凉爽条件下体感温度模型的建立及风速、水汽压、辐射的影响

本文通过对人体热量平衡方程的建立和分析结合不同年龄人群的新陈代谢特点 ,求得凉爽条件下 (日平均气温 Ta<2 1℃ )体感温度的理论计算公式和统计模型。在此基础上 ,分析了风、水汽压。

以热量平衡为基础的体感温度模型及气候要素的效应分析

通过对夏季人体热量平衡方程的建立与计算 ,结合我国不同年龄段人群的新陈代谢特点 ,分别建立了不同的体感温度模型。经与我国目前应用较为广泛的人体舒适度统计模型的计算结果相比较 ,证明以热量平衡为基础的人体体感温度模型更具有普遍性。还分析了风、湿度、辐射对体感温度的影响效应。这些结果将为拓宽舒适度服务范围 。

人体舒适度研究现状及其开发应用前景

人体舒适度指标是当前城市气象服务的主要内容之一。文中归纳了当前国内外有关人体舒适度的研究和发展动态 ,重点介绍由美国著名生物气象学家Steadman提出的以人体热量平衡为基础的体感温度模型以及北京市气象局和上海市气象局正在应用的舒适度模型 ,在此基础上讨论了人体舒适度理论的应用前景 。

洗出位置对列车驾驶模拟器逼真度的影响研究

以国内第一台自主研制的列车驾驶模拟器为对象,研究了洗出位置对于列车驾驶模拟器逼真度的影响.运用Matlab,通过对不同的洗出位置经过经典洗出算法和体感评价模型后产生的平台位移和运动感觉进行仿真分析比较,得出了上平台质心点为最优洗出位置的结论,对其它类型模拟器洗出位置的选择也具有借鉴作用.

GIS based Landslide Susceptibility Mapping of Tevankarai Ar Sub-watershed,Kodaikkanal,India using Binary Logistic Regression Analysis

Landslide susceptibility mapping is the first step in regional hazard management as it helps to understand the spatial distribution of the probability of slope failure in an area.An attempt is made to map the landslide susceptibility in Tevankarai Ar subwatershed,Kodaikkanal,India using binary logistic regression analysis.Geographic Information System is used to prepare the database of the predictor variables and landslide inventory map,which is used to build the spatial model of landslide susceptibility.The model describes the relationship between the dependent variable(presence and absence of landslide) and the independent variables selected for study(predictor variables) by the best fitting function.A forward stepwise logistic regression model using maximum likelihood estimation is used in the regression analysis.An inventory of 84 landslides and cells within a buffer distance of 10m around the landslide is used as the dependent variable.Relief,slope,aspect,plan curvature,profile curvature,land use,soil,topographic wetness index,proximity to roads and proximity to lineaments are taken as independent variables.The constant and the coefficient of the predictor variable retained by the regression model are used to calculate the probability of slope failure and analyze the effect of each predictor variable on landslide occurrence in thestudy area.The model shows that the most significant parameter contributing to landslides is slope.The other significant parameters are profile curvature,soil,road,wetness index and relief.The predictive logistic regression model is validated using temporal validation data-set of known landslide locations and shows an accuracy of 85.29 %.

Cell culture systems for the hepatitis C virus

Since the discovery of HCV in 1989, the lack of a cell culture system has hampered research progress on this important human pathogen. No robust system has been obtained by empiric approaches, and HCV cell culture remained hypothetical until 2005. The construction of functional molecular clones has served as a starting point to reconstitute a consensus infectious cDNA that was able to transcribe infectious HCV RNAs as shown by intrahepatic inoculation in a chimpanzee. Other consen- sus clones have been selected and established in a hu- man hepatoma cell line as replicons, i.e. self-replicating subgenomic or genomic viral RNAs. However, these repli- cons did not support production of infectious virus. Inter- estingly, some full-length replicons could be established without adaptive mutations and one of them was able to replicate at very high levels and to release virus particles that are infectious in cell culture and in vivo. This new cell culture system represents a major breakthrough in the HCV field and should enable a broad range of basic and applied studies to be achieved.

Accessing Alignments of Ontologies via IoT Based on SKOS Data Model

Many ontologies are provided to representing semantic sensors data.However,heterogeneity exists in different sensors which makes some service operators of Internet of Thing(IoT) difficult(such as such as semantic inferring,non-linear inverted index establishing,service composing) .There is a great deal of research about sensor ontology alignment dealing with the heterogeneity between the different sensor ontologies,but fewer solutions focus on exploiting syntaxes in a sensor ontology and the pattern of accessing alignments.Our solution infers alignments by extending structural subsumption algorithms to analyze syntaxes in a sensor ontology,and then combines the alignments with the SKOS model to construct the integration sensor ontology,which can be accessed via the IoT.The experiments show that the integration senor ontology in the SKOS model can be utilized via the IoT service,and the accuracy of our prototype,in average,is higher than others over the four real ontologies.

Resistance Analysis of Unsymmetrical Trimaran Model with Outboard Sidehulls Configuration

The application of multi-hull ship or trimaran vessel as a mode of transports in both river and sea environments have grown rapidly in recent years.Trimaran vessels are currently of interest for many new high speed ship projects due to the high levels of hydrodynamic efficiency that can be achieved,compared to the mono-hull and catamaran hull forms.The purpose of this study is to identify the possible effects of using an unsymmetrical trimaran ship model with configuration（S/L） 0.1-0.3 and R/L=0.1-0.2.Unsymmetrical trimaran ship model with main dimensions： L=2000mm,B=200 mm and T=45 mm.Experimental methods（towing tank） were performed in the study using speed variations at Froude number 0.1-0.6.The ship model was pulled by an electric motor whose speed could be varied and adjusted.The ship model resistance was measured precisely by using a load cell transducer.The comparison of ship resistance for each configuration with mono-hull was shown on the graph as a function of the total resistance coefficient and Froude number.The test results found that the effective drag reduction could be achieved up to 17% at Fr=0.35 with configuration S/L=0.1.

Landslide susceptibility mapping using an integrated model of information value method and logistic regression in the Bailongjiang watershed,Gansu Province,China

Bailongjiang watershed in southern Gansu province, China, is one of the most landslide-prone regions in China, characterized by very high frequency of landslide occurrence. In order to predict the landslide occurrence, a comprehensive map of landslide susceptibility is required which may be significantly helpful in reducing loss of property and human life. In this study, an integrated model of information value method and logistic regression is proposed by using their merits at maximum and overcoming their weaknesses, which may enhance precision and accuracy of landslide susceptibility assessment. A detailed and reliable landslide inventory with 1587 landslides was prepared and randomly divided into two groups,(i) training dataset and(ii) testing dataset. Eight distinct landslide conditioning factors including lithology, slope gradient, aspect, elevation, distance to drainages,distance to faults, distance to roads and vegetation coverage were selected for landslide susceptibility mapping. The produced landslide susceptibility maps were validated by the success rate and prediction rate curves. The validation results show that the success rate and the prediction rate of the integrated model are 81.7 % and 84.6 %, respectively, which indicate that the proposed integrated method is reliable to produce an accurate landslide susceptibility map and the results may be used for landslides management and mitigation.

GIS-based Frequency Ratio and Logistic Regression Modelling for Landslide Susceptibility Mapping of Debre Sina Area in Central Ethiopia

Ethiopia has a mountainous landscape which can be divided into the Northwestern and Southeastern plateaus by the Main Ethiopian Rift and Afar Depression. Debre Sina area is located in Central Ethiopia along the escarpment where landslide problem is frequent due to steep slope, complex geology, rift tectonics, heavy rainfall and seismicity. In order to tackle this problem, preparing a landslide susceptibility map is very important. For this, GISbased frequency ratio(FR) and logistic regression(LR) models have been applied using landslide inventory and the nine landslide factors(i.e. lithology, land use, distance from river & fault, slope, aspect, elevation, curvature and annual rainfall). Database construction, weighting each factor classes or factors, preparing susceptibility map and validation were the major steps to be undertaken. Both models require a rasterized landslide inventory and landslide factor maps. The former was classified into training and validation landslides. Using FR model, weights for each factor classes were calculated and assigned so that all the weighted factor maps can be added to produce a landslide susceptibility map. In the case of LR model, the entire study area is firstly divided into landslide and non-landslide areas using the training landslides. Then, these areas are changed into landslide and non-landslide points so as to extract the FR maps of the nine landslide factors. Then a linear relationship is established between training landslides and landslide factors in SPSS. Based on this relationship, the final landslide susceptibility map is prepared using LR equation. The success-rate and prediction-rate of FR model were 74.8% and 73.5%, while in case of LR model these were 75.7% and 74.5% respectively. A close similarity in the prediction and validation rates showed that the model is acceptable. Accuracy of LR model is slightly better in predicting the landslide susceptibility of the area compared to FR model.

Construction and Genetic Analysis of Murine Hepatitis Virus Strain A59 Nsp16 Temperature Sensitive Mutant and the Revertant Virus

Coronaviruses (CoVs) are generally associated with respiratory and enteric infections and have long been recognized as important pathogens of livestock and companion animals. Mouse hepatitis virus (MHV) is a widely studied model system for Coronavirus replication and pathogenesis. In this study,we created a MHV-A59 temperature sensitive (ts) mutant Wu"-ts18(cd) using the recombinant vaccinia reverse genetics system. Virus replication assay in 17C1-1 cells showed the plaque phenotype and replication characterization of constructed Wu"-ts18(cd) were indistinguishable from the reported ts mutant Wu"-ts18. Then we cultured the ts mutant Wu"-ts18(cd) at non-permissive temperature 39.5°C,which "forced" the ts recombinant virus to use second-site mutation to revert from a ts to a non-ts phenotype. Sequence analysis showed most of the revertants had the same single amino acid mutation at Nsp16 position 43. The single amino acid mutation at Nsp16 position 76 or position 130 could also revert the ts mutant Wu"-ts18 (cd) to non-ts phenotype,an additional independent mutation in Nsp13 position 115 played an important role on plaque size. The results provided us with genetic information on the functional determinants of Nsp16. This allowed us to build up a more reasonable model of CoVs replication-transcription complex.

A Cloud-Assisted Malware Detection and Suppression Framework for Wireless Multimedia System in IoT Based on Dynamic Differential Game

As a novel dynamic network service infrastructure, Internet of Things （IoT） has gained remarkable popularity with obvious su- periorities in the interoperability and real-time communication. Despite of the convenience in collecting information to provide the decision basis for the users, the vulnerability of embed- ded sensor nodes in multimedia devices makes the malware propagation a growing serious problem, which would harm the security of devices and their users financially and physi- cally in wireless multimedia system （WMS）. Therefore, many researches related to the mal- ware propagation and suppression have been proposed to protect the topology and system security of wireless multimedia network. In these studies, the epidemic model is of great significance to the analysis of malware prop- agation. Considering the cloud and state tran- sition of sensor nodes, a cloud-assisted model for malware detection and the dynamic differ- ential game against malware propagation are proposed in this paper. Firstly, a SVM based malware detection model is constructed with the data sharing at the security platform in the cloud. Then the number of malware-infected nodes with physical infectivity to susceptible nodes is calculated precisely based on the at- tributes of WMS transmission. Then the statetransition among WMS the modified epidemic devices is defined by model. Furthermore, a dynamic differential game and target cost function are successively derived for the Nash equilibrium between malware and WMS sys- tem. On this basis, a saddle-point malware de- tection and suppression algorithm is presented depending on the modified epidemic model and the computation of optimal strategies. Nu- merical results and comparisons show that the proposed algorithm can increase the utility of WMS efficiently and effectively.

六自由度VR娱乐平台变频率洗出算法研究

为提高VR娱乐平台模拟运动场景的逼真度，对经典洗出算法加以改进并提出一种变频率洗出算法（VFWA）。根据平台运动实时性要求，结合切换控制思想，并根据设定输入值与算法输出值的误差实时反馈调节算法滤波器的参数。利用MATLAB软件对VR娱乐平台纵向模式，偏航模式与垂直模式运动进行仿真，结果表明，运用本文所提出的变频率洗出算法（VFWA），既能将模拟逼真度从经典洗出算法的50％-60％提高至90％。又能防止VR娱乐平台运动超限，对正弦信号与方波信号输入具有较好的适用性。

ON INTERACTION OF SHOCK AND SOUND WAVE (Ⅰ)

This paper studies the ioteraction of shock and gradient wave (sound wave) of solutions to the system of inviscid isentropic gas dynamics as a model for the corresponding problems for nonlinear hyperbolic systems. The problem can be reduced to a boundary value problem in a wedged domain. By using the method of constructing asymptotic solutions and Newton’s iteration process it is proved that if a weak shock hits a gradient wave, then the grandient wave will split into two gradient waves, while the shock continuses propagating. In this paper the author reduces the problem to a standard form and constructs asymptotic solution of the problem. The existence of the genuine solution will be given in the following paper.

Global properties of nonlinear humoral immunity viral infection models

In this paper, we consider two nonlinear models for viral infection with humoraL immu- nity. The first model contains four compartments; uninfected target cells, actively infected cells, free virus particles and B cells. The second model is a modification of the first one by including the latently infected cells. The incidence rate, removal rate of infected cells, production rate of viruses and the latent-to-active conversion rate are given by more general nonlinear functions. We have established a set of conditions on these general functions and determined two threshold parameters for each model which are sufficient to determine the global dynamics of the models. The global asymptotic stability of all equilibria of the models has been proven by using Lyapunov theory and applying LaSalle＇s invariance principle. We have performed some numerical simulations for the models with specific forms of the general functions. We have shown that, the numerical results are consistent with the theoretical results.

Nonlinear multifunctional sensor signal reconstruction based on least squares support vector machines and total least squares algorithm

Least squares support vector machines (LS-SVMs) are modified support vector machines (SVMs) that involve equality constraints and work with a least squares cost function, which simplifies the optimization procedure. In this paper, a novel training algorithm based on total least squares (TLS) for an LS-SVM is presented and applied to multifunctional sensor signal reconstruction. For three different nonlinearities of a multifunctional sensor model, the reconstruction accuracies of input signals are 0.001 36%, 0.031 84% and 0.504 80%, respectively. The experimental results demonstrate the higher reliability and accuracy of the proposed method for multifunctional sensor signal reconstruction than the original LS-SVM training algorithm, and verify the feasibility and stability of the proposed method.