bluuebunny/crossref_metadata_2025 huggingface dataset:
Distinct freshwater migratory pathways in Arctic char (Salvelinus alpinus) coincide with separate patterns of marine spatial habitat-use across a large coastal landscape
Authors: Hollins Jack , Pettitt-Wade Harri , Gallagher Colin P. , Lea Ellen V. , Loseto Lisa L. , Hussey Nigel E.
Published: April 2022

Understanding variability in distributions and habitat-use among populations of anadromous salmonids is essential for their sustainable management. Arctic char ( Salvelinus alpinus) is an important cultural and socioeconomic species; however, knowledge of their spatiotemporal habitat-use during the marine phase is limited. Here, a large-scale acoustic telemetry array was used to determine intraspecific variation in Arctic char summer marine habitat-use tied to overwintering lake occurrence in the Amundsen Gulf. Arctic char tagged in the ocean migrated to two main overwintering lakes, corresponding to distinct migration corridors and separate patterns of marine habitat-use, with one individual exhibiting among the longest recorded char marine migration to date (∼330 km). Arctic char that undertook longer migration distances initiated travel in the ocean towards fresh water 11 days earlier than those completing shorter migration distances; mean departure days (±SD) 2 August (±8.1 days) and 13 August (±6.8 days), corresponding to migration distances of 252 and 131 km, respectively. These findings identify that Arctic char from different populations can occupy distinct marine foraging grounds within a region, with consequences for variable interactions with fisheries.
New optical analytical solutions to the full nonlinearity form of the space–time Fokas–Lenells model of fractional-order
Authors: Tripathy Ananya , Sahoo Subhadarshan , Rezazadeh Hadi , Izgi Zehra Pinar
Published: April 2022

In this paper, the full nonlinearity form of the space–time fractional Fokas–Lenells equation is scrutinized to get new analytical solutions. To achieve this, a convenient method is applied namely, a new Kudryashov method. The achieved solutions show pulse propagation in different wave patterns such as singular bell shape, peakon, singular anti-bell shape, dark, anti-bell and bright solutions. These physical characteristics are studied thoroughly by the graphical representation, which shows the fruitfulness and functionality of the proposed method.
A high precision time-multiplexed fully differential interface ASIC for capacitive MEMS accelerometer
Authors: Liu Yuntao , Fang Shuo , Wang Ying , Ma Meijuan , Wang Yun
Published: April 2022

A high precision time-multiplexed fully differential interface Application specific integrated circuit (ASIC) for micromechanical capacitive accelerometer is presented in this paper. A time-multiplexed fully differential capacitor-to-voltage (C-V) converter employs the half-bridge sensing structure and two paralleled single-end charge integrators to substitute the full-bridge or fully differential sensing element and restrain the influence of the common-mode voltage. A time-multiplexed fully differential switch-capacitor (SC) programmable gain amplifier (PGA) with continuous output is proposed, providing continuous signals to the following circuits. The proposed interface is fabricated in a 0.18 [Formula: see text]m CMOS process, occupying an area of [Formula: see text]. The measured results indicate that the total power dissipation is 8.25 mW from a 3.3 V power supply. The noise floor of the accelerometer is 10.5 [Formula: see text]g/Hz1/2, and the achieved figure of merit (FOM, 5.5 pW/Hz) is better than the previously reported works.
Stochastic Stability and Bifurcation of Centrifugal Governor System Subject to Color Noise
Authors: Zhang Jiangang , Liang Xiangling , Qiao Shuai , He Meijuan , An Xinlei
Published: April 2022

This paper presents a detailed investigation of stochastic stability and complex dynamics of a centrifugal governor system with approximately uniform color noise. The centrifugal governor system excited by noise is transformed into Itö equation using polar coordinate transformation and stochastic average method. According to the boundary conditions of attraction and repulsion, the stochastic stability is ensured. In addition, analyses concerning the influence of parameter variation and validity are carried out by employing numerical method. The results manifest that the effects of noise intensity and correlation time on stationary probability density are opposite. The amplitudes of probability density finally tend to a limit value, and the only limit cycle appears, which shows that when the bifurcation occurs, the trivial solution of the system converges to a limit cycle with a higher probability. Finally, the two-dimensional parameter bifurcation analysis of the centrifugal governor system subject to color noise excitation is studied. An interesting distribution characteristic is found that the periodic region is organized according to the sequence of Stern–Brocot trees, and this typical characteristic is a universal characteristic of the system on the two parameter planes. Furthermore, it is concluded that based on the largest Lyapunov exponent diagram and bifurcation diagram in two-dimensional parameter plane, the effects of noise intensity and correlation time on the periodic oscillation state are opposite, but both of them can transform the quasi-periodic oscillation into periodic oscillation. It should be emphasized that with the increase of noise intensity, the coexisting oscillation behavior of the centrifugal governor system will change, which is manifested by the destruction of coexisting attractors and the generation of chaotic attractors.
The Number of Limit Cycles for a Class of Cubic Systems with Multiple Parameters
Authors: Cai Meilan , Han Maoan
Published: April 2022

In this paper, we study the number of limit cycles for a class of cubic systems with general quadratic polynomial perturbations. By using the Melnikov function theory we obtain that five limit cycles can be bifurcated from a period annulus. We also study the Hopf bifurcation at the center surrounded by the annulus.
Evaluating the Randomness of Chaotic Binary Sequences Via a Novel Period Detection Algorithm
Authors: Fan Chunlei , Ding Qun , Tse Chi K.
Published: April 2022

When chaotic systems are applied to stream ciphers, chaotic real-valued sequences generally need to be converted into binary sequences with the purpose of encrypting data. However, the performance of binary sequences will be degraded under the joint influence of round-off and quantization errors. In this case, the randomness of some chaotic binary sequences may be weakened in a local range. Taking advantage of parallel computing, a fast period detection algorithm is designed to locate all local “periodicities” contained in chaotic binary sequences quickly and accurately. This algorithm evaluates the randomness of a chaotic binary sequence from a new perspective of periodicity which enriches the randomness test methods for binary sequences. Different logistic binary sequences are analyzed to demonstrate the effectiveness and practicability of the proposed algorithm.
COVID-19 and Its Effects on the Mental Health of People Living in Urban Slums in India
Authors: Pandey Ghanshyam , Moghal Sheeba , Barodia Rakshit , Carey William
Published: April 2022

The COVID-19 pandemic has had a devastating effect on the mental health of people from different backgrounds; these effects have been particularly acute among the lower-income households and in slums. There has been a steep rise in mental illness and behaviours associated with it since 2020, especially in the slums characterised by poverty, poor housing, high density and unhealthy environments. This paper aims to examine the effect of COVID-19 on the mental health of people living in the slums of Vijayawada and Visakhapatnam in the state of Andhra Pradesh in India. The results of the study confirm that more than three-fourth of people suffer from mental stress due to the spread of COVID-19 and the lockdown imposed by the government. Also, 80% of those surveyed stated that stress affected their decision-making. The study also confirms that the number of dependents, monthly income, number of living rooms, maintenance of physical distancing norms, avoidance of social gatherings, government support, health insurance and living in a rented house are significantly related to the mental stress of people living in the slums in Andhra Pradesh in India.
Evaluating the Impacts of COVID-19 on Operations and Management of Community Centres: An Auckland, New Zealand Case Study
Authors: Petrov Alexander , Omisakin Olufemi Muibi
Published: April 2022

This study evaluates the impact of COVID-19 on the operations and management of Community Centres (CCs) in Auckland. This Coronavirus posed unprecedented challenges to the communities and public facilities here and in many other countries. To mitigate the pandemic outbreak, the New Zealand government adopted the so-called “go hard, go early” strategy, which put all of the country to strict self-isolation for 52 days [Baker et al. (2020). The Medical Journal of Australia, 213(5), 198–200.e1]. This research aims to explore what challenges some of Auckland’s CCs faced during COVID-19 lockdown and what management decisions were taken to operate the CCs during these periods effectively. The study was based principally on primary data collected from the managers and visitors of eight CCs across Auckland via semi-structured interviews and anonymous online surveys. With all the information gathered and generated through thematic, correlation and deductive analysis, the study produced a “road map” for management actions. This framework should enable CCs to better articulate decisions for more effective and safer operating during future pandemic outbreaks.
Cyclic cubic extensions of ℚ
Authors: Majumdar Dipramit , Sury B.
Published: April 2022

We determine the irreducible trinomials [Formula: see text] for integers [Formula: see text] which generate precisely all possible Galois extensions of degree [Formula: see text] over [Formula: see text]. The proof, although involved, is elementary and one can parametrize all these polynomials explicitly. As an accidental by-product of the results, we prove that infinitely many primes congruent to [Formula: see text] or [Formula: see text] mod [Formula: see text] are sums of two rational cubes - thereby, giving the first unconditional result on a classical open problem.
A mixed reality simulation evaluation method for complex system
Authors: Wang Lijun , Xue Yang , Lv Yi , Wu Yufen , Wang Dawei , Xu Shuhong
Published: April 2022

In order to analyze the proposed method, this paper takes the cockpit as the complex system, since the traditional cockpit design evaluation method can set up an actual engineering prototype. Although this method can realize the accurate evaluation of the internal structure layout, control devices, and interface display of the cockpit, it is difficult to make modifications once the production is completed, which is not suitable for multi-scheme comparison and rapid iteration in the early stage of civil aircraft design. In this regard, this paper establishes the civil aircraft cockpit physical environment and the corresponding virtual cockpit environment based on the virtual-real matching technology, then proposes a mixed reality simulation evaluation method so as to realize the real-time ergonomic evaluation of the digital human body followed by a real person. Experimental results show that this mixed reality simulation evaluation method can effectively improve the evaluation accuracy of cockpit design, ensure the efficiency of multi-scheme comparison and optimization iteration in the early stage of cockpit design.
Resistance Mechanisms to Anti-PD Cancer Immunotherapy
Authors: Vesely Matthew D. , Zhang Tianxiang , Chen Lieping
Published: April 2022

The transformative success of antibodies targeting the PD-1 (programmed death 1)/B7-H1 (B7 homolog 1) pathway (anti-PD therapy) has revolutionized cancer treatment. However, only a fraction of patients with solid tumors and some hematopoietic malignancies respond to anti-PD therapy, and the reason for failure in other patients is less known. By dissecting the mechanisms underlying this resistance, current studies reveal that the tumor microenvironment is a major location for resistance to occur. Furthermore, the resistance mechanisms appear to be highly heterogeneous. Here, we discuss recent human cancer data identifying mechanisms of resistance to anti-PD therapy. We review evidence for immune-based resistance mechanisms such as loss of neoantigens, defects in antigen presentation and interferon signaling, immune inhibitory molecules, and exclusion of T cells. We also review the clinical evidence for emerging mechanisms of resistance to anti-PD therapy, such as alterations in metabolism, microbiota, and epigenetics. Finally, we discuss strategies to overcome anti-PD therapy resistance and emphasize the need to develop additional immunotherapies based on the concept of normalization cancer immunotherapy.
Instructive Cues of Thymic T Cell Selection
Authors: Irla Magali
Published: April 2022

A high diversity of αβ T cell receptors (TCRs), capable of recognizing virtually any pathogen but also self-antigens, is generated during T cell development in the thymus. Nevertheless, a strict developmental program supports the selection of a self-tolerant T cell repertoire capable of responding to foreign antigens. The steps of T cell selection are controlled by cortical and medullary stromal niches, mainly composed of thymic epithelial cells and dendritic cells. The integration of important cues provided by these specialized niches, including ( a) the TCR signal strength induced by the recognition of self-peptide-MHC complexes, ( b) costimulatory signals, and ( c) cytokine signals, critically controls T cell repertoire selection. This review discusses our current understanding of the signals that coordinate positive selection, negative selection, and agonist selection of Foxp3+regulatory T cells. It also highlights recent advances that have unraveled the functional diversity of thymic antigen-presenting cell subsets implicated in T cell selection.
Functional Hallmarks of Healthy Macrophage Responses: Their Regulatory Basis and Disease Relevance
Authors: Sheu Katherine M. , Hoffmann Alexander
Published: April 2022

Macrophages are first responders for the immune system. In this role, they have both effector functions for neutralizing pathogens and sentinel functions for alerting other immune cells of diverse pathologic threats, thereby initiating and coordinating a multipronged immune response. Macrophages are distributed throughout the body—they circulate in the blood, line the mucosal membranes, reside within organs, and survey the connective tissue. Several reviews have summarized their diverse roles in different physiological scenarios and in the initiation or amplification of different pathologies. In this review, we propose that both the effector and the sentinel functions of healthy macrophages rely on three hallmark properties: response specificity, context dependence, and stimulus memory. When these hallmark properties are diminished, the macrophage's biological functions are impaired, which in turn results in increased risk for immune dysregulation, manifested by immune deficiency or autoimmunity. We review the evidence and the molecular mechanisms supporting these functional hallmarks.
In Situ Construction of Hierarchical Nanoflower-Like MnO2/Biomass-Based Boron-Doped Carbon Spheres for Oxygen Evolution Reaction
Authors: Dong Guohua , Sun Beibei , Su Ting , Hao Lijuan , Chai Dong-feng , Zhang Wenzhi , Zhang Zhuanfang , Zhao Ming , Li Jinlong
Published: April 2022

Herein, a novel boron doped carbon sphere (BCS) and its derived MnO2 nanocomposite electrode (abbreviated as MnO2/BCS) are firstly prepared via a facile hydrothermal strategy, which was successfully confirmed via a combined characterization including SEM, TEM, EDS, FT-IR, Raman and XPS. Due to the introduction of BCS, the MnO2/BCS shows hierarchical nanoflower-like morphology with a smaller particle size and higher specific surface area than that of pristine MnO2. Importantly, the resultant MnO2/BCS with proper addition of BCS displays superior OER performance than those of the pristine MnO2. The electrochemical measurement results demonstrate that the optimal MnO2/BCS0.08 can give rise to a lowest overpotential mere 170 mV at 10 mA·cm−2, onset potential reaching 1.33 V together with smallest Tafel slope value of 31.43 mV dec−1, which can be mainly due to the higher conductivity, faster charge transfer kinetics and higher electrocatalytic active sites of the MnO2/BCS0.08 than those of other counterparts. Undoubtedly, the incorporation of BCS is mainly responsible for the enhanced electrocatalytic activity. Furthermore, the MnO2/BCS0.08 also has a prominent long-term stability in alkaline conditions. In conclusion, our present work demonstrates an effective strategy to enhance the OER performance of MnO2 by incorporation of the carbon nanomaterials.
Electrocatalytic Oxidation of Methanol Over Silver-Based Ag-M/C (M = Cu, Zn, Fe, Cr, Mn) Electrocatalysts Synthesized by Solution Combustion Technique
Authors: Logade Khulood , Shafath Sadiyah , Kumar Anand , Reesh Ibrahim Abu
Published: April 2022

Herein, we report the electrocatalytic properties of Ag-M/C (M = Cu, Zn, Fe, Cr, Mn) catalysts synthesized using solution combustion synthesis (SCS) method for methanol oxidation reaction (MOR). The morphological properties of the synthesized catalysts were studied using SEM, EDX, TEM, XRD and XPS techniques. The results indicated AgCu/C to be the most porous catalyst with small and well distributed nanoparticles making it a suitable choice for electrocatalytic applications. The XPS results showed a shift in peak in the AgCu/C sample due to the charge transfer between Ag and Cu indicating a strong interaction in the compound. The electrochemical measurements in 1 M methanol with 1 M KOH electrolyte by cyclic voltammetry (CV) and linear sweep voltammetry (LSV) revealed that AgCu/C showed high electrocatalytic activity for MOR. Further studies on AgCu/C for methanol concentrations of 0.5 M, 1 M, 1.5 M, 2.5 M to evaluate the rate dependency of the catalyst indicated a power-law dependency with an order of 0.55 on methanol concentration. According to chronoamperometry analysis, the catalyst was stable for at least 20 h.
Giant Dielectric Response of Corundum Structure Fe0.7Cr1.3O3 Nanocrystallite
Authors: Gatchakayala Naresh Babu , Rama Sekhara Reddy D.
Published: April 2022

We report the structure and dielectric properties of Fe0.7Cr1.3O3 nanocrystallites synthesized by co-precipitation method. X-ray diffraction shows that the nanoparticles possess a typical corundum structure and no other impurity phases are observed. These nanoparticles exhibit a high dielectric permittivity (ε′ ∼ 103) at room temperature below 1 kHz. The dielectric relaxation follows the thermally activated process with activation energy of 0.226 eV. Both components of grain relaxation and grain boundary relaxation times were extracted from modulus spectra. The internal barrier layer capacitance (IBLC) effect is responsible for observed high dielectric response in these nanoparticles.
Diagnostic Accuracy of Salivary Biomarkers including Lactate Dehydrogenase and Hemoglobin A1c for Screening Chronic Periodontitis
Authors: Ansari Moghadam Somaye , Ahmadi Moghadam Fateme Soude , Alijani Ebrahim
Published: April 2022

Aims: Periodontitis is one of the most common chronic bacterial infections in humans involving the tooth-supporting tissue. The present study aimed to evaluate and compare salivary biomarkers, including lactate dehydrogenase (LDH) and hemoglobin A1c (HbA1c), between patients with severe chronic periodontitis and healthy individuals. Methods: This study was performed on 29 patients with severe chronic periodontitis and 30 healthy individuals at Zahedan University of Medical Sciences, Zahedan, Iran, in 2021. Salivary samples were taken, and clinical parameters, including the clinical attachment loss (CAL) and probing pocket depth (PPD), were measured. Besides, the levels of LDH and HbA1c were measured using ELISA kits. The sensitivity, specificity, and positive and negative predictive values of HbA1c and LDH were examined for chronic periodontitis diagnosis. Results: Based on the present results, the levels of LDH and HbA1C did not show adequate sensitivity or specificity for screening chronic periodontitis. Conclusion: According to the present findings, salivary biomarkers, including LDH and HbA1c, cannot be used with certainty for screening chronic periodontitis.
On Generalized Topological Indices for Some Special Graphs
Authors: Afridi Sheeba , Yasin Khan Muhammad , ALi Gohar
Published: April 2022

Topological indices are numeric values associated with a graph and characterize its structure. There are various topological indices in graph theory such as degree‐based, distance‐based, and counting‐related topological indices. Among these indices, degree‐based indices are very interesting and studied well in literature. In this work, we studied the generalized form of harmonic, geometric‐arithmetic, Kulli–Basava indices, and generalized power‐sum‐connectivity index for special graph that are bridge graph over path, bridge graph over cycle, bridge graph over complete graph, wheel graph, gear graph, helm graph, and square lattice graph. We found exact values for the stated indices and for the stated special graphs. We also investigated the generalized form of the indices for various properties of alkane isomers, from which we obtained interesting results which are closed to that of experimental obtained results.
Performance of Machine Learning and Image Processing in Plant Leaf Disease Detection
Authors: Zamani Abu Sarwar , Anand L. , Rane Kantilal Pitambar , Prabhu P. , Buttar Ahmed Mateen , Pallathadka Harikumar , Raghuvanshi Abhishek , Dugbakie Betty Nokobi
Published: April 2022

The aim of this study is to evaluate infected leaf disease images. Precision agriculture's automatic leaf disease detection system employs image acquisition, image processing, image segmentation, feature extraction, and machine learning techniques. An automated disease detection system offers the farmer with a fast and accurate diagnosis of the plant disease. Automation of plant leaf disease detection system is essential for accelerating crop diagnosis. Using machine learning and image processing, this paper describes a framework for detecting leaf illness. An image of a leaf can be used as an input for this framework. To begin, leaf photographs are preprocessed in order to remove noise from their images. The mean filter is used to filter out background noise. Histogram equalization is used to enhance the quality of the image. The division of a single image into multiple portions or segments is referred to as segmentation in photography. It assists in establishing the boundaries of the image. Segmenting the image is accomplished using the K-Means approach. Feature extraction is carried by using the principal component analysis. Following that, images are categorized using techniques such as RBF-SVM, SVM, random forest, and ID3.
Effect of Big Data Analysis-Based Remote Management Combined with Yangyin Runfei Decoction on Coagulation Function, Pulmonary Function, and Quality of Life of Pulmonary Tuberculosis Patients
Authors: Jin Haihao
Published: April 2022

Objective. To explore the effect of big data analysis-based remote management combined with Yangyin Runfei decoction on coagulation function, pulmonary function, and quality of life (QOL) of pulmonary tuberculosis (PTB) patients. Methods. A total of 90 PTB patients treated in our hospital from May 2019 to May 2020 were selected as the subjects and divided into the experimental group (EG) and control group (CG) according to their admission order, with 45 cases each. Patients in CG accepted routine management and treatments and those in EG received big data analysis-based remote management combined with Yangyin Runfei decoction, so as to compare the clinical indicators between the two groups. Results. Compared with CG after treatment, EG presented an obviously higher total clinical effective rate, various pulmonary function indicators, and GQOLI-74 score (

P
<
0.001

) and significantly lower various coagulation indicators and inflammatory factor indicators (

P
<
0.001

). Conclusion. Performing big data analysis-based remote management combined with Yangyin Runfei decoction to PTB patients can effectively improve their QOL and pulmonary function and present a higher application value compared to routine management and treatments. Further research will be conducive to establishing a better solution for patients. This trial is registered with Clinical Study Registration Number: https://clinicaltrials.gov/ct2/show/ChiCTR2200057257.
Tail Risk in the Chinese Vegetable Oil Market: Based on the EGAS‐EVT Model
Authors: Zhang Yueqiang , Han Guanghui , Xie Hui , Wang Zixing
Published: April 2022

This paper uses extreme value theory and exponential generalised autoregressive score models to estimate the tail extremes of financial return series. The peak‐over‐threshold method based on the generalised pareto distribution is combined with the EGAS models and the nonparametric quantile method is used to determine the thresholds in the POT method, which is used to calculate the value‐at‐risk of financial markets and to perform backtesting. The empirical analysis was conducted on the soybean oil, rapeseed oil, and palm oil futures indices in the Chinese futures market. The study demonstrated that the EGAS‐POT models based on nonparametric quantile thresholds can effectively characterise tail risk and provide a feasible measure of risk for investors.
Object-Specific Four-Path Network for Stroke Risk Stratification of Carotid Arteries in Ultrasound Images
Authors: Ma Wei , Xia Yujiao , Wu Xiaoyan , Yue Zheng , Cheng Xinyao , Fenster Aaron , Ding Mingyue
Published: April 2022

Atherosclerotic carotid plaques have been shown to be closely associated with the risk of stroke. Since patients with symptomatic carotid plaques have a greater risk for stroke, stroke risk stratification based on the classification of carotid plaques into symptomatic or asymptomatic types is crucial in diagnosis, treatment planning, and medical treatment monitoring. A deep learning technique would be a good choice for implementing classification. Usually, to acquire a high-accuracy classification, a specific network architecture needs to be designed for a given classification task. In this study, we propose an object-specific four-path network (OSFP-Net) for stroke risk assessment by integrating ultrasound carotid plaques in both transverse and longitudinal sections of the bilateral carotid arteries. Each path of the OSFP-Net comprises of a feature extraction subnetwork (FE) and a feature downsampling subnetwork (FD). The FEs in the four paths use the same network structure to automatically extract features from ultrasound images of carotid plaques. The FDs use different object-specific pooling strategies for feature downsampling based on the observation that the sizes and shapes in the feature maps obtained from FEs should be different. The object-specific pooling strategies enable the network to accept arbitrarily sized carotid plaques as input and to capture a more informative context for improving the classification accuracy. Extensive experimental studies on a clinical dataset consisting of 333 subjects with 1332 carotid plaques show the superiority of our OSFP-Net against several state-of-the-art deep learning-based methods. The experimental results demonstrate better clinical agreement between the ground truth and the prediction, which indicates its great potential for use as a risk stratification and as a monitoring tool in the management of patients at risk for stroke.
Blockchain Empowers Chain Enterprises in the Digital Economy to Strengthen Risk Management Research
Authors: Su Weiwei
Published: April 2022

With the vigorous development of blockchain technology, researches on various “blockchain+” scenarios continue to bring forth new ideas. As some of the characteristics of the blockchain technology itself deeply meet the demands of the development of chain enterprises, it can better control the related risks of enterprises. Therefore, it is necessary to combine the characteristics of blockchain technology with the characteristics of chain enterprise risks and the interaction mechanism for research. This article aims to study how to strengthen risk management for chain enterprises in the digital economy. For this reason, this article proposes a method to empower the digital economy through the blockchain and calculates and analyzes the risk measurement so that it can effectively estimate the risk. This article also designs an experimental analysis to explore its effect. The experimental results of this paper show that after the improvement, the risk of chain enterprises is reduced by 35%, and the risk is effectively controlled.
Genome-Wide Identification and Functional Analysis of Lysine Histidine Transporter (LHT) Gene Families in Maize
Authors: Rabby Md. Golam , Hossen Md. Munnaf , Kamal Md. Mostafa , Islam Md. Numan
Published: April 2022

Amino acid transporters (AATs) are essential membrane proteins that transfer amino acids across cells. They are necessary for plant growth and development. The lysine histidine transporter (LHT) gene family in maize (Zea mays) has not yet been characterized. According to sequence composition and phylogenetic placement, this study found 15 LHT genes in the maize genome. The ZmLHT genes are scattered across the plasma membrane. The study also analyzed the evolutionary relationships, gene structures, conserved motifs, 3D protein structure, a transmembrane domain, and gene expression of the 15 LHT genes in maize. Comprehensive analyses of ZmLHT gene expression profiles revealed distinct expression patterns in maize LHT genes in various tissues. This study’s extensive data will serve as a foundation for future ZmLHT gene family research. This study might make easier to understand how LHT genes work in maize and other crops.
Optimization of University Financial Services Using the Blockchain Technology
Authors: Yang Guixing
Published: April 2022

At present, the financial work of most colleges and universities is facing the dilemma of low intelligence level. The financial sharing mode of colleges and universities using blockchain technology can effectively supervise their financial management while solving the problems of high costs related to financial sharing services, hidden dangers of data security, and low efficiency. Therefore, this paper makes an in-depth study on the application of blockchain technology and the financial sharing service mode of colleges and universities. Firstly, the University Financial Sharing Service Center platform based on blockchain technology is constructed. Furthermore, each module of the service center platform is described. Combined with the constructed platform, university finance is deeply mined by using the mining algorithm based on certain association rules, which is convenient for effective management. Finally, an artificial intelligence algorithm is used to adaptively optimize financial management. Similarly, the planning model and fitting algorithm of the least square method are used to control the risk of the financial management so as to realize the optimization of the financial sharing service mode. The experiment results demonstrate that the proposed method can effectively improve the efficiency of the financial sharing service and reduce the potential safety problems and costs of financial management.
Intelligent Monitoring System Based on Noise-Assisted Multivariate Empirical Mode Decomposition Feature Extraction and Neural Networks
Authors: Zhao Le Fa , Siahpour Shahin , Haeri Yazdi Mohammad Reza , Ayati Moosa , Zhao Tian Yu
Published: April 2022

Because of the nonlinearity and nonstationarity in the vibration signals of some rotating machinery, the analysis of these signals using conventional time- or frequency-domain methods has some drawbacks, and the results can be misleading. In this paper, a couple of features derived from multivariate empirical mode decomposition (MEMD) are introduced, which overcomes the shortcomings of the traditional features. A wind turbine gearbox and its bearings are investigated as rotating machinery. In this method, two types of feature structures are extracted from the decomposed signals resulting from the MEMD algorithm, called intrinsic mode function (IMF). The first type of feature vector element is the energy moment of effective IMFs. The other type of vector elements is amplitudes of a signal spectrum at the characteristic frequencies. A correlation factor is used to detect effective IMFs and eliminate the redundant IMFs. Since the basic MEMD algorithm is sensitive to noise, a noise-assisted extension of MEMD, NA-MEMD, is exploited to reduce the effect of noise on the output results. The capability of the proposed feature vector in health condition monitoring of the system is evaluated and compared with traditional features by using a discrimination factor. The proposed feature vector is utilized in the input layer of the classical three-layer backpropagation neural network. The results confirm that these features are appropriate for intelligent fault detection of complex rotating machinery and can diagnose the occurrence of early faults.
Fekete‐Szegö Functional for Bi‐univalent Functions Related with Gegenbauer Polynomials
Authors: Ahmad Ibrar , Ali Shah Syed Ghoos , Hussain Saqib , Darus Maslina , Ahmad Babar
Published: April 2022

In this paper, we introduce and investigate a new subclass of bi‐univalent functions related with generating function of Gegenbauer polynomials. We will mainly find bounds on Maclaurin series coefficients for functions belonging to this class. We also study the famous Fekete‐Szegö type problem for this subclass which is obtained. We will also point out many special cases as corollaries.
Preventive Effect of Intensive Nursing Intervention of Deep Vein Thrombosis of Lower Extremities in Elderly Patients with Gastrointestinal Tumors after Surgery
Authors: Li Yan , Xiao Fei
Published: April 2022

Tumors of the gastrointestinal system, known as gastroenteropapillary neoplasms, are very uncommon yet have a high propensity to progress to cancer. Thromboembolism of the veins (VTE) is a potentially deadly complication of surgery. In the vast majority of cases, deep vein thrombosis (DVT) in the lower extremities is the primary symptom of VTE (DVT). Deep vein thrombosis is more common in critical care units, where the prevalence ranges from 18 to 50 percent. DVT is a common complication after gastrointestinal tumor surgery, and proper nursing care is essential to lowering the risk of VTE. This research was thus done to examine if intensive nursing interventions may reduce the risk of lower limb DVT in elderly patients who had undergone surgery for gastrointestinal malignancies. The data is separated into two categories: control and treatment. As a self-care theory-based intervention strategy, we propose a hybridized KAP (knowledge, attitude, and practice) approach. Using the twin-bound decision tree algorithm (TBDTA), clinical outcomes including survival and patient satisfaction are examined. There was a considerable improvement in the treatment of DVT compared to the control group and a decrease in typical postoperative conditions. The bundles of care treatment have made a significant increase in the quality of nursing care.
A Hybrid Selection Strategy Based on Traffic Analysis for Improving Performance in Networks on Chip
Authors: Trik Mohammad , Molk Ali Mohammad Norouzzadeh Gil , Ghasemi Fatemeh , Pouryeganeh Pourya
Published: April 2022

Networks on chip (NoCs) are an idea for implementing multiprocessor systems that have been able to handle the communication between processing cores, inspired by computer networks. Efficient nonstop routing is one of the most significant applications of NOC. In fact, there are different routes to reach from one node to another node in these networks; therefore, there should be a function that can help to build the best route to reach the destination. In the current study, a new hybrid algorithm scored regional congestion-aware and neighbors-on-path (ScRN) is introduced to choose better output channel and thus improve NOC performance. Having utilized the ScRN algorithm, first an analyzer is used to inspect the traffic packets, and then the NoC traffic locality or nonlocality is determined based on the number of the hops. Finally, if the traffic is local, a scoring technique will choose better output channel; however, if the traffic is nonlocal, the best output channel will be chosen based on a particular parameter introduced here as well as the system status using NoP or RCA selection functions. In the end, via Nirgam simulation, the proposed approach was assessed in traffic scenarios through various selection functions. The simulation results showed that the solution was more successful in terms of delay time, throughput, and energy consumption in comparison to other solutions. It showed a reduction of 38% in packet latency, and the throughput increased by 20%. By considering these two parameters, energy consumption decreased by 10% on average.
Causes of Mortality in Korean Patients with Neurodegenerative Dementia
Authors: Choi Hyo Geun , Park Bumjung , Kim Ji Hee , Kim Joo-Hee , Kwon Mi Jung , Kim Miyoung
Published: April 2022

The prevalence of neurodegenerative dementia is increasing owing to the rapid growth of the older population. We investigated risks and causes of mortality in Korean patients with neurodegenerative dementia using data from the Korean Health Insurance Review and Assessment Service‐National Sample Cohort with the aim to improve their care. From a pool of 1,125,691 patients, 11,215 patients aged ≥60 years who were diagnosed with dementia between 2002 and 2013 were examined along with 44,860 matched controls. A Cox proportional hazard model was used to calculate crude and adjusted hazard ratios (HRs). During the follow‐up period, 34.5% and 18.8% of individuals in the neurodegenerative dementia and control groups, respectively, died (P < 0.001). The adjusted HR for mortality in the neurodegenerative dementia group was 2.11 (2.41 and 1.96 in men and women, respectively). Moreover, the adjusted HRs in patients with neurodegenerative dementia were 3.25, 2.77, and 1.84 for those diagnosed at ages 60–69, 70–79, and ≥80 years, respectively. The highest odds ratio for mortality was noted among patients with neurologic disease (15.93) followed by those with mental disease (4.89). These data show that the risk of mortality increased regardless of age and sex in Korean patients with neurodegenerative dementia.
Three‐Dimensional Expansion and Graphical Concept of Generalized Triangular Fuzzy Set
Authors: Yun Yong Sik
Published: April 2022

We have studied the extended algebraic operations between two fuzzy numbers and calculated Zadeh’s max‐min composition operator for two generalized triangular fuzzy sets in ℝ2. And we generalized the triangular fuzzy numbers from ℝ2 to ℝ3. We prove that the result of the three‐dimensional case is an extension of two‐dimensional case and presented it in a graph. The extension is proved by showing that the result obtained by restricting the three‐dimensional result to two‐dimensional result is consistent with the existing two‐dimensional result.
Antibiotics Resistance in Escherichia coli Isolated from Livestock in the Emirate of Abu Dhabi, UAE, 2014–2019
Authors: Abdelwahab Ghada Elderdiri , Ishag Hassan Zackaria Ali , Al Hammadi Zulaikha Mohamed , Al Yammahi Saeed Mohamed S , Mohd Yusof Mohd Faoruk Bin , Al Yassi Muna Sayed Y. , Al neyadi Shaikha Saeed A. , Al Mansoori Asma Mohammed A. , Al Hamadi Fawzia Hassan A. , Al Hamadi Ibtesam Abdullah S. , Hosani Mohamed Ali Abdalla Al , Mohammed Al Muhairi Salama Suhail
Published: April 2022

Escherichia coli (E. coli) is a zoonotic pathogen that showed growing resistance to antibiotics. No descriptive analysis highlights the threat of antimicrobial-resistant (AMR) of E. coli among livestock in the United Arab Emirates (UAE). Herein, we conducted phenotypic and genotypic resistance studies on E. coli isolates from livestock samples in the Emirate of Abu Dhabi based on routine diagnosis between the periods 2014–2019. Bacterial culture and disk diffusion methods were used for bacterial isolation and phenotypic resistance analysis. Resistance mechanism was studied by PCR targeting the most commonly resistance genes: ampicillin (blaSHV, blaCMY, and blaTEM-1B), tetracyclines (tetA and tetB), co-trimoxazole [sulfamethoxazole (sul1, sul2, and sul3) + trimethoprim (dfrA1 and dfrA17)], aminoglycosides [aph(3'')-Ia, aph(6)-Id, and aac(3)-IV], and fluoroquinolones (qnrA and aac(6’)-Ib-cr). Analysis of 165 E. coli isolates showed resistant to ampicillin, tetracycline, co-trimoxazole, gentamicin, and enrofloxacin by 157/165 (95.4%), 154/165 (93.6%), 141/165 (86%), 139/165 (85%), and 135/165 (82.7%), respectively. Predominant resistance gene/s detected by PCR were blaCMY (119/160, 72%) and blaTEM-1B (154/160, 96.3%) for ampicillin; tetA (162/164, 98.8%) and tetB (112/164, 68.3%) for tetracyclines; sul2 (156/164, 95%), sul3 (138/164, 84%), and dfra17 (74/164, 44.5%) for co-trimoxazole; aph(3'')-Ia (134/164, 82.1%) and aph(6)-Id (161/164, 98.2%) for aminoglycosides; and aac(6’)-Ib-cr (61/61, 100%) for enrofloxacin. Both phenotypic and genotypic analyses revealed that all E. coli isolates were multidrug-resistant (resistance to 3, 4, and 5 antibiotics classes by 3.6%, 57.6%, and 38.8%, respectively) carrying one or more resistance gene/s for the same antibiotic. PCR profiling confirmed the presence of resistance genes corresponding to their antibiotic profile. Results of the study will highlight the knowledge based on E. coli AMR related to livestock in UAE that may call for interventions.
Effectiveness of a Soft Robotic Glove to Assist Hand Function in Stroke Patients: A Cross-Sectional Pilot Study
Authors: Thimabut Wachirayongyot , Terachinda Pim , Kitisomprayoonkul Wasuwat
Published: April 2022

Purpose. Stroke patients have difficulty performing tasks using their paretic hands. There are limited data on the effects of using a soft robotic glove to assist with hand function. The objective of this study was to investigate the effectiveness of a soft robotic glove in assisting hand function in stroke patients. Methods. This study was a cross-sectional pilot study. Twenty stroke patients with partial or complete hand weakness were recruited from a rehabilitation centre. The Box and Block Test (BBT) and the Action Research Arm Test (ARAT) were performed under two conditions: with and without use of the soft robotic glove. The order of the conditions was randomly assigned by a computer-generated program. Results. BBT scores increased 6.4 blocks when using the soft robotic glove (

p
<
0.001

). ARAT grasp, grip, pinch, and overall scores increased by 27.08% (

p
<
0.01

), 28.75% (

p
<
0.001

), 15.89% (

p
<
0.01

), and 21.15% (

p
<
0.001

), respectively, using the glove versus not using the glove. Conclusions. The findings of this study suggest that using a soft robotic glove can assist a poststroke paretic hand in executing grasp, grip, and pinch.
Inverse Scattering Transform for the Generalized Derivative Nonlinear Schrödinger Equation via Matrix Riemann–Hilbert Problem
Authors: Fang Fang , Hu Beibei , Zhang Ling
Published: April 2022

The inverse scattering transformation for a generalized derivative nonlinear Schrödinger (GDNLS) equation is studied via the Riemann–Hilbert approach. In the direct scattering process, we perform the spectral analysis of the Lax pair associated with a

2
×
2

matrix spectral problem for the GDNLS equation. Then, the corresponding Riemann–Hilbert problem is constructed. In the inverse scattering process, we obtain an N-soliton solution formula for the GDNLS equation by solving the Riemann–Hilbert problem with the reflection-less case. In addition, we express the N-soliton solution of the GDNLS equation as determinant expression.
The Effect of Oral Mucosal Mesenchymal Stem Cells on Pathological and Long‐Term Outcomes in Experimental Traumatic Brain Injury
Authors: Dehghanian Fatemeh , Soltani Zahra , Farsinejad Alireza , Khaksari Mohammad , Jafari Elham , Darakhshani Ali , Sabet Nazanin , Bashiri Hamideh
Published: April 2022

Background. Neuroprotective effects of stem cells have been shown in some neurologic diseases. In this study, the effect of oral mucosal mesenchymal stem cells (OMSCs) on traumatic brain injury (TBI) was evaluated in long term. Materials and Methods. TBI was induced by Marmarou’s method. The number of 2 × 106 OMSCs was intravenously injected 1 and 24 h after the injury. Brain edema and pathological outcome were assessed at 24 h and 21 days after the injury. Besides, long‐term neurological, motor, and cognitive outcomes were evaluated at days 3, 7, 14, and 21 after the injury. Results. OMSCs administration could significantly inhibit microglia proliferation, and reduce brain edema and neuronal damage, at 24 h and 21 days after the injury. Neurological function improvement was observed in the times evaluated in OMSCs group. Cognitive and motor function dysfunction and anxiety‐like behavior were prevented especially at 14 and 21 days after the injury in the treatment group. Conclusion. According to the results of this study, OMSCs administration after TBI reduced brain edema and neuronal damage, improved neurologic outcome, and prevented memory and motor impairments and anxiety‐like behavior in long term.
Seahorse Protein Hydrolysate Ameliorates Proinflammatory Mediators and Cartilage Degradation on Posttraumatic Osteoarthritis with an Obesity Rat Model
Authors: Sudirman Sabri , Tseng Po-Sheng , Chen Chun-Kai , Tsou David , Kong Zwe-Ling
Published: April 2022

Osteoarthritis (OA) is one of the age‐related diseases and is highly present on the knees. Obesity and mechanical injuries as a risk factor of OA are attributed to cartilage disintegration, joint loading, and inflammation. This study is aimed at investigating the effects of seahorse protein hydrolysate (SH) on posttraumatic osteoarthritis in an obesity rat. The OA model was developed by anterior cruciate ligament transection with medial meniscectomy in a high‐fat diet‐ (HFD‐) induced obesity rat model. The male Sprague‐Dawley rats were fed a HFD for 6 weeks before OA surgery. The OA rats were treated with oral gavage by 4, 8, or 20 mg/kg of body weight of SH for 6 weeks of treatment. The expressions of plasma proinflammatory factors, C‐telopeptide of type II collagen, and matrix metalloproteinase‐ (MMP‐) 3 and MMP‐13 were reduced by SH treatment. Plasma superoxide dismutase and glutathione peroxidase activities were enhanced by SH. SH also relieved the pain of the knee joint and swelling as well as decreased proteoglycan loss in the knee articular cartilage caused by osteoarthritis. Based on these results, SH suppressed proinflammatory factors and attenuated cartilage degradation and pain in the OA model. Therefore, seahorse protein hydrolysate might be a potential opportunity for improving the development of osteoarthritis.