移动机器人导航与定位技术研究进展

本文综述了移动机器人的导航、定位及多传感器融合技术,介绍了导航技术的应用现状,并阐述了导航技术的发展趋势。

灾难救援机器人研究现状、关键性能及展望

对日本、美国和中国等国家灾难救援机器人的研究现状和研究计划进行综述。根据世界各国救援机器人技术的研究现状,结合救援机器人在实际应用中取得的经验和教训,归纳和总结出救援机器人的关键性能为：存活能力、运动能力、感知能力、通信能力和作业能力。研究结果表明,灾难救援机器人研究逐步从试验研究转入到实际应用,多种技术融合化、多智能体网络化是今后灾难救援机器人研究的发展方向。防灾、减灾和救灾事关人民生命和财产安全,是国家公共安全的重要组成部分。救援机器人技术是国家发展迫切需要的战略必争的核心技术之一,将在国民经济和安全中起着重要作用并具有重大的战略意义。

避免误操作的遥协作模糊控制方法

现有的遥操作系统中普遍存在的问题是受环境、心理、生理等影响,操作者在遥操作机器人过程中可能由于误操作产生不可预料的后果.为了解决操作者误操作问题,提出对基于操作者通过选择操作手法得到的模糊操作量和对基于多传感器融合决策产生的模糊控制量采取加权和的遥协作模糊控制方法.以遥操作机械手臂为例,通过单纯由操作者、单纯由多传感器融合决策和遥协作模糊控制3种方法进行实验,验证所提出方法的合理性.

移动机器人多传感器信息融合技术述评

多传感器信息融合技术是目前移动机器人领域的研究热点。详细阐述了多传感器信息融合技术在移动机器人领域中的应用与研究进展,尤其对多传感器信息融合实现方法进行了深入的探讨。指明了移动机器人领域中多传感器信息融合技术未来的发展方向。

砂泥岩薄互层储层预测方法与应用研究

With the deeply development of exploration and development in petroleum in China, new increasing reserves are found in old oil fields and the verge of the old ones through re-study of geological property. It is more and more important to discovery and develop thin layer or thin inter-bedded layers reservoirs. All of the targets are thin sand-shale inter-bedded reservoirs and the core technology is reservoir predictions between wells in thin sand-shale inter-bedded layers. The continuity of the thin sand-shale inter-bedded layers in space or separating and heterogeneity is the key of reservoir geology research. The seismic reflection, high resolution analysis method and inversion method to thin sand-shale inter-bedded layers are thorough discussed and deeply studied in this paper to try to find the methods and resolutions of reservoir geology research. The below is followed. 1. Based on the pre-research of other people, five models are created: the sand sphenoid body, interlay sandstone and interlay shale of the equal thickness, interlay sandstone of the equal thickness and interlay shale of the unequal thickness, interlay sandstone of the unequal thickness and interlay shale of the unequal thickness, interlay sandstone of the changing thickness in sequence and interlay shale of the changing thickness in sequence. Then the study of the forward modeling are conducted on the thin layer and thin inter-bedded layers geological characters and seismic reflections including amplitude, frequency, phase, wave shape and time-frequency responding in the domains of time and frequency. The affect of petro-physics difference of layers, single thin layer thickness, thickness of inter-bedded, layer number of inter-bedded, incident wavelet domain frequency and types, sample interval to seismic reflection characters, frequency spectrum and time-frequency respond of reflectivity is theoretically discussed. 2. Qualitatively analyzing the sedimentary rhythm of the thin inter-bedded layers in vertical orientation and computing the single layer thickness or the average thickness with the method of generalized S transform. Identifying the reflecting interface or lithology interface using the amplitude value of amplitude spectrum domain frequency. 3. Based on the seismic respond of thin sand-shale inter-bedded layers, bring out the high resolution analysis method of seismic data in thin sand-shale inter-bedded layers using wavelet analysis and the idea of affecting low and high frequency with middle frequency. Then analyzing the effect to the method and testing some wavelets in the method. This method is applied to the theoretical models and the field data. 4. Bring forward one improved very fast simulated annealing method (IVFSA) to resolve the problem nonlinearity and multi-parameters of the inversion in thin inter-bedded layers. And IVFSA is more productive and higher precision than general ways. 5. New target constrained function is used in the inversion based on the property of the inversion in thin inter-bedded layers. 6. Making the full use of geological and logging information, IVFSA and the new function are applied in the non-linear inversion to improve reservoir prediction and evaluation in thin inter-bedded formations combined with the idea of logging and seismic inversion. This method was applied to the field data and got good results.

Heat capacity and thermodynamic properties of N-(2-cyanoethyl) aniline (C9H10N2)

The low temperature heat capacities of N-(2-cyanoethyl)aniline were measured with an automated adiabatic calorimeter over the temperature range from 83 to 353 K. The temperature corresponding to the maximum value of the apparent heat capacity in the fusion interval, molar enthalpy and entropy of fusion of this compound were determined to be 323.33 +/- 0.13 K, 19.4 +/- 0.1 kJ mol(-1) and 60.1 +/- 0.1 J K-1 mol(-1), respectively. Using the fractional melting technique, the purity of the sample was determined to be 99.0 mol% and the melting temperature for the tested sample and the absolutely pure compound were determined to be 323.50 and 323.99 K, respectively. A solid-to-solid phase transition occurred at 310.63 +/- 0.15 K. The molar enthalpy and molar entropy of the transition were determined to be 980 +/- 5 J mol(-1) and 3.16 +/- 0.02 J K-1 mol(-1), respectively. The thermodynamic functions of the compound [H-T - H-298.15] and [S-T - S-298.(15)] were calculated based on the heat capacity measurements in the temperature range of 83-353 K with an interval of 5 K. (c) 2004 Elsevier B.V. All rights reserved.

Determination of heat capacities and thermodynamic properties of 2-(chloromethylthio)benzothiazole by an adiabatic calorimeter

The molar heat capacities of 2-(chloromethylthio)benzothiazole (molecular formula C8H6ClNS2, CA registry no. 28908-00-1) were measured with an adiabatic calorimeter in the temperature range between (80 and 350) K. The construction and procedures of the calorimeter were described in detail. The performance of the calorimetric apparatus was evaluated by heat capacity measurements on alpha-Al2O3. The deviation of experiment heat capacities from the corresponding smoothed values lies within 0.3%, whereas the uncertainty is within +/-0.5%, compared with that of the recommended reference data over the whole experimental temperature range. A fusion transition was found from the C-p-T curve of 2-(chloromethylthio)benzothiazole. The melting temperature and the molar enthalpy and entropy of fusion of the compound were determined to be T-m = (315.11 +/- 0.04) K, Delta(fus)H(m) = (17.02 +/- 0.03) kJ(.)mol(-1), and Delta(fus)S(m) = (54.04 +/- 0.05) J(.)mol(-1.)K(-1), respectively. The thermodynamic functions (H-T - H-298.15) and (S-T - S-298.15) were also derived from the heat capacity data. The molar fraction purity of the 2-(chloromethylthio)benzothiazole sample used in the present calorimetric study was determined to be 99.21 by fraction melting.

Tracking a Large Number of Objects from Multiple Views

We propose a multi-object multi-camera framework for tracking large numbers of tightly-spaced objects that rapidly move in three dimensions. We formulate the problem of finding correspondences across multiple views as a multidimensional assignment problem and use a greedy randomized adaptive search procedure to solve this NP-hard problem efficiently. To account for occlusions, we relax the one-to-one constraint that one measurement corresponds to one object and iteratively solve the relaxed assignment problem. After correspondences are established, object trajectories are estimated by stereoscopic reconstruction using an epipolar-neighborhood search. We embedded our method into a tracker-to-tracker multi-view fusion system that not only obtains the three-dimensional trajectories of closely-moving objects but also accurately settles track uncertainties that could not be resolved from single views due to occlusion. We conducted experiments to validate our greedy assignment procedure and our technique to recover from occlusions. We successfully track hundreds of flying bats and provide an analysis of their group behavior based on 150 reconstructed 3D trajectories.

Live-cell visualization of transmembrane protein oligomerization and membrane fusion using two-fragment haptoEGFP methodology

Protein interactions play key roles throughout all subcellular compartments. In the present paper, we report the visualization of protein interactions throughout living mammalian cells using two oligomerizing MV (measles virus) transmembrane glycoproteins, the H (haemagglutinin) and the F (fusion) glycoproteins, which mediate MV entry into permissive cells. BiFC (bimolecular fluorescence complementation) has been used to examine the dimerization of these viral glycoproteins. The H glycoprotein is a type II membrane-receptor-binding homodimeric glycoprotein and the F glycoprotein is a type I disulfide-linked membrane glycoprotein which homotrimerizes. Together they co-operate to allow the enveloped virus to enter a cell by fusing the viral and cellular membranes. We generated a pair of chimaeric H glycoproteins linked to complementary fragments of EGFP (enhanced green fluorescent protein)--haptoEGFPs--which, on association, generate fluorescence. Homodimerization of H glycoproteins specifically drives this association, leading to the generation of a fluorescent signal in the ER (endoplasmic reticulum), the Golgi and at the plasma membrane. Similarly, the generation of a pair of corresponding F glycoprotein-haptoEGFP chimaeras also produced a comparable fluorescent signal. Co-expression of H and F glycoprotein chimaeras linked to complementary haptoEGFPs led to the formation of fluorescent fusion complexes at the cell surface which retained their biological activity as evidenced by cell-to-cell fusion.

Atomic data for modelling fusion and astrophysical plasmas

Trends and focii of interest in atomic modelling and data are identified in connection with recent observations and experiments in fusion and astrophysics. In the fusion domain, spectral observations are included of core, beam penetrated and divertor plasma. The helium beam experiments at JET and the studies with very heavy species at ASDEX and JET are noted. In the astrophysics domain, illustrations are given from the SOHO and CHANDRA spacecraft which span from the solar upper atmosphere, through soft x-rays from comets to supernovae remnants. It is shown that non-Maxwellian, dynamic and possibly optically thick regimes must be considered. The generalized collisional-radiative model properly describes the collisional regime of most astrophysical and laboratory fusion plasmas and yields self-consistent derived data for spectral emission, power balance and ionization state studies. The tuning of this method to routine analysis of the spectral observations is described. A forward look is taken as to how such atomic modelling, and the atomic data which underpin it, ought to evolve to deal with the extended conditions and novel environments of the illustrations. It is noted that atomic physics influences most aspects of fusion and astrophysical plasma behaviour but the effectiveness of analysis depends on the quality of the bi-directional pathway from fundamental data production through atomic/plasma model development to the confrontation with experiment. The principal atomic data capability at JET, and other fusion and astrophysical laboratories, is supplied via the Atomic Data and Analysis Structure (ADAS) Project. The close ties between the various experiments and ADAS have helped in this path of communication.

HARNESSING iNKT CELLS WITH RECOMBINANT CD1d FUSION PROTEINS TO REDIRECT INNATE AND ADAPTIVE IMMUNITY TO THE TUMOR

Les thérapies du cancer, comme la radiothérapie et la chimiothérapie, sont couramment utilisées mais ont de nombreux effets secondaires. Ces thérapies invasives pour le patient nécessitent d'être améliorées et de nombreuses avancées ont été faites afin d'adapter et de personnaliser le traitement du cancer. L'immunothérapie a pour but de renforcer le système immunitaire du patient et de le rediriger de manière spécifique contre la tumeur. Dans notre projet, nous activons les lymphocytes Invariant Natural Killer T (iNKT) afin de mettre en place une immunothérapie innovatrice contre le cancer. Les cellules iNKT sont une unique sous-population de lymphocytes T qui ont la particularité de réunir les propriétés de l'immunité innée ainsi qu'adaptative. En effet, les cellules iNKT expriment à leur surface des molécules présentes aussi sur les cellules tueuses NK, caractéristique de l'immunité innée, ainsi qu'un récepteur de cellules T (TCR) qui représente l'immunité adaptative. Les cellules iNKT reconnaissent avec leur TCR des antigènes présentés par la molécule CD1d. Les antigènes sont des protéines, des polysaccharides ou des lipides reconnus par les cellules du système immunitaire ou les anticorps pour engendrer une réponse immunitaire. Dans le cas des cellules iNKT, l'alpha-galactosylceramide (αGC) est un antigène lipidique fréquemment utilisé dans les études cliniques comme puissant activateur. Après l'activation des cellules iNKT avec l'αGC, celles-ci produisent abondamment et rapidement des cytokines. Ces cytokines sont des molécules agissant comme des signaux activateurs d'autres cellules du système immunitaire telles que les cellules NK et les lymphocytes T. Cependant, les cellules iNKT deviennent anergiques après un seul traitement avec l'αGC c'est à dire qu'elles ne peuvent plus être réactivées, ce qui limite leur utilisation dans l'immunothérapie du cancer. Dans notre groupe, Stirnemann et al ont publié une molécule recombinante innovante, composée de la molécule CD1d soluble et chargée avec le ligand αGC (αGC/sCD1d). Cette protéine est capable d'activer les cellules iNKT tout en évitant l'anergie. Dans le système immunitaire, les anticorps sont indispensables pour combattre une infection bactérienne ou virale. En effet, les anticorps ont la capacité de reconnaître et lier spécifiquement un antigène et permettent l'élimination de la cellule qui exprime cet antigène. Dans le domaine de l'immunothérapie, les anticorps sont utilisés afin de cibler des antigènes présentés seulement par la tumeur. Ce procédé permet de réduire efficacement les effets secondaires lors du traitement du cancer. Nous avons donc fusionné la protéine recombinante αGC/CD1d à un fragment d'anticorps qui reconnaît un antigène spécifique des cellules tumorales. Dans une étude préclinique, nous avons démontré que la protéine αGC/sCD1d avec un fragment d'anticorps dirigé contre la tumeur engendre une meilleure activation des cellules iNKT et entraîne un effet anti-tumeur prolongé. Cet effet anti-tumeur est augmenté comparé à une protéine αGC/CD1d qui ne cible pas la tumeur. Nous avons aussi montré que l'activation des cellules iNKT avec la protéine αGC/sCD1d-anti-tumeur améliore l'effet anti- tumoral d'un vaccin pour le cancer. Lors d'expériences in vitro, la protéine αGC/sCD1d-anti- tumeur permet aussi d'activer les cellules humaines iNKT et ainsi tuer spécifiquement les cellules tumorales humaines. La protéine αGC/sCD1d-anti-tumeur représente une alternative thérapeutique prometteuse dans l'immunothérapie du cancer. - Les cellules Invariant Natural Killer T (iNKT), dont les effets anti-tumoraux ont été démontrés, sont de puissants activateurs des cellules Natural Killer (NK), des cellules dendritiques (DC) et des lymphocytes T. Cependant, une seule injection du ligand de haute affinité alpha-galactosylceramide (αGC) n'induit une forte activation des cellules iNKT que durant une courte période. Celle-ci est alors suivie d'une longue phase d'anergie, limitant ainsi leur utilisation pour la thérapie. Comme alternative prometteuse, nous avons montré que des injections répétées d'αGC chargé sur une protéine recombinante de CD1d soluble (αGC/sCD1d) chez la souris entraînent une activation prolongée des cellules iNKT, associée à une production continue de cytokine. De plus, le maintien de la réactivité des cellules iNKT permet de prolonger l'activité anti-tumorale lorsque la protéine αGC/sCD1d est fusionnée à un fragment d'anticorps (scFv) dirigé contre la tumeur. L'inhibition de la croissance tumorale n'est optimale que lorsque les souris sont traitées avec la protéine αGC/sCD1d-scFv ciblant la tumeur, la protéine αGC/sCD1d-scFv non-appropriée étant moins efficace. Dans le système humain, les protéines recombinantes αGC/sCD1d-anti-HER2 et anti-CEA sont capables d'activer et de faire proliférer des cellules iNKT à partir de PBMCs issues de donneurs sains. De plus, la protéine αGC/sCD1d-scFv a la capacité d'activer directement des clones iNKT humains en l'absence de cellules présentatrices d'antigènes (CPA), contrairement au ligand αGC libre. Mais surtout, la lyse des cellules tumorales par les iNKT humaines n'est obtenue que lorsqu'elles sont incubées avec la protéine αGC/sCD1d-scFv anti- tumeur. En outre, la redirection de la cytotoxicité des cellules iNKT vers la tumeur est supérieure à celle obtenue avec une stimulation par des CPA chargées avec l'αGC. Afin d'augmenter les effets anti-tumoraux, nous avons exploité la capacité des cellules iNKT à activer l'immunité adaptive. Pour ce faire, nous avons combiné l'immunothérapie NKT/CD1d avec un vaccin anti-tumoral composé d'un peptide OVA. Des effets synergiques ont été obtenus lorsque les traitements avec la protéine αGC/sCD1d-anti-HER2 étaient associés avec le CpG ODN comme adjuvant pour la vaccination avec le peptide OVA. Ces effets ont été observés à travers l'activation de nombreux lymphocytes T CD8+ spécifique de la tumeur, ainsi que par la forte expansion des cellules NK. Les réponses, innée et adaptive, élevées après le traitement avec la protéine αGC/sCD1d-anti-HER2 combinée au vaccin OVA/CpG ODN étaient associées à un fort ralentissement de la croissance des tumeurs B16- OVA-HER2. Cet effet anti-tumoral corrèle avec l'enrichissement des lymphocytes T CD8+ spécifiques observé à la tumeur. Afin d'étendre l'application des protéines αGC/sCD1d et d'améliorer leur efficacité, nous avons développé des fusions CD1d alternatives. Premièrement, une protéine αGC/sCD1d dimérique, qui permet d'augmenter l'avidité de la molécule CD1d pour les cellules iNKT. Dans un deuxième temps, nous avons fusionné la protéine αGC/sCD1d avec un scFv dirigé contre le récepteur 3 du facteur de croissance pour l'endothélium vasculaire (VEGFR-3), afin de cibler l'environnement de la tumeur. Dans l'ensemble, ces résultats démontrent que la thérapie médiée par la protéine recombinante αGC/sCD1d-scFv est une approche prometteuse pour rediriger l'immunité innée et adaptive vers le site tumoral. - Invariant Natural Killer T cells (iNKT) are potent activators of Natural Killer (NK), dendritic cells (DC) and T lymphocytes, and their anti-tumor activities have been well demonstrated. However, a single injection of the high affinity CD1d ligand alpha-galactosylceramide (αGC) leads to a strong but short-lived iNKT cell activation followed by a phase of long-term anergy, limiting the therapeutic use of this ligand. As a promising alternative, we have demonstrated that when αGC is loaded on recombinant soluble CD1d molecules (αGC/sCD1d), repeated injections in mice led to the sustained iNKT cell activation associated with continued cytokine secretion. Importantly, the retained reactivity of iNKT cell led to prolonged antitumor activity when the αGC/sCD1d was fused to an anti-tumor scFv fragments. Optimal inhibition of tumor growth was obtained only when mice were treated with the tumor-targeted αGC/CD1d-scFv fusion, whereas the irrelevant αGC/CD1d-scFv fusion was less efficient. When tested in a human system, the recombinant αGC/sCD1d-anti-HER2 and -anti-CEA fusion proteins were able to expand iNKT cells from PBMCs of healthy donors. Furthermore, the αGC/sCD1d-scFv fusion had the capacity to directly activate human iNKT cells clones without the presence of antigen-presenting cells (APCs), in contrast to the free αGC ligand. Most importantly, tumor cell killing by human iNKT cells was obtained only when co- incubated with the tumor targeted sCD1d-antitumor scFv, and their direct tumor cytotoxicity was superior to the bystander killing obtained with αGC-loaded APCs stimulation. To further enhance the anti-tumor effects, we exploited the ability of iNKT cells to transactivate the adaptive immunity, by combining the NKT/CD1d immunotherapy with a peptide cancer vaccine. Interestingly, synergistic effects were obtained when the αGC/sCD1d- anti-HER2 fusion treatment was combined with CpG ODN as adjuvant for the OVA peptide vaccine, as seen by higher numbers of activated antigen-specific CD8 T cells and NK cells, as compared to each regimen alone. The increased innate and adaptive immune responses upon combined tumor targeted sCD1d-scFv treatment and OVA/CpG vaccine were associated with a strong delay in B16-OVA-HER2 melanoma tumor growth, which correlated with an enrichment of antigen-specific CD8 cells at the tumor site. In order to extend the application of the CD1d fusion, we designed alternative CD1d fusion proteins. First, a dimeric αGC/sCD1d-Fc fusion, which permits to augment the avidity of the CD1d for iNKT cells and second, an αGC/sCD1d fused to an anti vascular endothelial growth factor receptor-3 (VEGFR-3) scFv, in order to target tumor stroma environment. Altogether, these results demonstrate that the iNKT-mediated immunotherapy via recombinant αGC/sCD1d-scFv fusion is a promising approach to redirect the innate and adaptive antitumor immune response to the tumor site.

Finite-Sample Inference Methods for Simultaneous Equations and Models with Unobserved and Generated Regressors

We propose finite sample tests and confidence sets for models with unobserved and generated regressors as well as various models estimated by instrumental variables methods. The validity of the procedures is unaffected by the presence of identification problems or \"weak instruments\", so no detection of such problems is required. We study two distinct approaches for various models considered by Pagan (1984). The first one is an instrument substitution method which generalizes an approach proposed by Anderson and Rubin (1949) and Fuller (1987) for different (although related) problems, while the second one is based on splitting the sample. The instrument substitution method uses the instruments directly, instead of generated regressors, in order to test hypotheses about the \"structural parameters\" of interest and build confidence sets. The second approach relies on \"generated regressors\", which allows a gain in degrees of freedom, and a sample split technique. For inference about general possibly nonlinear transformations of model parameters, projection techniques are proposed. A distributional theory is obtained under the assumptions of Gaussian errors and strictly exogenous regressors. We show that the various tests and confidence sets proposed are (locally) \"asymptotically valid\" under much weaker assumptions. The properties of the tests proposed are examined in simulation experiments. In general, they outperform the usual asymptotic inference methods in terms of both reliability and power. Finally, the techniques suggested are applied to a model of Tobin’s q and to a model of academic performance.

Factor Analysis of a Large DSGE Model

We study the workings of the factor analysis of high-dimensional data using artificial series generated from a large, multi-sector dynamic stochastic general equilibrium (DSGE) model. The objective is to use the DSGE model as a laboratory that allow us to shed some light on the practical benefits and limitations of using factor analysis techniques on economic data. We explain in what sense the artificial data can be thought of having a factor structure, study the theoretical and finite sample properties of the principal components estimates of the factor space, investigate the substantive reason(s) for the good performance of di¤usion index forecasts, and assess the quality of the factor analysis of highly dissagregated data. In all our exercises, we explain the precise relationship between the factors and the basic macroeconomic shocks postulated by the model.

Reinforcement Learning by Policy Search

One objective of artificial intelligence is to model the behavior of an intelligent agent interacting with its environment. The environment's transformations can be modeled as a Markov chain, whose state is partially observable to the agent and affected by its actions; such processes are known as partially observable Markov decision processes (POMDPs). While the environment's dynamics are assumed to obey certain rules, the agent does not know them and must learn. In this dissertation we focus on the agent's adaptation as captured by the reinforcement learning framework. This means learning a policy---a mapping of observations into actions---based on feedback from the environment. The learning can be viewed as browsing a set of policies while evaluating them by trial through interaction with the environment. The set of policies is constrained by the architecture of the agent's controller. POMDPs require a controller to have a memory. We investigate controllers with memory, including controllers with external memory, finite state controllers and distributed controllers for multi-agent systems. For these various controllers we work out the details of the algorithms which learn by ascending the gradient of expected cumulative reinforcement. Building on statistical learning theory and experiment design theory, a policy evaluation algorithm is developed for the case of experience re-use. We address the question of sufficient experience for uniform convergence of policy evaluation and obtain sample complexity bounds for various estimators. Finally, we demonstrate the performance of the proposed algorithms on several domains, the most complex of which is simulated adaptive packet routing in a telecommunication network.

Engagement y productividad en las empresas

El presente trabajo pretende mostrar algunos avances en el término “engagement”, y como puede ser implementado en las organizaciones, teniendo en cuenta los diferentes factores que intervienen, para que los trabajadores se sientan “engaged” dentro de la organización. Además busca relacionar las diferentes habilidades y tipos de liderazgo que los altos mandos utilizan con sus empleados y como éste afecta la productividad de los trabajadores en las organizaciones. Para esto, se realizó una investigación de las clases de liderazgo y los comportamientos de los altos mandos, que pueden afectar positiva y negativamente el vínculo y sentido de pertenencia que tienen los trabajadores con la empresa en la que trabajan. Considerando importante las habilidades del liderazgo transformacional, para lograr desarrollar algún grado de engagement en los trabajadores, lo cual genera a su vez, un alza en la productividad de sus resultados dentro de la organización.