bluuebunny/crossref_metadata_2025 huggingface dataset:
A Solar Altitude Angle Model for Efficient Solar Energy Predictions
Authors: Herrería-Alonso Sergio , Suárez-González Andrés , Rodríguez-Pérez Miguel , Rodríguez-Rubio Raúl F. , López-García Cándido
Published: March 2020

Sunlight is one of the most frequently used ambient energy sources for energy harvesting in wireless sensor networks. Although virtually unlimited, solar radiation experiences significant variations depending on the weather, the season, and the time of day, so solar-powered nodes commonly employ solar prediction models to effectively adapt their energy demands to harvesting dynamics. We present in this paper a novel energy prediction model that makes use of the altitude angle of the sun at different times of day to predict future solar energy availability. Unlike most of the state-of-the-art predictors that use past energy observations to make predictions, our model does not require one to maintain local energy harvesting patterns of past days. Performance evaluation shows that our scheme is able to provide accurate predictions for arbitrary forecasting horizons by performing just a few low complexity operations. Moreover, our proposal is extremely simple to set up since it does not require any particular tuning for each different scenario or location.
Detection of Gas Drifting Near the Ground by Drone Hovering Over: Using Airflow Generated by Two Connected Quadcopters
Authors: Sato Ryohei , Tanaka Kento , Ishida Hanako , Koguchi Saki , Pauline Ramos Ramirez Jane , Matsukura Haruka , Ishida Hiroshi
Published: March 2020

This paper describes the utilization of the downwashes of multicopters for gas-sensing applications. Multirotor drones are an attractive platform for sensing applications. Their high maneuverability enables swift scanning of a target area with onboard sensors. When equipped with a gas sensor and used for gas-sensing applications, however, the strong downwash produced by the rotors poses a problem. When a multicopter is hovering at a low altitude, gas puffs leaked from a gas source on the ground are all blown away. Here, we propose to use two multicopters connected by a rod or a string and place a gas sensor at the midpoint of the rod/string. The downwash generated by each multicopter spreads radially after it impinges on the ground. When two multicopters are connected, the airflows spreading radially along the ground from the two multicopters impinge at the center and are deflected in the upward direction. Gas puffs wafting near the ground surface between the two multicopters are carried by this upward airflow to the gas sensor. Experimental results are presented to show the soundness of the proposed method. The connected quadcopters hovering over an ethanol gas source was able to detect the gas even with a moderate cross-flow.
A Matching Game-Based Data Collection Algorithm with Mobile Collectors
Authors: Zhang Chun , Fei Shumin
Published: March 2020

Data collection is one of the key technologies in wireless sensor networks. Due to the limited battery resources of sensors, mobile collectors are introduced to collect data instead of multi-hop data relay. However, how to decrease the data delay based on the cooperation of mobile collectors is a main problem. To solve this problem, a matching game-based data collection algorithm is proposed. First, some high-level cluster heads are elected. Second, by introducing a matching game model, the data collection problem is modeled as a one to one matching problem. Then, according to the preferences of mobile collectors and cluster heads, the benefit matrices are established. Based on the proposed matching algorithm, each mobile collector selects a cluster head to collect the data packets. Performance analysis proves that the matching result is stable, optimal, and unique. Simulation results show that the proposed algorithm is superior to other existing approach in terms of the reduction in data delay.
Smart Sensor Architectures for Multimedia Sensing in IoMT
Authors: Silvestre-Blanes Javier , Sempere-Payá Víctor , Albero-Albero Teresa
Published: March 2020

Today, a wide range of developments and paradigms require the use of embedded systems characterized by restrictions on their computing capacity, consumption, cost, and network connection. The evolution of the Internet of Things (IoT) towards Industrial IoT (IIoT) or the Internet of Multimedia Things (IoMT), its impact within the 4.0 industry, the evolution of cloud computing towards edge or fog computing, also called near-sensor computing, or the increase in the use of embedded vision, are current examples of this trend. One of the most common methods of reducing energy consumption is the use of processor frequency scaling, based on a particular policy. The algorithms to define this policy are intended to obtain good responses to the workloads that occur in smarthphones. There has been no study that allows a correct definition of these algorithms for workloads such as those expected in the above scenarios. This paper presents a method to determine the operating parameters of the dynamic governor algorithm called Interactive, which offers significant improvements in power consumption, without reducing the performance of the application. These improvements depend on the load that the system has to support, so the results are evaluated against three different loads, from higher to lower, showing improvements ranging from 62% to 26%.
A Review on the Development of Tunable Graphene Nanoantennas for Terahertz Optoelectronic and Plasmonic Applications
Authors: Ullah Zaka , Witjaksono Gunawan , Nawi Illani , Tansu Nelson , Irfan Khattak Muhammad , Junaid Muhammad
Published: March 2020

Exceptional advancement has been made in the development of graphene optical nanoantennas. They are incorporated with optoelectronic devices for plasmonics application and have been an active research area across the globe. The interest in graphene plasmonic devices is driven by the different applications they have empowered, such as ultrafast nanodevices, photodetection, energy harvesting, biosensing, biomedical imaging and high-speed terahertz communications. In this article, the aim is to provide a detailed review of the essential explanation behind graphene nanoantennas experimental proofs for the developments of graphene-based plasmonics antennas, achieving enhanced light–matter interaction by exploiting graphene material conductivity and optical properties. First, the fundamental graphene nanoantennas and their tunable resonant behavior over THz frequencies are summarized. Furthermore, incorporating graphene–metal hybrid antennas with optoelectronic devices can prompt the acknowledgment of multi-platforms for photonics. More interestingly, various technical methods are critically studied for frequency tuning and active modulation of optical characteristics, through in situ modulations by applying an external electric field. Second, the various methods for radiation beam scanning and beam reconfigurability are discussed through reflectarray and leaky-wave graphene antennas. In particular, numerous graphene antenna photodetectors and graphene rectennas for energy harvesting are studied by giving a critical evaluation of antenna performances, enhanced photodetection, energy conversion efficiency and the significant problems that remain to be addressed. Finally, the potential developments in the synthesis of graphene material and technological methods involved in the fabrication of graphene–metal nanoantennas are discussed.
Comparing Airborne Particulate Matter Intake Dose Assessment Models Using Low-Cost Portable Sensor Data
Authors: Novak Rok , Kocman David , Robinson Johanna Amalia , Kanduč Tjaša , Sarigiannis Dimosthenis , Horvat Milena
Published: March 2020

Low-cost sensors can be used to improve the temporal and spatial resolution of an individual’s particulate matter (PM) intake dose assessment. In this work, personal activity monitors were used to measure heart rate (proxy for minute ventilation), and low-cost PM sensors were used to measure concentrations of PM. Intake dose was assessed as a product of PM concentration and minute ventilation, using four models with increasing complexity. The two models that use heart rate as a variable had the most consistent results and showed a good response to variations in PM concentrations and heart rate. On the other hand, the two models using generalized population data of minute ventilation expectably yielded more coarse information on the intake dose. Aggregated weekly intake doses did not vary significantly between the models (6–22%). Propagation of uncertainty was assessed for each model, however, differences in their underlying assumptions made them incomparable. The most complex minute ventilation model, with heart rate as a variable, has shown slightly lower uncertainty than the model using fewer variables. Similarly, among the non-heart rate models, the one using real-time activity data has less uncertainty. Minute ventilation models contribute the most to the overall intake dose model uncertainty, followed closely by the low-cost personal activity monitors. The lack of a common methodology to assess the intake dose and quantifying related uncertainties is evident and should be a subject of further research.
Optimization of Green Fresh Food Logistics with Heterogeneous Fleet Vehicle Route Problem by Improved Genetic Algorithm
Authors: Li Danlian , Cao Qian , Zuo Min , Xu Fei
Published: March 2020

In order to reduce the distribution cost of fresh food logistics and achieve the goal of green distribution at the same time, the Green Fresh Food Logistics with Heterogeneous Fleet Vehicle Route Problem (GFLHF-VRP) model is established. Based on the particularity of the model, an improved genetic algorithm called Genetic Algorithm with Adaptive Simulated Annealing Mutation (GAASAM) is proposed in which the mutation operation is upgraded to a simulated annealing mutation operation and its parameters are adjusted by the adaptive operation. The experimental results show that the proposed GAASAM can effectively solve the vehicle routing problem of the proposed model, achieve better performance than the genetic algorithm, and avoid falling into a local optimal trap. The distribution routes obtained by GAASAM are with lower total distribution cost, and achieve the goal of green distribution in which energy, fuel consumption and carbon emissions are reduced at the same time. On the other hand, the proposed GFLHF-VRP and GAASAM can provide a reliable distribution route plan for fresh food logistics enterprises with multiple types of distribution vehicles in real life, which can further reduce the distribution cost and achieve a greener and more environment-friendly distribution solution. The results of this study also provide a managerial method for fresh food logistics enterprises to effectively arrange the distribution work with more social responsibility.
Mapping the Landscape and Structure of Research on Education for Sustainable Development: A Bibliometric Review
Authors: Hallinger Philip , Nguyen Vien-Thong
Published: March 2020

This systematic review of research used science mapping as a means of analyzing the knowledge base on education for sustainable development (ESD) in K-12 schooling. The review documented the size, growth trajectory and geographic distribution of this literature, identified high impact scholars and documents, and visualized the “intellectual structure” of the field. The database examined in this review consisted of 1842 English language, Scopus-indexed documents published between 1990 and 2018. The review found that the knowledge base on ESD has grown dramatically over the past 30 years, with a rapidly accelerating rate of publication in the past decade. Although the field has been dominated by scholarship from Anglo-American_European nations, there is evidence of increasing geographic diversification of the ESD knowledge base over the past 15 years. Citation analyses identified authors who have had a significant influence on the development of this literature. Author co-citation analysis revealed three “schools of thought” that comprise the “intellectual structure” of this knowledge base: Education for Sustainable Development, Developing a Sustainability Mindset, Teaching and Learning for Sustainability. Document content analyses led to the conclusion that the current knowledge base is heavily weighted towards critical, descriptive and prescriptive papers, with an insufficient body of analytical empirical studies. Several recommendations are offered for strengthening this literature.
The Identity of Recycled Plastics: A Vocabulary of Perception
Authors: Veelaert Lore , Du Bois Els , Moons Ingrid , De Pelsmacker Patrick , Hubo Sara , Ragaert Kim
Published: March 2020

As designing with recycled materials is becoming indispensable in the context of a circular economy, we argue that understanding how recycled plastics are perceived by stakeholders involved in the front end of the design process, is essential to achieve successful application in practice, beyond the current concept of surrogates according to industry. Based on existing frameworks, 34 experiential scales with semantic opposites were used to evaluate samples of three exemplary recycled plastics by two main industrial stakeholders: 30 material engineers and 30 designers. We describe four analyses: (i) defining experiential material characteristics, (ii) significant differences between the materials, (iii) level of agreement of respondents, and (iv) similarities and differences between designers and engineers. We conclude that the three materials have different perceptual profiles or identities that can initiate future idea generation for high-quality applications. The study illustrates the potential of this evaluation method. We propose that designers can facilitate the valorization and adoption of these undervalued recycled materials, first by industry and ultimately by consumers as well.
Indoor Vertical Farming in the Urban Nexus Context: Business Growth and Resource Savings
Authors: Avgoustaki Dafni Despoina , Xydis George
Published: March 2020

In recent years, a new urban environment in the large metropolitan areas, the so-called “megacities”, has emerged. It is estimated that more than five billion people will be located in urban areas by 2030. Many projects have been initiated in the megacities to support the new ecosystem services in providing the most sustainable and efficient food supply solutions, as well as for transporting fresh and clean vegetables. One of the most important focus areas is research on energy sustainability, including how to optimize energy efficiency to meet the needs of citizens and companies. Indoor urban vertical farming (IUVF) is one of the greatest achievements of our time in agriculture, as it is entirely focused on meeting the food needs of people living in urban areas with the lowest environmental and energy costs. IUVF creates a new foundation in the urban food production system, providing opportunities for many other sustainable activities, such as energy and grey water recycling, but beyond all, it helps citizens to have access in fresh and nutritious fruits and vegetables and to become more creative building up their skills regarding sustainable food production. In this study, the internal rate of return (IRR) and the net present value (NPV) indexes were used to compare IUVF and greenhouse (GH) facilities under various financing schemes. Consistent with similar studies, this research also confirms that IUVF is much more profitable for investors, saving significant resources compared to GHs.
Oscillatory Behavior of Fourth-Order Differential Equations with Neutral Delay
Authors: Moaaz Osama , El-Nabulsi Rami Ahmad , Bazighifan Omar
Published: March 2020

In this paper, new sufficient conditions for oscillation of fourth-order neutral differential equations are established. One objective of our paper is to further improve and complement some well-known results which were published recently in the literature. Symmetry ideas are often invisible in these studies, but they help us decide the right way to study them, and to show us the correct direction for future developments. An example is given to illustrate the importance of our results.
Higher Dimensional Static and Spherically Symmetric Solutions in Extended Gauss–Bonnet Gravity
Authors: Bajardi Francesco , Dialektopoulos Konstantinos F. , Capozziello Salvatore
Published: March 2020

We study a theory of gravity of the form f ( G ) where G is the Gauss–Bonnet topological invariant without considering the standard Einstein–Hilbert term as common in the literature, in arbitrary ( d + 1 ) dimensions. The approach is motivated by the fact that, in particular conditions, the Ricci curvature scalar can be easily recovered and then a pure f ( G ) gravity can be considered a further generalization of General Relativity like f ( R ) gravity. Searching for Noether symmetries, we specify the functional forms invariant under point transformations in a static and spherically symmetric spacetime and, with the help of these symmetries, we find exact solutions showing that Gauss–Bonnet gravity is significant without assuming the Ricci scalar in the action.
Zero-Energy Modes, Fractional Fermion Numbers and The Index Theorem in a Vortex-Dirac Fermion System
Authors: Yanagisawa Takashi
Published: March 2020

Physics of topological materials has attracted much attention from both physicists and mathematicians recently. The index and the fermion number of Dirac fermions play an important role in topological insulators and topological superconductors. A zero-energy mode exists when Dirac fermions couple to objects with soliton-like structure such as kinks, vortices, monopoles, strings, and branes. We discuss a system of Dirac fermions interacting with a vortex and a kink. This kind of systems will be realized on the surface of topological insulators where Dirac fermions exist. The fermion number is fractionalized and this is related to the presence of fermion zero-energy excitation modes. A zero-energy mode can be regarded as a Majorana fermion mode when the chemical potential vanishes. Our discussion includes the case where there is a half-flux quantum vortex associated with a kink in a magnetic field in a bilayer superconductor. A normalizable wave function of fermion zero-energy mode does not exist in the core of the half-flux quantum vortex. The index of Dirac operator and the fermion number have additional contributions when a soliton scalar field has a singularity.
Research on Information Fusion for Machine Potential Fault Operation and Maintenance
Authors: Xu Wei , Wan Yi , Zuo Tian-Yu , Sha Xin-Mei
Published: March 2020

In recent years, the development of sensor technology in industry has profoundly changed the way of operation and management in manufacturing enterprises. Due to the popularization and promotion of sensors, the maintenance of machines on the production line are also changing from the subjective experience-based machine maintenance to objective data-driven maintenance decision-making. Therefore, more and more data decision model has been developed through AI technology and intelligence algorithms. Equally important, the information fusion between decision results, which got by data decision model, has also received widespread attention. Information fusion is performed on symmetric data structures. The asymmetric data under the symmetric structure leads to the difference in information fusion results. Therefore, fully considering the potential differences of asymmetric data under a symmetric structure is an important content of information fusion. In view of the above, this paper studies how to make information fusion between different decision results through the framework of D-S evidence theory and discusses the deficiency of D-S evidence theory in detail. Based on D-S evidence theory, then a comprehensive evidence method for information fusion is proposed in this paper. We illustrate the rationality and effectiveness of our method through analysis of experiment case. And, this method is applied to a real case from industry. Finally, the irrationality of the traditional D-S method in the comprehensive decision-making results of machine operation and maintenance was solved by our novel method.
A 3D Mask Presentation Attack Detection Method Based on Polarization Medium Wave Infrared Imaging
Authors: Sun Pengcheng , Zeng Dan , Li Xiaoyan , Yang Lin , Li Liyuan , Chen Zhouxia , Chen Fansheng
Published: March 2020

Facial recognition systems are often spoofed by presentation attack instruments (PAI), especially by the use of three-dimensional (3D) face masks. However, nonuniform illumination conditions and significant differences in facial appearance will lead to the performance degradation of existing presentation attack detection (PAD) methods. Based on conventional thermal infrared imaging, a PAD method based on the medium wave infrared (MWIR) polarization characteristics of the surface material is proposed in this paper for countering a flexible 3D silicone mask presentation attack. A polarization MWIR imaging system for face spoofing detection is designed and built, taking advantage of the fact that polarization-based MWIR imaging is not restricted by external light sources (including visible light and near-infrared light sources) in spite of facial appearance. A sample database of real face images and 3D face mask images is constructed, and the gradient amplitude feature extraction method, based on MWIR polarization facial images, is designed to better distinguish the skin of a real face from the material used to make a 3D mask. Experimental results show that, compared with conventional thermal infrared imaging, polarization-based MWIR imaging is more suitable for the PAD method of 3D silicone masks and shows a certain robustness in the change of facial temperature.
A Fixed-Point Subgradient Splitting Method for Solving Constrained Convex Optimization Problems
Authors: Nimana Nimit
Published: March 2020

In this work, we consider a bilevel optimization problem consisting of the minimizing sum of two convex functions in which one of them is a composition of a convex function and a nonzero linear transformation subject to the set of all feasible points represented in the form of common fixed-point sets of nonlinear operators. To find an optimal solution to the problem, we present a fixed-point subgradient splitting method and analyze convergence properties of the proposed method provided that some additional assumptions are imposed. We investigate the solving of some well known problems by using the proposed method. Finally, we present some numerical experiments for showing the effectiveness of the obtained theoretical result.
A Philos-Type Oscillation Criteria for Fourth-Order Neutral Differential Equations
Authors: Bazighifan Omar , Cesarano Clemente
Published: March 2020

Some sufficient conditions are established for the oscillation of fourth order neutral differential equations of the form r t z ‴ t α ′ + q t x β σ t = 0 , where z t : = x t + p t x τ t . By using the technique of Riccati transformation and integral averaging method, we get conditions to ensure oscillation of solutions of this equation. Symmetry ideas are often invisible in these studies, but they help us decide the right way to study them, and to show us the correct direction for future developments. Moreover, the importance of the obtained conditions is illustrated via some examples.
An Emergency Decision-Making Method for Probabilistic Linguistic Term Sets Extended by D Number Theory
Authors: Mo Hongming
Published: March 2020

Emergency decision-making has become as one of the hot issues in recent years. The aim of emergency decision-making is to reduce the casualties and property losses. All the processes of emergency decision-making are full of incompleteness and hesitation. The problem of emergency decision-making can be regarded as one of the multi-attribute decision-making (MADM) problems. In this manuscript, a new method to solve the problem of emergency decision-making named D-PLTS is proposed, based on D number theory and the probability linguistic term set (PLTS). The evaluation information given by experts is tidied to be the form of PLTS, which can be directly transferred to the form of the D number, no matter whether the information is complete or not. Furthermore, the integration property of D number theory is carried out to fuse the information. Besides, two examples are given to demonstrate the effectiveness of the proposed method. Compared with some existing methods, the D-PLTS is more straightforward and has less computational complexity. Allocation weights that are more reasonable is the future work for the D-PLTS method.
Residual Control Chart for Binary Response with Multicollinearity Covariates by Neural Network Model
Authors: Kim Jong-Min , Wang Ning , Liu Yumin , Park Kayoung
Published: March 2020

Quality control studies have dealt with symmetrical data having the same shape with respect to left and right. In this research, we propose the residual (r) control chart for binary asymmetrical (non-symmetric) data with multicollinearity between input variables via combining principal component analysis (PCA), functional PCA (FPCA) and the generalized linear model with probit and logit link functions, and neural network regression model. The motivation in this research is that the proposed control chart method can deal with both high-dimensional correlated multivariate data and high frequency functional multivariate data by neural network model and FPCA. We show that the neural network r control chart is relatively efficient to monitor the simulated and real binary response data with the narrow length of control limits.
Numerical Picard Iteration Methods for Simulation of Non-Lipschitz Stochastic Differential Equations
Authors: Geiser Jürgen
Published: March 2020

In this paper, we present splitting approaches for stochastic/deterministic coupled differential equations, which play an important role in many applications for modelling stochastic phenomena, e.g., finance, dynamics in physical applications, population dynamics, biology and mechanics. We are motivated to deal with non-Lipschitz stochastic differential equations, which have functions of growth at infinity and satisfy the one-sided Lipschitz condition. Such problems studied for example in stochastic lubrication equations, while we deal with rational or polynomial functions. Numerically, we propose an approximation, which is based on Picard iterations and applies the Doléans-Dade exponential formula. Such a method allows us to approximate the non-Lipschitzian SDEs with iterative exponential methods. Further, we could apply symmetries with respect to decomposition of the related matrix-operators to reduce the computational time. We discuss the different operator splitting approaches for a nonlinear SDE with multiplicative noise and compare this to standard numerical methods.
Modified Combined-Step-Size Affine Projection Sign Algorithms for Robust Adaptive Filtering in Impulsive Interference Environments
Authors: Li Guoliang , Zhang Hongbin , Zhao Ji
Published: March 2020

In this paper, to further improve the filtering performance and enhance the poor tracking capability of the conventional combined step-size affine projection sign algorithm (CSS-APSA) in system identification, we propose a simplified CSS-APSA (SCSS-APSA) by applying the first-order Taylor series expansion to the sigmoidal active function (of which the independent variable is symmetric) of CSS-APSA. SCSS-APSA has lower computational complexity, and can achieve comparable, or even better filtering performance than that of CSS-APSA. In addition, we propose a modification of the sigmoidal active function. The modified sigmoidal active function is a form of scaling transformation based on the conventional one. Applying the modified function to the CSS-APSA, we can obtain the modified CSS-APSA (MCSS-APSA). Moreover, the extra parameter of MCSS-APSA provides the power to accelerate the convergence rate of CSS-APSA. Following the simplification operations of SCSS-APSA, the computational complexity of MCSS-APSA can also be reduced. Therefore, we get the simplified MCSS-APSA (SMCSS-APSA). Simulation results demonstrate that our proposed algorithms are able to achieve a faster convergence speed in system identification.
An Automated Smart EPQ-Based Inventory Model for Technology-Dependent Products under Stochastic Failure and Repair Rate
Authors: Asghar Iqra , Kim Jong Soo
Published: March 2020

With the ever-growing technology development, high-tech products such as mobile phones, computers, electromagnetic devices and smart devices are facing high design and production modification requirements with relatively shorter life cycles. For instance, every forthcoming smart phone goes out of production in a shorter period after its launch, followed by its next generation. The design of high-tech products requires high investments in smart and automated manufacturing technology to ensure higher production efficiency. For high-tech products with short life spans, the manufacturing performance-quality variable is an important design parameter that affects system reliability, production efficiency and manufacturing costs. Major performance-quality factors of a manufacturing system which affect productivity and reliability of the manufacturing process are discussed in this research. The study investigates an integrated smart production maintenance model under stochastic manufacturing reliability for technology dependent demand and variable production rate. The smart unit production cost is a function of manufacturing reliability and controllable production rate, as a manufacturing system can be operated at different production rates within designed limits μ ϵ [ μ m i n , μ m a x ] . Manufacturing reliability is increased through investment in smart manufacturing technology and resources. The integrated smart production maintenance model is formulated under general failure and repair time distributions and the optimal production maintenance policy is investigated under specific failure and repair time distributions. A mathematical model is developed to optimize the manufacturing quality-performance parameter, variable production rate, per unit technology investment and production lot size. The total cost function is optimized through the Khun–Tucker method. The mathematical model is also validated with numerical analysis, comparative study, and sensitivity analysis for model key parameters.
Influence of Ramped Wall Temperature and Ramped Wall Velocity on Unsteady Magnetohydrodynamic Convective Maxwell Fluid Flow
Authors: Anwar Talha , Kumam Poom , Watthayu Wiboonsak , Asifa
Published: March 2020

This article provides a comprehensive analysis regarding effects of ramped wall temperature and ramped wall velocity on incompressible time-dependent magnetohydrodynamic flow of Maxwell fluid. The flow is due to free convection and bounded to an infinite vertical plate embedded in porous medium. Solutions of mass, shear stress, and energy fields are computed symmetrically by introducing some suitable non-dimensional parameters along with the Laplace transformation technique. The expression for the Nusselt number is also calculated. A comparison between solutions incorporating isothermal temperature and ramped wall temperature conditions is also executed to examine the profile differences. A graphical study is performed to highlight the influence of parameters on mass flow and energy transfer.
Investigation of Magneto Hydro-Dynamics Effects on a Polymer Chain Transfer in Micro-Channel Using Dissipative Particle Dynamics Method
Authors: Zakeri Ramin , Sabouri Moslem , Maleki Akbar , Abdelmalek Zahra
Published: March 2020

In this paper, the effect of Magneto Hydro-Dynamics (MHD) on a polymer chain in the micro channel is studied by employing the Dissipative Particle Dynamics simulation (DPD) method. First, in a simple symmetric micro-channel, the results are evaluated and validated for different values of Hartmann (Ha) Number. The difference between the simulation and analytical solution is below 10%. Then, two types of polymer chain including short and long polymer chain are examined in the channel and the effective parameters such as Ha number, the harmony bond coefficient or spring constant (K), and the length of the polymer chain (N) are studied in the MHD flow. It is shown that by increasing harmony bond constant to 10 times with Ha = 20, the reduction of about 80% in radius of gyration squared, and half in polymer length compared to Ha = 1 would occur for both test cases. For short and long length of polymer, proper transfer of a polymer chain through MHD particles flow is observed with less perturbations (80%) and faster polymer transfer in the symmetric micro-channel.
Analysis of Structural Changes in Financial Datasets Using the Breakpoint Test and the Markov Switching Model
Authors: Phoong Seuk Wai , Phoong Seuk Yen , Phoong Kok Hau
Published: March 2020

The price movements of commodities are determined by changes in the expectations about future economic variables. Crude oil price is non-stationary, highly volatile, and unstructured in nature, which makes it very difficult to predict over short-to-medium time horizons. Some analysts have indicated that the difficulty in forecasting the crude oil price is due to the fact that economic models cannot consistently show evidence of a strong connection between commodities and economic fundamentals, and, as a result, regarded the idea that economic fundamentals help predict price values as random luck. This study aimed to overcome the limitations of the economic models through the detection of structural changes as well as breaks in the data, using a breakpoint test. The Markov switching model is used to address the price patterns that led to a different market state. The results show that there are several changes as well as breaks in the estimated model. Moreover, there is an asymmetric correlation between the crude oil price and the GDP.
Breast and Colon Cancer Classification from Gene Expression Profiles Using Data Mining Techniques
Authors: AbdElNabi Mohamed Loey Ramadan , Wajeeh Jasim Mohammed , M. EL-Bakry Hazem , Hamed N. Taha Mohamed , M. Khalifa Nour Eldeen
Published: March 2020

Early detection of cancer increases the probability of recovery. This paper presents an intelligent decision support system (IDSS) for the early diagnosis of cancer based on gene expression profiles collected using DNA microarrays. Such datasets pose a challenge because of the small number of samples (no more than a few hundred) relative to the large number of genes (in the order of thousands). Therefore, a method of reducing the number of features (genes) that are not relevant to the disease of interest is necessary to avoid overfitting. The proposed methodology uses the information gain (IG) to select the most important features from the input patterns. Then, the selected features (genes) are reduced by applying the grey wolf optimization (GWO) algorithm. Finally, the methodology employs a support vector machine (SVM) classifier for cancer type classification. The proposed methodology was applied to two datasets (Breast and Colon) and was evaluated based on its classification accuracy, which is the most important performance measure in disease diagnosis. The experimental results indicate that the proposed methodology is able to enhance the stability of the classification accuracy as well as the feature selection.
Contractive Inequalities for Some Asymptotically Regular Set-Valued Mappings and Their Fixed Points
Authors: Debnath Pradip , de La Sen Manuel
Published: March 2020

The symmetry concept is a congenital characteristic of the metric function. In this paper, our primary aim is to study the fixed points of a broad category of set-valued maps which may include discontinuous maps as well. To achieve this objective, we newly extend the notions of orbitally continuous and asymptotically regular mappings in the set-valued context. We introduce two new contractive inequalities one of which is of Geraghty-type and the other is of Boyd and Wong-type. We proved two new existence of fixed point results corresponding to those inequalities.
Hypervolemia-Induced Immune Disturbances Do Not Involve IL-1ß but IL-6 and IL-10 Activation in Haemodialysis Patients
Authors: Ulrich Christof , Wilke Annegret , Schleicher Nadja , Girndt Matthias , Fiedler Roman
Published: March 2020

Dysregulated fluid homeostasis is frequent in haemodialysis (HD) patients and is linked to inflammation which may be elicited by endotoxemia. The impact of hypervolemia on immune cells has not been studied in detail. Therefore, we analysed the hypervolemic activation of peripheral blood mononuclear cells (PBMCs) in HD with special focus on the NLRP3 inflammasome response. First, 45 HD were included in the observational study. Immune parameters including cell counts, caspase-1, oxidative stress, cytokine gene expression and serum analysis (IL-1ß, IL-6, IL-10) were all measured at two time points. Fluid status was evaluated by electrical bioimpedance vector analysis, defining hypervolemia (H) as >75 vector percentile. Then, 17 patients were classified as hypervolemic (H-HD), 19 as normovolemic (N-HD) and 9 failed to meet the inclusion criteria. Monocytes were elevated and lymphocytes were decreased by hypervolemia. NLRP3 inflammasome components, caspase-1 and IL-1ß expression were not statistically different between the two groups. Serum IL-6 levels were significantly elevated in H-HD. IL-10 mRNA transcripts were elevated by 2-fold in H-HD but were not efficiently translated. We conclude that the NLRP3 inflammasome is not activated by hypervolemia thus refuting the thesis that endotoxemia may be a main driver for inflammation in H-HD. Nevertheless, inflammation is generally higher in H-HD compared to N-HD patients and is not sufficiently balanced by anti-inflammatory mechanisms.
Novel HPAIV H5N8 Reassortant (Clade 2.3.4.4b) Detected in Germany
Authors: King Jacqueline , Schulze Christoph , Engelhardt Andreas , Hlinak Andreas , Lennermann Sara-Lisa , Rigbers Kerstin , Skuballa Jasmin , Staubach Christoph , Mettenleiter Thomas C. , Harder Timm , Beer Martin , Pohlmann Anne
Published: March 2020

A novel H5N8 highly pathogenic avian influenza virus (HPAIV) was detected in a greater white-fronted goose in January 2020 in Brandenburg, Germany, and, in February 2020, in domestic chickens belonging to a smallholding in Baden-Wuerttemberg, Germany. Full-genome sequencing was conducted on the MinION platform, enabling further phylogenetic analyses. The virus of clade 2.3.4.4b holds six segments from a Eurasian/Asian/African HPAIV H5N8 reassortant and two segments from low pathogenic avian influenza H3N8 subtype viruses recently detected in wild birds in Central Russia. These new entries continue to show the reassortment potential of the clade 2.3.4.4 H5Nx viruses, underlining the necessity for full-genome sequencing and continuous surveillance.
Integrated Geological, Hydrogeological, and Geophysical Investigations of a Barchan Sand Dune in the Eastern Region of Saudi Arabia
Authors: Benaafi Mohammed , Hanafy Sherif M. , Al-Shuhail Abdullatif , El-Husseiny Ammar , Dvorkin Jack
Published: March 2020

In arid countries such as Saudi Arabia, aeolian sand often covers a large area of the country. Understanding the variations of sand properties in dunes, including grain size, sorting, mineral composition and water content, can be important for groundwater recharge, environmental, and construction applications. Earlier studies examined properties of sand dunes by collecting samples from the surface. This study aims to investigate variations of sand properties within a Barchan sand dune in the coastal area of Saudi Arabia, by collecting samples and measurements from two vertically drilled boreholes up to the ground water level; one drilled in the dune crest and another one in the limb. Representative samples were collected and analyzed for their texture parameters, water content, and mineralogy. Electrical resistivity survey data was also acquired to map water content variation in the dune limb, and for comparison with well bore data. The reported results show no vertical variations in grain size or sorting in the dune crest. In contrast, the upper 0.5 m of the dune limb shows a relatively poorer sorting than found in deeper parts of the dune. Laterally, no variations in minerology were observed between crest and limb sands while grain size tended to be slightly coarser in the dune limb compared to the crest. Regarding the water content, it was found to vary vertically, probably due to previous cycles of rainfall infiltration through the sand body. Such observed variation in water content is consistent with the measured resistivity profile which could clearly identify the water table and areas with higher water content. This study concludes that beyond the upper 0.5 m, the Barchan sand dune body can be treated as a homogeneous medium in terms of mineralogy and sorting while grain size increases slightly toward the limb side.
Estimating Current and Future Rainfall Erosivity in Greece Using Regional Climate Models and Spatial Quantile Regression Forests
Authors: Vantas Konstantinos , Sidiropoulos Epaminondas , Loukas Athanasios
Published: March 2020

A future variation of precipitation characteristics, due to climate change, will affect the ability of rainfall to precipitate soil loss. In this paper, the monthly and annual values of rainfall erosivity (R) in Greece are calculated, for the historical period 1971–2000, using precipitation records that suffer from a significant volume of missing values. In order to overcome the data limitations, an intermediate step is applied using the calculation of monthly erosivity density, which is more robust to the presence of missing values. Spatial Quantile Regression Forests, a data driven algorithm that imitates kriging without the need of strict statistical assumptions, was utilized and validated, in order to create maps of R and its uncertainty using error propagation. The monthly average precipitation for the historical period 1971–2000 estimated by five (5) Global Circulation Models-Regional Climatic Models were validated against observed values and the one with the best performance was used to estimate projected changes of R in Greece for the future time period 2011–2100 and two different greenhouse gases concentration scenarios. The main findings of this study are: (a) the mean annual R in Greece is 1039 MJ·mm/ha/h/y, with a range between 405.1 and 3160.2 MJ·mm/ha/h/y. The highest values are calculated at the mountain range of Pindos and the lowest at central Greece; (b) the monthly R maps adhere to the spatiotemporal characteristics of precipitation depth and intensities over the country; (c) the projected R values, as an average over Greece, follow the projected changes of precipitation of climatic models, but not in a spatially homogenous way.
Recent Developments and Future Challenges of Hydrogels as Draw Solutes in Forward Osmosis Process
Authors: Wang Jichao , Gao Shanshan , Tian Jiayu , Cui Fuyi , Shi Wenxin
Published: March 2020

Forward osmosis (FO) has been recently regarded as a promising water treatment technology due to its lower energy consumption and lower membrane fouling propensity compared to the reverse osmosis (RO). The absence of suitable draw solute constraints the wide-range application of the FO. Hydrogels are three-dimensional hydrophilic polymer networks that can absorb a huge amount of water. Particularly, stimuli-responsive polymer hydrogels can undergo a reversible volume change or solution-gel phase transition in response to external environmental stimuli, including temperature, light, pressure, solvent composition, and pH. These intrinsic properties indicate the lowest regeneration cost of draw solutes compared to the thermal method and other membrane processes. This review aims to introduce the research progress on hydrogels as draw solutes, clarify the existing problems and point out the further research direction.
Modelling and Management of Irrigation System
Authors: Rodríguez Díaz Juan Antonio , Perea Rafael González , Moreno Miguel Ángel
Published: March 2020

Nowadays, irrigation is becoming an activity of precision, whereby it is necessary to combine information collected from various sources to manage resources in an optimal way. New management strategies, such as big data techniques, sensors, artificial intelligence, unmanned aerial vehicles (UAV) and new technologies in general, are becoming more relevant every day. Related to this, modeling techniques, both at the water distribution network and at farm level, will be essential to gather information from various sources and offer useful recommendations for decision-making processes. In this Special Issue, ten high-quality papers were selected that cover a wide range of issues that are relevant to the different aspects related to irrigation management: water source and distribution network, plot irrigation systems and crop water management.
Coastal Wetlands: Ecosystems Affected by Urbanization?
Authors: Novoa Vanessa , Rojas Octavio , Ahumada-Rudolph Ramón , Sáez Katia , Fierro Pablo , Rojas Carolina
Published: March 2020

Coastal wetlands are ecosystems that provide multiple benefits to human settlements; nonetheless, they are seriously threatened due to both a lack of planning instruments and human activities associated mainly with urban growth. An understanding of their functioning and status is crucial for their protection and conservation. Two wetlands with different degrees of urbanization, Rocuant-Andalién (highly urbanized) and Tubul-Raqui (with little urbanization), were analyzed using temperature, salinity, dissolved oxygen, pH, turbidity, granulometry, fecal coliform, and macroinvertebrate assemblage variables in summer and winter. In both wetlands marked seasonality in salinity, temperature and sediment texture classification, regulated by oceanic influence and changes in the freshwater budget, was observed. In the Rocuant-Andalién wetland, the increases in pH, dissolved oxygen, gravel percentage, and coliform concentration were statistically significant. Urbanization generated negative impacts on macroinvertebrate assemblage structure that inhabit the wetlands; greater richness and abundance (8.5 times greater) were recorded in the Tubul-Raqui wetland than in the more urbanized wetland. The multivariate statistical analysis reflects the alteration of these complex systems.