Evaluation of Natural Radioactivity Levels and Exhalation rate of 222Rn and 220Rn in the Soil Samples from the Kuthiran Hills, Kerala, India

Background: Exposure to radon and its decay products is one of the important contributors of radiation doses to human population. Radon exhalation study is important for understanding the contribution of the soil towards the total radioactivity concentration found inside the dwellings. Purpose: The aim of the present study is to investigate the radioactivity levels and radium and radon exhalation rates in soil samples collected from Kuthiran hills and nearby places in Thrissur district, Kerala state, India. On the basis of this data, radiological health hazard parameters are also evaluated. Methods: About 18 soil samples were collected from the study location. The radium, thorium and potassium activity concentrations were analyzed by HPGe gamma ray spectrometer. The “can technique” using LR-115 type II plastic track detectors have been used for the measurement of radon exhalation rate in soil samples. Results: The mean values of activity concentrations of 226Ra, 232Th and 40K were 64.60 Bqkg-1, 109.03 Bqkg-1and 972.67 Bqkg-1 respectively. The mean value of radon mass exhalation rate is 9.19 mBqkg-1h-1 and thoron surface exhalation rate is and 237.9 mBqm-2s-1. The radium equivalent activity concentration of all the soil samples was below the level of 370 Bqkg-1, recommended for building materials, by OECD 1979 (Organization for Economic Cooperation and Development). Conclusions: The results show that the study area is safe, as far as the health hazard effects of radium and radon exhalation rate are concerned. This data will be helpful in establishing new regulations and safety limits, related to the radiation dose and radon activity in Kuthiran hills

AERODYNAMIC PERFORMANCE ANALYSIS OF CO-FLOW JET AIRFOIL

The work in this paper aims to increase the maximum lift coefficient of the airfoil by implementing the co-flow jet concept on NACA 0018 airfoil and also to investigate the performance of co-flow jet (CFJ) airfoil. To conduct numerical solution, RANS equations have been solved for 2D incompressible and unsteady flow using the Spalart-Allmaras turbulence model. The suction surface of the airfoil is modified by placing the injection slot near the leading edge and the suction slot near the trailing edge. A small mass of air is withdrawn into the airfoil suction slot, pressurized by a pumping system located inside the airfoil, and re-injecting into the injection slot tangentially to the main stream flow. The CFJ airfoil is enhancing the aerodynamic lift coefficient significantly compare to the baseline airfoil. And also, the numerical analysis is carried out to investigate the effect of the location of injection and suction slot. And it is observed that the aerodynamic lift coefficient of CFJ airfoil is increasing with varying the injection slot away from the leading edge

The Library of Babel

We show that heavy pure states of gravity can appear to be mixed states to almost all probes. Our arguments are made for $\rm{AdS}_5$ Schwarzschild black holes using the field theory dual to string theory in such spacetimes. Our results follow from applying information theoretic notions to field theory operators capable of describing very heavy states in gravity. For certain supersymmetric states of the theory, our account is exact: the microstates are described in gravity by a spacetime ``foam'', the precise details of which are invisible to almost all probes.Comment: 7 pages, 1 figure, Essay receiving honorable mention in the 2005 Gravity Research Foundation essay competitio

Exploring Societal Perplexes & Cultural Quandary in Amulya Malladi’s The Mango Season

Literature is a work of art blended with an aesthetic and artistic creation specifically in the written form. There are indeed many different kinds of literature around the globe, but Indian English Literature has its special qualities that make it stand out to readers. Indian English Literature is an amalgamation of various themes such as socio-historical, multicultural, and multilingual objectives. Amulya Malladi is an Indian women diasporic writer, she brings the concept of cultural dilemmas in her work. This paper investigates Amulya’s second fiction ‘The Mango Season’ and highlights the societal complications/ cultural confusions faced by the protagonist Priya Rao. Due to religious and cultural differences, the protagonist suffers a lot to decide between her love for her family and her love for her beloved. Cultural dilemmas are primarily the result of two living experiences that develop in one’s own country and in the host land. ‘The Mango Season’ is very naturalistic in its depiction of cultural confusions & societal norms faced by the protagonist who is well educated and graduated in the West while her parents are down-rooted in the Orient culture

Memory-efficient Stochastic methods for Memory-based Transformers

Training Memory-based transformers can require a large amount of memory and can be quite inefficient. We propose a novel two-phase training mechanism and a novel regularization technique to improve the training efficiency of memory-based transformers, which are often used for long-range context problems. For our experiments, we consider transformer-XL as our baseline model which is one of memorybased transformer models. We show that our resultant model, Skip Cross-head TransformerXL, outperforms the baseline on character level language modeling task with similar parameters and outperforms the baseline on word level language modelling task with almost 20% fewer parameters. Our proposed methods do not require any additional memory. We also demonstrate the effectiveness of our regularization mechanism on BERT which shows similar performance with reduction in standard deviation of scores of around 30% on multiple GLUE tasks

Customized CNN Model for Multiple Illness Identification in Rice and Maize

Crop diseases imperil global food security and economies, demanding early detection and effective management. Convolutional Neural Networks (CNNs), particularly in rice and maize leaf disease classification, have gained traction due to their automatic feature extraction capabilities. CNN models eliminate manual feature extraction, enabling precise disease diagnosis based on learned features. Researchers have rapidly advanced these models, achieving promising results. Leaf disease characteristics like color changes, texture variations, and lesion appearance have been identified as useful for automated diagnosis using machine learning. Developing CNN models involves crucial stages: dataset preparation, architecture selection, hyperparameter tuning, and model training and evaluation. Diverse and accurately annotated datasets are pivotal, and appropriate CNN architecture selection, such as ResNet101 and XceptionNet, ensures optimal performance. These architectures' pre-training on vast image datasets enhances feature extraction. Hyperparameter tuning fine-tunes the model, and training and evaluation gauge its precision. CNN models hold potential to enhance rice and maize productivity and global food security by effectively detecting and managing diseases

ENZYMOSOMES: A RISING EFFECTUAL TOOL FOR TARGETED DRUG DELIVERY SYSTEM

The study aims to develop enzymosomes as an emerging novel drug delivery system for site-specific action. Enzymosomes utilises the specific nature of an enzyme, which is binding to a specific substrate at a controlled rate and catalysing product production step. An enzyme is encapsulated by coupling covalently to the surface of liposomes/lipid vesicles to form enzymosomes. Enzymes links through acylation, direct conjugation, physical adsorption, encapsulation methods to prepare enzymosomes with targeted action. Such novel drug delivery systems prove effective drug release and concomitantly reduces undesirable side effects of conventional treatment methods and hence showcase improvement in the long-term therapy of the disease. They are a promising substitute to conventional treatment therapies of gout, antiplatelet activities etc. Enzymosomes are newly designed supramolecular vesicular delivery systems to be useful as a tool in pharmaceutics for the raising of drug targeting and physicochemical properties and hence bioavailability. It shows beneficial effects of drugs with a narrow precision because targeting of these drugs to their site of action improves the drugs overall pharmacodynamics and pharmacokinetic profile. It also minimizes alterations in the normal enzymatic activity, thus enhancing half-life and achieve enzyme activity on targeted sites such as cancerous cells