SURFACE RECONSTRUCTION IN IRON GARNETS

This dissertation presents the results of a study investigating the physical mechanisms underlying an unexpectedly large increase in magneto-optic efficiency observed in iron garnet. Such materials are technologically important for telecommunications due to their nonreciprocal optical action. In the past, our group had found evidence of an enhanced Faraday rotation in bismuth-substituted iron garnet films less than 50 nm thick. Subsequent investigation revealed that this enhancement could be traced to surface effects. This is significant because understanding these phenomena could be used to formulate engineering solutions for device miniaturization. In this dissertation, we present the result of a research project investigating the physical mechanisms underlying this unexpectedly large increase in Faraday response. Both experimental and theoretical techniques were brought to bear, including spectroscopic analysis and density-functional theory calculations, to understand how surface reconstruction effects impact the quantum origins of these curious phenomena. High-energy X-ray magnetic circular dichroism (XMCD) and X-ray absorption (XAS) measurements were used to analyze electronic transitions, while scanning transmission electron microscopy yielded concomitant structural analysis. The XAS and XMCD allowed us to produce a comparative analysis of surface and bulk densities of state impacting the 3d Fe orbitals responsible for Faraday rotation. This investigation was supplemented with surface-sensitive XPS analysis and ultraviolet and visible light absorption studies of the electronic distribution near the Fermi-level bands. These results were used to build and verify a density functional theory (DFT) model for iron garnet materials. Vienna ab-initio simulation (VASP) techniques yielded density-of-state (DOS) and band structure information for these systems. These allowed us to compare differences in bulk and surface band structures and DOS and to trace the surface-induced electronic origin of changes in Faraday rotation. DFT calculations based on these results showed that, indeed, the Faraday effect is enhanced in the visible and near-infrared regimes. Transition dipole matrix analysis was used to predict an accurate Faraday rotation response based on DFT calculations. Surface symmetry-breaking and surface reconstruction were thus found to be responsible for the effects under investigation. The combined evidence from this comprehensive study shows that a decrease in band gap at the surface plays a decisive role in the enhanced Faraday rotation

Prevalence of menopausal symptoms and its association with various factors among women in post menopausal age group: a cross-sectional study

Background: Menopause is an important time in women's life and it is a natural event in the process of aging. The onset of menopause heralds a time of diminished estrogen exposure, which may have both acute and chronic effect on health and quality of life.Methods: It was a cross sectional study, conducted for a period of 3months i.e. June to August 2018 among post menopausal women in 8 selected villages with a sample size of 247.Results: The common post- menopausal symptoms were joint and muscular discomfort, bladder problems, symptoms of dryness of vagina, physical and mental exhaustion. Factors like education, occupation, socio-economic status, marital status, parity, mode of delivery, age at menopause and BMI was related to one or more menopausal symptoms.  Conclusions: Proper and timely intervention among post menopausal women will help to reduce the symptoms and lead a better quality of life.

VLSI Implementation of RSA Cryptosystem

In the age of information, security issues play a crucial role. Security comes with three points’ confidentiality, integrity and availability. The entire above said thing will come from an efficient cryptographic algorithm. We need special hardware to implement these cryptographic algorithms to provide higher throughput. This hardware should have high flexibility since the cryptographic algorithms are constantly changing. To achieve this goal VLSI implementation of these cryptosystem is the best solution. Our work is mainly based on designing architectures for Rivest–Shamir–Adleman (RSA), one of the most well-known public key cryptosystem. This work started with the understanding of basics of cryptography and modular arithmetic which is essential to understand cryptographic algorithm. Then in the cryptographic module RSA, a public key cryptographic module is chosen as the algorithm for implementation. The design goal is to increase the speed or in other words the throughput of RSA cryptosystem

Farmers’ Toolkit: Deep Learning in Weed Detection and Precision Crop & Fertilizer Recommendations

Agriculture is widely recognized as a significant and indispensable occupation on a global scale. The current imperative is to optimize agricultural practices and progressively transition towards smart agriculture. The Internet of Things (IoT) technology has dramatically enhanced people’s daily lives via diverse applications across several domains. Previous studies have yet to effectively incorporate Artificial Intelligence (AI) with sensor technology to provide comprehensive guidance to agricultural practitioners, hindering their ability to achieve good outcomes. This research offers Farmers’ Toolkit with four layers: sensor, network, service, and application. This toolkit aims to facilitate the implementation of a smart farming system while effectively managing energy resources. With a specific emphasis on the application layer, the toolkit uses a deep learning methodology to construct a fertilizer recommendation system that aligns with the expert’s perspective. This study utilizes IoT devices and Wireless Sensor Network (WSN) methods to enhance the efficiency and speed of recommending appropriate crops to farmers. The recommendation process considers several criteria: temperature, yearly precipitation, land area, prior crop history, and available resources. The identification of undesirable vegetation on agricultural fields, namely the detection of weeds, is carried out using drone technology equipped with frame-capturing capabilities and advanced deep-learning algorithms. The findings demonstrate an accuracy rate of 94%, precision rate of 92%, recall rate of 96%, and F1 score of 94%. The toolkit for farmers alleviates physical labor and time expended on various agricultural tasks while enhancing overall land productivity, mitigating potential crop failures in specific soil conditions, and minimizing crop damage inflicted by weeds

Drive State Analysis Based Electric Drive Control Model for Improved Power Stabilization

The problem of power stabilization in electric drives has been well studied. There exist numbers of approaches around the problem which consider the input power alone and suffer to achieve higher performance in power stabilization. To handle this issue, an efficient Drive State Analysis based Electric Drive Control model (DSA-EDCM) is presented in this article. The model monitors the drive state of electric drive at each duty cycle. According to the drive state and its previous conditions like voltage consumption, voltage leak, rpm and torque required, the method performs drive state analysis. The drive state analysis algorithm computes the power required at different conditions by computing Power Support value (PSV). Based on the PSV value, the method selects specific drive according to the input voltage received. Selected drive has been triggered for the cycle to maintain power stability. The proposed model improves the performance of power stability and maximizes the utilization performance

Applications of Sustainable Business Models for PV Systems in Developing Countries

The global push to boost the adoption of renewable energy resources and decrease our dependency on fossil fuels for electricity generation has experienced substantial growth. Solar Photovoltaic (PV) panels have now achieved a level of extensive implementation and global economic feasibility. These panels, compact and resilient, require only sunlight exposure to generate electricity. Since their commercial use began in Europe in the 1990s, solar PV power has been electrifying countless households worldwide and providing energy access to numerous remote communities in less developed regions. As a result, the extensive global deployment of solar energy systems strengthens the energy industry and fosters job growth, thereby facilitating substantial progress. This study emphasizes the importance of Photovoltaic (PV) technologies and their contribution to advancing sustainability, particularly in emerging economies. It provides valuable perspectives and examinations of the sustainability of solar energy, covering both ecological and economic facets.Furthermore, it delineates the crucial contribution of PV technologies to sustainable development, as they meet energy needs, create job prospects, and enhance environmental conservation initiatives

Socio-health seeking profile of women in Post Menopausal Age group: A study in a Rural block of Ganjam district, South Odisha

Background: Menopause is defined as” the time when there has been no menstrual periods for 12 consecutive months and no other biological or physiological cause can be identified.” Objectives: 1) To describe the socio-demographic characteristics of post menopausal women in study area. 2) To explore out the various factors related to the age at menopause. 3) To assess the health seeking behaviour of study population. Materials and Methods: This study was a cross sectional community based observational study which was carried out among Postmenopausal women in 8 selected villages of Chhatrapur block of Ganjam district, Odisha for a period from October 2016 to September 2018 with a sample size of 247. Results: In the present study, 39.3% of the study population attained menopause at the age 46-50 years and 11.7% at the age 51-55years. Factors like socioeconomic status, age at menarche ,parity ,marital status , addiction status, family history of early menopause ,BMI and contraception user were found to have statistical significant association with the age at menopause. On logistic regression by adjusting all the variables it was found that age of study population [AOR=3.030 (1.639-5.602), educational qualification [AOR=11.798 (4.002-34.777)], and occupation [AOR= 3.913 (1.296-11.82)] were found to be significantly associated with the health seeking behaviour. Conclusion: In the present study the mean age at menopause was 46.98±4.080 years. Majority of postmenopausal women perceived that menopause occurred due to normal process of ageing. But less than half of the respondents sought treatment because of lack of knowledge about the symptoms and availability of treatment modalities. Awareness and knowledge about all the aspects of menopause should be provided to them through the health workers and women organisation

smileysushree/TDM_model: TDM Model from Band structure to calculate the Faraday Rotation

<p><a href="https://github.com/smileysushree/TDM_model/files/13358481/TDM_analysis_BS.docx">TDM_analysis_BS.docx</a></p&gt

Effect of climate change on soil erosion indicates a dominance of rainfall over LULC changes

Study region: Mahanadi River Basin in India Study focus: This study explores the effect of climate change and human-induced farming and construction activities on soil erosion in a rainfed basin during two time periods viz. 1981–2000 and 2001–2019. This study assesses erosion using the Geographic Information System integrated Revised Universal Soil Loss Equation (GIS-integrated RUSLE) model. Three different analyses are designed to assess the effect i) combined effect of change in all the RUSLE factors over these two time periods, ii) effect of only land use/cover change (LULC), and iii) only rainfall change impact on erosion rate. A modified sediment delivery ratio (SDR) has been proposed and the model performances are validated using the observed Sediment Yield data. New hydrological insights for the region: The results indicate an overall decrease in the erosion rate as a combined effect of change in all the factors, but at the same time, an increase in the spatial extent of the areas affected by soil erosion is noticed. The mean soil erosion rate varies between 37.02 tons ha⁻¹ yr⁻¹ in 1981–2000 and 31.89 tons ha⁻¹yr⁻¹ in 2001–2019, with a 40% decrease in the maximum erosion rate, while the total and mean erosion rates are both down 13.85% compared to 1981–2000. The analysis suggested overall effect of the change in rainfall is more profound on erosion than LULC change

Surface magneto-optics in yttrium iron garnets

We report a study of surface reconstruction effects in yttrium iron garnets using density functional theory. This work responds to the need to explain the physical basis of recent experimental results showing a significant enhancement in Faraday rotation in iron garnets. These materials are extensively used in the telecom industry for nonreciprocal device applications. Understanding the physical basis of the heightened Faraday response at the surface is important for the development of ultrathin nonreciprocal devices. Our results show that the bandgap near the surface is significantly reduced compared to that of the bulk, and that spin-orbit coupling effects become more important near the surface. We find that the decrease in band gap results in an enhancement and change in direction in the Faraday rotation in the visible range all the way to the deep red. Electronic transition matrix elements for surface-sensitive ultra-thin layers are calculated and compared to those of bulk samples, leading to the conclusion that the octahedrally-oxygen-coordinated iron sublattice in these ferrimagnetic materials is more strongly affected by surface reconstruction than the other, anti-ferromagnetically coupled, tetrahedral sublattice. We explain how these changes contribute to the enhancement in magneto-optic response near the surface as compared to the bulk