A Comparative Analysis of Portfolio Optimization Using Mean-Variance, Hierarchical Risk Parity, and Reinforcement Learning Approaches on the Indian Stock Market

This paper presents a comparative analysis of the performances of three portfolio optimization approaches. Three approaches of portfolio optimization that are considered in this work are the mean-variance portfolio (MVP), hierarchical risk parity (HRP) portfolio, and reinforcement learning-based portfolio. The portfolios are trained and tested over several stock data and their performances are compared on their annual returns, annual risks, and Sharpe ratios. In the reinforcement learning-based portfolio design approach, the deep Q learning technique has been utilized. Due to the large number of possible states, the construction of the Q-table is done using a deep neural network. The historical prices of the 50 premier stocks from the Indian stock market, known as the NIFTY50 stocks, and several stocks from 10 important sectors of the Indian stock market are used to create the environment for training the agent.Comment: The report is 52 pages long. It is based on the capstone project done in the post graduate course of data science in Praxis Business School, Kolkata, India, of the Autumn Batch, 202

Radio Observations of Four Active Galactic Nuclei Hosting Intermediate-mass Black Hole Candidates: Studying the Outflow Activity and Evolution

Observational searches for intermediate-mass black holes (IMBHs; 102-106 M ⊙) include relatively isolated dwarf galaxies. For those that host active galactic nuclei (AGNs), the IMBH nature may be discerned through the accretion-jet activity. We present radio observations of four AGN-hosting dwarf galaxies, which potentially harbor IMBHs. Very large array (VLA) observations indicate steep spectra (indices of −0.63 to −1.05) between 1.4 and 9 GHz. However, a comparison with the 9 GHz in-band spectral index shows a steepening for GH047 and GH158 (implying older/relic emission) and flattening for GH106 and GH163 (implying recent activity). Overlapping emission regions in the VLA 1.4 GHz and our very long baseline array (VLBA) 1.5 GHz observations, and possibly symmetric pc-scale extensions, are consistent with recent activity in the latter two. Using the compact VLBA radio luminosity, X-ray luminosity (probing the accretion activity), and the black hole masses, all AGNs are found to lie on the empirical fundamental plane relation. The four AGNs are radio-quiet with relatively higher Eddington ratios (0.04-0.32) and resemble X-ray binaries during spectral state transitions that entail an outflow ejection. Furthermore, the radio to X-ray luminosity ratio log R X of −3.9 to −5.6 in these four sources support the scenarios that include corona mass ejection from the accretion disk and wind activity. The growth to kpc-scales likely proceeds along a similar trajectory to young AGNs and peaked spectrum sources. These complex clues can thus aid in the detection and monitoring of IMBHs in the nearby universe

Biochar-based fertilizer: Supercharging root membrane potential and biomass yield of rice

Biochar-based compound fertilizers (BCF) and amendments have proven to enhance crop yields and modify soil properties (pH, nutrients, organic matter, structure etc.) and are now in commercial production in China. While there is a good understanding of the changes in soil properties following biochar addition, the interactions within the rhizosphere remain largely unstudied, with benefits to yield observed beyond the changes in soil properties alone. We investigated the rhizosphere interactions following the addition of an activated wheat straw BCF at an application rates of 0.25% (g·g−1 soil), which could potentially explain the increase of plant biomass (by 67%), herbage N (by 40%) and P (by 46%) uptake in the rice plants grown in the BCF-treated soil, compared to the rice plants grown in the soil with conventional fertilizer alone. Examination of the roots revealed that micron and submicron-sized biochar were embedded in the plaque layer. BCF increased soil Eh by 85 mV and increased the potential difference between the rhizosphere soil and the root membrane by 65 mV. This increased potential difference lowered the free energy required for root nutrient accumulation, potentially explaining greater plant nutrient content and biomass. We also demonstrate an increased abundance of plant-growth promoting bacteria and fungi in the rhizosphere. We suggest that the redox properties of the biochar cause major changes in electron status of rhizosphere soils that drive the observed agronomic benefits

Dynamics of Hot QCD Matter -- Current Status and Developments

The discovery and characterization of hot and dense QCD matter, known as Quark Gluon Plasma (QGP), remains the most international collaborative effort and synergy between theorists and experimentalists in modern nuclear physics to date. The experimentalists around the world not only collect an unprecedented amount of data in heavy-ion collisions, at Relativistic Heavy Ion Collider (RHIC), at Brookhaven National Laboratory (BNL) in New York, USA, and the Large Hadron Collider (LHC), at CERN in Geneva, Switzerland but also analyze these data to unravel the mystery of this new phase of matter that filled a few microseconds old universe, just after the Big Bang. In the meantime, advancements in theoretical works and computing capability extend our wisdom about the hot-dense QCD matter and its dynamics through mathematical equations. The exchange of ideas between experimentalists and theoreticians is crucial for the progress of our knowledge. The motivation of this first conference named "HOT QCD Matter 2022" is to bring the community together to have a discourse on this topic. In this article, there are 36 sections discussing various topics in the field of relativistic heavy-ion collisions and related phenomena that cover a snapshot of the current experimental observations and theoretical progress. This article begins with the theoretical overview of relativistic spin-hydrodynamics in the presence of the external magnetic field, followed by the Lattice QCD results on heavy quarks in QGP, and finally, it ends with an overview of experiment results.Comment: Compilation of the contributions (148 pages) as presented in the `Hot QCD Matter 2022 conference', held from May 12 to 14, 2022, jointly organized by IIT Goa & Goa University, Goa, Indi

SKA Science Data Challenge 2: analysis and results

The Square Kilometre Array Observatory (SKAO) will explore the radio sky to new depths in order to conduct transformational science. SKAO data products made available to astronomers will be correspondingly large and complex, requiring the application of advanced analysis techniques to extract key science findings. To this end, SKAO is conducting a series of Science Data Challenges, each designed to familiarise the scientific community with SKAO data and to drive the development of new analysis techniques. We present the results from Science Data Challenge 2 (SDC2), which invited participants to find and characterise 233245 neutral hydrogen (Hi) sources in a simulated data product representing a 2000~h SKA MID spectral line observation from redshifts 0.25 to 0.5. Through the generous support of eight international supercomputing facilities, participants were able to undertake the Challenge using dedicated computational resources. Alongside the main challenge, `reproducibility awards' were made in recognition of those pipelines which demonstrated Open Science best practice. The Challenge saw over 100 participants develop a range of new and existing techniques, with results that highlight the strengths of multidisciplinary and collaborative effort. The winning strategy -- which combined predictions from two independent machine learning techniques to yield a 20 percent improvement in overall performance -- underscores one of the main Challenge outcomes: that of method complementarity. It is likely that the combination of methods in a so-called ensemble approach will be key to exploiting very large astronomical datasets.Comment: Under review by MNRAS; 28 pages, 16 figure

Phylogentetic analysis of <i style="">Mycobacterium leprae </i>genome for identification of novel drug targets

58-61The reductive evolution provides a pathogen minimal gene set. Due to loss of genes, for drug target identification, biochemical techniques cannot be used since these pathogens are difficult to culture. Besides classical drug targets i.e. toxins, adhesions, some novel drug targets, using a molecular phylogeny approach, can be identified. Horizontally transferred genes in bacterial pathogen from their eukaryotic host has been classified as ‘Novel drug target’, and a reusable system for identifying horizontally transferred gene has been built using a molecular phylogeny approach. Using this system, two genes have been identified in Mycobacterium leprae, which have also been identified by other methods

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Not AvailableSpotted stem borer, Chilo partellus, is the most important constraint for increasing the production and productivity of maize and sorghum, the two major coarse cereals in Asia and Africa. The levels of resistance to this pest in the cultivated germplasm are low to moderate, and hence, farmers have to use insecticides for effective control of this pest. However, there is no information on the detoxification mechanisms in C. partellus, which is one of the constraints for deployment of appropriate insecticides to control this pest. The ability to detoxify insecticides varies across insect populations, and hence, we sequenced different populations of C. partellus to identify and understand detoxification mechanisms to devise appropriate strategies for deployment of different insecticides for controlling this pest. Larval samples were sequenced from three different cohorts of C. partellus using the Illumina HiSeq 2500 platform. The data were subjected to identify putative genes that are involved in detoxification on insecticides in our cohort insect species. These studies resulted in identification of 64 cytochrome P450 genes (CYP450s), and 36 glutathione S-transferases genes (GSTs) encoding metabolic detoxification enzymes, primarily responsible for xenobiotic metabolism in insects. A total of 183 circadian genes with > 80% homolog and 11 olfactory receptor genes that mediate chemical cues were found in the C. partellus genome. Also, target receptors related to insecticide action, 4 acetylcholinesterase (AChE), 14 γ-aminobutyric acid (GABA), and 15 nicotinic acetylcholine (nAChR) receptors were detected. This is the first report of whole genome sequencing of C. partellus useful for understanding mode of action of different insecticides, and mechanisms of detoxification and designing target-specific insecticides to develop appropriate strategies to control C. partellus for sustainable crop production.Not Availabl