain is constructed as a public chain. In the user chain, the data privacy of users is protected, and users can safely transmit data to doctors and realize the management of session keys. CNN (convolutional neural network) privacy protection protocol based on homomorphic encryption can protect users’ privacy input, server model parameters, and calculated intermediate values. Experimental analysis and comparison with other schemes show that the scheme in this model is safer and more practical.
Design and Implementation of Intelligent Analysis Technology in Sports Video Target and Trajectory Tracking Algorithm
Authors: Yang Xi , Wang Haiming
Published: June 2022

The object tracking is an important task to future generations to find accurate information from frame (sports or any cctv). The available models like RFO, DT, Xboosting, Gradient boosting, and CNN are outdated for sports video tracking using video. The target and trajectory finding are very important for accurate tracking. Therefore, for crossover, the above limitation’s intelligence analysis is performed with ANN. The video tracking can be very simple and efficient with proposed model. As a result, this ANN offers a sports camera target detection system based on an upgraded grey neural network. This research uses the automatic threshold technique to divide the target object of sports camera and derive the designated target of sports video based on the pixel grey difference of the target image in sports video. The moving objects are tracked by the object tracking algorithm, and features are extracted to obtain the results. The performance measures like accuracy of 95.23%, sensitivity of 94.45%, and recall of 93.34% had been attained.
The Underlying Molecular Basis and Mechanisms of Venous Thrombosis in Patients with Osteomyelitis: A Data-Driven Analysis
Authors: Chen Peisheng , Liu Yinhuan , Lin Xiaofeng , Yu Bin , Chen Bin , Lin Fengfei
Published: June 2022

Objective. Osteomyelitis (OM) is one of the most risky and challenging diseases. Emerging evidence indicates OM is a risk factor for increasing incidence of venous thromboembolism (VTE) development. However, the mechanisms have not been intensively investigated. Methods. The OM-related dataset GSE30119 and VTE-related datasets GSE19151 and GSE48000 were downloaded from the Gene Expression Omnibus (GEO) database and analyzed to identify the differentially expressed genes (DEGs) (OMGs1 and VTEGs1, respectively). Functional enrichment analyses of Gene Ontology (GO) terms were performed. VTEGs2 and OMGs2 sharing the common GO biological process (GO-BP) ontology between OMGs1 and VTEGs1 were detected. The TRRUST database was used to identify the upstream transcription factors (TFs) that regulate VTEGs2 and OMGs2. The protein-protein interaction (PPI) network between VTEGs2 and OMGs2 was constructed using the Search Tool for the Retrieval of Interacting Genes (STRING) database and then visualized in Cytoscape. Topological properties of the PPI network were calculated by NetworkAnalyzer. The Molecular Complex Detection (MCODE) plugin was utilized to perform module analysis and choose the hub modules of the PPI network. Results. A total of 587 OMGs1 and 382 VTEGs1 were identified from the related dataset, respectively. GO-BP terms of OMGs1 and shared DGEs1 were mainly enriched in the neutrophil-related immune response process, and the shared GO-BP terms of OMGs1 and VTEGs1 seemed to be focused on cell activation, immune, defense, and inflammatory response to stress or biotic stimulus. 230 VTEGs2, 333 OMGs2, and 13 shared DEGs2 were detected. 3 TF-target gene pairs (SP1-LSP1, SPI1-FCGR1A, and STAT1-FCGR1A) were identified. The PPI network contained 1611 interactions among 467 nodes. The top 10 hub proteins were TP53, IL4, MPO, ELANE, FOS, CD86, HP, SOCS3, ICAM1, and SNRPG. Several core nodes (such as MPO, ELANE, and CAMP) were essential components of the neutrophil extracellular traps (NETs) network. Conclusion. This is the first data-mining study to explore shared signatures between OM and VTE by the integrated bioinformatic approach, which can help uncover potential biomarkers and therapeutic targets of OM-related VTE.
Identities on Changhee Polynomials Arising fromλ‐Sheffer Sequences
Authors: Kim Byung Moon , Kim Taekyun , Park Jin-Woo , Radwan Taha Ali
Published: June 2022

In this paper, authors found a new and interesting identity between Changhee polynomials and some degenerate polynomials such as degenerate Bernoulli polynomials of the first and second kind, degenerate Euler polynomials, degenerate Daehee polynomials, degenerate Bell polynomials, degenerate Lah–Bell polynomials, and degenerate Frobenius–Euler polynomials and Mittag–Leffer polynomials by usingλ‐Sheffer sequences andλ‐differential operators to find the coefficient polynomial when expressing then‐th Changhee polynomials as a linear combination of those degenerate polynomials. In addition, authors derive the inversion formulas of these identities.
A Novel Image Edge Detection Method Based on the Asymmetric STDP Mechanism of the Visual Path
Authors: Fang Tao , Yuan Jiantao , Yin Rui , Wu Celimuge
Published: June 2022

The detection of image edges plays an important role for image processing. In view of the fact that these existing methods cannot effectively detect the edge of the image when facing the image with rich details. This paper proposes a novel method of asymmetric spike-timing-dependent plasticity (STDP) image edge detection based on the visual physiological mechanism. In the proposed method, the original image is preprocessed by the Gabor filter to simulate the visual physiological orientation characteristics to obtain the image information in different directions, and the orientation feature fusion is used to reconstruct the primary edge feature information of the image. Then, based on the mechanism of the visual nervous system, a neuron network composed of dynamic synapses based on the asymmetric STDP mechanism is constructed to further process it to obtain impulse response images. In order to eliminate disturbance of the neuron’s system noise on the impulse response image, the impulse response image is filtered by a Gaussian filter. Then, the lateral inhibition between neurons is applied to refine the filtered image edges. Finally, the result is normalized, and the final edge of the experimental image is obtained. Experimental results based on the colony image data set collected in the laboratory indicate that the proposed method achieved better performance than these state-of-the-art methods; meanwhile, the AUC value remains above 0.6.
Artistic Design Method of User Interaction Experience of Mobile System Based on Context Awareness
Authors: Bai Libo
Published: June 2022

This work combines context awareness to explore the art design technique of user interaction experience of mobile system and alters the conventional art communication and art appreciation methods in order to increase the impact of artistic interactive experience. Furthermore, this paper proposes that the spatial pattern will influence the aggregation value in wireless sensor networks, as well as the influence of the pattern of single-point extrapolation function and information coverage function measurement, which is quantified as a nonsampling error in sampling theory. Then, this paper proposes a hierarchical sampling theory to optimize the nonsampling error and improve the effect of artistic situation perception. Finally, on this basis, this paper constructs an art design system of context awareness and interactive experience. The findings of this study indicate that the state-of-the-art mobile system user interaction experience based on context awareness suggested in this work has a strong context awareness effect and user interaction experience.
Engineered Exosomes Loaded with miR-563 Inhibit Lung Cancer Growth
Authors: Gao Weiwei , Yang Nan , Yin Chunyang , Zeng Yi , Zhu Xiaoping
Published: June 2022

The malignancy of lung cancer (LC) is serious in the world. Exosomes are well-known natural nanovesicles, which are reported to have the potential to carry functional miRNAs as natural carriers and deliver chemotherapeutic drugs. However, the safety and functions of the engineered exosomes for delivering miRNA for the treatment of LC remain to be evaluated. In this study, we found that miR-563 is related to lung cancer from GeneCard database. RT-qPCR and in situ hybridization (ISH) were used to assess miR-563 expression in clinical samples. We prepared and verified the engineered exosomes loaded with miR-563 both in vitro and in vivo. In vitro, flow cytometry, Western blot, and other experimental methods were performed to evaluate the antitumor effect of miR-563 loaded exosomes. In in vivo, the LC mouse model was used to observe the effect of the prepared exosomes. The safety of using this exosomes was accessed by liver function test, hematological analysis, and H&E staining in major organs of the mice. Our findings indicated that the miR-563 loaded engineered exosomes inhibit the A549 cells growth in vitro, by inhibiting the tumor cell proliferation, migration, and invasion and promoting apoptosis. In in vivo, these engineered exosomes were enriched in tumor tissue after injecting to LC model mice and impacted tumor tissue by inhibiting the tumor volume and tumor weight. Importantly, our study indicated that miR-563 loaded engineered exosomes have the potential for clinical application for LC treatment with acceptable safety profiles. Our findings indicate a novel potential therapeutic target for lung cancer patients by miR-563 loaded engineered exosomes.
Prognosis Analysis and Perioperative Research of Elderly Patients with Non‐Muscle‐Invasive Bladder Cancer under Computed Tomography Image of Three‐Dimensional Reconstruction Algorithm
Authors: Ke Hongying , Qiu Dandan , Cong Zhicheng
Published: June 2022

To analyze the application value of computed tomography (CT) based on a three‐dimensional reconstruction algorithm in perioperative nursing research and prognosis analysis of non‐muscle‐invasive bladder cancer (NMIBC), a retrospective study was performed on 124 patients with NMIBC who underwent surgical treatment in the hospital. All patients underwent CT examination based on the three‐dimensional reconstruction algorithm before surgery, and transurethral resection of the bladder tumor was performed. The patients receiving conventional care were classified as the control group, and those receiving comprehensive care were classified as the case group, and the recovery status and recurrence of the two groups were compared. The results showed that the accuracy, specificity, and sensitivity of CT imaging information based on the three‐dimensional reconstruction algorithm for NMIBC patients were 89.38, 93.77, and 84.39, respectively. The incidence of bladder spasm (9.68%), bladder flushing time (1.56 d), and retention of drainage tube time (2.68 d) in the case group were obviously lower compared with the control group (30.65%, 2.32 d, and 5.19 d) (P < 0.05). Serum BLCA‐1 (3.72 ng/mL) and CYFRA21‐1 (5.68 μg/mL) in the case group were significantly lower than those in the control group, with a statistically considerable difference (P < 0.05). Compared with the control group, the scores of role function (89.82 points), emotional function (84.76 points), somatic function (79.23 points), and social function (73.93 points) in the case group were observably higher (P < 0.05). In addition, one year after the operation, CT examination showed that the recurrence rate in the case group (6.45%) was significantly lower than that in the control group (22.58%) (P < 0.05). Therefore, CT detection based on the three‐dimensional reconstruction algorithm was particularly important for preoperative diagnosis, prognosis, and recurrence monitoring of NMIBC patients. It could provide great clinical value for the diagnosis and prognosis monitoring of NMIBC.
[Retracted] Gene Differential Expression and Interaction Networks Illustrate the Biomarkers and Molecular Biological Mechanisms of Unsaponifiable Matter in Kanglaite Injection for Pancreatic Ductal Adenocarcinoma
Authors: Xu Bowen , Dan Wenchao , Zhang Xiaoxiao , Wang Heping , Cao Luchang , Li Shixin , Li Jie
Published: June 2022

Background. Kanglaite injection (KLTi) has shown good clinical efficacy in the treatment of pancreatic ductal adenocarcinoma (PDAC). While previous studies have demonstrated the antitumor effects of the oil compounds in KLTi, it is unclear whether the unsaponifiable matter (USM) also has antitumor effects. This study used network pharmacology, molecular docking, and database verification methods to investigate the molecular biological mechanisms of USM. Methods. Compounds of USM were obtained from GC‐MS, and targets from DrugBank. Next, the GEO database was searched for differentially expressed genes in cancerous tissues and healthy tissues of PDAC to identify targets. Subsequently, the protein‐protein interaction of USM and PDAC targets was constructed by BisoGenet to extract candidate genes. The candidate genes were enriched using GO and KEGG by Metascape, and the gene‐pathway network was constructed to screen the key genes. Molecular docking and molecular dynamic simulations of core compound targets were finally performed and to explore the diagnostic, survival, and prognosis value of targets. Results. A total of 10 active compounds and 36 drug targets were screened for USM, 919 genes associated with PDAC, and 139 USM candidate genes against PDAC were excavated. The enrichment predicted USM by acting on RELA, NFKB1, IKBKG, JUN, MAPK1, TP53, and AKT1. Molecular docking and dynamic simulations confirmed the screened core targets had good affinity and stability with the corresponding compounds. In diagnostic ROC validation, the above targets have certain accuracy for diagnosing PDAC, and the combined diagnosis is more advantageous. As the most diagnostic value of RELA, it is equally significant in predicting disease‐specific survival and progression‐free interval. Conclusions. USM in KLTi plays an anti‐PDAC role by intervening in the cell cycle, inducing apoptosis, and downregulating the NF‐κB, MAPK, and PI3K‐Akt pathways. It might participate in the pancreatic cancer pathway, and core target groups have diagnostic, survival, and prognosis value biomarker significance.
Electromagnetic Signal Intelligent Identification Based on Radio Frequency Fingerprints
Authors: Kang Jian , Mu Hui , Ren Hui , Jia Jicheng , Qi Lin , Zhang Zherui
Published: June 2022

Due to the open nature of WIFI connection, it is exposing its private information to the attackers. Traditional WIFI security methods are no longer able to meet the current security needs, and more and more wireless-side physical layer security solutions provide solutions, among which RF fingerprinting is an endogenous security technology with potential. Constructing an effective and accurate method to identify WIFI devices that steal information is a difficulty that today’s society needs to face. The main problem is not only that the recognition accuracy is difficult to improve but also the problem of data shortage. In this paper, we first construct a large-scale WIFI real-world measurement dataset. Next, we use PSD and bispectrum features, as well as complex ResNet schemes for WIFI device identification experiments, and compare and analyze them from multiple perspectives. The experimental results show that the proposed algorithm can achieve up to 97% recognition accuracy among 100 devices. Moreover, when the SNR is 0 dB, the complex ResNet method can still achieve 78% recognition accuracy among 100 devices. Finally, this paper summarizes the experimental analysis of the measured dataset and discusses the open issues related to this area.
Blockchain‐Based Contact Tracing and Information Sharing Model for COVID‐19 Pandemic
Authors: Mashat Arwa , Alabdali Aliaa M.
Published: June 2022

COVID‐19 is the worst contagious disaster in the history of humankind, triggering a worldwide sickness pandemic. In lacking specialized treatments or immunizations, finding and eliminating the infection source is the best option to decrease disease transmission and lower sickness and degree of fatality among the general public. Generally, few significant barriers are present in the existing system of monitoring the contamination. One of the obstacles is regarding health‐related data storage. The user’s e‐health data is kept in a traditional method that might have been compromised if shared with third parties. Secondly, the current disease tracking technologies fail to monitor diseases numerous ways. The tracing system is either personal or location‐based. Apart from these, gathering individual consent and sharing their health data with unknown associations is a real‐time problem. We propose a blockchain‐based data system that maintains confidentiality with transparency. Users can acquire unlimited and nontampered vital routes as the suggested blockchain solution leverages to link the user/patient and approved solvers. Also, automatically executed smart contracts are constructed to desensitize the user ID and reallocation. The anonymous feature delivered by private blockchain with wireless technologies defends the customer’s identity secrecy. We develop a matching approach using machine learning technology. Users may take safeguards in advance by employing our suggested analytical technique for predicting the risk due to infectious source presence.
Factors Affecting Transfusion during Percutaneous Nephrolithotomy: A Retrospective Study of 665 Cases
Authors: Zhao Hong , Li Junsheng , Li Li , Wang Hang , Guo Jianming , Miao Yi
Published: June 2022

Objective. This study was designed to evaluate the aspects that affect transfusion following percutaneous nephrolithotomy (PCNL). Patients and Methods. From 2016 to 2019, 665 patients underwent PCNL for the removal of renal calculi at our center (Department of Urology, Shanghai Xu-hui Central Hospital). Complications, including hemorrhages, have been reported. Twenty-three patients (3.5%) have received a blood transfusion, and 12 (1.9%) patients were treated with hyper-selective embolization. We focused on the influencing factors related to postoperative blood transfusion. The factors analyzed were age, sex, hypertension, diabetes, serum creatinine level, preoperative hemoglobin, and the use of anticoagulants or antiplatelet medications; renal and stone factors (i.e., previous surgery, abnormal anatomy, stone side, stone burden, and stone type); and surgical features (i.e., access number, the calyx of puncture, and stone-free rate). These data were analyzed for the presence of bleeding. Results. Among individual factors, preoperative hemoglobin level (

p
<
0.001

) and urinary infections (

p
<
0.001

) were significantly correlated with blood transfusion. Among renal and stone factors, only a history of open surgery was significantly correlated with blood transfusion (

p
<
0.05

). Stone type or stone burden did not correlate with transfusion. Furthermore, no statistically significant correlation was found between surgical features and bleeding, and a lower stone-free rate was reported for the transfusion group. Conclusion. The obtained results demonstrated that PCNL is a safer surgical procedure in a high-volume center; however, anemic conditions, infections, and history of open surgery will significantly increase the transfusion rate following PCNL.
IoT-Based Remote Health Monitoring System Employing Smart Sensors for Asthma Patients during COVID-19 Pandemic
Authors: Rafa Nafisa Shamim , Azmal Basma Binte , Dhruba Abdur Rab , Khan Mohammad Monirujjaman , Alanazi Turki M. , Almalki Faris A. , AlOmeir Othman
Published: June 2022

COVID-19 and asthma are respiratory diseases that can be life-threatening in uncontrolled circumstances and require continuous monitoring. A poverty-stricken South Asian country like Bangladesh has been bearing the brunt of the COVID-19 pandemic since its beginning. The majority of the country’s population resides in rural areas, where proper healthcare is difficult to access. This emphasizes the necessity of telemedicine, implementing the concept of the Internet of Things (IoT), which is still under development in Bangladesh. This paper demonstrates how the current challenges in the healthcare system are resolvable through the design of a remote health and environment monitoring system, specifically for asthma patients who are at an increased risk of COVID-19. Since on-time treatment is essential, this system will allow doctors and medical staff to receive patient information in real time and deliver their services immediately to the patient regardless of their location. The proposed system consists of various sensors collecting heart rate, body temperature, ambient temperature, humidity, and air quality data and processing them through the Arduino Microcontroller. It is integrated with a mobile application. All this data is sent to the mobile application via a Bluetooth module and updated every few seconds so that the medical staff can instantly track patients’ conditions and emergencies. The developed prototype is portable and easily usable by anyone. The system has been applied to five people of different ages and medical histories over a particular period. Upon analyzing all their data, it became clear which participants were particularly vulnerable to health deterioration and needed constant observation. Through this research, awareness about asthmatic symptoms will improve and help prevent their severity through effective treatment anytime, anywhere.
The Shift in the Narrative of Doctor-Patient Communication and the Cultivation of Medical Information Exchange Communication Based on the Information Technology Era
Authors: Zhang Hongqiang
Published: June 2022

Effective narrative turn of doctor-patient communication can strengthen the trust between doctors and patients, close the doctor-patient relationship, and reduce the contradiction between doctors and patients. Health humanities, as a more inclusive, open, and application-oriented discipline, has been gradually recognized by academic circles. Narrative medicine, as an interdisciplinary subject of humanities education and medicine, plays an important role in cultivating medical students’ narrative ability. 30 medical staff in a general hospital were selected as the research object by questionnaire survey. General information questionnaire and medical narrative ability scale were used to investigate and multiple linear regression was used to analyze the influencing factors of medical students’ medical narrative ability. The results show that the standardized regression coefficients of communication content, empathy, and communication results are 0.439, 0.367, and 0.138, respectively. The total score of medical narrative ability of medical students is 133, and the average score of items is 4.87, which is at a low level. In conclusion, the medical narrative ability of medical students is at a low level, and nursing managers should take targeted intervention measures to improve the medical narrative ability of medical students.
Comprehensive Analysis of the Expression and Prognostic Value of LMAN2 in HER2+ Breast Cancer
Authors: Zhang Di , Ye Liping , Hu Shuang , Zhu Qingqing , Li Chenxi , Zhu Chengming
Published: June 2022

Lectin, Mannose Binding 2 (LMAN2) encodes a type I transmembrane lectin that shuttles between the plasma membrane, the Golgi apparatus, and the endoplasmic reticulum. However, its expression, prognosis, and function in invasive breast carcinoma remain unknown. Nine databases were consulted to evaluate LMAN2 expression and prognosis in breast cancer. The possible function of LMAN2 in breast cancer was investigated in the Human Cell Landscape (HCL) database, Gene Regulatory Network database (GRNdb), and CancerSEA database. Moreover, N6-methyladenosine (m6A) modifications were analyzed using the RMBase v2.0 and M6A2Target databases. Seven databases were then used to analyze the potential action mechanisms of LMAN2. Our findings suggest that LMAN2, which is expressed at a high level in breast cancer, is linked to an unfavorable prognosis. Therefore, LMAN2 has the potential to be utilized as a treatment target in breast cancer. Furthermore, the single-cell analysis illustrated that LMAN2 expression had a positive link to breast cancer stemness, proliferation, metastasis, and differentiation. Moreover, m6A modifications were found in the LMAN2 gene. Consequently, modifications to m6A methylation may influence LMAN2 expression, which is associated with the homologous recombination (HR) in its DNA damage repair pathway .
Research on Cross-Contrast Neural Network Based Intelligent Painting: Taking Oil Painting Language Classification as an Example
Authors: Zeng Xi
Published: June 2022

With the continuous fermentation of the thought of intelligence, artificial intelligence has extended its tentacles into the field of artistic creation and has begun to try intelligent creation. Painting creation based on artificial intelligence is called “intelligent painting.” For oil paintings, the computational language is a relatively complicated description. How to correctly identify the computational language of oil paintings is essential for establishing a large oil painting database. This paper constructs a meaningful learning similarity measure and multiclassification model based on the CCNN model to realize the classification of oil painting language. A cropped CNN model is used to extract language features, and on this basis, oil painting works are cross-compared and multiclassified. This method realizes the classification of oil painting language and the corresponding painter and achieves superior accuracy. This paper constructs a data classification method based on small samples, measures similarity through cross-comparison, and provides a measuring approach for classifying the language of oil paintings. The CCNN model proposed combines the best classification results of oil painting language, which improves the accuracy of oil painting language classification. Moreover, it further enriches the methods of oil painting language classification and image recognition under computational intelligence.
A Rare Case of Extensive Cerebral Venous Sinus Thrombosis Complicated by Heparin-Induced Thrombocytopenia
Authors: Jang Khan Noman Ahmed , Farooqi Ashar , Alsharedi Mohamed
Published: June 2022

Cerebral venous sinus thrombosis (CVST) is a rare but potentially life-threatening cause of stroke. Several risk factors have been identified including hypercoagulable state, malignancy, use of oral contraceptives, pregnancy, head injury, infection, and prothrombotic states such as heparin-induced thrombocytopenia (HIT). HIT is a prothrombotic state leading to thrombosis in several distinct locations including CVST requiring prompt discontinuation of heparin and initiation of nonheparin anticoagulation to prevent catastrophic consequences. Very rarely, HIT can complicate the ongoing CVST leading to worsening thrombosis and clinical deterioration. We here report an exceedingly rare case of CVST complicated by HIT in a 22-year-old female patient who showed remarkable clinical improvement after discontinuation of heparin and initiation of argatroban.
Automatic Detection of Small- and Medium-Sized Targets in High-Resolution Images Based on Computer Vision and Deep Learning Energy
Authors: Lv Yi , Yin ZhengBo , Yu Zhezhou
Published: June 2022

In order to solve the problem that it is difficult for traditional manual feature algorithms to deal with complex image features quickly and automatically in high-resolution images, an automatic detection method for small objects in high-resolution images based on computer vision and deep learning energy is proposed. Starting from the deep learning target detection system, this paper studies many problems in the system according to the characteristics of target spatial deformation, more small targets, easy confusion, and rough regional proposal in high-score remote sensing images. The results showed that a combination of spatial deformation strength with spatial deformation resistance and multiphase coupling were all proposed to be comparable with spatial deformation. The process of tracking international products in the system has been extended to study local channels. Pay attention to the operation of the machine, make full use of rich semantic data of local characteristics and the world of spatial points, which will help to improve the accuracy of the purpose of the chaw, and identify ways to create a shared database. The proposed method is evaluated on three attribute, classification joint datasets; ACCNN on the AC-AID dataset, the performance of ACCNN is suboptimal on AC-AID and is very close to the best method for DCA fusion. The average error rate of DCA fusion is 5.67%; on the AC-UCM dataset, the error rate of ACCNN is 2.11% lower than the suboptimal method DCA fusion, and the error rate of DCA fusion is 6.16%. On the AC-Sydney dataset, the error rate of ACCNN is 1.86% lower than the suboptimal method DCA fusion, and the error rate of DCA fusion is 5.99%, which obtains quite competitive results, experimenting with high-resolution images.
Intensive Health Care plus Vitamin D Administration Benefits the Growth and Development of Young Children and Reduces the Incidence of Nutritional Disorders
Authors: Liu Yangyang , Zeng Qingwen
Published: June 2022

This study was intended to assess the effect of intensive health care plus vitamin D administration on the growth, development, and nutritional status of young children. Totally, 131 young children who were admitted to Shiyan Maternal and Child Health Care Hospital from January 2020 to January 2021 were included and assigned via the random number table method at a ratio of 1 : 1 : 1 to receive either vitamin D administration (vitamin D group, n = 42), intensive health care (IHC) (IHC group, n = 44), or vitamin D administration plus intensive health care (combination group, n = 45). All children received a normal diet and routine care. After the intervention, all children showed robust improvement in their height, weight, neuropsychological development, and nutritional status, in which the combination therapy was associated with better outcomes in terms of physical development, neuropsychological development, and nutritional status, and a higher serum 25-hydroxyvitamin D3 (25-(OH)D3) level of the children versus monotherapy. Children receiving combined therapy had a significantly lower incidence of nutritional disorders than those receiving single therapy. Intensive health care plus vitamin D benefits the growth and development of young children and reduces the incidence of nutritional disorders in children.