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As an environmentally friendly gas with good insulation and stable chemical properties, CF3I gas mixture is considered as a potential alternative to SF6 gas to compensate for the shortcomings of SF6 gas as a greenhouse gas. This article attempts to study the CF3I ternary gas mixtures with c-C4F8 and N2 by considering the process of streamer development in surface discharge. The model of surface discharge in CF3I gas mixture under DC voltage was established by COMSOL, and the drift-diffusion equations of particles was solved to show the discharge process, and the changes of electric field and particle concentration, etc. during the development of streamer were obtained, which provides the theoretical basis for the reliable diagnosis of partial discharge. On this basis, the model is compared with models for two other different gases (SF6/N2, artificial air) in terms of particle characteristics, streamer characteristics and streamer branches characteristics. Finally, it is concluded that under this model, although the insulation characteristics in CF3I gas mixture are weaker than those in SF6, the difference is not large and both are much better than those in artificial air, so c-C4F8/CF3I can be considered as a potential substitute for SF6.

To avoid large deformation, resulting from liquefaction, in inclined and deeply deposited liquefiable soil, it is necessary to design economical and reasonable reinforcement schemes. A reinforcement scheme employing subarea long-short gravel piles was proposed, and it was successfully applied in the embankment construction of the Aksu-kashgar highway. To reveal its underlying mechanism and effect on the seismic performance of the highway, the dynamic responses of natural foundation and two kinds of reinforced foundations were analyzed and compared under this scheme, using the program FEMEPDYN. Results showed that both the seismic subsidence and the excess pore pressure ratios were far less in the foundation reinforced with isometric gravel piles and in the foundation reinforced with subarea long-short gravel piles, compared with that in natural foundation. Therefore, the potential hazards of liquefaction were overcome in these two kinds of reinforced foundations. Furthermore, it was obvious that the shielding region only formed within the foundation reinforced with subarea long-short gravel piles. With the shielding effect, the proposed reinforcement scheme employing subarea long-short gravel piles not only eliminated liquefaction in deeply deposited liquefiable soil, but it also demonstrated an outstanding advantage in that the total length of gravel piles used was greatly reduced compared to the total length in the isometric gravel piles scheme and the interphase long-short gravel piles.

Photocatalytic water splitting for hydrogen production via heterojunction provides a convenient approach to solve the world crises of energy supply. Herein, graphene quantum dots modified TiO2 hybrids (TiO2-GQDs) with a “caterpillar”-like structure exhibit stronger light absorption in the visible region and an enhanced hydrogen production capacity of about 3.5-fold compared to the pristine TiO2 caterpillar. These results inferred that the addition of GQDs drastically promotes the interfacial electron transfer from GQDs to TiO2 through C–O–Ti bonds via the bonding between oxygen vacancy sites in TiO2 and in-plane oxygen functional groups in GQDs. Using a “caterpillar”-like structure are expected to provide a new platform for the development of highly efficient solar-driven water splitting systems based on nanocomposite photocatalyst.

Titanium (Ti) and its alloys offer favorable biocompatibility, mechanical properties and corrosion resistance, which makes them an ideal material choice for dental implants. However, the long-term success of Ti-based dental implants may be challenged due to implant-related infections and inadequate osseointegration. With the development of nanotechnology, nanoscale modifications and the application of nanomaterials have become key areas of focus for research on dental implants. Surface modifications and the use of various coatings, as well as the development of the controlled release of antibiotics or proteins, have improved the osseointegration and soft-tissue integration of dental implants, as well as their antibacterial and immunomodulatory functions. This review introduces recent nano-engineering technologies and materials used in topographical modifications and surface coatings of Ti-based dental implants. These advances are discussed and detailed, including an evaluation of the evidence of their biocompatibility, toxicity, antimicrobial activities and in-vivo performances. The comparison between these attempts at nano-engineering reveals that there are still research gaps that must be addressed towards their clinical translation. For instance, customized three-dimensional printing technology and stimuli-responsive, multi-functional and time-programmable implant surfaces holds great promise to advance this field. Furthermore, long-term in vivo studies under physiological conditions are required to ensure the clinical application of nanomaterial-modified dental implants.

The precision and reliability of the synchronous prediction of multi energy consumption indicators such as electricity and coal consumption are important for the production optimization of industrial processes (e.g., in the cement industry) due to the deficiency of the coupling relationship of the two indicators while forecasting separately. However, the time lags, coupling, and uncertainties of production variables lead to the difficulty of multi-indicator synchronous prediction. In this paper, a data driven forecast approach combining moving window and multi-channel convolutional neural networks (MWMC-CNN) was proposed to predict electricity and coal consumption synchronously, in which the moving window was designed to extract the time-varying delay feature of the time series data to overcome its impact on energy consumption prediction, and the multi-channel structure was designed to reduce the impact of the redundant parameters between weakly correlated variables of energy prediction. The experimental results implemented by the actual raw data of the cement plant demonstrate that the proposed MWMC-CNN structure has a better performance than without the combination structure of the moving window multi-channel with convolutional neural network.

Abstract Tung tree (Vernicia fordii) is an economically important tree widely cultivated for industrial oil production in China. To better understand the molecular basis of tung tree chloroplasts, we sequenced and characterized its genome using PacBio RS II sequencing platforms. The chloroplast genome was sequenced with 161,528 bp in length, composed with one pair of inverted repeats (IRs) of 26,819 bp, which were separated by one small single copy (SSC; 18,758 bp) and one large single copy (LSC; 89,132 bp). The genome contains 114 genes, coding for 81 protein, four ribosomal RNAs and 29 transfer RNAs. An expansion with integration of an additional rps19 gene in the IR regions was identified. Compared to the chloroplast genome of Jatropha curcas, a species from the same family, the tung tree chloroplast genome is distinct with 85 single nucleotide polymorphisms (SNPs) and 82 indels. Phylogenetic analysis suggests that V. fordii is a sister species with J. curcas within the Eurosids I. The nucleotide sequence provides vital molecular information for understanding the biology of this important oil tree.

ObjectiveThe purposes of this study are to investigate the regional homogeneity (ReHo) of spontaneous brain activities in Parkinson’s disease (PD) patients with freeze of gait (FOG) and to investigate the neural correlation of movement function through resting-state functional magnetic resonance imaging (RS-fMRI).MethodsA total of 35 normal controls (NC), 33 PD patients with FOG (FOG+), and 35 PD patients without FOG (FOG−) were enrolled. ReHo was applied to evaluate the regional synchronization of spontaneous brain activities. Analysis of covariance (ANCOVA) was performed on ReHo maps of the three groups, followed by post hoc two-sample t-tests between every two groups. Moreover, the ReHo signals of FOG+ and FOG− were extracted across the whole brain and correlated with movement scores (FOGQ, FOG questionnaire; GFQ, gait and falls questionnaire).ResultsSignificant ReHo differences were observed in the left cerebrum. Compared to NC subjects, the ReHo of PD subjects was increased in the left angular gyrus (AG) and decreased in the left rolandic operculum/postcentral gyrus (Rol/PostC), left inferior opercular-frontal cortex, left middle occipital gyrus, and supramarginal gyrus (SMG). Compared to that of FOG−, the ReHo of FOG+ was increased in the left caudate and decreased in the left Rol/PostC. Within the significant regions, the ReHo of FOG+ was negatively correlated with FOGQ in the left SMG/PostC (r = −0.39, p < 0.05). Negative correlations were also observed between ReHo and GFQ/FOGQ (r = −0.36/−0.38, p < 0.05) in the left superior temporal gyrus (STG) of the whole brain analysis based on AAL templates.ConclusionThe ReHo analysis suggested that the regional signal synchronization of brain activities in FOG+ subjects was most active in the left caudate and most hypoactive in the left Rol/PostC. It also indicated that ReHo in the left caudate and left Rol/PostC was critical for discriminating the three groups. The correlation between ReHo and movement scores (GFQ/FOGQ) in the STG has the potential to differentiate FOG+ from FOG−. This study provided new insight into the understanding of PD with and without FOG.

As compared with traditional ISAR imaging methods, the compressive sensing (CS)-based imaging methods can obtain high-quality images using much less under-sampled data. However, the availability or appropriateness of the sparse representation of the target scene and the relatively low computational efficiency of image reconstruction algorithms limit the performance and application of the CS-based ISAR imaging methods. In recent years, the deep learning technology has been applied in many fields and achieved outstanding performance in image classification, image reconstruction etc. DL implements the tasks using the deep neural network (DNN), which composes multiple hidden layers and non-linear activation layer. In this study, a novel ISAR imaging method that uses a complex-value deep neural network (CV-DNN) to perform the image formation using under-sampled data is proposed. The CV-DNN architecture can extract and exploit the sparse feature of the target image extremely well by multilayer non-linear processing. The experimental results show that the proposed CV-DNN-based ISAR imaging method can provide better shape reconstruction of target with less data than state-of-the-art CS reconstruction algorithms and improve the imaging efficiency obviously.

Interleukin (IL)-4-producing-CD8 (cytotoxic T cells, Tc) contribute to lung eosinophilia and airway hyper-responsiveness (AHR) to an antigen. CD4+CD25+ regulatory T cells (Tregs) attenuate airway inflammation and AHR. This study investigated whether Tregs decrease Tc2frequencies in ovalbumin (OVA)-induced asthma model of mice. Female C57BL/6 mice were sensitized with OVA intraperitoneally and challenged with OVA intranasally to induce allergic asthma model. Tregs were sorted by fluorescence activated cell sorting (FACS) and magnetic activated cell sorting (MACS) microbeads. OVA-sensitized mice were injected with Tregs or phosphate buffer saline (PBS) by tail vein ahead of the first challenge. Airway inflammation and airway hyper-responsiveness (AHR)were evaluated by histological analysis and invasive method, respectively. OVA-specific IgE and cytokine levels were detected by ELISA. Flow cytometry was used to detect the percentages of Tc1 and Tc2. Gata3 and T-bet mRNA was determined by quantitative PCR (qPCR). OVA-sensitized and challenged mice displayed typical asthma features, which included eosinophilic airway inflammation, higher levels of Th2 cytokines and AHR. Gata3 mRNA, Tc2 frequencies and OVA-specific IgE levels were significantly increased in OVA-sensitized and challenged mice. Compared to PBS treatment, Tregs decreased Tc2 frequencies, airway inflammation, Th2 cytokine levels and AHR in OVA-sensitized and challenged mice. IL-13 levels were negatively correlated with Tc1 frequencies and with IFNg levels in experimental mice. Our results demonstrated that Tregs could prevent airway inflammation and AHR by decreasing Tc2 frequencies and cytokine levels in OVA-induced asthma model of mice, supporting Tregmight be as a potent therapeutic target for alleviating airway inflammation and AHR.

Antiepileptic drugs frequently cause cutaneous adverse reactions (cADRs). Numerous studies have reported associations between human leukocyte antigen (HLA) alleles and cADRs caused by single antiepileptic drug in Southern Han Chinese people. However, the relationship between the HLA allele and cADRs sequentially induced by two or more antiepileptic drugs (AEDs-induced cross-reactivity) is unclear. To explore the associations between HLA alleles and AEDs-induced cross-reactivity, we prospectively recruited patients with AEDs-induced cross-reactivity from 2009 to 2017 and performed high-resolution genotyping to detect the HLA-A, B, C, and DRB1 alleles in patients for comparison with normal controls. To verify the important genotype, we compared its presence in patients with cross-reactivity to enlarged normal controls, and its presence in patients with carbamazepine (CBZ)-induced maculopapular exanthema (MPE) to CBZ-tolerant controls. Further, the important allele was replicated by meta-analysis. Twenty-three patients with AED-induced cross-reactivity and 500 healthy individuals were enrolled from Southern China. All patients had a mild rash without mucosal or systemic involvement. The HLA-B*13:01 allele was present in 34.78% (8/23) of patients, 14.60% (73/500) of healthy individuals, and 14.5% (763/5,270) healthy individuals, revealing a significant association (8/23 vs. 73/500; P = 0.02; OR: 3.12; 95% CI: 1.28–7.62; 8/23 vs. 763/5,270; P = 0.014; OR: 3.15; 95% CI: 1.33–7.46). HLA-B*13:01 was presented numerically higher in CBZ-induced MPE than that in CBZ-tolerant individuals without statistical significance (33/145, 22.76%, vs. 28/179, 15.64%; P = 0.103). Meta-analysis revealed an association between HLA-B*13:01 and cADRs induced by single AEDs or/and non-AEDs in Chinese and Thai populations (P = 0.000). This study suggests that HLA-B*13:01 is potentially associated with AED-cADRs in general, possibly with stronger effect in cross-reactivity. Screening for HLA-B*13:01 prior to starting AEDs therapy may help to avoid cADRs. However, this association requires further analysis in a multi-center study with a larger sample size.

INTRODUCTION:In order to improve the prediction accuracy of dengue fever incidence, we constructed a prediction model with interactive effects between meteorological factors, based on weekly dengue fever cases in Guangdong, China from 2008 to 2016. METHODS:Dengue fever data were derived from statistical data from the China National Notifiable Infectious Disease Reporting Information System. Daily meteorological data were obtained from the China Integrated Meteorological Information Sharing System. The minimum temperature for transmission was identified using data fitting and the Ross-Macdonald model. Correlations and interactive effects were examined using Spearman's rank correlation and multivariate analysis of variance. A probit regression model to describe the incidence of dengue fever from 2008 to 2016 and forecast the 2017 incidence was constructed, based on key meteorological factors, interactive effects, mosquito-vector factors, and other important factors. RESULTS:We found the minimum temperature suitable for dengue transmission was ≥18°C, and as 97.91% of cases occurred when the minimum temperature was above 18 °C, the data were used for model training and construction. Epidemics of dengue are related to mean temperature, maximum/minimum and mean atmospheric pressure, and mean relative humidity. Moreover, interactions occur between mean temperature, minimum atmospheric pressure, and mean relative humidity. Our weekly probit regression prediction model is 0.72. Prediction of dengue cases for the first 41 weeks of 2017 exhibited goodness of fit of 0.60. CONCLUSION:Our model was accurate and timely, with consideration of interactive effects between meteorological factors.

A low-frequency composite absorbing material with high permeability and low permittivity in low frequency was prepared after the flaky FeSiAl alloy powder was annealed in N _2 atmosphere and modified with zinc-based phosphate solution. The effects of annealing temperature and phosphating time on the phase composition, morphology and static magnetic properties of the flaky FeSiAl alloy were investigated with x-ray diffraction (XRD), scanning electron microscope (SEM) and vibrating sample magnetometer (VSM). With the aid of vector network analyzer (VNA), the electromagnetic properties and absorbing performance of the powder treated in two ways were studied. The results showed that after annealing in N _2 atmosphere, the crystallization degree of FeSiAl powder increased, the crystal type underwent a phase transition of A2-A2/B2-A2/B2/D03, the permittivity decreased, and the permeability was greatly improved. After phosphating, the phosphating reaction products were deposited on the surface of FeSiAl particles, the permittivity was significantly reduced, the low-frequency impedance matching and low-frequency absorption performance were improved. The causes and frequency changes of electromagnetic wave absorption peaks were analyzed with the λ /4 interference cancellation theory, the interface reflection model and the impedance matching principle.

This work comparatively investigates the influence of alcohol and liquid nitrogen medium-current annealing on GMI effect of rotated-dipping Co-based microwires. The temperature field distribution of Co-based microwires during current-annealing process is accordingly simulated, further to acquire experimental parameters of annealing current. Experimental results indicate that, GMI characteristics of current-annealed microwires in mentioned two mediums are both significantly improved, and GMI ratio [Δ Z / Z _max ] _max and magnetic field response sensitivity ξ _max of alcohol-medium current-annealed microwires increase more observable. When the excitation current frequency f = 3 MHz, [Δ Z / Z _max ] _max and ξ _max of microwires annealed by alcohol medium at 300 mA can reach 240.8% and 78.7%/Oe, respectively. During different type medium-current annealing, the higher-intensity annealing current can generate a larger circular magnetic field, which can effectively regulate the magnetic domain structure of Co-based microwires, so that, they tend to arrange densely and orderly, and the domain walls become much clearer. Meanwhile, the circular permeability μ _φ of microwires is significantly improved, thereby enhancing their GMI characteristics. Accordingly, the medium-current annealed Co-based microwires can be used as a typically sensitive material to provide technical support for the potential application of micromagnetic measurement field.

In [1], the complete affiliation of Yusheng Xue is as follows: Y. Xue (corresponding author) is with the School of Electrical Engineering, Southeast University, Nanjing, China, and he is also with State Grid Electric Power Research Institute (NARI Group Corporation), Nanjing, China, and State Key Laboratory of Smart Grid Protection and Operation Control, Nanjing, China.

In this work, poplar veneer (PV) rotary-cut from fast-growing polar was delignified to prepare flexible transparent poplar veneer (TPV). Lignin was gradually removed from the PV and then epoxy resin filled into the delignified PV. The study mainly concerns the effect of lignin content on microstructure, light transmittance, haze, tensile strength, and thermal stability of the PVs impregnated with epoxy resin. The results indicate that the lignin could be removed completely from the PV when the delignification time was around 8 h, which was proved by FTIR spectra and chemical component detection. Moreover, according to SEM observation and XRD testing, the porosity and crystallinity of the PVs were gradually increased with the removal of lignin. Also, the optical properties measurement indicated that the light transmittance and haze of the TPVs gradually increased, and the thermal stability also became more stable as shown by thermogravimetric analysis (TG). However, the tensile strength of the TPVs declined due to the removal of lignin. Among them, TPV8 exhibited excellent optical properties, thermal stability, and tensile strength. Consequently, it has great potential to be used as a substrate in photovoltaics, solar cells, smart windows, etc.

This paper introduces a novel controller into the tank level control of liquefied natural gas (LNG) carrier. The proposed controller can simplify the design process and save energy output of the controller under the premise of achieving a good control effect of the liquid level of a liquefied natural gas (LNG) carrier tank. Moreover, Gaussian function is adopted to decorate nonlinearly the output of the linear controller designed by using the second-order closed loop gain-shaping algorithm, and then the final controller is obtained. The effectiveness of the controller is verified by simulation experiments on the LNG carrier ‘‘Da-Peng Sun’’ No.2 liquid tank. The simulation results show that the comprehensive control performance index J of the second-order closed loop gain-shaping controller decorated by Gaussian function reduces by 11.8% and 95.3%, respectively, compared with the controller without nonlinear decoration and the linear proportional–integral–differential (PID) controller, meeting the requirement of energy saving and realizing a good control result of the tank level of the LNG carrier.

Determining the potential risks of musculoskeletal disorders through working postures in a workplace is expensive and time-consuming. A novel intelligent rapid entire body assessment (REBA) system based on convolutional pose machines (CPM), entitled the Quick Capture system, was applied to determine the risk levels. The aim of the study was to validate the feasibility and reliability of the CPM-based REBA system through a simulation experiment. The reliability was calculated from the differences of motion angles between the CPM-based REBA and a motion capture system. Results show the data collected by the Quick Capture system were consistent with those of the motion capture system; the average of root mean squared error (RMSE) was 4.77 and the average of Spearman’s rho (ρ) correlation coefficient in the different 12 postures was 0.915. For feasibility evaluation, the linear weighted Cohen’s kappa between the REBA score obtained by the Quick Capture system and those from the three experts were used. The result shows good agreement, with an average proportion agreement index (P0) of 0.952 and kappa of 0.738. The Quick Capture system does not only accurately analyze working posture, but also accurately determines risk level of musculoskeletal disorders. This study suggested that the Quick Capture system could be applied for a rapid and real-time on-site assessment.

With the rapid development of portable and wearable electronic devices, self-supporting flexible supercapacitors have attracted much attention, and higher requirements have been put forward for the electrode of the device, that is, it is necessary to have good mechanical properties while satisfying excellent electrochemical performance. In this work, a facile method was invented to obtain excellent self-supported flexible electrode materials with high mechanical properties and outstanding electrochemical performance by combining cellulose nanofibrils (CNFs) and reduced graphene oxide (RGO). We focused on the effect of the ratio of the addition of CNFs and the formation process of the film on the electrochemical and mechanical properties. The results show that the CNFs/RGO12 (where the ratio of CNFs to GO is 1:2) film displayed outstanding comprehensive properties; its tensile strength and conductivity were up to 83 MPa and 202.94 S/m, respectively, and its CA value was as high as 146 mF cm−2 under the current density of 5 mA cm−2. Furthermore, the initial retention rate of the specific capacitance was about 83.7% when recycled 2000 times; moreover, its capacitance did not change much after perpendicular bending 200 times. Therefore, the films prepared by this study have great potential in the field of flexible supercapacitors.

‘Huaxin’ is a new high-yielding timber cultivar of Camellia oleifera of high economic value, and has been widely cultivated in the red soil hilly region of Hunan Province of the People´s Republic of China in recent years. However, its quality and production are severely affected by low temperatures during flowering. To find genes related to cold tolerance and further explore new candidategenes for chilling-tolerance, Illumina NGS (Next Generation Sequencing) technology was used to perform transcriptomic analyses of C. oleifera ‘Huaxin’ leaves under long-term cold stress. Nine cDNA libraries were sequenced, and 58.31 Gb high-quality clean reads were obtained with an average of 5.92 Gb reads for each sample. A total of 191,150 transcripts were obtained after assembly. Among them, 100,703 unigenes were generated, and 44,610 unigenes were annotated. In total, 1564 differentially expressed genes (DEGs) were identified both in the A_B and A_C gene sets. In the current study, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed, andrevealed a group of cold-responsive genes related to hormone regulation, photosynthesis, membrane systems, and osmoregulation; these genes encoded many key proteins in plant biological processes, such as serine/threonine-protein kinase (STPK), transcription factors (TFs), fatty acid desaturase (FAD), lipid-transfer proteins (LTPs), soluble sugars synthetases, and flavonoid biosynthetic enzymes. Some physiological indicators of C. oleifera ‘Huaxin’ were determined under three temperature conditions, and the results were consistent with the molecular sequencing. In addition, the expression levels of 12 DEGs were verified using quantitative real-time polymerase chain reaction (qRT-PCR). In summary, the results of DEGs analysis together with qRT-PCR tests contribute to the understanding of cold tolerance and further exploring new candidate genes for chilling-tolerance in molecular breeding programs of C. oleifera ‘Huaxin’.

Miniature pigs have advantages over rodents in modeling atherosclerosis because their cardiovascular system and physiology are similar to that of humans. Apolipoprotein E (ApoE) deficiency has long been implicated in cardiovascular disease in humans. To establish an improved large animal model of familial hypercholesterolemia and atherosclerosis, the clustered regularly interspaced short palindromic repeats (CRISPR)-associated protein 9 system (CRISPR/Cas9) was used to disrupt the ApoE gene in Bama miniature pigs. Biallelic-modified ApoE pigs with in-frame mutations (ApoEm/m) and frameshift mutations (ApoE−/−) were simultaneously produced. ApoE−/− pigs exhibited moderately increased plasma cholesterol levels when fed with a regular chow diet, but displayed severe hypercholesterolemia and spontaneously developed human-like atherosclerotic lesions in the aorta and coronary arteries after feeding on a high-fat and high-cholesterol (HFHC) diet for 6 months. Thus, these ApoE−/− pigs could be valuable large animal models for providing further insight into translational studies of atherosclerosis.

Radio blackout has confused the aerospace industry for decades. The highly attenuated caused by the plasma sheath is the main cause of radio blackout. The transmission coefficient depends on the relationship between plasma density, collision frequency and radio wave frequency. Meanwhile, the reflection of waves and the mismatching of antenna impedance caused by plasma sheath lead to the change of antenna voltage standing wave ratio (VSWR). In this paper, we analysis the relationship between the VSWR and the Transmission Coefficient. The variation of GPS antenna’s VSWR with plasma sheath is simulated, the results demonstrate that VSWR is largely influenced with the electron density and the collision frequency. In addition, there is a strong correlation between VSWR, return loss and transmission loss. The correlation coefficient between the VSWR and wave transmission loss could be as high as -0.983. This relationship can support the idea that Transmission Coefficient can be predicted by detecting the variation of VSWR without requiring an additional feedback channel.

Affected by high temperature and pressure during the process of cutting stainless steel, the affinity element diffusion of tool-chips leads to the appearance of adhesion on the rake face, which eventually results in adhesion failure of the tool. In this study, we determined the formation of tool-chip adhesion during the cutting process using a cutting test; and put forward an experimental scheme of the element diffusion for clamped and welded specimens of the tool and workpiece. Fick's second law was used to develop a theoretical model of element diffusion to analyze the effect of tool-chip adhesion on the Fe and W element diffusion coefficient of Fe and W. The hardness of the tool surface was measured and analyzed after the diffusion experiment. The results showed that the tool-chip adhesion on the rake face of the tool was similar to pressure diffusion welding and that the tool-chip adhesion on the rake face directly affected the diffusion concentration of W, but had little effect on the diffusion concentration of Fe. In addition, the diffusion coefficient of Fe or W in the tool-chip adhesion is always greater for stick-welding than for non-stick-welding. The research results are of great significance for improving the cutting performance and tool life.

Predicting terrorist attacks by group networks is an important but difficult issue in intelligence and security informatics. Effective prediction of the behavior not only facilitates the understanding of the dynamics of organizational behaviors but also supports homeland security’s missions in prevention, preparedness, and response to terrorist acts. There are certain dynamic characteristics of terrorist groups, such as periodic features and correlations between the behavior and the network. In this paper, we propose a comprehensive framework that combines social network analysis, wavelet transform, and the pattern recognition approach to investigate the dynamics and eventually predict the attack behavior of terrorist group. Our ideas rely on social network analysis to model the terrorist group and extract relevant features for group behaviors. Next, based on wavelet transform, the group networks (features) are predicted and mutually checked from two aspects. Finally, based on the predicted network, the behavior of the group is recognized based on the correlation between the network and behavior. The Al-Qaeda data are investigated with the proposed framework to show the strength of our approaches. The results show that the proposed framework is highly accurate and is of practical value in predicting the behavior of terrorist groups.

Due to the influence of non-linear dynamic characteristic of clutch, external disturbance and parameter variation, the automated clutch is hard to control precisely during the engaging process of the automated clutch of automatic mechanical transmission vehicle. In this paper, adaptive generalized minimum variance controller is applied to the automated clutch which is driven by a brushless DC motor. The simulation results showed that the proposed controller is effective and robust to the parametric variation and external disturbance.

Due to the unbalance distribution of network resources and network traffic, congestion is an inherent property of the Internet. The consensus congestion controller based on the multiagent system theory is designed for the multirouter topology, which improves the performance of the whole networks. Based on the analysis of the causes of congestion, the topology of multirouter networks is modeled based on the graph theory and the network congestion control problem is described as a consensus problem in multiagent systems. Simulation results by MATLAB and Ns2 indicate that the proposed algorithm maintains a high throughput and a low packet drip ratio and improves the quality of the service in the complex network environment.

The protective role of electroacupuncture (EA) treatment in diverse neurological diseases such as ischemic stroke is well acknowledged. However, whether and how EA act on hippocampal neurogenesis following traumatic brain injury (TBI) remains poorly understood. This study aims to investigate the effect of EA on hippocampal neurogenesis and neurological functions, as well as its underlying association with toll-like receptor 4 (TLR4) signaling in TBI mice. BrdU/NeuN immunofluorescence was performed to label newborn neurons in the hippocampus after EA treatment. Water maze test and neurological severity score were used to evaluate neurological function posttrauma. The hippocampal level of TLR4 and downstream molecules and inflammatory cytokines were, respectively, detected by Western blot and enzyme-linked immunosorbent assay. EA enhanced hippocampal neurogenesis and inhibited TLR4 expression at 21, 28, and 35 days after TBI, but the beneficial effects of EA on posttraumatic neurogenesis and neurological functions were attenuated by lipopolysaccharide-induced TLR4 activation. In addition, EA exerted an inhibitory effect on both TLR4/Myd88/NF-κB and TLR4/TRIF/NF-κB pathways, as well as the inflammatory cytokine expression in the hippocampus following TBI. In conclusion, EA promoted hippocampal neurogenesis and neurological recovery through inhibition of TLR4 signaling pathway posttrauma, which may be a potential approach to improve the outcome of TBI.

Organizational external behavior changes are caused by the internal structure and interactions. External behaviors are also known as the behavioral events of an organization. Detecting event-related changes in organizational networks could efficiently be used to monitor the dynamics of organizational behaviors. Although many different methods have been used to detect changes in organizational networks, these methods usually ignore the correlation between the internal structure and external events. Event-related change detection considers the correlation and could be used for event recognition based on social network modeling and supervised classification. Detecting event-related changes could be effectively useful in providing early warnings and faster responses to both positive and negative organizational activities. In this study, event-related change in an organizational network was defined, and artificial neural network models were used to quantitatively determine whether and when a change occurred. To achieve a higher accuracy, Back Propagation Neural Networks (BPNNs) were optimized using Genetic Algorithms (GAs) and Particle Swarm Optimization (PSO). We showed the feasibility of the proposed method by comparing its performance with that of other methods using two cases. The results suggested that the proposed method could identify organizational events based on a correlation between the organizational networks and events. The results also suggested that the proposed method not only has a higher precision but also has a better robustness than the previously used techniques.

This paper investigates the problem of non-fragile L2–L¥ filter design for a kind of Takagi-Sugeno (T-S) fuzzy stochastic system with neutral delay and parameter uncertainties. The addressed problem is the design of a non-fragile fuzzy filter such that the error system is robustly stochastic stable and the filtering error system can tolerant some level of the gain variations in the filter. Based on the Lyapunov-Krasovskii functional we chose, the delay-dependent conditions are obtained. The resulting filters can ensure that the error system is both stochastically stable and the peak value of the estimation error is bounded by a prescribed level for all possible bounded energy disturbances. Finally, an illustrative example is given to substantiate the effectiveness of the proposed method.

Whether or how neural stem cells (NSCs) respond to toll-like receptor 4 (TLR4) in an inflammatory environment caused by traumatic brain injury (TBI) has not been understood. In the present study, association between TLR4 expression and NSCs proliferation in the hippocampus was investigated in a mouse model of TBI using controlled cortical impact (CCI). Hippocampal proliferating cells were labeled with the thymidine analog 5-bromo-2-deoxyuridine (BrdU). In order to identify NSCs, the proliferating cells were further co-labeled with BrdU/sex determination region of Y chromosome related high mobility group box gene 2 (SOX2). Morphological observation on the expression of BrdU, SOX2, and TLR4 in the hippocampus was performed by inmmunofluorescence (IF). Relative quantification of TLR4 expression at the protein and mRNA level was performed using Western blotting and real-time polymerase chain reaction (PCR). It was observed that BrdU+/SOX2+cells accounted for 95.80% ± 7.91% among BrdU+ cells; several BrdU+ cells and SOX2+ cells in the hippocampus were also TLR4-positive post injury, and that BrdU+ cell numbers, together with TLR4 expression at either protein or mRNA level, increased significantly in TBI mice over 1, 3, 7, 14, and 21 days survivals and changed in a similar temporal pattern with a peak at 3 day post-injury. These results indicate that hippocampal proliferating cells (suggestive of NSCs) expressed TLR4, and that there was a potential association between increased expression of TLR4 and the proliferation of NSCs post TBI. It is concluded that hippocampal TLR4 may play a potential role in endogenous neurogenesis after TBI.

We not only propose three flexible optical cross-connect (OXC) structures, with the ability of wavelength-division multiplexing (WDM) multicast, but also experimentally demonstrate two WDM multicast schemes based on four-wave mixing in a semiconductor optical amplifier (SOA). One-to-ten WDM multicast of 25-Gb/s QPSK signals is achieved with three pumps, and the power penalties for all signals are less than 1.7 dB. For the first time, dual-channel WDM multicasts are simultaneously realized with only two pumps. One-to-six multicast for one input with the largest power penalty of 1.28 dB is obtained, whereas one-to-three multicast for the other input with the power penalty of 1.27 dB is also realized. The demonstrated schemes can be applied to the proposed OXC structures, according to the different requirements. The effect of bias current on conversion efficiency and optical signal-to-noise ratio is also discussed, and the optimal value is given.

First-principles calculations have been used to investigate the effects of Co addition on the preferred site occupation and magnetic properties of Ni-Fe-Ga-Co ferromagnetic shape memory alloys. The formation energy results indicate that the excess Ni constituent preferentially occupies the Fe sites in the off-stoichiometric Ni-Fe-Ga ternary alloy. The added Co tends to take the normal-Ni sites in the Ni-Fe-Ga-Co quaternary alloy during composition adjustment process. The total magnetic moment increases with Co content of the Ni36-xFe12Ga16Cox (x=0, 1, 2, 3 and 4) alloys. The difference between the up and down electronic density of states at the Fermi level gives rise to the increased magnetic property.

A detailed description of the flooding process is crucial to analyze the complex hydrodynamic behaviors and enhance the survivability of the damaged ship. In this paper, through establishing three typical damage scenarios with various locations, the commercial software CD Adapco STAR-CCM+ based on the Reynolds-Averaged Navier-Stokes (RANS) solver is applied to simulate the flooding process involving multiple compartments. The basic computational fluid dynamics (CFD) models and specific simulation settings are elaborated. The volume of fluid (VOF) method combined with the user defined field function is developed to distribute the initial free surface. The captured flooding process indicates that the air compression due to the restricted ventilation decreases the flooding amount. The obtained flooding time can provide necessary data to support for appropriate rescue management and evacuation options.

Ontology is the formal representation of concepts and their mutual relations. It has wide application potential in the classification of agricultural information, the construction of information and knowledge database, the research and development of intelligent search engine, as well as the realization of cooperative information service, etc. In this research, an ontology-based agricultural knowledge management system framework is proposed, which includes modules of ontology-based knowledge acquisition, knowledge representation, knowledge organization, and knowledge mining, etc. The key technologies, building tools and applications of the framework are explored. Future researches on the theoretical refinement and intelligent simulation knowledge service are also envisioned.

Hydraulic instability is a complex factor causing the vibration of hydro-turbine generator shafting system (HGSS), and the mechanism is the uneven distribution of flow along the circumference. The common reasons for this phenomenon include the inconsistency of the blade exit flow angle, the relay stroke and the guide vane opening. This paper mainly focuses on the research of the hydraulic instability caused by the inconsistency of the blade exit flow angle. Firstly, based on the Kutta-Joukowski theorem, the hydraulic unbalance force model is firstly presented. Then, considering the chain reaction among the hydraulic, mechanical and electrical instability, a combined nonlinear mathematical model of the HGSS is established. Finally, by using numerical simulation, the dynamic characteristics of the HGSS with the changing of the deviation of the blade exit flow angle, the blade exit diameter and the guide vane opening angle are analyzed. Moreover, it is found that the hydraulic instability determines the overall changing trend of the shafting dynamic behaviors. In addition, some stable ranges of the HGSS are distinguished. But above all, these results can efficiently provide a reference for the design and manufacture of hydro-turbine blades and the operation of hydropower stations.

Modeling organizational dynamics of terrorist network is a critical issue in computational analysis of terrorism research. The first step for effective counterterrorism and strategic intervention is to investigate how the terrorists operate with the relational network and what affects the performance. In this paper, we investigate the organizational dynamics by employing a computational experimentation methodology. The hierarchical cellular network model and the organizational dynamics model are developed for modeling the hybrid relational structure and complex operational processes, respectively. To intuitively elucidate this method, the agent based modeling is used to simulate the terrorist network and test the performance in diverse scenarios. Based on the experimental results, we show how the changes of operational environments affect the development of terrorist organization in terms of its recovery and capacity to perform future tasks. The potential strategies are also discussed, which can be used to restrain the activities of terrorists.

Epidermal growth factor receptor tyrosine kinase (EGFR-TK) inhibitors are useful in treating different advanced human cancers; however, their clinical efficacy varies. This study detected K-ras mutations to predict the efficacy of EGFR-TK inhibitor cetuximab treatment on Chinese patients with metastatic colorectal cancer (mCRC). A total of 87 patients with metastatic colorectal cancer were treated with cetuximab for 2-16 months, in combination with chemotherapy between August 2008 and July 2012, and tissue samples were used to detect K-ras mutations. The data showed that K-ras mutation occurred in 27/87 (31%). The objective response rates and disease control rate in K-ras wild type and mutant patients were 42% (25/60) versus 11% (3/27) (p

This paper is concerned with the L2-L∞ filtering problem for a kind of Takagi-Sugeno (T-S) fuzzy stochastic system with time-varying delay and parameter uncertainties. Parameter uncertainties in the system are assumed to satisfy global Lipschitz conditions. And the attention of this paper is focused on the stochastically mean-square stability of the filtering error system, and the L2-L∞ performance level of the output error with the disturbance input. The method designed for the delay-dependent filter is developed based on linear matrix inequalities. Finally, the effectiveness of the proposed method is substantiated with an illustrative example.

With the wide deployment of Wi-Fi networks, Wi-Fi based indoor localization systems that are deployed without any special hardware have caught significant attention and have become a currently practical technology. At the same time, the Magnetic, Angular Rate, and Gravity (MARG) sensors installed in commercial mobile devices can achieve highly-accurate localization in short time. Based on this, we design a novel indoor localization system by using built-in MARG sensors and a Wi-Fi module. The innovative contributions of this paper include the enhanced Pedestrian Dead Reckoning (PDR) and Wi-Fi localization approaches, and an Extended Kalman Particle Filter (EKPF) based fusion algorithm. A new Wi-Fi/MARG indoor localization system, including an Android based mobile client, a Web page for remote control, and a location server, is developed for real-time indoor pedestrian localization. The extensive experimental results show that the proposed system is featured with better localization performance, with the average error 0.85 m, than the one achieved by using the Wi-Fi module or MARG sensors solely.

The congestion control algorithm based on the weighted directed graph is designed for the network congestion over the wireless sensor network. The congestion problem is modeled as a distributed dynamic system with time-varying delay, and it can be proven that the sent rate for all nodes converges to the available bandwidth of the sink by the proposed congestion control algorithm. Via Lyapunov function, the validity of the proposed algorithm is shown under the varying network topologies. Ns simulation results indicate that the proposed algorithm restrains the congestion over the wireless sensor network, maintains a high throughput and a low delay time, and also improves the quality of service for the whole network.

Focusing an annular laser beam can improve the axial trapping efficiency due to the reduction of the scattering force, which enables the use of a lower numerical aperture (NA) objective lens with a long working distance to trap particles in deeper aqueous medium. In this paper, we present an axicon-to-axicon scheme for producing parallel annular beams with the advantages of higher efficiency compared with the obstructed beam approach. The validity of the scheme is verified by the observation of a stable trapping of silica microspheres with relatively low NA microscope objective lenses (NA = 0.6 and 0.45), and the axial trapping depth of 5 mm is demonstrated in experiment.

The aim of this paper is to present a new indoor localization approach by employing the Angle-of-arrival (AOA) and Received Signal Strength (RSS) measurements in Wi-Fi network. To achieve this goal, we first collect the Channel State Information (CSI) by using the commodity Wi-Fi devices with our designed three antennas to estimate the AOA of Wi-Fi signal. Second, we propose a direct path identification algorithm to obtain the direct signal path for the sake of reducing the interference of multipath effect on the AOA estimation. Third, we construct a new objective function to solve the localization problem by integrating the AOA and RSS information. Although the localization problem is non-convex, we use the Second-order Cone Programming (SOCP) relaxation approach to transform it into a convex problem. Finally, the effectiveness of our approach is verified based on the prototype implementation by using the commodity Wi-Fi devices. The experimental results show that our approach can achieve the median error 0.7 m in the actual indoor environment.

In recent decades, the proliferation of smart phones, tablets, and wireless networks has fostered a growing interest in indoor passive positioning. The Wi-Fi-based passive positioning systems can provide Location-Based Services (LBSs) to the third party such as market and security departments. Most of the existing systems are based on the Receive Signal Strength Indication (RSSI) information, which are generally time-consuming and susceptible to environmental change. To overcome this problem, we propose the Wi-Fi compass for indoor passive positioning system (WIPP), an Angle of Arrival (AOA) based passive positioning system using the existing commodity Wi-Fi network. In this paper, we first propose a new algorithm for the joint estimation of AOA and Time of Arrival (TOA) measurements based on the fine-grained Channel State Information (CSI), which is collected by an off-the-shelf Wi-Fi device equipped with only three antennas. Second, we use the affinity propagation clustering algorithm to identify the direct signal path from the target to each Wi-Fi Access Point (AP). Finally, we deploy the WIPP in an actual indoor environment to conduct the performance comparison with the well-known radio-frequency (RF) based system for locating and tracking users inside buildings (RADAR), as well as the conventional passive positioning system using the AOA solely. The experimental results show that the WIPP is able to achieve the median positioning error 0.7 m, which is much lower than the ones by the RADAR system and the conventional system using the AOA solely.