Decentralization to decarbonize the Indian economy

Renewable energy plays an important role in India's energy security and reducing greenhouse gas emissions. Energy generated at the centralized level has significant shortcomings, and environmental concerns drive a shift to decentralized energy. India is a developing country; renewable energy power generation promotion is very important to make awareness among consumers and retailers. India's energy transition and decarbonization agenda aim to build a new clean energy system that is reliable, affordable, sustainable, and energy independent.  The Indian government has taken several initiatives to increase domestic manufacturing capacity, particularly solar PV, electric vehicles, and batteries. This paper aims to present significant achievements through different RE schemes, projections, and India’s ambition of net zero through the current policy in place concerning the decentralized use of renewable technologies prospects

Image Classification for Breast Cancer Using a Modified Convolution Neural Network Architecture

The most common type of cancer that results in death is breast cancer. In the world, millions of people struggle with this disease. Breast cancer can affect men and women but women are more affected. For awareness, it is necessary to understand the sign and symptoms of breast cancer. The most common sign is an abnormal lump in the breast. But there may be many reasons of develop abnormal lumps. Computer-Aided Diagnosis (CAD) is extensively used in pathological image analysis to help pathologists enhance diagnosis efficiency, accuracy, and consistency. Recent studies have looked into deep learning methodologies to improve the effectiveness of pathological CAD

Novel Bioinformatics Approaches for MicroRNA Detection and Target Prediction.

MicroRNAs (miRNAs) are regulators of gene expression at the post-transcriptional level. Scientists have not been able to fully unlock their therapeutic potential because their functions and mechanisms of action have not been fully characterized. In this thesis we address shortcomings and provide solutions for detecting miRNAs in a high-throughput manner and for predicting miRNA targets - areas key to understanding miRNA function. Profiling expression of miRNAs using microarrays has its limitations owing to diverse melting temperatures and high sequence similarities, which affects sensitivity and specificity. A simple yet effective strategy that we employ involves base changes to probes complementary to mature miRNAs. Using nearest-neighbour thermodynamic principles we determine the best probes for all mature miRNAs that serve to eliminate cross-hybridization and create a uniform melting temperature profile. We present a set of probes that are designed for the human let-7 family and demonstrate their power to resolve these similar sequences in a microarray experiment using both spiked-in and true biological samples. The second problem that is tackled in this thesis involves improving miRNA target prediction, a key to understanding miRNA function in various biological processes. We use a combination of thermodynamic and sequence-based searches to identify endogenous sites on 5′-UTRs. There are two aspects that make our approach unique compared to other target prediction methodologies. First, we not only consider seed-matches on the 3′-UTR but also 5′-UTR matches with 3′-ends of miRNAs. Second, we show that non-conserved sites on the 5′-UTR can possibly contribute to species-specific targeting. We verify our claims through in vitro experiments using two predicted miRNA-target pairs: hsa-miR-34a and its target AXIN2, and cel-lin-4 and its target lin28. Extending results from the target prediction study, we show that upstream AUGs (uAUGs), which are known to post-transcriptionally regulate gene expression, are probable binding sites for miRNAs. We show that the cell- or tissue-specific repression of genes that harbour uAUGs can be explained by the expression of targeting miRNAs in those cells. The approaches suggested here will help further our understanding of how these tiny RNAs regulate gene expression.Ph.D.BioinformaticsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/62207/1/sasubram_1.pd

Design and Evaluation of Sensor Housing for Boundary Layer Profiling Using Multirotors

Traditional configurations for mounting Temperature–Humidity (TH) sensors on multirotor Unmanned Aerial Systems (UASs) often suffer from insufficient radiation shielding, exposure to mixed and turbulent air from propellers, and inconsistent aspiration while situated in the wake of the UAS. Descent profiles using traditional methods are unreliable (when compared to an ascent profile) due to the turbulent mixing of air by the UAS while descending into that flow field. Consequently, atmospheric boundary layer profiles that rely on such configurations are bias-prone and unreliable in certain flight patterns (such as descent). This article describes and evaluates a novel sensor housing designed to shield airborne sensors from artificial heat sources and artificial wet-bulbing while pulling air from outside the rotor wash influence. The housing is mounted above the propellers to exploit the rotor-induced pressure deficits that passively induce a high-speed laminar airflow to aspirate the sensor consistently. Our design is modular, accommodates a variety of other sensors, and would be compatible with a wide range of commercially available multirotors. Extensive flight tests conducted at altitudes up to 500m Above Ground Level (AGL) show that the housing facilitates reliable measurements of the boundary layer phenomena and is invariant in orientation to the ambient wind, even at high vertical/horizontal speeds (up to 5m/s) for the UAS. A low standard deviation of errors shows a good agreement between the ascent and descent profiles and proves our unique design is reliable for various UAS missions

Design and Evaluation of Sensor Housing for Boundary Layer Profiling Using Multirotors

Traditional configurations for mounting Temperature–Humidity (TH) sensors on multirotor Unmanned Aerial Systems (UASs) often suffer from insufficient radiation shielding, exposure to mixed and turbulent air from propellers, and inconsistent aspiration while situated in the wake of the UAS. Descent profiles using traditional methods are unreliable (when compared to an ascent profile) due to the turbulent mixing of air by the UAS while descending into that flow field. Consequently, atmospheric boundary layer profiles that rely on such configurations are bias-prone and unreliable in certain flight patterns (such as descent). This article describes and evaluates a novel sensor housing designed to shield airborne sensors from artificial heat sources and artificial wet-bulbing while pulling air from outside the rotor wash influence. The housing is mounted above the propellers to exploit the rotor-induced pressure deficits that passively induce a high-speed laminar airflow to aspirate the sensor consistently. Our design is modular, accommodates a variety of other sensors, and would be compatible with a wide range of commercially available multirotors. Extensive flight tests conducted at altitudes up to 500m Above Ground Level (AGL) show that the housing facilitates reliable measurements of the boundary layer phenomena and is invariant in orientation to the ambient wind, even at high vertical/horizontal speeds (up to 5m/s) for the UAS. A low standard deviation of errors shows a good agreement between the ascent and descent profiles and proves our unique design is reliable for various UAS missions

Analytical study of Salsaradi Gana Bhawit (three times) Shilajatu

Ayurveda the science of life gives importance to the balance between nature and human relationship; and Rasashastra, one of its associate wings can be considered to hold a key role since it deals in almost all the substances created by nature and marshals then for alleviating the diseases. The therapeutic efficacy of drugs depends upon the genuineness of raw material and right. Shilajeet is an important herbomineral drug among the Maharasa. Describing its importance Charaka has said, “there is hardly any curable disease which cannot be alleviated or cured with the aid of Shilajeet. Aim of study is to evaluate the Physico-chemical parameterof Salsaradi Gana Bhawit Shilajatu. Shilajatu and all raw drugs were obtained from P.G. Department, G.A.C.H. Patna and Shilajeet Shodhana was done by Triphala Kwatha and three times Bhawana by Salsaradigana (Dravyas) Kwatha. All samples were analyzed at Laboratory of Govt. Ayurveda College & Hospital Patna. It found that Shilajatu after Bhawana appeared as semi solid colour brownish black, soft in consistency and having typical smell

Estimation of leakage power and delay in CMOS circuits using parametric variation

SummaryWith the advent of deep-submicron technologies, leakage power dissipation is a major concern for scaling down portable devices that have burst-mode type integrated circuits. In this paper leakage reduction technique HTLCT (High Threshold Leakage Control Transistor) is discussed. Using high threshold transistors at the place of low threshold leakage control transistors, result in more leakage power reduction as compared to LCT (leakage control transistor) technique but at the scarifies of area and delay. Further, analysis of effect of parametric variation on leakage current and propagation delay in CMOS circuits is performed. It is found that the leakage power dissipation increases with increasing temperature, supply voltage and aspect ratio. However, opposite pattern is noticed for the propagation delay. Leakage power dissipation for LCT NAND gate increases up to 14.32%, 6.43% and 36.21% and delay decreases by 22.5%, 42% and 9% for variation of temperature, supply voltage and aspect ratio. Maximum peak of equivalent output noise is obtained as 127.531nV/Sqrt(Hz) at 400mHz

The 2015 April 25 Gorkha (Nepal) earthquake and its aftershocks: implications for lateral heterogeneity on the Main Himalayan Thrust

The 2015 Gorkha earthquake (M-w 7.8) occurred by thrust faulting on a similar to 150 km long and similar to 70 km wide, locked downdip segment of the Main Himalayan Thrust (MHT), causing the Himalaya to slip SSW over the Indian Plate, and was followed by major-to-moderate aftershocks. Back projection of teleseismic P-wave and inversion of teleseismic body waves provide constraints on the geometry and kinematics of the main-shock rupture and source mechanism of aftershocks. The main-shock initiated similar to 80 km west of Katmandu, close to the locking line on the MHT and propagated eastwards along similar to 117 degrees. azimuth for a duration of similar to 70 s, with varying rupture velocity on a heterogeneous fault surface. The main-shock has been modelled using four subevents, propagating from west-to-east. The first subevent (0-20 s) ruptured at a velocity of similar to 3.5 km s(-1) on a similar to 6 degrees N dipping flat segment of the MHT with thrust motion. The second subevent (20-35 s) ruptured a similar to 18 degrees. Wdipping lateral ramp on the MHT in oblique thrust motion. The rupture velocity dropped from 3.5 km s(-1) to 2.5 km s(-1), as a result of updip propagation of the rupture. The third subevent (35-50 s) ruptured a similar to 7 degrees. N dipping, eastward flat segment of the MHT with thrust motion and resulted in the largest amplitude arrivals at teleseismic distances. The fourth subevent (50-70 s) occurred by left-lateral strike-slip motion on a steeply dipping transverse fault, at high angle to the MHT and arrested the eastward propagation of the main-shock rupture. Eastward stress build-up following the main-shock resulted in the largest aftershock (M-w 7.3), which occurred on the MHT, immediately east of the main-shock rupture. Source mechanisms of moderate aftershocks reveal stress adjustment at the edges of the main-shock fault, flexural faulting on top of the downgoing Indian Plate and extensional faulting in the hanging wall of the MHT.Peer reviewe

Induced Size Effects Of Gd3+ ions Doping On Structural And Magnetic Properties Of Ni-Zn Ferrite Nanoparticles

Gd3+ ions substituted in Ni0.5Zn0.5GdxFe2-xO4 (where x = 0.1, 0.2, 0.3) ferrite nanoparticles in the size range from 15 to 25 nm were prepared by chemical method. The effect of Gd3+ ions in spinel structure in correlation to structural and magnetic properties have been studied in detail using XRD, HRTEM and EPR techniques. The spin resonance confirms the ferromagnetic behaviour of these nanoparticles and higher order of dipolar-dipolar interaction. On increasing Gd3+ ions concentrations, the super exchange interaction i.e. increase in movement of electron among Gd3+ - O - Fe3+ in the core group and the spin biasing in the glass layer has been interpreted. The decrease in ‘g’ value and increase in relaxation time is well correlated with the change of particle size on different concentrations of Gd3+ ions in Ni-Zn ferrite

A big data MapReduce framework for fault diagnosis in cloud-based manufacturing

This research develops a MapReduce framework for automatic pattern recognition based on fault diagnosis by solving data imbalance problem in a cloud-based manufacturing (CBM). Fault diagnosis in a CBM system significantly contributes to reduce the product testing cost and enhances manufacturing quality. One of the major challenges facing the big data analytics in cloud-based manufacturing is handling of datasets, which are highly imbalanced in nature due to poor classification result when machine learning techniques are applied on such datasets. The framework proposed in this research uses a hybrid approach to deal with big dataset for smarter decisions. Furthermore, we compare the performance of radial basis function based Support Vector Machine classifier with standard techniques. Our findings suggest that the most important task in cloud-based manufacturing, is to predict the effect of data errors on quality due to highly imbalance unstructured dataset. The proposed framework is an original contribution to the body of literature, where our proposed MapReduce framework has been used for fault detection by managing data imbalance problem appropriately and relating it to firm’s profit function. The experimental results are validated using a case study of steel plate manufacturing fault diagnosis, with crucial performance matrices such as accuracy, specificity and sensitivity. A comparative study shows that the methods used in the proposed framework outperform the traditional ones