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Liriomyza trifolii is a significant pest of vegetable and ornamental crops across the globe. Microwave radiation has been used for controlling pests in stored products; however, there are few reports on the use of microwaves for eradicating agricultural pests such as L. trifolii, and its effects on pests at the molecular level is unclear. In this study, we show that microwave radiation inhibited the emergence of L. trifolii pupae. Transcriptomic studies of L. trifolii indicated significant enrichment of differentially expressed genes (DEGs) in ‘post-translational modification, protein turnover, chaperones’, ‘sensory perception of pain/transcription repressor complex/zinc ion binding’ and ‘insulin signaling pathway’ when analyzed with the Clusters of Orthologous Groups, Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes databases, respectively. The top DEGs were related to reproduction, immunity and development and were significantly expressed after microwave radiation. Interestingly, there was no significant difference in the expression of genes encoding heat shock proteins or antioxidant enzymes in L. trifolii treated with microwave radiation as compared to the untreated control. The expression of DEGs encoding cuticular protein and protein takeout were silenced by RNA interference, and the results showed that knockdown of these two DEGs reduced the survival of L. trifolii exposed to microwave radiation. The results of this study help elucidate the molecular response of L. trifolii exposed to microwave radiation and provide novel ideas for control.

Atopic dermatitis(AD) is a common inflammatory skin disorder induced by dysfunction of immune suppression, which resembles the mechanism of autoimmune diseases. To explore the association between autoimmune diseases and AD in their children, we linked the birth data from National Birth Registry with National Health Insurance Research Database. Demographic characteristics from 1174,941 parent-child linkages were obtained. There were 312,329 children diagnosed with AD before 5 years old, and they would be compared with the other 862,612 children without AD in the control group. Conditional logistic regression was utilized to calculate adjusted odds ratio (aOR) and 95% confidence interval (CI). After adjusting infant’s characteristics, perinatal factors, and other parental diseases, the odds ratio of parental rheumatoid arthritis(RA) was 2.269 (95% CI 1.333–3.861) and parental psoriasis was1.610 (95% CI, 1.094–2.369). Parental allergic diseases such as AD (aOR 2.071, 95% CI 1.952–2.198) and asthma (aOR 1.494, 95% CI 1.400-1.594) were also significant predictors for childhood AD. The subgroup analysis showed significant difference between children’s sex. Parental RA (aOR 3.070, 95% CI, 1.532–6.154) was crucial for boys, while parental psoriasis (aOR 1.945, 95% CI, 1.129–3.350)was a risk factor for girls. In conclusion, parental autoimmune diseases were found to be related to AD in their children before 5 years old. Additionally, there were different risk factors for AD between children’s sex.

The leafminer Liriomyza trifolii is an important insect pest of ornamental and vegetable crops worldwide. Cyromazine is an effective, commonly-used insecticide that functions as a growth regulator, but its effect on L. trifolii has not been previously reported. In this study, transcriptome analysis was undertaken in L. trifolii exposed to cyromazine. Clusters of orthologous groups analysis indicated that a large number of differentially expressed genes responding to cyromazine were categorized as "lipid transport and metabolism", "post-translational modification, protein turnover, chaperones", and "cell wall/membrane/envelope biogenesis". Gene ontology analysis indicated that pathways associated with insect hormones, growth and development, and cuticle synthesis were significantly enriched. In general, the transcriptome results showed that the genes related to insect hormones were significantly expressed after treatment with cyromazine. Furthermore, the combined exposure of L. trifolii to cyromazine and the hormone analogues 20-hydroxyecdysone (20E) or juvenile hormone (JH) indicated that hormone analogues can change the expression pattern of hormone-related genes (20EP and JHEH) and pupal length. The combined application of cyromazine with 20E improved the survival rate of L. trifolii, whereas the combination of JH and cyromazine reduced survival. The results of this study help elucidate the mechanistic basis for cyromazine toxicity and provide a foundation for understanding cyromazine resistance.

The Xinqiao Cu–S–Fe–Au deposit in the Tongling ore district, an important part of the Middle-Lower Yangtze River Valley metallogenic belt in eastern China, is located along the northern margin of the Yangtze Block. The deposit consists of two major mineralization types: stratiform and skarn (the genesis of the former is disputed). The more important stratiform orebody (90% of the total Cu, S and Fe reserves) has abundant garnet as the main gangue mineral, similar to the skarn orebody hosted in the intrusive contact. Garnets from the Xinqiao stratiform orebody range from pure andradite (And 100 ) to And 50 Gro 46 , and can be divided into the early (Grt1) and late (Grt2) generation. Both generations contain low MnO (0.19–0.89%), wide range of Y/Ho (39.0–40.7 for Grt1, 29.8–67.9 for Grt2), and do not contain melt or fluid-melt inclusions, indicative of a magmatic-hydrothermal replacement origin. Grt1 and the Grt2 cores are grandite, whilst the Grt2 rims are mainly andradite with some grandite zones. Grandite is enriched in heavy rare earth elements (HREEs), and displays low ΣLREE/ΣHREE, La N /Yb N and U concentrations with negative Eu anomalies, whereas andradite is HREE-depleted, and displays high ΣLREE/ΣHREE, La N /Yb N ratios and U concentrations with positive Eu anomalies. The distinct trace element features suggest that the hydrothermal fluids for Grt1 and the Grt2 cores were of nearly neutral (pH), relatively oxidized and HREE-enriched, whereas those for the Grt2 rims had experienced episodic inflections between a mildly acidic, relatively reduced and HREE-depleted fluid and a nearly neutral, relatively oxidized and HREE-enriched fluid. Meanwhile, they also reveal that Grt1 and the Grt2 cores may have formed by diffusive metasomatism in a closed system, whereas the Grt2 rims may have formed by infiltration metasomatism in an open fracture system, possibly related to the unconformity that hosts the Xinqiao stratiform orebody. We propose that the Xinqiao stratiform orebody may have formed from Early Cretaceous magmatic-hydrothermal fluids associated with the Jitou stock, similar to the skarn-type orebodies in the district.

The wireless sensor network (WSN) has received increasing attention since it has many potential applications such as the internet of things and smart city. The localization technology is critical for the application of the WSN. The obstacles induce the larger non-line of sight (NLOS) error and it may decrease the localization accuracy. In this paper, we mainly investigate the non-line of sight localization problem for WSN. Firstly, the Pearson's chi-squared testing is employed to identify the propagation condition. Secondly, the particle swarm optimization based localization method is proposed to estimate the position of unknown node. Finally the simulation experiments are implemented. The simulation results show that the proposed method owns higher localization accuracy when compared with other two methods.

In east Asia, “Baishouwu” has been used as an herbal drug and functional dietary supplement for hundreds of years. Actually, “Baishouwu” is the common name of the roots of Cynanchum auriculatum, Cynanchum bungei, and Cynanchum wilfordii. In the present study, roots of these three specie were extracted and then fractionated using petroleum ether (PE), dichloromethane (DCM), ethyl acetate (EA), and water. DPPH scavenging experiments revealed high antioxidant activity of DCM and EA fractions of C. bungei and the EA fraction of C. wilfordii. Treatments with these three fractions significantly reduced malondialdehyde content in heat‐stressed Daphnia magna, validating in vivo antioxidant activity. Gas chromatography–mass spectrometer (GC‐MS) analyses demonstrated that the chemical components of fractions extracted from C. bungei, C. bungei, and C. wilfordii were different. Further determination of total phenol and total flavonoids contents showed that DCM and EA fractions of C. bungei and EA fraction of C. wilfordii had much higher contents of total phenol and total flavonoids, which might be the reason to explain their strong antioxidant activity. Overall, the present study suggested that these three plants have different chemical components and biological activities. They could not be used as the same drug.

The existing object tracking method using covariance modeling is hard to reach the desired tracking performance when the deformation of moving target and illumination changes are drastic, we proposed a object tracking algorithm based on bilateral filtering. Firstly, the algorithm deals the image to be tracked with bilateral filtering, and extracts the needed features of filtered image to construct covariance matrix as tracking model. Secondly, under log-Euclidean Riemannian metric, we construct similarity measure for object covariance matrix and model updating strategy. Extensive experiments show that the proposed method has better adaptability for object deformation and illumination changes.

The paper researches on the comparison of two metrics methods under Riemannian metric and under Log-Euclidean metric respectively. Firstly, Experiments are done for comparing the distance and mean values worked out under the two metrics. And the time required for computing under these two metrics is also shown. Lastly, the two methods are applied to the field of image tracking. The performance of the two methods is compared, and the time required for tracking each frame is gained. Experiments results show that the two methods can gain similar distance and mean values, and similar tracking results, while the time required under Log-Euclidean metric is less than under Riemannian metric.

Because the direction goals of the snake robot are different in applications, e.g. the target point and target path, the direction control of a snake robot is a challenging problem. We have proposed a control method, which is called passive creeping based on the energy balance. In this paper, the direction of the snake robot which is controlled by the passive creeping control method is discussed. A new direction control method which is based on the torque compensation is proposed. The direction control method set a universal direction goal for all the applications. The torque of the head joint which leads the locomotion direction is adjusted by the torque compensation. The compensated torque decreases the angle between the direction of the body axis and the expected direction by the exponential decay function. In simulation, the trajectory and the angle express the process of direction adjustment. The error analysis proves the validity and adaptability of the proposed direction control. Also the validity of the proposed method is proved by the experiment which is based on the virtual/physical mixed experimental system.

The characteristics of interaction between WT wheelchair robot and stair environments is analyzed and possible patterns of WT wheelchair robot during the stairs climbing are summarized, and then the criterion to determine the pattern of the wheelchair robot is proposed. STATEFLOW module in MATLAB is used to simulating the whole stair-climbing of WT wheelchair robot, and an entire analytical procedure about how to determine the pattern by using the simulation curves is given.

Considering the process of objects imaging in the camera is essentially the projection transformation process. The paper proposes a novel visual tracking method using particle filtering on SL(3) group to predict the changes of the target area boundaries of next moment, which is used for dynamic model. Meanwhile, covariance matrices are applied for observation model. Extensive experiments prove that the proposed method can realize stable and accurate tracking for object with significant geometric deformation, even for nonrigid objects.

The Linearized Auto-Localization (LAL) algorithm estimates the position of beacon nodes in Local Positioning Systems (LPSs) which are based on the transmission of ultrasonic signals and proposed for indoor positioning of mobile robots. In this paper we propose an improved auto-localization algorithm based on weighted least squares (WLS). The improved algorithm depends on the different error estimations which caused by the different relative positions of the beacons and the measurements nodes. Simulation results show that our WLS-based Linearized Auto-Localization Algorithm can provide improved accuracy in both distance estimation and position estimation.

In order to obtain the actual characteristics of horizontal atmospheric diffusion direction, based on Gauss plume model and the measured data, we use BP neural network to fit the characteristic curve of the diffusion coefficient. We establish a BP neural network, and then we train the network and simulate the diffusion coefficient. According to the simulation results, we compare the characteristic curve with the curve based on the least square method. And the results show that the characteristic curve based on BP neural network has better fitting accuracy. Hence, using the trained neural network to predict the diffusion coefficient has certain theory meaning and actual application value.

For many applications in wireless sensor network (WSN) node positioning by unmanned aerial vehicle (UAV) need a path planning algorithm optimizing positioning error. In this article, we present an algorithm combining Voronoi diagram and geometric dilution of precision (GDOP) to make track points, considering both the efficiency of flying and accuracy of positioning. Then, we connect all the track points using genetic algorithm and we get the minimized flight path.

This paper describes an efficient Bayesian framework for localization based on Ultra-wide Bandwidth (UWB) system. Approximate grid-based method based on the Hidden Markov Model (HMM) is an effective method to estimate the position of the Moving Terminal (MT) with the mixed line-of-sight/non-line-of-sight (LOS/NLOS) situation. This article proposes an algorithm by modifying the Position Transition Probability (PTP) according to the practical dynamic model and uses the information fusion effectively. We compare the Maximum Likelihood (ML) estimation with Detection/Tracking Algorithm (D/TA) estimation and its improved algorithm by simulation, in which the localization to an identical trajectory has been tested. The results of the analysis show that the proposed method has better accuracy and stability.

In wireless sensor networks, NLOS propagation often enlarges the errors of position estimates when time-of-arrival (TOA) measurements are used. To mitigate the effects caused by NLOS propagation, herein, an EKF-based robust non-parametric approach is proposed. In this paper, we utilize the variable kernel method to obtain an approximate noise density function, which is inexpensively computational and then used to improve the mobile positioning accuracy. Note that the standard EKF often works well when NLOS error is adequately low. This property could also be used to improve the accuracy of mobile positioning. In the proposed algorithm, a hard decision is employed to choose the rational position estimate which may come from the non-parametric approach or the standard EKF. Numerical simulations show a significant improvement over the standard EKF.

There exist some mobile node localization algoriths in wireless sensor netwok,which require high computation and specialized hardware and high node large density of beacon nodes.The Monte Carlo localization method has been studied and an improved Monte Carlo node localization has been proposed. Predicting the trajectory of the node by interpolation and combing sampling box to sampling. The method can improve the efficiency of sampling and accuracy. The simulation results show that the method has achieved good localization accuracy.

To satisfy the requirement of the control parameters in greenhouse, this paper introduced the design scheme of monitoring and control system based on Zigbee due to its low-cost, simplicity and mobility. We designed the sensor node, control node and gateway node based on CC2430, described the design method of hardware circuit and the flow chart of software. By monitoring the environment factors in real time, such as illumination, temperature, humility and carbon dioxide, the spray system, ventilation fans and lighting lamps were automated controlled to satisfy crop growth requirement. The monitoring system is easy to expand and update, and the program interface is friendly to operate.

In view of the detection of moving object in video sequence, the traditional moving object detection algorithms are researched. The paper presents a new algorithm for object detection based on initial contour and improved variational GAC model. First, this method built up background model utilizing Gaussian mixture model and background subtraction to extract initial contour of the object; taking initial contour as initial value of curve evolution. Then, an improved restriction item is introduced into variational GAC vector model, the proposed restriction item that is a nonlinear hear equation with normalized diffusion rate, therefore re-initialization procedure of level set function is completely eliminated. Iteration number of curve evolution and run time is reduced. The experimental show that accurate contour of moving object is got and this algorithm is effective and feasible in real video environment.

The robot joints are usually rotational axis by two link joints, bionic features is not strong. The shortcomings of intelligent MR damper control multi-axis bionic knee can only provide resistance and certain sizes of regain momentum, cannot provide larger power, therefore this paper gives by the multi-axis four-bar structure, ball screw transmission hybrid drive multiaxial bionic active knee institutions. And analysis the human leg institutions and commonly used two-bar structure, solve the ball screw transmission installation location parameters. And established based on hybrid drive of the bionic active the knee's virtual prototype.

Node localization is one of the key technologies in wireless sensor networks,DV-Hop algorithm is wildly usded .The main DV-Hop localization error is the distance between unknown nodes ande anchor nodes.In this paper, The distance geometry constrain in two-dimensional space has been applied to reduce the error of measurement ,which is the distance between unknown nodes and anchor nodes. Simulation results show that this localization algorithm is effective ,which improves the positioning accuracy.

The effects of brazing temperature on microstructure and mechanical properties of vacuum brazed joints of 316L stainless steel were studied. Choose three soldering temperature. After soldering, observed the microstructure, element distribution, microhardness and shear strength of welding clearance. The results show that the welding temperature for 940 °C, the brazing clearance organization mainly by Ni-Cr-P phase composition. Joint performance is poor, element can't get enough spread. P element does not spread easily, mainly in the brazing clearance; Cr element can spread along the grain boundary into mother material; the ability of spread of Ni elements is less than the Cr element. While welding temperature of 970 °C, the shear strength is the highest, and the comprehensive performance is the best.

Vacuum brazing of 316L stainless steel with BNi-2 brazing filler metal.The effects of brazing temperature and brazing clearance on microstructure and mechanical properties of vacuum brazed joints of 316L stainless steel were studied. The results show that: As brazing temperature being 1 070 °C, with the increasing of the brazing clearance, the joint shear strength value become lower and lower. Brazing clearance compounds mainly contain intermetallic and solid solutions.

The robot joints are usually rotational axis by two link joints, bionic features is not strong. The shortcomings of intelligent MR damper control multi-axis bionic knee can only provide resistance and certain sizes to regain momentum, cannot provide larger power, therefore this paper gives by the multi-axis four-bar structure, ball screw transmission multiaxial bionic active knee institutions. And analysis the human leg institutions and commonly used two-bar structure, through multi-variable optimization method to solve the design parameters of knee joint structure, the motor angular velocity and torque. And established in a bionic active the knee's virtual prototype.

This paper proposed a preprocessing method of SWCNTs dispersion based on rinsing technology. With the assistance of SDS, SC and SDBS, this method adopted the ultrasonication oscillation technology to solve the problem of SWCNTs dispersion. In addition, it compared the effect of the three kinds of surfactants on SWCNTs dispersion under the same conditions. And AFM was applied in this experiment to scan and image the samples. The results showed that the solubility and adsorption efficiency of the surfactants had influence on the SWCNTs dispersion quality. Furthermore, the paper primarily and theoretically modeled and analyzed the experiment results from the aspect of the surfactants' hydrophilic and lipophilic structure.

Passive AKPs being currently in use do not respond to the needs of daily living activities of many amputees. For example, it is difficult to climb stairs with natural posture and to adjust the stiffness of the knee joint motion during the swing phase. Therefore this paper proposes the instantaneous center with variable rotating multiaxial knee, the multiaxial four league rod mechanism composition, have bionic similarity, involving active knee mechanism design and experiment. Artificial limb main part is through motor based on active control knee flexion knee actuator.This paper was designed by the ball screw electric a new initiative knee institutions.

A new computer-aided detection (CAD) scheme for detecting lung nodules is proposed in this paper. Firstly, the lung region is segmented from the CT data using adaptive threshold algorithm etc; Secondly, building active contour model to segment and remove lung vessel accurately in the lung region; Next, suspicious nodules are detected and omitted renal vessel is filtered using a selective shape filter; Finally, nodule features are extracted and rule-based classifier is used to distinguish true or false positive nodules. Experiment results indicate that this scheme can help radiologist improve the diagnosis efficiency.

Single-wall carbon nanotubes are candidates for a number of building blocks in nanoscale electronics. With respect to the assembly of carbon nanotube field effect transistor, the dielectrophoresis technology is adopted, which assembles SWCNTs between the micro-electrodes, SWCNTs are affected by the electrophoretic force which is carried out by the related theoretical analysis in a nonuniform electric field. The driving electric field of dielectrophoresis is simulated by the comsol software. According to the simulation results, a number of the experiments are done. It turns out that the required experimental parameters of the efficient assembly of SWCNT were obtained. AFM scanning and electrical properties of SWCNTs show that the method can achieve the effective assembly of carbon nanotube field effect transistor. SWCNTs are driven in the microelectrode gap, having a good arrangement of uniform orientation and assembly results, and proportional to the arrangement density along the electrode width direction and the duration of DEP. Meanwhile, it also provides an effective method of assembly and manufacture for other one-dimensional nanomaterials assembly of nanoelectronic devices.

The interactive approach to virtual system is a hot research topic. This paper presents a novel interactive approach based on hand gesture recognition. The hand gesture segmentation method is based on the adaptive background model. The method improves the ability of adaptation environment. And an improved algorithm of hand recognition is presented by using Fourier Descriptor and BP neural network. Experiment results indicate that the approach is flexible, realistic and exact.

To work out route guidance in gigantic traffic network, the traffic information forecasting method based on Artificial Neural Network is studied in-depth and the time-varied road weight matrixes are constructed, which solve the problem of limitation in traditional and static road weight. The Parallel Genetic Algorithm (PGA) for optimal route choice is discussed in this paper and the corresponding genetic operator, mutation operator and the refresh way of the populations are also proposed. A method of Rectangle Restricted Searching Area (RRSA) which can reduce the searching area of PGA is presented. The problem of bad real-time and astringency of PGA existed in computing the optimal route in gigantic traffic network has also been solved using RRSA. To probe into the technology of the Route Guidance, a large number of experiments combined with the required analysis of the results have been carried on. It is indicated by simulation that the presented method of optimal route choice has achieved the accuracy, real-time and quick guidance in gigantic traffic network.

In this paper, a hybrid method based on rough sets and genetic algorithms, is proposed to improve the speed of robot path planning. Decision rules are obtained using rough set theory. A series of available paths are produced by training obtained minimal decision rules. Path populations axe optimised by using genetic algorithms until the best path is obtained. Experiment results show that this hybrid method is capable of improving robot path planning speed.

Variable precision rough sets (VPRS) is used to reduce the redundant features in terms of its ability of knowledge reducts. An improved network algorithm including additional momentum, self-adaptive learning rate and dynamic error segmenting is presented to solve the shortcomings of traditional BP neural network (NN). The reduced features after VPRS are fed into the improved neural network proposed to inspect the defects of surface for wood veneer, which results in short training time and a high classification accuracy with a typical application in defect inspection of wood veneer.

An automatic inspection method based on rough set theory, fuzzy set and an improved BP algorithm is presented. The rough set method is used to remove redundant features for its data analysis and procession ability. The reduced data is fuzzified to represent the feature data in a more suitable form as input data of a BP network classifier. By the experimental research, the hybrid method shows good classification accuracy and short running time, which are better than the results using BP network and neural network with fuzzy input.

Variable precision rough sets (VPRS), as a extension of rough sets (RS) is adopted to reduce the redundant features for its ability of more useful information adopted compared with RS. The reduced features after VPRS are fed into the improved BP network proposed to inspect the defects of surface quality, which results in short training time and a high classification accuracy with a typical application in defect inspection of wood veneer.

A vision-based inspection method based on rough set theory, fuzzy set and neural network algorithm is presented. The rough set method is proposed to remove redundant features for its data analysis and processing. The reduced data is fuzzified to represent the feature data in a more suitable form for input to a BP network classifier. The BP neural classifier is considered the most popular, effective and easy-to-learn model for complex, multi-layered network. By the experiment research, the hybrid method shows good classification accuracy and short running time, which are better than the results using BP network and neural network with fuzzy input

A detailed DSPN (deterministic and stochastic Petri net) model and performance analysis of WorldFIP MAC sub-layer is constructed in this paper. Firstly, the MAC mechanism of WorldFIP is introduced. Secondly, the accurate modeling of WorldFIP MAC is constructed by using DSPN. Thirdly, the simulation research based on the DSPN model is developed, which gets some valuable quantitative results of WorldFIP system.

To solve the shortcomings of the traditional BP network, the improved algorithm is presented to accelerate the training and improve the accuracy, and reduce the possibility of getting into the local minimum. For optimal network structure, the UD method is introduced to optimise the parameters, and the 'best' level-combination is obtained so that the performance of the classifier is further improved.

Reconstruction of human action plays an important role in the field of image processing. In this paper, a new algorithm based on locally linear embedding (LLE) and kernel ridge regression (KRR) is proposed for the reconstruction of human action. On one hand, the images of colour and depth information are used to extract the human skeleton so that the training set of actions can be established. On the other hand, the training set is turned into an action vector library. Combined with the LLE algorithm, the human action of low-dimensional manifolds can be evaluated and the data of manifolds can be analysed. Furthermore, the human action can be reconstructed according to the KRR algorithms while the predicted convergence points of low-dimensional are inverse-mapped back to the high-dimensional Euclidean space. A lot of real experiments have been done to show that the proposed method of reconstruction of human action is greatly effective.