Manifestation of pernicious anaemia as hyperpigmentation of palms and soles

Vitamin B12 deficiency produces various manifestations involving CNS, heart, skin, blood and female reproductive systems. It is seen most commonly in the older individuals, malabsorptive states (>60% of all cases) and vegetarians. Pernicious anaemia may be confused to Addison’s disease as both may present with similar clinical features. Hereby we report a case of pernicious anaemia presenting with dermatological manifestation in the form of deep pigmentation of both palms of and both soles respectively, cortisol levels normal so Addition’s disease ruled out

Exploring reinforcement learning techniques for discrete and continuous control tasks in the MuJoCo environment

We leverage the fast physics simulator, MuJoCo to run tasks in a continuous control environment and reveal details like the observation space, action space, rewards, etc. for each task. We benchmark value-based methods for continuous control by comparing Q-learning and SARSA through a discretization approach, and using them as baselines, progressively moving into one of the state-of-the-art deep policy gradient method DDPG. Over a large number of episodes, Qlearning outscored SARSA, but DDPG outperformed both in a small number of episodes. Lastly, we also fine-tuned the model hyper-parameters expecting to squeeze more performance but using lesser time and resources. We anticipated that the new design for DDPG would vastly improve performance, yet after only a few episodes, we were able to achieve decent average rewards. We expect to improve the performance provided adequate time and computational resources.Comment: Released @ Dec 2021. For associated project files, see https://github.com/chakrabortyde/mujoco-control-task

Computational Studies of Coordinatively Unsaturated Transition Metal Complexes

In this research the validity of various computational techniques has been determined and applied the appropriate techniques to investigate and propose a good catalytic system for C-H bond activation and functionalization. Methane being least reactive and major component of natural gas, its activation and conversion to functionalized products is of great scientific and economic interest in pure and applied chemistry. Thus C-H activation followed by C-C/C-X functionalization became crux of the synthesis. DFT (density functional theory) methods are well suited to determine the thermodynamic as well as kinetic factors of a reaction. The obtained results are helpful to industrial catalysis and experimental chemistry with additional information: since C-X (X = halogens) bond cleavage is important in many metal catalyzed organic syntheses, the results obtained in this research helps in determining the selectivity (kinetic or thermodynamic) advantage. When C-P bond activation is considered, results from chapter 3 indicated that C-X activation barrier is lower than C-H activation barrier. The results obtained from DFT calculations not only gave a good support to the experimental results and verified the experimentally demonstrated Ni-atom transfer mechanism from Ni=E (E = CH2, NH, PH) activating complex to ethylene to form three-membered ring products but also validated the application of late transition metal complexes in respective process. Results obtained supported the argument that increase in metal coordination and electronic spin state increases catalytic activity of FeIII-imido complexes. These results not only encouraged the fact that DFT and multi-layer ONIOM methods are good to determine geometry and thermodynamics of meta-stable chemical complexes, but also gave a great support to spectroscopic calculations like NMR and Mossbauer calculations

Read Mapping on Genome Variation Graphs

Genome variation graphs are natural candidates to represent a pangenome collection. In such graphs, common subsequences are encoded as vertices and the genomic variations are captured by introducing additional labeled vertices and directed edges. Unlike a linear reference, a reference graph allows a rich representation of the genomic diversities and avoids reference bias. We address the fundamental problem of mapping reads to genome variation graphs. We give a novel mapping algorithm V-MAP for efficient identification of small subgraph of the genome graph for optimal gapped alignment of the read. V-MAP creates space efficient index using locality sensitive minimizer signatures computed using a novel graph winnowing and graph embedding onto metric space for fast and accurate mapping. Experiments involving graph constructed from the 1000 Genomes data and using both real and simulated reads show that V-MAP is fast, memory efficient and can map short reads, as well as PacBio/Nanopore long reads with high accuracy. V-MAP performance was significantly better than the state-of-the-art, especially for long reads

SECONDARY MARKET IN INDIA:A REVIEW OF EMERGING TRENDS

Indian Securities Market, especially the secondary market is witnessing fundamental changes in the last few years. Electronic financial services have modernized the stock exchanges, leading to drastic reduction in transaction costs and significant improvements in efficiency, transparency and safety in trading, leading to increased trading volumes and market capitalization. The changes in regulatory and governance framework have also brought about an improvement in investor confidence. With the total Market Capitalisation of 1, 01, 49,290 crore at BSE and 99, 30,122 crores at NSE as on May 2015, the secondary market is set to see phenomenal changes in the future.It is against this background, the paper aims to (i) study the trends in secondary market with regards Sensex and Nifty (ii) examine the growth in the number of investors accounts at NSDL and CDSL, (iii) analyse the growth of online trading in capital market (CM) segment of NSE with a view to assess its impact on the trading volume and turnover.  Â

Diverse small molecule inhibitors of human apurinic/apyrimidinic endonuclease APE1 identified from a screen of a large public collection.

The major human apurinic/apyrimidinic endonuclease APE1 plays a pivotal role in the repair of base damage via participation in the DNA base excision repair (BER) pathway. Increased activity of APE1, often observed in tumor cells, is thought to contribute to resistance to various anticancer drugs, whereas down-regulation of APE1 sensitizes cells to DNA damaging agents. Thus, inhibiting APE1 repair endonuclease function in cancer cells is considered a promising strategy to overcome therapeutic agent resistance. Despite ongoing efforts, inhibitors of APE1 with adequate drug-like properties have yet to be discovered. Using a kinetic fluorescence assay, we conducted a fully-automated high-throughput screen (HTS) of the NIH Molecular Libraries Small Molecule Repository (MLSMR), as well as additional public collections, with each compound tested as a 7-concentration series in a 4 µL reaction volume. Actives identified from the screen were subjected to a panel of confirmatory and counterscreen tests. Several active molecules were identified that inhibited APE1 in two independent assay formats and exhibited potentiation of the genotoxic effect of methyl methanesulfonate with a concomitant increase in AP sites, a hallmark of intracellular APE1 inhibition; a number of these chemotypes could be good starting points for further medicinal chemistry optimization. To our knowledge, this represents the largest-scale HTS to identify inhibitors of APE1, and provides a key first step in the development of novel agents targeting BER for cancer treatment

AN INTEGRATED DESIGN APPROACH OF HIGH-PERFORMANCE GREEN BUILDINGS

The Large carbon footprint of conventional buildings coupled with their high energy consumption in recent years, there is a necessity for an emphasis on the design process of energy-efficient high-performance green buildings. However, there exists limited research on the integration of green technologies into a high-performance green building with a special focus on energy, daylighting and green material. To solve this issue, an integrated design approach is presented from the perspective of making it practical and easier for architects and designers to design a high-performance green building. This paper introduces the benefit of the application of Environmental Impact Assessment and the integration of various green technologies along with the LEED rating system in the design process. Relevant case studies of various green buildings are exemplified and enumerated throughout the paper for the purpose of investigating the practicality of the approach. Lastly, the payback period for the initial cost premium for the construction of a high-performance green building is also given due consideration in the design process

Analysis on Security Vulnerabilities of the Modern Internet of Things (IOT) Systems

The IoT, or Internet of Things, has quickly grown in popularity as a means to collect data in real-time from any and all linked devices. These networked physical objects can exchange data with one another via their respective sensor technologies and have their own unique identifiers. Insightful data analytics applied to the obtained information also presents a substantial possibility for many organisations. Embedded devices, authentication, and trust management are all areas where the Internet of Things has shown a significant security hole. This study delves into the problems with the Internet of Things (IoT), covering topics such as its privacy and security, its vulnerability, its analytics at the moment, the impending ownership threat, trust management, IoT models, its roadmap, and its security issues. It then offers solutions to these problems

A Comprehensive Review Study of Cyber-Attacks and Cyber Security

In today's world, the majority of governmental, cultural, social, economic, and commercial interactions and activities take place online. This includes interactions between nations, individuals, NGOs, and government agencies. The threat of cyberattacks and wireless communication technologies has recently become an issue for numerous private organisations and government agencies across the globe. Nowadays, our world relies heavily on electronic technology, and safeguarding this data from cyber-attacks is no easy feat. Cybercriminals target businesses with the intention of stealing money. Cyberattacks may also serve political or military objectives in certain instances. Computer viruses, information breaches, data distribution services (DDS), and other attack vectors are among the causes of these damages. In order to accomplish this goal, different organisations employ different strategies to safeguard against cyberattacks. The most recent information technology data is tracked in real-time by cyber security. So far, academics from all around the globe have suggested a number of ways to either stop cyberattacks in their tracks or at least mitigate the harm they do. A few of the approaches have moved on to the study phase, while others are still in the operational stage. The purpose of this research is to examine the offered approaches, identify their strengths and shortcomings, and conduct a thorough evaluation of the standard advancements made in the area of cyber security

Applications of Deep Learning Approaches to Detect Advanced Cyber Attacks

The number and sophistication of cyber attacks have grown, making it tougher to detect and prevent them using traditional security technologies. Improving cyber threat identification and response has been greatly enhanced by deep learning, a subset of machine learning. Learn how to spot advanced cyberattacks with the help of Deep Learning algorithms in this article. The proposed approach collects, categorises, and arranges network traffic data using convolutional neural networks (CNNs) and intermittent neural networks (RNNs). Combining the RNN with the CNN allows us to capture temporal dependencies and derive spatial properties from the network data. In order to find the most important qualities for classification, the proposed method also incorporates a feature selection stage. To demonstrate that the proposed system outperforms signature-based and example AI systems in terms of exactness, accuracy, review, and F1-score, we conduct an exhibition survey using various datasets. An effective tool for improving cyber defences, the proposed method can detect zero-day and previously unknown attacks