Optimization of bipolar plate design for flow and temperature distributions using numerical techniques

Although water is fed controllably into the flow channels in the bipolar plates surrounding the membrane electrode assembly (MEA), the complex flow geometry can lead to non-uniformity of the flow and temperature distribution inside the channels. In addition, non-uniform temperature distribution in the cell will affect the electrochemical process for hydrogen production or fuel cell applications. There are many studies on the theoretical analysis of fuel cells, but not many have been reported on the characteristics of the PEM electrolyzer; In this thesis work, numerical simulations were carried out on the basic bipolar plate given by the Proton Energy Systems in the United States. A 3-D steady state, incompressible flow model was developed. Finite volume method was used to solve the model for flow and temperature distributions inside the channels of the bipolar plate; A parametric study was performed based on number of inlets and outlets and an optimized bipolar plate design was selected. Later, the optimized model was again simulated for two-phase flow. The flow and temperature distributions inside the channels of the new bipolar plate design were found to be uniform even for two-phase flow. Again a parametric study was performed based on volumetric flow rate of water and mass flow rate of oxygen production. Results were tabulated and numerical values were compared with the back of the envelope calculations

2D Floor Plan Segmentation Based on Down-sampling

In recent years, floor plan segmentation has gained significant attention due to its wide range of applications in floor plan reconstruction and robotics. In this paper, we propose a novel 2D floor plan segmentation technique based on a down-sampling approach. Our method employs continuous down-sampling on a floor plan to maintain its structural information while reducing its complexity. We demonstrate the effectiveness of our approach by presenting results obtained from both cluttered floor plans generated by a vacuum cleaning robot in unknown environments and a benchmark of floor plans. Our technique considerably reduces the computational and implementation complexity of floor plan segmentation, making it more suitable for real-world applications. Additionally, we discuss the appropriate metric for evaluating segmentation results. Overall, our approach yields promising results for 2D floor plan segmentation in cluttered environments

Host plant root exudates reduce phytonematode cuticle aging to maintain Pasteuria endospore attachment

Endospores of the nematode hyperparasite from the Pasteuria group of Gram-positive bacteria have the potential to suppress phytonematode populations and reduce root infection. Parasitism by the bacteria commences when endospores adhere to the nematode cuticle before they germinate and infect the developing nematode thereby prohibiting the nematode from producing eggs. Here we demonstrate that in a comparison between a Pasteuria endospore population that infects root-knot nematodes (Meloidogyne incognita) and an endospore population that infects pigeon pea cyst nematodes (Heterodera cajani), as the nematodes age there is a similar reduction in endospore encumbrance on both nematode species. To test the hypothesis that multitrophic evolutionary theory would suggest that plants might recruit bacteria that reduce phytonematode root parasitism, we exposed the two phytonematode species to root exudates of hosts, poor hosts and non-hosts plants and undertake standardised endospore encumbrance bioassays over a two-week aging period. The results showed that the normally expected reduction in endospore attachment due to aging was reduced when root-knot nematodes were exposed to root exudates from their host plants, cowpea and tomato, but not potato, whereas in the case of pigeon pea cyst nematode, the root-exudates from the homologous host plant, cowpea, also reduced the expected reduction in the decrease in endospore attachment due to aging. However, unexpectedly similar results were also produced by root exudates of the non-host, potato. These results are discussed in the light of the characterisation of the root-exudates by gas-liquid chromatography. It is concluded that signalling compounds present in root-exudates can affect cuticle aging both positively and negatively that in turn affects endospore attachment. However, the results are not strictly in line with what multitrophic interactions would have predicted.Non peer reviewe

A New Method for Impulse Noise Removal in Remote Sensing Images

Existing filtering algorithms use all pixels within a window to filter out the impulse noise. They increase the size of neighboring pixels with the increase of noise density. In this paper, we propose an impulse noise removal algorithm for remote sensing images, that emphasis on few noise-free pixels. The detection map (DM) is constructed from the input noisy image, by assigning a binary value 1 for each corrupted pixel in the input image. By using the detection map, the proposed iterative algorithm searches the noise free pixels with in a small neighborhood. The noisy pixel is then replaced with the median value estimated from noise free pixels. In-order to better appraise the noise cancellation behavior of our filter from the point of view of human perception, we perform segmentation via spline regression on remote sensing image for both noisy image and filtered image. Experimental results show that the filtering performance of the proposed approach is very satisfactory providing better feature extraction in remote sensing images

Understanding nematode suppressive soils: molecular interactions between Pasteuria endospores and the nematode surface coat

K. G. Davies, A. Srivastava, K. Kumar, and S. Mohan, ‘Understanding nematode suppressive soils: molecular interactions between Pasteuria endospores and the nematode surface coat’, Aspects of Applied Biology 130, 4th Symposium of Potato Cyst Nematode Management (including other nematode parasites of potatoes), pp. 143-147, September 2015.The knowledge that the plant-parasitic nematode hyperparasite Pasteuria penetrans is important in nematode suppressive soils has long been recognised. The ability to mass produce this organism in vitro circumvents one of its major constraints. However, successful biological control can only be established if the strains that are deployed can attach to and infect pest nematodes. Currently, in respect to the Pasteuria that infects root-knot nematodes (Meloidogyne spp), it is thought that collagen-like fibres on the surface of the endospore are interacting with a receptor on the nematode cuticle and that mucin-like molecules play an important role in modulating this process. Here we report that an antibody raised to whole endospores of P. penetrans also recognises extracts from endospores of Bacillus thuringiensis (Bt), suggesting that Bt can be used as a model for Pasteuria endospores. Bioinformatics shows that mucin-like genes identified in C. elegans are present in Globodera pallida.Final Accepted Versio

Development of a New Ground Motion Model for a Peninsular Indian Rock Site

The ground motion model (GMM) plays a vital role in the generation of seismic design basis ground motion parameters. Even though many intra-plate GMMs are available, very few of them are based on Peninsular India (PI) region-specific seismological parameters. Hence, it is imperative to develop a GMM using seismological parameters derived from earthquakes in the Peninsular Indian region. In this study, a new GMM is developed for a PI rock site. Due to the scarcity of real earthquakes, artificial earthquake records are simulated to generate a new GMM for PI. The accelerograms of these artificial earthquakes are obtained from the stochastic finite fault simulation technique. Region-specific seismological parameters are obtained from the available PI earthquakes. The generated GMM is compared with other intra-plate GMMs for different earthquake magnitudes. Also, the generated GMM is validated with the Koyna earthquake record and it is observed that the GMM’s predictions are closer to the record

Weight Function Approach for Semi Elliptical Crack at Blade Mounting Locations in Steam Turbine Rotor System

This paper presents analysis of stress intensity factors at blade mounting locations of steam turbine rotor system. General expressions for the stresses induced in a rotating disc are derived and these equations are applied to steam turbine rotor disc. It is observed that the radial stress increases instantly at blade mounting location which indicates the probability of crack initiation and growth. A semi elliptical crack is considered at that location and weight function approach is used to determine the stress intensity factors. The results are validated with the influence coefficient approach. The differences of present approach with influence coefficient approach are less than 3 %. Hence the present approach is suitable for determination of stress intensity factors in a semi elliptical crack at blade mounting locations of a steam turbine rotor disc

A clinical analysis of outcome in management of head injury in patients with highway road accidents

Background: Road traffic accidents (RTAs) are a major cause of misery, disability and death globally, with a disproportionate number occurring in developing countries. Complications from closed head injuries are the single largest cause of morbidity and mortality in patients who reach the hospital alive. The present study assesses the outcome in the management of head injury admitted in our hospital following RTA in the period of one year.  Methods: This retrospective study carried out in the department of Neurosurgery in a rural tertiary hospital, Kolar, Karnataka, India. Patients who got admitted between periods of January 2012 to January 2013 were included in the study. All patients were clinically evaluated by a team comprising of doctors from surgical, medical and orthopedics specialties in the emergency department and subsequently admitted and treated at neurosurgery. The study was conducted based on these reports and observations and outcome of patients. The results were expressed as percentages.Results: At the time of admission 41% patients were under alcoholic influence, 97% patients had history of LOC, 50% patients had ENT bleed and 7.5% had CSF leak.  The GCS score of less than 8 was seen in 33% cases, 9 to12 in 52% cases and between 12 to 14 in 15% patients. As per Glasgow outcome scale (GOS), 91% of patients had good recovery, 5.5% patients had disability (hemiparesis, ptosis) and 3.5% patients died in the course of treatment. Conclusions: Head injury due to RTA is a recognized major public health problem causing death and disability among the population. So it should be managed in time and also should be looked seriously by concerned authority for reducing the incidences of head injury associated with RTA and protecting people by debilitating conditions

Panoptic Out-of-Distribution Segmentation

Deep learning has led to remarkable strides in scene understanding with panoptic segmentation emerging as a key holistic scene interpretation task. However, the performance of panoptic segmentation is severely impacted in the presence of out-of-distribution (OOD) objects i.e. categories of objects that deviate from the training distribution. To overcome this limitation, we propose Panoptic Out-of Distribution Segmentation for joint pixel-level semantic in-distribution and out-of-distribution classification with instance prediction. We extend two established panoptic segmentation benchmarks, Cityscapes and BDD100K, with out-of-distribution instance segmentation annotations, propose suitable evaluation metrics, and present multiple strong baselines. Importantly, we propose the novel PoDS architecture with a shared backbone, an OOD contextual module for learning global and local OOD object cues, and dual symmetrical decoders with task-specific heads that employ our alignment-mismatch strategy for better OOD generalization. Combined with our data augmentation strategy, this approach facilitates progressive learning of out-of-distribution objects while maintaining in-distribution performance. We perform extensive evaluations that demonstrate that our proposed PoDS network effectively addresses the main challenges and substantially outperforms the baselines. We make the dataset, code, and trained models publicly available at http://pods.cs.uni-freiburg.de