Learned navigation in unknown terrains: A retraction method

The problem of learned navigation of a circular robot R, of radius delta (is greater than or equal to 0), through a terrain whose model is not a-priori known is considered. Two-dimensional finite-sized terrains populated by an unknown (but, finite) number of simple polygonal obstacles are also considered. The number and locations of the vertices of each obstacle are unknown to R. R is equipped with a sensor system that detects all vertices and edges that are visible from its present location. In this context two problems are covered. In the visit problem, the robot is required to visit a sequence of destination points, and in the terrain model acquisition problem, the robot is required to acquire the complete model of the terrain. An algorithmic framework is presented for solving these two problems using a retraction of the freespace onto the Voronoi diagram of the terrain. Algorithms are then presented to solve the visit problem and the terrain model acquisition problem

Fault Diagnosis of Hybrid Computing Systems Using Chaotic-Map Method

Computing systems are becoming increasingly complex with nodes consisting of a combination of multi-core central processing units (CPUs), many integrated core (MIC) and graphics processing unit (GPU) accelerators. These computing units and their interconnections are subject to different classes of hardware and software faults, which should be detected to support mitigation measures. We present the chaotic-map method that uses the exponential divergence and wide Fourier properties of the trajectories, combined with memory allocations and assignments to diagnose component-level faults in these hybrid computing systems. We propose lightweight codes that utilize highly parallel chaotic-map computations tailored to isolate faults in arithmetic units, memory elements and interconnects. The diagnosis module on a node utilizes pthreads to place chaotic-map threads on CPU and MIC cores, and CUDA C and OpenCL kernels on GPU blocks. We present experimental diagnosis results on five multi-core CPUs; one MIC; and, seven GPUs with typical diagnosis run-times under a minute

Determinants of range of motion in cruciate retaining total knee arthroplasty: a prospective study

Background: Total knee replacement (TKR) is to provide a stable painless knee with adequate range of motion (ROM) for daily activities. The aim of the study is to evaluate various factors that influence ROM in cruciate retaining TKR postoperatively.Methods: Fourty four patients with osteoarthritis knee treated in our institute with TKR using cruciate retaining prosthesis are included in study and analysed prospectively. Mean follow up was 6 months. Patients are analyzed for following factors–age, gender, BMI, preoperative ROM, changes in posterior femoral condylar offset, posterior tibial slope after surgery. Statistical analysis of effect of all factors on knee ROM was done. Assessment was done preoperatively and 3 and 6 months postoperatively.Results: Gender did not affect the final ROM. Mean age of patients is 65. Age has negative correlation with ROM (p=-0.45). The mean knee range improved from 92˚ to 101˚. Factors that negatively affect ROM include, BMI (p=-0.04) and Preoperative flexion deformity (p=-0.03). Factors that positively affect ROM include, knee scores and good preoperative flexion (p=0.001). Males have good amount of flexion preoperatively and post operatively when compared to females.Conclusions: Preoperative ROM, flexion contracture and BMI are the important factors affecting the range of motion in total knee arthroplasty. Proper counselling of patient preoperatively regarding these various factors and appropriate selection of patient is of utmost important for satisfactory functional outcome

An Algorithmic Framework for Robot Navigation in Unknown Terrains.

The problem of navigating a robot body through a terrain whose model is a priori known is well-solved problem in many cases. Comparatively, a lesser number of research results have been reported about the navigation problem in unknown terrains i.e., the terrains whose model are not a priori known. The focus of our work is to obtain an algorithmic framework that yields algorithms to solve certain navigational problems in unknown terrains. We consider a finite-sized two-dimensional terrain populated by a finite set of obstacles $O$ = \{O\sb1,O\sb2,\...,O\sb{n}\} where O\sb{i} is a simple polygon with a finite number of vertices. Consider a circular body R, of diameter $\delta\geq$ O, capable of translational and rotational motions. R houses a computational device with storage capability. Additionally, R is equipped with a sensor system capable of detecting all visible vertices and edges. We consider two generic problems of navigation in unknown terrains: the Visit Problem, VP, and the Terrain model acquisition Problem, TP. In the visit problem, R is required to visit a sequence of destination points d\sb1,d\sb2,\...,d\sb{M} in the specified order. In the terrain model acquisition problem, R is required to acquire the model of the terrain so that it can navigate to any destination without using sensors and by using only the path planning algorithms of known terrains. We present a unified algorithmic framework that yields correct algorithms to solve both VP and TP. In this framework, R \u27simulates\u27 a graph exploration algorithm on an incrementally-constructible graph structure, called the navigation course, that satisfies the properties of finiteness, connectivity, terrain-visibility and local-constructibility. Additionally, we incorporate the incidental learning feature in our solution to VP so as to enhance the performance. We consider solutions to VP and TP using navigation courses based two geometric structures, namely the visibility graph and the Voronoi diagram. In all the cases, we analyze the performance of the algorithms for VP and TP in terms of the number of scan operations, the distance traversed and the computational complexity

Phylogenetic relationships of three new microsporidian isolates from the silkworm, Bombyx mori

The pathogenicity, mode of transmission, tissue specificity of infection and the small subunit rRNA (SSU-rRNA) gene sequences of the three new microsporidian isolates from the silkworm Bombyx mori were studied. Out of the three, NIK-2r revealed life cycle features and SSU-rRNA gene sequence similar to Nosema bombycis, suggesting that it is N. bombycis. The other two, NIK-4m and NIK-3h, differed from each other as well as from N. bombycis. NIK-4m was highly pathogenic and did not show any vertical transmission, in accordance with the apparent lack of gonadal infection, whereas NIK-3h was less pathogenic and vertical transmission was not detected but could not be excluded. Phylogenetic analysis based on SSU-rRNA gene sequence placed NIK-3h and NIK-4m in a distinct clade that included almost all the Vairimorpha species and Nosema species that infect lepidopteran and non-lepidopteran hosts, while NIK-2r was included in a clade containing almost all the Nosema isolates that infect only lepidopteran hosts. Thus, we have presented molecular evidence that one of the three isolates is in fact the type species N. bombycis, while the other two isolates are Vairimorpha spp. There was distinct separation of microsporidian isolates infecting only lepidopteran hosts and those infecting lepidopteran and non-lepidopteran hosts, reflecting possible co-evolution of hosts and microsporidian isolates

The effect of magnesium sulfate as an adjuvant to 0.5% bupivacaine on motor and sensory supraclavicular brachial plexus blockade

Background: Magnesium is a physiologic cation that blocks neuromuscular transmission and does not allow the nerve to be stimulated. This study investigates the effect of adding magnesium sulfate to 0.5% bupivacaine to extend the duration of sensory and motor blocks of the supraclavicular brachial plexus in orthopedic surgeries of the upper extremities.Methods: This controlled randomized double-blind study was performed on patients who were candidates for orthopedic surgery of the upper extremities. A total of 60 patients between 18 and 60 years with ASA Class 1 or 2 participated in the study. One Group M received 0.5% bupivacaine (1.5 mg/kg) with magnesium sulfate 20% (3 ml) as the case group, while the second Group P received 0.5% bupivacaine (1.5 mg/kg) with normal saline (3 ml) as a placebo to block the supraclavicular brachial plexus using nerve locator. The duration of the sensory and motor block of the supraclavicular brachial plexus was monitored and evaluated using the pinprick and modified Bromage scale.Results: A total of 60 patients were included in the study with 30 patients having received 0.5% bupivacaine plus magnesium and the other 30 patients having received 0.5% bupivacaine plus normal saline. The mean sensory block duration in the case Group M was 249±9.36 and in control Group P was 160±5.62 (p<0.39). The mean motor block duration in the case Group M was 232±9.64 and in control Group P was 147±26.52 (both p<0.32). The mean onset of sensory block in case Group M was 15.5±2.16 and the onset block in control Group P was 12.73±1.18 (p<0.49; statistically not significant). The mean onset of motor block in case Group M was 23.5±1.1 and the onset block in control Group P was 41±3 (p<0.53; statistically not significant).Conclusions: The addition of magnesium sulfate to 0.5% bupivacaine increased the duration of motor and sensory supraclavicular brachial block in the upper extremities during surgeries when compared to the use of 0.5% bupivacaine alone, though statistically not significant, but definitely in clinically significant proportions

Energy Efficient Estimation of Gaussian Sources Over Inhomogeneous Gaussian MAC Channels

It has been shown lately the optimality of uncoded transmission in estimating Gaussian sources over homogeneous/symmetric Gaussian multiple access channels (MAC) using multiple sensors. It remains, however, unclear whether it still holds for any arbitrary networks and/or with high channel signal-to-noise ratio (SNR) and high signal-to-measurement-noise ratio (SMNR). In this paper, we first provide a joint source and channel coding approach in estimating Gaussian sources over Gaussian MAC channels, as well as its sufficient and necessary condition in restoring Gaussian sources with a prescribed distortion value. An interesting relationship between our proposed joint approach with a more straightforward separate source and channel coding scheme is then established. We then formulate constrained power minimization problems and transform them to relaxed convex geometric programming problems, whose numerical results exhibit that either separate or uncoded scheme becomes dominant over a linear topology network. In addition, we prove that the optimal decoding order to minimize the total transmission powers for both source and channel coding parts is solely subject to the ranking of MAC channel qualities, and has nothing to do with the ranking of measurement qualities. Finally, asymptotic results for homogeneous networks are obtained which not only confirm the existing optimality of the uncoded approach, but also show that the asymptotic SNR exponents of these three approaches are all the same. Moreover, the proposed joint approach share the same asymptotic ratio with respect to high SNR and high SMNR as the uncoded scheme

Crafts and gear used for marine fishing along the Andhra Pradesh coast

Until the middle of nineteen sixties fishing for marine finfishes and shellfishes along the Andhra Pradesh coast used to be carried out employing indigenous non-mechanised crafts. Subsequently trawlers and later mechanised vessels operating gillnets came into use which resulted in the increased fish production. Use of outboard engine on indigenous crafts for reaching fishing grounds is a recent feature of near the coast fishing. The different kinds of non-mechanised and mechanised crafts and gear employed in the region are dealt with in this article

Influence of Exogenous Glycinebetaine on Hot Pepper under Water Stress

A study was conducted to evaluate the effect of exogenous application of glycinebetaine (GB) on physiological response in hot-pepper (Capsicum annuum L. vs. Arka Lohit and Pusa Jwala) under water stress. Glycinebetaine was applied to seeds as well as plants through foliar applications. Water stress affected considerably the morphophysiological parameters in both the cultivars. However, in glycinebetaine (GB) treated plants, plant height, leaf area (LA), flower and fruit number and total dry matter (TDM) were greater compared to the untreated stress plants (T4) under water stress. Glycinebetaine application enhanced the photosynthesis (PN) in water deficit experiencing plants, mostly due to a greater stomatal conductance (gs) and carboxylation efficiency of CO2&nbsp;assimilation. In both the cultivars after 12 day of stress, the PN&nbsp;decreased from 10.1 to 1.0-1.3 μ mol m-2&nbsp;s-1&nbsp;in untreated stressed plants (T4), while in the treated stressed plants PNhad reduced to 2.0 - 3.0 μ mol m-2&nbsp;s-1&nbsp;(T1 - T3). The application of GB increased the WUE in both the cultivars. The better WUE in treated plants of hot-pepper under stress was attributed to the improved PN. The higher per plant yield in the GB applied plants under stress in both the cultivars associated with higher PNrate, gs and WUE in treated plants. Though there was an increase in PN&nbsp;rate, WUE and plant yield in the treated plants (T1 - T3), the better results were found in the plants (T2) where seeds were treated and foliar application was given at the time of imposing stress