bluuebunny/crossref_metadata_2025 huggingface dataset:
Maximum Entropy Bi-Objective Model and its Evolutionary Algorithm for Portfolio Optimization
Authors: Liu Chun-An , Lei Qian , Jia Huamin
Published: April 2022

Diversification of investment is a well-established practice for reducing the total risk of investing. Portfolio optimization is an effective way for investors to disperse investment risk and increase portfolio return. Under the assumption of no short selling, a bi-objective minimizing portfolio optimization model, in which the first objective is a semi-absolute deviation mean function used to measure the portfolio risk, and the second objective is a maximum entropy smooth function used to measure the portfolio return, is given in this paper. Also, a maximum entropy multi-objective evolutionary algorithm is designed to solve the bi-objective portfolio optimization model. In order to obtain a sufficient number of uniformly distributed portfolio Pareto optimal solutions located on the true Pareto frontier and fully exploit the useful asset combination modes which can lead the search process toward the frontier direction quickly in the objective space, a subspace multi-parent uniform crossover operator and a subspace decomposition mutation operator are given. Furthermore, a normalization method to deal with the tight constraint and the convergence analysis of the proposed algorithm are also discussed. Finally, the performance of the proposed algorithm is verified by five benchmark investment optimization problems. The performance evaluations and results analyses illustrate that the proposed algorithm is capable of identifying good Pareto solutions and maintaining adequate diversity of the evolution population. Also, the proposed algorithm can obtain faster and better convergence to the true portfolio Pareto frontier compared with the three state-of-the-art multi-objective evolutionary algorithms. The result can also provide optimal portfolio plan and investment strategy for investors to allocate and manage asset effectively.
Total dominator coloring number of middle graphs
Authors: Kazemnejad Farshad , Pahlavsay Behnaz , Palezzato Elisa , Torielli Michele
Published: April 2022

A total dominator coloring of a graph G is a proper coloring of G in which each vertex of the graph is adjacent to every vertex of some color class. The total dominator chromatic number of a graph is the minimum number of color classes in a total dominator coloring. In this paper, we study the total dominator coloring on middle graphs by giving several bounds for the case of general graphs and trees. Moreover, we calculate explicitly the total dominator chromatic number of the middle graph of several known families of graphs.
Quality Function Deployment Framework for Selecting Optimal Greenhouse Microclimate Control System
Authors: Elhegazy Hosam , Mahmoud Wafaa , Eid Mohamed , Khairy Nahed
Published: April 2022

As greenhouse production is considered the most water-conservative solution in the agricultural sector, greenhouse technology has become an integral approach for modern crop production methods. Different types of greenhouse structures are used to produce crops, and each type has advantages for a particular application, having been designed to meet multiple and specific requirements. This paper introduces a quality function deployment (QFD) framework to select two optimal greenhouse types (single-span and multi-span). This study aims to demonstrate greenhouse management and practices and review the development efforts during the last two decades. A market survey, focus group discussion, and personal interviews revealed nine key performance indicators (KPIs) (cost, wind loads, crop loads, roof slope, light transmission, flexibility, maintainability, rapid spread/ease of control, and heating and ventilation). Then, the participating decision-makers identified nine functional requirements, which, if fulfilled, would boost client satisfaction. The framework designed in this paper was developed to select and analytically investigate the optimal system for greenhouse microclimate control based on the retrieved KPIs and functional requirements for client satisfaction. This QFD framework can assist decision-makers, in the preliminary phase, in selecting optimal systems for greenhouse microclimate control based on their individualized situations.
Self-supervised Short-text Modeling through Auxiliary Context Generation
Authors: Choudhary Nurendra , Aggarwal Charu C. , Subbian Karthik , Reddy Chandan K.
Published: April 2022

Short text is ambiguous and often relies predominantly on the domain and context at hand in order to attain semantic relevance. Existing classification models perform poorly on short text due to data sparsity and inadequate context. Auxiliary context, which can often provide sufficient background regarding the domain, is typically available in several application scenarios. While some of the existing works aim to leverage real-world knowledge to enhance short-text representations, they fail to place appropriate emphasis on the auxiliary context. Such models do not harness the full potential of the available context in auxiliary sources. To address this challenge, we reformulate short-text classification as a dual channel self-supervised learning problem (that leverages auxiliary context) with a generation network and a corresponding prediction model. We propose a self-supervised framework,
Pseudo-Auxiliary Context generation network for Short-text Modeling (PACS)
, to comprehensively leverage auxiliary context and it is jointly learned with a prediction network in an end-to-end manner. Our PACS model consists of two sub-networks: a Context Generation Network (CGN) that models the auxiliary context’s distribution and a Prediction Network (PN) to map the short-text features and auxiliary context distribution to the final class label. Our experimental results on diverse datasets demonstrate that PACS outperforms formidable state-of-the-art baselines. We also demonstrate the performance of our model on cold-start scenarios (where contextual information is non-existent) during prediction. Furthermore, we perform interpretability and ablation studies to analyze various representational features captured by our model and the individual contribution of its modules to the overall performance of PACS, respectively.
A Survey on Fault Attacks on Symmetric Key Cryptosystems
Authors: Baksi Anubhab , Bhasin Shivam , Breier Jakub , Jap Dirmanto , Saha Dhiman
Published: April 2022

Fault attacks are among the well-studied topics in the area of cryptography. These attacks constitute a powerful tool to recover the secret key used in the encryption process. Fault attacks work by forcing a device to work under non-ideal environmental conditions (such as high temperature) or external disturbances (such as glitch in the power supply) while performing a cryptographic operation. The recent trend shows that the amount of research in this direction—which ranges from attacking a particular primitive, proposing a fault countermeasure, to attacking countermeasures—has grown up substantially and is going to stay as an active research interest for the foreseeable future. Hence, it becomes apparent to have a comprehensive yet compact study of the (major) works. This work, which covers a wide spectrum in the present-day research on fault attacks that fall under the purview of the symmetric key cryptography, aims at fulfilling the absence of an up-to-date survey. We present mostly all aspects of the topic in a way that is not only understandable for a non-expert reader, but also helpful for an expert as a reference.
Mitigation Measures for Windfarm Effects on Radar Systems
Authors: Ella Omar Abu , Alnajjar Khawla A.
Published: April 2022

Windfarms can have a significant impact on radar systems, especially air surveillance radar. This is because it is usually designed to show only moving targets and cancel out stationary objects. However, the rotation of wind turbine blades can be detected by radar as a false flight or target. Clutter or interference caused by windfarms can reduce radar sensitivity in critical regions, making real targets disappear. This could in turn affect the deployment of windfarms and lead to the cancellation of future renewable energy projects and plans. This paper presents the different strategies and techniques used to mitigate the windfarm impact on radar systems. Precisely, we aim throughout this article to classify the main currently adopted approaches, view the recent trends and research directions in this field, and try to trace the advantages and drawbacks along with the challenges of deploying such schemes.
Use of Off-Label Drugs and Nutrition Supplements among Patients with Amyotrophic Lateral Sclerosis in Norway
Authors: Skulstad Johanson Gard Aasmund , Tysnes Ole-Bjørn , Bjerknes Tale L.
Published: April 2022

Background and Objectives. Amyotrophic lateral sclerosis (ALS) is a lethal neurodegenerative disease, characterized by gradual paralysis and muscle atrophy. Riluzole, the only approved treatment in Norway, increases mean survival by 3–6 months. The use of off-label medications and nutritional supplements is common in other serious conditions, such as Parkinson’s disease and dementia. The aims of this study were to investigate to what extent Norwegian ALS patients use supplements and off-label medications and whether this is related to their health-related quality-of-life (HRQOL). Materials and Methods. A cross-sectional questionnaire study was performed, where 41 ALS patients reported their use of off-label treatments, as well as self-perceived HRQOL using the RAND-12 questionnaire. Results. A majority of respondents used riluzole. Of the 41 respondents, 18 (43.9%) reported use of off-label medications and 18 (43.9%) used nutritional supplements. Low-dose naltrexone was the most commonly used off-label medication, whereas vitamins accounted for most of the nutritional supplements. The respondents’ RAND-12 component scores were significantly lower than those of the general population. Low-dose naltrexone and vitamin B were associated with a better physical component score. Conclusions. Most of the respondents in our study adhere to the recommended treatment protocols, as less than half of them reported using off-label medications or nutritional supplements against ALS. Positive correlations between physical HRQOL and use of low-dose naltrexone or vitamin B were demonstrated. These results warrant further investigations.
Annotating Spike Protein Polymorphic Amino Acids of Variants of SARS-CoV-2, Including Omicron
Authors: Mahardika Gusti Ngurah , Mahendra Nyoman B. , Mahardika Bayu K. , Suardana Ida B. K. , Pharmawati Made
Published: April 2022

The prolonged global spread and community transmission of severe acute respiratory syndrome virus 2 (SARS-CoV-2) has led to the emergence of variants and brought questions regarding disease severity and vaccine effectiveness. We conducted simple bioinformatics on the spike gene of a representative of each variant. The data show that a number of polymorphic amino acids are located mostly on the amino-terminal side of the S1/S2 cleavage site. The Omicron variant diverges from the others, with the highest number of amino acid substitutions, including the receptor-binding site (RBS), epitopes, S1/S2 cleavage site, fusion peptide, and heptad repeat 1. The current sharp global increase in the frequency of the Omicron genome constitutes evidence of its high community transmissibility. In conclusion, the proposed guideline could give an immediate insight of the probable biological nature of any variant of SARS-Cov-2. As the Omicron diverged the farthest from the original pandemic strain, Wuhan-Hu-1, we expect different epidemiological and clinical patterns of Omicron cases. On vaccine efficacy, slight changes in some epitopes while others are conserved should not lead to a significant reduction in the effectiveness of an approved vaccine.
Cultivation of Teenagers’ Digital Media Literacy and Network Legal Literacy in the Era of Digital Virtual Technology
Authors: Lv Yipin
Published: April 2022

Digital virtual technology with media survival as an important representation, with the rapid development of the new media technology represented by the Internet, digital virtual technology with its entertainment, personalized service, open sharing of content, form of real-time interaction and other characteristics strongly attract the young group. In the digital virtual era, teenagers’ digital media literacy has not only become one of the essential qualities for them to cope with global competition, but also an essential quality for college students to realize lifelong learning. Therefore, it is not only necessary but also urgent to carry out systematic digital media literacy education for adolescent groups. This study first discusses that the typical illegal phenomenon in the network is the problem caused by the lack of network legal awareness, and analyzes the level of media literacy of the subject media in these cases and whether the network legal awareness is weak. Finally, from the perspective of school education, social publicity and national system support, this paper puts forward some Suggestions on how to improve teenagers’ media literacy and cultivate their network legal literacy, so as to create a harmonious network environment. Establish a scientific and reasonable indicator system of youth network literacy, and build a youth network literacy training mechanism.
Land Use Classification Using Improved U-Net in Remote Sensing Images of Urban and Rural Planning Monitoring
Authors: Xie Xiaoling , Ye Lin , Kang Xueqin , Yan Lei , Zeng LiQin
Published: April 2022

Aiming at the problem of low accuracy and efficiency of existing land use classification methods for high-resolution remote sensing image segmentation, a land use classification method using improved U-Net in remote sensing images of urban and rural planning monitoring is proposed. First, taking the high-resolution remote sensing images of different remote sensing satellites as the data source, the remote sensing images in the data source are registered and cropped so that the pixels at the corresponding positions represent the same geographical location. Then, the encoder of the U-Net model is combined with the residual module to share the network parameters and avoid the degradation of the deep network. The dense connection module is integrated into the decoder to connect the shallow features with the deep features, so as to obtain new features and improve the feature utilization rate. Finally, the depthwise separable convolution is used to process the spatial and channel information of the convolution process separately to reduce the model parameters. Experiments show that the pixel accuracy, recall rate, precision rate, and average intersection-over-union ratio of the proposed land use classification method based on improved U-Net are 92.35%, 80.56%, 83.45%, and 86.75%, respectively, which are better than the compared methods. Therefore, the proposed method is proved to have good land use classification ability.
Kindlin-2 Promotes Chondrogenesis and Ameliorates IL-1beta-Induced Inflammation in Chondrocytes Cocultured with BMSCs in the Direct Contact Coculture System
Authors: Chen Zhefeng , Shen Kai , Zheng Ziyang , Zhou Jinchun , Zhao Shujie , Song Huanghe , Liu Jiuxiang , Zhao Xuan , Liu Feng , Zuo Qiang
Published: April 2022

The osteoarthritis caused by trauma or inflammation is associated with severe patient morbidity and economic burden. Accumulating studies are focusing on the repair of articular cartilage defects by constructing tissue-engineered cartilage. Recent evidence suggests that optimizing the source and quality of seed cells is one of the key points of cartilage tissue engineering. In this study, we demonstrated that Kindlin-2 and its activated PI3K/AKT signaling played an essential role in promoting extracellular matrix (ECM) secretion and ameliorating IL-1beta-induced inflammation in chondrocytes cocultured with bone marrow stem cells (BMSCs). In vivo experiments revealed that coculture significantly promoted hyaline cartilage regeneration. In vitro studies further uncovered that chondrocytes cocultured with BMSCs in the direct contact coculture system upregulated Kindlin-2 expression and subsequently activated the PI3K/AKT signaling pathway, which not only increases Sox9 and Col2 expression but also restores mitochondrial membrane potential and reduces ROS levels and apoptosis under inflammatory conditions. Overall, our findings indicated that direct contact BMSC-chondrocyte coculture system could promote chondrogenesis, and identified Kindlin-2 represents a key regulator in this process.
Modelling the Effects of Meteorological Factors on Maximum Rainfall Intensities Using Exponentiated Standardized Half Logistic Distribution
Authors: Sasanya B. F. , Awodutire P. O. , Ufuoma O. G. , Balogun O. S.
Published: April 2022

Rainfall intensity prediction or forecast is vital in designing hydraulic structures and flood and erosion control structures. In this work, meteorological data were obtained from the National Aeronautics and Space Administration’s (NASA) website. Models estimating maximum rainfall intensities were derived, and some meteorological factors’ effects on the models were tested. The meteorological factors considered include annual relative humidity averages, specific humidity, temperature range at 2 m, maximum temperature, and minimum temperature. This research was aimed at developing a model for estimating maximum rainfall intensities, and the effects of various meteorological factors on the models were investigated. The exponentiated standardized half logistic distribution (ESLD) was used to model the effects of the factors and return periods on 35 years’ (1984–2018) annual maxima monthly rainfall intensities for Port Harcourt metropolis, Nigeria. The model parameters were estimated using the maximum likelihood estimation method. Compared with the results from the five standard distributions, three criteria were used to determine the best-performed distribution. These indicated that the ESLD performed considerably better than the other five compared distributions. Only the return period had significant effects on the model for the rainfall intensity prediction since

p
<
0.05

, while the effects of the meteorological factors are insignificant.
Maternal Age and Stage of Pregnancy as Determinants of UTI in Pregnancy: A Case of Tamale, Ghana
Authors: Laari Jacob Loonin , Anab Martin , Jabong Damyetin Peter , Abdulai Kasim , Alhassan Abdul Rauf
Published: April 2022

Introduction. Urinary tract infection (UTI) is the world’s second most common cause of death, trailing only respiratory tract infections. Because of anatomical and physiological changes along the urinary tract, pregnant women accounted for approximately 20% of all cases of urinary tract infection. Aim. This study sought to assess maternal age and stage of pregnancy as determinants of UTI among pregnant women in Tamale. Methods. This study employed a descriptive cross-sectional survey as the study design in the antenatal clinic of Tamale Central Hospital (TCH). This was carried out by reviewing laboratory records of urinalysis results done on pregnant women. Data entry and analysis were performed by the Statistical Package for the Social Sciences (SPSS) version 20. Chi-square and binary logistics analysis were used to determine the relationship. Results. Data analysis was done for 158 pregnant women, most (35.4%) were within the age group of 36-45 years, and most (38.6%) were within their first trimester. The overall prevalence of UTI infections among pregnant women was 33.5%. The prevalence was 27.8% for candiduria and 8.9% for bacteriuria. Women in the first trimester of their pregnancy were more likely to have UTI (

AOR
=
2.48

, 95% CI =1.03–5.94). Also, Pregnant women of the age group of 26-35 years were less likely to get UTIs as compared to those of the age group 15-25 years (

AOR
=
0.40

, 95% CI =0.17–0.92). Finally, those of the age group of 36-45 years were less likely to get UTI as compared to those of the age group 15-25 years (

AOR
=
0.28

, 95% CI =0.12–0.66). Conclusion. The prevalence of UTI among studied pregnant women was high (38.0%), and the most prone maternal age group and trimesters to UTI are 15-25 years and first trimester, respectively.
Performance Index Based on Predicted Auditory Reaction Time Analysis for the Evaluation of Human-Machine Interface in Flight Control
Authors: Yu Weiwei , Jin Dian , Yang Xinliang , Zhao Feng , Wang Haiyang , Peng Ran
Published: April 2022

With the rapid development of complex equipment, such as airplanes, the appropriate design of the human-machine interface is often upgraded, thus emerged many methods to evaluate whether such an upgrade is effective. Most researches focus on the time accumulation effect of the human state during the interaction to evaluate the interface. However, in the aviation application, the performance of the pilot’s instantaneous reactions also reveals the design efficiency of the interface, since the difficulty level of obtaining the useful information would severely influence the reaction time in some voice command tasks or emergency situations. Besides, there are so many flight scenarios that are impossible to be simulated in experiments or in a laboratory environment. Also, voice commands are too numerous to be traversed simulated. This paper introduced predicted auditory reaction time as an index to evaluate human-machine interface design. The proposed method has two advantages. On the one hand, it effectively measures the pilot’s auditory reaction time based on the eye movement tracking; thus, the data can be taken in flight task scenarios, and the experiment would not cause interference to the subjects. On the other hand, a prediction model is proposed, in which the pilot’s reaction time under more generalized voice command can be estimated based on a small-size sample set.
Application of Big Data Technology in Urban Greenway Design
Authors: Liu Shiyao
Published: April 2022

With the continuous advancement of big data technology, there are many drawbacks in the past urban greenway design. The environment, population distribution, geographic location, spatial distribution, and other factors affect the greenway design. At the same time, a large amount of historical data is mixed. The systematic arrangement has indirectly led to the fact that urban greenway design does not know how to analyze and use past data. There is always a waste of various resources. While greenways bring many positive impacts, they also have negative impacts: it is difficult for the wild animals in the greenways to move along the predetermined passages, and most animals spread in the greenways in a disorderly manner, so that the greenways accelerate the invasion of alien species and diseases to a certain extent. Using big data technology can enable us to allocate resources more reasonably and accurately. The purpose of this article is to study the use of big data technology to rationalize our urban greenway design. This paper adopts a calculation method that closely combines quantitative and qualitative features to study its features. The local feature analysis algorithm can extract and analyze urban spatial data. Spatial remote sensing image technology can deepen our knowledge and understanding of urban spatial characteristics, conduct data mining, provide all the information of urban space, analyze the content and type, and classify it; then filter and integrate the big data in the greenway planning and design information. The information about greenway planning and design in the big data of Dao Design is digitized. This information can be composed of traditional data and dynamic data. Finally, after scientific analysis, the data is subjected to scenario assumptions, modeling, and output, we applied various analysis results to actual operations, and we obtain the final inspection. In fact, this is also going out from actual work, summing up the experience we have done, and again starting from the perspective of specific practice. Compared with our traditional field investigation before, with the guidance of big data analysis, the experimental results of this article show that under the use of big data technology, the wrong resolution of the SegNet semantic classification algorithm for buildings is 9.6%, and the others are 10.9%, 16%, 20%, etc., which are all greater than 9.6%, so the segNet model has a higher image acquisition accuracy. It can solve the problems caused by the lag of the past questionnaires and the small sample size, improve the accuracy of data extraction through algorithms, find some features and problems of greenway design, and complete the urban greening rate through computer algorithms. Calculation and analysis can better provide the most reasonable method for greenway design site selection and route selection.
Antiangiogenic Strategies in Epithelial Ovarian Cancer: Mechanism, Resistance, and Combination Therapy
Authors: Jin Chengwen , Yuan Mingyuan , Bu Hualei , Jin Chengjuan
Published: April 2022

Angiogenesis is one of the hallmarks of cancer and plays a crucial role in carcinogenesis and progression of epithelial ovarian cancer. Antiangiogenic agent is the first approved targeted agent in ovarian cancer. Anti-angiogenic agents mainly include agents target VEGF/VEGFR pathway, such as bevacizumab and agents target receptor tyrosine kinase, and non-VEGF/VEGFR targets of angiogenesis. Antiangiogenic agents demonstrate certain effects in ovarian cancer treatment either as monotherapy or combined with chemotherapy. Unfortunately, antiangiogenic agents, such as bevacizumab, integrated into the ovarian cancer treatment paradigm do not increase cures. Thus, the benefits of anti-angiogenic agents must be carefully weighed against the cost and associated toxicities. Antiangiogenic agents drug resistance and short of predictive biomarkers are main obstacles in ovarian cancer treatment. A combination of poly (ADP-ribose) polymerase inhibitors or immune checkpoint inhibitors might be great strategies to overcome resistance as well as enhance anti-tumor activity of anti-angiogenic drugs. Predictive biomarkers of antiangiogenic agents are in urgent need.
Network Reconfiguration and Distributed Generation Placement for Multi-Goal Function Based on Improved Moth Swarm Algorithm
Authors: Nguyen Thuan Thanh , Duong Thanh Long , Ngo Thanh-Quyen
Published: April 2022

This paper demonstrates an effective method of performing network reconfiguration (NR) and distributed generation placement (DGP) simultaneously called NR-DGP for the multi-goal function of reducing power loss and voltage deviation as well as enhancing load balance and feeder balance with the least number of changing switches. These membership goals are combined by the fuzzy decision-making relied on the max-min technique. The results for the NR and NR-DGP on two test system including of 33 and 84 nodes are gained by the improved moth swarm algorithm (IMSA). Wherein, IMSA is developed based on the original moth swarm algorithm (MSA) with improvement of the exploration mechanism using Lévy distribution. The calculated results show that NR-DGP method has gained the better improvement of the test systems’ technical indicators than the NR only. The obtained results also show that IMSA has better performance for the NR and NR-DGP problems than the MSA in term the quality of the obtained optimal solution. Thus, IMSA can be an effective approach for determining the optimal solution of the NR and NR-DGP problems.
Complete Duplex of the Left Ureter with Lower Moiety Hydronephrosis Secondary to Ureteral Stone in Adult
Authors: Dino Masresha S. , Tefera Alemayehu Tegegn , Gebreselassie Kaleab Hebtemichael , Akkasa Sena Sefera , Mummed Ferid Ousman
Published: April 2022

Ureteral duplication is a common embryologic abnormality of the kidney with an incidence rate of 0.8% in adults. However, complete duplex ureters opening independently into the urinary bladder are rarely present. We report a 35-year-old female who presented with left flank pain in the last three years. Abdominal CT scan showed left complete duplicated system with lower moiety hydroureteronephrosis and obstructed midureteral stone. The patient underwent left retroperitoneal exploration with complete excision of the hydronephrotic sac. The postoperative course was uneventful without complications. In conclusion, a complete duplex kidney with lower moiety hydronephrosis caused by mid ureteric stone is rare. The renal duplication system should be diagnosed and followed with image guidance periodically as the late diagnosis may have poor outcomes with loss of the kidney or part of it.
Evaluation and Prediction Method of System Security Situational Awareness Index Based on HMM Model
Authors: Qian Mengjie
Published: April 2022

In recent years, with the continuous development and progress of information technology and science and technology, big data has entered all walks of life, integrated into the lives of the public, and has become a necessity for social operation; the gradual development of artificial intelligence has also made life in modern times. People in society are more and more convenient. However, the development of science and technology is also accompanied by corresponding problems, and the war in information has gradually started. This paper simulates the possible information security through the hidden Markov model and then verifies the feasibility and effectiveness of the situation assessment method and the situation prediction method, in order to effectively evaluate the relevant information security level and effectively predict the accuracy of the situation value. The experimental results show that the fluctuation of the situation value corresponds to the different attack behaviors carried out by the attacker, accurately describes the information security status of the system, and verifies the effectiveness and accuracy of the situational awareness method proposed in this paper, while the situation prediction method based on ARIMA predictable short-term changes in situational values can be used for short-term forecasts that require high accuracy.
Application of Style Transfer Algorithm in Interactive Art Design of Mobile Phone Interface
Authors: Guo Juan , Wang Ling
Published: April 2022

In recent years, touch-screen mobile phones have been loved by more and more users, and the word user experience has been mentioned more and more, and interface design has undoubtedly become an important method of interactive design of touch-screen mobile phones. With the progress of technology and market demand, the importance of rational design of smart phone interactive interface is particularly prominent, and user-centered experience design has been paid more and more attention. The traditional style migration is only used on computers, and its target audience is relatively small, with low efficiency and poor effect. At present, the application of interactive art design is becoming more and more homogeneous, without too much change in essential functions, and with no outstanding features in mature applications, some applications have failed to meet users’ expectations in terms of functions and operation modes, resulting in polarization of application use and difficulty for new applications to survive. Mobile phone theme design, as a new field of interface interaction design, meets the personalized needs of users and attracts more and more designers’ attention. With the rise of artificial intelligence technology, especially the rapid development of deep learning and convolutional neural network, a large number of advanced theories and algorithms have emerged in the field of computer vision. As an important direction of vision research, target detection and style transfer have become the research hotspot of many researchers. How to reasonably formulate the interaction mode, determine the user interface style, layout structure, and information display mode and how to organically combine the mobile phone theme interface design and user interaction experience are problems worthy of discussion and research at present. By studying the process of smart phone theme interface interaction design, sorting out the methods of mobile phone interface interaction design style, this paper deeply analyzes the popular flat and quasi-materialized style and discusses the skills of application.
Dexmedetomidine Can Enhance PINK1/Parkin-Mediated Mitophagy in MPTP-Induced PD Mice Model by Activating AMPK
Authors: Chen Cheng , Chen Yaohua , Liu Tingting , Song Dan , Ma Di , Cheng Oumei
Published: April 2022

Parkinson’s disease (PD) is a common neurodegenerative disease characterized by the degeneration of dopaminergic (DA) neurons in the substantia nigra (SN). Our previous study has shown that dexmedetomidine (Dex) can protect mitochondrial function and reduce apoptosis in MPP+-induced SH-SY5Y cells. Evidences have shown that mitophagy is related to the development of PD. In this study, we investigated whether Dex can enhance mitophagy in MPTP-induced mice to play a neuroprotective effect. In our experiment, mice were injected with MPTP 30 mg/kg intraperitoneally for 5 consecutive days to establish a PD subacute model. Dex (30, 50, and 100 μg/kg) was injected intraperitoneally 30 minutes before each injection of MPTP, respectively. Our results showed that Dex (50 μg/kg) most significantly attenuated MPTP-induced motor dysfunction and restored TH-positive neurons in the SN, increased the expression of the antiapoptotic protein Bcl-2, and decreased the expression of apoptotic proteins cleaved casepase3, cleaved casepase9, and Bax. Moreover, Dex increased the activity of mitochondrial Complexes I-IV and decreased the level of oxidative stress, manifesting as decreased MDA levels and increased SOD and GSH-PX levels. Besides, under transmission electron microscopy, Dex increased the mitophagosome which is an autophagosome with a mitochondrion-like structure inside under the electron microscope. In addition, Dex could also increase the expression of mitophagy-related proteins p-AMPK, LC3II/I, PINK1, and Parkin and decrease P62. However, after using Compound C (CC, 10 mg/kg, AMPK inhibitor), the effects of Dex on increasing PINK1/Parkin-induced mitophagy and neuroprotection were attenuated. In conclusion, Dex may improve mitochondrial function by activating AMPK to enhance PINK1/Parkin-induced mitophagy, thereby protecting dopaminergic neurons.
Resource Scheduling Method for Optimizing the Distribution Path of Fresh Agricultural Products under Low-Carbon Environmental Constraints
Authors: Fu Qimin , Li Jun , Chen Huanhuan
Published: April 2022

Aiming at the development concept of relative dispersion of urban multiregional business centers, saving energy, and emission reduction, this article proposes an algorithm for solving the problem of green logistics distribution to fresh agricultural products considering low-carbon and environmental protection, to realize the economic and environmental protection of cold chain logistics. Firstly, we comprehensively consider the fixed costs of delivery vehicles, transportation costs, damage costs of fresh agricultural products, cooling costs, carbon emissions costs, and penalty costs due to service time windows that do not meet customer requirements as the objective function to construct green logistics distribution location-routing optimization model. Then, Tent chaotic perturbation method is introduced to optimize the genetic algorithm and an improved genetic algorithm is used to solve the distribution location-routing optimization model to obtain the best scheme. Finally, the proposed algorithm is verified experimentally based on the MATLAB simulation platform. Experimental results show that the total distance and total cost of the distribution plan obtained by the proposed algorithm are 128.96 km and 12,593 yuan, respectively, which are superior to other comparison algorithms and can be used as a reference for logistics enterprises’ distribution decision-making.
The Spatial Distribution and Evolution of Traditional Villages Based on Remote Sensing Technology
Authors: Zhang Hongchen
Published: April 2022

With the rapid progress of the era and the intensification of urbanization, the traditional villages in the fringe areas have become empty villages. Based on the protection of China’s long-standing farming culture, the state preserves the traditional Chinese rural characteristics with the support of advocating the development of urbanization in villages; the proposal of the revitalization strategy with Chinese rural characteristics pays great attention to and supports the development of rural characteristics to a great extent. However, China’s vast land and resources and the lack of observation technology make most people do not know enough about traditional villages. Based on the rapid development of drones and remote sensing technology in recent years, this article observes the administrative area of A county in the province of A with the support of big data technology. The DEM data taken by drones is the basic data source; that is, within a certain degree of restriction, elevation data (DEM) can realize effective digital simulation. And the current situation of rural settlement space in County A is analyzed through comprehensive technologies such as GIS technology, parametric analysis technology, and landscape pattern index grading; GIS technology can transform data from multiple sources into geographic graphics. And from the perspective of the ecological environment, the geographical, land use, and settlement spatial pattern of the rural settlements in County A are analyzed, revealing that the spatial distribution of rural settlements in County A is affected by the ecological environment. The results of the study show that the classification statistics table of rural residential areas in County A shows that the base number of independent courtyards is particularly large, accounting for about 83% of the total residential areas. The rural residential areas in County A are dominated by single-family clusters and small clusters, which together account for more than 99.1% of the total area. Large- and medium-sized gathering points are relatively small, accounting for only about 0.87% of the number of village gatherings.
Action Recognition, Tracking, and Optimization Analysis of Training Process Based on SVR Model and Multimedia Technology
Authors: Zhong Xuejiao
Published: April 2022

In order to explore the action recognition, tracking, and optimization analysis of the training process based on the SVR model and multimedia technology, the author proposes based on the radial basis function model, researching a new surrogate model technology-support vector regression (SVR). We first introduce the basic principles of SVR, select the parameters of SVR, and then elaborate the basic steps of SVR modeling. Then, we design and optimize application examples through numerical example multimedia technology; the validity of the support vector regression method is verified. Experimental results: the comparison of SVR1 and SVR2 shows that the utilization of multiscale timing feature maps should occur after tem (SVR2) rather than being directly fused in the feature dimension (SVR1), mainly because small-scale information affects the resolution of large-scale information; on data sets such as ActivityNet, in order to verify the effectiveness of SVR and DR-Dvc algorithms, the performance of the proposed algorithm and the baseline before improvement and the current mainstream algorithm are respectively compared. Experimental results show the proposed algorithm has a significant performance improvement compared to before the improvement; at the same time, it is better than most current mainstream algorithms, which proves the feasibility and effectiveness of the algorithm. Describing the introduction of regression can effectively improve the performance of sequential action proposals and event description algorithms, and compared with the current mainstream methods, it has certain performance advantages.
A Survey of Game-Theoretic Approach for Resource Management in Cloud Computing
Authors: Agbaje M. O. , Ohwo O. B. , Ayanwola T. G. , Olufunmilola Ogunyolu
Published: April 2022

Cloud computing is a groundbreaking technique that provides a whole lot of facilities such as storage, memory, and CPU as well as facilities such as servers and web service. It allows businesses and individuals to subcontract their computing needs as well as trust a network provider with its data warehousing and processing. The fact remains that cloud computing is a resource-finite domain where cloud users contend for available resources to carry out desired tasks. Resource management (RM) is a process that deals with the procurement and release of resources. The management of cloud resources is desirable for improved usage and service delivery. In this paper, we reviewed various resource management techniques embraced in literature. We concentrated majorly on investigating game-theoretic submission for the management of required resources, as a potential solution in modeling the resource allocation, scheduling, provisioning, and load balancing problems in cloud computing. This paper presents a survey of several game-theoretic techniques implemented in cloud computing resource management. Based on this survey, we presented a guideline to aid the adoption and utilization of game-theoretic resource management strategy.
Trehalose Protects Keratinocytes against Ultraviolet B Radiation by Activating Autophagy via Regulating TIMP3 and ATG9A
Authors: Li Li , Chen Hongying , Chen Xu , Chen Sihan , Gu Heng
Published: April 2022

Trehalose, a natural disaccharide, is synthesized by many organisms when cells are exposed to stressful stimuli. On the basis of its ability to modulate autophagy, trehalose has been considered an innovative drug for ameliorating many diseases, but its molecular mechanism is not well described. Previous findings demonstrated that trehalose plays a photoprotective role against ultraviolet (UV) B-induced damage through autophagy induction in keratinocytes. In this study, coimmunoprecipitation, label-free quantitative proteomic and parallel reaction monitoring, and western blot analysis demonstrated that trehalose promotes the interaction between tissue inhibitor of metalloproteinase (TIMP) 3 and Beclin1. Western blot and immunofluorescence staining analysis suggested that trehalose increases ATG9A localization in lysosomes and decreases its localization in the endoplasmic reticulum. Furthermore, in the presence or absence of UVB radiation, we evaluated the influence of TIMP3 and ATG9A small interfering RNA (siRNA) on the effect of trehalose on autophagy, cell death, migration, or interleukin-8 expression in keratinocytes, including HaCaT, A431, and human epidermal keratinocytes. The results revealed that in HaCaT cells, TIMP3 and ATG9A siRNA resulted in attenuation of trehalose-induced autophagy and inhibited cell death. In A431 cells, TIMP3 and ATG9A siRNA led to attenuation of trehalose-induced autophagy and cell death and inhibited migration. In human epidermal keratinocytes, trehalose-induced autophagy and inhibition of the interleukin-8 expression were blocked by ATG9A but not TIMP3 siRNA. In addition, the results of quantitative real-time PCR and immunohistochemistry analysis demonstrated the abnormal expression of TIMP3 and ATG9A in actinic keratosis and cutaneous squamous cell carcinoma skin tissues. These findings suggest the protective effects of trehalose in normal keratinocytes and its inhibitory effects on cancerous keratinocytes, possibly mediated by activation of autophagy and regulation of TIMP3 and ATG9A, providing the mechanistic basis for the potential use of trehalose in the prevention or treatment of UVB-induced skin diseases.
Study on Temperature Sensor Data Anomaly Diagnosis Method Based on Deep Neural Network
Authors: Jing Wei , Wang Peng , Zhang Ningchao
Published: April 2022

In order to solve the problems of low accuracy and low efficiency of traditional sensor data anomaly diagnosis methods, a new temperature sensor data anomaly diagnosis method based on deep neural network is proposed in this paper. Firstly, the temperature sensor data in a running cycle is collected, and the characteristics of the temperature sensor data are extracted by the sliding window technology. Secondly, based on the feature extraction results, a deep neural network model for anomaly diagnosis of temperature sensor data is constructed. The feature data are input into the model, and the result obtained is the diagnosis result. Finally, the simulation comparison experiment is carried out. The experimental results show that the error rate of feature extraction of temperature sensor data in this method changes between −2.1% and 5.9%, the diagnosis accuracy remains above 95%, the average diagnosis time is only 59 ms, and the diagnosis efficiency is high.
Circadian Regulator CLOCK Drives Immunosuppression in Glioblastoma
Authors: Xuan Wenjing , Hsu Wen-Hao , Khan Fatima , Dunterman Madeline , Pang Lizhi , Wainwright Derek A. , Ahmed Atique U. , Heimberger Amy B. , Lesniak Maciej S. , Chen Peiwen
Published: April 2022

The symbiotic interactions between cancer stem cells and the tumor microenvironment (TME) are critical for tumor progression. However, the molecular mechanism underlying this symbiosis in glioblastoma (GBM) remains enigmatic. Here, we show that circadian locomotor output cycles kaput (CLOCK) and its heterodimeric partner brain and muscle ARNT-like 1 (BMAL1) in glioma stem cells (GSC) drive immunosuppression in GBM. Integrated analyses of the data from transcriptome profiling, single-cell RNA sequencing, and TCGA datasets, coupled with functional studies, identified legumain (LGMN) as a direct transcriptional target of the CLOCK–BMAL1 complex in GSCs. Moreover, CLOCK-directed olfactomedin-like 3 (OLFML3) upregulates LGMN in GSCs via hypoxia-inducible factor 1-alpha (HIF1α) signaling. Consequently, LGMN promotes microglial infiltration into the GBM TME via upregulating CD162 and polarizes infiltrating microglia toward an immune-suppressive phenotype. In GBM mouse models, inhibition of the CLOCK–OLFML3–HIF1α–LGMN–CD162 axis reduces intratumoral immune-suppressive microglia, increases CD8+ T-cell infiltration, activation, and cytotoxicity, and synergizes with anti–programmed cell death protein 1 (anti–PD-1 therapy). In human GBM, the CLOCK-regulated LGMN signaling correlates positively with microglial abundance and poor prognosis. Together, these findings uncover the CLOCK–OLFML3–HIF1α–LGMN axis as a molecular switch that controls microglial biology and immunosuppression, thus revealing potential new therapeutic targets for patients with GBM.