bluuebunny/crossref_metadata_2025 huggingface dataset:
Structural engineering of ultrathin vertical NbS2 on carbon cloth by chemical vapor deposition for hydrogen evolution reaction
Authors: Zhao Yajuan , Zhang Zhaohui , Li Jianguo , Li Xiang , Liu Tianmeng
Published: April 2022

Layered transition metal dichalcogenides (TMDs) with rich chemistry and diverse properties are considered promising candidates for applications in nanoscale electronics and energy conversion. Among the wide range of TMDs, niobium dichalcogenides (NbS[Formula: see text] are ubiquitously considered to be a great promise material for hydrogen evolution reaction (HER) due to its metallic 2D feature with good conductivity. However, a few reports focus on the systematic structural optimization of NbS2 nanosheets on conductive substrates by chemical vapor deposition (CVD) towards HER. Here, vertical NbS2 nanoflowers are designed and constructed on carbon cloth using CVD. Systematic growth experiments are carried out to investigate the structure variation of the nanostructures. By tuning the growth temperature, the architecture with dense exposed basal planes is achieved, which exhibits highly structure-sensitive properties for HER. The results show NbS2 microflowers with maximized edge and plane sites exhibited optimal catalytic performance. The growth mechanism of NbS2 nanoplates on carbon cloth is further explored. These findings provide a guideline for optimization of microstructure and electrocatalytic activity for NbS2 and broaden our vision for improving HER performance of novel 2D TMDs.
Deer hunting optimization technique for clustering unsupervised data in data mining
Authors: Azeez Hayder Hussein
Published: April 2022

Unsupervised data clustering investigation is a standout among the most valuable tools and is an informative task in data mining that looks to characterize similar articles’ gatherings. One of the eminent algorithms for the clustering field is K-means clustering. Scholars recommended enhancing the nature of K-means, and optimization algorithms were hybridized. In this study, a heuristic calculation, deer hunting optimization algorithm (DHOA), was adjusted for K-means data clustering by altering the fundamental parameters of DHOA calculation, which are propelled from the characteristic enlivened calculations. During this work, a new human-based descriptive DHOA has been developed following a human deer hunting strategy. In order to attack the fawn, hunters update their positions based on the movement of the leader and backward movement while also considering the angle of the deer. In this work, the DHOA was hybridized with K-means clustering and the performance of the proposed approach is tested against UCI repository data with different algorithms.
Review on Wind Resistance for Quadrotor UAVs: Modeling and Controller Design
Authors: Shen Jiahao , Wang Biao , Chen Ben M. , Bu Ruiyu , Jin Bao
Published: April 2022

Micro-Unmanned Air Vehicles (Micro-UAVs), especially quadrotor UAVs, have been widely used in recent years because of their simple structure and convenient operation. However, due to under-actuated and strongly-coupled characteristics, their flight performance is not perfect when suffering external uncertainty such as wind disturbance. Therefore, in this paper, the literature is reviewed related to wind acting on UAVs and makes some conclusions. First, we review the wind field model of quadrotor operation and decompose it into wind turbulent model, wind shear model, and other typical wind field models. Then we focus on the mathematic model of wind disturbance on UAVs and divide it into effect on rotors and effect on the fuselage. Finally, various control laws are used to study the wind resistance of quadrotors. We review the promising works which have been done before and determine the research emphasis to be focused on in the future.
Treatment Options for Bifid Ulna Deformity Following Galeazzi-equivalent Injury in Adolescents
Authors: MELLA Joni , SOMMARHEM Antti , PÄÄKKÖNEN Markus
Published: April 2022

A Galeazzi-equivalent lesion occurs in children and adolescents following a traumatic distal radius fracture when the strong radioulnar ligaments and relative weakness of the ulnar physis result in an avulsion-type Salter-Harris III fracture of the distal ulna. In unreduced fractures, the osteogenic nature of the torn periosteal sleeve may result in the formation of a bifid distal ulna. We describe two cases of bifid distal ulna that developed after missed Galeazzi-equivalent lesions. The first case was treated with resection of the volar limb and reduction of the ulnar fracture, whereas the second case was treated with simple resection of the dorsal limb. Negative ulnar variance developed in both cases.

Level of Evidence: Level V (Case report)
Complete Occlusion of Radial and Ulnar Arteries Following Hand Crush Injury with Multiple Carpometacarpal Joint Fracture-Dislocations
Authors: LEE Jun-Ku , HWANG Daehyun , HAN Soo-Hong , LEE Younghun
Published: April 2022

Multiple dorsal fracture-dislocations of the carpometacarpal joints (CMCJ) occur from very high-energy trauma and are often associated with soft tissue injury or ischaemia. We report a 54-year-old male manual worker and a smoker who presented to the emergency room with history of compression of his right hand in a press machine. Radiographs showed dorsal fracture-dislocations of the scapho-trapezio-trapezoidal and third to fifth CMCJ’s. Despite emergent Guyon canal and carpal tunnel release and closed reduction and pinning, skin pallor persisted in all digits. Brachial angiography revealed total occlusion of the radial and ulnar arteries and loss of the palmar arch at the level of the fracture. Heparin and Alprostadil were injected directly. On follow-up angiography three weeks later, the vessels were still occluded and collaterals provided digital circulation. Although digital sensations recovered, cold intolerance and stiffness resulted in a poor functional outcome.

Level of Evidence: Level V (Therapeutic)
Neurolymphomatosis of the Ulnar Nerve Presenting as Cubital Tunnel Syndrome: A Case Report
Authors: LEE Yeong Chang , JUHNG Seon Kwan , KANG Hong Je
Published: April 2022

Lymphoma is a malignant tumour of the lymphatic system. Neurolymphomatosis occurs when lymphoma cells invade the peripheral nervous system (PNS). Neurolymphomatosis has been reported involving the sciatic nerve, nerve roots and within the axilla and the upper arm. It can cause nerve dysfunction depending on the involved nerve. Neurolymphomatosis involving the ulnar nerve is rare. We report a patient with neurolymphomatosis of the ulnar nerve around the elbow that presented with features of cubital tunnel syndrome. A high index of suspicion is necessary in patients with cubital tunnel syndrome that present with uncommon symptoms such as sudden onset, rapid progression and/or severe pain.

Level of Evidence: Level V (Therapeutic)
Ulnar Nerve Injury Following Distal Radius Fracture Assessed by Ultrasonography: Management of an Ulnar Nerve Lesion
Authors: TSUJINO Shohei , SEKI Yasuhiro , MAEHARA Manabu , SHIRASAWA Shinichi
Published: April 2022

A fracture of the distal radius with an associated injury to the ulnar nerve is rare. The management of the ulnar nerve lesion is unclear. We present a patient with a closed distal radius fracture related to an injury to the ulnar nerve associated with diminished sensation and a claw deformity. This was assessed by ultrasonography (US) that showed the nerve to be in continuity without any evidence of compression. The nerve was deviated towards the volar side at the distal end of the ulna and was enlarged at the same point. Open reduction and internal fixation was performed for the fracture. Emergent nerve exploration was not performed. The function of the ulnar nerve was completely restored at 16 weeks after injury. In cases presenting with ulnar nerve injury, we recommend US to evaluate the condition of the ulnar nerve. Nerve exploration should be performed when neurological deficits were found on US or symptoms did not recover over 4 months observation.

Level of Evidence: Level V (Therapeutic)
A Study on the Influence of Traditional Architectural Elements on the Urban Context from the Perspective of Perception: Taking the Yangtze River Delta, the Pearl River Delta, and the Bohai Rim as Examples
Authors: Niu Tingting , Li Ruibin
Published: April 2022

As one of the important components of a city, traditional buildings in different regions just reflect the differences of cities in different regions, and the analysis of the value hierarchy of its constituent elements can reveal the corresponding urban characteristics. This paper selects the representative traditional buildings in the Yangtze River Delta, the Pearl River Delta, and the Bohai Rim region as the research object, takes “perception” as the core concept, combines questionnaires, status surveys, and other methods to obtain and filter traditional architectural elements, and uses the principal components with the help of SPSS software. The analysis method calculates the filtered traditional building elements in the three regions and obtains the principal component composition and hierarchical order of them. Finally, the data results are combined with qualitative analysis to judge the different orders of the traditional building elements in the three regions and their impact on the development of their respective urban contexts.
Variability of the Minor Season Rainfall over Southern Ghana (1981–2018)
Authors: Braimah Mohammed , Asante Vincent A. , Ahiataku Maureen A. , Ansah Samuel O. , Otu-Larbi Frederick , Yahaya Bashiru , Ayabilah John B. , Nkrumah Francis
Published: April 2022

The monitoring of rainfall variability over recent decades has become a necessity due to its devastating effects such as floods and droughts, which render humans vulnerable across different parts of the West African region. The current study seeks to provide a good understanding of variability within the minor rainfall season over southern Ghana by employing statistical tools to quantify variability in rainfall. Daily rainfall data from 1981 to 2018 for seventeen (17) synoptic weather stations across southern Ghana are used for this analysis. We perform trend and descriptive statistics of rainfall amount and extreme indices intending to identify the areas with the greatest variability in rainfall. Further, for five recent years (2014–2018), we do an interpolation of the ground station rainfall data and compute anomalies. We find increasing trends of rainfall in the minor rainy season for 16 out of the 17 stations, with rainfall increasing between 0.10 mm and 4.30 mm each season. For extreme rainfall indices, the 17 stations show nonsignificant trends of very wet and extremely wet days. We also find that the middle parts of Ghana have the highest rainfall amounts (262.7 mm/season–400.2 mm/season), while the East Coast has the lowest (125.2 mm/season–181.8 mm/season). Over the whole of southern Ghana, we find high variability in rainfall amount with the coefficient of variations (CV) between 25.3% and 70.8% and moderate to high variability in rainfall frequency (CV = 14.0%–48.8%). The results of rainfall anomalies show that the middle parts had an above-normal rainfall amount. In the same period, the transition areas experienced below-normal rainfall. Our finding of high variability in the minor rainfall season has implications for agricultural productivity in Ghana and countries in the West African region, which rely heavily on rain-fed agriculture. Hence, this study recommends more research to understand the causes of variability in the West African monsoon and how this will change in the region.
A New Generalized Modified Weibull Model: Simulating and Modeling the Dynamics of the COVID-19 Pandemic in Saudi Arabia and Egypt
Authors: Emam Walid , Tashkandy Yusra
Published: April 2022

The flare-up of coronavirus disease 2019 (COVID-19) was first identified in China and then spread worldwide. The concerning articles are significant because of their increasing average infection rate. The exact scientific anatomy of this circumstance remains to be discussed. Nevertheless, it is important for governments and all responsible organizations to have sound statistics and analysis to decide on possible necessary actions. This article compares the dynamics of the COVID-19 pandemic between Saudi Arabia and Egypt. We provide an appropriate process of convergence of facts that can be useful for both administrations to implement appropriate quarantine procedures. In addition, the new generalized modified Weibull distribution is provided to provide the preferred description about COVID-19 total cases, daily new cases, total deaths, and daily death statistics of Saudi Arabia and Egypt.
Multipath Transmission Control Protocol for Live Virtual Machine Migration in the Cloud Environment
Authors: Ramana Kadiyala , Aluvalu Rajanikanth , Gunjan Vinit Kumar , Singh Ninni , Prasadhu M. Nageswara
Published: April 2022

For mobile cloud computing (MCC), a local virtual machine- (VM-) based cloudlet is proposed to improve the performance of real-time resource-intensive mobile applications. When a mobile device (MD) discovers a cloudlet nearby, it takes some time to build up a virtual machine (VM) inside the cloudlet before data offloading from the MD to the VM can begin. Live virtual machine migration refers to the process of transferring a running Virtual Machine (VM) from one host to another without interrupting its state. Theoretically, live migration process must not render the instance being migrated unavailable during its execution. However, in practice, there is always a service downtime associated with the process. This paper focuses on addressing the need to reduce the service downtime in case of live VM migration in cloud and providing a solution by implementing and optimizing the multipath transmission control protocol (MPTCP) ability within an Infrastructure as a service (IaaS) cloud to increase the efficiency of live migration. We have also introduced an algorithm, the α-best fit algorithm, to optimize the usage of bandwidth and to effectively streamline the MPTCP performance.
Big Data Image Processing Based on Coefficient 3D Reconstruction Model
Authors: Sun Hujun
Published: April 2022

In the history of human society, information is an indispensable part of development, and extracting useful data from the huge amount of data can effectively solve some real-life problems. At the same time, with the continuous improvement of modern technology and computer hardware and equipment, the demand for information subjects is getting higher and higher. The field of human research is gradually moving in the direction of multiscientific exploration and deepening of related work. The related information disciplines have been studied by more scholars and experts in the field to a greater extent and put forward more demanding theories and methods. In the process of human social development, things are constantly changing and updating, which makes data mining technology more and more attention. This article first describes the relevant basic theoretical knowledge of 3D reconstruction, and secondly, it analyzes the big data platform technology, which mainly includes the analysis of the big data platform architecture, the description of the Hadoop distributed architecture, and the analysis of the HBase nonrelational database. Finally, it studies the video image feature extraction technology of video content and uses this to study the design of a big data image processing platform for 3D reconstruction models.
Python Data Analysis and Attribute Information Extraction Method Based on Intelligent Decision System
Authors: Li Yongquan
Published: April 2022

In order to improve the effect or characteristics of Python data analysis and attribute information extraction, a method for intelligent decision system is proposed. The content of the method is as follows: to create a big data mining model for optimal decision making, to use smart data integration method to integrate data functions, to reconstruct management data evaluation information, and to extract and use management multidimensional information parameters regularly. Characterization methods multidimensional information breakdown and optimization of features are performed, characteristics are classified according to their differences, and management and decision-making optimizations are implemented. Based on linguistic Python, combined with rich and powerful libraries such as regular expression, urllib2, and Beautiful Soup, this paper discusses the methods of building modular web data collection, HTML parsing, and capturing link data. The experimental results show that there is a certain gap in the decision support time of the three methods with the change of iteration times. Among them, the decision support time of the method in this paper is always less than 2 s, while the time of the other two methods is longer. Compared with the other two methods, the decision support time of the method in this paper is shortened by about 1.7 s and 3.1 s, respectively. This is because this method classifies the data attribute gap in decision support, which saves the time of decision support. It is verified that the method in this paper can carry out decision support quickly and has certain reliability. It is proved that intelligent decision system can effectively improve Python data analysis and attribute information extraction.
Spatial Distribution Characteristics and Accessibility Analysis of Characteristic Towns in Guangdong Province Based on Ripley’s K Function
Authors: Liao Zhenjie , Zhang Lijuan
Published: April 2022

Characteristic towns are an essential focus for developing urbanization and implementing rural revitalization in China. Studying the spatial distribution characteristics and influencing factors are of great significance for the scientific and rational cultivation and deployment of characteristic towns and promotion of the integrated development of urban and rural areas. The spatial distribution characteristics and accessibility of 142 characteristic towns in Guangdong Province were investigated using Ripley's K function and kernel density estimation. The results show that (1) the characteristic towns in Guangdong Province present the overall spatial distribution characteristics of “the Pearl River Delta region” and the local distribution characteristics of multicore diffusion in “eastern Guangdong” and “western Guangdong”; (2) the spatial distribution of industrial development, cultural tourism type, innovative and creative characteristic towns shows significant agglomeration, whereas the agglomeration characteristics of agricultural service‐oriented and commercial and trade circulation‐oriented characteristic towns are not significant; (3) population, economy, resources, and location are the main factors affecting the spatial distribution of characteristic towns in Guangdong Province; (4) the overall spatial accessibility of characteristic towns in Guangdong Province is relatively good. However, the accessibility of characteristic towns of industrial development is better than that of other types of characteristic towns.
Topological Study of Zirconium TetrachlorideZrCl4under Molecular Descriptors
Authors: Mufti Zeeshan Saleem , Anjum Rukhshanda , Tchier Fairouz , Sajid Hafsa , Xin Qin , Shami Faria Ahmed
Published: April 2022

Topological index is a numerical parameter which characterizes the topology of the molecular structure. Topological indices are a very prominent part of the study of chemical structures in which properties of organic or inorganic compounds are under observation and calculated such as physical properties, chemical reactivity, or biological activity. Most of the topological indices of molecular graph-based structure which depends on vertex degrees have been visualized. In this study, we compute some degree-based topological indices of zirconium tetrachlorideZnCl4m,n.
IoT‐Based Wearable Devices for Patients Suffering from Alzheimer Disease
Authors: Salehi Waleed , Gupta Gaurav , Bhatia Surbhi , Koundal Deepika , Mashat Arwa , Belay Assaye
Published: April 2022

The disorder of Alzheimer’s (AD) is defined as a gradual deterioration of cognitive functions, such as the failure of spatial cognition and short‐term memory. Besides difficulties in memory, a person with this disease encounters visual processing difficulties and even awareness and identifying of their beloved ones. Nowadays, recent technologies made this possible to connect everything that exists around us on Earth through the Internet, this is what the Internet of Things (IoT) made possible which can capture and save a massive amount of data that are considered very important and useful information which then can be valuable in training of the various state‐of‐the‐art machine and deep learning algorithms. Assistive mobile health applications and IoT‐based wearable devices are helping and supporting the ongoing health screening of a patient with AD. In the early stages of AD, the wearable devices and IoT approach aim to keep AD patients mentally active in all of life’s daily activities, independent from their caregivers or any family member of the patient. These technological solutions have great potential in improving the quality of life of an AD patient as this helps to reduce pressure on healthcare and to minimize the operational cost. The purpose of this study is to explore the State‐of‐the‐Art wearable technologies for people with AD. Significance, challenges, and limitations that arise and what will be the future of these technological solutions and their acceptance. Therefore, this study also provides the challenges and gaps in the current literature review and future directions for other researchers working in the area of developing wearable devices.
Performance Comparison of New Adjusted Min-Max with Decimal Scaling and Statistical Column Normalization Methods for Artificial Neural Network Classification
Authors: Sinsomboonthong Saichon
Published: April 2022

In this research, the normalization performance of the proposed adjusted min-max methods was compared to the normalization performance of statistical column, decimal scaling, adjusted decimal scaling, and min-max methods, in terms of accuracy and mean square error of the final classification outcomes. The evaluation process employed an artificial neural network classification on a large variety of widely used datasets. The best method was min-max normalization, providing 84.0187% average ranking of accuracy and 0.1097 average ranking of mean square error across all six datasets. However, the proposed adjusted-2 min-max normalization achieved a higher accuracy and a lower mean square error than min-max normalization on each of the following datasets: white wine quality, Pima Indians diabetes, vertical column, and Indian liver disease datasets. For example, the proposed adjusted-2 min-max normalization on white wine quality dataset achieved 100% accuracy and 0.00000282 mean square error. To conclude, for some classification applications on one of these specific datasets, the proposed adjusted-2 min-max normalization should be used over the other tested normalization methods because it performed better.
Evaluation and Selection of Insurance Marketing Schemes Driven by Multisource Big Data
Authors: Wu Xian , Liu Huan
Published: April 2022

Insurance marketing is a discipline that maximizes the benefits between policyholders and insurance companies. A big data-driven approach combined with insurance promotions can leverage a wealth of empirical data to develop new customers, motivate existing customers to engage in more activities, and retain existing customers. Insurance business involves a wide variety of scopes and types, and it is labor-intensive and resource-intensive to rely solely on insurance business personnel to process these tedious data. The data-driven approach can find correlations and perform automatic prediction matching according to the characteristics of insurance business data, which saves a lot of time and labor costs. This research uses data mining method and neural network method to mine insurance business data and predict insurance business. This method can accurately capture factors such as the type of insurance business and the amount of the policyholder. The research results show that data mining technology and neural network method have high accuracy and feasibility in predicting insurance business, the prediction error is within 2.38%, and the linear correlation exceeds 0.96. The method used in this study has high accuracy both in terms of new customers and retention of old customers.
Application of IoT Authentication Key Management Algorithm to Personnel Information Management
Authors: Wang Qing , Li Haoran
Published: April 2022

A new IoT authentication protocol is presented to address the security deficiencies in the Z-Wave protocol. The new protocol is based on Diameter and includes authentication/authorization module, billing module, and secure communication module. According to the characteristics of IoT devices, the relevant algorithms are optimized, and the key agreement scheme based on elliptic curve algorithm and the symmetric encryption scheme based on AES and RC4 are introduced, which enhances the security of the protocol and also improves the system performance. The speed of response reduces the energy consumption of the system. Aiming at solving the problem that the existing polynomial-based key predistribution management scheme is limited by the key sharing rate between the nodes and the network connectivity rate, a quadratic-based wireless sensor key management scheme is proposed. The scheme breaks through the existing idea of building a shared key with a binary t-order symmetric polynomial, introduces a multivariate asymmetric quadratic polynomial, and utilizes the relationship between the quadratic eigenvalues and eigenvectors. The analysis proves that the quadratic form can be orthogonally diagonalized and uses it to generate key information, and nodes realize identity authentication by exchanging key information. The establishment of an independent and unique session key with the neighbor node is completed. The security performance analysis and simulation results show that, compared with the existing key management schemes, the scheme has great improvements in anti-capture property, connectivity, scalability, communication overhead, and storage overhead. After a series of functional tests, the enterprise information system based on the SaaS platform in this paper basically met the design requirements and finally realized the networking of the enterprise information management process and the sharing of information. Each functional module of the system can be used normally. When the input and output are wrong, the system will have a correct prompt. The buttons and various controls of the system can work normally, meeting the requirements of functional testing. Each document of the system is correct and complete, and the language description and logic meet the needs of users and meet the requirements of document testing. The test results show that the interface of the system is friendly and easy to operate and the performance of the system is stable, which is basically in line with the needs of users and achieves the design goal of this system.
A New Mn(II) Complex: Magnetic Property and Application Values in Foot and Ankle Arthritis
Authors: Jia Xiaochuan , Jiang Liqiang , Cui Shubei , Jia Haidong
Published: April 2022

The solvothermal reactions of C3-symmerical 4,4

′

,4

′

-nitrilotribenzoic acid and MnCl2 afforded a novel Mn(II) compound, and its formula is [Mn3(TCA)2(e-urea)2(DMA)2]n·n(urea)·n(DMA) (1, H3TCA=4,4

′

,4

′

-nitrilotribenzoic acid, e-urea=2-imidazaolidone, DMA=N,N

′

-dimethylacetamide). Magnetic property investigation of 1 indicates weak antiferromagnetic mutual effects exist between neighboring Mn(II) ions. Serial biological tests were adopted to discover new compound activity. Firstly, the enzyme-linked immunosorbent assay (ELISA) was conducted to measure the content of inflammatory cytokines released into the synovial fluid. In addition, we also studied adenosine 5

′

-monophosphate- (AMP-) activated protein kinase (AMPK) inflammatory signaling pathway activation through real-time reverse transcription-polymerase chain reaction (RT-PCR).
PTFE in Wet and Dry Drilling: Two-Tier Modeling and Optimization through ANFIS
Authors: Elango Sangeetha , Varadaraju Kaviarasan , Natarajan Elango , Abraham Gnanamuthu Ezra Morris , Durairaj R. , Mariappan P.
Published: April 2022

This research is done to determine the optimum parameters to drill polytetrafluoroethylene (PTFE) and to investigate the effect of two-tier modeling for enhanced response in optimization. RSM model was done with L27 experimental design, considering speed (N), feed (f), and tool point angle (Ɵ). RSM data were further trained and tested using the Adaptive Neuro-Fuzzy Inference System (ANFIS), and β coefficient values were restructured to form revised RSM model. Both nonrevised RSM model and revised RSM model were used in Genetic Algorithm to locate the minimum surface roughness. ANFIS revised RSM model deviates from the experimental results by 2.6% and 2.86% for dry and wet condition; meanwhile, nonrevised RSM model deviates by 4.76% and 4.94%, respectively. The research concludes that two-tier modeling using RSM and ANFIS is better. Spindle speed of 1656 rpm, feed rate of 0.05 mm/min, and point angle of 100° are the optimum conditions to drill PTFE material where the best surface quality of 0.68 μm at wet drilling can be achieved.
Multiparametric Optimization on Influence of Ethanol and Biodiesel Blends on Nanocoated Engine by Full Factorial Design
Authors: Venkatesh A. P. , Latchoumi T. P. , Chezhian Babu S. , Balamurugan K. , Ganesan S. , Ruban M. , Mulugeta Lijalem
Published: April 2022

Energy conservation and management have become critical industrial activities, since energy expenses account for a significant portion of production costs. This proactive strategy has had an effect on worldwide energy consumption trends. Integration of thermal barrier coatings into engine design is necessary to solve efficiency concerns, and this coating technology has the potential to increase engine power while lowering specific fuel consumption. In a similar line, biodiesel has been presented as a possible substitute to diesel since it is nontoxic and sourced from renewable energy sources. The present study aims to enhance the performance of a diesel engine via the use of a thermal barrier‐coated piston that works on biodiesel mixes. Due to its outstanding thermal insulation qualities, yttria‐stabilized zirconia is the preferred material for thermal barrier coatings. Brake thermal efficiency for B20E15 is about 4% better than diesel and for B20E05 and B20E15 is about 4.6% and 13.5% less fuel consumption. CO and HC emissions were reduced by 6% to 8% on average with the B20 blends. Biodiesel blends were compared to pure diesel in terms of performance and emissions, and the blend ratio was improved using a design of experiment tool.
Seismic Analysis of Reticulated Shell Structure Based on Sensor Network for Smart Transportation Seismic Isolation Bearings
Authors: Peng Jun , Li Yufei
Published: April 2022

Earthquakes are one of the most frequent and inevitable natural disasters that occur on Earth. The most important seismic isolation device used in the isolation technology is the isolation bearing, but the limited structure of the isolation bearing is not suitable for the seismic isolation and shock absorption of smart transportation buildings. Therefore, it is very important to improve the new generation of seismic isolation structures with good seismic isolation effect, stable performance, and economical performance. It is very important to study the structural composition of the isolation bearing and the rigidity of the isolation structure. Isolation bearings are designed to resist and absorb the energy of seismic shocks by installing substructures in the structure. Active control involves installing sensors on the structure and its foundation to determine how the structure responds to seismic action. In this paper, based on the intelligent transportation of the sensor network, the reticulated shell structure of the isolation bearing is analyzed. By introducing the architecture and network layout of the sensor network, it is beneficial to obtain more accurate seismic data in complex and difficult terrain. This paper analyzes the technical principle of seismic isolation technology, which can effectively avoid the upward transmission of ground vibration by increasing the flexibility and proper damping of the system. From the experimental data of the seismic response of the ground-isolated structure to the near-field pulsation and far-field vibration, the total energy of the ground-isolated structure under the near-field pulsed ground motion is the largest. The seismic isolation effect of the reticulated shell structure of the seismic isolation bearing prevents more than 80% of the seismic energy from being transmitted to the superstructure.
Application of Digital 3D Printing Technology in Ceramic Art Creation
Authors: Wang Mian , Zhao Xinyu , Sun Dan
Published: April 2022

3D printing technology is a modern technical means and process based on three-dimensional molding, digital manufacturing, reverse engineering, and other emerging fields. 3D printing ceramics is one of the diversified designs of modern ceramics. At the same time, with the development of 5G technology, the platform access method will make 3D printing easier and more common. The purpose of this paper is to study the printing, preparation, and sintering processes of ceramic materials based on 3D printing technology and realize the rapid prototyping of ceramic parts, which can meet the requirements of low-cost, single-piece, and small-batch processing. This paper proposes to focus on the research on materials, design methods, and technological processes suitable for ceramic 3D printing technology from the perspective of the integration of art and science. By using 3D printing technology to perform geometric functions, mixing, recombination, and other cutting-edge tasks, the composite design of works is enhanced. The experimental results show that in the high temperature sintering stage, 1600°C is the holding temperature, the heating rate is 0.5°C/min, and the holding time is 600 min, and the sintering effect of ceramic parts is better. The measured shrinkage rate of the ceramic sample does not exceed 16%, the porosity is 47%, the bulk density is 2.27 g/cm3, and the density is 53.2%. The results show that the ceramic parts prepared by this process can meet the basic performance requirements.
The Asymmetry of the Cosmic Microwave Background Radiation as Signature of Local Lorentz Invariance Violation
Authors: Albertini Gianni , Cardone Fabio , Bellucci Stefano
Published: April 2022

A difference in electric potential in a static conductor inside a static magnetic field and an anisotropic and asymmetric distribution of neutrons emitted in nuclear reactions induced by ultrasound are assumed as marks of local Lorentz invariance (LLI) violation. The asymmetry of the two experiments is related to the asymmetry of the Cosmic Microwave Background Radiation (CMBR). As common directions of asymmetry are found in these three cases, a fundamental asymmetry of the interactions is suggested which can also shed new light on the question of symmetry breaking in the history of the Universe.
Investigation of CO2 Extract of Portulaca oleracea for Antioxidant Activity from Raw Material Cultivated in Kazakhstan
Authors: Tleubayeva Meruyert I. , Abdullabekova Raisa M. , Datkhayev Ubaidilla М. , Ishmuratova Margarita Yu. , Alimzhanova Mereke B. , Kozhanova Kaldanay K. , Seitaliyeva Aida M. , Zhakipbekov Kairat S. , Iskakova Zhanar B. , Serikbayeva Elmira A. , Flisyuk Elena V.
Published: April 2022

Medicinal plants remain as an important resource in the fight against many diseases, especially in developing countries. Antioxidants are substances capable of delaying, retarding, and preventing the oxidation of lipids or substances that delay or prevent free radical reactions during lipid oxidation. Natural antioxidants such as ascorbic acid, tocopherol, phenolic compounds, and flavonoids are a safe alternative to chemical antioxidants. In present work, results of antioxidant activity of raw materials from the cultivated plant Portulaca oleracea are presented. The extraction time was optimized to 780 minutes; the yield of extractive substances was 1.25% in the production of CO2 extract under subcritical conditions. For the first time, the antioxidant activity of Portulaca oleracea CO2 extract was determined by the amperometric method. Gas chromatography-mass spectrometry (GC-MS) chemical analysis of Portulaca oleracea CO2 extract dissolved in hexane revealed 37 components, including a complex mixture of aldehydes, alkanes, alkenes, esters, diterpenes, steroids, vitamin E, and carbohydrates. The investigation results showed that the Portulaca oleracea CO2 extract was promising for pharmaceutical, cosmetic, and food industries and had great potential for the prevention and treatment of diseases caused by oxidative stress.
[Retracted] Leveraging Digital Library to Enhance Research and Learning Experience of College Students: An In‐Depth Study
Authors: Yang Chunying
Published: April 2022

A digital library is a platform that contains collections of books, services, and personnel to support the sharing of knowledge with creation, dissemination, and preservation. In this context, any university library should comprehensively embrace the developmental trend occurring in the library setting, which should be strictly followed by university libraries as a special mission. Digital libraries should also actively promote the updating of the embedded service model and further upgrade the various resources of the university library. Thus, the digital library provides a platform to assist students to develop an inclination towards learning and emotional shaping. Its functional system thus serves both comprehensive and harmonious development of students. Especially, the knowledge service module of the digital library incorporates users’ scientific research context. Most of the existing research studies focus on the individual researcher and neglects the context of the entire research team. Knowledge recommendation for the context of team‐based scientific research activities can better serve more scientific research activities and team cooperation. In this work, we propose a knowledge recommendation algorithm for digital libraries based on team research‐knowledge application in context matching. We leverage the context‐aware learning model to construct the corresponding application context of the digital library knowledge and the context model of team scientific research. Subsequently, we select alternative knowledge and neighbor users as active users and further complete knowledge sorting and recommendation. According to the knowledge recommendation system in a digital library, it is confirmed that the proposed method can effectively deliver the knowledge of researchers in the context of the digital library.
Descriptive Literature Review and Classification of Community Cloud Computing Research
Authors: Aldahwan Nouf S. , Ramzan Muhammed S.
Published: April 2022

Cloud computing has been devoted to the development of recent advanced technology, aiding in improving a government’s functioning and the services it offers to its people and organizations. It has achieved widespread popularity due to the rising number of benefits, including scalability, versatility, reliability, safety, confidentiality, pay-per-use, and dynamicity for the distribution of IT services. This paper explores a descriptive literature review and aims to classify the scattered communities involved in cloud computing research in information technology. This involves 51 referred published articles between 2010 and 2020 relating to the inception of community cloud computing by various organizations. Based on a systematic structured of reviewed literature and grounded theory approach, articles are categorized with respect to the eleven key influencing variables: cost, security, performance, QoS, trust, accuracy, ease of use, usefulness, architecture, framework, and model. Following that, those variables are comprehended into final one in order to envisage the community cloud computing adoption factors and concepts. This will consent for a strong examination of the community cloud computing phenomenon. The study is a novel attempt to demonstrate the differences in key factors for cloud computing in varying community settings and their causal relationships among the considered variables. The findings from the long-term systematic review contribute by assisting a collection of determinants for the penetration of community clouds services and potential adopters. It could serve as a basis for future directions and the development of theories in the exploring the community cloud computing in the field of information systems. This study contributes to identify various existing research gaps by providing holistic insights and future exploratory approaches that are anticipated to result in a robust unified structure for the adoption of community cloud computing services in the higher education institution (HEIs).
Study on Mechanical Performance of ECC Reinforced by Polypropylene Fiber Mixed with Manufactured Sand and Carbon Black (CBMSPP-ECC) Based on Response Surface Method
Authors: Song Nixia , Song Min , Zhang Yunlong , Wang Jing
Published: April 2022

In order to study the mechanical performance of Engineered Cementitious Composites (ECCs) mixed with carbon black (CB), manufactured sand (MS), and polypropylene fiber (PPF), response surface methodology (RSM) was used to design the experiment, and three process variables including PPF content, fly ash content (FA), and CB content were selected as factors. The flexural strength, compressive strength, flexural-compressive ratio, and splitting tensile strength were used as four responses to study the mechanical performance. The prediction model indicates that there is a good correlation between the factors and the responses. Multiobjective optimization results show that the optimal content of the three factors is 2.4%, 58.48%, and 1.09%, respectively, for the carbon black, and manufactured sand of polypropylene fiber reinforced ECC development laid a foundation.
A Sport Monitoring System Based on the Optimized Adaptive Fuzzy PID Control Algorithm in OneNet Internet of Things and Cloud Platform
Authors: Zhang Di , Min Hyun Joo
Published: April 2022

Aiming at some problems existing in the existing sports monitoring system, based on the joint action of OneNet Internet of Things (IoT) and cloud platform, an optimized adaptive fuzzy PID control algorithm is adopted to monitor and analyze sports. Finally, the accuracy of the optimization model is verified through the comparison of different models, and the algorithm is used to predict and analyze sports. The research shows that (1) as the index calculation of cloud platform shows, with the increase of iteration time, the change curve of relevant indexes can be divided into four different stages, namely, rapid fluctuation stage, slow decline stage, slow fluctuation stage, and rapid decline stage. (2) The conventional calculation method (CPID) cannot well describe the change rule of the test data in the early stage of settlement. The fuzzy adaptive calculation method (NPID) also exposes some errors in the fitting and description of the test curve in the calculation process, while the improved adaptive calculation method (GPID) can describe the change characteristics and rules of the test curve well for different stages. (3) Compared with the original model, the optimization model can better describe the first and second stages of index change, indicating the accuracy of the optimization model. And the algorithm can be used to predict and analyze the changes of indicators and sports monitoring better, and the analysis results can provide relevant guidance for sports monitoring. This optimization scheme provides basis and theoretical support for the application of OneNet IoT and cloud platform.
In Vitro Immunomodulatory Effects of Inonotus obliquus Extracts on Resting M0 Macrophages and LPS-Induced M1 Macrophages
Authors: Shen Dayue , Feng Yating , Zhang Xilan , Liu Jing , Gong Le , Liao Hui , Li Rongshan
Published: April 2022

Background. Inonotus obliquus (Chaga) is a parasitic fungus that is distributed mainly in northeast China. Our literature research showed chaga polysaccharides have bilateral effects on tumor necrosis factor (TNF)-α and interleukin (IL)-1β levels when they exert antitumor and antidiabetic activities. The current research tried to explore the influence of chaga extracts on inflammatory factors via macrophage polarization which has bilateral immune-regulation not only on healthy tissue homeostasis but also on pathologies. Methods. Chaga was extracted with 100°C water and precipitated with 80% ethanol. The extracts were studied on RAW264.7 macrophage at resting condition (M0) and lipopolysaccharide (LPS)-activated subtype (classic activated macrophage, M1). The IL-1β, TNF-α, nitric oxide (NO) level, and the protein expressions of M1 and alternative activated macrophage (M2) markers including IL-1β, inducible NO synthase (iNOS), mannose receptor (CD206), and arginase (Arg)-1 were compared. Results. The 100 g extracts contained 13.7 g polysaccharides and 1.9 g polyphenols. Compared with M0, the 50 μg/mL extracts increased NO level (

P
<
0.05

) and decreased CD206 and Arg-1 expression significantly (

P
<
0.05

). The extracts at 100–200 μg/mL increased NO and TNF-α level (

P
<
0.05

), but increased iNOS and IL-1β expression significantly (

P
<
0.05

). Compared with M1, the extracts decreased NO level at 25, 50, 100, and 200 μg/mL and decreased IL-1β and TNF-α level at 100–200 μg/mL significantly (

P
<
0.05

). At 25–200 μg/mL, the extracts significantly increased CD206 and Arg-1 expression and decreased IL-1β and iNOS expression separately (

P
<
0.05

). Conclusions. Our research suggested that the bilateral effects of the chaga extracts on iNOS, IL-1β, and NO level on M0/M1 macrophages might be related with chaga polysaccharides and chaga polyphenols. Some in vivo anticancer and antidiabetic research of purified chaga polysaccharides related to macrophage differentiation should be conducted further.