ALBERT

Description: In addition to direct virus infection of target cells, HIV can also be transferred from infected to uninfected cells (cell-to-cell transmission). These two routes might facilitate viral production and the establishment of the latent virus pool, which is considered as a major obstacle to HIV cure. We studied an HIV infection model including the two infection routes and the time since latent infection. The basic reproductive ratio R0 was derived. The existence, positivity, and boundedness of the solution are proved. We investigated the existence of steady states and their stability, which were shown to depend on R0. We established the global asymptotic dynamical behavior by proving the existence of the global compact attractor and uniform persistence of the system and by applying the method of Lyapunov functionals. In the end, we formulated and solved the optimal control problem for the age-structured model. The necessary condition for minimization of the viral level and the cost of drug treatment was obtained, and numerical simulations of various optimal control strategies were performed.

Description: In the past decades, the booming growth of housing markets in China triggers the urgent need to explore how the rapid urban spatial expansion, large-scale urban infrastructural development, and fast-changing urban planning determine the housing price changes and spatial differentiation. It is of great significance to promote the existing governing policy and mechanism of housing market and the reform of real-estate system. At the level of city, an empirical analysis is implemented with the traditional econometric models of regressive analysis and GIS-based spatial autocorrelation models, focusing in examining and characterizing the spatial homogeneity and nonstationarity of housing prices in Guangzhou, China. There are 141 neigborhoods in Guangzhou identified as the independent individuals (named as area units), and their values of the average annual housing prices (AAHP) in (2009–2015) are clarified as the dependent variables in regressing analysis models used in this paper. Simultaneously, the factors including geographical location, transportation accessibility, commercial service intensity, and public service intensity are identified as independent variables in the context of urban development and planning. The integration and comparative analysis of multiple linear regression models, spatial autocorrelation models, and geographically weighted regressing (GWR) models are implemented, focusing on exploring the influencing factors of house prices, especially characterizing the spatial heterogeneity and nonstationarity of housing prices oriented towards the spatial differences of urban spatial development, infrastructure layout, land use, and planning. This has the potential to enrich the current approaches to the complex quantitative analysis modelling of housing prices. Particularly, it is favorable to examine and characterize what and how to determine the spatial homogeneity and nonstationarity of housing prices oriented towards a microscale geospatial perspective. Therefore, this study should be significant to drive essential changes to develop a more efficient, sustainable, and competitive real-estate system at the level of city, especially for the emerging and dynamic housing markets in the megacities in China.

Description: Thermal performance development, heat transfer structure, and flow behavior in the heat exchanger square duct equipped with a 45° inclined square ring are investigated numerically. The effects of flow blockage ratios and spacing ratios for the inclined square ring on fluid flow and heat transfer are considered. The Reynolds number (Re = 100–2000, laminar regime) based on the hydraulic diameter of the square duct is selected for the present work. The numerical domain of the square duct inserted with the 45° inclined square ring is solved with the finite volume method. The SIMPLE algorithm is picked for the numerical investigation. The heat transfer characteristics and flow topologies in the square duct inserted with the inclined square ring are plotted in the numerical report. The heat transfer rate, pressure loss, and efficiency for the square duct placed with the inclined square ring are presented in forms of Nusselt number, friction factor, and thermal enhancement factor, respectively. As the numerical results, it is detected that the heat transfer rate of the heat exchanger square duct inserted with the inclined square ring is around 1.00–10.05 times over the smooth duct with no inclined square ring. Additionally, the maximum thermal enhancement factor for the heat exchanger square duct inserted with the inclined square ring is around 2.84.

Description: In the present work, the statistical dispersion of the mortar compressive strength as a function of the geometric parameters of the specimens as well as the effect of the mortar workability difference on the compressive strength was investigated. For this purpose, specimens were prepared for six types of mortars: two conventional mortars in the proportions of 1 : 1 : 6 and 1 : 2 : 9 of cement, hydrated lime, and sand, respectively, two with clay replacing lime, and two with marble waste in place of lime. The results confirm the difference between the results found for the two geometries due to the differences in the heights of the molding layers and show that the workability of the mortar modifies the resistance properties, especially in the cylindrical mold where the molding of the specimens is more complex. By comparing the differences between the destructive test results and those defined by the Finite Element Modeling (FEM) for conventional mortars, it was clear that the effect of excess material in the sample during the compression tests did not change the strength properties studied. This facilitates the performance of the assay as specimens may be used excessively on the side without the need for sample rectification.

Description: This research aimed to address health and food security challenges affecting Los Angeles and beyond in our own backyard. One possible way to combat these challenges is through biotechnology. The purpose of this research was to characterize the arable soils at Los Angeles Pierce College and their potential uses. The methods employed were collection of soil physical and chemical properties, cultivation of soil microorganisms, and 16S rDNA sequencing with a citizen science platform. Statistical analysis in R revealed associations between field conditions and life in the soil. The testing of plant-based antimicrobial agents on antibiotic-resistant bacteria revealed that plant oils could be more efficacious for control than common antibiotics. We found evidence of plant growth-promoting, antibiotic-producing, and bioremediating bacteria in different fields with distinct microclimates based on the 16S rDNA taxonomy results and inferred functional profiles. The major findings included an abundance of Streptomyces, Bacillus, Methylobacteria, and others with desirable functions. Numerous Streptomyces isolates cultivated on selective media demonstrated the ability to reduce nitrate. These results will empower future trials and product development by identifying target soil microorganisms and the most viable fields.

Description: Network embedding is a frontier topic in current network science. The scale-free property of complex networks can emerge as a consequence of the exponential expansion of hyperbolic space. Some embedding models have recently been developed to explore hyperbolic geometric properties of complex networks—in particular, symmetric networks. Here, we propose a model for embedding directed networks into hyperbolic space. In accordance with the bipartite structure of directed networks and multiplex node information, the method replays the generation law of asymmetric networks in hyperbolic space, estimating the hyperbolic coordinates of each node in a directed network by the asymmetric popularity-similarity optimization method in the model. Additionally, the experiments in several real networks show that our embedding algorithm has stability and that the model enlarges the application scope of existing methods.

Description: The conjugate gradient method is very effective in solving large-scale unconstrained optimal problems. In this paper, on the basis of the conjugate parameter of the conjugate descent (CD) method and the second inequality in the strong Wolfe line search, two new conjugate parameters are devised. Using the strong Wolfe line search to obtain the step lengths, two modified conjugate gradient methods are proposed for general unconstrained optimization. Under the standard assumptions, the two presented methods are proved to be sufficient descent and globally convergent. Finally, preliminary numerical results are reported to show that the proposed methods are promising.

Description: One of the most important threats to today’s civilization is terrorism. Terrorism not only disturbs the law and order situations in a society but also affects the quality of lives of humans and makes them suppressed physically and emotionally and deprives them of enjoying life. The more the civilizations have advanced, the more the people are working towards exploring different mechanisms to protect the mankind from terrorism. Different techniques have been used as counterterrorism to protect the lives of individuals in society and to improve the quality of life in general. Machine learning methods have been recently explored to develop techniques for counterterrorism based on artificial intelligence (AI). Since deep learning has recently gained more popularity in machine learning domain, in this paper, these techniques are explored to understand the behavior of terrorist activities. Five different models based on deep neural network (DNN) are created to understand the behavior of terrorist activities such as is the attack going to be successful or not? Or whether the attack is going to be suicide or not? Or what type of weapon is going to be used in the attack? Or what type of attack is going to be carried out? Or what region is going to be attacked? The models are implemented in single-layer neural network (NN), five-layer DNN, and three traditional machine learning algorithms, i.e., logistic regression, SVM, and Naïve Bayes. The performance of the DNN is compared with NN and the three machine learning algorithms, and it is demonstrated that the performance in DNN is more than 95% in terms of accuracy, precision, recall, and F1-Score, while ANN and traditional machine learning algorithms have achieved a maximum of 83% accuracy. This concludes that DNN is a suitable model to be used for predicting the behavior of terrorist activities. Our experiments also demonstrate that the dataset for terrorist activities is big data; therefore, a DNN is a suitable model to process big data and understand the underlying patterns in the dataset.

Description: In this paper, the fractional order models are used to study the propagation of ion-acoustic waves in ultrarelativistic plasmas in nonplanar geometry (cylindrical). Firstly, according to the control equations, (2 + 1)-dimensional (2D) cylindrical Kadomtsev–Petviashvili (CKP) equation and 2D cylindrical-modified Kadomtsev–Petviashvili (CMKP) equation are derived by using multiscale analysis and reduced perturbation methods. Secondly, using the semi-inverse method and the fractional variation principle, the abovementioned equations are derived the time-space fractional equations (TSF-CKP and TSF-CMKP). Furthermore, based on the fractional order transformation, the 1-decay mode solution of the TSF-CKP equation is obtained by using the simplified homogeneous balance method, and using the generalized hyperbolic-function method, the exact analytic solution of TSF-CMKP equation is obtained. Finally, the effects of the phase speed λ, electron number density (through β3) and the fractional order α,β,ω on the propagation of ion-acoustic waves in ultrarelativistic plasmas are analyzed.

Description: Symmetry is an important property found in a large number of nonlinear systems. The study of chaotic systems with symmetry is well documented. However, the literature is unfortunately very poor concerning the dynamics of such systems when their symmetry is altered or broken. In this paper, we investigate the dynamics of a simple jerk system with hyperbolic tangent nonlinearity (Kengne et al., Chaos Solitons, and Fractals, 2017) whose symmetry is broken by adding a constant term modeling an external excitation force. We demonstrate that the modified system experiences several unusual and striking nonlinear phenomena including coexisting bifurcation branches, hysteretic dynamics, coexisting asymmetric bubbles, critical transitions, and multiple (i.e., up to six) coexisting asymmetric attractors for some suitable ranges of system parameters. These features are highlighted by exploiting common nonlinear analysis tools such as graphs of largest Lyapunov exponent, bifurcation diagrams, phase portraits, and basins of attraction. The control of multistability is investigated by using the method of linear augmentation. We demonstrate that the multistable system can be converted to a monostable state by smoothly adjusting the coupling parameter. The theoretical results are confirmed by performing a series of PSpice simulations based on an electronic analogue of the system.

Description: Soil conservation practices such as cover crops can improve crop production, soil quality, and water quality. Cover crops can also influence soil microbial growth and activity. Cover cropped and manured soils can potentially store and transmit fecal bacteria (e.g., E. coli) to surface water if runoff and subsurface seepage occur. While many studies have shown the soil health benefits of cover crops, fewer studies have evaluated the extent to which cover crops influence the abundance of potential waste-borne pathogens. A two-year study (2015–2017) was conducted on a limited-resource farm in Logan County, Kentucky, USA, to quantify the abundance of the fecal indicator Escherichia coli (E. coli) bacteria (as a proxy for fecal coliforms) in treatments with and without cover crops or composted poultry litter. The cover crop consisted of a cereal rye (Secale cereale L.), Austrian winter pea (Pisum sativum L.), and crimson clover (Trifolium incarnatum L.) mix. Summer crops consisted of a no-till maize (Zea mays L.)—soybean (Glycine max L.) rotation. Soil samples were taken before and after each summer crop season and assessed to detect and enumerate E. coli. At the end of the study period, no significant treatment differences in the E. coli abundance in soil were detected (ca. 104 CFU·g−1) (). However, season/time was a significant factor (). We conclude that the background E. coli already present in soil was sufficiently high, inhibiting the detection of the influence of added composted litter. These indigenous E. coli were unaffected by cover crop and nutrient management but did fluctuate on a seasonal basis.

Description: The current study performs an explicit nonlinear finite element simulation to predict temperature distribution and consequent stresses during the friction stir welding (FSW) of AA 7075-T651 alloy. The ABAQUS® finite element software was used to model and analyze the process steps that involve plunging, dwelling, and traverse stages. Techniques such as Arbitrary Lagrangian–Eulerian (ALE) formulation, adaptive meshing, and computational feature of mass scaling were utilized to simulate sequence events during the friction stir welding process. The contact between the welding tool and workpiece was modelled through applying Coulomb’s friction model with a nonlinear friction coefficient value. Also, the model considered the effect of nonlinear material properties as well as heat transfer conditions such as heat losses due to convection and thermal contact conductance between the workpiece and the backing plate interface on the thermal history. To validate the computational model results, an experimental procedure was carried out to measure temperature history on both sides of the specimen as well as the plunging force throughout the whole process time. The results obtained showed that symmetrical temperature distribution throughout the workpiece width was distinguished, implying that the tool rotation has a minor effect on the final temperature distribution. In addition, asymptotic V shape with high gradient temperature value in the weld nugget region after the full plunging was distinguished. Mechanical stresses and related plastic deformations generated, while achieving the FSW samples were evaluated in addition to the tool reaction force and heat generated to protect against tool failure.

Description: Seven field trials were completed over a three-year period (2016 to 2018) in southwestern Ontario, Canada, to assess weed control in conventional-till dicamba-resistant (DR) soybean with glyphosate/dicamba (2 : 1 ratio) applied postemergence (POST) at 3 doses (900, 1350, and 1800 g·ae·ha−1) and 3 application timings (up to 5, 15, and 25 cm weeds). There was minimal soybean injury (≤2%) from treatments evaluated. Glyphosate/dicamba applied at application timing of up to 5, 15, and 25 cm weeds, controlled Amaranthus spp. (pigweed spp.) 87–96, 94–99, and 99%; Ambrosia artemisiifolia (common ragweed) 93–99, 97–99, and 99–100%; Chenopodium album (lambsquarters) 89–99, 95–100, and 99–100%; Echinochloa crus-galli (barnyardgrass) 81–84, 94–96, and 96–97%; Setaria faberi (giant foxtail) 37–90, 77–98, and 99–100%; and Setaria viridis (green foxtail) 94–96, 99, and 99–100%, respectively. Additionally, glyphosate/dicamba applied POST at 900, 1350, and 1800 g·ae·ha−1 controlled Amaranthus spp. 90–97, 95–98, and 97–99%; A. artemisiifolia 95–98, 97–99, and 99–100%; C. album 92–99, 95–100, and 98–100%; E. crus-galli 84–88, 93-94, and 95-96%; S. faberi 74–95, 75–97, and 79–98%; and S. viridis 98, 98–99, and 98–100%, respectively. Weed interference reduced DR soybean yield as much as 51% compared to the highest yielding treatments. Results indicate that glyphosate/dicamba applied POST at the label doses can provide an adequate control of troublesome weeds in DR soybean. Weed control was generally most consistent when glyphosate/dicamba was applied at the highest registered dose in Ontario (1800 g·ae·ha−1) and when weeds were up to 25 cm tall.

Description: This study compared the effects of shading in individual branch orders 2 and 3 on the needle survival, growth, and reproduction of five categories of short shoots of the proximal part of wild Atlas cedar (Cedrus atlantica (Endl.) G. Manetti ex Carrière). The sun exposure did not affect the number of short shoots in the two branch orders, whereas light compared to shade only stimulates the unbranched short shoot elongation of the branch order 3. The impact of shade exposure compared to sun on the loss of needles depends on the order of branching; it is weak to order 2 and increases to higher order. This effect in the branch order 3 is achieved by a significant decrease of the fallen leaf number in the unbranched short shoot SSnr and the short shoot SS/T worn by Twigs while in the branch order 2 only short shoot SS (nr + r) loses significantly few needles. In terms of short shoot extension and needle loss, the SS/T of the branch order 3 behaves in the same way as the SS (nr + r) of the branch order 2. The shadow compared to sunlit only decreases significantly the production of pollen strobili of the branch order 2. Close relationships between short shoot extension, leaf life span, and pollen strobili production of axillary products in the proximal part of C. atlantica crown were found.

Description: As an effect of intensive agricultural development of the steppes of the northern Black Sea coast, the finds of postantique agricultural landscapes that preserve relic elements of ancient land-use infrastructure are extremely rare. To these belongs the uniquely preserved ancient Greek land division system on the Tarkhankut Peninsula (north-western Crimea), which was studied using the methods of soil science and biomorphic analysis. This paper explores ancient land-use practices in order to reconstruct the original parameters of the land division system, as well as agricultural techniques employed. For postantique agricultural landscapes, an integrated geoarchaeological approach that includes GIS and remote sensing methodologies, in-field study of microrelief and soil registrograms, pedochronological dating technique, and physicochemical, geochemical, and biomorphic soil analyses has been developed and tested. The soil-geomorphological reconstruction shows that the Hellenistic land division system included a 4.5–4.9 m wide strip of land bordered by a 4.1–4.7 m wide (at the base) and c. 0.2 m high wall and a c. 2 m wide and over 15 cm deep trench, which controlled surface runoff and erosion. Ancient agricultural practices of slope farming resembled the modern ones. Surface runoff and soil erosion were controlled by dividing the catchment area into narrow plots, the borders of which on arable land were marked by simple earthen structures (low walls with shallow trenches). The biomorphic analysis of soil sampled atop these structures indicates that in ancient times, these earthen walls were not cultivated. The study of conservative properties preserved in pedomemory of postagrogenic soils provided valuable evidence of agricultural techniques used in the palaeogeographic conditions of the 4th and 3rd centuries BC.

Description: Production of pearl millet with yield improvement would have a direct impact on the drought-prone areas of Ethiopia since pearl millet is drought tolerant and early maturing with high water use efficiency. An experiment was conducted to study the performance of pearl millet under different technologies in 2013 and 2014 main cropping seasons at the main site of the research center, Aybra, with the objective of evaluating and identifying appropriate combinations of technologies that enhance the production of pearl millet in the study area. About fourteen integrated technologies were applied in a randomized complete block design with three replications. The analysis was done by using SAS software version 9.1, and means were separated through the Duncan multiple range test. Results of analysis of variance showed that yield-related traits of pearl millet were significantly influenced by the integration of technologies in the 2013 cropping season. According to the results, the maximum yield (3084 kg ha−1) was recorded with the application of the treatment combination of recommended fertilizer application + seed primming + tie ridging, while the minimum was recorded (919 kg ha−1) in the treatment combination of microdose application of fertilizer + primed seed + intercropping of pearl millet with mung bean. In the case of the 2014 cropping season, the highest grain yield (3687 kg ha−1) was recorded with the treatment combination of microdose fertilizer application + primed seed + tie ridging + intercropping of pearl millet with mung bean, whereas the lowest grain yield (2115 kg ha−1) was recorded in the treatment combination of no fertilizer application + primed seed + flat bed. Based on the results of the current investigation, it could be recommended that using technology integration of microdose, tied ridge, primed seed, and intercropping of pearl millet with mung bean is better to attain maximum yield in the study area and similar agroecologies.

Description: Autism spectrum disorder (ASD) is an early developmental disorder characterized by mutation of enculturation associated with attention deficit disorder in the visual perception of emotional expressions. An estimated one in more than 100 people has autism. Autism affects almost four times as many boys than girls. Data analysis and classification of ASD is still challenging due to unsolved issues arising from many severity levels and range of signs and symptoms. To understanding the functions which involved in autism, neuroscience technology analyzed responses to stimuli of autistic audio and video. The study focuses on analyzing the data set of adults and children with ASD using practical component analysis method. To satisfy this aim, the proposed method consists of three main stages including: (1) data set preparation, (2) Data analysis, and (3) Unsupervised Classification. The experimental results were performed to classify adults and children with ASD. The classification results in adults give a sensitivity of 78.6% and specificity of 82.47%, while the classification results in children give a sensitivity of 87.5% and specificity of 95.7%.

Description: Land degradation is a global negative environmental process that causes the decline in the productivity of land resources’ capacity to perform their functions. Though soil and water conservation (SWC) technologies have been adopted in Geshy subcatchment, their effects on soil quality were limitedly studied. The study was conducted to evaluate the effects SWC measures on soil quality indicators in Geshy subcatchment, Gojeb River Catchment, Ethiopia. A total of 54 soil samples (two treatments–farmlands with and without SWC measures  three slope classes  three terrace positions  three replications) were collected at a depth of 20 cm. Statistical differences in soil quality indicators were analyzed using multivariate analysis of variance (ANOVA) following the general linear model procedure of SPSS Version 20.0 for Windows. Means that exhibited significant differences were compared using Tukey’s honest significance difference at 5% probability level. The studied soils are characterized by low bulk density, slightly acidic with clay and clay loam texture. The results revealed that farmlands with SWC measures had significantly improved soil physical (silt and clay fractions, and volumetric soil water content (VSWC)) and chemical (pH, SOC, TN, C : N ratio, and Av. phosphorus) quality indicators as compared with farmlands without SWC measures. The significantly higher VSWC, clay, SOC, TN, C : N ratio, and Av. P at the bottom slope classes and terrace positions could be attributed to the erosion reduction and deposition effects of SWC measures. Generally, the status of the studied soils is low in SOC contents, TN, C : N ratio, and Av. P (deficient). Thus, integral use of both physical and biological SWC options and agronomic interventions would have paramount importance in improving soil quality for better agricultural production and productivity.

Description: Decomposition is a key flux of terrestrial carbon to the atmosphere. Therefore, gaining a better understanding of how plant litter decomposes in soil, and what governs this process, is vital for global climate models. The Tea Bag Index (TBI) was introduced by Keuskamp et al. (2013) as a novel method for measuring litter decomposition rate and stabilisation. The TBI uses two types of tea bags representing fast (green tea) and slow (rooibos tea) decomposition substrates as standardised litter bags. To date, the TBI method has been used in over 2000 locations across the globe. However, before now, there has been no information on how the composition of the tea leaves change during incubation. These data are crucial in determining the validity of the use of the TBI method globally, to ensure the tea leaves decompose in a way that is representative of so-called “native” litters. To provide chemical underpinning of the TBI method, a laboratory incubation of the tea bags was conducted with destructive sampling at 0, 7, 14, 21, 28, 35, 42, 49, 56, 63, 70, 77, 84, and 91 d. The incubated tea was analysed for total C and N. In addition, C was characterised as alkyl, O-alkyl, aromatic, or carbonyl C using solid-state 13C nuclear magnetic resonance spectroscopy with cross-polarization and magic angle spinning (CPMAS NMR). The results suggest that changes in carbon in both tea types are comparable to other litter studies, with a net decrease in total C and relative proportion of O-alkyl C fraction, which contains carbohydrates and cellulose. We conclude that the decomposition of tea leaves in the bags used in the TBI is representative of other litters.

Description: Thermal performance development, heat transfer structure, and flow behavior in the heat exchanger square duct equipped with a 45° inclined square ring are investigated numerically. The effects of flow blockage ratios and spacing ratios for the inclined square ring on fluid flow and heat transfer are considered. The Reynolds number (Re = 100–2000, laminar regime) based on the hydraulic diameter of the square duct is selected for the present work. The numerical domain of the square duct inserted with the 45° inclined square ring is solved with the finite volume method. The SIMPLE algorithm is picked for the numerical investigation. The heat transfer characteristics and flow topologies in the square duct inserted with the inclined square ring are plotted in the numerical report. The heat transfer rate, pressure loss, and efficiency for the square duct placed with the inclined square ring are presented in forms of Nusselt number, friction factor, and thermal enhancement factor, respectively. As the numerical results, it is detected that the heat transfer rate of the heat exchanger square duct inserted with the inclined square ring is around 1.00–10.05 times over the smooth duct with no inclined square ring. Additionally, the maximum thermal enhancement factor for the heat exchanger square duct inserted with the inclined square ring is around 2.84.

Description: Darrieus wind rotor is a vertical axis wind turbine that is a very promising kind of wind converters at remote and domestic locations that have soft and weak wind potential and speed, but from the quantitative comparison with horizontal axis wind turbines, this type of turbines has a weak performance. Additional researches are still needed to develop its efficiency to identify all the requirements of the generated power in low power demands. The aim of the current investigation is to analyze all the acting forces on the main parts of Darrieus rotor over the rotations as well as in maintenance and stationary conditions. Aerodynamic forces assessment will be executed for 3 different blade shapes (nonsymmetric and symmetric airfoils) like the airfoil section shapes of the Darrieus rotor blades. NACA 0021, LS413, and S1046 are selected as cross-sectional profile in this work. CFD simulations have been used in this work to get the different aerodynamic forces on the rotor blades of the Darrieus turbines. The present results indicated that the symmetric S1046 blade has higher forces during the rotation and stagnant (static) conditions. Moreover, the self-starting capability of NACA 0021 is better than S1046 due to low aerodynamic torsion on the S1046 blades.

Description: A cellular automaton (CA) model is proposed to simulate the egress of pedestrians while gaseous hazardous material is spreading. The advection-diffusion with source term is used to describe the propagation of gaseous hazardous material. It is incorporated into the CA model. The navigation field in our model is determined by the solution of the Eikonal equation. The state transition of a pedestrian relies on the arrival time of cells in the Moore neighborhood. Numerical experiments are investigated in a room with multiple exits, and their results are shown.

Description: In the present paper, we report a numerical study of dynamic and thermal behavior of the incompressible turbulent air flow by forced convection in a two-dimensional horizontal channel. This one contains the complicated form of the deflector which has been studied by varying the inclination angle from φ = 40°, φ = 55° to φ = 65°. The baffles are mounted on lower and upper walls of the channel. The walls are maintained at a constant temperature (375 K), the inlet velocity of air is Uint = 7.8 m/s, and the Reynolds number Re = 8.73 × 104. A specifically developed numerical model was based on the finite-volume method to solve the coupled governing equations and the SIMPLE (Semi Implicit Method for Pressure Linked Equation) algorithm for the treatment of velocity-pressure coupling. For Pr = 0.71, the results obtained show that (i) the streamlines and isotherms are strongly affected by the inclinations angles at Re = 8.73 × 104, (ii) the friction coefficient near the baffles increases under the angle exchange effect, and (iii) for a constant Re, the local Nusselt number at the walls of the channel varies with increasing the inclination angle of the deflector. Furthermore, the deflectors are generally used to change the direction of the structure of flow and also to increase the turbulence levels. We can conclude that the contribution of inclined baffles improves the increase of heat and mass transfer in which the Nusselt number at a certain angle increases noticeably.

Description: Humor refers to the quality of being amusing. With the development of artificial intelligence, humor recognition is attracting a lot of research attention. Although phonetics and ambiguity have been introduced by previous studies, existing recognition methods still lack suitable feature design for neural networks. In this paper, we illustrate that phonetics structure and ambiguity associated with confusing words need to be learned for their own representations via the neural network. Then, we propose the Phonetics and Ambiguity Comprehension Gated Attention network (PACGA) to learn phonetic structures and semantic representation for humor recognition. The PACGA model can well represent phonetic information and semantic information with ambiguous words, which is of great benefit to humor recognition. Experimental results on two public datasets demonstrate the effectiveness of our model.

Description: In this paper, a multi-unmanned underwater vehicle (UUV) cooperative dynamic maneuver decision-making algorithm is proposed based on the combination of game theory and intuitionistic fuzzy sets. Underwater environments with weak connectivity, underwater noise, and dynamic uncertainties are fully considered through intuitionistic fuzzy sets, which solves one of the main problems in making decisions underwater. Subsequently, the intuitionistic fuzzy multiattribute evaluation of a UUV maneuver strategy is conducted, and the intuitionistic fuzzy payment matrix of the cooperative dynamic maneuver game is obtained. Thereafter, the Nash equilibrium condition is proposed to satisfy the intuitionistic fuzzy total order, and the Nash equilibrium maneuver decision-making model under a dynamic underwater environment is established. Meanwhile, the modified particle swarm optimization method is presented to solve the established problem and find the optimal strategy. Finally, an example is used to verify the superiority of the proposed cooperative dynamic maneuver decision-making algorithm.

Description: The design of a swarm optimization-based fractional control for engineering application is an active research topic in the optimization analysis. This work offers the analysis, design, and simulation of a new neural network- (NN) based nonlinear fractional control structure. With suitable arrangements of the hidden layer neurons using nonlinear and linear activation functions in the hidden and output layers, respectively, and with appropriate connection weights between different hidden layer neurons, a new class of nonlinear neural fractional-order proportional integral derivative (NNFOPID) controller is proposed and designed. It is obtained by approximating the fractional derivative and integral actions of the FOPID controller and applied to the motion control of nonholonomic differential drive mobile robot (DDMR). The proposed NNFOPID controller’s parameters consist of derivative, integral, and proportional gains in addition to fractional integral and fractional derivative orders. The tuning of these parameters makes the design of such a controller much more difficult than the classical PID one. To tackle this problem, a new swarm optimization algorithm, namely, MAPSO-EFFO algorithm, has been proposed by hybridization of the modified adaptive particle swarm optimization (MAPSO) and the enhanced fruit fly optimization (EFFO) to tune the parameters of the NNFOPID controller. Firstly, we developed a modified adaptive particle swarm optimization (MAPSO) algorithm by adding an initial run phase with a massive number of particles. Secondly, the conventional fruit fly optimization (FFO) algorithm has been modified by increasing the randomness in the initialization values of the algorithm to cover wider searching space and then implementing a variable searching radius during the update phase by starting with a large radius which decreases gradually during the searching phase. The tuning of the parameters of the proposed NNFOPID controller is carried out by reducing the MS error of 0.000059, whereas the MSE of the nonlinear neural system (NNPID) is equivalent to 0.00079. The NNFOPID controller also decreased control signals that drive DDMR motors by approximately 45 percent compared to NNPID and thus reduced energy consumption in circular trajectories. The numerical simulations revealed the excellent performance of the designed NNFOPID controller by comparing its performance with that of nonlinear neural (NNPID) controllers on the trajectory tracking of the DDMR with different trajectories as study cases.

Description: We study herein the problem of the location of the information propagation source in social networks based on the network topology and a set of observations. We propose a concise and novel method to accurately locate the source of information using naming game theory. This study introduces the design of a dynamic deployment method that reduces considerably the number of observations and the time needed to locate the source. Moreover, it calculates the probability of each node that acts as a source based on the information provided by observations. This method can be potentially applied to various information propagation models. The simulation results reveal that the method is able to estimate the information source within a small number of hops from the true source.

Description: Are nearby places (e.g., cities) described by related words? In this article, we transfer this research question in the field of lexical encoding of geographic information onto the level of intertextuality. To this end, we explore Volunteered Geographic Information (VGI) to model texts addressing places at the level of cities or regions with the help of so-called topic networks. This is done to examine how language encodes and networks geographic information on the aboutness level of texts. Our hypothesis is that the networked thematizations of places are similar, regardless of their distances and the underlying communities of authors. To investigate this, we introduce Multiplex Topic Networks (MTN), which we automatically derive from Linguistic Multilayer Networks (LMN) as a novel model, especially of thematic networking in text corpora. Our study shows a Zipfian organization of the thematic universe in which geographical places (especially cities) are located in online communication. We interpret this finding in the context of cognitive maps, a notion which we extend by so-called thematic maps. According to our interpretation of this finding, the organization of thematic maps as part of cognitive maps results from a tendency of authors to generate shareable content that ensures the continued existence of the underlying media. We test our hypothesis by example of special wikis and extracts of Wikipedia. In this way, we come to the conclusion that geographical places, whether close to each other or not, are located in neighboring semantic places that span similar subnetworks in the topic universe.

Description: Evaluation of rock mass quality is of great significance to the design and construction of geotechnical engineering. In order to evaluate the quality of engineering rock mass scientifically and deal with the fuzzy information in the rock mass quality evaluation reasonably, a model for evaluation of rock mass quality based on unascertained measure and intuitionistic fuzzy sets (UM-IFS) was proposed. First, the membership of rock mass quality evaluation index was determined by the single index measure function of unascertained measure (UM) theory. Based on the intuitionistic fuzzy sets (IFS) theory, the single index measure evaluation matrix based on IFS (IFS-single index measure evaluation matrix) was obtained. By synthesizing various subjective and objective weighting methods, the range of index weight was determined, and the index weight vector based on IFS (IFS-index weight vector) was constructed. Then, the IFS-single index measure evaluation matrix and the IFS-index weight vector were used to calculate the scores of rock mass samples and evaluate rock mass quality. Finally, fuzzy analysis was performed on the weight of rock mass quality evaluation index. The established model for evaluation of rock mass quality was applied to the underground engineering rock mass in Guangzhou pumped storage power plant, and the evaluation results were compared with the other 4 effective models for rock mass quality evaluation. The results show that rock mass quality evaluation based on UM-IFS is consistent with the actual situation, and the fuzziness of evaluation index weight has no obvious correlation with its value.

Description: In this paper, a decision-making competition game model concerning governments, agricultural enterprises, and the public, all of which participate in the reduction of nitrogen emissions in the watersheds, is established based on bounded rationality. First, the stability conditions of the equilibrium points in the system are discussed, and the stable region of the Nash equilibrium is determined. Then, the bifurcation diagram, maximal Lyapunov exponent, strange attractor, and sensitive dependence on the initial conditions are shown through numerical simulations. The research shows that the adjustment speed of three players’ decisions may alter the stability of the Nash equilibrium point and lead to chaos in the system. Among these decisions, a government’s decision has the largest effect on the system. In addition, we find that some parameters will affect the stability of the system; when the parameters become beneficial for enterprises to reduce nitrogen emissions, the increase in the parameters can help control the chaotic market. Finally, the delay feedback control method is used to successfully control the chaos in the system and stabilize it at the Nash equilibrium point. The research of this paper is of great significance to the environmental governance decisions and nitrogen reduction management.

Description: With the rapid growth of E-commerce business, logistics service, especially the last-mile distribution, has become one bottleneck, which leads to the rise of coordination complexity of logistics service supply chain (LSSC). This research, based on Stackelberg’s game theory, studies the coordination of a new three-echelon LSSC consisting of an E-commerce mall, an express company, and a terminal distribution service provider and investigates the optimal solutions and profits for each party within the semicentralized and centralized LSSC alliances, respectively. To accomplish this, it firstly shows that the three-echelon LSSC can lead to global optimum under the centralized decision-making scenario and then deploys the contract coordination schemes, including revenue sharing, cost sharing, and unit delivery price contracts, in three semicentralized alliances, so as to achieve the same performance of the centralized decision-making scenario, in which each party in the LSSC can achieve the win-win situation. Finally, numerical examples are provided to illustrate the feasibility and the effectiveness of the proposed coordination strategies. This study enriches the coordination theory in the field of LSSC and provides managerial insights for decision makers in LSSC.

Description: In this paper, a stochastic chemostat model with variable yield and Contois growth function is investigated. The yield coefficient depends on the limiting nutrient, and the environmental noises are given by independent standard Brownian motions. First, the existence and uniqueness of global positive solution are proved. Second, by using stochastic Lyapunov function, Itô’s formula, and some important inequalities, stochastic characteristics for the stochastic model are studied, including the extinction of micro-organism, the strong persistence in the mean of micro-organism and, the existence of a unique stationary distribution of the stochastic model. Third, the necessary condition of an optimal stochastic control for the stochastic model is established by Hamiltonian function. In addition, some numerical simulations are carried out to illustrate the theoretical results and the influence of the variable yield on the microorganism.

Description: This paper examines approximation-based fixed-time adaptive tracking control for a class of uncertain nonlinear pure-feedback systems. Novel virtual and actual controllers are designed that resolve the meaninglessness of virtual and actual controllers at the origin and in the negative domain, and the sufficient condition for the system to have semiglobal fixed-time stability is also provided. Radial basis function neural networks are introduced to approximate unknown functions for solving the fixed-time control problem of unknown nonlinear pure-feedback systems, and the mean value theorem is used to solve the problem of nonaffine structure in nonlinear pure-feedback systems. The controllers designed in this paper ensure that all signals in the closed-loop system are semiglobally uniform and ultimately bounded in a fixed time. Two simulation results show that appropriate design parameters can limit the tracking error within a region of the origin in a fixed time.

Description: Video-based moving vehicle detection and tracking is an important prerequisite for vehicle counting under complex transportation environments. However, in the complex natural scene, the conventional optical flow method cannot accurately detect the boundary of the moving vehicle due to the generation of the shadow. In addition, traditional vehicle tracking algorithms are often occluded by trees, buildings, etc., and particle filters are also susceptible to particle degradation. To solve this problem, this paper proposes a kind of moving vehicle detection and tracking based on the optical flow method and immune particle filter algorithm. The proposed method firstly uses the optical flow method to roughly detect the moving vehicle and then uses the shadow detection algorithm based on the HSV color space to mark the shadow position after threshold segmentation and further combines the region-labeling algorithm to realize the shadow removal and accurately detect the moving vehicle. Improved affinity calculation and mutation function of antibody are proposed to make the particle filter algorithm have certain adaptivity and robustness to scene interference. Experiments are carried out in complex traffic scenes with shadow and occlusion interference. The experimental results show that the proposed algorithm can well solve the interference of shadow and occlusion and realize accurate detection and robust tracking of moving vehicles under complex transportation environments, which has the potentiality to be processed on a cloud computing platform.

Description: This study develops a novel dominance degree-based heterogeneous linguistic decision-making technique for identifying the most sustainable third-party reverse logistics providers (3PRLPs) under complex input environments. First, qualitative and uncertain inputs that arise from real-world 3PRLP evaluation process are successfully managed by using linguistic terms, hesitant fuzzy linguistic terms, and probabilistic linguistic term sets with different granularities. Then, the dominance degrees of each 3PRLP related to the other 3PRLPs are calculated based on a new ratio index-based probabilistic linguistic ranking method and the dominance matrix is constructed. Furthermore, to represent the closeness of each 3PRLP to the ideal solution, we propose a sort of measures including the dominance-based group utility measure, the dominance-based individual regret measure, and the dominance-based compromise measure. Accordingly, the selection results of 3PRLPs are obtained according to these measures. Finally, the developed method is applied to a case study from car manufacture industry, and the comparison analysis shows that the proposed method is reliable and stable for dealing with the problem of the 3PRLP selection. The main advantage of the developed method is that it cannot only well avoid the potential loss risks but also balance group utility scores and individual regret scores.

Description: Additive eigenvalue problem appears in ergodic optimal control or the homogenization of Hamilton–Jacobi equations. It has wide applications in several fields including computer science and then attracts the attention. In this paper, we consider the Poisson equations with the prescribed contact angle boundary condition and finally derive the existence and the uniqueness of the solution to the additive problem of the Laplace operator with the prescribed contact angle boundary condition.

Description: In this paper, an impulsive semidynamic system of the relationship between plankton and herbivore is established, and the Poincaré map method is used to extend the new properties of the model. We define the Poincaré map of the impulsive point series in phase concentration and analyze the characteristics. A comprehensive and detailed analysis of the periodic solution is performed. In addition, the numerical simulations illustrate the correctness of our arguments. The results show that plankton and herbivore can survive stably under effective control.

Description: Purpose. This paper aims to design the contract and present the profit distribution mechanism for CL platform, so as to realize the intelligent and automatic operation of the artificial intelligent- (AI-) based CL platform. Design/Methodology. A smart contract based on BT is designed for the AI-based CL platform. Profit distribution mechanism based on the Nash bargaining model for the CL platform is also put forward to coordinate different participators’ benefit relationship in CL. Findings. The AI-based CL platform and the proposed smart contract based on BT map the scenario which may be influenced by human factors and involve trust issues onto execution of codes. Practical Implications. The study will help CL practitioners in establishing effective profit mechanism and designing contracts on the platform, thus facilitating its sustainable operation. Originality/Value. The AI-based CL platform with BT smart contract can be totally free of human intervention, and hence, the problems of trust during CL platform’s operation are solved.

Description: Soil loss triggered by water erosion constitutes a major issue that causes several environmental and socioeconomic concerns. The Moroccan Western High Atlas is the most vulnerable area in the High Atlas Mountains, due to the existence of different forms of landslides, and evidences of erosion are widely observed. This study aims at estimating and quantifying the amount of soil loss as well as highlighting potential areas to erosion risk, using the Revised Universal Soil Loss Equation (RUSLE) combined with GIS and remote sensing. The RUSLE model provides a possibility of computing erosion susceptibility for each pixel on the basis of the controlling factors which are rainfall aggressivity, topography, vegetation cover, soil erodibility, and support practices. In this study, results show that the erosion rate varies between 0 and 227.67 t/ha/year, with an average annual soil loss of 40.38 t/ha/year, and the Beni Mohand River basin is subject to very high rates of erosion which can be irreversible since it exceeds the tolerable standard rate which is 1 t/ha/year. These findings will provide land use planners baseline for land use and risk management and will provide data within the Moroccan Western High Atlas Mountains.

Description: In this paper, we investigate the finite-time synchronization control for a class of nonlinear coupled multiweighted complex networks (NCMWCNs) with Markovian switching and time-varying delay analytically and quantitatively. The value of this study lies in four aspects: First, it designs the finite-time synchronization controller to make the NCMWCNs with Markovian switching and time-varying delay achieve global synchronization in finite time. Second, it derives two kinds of finite-time estimation approaches by analyzing the impact of the nonlinearity of nonlinear coupled function on synchronization dynamics and synchronization convergence time. Third, it presents the relationship between Markovian switching parameters and synchronization problems of subsystems and the overall system. Fourth, it provides some numerical examples to demonstrate the effectiveness of the theoretical results.

Description: A fractional-order tumor-immune interaction model with immunotherapy is proposed and examined. The existence, uniqueness, and nonnegativity of the solutions are proved. The local and global asymptotic stability of some equilibrium points are investigated. In particular, we present the sufficient conditions for asymptotic stability of tumor-free equilibrium. Finally, numerical simulations are conducted to illustrate the analytical results. The results indicate that the fractional order has a stabilization effect, and it may help to control the tumor extinction.

Description: Effective teamwork in an initially leaderless group requires a high level of collective leadership emerging from dynamic interactions among group members. Leader emergence is a crucial topic in collective leadership, yet it is challenging to investigate as the problem context is typically highly complex and dynamic. Here, we explore leadership emergence and leadership perception by means of computational simulations whose assumptions and parameters were informed by empirical research and human-subject experiments. Our agent-based model describes the process of group planning. Each agent is assigned with three key attributes: talkativeness, intelligence, and credibility. An agent can propose a suggestion to modify the group plan as a speaker or respond and evaluate others’ suggestions and leadership as a listener. Simulation results suggested that agents with high values of talkativeness, intelligence, and credibility tended to be perceived as leaders by their peers. Results also showed that talkativeness may be the most significant and instantaneous predictor for leader emergence of the three investigated attributes: talkativeness, intelligence, and credibility. In terms of group performance, smaller groups may outperform larger groups regarding their problem-solving ability in the beginning, but their performance tends to be of no significant difference in a long run. These results match the empirical literature and offer a mechanistic, operationalized description of the collective leadership processes.

Description: Potential damages to existing tunnels represent a major concern for constructing deep excavations in urban areas. The uncertainty of subsurface conditions and the nonlinear interactions between multiple agents (e.g., soils, excavation support structures, and tunnel structures) make the prediction of the response of tunnel induced by adjacent excavations a rather difficult and complex task. This paper proposes an initiative to solve this problem by using process-based modelling, where information generated from the interaction processes between soils, structures, and excavation activities is utilized to gradually reduce uncertainty related to soil properties and to learn the interaction patterns through machine learning techniques. To illustrate such a concept, this paper presents a simple process-based model consisting of artificial neural network (ANN) module, inverse modelling module, and mechanistic module. The ANN module is trained to learn and recognize the patterns of the complex interactions between excavation deformations, its geometries and support structures, and soil properties. The inverse modelling module enables a gradual reduction of uncertainty associated with soil characterizations by accumulating field observations during the construction processes. Based on the inputs provided by the former two modules, the mechanistic module computes the response of tunnel. The effectiveness of the proposed process-based model is evaluated against high-fidelity numerical simulations and field measurements. These evaluations suggest that the strategy of combining artificial intelligence techniques with information generated during interaction processes can represent a promising approach to solve complex engineering problems in conventional industries.

Description: Innovation subsidy is of great significance to promoting enterprise innovation development. However, in recent years, the frequent occurrence of R&D subsidy deception in China has greatly reduced effectiveness of innovation. From the perspective of the strategic choice motivation of the innovation subject (including the enterprises, research institutions, and local governments), this paper constructs a multiplayer stochastic evolutionary game model. The influence of each variable on the subject strategy adoption is analyzed by simulation. There are two important findings in this paper. First, the paper confirms that there is an optimal boundary for the high subsidies received by enterprises and academic institutions, and the “subsidy boundary” is solved through the model. Second, this paper analyzes the effectiveness of the regulation of each variable through simulation and provides management and policy implications.

Description: This paper concerns robust stabilization of nonlinear fractional order interconnected systems. Based on uncertain fractional order Takagi–Sugeno fuzzy model and the fractional order extension of lyapunov direct method, a parallel distributed compensate controller is designed to asymptotically stabilize the fractional order interconnected systems. Then, a sufficient condition is given in the format of linear matrix inequalities. Simulation example is given to validate the effectiveness of the approach.

Description: Since the conservative chaotic system (CCS) has no general attractors, conservative chaotic flows are more suitable for the chaos-based secure communication than the chaotic attractors. In this paper, two Hamiltonian conservative chaotic systems (HCCSs) are constructed based on the 4D Euler equations and a proposed construction method. These two new systems are investigated by equilibrium points, dynamical evolution map, Hamilton energy, and Casimir energy. They look similar, but it is found that one can be explained using Casimir power and another cannot be explained in terms of the mechanism of chaos. Furthermore, a pseudorandom signal generator is developed based on these proposed systems, which are tested based on NIST tests and implemented by using the field programmable gate array (FPGA) technique.

Description: Identifying important nodes in complex networks is essential in disease transmission control, network attack protection, and valuable information detection. Many evaluation indicators, such as degree centrality, betweenness centrality, and closeness centrality, have been proposed to identify important nodes. Some researchers assign different weight to different indicator and combine them together to obtain the final evaluation results. However, the weight is usually subjectively assigned based on the researcher’s experience, which may lead to inaccurate results. In this paper, we propose an entropy-based self-adaptive node importance evaluation method to evaluate node importance objectively. Firstly, based on complex network theory, we select four indicators to reflect different characteristics of the network structure. Secondly, we calculate the weights of different indicators based on information entropy theory. Finally, based on aforesaid steps, the node importance is obtained by weighted average method. The experimental results show that our method performs better than the existing methods.

Description: Visceral leishmaniasis (VL), known as kala-azar, is a serious parasitic disease. After malaria, VL is the second largest parasitic killer. This paper focuses on the VL transmission around sandflies, dogs, and people. Kashgar is located on the southwestern edge of Xinjiang, where kala-azar parasite infection occurs every year. According to the cases reported in the Kashgar Prefecture from 2004 to 2016, we proposed a dynamic model based on these three populations. The SEIR model was established for human population, the SI model was established for sandfly population, and the SI model was established for dog population. We fitted the model to cumulative cases from 2004 to 2016 for the epidemic in Kashgar and predicted that the cumulative incidence of kala-azar in Kashgar would continue to increase, but its growth rate would gradually slow down, which means that the number of cases would gradually decrease every year. We also estimated the basic reproduction number R0 = 1.76 (95% CI: 1.49–1.93). The sensitivity analysis shows that the mutual infection between sandfly and dog contributes the most to the basic reproduction number, while the transmission proportion of sandfly to the susceptible person and the mutual infection between sandfly and dog contribute the most to the number of leishmaniasis human cases. Therefore, according to the sensitivity analysis results, reducing the contact between sandflies and dogs is an effective way to reduce kala-azar.

Description: We show the effect of investor anxiety on momentum in the Chinese stock market. In this market dominated by retail investors, we examine the momentum profits in 900 types of daily testing periods. We find prevalent price reversals in the long formation and holding periods in the Chinese A-share market. Compared to Goyal and Wahal (2015), Wang and Xie (2010), and Kang et al. (2002) who found no momentum, our novel finding from a daily basis is that the A-share market presents price momentum within the short formation and holding periods. We first test the momentum profits under different strengths of anxiety in the A-share market. The stocks held by the least anxious investors elicit the strongest price momentum, whereas the stocks held by the most anxious investors encounter much weaker price momentum in the A-share market. According to our empirical outcomes, the A-share market overall exhibits higher anxiety and weaker momentum, whereas the B-share market embodies milder anxiety and stronger momentum. From the results of single market and cross-market comparisons, the intrinsic anxiety of retail investors is an essential factor stimulating the Chinese stock market to be prone to price reversals.

Description: In this paper, we introduce the definitions of d¯-shadowing property, d¯-shadowing property, topological ergodicity, and strong ergodicity of iterated function systems IFSf0,f1. Then, we show the following: 1 if IFSf0,f1 has the d¯-shadowing property (respectively, d¯-shadowing property), then ℱk has the d¯-shadowing property (respectively, d¯-shadowing property) for any k∈Z+; 2 if ℱk has the d¯-shadowing property (respectively, d¯-shadowing property) for some k∈Z+, then IFSf0,f1 has the d¯-shadowing property (respectively, d¯-shadowing property); 3 if IFSf0,f1 has the d¯-shadowing property or d¯-shadowing property, and f0 or f1 is surjective, then IFSf0,f1 is chain mixing; 4 let f0,f1 be open maps. For IFSf0,f1 with the d¯-shadowing property (respectively, d¯-shadowing property), if A⊂X is dense in X, and s is a minimal point of f0 or f1 for any s∈A, then IFSf0,f1 is strongly ergodic, and hence, ℱk is strongly ergodic; and 5 for IFSf0,f1 with the average shadowing property, if S⊂X is dense in X, and s is a quasi-weakly almost periodic point of f0 or f1 for any s∈S, then IFSf0,f1 is ergodic.

Description: The trajectory tracking task of a magnetic levitation system connected to a beam mechanism is solved by means of a nested saturation control with a feedforward term. The flatness property of the system allows to use the nested saturation control technique and the feedforward control to stabilize the output tracking error around the equilibrium. The closed-loop error dynamics is proven to be locally exponentially stable. Numerical simulations prove the effectiveness of the proposal.

Description: The analysis of network robustness tackles the problem of studying how a complex network behaves under adverse scenarios, such as failures or attacks. In particular, the analysis of interdependent networks’ robustness focuses on the specific case of the robustness of interacting networks and their emerging behaviors. This survey systematically reviews literature of frameworks that analyze the robustness of interdependent networks published between 2005 and 2017. This review shows that there exists a broad range of interdependent network models, robustness metrics, and studies that can be used to understand the behaviour of different systems under failure or attack. Regarding models, we found that there is a focus on systems where a node in one layer interacts with exactly one node at another layer. In studies, we observed a focus on the network percolation. While among the metrics, we observed a focus on measures that count network elements. Finally, for the networks used to test the frameworks, we found that the focus was on synthetic models, rather than analysis of real network systems. This review suggests opportunities in network research, such as the study of robustness on interdependent networks with multiple interactions and/or spatially embedded networks, and the use of interdependent network models in realistic network scenarios.

Description: Aiming at the chaotic characteristics of underwater acoustic signal, a prediction model of grey wolf-optimized kernel extreme learning machine (OKELM) based on MVMD is proposed in this paper for short-term prediction of underwater acoustic signals. To solve the problem of K value selection in variational mode decomposition, a new K value selection method MVMD is proposed from the perspective of mutual information, which avoids the blindness of variational mode decomposition (VMD) in the preset modal number. Based on the prediction model of kernel extreme learning machine (KELM), this paper uses grey wolf optimization (GWO) algorithm to optimize and select its regularization parameters and kernel parameters and proposes an optimized kernel extreme learning machine OKELM. To further improve the prediction performance of the model, combined with MVMD, an underwater acoustic signal prediction model based on MVMD-OKELM is established. MVMD-OKELM prediction model is applied to Mackey–Glass chaotic time series prediction and underwater acoustic signal prediction and is compared with ARIMA, EMD-OKELM, and other prediction models. The experimental results show that the proposed MVMD-OKELM prediction model has a higher prediction accuracy and can be effectively applied to the prediction of underwater acoustic signal series.

Description: Road networks serve as the backbone of cities, shaping urban structure as well as providing the critical function of transport for people, goods, and services. The design and management of resilient road infrastructure, therefore, is essential for building a sustainable city. Road networks grow and evolve over time, such that their topology shifts from an initially planned state to the one that emerges from self-organization and urban growth. In this work, we use a dual mapping approach to compare the topological features of road networks in 25 districts in Seoul, South Korea. By using average node degree as an indicator of the level of self-organization, we present that multiple topological variables including power-law exponent gradually shift as a network grows. By testing static error and attack tolerance of these networks, we also show that the gradual shift in topology also has an important implication in network resilience. We suggest a new method, inspired by Lorenz curve, for quantifying network vulnerability. This modified Lorenz curve enables calculating the relative impact of intensive attacks to random failures and shows that a more self-organized road network tends to become more vulnerable to selective attacks.

Description: Nowadays, scholar recommender systems often recommend academic papers based on users’ personalized retrieval demands. Typically, a recommender system analyzes the keywords typed by a user and then returns his or her preferred papers, in an efficient and economic manner. In practice, one paper often contains partial keywords that a user is interested in. Therefore, the recommender system needs to return the user a set of papers that collectively covers all the queried keywords. However, existing recommender systems only use the exact keyword matching technique for recommendation decisions, while neglecting the correlation relationships among different papers. As a consequence, it may output a set of papers from multiple disciplines that are different from the user’s real research field. In view of this shortcoming, we propose a keyword-driven and popularity-aware paper recommendation approach based on an undirected paper citation graph, named PRkeyword+pop. At last, we conduct large-scale experiments on the real-life Hep-Th dataset to further demonstrate the usefulness and feasibility of PRkeyword+pop. Experimental results prove the advantages of PRkeyword+pop in searching for a set of satisfactory papers compared with other competitive approaches.

Description: In capable person governing agricultural cooperatives, the internal governance is essential for cooperatives to achieve sustainable development. As an important mechanism of cooperative internal governance, relational governance is the focus of the current research in the field of cooperative internal governance. Based on the theory of organizational justice, relational embeddedness theory, and relational governance theory, this paper constructs the relationship between interactive justice, relational embeddedness, and governance performance based on fuzzy cognitive map and discusses the influence mechanism of interactive justice on relational governance performance. Taking 245 members of 18 agricultural cooperatives as samples, this paper makes an empirical test by using the machine learning method. Through the analysis of the data, we find that interactive justice has a significant positive impact on the governance performance. Relational embeddedness also has a significant positive impact on the governance performance. And relational embeddedness plays an intermediary role in the positive impact of interactive justice on governance performance. To some extent, the research results broaden the relationship between interactive justice and relational governance performance and provide useful reference for cooperatives to strengthen internal governance and achieve sustainable growth.

Description: Understanding cultivar responses to a new herbicide is crucial to determining appropriate herbicide use and management practices. Florpyrauxifen-benzyl is a new rice herbicide developed to control troublesome weeds in rice production. Little research has been conducted to characterize rice cultivar responses to florpyrauxifen-benzyl, and thus, a field experiment was conducted at the Pine Tree Research Station (PTRS) in 2017 and 2018 and at the Rice Research and Extension Center (RREC) in 2018 to determine rice cultivar tolerance to florpyrauxifen-benzyl as influenced by herbicide rate, the addition of imazethapyr, and rice growth stage. Another experiment was conducted in 2018 at PTRS and RREC to assess crop response when florpyrauxifen-benzyl at different rates is applied with and without malathion, a known cytochrome P450 inhibitor. Three cultivars were evaluated in both experiments: a long-grain variety “CL111,” a medium-grain variety “CL272,” and a long-grain hybrid “CLXL745.” Injury in the first experiment was higher when florpyrauxifen-benzyl was applied at 60 g ae ha−1 than at the labeled rate of 30 g ha−1, with the most injury being 10% when averaged over growth stage at the time of application. Generally, applications made at the 3-leaf growth stage resulted in the most injury; however, this injury was at most 14%. Additionally, there was no reduction in grain yield for any cultivar, indicating florpyrauxifen-benzyl can be used safely in conjunction with imazethapyr in imidazolinone-resistant rice. In the second experiment, there was no more than 10% injury and no reduction in grain yield, with the addition of malathion not causing an increase in rice injury. Results from these experiments indicate florpyrauxifen-benzyl can be mixed with imazethapyr and the addition of malathion will not lead to increased risk for injury to rice.

Description: Improved nitrogen use-efficient cultivars could be the most economically beneficial and environmentally friendly approach to reduce pollution associated with excessive N fertilization. The performance and genetic gain in grain yield and nitrogen use efficiency (NUE) of a historical set of 12 bread wheat cultivars released for a heat-stressed environment were investigated at four N levels (0 (N0), 43 (N43), 86 (N86), and 129 (N129) kg/ha) for two seasons. Averaged across seasons, increasing N level from N0 to N43, N86, and N129 resulted in yield increases ranging from 4−45%, 13–69%, and 34–87% at N43, N86, and N129, respectively. These yield increases were associated with increases in biomass (r = 0.86, P

Description: The study was carried out at Entoto Mountain and its surrounding area, about 10 km north of the center of Addis Ababa. The purpose of this study was to assess the floristic composition and regeneration status of woody species and recommend further conservation methods. Ten transect lines were laid from south-north at 1 km interval. Along these transect lines, 62 sample plots of 400 m2 (20 m × 20 m) were laid at 1 km interval. A total of 179 plant species belonging to 107 genera and 60 families were recorded. Asteraceae (30 species) was the most dominant family. Of 179 plant species, 73 were naturally regenerated woody species representing 48 genera and 34 families. Herbs account for the largest growth form (91, 50.84%), indicating the fact that disturbance favors herb species. For the analysis of vegetation diversity, woody species composition, and density, the study area was classified into five land-use types. Of the five land-use types, degraded land-use type had low species diversity and evenness (1.48 and 0.295), and it had a low density of economically and ecologically important larger trees. However, the density of seedlings and saplings showed the normal regeneration status for the herbs and shrubs. Therefore, responsible stakeholders should give high priority for the conservation of ecologically and economically important large trees using appropriate conservation methods in the study area.

Description: Binucleate Rhizoctonia (BNR) fungi are essential for the germination of vanilla seeds. Chemical control of the soil-borne pathogen might adversely affect BNR. The purpose of this study is to determine the effect of Nicotiana tabacum extract biopesticides and Fusarium oxysporum f.sp. vanillae (Fusarium) on vanilla plant nutrient content induced by BNR. Materials and Methods. The research design was completely randomized design with two factors and three replications. The first factor was biopesticide (dosage of 0, 10, 20, and 30 ml/seedling), and the second factor was the application of Fusarium. Results. The increase in the nitrogen, phosphorus, and potassium content of vanilla was affected by biopesticides and Fusarium inoculation. Fusarium inoculation has no significant effect on nitrogen and phosphorus levels but significantly affects potassium levels. The biopesticide dosage is significant for nitrogen, phosphorus, and potassium. The interaction of biopesticides with Fusarium inoculation did not significantly affect the parameters of nitrogen and phosphorus content, but significantly affected potassium content. Conclusion. The application of biopesticides and Fusarium inoculation after induction of BNR can increase nitrogen, phosphorus, and potassium content of vanilla plants.

Description: The goal of this research is to design an Artificial Intelligence controller for the active suspension system of vehicles. The Ring Probabilistic Logic Neural Network (RPLNN) architecture has been adopted to design the proposed controller, and the pavement condition has been modelled utilizing Gaussian white noise. The results show that the proposed RPLNN controller has an effective performance to reduce the unwanted stochastic effect of the road profile.

Description: In this paper, a new 4D memristor-based chaotic system is constructed by using a smooth flux-controlled memristor to replace a resistor in the realization circuit of a 3D chaotic system. Compared with general chaotic systems, the chaotic system can generate coexisting infinitely many attractors. The proposed chaotic system not only possesses heterogeneous multistability but also possesses homogenous multistability. When the parameters of system are fixed, the chaotic system only generates two kinds of chaotic attractors with different positions in a very large range of initial values. Different from other chaotic systems with continuous bifurcation diagrams, this system has discrete bifurcation diagrams when the initial values change. In addition, this paper reveals the relationship between the symmetry of coexisting attractors and the symmetry of initial values in the system. The dynamic behaviors of the new system are analyzed by equilibrium point and stability, bifurcation diagrams, Lyapunov exponents, and phase orbit diagrams. Finally, the chaotic attractors are captured through circuit simulation, which verifies numerical simulation.

Description: Conservative chaotic systems have potentials in engineering application because of their superiority over the dissipative systems in terms of ergodicity and integer dimension. In this paper, five-dimension Euler equations are constructed by integrating two of sub-Euler equations, which are contributory to the exploration of higher-dimensional systems. These Euler equations compose the conservative parts from their antisymmetric structure, which have been proved to be both Hamiltonian and Casimir energy conservative. Furthermore, a family of Hamiltonian conservative hyperchaotic systems are proposed by breaking the conservation of Casimir energy. The numerical analysis shows that the system displays some interesting behaviors, such as the coexistence of quasi-periodic, chaotic, and hyperchaotic behaviors. Adaptive synchronization method is used to realize the hyperchaos synchronization. Finally, the system passed the NIST tests successfully. Field programmable gate array (FPGA) platform is used to implement the proposed Hamiltonian conservative hyperchaos.

Description: Real-world complex systems always interact with each other, which causes these systems to collapse in an avalanche or cascading manner in the case of random failures or malicious attacks. The robustness of multilayer networks has attracted great interest, where the modeling and theoretical studies of which always rely on the concept of multilayer networks and percolation methods. A straightforward and tacit assumption is that the interdependence across network layers is strong, which means that a node will fail entirely with the removal of all links if one of its interdependent nodes in other network layers fails. However, this oversimplification cannot describe the general form of interactions across the network layers in a real-world multilayer system. In this paper, we reveal the nature of the avalanche disintegration of general multilayer networks with arbitrary interdependency strength across network layers. Specifically, we identify that the avalanche process of the whole system can essentially be decomposed into two microscopic cascading dynamics in terms of the propagation direction of the failures: depth penetration and scope extension. In the process of depth penetration, the failures propagate from layer to layer, where the greater the number of failed nodes is, the greater is the destructive power that will emerge in an interdependency group. In the process of scope extension, failures propagate with the removal of connections in each network layer. Under the synergy of the two processes, we find that the percolation transition of the system can be discontinuous or continuous with changes in the interdependency strength across network layers, which means that a sudden system-wide collapse can be avoided by controlling the interdependency strength across network layers. Our work not only reveals the microscopic mechanism of global collapse in multilayer infrastructure systems but also provides stimulating ideas on intervention programs and approaches for cascade failures.

Description: The purpose of this study was to examine the joint effect of overconfidence and fairness concern on supply chain decisions and design contracts to achieve a win-win situation within the supply chain. For this study, a centralized supply chain model was established without considering the retailers’ overconfidence and fairness concern. Furthermore, the retailers’ overconfidence and fairness concerns were introduced into the decentralized supply chain, while the Stackelberg game model between the manufacturer and the retailer was built. Furthermore, an innovative supply chain contract, i.e., buyback contract, with promotional cost sharing was designed to achieve supply chain coordination along with overconfidence and fairness concern. Finally, a numerical analysis was also conducted to analyze the effect of overconfidence, fairness concern, and the validity of the contract. The principal findings of the study include the positive correlation between retailers’ overconfidence and optimal order quantity, sales effort, expected utility, and profit. Although the order quantity and sales efforts were not affected by the fairness concern of the retailer, the contract achieved coordination with a win-win outcome when the level of overconfidence and fairness concern was moderate.

Description: Darrieus wind rotor is a vertical axis wind turbine that is a very promising kind of wind converters at remote and domestic locations that have soft and weak wind potential and speed, but from the quantitative comparison with horizontal axis wind turbines, this type of turbines has a weak performance. Additional researches are still needed to develop its efficiency to identify all the requirements of the generated power in low power demands. The aim of the current investigation is to analyze all the acting forces on the main parts of Darrieus rotor over the rotations as well as in maintenance and stationary conditions. Aerodynamic forces assessment will be executed for 3 different blade shapes (nonsymmetric and symmetric airfoils) like the airfoil section shapes of the Darrieus rotor blades. NACA 0021, LS413, and S1046 are selected as cross-sectional profile in this work. CFD simulations have been used in this work to get the different aerodynamic forces on the rotor blades of the Darrieus turbines. The present results indicated that the symmetric S1046 blade has higher forces during the rotation and stagnant (static) conditions. Moreover, the self-starting capability of NACA 0021 is better than S1046 due to low aerodynamic torsion on the S1046 blades.

Description: Production of pearl millet with yield improvement would have a direct impact on the drought-prone areas of Ethiopia since pearl millet is drought tolerant and early maturing with high water use efficiency. An experiment was conducted to study the performance of pearl millet under different technologies in 2013 and 2014 main cropping seasons at the main site of the research center, Aybra, with the objective of evaluating and identifying appropriate combinations of technologies that enhance the production of pearl millet in the study area. About fourteen integrated technologies were applied in a randomized complete block design with three replications. The analysis was done by using SAS software version 9.1, and means were separated through the Duncan multiple range test. Results of analysis of variance showed that yield-related traits of pearl millet were significantly influenced by the integration of technologies in the 2013 cropping season. According to the results, the maximum yield (3084 kg ha−1) was recorded with the application of the treatment combination of recommended fertilizer application + seed primming + tie ridging, while the minimum was recorded (919 kg ha−1) in the treatment combination of microdose application of fertilizer + primed seed + intercropping of pearl millet with mung bean. In the case of the 2014 cropping season, the highest grain yield (3687 kg ha−1) was recorded with the treatment combination of microdose fertilizer application + primed seed + tie ridging + intercropping of pearl millet with mung bean, whereas the lowest grain yield (2115 kg ha−1) was recorded in the treatment combination of no fertilizer application + primed seed + flat bed. Based on the results of the current investigation, it could be recommended that using technology integration of microdose, tied ridge, primed seed, and intercropping of pearl millet with mung bean is better to attain maximum yield in the study area and similar agroecologies.

Description: Land degradation is a global negative environmental process that causes the decline in the productivity of land resources’ capacity to perform their functions. Though soil and water conservation (SWC) technologies have been adopted in Geshy subcatchment, their effects on soil quality were limitedly studied. The study was conducted to evaluate the effects SWC measures on soil quality indicators in Geshy subcatchment, Gojeb River Catchment, Ethiopia. A total of 54 soil samples (two treatments–farmlands with and without SWC measures  three slope classes  three terrace positions  three replications) were collected at a depth of 20 cm. Statistical differences in soil quality indicators were analyzed using multivariate analysis of variance (ANOVA) following the general linear model procedure of SPSS Version 20.0 for Windows. Means that exhibited significant differences were compared using Tukey’s honest significance difference at 5% probability level. The studied soils are characterized by low bulk density, slightly acidic with clay and clay loam texture. The results revealed that farmlands with SWC measures had significantly improved soil physical (silt and clay fractions, and volumetric soil water content (VSWC)) and chemical (pH, SOC, TN, C : N ratio, and Av. phosphorus) quality indicators as compared with farmlands without SWC measures. The significantly higher VSWC, clay, SOC, TN, C : N ratio, and Av. P at the bottom slope classes and terrace positions could be attributed to the erosion reduction and deposition effects of SWC measures. Generally, the status of the studied soils is low in SOC contents, TN, C : N ratio, and Av. P (deficient). Thus, integral use of both physical and biological SWC options and agronomic interventions would have paramount importance in improving soil quality for better agricultural production and productivity.

Description: Autism spectrum disorder (ASD) is an early developmental disorder characterized by mutation of enculturation associated with attention deficit disorder in the visual perception of emotional expressions. An estimated one in more than 100 people has autism. Autism affects almost four times as many boys than girls. Data analysis and classification of ASD is still challenging due to unsolved issues arising from many severity levels and range of signs and symptoms. To understanding the functions which involved in autism, neuroscience technology analyzed responses to stimuli of autistic audio and video. The study focuses on analyzing the data set of adults and children with ASD using practical component analysis method. To satisfy this aim, the proposed method consists of three main stages including: (1) data set preparation, (2) Data analysis, and (3) Unsupervised Classification. The experimental results were performed to classify adults and children with ASD. The classification results in adults give a sensitivity of 78.6% and specificity of 82.47%, while the classification results in children give a sensitivity of 87.5% and specificity of 95.7%.

Description: Decomposition is a key flux of terrestrial carbon to the atmosphere. Therefore, gaining a better understanding of how plant litter decomposes in soil, and what governs this process, is vital for global climate models. The Tea Bag Index (TBI) was introduced by Keuskamp et al. (2013) as a novel method for measuring litter decomposition rate and stabilisation. The TBI uses two types of tea bags representing fast (green tea) and slow (rooibos tea) decomposition substrates as standardised litter bags. To date, the TBI method has been used in over 2000 locations across the globe. However, before now, there has been no information on how the composition of the tea leaves change during incubation. These data are crucial in determining the validity of the use of the TBI method globally, to ensure the tea leaves decompose in a way that is representative of so-called “native” litters. To provide chemical underpinning of the TBI method, a laboratory incubation of the tea bags was conducted with destructive sampling at 0, 7, 14, 21, 28, 35, 42, 49, 56, 63, 70, 77, 84, and 91 d. The incubated tea was analysed for total C and N. In addition, C was characterised as alkyl, O-alkyl, aromatic, or carbonyl C using solid-state 13C nuclear magnetic resonance spectroscopy with cross-polarization and magic angle spinning (CPMAS NMR). The results suggest that changes in carbon in both tea types are comparable to other litter studies, with a net decrease in total C and relative proportion of O-alkyl C fraction, which contains carbohydrates and cellulose. We conclude that the decomposition of tea leaves in the bags used in the TBI is representative of other litters.

Description: Wet snow accumulation on bridge cables and its shedding due to external phenomena such as rise in temperature, wind, and gravity is a serious threat to the safety of cars and pedestrians crossing the bridge. Commonly the accumulated snow on bridge cables is removed by external means such as mechanical removal or heat treatment which are expensive, time-consuming, and high-risk processes and are conducted based on little or no information available regarding the actual size and shape of the accumulated snow. In addition, cleaning of cables using the mechanical methods can potentially lead to erosion of cable materials when applied over years, resulting in enhanced surface roughness and potentially increased wet snow/ice accumulation during future precipitation events, and sometimes might require replacement of cable stays, which is an extremely costly and complicated task. Optimizing the number of mechanical cleaning procedures such as chain release through predicting the shape and thickness of the accumulated snow on the cable stays reduces the cost, time, and risk associated with the process. In this study, wet snow accumulation on torsionally rigid inclined cylinders of high-density polyethylene (HDPE) has been studied experimentally and numerically. A 2-D numerical model has been developed utilizing weather data to predict the thickness and the shape of the accumulated wet snow on inclined cylindrical surfaces. Outdoor experiments were also conducted to measure the density and thickness of accumulated snow, while monitoring the weather data real time. Overall, snow density was found to be linearly increasing with an increase in wind velocity, during snow precipitation. The maximum thickness and shape of the accumulated snow on cables obtained from the numerical model were found to be in good agreement with the outdoor experimental data. This work aims to provide a mean for prediction of snow accumulation on surfaces for optimizing the efficiency of the costly and high-risk snow removal procedures.

Description: In this paper, we study the existence and uniqueness of solutions to implicit the coupled fractional differential system with the Katugampola–Caputo fractional derivative. Different fixed-point theorems are used to acquire the required results. Moreover, we derive some sufficient conditions to guarantee that the solutions to our considered system are Hyers–Ulam stable. We also provided an example that explains our results.

Description: This paper introduces an image interpolation method that provides performance superior to that of the state-of-the-art algorithms. The simple linear method, if used for interpolation, provides interpolation at the cost of blurring, jagging, and other artifacts; however, applying complex methods provides better interpolation results, but sometimes they fail to preserve some specific edge patterns or results in oversmoothing of the edges due to postprocessing of the initial interpolation process. The proposed method uses a new gradient-based approach that makes an intelligent decision based on the edge direction using the edge map and gradient map of an image and interpolates unknown pixels in the predicted direction using known intensity pixels. The input image is subjected to the efficient hysteresis thresholding-based edge map calculation, followed by interpolation of low-resolution edge map to obtain a high-resolution edge map. Edge map interpolation is followed by classification of unknown pixels into obvious edges, uniform regions, and transitional edges using the decision support system. Coefficient-based interpolation that involves gradient coefficient and distance coefficient is applied to obvious edge pixels in the high-resolution image, whereas transitional edges in the neighborhood of an obvious edge are interpolated in the same direction to provide uniform interpolation. Simple line averaging is applied to pixels that are not detected as an edge to decrease the complexity of the proposed method. Applying line averaging to smooth pixels helps to control the complexity of the algorithm, whereas applying gradient-based interpolation preserves edges and hence results in better performance at reasonable complexity.

Description: This paper presents an active fault-tolerant method to mitigate sensor failures in multimotor synchronous control. First, inspired by the construction of the coupling matrix in complex network synchronous output, a consistent matrix is designed based on structural redundancy in synchronous control. This consistent matrix has two advantages: one is that it can reflect different sensor output similarities and the other one is that it can detect, locate, and estimate the sensor fault. Then, the fault information is integrated into the design of tolerance control with an improved mean feedback mechanism. The proposed method is suitable for both single and multiple fault situations, and its effectiveness is finally verified by both MATLAB simulation and the ABB semiphysical experimental platform.

Description: The objective of the present study was to determine physical and chemical parameters that determine grain and flour quality of wheat grown in Mexico’s highlands (Toluca, Estado de Mexico) as a response of nitrogen fertilization and growing season. Experiments were carried out in winter-spring 2010 (irrigation) and summer-autumn 2011 (rainfed) season cycles. Nine wheat cultivars were tested under four levels of nitrogen fertilization (N00, N100, N200, and N300 kg N·ha−1) with a population density of 336 seeds m−2. For each growing season and N rate, three replications were performed for each experiment under a randomized complete block design. Best quality indexes were obtained in the winter-spring cycle as a result of genetic variability. Nitrogen availability modified significantly some quality parameters (grain and flour protein, test weight, and hardness) obtaining the highest values at a rate of 100 kg N·ha−1. On the other hand, volume of sedimentation showed positive effects only at a rate of 300 kg N·ha−1. This rate showed positive effects on grain and flour protein, sedimentation volume, and hardness during the summer-autumn cycle. Eneida F94, Tollocan F2005, and Urbina S2007 cultivars presented the highest grain and flour protein content of tested varieties. Finally, Eneida F94 and Tollocan F2005 presented the highest test weight and flour percentage.

Description: In this paper, we investigate the impact of a periodically evolving domain on the dynamics of the diffusive West Nile virus. A reaction-diffusion model on a periodically and isotropically evolving domain which describes the transmission of the West Nile virus is proposed. In addition to the classical basic reproduction number, the spatial-temporal basic reproduction number depending on the periodic evolution rate is introduced and its properties are discussed. Under some conditions, we explore the long-time behavior of the virus. The virus will go extinct if the spatial-temporal basic reproduction number is less than or equal to one. The persistence of the virus happens if the spatial-temporal basic reproduction number is greater than one. We consider special case when the periodic evolution rate is equivalent to one to better understand the impact of the periodic evolution rate on the persistence or extinction of the virus. Some numerical simulations are performed in order to illustrate our analytical results. Our theoretical analysis and numerical simulations show that the periodic change of the habitat range plays an important role in the West Nile virus transmission, in particular, the increase of periodic evolution rate has positive effect on the spread of the virus.

Description: To analyze whether information sharing in the institutional investors plays the role of a market stabilizer or risk booster, this paper constructs the institutional investor information network employing the common holding stocks of the mutual funds as links. The information linkages between two funds with large positions in the same stock are hypothesized to be connected to each other. Then, we use the information sharing efficiency in the fund networks to study the effects of information transmission on stock market extreme risk and financial systemic risk. Especially, the speed of information diffusion in the network is characterized by the topology structures based on social network theory. Empirical research studies find that the Chinese fund information network exhibits small-world characteristics, which reflects rapid speed of information diffusion. Seen from the idiosyncratic risk of volatility, information sharing of institutional investors can improve the behavior consistency of fund managers, thus increasing the stock volatility via herd effects. Besides, it can be concluded that institutional investor information sharing can reduce the extreme risk by promoting the comprehensiveness of information flow and the market pricing efficiency of stocks, thereby reducing the degree of financial systemic risk. The obtained conclusions provide suggestions for decision-making of institutional investors. It can help the regulators to pay attention to the herd effects so as to control systemic risk.

Description: This paper studies the multiconsensus problem of multiagent networks based on sampled data information via the pulse-modulated intermittent control (PMIC) which is a general control framework unifying impulsive control, intermittent control, and sampling control. Two kinds of multiconsensus, including stationary multiconsensus and dynamic multiconsensus of multiagent networks, are taken into consideration in such control framework. Based on the eigenvalue analysis and algebraic graph theory, some necessary and sufficient conditions on the feedback gains and the control period are established to ensure the multiconsensus. Finally, several simulation results are included to show the theoretical results.

Description: The perforation plates and vessel-ray pitting of tropical hardwoods are typical features that make it possible to mark species within a botanical family. This study aims to bring out a consistent and robust framework for a clear distinction through anatomical features among various Ekop woods based on usual nomenclature on trade. Perforations plates and vessel-ray pitting are determining components for the classification of the species. Indeed, several species exploited under the trade name Ekop because of their grain, color, and wooden decoration patterns do not belong to the same taxonomic class. With the natural structure of cells and their intervessel pits observed in xylem and phloem, it appears that the perforation plates and the vessel-ray pitting are decisive components for the classification of Ekop species. Forty-three wood specimens of Ekop were collected from forests in Ebolowa, Mbalmayo, and Abong Mbang. In addition, 155 microscopic sections of Ekop slides with at least 3 representatives of identified species were observed. Thus, macroscopic observations through a hand magnifying glass were performed on wood carrots. Then, the microscopic sections of slides in the first 63 features of the International Association of Wood Anatomists list were analyzed. Correlations were observed between vessels elements and other main features through component analysis. Four groups of Ekop were differentiated by gathering in each genus a matrix of similar features across their vessels groupings, perforation plates, and vessel-ray pittings. A tabular key was used to further define the identity of the Ekop species. This study makes it possible to recognize Ekop wood beyond the dendrological aspects of vegetative and reproductive organs. Finally, a few typical features used for a precise demarcation were identified, for a taxonomic classification within the Ekop group.

Description: Two nonidentical dimension Markovian jumping complex networks with stochastic perturbations are taken as objects. The network models under two conditions including single weight and double weights are established, respectively, to study the problem of synchronization and identification. A finite-time projection lag synchronization method is proposed and the unknown parameters of the network are identified. First of all, based on Itô’s formula and the stability theory of finite-time, a credible finite-time adaptive controller is presented to guarantee the synchronization of two nonidentical dimension Markovian jumping complex networks with stochastic perturbations under both conditions. Meanwhile, in order to identify the uncertain parameters of the network with stochastic perturbations accurately, some corresponding sufficient conditions are given. Finally, numerical simulations under two working conditions are given to demonstrate the effectiveness and feasibility of the main theory result.

Description: The stability of grazing bifurcation is lost in three ways through the local analysis of the near-grazing dynamics using the classical concept of discontinuity mappings in the two-degree-of-freedom vibroimpact system with symmetrical constraints. For this instability problem, a control strategy for the stability of grazing bifurcation is presented by controlling the persistence of local attractors near the grazing trajectory in this vibroimpact system with symmetrical constraints. Discrete-in-time feedback controllers designed on two Poincare sections are employed to retain the existence of an attractor near the grazing trajectory. The implementation relies on the stability criterion under which a local attractor persists near a grazing trajectory. Based on the stability criterion, the control region of the two parameters is obtained and the control strategy for the persistence of near-grazing attractors is designed accordingly. Especially, the chaos near codimension-two grazing bifurcation points was controlled by the control strategy. In the end, the results of numerical simulation are used to verify the feasibility of the control method.

Description: In this paper, we study the exact solitary wave solutions and periodic wave solutions of the S-S equation and give the relationships between solutions and the Hamilton energy of their amplitudes. First, on the basis of the theory of dynamical system, we make qualitative analysis on the amplitudes of solutions. Then, by using undetermined hypothesis method, the first integral method, and the appropriate transformation, two bell-shaped solitary wave solutions and six exact periodic wave solutions are obtained. Furthermore, we discuss the evolutionary relationships between these solutions and find that the appearance of these solutions for the S-S equation is essentially determined by the value which the Hamilton energy takes. Finally, we give some diagrams which show the changing process from the periodic wave solutions to the solitary wave solutions when the Hamilton energy changes.

Description: In this article, the diffraction of the electromagnetic wave by the building with two rooms is considered. The rooms have doors and windows with lossy dielectric walls. The electromagnetic properties of the building as an opened coupled resonator system are investigated at different source locations and several frequencies including 5G band. The problem is solved by using the Method of Auxiliary Sources. The near electric field distributions are calculated and analyzed.

Description: In this paper, we investigate single-strain and multistrain viral infection models with general incidence function and density-dependent diffusion subject to the homogeneous Neumann boundary conditions. For the single-strain viral infection model, by using the linearization method and constructing appropriate Lyapunov functionals, we obtain that the global threshold dynamics of the model is determined by the reproductive numbers for viral infection ℛ0. For the multistrain viral infection model, we have discussed the competitive exclusion problem. If the reproduction number ℛi for strain i is maximal and larger than one, the steady state Ei corresponding to the strain i is globally stable. Thus, competitive exclusion happens and all other strains die out except strain i. Meanwhile, we can prove that the single-strain and multistrain viral infection models are well posed. Furthermore, numerical simulations are also carried out to illustrate the theoretical results, which is seldom seen in the relevant known literatures.

Description: Due to the limited band width and congestion of communication channels in the wireless vehicle-to-vehicle (V2V) communication, time delay inevitably arises and dramatically leads to the disturbances for the automated vehicular platoon. This paper focuses on computing the exact time delay stability margin. In this study, we treat this problem as a stability issue of a consensus system with time delay, where each vehicle in the platoon is recognized as a node, and the interconnected information flow is represented as a graph. Then, the distributed controller is designed by combining the states of the vehicle itself and its neighbouring vehicles. Furthermore, the stability of the entire platoon is analysed according to the characteristic equation of the closed-loop system, and a necessary and sufficient condition for the exact time delay stability margin is obtained. Especially, for the automated vehicular platoon with undirected topology, it is revealed that exact time delay stability margin is determined by the largest eigenvalue of the augmented Laplacian matrix. Furthermore, a rapid method for finding exact time delay stability margin is proposed. Finally, numerical simulations demonstrate that this work generates exact and satisfactory time delay stability margin for the automated vehicular platoon.

Description: This paper investigates the hybrid-driven mechanism problem for Markov jump system, where both channel quantization (BCQ) and network-induced delay based on uncertain network are considered. Firstly, comparing with the traditional event-triggered scheme, a hybrid-driven mechanism is employed in networked control systems (NCSs) for the finite capacity of communication bandwidth resources and system performance in equilibrium. Then, the quantization technology is applied in the communication channel from sensor-to-controller and controller-to-actuator. The application of BCQ is for further investigation that mitigate data packet transmission rate. Thirdly, Markov jump system is modeled for the hybrid-driven mechanism and network-induced delay. By constructing the Lyapunov–Krasovskii function, a sufficient condition is derived as the stability criterion, and the controller is designed in which the nonlinear term is rewritten for simplifying the calculation. Finally, two simulation examples are provided to demonstrate the effectiveness of the proposed approach.

Description: In this paper, we focus on the interaction solutions of a (2 + 1)-dimensional Vakhnenko equation. By using Hirota’s transformation combined with the three-wave method and with symbolic computation, some interaction solutions which include interaction solutions between exponential and trigonometric functions and interaction solutions between exponential and trigonometric and hyperbolic functions are presented.

Description: With the establishment of China’s national air quality monitoring network, large amounts of monitoring data are available for different kinds of users. How to process and use this big data is a tough problem for users: most users have limited computing power, and new data are collected at every moment. Cloud computing may be an efficient and low-cost way to solve this problem. This paper investigates a problem of a complex system: the impact of PM2.5 on hospitalization for respiratory diseases. A change-point detection method based on grey relation analysis was used to solve this problem. Daily air pollution monitoring data and patient data were used in this study. Our results showed that (1) PM2.5 pollution showed a positive correlation on hospital admission for respiratory disease; (2) most patients went to hospital 2 days after PM2.5 pollution events; and (3) male, children, and old people were significantly affected by PM2.5 pollution. Our study is of great significance to help the government formulate suitable policies to reduce the damage caused by PM2.5 pollution and help hospitals allocate medical resources efficiently.

Description: In the field of ophthalmology, diabetic retinopathy (DR) is a major cause of blindness. DR is based on retinal lesions including exudate. Exudates have been found to be one of the signs and serious DR anomalies, so the proper detection of these lesions and the treatment should be done immediately to prevent loss of vision. In this paper, pretrained convolutional neural network- (CNN-) based framework has been proposed for the detection of exudate. Recently, deep CNNs were individually applied to solve the specific problems. But, pretrained CNN models with transfer learning can utilize the previous knowledge to solve the other related problems. In the proposed approach, initially data preprocessing is performed for standardization of exudate patches. Furthermore, region of interest (ROI) localization is used to localize the features of exudates, and then transfer learning is performed for feature extraction using pretrained CNN models (Inception-v3, Residual Network-50, and Visual Geometry Group Network-19). Moreover, the fused features from fully connected (FC) layers are fed into the softmax classifier for exudate classification. The performance of proposed framework has been analyzed using two well-known publicly available databases such as e-Ophtha and DIARETDB1. The experimental results demonstrate that the proposed pretrained CNN-based framework outperforms the existing techniques for the detection of exudates.

Description: The equipment scheduling and propagation characteristics of vibration wave from vibratory roller ⟶ filling material nonlinear systems with multistability are the core problems of subgrade intelligent construction technology, and the logistics scheduling of the equipment is directly related to the construction efficiency. Aiming at the shortages, one typical subgrade located at the Gu’an station of Beijing-Xiong’an city railway is selected to research and finish the field tests; some findings are shown as follows: first, some valuable suggestions about the logistics scheduling of intelligent equipment are proposed, which can break the barriers between the organizations and improve construction efficiency; second, when the vibration wave propagates from the vibratory roller ⟶ surface of filling material ⟶ different buried depths of filling material, the peak acceleration of vibration wave gradually decreases and is hyperbolic distribution approximately. At the same time, the sensitive of attenuation is shown as follows: Z0.9), and the concrete functional relationship among different amplitudes of harmonics can be summarized as y = Ae−BX; fourth, the vibration energy is mainly concentrated near 10–30 Hz in the vibratory roller, but when the vibration wave propagates from vibratory roller⟶filling material, the vibration energy gradually decreases with the increase in depth, and the marginal spectrum gradually changes from one peak to two peaks, that is, 30–50 Hz and 50–100 Hz; fifth, the vibration energy in the vibrational wheel is distributed averagely in the compaction process, and the effective compaction time is two seconds, which will be helpful for revealing the propagation characteristics of vibration wave, optimizing the compaction quality control models and providing some support for the development of intelligent compaction theory of railway subgrade.

Description: Wireless sensor networks are widely used in many fields, such as medical and health care, military monitoring, target tracking, and people’s life, because of their advantages of convenient deployment, low cost, and good concealment. However, due to the low battery capacity of sensor nodes and environmental changes, the energy consumption of nodes is serious and the accuracy of data collection is low. In the data collection method of multiple random paths, due to the uneven geographical distribution between nodes and the influence of the environment, it is easy to cause the communication between nodes to be blocked and the construction of random paths to fail. This paper proposes an efficient data collection algorithm for this problem. The algorithm is improved on the basis of the random node selection algorithm. This method can effectively avoid the failure of random path node selection and improve the node selection of random path in wireless sensor networks. Then, the sensor network in the dynamic environment is analyzed based on the static environment. An efficient data collection algorithm based on the position prediction of extreme learning machines is proposed. This method uses extreme learning machine methods to perform trajectory prediction for nodes in a dynamic environment.

Description: In order to make the performance evaluation of community detection algorithms more accurate and deepen our analysis of community structures and functional characteristics of real-life networks, a new benchmark constructing method is designed from the perspective of directly rewiring edges in a real-life network instead of building a model. Based on the method, two kinds of novel benchmarks with special functions are proposed. The first kind can accurately approximate the microscale and mesoscale structural characteristics of the original network, providing ideal proxies for real-life networks and helping to realize performance analysis of community detection algorithms when a real network varies characteristics at multiple scales. The second kind is able to independently vary the community intensity in each generated benchmark and make the robustness evaluation of community detection algorithms more accurate. Experimental results prove the effectiveness and superiority of our proposed method. It enables more real-life networks to be used to construct benchmarks and helps to deepen our analysis of community structures and functional characteristics of real-life networks.

Description: In order to reduce the damage of apple harvesting robot to fruits and achieve compliant picking, an adaptive variable parameter impedance control method for apple harvesting robot compliant picking is proposed in this paper. Firstly, the Burgers viscoelastic model is used to characterize the rheological properties of apples and study the variation of mechanical properties of apple grasping at different speeds. Then, a force-based impedance control system is designed. On this basis, aiming at the influence of impedance controller parameters on contact force, three impedance parameters self-tuning functions are constructed to complete the design of an improved force-based impedance control system based on the hyperbolic secant function. The simulation and experimental results show that the proposed control makes the desired force smoother, and its overshoot is about 2.3%. The response speed is faster, and the adjustment time of contact force is shorter of about 0.48 s. The contact force overshoot is about 2%, which is 37.5% less than that of the traditional force-based impedance control. This research improves the control performance for apple harvesting robot compliant picking.

Description: Laplacian Biogeography-Based Optimization (LxBBO) is a BBO variant which improves BBO’s performance largely. When it solves some complex problems, however, it has some drawbacks such as poor performance, weak operability, and high complexity, so an improved LxBBO (ILxBBO) is proposed. First, a two-global-best guiding operator is created for guiding the worst habitat mainly to enhance the exploitation of LxBBO. Second, a dynamic two-differential perturbing operator is proposed for the first two best habitats’ updating to improve the global search ability in the early search phase and the local one in the late search one, respectively. Third, an improved Laplace migration operator is formulated for other habitats’ updating to improve the search ability and the operability. Finally, some measures such as example learning, mutation operation removing, and greedy selection are adopted mostly to reduce the computation complexity of LxBBO. A lot of experimental results on the complex functions from the CEC-2013 test set show ILxBBO obtains better performance than LxBBO and quite a few state-of-the-art algorithms do. Also, the results on Quadratic Assignment Problems (QAPs) show that ILxBBO is more competitive compared with LxBBO, Improved Particle Swarm Optimization (IPSO), and Improved Firefly Algorithm (IFA).

Description: Oscillatory behavior is absolutely necessary for the normal functioning of various organisms and their performance. Therefore, it is necessary to protect the oscillatory behavior in an aging network which consists of oscillatory and nonoscillatory nodes. In this work, we investigate numerically and theoretically the effect of time delay on oscillatory behaviors in a network which includes active and inactive Stuart–Landau oscillators. Interestingly, we find a chimera oscillatory state where a part of oscillators is a steady state while other oscillators preserve oscillatory motion; such dynamical behaviors are considered generally to be impossible for globally coupled systems when the coupling strength is sufficiently large. Furthermore, our results reveal that time delay can effectively inhibit aging transition and recover the oscillatory behavior from the aging network.