bluuebunny/crossref_metadata_2025 huggingface dataset:
Wharton’s Jelly-Derived Mesenchymal Stem Cells with High Aurora Kinase A Expression Show Improved Proliferation, Migration, and Therapeutic Potential
Authors: Kim Sun Jeong , Park Sang Eon , Jeong Jang Bin , Oh Shin Ji , Choi Alee , Kim Yun Hee , Choi Suk-joo , Oh Soo-young , Ryu Gyu Ha , Jeon Hong Bae , Chang Jong Wook
Published: April 2022

Mesenchymal stem cells (MSCs) are effective therapeutic agents that contribute to tissue repair and regeneration by secreting various factors. However, donor-dependent variations in MSC proliferation and therapeutic potentials result in variable production yields and clinical outcomes, thereby impeding MSC-based therapies. Hence, selection of MSCs with high proliferation and therapeutic potentials would be important for effective clinical application of MSCs. This study is aimed at identifying the upregulated genes in human Wharton’s jelly-derived MSCs (WJ-MSCs) with high proliferation potential using mRNA sequencing. Aurora kinase A (AURKA) and dedicator of cytokinesis 2 (DOCK2) were selected as the upregulated genes, and their effects on proliferation, migration, and colony formation of the WJ-MSCs were verified using small interfering RNA (siRNA) techniques. mRNA expression levels of both the genes were positively correlated with the proliferation capacity of WJ-MSCs. Moreover, AURKA from human WJ-MSCs regulated the antiapoptotic effect of skeletal muscle cells by upregulating the chemokine (C motif) ligand (XCL1); this was further confirmed in the mdx mouse model. Taken together, the results indicated that AURKA and DOCK2 can be used as potential biomarkers for proliferation and migration of human WJ-MSCs. In particular, human WJ-MSCs with high expression of AURKA might have therapeutic efficacy against muscle diseases, such as Duchenne muscular dystrophy (DMD).
Chimp Optimization Algorithm to Optimize a Convolutional Neural Network for Recognizing Persian/Arabic Handwritten Words
Authors: Khosravi Sara , Chalechale Abdolah
Published: April 2022

Handwritten character recognition is an attractive subject in computer vision. In recent years, numerous researchers have implemented techniques to recognize handwritten characters using optical character recognition (OCR) approaches for many languages. One the most common methods to improve the OCR accuracy is based on convolutional neural networks (CNNs). A CNN model contains several kernels accompanying with pooling layers and nonlinear functions. This model overcomes the problem of adjusting the value of weights and interconnections of the neural network (NN) for creating an appropriate pipeline to process the spatial and temporal information. However, the training process of a CNN is a challenging issue. Various optimization strategies have been recently utilized for optimizing CNN’s biases and weights such as firefly algorithm (FA) and ant colony optimization (ACO) algorithms. In this study, we apply a well-known nature-inspired technique called chimp optimization algorithm (ChOA) to train a classical CNN structure LeNet-5 for Persian/Arabic handwritten recognition. The proposed method is tested on two known and publicly available handwritten word datasets. To deeply investigate and evaluate the approach, the results are compared with three optimization methods including ACO, FA, and particle swarm optimization (PSO). Outcomes indicated that the proposed ChOA technique considerably improves the performance of the original LeNet model and also shows a better performance than the others.
Dynamic Strategy Analysis of Emission-Reduction Technology Investment Based on Pricing Coordination Mechanism under Cost Subsidy Policy
Authors: Guan Yue , Hou Qiang , Sun Jiayi
Published: April 2022

Climate change has become a pressing concern in recent decades, and the reduction of greenhouse gas emissions is now recognised as an important strategy for redressing that concern. The carbon trading system and the provision of low-carbon cost subsidies are essential measures for reducing emissions in various countries and regions. In this context, we study the investment decision of emission reduction technology in a supply chain composed of a leading manufacturer and a following retailer under the cost subsidy policy of carbon emission reduction. We consider consumers’ low-carbon preferences and utilise differential game theory and dynamic optimisation technology to construct the investment game model under a cost subsidy policy affecting manufacturers and retailers. We then identify the equilibrium strategy and the evolution path of emission reduction, profit, and social welfare according to the interest’s composition and game relationship of each stakeholder. We also use numerical simulation method to analyse the evolution path of the system and the sensitivity of related parameters, so as to determine the influence of related parameters on the structure and path of the system. We conclude that under the current carbon trading system, the cost subsidy policy implemented by the government plays a positive role in promoting emission reduction investment and corporate profits of supply-chain-related enterprises.
Relationships between Fitness Status and Blood Biomarkers in Professional Soccer Players
Authors: Silva Ana Filipa , González-Fernández Francisco Tomás , Ceylan Halil Ibrahim , Silva Rui , Younesi Saeid , Chen Yung-Sheng , Badicu Georgian , Wolański Paweł , Murawska-Ciałowicz Eugenia , Clemente Filipe Manuel
Published: April 2022

Background. Physical conditions are recognized to be optimal after the pre-season (PS) phase in professional sports. Given that blood measures may also reveal variations, which in turn, may present associations with fitness changes. Objective. The aim of this study is to test the changes of blood markers and physical fitness outcomes at the beginning and following the PS phase. Additionally, we aimed also to analyze the associations of training adaptations between blood markers and the physical fitness measures. Methodology. 25 professional male soccer players (28.1 ± 4.6 years old, 2.0 ± 7.8 kg, and 176.7 ± 4.9 cm) were assessed for hematological and biochemical parameters, and physical fitness measures in the baseline and after the phase of PS. Results. Increases in platelets were observed after the PS phase (p = 0.001, η2 = 0.39). Regarding the biochemical parameters, significant increases between PS were found for creatinine (Cre) (p = 0.001, η2 = 0.66), alkaline phosphatase (ALP) (p = 0.001, η2 = 0.79), C-Reactive Protein (CRP) (p = 0.001, η2 = 0.74), cortisol (C) (p = 0.001, η2 = 0.63), and testosterone (T) (p = 0.001, η2 = 0.76), whereas significant decreases were found for albumin (Alb) (p = 0.004, η2 = 0.29), and calcium corrected (Ca Corr.) (p = 0.002, η2 = 0.32). Moderate correlations were found between albumin and the 5-meter linear sprint split (r = –0.44 (95%CI: –0.71; –0.05)) and CRP (r = –0.48 (95%CI: –0.74; –0.10)). Moderate correlations were found between VAMEVAL and hemoglobin (r = 0.44 (95%CI: 0.05; 0.71)). Conclusions. The overall physical fitness measures improved after the PS phase. Also, significant variations (decreases/increases) were observed for the case of biomchemical and hematological outcomes. Coaches should carefully consider the adaptative changes observed in blood parameters as the changes in whole organism and metabolism after specific critical phases as the PS in professional players. Thus, optimal management of stimulus/recovery can be warranted to minimize illness and injury rate and to follow the direction and dynamics of adaptative changes.
Development an Immune-Related MicroRNA Risk Index in Hepatocellular Carcinoma
Authors: Zhou Shun , Xu Jian , Wang Dong , Wang Yong , Meng Lijuan
Published: April 2022

Purpose. Hepatocellular carcinoma (HC) has emerged as one of the most prevalent malignancies on a global scale. Recently, immunotherapy has achieved favorable effectiveness in the management of multiple cancers. However, there are limited therapeutic options for advanced HC. As the liver is a special immune organ, we intend to uncover potential and effective immunotherapeutic modalities for HC. Our study was designed to develop specific immune-related miRNAs (IRMs) for outcome assessment and individualized strategies for the management of HC. Methods. The miRNA-seq and survival data of TCGA-LIHC dataset was enrolled into this program. We first collected IRMs from Immune-miR website. Differentially expression analysis was applied to screen aberrantly expressed IRMs. In order to set up an IRM-related index (IRMRI) in HC, we conducted the Cox relevant methods. Next, the statistical approaches (survival curve and ROC curve analyses) were utilized to detect the evaluation capacity of our IRMRI. Subsequently, we obtained the target genes of hub miRNAs from IRMRI through three miRNA-related predictive online tools (miRDB, miRTarBase, and TargetScan websites). Results. Five IRMs were determined to develop the IRMRI. It can effectively segregate all HC cases from two different risk subgroups. We identified a marked discrepancy in survival outcome between the two groups by survival analysis and confirmed the reliability of IRMRI in two testing sets. Moreover, we collected 10 hub target genes (ESR1, IGF1, PDGFRB, JUN, MYC, ZWINT, MAD2L1, TOP2A, KIF11, and CDCA8) which were strongly linked to HC progression and malignant behavior. Conclusion. We screened out five hub IRMs with clinical value and constructed a risk index model in HC, which can precisely assess the risk status and outcome of patients to a certain extent.
Human-Computer Interaction of Networked Vehicles Based on Big Data and Hybrid Intelligent Algorithm
Authors: Shang Jianfeng , Liu Huiying , Li Weidong
Published: April 2022

Intelligent connected vehicle (ICV) refers to realizing the exchange and sharing of intelligent information between vehicles, roads, people, clouds, and so on by carrying advanced on-board sensors, controllers, actuators, and other devices and combining modern communication and network technology. In the age of big data, the information of everything can be transformed into digital resources, and transportation big data has become a basic resource. This paper constructs a big data platform for traffic data processing to realize the function of real-time collection, processing, and analysis of traffic data. Based on the proposed big data platform, the parallel programming framework of MapReduce and HDFS distributed storage system are used to process the real-time vehicle dynamic information in parallel, and the output result is used as the input of running genetic algorithm simulated annealing (GA-SA) for parallel calculation. At the same time, it studies the impact of various elements on users’ interactive behavior, constructs the demand framework and design model of automobile human-computer interaction, and then realizes fast and comprehensive search. The experimental results show that the human-computer interaction method of intelligent networked vehicle can find the optimal driving path, transmit it to each networked vehicle through the human-computer interaction system, realize human-computer interaction, reduce the impact of user unintentional operation on redundant motion, reduce the motion error accumulation of the system, and improve the performance of human-computer interaction system.
Assessment of Causes of Delays in the Road Construction Projects in the Benin Republic Using Fuzzy PIPRECIA Method
Authors: Stević Željko , Bouraima Mouhamed Bayane , Subotić Marko , Qiu Yanjun , Buah Peter Antwi , Ndiema Kevin Maraka , Ndjegwes Christian Magloire
Published: April 2022

Purpose. The purpose of this study is to examine the causes of delays in road construction projects in the Benin Republic from the consultant, client, and contractor perspectives. Design/Methodology/Approach. Through construction project reports, 20 factors that could cause delays in road construction projects were identified. The factors were arranged into a questionnaire, which was distributed to three separate experts. The fuzzy PIPRECIA (PIvot Pairwise RElative Criteria Relevance Assessment) method was used to calculate the independent importance of each delay factor. The Spearman and Pearson correlation coefficients were used to test the method’s consistency. Findings. The top five road construction project delays in the Benin Republic, according to the analysis of the 20 factors considered, are project funding, slowness during the client-endorsed payment process, scarcity of professional personnel, delay in indemnifying reimbursement (land-owners), and price escalation. This shows that of the various types of delays, the financial delay group is the most crucial. Originality/value. This study evaluates the causes of delays in road construction projects in the Benin Republic for the first time in literature. This study also examined the top 5 delay factors in road construction projects. This study is based on reports from road construction projects and a performed questionnaire survey. Based on the findings, measures have been formulated to aid project managers to alleviate the road construction delays in the Benin Republic. In addition, this study is practical for both scholars and road construction parties and provides a complete and verifiable analysis of the progress of a road construction project to make it easier and attain a competitive level of time, cost, and quality for successful road construction.
Interbank Offered Interest Rate Risk Measurement Based on Embedded Sensor Network
Authors: Xie Wangsong
Published: April 2022

Interbank lending rate is the main benchmark interest rate in the domestic currency market, looking for an appropriate financial time series model to describe its stochastic fluctuation process, and choosing an appropriate risk measurement method to measure the domestic interbank lending interest rate risk. The risk management of the interest rate market has great theoretical and practical significance. This article is aimed at studying the interbank interest rate risk measurement based on the embedded sensor network and proposes the key technology of sensor network, sensor network MAC layer protocol, LEACH energy model, and other methods in the article. Related experiments have been carried out on the interbank interest rate risk measurement. The experimental results show that the interbank interest rate risk measurement model based on the embedded sensor network is much more efficient than the traditional interest rate risk measurement model. This has reduced the bank’s loss of interest rate by at least 7%.
Cross‐Sectional Study on Assessment of Frequency of Intestinal Helminth Infections and Its Related Risk Factors among School Children from Adola Town, Ethiopia
Authors: Husen Edaso Amana , Tafesse Geremew , Hajare Sunil Tulshiram , Chauhan Nitin Mahendra , Sharma Rajesh J. , Upadhye Vijay J.
Published: April 2022

The three main intestinal helminth infections (IHIs), ascariasis, trichuriasis, and hookworm, are common clinical disorders worldwide. These IHIs are more prevalent in tropics and subtropical countries especially in developing countries like sub‐Saharan Africa responsible for morbidity, mortality, and physical as well as intellectual growth retardation in children. In Ethiopia, the burden of IHIs appears in all ages mainly due to factors like lack of education, low socio‐economic status, and inadequate supply of drugs and proper awareness. The present study was carried out to access the prevalence of intestinal helminth infections and associated risk factors among school children in Adola town from Guji Zone, Oromia, Ethiopia, from August 2019 to December 2019. 404 stool samples were collected in a clean, dry, screw‐capped, and wide‐mouthed plastic container, fixed with 10% formal‐saline solution, and transported to the Adola Hospital laboratory for further microscopic analysis by wet mount following formal ether concentration technique. Data were analyzed using SPSS version 20 by binary logistic regression model using odd ratio with 95% CI. The overall prevalence of IHIs among school children was found to be 33.91% (137/404). Rate of double infection was noted to be 2.72% (11/404). Most dominant species was Ascaris lumbricoides (8.9%) followed by Hymenolepis nana (7.7%), Taenia saginata (5.4%), hookworm (4.7%), Trichuris trichiura (2.5%), Schistosoma mansoni (2.2%), Enterobius vermicularis (1.7%), and Strongyloides stercoralis (0.7%), respectively. Highest prevalence was observed in male students (39.6%) compared to female students (28.8%) (P < 0.05). The prevalence of IHIs among school children in the age group of 6‐10, 11‐15, 16‐20, and above 20 was 49.6%, 35.8%, 10.9%, and 3.6%, respectively (P < 0.05). IHI was significantly associated with some of the risk factors such as gender, educational level of students’, toilet usage habit, habit of hand washing, hand washing habit before feeding and after defecation, purpose of hand washing, and awareness to intestinal helminths (P < 0.05). In the study area, the prevalence of IHIs is moderately high and represents a public health problem in the school children. Therefore, all stakeholders should pay attention to raise awareness about health education programs such as proper personal hygiene, environmental sanitation, improving the quality of drinking water, and treatment to reduce the consequences of intestinal helminths.
The Curriculum System of Business English Majors in Higher Vocational Colleges from the Perspective of the Internet of Things Business Model
Authors: Wen Pilan
Published: April 2022

As the country pays more attention to higher vocational education, major higher vocational schools have begun to enroll in multiple majors, but many higher vocational schools do not have the admission requirements for business English majors. This paper is aimed at studying the business English curriculum system in higher vocational colleges from the perspective of the Internet of Things business model. This paper proposes a questionnaire survey analysis method based on the professional curriculum system of business English in higher vocational colleges. This algorithm is more pertinent than ordinary algorithms, and it is more explanatory for the research on the curriculum system of higher vocational business English. This method can more accurately explain the problems existing in the current higher vocational business English courses through detailed analysis of the course objectives, course implementation, and course evaluation. The experimental results of this paper show that the current curriculum system for business English majors in higher vocational colleges has problems in three aspects: curriculum objectives, curriculum implementation, and curriculum evaluation. 20% of the student group thinks that the curriculum system for business English majors has problems.
Automatic COVID-19 Lung Infection Segmentation through Modified Unet Model
Authors: Shamim Sania , Awan Mazhar Javed , Mohd Zain Azlan , Naseem Usman , Mohammed Mazin Abed , Garcia-Zapirain Begonya
Published: April 2022

The coronavirus (COVID-19) pandemic has had a terrible impact on human lives globally, with far-reaching consequences for the health and well-being of many people around the world. Statistically, 305.9 million people worldwide tested positive for COVID-19, and 5.48 million people died due to COVID-19 up to 10 January 2022. CT scans can be used as an alternative to time-consuming RT-PCR testing for COVID-19. This research work proposes a segmentation approach to identifying ground glass opacity or ROI in CT images developed by coronavirus, with a modified structure of the Unet model having been used to classify the region of interest at the pixel level. The problem with segmentation is that the GGO often appears indistinguishable from a healthy lung in the initial stages of COVID-19, and so, to cope with this, the increased set of weights in contracting and expanding the Unet path and an improved convolutional module is added in order to establish the connection between the encoder and decoder pipeline. This has a major capacity to segment the GGO in the case of COVID-19, with the proposed model being referred to as “convUnet.” The experiment was performed on the Medseg1 dataset, and the addition of a set of weights at each layer of the model and modification in the connected module in Unet led to an improvement in overall segmentation results. The quantitative results obtained using accuracy, recall, precision, dice-coefficient, F1score, and IOU were 93.29%, 93.01%, 93.67%, 92.46%, 93.34%, 86.96%, respectively, which is better than that obtained using Unet and other state-of-the-art models. Therefore, this segmentation approach proved to be more accurate, fast, and reliable in helping doctors to diagnose COVID-19 quickly and efficiently.
Bank Competition, Combination of Industry and Finance, and Enterprise Innovation: Evidence from China
Authors: Tan Xiaofang , Dong Yunshan , Fang Tongyu
Published: April 2022

Bank competition promotes enterprises to obtain credit funds through market mechanisms, and a combination of industry and finance (CIF) has an important influence on establishing bank‐enterprise relationship. Based on data of 2,245 manufacturing enterprises and branches of commercial banks in China from 2007 to 2019, this research establishes a moderated mediation model to verify whether CIF has a moderating effect on bank competition on enterprise innovation. The results are as follows. First, bank competition can both directly and indirectly promote enterprise innovation by alleviating financing constraints. Second, CIF has no moderating effect on the direct effect of bank competition on enterprise innovation but has a negative moderating effect on the first half of mediating effect.
Validity and Predictive Performance of Mini Nutritional Assessment Tool for Institutionalized Elders in Ethiopia
Authors: Oumer Abdu , Abebe Tariku , Hassan Kalkidan , Hamza Aragaw
Published: April 2022

Background. Despite the high burden of malnutrition in the country, there is a lack of a simple and valid tool to screen elders in Ethiopia. The Mini Nutritional Assessment (MNA) tool has been validated for comprehensive geriatric assessment to identify malnutrition in other countries. However, there is a lack of evidence on the potential validity and reliability of the tool for institutionalized elders in Ethiopia. This study was aimed at determining the validity and predictive performance of MNA tool for malnutrition among Ethiopian institutionalized elderly. Methods. A facility‐based survey was conducted on randomly selected 164 elders in geriatric centers to evaluate the validity, reliability, and predictive performance of full MNA against hemoglobin (Hgb) and ideal body weight (IBW) measured under standard procedures. The data was presented in ROC graphs, and reliability was evaluated with Cronbach alpha. The receiver‐operating characteristic curve (ROC) analysis was used to assess the predictive performance of the tool. The area under the curve (AUC) with its 95% CI was reported. The Youden index, at maximum sensitivity and specificity, was used to obtain optimal cutoff points. Results. The internal consistency of the tool was good (α = 0.80). The full MNA score can better predict Hgb (AUC = 0.845; 0.783‐0.899) and percentage of IBW (AUC = 0.90; 0.842‐0.941) at specified cutoff points. A full MNA can predict malnutrition or risk of malnutrition based on percentage IBW at a sensitivity and specificity of 97.3% and 72.2%, respectively. Conclusions. The full MNA has the potential to be a reliable and valid nutritional assessment tool for institutional elders.
Existence Solutions for a Class of Schrödinger-Maxwell Systems with Steep Well Potential
Authors: Yang Guocui , Duan Shengzhong
Published: April 2022

In this paper, we are concerned with the system of the Schrödinger-Maxwell equations

−
Δ
u
+
λ
V

x

u
+
b
K

x

ϕ
u
=

u

p
−
2

u
,
in
 

R

3

,

−
Δ
ϕ
=
K

x

u

2

,
in
 

R

3

,

where

λ
,
b
>
0

are constants, and

3
<
p
<
6

. Under appropriate assumptions on

V

and

K

, we prove the existence of positive solutions in the case

3
<
p
<
4

via the truncation technique. Moreover, suppose that

V

may change sign, we also obtain the multiplicity of solutions for the case

4
<
p
<
6

.
Potential Pleiotropic Genes and Shared Biological Pathways in Epilepsy and Depression Based on GWAS Summary Statistics
Authors: Lin Han , Lin Wan-Hui , Lin Feng , Liu Chang-Yun , Che Chun-Hui , Huang Hua-Pin
Published: April 2022

Current epidemiological and experimental studies have indicated the overlapping genetic foundation of epilepsy and depression. However, the detailed pleiotropic genetic etiology and neurobiological pathways have not been well understood, and there are many variants with underestimated effect on the comorbidity of the two diseases. Utilizing genome-wide association study (GWAS) summary statistics of epilepsy (15,212 cases and 29,677 controls) and depression (170,756 cases and 329,443 controls) from large consortia, we assessed the integrated gene-based association with both diseases by Multimarker Analysis of Genomic Annotation (MAGMA) and Fisher’s meta-analysis. On the one hand, shared genes with significantly altered transcripts in Gene Expression Omnibus (GEO) data sets were considered as possible pleiotropic genes. On the other hand, the pathway enrichment analysis was conducted based on the gene lists with nominal significance in the gene-based association test of each disease. We identified a total of two pleiotropic genes (CD3G and SLCO3A1) with gene expression analysis validated and interpreted twenty-five common biological process supported with literature mining. This study indicates the potentially shared genes associated with both epilepsy and depression based on gene expression, meta-data analysis, and pathway enrichment strategy along with traditional GWAS and provides insights into the possible intersecting pathways that were not previously reported.
Diagnosis of Chronic Obstructive Pulmonary Disease and Regulatory Mechanism of miR-149-3p on Alveolar Inflammatory Factors and Expression of Surfactant Proteins A (SP-A) and D (SP-D) on Lung Surface Mediated by Wnt Pathway
Authors: Zhang Xiuli , Wang Yaping , He Xiang , Sun Zerui , Shi Xuefeng
Published: April 2022

Objective. To study the mechanism of chronic obstructive pulmonary disease (COPD) in diagnosing alveolar factors and analyze the effect of miR-149-3p on alveolar inflammatory factors and the expression of surfactant protein D (SP-D) and SP-A on the lung surface mediated by Wnt pathway. Methods. Patients with stable COPD were taken as the research subjects, and healthy volunteers as the control group. Cardiac color Doppler ultrasound was adopted to measure the ventricular structure of patients. The ultrasound simulation method was introduced in the ultrasound imaging. The ultrasound image was processed based on the intelligent ultrasound simulation algorithm. The changes in the structure of the left and right ventricles were analyzed and compared in the two groups. The expression changes of miR-149-3p, Wnt1, β-catenin, RhoA, and Wnt5a in lung tissues of mice in three groups were detected, as well as the content of tumor necrosis factor- (TNF-) α, IL-1β, interleukin (IL-6), nuclear factor kB (NF-kB), and other inflammatory factors in bronchoalveolar tissues of mice in three groups. Results. The position where the attenuation ratio was less than 0.92 in the experiment under the ultrasonic simulation algorithm had a gray value of 50. Compared with the control group, the right ventricular mass index of patients with stable COPD was statistically considerable (

P
<
0.05

). In patients with stable COPD, the overall right ventricular longitudinal strain, right ventricular diastolic longitudinal strain rate (RV DLSR), right ventricular diastolic circumferential strain rate, and right ventricular longitudinal displacement were significantly impaired (

P
<
0.05

). The content of miR-149-3p in the lung tissue of the model group was dramatically inferior to that of the control group and the interference group (

P
<
0.05

). The contents of Wnt1, β-catenin, RhoA, and Wnt5a in the lung tissue of the model group were dramatically superior to those of the control group (

P
<
0.05

). In addition, the expressions of TNF-α, IL-1β, IL-6, and NF-kB in the alveolar lavage fluid of the model group were statistically different from those of control group (

P
<
0.05

). The expression levels of SP-D and surfactant protein A (SP-A) in the COPD group were also statistically different from those of control group (

P
<
0.05

). Conclusion. miR-149-3p regulated the expression of Wnt1, β-catenin, RhoA, and Wnt5a, which also affected the signal transmission of the Wnt pathway, causing changes in the expression of alveolar inflammatory factors. Eventually, it affected the development of COPD.
Hybrid Block-Based Lightweight Machine Learning-Based Predictive Models for Quality Preserving in the Internet of Things- (IoT-) Based Medical Images with Diagnostic Applications
Authors: Reshma V. K. , Khan Ihtiram Raza , Niranjanamurthy M. , Aggarwal Puneet Kumar , Hemalatha S. , Almuzaini Khalid K. , Tetteh Amoatey Enoch
Published: April 2022

In the contemporary era of unprecedented innovations such as the Internet of Things (IoT), modern applications cannot be imagined without the presence of a wireless sensor network (WSN). Nodes in WSN use neighbor discovery (ND) protocols to have necessary communication among the nodes. The neighbor discovery process is crucial as it is to be done with energy efficiency and minimize discovery latency and maximum percentage of neighbors discovered. The current ND approaches that are indirect in nature are categorized into methods of removal of active slots from wake-up schedules and intelligent addition of new slots. This work develops a lightweight intrusion detection system (IDS) based on two machine learning approaches, namely, feature selection and feature classification, in order to improve the security of the Internet of Things (IoT) while transferring medical data through a cloud platform. In order to take advantage of the comparatively cheap processing cost of the filter-based technique, the feature selection was carried out. The two methods are found to have certain drawbacks. The first category disturbs the original integrity of wake-up schedules leading to reduced chances of discovering new nodes in WSN as neighbors. When the second category is followed, it may have inefficient slots in the wake-up schedules leading to performance degradation. Therefore, the motivation behind the work in this paper is that by combining the two categories, it is possible to reap the benefits of both and get rid of the limitations of both. Making a hybrid is achieved by introducing virtual nodes that help maximize performance by ensuring the original integrity of wake-up schedules and adding efficient active slots. Thus, a Hybrid Approach to Neighbor Discovery (HAND) protocol is realized in WSN. The simulation study revealed that HAND outperforms the existing indirect ND models.
Novel Searchable Attribute-Based Encryption for the Internet of Things
Authors: Lu Zhenhua , Guo Yuyan , Li Jiguo , Jia Weina , Lv Liping , Shen Jie
Published: April 2022

As the product of the third information technology revolution, the Internet of Things (IoT) has greatly altered our way of lifetime. Cloud storage has gradually become the best choice for data processing due to its scalability and flexibility. However, the cloud is not a completely trusted entity, such as tampering with user data or leaking personal privacy. Therefore, cloud storage usually adopts attribute-based encryption schemes to accomplish data confidentiality and fine-grained access control. However, applying the ABE scheme to the Internet of Things still faces many challenges, such as dynamic user revocation, data sharing, and excessive computational burden. In this paper, we propose a novel searchable attribute encryption system that replaces the traditional key generation center with consortium blockchain to generate and manage partial keys. In addition, our scheme can perform predecryption operations in the cloud, and users only need to spend a small amount of computational cost to achieve decryption operations. Security analysis proves that our scheme achieves security under both the chosen keyword attack and the chosen plaintext attack. Compared with other schemes, this scheme is more economical in terms of computing and storage.
Correlation Analysis of Surplus Labor Transfer and Economic Growth Based on STR Model
Authors: Yu Zehui , Li Yiming , Bai Liru
Published: April 2022

For a long time, the research on the relationship between economic growth and the transfer of surplus labor has been the focus and hot issue of all kinds of people. As a model that can describe the nonlinear transformation between different states of variables in detail, the STR model is the Frontier and hot topic of nonlinear time series analysis. In recent years, it has been successfully applied in the fields of economy, finance, capital market, macro policy simulation, and so on. The STR model can well describe the nonlinear and nonequivalent linkage effect between economic growth and surplus labor and has significance in both practice and theory. By constructing an STR model of four variables, including the added value of rural labor transfer and the real added value of each industry, this paper conducts an empirical analysis on the extremely dynamic interaction between the transfer of rural surplus labor and various industries in China. There is an interactive effect of economic growth. The results of the study show that the relationship between human capital and economic growth in China presents a nonlinear characteristic of periodic changes, and frequently switches between linear and nonlinear relationships.
Therapeutic Targets for Regulating Oxidative Damage Induced by Ischemia-Reperfusion Injury: A Study from a Pharmacological Perspective
Authors: Trujillo-Rangel Walter Ángel , García-Valdés Leonel , Méndez-del Villar Miriam , Castañeda-Arellano Rolando , Totsuka-Sutto Sylvia Elena , García-Benavides Leonel
Published: April 2022

Ischemia-reperfusion (I-R) injury is damage caused by restoring blood flow into ischemic tissues or organs. This complex and characteristic lesion accelerates cell death induced by signaling pathways such as apoptosis, necrosis, and even ferroptosis. In addition to the direct association between I-R and the release of reactive oxygen species and reactive nitrogen species, it is involved in developing mitochondrial oxidative damage. Thus, its mechanism plays a critical role via reactive species scavenging, calcium overload modulation, electron transport chain blocking, mitochondrial permeability transition pore activation, or noncoding RNA transcription. Other receptors and molecules reduce tissue and organ damage caused by this pathology and other related diseases. These molecular targets have been gradually discovered and have essential roles in I-R resolution. Therefore, the current study is aimed at highlighting the importance of these discoveries. In this review, we inquire about the oxidative damage receptors that are relevant to reducing the damage induced by oxidative stress associated with I-R. Several complications on surgical techniques and pathology interventions do not mitigate the damage caused by I-R. Nevertheless, these therapies developed using alternative targets could work as coadjuvants in tissue transplants or I-R-related pathologies
Theoretical Model Development for Energy Motion of Dusty Turbulent Flow of Fibre Suspensions in a Rotational Frame
Authors: Ahmed Shams Forruque
Published: April 2022

Fibre suspension has garnered considerable attention in turbulent flows that are used in many industries. Solid particles, such as dust particles, notably affect the turbulent flow field in a rotational frame. In assessing their impacts, the dusty turbulent flow for fibre suspensions needs to be studied in a frame of rotation that can be substantially applied in many industries. This study, therefore, aims to build a theoretical model for the energy motion of dusty turbulent flow of fibre suspensions in a rotational frame. The turbulence momentum equation was considered to formulate the model in presence of dusty fluid rotating flow of fibre suspensions. The newly derived equation was derived in second‐order correlation tensors Fi,j, Wi,j, Gi,j, Si,j, Xi,j, Yi,j, Qi,j, and Ri,j at any two points in the flow domain, where the tensors were expressed as space, time, and distance functions. The developed model is a considerable improvement because it takes into account all of the potential influential parameters that could affect the motion of turbulent energy, such as dust particles, suspending particles (fibres), and rotating frame. However, the impact of these parameters on turbulence energy motion must be evaluated in order to assess the performance of turbulence systems utilized in a variety of industries, such as paper manufacturing. The present theoretical development will contribute to open up experimental and numerical research opportunities for the advancement of the industry, science, and technology.
Predictive Factors, Treatment, and Outcomes of Coagulase-Negative Staphylococcal Peritonitis in Malaysian Peritoneal Dialysis Patients: A Single-Center Study
Authors: Lau Siew Yan , Bee Boon Cheak , Wong Hin-Seng , Omar Marhanis Salihah , Bahari Norazlah
Published: April 2022

Aims. Coagulase-negative Staphylococci (CoNS) are frequently isolated in peritoneal dialysis (PD)-related peritonitis with a high rate of relapse and repeat peritonitis after initial response to antimicrobials. The optimal treatment regimen for CoNS peritonitis remains debatable. Hence, this study aimed to describe the clinical and microbiologic characteristics of CoNS peritonitis in a PD center and determine predictive factors influencing the outcomes. Methods. All cases of CoNS peritonitis in Selayang Hospital between 2011 and 2019 were reviewed retrospectively. Results. A total of 906 episodes of peritonitis were recorded; 140 episodes (15%) in 98 patients were caused by CoNS. The oxacillin and gentamicin resistance rates were 47% and 46%, respectively. The overall primary response rate was 90%, and the complete cure rate was 79%. Patients with concomitant exit-site infection (odds ratio (OR) 0.06, 95% confidence interval (CI) 0.01 to 0.40,

P
<
0.01

) and history of recent systemic antibiotic use (OR 0.04, 95% CI 0.01 to 0.82,

P
=
0.04

) were less likely to achieve primary response. CoNS episodes that were treated with beta-lactam-based or vancomycin-based therapy had a similar primary response rate and complete cure rate. The rates of relapse and repeat were 12% and 16%, respectively. Relapsed episodes (OR 0.35, 95% CI 0.13 to 0.97,

P
=
0.04

) had a significantly lower complete cure rate than the first episodes. Conclusion. Relapsed CoNS peritonitis was common and was associated with worse outcomes than the first episode of CoNS peritonitis. Oxacillin resistance was common, but the treatment outcome remained favourable when a beta-lactam-based regimen was used as empirical therapy.
Data Mining and Soft Computing in Business Model for Decision Support System
Authors: Gazzawe Foziah , Alturki Ryan
Published: April 2022

Several studies were taken to effectively determine the importance of data mining in business model development for decision support system. It was later discovered that most businesses have invested heavily in the data mining process which enables them to easily study and analyse the market environment and improve their domination in the market. Data mining is a process used by most firms to effectively collect information about certain topic. One factor that business model development usually focuses more on is the value of measurable performance and increased innovation in the market. The aim of the current research is to investigate the values and key roles played by data mining prospects in the business model development. It also revolves around current techniques used within business model development that are crucial in enhancing the position and competitiveness of a firm in the market. Although the data mining prowess varies in regards to the firm and effort used, the main concept remains on how to fully have the firm understand the effects and role played by data mining techniques in their overall business flow. In methodology, secondary sources are categorically used to enhance the overall flow of the study question by comparing them and analyzing them using the techniques provided. The results and analysis reveal that the effects of using data mining techniques are huge towards achieving success for various businesses. Moreover, the practical implications have categorically increased the notion of how influential the prospects of data mining can be when applied in businesses.
Evaluation of the Joint Impact of the Storage Assignment and Order Batching in Mobile-Pod Warehouse Systems
Authors: Yang Ning
Published: April 2022

The rapid development of e-commerce has impacted the intelligence level of warehouses. The robotic mobile fulfillment system (RMFS) demonstrated that mobile-pod warehouse systems could process a significant number of order-picking operations within the same amount of time as other systems, saving money and improving operational efficiency. The order-picking mode in such a system is “parts-to-picker,” which is becoming both a prevailing operation mode in industrial warehouses and an encouraging research field during these years. One of the most significant fundamental factors in RMFS is the operational efficiency that is affected by storage assignment and order batching. This paper considers the joint impact of the storage assignment policies and order batching policies on order picking process. Our goal is to minimize the moving times of robots, which reflects the order-picking cost or efficiency. We propose using order similarity and item similarity to batch orders and assign item storage locations, respectively. Both the order batching and item grouping are tackled by a clustering model which is an integer linear program. We also develop a policy evaluation model to measure the order picking cost. We conduct numerical tests on six order batching and storage assignment policy combinations. A comparative analysis and an ANOVA analysis are then performed on the test results to compare the performances of these policy combinations. We find that the Weighted Support Count-based storage allocation combining with the correlation-based order batching achieves the best order-picking performance. Also, the more accurate information about the items and orders we can get from the historical data, the more order-picking workload we can save by exploiting the similarity features.
Antioxidant, Antimicrobial, and Photocatalytic Potential of Cobalt Fluoride (CoF2) Nanoparticles
Authors: Khan Jamshid , Ullah Hameed , Ullah Riaz , Sajjad Muhammad , Thebo Khalid Hussain , Alotaibi Amal , Zahoor Muhammad , Bukhari Nadia , Murthy H. C. Ananda
Published: April 2022

Herein, CoF2 nanoparticles (NPs) are prepared by simple coprecipitation method and are characterized by various techniques, i.e., XRD, SEM/EDX, FTIR, and UV/Vis, for their structure identification. As-prepared nanostructures were used as photocatalyst, as antioxidant, and as antimicrobial agent. The degradation studies of the prepared samples were carried out for specific time for the degradation of methylene blue (MLB) dye under a UV/visible spectrophotometer to determine decolorization and change in concentration of MLB with respect to time. The antibacterial activity against Escherichia coli ( E. coli) and Bacillus subtilis ( B. subtilis) was measured by well diffusion and serial dilution method to determine their efficiency against these two bacteria, through a dose-dependent method. The antibacterial activity was further confirmed against the experimental bacteria through calculation of minimum inhibition concentration (MIC). The antioxidant activity (radical scavenging activity) of the prepared CoF2 NPs was also assessed.
Experimental and Numerical Investigation of Seismic Performance of UHPC Thin‐Walled Short Piers
Authors: Liu Yang , Chen Aijun , Bai Fan , He Guojin , Wang Haolei , Wan Jiejun
Published: April 2022

Rigid frame bridges with different heights of adjacent piers are inclined to crack the main girder at the pier‐beam connection. This cracking occurs due to a significant difference in thrust stiffness between tall and short piers. This problem can be resolved by applying ultra‐high performance concrete (UHPC) materials. Thus, in the present paper, the seismic performance and failure behavior of UHPC thin‐walled short piers were tested under low‐frequency cyclic loads. Based on previous studies, the test was conducted using a proposed experimental model, where the effects of longitudinal reinforcement ratio, stirrup reinforcement ratio, and axial load ratio were considered. The failure mode, ultimate bearing capacity, stiffness, displacement ductility factor, and other performance parameters were analyzed. It was found that the specimens present the bending‐shear failure mode. Also, the load‐bearing capacity of the UHPC thin‐walled piers was significantly improved by increasing the longitudinal ratio of the thin‐walled short piers, while the contribution of the stirrup ratio was limited. In addition, compared with traditional short piers, the ductility of UHPC thin‐walled short piers increased by 53.36%, and the thrust stiffness decreased by 23.73%, indicating that UHPC thin‐walled short piers have more efficient seismic performance than RC short piers. Note that, in the present paper, UHPC thin‐walled short piers’ internal behavior was also analyzed by establishing a finite element model. The analysis proves that the numerical results are consistent with the experimental data, which is promising to better understand the failure behavior.
Stability and Phase Response Analysis of Optimum Reduced-Order IIR Filter Designs for ECG R-Peak Detection
Authors: Amhia Hemant , Wadhwani A. K.
Published: April 2022

Cardiovascular health and training success can be assessed using electrocardiogram (ECG) data. For over a quarter of a century, an individual’s resting heart rate is varying more. As a result, it has become the subject of inquiry and reveals the intricate relationship between the human body and its environment. The autonomic nervous system has impact on blood flow system based on the rate of heartbeats. However, heart rate variation (HRV) characteristics analysis throughout the time period has lack of physical activity information. In the presence of patient movement, ECG signal is suffering from hard artefacts. Time-varying HRV parameters can be derived from low-frequency (LF) and high-frequency (HF) domains of the correct frequency. However, sometimes it is critical to ensuring accurate detection of the R-peak position. The proposed ROIIR (reduced-order IIR) offers 8.8% improvement in peak-to-peak swing than earlier IIR filter. We present an advanced filtering algorithm that is used for R-peak detection.