Electrical and microphysical responses to salt seeding in warm maritime cumulus clouds

Electrical, microphysical and dynamical responses to salt seeding have been investigated during cloud seeding experiments in several parts of India. Following massive salt seeding, increases in cloud temperature by I to 2 Celsius and cloud liquid water content up to 200 percent were observed in warm cumulus clouds (Ramahandra Murty eta., 1975, 1976). Cloud drop size distributions in seeded warm cumulus clouds increased in mean volume diameter up to 478 percent and computed liquid water content increased upward of 60 percent (Kapoor et al., 1976). In maritime warm cumulus clouds, which developed rain following seeding, the electric field reversed from initial negative to positive, occasionally preceded by intensification (Ramachandra Murty et al., 1976). This field reversal was attributed to the transport of large positive charges, from upper cloud levels to the base, by raindrops which form initially at higher levels in vigorous updraft regions. The prior intensification was attributed to updraft invigoration produced by massive salt seeding, since electrical activity is closely associated with convective activity (Latham and Stow, 1969)

Hypohidrotic Ectodermal Dysplasia with total anodontia: a case report

Ectodermal dysplasia is a hereditary disorder that occurs as a consequence of disturbances in the ectoderm of the developing embryo. The triad of nail dystrophy, alopecia or hypotrichosis and palmoplantar hyperkeratosis is usually accompanied by a lack of sweat glands and a partial or complete absence of primary and/ or permanent dentition. A case report illustrating the prosthetic rehabilitation of a seven year old boy with hypohidrotic ectodermal dysplasia associated with total anodontia is presented

CO2 fixation by seaweeds and their role in De-acidifying Ocean - An experimental approach

CO2 fixation by seaweeds and their role in De-acidifying Ocean - An experimental approac

Responses of Cyprinus carpio var. communis to Cyhalothrin, a pyrethroid insecticide

Haematological and biochemical profiles in a freshwater teleost, Cyprinus carpio var. communis, exposed to sub-lethal toxicity of the insecticide cyhalothrin were studied. During the treatment, erythrocyte count, haemoglobin content and protein content decreased, whereas leucocyte count and glucose level increased. The data are discussed in relation to the significance of haematological and biochemical changes as non-specific biomarkers against anthropogenic stress

Extending and validating the stencil processing unit

2016 Summer.Includes bibliographical references.Stencils are an important class of programs that appear in the core of many scientific and general-purpose applications. These compute-intensive kernels can benefit heavily from the massive compute power of accelerators like the GPGPU. However, due to the absence of any form of on-chip communication between the coarse-grain processors on a GPU, any data transfer/synchronization between the dependent tiles in stencil computations has to happen through the off-chip (global) memory, which is quite energy-expensive. In the road to exascale computing, energy is becoming an important cost metric. The need for hardware and software that can collaboratively work towards reducing energy consumption of a system is becoming more and more important. To make the execution of dense stencils more energy efficient, Rajopadhye et al. proposed the GPGPU-based accelerator called Stencil Processing Unit that introduces a simple neighbor-to-neighbor communication between the Streaming Multiprocessors (SM) on the GPU, thereby allowing some restricted data sharing between consecutive threadblocks. The SPU includes special storage units, called Communication Buffers, to orchestrate this data transfer and also provides an explicit mechanism for inter-threadblock synchronization by way of a special instruction. It claims to achieve energy-efficiency, compared to GPUs, by reducing the number of off-chip accesses in stencils which in turn reduces the dynamic energy overhead. Uguen developed a cycle-accurate performance simulator for the SPU, called SPU-Sim, and evaluated it using a matrix multiplication kernel which was not suitable for this accelerator. This work focuses on extending the SPU-Sim and evaluating the SPU architecture using a more insightful benchmark. We introduce a producer-consumer based inter-block synchronization approach on the SPU, which is more efficient than the previous global synchronization, and an overlapped multi-pass execution model in the SPU runtime system. These optimizations have been implemented into SPU-Sim. Furthermore, the existing GPUWattch power model in the simulator has been refined to provide better power estimates for the SPU architecture. The improved architecture has been evaluated using a simple 2-D stencil benchmark and we observe an average of 16% savings in dynamic energy on SPU compared to a fairly close GPU platform. Nonetheless, the total energy consumption on SPU is still comparatively high due to the static energy component. This high static energy on SPU is a direct impact of the increased leakage power of the platform resulting from the inclusion of special load/store units. Our conservative estimates indicate that replacing the current design of these L/S units with DMA engines can bring about a 15% decrease in the current leakage power of the SPU and this can help SPU outperform GPU in terms of energy

Knowledge Enabled Location Prediction of Twitter Users

As the popularity of online social networking sites such as Twitter and Facebook continues to rise, the volume of textual content generated on the web is increasing rapidly. The mining of user generated content in social media has proven effective in domains ranging from personalization and recommendation systems to crisis management. These applications stand to be further enhanced by incorporating information about the geo-position of social media users in their analysis. Due to privacy concerns, users are largely reluctant to share their location information. As a consequence of this, researchers have focused on automatic inferencing of location information from the contents of a user\u27s tweets. Existing approaches are purely data-driven and require large training data sets of geotagged tweets. Furthermore, these approaches rely solely on social media features or probabilistic language models and fail to capture the underlying semantics of the tweets. In this thesis, we propose a novel knowledge based approach that does not require any training data. Our approach uses Wikipedia, a crowd sourced knowledge base, to extract entities that are relevant to a location. We refer to these entities as local entities. Additionally, we score the relevance of each local entity with respect to the city, using the Wikipedia Hyperlink Graph. We predict the most likely location of the user by matching the scored entities of a city and the entities mentioned by users in their tweets. We evaluate our approach on a publicly available data set consisting of 5119 Twitter users across continental United States and show comparable accuracy to the state-of-the-art approaches. Our results demonstrate the ability to pinpoint the location of a Twitter user to a state and a city using Wikipedia, without needing to train a probabilistic model