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Long noncoding RNAs (lncRNAs) are emerging as important regulators of tissue physiology and disease processes including cancer. To delineate genome-wide lncRNA expression, we curated 7,256 RNA sequencing (RNA-seq) libraries from tumors, normal tissues and cell lines comprising over 43 Tb of sequence from 25 independent studies. We applied ab initio assembly methodology to this data set, yielding a consensus human transcriptome of 91,013 expressed genes. Over 68% (58,648) of genes were classified as lncRNAs, of which 79% were previously unannotated. About 1% (597) of the lncRNAs harbored ultraconserved elements, and 7% (3,900) overlapped disease-associated SNPs. To prioritize lineage-specific, disease-associated lncRNA expression, we employed non-parametric differential expression testing and nominated 7,942 lineage- or cancer-associated lncRNA genes. The lncRNA landscape characterized here may shed light on normal biology and cancer pathogenesis and may be valuable for future biomarker development.

Machine vision is a computer vision system that enables a computer to work on image-based inspection and analysis for different applications. In this computer vision, a camera and sensor were used to view an image for its analysis with the help of some sort of algorithms, then processed to infer the image-based data. Machine vision systems along with Python programs can be used for many interdisciplinary applications like weld inspection, online monitoring in manufacturing auto components etc. In this study, the "Edge detection python algorithm" was developed and run through "Google Colab" notebook to inspect the edges and the boundaries of samples like faying surface-modified friction welded dissimilar joints and a binder clip (paper clamp) to check any defects or cracks and straightness etc. With the help of this Python algorithm, the edge detection was done by Sobel, Scharr, and Prewit operators. An input image of the weld joint and the binder clip were converted into Otsu's binary threshold image. The matrix vision camera and the CMOS sensor were used in the machine vision set-up to take the images. This written algorithm is helpful to trace the edges of any kind of solids components. The edges of the binder clips and the weld joint/zone were detected. The binder clips were inspected under two different cases namely the clip in folding condition (Case I) and the binder clip in unfolding condition (Case II). The results showed a defect that was identified in the weld zone and no bending was in the binder clips. This kind of study is useful in manufacturing industries for quality inspection purposes with a new machine vision set up for online inspection of fabricated components like nuts and bolts etc. [ABSTRACT FROM AUTHOR]

Quality Of Work Life Is The Degree To Which Individuals Are Able To Satisfy Their Important Personal Needs While Employed By The Firm. The Quality Of Work Life Is A Based On The Individual Satisfaction, Motivation, Involvement, Experience, And Commitments With Reference To Their Work. Quality Of Work Life May Be A Process In Organizations, Which Enables Its Members From All Levels To Participate Actively And Effectively In Shaping The Organization Environment, Methods, And Outcomes. There Is An Attempt To Look Into The Quality Of Work Life Among Employees. The Main Objective Of This Project Is To Understand The Current Scenario On Quality Of Work Life Among The Employees And Provide Measures To Improve It. This Could Be Found Out By Finding The Reasons, Which Affect The Employee's Quality Of Work Life, Satisfaction Level Of Employees Towards The Welfare Activities, Career Development Opportunities Provided By The Employer Which Will Be Our Secondary Objective. The Research Was Carried Out Using Descriptive Research Design And Convenience Sampling Method. The Sample Size Is Taken As 100 And Analysis Was Done Based On The Data Collected From The Questionnaire. The Tools Used For Analyzing The Data Are Chi-Square, Anova, Correlation Analysis. Based On The Findings, The Organization Should Focus On The Factors To Increase The Quality Of Work Life In The Organization. From The Research, The Reasons, The Areas That Is Needed To Improve The Quality Of Work Life Of Employees Could Be Identified And The Methods To Improve Them Could Be Found. [ABSTRACT FROM AUTHOR]

Abstract Servo press forming machines are advanced forming systems that are capable of imparting interrupted punch motion, resulting in enhanced room temperature formability. The exact mechanism of the formability improvement is not yet established. The contribution of interrupted motion in the ductility improvement has been studied through stress relaxation phenomena in uniaxial tensile (UT) tests. However, the reason for improved formability observed when employing servo press is complicated due to the additional contribution from frictional effects. In the present work, an attempt is made to decouple the friction effect on formability improvement numerically. The improved formability is studied using a hole expansion test (HET). The limit of forming during hole expansion is modeled using the Hosford-Coulomb (HC) damage criteria, which is implemented as a user subroutine in a commercial explicit finite element (FE) software. Only the contribution of stress relaxation is accounted for in the evolution of the damage variable during interrupted loading. Therefore, the difference between simulation and experimental hole expansion ratio (HER) can be used to decouple the friction effect from the overall formability improvement during hole expansion. The improvement in HER due to stress relaxation and friction effect is different. The study showed that the model effectively captures the hole expansion deformation process in both monotonic and interrupted loading conditions. Compared to stress relaxation, friction effect played a major role during interrupted HET.

With 30 antennas and a maximum baseline length of 25 km, the Giant Metrewave Radio Telescope (GMRT) is the premier low-frequency radio interferometer today. We have carried out a study of possible expansions of the GMRT, via adding new antennas and installing focal plane arrays (FPAs), to improve its point-source sensitivity, surface brightness sensitivity, angular resolution, field of view, and UV coverage. We have carried out array configuration studies, aimed at minimizing the number of new GMRT antennas required to obtain a well-behaved synthesized beam over a wide range of angular resolutions for full-synthesis observations. This was done via two approaches, tomographic projection and random sampling, to identify the optimal locations for the new GMRT antennas. We report results for the optimal locations of the antennas of an expanded array (the 'EGMRT'), consisting of the existing 30 GMRT antennas, 30 new antennas at short distances, ≲2.5 km from the GMRT array centre, and 26 additional antennas at relatively long distances, ≈5–25 km from the array centre. The collecting area and the field of view of the proposed EGMRT array would be larger by factors of, respectively, ≈3 and ≈30, than those of the GMRT. Indeed, the EGMRT continuum sensitivity and survey speed with 550–850 MHz FPAs installed on the 45 antennas within a distance of ≈2.5 km of the array centre would be far better than those of any existing interferometer, and comparable to the sensitivity and survey speed of Phase-1 of the Square Kilometre Array. [ABSTRACT FROM AUTHOR]

The flow stress reduction during plastic deformation superposed with electric current, commonly referred as ‘electroplasticity’ has been actively researched over the past few decades. While the existence of an electron–dislocation interaction, independent of Joule heating is established, the exact rate controlling mechanism of the observed behaviour lacks consensus. Understanding the governing mechanism is complex due to the combined effect of Joule heating and electron–dislocation interaction. The present work attempts to establish the electroplastic mechanism in AA 6063 alloy and its nanocomposites. The role of microstructure on the electron interaction is investigated by preparing four distinct microstructure from the base alloy. All the samples were subjected to constant amplitude direct current during plastic deformation. The Joule heating effect is decoupled using the experimentally measured temperature history. The potential electroplastic mechanism for the alloy is elucidated by analysing the trend of flow stress reduction with strain and strain rate. It is inferred that micro Joule heating and electron wind effect cannot completely explain the observed electroplastic behaviour in AA 6063. The SiC particles in nano-composites suppressed the electroplastic effect.The observed mechanical behaviour under electric current is in agreement with the trend predicted assuming magnetic depinning mechanism. The reduction of dislocation density quantified using X-ray diffraction is found to concur with the inferred mechanism.

Abstract Internet of things (IoTs) enabled cyber‐physical systems is a system that provides communication between physical devices and cyber environment. They run independently without any user interaction. Because the IoT devices are vulnerable to a variety of attacks, security is a noteworthy factor in the development process during communication. To improve secure communication with minimum time consumption, a novel technique called jackknife regressive Schmidt Samoa cryptography‐based deep artificial structure learning (JRSSC‐DASL) is introduced. Initially, the data is monitored by IoT devices and is collected from the dataset. The proposed deep artificial structure learning technique trains the gathered data with multiple layers. Then, the collected data is analysed in the first hidden layer with the help of the jackknife regression function by learning the feature and it classifies the data with higher accuracy. The classified data is sent to the next hidden layer where encryption is performed using Schmidt Samoa (SS) encryption algorithm. Then, the encrypted data is sent to the cloud server where the decryption is performed using the SS decryption algorithm. The cloud server obtains the original data and it is stored in their database for further processing. This process enhances the security of data communication and achieves high data confidentiality with less processing time. Experimental estimation is performed on the factors such as classification accuracy, confidentiality rate, processing time and memory usage to the number of data sensed from IoT device. Conferred results reveal that the proposed JRSSC‐DASL technique has high confidentiality rate and minimum processing time as well as memory usage when compared to state‐of‐the‐art methods.