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The limited electrical performance of microelectronic devices caused by low inter-particle connectivity and inferior printing quality is still the greatest hurdle to overcome for Aerosol jet printing (AJP) technology. Despite the incorporation of carbon nanotubes (CNTs) and specified solvents into functional inks can improve inter-particle connectivity and ink printability respectively, it is still challenging to consider multiple conflicting properties in mixture design simultaneously. This research proposes a novel hybrid multi-objective optimization method to determine the optimal functional ink composition to achieve low electrical resistivity and high printed line quality. In the proposed approach, silver ink, CNTs ink and ethanol are blended according to mixture design, and two response surface models (ReSMs) are developed based on the Analysis of Variance. Then a desirability function method is employed to identify a 2D optimal operating material window to balance the conflicting responses. Following that, the conflicting objectives are optimized in a more robust manner in the 3D mixture design space through the integration of a non-dominated sorting genetic algorithm III (NSGA-III) with the developed ReSMs and the corresponding statistical uncertainty. Experiments are conducted to validate the effectiveness of the proposed approach, which extends the methodology of designing materials with multi-component and multi-property in AJP technology. Published version This work was partly supported by the Major Projects of Natural Science Research in Universities of Anhui Province [grant number KJ2021ZD0137], Key Natural Science Project of Anhui Provincial Education Department [grant number KJ2021A1111] and partly by Doctoral Research Startup Project of Suzhou University [grant number 2021BSK023].

Supplemental material, sj-docx-1-ijb-10.1177_13670069231170142 for The effect of cognitive load on code-switching by Hong Liu, Zhixin Liu, Meng Yuan and Tingyu Chen in International Journal of Bilingualism

Psychiatric diseases, such as schizophrenia, bipolar disorder, autism spectrum disorder, and major depressive disorder, place a huge health burden on society. Cognitive impairment is one of the core characteristics of psychiatric disorders and a vital determinant of social function and disease recurrence in patients. This review thus aims to explore the underlying molecular mechanisms of cognitive impairment in major psychiatric disorders and identify valuable biomarkers for diagnosis, treatment and prevention of patients.

Originally developed for metrology, optical frequency combs are becoming increasingly pervasive in a wider range of research topics including optical communications, spectroscopy, and radio or microwave signal processing. However, application demands in these fields can be more challenging as they require compact sources with a high tolerance to temperature variations that are capable of delivering flat comb spectra, high power per tone, narrow linewidth and high optical signal-to-noise ratio. This work reports the generation of a flat, high power frequency comb in the telecom band using a 17 mm fully-integrated silicon core fibre as a parametric mixer. Our all-fibre, cavity-free source combines the material benefits of planar waveguide structures with the advantageous properties of fibre platforms to achieve a 30 nm bandwidth comb source containing 143 tones with 30 dB OSNR over the entire spectral region.

Objectives: This study aimed to identify novel biomarkers for osteoarthritis (OA) and explore potential pathological immune cell infiltration.Methods: We identified differentially expressed genes (DEGs) between OA and normal synovial tissues using the limma package in R, and performed enrichment analyses to understand the functions and enriched pathways of DEGs. Weighted gene co-expression network analysis (WGCNA) and distinct machine-learning algorithms were then used to identify hub modules and candidate biomarkers. We assessed the diagnostic value of the candidate biomarkers using receiver operating characteristic (ROC) analysis. We then used the CIBERSORT algorithm to analyze immune cell infiltration patterns, and the Wilcoxon test to screen out hub immune cells that might affect OA occurrence. Finally, the expression levels of hub biomarkers were confirmed by quantitative reverse transcription-polymerase chain reaction (qRT-PCR).Results: We identified 102 up-regulated genes and 110 down-regulated genes. The functional enrichment analysis results showed that DEGs are enriched mainly in immune response pathways. Combining the results of the algorithms and ROC analysis, we identified GUCA1A and NELL1 as potential diagnostic biomarkers for OA, and validated their diagnosibility using an external dataset. Construction of a TF-mRNA-miRNA network enabled prediction of potential candidate compounds targeting hub biomarkers. Immune cell infiltration analyses revealed the expression of hub biomarkers to be correlated with CD8 T cells, memory B cells, M0/M2 macrophages, resting mast cells and resting dendritic cells. qRT-PCR results showed both GUCA1A and NELL1 were significantly increased in OA samples (p < 0.01). All validations are consistent with the microarray hybridization, indicating that GUCA1A and NELL1 may be involved in the pathogenesis of OA.Conclusion: The findings suggest that GUCA1A and NELL1, closely related to OA occurrence and progression, represent new OA candidate markers, and that immune cell infiltration plays a significant role in the progression of OA.

Time delay and Doppler shift between the echo signal and the reference signal are two most commonly used measurements in target localization for the passive radar. Doppler rate, which can be obtained from the extended cross ambiguity function, offers an opportunity to further enhance the localization accuracy. This paper considers using the measurement Doppler rate in addition to measurements of time delay and Doppler shift to locate a moving target. A closed-form solution is developed to accurately and efficiently estimate the target position and velocity. The proposed solution establishes a pseudolinear set of equations by introducing some additional variables, imposes weighted least squares formulation to yield a rough estimate, and utilizes the function relation among the target location parameters and additional variables to improve the estimation accuracy. Theoretical covariance and Cramer-Rao lower bound (CRLB) are derived and compared, analytically indicating that the proposed solution attains the CRLB. Numerical simulations corroborate this analysis and demonstrate that the proposed solution outperforms existing methods.

Additional file 1: Supplementary Table.Definition and coding of variables.

This paper considers the distributed sparse identification problem over wireless sensor networks such that all sensors cooperatively estimate the unknown sparse parameter vector of stochastic dynamic systems by using the local information from neighbors. A distributed sparse least squares algorithm is proposed by minimizing a local information criterion formulated as a linear combination of accumulative local estimation error and L_1-regularization term. The upper bounds of the estimation error and the regret of the adaptive predictor of the proposed algorithm are presented. Furthermore, by designing a suitable adaptive weighting coefficient based on the local observation data, the set convergence of zero elements with a finite number of observations is obtained under a cooperative non-persistent excitation condition. It is shown that the proposed distributed algorithm can work well in a cooperative way even though none of the individual sensors can fulfill the estimation task. Our theoretical results are obtained without relying on the independency assumptions of regression signals that have been commonly used in the existing literature. Thus, our results are expected to be applied to stochastic feedback systems. Finally, the numerical simulations are provided to demonstrate the effectiveness of our theoretical results., Comment: 15 pages, 2 figures, submitted to Automatica

The evolved Multimedia Broadcast Multicast Services, eMBMS (evolved Multimedia Broadcast Multicast Service), promises to be a powerful method for distributing common multimedia content. However, rapid deployment of 5G broadcating services in China cannot be supported by eMBMS due to the obstacles of regional simple deployment and one-way interface between core network and RAN (Radio Access Network) side. This article fills the gap by describing solutions for new core network architecture. Two innovative solutions realize the control plane function. The proposed architecture alternative satisfies the objective needs of radio and television service deployment in China and reduces the complexity of signaling processing, which is favorable for collaborative coverage of broadcast and unicast.

Tilapia lake virus (TiLV) is the main tilapia-infecting virus worldwide, causing serious economic losses. However, there is no vaccine for this viral disease. Here, TiLV ORF10 (TiLV-ORF10) encoding a protein with abundant epitopes was constructed into the eukaryotic expression vector pcDNA3.1, and used to evaluate the immune protective effects in Nile tilapia (Oreochromis niloticus). RT-PCR and western blot analyses confirmed vaccine plasmid expression in tilapia muscle tissues. Moreover, the transcription levels of immunoglobulin M, toll-like receptor 2, myeloid differentiation factor 88, interleukin 8, tumor necrosis factor alpha, gamma-IFN, and nuclear factor κB immune-related genes were statistically significantly upregulated in the spleen, liver, and kidney of vaccinated tilapias (P < 0.05). TiLV challenge experiments showed that relative percent survival (RPS) was significantly enhanced in fish by this DNA vaccine. Moreover, RPS was enhanced further when using a higher amount of the DNA vaccine (85.72% RPS at a DNA dose of 45 μg pcDNA3.1–ORF10). Vaccination with pcDNA3.1–ORF10 significantly reduced virus replication, as evidenced by the low amount of virus in the spleen, liver, and kidney of vaccinated tilapias after TiLV challenge. Thus, pcDNA3.1–ORF10 could induce protective immunity in tilapia and may be a potential vaccine candidate for controlling diseases caused by TiLV.

Working environment of mechanical operators is complex, and the amount of process monitoring video information is large, which brings serious interference for human body target recognition of abnormal behavior. The algorithm is more complex, and the reaction time is longer. Through the analysis and comparison of image RGB model, YUV model and gray processing, when segmenting video sequence image, transforming RGB color image into gray image is conducive to image recognition. When the scene background is complex, the image can be analyzed in the normalized RGB color space, which can effectively eliminate the influence of shadow. The filtering denoising of Gaussian low-pass filter and median filter are analyzed, which have good denoising effect. It is very suitable for image preprocessing and denoising after recognition. Through the analysis of morphology operation such as corrosion and expansion, the cavity problem can be effectively improved. Before the target detection, preprocessing the target video sequence by computer graphics method can highlight the useful image characteristics and remove the useless image information, which can help to improve the detection effect.

High frequency of safety accidents in the process of mechanical production has brought great pressure and loss to the social economy. Relevant statistics show that the proportion of illegal operation of operators is the main factor. In order to reduce the occurrence of safety accidents, the computer vision research technology based on monitoring video is applied to the direction of mechanical safety behavior recognition. The content of abnormal behavior of mechanical operators is relatively broad. A foundation for the subsequent simulation analysis can be formed through extracting the characteristics of the actor, calculating the characteristic operator of human behavior, and debugging and modifying the threshold value of the characteristic operator for judging the abnormal behavior.

Liu, Zhixin, Xiao, Xiao, Wei, Xiuli, Li, Jian, Yang, Jing, Tan, Huabing, Wu, Jianguo, Liu, Long (2020): Composition and divergence of coronavirus spike proteins and host ACE2 receptors predict potential intermediate hosts of SARS- CoV-2. Journal of Medical Virology 7: 1-7, DOI: 10.1002/jmv.25726

Space division multiplexing using multi-core fiber (MCF) is a promising solution to cope with the capacity crunch in standard single-mode fiber based optical communication systems. Nevertheless, the achievable capacity of MCF is limited by inter-core crosstalk (IC-XT). Many existing researches treat IC-XT as a static interference, however, recent research shows that IC-XT varies with time, wavelength and baud rate. This inherent stochastic feature requires a comprehensive characterization of the behaviour of MCF to its application in practical transmission systems and the theoretical understanding of IC-XT phenomenon. In this paper, we experimentally investigate the IC-XT behaviour of an 8-core trench-assisted MCF in a temperature-controlled environment, using popular modulation formats. We compare the measured results with the theoretical prediction to validate the analytical IC-XT models previously developed. Moreover, we explore the effects of the measurement configurations on the IC-XT accuracy and present an analysis on the IC-XT step distribution. Our results indicate that a number of transmission parameters have significant influence on the strength and volatility of IC-XT. Moreover, the averaging time of the power meter and the observation time window can affect the value of the observed IC-XT, the degrees of the effects vary with the type of the source signals., Comment: 14 pages

This paper presents a novel neural network design that learns the heuristic for Large Neighborhood Search (LNS). LNS consists of a destroy operator and a repair operator that specify a way to carry out the neighborhood search to solve the Combinatorial Optimization problems. The proposed approach in this paper applies a Hierarchical Recurrent Graph Convolutional Network (HRGCN) as a LNS heuristic, namely Dynamic Partial Removal, with the advantage of adaptive destruction and the potential to search across a large scale, as well as the context-awareness in both spatial and temporal perspective. This model is generalized as an efficient heuristic approach to different combinatorial optimization problems, especially to the problems with relatively tight constraints. We apply this model to vehicle routing problem (VRP) in this paper as an example. The experimental results show that this approach outperforms the traditional LNS heuristics on the same problem as well. The source code is available at \href{https://github.com/water-mirror/DPR}{https://github.com/water-mirror/DPR}.

CO2-responsive and photopolymerizable prepolymers are designed and synthesized. Their good photopolymerization kinetics and reversible CO2 and N2 responses to a bulk state and in a solution are reported. Stepwise modulation is verified in template imprinting. Results reveal that stable and high-resolution patterns can be produced by imprinting liquid prepolymers in CO2 atmosphere, erased by warm heating, or retained permanently by chemical cross-linking through photopolymerization with the aid of a photoinitiator. By contrast, only blurry patterns are obtained in air.

By measuring point-contact Andreev reflection (PCAR) spectra in the newly discovered chromium-based quasi-one-dimensional superconductor RbCr$_{3}$As$_{3}$, we find clear evidence of two superconducting components, i.e., one having a gap value of about 1.8 meV and another with a gap value of about 5 meV. Since the current injection may have components in both the direction parallel and perpendicular to the [(Cr$_{3}$As$_{3}$)$^{-}$]$_\infty$ chains in the PCAR measurements, it naturally explains the two-component feature observed in this multi-band superconductor. Detailed analysis shows that the larger gap may have an $s$-wave nature. We then carry out the single-particle tunneling measurements based on a scanning tunneling spectroscope by using the needle-like sample as the tip, and in this case the measured current is mainly parallel to the [(Cr$_{3}$As$_{3}$)$^{-}$]$_\infty$ chains. The single-particle tunneling spectra show only one gap feature with a gap value of about 1.8 meV. Fitting to the single particle tunneling spectra indicates that the gap should have a large anisotropy or even node(s). We argue that the absence of the larger gap may be related to the direction of the injecting current. Therefore, our combined experiments show the multiband superconductivity with one gap being nodal or highly anisotropic., Comment: 9 pages, 7 figures

Flavobacterium columnare causes columnaris disease in freshwater fish. In the present study, the antigenic regions of five outer membrane proteins (OMPs), including zinc metalloprotease, prolyl oligopeptidase, thermolysin, collagenase and chondroitin AC lyase, were bioinformatically analyzed, fused together, and then expressed as a recombinant fusion protein in Escherichia coli. The expressed protein of 95.6 kDa, as estimated by 10% sodium dodecyl sulfate-polyacrylamide gel electrophoresis, was consistent with the molecular weight deduced from the amino acid sequence. The purified recombinant protein was used to vaccinate the grass carp, Ctenopharyngodon idella. Following vaccination of the fish their IgM antibody levels were examined, as was the expression of IgM, IgD and IgZ immunoglobulin genes and other genes such as MHC Iα and MHC IIβ, which are also involved in adaptive immunity. Interleukin genes (IL), including IL-1β, IL-8 and IL-10, and type I and type II interferon (IFN) genes were also examined. At 3 and 4 weeks post-vaccination (wpv), significant increases in IgM antibody levels were observed in the fish vaccinated with the recombinant fusion protein, and an increase in the expression levels of IgM, IgD and IgZ genes was also detected following the vaccinations, thus indicating that an adaptive immune response was induced by the vaccinations. Early increases in the expression levels of IL and IFN genes were also observed in the vaccinated fish. At four wpv, the fish were challenged with F. columnare, and the vaccinated fish showed a good level of protection against this pathogen, with 39% relative percent survival (RPS) compared with the control group. It can be concluded, therefore, that the five OMPs, in the form of a recombinant fusion protein vaccine, induced an immune response in fish and protection against F. columnare.

Flavobacterium columnare is an important bacterial pathogen of freshwater fish that causes high mortality of infected fish and heavy economic losses in aquaculture. The pathogenesis of this bacterium is poorly understood, in part due to the lack of efficient methods for genetic manipulation. In this study, a gene deletion strategy was developed and used to determine the relationship between the production of chondroitin lyases and virulence. The F. johnsoniae ompA promoter (P ompA ) was fused to sacB to construct a counterselectable marker for F. columnare . F. columnare carrying P ompA-sacB failed to grow on media containing 10% sucrose. A suicide vector carrying P ompA-sacB was constructed, and a gene deletion strategy was developed. Using this approach, the chondroitin lyase-encoding genes, cslA and cslB , were deleted. The Δ cslA and Δ cslB mutants were both partially deficient in digestion of chondroitin sulfate A, whereas a double mutant (Δ cslA Δ cslB ) was completely deficient in chondroitin lyase activity. Cells of F. columnare wild-type strain G 4 and of the chondroitin lyase-deficient Δ cslA Δ cslB mutant exhibited similar levels of virulence toward grass carp in single-strain infections. Coinfections, however, revealed a competitive advantage for the wild type over the chondroitin lyase mutant. The results indicate that chondroitin lyases are not essential virulence factors of F. columnare but may contribute to the ability of the pathogen to compete and cause disease in natural infections. The gene deletion method developed in this study may be employed to investigate the virulence factors of this bacterium and may have wide application in many other members of the phylum Bacteroidetes .

In this study, a spectrum allocation algorithm is proposed to reduce the cost and the packets loss rate in the communications between the utility company and the consumers. We establish a cost model based on spectrum allocation in smart grid. Specifically, the subbands are allocated to different data aggregator units (DAUs) according to the confidence level and the maximum cost requirements. The maximum cost corresponding to the DAUs are provided by different utility companies. Simulation results demonstrate that the spectrum allocation algorithm can reduce the packets loss rate and make the cost of the utility companies all below the maximum cost requirements.

We investigated the role of miR-301b in the modulation of the proliferation, migration, and invasion of bladder cancer (BLCA) cells. The expression of miR-301b and EGR1 (early growth response gene 1) mRNA were analyzed by quantitative real-time polymerase chain reaction (qRT-PCR). A dual-luciferase reporter gene system was used to identify the target relationship between miR-301b and EGR1. Cell proliferation, cell cycle, and apoptosis were analyzed by MTT assay, colony-forming assay, and flow cytometry, respectively. Cell motility and invasiveness were assessed by wound healing and Transwell assays. The expression of proteins involved in epithelial-to-mesenchymal transition (EMT) and EGR1 were determined by Western blot. Our results showed that miR-301b was up-regulated while EGR1 was down-regulated in BLCA tissues compared with adjacent normal tissues. The proliferation, migration, and invasiveness of T24 cells (a kind of human BLCA cell) were suppressed by decreasing miR-301b expression or increasing EGR1 expression. In addition, miR-301b promoted EMT signaling by influencing the expression of related proteins. In conclusion, miR-301b promotes the proliferation, migration, and aggressiveness of human BLCA cells by inhibiting the expression of EGR1.

This paper proposed a kind of measuring system of the support reaction of the aerial work platform based on wireless communications mode, which can resolve the problem of the signal cable tangling compared with traditional mode. And a frequency transfer method is adopted to avoid interference or occupation of communications frequency in the wireless communications design, Test results show that measuring equipment has stable and reliable wireless communications with the outside world.

Small overlap crash covers 48% of all road accidents every year and is being a most common form of accidents. Analysis of different test methods of NHTSA RMDB offset oblique, IIHS small overlap and car-car 25% small overlap is made. A mid-level sedan is chosen for the test of three kinds of offset impact. Through the comparative analysis of car body deformation, body motion state and dummy injury, differences among these tests are figured out. The causes of the differences are put forward: impact velocity, overlap rate and barrier material, etc. In this way, a reference guide is given for the improvement of car crash safety.

In the international regulations and standards for child restraint system, the standard ECE R44 issued by the European Economic Commission and the Federal Motor Vehicle Safety Standards -- FMVSS213 are widely used in the world. In this paper, we study the FMVSS213 standard. Child restraint system dynamic test performance is an important index for evaluating it's safety, In this paper, based on FMVSS213 and the accelerate sled, with child dummy, we do in-depth research on child restraint system dynamic performance test method.

The problem of automatically labelling the appearances of characters in video with their names is challenging due to the huge variation in the appearance of each character and the weakness and ambiguity of available annotations. We can achieve high precision by combining multiple sources of information, both visual and textual. The principal novelties that we introduce in this paper are: (i) extracting face features in video by neural network; (ii) strengthening the mapping between names and faces by analyzing the co-occurrence of names and faces; (iii) automatically and efficiently labelling appearances of main characters with their names.

Flavobacterium columnare is a Gram-negative bacterium causing columnaris disease of freshwater fish worldwide, and development of efficacious vaccines has been a continuous challenge in aquaculture. In this study, 14 proteins were identified from cellular components of F.similar to columnare using an immunoblotting approach in two-dimensional electrophoresis map gels with antibacterial sera from grass carp, Ctenopharyngodon idella (Valenciennes), and then anti-grass carp-recombinant Ig (rIg) polyclonal antibodies. These proteins were characterized conclusively by matrix-assisted laser desorption/ionization-time of flight-mass spectrometry (MALDI-TOF/TOF MS). The 14 proteins are immunogenic molecules of F.similar to columnare, including chaperonins DnaK, GroEL and trigger factor, and translation elongation factor G, translation elongation factor Tu, 30S ribosomal subunit protein S1, dihydrolipoamide succinyltransferase, succinyl-CoA synthetase, SpoOJ regulator protein, alcohol dehydrogenase, fructose-bisphosphate aldolase, 3-hydroxybutyryl-CoA dehydrogenase and two conserved hypothetical proteins. These identified immunogenic proteins may provide candidate molecules for the development of vaccines against columnaris disease.

One of the more challenging and unresolved issues in ATM networks is the congestion control of available bit rate (ABR). The dynamic controller is designed based on the control theory and the feedback mechanism of explicit rates. With the given method of a chosen parameter, it can guarantee the stability of the controller and closed loop system with propagation delay and bandwidth oscillation. It needs less parameters(only one) to be designed. The queue length can converge to the given value in the least steps. The fairness of different connections is considered further. The simulations show better performance and good quality of service(QoS) is achieved.

By integrating multimodal information in multimodal news, a novel scheme is developed in this paper for facilitating more effective people news search via name-face association analysis. It is treated as a problem of bi-media multimodal semantic mapping on multimodal news, and modeled as an inter-related correlation distribution over multimodal semantic representations of name-face associations. Very positive results have been obtained in our experiments using a large quantity of public multimodal news data.

This paper provides an optimized method for measuring dummy’s knee displacement in vehicle sled crash test. The proposed method utilizes completely new elements for measurement, which are acceleration and angular velocity of dummy’s pelvis, as well as the rotational angle of its femur. Compared with the traditional measurement only using camera-based high-speed motion image analysis, the optimized one can not only maintain the measuring accuracy, but also avoid the disturbance caused by dummy movement, dashboard blocking and knee deformation during the crash. An experiment is made to verify the accuracy of the proposed method, which eliminates the strong dependence on single target tracing in traditional method. Moreover, it is very appropriate for calculating the penetration depth to the dashboard.

Wireless sensor networks are becoming increasing important due to their outstanding ability to detect and transmit real-time and wide application in many fields. Reducing energy consumption and extending lifetime of networks are important targets in the design of wireless sensor networks. In this paper, an optimal scheme is proposed based on mixed routing. The switch factor is presented and the optimal problem is converted into a nonlinear programming problem. The target is to optimize the lifetime of bottleneck node. The optimal solution is gained by the sub-gradient iterative algorithm. The simulations show that the lifetime of the networks is extended effectively.

Many natural and artificial systems, for example, fish school, bird flocks, robot team, are often composed of two different classes of agents: autonomous agents and leaders. The leaders have pertinent information, such as the location of the food source, while the autonomous agents make decisions according to local interactions. Then a basic problem is: how many leaders are required in order to induce all agents move with the same direction as leaders(such collective behavior is called consensus)? In this paper, we will consider a simple, but typical model proposed by Vicsek et al.(Vicsek model), in addition to the ordinary agents moving at the constant velocity with heading updated according to local rules, we add some leaders at the same velocity but with fixed heading. We will show that in order to induce the whole system reach consensus, the proportion of the leaders decreases as the number of autonomous agents increases under some conditions on the velocity v and neighborhood radius r. And the numerical examples are given to illustrate the necessity of the leaders. The proof is based on the analysis of the system dynamics and the initial neighbor graph, where multi-array martingale theorem play a key role.

This paper is about a kind of mobile robot used to polish free form surface of large metal model above and a method is presented for fitting the robotpsilas configuration to the measured data obtained by machine vision system. In the close loop of control system of the robot, a single camera machine vision system is employed to measure robotpsilas position and pose. Due to 2D state data can only be obtained by signal camera, the real 3D parameters of robot must be calculated out when it is moving on uneven surface. But errors usually exist in the calculated data. Thus to obtain more accurate data about robotpsilas state, it is needed to fit the measured data group with the robotpsilas configuration. Base on genetic algorithm (GA), an optimal fitting method is proposed and better result is got.

In this paper, queue length in the buffer is regarded as a scale to evaluate Quality of Service. A dual Smith predictor is designed for flow control in a single bottleneck linked ATM network to guarantee the stability of the system with unmatched information in the model. It is shown that in the complex and dynamic environment, the dynamic performance of the network can be greatly improved by setting appropriate parameters, feedback filter and assistant inner feedback mechanism. A number of simulations are done to verify the theoretical analysis.

In this letter we present fairness performance comparison between HSTCP with DropTail router and that with AQM router. With the assumption of synchronous feedback, the RTT unfairness of TCP AIMD congestion avoidance algorithm is obvious. However, the RTT unfairness may be exponential increased in HSTCP with DropTail router. By constructing the duality model of HSTCP with AQM router, we highlight that AQM can improve the fairness performance of HSTCP. Our quantitative result shows that the unfairness of HSTCP/AQM is inverse proportional to its RTT. The insight is validated by NS2 simulation.

The Vicsek model can be used to describe a basic class of multi-agent systems with local interactions: each agent has the tendency to behave as other agents do in its neighborhood. Through computer simulations, Vicsek et al.(1995) showed that such simple local interactions may lead to certain kind of cooperative phenomenon (synchronization) of the overall system, if the size of the system population is large. Since this model is of fundamental importance in understanding multi-agent systems, it has attracted much attention from researchers in recent years. In this paper, we will present a comprehensive theoretical analysis of the Vicsek model in a random framework with large population. To be precise, we will show that if both the interaction radius r and the agents' moving velocity v decrease as the population size n increases, but satisfy a certain constraint on the decreasing rates, then the overall system will synchronize for large n. The proofs are based on the recent work of Tang and Guo[1,2], and involves the use of spectral graph theory and double array martingale estimation theory.

The wavelet threshold method may produce pseudo-Gibbs phenomenon on the singularity points of signal. The translation invariant wavelet is an improve method based on that algorithm. Comparing with threshold method, a translation invariance method can suppress pseudo-Gibbs phenomenon and minish RMSE between the original signal and estimated one. At the same time, SNR of estimated signal can also be improved. This method is used to de-noise acoustic emission signals and compared with threshold method. The simulation result shows that this method can effectively eliminate noise, extract characteristic information of acoustic emission signals. It has strong engineering practicality.

We construct a low-bit rate multimedia communication system (LBMCS) and propose a new fast motion estimation algorithm which guarantees the implementation of a software-based H.263 codec. Based on this system we implement some practical functions such as remote monitor, videophone, audio recording, video recording, facsimile (FAX) and white board. Besides discussing the hardware structure and software frameworks of the system, we place the emphasis on the efficient implementation of the H.263 codec where the improvement in half-pel estimation is mentioned, and a novel search algorithm SSS (synthetical switch search) is expatiated on. Simulation results show that SSS is rather better than the common-used search algorithm, the TSS (three step search).

The linearity, time shifting, time scaling, and time inversion properties of FMmlet transform are proved, and the frequency shifting property of one of the subspaces of FMmlet transform, namely the chirplet transform is presented. Moreover, it is proved that in the process of FMm let based atomic signal decomposition, the residual signals decay exponentially.

Objective To research the anti-cancer mechanism of the Traditional Chinese Medicine Fanbaicao ( Herba Potentillae Discoloris ) oil in the human hepatoma cell line HepG2. Methods Gas chromatography was used to analyze the components of Fanbaicao ( Herba Potentillae Discoloris ). We tested the inhibitory effect of Fanbaicao ( Herba Potentillae Discoloris ) oil on the human hepatoma cell line HepG2 in vitro using 3-(4, 5-Dimet hylt hiazol-2-yl)-2,5-dip henyltetrazolium bromide assays. Fluorescence activating cell sorter analysis was used to examine the levels of apoptosis, and western blot and immunofluorescence were used to detect the expression of p21, p-p21 and CDK4 proteins. Results Fanbaicao ( Herba Potentillae Discoloris ) oil contains 45 ingredients, and L-ascorbic acid 2, 6-bispalmitate was the main component and accounted for 44.96% of total drive-off peak area. Other components included (Z)−14-met hyl-8-exadecenal-acetal (8.56%), phytol (7.74%) and lauric acid (6.31%). Fanbaicao ( Herba Potentillae Discoloris ) oil treatment reduced the proliferation of HepG2 cells and the half growth inhibition concentration (IC 50 ) was 2.03 mg/mL. Furthermore, we also observed significantly increased HepG2 cell apoptosis in a dose-dependent manner ( P Herba Potentillae Discoloris ) oil significantly increased the expression of p21 and p-p21 and significantly decreased the expression of CDK4 in HepG2 cells compared with controls ( P Conclusion Our results showed that Fanbaicao ( Herba Potentillae Discoloris ) oil has anti-cancer activities in HepG2 cells, which is probably related to the upregulation of p21 and p-p21 and downregulation of CDK4 expression.

IntroductionMethamphetamine dependence is a growing public health concern. There is currently no pharmacotherapy approved for methamphetamine dependence. Lisdexamfetamine (LDX) dimesylate, used in the treatment of attention-deficit hyperactivity disorder and binge eating disorder, has potential as an agonist therapy for methamphetamine dependence, and possible benefits of reduced risk of aberrant use due to its novel formulation.Methods and analysisA double-blind randomised controlled trial will be used to evaluate the efficacy of LDX in reducing methamphetamine use. The target sample is 180 participants with methamphetamine dependence of ≥2 years, using ≥14 days out of the previous 28, who have previously attempted but not responded to treatment for methamphetamine use. Participants will be randomly assigned to receive either a 15-week intervention consisting of induction (1 week of 150 mg LDX or placebo), maintenance (12 weeks of 250 mg LDX or placebo) and reduction (1 week of 150 mg LDX or placebo and 1 week of 50 mg LDX or placebo). All participants will be given access to four sessions of cognitive–behavioural therapy as treatment as usual and receive a 4-week follow-up appointment. The primary outcomes are efficacy (change from baseline in days of methamphetamine use by self-report for the last 28 days at week 13 and urinalyses confirmation of methamphetamine use) and safety (treatment-related adverse events). Secondary outcomes are total number of days of self-report methamphetamine use over the 12-week active treatment, longest period of abstinence during treatment period, percentage of achieving ≥21 days abstinence, craving, withdrawal, dependence, retention, bloodborne virus transmission risk behaviour, criminal behaviour, as well measures of abuse liability, physical and mental health, other substance use, cognitive performance, psychosocial functioning, treatment retention and satisfaction. Additionally, the study will assess the cost-effectiveness of LDX relative to the placebo control.Ethics and disseminationThe study has been approved by the Human Research Ethics Committee of St. Vincent’s Hospital, Sydney, Australia (HREC/16/SVH/222). Contact the corresponding author for the full trial protocol.Trial registration numberACTRN12617000657325; Pre-results.