Aditya Birla (India)

BACKGROUND: Arrhythmogenic right ventricular dysplasia/cardiomyopathy (ARVD/C) is a progressive cardiomyopathy. We aimed to define long-term outcome in a transatlantic cohort of 1001 individuals. METHODS AND RESULTS: Clinical and genetic characteristics and follow-up data of ARVD/C index-patients (n=439, fulfilling of 2010 criteria in all) and family members (n=562) were assessed. Mutations were identified in 276 index-patients (63%). Index-patients presented predominantly with sustained ventricular arrhythmias (268; 61%). During a median follow-up of 7 years, 301 of the 416 index-patients presenting alive (72%) experienced sustained ventricular arrhythmias. Sudden cardiac death during follow-up occurred more frequently among index-patients without an implantable cardioverter-defibrillator (10/63, 16% versus 2/335, 0.6%). Overall, cardiac mortality and the need for cardiac transplantation were low (6% and 4%, respectively). Clinical characteristics and outcomes were similar in index-patients with and without mutations, as well as in those with familial and nonfamilial ARVD/C. ARVD/C was diagnosed in 207 family members (37%). Symptoms at first evaluation correlated with disease expression. Family members with mutations were more likely to meet Task Force Criteria for ARVD/C (40% versus 18%), experience sustained ventricular arrhythmias (11% versus 1%), and die from a cardiac cause (2% versus 0%) than family members without mutations. CONCLUSIONS: Long-term outcome was favorable in diagnosed and treated ARVD/C index-patients and family members. Outcome in index-patients was modulated by implantable cardioverter-defibrillator implantation, but not by mutation status and familial background of disease. One third of family members developed ARVD/C. Outcome in family members was determined by symptoms at first evaluation and mutations.

Collaborative manufacturer–retailer relationships based on efficient consumer response (ECR) have become ubiquitous over the past decade. Yet academic studies of ECR adoption and its impact on marketing relationships are relatively scarce. Inspired by the relational view of competitive advantage, the authors empirically investigate whether the extent to which suppliers of a major retailer adopt ECR has a beneficial impact on their outcomes. The results demonstrate that whereas ECR adoption has a positive impact on supplier economic performance and capability development, it also generates greater perceptions of negative inequity on the part of the supplier. However, retailer capabilities and supplier trust moderate some of these main effects. The overall results are robust with respect to differences in supplier size as well as between branded and private-label suppliers.

Purpose This paper aims to investigate the interaction between sustainability and financial performance. Can socially responsible investors, integrating environmental, social and ethical issues in their investment policy, expect the same return as traditional investors? Design/methodology/approach Based on the sustainability ratings of a specialized rating agency, Vigeo, a Fama and French approach is performed to adapt for style biases in the performances. Findings The results indicate that, on a style‐adjusted basis, high sustainability‐rated portfolios have performed better than low‐rated portfolios, but, probably due to the short horizon, not to a significant extent. The same results are found for four out of the five sub‐ratings of which the sustainability rating is composed, suggesting that sustainability is a broad and multidimensional concept that cannot be attributed to one specific theme or topic. The results also indicate that investors are ready to pay a premium for companies with good management of their relations with shareholders, clients and suppliers. Research limitations/implications Owing to the rather new concept of socially responsible investing and in order to avoid survivorship bias, only a relative time horizon is considered. Practical implications There is no cost involved in integrating sustainable dimensions in the investment policy. Originality/value The paper shows the relevance of socially responsible investing when one adjusts for style differences within the portfolio.

Teledentistry is a combination of telecommunications and dentistry involving the exchange of clinical information and images over remote distances for dental consultation and treatment planning. Teledentistry has the ability to improve access to oral healthcare, improve the delivery of oral healthcare, and lower its costs. It also has the potential to eliminate the disparities in oral health care between rural and urban communities. This article reviews the origin, rationale, scope, basis, and requirements for teledentistry, along with the current evidence that exists in the literature. This article also reviews the ethical and legal issues related to the practice of teledentistry and the future of this alternative and innovative method of delivering dental care.

Consumer products, such as foods, contain numerous polymeric and particulate additives that play critical roles in maintaining their stability, quality and function. The resulting materials exhibit complex bulk and interfacial rheological responses, and often display a distinctive power-law response under standard rheometric deformations. These power laws are not conveniently described using conventional rheological models, without the introduction of a large number of relaxation modes. We present a constitutive framework using fractional derivatives to model the power-law responses often observed experimentally. We first revisit the concept of quasi-properties and their connection to the fractional Maxwell model (FMM). Using Scott-Blair's original data, we demonstrate the ability of the FMM to capture the power-law response of ‘highly anomalous’ materials. We extend the FMM to describe the viscoelastic interfaces formed by bovine serum albumin and solutions of a common food stabilizer, Acacia gum. Fractional calculus allows us to model and compactly describe the measured frequency response of these interfaces in terms of their quasi-properties. Finally, we demonstrate the predictive ability of the FMM to quantitatively capture the behaviour of complex viscoelastic interfaces by combining the measured quasi-properties with the equation of motion for a complex fluid interface to describe the damped inertio-elastic oscillations that are observed experimentally.

The power available at the output of solar arrays keeps changing with solar insolation and ambient temperature. Expensive and inefficient, the solar arrays must be operated at maximum power point (MPP) continuously for economic reasons. Of the numerous algorithms for this purpose, perturb and observe (P&O) is a standard. A derivative of gradient ascent method used in the optimization theory, this algorithm introduces a tradeoff between tracking and dynamic performance. This algorithm also has a tendency to drift the system away from the MPP as atmospheric conditions change. With continually changing atmospheric conditions, these inadequacies lead to poor utilization of solar arrays. This paper addresses both the issues. A variable-step-length algorithm is proposed to eliminate the tradeoff. The drift is minimized by evaluating the entire trend in a power versus voltage curve. Analytical results, validated on a prototype system show excellent performance.

Abstract In recent years, numerous investigations have explored the use of biochar for the removal of organic and inorganic pollutants in single component systems. Biochar is a carbonaceous material produced from waste biomass, mainly by thermochemical conversion methods. This material was used as a biosorbent in various removal processes of pollutants, and its efficiency was strongly influenced by the characteristics of the biomass feedstock. This review integrates the recent works of literature to understand the biosorption behaviour of dyes onto biochar-based biosorbents. The factors influencing the biosorption process and the mechanisms describing the biosorption behaviours of the biochar have been broadly reviewed. Furthermore, the biosorption models can be used to comprehend the competence of the biochar as biosorbent for dye removal techniques. Graphical Abstract

ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTAn Ion-exchange Study of Possible Hybridized 5f Bonding in the Actinides1R. M. Diamond, K. Street Jr., and G. T. SeaborgCite this: J. Am. Chem. Soc. 1954, 76, 6, 1461–1469Publication Date (Print):March 1, 1954Publication History Published online1 May 2002Published inissue 1 March 1954https://doi.org/10.1021/ja01635a001Request reuse permissionsArticle Views712Altmetric-Citations235LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InReddit PDF (859 KB) Get e-Alertsclose Get e-Alerts

BACKGROUND: Prior studies evaluating the efficacy of catheter ablation of ventricular tachycardia (VT) among patients with arrhythmogenic right ventricular dysplasia/cardiomyopathy (ARVD/C) have reported varied outcomes. More recently, studies have suggested that an epicardial ablation is necessary for improved outcomes after catheter ablation of VT. The overall objective of the present study was to assess the efficacy of radiofrequency catheter ablation (RFA) of VT in ARVD/C, with particular focus on newer ablation strategies, including epicardial catheter ablation. METHODS AND RESULTS: The study population included 87 patients with ARVD/C who underwent a total of 175 RFA procedures between 1992 and 2011 at 80 different electrophysiology centers. Recurrence of VT following RFA and effect of RFA on the burden of VT were assessed. The mean age of the cohort was 38±13 years. Over a mean follow-up of 88.3±66 months, the overall freedom from VT of the 175 procedures was 47%, 21%, and 15%, at 1, 5, and 10 years, respectively. The cumulative freedom from VT following epicardial RFA was 64% and 45% at 1 and 5 years, respectively, which was significantly longer than endocardial RFA (P=0.021). Survival free of VT among procedures with 3D electroanatomic mapping was significantly longer compared to those without (P=0.016). Burden of VT was reduced irrespective of the ablation strategy (P<0.001). CONCLUSIONS: Although VT recurrences are common, RFA results in a significant reduction in the burden of VT in patients with ARVD/C. Further, although the use of 3D electroanatomic mapping systems and epicardial ablation strategies are associated with longer survival free of VT, recurrence rates remain considerable.

This study inspects the viability of engaging the discarded paper wastes in concrete by varying the volume proportions from 0%–20% with each 5% increment in replacement of the weight of cement. A physiomechanical study was conducted, and the results were presented. A glass fiber reinforced rectangular slab with a longer span ( l y ) to shorter span ( l x ) ratio of ( l y : l x ) 1.16 was cast with optimum replacement of waste‐paper mass and compared the force‐deformation characteristics with the conventional concrete slab without waste paper. The optimum percentage of discarded papers for the replacement of cement is 5%. Also, the results imply that the compressive strength at the age of 28 days is 30% improved for the optimum replacement. Based on the outcomes of the investigation, it can be inferred that the compressive strength gets progressively reduced if the volume of the discarded paper gets increases. The incorporation of glass fibers improves the split and flexural strength of the concrete specimens considerably. The ultimate load‐carrying capacity of the glass fiber reinforced waste paper incorporated concrete slab measured 42% lower than that of the conventional slab. However, development of the new type of concrete incorporating waste papers is the new trend in ensuring the sustainability of construction materials.

The future sixth generation (6G) wireless communication networks will face the challenges of large-scale connections green communication. To meet these requirements, cognitive ambient backscatter communication (C-AmBC) has been proposed as a new spectrum paradigm for the green Internet-of-Things (IoT) with stringent energy and spectrum constraints, in which the backscatter device (BD) can achieve communications by simultaneously sharing both spectrum and radio-frequency (RF) sources. However, due to the broadcasting nature of wireless communication channels, BD is vulnerable to eavesdropping from unlicensed eavesdroppers. To address this, this paper proposes a framework of C-AmBC networks in the presence of an unlicensed eavesdropper. Specifically, we investigate the reliability and security of the proposed framework by invoking the outage probability (OP) and intercept probability (IP) with analytical derivations. In addition, the asymptotic behaviors are conducted for the OP in the high signal-to-noise ratio (SNR) regime and IP in the high main-to-eavesdropper ratio (MER) regime. Extensive analytical and computer simulated performance evaluation results show that: 1) when the considered system is under high SNR, the OP of the legitimate user and BD tends to be a non-zero fixed constant, indicating that the existence of error floors for the diversity orders; 2) the performance trade-off of reliability and security can be optimized by adjusting various parameters of the considered system; 3) with the increase of MER, the security of the legitimate user increases, while that of BD decreases.

This research reports the significance of influence of speed, feed and depth of cut on cutting force and surface roughness while working with tool made of ceramic with an Al2O3+TiC matrix (KY1615)and the work material of AISI 1050 steel (hardness of 484 HV). Experiments were conducted using Johnford TC35 Industrial type of CNC lathe. Taguchi method (L27 design with 3 levels and 3 factors) was used for the experiments. Analysis of variance with adjusted approach has been adopted. The results have indicated that it is feed rate which has significant influence both on cutting force as well as surface roughness. Depth of cut has a significant influence on cutting force, but has an insignificant influence on surface roughness. The interaction of feed and depth of cut and the interaction of all the three cutting parameters have significant influence on cutting force, whereas, none of the interaction effects are having significant influence on the surface roughness produced. If power consumption minimization is to be achieved for the best possible surface finish, the most recommended combination of feed rate and depth of cut is also determined.

), and above this threshold the emission becomes excitation dependent. We also demonstrate that a similar trend is apparent for nearly all variants of 0D carbon reported in the literature. The threshold wavelength correlates well with the excitation wavelength for the most intense emission and the photoluminescence excitation peaks, suggesting a common origin of light emission in these carbon dots. The findings provide important clues for developing a unified general picture for understanding the light emission mechanism in 0D carbon nanostructures.

This review article aims to provide an in-depth analysis of the literature along with comprehensive bibliography on automatic generation control (AGC)/load frequency control investigations. Different control perspectives concerning frequency and power control have been featured. Diverse linear, non-linear power system models are discussed under conventional and deregulated environments considering various power generation sources, including conventional, renewable energy sources (RES), and realistic RES. Moreover, AGC literature briefly explains various secondary controllers like integer order, fractional order, intelligent, cascade, and some recently used controllers. To obtain the optimum values of secondary controllers, various optimization strategies such as numerical approach, heuristic, and meta-heuristic techniques for AGC issues are mentioned. Also, AGC studies concerning power transmission, considering inertia and phase-locked loops in high voltage direct current (HVDC) and accurate HVDC models are discussed. Further, AGC literature integrated with flexible alternating current transmission system devices in loaded transmission lines and energy storage devices due to intermittent power generation in RES is deliberated. Furthermore, various performance index criteria (PIC) such as standard PIC and hybrid peak area (HPA)–PIC for controller optimization with algorithms are also conferred.

The Internet of things aspires to connect anyone with anything at any point of time at any place. Internet of Thing is generally made up of three-layer architecture. Namely Perception, Network and Application layers. A lot of security principles should be enabled at each layer for proper and efficient working of these applications. This paper represents the overview of Security principles, Security Threats and Security challenges at the application layer and its countermeasures to overcome those challenges. The Application layer plays an important role in all of the Internet of Thing applications. The most widely used application layer protocol is MQTT. The security threats for Application Layer Protocol MQTT is particularly selected and evaluated. Comparison is done between different Application layer protocols and security measures for those protocols. Due to the lack of common standards for IoT protocols, a lot of issues are considered while choosing the particular protocol.

Perioperative stroke is one of the most severe and feared complications of cardiac surgery. Based on the timing of onset and detection, perioperative stroke can be classified as intraoperative or postoperative. The pathogenesis of perioperative stroke is multifactorial, which makes prediction and prevention challenging. However, information on its incidence, mechanisms, diagnosis, and treatment can be helpful in minimizing the perioperative neurological risk for individual patients. We herein provide suggestions on preoperative, intraoperative, and postoperative strategies aimed at reducing the risk of perioperative stroke and at improving the outcomes of patients who experience a perioperative stroke.

The recent outbreak of a novel coronavirus, named COVID-19 by the World Health Organization (WHO) has pushed the global economy and humanity into a disaster. In their attempt to control this pandemic, the governments of all the countries have imposed a nationwide lockdown. Although the lockdown may have assisted in limiting the spread of the disease, it has brutally affected the country, unsettling complete value-chains of most important industries. The impact of the COVID-19 is devastating on the economy. Therefore, this study has reported about the impact of COVID-19 epidemic on various industrial sectors. In this regard, the authors have chosen six different industrial sectors such as automobile, energy and power, agriculture, education, travel and tourism and consumer electronics, and so on. This study will be helpful for the policymakers and government authorities to take necessary measures, strategies and economic policies to overcome the challenges encountered in different sectors due to the present pandemic.

Copy–Move Forgery Detection (CMFD) helps to detect copied and pasted areas in one image. It plays a crucial role in legal evidence, forensic investigation, defence, and many more places. In the proposed CMFD method, a two-step identification of forgery is presented. In step one, the suspected image will be classified into either one of two classes that are forged or authentic. Step two is carried out​ only if the suspected is classified as forged, then forged location will be identified using the block-matching procedure. Initially, the suspected image is decomposed into different orientations using Steerable Pyramid Transform (SPT); Grey Level Co-occurrence Matrix (GLCM) features are extracted from each orientation. These features are used to train Optimized Support Vector Machine (OSVM) as well as to classify. If the suspected image is categorized into forged, then the suspected grey image is converted into overlapping blocks, and from each block, GLCM features are extracted. The proper similarity threshold value and distance threshold value can locate the forged region using GLCM block features. The performance of the proposed method is tested using standard datasets CoMoFoD and CASIA Datasets. The proposed CMFD approach results are consistent, even the forged image suffered from attacks like JPEG compression, scaling, and rotation. The OSVM classifier is showing superiority over the Optimized Naive Bayes Classifier (ONBC), Extreme Learning Machine (ELM) and Support Vector Machine (SVM).

Artificial intelligence (AI) based disease identification has the potential to transform medicine by utilizing machine learning algorithms and techniques to analyze large volumes of medical data and identify patterns and features that may be difficult for human experts to detect. However, there are still challenges and limitations to overcome, such as the need for high-quality medical data and concerns around privacy and bias. This chapter explores the growing intersection of machine learning (ML) and AI techniques with disease prediction. The chapter begins by providing an overview of ML and AI methodologies commonly employed in disease prediction, including supervised and unsupervised learning algorithms, deep learning techniques, and ensemble methods. Lastly, the chapter outlines future directions and research opportunities in the field.

Image segmentation is a very important and pre-processing step in image analysis. The conventional multilevel thresholding methods are efficient for bi-level thresholding because of its simplicity, robustness, less convergence time and accuracy. However, a mass of computational cost is needed and efficiency is broken down as an exhaustive search is utilized for finding the optimal thresholds, which results in application of evolutionary algorithm and swarm intelligence to obtain the optimal thresholds. The main aim of image segmentation was to segregate the foreground from background. For the first time this paper established a naturally inspired firefly algorithm based multilevel image thresholding for image segmentation by maximizing Shannon entropy or Fuzzy entropy. The proposed algorithm is tested on standard set of images and results are compared with the Shannon entropy or Fuzzy entropy based methods that are optimized by Differential Evolution (DE), Particle Swarm Optimization (PSO) and bat algorithm (BA). It is demonstrated that the proposed method shows better performance in objective function, structural similarity index, peak signal to noise ratio, misclassification error and CPU time than state of art methods.