A clinical retrospective evaluation of FA/HA coated (Biocomp) dental implants. Results after 1 year

The development of ovulation-inducing drugs has enabled clinicians to more effectively treat the hypothalamic, pituitary, and ovarian abnormalities resulting in infertility. Pregnancy rates have been improved with the use of agents such as clomiphene citrate (CC), human menopausal gonadotropin [hMG or follicle-stimulating hormone (FSH) preparations], with gonadotropin-releasing hormone (GnRH) and its analogs, stimulating the development of multiple ovarian follicles and increasing the number of fertilizable oocytes. The use of these drugs is not without certain detrimental or "toxic" consequences. The negative effects from superovulation can occur during follicle development, decreasing the number of healthy oocytes and embryos capable of leading to viable pregnancy. Ovulation induction can lead not only to higher incidences of spontaneous abortions, and multiple and ectopic pregnancies, but also to poor pregnancy rates, due, in part, to asynchrony between embryonic development and the uterine environment. Diseases such as ovarian hyperstimulation syndrome (OHSS), resulting in the secretion of supraphysiologic levels of estradiol, can lend to severe health complications, possibly requiring hospitalization. Most drugs used for ovulation induction can lead to OHSS. Although incidences of OHSS following CC use are less frequent, CC has been associated with hot flushes, multiple gestations, visual disturbances, cervical mucus abnormalities, and luteal phase deficiency. Finally, there are reports that link any or all of the ovulation-inducing drugs with a higher incidence of ovarian and breast cancer, however, a cause-effect relationship has yet to be proven.     

Functional correction of renal defects in a mouse model for ARPKD through expression of the cloned wild-type Tg737 cDNA

Autosomal recessive polycystic kidney disease (ARPKD) is characterized by the formation of large collecting tubule and ductular cysts that often result in renal insufficiency within the first decade of life. Understanding the process leading to cyst formation will require the identification and characterization of genes involved in the etiology of this disease. In this regard, we previously described the generation of a mouse model (TgN737Rpw) for ARPKD and the cloning of a candidate gene. Here we show direct involvement of the Tg737 gene in collecting duct cyst formation by expressing the wild-type Tg737 cDNA as a transgene in TgN737Rpw mutants. In contrast to TgN737Rpw mutants, the "rescued" animals survive longer, have normal renal function and normal localization of the EGFr to the basolateral surfaces of collecting duct epithelium.     

Isotype-specific antibody responses to foot-and-mouth disease virus in sera and secretions of "carrier' and "non-carrier' cattle

Isotype-specific antibody responses to foot-and-mouth disease virus (FMDV) were measured in the sera and upper respiratory tract secretions of vaccinated and susceptible cattle challenged with FMDV by direct contact or by intranasal inoculation. A comparison was made between cattle that eliminated FMDV and those that developed and maintained a persistent infection. Serological and mucosal antibody responses were detected in all animals after challenge. IgA and IgM were detected before the development of IgG1 and IgG2 responses. IgM was not detected in vaccinated cattle. Challenge with FMDV elicited a prolonged biphasic secretory antibody response in FMDV "carrier' animals only. The response was detected as FMDV-specific IgA in both mucosal secretions and serum samples, which gained statistical significance (P < 0.05) by 5 weeks after challenge. This observation could represent the basis of a test to differentiate vaccinated and/or recovered convalescent cattle from FMDV "carriers'.     

Localization of an unmanned ground vehicle based on hybrid 3D registration of 360 degree range data and DSM

A computer vision technique to identify the location of an outdoor unmanned ground vehicle (UGV) is presented. The proposed technique is based on hybrid 3D registration of 360 degree laser range data to a digital surface model (DSM). Range frames obtained from 48 laser detectors are aligned with the reference coordinate system of the DSM. Three novel approaches are proposed for accurate and fast 3D registration of range data and the DSM. First, a two-step hybrid 3D registration technique is proposed. A pair-wise registration step of two consecutive range frames is followed by a refinement step using a layered DSM. Second, a fast projection-based pair-wise registration is proposed by employing rasterized 360 degree range frames. Third, a high elevation DSM is divided into several elevation layers and correspondence search is done near the vehicle’s current elevation. This reduces the number of matching outliers and facilitates fast localization. Experimental results show that the proposed approaches yield better performance in 3D localization compared to conventional 3D registration techniques. Error analysis on five outdoor paths is presented with respect to ground truth.     

Localization algorithm using a virtual label for a mobile robot in indoor and outdoor environments

Scanning laser range sensors provide range data consisting of a set of point measurements. The laser sensor URG-04LX has a distance range of approximately 0.02–4 m and a scanning angle range of 240°. Usually, such an image range is acquired from one viewpoint by “moving” the laser beam using rotating mirrors/prisms. The orientation of the laser beam can easily be measured and converted into the coordinates of the image. This article conducts localization using virtual labels with data about distances in the environment obtained from 2D distance laser sensors. This method puts virtual labels on special features and points which are along the mobile robot’s path. The current location is calculated by combining the virtual label and the range image of the laser range finder.     

Redundant multicast routing in multilayer networks with shared risk resource groups: Complexity,models and algorithms

This paper presents a redundant multicast routing problem in multilayer networks that arises from large-scale distribution of realtime multicast data (e.g., Internet TV, videocasting, online games, stock quotes). Since these multicast services commonly operate in multilayer networks, the communications paths need to be robust against a single router or link failure as well as multiple such failures due to shared risk link groups (SRLGs). The main challenge of this multicast is to ensure the service availability and reliability using a path protection scheme, which is to find a redundant path that is SRLG-disjoint (diverse) from each working path. The objective of this problem is, therefore, to find two redundant multicast trees, each from one of the two redundant sources to every destination, at a minimum total communication cost whereas two paths from the two sources to every destination are guaranteed to be SRLG-diverse (i.e., links in the same risk group are disjoint). In this paper, we present two new mathematical programming models, edge-based and path-based, for the redundant multicast routing problem with SRLG-diverse constraints. Because the number of paths in path-based model grows exponentially with the network size, it is impossible to enumerate all possible paths in real life networks. We develop three approaches (probabilistic, non-dominated and nearly non-dominated) to generate potentially good paths that may be included in the path-based model. This study is motivated by emerging applications of internet-protocol TV service, and we evaluate the proposed approaches using real life network topologies. Our empirical results suggest that both models perform very well, and the nearly non-dominated path approach outperforms all other path generation approaches.     

Pattern recognition using feature feedback: Application to face recognition

In this paper, we propose a new pattern recognition method using feature feedback and present its application to face recognition. Conventional pattern recognition methods extract the features employed for classification using PCA, LDA and so on. On the other hand, in the proposed method, the extracted features are analyzed in the original space using feature feedback. Using reverse mapping from the extracted features to the original space, we can identify the important part of the original data that affects the classification. In this way, we can modify the data to obtain a higher classification rate, make it more compact or abbreviate the required sensors. To verify the applicability of the proposed method, we apply it to face recognition using the Yale Face Database. Each face image is divided into two parts, the important part and unimportant part, using feature feedback, and the classification performed using the feature mask obtained from feature feedback. Also, we combine face recognition with image compression. The experimental results show that the proposed method works well.     

Improving traversability of quadruped walking robots using body movement in 3D rough terrains

This paper presents a study on improving the traversability of a quadruped walking robot in 3D rough terrains. The key idea is to exploit body movement of the robot. The position and orientation of the robot are systematically adjusted and the possibility of finding a valid foothold for the next swing is maximized, which makes the robot have more chances to overcome the rough terrains. In addition, a foothold search algorithm that provides the valid foothold while maintaining a high traversability of the robot, is investigated and a gait selection algorithm is developed to help the robot avoid deadlock situations. To explain the algorithms, new concepts such as reachable area, stable area, potential search direction, and complementary kinematic margin are introduced, and the effectiveness of the algorithms is validated via simulations and experiments.