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With the rapid progress in science and technology, intelligent AGV (Automated Guided Vehicle) is more and more popular in industrial automation. However, since it is very difficult for the traditional proportional-integral-derivative (PID) to strike a balance between the static and dynamic performance of system. In order to make AGV control system more smooth and stable, a fuzzy PID controller to improve the performance of traditional PID control is applied in such system in this paper. Of course, since there are some noise in the physical recognition system, the Kalman filter is also used to reduce the effect of noise. Firstly, on the base of the fuzzy control principle, a fuzzy PID controller is designed, which includes fuzzy language variables, membership function and fuzzy control rules. Secondly, the output fuzzy values through fuzzification, fuzzy control rule and fuzzy decision are fed into conventional PID control system. Thirdly, through the establishment of AGV model, the Kalman filter is utilized to predict the pose of AGV at the next moment by filtering the recognition noise. Finally, simulation results shows its improvement over the conventional PID controller in AGV control system and experiment results of Fuzzy PID with Kalman filter are also given to testify the advantage of the new algorithm.

Interleukin (IL)-17 is a proinflammatory cytokine mainly secreted by activated T helper 17 cells and involved in inflammatory immune responses. This study aimed to investigate the association between IL-17 variants as well as serum IL-17 levels with gout in male Chinese Han individuals. A total of 1,101 male gout patients and 1,239 ethic-matched controls were enrolled. Genetic distributions of three variants (rs2275913 in IL-17A, rs763780 in IL-17F, and rs4819554 in IL-17RA) were detected by real-time polymerase chain reaction using the Taqman probe method. The plasma concentrations of IL-17A and IL-17F were measured in 228 gout patients and 198 controls that came from above samples by an enzyme-linked immunosorbent assay. No significant differences were observed in the genetic distribution of these polymorphisms between cases and controls (rs2275913: χ2 = 0.15, p = 0.928 by genotype, χ2 = 0.14, p = 0.711 by allele; rs763780: χ2 = 2.24, p = 0.326 by genotype, χ2 = 0.26, p = 0.609 by allele; rs4819554: χ2 = 1.79, p = 0.409 by genotype, χ2 = 1.46, p = 0.227 by allele). Levels of serum IL-17A and IL-17F were significantly decreased in gout patients (both p0.05). Although the genetic variants in IL-17 we studied in this research do not appear to be involved in the development of gout in male Chinese Han individuals, the IL-17 cytokine family may participate in gouty inflammation in an undefined way, which requires further validation.

International audience; A new generic object recognition (GOR) method for robot perception is proposed in this paper, based on multi-feature fusion of two-dimensional (2D) and 3D scale invariant feature transform descriptors drawn from 2D images and 3D point clouds. The trained support vector machine is utilized to construct multi-category classifiers that recognize the objects. According to our results, this new GOR approach achieves higher recognition rates than classical methods tested, even when one has large intra-class variations, or high inter-class similarities of the objects. Simulation results demonstrate the effectiveness and efficiency of the proposed GOR approach.

In this paper, considering the information fusion of multi-sensors on mobile robot, a new tool (the fusion machine of DSmT (Dezert-Smarandache Theory) coupling with PCR5 (Proportional Conflict Redistribution Rule)) is applied to autonomous mobile robot’s map reconstruction from 16 sonar rangefinders.

A mentoring scheme is carried out in our school to bring professional electrical engineers and university electrical engineering students together that takes advantage of resource of electrical engineers to mentor senior design projects. Electrical engineering design projects rely heavily on engineering experience and teamwork. Professional engineer involvement in this process can bring valuable experience to the students. Streamlining this collaborative development and introducing practical experience, is an essential training subject in electrical engineering education. Depending on the source of the design project, engineers are assigned to assist the students in concentrating on the important aspects of the project as well as in guidance on testing, development, implementation, technologies, and methodologies. This paper addresses the procedure of implementing this mentoring scheme. The positive effects of this mentoring scheme are examined and assessed through assessment and evaluation between engineers and students. The results reveal that this scheme significantly enhances design project in terms of student communication and coordination as well as project implementation with guidance and mentoring by professional electrical engineers.

In order to solve the water crisis, it is important to optimize the allocation of water resources. In this paper, the Whale Optimization Algorithm (WOA) is applied to the optimal allocation of water resources in Xingtai with the goal of maximum economic benefit and minimum total water shortage. The results show that the total water demand of different water users in each district is 26.94×108m3, the total allocated water is 19.83×108m3, the total water shortage is 7.11×108m3, and the water shortage rate was 26.39%. The lack of water is mainly concentrated in the primary industry. The result of the solution reflects the principle of water supply order and water use equity, which is in line with the actual development and utilization of water resources in the study area. It also verifies the feasibility of the whale optimization algorithm, such as less parameter adjustment, faster convergence, and better global optimization ability when solving water resources optimization problems.

With the increment of focal elements number in discernment framework, the computation amount in Dezert-Smarandache Theory (DSmT) will exponentially go up. This has been the bottleneck problem to block the wide application and development of DSmT. Aiming at this difficulty, in this paper, a kind of fast approximate reasoning method in hierarchical DSmT is proposed. Presently, this method is only fit for the case that there are only singletons with assignment in hyper-power set. These singletons in hyper-power set are forced to group through bintree or tri-tree technologies. At the same time, the assignments of singletons in those different groups corresponding to each source are added up respectively, in order to realize the mapping from the refined hyper-power set to the coarsened one. And then, two sources with the coarsened hyper-power set are combined together according to classical DSm Combination rule (DSmC) and Proportional Conflict Redistribution rule No. 5 (PCR5). The fused results in coarsened framework will be saved as the connecting weights between father and children nodes. And then, all assignments of singletons in different groups will be normalized respectively. Tree depth is set, in order to decide the iterative times in hierarchical system. Finally, by comparing new method with old one from different views, the superiority of new one over old one is testified well.

Modern systems for information retrieval, fusion and management need to deal more and more with information coming from human experts usually expressed qualitatively in natural language with linguistic labels. In this paper, we propose and use two new 2-Tuple linguistic representation models (i.e., a distribution function model (DFM) and an improved Herrera-Martinez’s model) jointly with the fusion rules developed in Dezert-Smarandache Theory (DSmT), in order to combine efficiently qualitative information expressed in term of qualitative belief functions. The two models both preserve the precision and improve the efficiency of the fusion of linguistic information expressing the global expert’s opinion. However, DFM is more general and efficient than the latter, especially for unbalanced linguistic labels. Some simple examples are also provided to show how the 2-Tuple qualitative fusion rules are performed and their advantages.

Most of modern systems for information retrieval, fusion and management have to deal with more and more qualitative information (by linguistic labels) besides information expressed quantitatively (by numbers), since human reports are better and easier expressed in natural language than with numbers. In this paper, Herrera-Martinez’s 2-Tuple linguistic representation model is extended for reasoning with uncertain and qualitative information in Dezert-Smarandache Theory (DSmT) framework, in order to overcome the limitations of current approaches, i.e., the lack of precision in the final results of linguistic information fusion according to 1-Tuple representation (q1). The linguistic information which expresses the expert’s qualitative beliefs is expressed by means of mixed 2 Tuples (equidistant linguistic labels with a numeric biased value). Together with the 2-Tuple representation model, some basic operators are presented to carry out the fusion operation among qualitative information sources. At last, through simple example how 2-Tuple qualitative DSmT-based (q2 DSmT) fusion rules can be used for qualitative reasoning and fusion under uncertainty, which advantage is also showed by comparing with other methods.

In this paper, we present a new 2-tuple linguistic representation model, i.e. Distribution Function Model (DFM), for combining imprecise qualitative information using fusion rules drawn from Dezert-Smarandache Theory (DSmT) framework. Such new approach allows to preserve the precision and efficiency of the combination of linguistic information in the case of either equidistant or unbalanced label model. Some basic operators on imprecise 2-tuple labels are presented together with their extensions for imprecise 2-tuple labels. We also give simple examples to show how precise and imprecise qualitative information can be combined for reasoning under uncertainty. It is concluded that DSmT can deal efficiently with both precise and imprecise quantitative and qualitative beliefs, which extends the scope of this theory.

OBJECTIVE To assess the association of single nucleotide polymorphisms (SNPs) of susceptibility genes of type 2 diabetes mellitus (T2DM) with liability to gout among ethnic Han Chinese males from coastal region of Shandong province. METHODS Seven SNPs within the susceptibility genes of T2DM, including rs10773971(G/C) and rs4766398(G/C) of WNT5B gene, rs10225163(G/C) of JAZF1 gene, rs2069590(T/A) of BDKRB2 gene, rs5745709(G/A) of HGF gene, rs1991914(C/A) of OTOP1 gene and rs2236479(G/A) of COL18A1 gene, were typed with a custom-made Illumina GoldenGate Genotyping assay in 480 male patients with gout and 480 male controls. Potential association was assessed with the chi-square test. RESULTS No significant difference was detected for the 7 selected SNPs in terms of genotypic and allelic frequencies (P0.05). When age and body mass index (BMI) were adjusted, the 7 genetic variants still showed no significant association with gout. CONCLUSION The genotypes of the 7 selected SNPs are not associated with gout in ethnic Han Chinese male patients from the coastal region of Shandong province. However, the results need to be replicated in larger sets of patients collected from other regions and populations.

To assess the association of cytochrome P450 gene single nucleotide polymorphisms (SNPs) with susceptibility to gout in ethnic Han males from coastal regions of Shandong province.Four hundred and eighty male patients with gout and 480 healthy male controls were included. Genotyping was carried out with a custom Illumina GoldenGate Genotyping assay to detect SNP rs2275620 of CYP2C8 gene, SNP rs2070676 of CYP2E1 gene, SNP rs837395 of CYP4B1 gene, and SNP rs194150 of TBXAS1 gene. The association was assessed with chi-square test.No significant difference has been found between the two groups in regard to the genotypic and allelic frequencies of the TT, AT, AA genotypes and A, T alleles of the SNP rs2275620 of the CYP2C8 gene (P=0.88; P=0.97), the CC, CG, GG genotypes and C,G alleles of SNP rs2070676 of the CYP2E1 gene (P=0.24; P=0.09), the TT, AT, AA genotypes and A, T alleles of SNP rs837395 of the CYP4B1 (P=0.88; P=0.97), and TT, AT, AA genotypes and the A,T alleles of SNP rs194150 of TBXAS1 gene (P=0.15; P=0.06).This study has identified no association of SNP loci rs2275620(A/T) of CYP2C8, rs2070676(C/G) of CYP2E1, rs837395(A/T) of CYP4B1 and rs194150(A/T) of TBXAS1 with gout in ethnic Han males from coastal regions in Shandong province. However, our result needs to be replicated in larger sets of patients collected from other regions and populations.

A coverage motion planning (CMP) is a kind of coverage path planning, which requires the robot path to fill every grid of the workspace. It is an essential issue in plenty of robotic applications. Safety aware collision-free coverage motion planning of an autonomous vehicle is one of the major challenges in intelligent vehicle systems. Many studies have been focused on the obstacle avoidance to prevent “too close” or “too far” from obstacles, but difficult to obtain an optimal path. In this paper, a virtual obstacle (VO) based safety aware strategy integrated with a biologically inspired neural network (BNN) method is proposed for CMP in a non-stationary environment as safety consideration is greatly crucial in vehicle CMP. The real-time vehicle trajectory is planned through the varying neural activity landscape that represents the dynamic environment. The proposed model for vehicle navigation with safety consideration is capable of planning a real-time appropriate trajectory. The proposed approach is capable of overcoming the either “too close” or “too far” shortcoming. Simulation and comparison studies validate that the proposed model is capable of performing CMP mission to plan more reasonable and shorter collision-free trajectories in non-stationary and unstructured environments.

Knowledge acquisition in map building is characterized with uncer- tainty and imprecision. This uncertainty is especially severe in the course of build- ing grid maps using sonar. Jean Dezert and Florentin Smarandache have recently proposed a new information fusion paradigm (DSmT), whose major advantage is that it deals with uncertainty and conflict of information. In this article, based on the Dezert-Smarandache Theory, the authors demonstrate how to fuse information from homogeneous or heterogeneous sensors differing in reliability. Then, they build the belief model of sonar grid map and construct the generalized basic belief assignment function (gbbaf). Pioneer II mobile robot has served as experimental platform and a 3D-Map has been built online based on DSmT. Finally, this work has established a firm foundation for a firm foundation for the simultaneous study of a dynamic unknown environment and multi-robots' map building.

Gout is one of the most common types of inflammatory arthritis, caused by the deposition of monosodium urate crystals in and around the joints. Previous genome-wide association studies (GWASs) have identified many genetic loci associated with raised serum urate concentrations. However, hyperuricemia alone is not sufficient for the development of gout arthritis. Here we conduct a multistage GWAS in Han Chinese using 4,275 male gout patients and 6,272 normal male controls (1,255 cases and 1,848 controls were genome-wide genotyped), with an additional 1,644 hyperuricemic controls. We discover three new risk loci, 17q23.2 (rs11653176, P=1.36 × 10−13, BCAS3), 9p24.2 (rs12236871, P=1.48 × 10−10, RFX3) and 11p15.5 (rs179785, P=1.28 × 10−8, KCNQ1), which contain inflammatory candidate genes. Our results suggest that these loci are most likely related to the progression from hyperuricemia to inflammatory gout, which will provide new insights into the pathogenesis of gout arthritis., Raised serum urate levels are a risk factor for gout, a common form of inflammatory arthritis. Here Li et al. conduct a multistage genome-wide association study in a Han Chinese population and identify three novel loci likely associated with the progression from hyperuricemia to gout.

Real-time navigation and mapping of an autonomous robot is one of the major challenges in intelligent robot systems. In this paper, a novel sensor-based biologically inspired neural network algorithm to real-time collision-free navigation and mapping of an autonomous mobile robot in a completely unknown environment is proposed. A local map composed of square grids is built up through the proposed neural dynamics for robot navigation with restricted incoming sensory information. With equipped sensors, the robot can only sense a limited reading range of surroundings with grid map representation. According to the measured sensory information, an accurate map with grid representation of the robot with local environment is dynamically built for the robot navigation. The real-time robot motion is planned through the varying neural activity landscape, which represents the dynamic environment. The proposed model for autonomous robot navigation and mapping is capable of planning a real-time reasonable trajectory of an autonomous robot. Simulation and comparison studies are presented to demonstrate the effectiveness and efficiency of the proposed methodology that concurrently performs collision-free navigation and mapping of an intelligent robot.

This paper presents a chirp based ultrasonic positioning system (UPS) using orthogonal chirp waveforms. In the proposed method, multiple transmitters can simultaneously transmit chirp signals, as a result, it can efficiently utilize the entire available frequency spectrum. The fundamental idea behind the proposed multiple access scheme is to utilize the oversampling methodology of orthogonal frequency-division multiplexing (OFDM) modulation and orthogonality of the discrete frequency components of a chirp waveform. In addition, the proposed orthogonal chirp waveforms also have all the advantages of a classical chirp waveform. Firstly, the performance of the waveforms is investigated through correlation analysis and then, in an indoor environment, evaluated through simulations and experiments for ultrasonic (US) positioning. For an operational range of approximately 1000 mm, the positioning root-mean-square-errors (RMSEs) &90% error were 4.54 mm and 6.68 mm respectively.

Nowadays, people expect robots to perceive environments in a concept-oriented way, and how to teach robots some abstract concepts becomes a new problem. Aiming at teaching robots abstract place concepts, a method using a sketch map is proposed. The method is based on a prototype mechanism, in which feature objects and qualitative spatial relationships among them are taken into account simultaneously. Two primitives used on a sketch map are defined: one is the closed curve which represents an object, and the other is the arrow which is used to assist to get the orientation of a certain object. A concept prototype is gotten through analyzing primitives on a sketch map. The analysis is divided into two parts: getting information about objects and getting the scores of spatial relationships according to certain usual relationship attributes. Finally, the method is verified by simulation, and place concept teaching can be reliably realized.

Nowadays, direction relation research has become an important branch in spatial representation and reasoning area, and especially, the research considering fuzziness and uncertainty may become more and more important. In this paper, a solution is proposed for composing fuzzy direction relations based on fuzzy direction-relation matrix. Firstly, a formal definition and an algorithm are given for the Most operator. Then, a practical method is proposed for composing accurate direction relations. At last, based on composing accurate direction relations on every λ level, our fuzzy composing method is given. Our method is consistent with people's intuition, and it is feasible to be used in the applications which need to compose fuzzy direction information.

In this paper a multilayer hierarchical visual processing architecture integrated with a bottom-up and top-down combined inference algorithm is proposed for robust weld joint recognition and localization. Three layers-pixel layer, primitive layer, and profile layer-are defined, firstly laser stripe centerline points are coarsely extracted from the image in pixel layer, then the primitive layer primitives are obtained by a grouping algorithm with a hypothesis-verification scheme, and at last a hypothesis for a joint pattern based on partial match is generated from profile layer and verified by searching through the lower layers of the hierarchy. During the top-down verification process, primitive that is partially extracted during former processing is recovered by using a local adaptive segmentation technique, which is intended to accommodate to different noise-to-signal levels. Experimental results validate the robust performance of this approach in the presence of heavy noise in real-time.

In this paper, considering the imperfect (incomplete, imprecise, uncertain, inconsistent) information sources in information fusion, To avoid and reduce the influence of the mistaken or misleading information on the final precision of fusion, the ESMS (evidence supporting measure of similarity) filter is designed and added to generalized fusion machine (GFM), and an ESMS function (not unique) to select evidence sources before the multi-sources information entering into the Fusion Machine is proposed and proved. Due to considering the barycentre of belief masses in four cases respectively, the fusion result becomes more precise. At last, we apply the new tool coupling with the fusion machine based on DSmT and PCR5 to robotpsilas robot perception. It shows a better performance in solving the challenging work with ESMS filter than that without one.

In this paper, we propose the pre-processor based on the Evidence Supporting Measure of Similarity (ESMS) filter and also propose the unified fusion approach (UFA) based on the general fusion machine coupled with ESMS filter, which improve the correctness and precision of information fusion in any fields of application. Here we mainly apply the new approach to Simultaneous Localization And Mapping (SLAM) of Pioneer II mobile robots. A simulation experiment was performed, where an autonomous virtual mobile robot with sonar sensors evolves in a virtual world map with obstacles. By comparing the result of building map according to the general fusion machine (here DSmT-based fusing machine and PCR5-based conflict redistributor considereded) coupling with ESMS filter and without ESMS filter, it shows the benefit of the selection of the sources as a prerequisite for improvement of the information fusion, and also testifies the superiority of the UFA in dealing with SLAM., {"references":["U. Frese, P. Larsson, T. Duckett (2005). A Multilevel Relaxation\nAlgorithm for Simultaneous Localization And Mapping. IEEE Trans.\nRobotics and Automation, 21(2), 196-207.","Shafer G. A. (1976). Mathematical Theory of Evidence. Princeton\nUniversity Press, Princeton, NJ, 297pp.","Ph. Smets (2000). Data Fusion in the Transferable Belief Model,\nPresented at the 2000 Int. Conf. Information Fusion, Paris.","Smarandache F., Dezert J. (Editors)( 2004), Advances and Applications\nof DSmT for Information Fusion, American Research Press, Rehoboth, ,\nAvailable: http://www.gallup.unm.edu/~smarandache/DSmT-book1.pdf","F. Smarandache (2004) Unification of Fusion Theories (UFT).\nInternational Journal of Applied Mathematics & Statistics, vol. 2,1-14.","R.R.Yager(1983). Hedging in the Combination of Evidence. Journal of\nInformation and Optimization Science, 4(1), 73~81.","D. Dubois, H. Prade (1988). Representation and Combination of\nUncertainty with Belief Functions and Possibility Measures.\nComputational Intelligence, vol.4, 244~264.","M. Daniel (2000). Distribution of Contradictive Belief Masses in\nCombination of Belief Functions. Information, Uncertainty and Fusion,\nKluwer Academic Publishers, 431~446","F. Smarandache, J. Dezert (2005). Information Fusion Based on New\nProportional Conflict Redistribution Rules. Presented at the 2005 Int.\nConf. Information Fusion, Philadelphia, PA, USA.\n[10] X. Li, J. Dezert, X. Huang (2006). Selection of Sources as a Prerequesite\nfor Information Fusion with Application to SLAM. Proc. Int. Conf. on\nInformation Fusion, Florence, Italy, July 10-13.\n[11] J. Dezert, F. Smarandache (2003). On the Generation of Hyper-power\nSets for the DSmT. Presented at the 2003 Int. Conf. Information Fusion,\npp.1118-1125, Cairns, Queensland, Australia,8-11 .\n[12] J. Dezert, F. Smarandache (2003). Partial Ordering of Hyper-power Sets\nand Matrix Representation of Belief Functions within DSmT. Presented at\nthe 2003 Int. Conf. Information Fusion, pp.1230-1138, Cairns,\nQueensland, Australia, 8-11.\n[13] B. Ristic, Ph. Smets (2006) Association of Uncertain Combat ID\nDeclarations. Presented at the Proc. of Cogis-06 Conf.,Paris.\n[14] X. Li, X. Huang, M. Wang (2006). A Comparision of The Effect of Sonar\nGrid Map Building Based on DSmT and DST. IEEE Int Conf\nWCICA2006, Dalian, China, in press.\n[15] X. Li, X. Huang, M. Wang (2006). Robot Map Building from Sonar\nSensors and DSmT,\" Inf. & Sec.: An Int. J., Bulg. Acad. of Sci., Sofia.\n[16] A. Martin, C. Osswald (2006). A New Generalization of The\nProportional Conflict Redistribution Rule Stable in Terms of Decision. To\nappear in \"Advances and Applications of DSmT for Information Fusion\",\nVol.2, July 2006, F. Smarandache and J. Dezert (Editors), in preparation."]}

The scale-invariant feature detecting methods always require a lot of computation yet sometimes still fail to meet the real-time demands in robot vision fields. To solve the problem, a quick method for detecting interest points is presented. To decrease the computation time, the detector selects as interest points those whose scale normalized Laplacian values are the local extrema in the nonholonomic pyramid scale space. The descriptor is built with several subregions, whose width is proportional to the scale factor, and the coordinates of the descriptor are rotated in relation to the interest point orientation just like the SIFT descriptor. The eigenvector is computed in the original color image and the mean values of the normalized color g and b in each subregion are chosen to be the factors of the eigenvector. Compared with the SIFT descriptor, this descriptor's dimension has been reduced evidently, which can simplify the point matching process. The performance of the method is analyzed in theory in this paper and the experimental results have certified its validity too.

This paper deals with enriched qualitative belief functions for reasoning under uncertainty and for combining information expressed in natural language through linguistic labels. In this work, two possible enrichments (quantitative and/or qualitative) of linguistic labels are considered and operators (addition, multiplication, division, etc) for dealing with them are proposed and explained. We denote them $qe$-operators, $qe$ standing for "qualitative-enriched" operators. These operators can be seen as a direct extension of the classical qualitative operators ($q$-operators) proposed recently in the Dezert-Smarandache Theory of plausible and paradoxist reasoning (DSmT). $q$-operators are also justified in details in this paper. The quantitative enrichment of linguistic label is a numerical supporting degree in $[0,\infty)$, while the qualitative enrichment takes its values in a finite ordered set of linguistic values. Quantitative enrichment is less precise than qualitative enrichment, but it is expected more close with what human experts can easily provide when expressing linguistic labels with supporting degrees. Two simple examples are given to show how the fusion of qualitative-enriched belief assignments can be done., Comment: 12 pages

Detecting scale-invariant feature is very important in robot vision fields, such as object recognition and vision-based localization. However, the methods detecting features always have a lot of computation and can not meet the real-time demand. To solve the problem, a quick method for detecting interest points is presented. It is based on a nonholonomic pyramid frame, whose influence on the repeatability is analyzed in theory in this paper. The method computes the Harris corners in each level in image nonholonomic pyramid scale space and uses difference of Gaussian to select the interest points. The points are robust to image translation, image rotation, image noise, scale changes, illumination changes and so on. Most important of all, the method can ensure the performance and evidently decrease the computation time at the same time. The experimental results have certified its validity.

In this paper, a new method of information fusion – DSmT (Dezert and Smarandache Theory) is introduced to apply to managing and dealing with the uncertain information from robot map building. Here we build grid map form sonar sensors and laser range finder (LRF). The uncertainty mainly comes from sonar sensors and LRF. Aiming to the uncertainty in static environment, we propose Classic DSm (DSmC) model for sonar sensors and laser range finder, and construct the general basic belief assignment function (gbbaf) respectively. Generally speaking, the evidence sources are unreliable in physical system, so we must consider the discounting theory before we apply DSmT. At last, Pioneer II mobile robot serves as a simulation experimental platform. We build 3D grid map of belief layout, then mainly compare the effect of building map using DSmT and DST. Through this simulation experiment, it proves that DSmT is very successful and valid, especially in dealing with highly conflicting information. In short, this study not only finds a new method for building map under static environment, but also supplies with a theory foundation for us to further apply Hybrid DSmT (DSmH) to dynamic unknown environment and multi-robots- building map together.

This paper presents a new tool based on DSmT (Dezert-Smarandache Theory) and fast-Hough self-localization which is applied to autonomous mobile robot's map reconstruction. Uncertainty from sonar information is fused and managed in rebuilding grid map effectively with DSmT, since fast-Hough self-localization from laser information overcomes some shortcomings of classical Hough transformation including high amount of computation and low precision of localization. When a virtual mobile robot evolves in the virtual environment with different outline features, the result can adequately testify that the new tool owns better performance to rebuild map. In general, this research provides an approach for studying autonomous navigation of mobile robot or unmanned land vehicle (ULV) in unknown environment, also provides a human- computer interactive interface to manage and manipulate the robot remotely.

We consider in this work evidential sources of information and propose a very general Evidence Supporting Measure of Similarity (ESMS) for selecting the most coherent subset of sources to combine among all sources available at each instant. The methodology proposed here coupled with a DSmT-based fusion machine is tested in robotics for the automatic estimation of an unknown simulated environment with obstacles where an autonomous mobile Pioneer II robot with sonar sensors evolves. Our simulation results are based on the fusion of similar and equireliable sensors but same approach can also be used with dissimilar sources as well by using a discounting method taking into account the reliability of each sensor. Our results show clearly the benefit of the selection of the sources as prerequesite for improvement of information fusion.

In this paper, considering the information fusion of multi-sensors on mobile robot, a new tool (the fusion machine of DSmT (Dezert-Smarandache theory) coupling with PCR5 (proportional conflict redistribution rule)) is applied to autonomous mobile robot's map reconstruction from 16 sonar rangefinders. According to the physical characteristics of sonar rangefinder, general basic belief assignment functions are constructed respectively. By comparing the result of map reconstruction with this new tool from other approaches (i.e. probability, fuzzy, DST), when a virtual mobile robot evolves in the virtual environment with obstacles, we can adequately testify that the new tool owns better performance to rebuild map and even can solve the challenging SLAM problem more effectively

Information acquired in map building presents characteristics of uncertainty, imprecision and even high conflict, especially in the course of building grid map using sonar. Here a new method of information fusion - DSmT (Dezert-Smarandache theory) recently developed from DST and Bayesian theory was introduced to apply to managing and dealing with this uncertainty. Aiming to static environment, classic DSm mathematic modal was established by constructing the general basic belief assignment function, so that the global evidence grid map is built by applying the classic DSm rule. Pioneer II virtual mobile robot served as an experiment platform. By comparing the numbers of acquiring-information spot, the quality of grid map building and the time in need of finishing the global map building, better fusion results than that with DST are gotten. Especially when dealing with high conflictive information from sonar grid map building, DSmT was more effective and successful than DST. In short, this study not only found a new method for building map under static environment, but also supplied with a theory foundation for us to further apply hybrid DSmT to dynamic unknown environment and multi-robots' building map together

Transurethral electrovaporization of the prostate (TVP) for benign prostatic hyperplasia (BPH) has proven to be efficacious with lower morbidity than transurethral resection of the prostate (TURP) on clinical studies. However, no histopathologic data are available to support the clinical findings in human studies. The following study was done using a canine model in an effort to evaluate these histopathologic changes.Nine canines received antegrade electrovaporization or resection of the prostate, via an open cystoma, using Storz series resectoscope and video equipment. The dogs were sacrificed and their prostates harvested at 0 week (immediately after operation), 1 week or 5 weeks after electrovaporization or resection. The prostates were evaluated grossly as well as histologically for cavitary defects and depth of necrosis.Prostate examination revealed superficial necrosis (less than 1.8 mm deep) at 0 week following the 270 watts operation, and less than 3 mm deep necrosis with acute inflammation and focal hemorrhage at 1 week. The depths of necrosis were less than 1.3 mm and 2.2 mm at 0 week and 1 week after the 180 W electrovaporizion. And the 120 W resection resulted in necrosis 1.1 mm and 1.6 mm deep at most, which was localized in the vaporized prostate only, with no histopathologic change in the surrounding tissues. Epithelial stratification was underway by the fifth week, but with inflammation.TVP in the canine model showed only shallow necrosis at the site of the vaporization. These data provide a histopathologic rationale for the minimal morbidity and efficacious nature of this technique demonstrated in clinical studies.

To evaluate spiral CT urography (SCTU) and CT virtual endoscopy (CTVE) in detecting urologic diseases.SCTU was performed in 46 patients with urological diseases including renal neoplasms (2), paropelvic cysts (2), ureteral calculi (6), ureteral stenosis (4), ureteral neoplasms (2), double kidneys and ureter malformation (1), bladder neoplasms (28) and bladder endometreosis (1). The 6 patients with ureteral diseases and 29 patients with bladder diseases underwent CTVE based on spiral CT scan. All CTVE findings were compared with those of B-mode ultrosonography, intravenous urography (IVU), retrograde pyelography (RGP), conventional CT or cystoscopy.All upper urinary tract diseases and bladder diseases (28 cases) were detected by SCTU and CTVE scans and they were confirmed operatively or pathologically except one case of bladder neoplasm (diameter less than 5 mm) was missed.SCTU and CTVE have proved to be non-invasive and reliable in the diagnosis of urological diseases and are superior to IVU or conventional CT. CTVE can serve as a supplementary method to fiberoptic cystoscopy or ureteroscopy.

Our previous studies showed that recombinant high-density lipoprotein (rHDL) rHDL74 exhibited higher anti-inflammatory capabilities compared to wild-type rHDL (rHDLwt), while rHDL228 showed hyper-proinflammation. In this paper, we further investigated the potential mechanisms involved in their different inflammatory functions using two models: endotoxemic mice and the RAW264.7 inflammation model. Our results showed that 24 h after the injection of lipopolysaccharide (LPS), mice treated with rHDL74 had a significant decrease in plasma CRP (P