bluuebunny/crossref_metadata_2025 huggingface dataset:
Exploring the Protective Effect and Mechanism of Buddlejae Flos on Sodium Selenite-Induced Cataract in Rats by Network Pharmacology, Molecular Docking, and Experimental Validation
Authors: Liu Xian-Yin , Wang Xue-Lin , Qiu Mo-Chang , Ye Ying-Jun , Wang Fang , Xu Yan-Qi , Gong Jun-Jie , Xu Zi-Jin
Published: May 2022

Objective. Buddlejae Flos has a long history of utilization by humans to treat ophthalmic diseases. Although in vitro study revealed that it can be used for treating cataract, the bioactive components and the mechanism of efficacy remained unclear. This study aims to discover the bioactive components and mode of efficacy of Buddlejae Flos in cataract treatment. Methods. Several databases were screened for bioactive components and corresponding targets, as well as cataract-related targets. Using the String database, common targets were determined and utilized to construct protein-protein interactions (PPI). The drug-component-target-disease network map was drawn using Cytoscape software. R language was utilized to execute Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) pathway enrichment analysis. Molecular docking was done through Schrödinger Maestro software utilization. Luteolin’s (LUT) effect on cataract induced by sodium selenite in rat pups was evaluated. Results. Six bioactive components with 38 common targets were identified as being associated with cataract. TP53, AKT1, EGFR, CASP3, TNF, ESR1, INS, IL6, HIF1A, and VEGFA were identified as core targets in PPI analysis, and the binding energy of LUT with AKT was the lowest. LUT has been demonstrated to significantly lower MDA levels, raise glutathione (GSH) levels, and boost the activity of antioxidant enzymes like GST, SOD, GPx, and CAT. After LUT treatment, TNF-a, IL-2, and IL-6 levels were significantly lowered. Bcl-2 mRNA expression levels and p-PI3K and p-AKT protein expression were significantly elevated. In contrast, caspase-3 and Bax mRNA expression levels were significantly decreased. Conclusion. This study demonstrates that LUT is a possible bioactive component that may be utilized for cataract treatment. Its mode of action includes oxidative stress suppression, reducing inflammation, and inhibiting apoptosis via regulating the PI3K/AKT single pathway.
Brain Network Changes in Lumbar Disc Herniation Induced Chronic Nerve Roots Compression Syndromes
Authors: Zhang Yan-Peng , Hong Guang-Hui , Zhang Chuan-Yin
Published: May 2022

Lumbar disc herniation (LDH) induced nerve compression syndromes have been a prevalent problem with complex neural mechanisms. Changes in distributed brain areas are involved in the occurrence and persistence of syndromes. The present study aimed to investigate the changes of brain functional network in LDH patients with chronic sciatica using graph theory analysis. A total of thirty LDH adults presenting L4 and/or L5 root (s) compression syndromes (LDH group) and thirty age-, sex-, BMI- and education-matched healthy control (HC group) were recruited for functional MRI scan. Whole-brain functional network was constructed for each participant using Pearson’s correlation. Global and nodal properties were calculated and compared between two groups, including small-worldness index, clustering coefficient, characteristic path length, degree centrality (DC), betweenness centrality (BC) and nodal efficiency. Both LDH and HC groups showed small-world architecture in the functional network of brain. However, LDH group showed that nodal centralities (DC, BC and nodal efficiency) increased in opercular part of inferior frontal gyrus; and decreased in orbital part of inferior frontal gyrus, lingual cortex and inferior occipital gyrus. The DC and efficiency in the right inferior occipital gyrus were negatively related with the Oswestry Disability Index in LDH group. In conclusion, the LDH-related chronic sciatica syndromes may induce regional brain alterations involving self-referential, emotional responses and pain regulation functions. But the whole-brain small-world architecture was not significantly disturbed. It may provide new insights into LDH patients with radicular symptoms from new perspectives.
Parametric Identification for the Biased Ship Roll Motion Model Using Genocchi Polynomials
Authors: Swaminathan G. , Hariharan G. , Mohiuddine S. A. , Tamilvanan Kandhasamy , Kabeto Masho Jima
Published: May 2022

Roll motion is one of the key motions related to a vessel’s dynamic stability. It is essential for the dynamic stability of ships in the realistic sea. For this research study, we have investigated the parameters involved in damping of the ship. In general, mathematical modelling of the rolling response of a ship can be formulated by the linear, nonlinear, and fractional differential equations because the amplitude of oscillation is increased. An efficient Genocchi polynomial approximation method (GPAM) is successfully applied for the biased ship roll motion model. The basic idea of the collocation method together with the operational matrices of derivatives used for nonlinear differential equation and convert it into a system of algebraic equations. The convergence and error analysis of the proposed method are also discussed. A few numerical experiments are carried out for some specific and important types of problems including the biased roll motion equations. The results are compared to those produced using the Legendre wavelet method (LWM) and the homotopy perturbation method (HPM). It is observed that the proposed spectral algorithm is robust, accurate, and easy to apply.
A Channel State Information-Based Key Generation Scheme for Internet of Things
Authors: Usman Muhammad , Althunibat Saud , Qaraqe Marwa
Published: May 2022

Internet-of-Things (IoT) networks generally contain resource-constrained devices that require an energy-efficient key generation procedure to producing secure keys at a faster rate. The physical characteristics of the wireless channel can be exploited to secure communication within IoT networks. In particular, secret keys can be generated by leveraging on the randomness of the wireless physical channel between two communicating parties. The conventional mechanism of generating keys at the physical layer, i.e., using channel probing, quantization, information reconciliation, and privacy amplification, may not be preferable for IoT devices. In addition, in some cases IoT devices may be deployed in static environments, wherein the channel coherence time is too high to generate keys at a faster rate and with the desired randomness. This study proposes a mapping table-based key distribution scheme for IoT environments, wherein multiple characteristics of the random channel are combined to improve not only the key generation rate (KGR) but also the key agreement rate (KAR) and bit error rate (BER). In the proposed scheme, both the channel magnitude and the phase are exploited in the key generation process. The proposed scheme is immune to channel estimation errors while providing sufficient randomness in the static environment. Additionally, the scheme is thoroughly investigated for different scenarios including the case of a smarter eavesdropper, which attempts to estimate the channel between the legitimate nodes. This case verifies the robustness of the proposed scheme in different settings and attack models.
Wiener Index of Intuitionistic Fuzzy Graphs with an Application to Transport Network Flow
Authors: Naeem Tulat , Jamil Muhammad Kamran , Fahd Khawaja Muhammad , alAmeri Abdu
Published: May 2022

The Wiener index is one of the connectivity parameters used to know the biochemical and physicochemical properties of compounds depending upon their molecular structures. Intuitionistic fuzzy graphs (IFGs) are a convenient tool to represent the objects and relations between them with two types of information using truth membership degree and falsity membership degree. This research work presents the concept of under the structure IFGs, IF trees, and IF cycles. Some bounds on are investigated. The relationship between and connectivity index is also studied. In the end of this study, an application of the in transport network flow is proposed.
The Application of Edge Computing in the Urban Industrial Spatial Form of Macau
Authors: Li Haiyu
Published: May 2022

The proposal and development of edge computing provide new ideas for the management of industrial space forms in high-density cities. With the acceleration of China’s urbanization process, the spatial distribution system of industries in cities is relatively complicated and is not suitable for benefit and suitability evaluation. There is still a lack of in-depth quantitative analysis and research on the industrial spatial form of Macau’s high-density cities, which is restricted by factors such as shortage of land and simplification of industries. Therefore, it is necessary to explore the relationship between Macau’s industrial spatial pattern and its urban spatial pattern, deepen its industrial system reform, and put forward suggestions that are more in line with the needs of urbanization. Among them, the sports, leisure, and entertainment industry account for a relatively large proportion of the industrial structure of Macau city, which is a very important part. This paper studies the aggregation and correlation of its spatial distribution through the method of nuclear density analysis and aims to provide a better basis and support for its more reasonable industrial upgrading.
Coalbed Methane Industry Development Framework and Its Limiting Factors in China
Authors: Li Rui , Li Guofu
Published: May 2022

The current average daily gas production of single coalbed methane (CBM) wells in China is less than 1,300 m3. The low production rate of CBM wells dramatically limits the sustainable development of the CBM industry in China. To promote CBM industry development, three universal geological factors, i.e., gas sources, channels, and driving force of the low production wells are analyzed, considering the various and complicated geological conditions of CBM reservoirs in China. Additionally, we find that the growth in proven CBM reserves should be greatly promoted as the CBM proven rate is only less than 3% by the end of 2020. The widespread CBM extraction mode based on depressurization via dewatering generates very limited effects in coal seams with notable deformation, high in situ stress, or little water. Therefore, a specific design of CBM development modes is proposed, according to the applicable geological conditions of different CBM development modes. It covers depressurization via dewatering, depressurization via stress release, and coal and CBM comining. Moreover, the regional governments play a key role in the development of the regional CBM industry, and favorable policies should be formulated to promote the multipoint development conditions across China. This study is concluded to provide a recommended development framework involving sustainable CBM production in China and its development processes.
Concentrations of Lead in Groundwater and Human Blood in the Population of Palosai, a Rural Area in Pakistan: Human Exposure and Risk Assessment
Authors: Ren Yu Shuang , Ilyas Muhammad , Xu Rui Ze , Ahmad Waqas , Wang Rui
Published: May 2022

Lead (Pb) is a toxic environmental contaminant, which enters water bodies from natural and anthropogenic activities. The present study investigates the Pb concentration in groundwater sources and evaluates their potential health risks in Palosai area, Peshawar, Khyber Pakhtunkhwa, Pakistan. Groundwater samples were collected from different groundwater sources in the area where the human blood samples were from the dependent residents. Pb concentration was analyzed using an atomic absorption spectrophotometer and compared with the permissible limits set by Pakistan Environmental Protection Agency and World Health Organization (WHO). The levels of physicochemical parameters were observed within the said safe limits, while the levels of Pb in different groundwater sources (tube wells and wells) showed a little bit variation. Health risk indicators such as chronic daily intake (CDI) and hazard quotient (HQ) were calculated for Pb. The calculated value of CDI and HQ for Pb via groundwater consumption was 0.001 mg/kg·day and [Formula: see text] mg/kg·day, respectively; however, the overall HQ values of Pb in the groundwater were less than 1, indicating no health risk to the local depending community.
Analysis of Urban Residents’ Consumption Behavior and Influencing Factors of Ecological Agricultural Products in the Post-Pandemic Era of COVID-19
Authors: Chen Ximing , Shang Jie
Published: May 2022

Based on consumer survey data in the post-pandemic era of COVID-19, a binary Logit model was used to analyze the consumers’ consumption behavior and the influencing factors of ecological agricultural products in the post-pandemic era. The results showed that: family size, average annual household income, gender, and education level would not affect the consumers’ behavior in purchasing ecological agricultural products after the pandemic; age and whether consumers have purchased agricultural products before had a significant negative impact on consumption behavior; the degree of consumers’ skepticism about agricultural products in the market after the pandemic had a significant positive impact on their purchase behavior. According to the analysis results, it is proposed that: we should vigorously develop the connection between agricultural socialized service industry and large supermarkets, improve the online and offline sales model of ecological agricultural products, establish an ecological agricultural product service platform, and enhance the scientific and technological researches and their application to ecological agricultural products.
Investigating the Hydraulic Properties of Unsaturated Crushed Stone Aggregate to Enhance Horizontal Drainage Systems on Soft Ground
Authors: Lim Seongyoon , Kim Myeonghwan
Published: May 2022

Crushed stone aggregate materials are commonly used for basal embankment support on soft subgrades or for horizontal drainage in soft soils. When the drainage material is constrained by earth pressure and water pressure, it changes to an unsaturated water‐permeable state. If the pore water pressure decreases as the compaction of the soft ground increases, the water does not drain through the drainage material. Therefore, it is necessary to measure the critical pressure value (air entry value) going from saturation to desaturation. That is, even if the pore water pressure is small, the water must be discharged through the drainage material. Therefore, this study presents experimental results for gravity drainage and soil‐water retention curves (SWRCs) using mixed crushed stone aggregate samples at different particle size distributions and different compaction conditions. SWRC experiments indicate that porosity, hydraulic conductivity under saturated conditions, and air entrapment decrease with increasing sand content. Also, the samples retained more water at higher suction values, although the porosity decreased with increasing sand content. This phenomenon is due to the tendency of the uniformity coefficient to increase as more fine particles are added to the crushed stone aggregate. In addition, it is considered that the function as a drainage material is possible only when it shows a higher air entry value than that of the loose crushed stone aggregate drainage material. Therefore, for drainage materials using crushed stone aggregate, analysis of the soil‐water retention curve for unsaturated soil should be preceded.
HRM Risk Early Warning Based on a Hybrid Solution of Decision Tree and Support Vector Machine
Authors: Cai Wei
Published: May 2022

Human resource management is the core support and strong guarantee for the survival and innovative development of enterprises, which is directly related to the realization of the strategic development goals of enterprises. However, in today’s rapidly changing internal and external environment, HRM (Human Resource Management) activities of enterprises may face various risks at any time. Therefore, this paper designs a HRM risk warning scheme based on decision tree and support vector machine, which combines the features of support vector machine binary classification and recombines each category of multicategory classification according to decision tree multi-sub-category classification, and can identify all categories more accurately. Simulation experiments show that the convergence of the network designed in this way tends to be stable, and the performance of the early warning for enterprises meets the standard.
A High-Precision Classification Method of Mammary Cancer Based on Improved DenseNet Driven by an Attention Mechanism
Authors: Xu Xuebin , An Meijuan , Zhang Jiada , Liu Wei , Lu Longbin
Published: May 2022

Cancer is one of the major causes of human disease and death worldwide, and mammary cancer is one of the most common cancer types among women today. In this paper, we used the deep learning method to conduct a preliminary experiment on Breast Cancer Histopathological Database (BreakHis); BreakHis is an open dataset. We propose a high-precision classification method of mammary based on an improved convolutional neural network on the BreakHis dataset. We proposed three different MFSCNET models according to the different insertion positions and the number of SE modules, respectively, MFSCNet A, MFSCNet B, and MFSCNet C. We carried out experiments on the BreakHis dataset. Through experimental comparison, especially, the MFSCNet A network model has obtained the best performance in the high-precision classification experiments of mammary cancer. The accuracy of dichotomy was 99.05% to 99.89%. The accuracy of multiclass classification ranges from 94.36% to approximately 98.41%.Therefore, it is proved that MFSCNet can accurately classify the mammary histological images and has a great application prospect in predicting the degree of tumor. Code will be made available on http://github.com/xiaoan-maker/MFSCNet.
Music Morphology Interaction under Artificial Intelligence in Wireless Network Environment
Authors: Zhang LiLan
Published: May 2022

Music has become the main information carrier, and music and its emotional expression are accurately classified to obtain relevant information. However, how to classify music accurately is a problem that needs to be discussed. The concept and feature extraction strategy of the morphology of music are described. Moreover, the feature extraction and morphological classification elements of digital music are introduced. Next, music morphology is recognized and classified based on the neural network and relief algorithm. In the network, by randomly selecting different music types, the audio data is input into the neural network as the original data and processed by the relief algorithm. The classification and recognition accuracy of the Relief algorithm are verified by changing the number of iterations. The results show that the model’s classification accuracy based on the number of iterations is 78.958%. Then, the traditional statistical analysis classification method’s performance is compared with the proposed model. The recognition accuracy of the model proposed reaches 92%, which shows that the model can effectively classify music morphology. This study provides a theoretical basis for music morphology recognition in the wireless network environment.
Singular Signal Measurement Based on Bidirectional Recursive Complex-Valued Wavelet Algorithm
Authors: Lv Weiping , Xie Jinshan , Huang Jing
Published: May 2022

The normal operation fault of the power system is usually caused by a short-circuit fault. At this time, the system changes drastically from one state to another, accompanied by complex transient phenomena. Therefore, the measured signal contains a large number of transient components. How to effectively analyze such signals, extract their characteristics, and develop new protection devices has always been an important research field in power system protection technology. The protection of the power system is to achieve the purpose of correct action and elimination of faults by quickly detecting and locating faults. At present, the power signal analysis tools used in microcomputer protection include FFT, Kalman filter, and finite impulse response filter. They are efficient for the analysis of stationary signals, but have their limitations in analyzing nonstationary signals; especially it is difficult to identify nonlinear faults, such as the detection of high-impedance nonlinear short-circuit faults, which is a long-term unsolved problem in power systems. Based on wavelet transform, this paper selects complex-valued wavelet algorithm, analyzes a real-time recursive wavelet algorithm, and deduces the realization process of the algorithm in detail. The algorithm greatly reduces the computational complexity of the existing two-way recursive algorithm, can be used for real-time detection of fault signals in various fields of power system, and can be extended to realize other fast recursive algorithms of wavelet functions. Based on the sensitivity of complex-valued wavelet transform phase information to singularity, a method for real-time monitoring of power system fault mutation signals using the phase information of complex-valued wavelet fast recursion algorithm to assist amplitude information is proposed. The validity and practicability of this complex-valued wavelet and its real-time recursive algorithm for fault detection are demonstrated by an example.
Statistical Analysis on Time to Blindness of Glaucoma Patients at Jimma University Specialized Hospital: Application of Accelerated Failure Time Model
Authors: Bambo Meseret Mesfin , Gebremariam Meskerem Getachew
Published: May 2022

Background. Glaucoma is one of the most frequent vision-threatening eye diseases. It is frequently associated with excessive intraocular pressure (IOP), which can cause vision loss and damaged optic nerves. The main objective of this study was to model time to blindness of glaucoma patients by using appropriate statistical models. Study Design. A Retrospective Community-Based Longitudinal Study design was applied. Materials and Procedures. The data were obtained from Ophthalmology Department of JUSH from the period of January 2016 to August 2020. The glaucoma patient’s information was extracted from the patient card and 321 samples were included in the study. To discover the factors that affect time to blindness of glaucoma patients’, researchers used the Accelerated Failure Time (AFT) model. Results. 81.3 percent of the 321 glaucoma patients were blind. Unilaterally and bilaterally blinded female and male glaucoma patients were 24.92 and 56.38%, respectively. After glaucoma disease was confirmed, the median time to the blindness of both eyes and one eye was 12 months. The multivariable log-logistic accelerated failure-time model fits the glaucoma patient’s time to blind dataset well. The result showed that the chance of blindness of glaucoma patients who have absolute stage of glaucoma, medium duration of diagnosis, long duration of diagnosis, and IOP greater than 21 mmHg were high with parameters (ϕ = 2.425,

p

value = 0.049, 95% CI [2.249, 2.601]), (ϕ = 1.505,

p

value = 0.001, 95% CI [0.228, 0.589]), (ϕ = 3.037,

p

value = 0.001, 95% C.I [2.850, 3.22]) and (ϕ 0.851,

p

value = 0.034, 95% C.I [0.702, 0.999]), respectively. Conclusion. The multivariable log-logistic accelerated failure time model evaluates the prognostic factors of time to blindness of glaucoma patients. Under this finding, duration of diagnosis, IOP, and stage of glaucoma were a key determinant factors of time to blindness of glaucoma patients’. Finally, the log-logistic accelerated failure-time model was the best-fitted parametric model based on AIC and BIC values.
Covariance Matrix Reconstruction via a Subspace Method and Spatial Spectral Estimation for Robust Adaptive Beamforming
Authors: Lv Yan , Cao Fei , He Chuan , Feng Xiaowei , Qin Jianqiang
Published: May 2022

Several robust adaptive beamforming (RAB) algorithms based on interference plus noise covariance matrix (INCM) reconstruction have been recently proposed, which can enhance the robustness of beamforming algorithms when certain mismatches occur in the model. However, some approaches ignore the resolution of the Capon spectral estimator (CSE), leading to reconstruction errors. This paper proposes a novel RAB algorithm formulated using the subspace projection method and spatial spectral estimation (SSE), which is named INCM-SSE. First, without using the CSE, the subspace projection matrix (SPM) is obtained through the integral of the angular sector where the signal of interest (SOI) is located. Subsequently, after estimating the direction of arrival (DOA) of incident signals using the multiple signal classification (MUSIC) algorithm, we project the sample covariance matrix (SCM) onto the SPM to eliminate the SOI influence. Then, the estimation method of interference powers is derived. Moreover, the INCM is reconstructed based on the estimated powers and steering vector (SV) of interferences. The SV of the SOI is optimized by solving a quadratic convex optimization problem. The INCM-SSE algorithm not only employs SSE to improve the angular resolution but also reduces the influence of the SOI component by using SPM. Simulation results indicate that the proposed method is robust against various types of mismatches, thus achieving superior overall performance.
Spectrum of Superhypergraphs via Flows
Authors: Hamidi Mohammad , Smarandache Florentin , Davneshvar Elham
Published: May 2022

For any n ∈ ℕ and given nonempty subset V, the concept of n‐superhypergraphs is introduced by Florentin Smarandache based on Pn(V) (n‐th power set of V). In this paper, we present the novel concepts supervertices, superedges, and superhypergraph via the concept of flow. This study computes the number of superedges of any given superhypergraphs, and based on the numbers of superedges and partitions of an underlying set of superhypergraph, we obtain the number of all superhypergraphs on any nonempty set. As a main result of the research, this paper is introducing the incidence matrix of superhypergraph and computing the characteristic polynomial for the incidence matrix of superhypergraph, so we obtain the spectrum of superhypergraphs. The flow of superedges plays the main role in computing of spectrum of superhypergraphs, so we compute the spectrum of superhypergraphs in some types such as regular flow, regular reversed flow, and regular two-sided flow. The new conception of superhypergraph and computation of the spectrum of superhypergraphs are introduced firstly in this paper.
Intestinal Tuberculosis Presenting with Gastrointestinal Bleeding in Patient on Warfarin Therapy
Authors: Kuka Werimo Pascal , Rakiro Joe , Gatheru Joseph , Riunga Felix , Rajula Allan
Published: May 2022

Background. Intestinal tuberculosis (ITB) constitutes less than 5% of overall cases of extrapulmonary disease and mostly affects the ileocecal region. The presentation and radiologic findings in enteric tuberculosis can mimic Crohn’s disease (CD). Case Presentation. We present a case report of an African woman who presented to a Kenyan hospital with lower gastrointestinal bleeding while on anticoagulation for valvular atrial fibrillation, and was diagnosed with intestinal tuberculosis after colonoscopy, biopsy, and positive staining for tuberculous bacilli. Conclusion. Intestinal tuberculosis causing gastrointestinal bleeding is rare but should be suspected in patients living in TB endemic regions.
Clinical Outcome Discrimination in Pediatric ARDS by Chest Radiograph Severity Scoring
Authors: Yan Yu-Chun , Hao Wen-Han , Bai Feng-Sen , Liu Shuang , Qu Dong , Yuan Xin-Yu
Published: May 2022

Background. There is no accurate radiological measurement to estimate the severity of pediatrics acute respiratory distress syndrome (PARDS). We validated the effectiveness of an adult radiographic assessment of lung edema (RALE) score in PARDS. Aim. To assess the severity and prognosis of PARDS based on a chest radiograph (CXR) RALE scoring method. Methods. Pediatric Acute Lung Injury Consensus Conference (PALICC) criteria were used to diagnose PARDS. General demographics, pulmonary complications, and 28‐day mortality of the patients were recorded. Subgroups were compared by prognosis (survive and death) and etiology (infection and noninfection). Two observers calculated RALE independently. Each quadrant of CXR was scored by consolidation scores 0 (none alveolar opacity), 1 (extent <25%), 2 (extent 25%–50%), 3 (50%–75%), and 4 (>75%) and density scores 1 (hazy), 2 (moderate), and 3 (dense). Quadrant score equals consolidation score times density score. Total score equals to the sum of four quadrants scores. The ROC curve and survival curve were established, and the optimal cutoff score for discrimination prognosis was set. Results. 116 PARDS (72 boys and 44 girls) and 463 CXRs were enrolled. The median age was 25 months (5 months, 60.8 months) and with a mortality of 37.9% (44/116). The agreement between two independent observers was excellent (ICC = 0.98, 95% CI: 0.97–0.99). Day 3 score was independently associated with better survival (

p
<
0.001

). The area under the curve of ROC was 0.773 (95% CI: 0.709–0.838). The cutoff score was 21 (sensitivity 71.7%, specificity 76.5%), and the hazard ratio (HR) was 9.268 (95% CI: 1.257–68.320). The pulmonary complication showed an HR of 3.678 (95% CI: 1.174–11.521) for the discrimination. Conclusion. CXR RALE score can be used in PARDS for discriminating the prognosis and has a better agreement among radiologist and pediatrician. PARDS with pulmonary complications, day 3 score whether greater than 21 points, have a better predictive effectiveness.
Convergence and Stability of a Novel
M
‐Iterative Algorithm with an Application
Authors: Kaur Manjinder , Chandok Sumit
Published: May 2022

In this manuscript, we propose a novel three - step iteration scheme called

M

- iteration to approximate the invariant points for the class of weak contractions in the sense of Berinde and obtain that

M

- iteration strongly converges to one and only one fixed point for Berinde mappings. Proving ‘almost - stability’ of

M

- iteration, we compare the

M

- iterative scheme with other chief iterative algorithms, namely. Picard, Mann, Ishikawa, Noor, S, normal-S, Abbas, Thakur, Varat, Ullah and

F

∗

and claim that the framed iterative procedure converges to the invariant points of weak contractions at faster rate than other vital algorithms. Some numerical illustrations are adduced to strengthen our claim. We further ascertain data dependency through

M

- iteration. Finally, we establish the solution of Caputo type fractional differential equation as an application and exhibit that

M

- fixed point procedure converges to the solution of a fractional differential equation. The obtained results are not only new but, also, extend the scope of previous findings.
Research on the Method of Ground Stress Balance under Complex Conditions Based on Geometric Tracing
Authors: Wang Ge
Published: May 2022

The accuracy of the initial ground stress balance determines the accuracy of the finite element analysis of geotechnical problems. The traditional ground stress balance method has a good balance effect for simple geotechnical models but has strong limitations when the structure and soil interact with each other, the geometry of the model is complex, or the constraints are complicated. To deal with such problems, this paper proposes a general ground stress balance method based on geometric tracing by iteratively superimposing the static displacement field of the numerical model with the initial node coordinates of the numerical model. Two commonly used methods as well as the proposed method were tested with a model which contains both soil elements and structural elements and a case study. Test results show that the proposed method is capable of dealing with a complex model in which the commonly used methods fail to. Furthermore, the proposed ground stress balance method was demonstrated to be clear and has rapid convergence and high accuracy for complex stratum‐structure geotechnical problems.
Effects of Real-Time High Temperature and Loading Rate on Deformation and Strength Behavior of Granite
Authors: Zhang YiFeng , Zhang Fan , Yang Ke , Cai ZhengYu
Published: May 2022

Knowledge of deformation and strength behavior of rocks under high in situ temperature is highly important for the control of geological disasters in exploration of hot dry rock and mining in deep formation. In this study, uniaxial compression tests were carried out on granite under different real-time high-temperature conditions (25, 200, 300, 400, 500, 600, and 700°C) and loading rates (0.01, 0.1, and 0.5 mm/min). The effects of real-time high temperature and loading rate on the uniaxial compressive strength and elastic modulus of granite were studied, and the microscopic morphology of the fracture surface was analyzed. The results show that the uniaxial compressive strength and elastic modulus of granite increase first and then decrease with the increase of temperature. The uniaxial compressive strength clearly increases at 200°C and decreases gradually when the temperature exceeds 300°C. Under the same temperature conditions, the uniaxial compressive strength of granite decreases and the elastic modulus increases with increasing loading rate. When the temperature reaches 600°C, the effect of the loading rate on the uniaxial compressive strength and elastic modulus of granite decreases significantly. The test results are compared with the results of work performed on quenched granite. Under real-time high-temperature conditions, the thermal crack effect has a significant influence on the uniaxial compressive strength and elastic modulus of granite, without the thermal hardening effect of quenched granite. During hydraulic fracturing, the rock skeleton near the injection well is cooled and shrunk, as is the thermal hardening effect caused by high-temperature quenching. The formation of thermal equilibrium leads to the large-scale extension of fracture cracks along the weak plane structure, such as the effect of thermal cracks on granite under real-time high-temperature conditions.
Analysis and Prediction of Subway Tunnel Surface Subsidence Based on Internet of Things Monitoring and BP Neural Network
Authors: Wang Baitian , Zhang Jing , Zhang Longhao , Yan Shi , Ma Qiangqiang , Li Wentao , Jiao Maopeng
Published: May 2022

With the acceleration of the urban development process and the rapid growth of China’s population, the subway has become the first choice for people to travel, and the urban underground space has been continuously improved. The subway construction has become the focus of urban underground space development in the 21st century. During the construction of subway tunnels, the problem of surface settlement will inevitably be caused, and the problem of surface settlement will have a certain safety impact on the safe use of surface buildings. The impact of surface construction is predicted, so as to select the best construction technology and avoid the problem of surface subsidence to the greatest extent. On the basis of analyzing the principle of surface subsidence, this paper studies the optimal control strategy and process of subsidence in subway tunnel engineering. The research results of the article show the following. (1) The two sections of the pebble soil layer have basically the same subsidence trend. Among them, the first section has a larger settlement amplitude and both sides are steeper. The second section is mainly cobble clay soil. The pebble layer has good mechanical properties. If it can be well filled, its stability will be improved. The comparative analysis of the two sections shows that with the increase of the soil cover thickness, the maximum subsidence at the surface gradually decreases. The reason is that when the stratum loss is the same, the greater the soil cover thickness, the greater the settlement width. Sections 2 and 3 of a single silty clay have relatively close settlement laws, and the settlement changes on both sides of the tunnel are similar. (2) The surface subsidence caused by the excavation of the side hole accounts for more than 50% of the total surface subsidence, and the width of the settlement tank after the excavation of the side hole is increased by 8–10 meters compared with the excavation of the middle hole. (3) The prediction error of the BP neural network model proposed in this paper is the lowest among the four models, whether it is the prediction of the cumulative maximum surface subsidence or the location of the cumulative maximum surface subsidence, and the average relative error of the cumulative maximum surface subsidence is 3.27%, the root mean square error is 3.87, the average relative error of the location of the cumulative maximum surface subsidence is 7.96%, and the root mean square error is 21.06. In the prediction process of the cumulative maximum surface subsidence, the prediction error value of the Elman neural network is relatively large, and the GRNN generalized neural network and RBF neural network have no significant changes; in the process of predicting the position where the cumulative maximum surface subsidence occurs, the prediction error value of RBF neural network is maximum.
Meshing Characteristics of Toroidal Drive of Spherical Planetary Gear
Authors: Zhang Yanhua , Cao Jujiang
Published: May 2022

Globoidal cam transmission of planetary gear train is a complex form of space transmission. The curved surface and meshing state of the inner and outer globoidal cam are determined by the curved surface of the rolling tooth on the planetary gear. Therefore, a unified mathematical expression method of the curved surface of the rolling tooth of the planetary gear is established. The envelope of the contact line on the tooth surface of the inner and outer cambered cam is a kind of boundary line, which determines the undercut limit of this kind of transmission, and the second kind of boundary line determines the meshing limit of this kind of transmission. Based on the principle of spatial meshing, the contact line between the curved surface of the rolling tooth on the planetary gear and the inner and outer globoidal cam is deduced, and the tooth profile curved surface equation of the spherical tooth and the inner and outer globoidal cam is analyzed. The boundary curve equation of planetary gear with spherical teeth is studied. By comparing transmission parameters of a/R,

i
1
H

,

i
2
H

, β, and △β, the influence of transmission parameters on the meshing characteristics of globoidal cam transmission of planetary gear train is analyzed. The research in this paper is helpful to realizing the manufacture of a prototype.
Effects of Three Compound Attractants in Plant Protein Diets on Growth, Immunity, and Intestinal Morphology of Yellow River Carp Cyprinus carpio var
Authors: Fang Tingting , Li Xiang , Wang Jiting , Guan Dongyan , Sun Huiwen , Yun Xiao , Zhou Jie
Published: May 2022

A feeding experiment was conducted to evaluate the effects of three compound attractants on the growth performance, immunity, and intestinal morphology of Yellow River (YR) carp. Five treatment groups were included in the feeding experiment. Group I consisted of a fishmeal-based diet (positive control), and group II was a plant protein diet (negative control). The compound attractants 1 (

0.06
%
dimethyl
−
beta
−
propiothetin
 

DMPT

+
0.22
%
tangerine
 
peel
 
powder
+
0.75
%
yeast
 
powder

), 2 (

0.05
%
garlic
 
powder
+
0.06
%
DMPT
+
0.75
%
yeast
 
powder

), and 3 (

0.07
%
sodium
 
glutamate
+
0.22
%
tangerine
 
peel
 
powder
+
0.34
%
betaine

) were added to the plant protein diet, belonging to groups III, IV, and V, respectively. The three different compound attractants significantly improved the weight gain rate, special growth rate, and protein efficiency ratio of Yellow River (YR) carp (

P
<
0.05

) compared with the negative control, among which group III performed best. Similarly, group III had significantly higher serum lysozyme (LZM) and acid phosphatase (ACP) activities than the negative control, and groups III, IV, and V depicted significantly higher LZM activities in the liver and gill (

P
<
0.05

). Groups III, IV, and V revealed significantly higher superoxide dismutase (SOD), catalase (CAT), and total antioxidant capacity (T-AOC) activities in the serum and liver than the negative control (

P
<
0.05

), while the malondialdehyde (MDA) content was the opposite (

P
<
0.05

). Moreover, the height and width of the plica in the foregut and midgut and the thickness of the midgut muscle layer in group III were significantly higher than those in the negative control (

P
<
0.05

). Therefore, adding compound attractants in a plant protein diet can significantly enhance the total antioxidant and immune capacity, along with improved growth performance of YR carp. Similarly, compound attractants significantly elevated the height and width of the intestinal fold within the anterior and middle sections of the intestine, depicting that compound attractants promote intestinal digestion and absorption, thereby reducing intestinal injury. The results from the three experimental groups found that the compound attractants combined with 0.06% DMPT, 0.22% tangerine peel powder, and 0.75% yeast powder were more suitable for the basic plant protein diet of YR carp.
A Model for Surface Defect Detection of Industrial Products Based on Attention Augmentation
Authors: Li Gang , Shao Rui , Wan Honglin , Zhou Mingle , Li Min
Published: May 2022

Detecting product surface defects is an important issue in industrial scenarios. In the actual scene, the shooting angle and the distance between the industrial camera and the shooting object often vary, which results in a large variation in the scale and angle. In addition, high-speed cameras are prone to motion blur, which further deteriorates the defect detection results. In order to solve the above problems, this study proposes a surface defect detection model for industrial products based on attention enhancement. The network takes advantage of the lower-level and higher-resolution feature map from the backbone to improve Path Aggregation Network (PANet) in object detection. This study makes full use of multihead self-attention (MHSA), an independent attention block for enhancing the backbone network, which has made considerable progress for practical application in industry and further improvement of the surface defect detection. Moreover, some tricks have been adopted that can improve the detection performance, such as data augmentation, grayscale filling, and channel conversion of input images. Experiments in this study on internal datasets and four public datasets demonstrate that our model has achieved good performance in industrial scenarios. On the internal dataset, the mAP@.5 result of our model is 98.52%. In the RSDDs dataset, the model in this study achieves 86.74%. In the BSData dataset, the model reaches 82.00%. Meanwhile, it achieves 81.09% and 74.67% on the NRSD-MN and NEU-DET datasets, respectively. This study has demonstrated the effectiveness and certain generalization ability of the model from internal datasets and public datasets.
Hybrid Methods Using Neural Network and Kalman Filter for the State of Charge Estimation of Lithium-Ion Battery
Authors: Cui Zhenhua , Dai Jiyong , Sun Jianrui , Li Dezhi , Wang Licheng , Wang Kai
Published: May 2022

With the increasing carbon emissions worldwide, lithium-ion batteries have become the main component of energy storage systems for clean energy due to their unique advantages. Accurate and reliable state-of-charge (SOC) estimation is a central factor in the widespread use of lithium-ion batteries. This review, therefore, examines the recent literature on estimating the SOC of lithium-ion batteries using the hybrid methods of neural networks combined with Kalman filtering (NN-KF), classifying the methods into Kalman filter-first and neural network-first methods. Then the hybrid methods are studied and discussed in terms of battery model, parameter identification, algorithm structure, implementation process, appropriate environment, advantages, disadvantages, and estimation errors. In addition, this review also gives corresponding recommendations for researchers in the battery field considering the existing problems.
Two new species of Branchinotogluma (Polynoidae: Annelida) from chemosynthesis-based ecosystems in Japan
Authors: JIMI NAOTO , CHEN CHONG , FUJIWARA YOSHIHIRO
Published: May 2022

The widely distributed polychaete family Polynoidae Kinberg, 1856 is found across all oceans and from shallow to deep waters, including deep-sea hydrothermal vents and hydrocarbon seeps. Taxa inhabiting chemosynthesis-based ecosystems are often endemic to those specific habitats commonly targeted by deep-sea mining, and understanding their species diversity is essential for shaping conservation plans. Here, we report two previously undescribed scale-worms in the genus Branchinotogluma Pettibone, 1985 from the Off Hatsushima hydrocarbon seep of Sagami Bay and the Nikko Seamount hydrothermal vent on the Izu-Ogasawara Arc, and describe them as B. nikkoensis sp. nov. and B. sagamiensis sp. nov. Branchinotogluma nikkoensis sp. nov. is distinguished from the known species by the following characters: i) ventral segmental lamellae near ventral bases of neuropodia present on segments 13–17, ii) dorsal tentacular cirri being longer than ventral tentacular cirri, iii) absence of dorsal tubercles. Branchinotogluma sagamiensis sp. nov. can be differentiated from other congeners by i) 20 segments, ii) dorsal tentacular cirri being longer than ventral tentacular cirri, iii) ventral segmental lamellae near ventral bases of neuropodia present on segments 13–18, and iv) thin median antennae. The two new species are distinct in both morphology and four gene sequences from the only two species previously known from Japan including Branchinotogluma japonicus (Miura & Hashimoto, 1991) and B. elytropapillata Zhang, Chen & Qiu, 2018, originally described from Kaikata Seamount vent on the Izu-Ogasawara Arc and Okinawa Trough, respectively
The Nazeris fauna of the Leigong Mountain, Guizhou, China (Coleoptera, Staphylinidae, Paederinae)
Authors: LIN XIAO-BIN , YU DE-HUI , HU JIA-YAO
Published: May 2022

Seven species of Nazeris Fauvel, 1873 are reported for Guizhou, China. All of them are described as new: N. ingentis Lin, Yu & Hu, sp. n., N. resimus Lin, Yu & Hu, sp. n., N. leigongensis Lin, Yu & Hu, sp. n., N. yujiei Lin, Yu & Hu, sp. n., N. muricatus Lin, Yu & Hu, sp. n., N. excertus Lin, Yu & Hu, sp. n. and N. serratus Lin, Yu & Hu, sp. n.
Two new Telebasis Selys, 1865 species (Odonata: Zygoptera: Coenagrionidae) from Western Colombia
Authors: BOTA-SIERRA CORNELIO ANDRÉS , SANDOVAL-H. JULIANA , PÉREZ-GUTIÉRREZ LEÓN
Published: May 2022

Telebasis Selys, 1865 is a genus well represented in Colombia, with 18 species distributed throughout the territory, one of them being endemic to the country. One of the most underexplored biogeographic regions of the country is the Chocó, where we found the two new endemic species of Telebasis here described, Telebasis blasi sp. nov. and Telebasis noveloi sp. nov. In the description of both species, we provide detailed information about their distribution, diagnostic characteristics for males and females, pictures of living specimens and diagnostic characteristics, and a map showing the localities where each species was found. Finally, remarks on the conservation status of these species are presented; we consider that they are probably endangered, since they occupy small ranges and are threatened by several human activities.