Application of Taguchi method for optimization of resistance spot welding of austenitic stainless steel AISI 301L

This study presents a systematic approach to determine effect of process parameters on indentation as a primary & initial measure of weld quality and subsequently tensile strength, nugget diameter and penetration. To achieve the objective an attempt has been made to select important welding parameters like welding current, weld cycle, hold time  & cool cycle using quality tools, available literature and on scientific reasons. On the selected parameters, Experiment have been conducted as per Taguchi method and fixed the levels for the parameters. The experiment has four factors and all factors are at two levels. To have wide spectrum of analysis and variability with time, L32 Orthogonal Array (OA) experiments are conducted. Optimum welding parameters determined by Taguchi method improved indentation which in turn confirms the value of nugget size, tensile strength and penetration. Analysis of variance (ANOVA) and F-test has been used for determining most significant parameters affecting the spot weld parameters. Keywords: Welding parameters; Taguchi Method; Resistance spot welding (RSW); Orthogonal array; ANOV

A comparison of dose-response characteristics of four NTCP models using outcomes of radiation-induced optic neuropathy and retinopathy

<p>Abstract</p> <p>Background</p> <p>Biological models are used to relate the outcome of radiation therapy to dose distribution. As use of biological models in treatment planning expands, uncertainties associated with the use of specific models for predicting outcomes should be understood and quantified. In particular, the question to what extent model predictions are data-driven or dependent on the choice of the model has to be explored.</p> <p>Methods</p> <p>Four dose-response models--logistic, log-logistic, Poisson-based and probit--were tested for their ability and consistency in describing dose-response data for radiation-induced optic neuropathy (RION) and retinopathy (RIRP). Dose to the optic nerves was specified as the minimum dose, <it>D_min</it>, received by any segment of the organ to which the damage was diagnosed by ophthalmologic evaluation. For retinopathy, the dose to the retina was specified as the highest isodose covering at least 1/3 of the retinal surface (<it>D_33%</it>) that geometrically covered the observed retinal damage. Data on both complications were modeled separately for patients treated once daily and twice daily. Model parameters <it>D₅₀</it>and <it>γ </it>and corresponding confidence intervals were obtained using maximum-likelihood method.</p> <p>Results</p> <p>Model parameters were reasonably consistent for RION data for patients treated once daily, <it>D₅₀</it>ranging from 94.2 to 104.7 Gy and <it>γ </it>from 0.88 to 1.41. Similar consistency was seen for RIRP data which span a broad range of complication incidence, with <it>D₅₀</it>from 72.2 to 75.0 Gy and <it>γ </it>from 1.51 to 2.16 for patients treated twice daily; 72.2-74.0 Gy and 0.84-1.20 for patients treated once daily. However, large variations were observed for RION in patients treated twice daily, D₅₀from 96.3 to 125.2 Gy and <it>γ </it>from 0.80 to 1.56. Complication incidence in this dataset in any dose group did not exceed 20%.</p> <p>Conclusions</p> <p>For the considered data sets, the log-logistic model tends to lead to larger <it>D₅₀</it>and lower <it>γ </it>compared to other models for all datasets. Statements regarding normal tissue radiosensitivity and steepness of dose-response, based on model parameters, should be made with caution as the latter are not only model-dependent but also sensitive to the range of complication incidence exhibited by clinical data.</p

A prospective study of the study of maternal and perinatal outcome in cases of eclampsia

Background: This is an observational analytical study carried out in the department of obstetrics and gynecology, in a tertiary care center to determine the factors influencing fetal and maternal outcome, prognosis and complications in booked and unbooked eclamptic cases.Methods: The present study is a prospective study of perinatal and maternal outcome in 50 cases of eclampsia, above 32 weeks of gestation, from 1st May 2013 to 30th April 2014. Patients with medical complications like anemia, preexisting hypertension, diabetes, vascular or renal disease, multiple gestation, polyhydraminos, etc. are excluded from the study. Detailed history, physical examinations were carried out and appropriate management instituted as per individual patient need. Follow-up of mothers up to 6weeks postpartum and neonates in the early neonatal period was done.                Results: Incidence of eclampsia is 0.64%, incidence of maternal mortality is 0.4% and perinatal mortality is 24%. 36% of patients developed complications. Maternal mortality was significantly high in patients with 6 or more episodes of convulsions. The most common cause of perinatal mortality is prematurity. Antepartum eclampsia with gestational age less than 36 weeks, BP >160/100, preterm births, low birth weight babies, low apgar scores influenced adverse perinatal outcome.Conclusions: Eclampsia still remains a major problem in developing countries. It is one of the important causes of maternal and perinatal morbidity and mortality due to lack of proper ANC, low socio-economic status and lack of education

AN EFFECTIVE STRATEGY FOR IDENTIFY HIGH QUALITY JPEG COMPRESSION BY USING NETWORKS PREDICTOR IMPLEMENTATION

Revealing the Trace of High-Quality JPEG Compression through Quantization Noise Analysis To recognize whether a picture continues to be JPEG compressed is a vital issue in forensic practice. The condition-of-the-art techniques neglect to identify high-quality compressed images that are common on the web. Within this paper, we offer a manuscript quantization noise-based means to fix reveal the traces of JPEG compression. In line with the analysis of noises in multiple-cycle JPEG compression, we define a sum known as forward quantization noise. We analytically derive that the decompressed JPEG image includes a lower variance of forward quantization noise than its uncompressed counterpart. Using the conclusion, we create a simple yet extremely effective recognition formula to recognize decompressed JPEG images. Within this paper, we concentrate on the problem of determining whether a picture presently in uncompressed form is really uncompressed or continues to be formerly JPEG compressed. We analytically derive that the decompressed JPEG image includes a lower variance of forward quantization noise than its uncompressed counterpart. To recognize whether a picture has been JPEG compressed is a vital issue in forensic practice. The suggested formula does apply in certain practical programs, for example Internet image classification and forgery recognition. This Tate-of-the-art techniques neglect to identify high-quality compressed images, that are common on the web. Within this paper, we offer a manuscript quantization noise-based means to fix reveal the traces of JPEG compression. In line with the analysis of noises in multiple-cycle JPEG compression, we define a quantity called forward quantization noise. With the conclusion, we create a simple yet extremely effective detection algorithm to recognize decompressed JPEG images. We show that our method outperforms the condition-of-the-art techniques with a large margin specifically for high-quality compressed images through extensive experiments on various causes of images. We also demonstrate the suggested technique is robust to small image size and chromo sub sampling

Ferroelectric Dead Layer Driven by a Polar Interface

Based on first-principles and model calculations we investigate the effect of polar interfaces on the ferroelectric stability of thin-film ferroelectrics. As a representative model, we consider a TiO2-terminated BaTiO3 film with LaO monolayers at the two interfaces that serve as doping layers. We find that the polar interfaces create an intrinsic electric field that is screened by the electron charge leaking into the BaTiO3 layer. The amount of the leaking charge is controlled by the boundary conditions which are different for three heterostructures considered, namely Vacuum/LaO/BaTiO3/LaO, LaO/BaTiO3, and SrRuO3/LaO/BaTiO3/LaO. The intrinsic electric field forces ionic displacements in BaTiO3 to produce the electric polarization directed into the interior of the BaTiO3 layer. This creates a ferroelectric dead layer near the interfaces that is non-switchable and thus detrimental to ferroelectricity. Our first-principles and model calculations demonstrate that the effect is stronger for a larger effective ionic charge at the interface and longer screening length due to a stronger intrinsic electric field that penetrates deeper into the ferroelectric. The predicted mechanism for a ferroelectric dead layer at the interface controls the critical thickness for ferroelectricity in systems with polar interfaces.Comment: 33 Pages, 5 figure

Prediction of a Switchable Two-Dimensional Electron Gas at Ferroelectric Oxide Interfaces

The demonstration of a quasi-two-dimensional electron gas (2DEG) in LaAlO3=SrTiO3 heterostructures has stimulated intense research activity in recent years. The 2DEG has unique properties that are promising for applications in all-oxide electronic devices. For such applications it is desirable to have the ability to control 2DEG properties by external stimulus. Here, based on first-principles calculations we predict that all-oxide heterostructures incorporating ferroelectric constituents, such as KNbO3=ATiO3 (A = Sr, Ba, Pb), allow creating a 2DEG switchable between two conduction states by ferroelectric polarization reversal. The effect occurs due to the screening charge at the interface that counteracts the depolarizing electric field and depends on polarization orientation. The proposed concept of ferroelectrically controlled interface conductivity offers the possibility to design novel electronic devices

Suppression of Octahedral Tilts and Associated Changes of Electronic Properties at Epitaxial Oxide Heterostructure Interfaces

Epitaxial oxide interfaces with broken translational symmetry have emerged as a central paradigm behind the novel behaviors of oxide superlattices. Here, we use scanning transmission electron microscopy to demonstrate a direct, quantitative unit-cell-by-unit-cell mapping of lattice parameters and oxygen octahedral rotations across the BiFeO3-La0.7Sr0.3MnO3 interface to elucidate how the change of crystal symmetry is accommodated. Combined with low-loss electron energy loss spectroscopy imaging, we demonstrate a mesoscopic antiferrodistortive phase transition and elucidate associated changes in electronic properties in a thin layer directly adjacent to the interface

SYSTEMIC SCLEROSIS: A CASE STUDY IN AYURVEDIC SETTINGS

ABSTRACT Systemic sclerosis (SSc) is a multisystem disorder of unknown cause characterized by fibrosis of skin, blood vessels, and visceral organs including the gastrointestinal tract, lungs, heart, and kidneys. There are two distinct clinical presentations viz., Diffuse and limited forms. We are herewith reporting a case of diffuse cutaneous scleroderma in a 21 year old female student. The possible understanding of the case in terms of Ayurveda and a therapeutic protocol with promising result has beendiscussed

CI-SpliceAI—Improving machine learning predictions of disease causing splicing variants using curated alternative splice sites

Background It is estimated that up to 50% of all disease causing variants disrupt splicing. Due to its complexity, our ability to predict which variants disrupt splicing is limited, meaning missed diagnoses for patients. The emergence of machine learning for targeted medicine holds great potential to improve prediction of splice disrupting variants. The recently published SpliceAI algorithm utilises deep neural networks and has been reported to have a greater accuracy than other commonly used methods. Methods and findings The original SpliceAI was trained on splice sites included in primary isoforms combined with novel junctions observed in GTEx data, which might introduce noise and de-correlate the machine learning input with its output. Limiting the data to only validated and manual annotated primary and alternatively spliced GENCODE sites in training may improve predictive abilities. All of these gene isoforms were collapsed (aggregated into one pseudo-isoform) and the SpliceAI architecture was retrained (CI-SpliceAI). Predictive performance on a newly curated dataset of 1,316 functionally validated variants from the literature was compared with the original SpliceAI, alongside MMSplice, MaxEntScan, and SQUIRLS. Both SpliceAI algorithms outperformed the other methods, with the original SpliceAI achieving an accuracy of ∼91%, and CI-SpliceAI showing an improvement at ∼92% overall. Predictive accuracy increased in the majority of curated variants. Conclusions We show that including only manually annotated alternatively spliced sites in training data improves prediction of clinically relevant variants, and highlight avenues for further performance improvements