bluuebunny/crossref_metadata_2025 huggingface dataset:
Relationship of soil water retention characteristics and soil properties: a case study from the Colombian Andes
Authors: Roa García Clara , Brown Sandra , Krzic Maja , Lavkulich Les , Roa-García María Cecilia
Published: August 2020

Differences in soil water retention (SWR) characteristics between soil types and the factors driving those differences provide important information for land management, particularly in regions such as the Colombian Andes, which have limited water-storage infrastructure and where soils provide plant-available water and other ecosystem services. The objective of this study was to explore relationships between SWR and physical, chemical, and mineralogical properties of Andisols and Inceptisols through a case study of two watersheds in the Colombian Andes. This study identified a complex relationship between total carbon (TC), short-range order (SRO) minerals, and SWR. Both soil types had high SWR, with volumetric water content at permanent wilting point between 39% and 53%. Principal component analysis showed association of SWR with TC, SRO minerals, and % clay in both soil types. The Andisols of this study were coarse textured, allophanic (rich in allophane and imogolite — up to 17% in the B horizon), and with up to 15% TC in the A horizon. In contrast, the Inceptisols were fine textured (>30% clay) and higher in ferrihydrite than the Andisols. The formation of organo-metallic complexes was observed in A horizons; however, TC was lower under pasture than forest in both soil types. The addition of organic matter to soils with SRO minerals, such as the soils of this study, may foster the formation of organo-metallic complexes, stabilize soil C, and enhance SWR. Consequently, both study sites may benefit from management practices that increase soil organic matter.
When Painlevé–Gullstrand coordinates fail
Authors: Faraoni Valerio , Vachon Geneviève
Published: August 2020

Painlevé–Gullstrand coordinates, a very useful tool in spherical horizon thermodynamics, fail in anti-de Sitter space and in the inner region of Reissner–Nordström. We predict this breakdown to occur in any region containing negative Misner–Sharp–Hernandez quasilocal mass because of repulsive gravity stopping the motion of PG observers, which are in radial free fall with zero initial velocity. PG coordinates break down also in the static Einstein universe for completely different reasons. The more general Martel-Poisson family of charts, which normally has PG coordinates as a limit, is reported for static cosmologies (de Sitter, anti-de Sitter and the static Einstein universe).
The evolution equation of non-linear waves and its exact solutions by subsidiary ordinary differential equation method
Authors: Yin Xiaojun , Yang Liangui , Liu Quansheng
Published: August 2020

In this work, we investigate the dynamics of the equatorial Rossby waves by including the complete Coriolis force, external source and dissipation. The amplitude evolution of equatorial Rossby waves is described as an extended non-linear mKdV–Burgers equation from a potential vorticity equation and it is unlike the standard mKdV–Burgers equation. Built on the obtained model, the corresponding physical phenomena related to the non-linear Rossby waves are analyzed. Also, the subsidiary ordinary differential equation method is employed to solve the solitary solution of the mKdV equation. By analyzing the solution, we find that the horizontal component of Coriolis parameter works on the amplitude of the Rossby waves. Meanwhile, we use the Adomian decomposition method to obtain the approximate soliton solution of the model.
Calculation of the energy eigenvalues of the Yukawa potential via variation principle
Authors: Yazdankish E.
Published: August 2020

The Yukawa potential has an important and significant rule in some branches of physics such as nuclear, plasma and solid state. However, there is no analytical solution for Schrödinger equation with this potential without approximation, therefore, other ways, such as numerical, perturbation, variation and so on, are taken to deal with this potential. In this work, the variation principle is taken to obtain some of its energy eigenvalues. In the arbitrary [Formula: see text]-state, the Yukawa potentials with centrifugal term are taken together as effective potential and then by choosing the wave functions of the Hulthen potential as trial function which are obtained in this work from the Nikiforov–Uvarov method, and then by applying the variation principle, the energy eigenvalues are obtained. After that, the result is compared with the former numerical result. The comparison shows excellent agreement between our result and the former numerical ones.
THE INHIBITION EFFECT OF ZINC AND SILICATE IONS ON PITTING CORROSION INDUCED BY CERIUM(III) IONS OF CARBON STEEL IN SODIUM CHLORIDE SOLUTION
Authors: LI QIONGWEI
Published: August 2020

Pitting corrosion of carbon steel in sodium chloride solution induced by Ce[Formula: see text] and the synergistic inhibition effects of Ce[Formula: see text] and Zn[Formula: see text]/SiO[Formula: see text] were investigated using in-situ observation and electrochemical methods. The results showed that the presence of Ce[Formula: see text] could result in severe pitting corrosion and a positive shift in the corrosion potential. It was found that individual Ce[Formula: see text], Zn[Formula: see text], or SiO[Formula: see text] had low inhibition efficiencies, whereas the combination of Ce[Formula: see text] and Zn[Formula: see text] or SiO[Formula: see text] proved to be highly effective in inhibiting the development of pits in two different ways and in enhancing the corrosion resistance. The pitting corrosion and inhibition mechanisms were discussed based on the results.
A Model of Multiproduct Firm Growth
Authors: Huangfu Bingchao
Published: August 2020

This paper studies optimal growth strategies of a multiproduct firm that invests in the qualities of different products, which have persistent effects on future payoffs and are modeled as a state variable of a stochastic game. We derive a unique Markov perfect equilibrium under a monotonicity condition. At the early stage, the firm focuses on the product with higher quality, and may switch its specialization. If the quality of the specialized good is high enough, the firm diversifies to capture demands for all products. However, the firm may lose its focus on either product and get no demand, due to a moral hazard problem.
Game-Theoretic Analysis of Green Supply Chain Under Cost-Sharing Contract with Fairness Concerns
Authors: Sharma Abhishek , Jain Deepika
Published: August 2020

This study investigates the fairness concerned behavior of the supply chain members in a dyadic supply chain with one manufacturer and one retailer, wherein the manufacturer puts efforts for improving the product’s greening level and sells it to the customers through the retailer. Through manufacturer-led and retailer-led Stackelberg game frameworks, the study presents two models- one in which only the manufacturer exhibits advantageous inequity averse behavior and the other in which only the retailer exhibits them. The results demonstrate the following findings: (1) the manufacturer’s profit is decreasing while product’s greening level, retailer’s and total supply chain’s profits are increasing and manufacturer’s wholesale price and retailer’s market price are nonmonotone in manufacturer’s fairness concern, (2) the wholesale price, product’s greening level, manufacturer’s profit, and total supply chain’s profit are increasing while retailer’s profit is decreasing and market price is nonmonotone in retailer’s fairness concern. In addition, the study examines the optimality of cost-sharing contract for different ranges of the model parameters. Furthermore, the findings are elucidated through the numerical analysis and managerial insights are generated.
Spatio Temporal Joint Distance Maps for Skeleton-Based Action Recognition Using Convolutional Neural Networks
Authors: Naveenkumar M. , Domnic S.
Published: August 2020

Skeleton-based action recognition has become popular with the recent developments in sensor technology and fast pose estimation algorithms. The existing research works have attempted to address the action recognition problem by considering either spatial or temporal dynamics of the actions. But, both the features (spatial and temporal) would contribute to solve the problem. In this paper, we address the action recognition problem using 3D skeleton data by introducing eight Joint Distance Maps, referred to as Spatio Temporal Joint Distance Maps (ST-JDMs), to capture spatio temporal variations from skeleton data for action recognition. Among these, four maps are defined in spatial domain and remaining four are in temporal domain. After construction of ST-JDMs from an action sequence, they are encoded into color images. This representation enables us to fine-tune the Convolutional Neural Network (CNN) for action classification. The empirical results on the two datasets, UTD MHAD and NTU RGB+D, show that ST-JDMs outperforms the other state-of-the-art skeleton-based approaches by achieving recognition accuracies 91.63% and 80.16%, respectively.
Pixel Prediction-Based Image Steganography Using Crow Search Algorithm-Based Deep Belief Network Approach
Authors: Ravikumar K. P. , Reddy H. S. Manjunatha
Published: August 2020

Securing the confidentiality of patient information using the image steganography process has gained more attention in the research community. However, embedding the patient information is a major task in the steganography process due to the complexity in identifying the pixel features. Thus, an effective Crow Search Algorithm-based deep belief network (CSA-DBN) is proposed for embedding the information in the medical image. Initially, the appropriate pixels and the features, like pixel coverage, wavelet energy, edge information, and texture features, such as local binary pattern (LBP) and local directional pattern (LDP), are extracted from each pixel. The proposed CSA-DBN utilizes the feature vector and identifies the suitable pixels used for embedding. The patient information is embedded into the image by using the embedding strength and the DWT coefficient. Finally, the embedded information is extracted using the DWT coefficient. The analysis of the proposed CSA-DBN approach is done based on the performance metrics, such as correlation coefficient, peak signal-to-noise ratio (PSNR), and structural similarity index (SSIM) that acquired the average values as 0.9471, 24.836[Formula: see text]dB, and 0.4916 in the presence of salt and pepper noise and 0.9741, 57.832[Formula: see text]dB, and 0.9766 in the absence of noise.
Diagnosis of Parkinson’s Disease Using SVM Classifier
Authors: Wiselin Jiji G. , Rajesh A. , Johnson Durai Raj P.
Published: August 2020

Parkinson’s disease (PD) is the most common disease that affects aged people which leads to dopamine-producing cells in substantia nigra to be damaged when motor system degenerates. Clinical Diagnosis of Parkinson’s disease at the earlier stage is very difficult. This work is carried out to find the significance of cognition function of basal ganglia (BG) region and speech data values. The BG can be segmented using morphological operation and active contour algorithm. Co-occurrences features are extracted and out of 720 features, the promising 110 features are selected using variance method. More promising 22 features are selected in speech data and both features are individually classified using SVM to find out the efficiency in Diagnosis. The outcome shows cognition function of BG performing a major role in early diagnosis of Parkinson’s disease when compared to speech data.
Twin Nicomachean q-identities and conjectures for the associated discriminants, polynomials, and inequalities
Authors: Kim Seon-Hong , Stolarsky Kenneth B.
Published: August 2020

We insert additional variables into Warnaar’s [Formula: see text]-analogue of Nicomachus’ identity and other related identities, and compute discriminants with respect to [Formula: see text]. Factorization of these discriminants reveals pairs of partitions that conjecturally relate in the manner of Wheatstone. The factorization also yields, conjecturally, families of polynomials with relations to various Molien series, remarkable rational generating functions, and notable root distributions. For a [Formula: see text]-analogue of Nicomachus’ identity produced by Cigler, we provide proofs of the partition properties. We also state and in part prove tight inequalities for the elements of two interlacing sequences that led us to the “twin” of Warnaar’s [Formula: see text]-analogue.
Log-concavity results for a biparametric and an elliptic extension of the q-binomial coefficients
Authors: Schlosser Michael J. , Senapati Koushik , Uncu Ali K.
Published: August 2020

We establish discrete and continuous log-concavity results for a biparametric extension of the [Formula: see text]-numbers and of the [Formula: see text]-binomial coefficients. By using classical results for the Jacobi theta function we are able to lift some of our log-concavity results to the elliptic setting. One of our main ingredients is a putatively new lemma involving a multiplicative analogue of Turán’s inequality.
Nitrogen-Doped Mesoporous Carbons Bearing Fe3O4 as Adsorbent for Effective Ag(I) Removal
Authors: Zhang Wenjuan , Feng Qiancheng , Zhang Bobo , Wang Youliang , Fei Yulong , Kou Miao , Zhang Zhaoxiong , Shen Yingying , Du Xueyan
Published: August 2020

An efficient route is proposed to synthesize magnetic nitrogen-doped mesoporous carbon (Fe3O4/NMC) composites. The nitrogen-doped mesoporous carbon (NMC) material was prepared using a melamine–formaldehyde resin as nitrogen and carbon source and fumed silica as a template via a template method, and Fe3O4nanoparticles were introduced via an in situ formation method. The effects of the loading amount of Fe3O4on the morphology, structure, magnetic properties and adsorption performance of the Fe3O4/NMC composites were investigated. Fe3O4nanoparticles dispersed well on the surface and inside the NMC, and the Fe3O4/NMC remained a mesoporous structure. Fe3O4/NMC exhibited superparamagnetic behavior, and the maximum saturation magnetization was 30.1[Formula: see text]emu/g. Fe3O4/NMC had a decreased specific surface area and pore volume compared to NMC, but the Fe3O4/NMC composites still showed excellent adsorption capacity for Ag(I), reaching 71.9[Formula: see text]mg/g. The adsorption efficiency of Fe3O4/NMC remained at 90.3% of the initial removal capability after five cycles, which demonstrated the potential large-scale industrial applications of these composites.
Development of a wheat aphid population dynamics model based on cusp catastrophe theory
Authors: Li Yuan , Li Zhen , Zhao Lichun , Hu Zuqing , Zhao Huiyan
Published: August 2020

Aphids are a major global wheat pest that can cause considerable loss of yield. Modeling of aphid population dynamics is an integral part of management strategies to manage or control aphid populations. In this paper, first, a wheat aphid population dynamics model was developed based on a logistic model and the Holling III functional response, which includes three factors: temperature, natural enemies and insecticide. Second, this model fitted with a cusp catastrophe model to describe how abrupt changes in the wheat aphid population were influenced by these factors. Finally, the system was validated with field data from 2016 to 2018. The bifurcation set of the cusp catastrophe model was deemed to be the quantified dynamic control threshold, so an outbreak of aphid’s population can be explained according to the variation of control variables. In short, this aphid population model was successfully validated on survey data, which can be used to guide the prevention and control of aphids.
Wire Load Oriented Analog Routing with Matching Constraints
Authors: Chi Hao Yu , Liu Chien Nan Jimmy , Chen Hung Ming
Published: August 2020

As design complexity is increased exponentially, electronic design automation (EDA) tools are essential to reduce design efforts. However, the analog layout design has still been done manually for decades because it is a sensitive and error-prone task. Tool-generated layouts are still not well-accepted by analog designers due to the performance loss under non-ideal effects. Most previous works focus on adding more layout constraints on the analog placement. Routing the nets is thus considered as a trivial step that can be done by typical digital routing methodology, which is to use vias to connect every horizontal and vertical lines. Those extra vias will significantly increase the wire loads and degrade the circuit performance. Therefore, in this article, a wire load oriented analog routing methodology is proposed to reduce the number of layer changing of each routing net. Wire load is considered in the optimization goal as well as the wire length to keep the circuit performance after layout, while the analog layout constraints like symmetry and length matching are still satisfied during routing. As shown in the experimental results, this approach significantly reduces the wire load and performance loss after layout with little overhead on wire length.
Global Banking: Toward an Assessment of Benefits and Costs
Authors: Buch Claudia M. , Goldberg Linda S.
Published: August 2020

Global activities of banks are a core manifestation of broader patterns of globalization of production, trade, and finance. This article reviews the extensive recent empirical and theoretical literature on global banking, emphasizing the careful empirical analyses that incorporate key dimensions of heterogeneity among borrowers and lenders, and across activities. The actions of globally active banks are consequential, with cost and benefit trade-offs that differ during their lifetimes and at times of stress. Both research and policymaking around global banking benefit from improved infrastructures around collection of and access to granular data and repositories of evaluation studies. Although overall positive contributions from welfare perspectives arise from the activities of global banks, these organizations require appropriately targeted policy frameworks and oversight.
In Vivo Antimalarial Activity of Crude Fruit Extract of Capsicum frutescens Var. Minima (Solanaceae) against Plasmodium berghei‐Infected Mice
Authors: Habte Getu , Assefa Solomon
Published: August 2020

Background. The alarming spread of parasite resistance to current antimalarial agents is threatening malaria controlling efforts. This, consequently, urged the scientific community to discover novel antimalarial drugs. Successful and most potent antimalarial drugs were obtained from medicinal plants. Capsicum frutescens is claimed to possess an antiplasmodial activity in Ethiopian and Ugandan folkloric medicine. However, there is a lack of pharmacological evidence for its antiplasmodial activity. This study, hence, was aimed at evaluating the in vivo antiplasmodial activity of C. frutescens in a mouse model. Methods. The dried fruits of the plant were extracted with 80% methanol using cold maceration. A 4‐day suppressive test was employed to ascertain the claimed antiplasmodial effect of the plant. Following inoculation with P. berghei, mice in treatment groups were provided with three dose levels (100, 200, and 400 mg/kg) of the extract, while 2% Tween 80 and chloroquine served as the negative and positive controls, respectively. Weight, temperature, packed cell volume, parasitemia, and survival time were then monitored. Results. The acute oral toxicity study revealed that the crude extract caused no mortality and revealed no overt sign of toxicity. In the 4‐day suppressive test, all dose levels of the extract were found to exhibit a significant (p < 0.05) inhibition of parasitemia compared to those of the negative control. Maximum parasite suppression (93.28%) was exerted by the highest dose (400 mg/kg/day) of extract. Also, the extract significantly (p < 0.05) prolonged survival time and prevented body weight loss and reduction in temperature and anemia compared to the vehicle‐treated group. Conclusion. This investigation found strong evidence that the fruit extract of C. frutescens is endowed with promising antiplasmodial activity. Hence, the plant could serve as a potential source of a newer antimalarial agent.
Self-Care Experiences of Adults with Chronic Disease in Indonesia: An Integrative Review
Authors: Lukman Nurul Akidah , Leibing Annette , Merry Lisa
Published: August 2020

We conducted a literature review to document what is known regarding the self-care experiences and various influencing factors among adults living with chronic disease in Indonesia, from the perspective of those living with the illness. We searched CINAHL and Google Scholar to identify peer-reviewed research focused on men and/or women living with a chronic disease (the most prevalent) in urban or rural settings in Indonesia. Using a “Self-Care of Chronic Illness” framework as a guide, information on self-care experiences and how various factors influence these experiences, was extracted and synthesized. Nine studies were included (3 quantitative; 6 qualitative). Self-care involves maintaining well-being through different strategies (e.g., foot hygiene, seeking information/care, praying, diet, resting, and simplifying life), following prescribed treatments, and using traditional remedies. Religion sometimes serves as a means for taking care of one’s health (e.g., prayer), or as a source of motivation to self-care, while in other instances, it results in a fatalistic attitude. Which treatments (conventional versus traditional) are sought, it is affected by an understanding of the disease and treatments, which is shaped by beliefs, values, emotions, health literacy, and SES. The literature shows that family, especially women, has a key role in providing support. Community organizations also play an important supportive role, particularly for patients in rural areas. Significant barriers to healthcare include costs and care not being well-adapted to the psychosocial needs and contexts of patients. The literature highlights a disconnection between the self-care experiences and how healthcare and support are delivered. To better support self-care, healthcare professionals should use a personalized approach; however, more research is needed to gain a better understanding of what patients want and expect regarding how religion, beliefs, life circumstances, and the use of alternative therapies should be addressed within the patient-professional dynamic.
Cascade Delayed Controller Design for a Class of Underactuated Systems
Authors: Ochoa-Ortega G. , Villafuerte-Segura R. , Luviano-Juárez A. , Ramírez-Neria M. , Lozada-Castillo N.
Published: August 2020

In this paper, a delayed control strategy for a class of nonlinear underactuated fourth-order systems is developed. The proposal is based on the implementation of the tangent linearization technique, differential flatness, and a study of the σ-stabilization of the characteristic equation of the closed-loop system. The tangent linearization technique allows obtaining a local controllability property for the analyzed class of systems. Also, it can reduce the complexity of the global control design, through the use of a cascade connection of two second-order controllers instead of designing a global controller of the fourth-order system. The stabilizing behavior of the delayed controller design is supported by the σ-stability criterion, which provides the controller parameter selection to reach the maximum exponential decay rate on the system response. To illustrate the efficiency of the theoretical results, the proposal is experimentally assessed in two cases of study: a flexible joint system and a pendubot.
A Hybrid Method Based on Extreme Learning Machine and Self Organizing Map for Pattern Classification
Authors: Jammoussi Imen , Ben Nasr Mounir
Published: August 2020

Extreme learning machine is a fast learning algorithm for single hidden layer feedforward neural network. However, an improper number of hidden neurons and random parameters have a great effect on the performance of the extreme learning machine. In order to select a suitable number of hidden neurons, this paper proposes a novel hybrid learning based on a two-step process. First, the parameters of hidden layer are adjusted by a self-organized learning algorithm. Next, the weights matrix of the output layer is determined using the Moore–Penrose inverse method. Nine classification datasets are considered to demonstrate the efficiency of the proposed approach compared with original extreme learning machine, Tikhonov regularization optimally pruned extreme learning machine, and backpropagation algorithms. The results show that the proposed method is fast and produces better accuracy and generalization performances.
The Ultrasonographic Features of Shoulder Pain Patients in a Tertiary Hospital in South China
Authors: Jiang Li , He Juanjuan , Chen Carl P. C. , Xie Dongfeng , Mai Yiying , Yue Boyu , Dou Zulin
Published: August 2020

Background and Objective. Musculoskeletal ultrasound imaging can play a role as an accurate tool in offering an accurate diagnosis of shoulder pain. However, it is still not commonly used in mainland China. The aim of this study was to explore the epidemiology and ultrasound imaging characteristics of shoulder pain patients in south China and hoping to use these data in the future development of artificial intelligent ultrasound interpretation of shoulder pathology. Methods. Patients with shoulder pain were recruited in an outpatient rehabilitation clinic at the Third Affiliated Hospital of Sun Yat‐Sen University from January 1, 2017, to June 30, 2018. These shoulder pain patients with or without limitation in joint movement can be included in the study. All of them received musculoskeletal ultrasound scanning. Demographic and imaging data including age, gender, duration of shoulder pain, pain side, and pathologies found by musculoskeletal ultrasound imaging were collected and analyzed. Patients were divided into three groups: <45 years (young group), between 45 and 60 years (middle‐aged group), and >60 years (elderly group). The rates of various shoulder pathologies were evaluated and compared between the groups. Results. This study recruited a total of 346 patients with shoulder pain. There were more female (62.1%) than male patients (37.9%), with the largest number of patients in the 45‐60 years of age group (40.5%). Forty‐eight percent of patients had shoulder pain within a period of 3 months. A total of 380 shoulders were assessed using musculoskeletal ultrasound imaging. The occurrence rate of subacromial disorder (83.8%) was the highest. The rate of supraspinatus tendinopathy, acromioclavicular joint degeneration, and adhesive shoulder capsulitis varied significantly between age groups (P < 0.05). The rate of acromioclavicular joint degeneration was the highest in the elderly group followed by the middle‐aged and young groups (P < 0.0167). The rate of supraspinatus tendinopathy and adhesive capsulitis in the middle‐aged and elderly groups was significantly higher than that in the young group (P < 0.0167). Conclusions. Musculoskeletal ultrasound can be a useful imaging tool in making an accurate diagnosis of shoulder pain. The occurrence rates of different shoulder pain pathologies in all age groups were thoroughly calculated in this study. More female and more subcoracoid disorder patients than western countries are attributed to repetitive lifting in daily life and work in this study. Correlations between these pathologies and their associated images can be a solid foundation for the development of artificial intelligence in diagnosing the cause of shoulder pain.
DWT-Net: Seizure Detection System with Structured EEG Montage and Multiple Feature Extractor in Convolution Neural Network
Authors: Zhang Zhe , Ren Yun , Sabor Nabil , Pan Jing , Luo Xiaona , Li Yongfu , Chen Yucai , Wang Guoxing
Published: August 2020

Automated seizure detection system based on electroencephalograms (EEG) is an interdisciplinary research problem between computer science and neuroscience. Epileptic seizure affects 1% of the worldwide population and can lead to severe long-term harm to safety and life quality. The automation of seizure detection can greatly improve the treatment of patients. In this work, we propose a neural network model to extract features from EEG signals with a method of arranging the dimension of feature extraction inspired by the traditional method of neurologists. A postprocessor is used to improve the output of the classifier. The result of our seizure detection system on the TUSZ dataset reaches a false alarm rate of 12 per 24 hours with a sensitivity of 59%, which approaches the performance of average human detector based on qEEG tools.
Short-Term Passenger Flow Forecast of Rail Transit Station Based on MIC Feature Selection and ST-LightGBM considering Transfer Passenger Flow
Authors: Zhang Zhe , Wang Cheng , Gao Yueer , Chen Jianwei , Zhang Yiwen
Published: August 2020

To solve the problems of current short-term forecasting methods for metro passenger flow, such as unclear influencing factors, low accuracy, and high time-space complexity, a method for metro passenger flow based on ST-LightGBM after considering transfer passenger flow is proposed. Firstly, using historical data as the training set to transform the problem into a data-driven multi-input single-output regression prediction problem, the problem of the short-term prediction of metro passenger flow is formalized and the difficulties of the problem are identified. Secondly, we extract the candidate temporal and spatial features that may affect passenger flow at a metro station from passenger travel data based on the spatial transfer and spatial similarity of passenger flow. Thirdly, we use a maximal information coefficient (MIC) feature selection algorithm to select the significant impact features as the input. Finally, a short-term forecasting model for metro passenger flow based on the light gradient boosting machine (LightGBM) model is established. Taking transfer passenger flow into account, this method has a low space-time cost and high accuracy. The experimental results on the dataset of Lianban metro station in Xiamen city show that the proposed method obtains higher prediction accuracy than SARIMA, SVR, and BP network.
Two-Player Location Game in a Closed-Loop Market with Quantity Competition
Authors: Chen Xiaofeng , Song Qiankun , Zhao Zhenjiang
Published: August 2020

This paper considers the two-player location game in a closed-loop market with quantity competition. Based on the Cournot and Hotelling models, a circle model is established for a closed-loop market in which two players (firms) play a location game under quantity competition. Using a two-stage (location-then-quantity) pattern and backward induction method, the existence of subgame-perfect Nash equilibria is proved for the location game in the circle model with a minimum distance transportation cost function. In addition, sales strategies are proposed for the two players for every local market on the circle when the players are in the equilibrium positions. Finally, an algorithm for simulating the competitive dynamics of the closed-loop market is designed, and two numerical simulations are provided to substantiate the effectiveness of the obtained results.
Structure and Dynamic of Global Population Migration Network
Authors: Gou Wensha , Huang Siyu , Chen Qinghua , Chen Jiawei , Li Xiaomeng
Published: August 2020

People are the most important factors of economy and the primary carriers of social culture. Cross-border migration brings economic and cultural impacts to the origin and destination and is also a key to reflect the international relations of related countries. In fact, the migration relationships of countries are complex and multilateral, but most traditional migration models are bilateral. Network theories could provide a better description of global migration to show the structure and statistical characteristics more clearly. Based on the estimated migration data and disparity filter algorithm, the networks describing the global multilateral migration relationships have been extracted among 200 countries over fifty years. The results show that the global migration networks during 1960–2015 exhibit a clustering and disassortative feature, implying globalized and multipolarized changes of migration during these years. The networks were embed into a Poincaré disk, yielding a typical and hierarchical “core-periphery” structure, which is associated with angular density distribution, and has been used to describe the “multicentering” trend since 1990s. Analysis on correlation and evolution of communities indicates the stability of most communities, yet some structural changes still exist since 1990s, which reflect that the important historical events are contributable to regional and even global migration patterns.
Acetabular Bone Defect in Total Hip Arthroplasty for Crowe II or III Developmental Dysplasia of the Hip: A Finite Element Study
Authors: Du Yinqiao , Fu Jun , Sun Jingyang , Zhang Guoqiang , Chen Jiying , Ni Ming , Zhou Yonggang
Published: August 2020

Background. The purpose of this study was to establish the finite element analysis (FEA) model of acetabular bone defect in Crowe type II or III developmental dysplasia of the hip (DDH), which could evaluate the stability of the acetabular cup with different types of bone defects, different diameters of femoral ceramic heads, and the use of screws and analyze the stress distribution of screws. Methods. The FEA model was based on the CT scan of a female patient without any acetabular bone defect. The model of acetabular bone defect in total hip arthroplasty for Crowe II or III DDH was made by the increasing superolateral bone defect area of the acetabular cup. Point A was located in the most medial part of the acetabular bone defect. A 52 mm PINNACLE cup with POROCOAT Porous coating was implanted, and two screws (the lengths were 25 mm and 40 mm) were implanted to fix the acetabular cup. The stability of the acetabular cup and the von Mises stress of point A and screws were analyzed by a single‐legged stance loading applied in 1948 N (normal working). The different diameters of the femoral ceramic head (28 mm, 32 mm, and 36 mm) were also analyzed. Results. The von Mises stress of point A was gradually increased with the increasing uncoverage values. When the uncoverage values exceeded 24.5%, the von Mises stress of point A without screws increased significantly, leading to instability of the cup. Screws could effectively reduce the von Mises stress of point A with uncoverage values of more than 24.5%. However, the peak von Mises stress in the screws with the uncoverage values that exceeded 24.5% was considerably increased. The diameter of the femoral ceramic head had no significant effect on the von Mises stress and the stability of the acetabular cup. Conclusions. We recommend that uncoverage values of less than 24.5% with or without screw is safe for patients with Crowe II or III DDH.
Continuous Time Formulation and Lagrangian Relaxation Algorithm for the Gate Assignment Problem
Authors: Yuan Yuan , Yan Ping , Zhao Liqiang
Published: August 2020

Gates are important operating facilities and resources in civil airports. It is a core task in the airport operation management to select reasonable gates for inbound and outbound flights. We present a continuous time formulation with second-order cone programming (SOCP) for the gate assignment problem which allocates flights to available gates to optimize both the transfer time of passengers and the robustness of the airport operations schedules. The problem is formulated as a mixed integer nonlinear program, and then, the quadratic objective that minimizes the walking distance of transferring passengers is linearized, and the objective that minimizes the variance of idle time at the gates is transformed to a second-order cone constraint with a linear objective function. Then, a Lagrangian relaxation algorithm is developed by exploiting the problem structure. Computational tests are carried out to illustrate the efficiency of the model and the algorithms. It is shown that the continuous time formulation is more efficient than the existing model, and the Lagrangian relaxation algorithm can obtain better solutions faster than a commercial solver.
A Novel RLWE-Based Anonymous Mutual Authentication Protocol for Space Information Network
Authors: Guo Junyan , Du Ye
Published: August 2020

Currently, space information network (SIN) has become an increasingly important role in real life. As a large heterogeneous wireless network, SIN can better provide global mobile services to users anytime and anywhere, even in extreme geographic environments. In addition, there is no need to build the communication base-stations every few kilometers on the ground to ensure high service quality, which greatly reduces the construction costs and can be used as an economical communication method in sparsely populated areas. So there is a trend that more and more end users are more likely to get SIN services than traditional terrestrial cellular networks. However, due to the openness and publicity of the satellite wireless channel and the limited resources of the satellite nodes, the privacy and security cannot be perfectly guaranteed and may even be vulnerable to attacks initiated by the adversary such as replay attacks, impersonation attacks, and eavesdropping attacks. To improve the access security of SIN, researchers have proposed a series of authentication protocols based on different cryptographic assumptions. Nevertheless, existing research shows that these protocols cannot meet the requirements of higher and higher security and short authentication delay. In addition, these protocols are mainly based on public key cryptography mechanisms such as DLP and ECDLP, which can be solved by postquantum computers in polynomial time, so these protocols will no longer be secure. To solve the vulnerability of these protocols, in this paper, we propose a new RLWE-based anonymous mutual authentication and key agreement protocol, which guarantees higher security with low computational overhead even in the postquantum era. Detailed security analysis shows that our protocol meets security requirements and is resistant to a variety of known attacks. Besides, combining security comparison and performance analysis, our proposed protocol is more practical than other protocols in SIN.
Discovery of Prognostic Signature Genes for Overall Survival Prediction in Gastric Cancer
Authors: Meng Changyuan , Xia Shusen , He Yi , Tang Xiaolong , Zhang Guangjun , Zhou Tong
Published: August 2020

Background. Gastric cancer (GC) is one of the most common malignant tumors in the digestive system with high mortality globally. However, the biomarkers that accurately predict the prognosis are still lacking. Therefore, it is important to screen for novel prognostic markers and therapeutic targets. Methods. We conducted differential expression analysis and survival analysis to screen out the prognostic genes. A stepwise method was employed to select a subset of genes in the multivariable Cox model. Overrepresentation enrichment analysis (ORA) was used to search for the pathways associated with poor prognosis. Results. In this study, we designed a seven-gene-signature-based Cox model to stratify the GC samples into high-risk and low-risk groups. The survival analysis revealed that the high-risk and low-risk groups exhibited significantly different prognostic outcomes in both the training and validation datasets. Specifically, CGB5, IGFBP1, OLFML2B, RAI14, SERPINE1, IQSEC2, and MPND were selected by the multivariable Cox model. Functionally, PI3K-Akt signaling pathway and platelet-derived growth factor receptor (PDGFR) were found to be hyperactive in the high-risk group. The multivariable Cox regression analysis revealed that the risk stratification based on the seven-gene-signature-based Cox model was independent of other prognostic factors such as TNM stages, age, and gender. Conclusion. In conclusion, we aimed at developing a model to predict the prognosis of gastric cancer. The predictive model could not only effectively predict the risk of GC but also be beneficial to the development of therapeutic strategies.
An Improved Test Method for Energy Consumption and Range of Fuel Cell Vehicles
Authors: Hao Dong , Zhang Yanyi , Wang Renguang , Wang Xiaobing , Zhu Kai , Li Jun , Hou Yongping
Published: August 2020

At present, there are two main standards, ISO 23828 : 2013 and SAE J 2572–2014, which prescribe the hydrogen consumption test using the pressure method, gravimetric method, and flow method. However, these methods do not meet the test requirements for electric energy consumption and the range of plug-in hybrid fuel cell vehicles (FCVs) which are the main technical considerations in China and Europe. In this paper, a new test method for the hydrogen consumption, electric energy consumption, and range of FCVs is proposed without the use of additional hydrogen supply, measurement instruments, or energy consumption correction, which can improve the operability of the test and avoid the conversion between electric energy and hydrogen. One plug-in hybrid FCV and one nonplug-in hybrid FCV were tested using the proposed method. The results show that the new method meets the requirements of fuel economy test for FCVs with hydrogen consumption rate, electric energy consumption rate, the range for plug-in hybrid FCVs, hydrogen consumption rate, and the range for nonplug-in FCVs.
Club Characteristic and the Proximity Effect of Travel Links between Cities in China
Authors: Chen Mingxing , Luo Xinyue , Hu Maogui , Zhang Xiaoping
Published: August 2020

With the increasingly close relations between cities in China, it is of great significance to explore the regular characteristics of the intercity connection. Through Tencent’s population migration heat and Baidu map big data, this paper analyzes the regular characteristics of the relations between complex cities based on such index as the rich node propensity index, preference level index, and relative heat index and also investigates the influence of geographical proximity factors on the external relations of different cities. The research has the following results. Firstly, the relations between cities have obvious club characteristics. The rich nodes tend to connect with the rich nodes, while the nonrich nodes tend to connect with the nonrich nodes. Secondly, the connection between cities has the effect of hierarchical proximity, and cities mainly establish spatial connections with cities of the same level and adjacent level. Thirdly, the relations between cities also have the effect of geographical proximity, and the degree of influence of geographical proximity in low-level cities is greater than that in high-level cities. Fourthly, the external connection mode of high-level cities is to establish close contact with high-level cities adjacent to the level, with strong attraction to low-level cities adjacent to the location at the same time. The low-level cities are closely related to the high-level cities adjacent to the location and other cities of geographical proximity or adjacent level. This study helps to further understand the complex characteristics and laws of intercity connections and urban networks.
Change Detection of Remote Sensing Images Based on Attention Mechanism
Authors: Chen Long , Zhang Dezheng , Li Peng , Lv Peng
Published: August 2020

In recent years, image processing methods based on convolutional neural networks (CNNs) have achieved very good results. At the same time, many branch techniques have been proposed to improve accuracy. Aiming at the change detection task of remote sensing images, we propose a new network based on U-Net in this paper. The attention mechanism is cleverly applied in the change detection task, and the data-dependent upsampling (DUpsampling) method is used at the same time, so that the network shows improvement in accuracy, and the calculation amount is greatly reduced. The experimental results show that, in the two-phase images of Yinchuan City, the proposed network has a better antinoise ability and can avoid false detection to a certain extent.
Fracturing of the Soft Rock Surrounding a Roadway Subjected to Mining at Kouzidong Coal Mine
Authors: Su Zhili , Xie Wenbing , Jing Shengguo , Wang Xingkai , Tang Qingteng
Published: August 2020

The fracture development and distribution around the deep soft rock roadway are pivotal to any underground design. In this paper, both field investigation and numerical simulation were taken to study the fracture evolution and rock deformation of a coal mine roadway at Kouzidong mine, Fuyang, Anhui Province, China. Based on the borehole imaging technique, we found an asymmetric distribution of the fracture zone in the surrounding rock of the roadway. By analyzing the C value of the fractures in the borehole images,we found that the fracture interval distribution of the surrounding rock of the tunnel, the number of fractures will fluctuate decrease with the increase of the depth. To effectively study the fracture propagation and distribution of the roadway under longwall retreatment and roadway excavation, the global‐local numerical technique was applied via FLAC3D and PFC2D. In the roadway excavation process, fractures were first formed in the shallow section of the roadway and progressively propagated toward the deeper soft rock layer; the main failure mechanism was a tensile failure. During longwall retreatment, fractures continuously developed toward the deeper soft rock layer. However, the failure mechanism transformed to shear failure. From numerical results, it can be seen that the stress concentration at the ribs was released, which led to shear failure at the roof and floor. Due to the extensive tensile cracks in the shallow section, the surrounding rock experienced expansion and fracture. The deep shear failure also induced the formation of the nonadjacent crushing zone and elastic zone, which is in line with the borehole imaging results.
Financial Assessment of Forest Management Systems in the Community Forests: A Case Study from the Midhills of Nepal
Authors: Basnyat Bijendra
Published: August 2020

In Nepal, forest management priority is shifting to scientific management from conventional management. Though, the forest officials claims that scientific management is beneficial to the forest user groups, comparative financial assessment with conventional management remains unexplored. Following a case study approach, this study compares financial efficiency of two forest management systems in the community forests, focusing on benefit-cost ratio. The study conducted documents review, focus group discussions, and rapid survey to quantify costs and benefits from each forest management system. Conventional management gave a higher benefit-cost ratio to the forest user groups, irrespective of whether forest products are sold at a subsidized price or par with the market price. However, scientific management required high forest management costs and thus had a lower benefit-cost ratio. Sensitivity analysis between two systems revealed that conventional management gave a higher benefit-cost ratio in all cases. The study concludes that forest user groups would bear financial loss if they do not fix the price of the timber at par with the market in scientific management, and in such a case, the tagged price will be beyond affordability of the forest users. Furthermore, scientific management has discouraged kind contribution of users in managing forest. Besides, social and environmental consequences of scientific management cannot be ignored. Hence, the study argues for reconsidering current scientific management considering likely economic and social consequences to the forest user groups.