bluuebunny/crossref_metadata_2025 huggingface dataset:
Renal response at 2 years post biopsy to predict long-term renal survival in lupus nephritis: a retrospective analysis of the Hopkins Lupus Cohort
Authors: Cooper Blenkinsopp Selin , Fu Qinggong , Green Yulia , Madan Anuradha , Juliao Patricia , Goldman Daniel W , Roth David A , Petri Michelle A
Published: August 2022

Objective

This retrospective analysis evaluated the prognostic value of renal response status 2 years after biopsy-proven lupus nephritis (LN) for the prediction of long-term renal outcomes.

Methods

Eligible patients with SLE as per American College of Rheumatology or Systemic Lupus International Collaborating Clinics criteria and biopsy-proven class III, IV, V or mixed LN were identified from the Hopkins Lupus Cohort, and categorised into binary renal response categories (modified primary efficacy renal response (mPERR) or no mPERR at 2 years post biopsy). These categories were defined by a modified version of the Belimumab International Lupus Nephritis Study (BLISS-LN) protocol using urine protein:creatinine ratio (≤0.7 g/day) and estimated glomerular filtration rate (≥60 mL/min/1.73 m2or ≤20% below the baseline value) criteria. Long-term renal survival (defined as survival without end-stage renal disease (ESRD) or death) and chronic renal insufficiency-free survival were assessed in Kaplan–Meier plots with log-rank test and covariate-adjusted Cox proportional hazards models.

Results

Of the 173 eligible patients, 91.3% were female; the mean (SD) age at biopsy was 36.2 (11.8) years. At 2 years post biopsy, 114 (65.9%) patients achieved mPERR. These patients showed a lower risk of ESRD/death and chronic renal insufficiency in the follow-up period (HR (95% CI) 0.33 (0.13 to 0.87), p=0.0255; and HR (95% CI) 0.26 (0.14 to 0.47), p<0.0001, respectively).

Conclusions

The 2-year post-biopsy renal response status, defined per 2019-updated BLISS-LN criteria, has prognostic value for long-term renal survival and lower risk of chronic renal insufficiency in patients with LN.
Prehospital emergency care in a humanitarian environment: an overview of the ethical considerations
Authors: Prescott Tim , May S , Horne S , Barnard E
Published: August 2022

Recent history has demonstrated that UK Defence personnel can be used, potentially with little notice, in humanitarian disaster zones. The provision of prehospital emergency care (PHEC) in a humanitarian environment requires an innovative approach to overcome the technical challenges of a resource-limited setting. In addition to technical challenges, prehospital practitioners working in a humanitarian environment can expect to be faced with ethically testing situations that they are not familiar with in their usual practice. The organisational and individual ethical decision-making burden can result in significant harms. Therefore, the aim of this paper is to discuss the ethical considerations relevant to providing PHEC during a humanitarian disaster in order that personnel can be more prepared to optimally deliver care. This is a paper commissioned as a part of the Humanitarian and Disaster Relief Operations special issue ofBMJ Military Health.
Zebrafish optineurin: genomic organization and transcription regulation
Authors: Silva Iris A.L. , Varela Débora , Cancela M. Leonor , Conceição Natércia
Published: August 2022

Optineurin (OPTN) is involved in a variety of mechanisms, such as autophagy, vesicle trafficking, and nuclear factor kappa-B (NF-κB) signaling. Mutations in the OPTN gene have been associated with different pathologies, including glaucoma, amyotrophic lateral sclerosis, and Paget's disease of bone. Since the relationship between fish and mammalian OPTN is not well understood, the objective of the present work was to characterize the zebrafish optn gene and protein structure and to investigate its transcriptional regulation. Through a comparative in silico analysis, we observed that zebrafish optn presents genomic features similar to those of its human counterpart, including its neighboring genes and structure. A comparison of OPTN protein from different species revealed a high degree of conservation in its functional domains and three-dimensional structure. Furthermore, our in vitro transient-reporter analysis identified a functional promoter in the upstream region of the zebrafish optn gene, along with a region important for its transcription regulation. Site-directed mutagenesis revealed that the NF-κB motif is responsible for the activation of this region. In conclusion, with this study, we characterize zebrafish optn and our results indicate that zebrafish can be considered as an alternative model to study OPTN's biological role in bone-related diseases.
Complex Dynamics on a Discrete Tritrophic Model of Leslie Type with General Functional Responses
Authors: Blé Gamaliel , Dela-Rosa Miguel Angel
Published: August 2022

In this paper, by averaging the growth rate on each state, we analyze the dynamics of a discrete dynamical system coming from a system of ODEs. This differential system corresponds to a tritrophic Leslie type model which is formed by three populations (prey (P), mesopredator (MP) and superpredator (SP)), where the last two populations are generalist predators. We give sufficient conditions where the discrete model undergoes a Neimark–Sacker bifurcation at a coexistence point. This analysis is independent of the functional responses that govern the interactions. To illustrate our results, several applications are given, under the assumptions that the population P has logistic growth and that the relations MP–P and SP–MP are carried out through Holling type functional responses. From these applications, we conclude that there are sufficient conditions to guarantee that the three species coexist by means of a supercritical Neimark–Sacker bifurcation. Moreover, numerically we can detect that the discrete system exhibits a chaotic behavior.
Multi-Mode Motion Dynamics of a Top Tensioned Riser Excited by Vortices and Varying Tension
Authors: Wang Dan , Hao Zhifeng , Chen Fangqi , Chen Yushu
Published: August 2022

A coupled model of a top tensioned riser (TTR) under combined excitations from vortices and time-varying tension is proposed. And the van der Pol oscillator is introduced to simulate the time-varying characteristics of vortex shedding. The first three mode approximations as a six degree-of-freedom (DOF) system of vibrations of the fluid-structure interaction system are derived. Two cases of resonances are analyzed by using the numerical method. One case is on the vortex induced vibration (VIV) of the six DOF system, where the 1-to-1 internal resonance (also named “lock-in” phenomenon) between frequencies of the first modes of structure and the wake oscillator are investigated. Bifurcation curves between dynamic responses in terms of the shedding frequency are derived. Comparing to the vibrations of the first order mode, the “lock-in” phenomenon for vibrations of the higher order modes can occur in the wider parameter range with large values. The second case is on the combined resonance between the 1-to-1 internal and 1-to-2 parametric resonance. Response curves versus the shedding frequency under different amplitude ratios are calculated by the Runge–Kutta method. Effects of system parameters including the amplitude ratio of the parametric excitation, shedding frequency on the response curves are investigated. Comparing to the case when only considering the 1-to-1 internal resonance in the VIV, results of the combined resonance show those large-amplitude responses of the structure and wake oscillator can be induced. Responses will increase rapidly as the amplitude of the varying tension increases. Unstable responses can occur within a large frequency band of nondimensional shedding frequency. Furthermore, the dynamic characteristics of the responses of the six DOF system including the bifurcation diagrams, time histories, phase-plane projection and Poincaré sections are computed for different amplitude ratios. Results indicate that complex dynamics such as the quasi-periodic and chaotic solutions can occur for different amplitude ratios. The analysis can be helpful for the parameter design of deep-water risers.
Detecting Order and Chaos by the mLE, SALI and GALI Methods in Three-Dimensional Nonlinear Yang–Mills System
Authors: Chatar Walid , El Ghamari Mohammed , Kharbach Jaouad , Benkhali Mohamed , Masrour Rachid , Rezzouk Abdellah , Ouazzani-Jamil Mohammed
Published: August 2022

The main objective of this study is to explore the nonlinear dynamics and chaos detecting in the three-dimensional (3D) generalized Hamiltonian Yang–Mills system as coupled quartic oscillators. We investigate its Liouvillian integrability. The integrable system is obtained and its associated first integral of motion is explicitly given. Also, a variety of nonlinear phenomena could be expressed using various numerical analysis, such as the construction of the system’s Poincaré Surface of Section (PSS), the maximum Lyapunov exponent (mLE), and the modern numerical methods like the Smaller (SALI) and the Generalized (GALI) Alignment Indexes. In this context, a series of numerical simulations are appropriate in order to explore ordered and chaotic motions of the system both in two (2D) and three dimensions, and one can observe chaos–order–chaos transition of the system when any parameters on which the system depends vary. Finally, several numerical schemes are shown to demonstrate the effectiveness and rapidity of these proposed methods for distinguishing chaos and order states of the system.
Heteroclinic Cycles Generated by Piecewise Affine Systems in ℝn
Authors: Lu Kai , Xu Wenjing , Wei Yongchang , Xu Wei
Published: August 2022

It is essential yet challenging to investigate heteroclinic trajectories in chaotic dynamics of high-dimensional systems. This paper presents an efficient approach for precise prediction of heteroclinic cycles in [Formula: see text]-dimensional ([Formula: see text]) piecewise affine systems. Moreover, it systemically investigates different types of heteroclinic cycles in the considered systems, and proposes the corresponding existence conditions with rigorous proofs by analyzing the dynamics of stable and unstable manifolds. In addition, three numerical examples with both a heteroclinic cycle and a chaotic set are provided to verify the established results.
Time-Delay Memristive Recurrent Neural Network and Its Complex Dynamics
Authors: Zhou Wei , Fu Bowei , Wang Guangyi
Published: August 2022

This paper focuses on the hybrid effects of memristor characteristics, coupling coefficient and time-delay on the recurrent neural network. We construct a novel time-delay recurrent neural network based on a passive hyperbolic tangent memristor, whose instability condition at equilibrium points is judged according to the Routh criterion. Under the changes of the memristor internal parameter, coupling coefficient and time-delay, some complex dynamic behaviors, including chaos and various coexisting attractors, of the time-delay memristive recurrent neural network are observed in detail through the bifurcation diagram, the largest Lyapunov exponent, and the basin of attraction. Finally, the theoretical results are verified by the circuit simulation through MULTISIM.
Bifurcation Analysis of a Tumour-Immune Model with Nonlinear Killing Rate as State-Dependent Feedback Control
Authors: Guan Likun , Yang Jin , Tan Yuanshun , Liu Zijian , Cheke Robert A.
Published: August 2022

Impulsive control strategies have been widely used in cancer treatment and linear impulsive control has always been considered in previous studies. We propose a novel tumour-immune model with nonlinear killing rate as state-dependent feedback control, which can better reflect the saturation effects of the tumour and immune cell mortalities due to chemotherapy, and its dynamic behaviors are investigated. The paper aims to discuss the transcritical and subcritical bifurcations of the model. To begin with, the threshold conditions for tumour eradication and tumour persistence in the model without pulse interventions are provided. We define the Poincaré map of the proposed model and then address the existence and orbital asymptotically stability of the model’s tumour-free periodic solution. Furthermore, by using the bifurcation theory of the discrete one-parameter family of maps, which is determined by the Poincaré mapping, we investigate the model’s transcritical and subcritical pitchfork bifurcations with respect to the key parameter.
Visualizing Android Malicious Applications Using Texture Features
Authors: Sharma Tejpal , Rattan Dhavleesh
Published: August 2022

Context: Due to the change and advancement in technology, day by day the internet service usages are also increasing. Smartphones have become the necessity for every person these days. It is used to perform all basic daily activities such as calling, SMS, banking, gaming, entertainment, education, etc. Therefore, malware authors are developing new variants of malwares or malicious applications especially for monetary benefits.

Objective: Objective of this research paper is to develop a technique that can be used to detect malwares or malicious applications on the android devices that will work for all types of packed or encrypted malicious applications, which usually evade decompiling tools.

Method: In the proposed approach, visualization method is used for the detection of malware. In the first phase, application files are converted into images and then in second phase, texture feature of images are extracted using Grey Level Co-occurrence Matrix (GLCM). In the last phase, machine learning classification algorithms are used to classify the malicious and benign applications.

Results: The proposed approach is run on different datasets collected from various repositories. Different efficiency parameters are calculated and the proposed approach is compared with the existing approaches.

Conclusion: We have proposed a static technique for efficient detection of malwares. The proposed technique performs better than the existing technique.
Flow Injection Analysis-Based Electrochemiluminescence: An Overview of Experimental Design and Its Biosensing Applications
Authors: Venkateswara Raju Chikkili , Rani Gokana Mohana , Haribabu Jebiti , Kumar Shanmugam Senthil
Published: August 2022

Over the past few decades, electrochemiluminescence (ECL) has been used as a powerful analytical tool for in vitro diagnosis due to its promising potential in light-emitting and, which has greatly promoted recent for biosensor studies. Plenty of research articles on the ECL technique have been published by various researchers around the globe. On the other hand, studies on the coupling of ECL sensing strategies with other techniques are recently getting widespread attention. ECL strategies have been effectively coupled with scanning electrochemical microscope (SECM), flow injection analysis (FIA), and capillary electrophoresis. These coupled techniques have been effectively employed for various health care applications. Among these techniques, FIA coupled ECL sensing strategies have been designated as the most emerging technique, especially sensing of clinical samples. This critical review discusses the vibrant developments in FIA-ECL, the mechanism of ECL, the design of FIA-ECL, and highlights the application of FIA-ECL for the detection of immunoassays, catecholamines, antioxidant compounds, choline, tetracyclines, and pharmaceutical drugs. The current review will pave the way for the design and development of FIA-ECL for efficient point-of-care applications.
Impact of Non-Conformal Lithium Contact on Electro-Chemo-Mechanics and Dendrite Growth
Authors: Meyer Julia , Harrison Katharine , Mukherjee Partha P. , Roberts Scott Alan
Published: August 2022

Lithium plating and dendrite growth hinder the implementation of lithium metal anodes with liquid electrolyte in commercial batteries due to safety concerns. In this study, we developed a 3-D finite element model and studied the mechanical and electrochemical mechanisms that drive plating at the microscale. With this model, we investigated electrochemical response across a lithium protrusion characteristic of rough anode surfaces. We represented the separator as a porous, polymer material in non-conformal contact with a lithium anode. The impact of applied stack pressure on separator morphology and electrochemical response is of particular interest, as external pressure can improve cell performance below a critical threshold. We explored the relationships between plating propensity, stack pressure, and material properties. External pressure suppresses lithium plating due to interfacial stress and separator pore closure, leading to inhomogeneous plating rates across the anode surface. For moderate applied pressures, dendrite growth is completely suppressed and it is expected that plating will occur in the electrolyte-filled gaps between anode and separator. In fast-charging conditions and systems with low electrolyte diffusivities, the benefits of stack pressure are overridden by ion transport limitations.
Nutrient composition influences the gut microbiota in chronic thoracic spinal cord-injured rats
Authors: Smith Allie M. , Welch Bradley A. , Harris Kwamie K. , Garrett Michael R. , Grayson Bernadette E.
Published: August 2022

Chronic spinal cord injury (SCI) results in an increased predisposition to various metabolic problems that can be exacerbated by consuming a diet rich in calories and saturated fat. In addition, gastrointestinal symptoms have been reported after SCI, including intestinal dysbiosis of the gut microbiome. The effects of both diet and SCI on the gut microbiome of adult male Long Evans rats euthanized 16 wk after injury were investigated. The rats were either thoracic spinal contused or received sham procedures. After 12 wk of either a low-fat or high-fat diet, cecal contents were analyzed, revealing significant microbial changes to every taxonomic level below the kingdom level. Shannon α diversity analyses demonstrated a significant difference in diversity between the groups based on the surgical condition of the rats. SCI produced a unique signature of changes in commensal bacteria that were significantly different than Sham. Specific changes in commensal bacteria as a result of diet manipulation had high fidelity with reports in the literature, such as Clostridia, Thiohalorhabdales, and Pseudomonadales. In addition, novel changes in commensal bacteria were identified that are unique dietary influences on SCI. Linear regression analysis on body fat and lean mass showed that a consequence of chronic SCI produces uncoupled associations between some commensal bacteria and body composition. In conclusion, despite tightly controlling the protein content and varying the carbohydrate and fat contents, Sham and SCI rats respond uniquely to diet. These data provide potential direction for therapeutic modulation of the microbiome to improve health and wellness following SCI.
Diagnosing Oncocytoma by Core Needle Biopsy: A Single-Center Experience
Authors: Mayer Chen , Abu-Ghanem Yasmin , Dotan Zohar A. , Barshack Iris , Fridman Eddie
Published: August 2022

Background. Oncocytoma is one of the most common benign kidney tumors, accounting for 3–7% of all solid renal masses. Diagnosing oncocytomas using renal biopsy remains a controversy in the uro-pathologic community. With the increasing use of biopsies for assessment of renal lesions, reaching this pathologically benign diagnosis may prevent further surgical measures and have significant clinical benefit. Objective. To demonstrate our center’s results using renal biopsy to diagnose oncocytomas and to suggest that this diagnosis can be made with high success rates. Design, Setting, and Participants. From our center’s database, we retrospectively identified and retrieved all cases of oncocytoma diagnosed between the years 2011 and 2020 by renal biopsy. Medical records of those patients were then reviewed to view follow-up meetings and imaging of the lesions biopsied. Outcome Measurements and Statistical Analysis. In 21 biopsies performed on 19 patients, diagnosis was supported by subsequent follow-up averaging at 3.44 years per patient. Results and Limitations. The lesions exhibited benign behavior during follow-up after biopsy, consistent with the diagnosis of oncocytoma. Conclusions. Our study demonstrates that with good patient selection and proficient cooperation between urologists, radiologists and dedicated uro-pathologists, correctly diagnosing oncocytomas using RCB is a viable task. Patient Summary. Oncocytomas are benign lesions of the kidney. In our study, we reviewed all cases of oncocytomas pathologically diagnosed using renal biopsy from our center’s database. We found that in subsequent follow-up later to biopsy, the lesions displayed benign behavior consistent with oncocytoma. The use of percutaneous biopsies to reach this diagnosis could save patients more extensive surgeries.
Risk Assessment of Constructing Deep Foundation Pits for Metro Stations Based on Fuzzy Evidence Reasoning and Two-tuple Linguistic Analytic Network Process
Authors: Jiang Jie , Liu Guangyang , Huang Xi , Ou Xiaoduo
Published: August 2022

Accidents occur frequently while constructing deep foundation pits for metro stations, thereby risking substantial economic losses and casualties. To subject the construction of such pits to scientific and rational risk assessment and overcome the limitations of existing risk evaluation models and risk fusion problems, proposed here is a risk-assessment model for such pits based on fuzzy evidential reasoning and the two-tuple linguistic analytic network process (TL-ANP). First, the risk loss indicators are optimized, the weights of different risk events and of each risk loss indicator in the metro-station deep-foundation-pit construction project are calculated using TL-ANP, and trapezoidal fuzzy numbers are used to describe the occurrence probability of each risk event and loss. Second, relying on a table of expert weight indices, the best–worst method based on generalized interval-valued trapezoidal fuzzy numbers is used to determine the weights of experts. Finally, the overall risk grade of the construction project is evaluated by aggregating the risk levels of all risk events through an evidence-reasoning algorithm. The analysis results for a deep foundation pit for a station on Line 5 of Nanning Metro show that the model provides a quantitative basis for determining expert weights and risk loss weights reasonably and improving the reliability of the evaluation system. Also, not only does applying the method show that such a construction project can be judged as having a certain risk grade, but more importantly it can identify the key factors and loss indicators affecting the overall risk grade of the pit, whereupon risk control measures can be adopted in a targeted manner. In comparison with traditional methods, the proposed method is shown to be practical and effective, providing a reference basis for analyzing the risks of similar projects in the future and guaranteeing construction safety.
Multifeedback Behavior-Based Interest Modeling Network for Adaptive Click-Through Rate Prediction
Authors: Shang Xiaoran , Huang Bangbo , Ma Hongbin
Published: August 2022

With the rapid development of the Internet, the recommendation system is becoming more and more important in people’s life. Click-through rate prediction is a crucial task in the recommendation system, which directly determines the effect of the recommendation system. Recently, researchers have found that considering the user behavior sequence can greatly improve the accuracy of the click-through rate prediction model. However, the existing prediction models usually use the user click behavior sequence as the input of the model, which will make it difficult for the model to obtain a comprehensive user interest representation. In this paper, a unified multitype user behavior sequence modeling framework named as MBIN, a.k.a. multifeedback behavior-based Interest modeling network, is proposed to cope with uncertainties in the noisy data. The proposed adaptive model uses deep learning technology, obtains user interest representation through multihead attention, denoises user interest representation using the vector projection method, and fuses the user interests using adaptive dropout technology. First, an interest denoising layer is proposed in the MBIN, which can effectively mitigate the noise problem in user behavior sequences to obtain more accurate user interests. Second, an interest fusion layer is introduced so as to effectively model and fuse various types of interest representations of users to achieve personalized interest fusion. Then, we used auxiliary losses based on behavior sequences to enhance the effect of behavior sequence modeling and improve the effectiveness of user interest characterization. Finally, we conduct extensive experiments based on real-world and large-scale dataset to validate the effectiveness of our approach in CTR prediction tasks.
State Diagnosis and Monitoring Method of Robot Electric Power Equipment Based on Data Mining
Authors: Guo Haifeng , Meng Zhaojun , Yu Huimin , Chen Rui , Li Ling , Cheng Li
Published: August 2022

In recent years, with the continuous improvement of system networking, the use of robot electric power equipment is becoming more and more extensive, so it is very necessary to diagnose and monitor its status. Therefore, a diagnosis and monitoring system based on the data mining algorithm is constructed. This study mainly uses the gray prediction algorithm and discrete prediction algorithm; the results showed that after the combination of gray prediction has a certain degree of increase, through the analysis, we can draw the reason for this is that gray prediction algorithm to check the failure data is no longer as input data in the detection of outliers, thereby reducing the noise of the data set, so that the perfomance of oulier detection algorithm can ahieve a great progress. In terms of the running time of outlier detection, the running time of outlier detection using K-Mean algorithm and DBSCAN algorithm increases to a certain extent because the algorithm combines gray prediction and increases the algorithm process.
Construction and Application of a Task-Based Teaching Model of College English Based on Random Matrix Theory
Authors: Dang Leilei
Published: August 2022

Society is in urgent need of English talents with high comprehensive English application ability and strong independent learning ability. Task-based language teaching has always been an effective way to improve English talents, but the shortcomings of traditional task-based language teaching in teaching practice are beginning to emerge, such as insufficient classroom time, lack of real-time monitoring, and scientific evaluation mechanisms. Therefore, the traditional task-based language teaching cannot meet the new requirements of society for the cultivation of English talents. Random matrix theory uses the principles of statistical mechanics to model the interaction of complex systems in multiple mathematical domains to improve the teaching effectiveness. Random matrix theory has been widely used in theoretical neuroscience and optimal control. This paper is based on teaching task-based language and analyzing the data from the teaching process with big data so as to give timely feedback and suggestions to teachers. This paper constructs a model of college English teaching based on random matrix theory using a task-based teaching model. Since the teaching model of college English is a typical high-dimensional nonlinear function problem, a network model of deep confidence network is used to determine the implicit relationship between input and output. To verify the effectiveness of the model, this paper conducts a practical study of the constructed model. The study shows that the task-based teaching model of college English based on random matrix theory improves college students’ English expertise and English language usage ability and also greatly enhances students’ enthusiasm for learning English.
The Analysis of the Basic Types and Specific Characteristics of the Qinba Mountain Village Landscape along the Shu Road in the Late Qing Dynasty Based on IOT
Authors: Wang Xiaodong , Chen Gang
Published: August 2022

The Internet of Things is a huge system that collects and transmits real-time information. The smart space location is a part of IOT that collects location information, and on the other hand, it is an important tool to analyze the internal relationship of information and help users better understand its laws. As an integral part of the geographical landscape, human settlement environments have the main characteristics of both physical and cultural geography. The human settlement environments in the area along the Shu Road in the late Qing Dynasty (1840–1912) have important historical and geographical features. The main route of the Road to Sichuan takes the basic pattern of “Four in the north and three in the south,” with extensive coverage and overflow range; its complex landform brings diverse climate types and vastly different scenery as there are many factors related to the three cultural regions of Guanzhong, Qinba, and Shudi involved. In the application of the Internet of Things in geography, through high-frequency active monitoring, the situation changes can be grasped in a timely manner, the law of changes and trends can be discovered, and the geographic information of mountain village landforms can be provided to the public in a timely manner. Based on Ferdinand von Richthofen: Tagebücher aus China and Hand Drawing of China: Record of the History of Chinese Architecture in Japan, by retrospective restoration, on-site investigation, comprehensive application of relevant theories, and methods in historical geography, architectural typology, art phenomenology, and aesthetics, this study attempted to reasonably divide, scientifically classify, thoroughly analyze, extract the characteristics from, and improve the culture of the village landscapes in the Qinba Mountains along the Shu Road in the late Qing Dynasty from the perspectives including the size types and site relationship, building types and form structures, construction materials and decorative arts, general style, and aesthetic characteristics. It intends to revitalize the culture of village landscapes in the Qinba Mountains along the Shu Road in the late Qing Dynasty.
Boolean Algebra of Soft Q-Sets in Soft Topological Spaces
Authors: Al Ghour Samer
Published: August 2022

We define soft Q-sets as soft sets whose soft closure and soft interior are commutative. We show that the soft complement, soft closure, and soft interior of a soft Q-set are all soft Q-sets. We show that a soft subset K of a given soft topological space is a soft Q-set if and only if K is a soft symmetric difference between a soft clopen set and a soft nowhere dense set. And as a corollary, the class of soft Q-sets contains simultaneously the classes of soft clopen sets and soft nowhere dense sets. Also, we prove that the class of soft Q-sets is closed under finite soft intersections and finite soft unions, and as a main result, we prove that the class of soft Q-sets forms a Boolean algebra. Furthermore, via soft Q-sets, we characterize soft sets whose soft boundaries and soft interiors are commutative. In addition, we investigate the correspondence between Q-sets in topological spaces and soft Q-sets in soft topological spaces.
Study on the Support System Mechanism of Entry Roof with Roof Cutting Pressure Releasing Gob‐Side Entry Retaining Technology
Authors: Ma Xingen , Li Guihe , Cao Haitao , Wang Haijun , Shi Xiangyuan , Zhao Qingquan , Han Zhengcan , Zhang Tianyi , Dai Weiping , Zhang Jiangling
Published: August 2022

To improve the technical system of the roof cutting pressure releasing gob‐side entry retaining technology (RCPRGERT) and provide reference for the adaptive promotion and optimization of the new technology, the entry support system mechanism with RCPRGERT is studied in this paper. Firstly, the stress structure of the roof cutting short beam is analyzed by the mechanical theory analysis method. Then, taking 8304 working face of Tashan Coal Mine as an example, the stress distribution characteristics of the surrounding rock in different entry retaining stages are simulated by numerical simulation, which provides an important reference for the field support design and puts forward an idea of hierarchical support. Finally, an engineering test is carried out in the experimental working face to verify the design of the retaining entry support, which obtains a well entry retaining effect. The research results in this study provide powerful theoretical and practical references for the promotion of RCPRGERT under similar geological conditions.
Effect Evaluation and Student Behavior Design Method of Moral Education in Colleges and Universities under the Environment of Deep Learning
Authors: Zhang Yeqing , Liu Tianji , Ru Bao
Published: August 2022

The traditional ideological and moral education evaluation mechanism in colleges and universities faces many challenges. Among them, the traditional ideological and political theory course evaluation mechanism is difficult to solve the contradiction between the teaching content of the ideological and political theory course and the ideological knowledge of the educated, and the test scores of the ideological and political theory course are difficult to measure the level of students’ ideological awareness that has become a prominent problem. The evaluation mechanism of ideological and political education in colleges and universities based on deep learning technology can play a role in the formative evaluation and consequential evaluation of courses, thus forming a new mechanism for evaluating ideological and political education in colleges and universities, and further improving the effectiveness of ideological and political education.
Blockchain-Assisted Distributed Fog Computing Control Flow Attestation
Authors: Li Hongchao , Shen Tao , Bai Fenhua , Gong Bei
Published: August 2022

The control flow hijacking attack poses a serious threat to the integrity of the software. The attacker exploits the loophole to hijack the control flow of the running program to achieve the purpose of the attack. Remote control flow attestation is a method for embedded devices to ensure the integrity of the software. With the continuous development of Internet of Things (IoT) technology, embedded devices have exploded. None of the existing control flow attestation schemes can adapt to the real-time attestation requests of such massive embedded devices. This paper proposes a blockchain-assisted distributed fog computing control flow attestation scheme BDFCFA to deal with this scenario. The scheme uses a simplified control flow representation model, which can effectively represent the control flow of the program and reduce the runtime overhead of the prover in the attestation process. We use SGX technology to protect the integrity and confidentiality of verifier and prover data during the attestation process. Our proposed bidirectional control flow attestation protocol based on the elliptic curve can greatly protect the communication security between verifiers and provers without incurring excessive performance overhead and communication cost. We evaluate the performance of BDFCFA through the SNU real-time benchmark and demonstrate that BDFCFA has better performance. Finally, compared to the existing remote control flow attestation scheme, the results show that BDFCFA has the highest security.
Prevalence of Work‐Related Health Hazard and Associated Factors among Health Workers in Public Health Institutions of Gambella Town, Western Ethiopia: Cross‐Sectional Survey
Authors: Ayenew Ewnetu , Akafu Wakuma , Wolde Daka Dawit
Published: August 2022

Background. Many health‐related occupational hazards confront healthcare workers. Examining the prevalence of hazards enables to search for better risk management for healthcare workers because these workers are often the first point of interaction, particularly in resource‐limited settings like Ethiopia. Therefore, this study assessed the prevalence of work‐related occupational hazards and identified related factors among healthcare workers in public health facilities of Gambella town, Western Ethiopia. Methods. Institution‐based cross‐sectional study was conducted among 260 randomly selected healthcare workers from June 1‐21, 2021. A semi structured tool was used to collect data and data analysis was performed using SPSS version 25. Multivariable logistic regression was used to identify the predictors of outcome variable and the significance of associations was declared by using a 95% CI and a p‐value of <0.05. Results. The prevalence of occupational health hazards among healthcare workers was 36.5% (95% CI: 31, 42). The absence of immediate treatments for injured health workers (AOR = 8.86, 95% CI: 2.5, 31.4), lack of personal protective equipment (AOR = 3.6, 95% CI: 1.5, 8.4), working greater than eight hours per day (AOR = 7.9, 95% CI: 3.1, 19.7), working in the night shifts (AOR = 8.1, 95% CI: 2.5, 26.1), and absence of effective leadership in the health facility (AOR = 5.2, 95% CI: 1.9, 14.5) were factors associated with the prevalence of occupational hazards. Conclusions. There was a relatively high degree of occupational health hazard exposure among health workers in the study area compared to kinds of literature from other settings. Health workers were exposed to a wide range of occupational hazards, and risk reduction mechanisms and safety actions were inadequately implemented. Therefore, the health workers’ occupational health and safety needs should be prioritized and appropriate measures should be taken to mitigate the problems.
Bearing Fault Diagnosis Based on Frequency Subbands Feature Extraction and Multibranch One-Dimension Convolutional Neural Network
Authors: Chen Chih-Cheng , Liu Po-Yi
Published: August 2022

The rolling bearing is one of the important parts of rotating machinery, while the degree of dependence on the machine is becoming heavier nowadays. Therefore, it is always necessary to monitor its operating status and diagnose faults. To better analyze the bearing vibration signal from the time domain and frequency domain and reduce information loss, we propose a model that decomposes the original bearing vibration signal with a length of 1024 by a two-layer wavelet packet. For the analysis, four low-frequency and high-frequency feature vectors of a length of 1024 are obtained as the input for the analysis model. The proposed model uses frequency subbands to automatically extract features from network input and then fuse the features. The accuracy of the model on a single load on the Case Western Reserve University (CWRU) dataset is 98−100%, which shows the diagnostic effect is satisfactory.
QA Learning System-Based English Listening and Speaking Ability Improvement Strategy
Authors: Ma Yanbin
Published: August 2022

For most students, English learning is a strong affirmation of their self-learning ability, while not mastering effective learning methods and strategies makes most students doubt their language learning ability. One of the most important abilities in English learning is listening and speaking ability. How to enhance listening and speaking ability is quite important to improving English level. In this context, this study analyzes the problems in English listening and speaking teaching by understanding the current situation of students’ English listening and speaking training. On this basis, this study proposes a question-answering (QA) system based on deep learning to improve English listening and speaking ability. The results show that the proposed method in this study can not only effectively improve the accuracy of students’ answers but also improve their interest in English learning. The new method can effectively improve English listening and speaking ability and provide technical reference and method reference for the improvement of English listening and speaking ability.
A Reference Source Circuit Design for Voltage Controlled Oscillator Chips
Authors: Tan Chuanwu , Gong Jiangtao , Fu Zongchun
Published: August 2022

The basic principle and typical structure of the bandgap voltage reference source are introduced in detail in this paper. The performance index of the bandgap voltage reference is analyzed. The core circuit of a bandgap voltage reference source with good temperature characteristics and a high power supply rejection ratio (PSRR) is designed, in which a two-stage differential operational amplifier with a buffer stage is used, a start-up circuit without a capacitor is used to reduce the start-up time, and a common beta multiplication self-bias circuit is used to attenuate the effects of the power supply voltage. It is shown from the final HSPICE simulation results that the reference voltage temperature coefficient is approximately 7 ppm/°C within the range of -20 to 80°C in temperature, and the average PSRR can reach more than −56 dB within the range of 1 Hz to 10 kHz in frequency.
Omni channel Supply Chain Optimization and Mode Selection Based on Smart New Retail
Authors: Zhang Simin , Li Qi
Published: August 2022

Smart new retail mode has rapidly become the hot shopping mode. In order to develop vigorously in the new retail environment, it is urgent for merchants to set up supply chain network reasonably. This paper constructs a supply chain newsvendor model consisting of 1 wholesaler and N retailers. Analyse how channel conversion rate, negotiation ability of supply chain members, number of retailers, and other factors affect the balance among supply chain members when offline demand, online demand, and cross-channel demand exist simultaneously. Combined with the case data of two fast fashion brands, this paper compares and analyses the profit changes of decentralized supply chain and centralized supply chain under the influence of multiple factors. The study shows that there is no absolute optimal supply chain model and the choice of supply chain model will change with the change of influencing factors. However, no matter in which supply chain mode, improving channel conversion rate and controlling the number of retailers are beneficial. In addition, in decentralized supply chain, balance can be achieved among supply chain members so as to achieve Pareto optimality. Wholesalers should take the initiative to promote the transformation of demand among channels, and should not be too strong in member negotiations. This paper analyses the basic characteristics of the supply chain network under the new retail, and establishes the network optimization strategy that is easy to implement, which can help enterprises to carry out the supply network layout more effectively under the smart new retail mode.
Zuogui Pill Ameliorates Glucocorticoid-Induced Osteoporosis through ZNF702P-Based ceRNA Network: Bioinformatics Analysis and Experimental Validation
Authors: Zhang Peng , Chen Honglin , Shang Qi , Chen Guifeng , He Jiahui , Shen Gengyang , Yu Xiang , Zhang Zhida , Zhao Wenhua , Zhu Guangye , Huang Jinglin , Liang De , Tang Jingjing , Cui Jianchao , Liu Zhixiang , Jiang Xiaobing , Ren Hui
Published: August 2022

Glucocorticoid-induced osteoporosis (GIOP) is a musculoskeletal disease with increased fracture risk caused by long-term application of glucocorticoid, but there exist few effective interventions. Zuogui Pill (ZGP) has achieved clinical improvement for GIOP as an ancient classical formula, but its molecular mechanisms remain unclear due to scanty relevant studies. This study aimed to excavate the effective compounds and underlying mechanism of ZGP in treating GIOP and construct relative ceRNA network by using integrated analysis of bioinformatics analysis and experimental validation. Results show that ZNF702P is significantly upregulated in GIOP than normal cases based on gene chip sequencing analysis. Totally, 102 ingredients and 535 targets of ZGP as well as 480 GIOP-related targets were selected, including 122 common targets and 8 intersection targets with the predicted mRNAs. The ceRNA network contains one lncRNA (ZNF702P), 6 miRNAs, and 8 mRNAs. Four hub targets including JUN, CCND1, MAPK1, and MAPK14 were identified in the PPI network. Six ceRNA interaction axes including ZNF702P-hsa-miR-429-JUN, ZNF702P-hsa-miR-17-5p/hsa-miR-20b-5p-CCND1, ZNF702P-hsa-miR-17-5p/hsa-miR-20b-5p-MAPK1, and ZNF702P-hsa-miR-24-3p-MAPK14 were obtained. By means of molecular docking, we found that all the hub targets could be effectively combined with related ingredients. GO enrichment analysis showed 649 biological processes, involving response to estrogen, response to steroid hormone, inflammatory response, macrophage activation, and osteoclast differentiation, and KEGG analysis revealed 102 entries with 36 relative signaling pathways, which mainly contained IL-17 signaling pathway, T cell receptor signaling pathway, FoxO signaling pathway, the PD-L1 expression and PD-1 checkpoint pathway, MAPK signaling pathway, TNF signaling pathway, Estrogen signaling pathway, and Wnt signaling pathway. Our experiments confirmed that ZNF702P exhibited gradually increasing expression levels during osteoclast differentiation of human peripheral blood monocytes (HPBMs) induced by RANKL, while ZGP could inhibit osteoclast differentiation of HPBMs induced by RANKL in a concentration-dependent manner. Therefore, by regulating inflammatory response, osteoclast differentiation, and hormone metabolism, ZGP may treat GIOP by regulating hub target genes, such as JUN, CCND1, MAPK1, and MAPK14, and acting on numerous key pathways, which involve the ZNF702P-based ceRNA network.
Ultrasound-Guided Fine Needle Aspiration of Deep Thyroid Nodule: Is There a Correlation between the Nodule’s Depth and Nondiagnostic Results?
Authors: Asakly Majd , Farhat Raed , El Khatib Nidal , Khater Ashraf , Safia Alaa , karam Marwan , Massoud Saqer , Bishara Taiser , Avraham Yaniv , Sharabi-Nov Adi , Merchavy Shlomo
Published: August 2022

Objective. To evaluate whether thyroid nodule depth correlates with nondiagnostic results in ultrasound-guided fine needle aspiration cytopathology. Background. Many factors correlate with nondiagnostic ultrasound-guided fine needle aspiration cytology (FNAC) results, including older age, macrocalcification, small-sized nodules, aspirin medication, and cystic portion in more than 50% of the thyroid nodules. However, there are few studies which have examined whether there is a relationship between the depth of nodules and the percentage of nondiagnostic results in cytology (Bethesda category I). We conducted this study in order to investigate if such a correlation exists. Materials and Methods. FNAC was performed on 283 thyroid nodules between January 2019 and December 2020. Cytological analyses of the nodules were reviewed and sorted as nondiagnostic and diagnostic according to the Bethesda score. Patient files and ultra sound (US) scans were reviewed for clinical information (such as age, sex, and ethnic group) and sonographic features of nodules (such as depth, size, cystic portion, type of calcification, and echogenicity) and were compared between the nondiagnostic and diagnostic nodule results. The depth of a nodule was calculated as the shortest distance from the skin to the most superficial border of the nodule in the axial plane, using our medical center’s computer program, which allows reviewing all saved shots of the US scan. Results. Age, sex, and ethnicity were not significantly different between the nondiagnostic group and the diagnostic group (

p
>
0.05

). Nodule diameter, cystic portion, calcification, and echogenicity were also not associated with the frequency of nondiagnostic results. The depth of nodules ≥9 mm was correlated with nondiagnostic US-guided FNA cytological results (OR = 2.55,

p
=
0.018

). Conclusions. Deep thyroid nodules correlated with nondiagnostic US-guided FNA cytological results. Further studies are needed for optimizing the approach to deep thyroid nodules in order to improve the efficacy of FNA in deep thyroid nodules.