bluuebunny/crossref_metadata_2025 huggingface dataset:
A Novel Martingale Based Model Using a Smartphone to Detect Gait Bout in Human Activity Recognition
Authors: Etumusei Jonathan , Martinez Jorge Carracedo , McClean Sally
Published: April 2022

Gait bout is when an individual performs certain physical activities such as walking or running. In the last few decades, the study of gait bout has led to substantial progress in treating gait impairment (neuropathic, myopathic, and parkinsonian) in a person. Recently, gait bout study has been improved by advancing smartphone technology. To perform gait bout tasks, two different human activity scenarios, such as walking upstairs and standing, are obtained using the axis orientation of a smartphone accelerometer. To capture the pattern of walking upstairs and standing, we utilize a smartphone device attached to the waist of 30 subjects within the age group from 19 to 48 years old. We propose a human activity recognition model known as the multivariate triple exponential weighted moving average of the martingale sequence using particle swarm optimization (MTMS(PSO)) in the experimental setup. MTMS(PSO) utilizes the martingale framework to capture gait bout in human activity recognition data. Firstly, MTMS(PSO) is an unsupervised learning method that uses smoothing techniques such as triple exponential smoothing to remove high-frequency noise from the processed activity times series, making the patterns more visible. Secondly, the activity recognition model involves computing a threshold for identifying gait bout. Thirdly, MTMS(PSO) uses logical precedent and particle swarm optimization to enhance accuracy and precision. As a result, the overall MTMS(PSO) accuracy and G-mean are95.4%and96.1%, respectively. In addition, MTMS(PSO) technique independently outperforms other traditional methods such as MRPM(PSO), MGM(PSO), and ELM.
Bayesian Estimation of Different Scale Parameters Using a LINEX Loss Function
Authors: Mohammed M. A. , Al-Aziz Sundus N. , Al Sumati Eateraf M. A. , Mahmoud Emad E.
Published: April 2022

The LINEX loss function, which climbs exponentially with one-half of zero and virtually linearly on either side of zero, is employed to analyze parameter analysis and prediction problems. It can be used to solve both underestimation and overestimation issues. This paper explained the Bayesian estimation of mean, Gamma distribution, and Poisson process. First, an improved estimator for

μ

2

is provided (which employs a variation coefficient). Under the LINEX loss function, a better estimator for the square root of the median is also derived, and an enhanced estimation for the average mean in such a negatively exponential function. Second, giving a gamma distribution as a prior and a likelihood function as posterior yields a gamma distribution. The LINEX method can be used to estimate an estimator

λ

B
L

^

using posterior distribution. After obtaining

λ

B
L

^

, the hazard function

h

B
L

^

and

D

B
L

^

the function of survival estimators are used. Third, the challenge of sequentially predicting the intensity variable of a uniform Poisson process with a linear exponentially (LINEX) loss function and a constant cost of production time is investigated using a Bayesian model. The APO rule is offered as an approximation pointwise optimal rule. LINEX is the loss function used. A variety of prior distributions have already been studied, and Bayesian estimation methods have been evaluated against squared error loss function estimation methods. Finally, compare the results of Maximum Likelihood Estimation (MLE) and LINEX estimation to determine which technique is appropriate for such information by identifying the lowest Mean Square Error (MSE). The displaced estimation method under the LINEX loss function was also examined in this research, and an improved estimation was proposed.
Tripartite Game Analysis of Military-Civilian Technology Transfer from the Perspective of Technology Characteristics
Authors: Qu Ying , Guo Fei
Published: April 2022

Given the enterprise technology corporation technological learning problem of challenging to reduce the efficiency of technology transfer based on evolutionary game theory, from the nature of technical knowledge, military field, and civilian field of technology spillover, recessive and technical complexity, and other technical features, construction of bounded rationality under the condition of the private enterprise, the enterprise, and the government's three evolutionary game models, the influence of different technical characteristics on the three parties is analyzed by Matlab numerical simulation. The results show that intratechnological recessive only negatively inhibits the cooperative behavior of private enterprises. Both technology spillover and technology complexity promote the evolution of noncooperative behavior between military and civilians. The evolution speed of government support behavior is faster under high-intensity technology spillover. Finally, it is suggested that the technology transfer can be effectively promoted by strengthening the technology level of the private military enterprises, improving the technology transferability of the military enterprises, and perfecting the property right incentive mechanism of technological innovation.
Tripartite Evolutionary Game Analysis of Financial Support for Science-Tech Enterprises’ Innovation with Government Participation
Authors: Liu Wei , Liu Yang , Gu Jun , Zhao Jing , Zhang Rong
Published: April 2022

In this study, we use a tripartite evolutionary game model to analyze the financial support for science-tech enterprises’ innovation with government participation. Based on the game model, the study uses replication dynamics to analyze the stability of evolutionary trajectory in the eight scenarios of enterprises, the government, and the financial institutes. Then, we discuss the effect of the reputation multiplier, the efficiency of firms’ innovation output, and the positive socio-economic externalities multiplier by simulation as the important innovative points in this study. The study draws the following conclusions: (1) enterprises will choose high R&D intensity instead of low R&D intensity if the output of former exceeds that of the latter, (2) enterprises’ R&D output is closely related to the strategy choices of the government and financial institutes, and (3) enterprises can attract government subsidy by boosting economic and social externalities. The government subsidies to enterprises with high R&D intensity will improve the innovation output by the innovation investment and reputation multiplier. So, the government can implement subsidy policy to boost high-intensive R&D activity. Financial institutes’ strategy choice between equity investment and debt investment is influenced by investment yield difference and can influence enterprises’ R&D intensity choices.
Self-Monitoring Home Blood Pressure in Community-Dwelling Older People: Age Differences in White-Coat and Masked Phenomena and Related Factors—The SONIC Study
Authors: Tuo Jinmei , Godai Kayo , Kabayama Mai , Akagi Yuya , Akasaka Hiroshi , Takami Yoichi , Takeya Yasushi , Yamamoto Koichi , Sugimoto Ken , Yasumoto Saori , Masui Yukie , Arai Yasumichi , Ikebe Kazunori , Gondo Yasuyuki , Ishizaki Tatsuro , Rakugi Hiromi , Kamide Kei
Published: April 2022

Some studies reported that home blood pressure (HBP) monitoring was conducted by community-dwelling older people themselves, but there have been few studies on HBP including very old populations aged over 90 years old. Thus, the aim of the present study was to clarify the current situation of white-coat and masked phenomena defined by on-site and home BP measurements in community-dwelling old and oldest-old populations. The study subjects were 380 participants from the SONIC study, a cohort study of a community-dwelling old population, who measured their HBP in a series of 3–5 days by themselves and brought their HBP records to the venue on the survey day. Study participants’ characteristics were as follows: female, 185 (48.7%); male, 195 (51.3%); 70s, 95 (25.0%); 80s, 245 (64.5%); and 90s, 40 (10.5%). A total of 344 (90.5%) participants had hypertension. A total of 291 (76.6%) hypertensive participants taking antihypertensive medication were analyzed in the present study. Regarding the types of hypertension defined by home and on-site BP, they showed white-coat phenomenon, 183 (48.2%); masked phenomenon, 115 (30.3%); sustained hypertension, 130 (34.2%); and normotension, 82 (21.6%). On comparison of age groups, there was a tendency for the white-coat phenomenon to be common in young-old people in their 70s and the masked phenomenon to be common in very old people in their 90s. Therefore, since the detection of white-coat and masked phenomena is closely associated with appropriate BP management, it is very important for community-dwelling older populations to self-monitor HBP.
Deep Reinforcement Learning for Stock Prediction
Authors: Zhang Junhao , Lei Yifei
Published: April 2022

Investors are frequently concerned with the potential return from changes in a company’s stock price. However, stock price fluctuations are frequently highly nonlinear and nonstationary, rendering them to be uncontrollable and the primary reason why the majority of investors earn low long-term returns. Historically, people have always simulated and predicted using classic econometric models and simple machine learning models. In recent years, an increasing amount of research has been conducted using more complex machine learning and deep learning methods to forecast stock prices, and their research reports also indicate that their prediction accuracy is gradually improving. While the prediction results and accuracy of these models improve over time, their adaptability in a volatile market environment is questioned. Highly optimized machine learning algorithms include the following: FNN and the RNN are incapable of predicting the stock price of random walks and their results are frequently not consistent with stock price movements. The purpose of this article is to increase the accuracy and speed of stock price volatility prediction by incorporating the PG method’s deep reinforcement learning model. Finally, our tests demonstrate that the new algorithm’s prediction accuracy and reward convergence speed are significantly higher than those of the traditional DRL algorithm. As a result, the new algorithm is more adaptable to fluctuating market conditions.
Assessing the Influence of Dietary Pediococcus acidilactici Probiotic Supplementation in the Feed of European Sea Bass (Dicentrarchus labrax L.) (Linnaeus, 1758) on Farm Water Quality, Growth, Feed Utilization, Survival Rate, Body Composition, Blood Biochemical Parameters, and Intestinal Histology
Authors: Eissa El-Sayed H. , Baghdady Elsayed S. , Gaafar Alkhateib Y. , El-Badawi Ashraf A. , Bazina Walaa K. , Abd Al-Kareem Omayma M. , Abd El-Hamed Nadia N. B.
Published: April 2022

The probiotics are being used as ecofriendly and bioremediation tools for developing sustainability to aquaculture. The present study was conducted to explore the practical capability of using dietary lactic acid bacteria (Pediococcus acidilactici) probiotics and see how its dose variation affected the water quality, growth performance, survival rate, body composition, blood biochemical parameters, and intestinal histology of European sea bass (Dicentrarchus labrax L.). A total of 120 fingerlings with an initial weight of

9
±
0.2

 g were divided into four groups, each with three replicates. The feeding experiment lasted for 60 days. In addition to the control (without probiotics) (T0), fish were fed diets containing (T1) 2.0, (T2) 2.5, and (T3) 3.0 g of probiotics per kg of diet twice a day. When compared to the control, sea bass fed probiotic-supplemented diets had significantly higher growth parameters, fish body “crude lipid,” and villi height (

p
<
0.05

,

p
<
0.01

, and

p
<
0.001

). The P. acidilactici probiotic treatments improved survival rate, feed conversion ratio, body composition, and blood biochemical markers, but not statistically significant (

p
>
0.05

). Also, in regard to water quality, P. acidilactici drastically reduced ammonia and pH levels. In this experiment, fish fed with a dosage of 3.0 g of this commercial probiotic per kg of probiotics performed better. The study found that including probiotics in the diets of European sea bass improved growth, body composition, survival rate, blood biochemical markers, intestinal histology, and some water quality parameters.
Analyzing Ride-Sourcing Market Equilibrium and Its Transitions with Heterogeneous Users
Authors: Zhang Junlin , Mo Dong , Chen Xiqun (Michael)
Published: April 2022

With the justification of a comprehensive matching function approach, this study analyzes the ride-sourcing market with heterogeneous users. A single origin-destination (O-D) ride-sourcing market model is first developed. The model fills the major research gap to extend general user heterogeneity modeling from the transit market to the two-sided ride-sourcing market. Sufficient conditions that guarantee a unique market equilibrium are given. Equilibrium market operation with a profit-maximizing platform is explored. Equilibrium transitions with respect to the changes in different exogenous market variables are investigated. Nonequilibrium modeling to understand the transition path is also analyzed, revealing how the detailed transition evolves. Extensions of the single O-D market model to aggregate and disaggregate markets and incorporation of travel time reliability are briefly discussed. Numerical experiments, which are based on real-world data in the city of Ningbo, China, and cover an aggregate/single O-D base case, sensitivity analysis, equilibrium transitions, and disaggregate market equilibrium, are presented to illustrate the theoretical model. The larger network of Sioux Falls is also tested as a demonstration of the disaggregate market equilibrium. Discussions are made regarding operation and policy implications.
The Neglected Traditional Enset (Ensete ventricosum) Crop Landraces for the Sustainable Livelihood of the Local People in Southern Ethiopia
Authors: Feleke Newarinesh , Tekalign Wondimagegnehu
Published: April 2022

Enset (Ensete ventricosum, Musaceae) is a neglected traditional multipurpose crop plant critical for Ethiopian food security. It has drawn a lot of attention in the last few years. This study was undertaken on the morphological diversity among the enset landraces and their cultural use for the livelihood of the people in Southern Ethiopia. The study was administered in four purposively selected kebeles of the Mareka District. A total of 145 individuals were interviewed using semistructured interviews, and field observation has also occurred. The descriptors for enset developed by the International Board for Plant Genetic Resources were used to measure the morphological features. This study found twenty-two enset landraces. Landraces were categorized into five groups based on their morphological trait variability. The highest mean was in cluster five, while the lowest was in cluster three. The highest landrace diversity was found in Ocha (

n
=
2.28

) and the lowest in Guta (

n
=
2.17

). This study confirmed that the study area has a diverse range of ecosystems. However, a reduction in production and the loss of some landraces were observed. As a result, the protection and preservation of enset landraces must be a priority for all responsible entities.
Construction of a Recommendation Method for Financial Insurance Products Based on Machine Learning
Authors: Wu Bingyan , An Xiaoqing , Sun Wei , Chang Xue , Su Huadong
Published: April 2022

In the era of the rise of big data, if insurance companies can effectively and reasonably use existing data to tap more potential information, it can not only improve work efficiency but also achieve precise marketing to customers, thereby saving costs. At the same time, China pays more and more attention to financial insurance, so it is of great significance to use customer information to explore the purchase behavior of financial insurance. This paper mainly analyzes the factors that affect the purchase of financial insurance from the aspects of individuals and families and provides references for insurance marketing. This paper selects the results of the China Comprehensive Social Survey in 2020 as the empirical sample data of this paper and sets whether to purchase financial insurance as the target variable. The characteristic variables were screened, and the 10 variables selected after screening were finally used to build the model. Next, the data are divided into training set and test set, and a decision tree learning model is established on the two data sets at the same time. The classification results of the model are evaluated according to the classification evaluation indicators. Finally, the decision tree analysis results provide suggestions and strategies for the construction of insurance marketing recommendation methods.
Influence and Effectiveness Analysis of Urban Community Planning on Children’s Play Environment Based on Artificial Intelligence
Authors: Zheng Tianzhu , Qin Haifang
Published: April 2022

With the development of the times, the progress of science and technology, and the growing needs of people, more and more urban community planning chooses artificial intelligence to replace the traditional urban community planning, at the same time, it also brings new influences and changes to children’s play environment. Firstly, GA, BP, and GA-BP algorithms are explained, and IGA-BP algorithm is proposed. Secondly, the planning and allocation schemes of different communities in children’s environment are planned, and genetic algorithm and BP neural network are used to plan and apply children’s play environment in urban communities. Finally, the experiment compares and predicts the optimal path of the above three algorithms, and the results show that IGA-BP algorithm can wait for the optimal path. Then, GA-BP and IGA-BP algorithms were used to compare the heat of children’s community and other related indicators. IGA-BP algorithm has obvious advantages in heat prediction, absolute error, and relative error.
In Silico Identification of Hub Genes as Observing Biomarkers for Gastric Cancer Metastasis
Authors: Ajucarmelprecilla Arulprakasam , Pandi Jhansi , Dhandapani Ranjithkumar , Ramanathan Saikishore , Chinnappan Jayaprakash , Paramasivam Ragul , Thangavelu Sathiamoorthi , Mohammed Ghilan Abdul-Kareem , Aljohani Saad Ali S. , Oyouni Atif Abdulwahab A. , Farasani Abdullah , Altayar Malik A. , Althagafi Hussam Awwadh E. , Alzahrani Othman R. , Durairaj Kaliannan , Shrestha Anupama
Published: April 2022

Perception of hub genes engaged in metastatic gastric cancer (mGC) promotes novel ways to diagnose and treat the illness. The goal of this investigation is to recognize the hub genes and reveal its molecular mechanism. In order to explore the potential facts for gastric cancer, the expression profiles of two different datasets were used (GSE161533 and GSE54129). The genes were confirmed to be part of the PPI network for gastric cancer pathogenesis and prognosis. In Cytoscape, the CytoHubba module was used to discover the hub genes. Responsible hub genes were identified. Data from Kaplan–Meier plotter confirmed the predictive value of these distinct genes in various stages of gastric malignancy. Upregulated and downregulated genes were identified to utilize for further analysis. Positive regulation by a host of viral process, positive regulation of granulocyte differentiation, negative regulation of histone H3–K9 methylation were found in DEGs analysis. In addition, five KEGG pathways were identified as an essential enhancer that include nucleotide excision repair; base excision repair; DNA replication; homologous recombination; and complement and coagulation cascades. POLE, BUB1B, POLD4, C3, BLM, CCT7, PRPF31, APEX1, PSMA7, and CDC45 were chosen as hub genes after combining the PPI results. Our study recommends that BUB1B, CCT7, APEX1, PSMA7, and CDC45 might be potential biomarkers for gastric cancer. These biomarkers are upregulated genes. Therefore, suppression of these genes will increase the survival rate in gastric cancer patients.
On the Numerical Semigroup Generated by {(2k − m) · 2n+i − 1|i ∈ ℕ}
Authors: Gu Ze , Li Donglin , Huang Yucong
Published: April 2022

Let k, n be two positive integers such that 2 ≤ k ≤ 2n and m be an odd number with 1 ≤ m < 2k−1. Denote by T(k, m, n) a numerical semigroup generated by {(2k − m) · 2n+i − 1|i ∈ ℕ}. In this paper, we give the formula for the embedding dimension of T(k, m, n). In particular, the formulas for computing the Frobenius number and the genus of T(k, 2t + 1, n) with 2 ≤ t < k − 1 are given.
Prevalence and Associated Risk Factors of Endoparasites among Under-Five Children in Debre Tabor Comprehensive Specialized Hospital, Debre Tabor, Northwest Ethiopia: A Cross-Sectional Study
Authors: Eyasu Atalel , Molla Mulugeta , Kefale Belayneh , Sisay Woretaw , Andargie Yared , Kebede Fassikaw , Jemere Tadeg
Published: April 2022

Many endoparasites are still considered neglected tropical illnesses. The term “endoparasites” refers to infections caused by both helminths and protozoa. In many places in Ethiopia, particularly Debre Tabor, epidemiological data on the prevalence and associated variables of endoparasites among under-five children is unavailable. Thus, the aim of this study was to gather baseline data on the prevalence of endoparasites and their associated variables among under-five children who visited the Debre Tabor comprehensive specialized hospital in Northwest Ethiopia. A hospital-based quantitative cross-sectional study was used. The study was carried out from May 1 to November 30, 2021. Study participants were selected by a systematic sampling technique. The stool specimen was examined for the presence of different stages of intestinal parasites (adult, trophozoite, larvae, cysts, and ova) using direct wet mount, modified formal-ether sedimentation, and modified Ziehl–Neelsen methods. The IBM SPSS statistical package (version 23) was used to enter and analyze the collected data. The data was summarized using frequency tables and a bar chart. The adjusted odds ratio and

p

value <0.05 were used to declare the final association. In the present study, a total of 258 under-five children and their mothers/guardians were involved in the study, with a response rate of 100%. More than half of the respondents, 137 (53.10%), were females, and 159 (61.63%) were in the age group of 24 to 59 months. The overall prevalence of one or more endoparasites among under-five children was 45 (17.44%). Multivariate logistic regression analysis showed that health supervision, child food freshness, regular trimming of fingernails, and children’s playground cleanliness were significantly associated with childhood endoparasites. The present study demonstrated a higher prevalence of endoparasites among under-five children. Health supervision, child food freshness, regular trimming of fingernails, and children’s playground cleanliness were significantly associated with endoparasites. Thus, strengthening health education about food, personal, and environmental hygiene for both children and their mothers/guardians is crucial.
Variation in the Positioning of the Asian Summer Monsoon Boundary in the Tibetan Plateau and Potential Drivers
Authors: Li Jie , Jin Liya , Li Jinjian , Zheng Zeyu , Yan Zhitao
Published: April 2022

Studying the variation in the boundary position of the Asian summer monsoon in the Tibetan Plateau (TP) region and its potential drivers is important for understanding the climate in this region. Three sets of mean monthly precipitation data from 1980 to 2019 were sourced from the Global Precipitation Climatology Centre, the Climate Research Unit, and China Meteorological Information Service Centre. Several indicators that represent the Asian summer monsoon boundary (ASMB) were selected to compare their applicability to the TP region and elucidate the changes in the location of the ASMB in the TP over the last four decades. The results showed that the ASMB in the TP region extends in a southwest-northeast direction, with a clear north-south variation. It reaches as far north as the Kunlun Mountains and as far south as the Himalayas. The largest amplitude in spatial fluctuation occurs in the middle of the TP, and the smallest amplitude occurs at both ends of the region. A “small-large-small” fluctuation pattern was observed from west to east. The water vapor mainly originates from the South Asian region. The South Asian summer monsoon can move the ASMB position northward, whereas the westerly wind moves the ASMB position southward. Variation in the ASMB in the TP region is closely associated with the South Asian monsoon and westerly wind.
EvadeRL: Evading PDF Malware Classifiers with Deep Reinforcement Learning
Authors: Mao Zhengyang , Fang Zhiyang , Li Meijin , Fan Yang
Published: April 2022

With the growing popularity of information digitization and the advancement of executable file detection technology, PDF has emerged as an important carrier of malicious documents. Despite the improved efficacy of machine learning-based classifiers in detecting PDF malware, adversaries have proposed a variety of countermeasures to evade detection, such as generating adversarial examples. In contrast to other peer works attempting to expose the vulnerability of learning-based detection models, this work addresses the deficiencies of existing research by pointing out that the stochastic manipulations they applied may be highly computationally demanding. This work proposed EvadeRL, a general framework for automatically generating adversarial examples based on double deep Q-Network. The details of EvadeRL are briefly described as follows. First, the EvadeRL agent chooses a series of actions to modify the given PDF files and uses the classification results, as well as observations returning from the environment, to calculate the approximate value of each action. Second, through the interaction of the agent and the environment, the experiences gained are stored to train the decision network. Finally, the agent can generate adversarial examples against the target detector by taking the optimal behaviors after training. This study also contributes to the sustainability of evasion attacks by online fine-tuning; to the best of our current knowledge, this is the first study in the field that focuses on evolving malware. The experiments reveal that EvadeRL obtains a high evasion rate against PDF malware detectors and outperforms other approaches in terms of execution cost, robustness against hardened detectors, and sustainability against evolving malware and detectors.
Photoelectric Performance Optimization of Dye‐Sensitized Solar Cells Based on ZnO‐TiO2 Composite Nanofibers
Authors: Chang Qiqi , Xu Jun , Han Yijun , Ehrmann Andrea , He Tianhong , Zheng Ruiping
Published: April 2022

As the electron transport layer of dye‐sensitized solar cells (DSSCs), the photoanode is an important component that affects photoelectric conversion efficiency (PCE). The commonly used material titanium dioxide (TiO2) is difficult to prepare as nanostructures with large specific surface area, which affects dye loading and electrolyte diffusion. Herein, TiO2 nanofibers and ZnO‐TiO2 composite nanofibers with different molar ratios are synthesized by electrospinning technology. The above nanofibers are coated on photoanodes by the doctor blade method to assemble DSSCs. The influence of the composite ratio of ZnO‐TiO2 composite nanofibers on the photoelectric performance of the assembled DSSCs is explored. The ZnO‐TiO2 composite nanofibers with a molar ratio of 1 : 2 have large specific surface area and porosity and have the smallest charge transfer resistance at the photoanode‐electrolyte interface. The PCE of the nanofiber‐modified DSSCs reaches a maximum of 3.66%, which is 56% higher than that of the TiO2 nanofiber‐modified DSSCs. The photovoltaic parameters such as open circuit voltage (VOC), current density (JSC), and fill factor (FF) are 0.58 V, 10.36 mA/cm2, and 0.61, respectively. Proper compounding of zinc oxide (ZnO) can not only make the nanofibers absorb more dyes and enhance the light‐harvesting ability but also improve the diffusion of the electrolyte and enhance the electron transport, thus successfully improving the power conversion efficiency of DSSCs.
Efficiency of Coriandrum sativum (Linn.) and Petroselinum crispum (Mill.) in Enhancing Iron Absorption: An In Silico and In Vitro Approach
Authors: Sangeetha T. , Ibrahim K. Syed , Deepa S. , Balamuralikrishnan B. , Arun M. , Velayuthaprabhu S. , Saradhadevi K. M. , Anand A. Vijaya
Published: April 2022

Coriandrum sativum (Linn.) and Petroselinum crispum (Mill.) are the common herbs used for culinary purposes in daily life. The chlorophyll pigment in plants is being identified with various medicinal values, whereas iron is an essential micronutrient for the proper metabolism of the human body. The current research has been aimed at predicting the role of C. sativum and P. crispum in enhancing iron absorption via an in vitro approach. C. sativum and P. crispum have been analyzed for their capability of being a source of chlorophyll and iron concentration. The extracts prepared from solvents like carbinol, petroleum ether, and water were subjected to the identification of phytoconstituents through gas chromatography-mass spectrometry analysis, and the identified compounds were subjected to in silico studies against the iron-binding receptor, transferrin, to depict the binding affinity of the identified compounds. The carbinol extract was then put through in vitro analytical studies in Caco2 cell lines with a concentration of 500 µg/ml. Current research has shown that the leaves of C. sativum and P. crispum are an excellent source of chlorophyll and iron and has also suggested that these herbs efficiently enhance the absorption of iron in human intestinal cells.
Cryopreservation Techniques for Ram Sperm
Authors: Saha Amit , Asaduzzaman Mohammad , Bari Farida Yeasmin
Published: April 2022

Germplasm storage and transportation in artificial insemination (AI) and other advanced technologies are facilitated by cryopreservation. In reproduction, the cryopreservation of sperm allows it to be transported across vast distances and used even after the sire’s death. However, the technique of cryopreservation might damage sperm and limit their activity. Several cryobiological investigations have reported that the integrity of the sperm membrane is frequently involved in the physical and biological elements that affect sperm survival at low temperatures during the cryopreservation process. However, successful cryopreservation of ram sperm is still a work in progress because a considerable percentage of sperm do not survive the freezing and thawing process. Sperms are destroyed during cryopreservation of semen due to varying concentrations of cryoprotective chemicals and if semen is not cooled at optimal cooling rates. Hence, it is crucial to know the optimum cooling rates with freezing and thawing protocols for maximum recovery of viable and functional sperm cells for a successful cryo-freezing of ram spermatozoa. Therefore, the current study compiled and compared the research on the impact of different cryopreservation procedures, cooling rates, equilibration time, and thawing protocols on post-thaw ram semen quality.
Finite-Element Analysis of Vertical Displacement of Laminated Rubber Bearing under Earthquake Action for Disaster Resilience of the Smart City
Authors: Yang Denglian , Liu Yanli
Published: April 2022

With the construction and development of smart cities, higher requirements have been put forward for the prediction and control of major natural disasters. For the prevention of earthquake disasters in super high-rise buildings, the rubber bearings of high-rise seismic isolation structures may have the risk of tensile damage in high-intensity areas, which has always been an urgent problem to be solved. In this paper, a unidirectional horizontal compression-shear experiment with 400% large deformation was conducted on the laminated rubber bearing (LNR500), and the relationship curve of vertical displacement with horizontal displacement of the bearing was obtained. According to the experimental data, an ideal elastic-plastic principal structure model was selected for the steel and a Yeoh principal structure model was selected for the rubber material, and the finite element analysis was carried out for the bearing. The time course curves of displacement, velocity and acceleration of the vertical and horizontal deformation of the laminated rubber bearing under the earthquake were obtained.
Forecasting Solar Energy Production Using Machine Learning
Authors: Vennila C. , Titus Anita , Sudha T. Sri , Sreenivasulu U. , Reddy N. Pandu Ranga , Jamal K. , Lakshmaiah Dayadi , Jagadeesh P. , Belay Assefa
Published: April 2022

When it comes to large-scale renewable energy plants, the future of solar power forecasting is vital to their success. For reliable predictions of solar electricity generation, one must take into consideration changes in weather patterns over time. In this paper, a hybrid model that integrates machine learning and statistical approaches is suggested for predicting future solar energy generation. In order to improve the accuracy of the suggested model, an ensemble of machine learning models was used in this study. The results of the simulation show that the proposed method has reduced placement cost, when compared with existing methods. When comparing the performance of an ensemble model that integrates all of the combination strategies to standard individual models, the suggested ensemble model outperformed the conventional individual models. According to the findings, a hybrid model that made use of both machine learning and statistics outperformed a model that made sole use of machine learning in its performance.
Optimization of Cold Spray Process Inputs to Minimize Porosity and Maximize Hardness of Metal Matrix Composite Coatings on AZ31B Magnesium Alloy
Authors: Mohankumar Ashokkumar , Duraisamy Thirumalaikumarasamy , Sampathkumar Deepak , Ranganathan Sathiyamoorthy , Balachandran Guruprasad , Kaliyamoorthy Murugan , Mariappan Mathanbabu , Mulugeta Lijalem
Published: April 2022

In this investigation, the development of an empirical relationship to determine the porosity and microhardness of the coatings through low‐pressure cold‐sprayed (LPCS) aluminum alloy/alumina metal matrix composite (MMC) deposit. Spray parameters like temperature, standoff distance (SOD), and powder feed rate play an essential part in the determination of the coating effectiveness. In this study, 3 variables, 5 levels of central composite rotatable design (CCD) were used to decrease the total count of the experimentation. A mathematical model has been developed to evaluate the porosity and hardness of the coated samples along with LPCS spray parameters, and the model’s applicability was inspected by ANOVA. Utilizing response surface methodology, spray parameter optimization was carried out. The deposit developed by optimal spray parameters produces the lowest surface porosity of 3.31 vol.% and a higher hardness of 137.21 HV compared with other coated samples. It is validated through the response graph. As a result, the optimized parameters for aluminum alloy/alumina metal matrix composite (MMC) coatings via LPCS are 500 degrees Celsius, 10 mm SOD, and 20 grams/min powder feed rate.
Network Pharmacology and Molecular Docking-Based Strategy to Investigate the Multitarget Mechanisms of Shenqi Yizhi Granule on Alzheimer’s Disease
Authors: Wang Linshuang , Xu Xiaoyu , Wang Zikang , Chen Qian , Wei Xiaodie , Xue Jingfan , Zhang Zhanjun , Wang Miao , Li Yanping , Zhang Junying , Wei Dongfeng
Published: April 2022

Background. Traditional Chinese herbal medicine draws more attention to explore an effective therapeutic strategy for Alzheimer’s disease (AD). Shenqi Yizhi granule (SQYG), a Chinese herbal recipe, has been applied to ameliorate cognitive impairment in mild-to-moderate AD patients. However, the overall molecular mechanism of SQYG in treating AD has not been clarified. Objective. This study aimed to investigate the molecular mechanism of SQYG on AD using an integration strategy of network pharmacology and molecular docking. Methods. The active compounds of SQYG and common targets between SQYG and AD were screened from databases. The herb-compound network, compound-target network, and protein-protein interaction network were constructed. The enrichment analysis of common targets and molecular docking were performed. Results. 816 compounds and 307 common targets between SQYG and AD were screened. KEGG analysis revealed that common targets were mainly enriched in lipid metabolism, metal ion metabolism, IL-17 signaling pathway, GABA receptor signaling, and neuroactive ligand-receptor interaction. Molecular docking analysis showed high binding affinity between ginsenoside Rg1 and Aβ1–42, tanshinone IIA and BACE1, baicalin, and AchE. Conclusions. The therapeutic mechanisms of SQYG on AD were associated with regulating lipid metabolism, metal ion metabolism, IL-17 signaling pathway, and GABA receptor signaling. Ginsenoside Rg1, tanshinone IIA, baicalin, astragaloside IV, and folic acid may play an important role in AD treatment.
Efficacy of Moxibustion in the Treatment of Parkinson’s Disease Based on Meta-Analysis under Intelligent Medical Treatment
Authors: Niu Qianqian , Xu Weijie
Published: April 2022

Dementia in Parkinson’s disease (PD) has become a major factor affecting the quality of life of patients with Parkinson’s disease. Early detection and timely prevention can delay the progression of dementia, improve the quality of life of patients, and reduce the burden on society. This article is aimed at studying how to analyze the efficacy of moxibustion in the treatment of Parkinson’s disease through meta-analysis on the basis of smart medicine. This article puts forward the related conceptual knowledge of smart medicine and meta-analysis and moxibustion treatment and proposes a deep learning method based on smart medicine to analyze the effects of moxibustion treatment on patients. The experiment in this article can be seen from the data in one of the figures that the highest curative effect of using a single moxibustion to treat Parkinson’s disease is about 46%, while the curative effect of using a combination of moxibustion and Western medicine has reached 90%. It can be seen that a single moxibustion is not as effective as a combination of the two for Parkinson’s disease. From the data in one of the tables, it can be seen that the proportion of Parkinson’s disease in 2016 was 15%, showing an increase of 5%. By 2020, the proportion of Parkinson’s disease was as high as 38%, and the growth rate reached 9%. It can be seen that the prevalence of this disease is getting higher and higher. Parkinson’s disease has caused many undesirable effects on patients, such as slow movement, mental disorders, and a decline in mental state. Therefore, it is urgent to study the treatment of Parkinson’s disease. Moxibustion can improve the patient’s blood circulation and help the patient’s local limbs to recover more easily and can help improve the patient’s motor function.
Design of Personalized Cervical Fixation Orthosis Based on 3D Printing Technology
Authors: Xu Yangyang , Li Xiangyu , Chang Yafei , Wang Yi , Che Lifang , Shi Guopeng , Niu Xiaofen , Wang Haiyan , Li Xiaohe , He Yujie , Pei Baoqing , Wei Guoqiang
Published: April 2022

The movement of the cervical spine should be restricted throughout the rehabilitation phase after it has been injured. Cervical orthosis is commonly utilized in clinical settings to guarantee cervical spine stability. However, to date, the investigations are limited to patient-specific cervical fixation orthoses. This study provides a new idea for making personalized orthoses. The CT data of the patient’s cervical spine were collected, then mimics were used for reconstructing the skin of the cervical spine, the Geomagic Studio was used for surface fitting, the Inspire Studio was used for structural topology optimization, redundant structures were removed, the resulting orthotics were postprocessed, and finally, it was printed with a 3D printer. No signs of pain or discomfort were observed during the wearing. The cervical spine range of motion in flexion, extension, lateral flexion, and rotation is all less than 8° after using the device. Low cost, quick manufacturing time, high precision, attractive appearance, lightweight structure, waterproof design, and practical customized orthotics for patients are all advantages of 3D printing technology in the field of orthopedics. Many possible benefits of using 3D printing to build new orthotics include unique design, stiffness, weight optimization, and improved biomechanical performance, comfort, and fit. Personalized orthotics may be designed and manufactured utilizing 3D printing technology.
Study on the Influence of Connected Vehicle Fog Warning Systems on Driving Behavior and Safety
Authors: Guan Wei , Chen Haolin , Li Xuewei , Li Haijian , You Xin
Published: April 2022

Driving speeds are higher on freeways, and the visibility reduction occurring in freeway fog zones often increases traffic accidents. This study aims at assessing the impact of different levels of connected vehicle fog warning systems on driving behavior and safety. A connected vehicle fog warning system is developed based on driving simulators, and virtual scenes are developed based on fog zones. The connected vehicle technology includes three levels: a normal level, a level including a human-machine interface, and a level with both a human-machine interface and dynamic message signs. Speed and lateral deviation are chosen as assessment indicators and combined with sample entropy to evaluate the impact of the connected vehicle fog warning system on safety. The deceleration ratio of the warning point is used to evaluate the efficiency of the connected vehicle fog warning system. Results show that the connected vehicle fog warning system can significantly reduce driving speed, and that there are differences in the speed-reduction effectiveness for different technical levels. The connected vehicle fog warning system can reduce the lateral deviation and improve the lateral driving safety. From the perspective of change stability, speed safety entropy and lateral deviation safety entropy are increased, which indicates that the connected vehicle fog warning system will negatively impact safety because of the additional workload. Drivers’ responses are more pronounced in the human-machine interface group compared to the group with dynamic message signs, where the drivers maintained a lower speed. This study provides a reference for the studies on connected vehicle technology based on driving simulators and supports the optimization, design, and evaluation of connected vehicle fog warning systems.
MAM: Multiple Attention Mechanism Neural Networks for Cross-Age Face Recognition
Authors: Ren Xudie , Wang Jialve , Li Shenghong
Published: April 2022

Cross-age face recognition problem is of great challenge in practical applications because face features of the same person at different ages contain variant aging features in addition to the invariant identity features. To better extract the age-invariant identity features hiding beneath the age-variant aging features, a deep learning-based approach with multiple attention mechanisms is proposed in this paper. First, we propose the stepped local pooling strategy to improve the SE module. Then by incorporating the residual-attention mechanism, the self-attention mechanism, and the improved channel-attention mechanism to the backbone network, we proposed the Multiple Attention Mechanism Network (MAM-CNN) framework for the cross-age face recognition problem. The proposed framework can focus on essential face regions to highlight identity features and diminish the distractions caused by aging features. Experiments are carried out on two well-known public domain face aging datasets (MORPH and CACD-VS). The results yielded prove that the introduced multiple mechanisms jointly enhance the model performance by 0.96% and 0.52%, respectively, over the state-of-the-art algorithms.
Field Monitoring and Numerical Simulation Analysis of Deep Shaft Concrete Wall Support
Authors: Ji Hongguang , Fu Zhen , Zhang Yuezheng , Zhang Chunrui
Published: April 2022

Affected by faults, fractures, and high ground stress, the deep shaft wall is prone to deformation and fracture, which affects the safety of mine construction. To investigate the stress and deformation of the shaft wall at the horsehead gate connection, the force-measuring bolt and vibrating string concrete strain gauges were installed for on-site monitoring prior to the shaft wall pouring. It was found that the concrete strains and forces on the shaft wall were divided into four stages during the tedious shaft construction. The measured data showed that the maximum pressure and tension on the shaft wall were 4.5 MPa and 1.3 MPa, respectively, the maximum axial compressive and tensile strains were -500 με and 1700 με, and the maximum circumferential compressive and tensile strains were -1000 με and 400 με. During the shaft excavation construction, there is a tensile state in the shaft wall at the connection of the horsehead gate. In addition, there will be uneven stress in the concrete support structure and a sharp increase in the local stress of the shaft wall. Therefore, the problem of supporting the wall of deep shafts is undoubtedly a significant challenge in the construction of shafts. The numerical simulation results combined with the on-site monitoring of the layers show that stress concentrations occur at the lower end of the shaft wall and the interconnections between the walls during the excavation process. Therefore, it is essential to pay attention to the stress values in the lower part of the wall when constructing deeper sections to avoid stress concentrations and pay attention to the construction quality when constructing the wall joints to meet the wall’s safety needs support.
Rescue Revascularisation in Acute Internal Carotid Artery Occlusion with a Super Extended Time Window of More than 48 hours
Authors: Berger Katharina , Sartor-Pfeiffer Jennifer , Mengel Annerose , Ernemann Ulrike , Ziemann Ulf , Hennersdorf Florian , Feil Katharina
Published: April 2022

Background and Aim. Mechanical thrombectomy (MT) and intravenous thrombolysis are the gold standard treatment for large vessel occlusion (LVO) strokes. 10–20% of LVO patients present as “minor strokes” with a National Institutes of Health Stroke Scale (NIHSS) ≤5 points. Therefore, MT is often not primarily performed. These patients rely on collateral blood flow but are prone to clinical deterioration and unfavourable outcome. MT is performed after clinical deterioration, often in an extended time window within 24 hours. No scores identify patients at risk for clinical deterioration. Methods. We present the case of a 71-year-old Caucasian male “minor stroke” patient with LVO, good collateral flow via the ophthalmic artery, receiving rescue MT following clinical deterioration after >48 hours. NIHSS and modified Rankin scale (mRS) were used for follow-up and modified treatment in cerebral infarction (mTICI) score for angiographic results. Results. Excellent angiographic result (mTICI 3) and clinical improvement were achieved (NIHSS preintervention 18, on discharge 2 points). 90-day follow-up showed excellent outcome (mRS 1). Conclusions. Late intervention MT should be encouraged when clinical deficit exceeds infarct demarcation. Standardized identification based on clinical and imaging data is required to target critical patients with LVO and low NIHSS, favouring a primary intervention.