ALBERT

Description: The spectrophotometric-chemometric analysis of levodopa and carbidopa that are used for Parkinson’s disease was analyzed without any prior reservation. Parkinson’s drugs in the urine sample of a healthy person (never used drugs in his life) were analyzed at the same time spectrophotometrically. The chemometric methods used were partial least squares regression (PLS) and principal component regression (PCR). PLS and PCR were successfully applied as chemometric determination of levodopa and carbidopa in human urine samples. A concentration set including binary mixtures of levodopa and carbidopa in 15 different combinations was randomly prepared in acetate buffer (pH 3.5).). UV spectrophotometry is a relatively inexpensive, reliable, and less time-consuming method. Minitab program was used for absorbance and concentration values. The normalization values for each active substance were good (r2〉0.9997). Additionally, experimental data were validated statistically. The results of the analyses of the results revealed high recoveries and low standard deviations. Hence, the results encouraged us to apply the method to drug analysis. The proposed methods are highly sensitive and precise, and therefore they were implemented for the determination of the active substances in the urine sample of a healthy person in triumph.

Description: This paper developed a principal component analysis (PCA)-integrated algorithm for feature identification in manufacturing; this algorithm is based on an adaptive PCA-based scheme for identifying image features in vision-based inspection. PCA is a commonly used statistical method for pattern recognition tasks, but an effective PCA-based approach for identifying suitable image features in manufacturing has yet to be developed. Unsuitable image features tend to yield poor results when used in conventional visual inspections. Furthermore, research has revealed that the use of unsuitable or redundant features might influence the performance of object detection. To address these problems, the adaptive PCA-based algorithm developed in this study entails the identification of suitable image features using a support vector machine (SVM) model for inspecting of various object images; this approach can be used for solving the inherent problem of detection that occurs when the extraction contains challenging image features in manufacturing processes. The results of experiments indicated that the proposed algorithm can successfully be used to adaptively select appropriate image features. The algorithm combines image feature extraction and PCA/SVM classification to detect patterns in manufacturing. The algorithm was determined to achieve high-performance detection and to outperform the existing methods.

Description: Ferulic acid (FA), an important phenolic acid, is widely distributed in higher plants and presents many pharmacological effects. Therefore, sensitive determination of FA in complex matrix is necessary. Molecularly imprinted polymers-coated CdTe quantum dots (CdTe-QDs@MIPs) exhibited incomparable advantages because of their combination of excellent selectivity of MIPs and high sensitivity of QDs. Here, a fluorescent probe based on CdTe-QDs@MIPs was successfully fabricated for selective and sensitive determination of FA. MIPs shell was obtained by the reverse microemulsion method using FA, 3-(aminopropyl) triethoxysilane (APTES), and tetraethyl orthosilicate (TEOS), as template, functional monomer, and crosslinker. In optimal conditions, the fluorescence CdTe-QDs@MIPs sensor exhibited fast response (within only 3 min), high sensitivity (limit of detection, LOD at 0.85 μg/l), excellent linear ranges (2–100 μg/l) with a correlation coefficient of 0.9996, and distinguished selectivity for FA. Satisfactory recoveries from 91.8% to 110.3% were achieved with precisions below 6.6% for FA analysis in real pineapple juice and apple juice by developed CdTe-QDs@MIPs. The fluorescence results coincided well with those obtained by high-performance liquid chromatography (HPLC). It could be concluded that the resultant CdTe-QDs@MIPs offered a new way for rapid and sensitive analysis of FA in the complex matrix.

Description: Telescoping path optimization (TPO) of single-cylinder pin-type multisection boom (SPMB) is a practical engineering problem that is valuable to investigate. This article studies the TPO problem and finds the key of TPO is to obtain the maximum retraction backmost combination. A mathematic model on the basis of the quadratic penalty function of a Hopfield neural network (HNN) is constructed. Two strategies are presented to improve the performance of TPO model: one is proportional integral derivative (PID) strategy that adaptively adjusts the parameter λ of the constrained term and the parameter of the optimization objective term by controlling the value of constraint violation and the other is efficiency factor strategy that an efficiency factor is introduced in model for prioritizing the constrained term over the objective term. Data test shows that compared with the path of boom length changing before optimization, both the number of sections that need to be moved and the total travels of cylinder can be reduced by 10%-30% after optimization. Both the PID strategy and the efficiency factor strategy achieve good optimization effects. The efficiency factor strategy is excellent at moderating the conflicts between the constrained term and the objective term; thus the generations of the valid and the optimal solutions get well improved.

Description: A belt drive and a chain drive are the main types of flexible power transmission. In the traditional belt and chain drive design process, engineers need to do a lot of rework to get a design. To solve this problem, taking the Shell Eco-Marathon vehicle as an example, the traditional design and optimization design of the transmission system are carried out. In the optimization design, component optimization and overall optimization design model of the belt and chain drive are first established. Second, the charts in the design manual are converted into formulas by using MATLAB. Finally, an optimization design model is established in Microsoft Excel, and the Excel Solver tool is used to find the optimal design result. The design method proposed in this paper can effectively determine the optimal design of transmission system and provides a new method for the processing of such problems.

Description: This paper proposes a superresolution two-dimensional (2D) direction of arrival (DOA) estimation algorithm for a rectangular array based on the optimization of the atomic norm and a series of relaxation formulations. The atomic norm of the array response describes the minimum number of sources, which is derived from the atomic norm minimization (ANM) problem. However, the resolution is restricted and high computational complexity is incurred by using ANM for 2D angle estimation. Although an improved algorithm named decoupled atomic norm minimization (DAM) has a reduced computational burden, the resolution is still relatively low in terms of angle estimation. To overcome these limitations, we propose the direct minimization of the atomic norm, which is demonstrated to be equivalent to a decoupled rank optimization problem in the positive semidefinite (PSD) form. Our goal is to solve this rank minimization problem and recover two decoupled Toeplitz matrices in which the azimuth-elevation angles of interest are encoded. Since rank minimization is an NP-hard problem, a novel sparse surrogate function is further proposed to effectively approximate the two decoupled rank functions. Then, the new optimization problem obtained through the above relaxation can be implemented via the majorization-minimization (MM) method. The proposed algorithm offers greatly improved resolution while maintaining the same computational complexity as the DAM algorithm. Moreover, it is possible to use a single snapshot for angle estimation without prior information on the number of sources, and the algorithm is robust to noise due to its iterative nature. In addition, the proposed surrogate function can achieve local convergence faster than existing functions.

Description: In this paper, we enrich and develop power-type Aczél-Vasić-Pečarić’s inequalities. First of all, we give some new versions of theorems and corollaries about Aczél-Vasić-Pečarić’s inequalities by quoting some lemmas. Moreover, in combination with Hölder’s inequality, we give some applications of the new version of Aczél-Vasić-Pečarić’s inequality and give its proof process.

Description: In this paper, we firstly discuss the existence of the least energy sign-changing solutions for a class of p-Kirchhoff-type problems with a -linear growth nonlinearity. The quantitative deformation lemma and Non-Nehari manifold method are used in the paper to prove the main results. Remarkably, we use a new method to verify that . The main results of our paper are the existence of the least energy sign-changing solution and its corresponding energy doubling property. Moreover, we also give the convergence property of the least energy sign-changing solution as the parameter .

Description: The study area is located in the extreme southwest of the Ougnat Mountains in the eastern Anti-Atlas, which is part of the distorted northern margin of the West African craton. It has Late Neoproterozoic to terminal, Paleozoic and Quaternary lands. In order to obtain a better recognition of the different structural contacts and to define the alignment of mineralized veins in barite and galena at the level of the study area, we used the technique of electrical tomography. The resulting response, in the form of electrical imaging, informed us in detail about the different zones of heterogeneity existing in the prospected soil. In induced polarization, the pseudosections obtained were able to locate the passages of the zones of anomalies encountered and thus confirm their alignments defined by the electrical resistivity measurement results.

Description: Pearl millet is a dominant staple cereal crop for smallholder farmers in Senegal. However, the crop is constrained by various nonbiotic and biotic stresses such as downy mildew disease. To assess the prevalence of this disease in Senegal, a field survey was conducted during the rainy season of 2017 across eight main pearl millet production regions following latitudinal gradient with different climatic conditions. Results showed that downy mildew prevalence was higher in Kaolack (incidence = 68.19%), Kaffrine (incidence = 77.19%), Tambacounda (incidence = 97.03%), Sedhiou (incidence = 82.78%), and Kolda (incidence = 98.01%) than Thies (incidence = 28.21%), Diourbel (incidence = 24.46%), and Fatick (incidence = 37.75%) regions. The field survey revealed an incidence as high as 98% and 28% of infected area in surveyed fields. Significant correlations between geographic coordinates, disease incidence, and infected areas were also observed. This study provided information that could help to understand the prevalence of downy mildew in pearl millet in Senegal.

Description: For the problem of joint angle and range estimation with frequency diverse array (FDA), MIMO radar, staggered frequency increment is proposed to expand the range ambiguity and the joint algorithm of ESPRIT and MUSIC is proposed to reduce the computational complexity. The uniformly weighted beampattern of FDA is a SINC-like function. Therefore, the grating lobe of range estimation exists. In this paper, staggered frequency increment is proposed to increase the distance of adjacent grating lobes. The proposed joint estimation algorithm firstly estimates the angle by using ESPRIT algorithm. Then we get the range estimation by MUSIC one-dimensional range search using the above estimated angle. In simulation results section, it is indicated in simulation results that the proposed method improves the range grating lobe and reduces the complexity.

Description: 5G new radio (NR) provides enhanced transmission capabilities to transceivers by utilizing the massive multiple-input multiple-output (MIMO) technology with a significantly increased number of antenna elements. Such transmission requires massive arrays to perform accurate high-gain beamforming over the millimeter-wave frequency band. There is no fixed form of array structures for 5G NR base stations, but they are likely to include multiple subarrays or panels for practicality of implementation and are expected to cover the user equipment (UE) in various locations. In this paper, we propose an array structure to transmit signals over the three-dimensional (3D) space in an isotropic fashion for all types of UEs in ground, aerial, and high-rise building locations, by employing panels on surfaces of a polyhedron. We further derive exact beamforming equations for the proposed array and show the resulting beams provide improved receiver performance over the exiting conventional beamforming. The presented beamforming expressions can be applied to an arbitrary multipanel array with massive antenna elements.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 7, July 2019. 〈br/〉In order to resolve the issue of coverage limitation for the future fifth-generation network, deploying a relay node within a cell is one of the most capable and cost-effective solution, which not only enhances the coverage but also improves the spectral efficiency. However, this solution leads to the undesired interferences from nearby base station and relay nodes that affects user’s signal-to-interference-plus-noise ratio and can cause the ambiguous received signal at the user end. In this article, we have analyzed a relay-based interference-limited network at millimeter wave frequency and proposed a Poisson point process–based model using a stochastic geometrical approach. The results for the proposed Poisson point process model have been evaluated in terms of success probability, network ergodic capacity, and outage probability, compared with the ideal grid model and conventional multiple-antenna ultra-dense network model. The results proved that the success probability and ergodic capacity for the proposed model are 3.5% and 2.3% higher as compared to the most commonly used model for the high-density network, respectively. Furthermore, the results have been analyzed at different multiple-input-multiple-output antenna configuration, which validates the model in the improvement of overall network performance even for higher number of antennas.

Description: The incidence of antimicrobial resistance among microbial communities is a major threat to global health care and security. Landfills, which are reservoirs for many pharmaceuticals, provide a conducive habitat for antimicrobial-resistant microbes and resistant gene transfer and are therefore a major contributor to the phenomenon of antimicrobial resistance. Hence, this study determined the levels of three widely used antibiotics, metronidazole, penicillin, and amoxicillin, and the occurrence of antimicrobial resistance amongst microbes in soil and leachate samples from active and abandoned landfill sites in Kumasi, Ghana. Soil samples were collected from one active and four abandoned landfills, while leachate specimen was collected only from the active landfill. Sonication and solid-phase extraction (SPE) were used for sample preparation, followed by analysis via an HPLC-PDA method. Isolation and characterization of bacteria were done using standard bacteriological techniques. Antibiotic susceptibility testing was determined following the European Committee on Antimicrobial Susceptibility Testing (EUCAST) guidelines. Antibiotics were detected at very high concentrations in the specimen collected from both active and abandoned landfill sites. For leachate samples obtained from Dompoase, penicillin was present at the highest concentration (67.42 ± 5.35 μg/mL, ) followed by metronidazole (18.25 ± 7.92 μg/mL) and amoxicillin (10.96 ± 6.93 μg/mL). In general, the levels of antibiotics in soil samples were similar at both active and abandoned landfill sites. Nonetheless, as with leachates, penicillin levels were much higher () than levels of amoxicillin and metronidazole within any particular site. When screened against some antibiotics, Enterobacteriaceae and some Bacillus and Listeria species isolated from the soil and leachate samples proved to be resistant. The high levels of antibiotics coupled with the presence of resistant microbes at these landfills sites call for immediate measures to halt the disposal of pharmaceuticals in the environment so as to avert any possible public health setback.

Description: Landfill operations generate particulate matters (PM) and toxic gases that can jeopardize human health. This study was conducted in February 2016 to assess the air quality in the residential areas around the Nkolfoulou landfill in Yaoundé. The concentrations of PM2.5 and PM10 were determined with Dust Sentry while those of CO, O3, NO2, CH4, CO2, CH2O, H2S, and SO2 were measured using gas sensors. At the landfill neighborhood, 30% of the daily mean concentrations of PM2.5 and PM10 crossed the daily safe limits. The concentrations of CO, O3, NO2, SO2, and H2S recorded at the propinquity of the landfill complied with the emission standards. Near the landfill, hourly mean concentrations of CH2O and H2S higher than their odour thresholds were recorded at each sampling site. The concentrations of CH4 were less than its lower explosive limit while those of CO2 were far below the safe limit for occupational health. The values of cancer risk (CR) due to the inhalation of CH2O were 〉10−6 while those of hazard index (HI) due to the inhalation of CH2O, H2S, and SO2 were

Description: Artificial vision systems (AVS) have become very important in precision agriculture applied to produce high-quality and low-cost foods with high functional characteristics generated through environmental care practices. This article reported the design and implementation of a new fuzzy classification architecture based on the RGB color model with descriptors. Three inputs were used that are associated with the average value of the color components of four views of the tomato; the number of triangular membership functions associated with the components and were three and four for the case of component . The amount of tomato samples used in training were forty and twenty for testing; the training was done using the Matlab© ANFISEDIT. The tomato samples were divided into six categories according to the US Department of Agriculture (USDA). This study focused on optimizing the descriptors of the color space to achieve high precision in the prediction results of the final classification task with an error of -6. The Computer Vision System (CVS) is integrated by an image isolation system with lighting; the image capture system uses a Raspberry Pi 3 and Camera Module Raspberry Pi 2 at a fixed distance and a black background. In the implementation of the CVS, three different color description methods for tomato classification were analyzed and their respective diffuse systems were also designed, two of them using the descriptors described in the literature.

Description: Nowadays water bodies across the world are heavily polluted due to uncontrollable contamination of heavy metal particles, toxic dyes, and other harmful wastes discharged by emerging industries other than normal domestic wastages. This contamination needs sufficient control to protect the natural water bodies. There are various methodologies to be followed to perform wastewater treatment, in which the adsorption method of filtration is found to be efficient. The adsorption method is a high priority and preferable filtration method compared to other waste water treatment methods due to its peculiar characteristics. Considering the adsorption method, there are multiple options available in selecting material and methodology for the filtration process. In selecting the filtering material, there is much attraction towards graphene and its oxides, which have widespread range of differential applications in commercial industries because of their eco-friendly characteristic features. The importance of various graphene composites and their chemical properties is found to be significant in various fields. Analyzing the adsorbing properties of graphene widely, this article deeply reviews about the improvements and the technologies identified for using graphene and (GO) graphene oxide in wastewater treatment taken into discussion elaborately. Therefore, in this hard review, the advantages and demerits of using graphene for wastewater treatment as well as improving its properties to make it more suitable for wastewater treatment are detailed.

Description: Analysis of electromagnetic wave coupling to thin-wire structures plays a very important role in electromagnetic compatibility (EMC). In this paper, a hybrid method, which is integrated parabolic equation (PE) and two-potential integral equation (TPIE), is presented to analyze the coupling problems in terrain environments. To model the realistic scenarios, PE based on the split-step Fourier transform (SSFT) technique is applied to solve the three-dimensional field distribution to obtain the external excitations for the wires. According to the boundary conditions, the high-precision TPIE solved via the moment method (MoM) is developed to simulate the induced currents on the wires. The hybrid method takes the terrain influences into account and provides a more reasonable result compared to the traditional approaches. Numerical examples are given to demonstrate correctness of the proposed method. Simulation experiments of field-to-transmission lines with different frequencies, radiation source heights, conductor radii, and lengths, in a realistic scenario constructed by a digital map, are carried out to investigate the coupling properties.

Description: In this study, we have investigated the effects of brine and biosurfactant compositions on crude-oil-rock-brine interactions, interfacial tension, zeta potential, and oil recovery. The results of this study show that reduced brine salinity does not cause significant change in IFT. However, addition of biosurfactants to both high and low salinity brines resulted in IFT reduction. Also, experimental results suggest that the zeta potential of high salinity formation brine-rock interface is positive, but oil-brine interface was found to be negatively charged for all solutions used in the study. When controlled salinity brine (CSB) with low salinity and CSB with biosurfactants were injected, both the oil-brine and rock-brine interfaces become negatively charged resulting in increased water-wetness and, hence, improved oil recovery. Addition of biosurfactants to CSB further increased electric double layer expansion which invariably resulted in increased electrostatic repulsion between rock-brine and oil-brine interfaces, but the corresponding incremental oil recovery was small compared with injection of low salinity brine alone. Moreover, we found that the effective zeta potential of crude oil-brine-rock systems is correlated with IFT. The results of this study are relevant to enhanced oil recovery in which controlled salinity waterflooding can be combined with injection of biosurfactants to improve oil recovery.

Description: In this paper, we present a corresponding fractional order three-dimensional autonomous chaotic system based on a new class of integer order chaotic systems. We found that the fractional order chaotic system belongs to the generalized Lorenz system family by analyzing its linear term and topological structure. We also found that the equilibrium point generated by the fractional order system belongs to the unstable saddle point through the prediction correction method and the fractional order stability theory. The complexity of fractional order chaotic system is given by spectral entropy algorithm and algorithm. We concluded that the fractional order chaotic system has a higher complexity. The fractional order system can generate rich dynamic behavior phenomenon with the values of the parameters and the order changed. We applied the finite time stability theory to design the finite time synchronous controller between drive system and corresponding system. The numerical simulations demonstrate that the controller provides fast and efficient method in the synchronization process.

Description: Aiming at the problems in which there exists collocation between services and manufacturing tasks, multiobjective cloud manufacturing service composition optimization seldom considers the synergy degree of composite cloud services and the complexity of service composition, so a novel service composition optimization approach, called improved genetic algorithm based on entropy (IGABE), is put forward. First, the mathematical expressions of service collocation degree, composition synergy degree, composition entropy, and their related influence factors of the service composition are analyzed, and their definitions and calculation methods are given. Then, a multiobjective cloud manufacturing service composition optimization mathematical model is established. Moreover, crossover and mutation operators are improved by introducing normal cloud model theory and piecewise function, and improved roulette selection method is used to perform the selection operation. And the fitness function of the proposed IGABE is designed by combining Euclidean deviation with angular deviation. Finally, the manufacturing task of a wheeled cleaning robot is exemplified to verify the correctness of the proposed multiobjective optimization model for cloud manufacturing service composition and the effectiveness of the proposed algorithm, compared with Standard Genetic Algorithm (SGA), Hybrid Genetic Algorithm (HGA), and Cloud-entropy Enhanced Genetic Algorithm (CEGA). The studied results show that IGABE converges faster than SGA and HGA and can analyze and reflect the content difference expressed by the objective functions of service composition scheme and its approximation degree to the corresponding dimensions of the ideal point vector more comprehensively than CEGA. As such, the optimal service composition obtained by IGABE algorithm can better meet the complex needs of users.

Description: The phenomenon of coordinate measuring machines has led to a significant improvement in accuracy, adaptability, and reliability for measurement jobs. The coordinate measuring machines with scanning capabilities provide the alternative to output precise acquisition at a faster rate. However, they are less accurate as compared to discrete probing systems and slower than the noncontact techniques. Therefore, the data acquisition using a scanning touch probe needs improvement, so that it can provide commendable performance both in terms of accuracy and scanning time. The determination of appropriate scanning parameters is crucial to minimize the inaccuracy and time associated with the scanning process. However, it can be demanding as well as unreliable owing to the presence of uncertainty from a multitude of factors that may influence the measurement process. The optimization of data acquisition using a scanning touch probe is a multiresponse process which involves definite uncertainties from various sources. Therefore, multioptimization tools based on grey relational analysis coupled with principal component analysis and fuzzy logic were employed to enhance the utilization of the scanning touch probe. The work described here has the objective to identify the appropriate combination of scanning factors which can simultaneously boost the accuracy and lessen the scanning time. This study demonstrates the capability and effectiveness of the uncertainty theory based optimization methods in coordinate metrology. It also suggests that the uncertainty associated with the parameter optimization can be significantly reduced using these techniques. It has also been noticed that the results from the two techniques are in accord, which corroborates their application in coordinate metrology. The result from this study can be applied to other probing systems and can be broadened to include more experiments and parameters in various scenarios as needed by the specific application.

Description: Dissolved gas-in-oil analysis (DGA) is a powerful method to diagnose and detect transformer faults. It is of profound significance for the accurate and rapid determination of the fault of the transformer and the stability of the power. In different transformer faults, the concentration of dissolved gases in oil is also inconsistent. Commonly used gases include hydrogen (H2), methane (CH4), acetylene (C2H2), ethane (C2H6), and ethylene (C2H4). This paper first combines BP neural network with improved Adaboost algorithm, then combines PNN neural network to form a series diagnosis model for transformer fault, and finally combines dissolved gas-in-oil analysis to diagnose transformer fault. The experimental results show that the accuracy of the series diagnosis model proposed in this paper is greatly improved compared with BP neural network, GA-BP neural network, PNN neural network, and BP-Adaboost.

Description: The present study describes the growth of carbon nanotubes (CNTs) from liquefied petroleum gas (LPG) on an Fe2O3/Al2O3 precatalyst via a chemical vapour deposition (CVD) process without hydrogen. The obtained multiwalled CNTs exhibit a less-defective structure with an identical external diameter of tubes of around 50 nm. The growth mechanism of CNTs suggests that the Fe2O3/Al2O3 precatalyst is reduced to Fe/Al2O3 during the synthesis process using the products of LPG decomposition, and the tip-growth mechanism is suggested. The resulting CNTs are surface-modified with potassium permanganate in the acid medium and used as an adsorbent for copper from aqueous solutions. The Langmuir and Freundlich isotherm models are employed to evaluate the adsorption data, and the maximum adsorption capacity of Cu(II) is 163.7 mg·g−1.

Description: This paper proposes a lunar night survival method for small rovers using an MLI (Multilayer Insulation) curtain system for long-term missions. Until recently, it was difficult to install RHU (Radioisotope Heating Units) or other temperature maintenance devices on small lunar rovers to enable lunar night survival, and so such rovers could only perform short two-week missions. Thermal analysis results show that small rovers could survive during lunar nights by moving into a shelter located inside the MLI curtain of the lander without mounting temperature maintenance devices. In order to enhance the feasibility of the MLI curtain system, we also propose ideas of a double-layer MLI and a rover configuration without solar cells.

Description: Traffic data plays a very important role in Intelligent Transportation Systems (ITS). ITS requires complete traffic data in transportation control, management, guidance, and evaluation. However, the traffic data collected from many different types of sensors often includes missing data due to sensor damage or data transmission error, which affects the effectiveness and reliability of ITS. In order to ensure the quality and integrity of traffic flow data, it is very important to propose a satisfying data imputation method. However, most of the existing imputation methods cannot fully consider the impact of sensor data with data missing and the spatiotemporal correlation characteristics of traffic flow on imputation results. In this paper, a traffic data imputation method is proposed based on improved low-rank matrix decomposition (ILRMD), which fully considers the influence of missing data and effectively utilizes the spatiotemporal correlation characteristics among traffic data. The proposed method uses not only the traffic data around the sensor including missing data, but also the sensor data with data missing. The information of missing data is reflected into the coefficient matrix, and the spatiotemporal correlation characteristics are applied in order to obtain more accurate imputation results. The real traffic data collected from the Caltrans Performance Measurement System (PeMS) are used to evaluate the imputation performance of the proposed method. Experiment results show that the average imputation accuracy with proposed method can be improved 87.07% compared with the SVR, ARIMA, KNN, DBN-SVR, WNN, and traditional MC methods, and it is an effective method for data imputation.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 7, July 2019. 〈br/〉Multi-hop wireless sensor networks are widely used in many location-dependent applications. Most applications assume the knowledge of geographic location of sensor nodes; however, in practical scenarios, the high accuracy on position estimates of sensor nodes is still a great challenge. In this research, we propose a hop-weighted scheme that can be useful in distance-based distributed multi-hop localization. The hop-weighted localization approach generates spatial locations around position estimates of unknown sensors and computes local functions that minimize distance errors among hop-weighted and static neighboring sensors. The iterative process of each unknown sensor to re-estimate its own location allows a significant reduction of initial position estimates. Simulations demonstrate that this weighted localization approach, when compared with other schemes, can be suitable to be used as a refinement stage to improve localization in both isotropic and anisotropic networks. Also, under rough initial position estimates, the proposed algorithm achieves root mean square error values less than the radio range of unknown sensors, in average, with only a few iterations.

Description: The study was carried out in a shallow phreatic aquifer in the piedmont zone between the Atlas Mountains and Tadla plain in Morocco. This study is carried out using physicochemical analyses with statistical analysis (CA and PCA) to show variability of groundwater hydrochemical parameters beneath Beni Mellal city in order to know spatial variability of water quality under urban activities. Total dissolved solid shows large variation from 355 mg/L to 918 mg/L with high values recorded, as electric conductivity, in the city center. High sulfate content is intercepted also in the old city center with values exceeding the threshold in the Moroccan guideline. Sulfate ions are often suspected of having an anthropogenic origin. All water samples show a dominance of Ca against Mg (Ca/Mg: 1.08–6.25) and HCO3 against SO4 (HCO3/SO4: 0.29–6.92). For most of the trace elements, the measured concentrations were far below the standard values except Al and Fe in some samples which exceed all guideline values. PCA of all dataset highlights eight factors with eigenvalues higher than 1 that explained about 80.34% of the total variance. The first two components PC1 and PC2 explained about 41.14% of the total cumulative variance and were responsible for 24.25% and 16.89% of the variance for each one, respectively. The component PC1 is mostly correlated with electric conductivity, TDS, and chloride. The component PC2 was highly correlated with Ca, Cr, and Zn. The dendrogram at a linkage distance of about 10.5 leads to dividing the diagram into three clusters of water samples, C1, C2, and C3. Cluster C1 shows a medium content of EC, HCO3, and NO3 and low content of TDS, Ca, Mg, Na, K, SO4, and Ba compared with C2 and C3. C1 samples show the lowest ion content, resulting probably from the minimal time of residence within the aquifer with low rock interactions. Cluster C2 regroups samples with high content of Ca, Mg, K, SO4, Al, and Cr, medium content of TDS and Na, and low content of EC, HCO3, NO3, and Cl. Samples in cluster C3 have more content of heavy metal (Cd, Fe, Mn, and Ni), CE, TDS, Ca, Mg, Na, HCO3, NO3, and Cl, with low content of Cr and Al and medium values of K and SO4. We recommended the monitoring and follow-up of the water quality under the city and the repair of pipes especially in the downtown area to limit unwanted infiltration. Spatial autocorrelation used with variograms and Moran'I leads to conclude that groundwater parameters varied differently according to the direction, which means that the semivariance depended on direction and distance between samples.

Description: Low soil phosphorous level is among several constraints limiting crop productivity in southwestern Ethiopia. The dominant soil types in the region are acidic nitosols that are low in plant-available phosphorus. Most farmers cultivate maize with minimal external inputs and hence result in suboptimal yield levels. The effect of applying Tithonia biomass and phosphorus fertilizer on the agronomic efficiency of phosphorus and yield of maize was therefore investigated in a randomized complete block design with three replications. Tithonia (Tithonia diversifolia) biomass and Triple Superphosphate (TSP) were used as organic and inorganic sources of phosphorus, respectively. Significant treatment differences () were observed for most of the parameters studied including agronomic efficiency, partial factor productivity (PFP), and grain yield. Agronomic phosphorus use efficiency increased from 26.3 at the sole TSP to 163 at treatment 7, a staggering 520% increment when combined with Tithonia biomass. Similarly, PFP of phosphorus increased from 169.1 to 324.8. At the same time, 53% increment of the grain yield was recorded over the control. Although applying the highest Tithonia biomass alone gave the highest grain yield, application of just 50% of the highest rate of Tithonia biomass and TSP looks more appealing to smallholder maize producers in the region. The result therefore indicated that Tithonia biomass could be utilized in smallholder maize production system as a source of plant nutrients such as phosphorus; it also emphasized the need to allot more resources and attention in exploring locally available and cheap sources of plant nutrients which could augment crop productivity amid the mounting financial challenges faced by farmers in the region.

Description: The proposed Iron Calorimeter (ICAL) detector at Indian Neutrino Observatory (INO) will be a large (50 kt) magnetized detector located 1270 m underground at Bodi West Hills in Tamilnadu. ICAL is capable of identifying the charge of the particles. In this paper its potential for the measurement of the muon charge ratio is explored by means of a detailed simulation-based study, first using the CORSIKA code and then comparing it with an analytical model (the pika model). The simulated muon charge ratio is in agreement with the existing experimental observations; its measure can be extended by INO-ICAL up to 10.50 TeV and up to 60 degrees.

Description: This paper presents a hybrid metaheuristic that combines estimation of distribution algorithm with tabu search (EDA-TS) for solving the max-mean dispersion problem. The proposed EDA-TS algorithm essentially alternates between an EDA procedure for search diversification and a tabu search procedure for search intensification. The designed EDA procedure maintains an elite set of high quality solutions, based on which a conditional preference probability model is built for generating new diversified solutions. The tabu search procedure uses a fast 1-flip move operator for solution improvement. Experimental results on benchmark instances with variables ranging from 500 to 5000 disclose that our EDA-TS algorithm competes favorably with state-of-the-art algorithms in the literature. Additional analysis on the parameter sensitivity and the merit of the EDA procedure as well as the search balance between intensification and diversification sheds light on the effectiveness of the algorithm.

Description: The measured temperature of a concrete pouring block depends strongly on the position of the buried thermometer. Only when the temperature measured by the thermometer accurately reflects the actual temperature of the concrete pouring block do reasonable temperature-control measures become possible. However, little research has been done on how to determine the proper position of thermometers buried in a concrete pouring block embedded with cooling pipes. To address this situation, we develop herein a method to determine the position of thermometers buried in a concrete pouring block. First, we assume that the design temperature-control process line characterizes the average-temperature history of the concrete pouring block. Under this assumption, we calculate the average-temperature history of the concrete pouring block by using the water-pipe-cooling FEM, following which the temperature history of an arbitrary point in the concrete pouring block is obtained by interpolating the shape function. Based on the average-temperature history of the concrete pouring block and the temperature history of the arbitrary point, we build a mathematical model to optimize the buried position of the thermometer and use the optimization algorithm to determine this position. By using this method, we establish finite-element models of concrete prisms with four typical water-pipe spacing cases for concrete-dam engineering and obtain the geometric position of the thermometers by using the optimization algorithm. By burying thermometers at these positions, the measured temperature should better characterize the average-temperature history of the concrete pouring block, which can provide useful information for regulating the temperature of concrete pouring blocks.

Description: In this paper, we consider a risk averse competitive firm that adopts currency futures and options for hedging purpose. Based on the assumption of unbiased markets of currency futures and options, we propose the optimal hedging model in dynamic setting. By using two-stage optimization method, we prove that it is desirable for the prudent enterprise to buy exchange rate options to hedge currency risk. Furthermore, we derive the closed-form solutions of the multiperiod hedging problem with the quadratic utility function. We investigate an empirical study incorporated into GARCH-t prediction on the efficiency of hedging with currency futures and options. The empirical results demonstrate that hedging with currency futures and options can reduce the silver export firm’s risk exposure. Profits and the effective boundaries are compared in three cases: hedging with futures and options synchronously, only with futures and without any hedge. The results of multiple comparisons among different hedging strategies show that hedging with linear and nonlinear derivatives is advisable for the export firm.

Description: Currently, it is a challenge to effectively assess the seismic performance of the high-speed railway bridge line. To figure it out, this paper discussed the applicability of the Pushover analysis in the seismic fragility of the high-speed railway bridge. As the piers are the core components to resist the earthquakes, a typical high-speed railway bridge line consisting of 22 piers was established by the finite element software OpenSees. The influences of the different pier height and sites on the fragility analysis of the pies were investigated. From the component level, the seismic performance of the high-speed railway bridge line was evaluated by the Pushover analysis. The results show that the seismic responses of the piers by the Pushover analysis are agreeable with those by the incremental dynamical analysis when the peak ground acceleration is less than 0.4g. The high piers have better seismic performance than the lower piers. The high-speed railway bridge line exhibits good seismic performance under the 7-degree design earthquake (0.15g) and the 8-degree low-level earthquake (0.10g) but may be severely damaged under the 9-degree low-level earthquake (0.40g).

Description: A new series of p-dimethylaminobenzaldehyde derivatives were tested for therapeutic potential by exploring their properties through characterization. The derivatives were synthesized by 1 : 1 condensation reaction of p-dimethylaminobenzaldehyde and substituted amines. The synthesized compounds 1–8 were characterized by different characterization techniques including IR, mass, 1H NMR, and 13C NMR spectroscopy, elemental analysis, and mass spectrometry. Furthermore, binding of these Schiff bases to Ct-DNA was examined by absorption spectroscopy, fluorescence quenching, circular dichroic, viscosity measurement, molecular docking, and molecular dynamics simulation methods. Schiff bases were tested for antimicrobial activity against bacterial species Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa, and Staphylococcus aureus by the disc diffusion method. The pharmacological treatment of Schiff bases showed that 1–8 have promising potential against tested bacterial strains. The molecular docking study of the target compounds was also carried out against B-DNA dodecamer d(CGCGAATTCGCG)2, and it has been found that 1–8 can bind to Ct-DNA via an intercalative mode. DPPH free radical and hydrogen peroxide scavenging assays were employed to assess the antioxidant potential of synthesized Schiff bases.

Description: As typical thermostatically controlled loads (TCL) driven by constant-speed compressor, constant-speed air-conditioners play important roles in demand-side response for their abilities of energy conversion and storage. Their great potential for load regulation can be incorporated into power system scheduling through demand response. In view of their operating characteristics, a virtual energy storage (VES) model of thermostatically controlled loads with electrical and thermal parameters is established. This model is discretized and linearized to simplify calculation. By analyzing the control function and constraints of the VES model, the control strategy of VES of constant-speed air-conditioners load with virtual charging state priority is proposed. Example analysis shows that this strategy can solve and alleviate power shortage problem of the system by participating in demand response, which provides methodological support for constant-speed compressor temperature-control load to participate in the system operation.

Description: There is no effective therapeutic or vaccine for Middle East Respiratory Syndrome and this study attempts to find therapy using peptide by establishing a basis for the peptide-protein interactions through in silico docking studies for the spike protein of MERS-CoV. The antimicrobial peptides (AMPs) were retrieved from the antimicrobial peptide database (APD3) and shortlisted based on certain important physicochemical properties. The binding mode of the shortlisted peptides was measured based on the number of clusters which forms in a protein-peptide docking using Piper. As a result, we identified a list of putative AMPs which binds to the spike protein of MERS-CoV, which may be crucial in providing the inhibitory action. It is observed that seven putative peptides have good binding score based on cluster size cutoff of 208. We conclude that seven peptides, namely, AP00225, AP00180, AP00549, AP00744, AP00729, AP00764, and AP00223, could possibly have binding with the active site of the MERS-CoV spike protein. These seven AMPs could serve as a therapeutic option for MERS and enhance its treatment outcome.

Description: Linpan settlements (abbreviated as Linpan) are the most important traditional type of rural settlement in the Chengdu Plain, and they are an important part of the agroforestry ecological system in southwest China. In this study, we measured the micrometeorological parameters (air temperature, solar radiation, relative humidity, and wind speed) in 12 Linpans for two years to determine the seasonal micrometeorology variations; then, we explored the impacts of Linpan size and tree distribution on the Linpan micrometeorology. The results show that the Linpans undergo seasonal cooling (from 0.6 to 1.3°C), humidification (from 0.9% to 4.1%), reduction in solar radiation flux (from 92.1 to 496.0 W/m2), and changes in wind speed (by 0.4 to 0.5 m/s) compared to the surrounding environment. Both solar radiation flux and wind speed showed the following decreasing trend with respect to sampling positions in the Linpan: outside 〉 edge 〉 center. The Linpan size did not affect the solar radiation flux or wind speed over the four seasons. The main factor affecting solar radiation flux and wind speed was the horizontal tree distribution not the Linpan size. However, the Linpan size was significantly correlated with the air temperature in summer and winter. Large Linpans (〉5 × 103 m2) showed better ability to control the temperature to within a comfortable range in extremely hot and cold seasons. The Linpan size also showed a negative relationship with the relative humidity, but only in winter. Among the tree distribution patterns, a scattered distribution was optimal to achieve a comfortable micrometeorology over the course of the year. In addition, we suggest some ways to adapt the Linpan micrometeorology, which could be used to protect traditional Linpans, as well as for ecological restoration.

Description: Recent studies reveal that Allee effect may play important roles in the growth of tumor. We present one of the first mathematical models of avascular tumor that incorporates the weak Allee effect. The model considers the densities of tumor cells in three stages: proliferating cells, quiescent cells, and necrotic cells. We investigate how Allee effect impacts the growth of the avascular tumor. We also investigate the effect of apoptosis of proliferating cells and necrosis of quiescent cells. The system is numerically solved in 2D using different sets of parameters. We show that Allee effect and apoptosis play important roles in the growth of tumor and the formation of necrotic core.

Description: Utilising climate funds properly to reduce the impact of potential risks of climate change at the local level is essential for successful adaptation to climate change. Climate change has been disrupting the lives of millions of households along the coastal region of Bangladesh. The country has allocated support from its national funds and accessed international funds for the implementation of adaptation interventions. With the focus of the scientific community on climate finance mechanisms and governance at the global and the national level, there is a lacuna in empirical evidence of how climate finance affects risk appraisal and engagement in adaptation measures at the local level. This paper aims to examine how the support from climate finance affects risk appraisal in terms of the perceived probability and severity and the factors which influence risk appraisal. A field survey was conducted on 240 climate finance recipient households (CF HHs) and 120 nonclimate finance recipient households (non-CF HHs) in Galachipa Upazila of Patuakhali District in coastal Bangladesh. The results indicate that both CF and non-CF HHs experience a high probability of facing climatic events in the future; however, CF HHs anticipated a higher severity of impacts of climatic events on different dimensions of their households. With higher income and social capital, the overall risk appraisal decreases for CF HHs. CF HHs have higher engagement in adaptation measures and social groups and maintain alternative sources of income. Climate finance played a critical role in supporting households in understanding the risks that they were facing, assisting them in exploring as well as enhancing their engagement in adaptation options.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 7, July 2019. 〈br/〉Due to the increased demand of wireless sensor networks for their characteristics like low energy consumption, robustness, and low cost in several demanding and complex applications like smart grid, health and safety, traffic and weather updates, there is need of monitoring the infrastructure in a timely manner with high reliability. In this article, a cross-layer data communication scheme target-aware cross-layer technique is proposed to enhance reliability and to reduce the latency in wireless sensor networks. The proposed scheme uses connected dominating set at network layer where nodes in the connected dominating set are directly connected to all the other nodes in the network. Each sensor node sends the data to the nodes present in the connected dominating set, which forwards it to their respective destinations. The proposed scheme reduces the chances of collision resulting reduced delays. Higher packet delivery ratio is achieved with the proposed scheme results in improved reliability. The proposed scheme is outperforming other state-of-the-art schemes in terms of packet delivery ratio, latency, and data throughput with the default 802.15.4 and delay-responsive cross layer in both static and mobile scenarios using network simulator tool.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 7, July 2019. 〈br/〉In this article, we present a sensitivity-enhancing feedback control–based damage detection method for piezoelectric actuator and sensor bonded composite laminates with delamination failures. The present method mainly consists of two parts: delamination modeling and feedback controller design. We first introduce the adopted improved layerwise theory–based mathematical model for delamination modeling with finite element implementation. The obtained second-order governing equations are transformed into the state space model for design of state feedback controller. Proper pole placement is required to enhance the sensitivity of frequency shifts to stiffness change caused by delamination. We investigated different delamination interfaces and longitudinal locations for studying the feasibility and efficiency of the present method. The present results clearly demonstrate that with the applied state feedback controller, the frequency shifts of the closed-loop system are significantly enhanced. The proposed sensitivity-enhancing feedback control can be used as an efficient tool for detecting delamination failures in smart composite structures.

Description: The buckling loads of shell structures are sensitive to initial geometric imperfections. Conventional methods used to model geometric imperfections cannot determine the accuracy of buckling loads with high computational efficiency. A new computational approach based on particle swarm optimization (PSO) is proposed to obtain the lower bound of the buckling load of shell structures with geometric imperfections. The proposed approach assumes a nodal geometric position using uncertain parameters. The buckling loads of the shell structures are then optimized using the PSO-based approach. Both academic and practical numerical examples have been thoroughly investigated. Thus, the applicability and accuracy of the proposed method is critically validated.

Description: This paper proposes the end-to-end detection of a deep network for far infrared small target detection. The problem of detecting small targets has been a subject of research for decades and has been applied mainly in the field of surveillance. Traditional methods focus on filter design for each environment, and several steps are needed to obtain the final detection result. Most of them work well in a given environment but are vulnerable to severe clutter or environmental changes. This paper proposes a novel deep learning-based far infrared small target detection method and a heterogeneous data fusion method to solve the lack of semantic information due to the small target size. Heterogeneous data consists of radiometric temperature data (14-bit) and gray scale data (8-bit), which includes the physical meaning of the target, and compares the effects of the normalization method to fuse heterogeneous data. Experiments were conducted using an infrared small target dataset built directly on the cloud backgrounds. The experimental results showed that there is a significant difference in performance according to the various fusion methods and normalization methods, and the proposed detector showed approximately 20% improvement in average precision (AP) compared to the baseline constant false alarm rate (CFAR) detector.

Description: A three-dimensional computational fluid dynamics (CFD) study was carried out for drilling fluid flow with drill cuttings in open channels. The flow is similar to the return flow when drilling, stream containing drilling fluid, and drill cuttings. The computational model is under the framework of the Eulerian multifluid volume of the fluid model. The Herschel–Bulkley rheological model was used to describe the non-Newtonian rheology of the drilling fluid, and the computational model was validated with experimental results for two-phase flow in the literature. The effect of flow depth and flow velocity in an open channel was studied for drill cutting size of up to 5 mm and for a solid volume fraction of up to 10%. For constant cross section and short open channels, the effect of drill cuttings on flow depth and mean velocity was found to be small for particle sizes less than 5 mm and solid volume fractions less than 10%. High momentum force in the downward direction can carry the solid-liquid mixture at higher velocities than a lower density mixture. Higher inclination angles mean that the gravity effect upon the flow direction is more significant than the particle friction for short channels.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 8, August 2019. 〈br/〉With the continuous development of Internet of things, all kinds of smart systems are quickly evolving to make our day-to-day life smoother and safer. Like many other sectors, transportation has entered a period of rapid change. Intelligent Traffic System is one of the fastest-growing fields within the smart systems, which is expected to increase road safety, mitigate traffic congestion, and enable fuel efficiency. The main functionalities of Intelligent Traffic System are as follows: (1) monitoring real-time traffic conditions in specific areas, (2) locating traffic emergencies (i.e. traffic accidents) in specific areas, and (3) dynamic monitoring and managing the continuous use in public transit services (i.e. change in car lanes) that may lead to changes in macro traffic conditions. This article will use the above-mentioned functionalities of the Intelligent Traffic System as underlying simulative scenarios, to design and to implement a smart transportation system based on Internet of things and blockchain—both share inherent distributed technology characteristics—combining both Internet of things sensor nodes and distributed ledger technology, to (1) record the changes in intelligent transportation systems and (2) set up a credit-token mechanism for paying the use and misuses in public transit services accordingly. The Intelligent Traffic System described in this article is intended to be used as experimental project only, given the terms and conditions as depicted in the simulated scenario. In real-life traffic scenarios, it may generate more complex system and data security issues, which will be elaborated and analyzed at the end of this article. Intelligent Traffic System is a comprehensive smart system; it can significantly change and reinvent the wheel for traffic conditions. Based on the system development as discussed in this article, there are still a lot of demands and challenges that need to be addressed in the future. Such topic scope will be explored in depth in our subsequent research.

Description: The standard model of elementary particles (SM) suffers from various problems, such as power-law ultraviolet (UV) sensitivity, exclusion of general relativity (GR), and absence of a dark matter candidate. The LHC experiments, according to which the TeV domain appears to be empty of new particles, started sidelining TeV-scale SUSY and other known cures of the UV sensitivity. In search for a remedy, in this work, it is revealed that affine curvature can emerge in a way restoring gauge symmetries explicitly broken by the UV cutoff. This emergent curvature cures the UV sensitivity and incorporates GR as symmetry-restoring emergent gravity (symmergent gravity, in brief) if a new physics sector (NP) exists to generate the Planck scale and if SM+NP is Fermi-Bose balanced. This setup, carrying fingerprints of trans-Planckian SUSY, predicts that gravity is Einstein (no higher-curvature terms), cosmic/gamma rays can originate from heavy NP scalars, and the UV cutoff might take right value to suppress the cosmological constant (alleviating fine-tuning with SUSY). The NP does not have to couple to the SM. In fact, NP-SM coupling can take any value from zero to if the SM is not to jump from to the NP scale . The zero coupling, certifying an undetectable NP, agrees with all the collider and dark matter bounds at present. The seesawic bound , directly verifiable at colliders, implies that (i) dark matter must have a mass , (ii) Higgs-curvature coupling must be , (iii) the SM RGEs must remain nearly as in the SM, and (iv) right-handed neutrinos must have a mass . These signatures serve as a concise testbed for symmergence.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 8, August 2019. 〈br/〉3D coverage is not only closer to the actual application environment, but also a research hotspot of sensor networks in recent years. For this reason, a node optimization coverage method under link model in passive monitoring system of three-dimensional wireless sensor network is proposed in this article. According to wireless link-aware area, the link coverage model in three-dimensional wireless sensor network is constructed, and the cube-based network coverage is used to represent the quality of service of the network. This model takes advantage of the principle that the presence of human beings can change the transmission channel of the link. On this basis, the intruder is detected by the data packets transmitted between the wireless links, and then the coverage area is monitored by monitoring the received signal strength of the wireless signal. Based on this new link awareness model, the problem of optimal coverage deployment of the receiving node is solved, that is, how to deploy the receiving node to achieve the optimal coverage of the monitoring area when the location of the sending node is given. In the process of optimal coverage, the traditional genetic algorithm and particle swarm optimization algorithm are introduced and improved. Based on the genetic algorithm, the particle swarm optimization algorithm which integrates the idea of simulated annealing is regarded as an important operator of the genetic algorithm, which can converge to the optimal solution quickly. The simulation results show that the proposed method can improve the network coverage, converge quickly, and reduce the network energy consumption. In addition, we set up a real experimental environment for coverage verification, and the experimental results verify the feasibility of the proposed method.

Description: The actual burden and future burden of the small-for-gestational-age (SGA) babies turn their screening in pregnancy a question of major concern for clinicians and policymakers. Half of stillbirths are due to growth restriction in utero, and possibly, a quarter of livebirths of low- and middle-income countries are SGA. Growing body of evidence shows their higher risk of adverse outcomes at any period of life, including increased rates of neurologic delay, noncommunicable chronic diseases (central obesity and metabolic syndrome), and mortality. Although there is no consensus regarding its definition, birthweight centile threshold, or follow-up, we believe birthweight

Description: Online quality prediction helps to identify the web service quality degradation in the near future. While historical web service usage data are used for online prediction in preventive maintenance, the similarities in the usage data from multiple users invoking the same web service are ignored. To improve the service quality prediction accuracy, a multivariate time series model is built considering multiple user invocation processes. After analysing the cross-correlation and similarity of the historical web service quality data from different users, the time series model is estimated using the multivariate LSTM network and used to predict the quality data for the next few time series points. Experiments were conducted to compare the multivariate methods with the univariate methods. The results showed that the multivariate LSTM model outperformed the univariate models in both MAE and RMSE and achieved the best performance in most test cases, which proved the efficiency of our method.

Description: The problem of artificial potential function (APF) safety and obstacle avoidance guidance for autonomous rendezvous and docking of chaser spacecraft with noncooperative spacecraft is studied. The relative motion equation of the chaser and the target is established based on the line-of-sight coordinate system, the reference state is designed, and the corresponding state error is deduced. The attitude motion equation of the noncooperative target spacecraft in space is established. The safety and obstacle avoidance guidance problem of autonomous rendezvous and docking with noncooperative target is transformed into a path planning problem in a dynamic environment. The attractive potential function is designed according to the state error. In order to ensure that the chaser can safely approach the noncooperative target spacecraft, a safe corridor with ellipse cissoid is designed in the final approaching stage of autonomous rendezvous and docking. The obstacle is assumed to be a sphere with a certain radius to avoid its influence in the approach, and the obstacle potential function is designed based on the Gaussian function method. The total potential function of the system is designed according to the attractive potential function, the safe potential function, and the obstacle potential function. The total potential function of the system is modified to ensure that the reference state is the minimum of the total potential function of the system. The stability of the system is proven according to the Lyapunov stability principle, and the conditions for satisfying the monotonic decrease in the total potential function of the system are deduced. Finally, the effectiveness of the proposed method is verified by three sets of numerical simulations.

Description: The integrals evaluated are the products of multivariable Aleph-functions with algebraic functions, Jacobi polynomials, Legendre functions, Bessel-Maitland functions, and general class of polynomials. The main results of our paper are quite general in nature and competent at yielding a very large number of integrals involving polynomials and various special functions occurring in the problem of mathematical analysis and mathematical physics.

Description: In this work, we studied the effect of TiO2 sensitization with dry biomass extracted of cyanobacteria on the degradation of methylene blue dye (AM). Cyanobacterial cultures isolated from water samples were collected from the swamp of Malambo in Colombia; two main genera of cyanobacteria were identified, and they were cultivated with BG-11 culture medium. The concentrations of chlorophyll a in the exponential and stationary phases of growth were measured; the phycobilin content was quantified by spectrophotometry. Thin films of TiO2 were deposited by a doctor blade method, and they were sensitized by wet impregnation. Furthermore, a methylene blue (MB) photodegradation process was studied under visible light irradiation on the cyanobacterial biomass sensitized TiO2 material (TiO2/sensitizer); besides, the pseudo-first-order model was used to obtain kinetic information about photocatalytic degradation. The results showed that the BG-11+ treatment reported a higher amount of dry biomass and phycobiliproteins. After the sensitization process, the TiO2/sensitizer thin films showed a significant red shift in the optical activity; besides the thin film roughness decreasing, the TiO2/sensitizer showed photocatalytic activity of 23.2% under visible irradiation, and besides, the kinetic () constant for TiO2/sensitizer thin films was 3.1 times greater than the value of TiO2 thin films. Finally, results indicated that cyanobacterial biomass is a suitable source of natural sensitizers to be used in semiconductor sensitization.

Description: This paper presents spatial distribution, temporal seismotectonics, and return period of earthquake in East Nusa Tenggara Province, Indonesia, using earthquake data and Maximum Likelihood methods. The data used are ISC, USGS/NEIC, and Indonesian Meteorology, Climatology and Geophysics Agency (IMCGA) earthquake catalog data for the period of 1918 to 2015. The results show that the a-value ranges from 5.0 to 8.5 and b-value ranges from 0.6 to 1.3. The pattern of spatial distribution of b-value is relatively low corresponding to the low of a-value, which means the high level of stress of rock in the area. The fractal dimension shows that the D value ranges from 1.384 to 1.874. The earthquake that occurred in East Nusa Tenggara Province was dominated by a small magnitude with great seismicity and the fastest return period is in Alor and Timor islands which is 44 days.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 8, August 2019. 〈br/〉In the context of fingerprinting applications, this article presents the performance analysis of a type of space labeling based on the binary quantization of the received signal strength indicator. One of the common drawbacks of fingerprinting is the large data size and consequently the large search space and computational load as a result of either vastness of the positioning area or the finer resolution in the fingerprinting grid map. Our approach can be considered, for example, when we use very small, inexpensive beacons, like those based on bluetooth low energy technology, radio frequency identification, or in the future context of the Internet of Things. One of the interesting properties of this deployment is that it can be interpreted as a form of space labeling or encoding since space is divided into cells, and each cell is associated to a binary codeword with the corresponding scalability of the spatial resolution. Here, it developed the performance estimation, exploiting the association of this deployment to an error correcting code. The analysis and numerical and experimental results allow a deeper understanding of the impact of the proposed solution and show that it is robust and computationally efficient with respect to the traditional fingerprinting technique.

Description: The concentration dependence of a microwave frequency radiation from a solution of a functioning enzyme system (ES) (with the example of cytochrome P450 BM3 (CYP102A1) system during lauric acid (LA) hydroxylation) has been studied with a radiothermometric sensor. Registration of the radiation from the enzyme solution has been performed in the frequency range from 3.4 to 4.2 GHz at the enzyme concentrations from 10−10 М to 10−6 М. It has been demonstrated that the catalysis of LA hydroxylation in a reconstituted CYP102A1 system is accompanied by a generation of microwave radiation over the entire range of concentrations studied. It has been found that a transition from a multipulse mode (at nanomolar enzyme concentrations from 10−10М to 10−8М) to a single-pulse mode (at micromolar enzyme concentrations from 10−7М to 10−6М) is observed. This effect is discussed on the basis of assumptions considering possible realization of biomaser-like radiation in the enzyme system. The discovered concentration-based effect of the transition of an unsynchronized pulsed radiation into a synchronized one in ES can further be used in the development of novel methods of noninvasive diagnostics of diseases, in mathematical modeling of the functioning of living systems, and in the development of next-generation quantum computers.

Description: Target signal extraction has a great potential for applications. To solve the problem of error extraction of target signals in the current constrained independent component analysis (cICA) method, an enhanced independent component analysis with reference (EICA-R) method is proposed. The new algorithm establishes a unified cost function, which combines the negative entropy contrast function and the distance metric function. The EICA-R method transforms the constrained optimization problem into unconstrained optimization problem to overcome the problem of threshold setting of distance metric function in constrained optimization problem. The theoretical analysis and simulation experiment show that the proposed EICA-R algorithm overcomes the problem of the error extraction of the existing algorithm and improves the reliability of the target signal extraction.

Description: A mathematical model is developed to examine the behaviors of a peristalsis flow with nanoparticles in a symmetric channel under the magnetic environment. Here, the nanofluid is electrically conducted through an external magnetic field. Thermal radiation and Joule heating effects are also retained in the present analysis. Under the lubrication approach, the reduced nonlinear systems are obtained. Then, they are solved very efficiently by means of a homotopy analysis method-based package BVPh 2.0. The influences of important physical parameters on the flow behaviors are presented. Analysis of the entropy generation is illustrated. It is found that the Brownian diffusion and the thermophoresis are the two most important nanoparticle slip mechanisms in the Jeffery fluids as well. Besides, the Hartman number, the type of the Jeffery fluid, the Brinkman number, and the thermal radiation parameter play important roles on flow behaviors. Results show that the temperature profile enhanced but the nanoparticles’ volume fraction profiles lowered with increase in the Hartman number. However, using the Jeffery nanofluid induces effect on the velocity distribution that decreases with the increase in the Jeffery fluid parameter. It is also found that the generated total entropy increases with an increase in the Brownian motion parameter but with a decrease in the thermophoresis parameter.

Description: Adsorption of cationic methyl green (MG) on nontreated (AB) and purified (AP) natural Sejnane clay type was studied in an equilibrium batch process. This work reported the application of kaolinite-rich heterogeneous clay for the removal of a cationic dye. Effects of contact time, initial dye concentration, mass adsorbent, pH, and temperature on the MG removal were checked. The adsorbent before and after adsorption processes was characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), Fourier transform infrared (FTIR), and atomic adsorption spectrophotometer. Equilibrium data were mathematically modeled using the Freundlich, Langmuir, and intraparticle diffusion models. Kinetic of adsorption was determined by pseudo-first-order and pseudo-second-order models. The free energy (ΔG°), standard enthalpy (ΔH°), and standard entropy (ΔS°) were calculated. A fast increase in the equilibrium removal of the cationic dye was obtained at a pH ranging between 3 and 11 and moderate temperature. This rapid MG adsorption proved the efficiency of kaolinite clay in cationic dye removal. Decolorizing yields were 73.3% for AB and 99.8% for AP. Thus, the adsorption capacity of purified clay was clearly higher than of H2SO4 and thermic activated clays. The data more closely resembled a pseudo-second-order model process, and the clay had reasonable Freundlich adsorption capacity. Adsorption process was endothermic and spontaneous chemisorption. SEM analysis showed that the adsorbed MG had remarkably changed the morphology of raw and purified clay surface. The low desorption rates confirmed effectiveness of this type of material for the retention of methyl green molecules. Thus, tested clays have no environmental impact.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 8, August 2019. 〈br/〉Accurately predicting the load change of the information system during operation has important guiding significance for ensuring that the system operation is not interrupted and resource scheduling is carried out in advance. For the information system monitoring time series data, this article proposes a load trend prediction method based on isolated forests-empirical modal decomposition-long-term (IF-EMD-LSTM). First, considering the problem of noise and abnormal points in the original data, the isolated forest algorithm is used to eliminate the abnormal points in the data. Second, in order to further improve the prediction accuracy, the empirical modal decomposition algorithm is used to decompose the input data into intrinsic mode function (IMF) components of different frequencies. Each intrinsic mode function (IMF) and residual is predicted using a separate long-term and short-term memory neural network, and the predicted values are reconstructed from each long-term and short-term memory model. Finally, experimental verification was carried out on Amazon’s public data set and compared with autoregressive integrated moving average and Prophet models. The experimental results show the superior performance of the proposed IF-EMD-LSTM prediction model in information system load trend prediction.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 8, August 2019. 〈br/〉The coverage intensity of sensors is the most important issue on structural health monitoring technique. The geometric configuration of sensors must be optimized based on coverage intensity with proper objectives. In this article, a novel algorithm for optimal sensor placement in various steel frames was evaluated. These frames including moment-resisting frame, moment-resisting frame with base isolation, and moment-resisting frame with base isolation with steel shear wall were selected for case studies. This approach was proposed based on combination of common optimal sensor placement algorithm and nonlinear time history analysis. A new method called transformed time history to frequency domain approach was evaluated to transform nonlinear time history analysis results to frequency domain and then the effective frequencies according the maximum range of Fourier amplitude were selected. The modified type of modal assurance criterion values can be achieved from modal assurance criterion with the exact seismic displacement. All of novel optimal sensor placement processes were done through FEM-MAC-TTFD code modeled and developed in MATLAB by authors of this article. The results show that there is good relative correlation between the sensors number and coverage intensity obtained with modal and modified modal assurance criterion approaches for moment-resisting frame system, but for integrated frame such as moment-resisting frame with base isolation and moment-resisting frame with base isolation with steel shear wall, the modified modal assurance criterion approach is better approach. There is no significant difference between coverage intensity of sensors for top joints between modal assurance criterion and modified modal assurance criterion approaches for moment-resisting frame, moment-resisting frame with base isolation, and moment-resisting frame with base isolation with steel shear wall systems (R2 = 0.994, 0.986, and 0.724, respectively). It was found that if reference point is located in center of frame, there is significant difference between modal assurance criterion and modified modal assurance criterion approaches, and modified modal assurance criterion generated slightly better results.

Description: We study the electromagnetic (EM) duality from derivative theory with homogeneous disorder. We find that, with the change of the sign of the coupling parameter of the derivative theory, the particle-vortex duality with homogeneous disorder holds better than that without homogeneous disorder. The properties of quasinormal modes (QNMs) of this system are also explored. When the homogeneous disorder is introduced, some modes emerge at the imaginary frequency axis for negative but not for positive . In particular, with an increase in the magnitude of , new branch cuts emerge for positive . These emerging modes violate the duality related to the change of the sign of . With the increase of , this duality is getting violated more.

Description: This research proposes a circularly polarized (CP) single-fed omnidirectional dipole antenna operable in 2.45 GHz frequency for the industrial, scientific, and medical (ISM) radio band applications. The proposed antenna consisted of bisectional dipole core, a pair of quarter-wave baluns, and four diagonally adjoined parasitic braces. The bisectional dipole core was utilized to improve the antenna gain and realize omnidirectional radiation pattern, and the quarter-wave baluns were to symmetrize the current on the bisectional core. The four parasitic braces collectively generated circular polarization. In the study, simulations were conducted using CST Microwave Studio and a prototype antenna fabricated. To validate, experiments were carried out, and simulation and experimental results compared. The finding revealed good agreement between the simulation and experimental results. Essentially, in addition to achieving an antenna gain of 2.07 dBic, the proposed CP single-fed omnidirectional antenna is suited to ISM frequency band applications.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 8, August 2019. 〈br/〉It is difficult to reconstruct the complete light field, and the reconstructed light field can only recognize specific fixed targets. These have limited the applications of the light field in practice. To solve the problems above, this article introduces the multi-perspective distributed information fusion into light field reconstruction to monitor and recognize the maneuvering targets. First, the light field is represented as sub-light fields at different perspectives (i.e. the Multi-sensor distributed network), and sparse representation and reconstruction are then performed. Second, we establish the multi-perspective distributed information fusion under the condition of regional full-coverage constraints. Finally, the light field data from multiple perspectives are fused and the states of the maneuvering targets are estimated. Experimental results show that the light field reconstruction time of the proposed method is less than 583 s, and the reconstruction accuracy exceeds 92.447% compared with the existing spatially variable bidirectional reflectance distribution function, micro-lens array, and others. In the aspect of maneuvering target recognition, the recognition time of the algorithm in this article is no more than 3.5 s. The recognition accuracy of the algorithm in this article is up to 86.739%. Moreover, the more viewing angles used, the higher the accuracy.

Description: Multicomponent cyclocondensation of hydrazine derivatives, ethyl acetoacetate, aromatic aldehydes, and 4-hydroxycoumarin has been reported. The optimization details of the developed novel protocol are recorded. The novel procedure features short reaction time, moderate yields, and simple workup. In addition, BMIM[triflate] was chosen as a green solvent. The structures of the obtained benzylpyrazolyl coumarins were determined and confirmed by 1H NMR, 13C NMR, IR, and elemental analysis. The MIC values of benzylpyrazolyl coumarin derivatives were determined by the microbroth dilution method using 96-well plates. However, the derivatives 5a, 5b, 5d, and 5g possess the strongest activities. Compound 5b was the most active derivative against Candida albicans. Moreover, the antioxidant activity determination of these coumarins derivatives 5(a–g)–6(a–g) were studied with the DPPH and compared with gallic acid (GA)and butylated hydroxytoluene (BHT). Molecular modelling studies using DFT (density functional theory) calculations showed that there two tautomers A and B in which A is more stable than B. The benzylpyrazolyl coumarin derivatives 5e and 6f exhibited the most cytotoxic effect on the promising cytotoxic activity with IC50 values 4.45 μg/mL against MDA-MB-231 and 4.85 μg/mL against MCF7, respectively.

Description: Given a tree network with vertices where each edge has an independent operational probability, we are interested in finding the optimal location of a reliable service provider facility in a shape of subtree with exactly leaves and with a diameter of at most which maximizes the expected number of nodes that are reachable from the selected subtree by operational paths. Demand requests for service originate at perfectly reliable nodes. So, the major concern of this paper is to find a location of a reliable tree-shaped facility on the network in order to provide a maximum access to network services by ensuring the highest level of network connectivity between the demand nodes and the facility. An efficient algorithm for finding a reliable – tree core of is developed. The time complexity of the proposed algorithm is Examples are provided to illustrate the performance of the proposed algorithm.

Description: Since perfluoroalkyl acids (PFAs) are widely used and harmless to organisms, they have attracted great attention in recent years. The distribution of PFAs in the oceans all around the world is well documented. However, the study of PFAs in Xiamen could be a beneficial complement, for its unique geologies of no rivers that originate from other cities to influence the concentration of PFAs in this area. In this paper, six PFAs were analyzed in water, sediments, and organisms from both freshwater and seawater and the bioaccumulation factors (BAFs) were calculated with the quantity of PFAs in different trophic levels of aquatic organisms. The results showed that the ΣPFA concentrations ranged from 7.66 to 11.98 ng·L−1 for seawater samples and from 2.12 to 8.61 ng·L−1 for freshwater. The concentration of ΣPFAs in sediments was 7.43–12.89 ng·g−1 and 4.53–5.80 ng·g−1 in seawater and freshwater, respectively. The PFA concentration in water is highly positive correlated with the PFA concentration in sediments (R2 = 0.85). The calculated bioaccumulation factors (BCFs) were 6412–14254 L·kg−1 and 2927–7959 L·kg−1 for perfluorooctanoic acid (PFOA) and perfluorooctane sulfonates (PFOS), respectively. PFOA seems more bioaccumulative than PFOS in seawater. The results illustrated the PFA pollution in the Xiamen sea area, and it is useful for the protection and control of the organic pollutants in this area.

Description: Launch vehicles suffer from severe base heating during ascents. To predict launch vehicle base heat flux, the computational fluid dynamics (CFD) tools are widely used. The selection of the turbulence model determines the numerical simulation results of launch vehicle base heating, which may instruct the thermal protection design for the launch vehicle base. To assess performances, several Reynolds-averaged turbulence models have been investigated for the base heating simulation based on a four-nozzle launch vehicle model. The finite-rate chemistry model was used for afterburning. The results showed that all the turbulence models have provided nearly identical mean flow properties at the nozzle exit. Menter’s baseline (BSL) and shear stress transport (SST) models have estimated the highest collision pressure and have best predicted base heat flux compared to the experiment. The Spalart-Allmaras (SA) model and the renormalization group (RNG) model have performed best in temperature estimation, respectively, in around and . The realizable (RKE) model has underestimated the reverse flow and failed to correctly reflect the recirculation in the base region, thus poorly predicted base heating. Among all the investigated turbulence models, the BSL and SST models are more suitable for launch vehicle base heating simulation.

Description: In this paper, a high-order compact finite difference method is proposed for a class of temporal fractional subdiffusion equation. A numerical scheme for the equation has been derived to obtain in time and fourth-order in space. We improve the results by constructing a compact scheme of second-order in time while keeping fourth-order in space. Based on the - approximation formula and a fourth-order compact finite difference approximation, the stability of the constructed scheme and its convergence of second-order in time and fourth-order in space are rigorously proved using a discrete energy analysis method. Applications using two model problems demonstrate the theoretical results.

Description: Iris recognition is one of the most useful methods to identify or verify people in biometric recognition systems. Iris patterns contain many features that distinguish people from each other. In this paper, a novel iris recognition method is proposed based on the fusion of Fisher Linear Discriminate Analysis (FLDA) with embedding Principal Component Analysis (PCA) method. In this work, firstly we use 1D Log-Gabor to elicit the iris features from an approximation part. Secondly, we obtain an appropriate degree of clarity for the iris with fusion of FLDA/PCA to eliminate the optical reflections on the iris image. Experiments of our proposed algorithm are performed on the CASIA V1 database. The results of our proposed approach show a good performance with recognition rate up to 99.99%.

Description: A weakly compressible smoothed particle hydrodynamics (WCSPH) method was developed to model open-channel flow over rough bed. An improved boundary treatment is proposed to quantitatively characterize bed roughness based on the ghost boundary particles (GBPs). In this model, the velocities of GBPs are explicitly calculated by using evolutionary polynomial regression with a multiobjective genetic algorithm. The simulation results show that the proposed boundary treatment can well reflect the influence of wall roughness on the vertical flow structure. A fully developed open channel is established, and its flume length, processing time, and turbulent model are discussed. The mixed-length-based subparticle scale (SPS) turbulence model is adopted to simulate uniform flow in open channel, and this model is compared with the Smagorinsky-based one. For the modified WCSPH model, the results show that the calculated vertical velocity and turbulent shear stress distribution are in good agreement with experimental data and fit better than the calculations obtained from the traditional Smagorinsky-based model.

Description: Facial expression recognition plays an important role in communicating the emotions and intentions of human beings. Facial expression recognition in uncontrolled environment is more difficult as compared to that in controlled environment due to change in occlusion, illumination, and noise. In this paper, we present a new framework for effective facial expression recognition from real-time facial images. Unlike other methods which spend much time by dividing the image into blocks or whole face image, our method extracts the discriminative feature from salient face regions and then combine with texture and orientation features for better representation. Furthermore, we reduce the data dimension by selecting the highly discriminative features. The proposed framework is capable of providing high recognition accuracy rate even in the presence of occlusions, illumination, and noise. To show the robustness of the proposed framework, we used three publicly available challenging datasets. The experimental results show that the performance of the proposed framework is better than existing techniques, which indicate the considerable potential of combining geometric features with appearance-based features.

Description: This paper presents a fuzzy regression analysis method based on a general quadrilateral interval type-2 fuzzy numbers, regarding the data outlier detection. The Euclidean distance for the general quadrilateral interval type-2 fuzzy numbers is provided. In the sense of Euclidean distance, some parameter estimation laws of the type-2 fuzzy linear regression model are designed. Then, the data outlier detection-oriented parameter estimation method is proposed using the data deletion-based type-2 fuzzy regression model. Moreover, based on the fuzzy regression model, by using the root mean squared error method, an impact evaluation rule is designed for detecting data outlier. An example is finally provided to validate the presented methods.

Description: The discrete element method (DEM) and smoothed particle hydrodynamics (SPH) can be adopted to simulate the granular materials and fluid media respectively. The DEM-SPH coupling algorithm can be developed for the dynamic interaction between the two media. When the particle material is simulated by polyhedral element, a fluid-solid coupling interface would lead to the complex geometry between the granular particle and the fluid. The boundary particle method is traditionally used for the fluid-solid interface but with low computational efficiency. In this paper, the dilated polyhedral element is constructed based on Minkowski sum theory, while the contact force between the elements is calculated by Hertzian contact model. Accordingly the dilated polyhedra based DEM is established. The weakly compressible SPH is adopted to simulate the fluid medium, while the interaction on the geometrically complex fluid-solid interface is evaluated with the repulsive force model which can be determined by the contact detection between SPH particles and solid particles in geometry. This method avoids the storage and calculation of a large number of boundary particles, which can be potentially applied for the complex fluid-solid boundary. In order to improve the computational efficiency, a GPU-based parallel algorithm is employed to achieve high performance computation of SPH. The acceleration of the parallel algorithm is evaluated by the cases of dam break. The numerical simulation of the impact of dam break on cubes is implemented. The simulation results are verified with the corresponding experimental and simulation results. Therefore, the rationality and accuracy of the DEM-SPH coupling method for numerical simulation of the interaction between granular materials and fluid media are illustrated. This method is then adopted for the impact of falling rocks on underwater pipeline. The force of water and rocks on the pipeline is analyzed. This method can be further applied for real engineering problems.

Description: The durability of lightweight cellular concrete (LCC) and the corresponding assessment method are studied in this paper to improve the utilization of LCC in subgrade construction engineering. The durability assessment method is established by combining the analytic hierarchy process (AHP) with fuzzy comprehensive evaluation (FCE). The main assessment processes are as follows. Firstly, based on the physical and mechanical properties of LCC, the influencing factors are selected in terms of preliminary design, construction technology, and operation and management after completion of construction. The grading standard of influencing factors is established as well. Secondly, a multilevel assessment model with targets level, criteria level, and indexes level is established. AHP determines the effective weight of the lower level relative to the upper level. The consistency check of the judgment matrix is conducted to prove the rationality of the distribution of influencing factors’ effect weight. Thirdly, the membership function which is suitable for each influencing factor is built to calculate the membership degree. Besides, the practicality and reliability of AHP combined with FCE are demonstrated through a practical engineering case, which is the third section of a highway in Guangdong Province, China.

Description: In this paper, the problem of input-output finite-time control of positive switched nonlinear systems with time-varying and distributed delays is investigated. Nonlinear functions considered in this paper are located in a sector field. Firstly, the proof of the positivity of switched positive nonlinear systems with time-varying and distributed delays is given, and the concept of input-output finite-time stability ( IO-FTS) is firstly introduced. Then, by constructing multiple co-positive-type nonlinear Lyapunov functions and using the average dwell time (ADT) approach, a state feedback controller is designed and sufficient conditions are derived to guarantee the corresponding closed-loop system is IO-FTS. Such conditions can be easily solved by linear programming. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed method.

Description: This paper presents the analytical modeling and simulation of an electromagnetic energy harvester (having linear behaviour) that generates power from pulsating fluid flow for pipeline condition monitoring systems. The modeled energy harvester is comprised of a cylindrical permanent magnet and a wound coil attached to a flexible membrane which oscillates due to the pulsating fluid flow in the pipe over which the prototype is considered to be mounted. In the harvester electrical energy is produced due to the relative motion between the coil and magnet. Based on the harvester’s architecture a lumped parameter model (single degree of freedom system) is developed and is simulated at different physical operational conditions. The simulation is performed at pressure amplitude of 625 Pa. When subjected to the operational frequency sweep, at the harvester’s resonant frequency (500 Hz) and damping ratio of 0.01, the devised model predicted the maximum open circuit voltage of 2.55 V and load voltage of 1.27 V. While operating under resonance, the maximum load voltage of 2.45 V is estimated at load resistance of 100 Ω. However, at an optimum load of 4.3 Ω, the simulation shows a production of 188151.2 μW power at a frequency of 500 Hz.

Description: Background. In the last decades, medicines have had an unprecedented positive effect on health, leading to reduced mortality and disease burden and consequently to an improved quality of life. The rapid and ongoing spread of antimicrobial-resistant organisms threatens our ability to successfully treat a growing number of infectious diseases. In the absence of the development of new generations of antibiotic drugs, appropriate use of existing antibiotics is needed to ensure the long-term availability of effective treatment for bacterial infections. Irrational use of antibiotics is an ongoing global public health problem that deserves more attention. This review is conducted to evaluate the prevalence of inappropriate antibiotic utilization and resistance to antibiotics in Ethiopia. Methods. Electronic search in PubMed/MEDLINE and Google was used to find published literature with reference lists of relevant articles searched manually. Titles and abstracts were initially screened for eligibility. The full texts of articles judged to be eligible were reviewed if they meet the inclusion criteria. Data were extracted on important variables like the sample size, region of the study, the inappropriate antibiotic use, bacterial detection rate, multidrug resistance pattern, and more other variables. Microsoft Excel was used for data extraction. Quantitative analysis was performed using STATA version 11. Results. The electronic searches identified 193 articles of which 33 were found eligible. The random-effects model was used to provide point estimates (with 95% confidence interval (CI)) of bacterial detection rate, inappropriate antibiotic use, and multidrug resistance rate to account for heterogeneity. The pooled bacteria detection rate was 29.1 with 95% CI (16.6–41.7). The pooled prevalence of multidrug resistant strains identified was 59.7% (95% CI: 43.5–75.9). The pooled estimate of inappropriate antibiotic use was 49.2% (95% CI: 32.2–66.2). The pooled proportion of self-antibiotic prescription was 43.3% (95% CI: 15.7–70.9). Other reasons for inappropriate antibiotic use included a wrong indication, wrong duration, improper route of administration, use of leftover antibiotics from a family member, and immature discontinuation of antibiotics. Conclusion and Recommendations. Inappropriate antibiotic use is a huge problem in Ethiopia, and many bacteria were resistant to commonly used antibiotics and similarly, multidrug-resistant bacterial strains are numerous. Appropriate antibiotic use should be ensured by prohibiting over-the-counter sale of antibiotics and strengthening antimicrobial stewardship.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 9, September 2019. 〈br/〉Wireless sensor networks have drawn tremendous attentions from all fields because of their wide application. Maximizing network lifetime is one of the main problems in wireless sensor networks. This article proposes an energy-efficient routing protocol which adopts unequal clustering technology to solve the hot spots problem and proposes double cluster head strategy to reduce the energy consumption of head nodes in the clusters. In addition, to balance the energy consumption between cluster heads and cluster members, a hybrid cluster head rotation strategy based on time-driven and energy-driven is proposed, which can make the timing of rotation more reasonable and the energy consumption more efficient. Finally, we compare the proposed protocol with LEACH, DEBUC, and UCNPD by simulation experiments. The simulation results prove that our proposed protocol can effectively improve the performance in terms of network lifetime, energy consumption, energy balance, stability, and throughput.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 9, September 2019. 〈br/〉Wireless sensor networks require time synchronization, which is the coordination of events or actions to make a system operate in unison. In this work, real experiments and a theoretical analysis of the behavior of the clock sources, most used in wireless sensor networks, have been carried out. The experiments have been performed on two real platforms from two different manufacturers in real environments with sudden changes in temperature. Complementary metal-oxide-semiconductor oscillators have a low accuracy, bigger than 500 ppm, and a high dependency with temperature. External crystal oscillators have good accuracy, around 20 ppm, and are stable with temperature. Temperature-compensated crystal oscillators are very accurate, around 5 ppm, and the temperature has no influence in their drift. The use of phase-locked loop circuits minimizes the impact of temperature and stabilizes oscillators. We highlight and demonstrate the importance of the early stages of design, especially the selection of the clock source, because that decision has a great impact on the performance of the time synchronization in wireless sensor networks.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 9, September 2019. 〈br/〉Smart grids have recently attracted increasing attention because of their reliability, flexibility, sustainability, and efficiency. A typical smart grid consists of diverse components such as smart meters, energy management systems, energy storage systems, and renewable energy resources. In particular, to make an effective energy management strategy for the energy management system, accurate load forecasting is necessary. Recently, artificial neural network–based load forecasting models with good performance have been proposed. For accurate load forecasting, it is critical to determine effective hyperparameters of neural networks, which is a complex and time-consuming task. Among these parameters, the type of activation function and the number of hidden layers are critical in the performance of neural networks. In this study, we construct diverse artificial neural network–based building electric energy consumption forecasting models using different combinations of the two hyperparameters and compare their performance. Experimental results indicate that neural networks with scaled exponential linear units and five hidden layers exhibit better performance, on average than other forecasting models.

Description: International Journal of Distributed Sensor Networks, Volume 15, Issue 9, September 2019. 〈br/〉Home-based multi-sensor Internet of Things, as a typical application of Internet of Things, interconnects a variety of intelligent sensor devices and appliances to provide intelligent services to individuals in a ubiquitous way. As families become more and more intelligent, complex, and technology-dependent, there is less and less need for human intervention. Recently, many security attacks have shown that Internet home-based Internet of Things have become a vulnerable target, leading to personal privacy problems. For example, eavesdroppers can acquire the identity of specific devices or sensors through public channels, which is not secure, to infer individual public life in the home area network. Authentication is the essential portion of many secure systems processing of verifying and declaring identity. Before providing confidential information, home-based-Internet of Things service authenticates users and devices. The communication and processing capabilities of intelligent devices are limited. Therefore, in home-based Internet of Things, lightweight authentication and key agreement technology are very important to resist known attacks. This article proposes an anonymous authenticated key agreement protocol using pairing-based cryptography. The protocol proposed in this article provides lightweight computation and ensures the security of communication between home-based multi-sensor Internet of Things network and Internet network.

Description: Several experimental proposals expect to confirm the recent measurement of the coherent elastic neutrino-nucleus scattering (CEvNS). Motivated in particular by the next generation experiments of the COHERENT collaboration, we study their sensitivity to different tests of the Standard Model and beyond. We analyze the resolution that can be achieved by each future proposed detector in the measurement of the weak mixing angle; we also perform a similar analysis in the context of Nonstandard Interaction (NSI) and in the case of oscillations into a sterile neutrino state. We show that future perspectives are interesting for these types of new physics searches.

Description: An urban agglomeration (shorted as UA) is a highly developed spatial form of integrated city and an important driving force for regional economic development. The network of UA mainly reflects the spatial connections and organizational structure of all cities, which is of great significance for understanding the development status of UAs and revealing their development laws. However, there are few horizontal studies comparing the network structure of China’s UAs. This study constructs the economic network of China’s eight UAs with the gravity model and explores the overall network structure and city centrality using indicators in network analysis. Then, two groups of UAs with similar network structures are compared. Finally, the association between the gravity model and empirical data is discussed. The results show that the spatial pattern of cities in UAs can be expressed by the gravity model approximately. Besides, UAs with different development levels present different spatial network structures, but the network structures cannot reflect the development levels of UAs directly. We also find that the cities with high betweenness centrality have greater development potential to be the next growth pole.

Description: Due to the equipment characteristics (for example, the crane of each span cannot transfer products directly to other spans and path has less turning points and no slash lines) in a slab library, slab transportation is mainly realized by manually operating the crane. Firstly, the grid method is used to model the slab library. Secondly, an improved ant colony algorithm is proposed. The algorithm is used to solve the path planning of the slab library crane, which is improved by integrating the turning points, filtering the candidate solutions, dynamically evaporating pheromone, setting the dynamic region, etc. Finally, the algorithm is applied to plan the crane path of the slab library. The results show that the obstacle-free optimal path with fewer turning points, no slash lines, and short paths is found automatically.

Description: Ground penetrating radar (GPR), as a kind of fast, effective, and nondestructive tool, has been widely applied to nondestructive testing of road quality. The finite-difference time-domain method (FDTD) is the common numerical method studying the GPR wave propagation law in layered structure. However, the numerical accuracy and computational efficiency are not high because of the Courant-Friedrichs-Lewy (CFL) stability condition. In order to improve the accuracy and efficiency of FDTD simulation model, a parallel conformal FDTD algorithm based on graphics processor unit (GPU) acceleration technology and surface conformal technique was developed. The numerical simulation results showed that CUDA-implemented conformal FDTD method could greatly reduce computational time and the pseudo-waves generated by the ladder approximation. And the efficiency and accuracy of the proposed method are higher than the traditional FDTD method in simulating GPR wave propagation in two-dimensional (2D) complex underground structures.

Description: The behavior of a fine-grained piezoelectric coating/substrate with multiple Griffith interface cracks under electromechanical loads is investigated. In this work, double coupled singular integral equations are proposed to solve the fracture problems. Both the singular integral equation and single-valued conditions are simplified into an algebraic equation and solved by numerical calculation. Thereby, the intensity factors of electric displacement and stress obtained are used to obtain the expression of the energy release rate. Furthermore, numerical results of the energy release rate with material parameters are demonstrated. Based on the obtained results, it could be concluded that the energy release rate is closely related to the size of the interface cracks and the mechanical-electrical loading. For a bimaterial structure, the fine-grained piezoelectric structure exhibited better material performance compared to the large one.

Description: Weapon-target assignment (WTA) is critical to command and decision making in modern battlefields and is a typical nondeterministic polynomial complete problem. To solve WTA problems with multiple optimization objectives, a multipopulation coevolution-based multiobjective particle swarm optimization (MOPSO) algorithm is proposed to realize the rapid search for the globally optimal solution. The algorithm constructs a master-slave population coevolution model. Each slave population corresponds to an objective function and is used to search for noninferior solutions. The master population receives all the noninferior solutions from the slave populations, repairs the gaps between the noninferior solutions, and generates a relatively optimal Pareto optimal solution set. In addition, to accelerate the slave populations searching for noninferior solutions and master population repairing the gaps between noninferior solutions, the particle velocity update method is improved. The simulation results show that the proposed algorithm has higher computational efficiency and achieves better solutions than existing algorithms capable of providing a good solution. The method is suitable for rapidly solving multiobjective WTA (MOWTA) problems.

Description: In this work, a controller design technique called linear algebra based controller (LABC) is presented. The controller is obtained following a systematic procedure that is summarized in this work. In addition, the influence of additive uncertainty on the tracking error is analyzed, and a solution using integrators is proposed. A mobile robot is used as a benchmark to test the performance of the proposed algorithms. In addition, implementation to other systems such as marine vessel is referenced. In this work, the design of controllers in continuous and discrete time is included and experimental and simulation results are shown in a Pioneer 3AT mobile robot. Comparisons are also shown with other controllers proposed in the literature.

Description: Using a resonance nonlinear Schrödinger equation as a bridge, we explore a direct connection of cold plasma physics to two-dimensional black holes. Namely, we compute and diagonalize a metric attached to the propagation of magnetoacoustic waves in a cold plasma subject to a transverse magnetic field, and we construct an explicit change of variables by which this metric is transformed exactly to a Jackiw-Teitelboim black hole metric.

Description: Cutting mixed oil in product pipelines has a great influence on the economy of the pipeline operation processes. The reasonable prediction of CDMS (the concentration distribution in the mixed segment) is important for cutting mixed segments. The classical model cannot explain the tailing phenomenon well which should not be neglected during operation processes. Based on Fick’s diffusion law, a new model for calculating the diffusion coefficient is proposed in this article, which originates from the essence of the diffusion phenomenon and considers the effects of both physical properties of oil products and the turbulence. At the same time, the dynamic fluid equilibrium model of CDMS near the pipe wall is given which has considered the adsorption effect of wall roughness. Based on these two factors, a novel numerical model for simulating the quantity of tailing oil is proposed, which is solved via the characteristic method and the finite difference method. The effects of different physical properties, as well as the adsorption, on both LFMS (the length of the front of the mixed segment) and LTMS (the length of the tail of the mixed segment), are analyzed. The comparison between the simulation results and the experimental data is utilized to validate the proposed numerical model. The simulation results show that the novel model can well describe the mixed segment tailing phenomenon and also explain the mixing essence of two miscible but dissimilar fluids in the pipeline more clearly. To sum up, this model can provide theoretical guidance for the prediction of CDMS and cutting process in practical operation processes; therefore, more economic benefit can be obtained.

Description: The variation trend, failure trajectory, probability distribution, and other information vary with time and working conditions for rolling bearing vibration performance, which makes the evaluation and prediction of the evolution process difficult for the performance reliability. In view of this, the chaos theory, grey bootstrap method, and maximum entropy method were effectively fused to propose a mathematical model for the dynamic uncertainty evaluation of rolling bearing vibration performance. After reconstructing the phase space of the vibration performance time series, four local prediction methods were applied to predict the vibration values of bearings to verify the effectiveness and validity of chaos theory. The estimated true value and estimated interval were calculated using the grey bootstrap method (GBM) and maximum entropy method. Finally, the validity of the proposed model was verified by comparing the probability that the original data fall into the estimated interval with the given confidence level. The experimental results show that the proposed method can effectively predict the variation trend and failure trajectory of the vibration performance time series so as to realize the dynamic monitoring of the evolution process for rolling bearing vibration performance online.

Description: The purpose of this paper is to solve the problem of controlling of the quadrotor exposed to external constant disturbances. The quadrotor system is partitioned into two parts: the attitude subsystem and the position subsystem. A new robust integral terminal sliding mode control law (RITSMC) is designed for stabilizing the inner loop and the quick tracking of the right desired values of the Euler angles. To estimate the disturbance displayed on the -axis and to control the altitude position subsystem, an adaptive backstepping technique is proposed, while the horizontal position subsystem is controlled using the backstepping approach. The stability of the quadrotor subsystems is guaranteed by the Lyapunov theory. The effectiveness of the proposed methods is clearly comprehended through the obtained results of the various simulations effectuated on MATLAB/Simulink, and a comparison with another technique is presented.

Description: Stem cells as a therapeutic measure for the treatment of different diseases have a great potential to give rise to different mature cells as they could be used to treat HIV-1 patients when provided with the convenient factors. Thus, this paper proposes a new mathematical model, represented by a system of ODEs, to study the effect of stem cell transplantation for HIV-1 patients. Since stem cells lineage passes through many stages to become more specialized cell types, investigating (theorizing) the best stage for these cells to be engrafted was needed. The proposed system of ODEs can help medicine make the right decision about the proposed therapy.

Description: Abrupt changes in wind velocities over small distances in a lateral or vertical direction can produce wind shear which is known to have serious effects upon the performance of an aircraft. Brought about by large-scale changes in the atmospheric conditions, it is a three-dimensional flow phenomenon imposing severe velocity gradients on an aircraft from all possible directions. While it would be difficult to model an instantaneous velocity gradient in a lateral plane, a vortical flow impinging from the sides which represents a wind shear in a vertical direction is imposed on a forward-moving aircraft to investigate the effect on the aerodynamic performance. The maximum shear wind speed from the side was fixed at 0.3 times the forward velocity. After due validations under no-wind shear conditions on simpler half-reflection plane models, a BGK airfoil-based full 3D wing and the ONERA M6 3D wing model were selected for preliminary studies. The investigation was concluded using the ARA M100 wing-fuselage model.

Description: An equivalent circuit method (ECM) is proposed for the design of multilayer frequency-selective surfaces (FSSs). In contrast to the existing ECMs that were developed mainly for the analysis of the properties of a given FSS, the presented ECM aims at providing the initial design parameters of an FSS from the desired frequency response. In this method, four types of basic FSS structures are used as the building blocks to construct the multilayer FSSs, and their surface impedances in both the normal- and the oblique-incidence situations are studied in detail in order to achieve more accurate equivalent circuit (EC) representation of the entire FSS. For a general FSS design with expected frequency response, the EC parameters and the geometrical sizes of the required basic building blocks can be synthesized from a few typical S-parameter (S11/S12) samplings of the response curves via a simple least-square curve-fitting process. The effectiveness and accuracy of the method are shown by the designs of a band-pass FSS with steep falling edge and a miniaturized band-pass FSS with out-of-band absorption. The prototype of one design is fabricated, and the measured frequency response agrees well with the numerical results of the ECM and the full-wave simulations.

Description: A novel Gysel power divider with negative group delay (NGD), good matching, and low insertion loss is proposed. Resistors connected with short-circuited coupled lines (RCSCL) are shunted at output ports of the Gysel power divider to obtain NGD characteristics, and another resistor is shunted at the input port to realize perfect input and output matching. To verify the proposed structure, an NGD Gysel power divider is designed and fabricated. At the center frequency of 1.0 GHz, the measured NGD times for different output ports are −1.94 ns and −1.97 ns, the input/output port return loss is greater than 38 dB, the insertion loss is less than 8.3 dB, and the isolation between output ports is higher than 41 dB. To enhance the NGD bandwidth, two RCSCL networks having slightly different center frequencies are connected in parallel, which provides wider bandwidth with good input matching characteristics.

Description: Constant exposure of a photovoltaic (PV) panel to sunlight causes it to overheat and, consequently, its rated efficiency decreases leading to a drop in its generated power. In this study, a PV panel was tested under standard test conditions in a halogen lamp solar simulator at different solar irradiance values. The PV panel was then fitted with heat dissipating fins and measured under identical test parameters; thereafter, repurposed materials such as high-density polyethylene (HDPE) and plastic bags were, separately, added to the PV panel with fitted heat-extraction fins and the performance was evaluated again. Passively cooling the PV panel with fins and repurposed materials resulted in a 22.7% drop in the PV panel’s temperature, while an 11.6% increase in power output occurred at 1000 W m-2. Utilizing repurposed waste materials in PV cooling improves a panel’s efficiency and saves the environment from the ecological effects of dumping these materials.

Description: Lithology identification is an indispensable part in geological research and petroleum engineering study. In recent years, several mathematical approaches have been used to improve the accuracy of lithology classification. Based on our earlier work that assessed machine learning models on formation lithology classification, we optimize the boosting approaches to improve the classification ability of our boosting models with the data collected from the Daniudi gas field and Hangjinqi gas field. Three boosting models, namely, AdaBoost, Gradient Tree Boosting, and eXtreme Gradient Boosting, are evaluated with 5-fold cross validation. Regularization is applied to the Gradient Tree Boosting and eXtreme Gradient Boosting to avoid overfitting. After adapting the hyperparameter tuning approach on each boosting model to optimize the parameter set, we use stacking to combine the three optimized models to improve the classification accuracy. Results suggest that the optimized stacked boosting model has better performance concerning the evaluation matrix such as precision, recall, and f1 score compared with the single optimized boosting model. Confusion matrix also shows that the stacked model has better performance in distinguishing sandstone classes.