Appearance Based Stage Recognition of Drosophila Embryos

Stages in Drosophila development denote the time after fertilization at which certain specific events occur in the developmental cycle. Stage information of a host embryo, as well as spatial information of a gene expression region is indispensable input for the discovery of the pattern of gene-gene interaction. Manual labeling of stages is becoming a bottleneck under the circumstance of high throughput embryo images. Automatic recognition based on the appearances of embryos is becoming a more desirable scheme. This problem, however, is very challenging due to severe variations of illumination and gene expressions. In this research thesis, we propose an appearance based recognition method using orientation histograms and Gabor filter. Furthermore, we apply Principal Component Analysis to reduce the dimension of the low-level features, aiming to accelerate the speed of recognition. With the experiments on BDGP images, we show the promise of the proposed method

A framework for clustering and adaptive topic tracking on evolving text and social media data streams.

Recent advances and widespread usage of online web services and social media platforms, coupled with ubiquitous low cost devices, mobile technologies, and increasing capacity of lower cost storage, has led to a proliferation of Big data, ranging from, news, e-commerce clickstreams, and online business transactions to continuous event logs and social media expressions. These large amounts of online data, often referred to as data streams, because they get generated at extremely high throughputs or velocity, can make conventional and classical data analytics methodologies obsolete. For these reasons, the issues of management and analysis of data streams have been researched extensively in recent years. The special case of social media Big Data brings additional challenges, particularly because of the unstructured nature of the data, specifically free text. One classical approach to mine text data has been Topic Modeling. Topic Models are statistical models that can be used for discovering the abstract ``topics\u27\u27 that may occur in a corpus of documents. Topic models have emerged as a powerful technique in machine learning and data science, providing a great balance between simplicity and complexity. They also provide sophisticated insight without the need for real natural language understanding. However they have not been designed to cope with the type of text data that is abundant on social media platforms, but rather for traditional medium size corpora consisting of longer documents, adhering to a specific language and typically spanning a stable set of topics. Unlike traditional document corpora, social media messages tend to be very short, sparse, noisy, and do not adhere to a standard vocabulary, linguistic patterns, or stable topic distributions. They are also generated at high velocity that impose high demands on topic modeling; and their evolving or dynamic nature, makes any set of results from topic modeling quickly become stale in the face of changes in the textual content and topics discussed within social media streams. In this dissertation, we propose an integrated topic modeling framework built on top of an existing stream-clustering framework called Stream-Dashboard, which can extract, isolate, and track topics over any given time period. In this new framework, Stream Dashboard first clusters the data stream points into homogeneous groups. Then data from each group is ushered to the topic modeling framework which extracts finer topics from the group. The proposed framework tracks the evolution of the clusters over time to detect milestones corresponding to changes in topic evolution, and to trigger an adaptation of the learned groups and topics at each milestone. The proposed approach to topic modeling is different from a generic Topic Modeling approach because it works in a compartmentalized fashion, where the input document stream is split into distinct compartments, and Topic Modeling is applied on each compartment separately. Furthermore, we propose extensions to existing topic modeling and stream clustering methods, including: an adaptive query reformulation approach to help focus on the topic discovery with time; a topic modeling extension with adaptive hyper-parameter and with infinite vocabulary; an adaptive stream clustering algorithm incorporating the automated estimation of dynamic, cluster-specific temporal scales for adaptive forgetting to help facilitate clustering in a fast evolving data stream. Our experimental results show that the proposed adaptive forgetting clustering algorithm can mine better quality clusters; that our proposed compartmentalized framework is able to mine topics of better quality compared to competitive baselines; and that the proposed framework can automatically adapt to focus on changing topics using the proposed query reformulation strategy

Research Notes: Potential of exotic soybeans in the sub-montane region of Himachal Pradesh (India)

Himachal Pradesh is a hilly state of Northern India , with its global location between 75°45\u27 - 79°04 \u27 E longitude and 30°22\u27 - 33°12\u27 N latitude. In this part of the country, soybean is indigenously grown as a rainy season crop up to an altitude of 1800 m above mean sea level . The indigenous soybean comprise small seeded, twining type low- yielding varieties

ECOLOGICAL FEATURES AND CONSERVATION OF ARNEBIA EUCHROMA. A CRITICALLY ENDANGERED MEDICINAL PLANT IN WESTERN HIMALAYA

Arnebia euchroma (Royle ex Benth.) Johnston, commonly known as ‘Ratanjot’ is an important medicinal plant species and is found distributed in the western Himalaya at elevations ranging between 3200 - 4500 m above sea level. Considering its potent medicinal properties, cultural significance, declining population density and critically endangered status of this taxon, the present investigation was carried out for the assessment of its availability in the natural alpine landscapes of the Spiti cold desert of western Himalaya in Himachal Pradesh (India). We focused our study on its ecological features, population dynamics and performance in natural habitats, so as to formulate conservation plans. In order to achieve the objectives of the present study, a total of 620 areas were set by using a random sampling technique at six different locations where A. euchroma was found distributed naturally. The highest population density was recorded in undulating meadows (5.30 individuals/m2) with a maximum circumference (4.18±1.80cm) at an elevation of 4240 m above sea level, with maximum frequency of occurrence (100%). Ecological surveys revealed that distribution was restricted in specific habitats rich in soil nutrients with high pH (8.025 - 8.37). The significance of the role of various ecological variables is explained in detail in the present paper. Habitat specificity, low population, and anthropogenic pressure justify the rarity status of this taxon in the Spiti valley. The authors discussed different implications to develop appropriate strategies for a long-term monitoring and sustainability of A. euchroma in the Spiti cold desert of western Himalaya

Effect of Phosphorus, Sulphur and Zinc on Plant height, Green leaves, Pod per plant, Grain yield per plant and Straw yield per plant of Black gram

Abstract The experiment was conducted in Kharif season (July-October

Silencing, Positive Selection and Parallel Evolution: Busy History of Primate Cytochromes c

Cytochrome c (cyt c) participates in two crucial cellular processes, energy production and apoptosis, and unsurprisingly is a highly conserved protein. However, previous studies have reported for the primate lineage (i) loss of the paralogous testis isoform, (ii) an acceleration and then a deceleration of the amino acid replacement rate of the cyt c somatic isoform, and (iii) atypical biochemical behavior of human cyt c. To gain insight into the cause of these major evolutionary events, we have retraced the history of cyt c loci among primates. For testis cyt c, all primate sequences examined carry the same nonsense mutation, which suggests that silencing occurred before the primates diversified. For somatic cyt c, maximum parsimony, maximum likelihood, and Bayesian phylogenetic analyses yielded the same tree topology. The evolutionary analyses show that a fast accumulation of non-synonymous mutations (suggesting positive selection) occurred specifically on the anthropoid lineage root and then continued in parallel on the early catarrhini and platyrrhini stems. Analysis of evolutionary changes using the 3D structure suggests they are focused on the respiratory chain rather than on apoptosis or other cyt c functions. In agreement with previous biochemical studies, our results suggest that silencing of the cyt c testis isoform could be linked with the decrease of primate reproduction rate. Finally, the evolution of cyt c in the two sister anthropoid groups leads us to propose that somatic cyt c evolution may be related both to COX evolution and to the convergent brain and body mass enlargement in these two anthropoid clades

Study of Growth and Biomass Production of some uel-wood Species in Northwestern Himalaya-Palampur under Short Rotation High Density Plantation

54-58The growth and biomass production of some fuel-wood species, found locally as well a exotic, were studied under short rotation high-density plantation under the agroclimatic conditions of Palampur in the northwestern Himalaya. Observations at 3 years after planting showed that the significantly highest vertical growth rate was exhibited by Crevillea robltsta followed by jacaranda acutifolia and Eucalyptus hybrid. Significantly highest radial growth was atttained by Bauhinia variegata followed by Eucalyptus and Grevillea, after 36 months. The different spacings of the trees had no significant effect on vertical and radial growth . The lowest dose of NPK fertilizers, i.e. 50:25:25 kg/ha, produced the highest vertical and radial growth rate. In the interaction studies (species ' spacing), between the species G. robusta, J. acutifalia, Elicalyptus and B. voeriegata produced significantly highest vertical growth in comparison to Populus deltoides, which was considered as the check species

Performance Analysis of Enhanced Activated Sludge as Drilling Mud Additive

The use of drilling fluids alone is not sufficient to reduce friction substantially, so a suitable lubricant has to be added to the drilling fluid so as to reduce the friction to an acceptable range. The lubricant reduces friction of fluid by producing a thin film of liquid that separates the solid surfaces in contact. The primary objective of this research is to evaluate the performance of enhanced activated sludge (EAS) as a lubricant in drilling fluids. Enhanced activated sludge is composed of mixed consortium of microorganisms grown under conditions that promote lipid accumulation. Experiments were conducted to evaluate (EAS) with different lipid contents. Performance of EAS as drilling fluid additive was compared with commercial lubricants in terms of lubricity and flow properties. Lubricants are evaluated using water-based drilling mud at lubricant concentrations of 1.78, 3.11, 4.43, and 6.17 pounds per barrel (ppb). Experiments were carried out in a standard lubricity meter. The Lubricity meter tests the ability of the lubricant in the drilling mud to reduce friction. Other parameters measured re plastic viscosity, gel strength, fluid loss, mud cake thickness, sand content, methylene blue test (MBT), alkalinity, and chlorides. All the lubricants studied (including EAS) lowered the coefficient of friction and significant torque reduction. EAS reduced the torque and fluid loss better than raw sludge. However, the top performers in terms of reducing the torque were the commercial lubricants. Bio Add was the best performer in the presence of both barite and bentonite. HDL+ resulted in the least coefficient of friction when the mud was prepared with only bentonite. A cost analysis was prepared to show the economics involved in using sludge (raw and EAS) as additive in drilling fluids. These findings show the potential of activated sludge for improving the properties of water-based drilling mud