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Given the highly variable clinical phenotype of Coronavirus disease 2019 (COVID-19), a deeper analysis of the host genetic contribution to severe COVID-19 is important to improve our understanding of underlying disease mechanisms. Here, we describe an extended GWAS meta-analysis of a well-characterized cohort of 3,260 COVID-19 patients with respiratory failure and 12,483 population controls from Italy, Spain, Norway and Germany/Austria, including stratified analyses based on age, sex and disease severity, as well as targeted analyses of chromosome Y haplotypes, the human leukocyte antigen (HLA) region and the SARS-CoV-2 peptidome. By inversion imputation, we traced a reported association at 17q21.31 to a highly pleiotropic ∼0.9-Mb inversion polymorphism and characterized the potential effects of the inversion in detail. Our data, together with the 5th release of summary statistics from the COVID-19 Host Genetics Initiative, also identified a new locus at 19q13.33, including NAPSA, a gene which is expressed primarily in alveolar cells responsible for gas exchange in the lung., Andre Franke and David Ellinghaus were supported by a grant from the German Federal Ministry of Education and Research (01KI20197), Andre Franke, David Ellinghaus and Frauke Degenhardt were supported by the Deutsche Forschungsgemeinschaft Cluster of Excellence “Precision Medicine in Chronic Inflammation” (EXC2167). David Ellinghaus was supported by the German Federal Ministry of Education and Research (BMBF) within the framework of the Computational Life Sciences funding concept (CompLS grant 031L0165). David Ellinghaus, Karina Banasik and Søren Brunak acknowledge the Novo Nordisk Foundation (grant NNF14CC0001 and NNF17OC0027594). Tobias L. Lenz, Ana Teles and Onur Özer were funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation), project numbers 279645989; 433116033; 437857095. Mareike Wendorff and Hesham ElAbd are supported by the German Research Foundation (DFG) through the Research Training Group 1743, "Genes, Environment and Inflammation". This project was supported by a Covid-19 grant from the German Federal Ministry of Education and Research (BMBF; ID: 01KI20197). Luca Valenti received funding from: Ricerca Finalizzata Ministero della Salute RF2016-02364358, Italian Ministry of Health ""CV PREVITAL – strategie di prevenzione primaria cardiovascolare primaria nella popolazione italiana; The European Union (EU) Programme Horizon 2020 (under grant agreement No. 777377) for the project LITMUS- and for the project ""REVEAL""; Fondazione IRCCS Ca' Granda ""Ricerca corrente"", Fondazione Sviluppo Ca' Granda ""Liver-BIBLE"" (PR-0391), Fondazione IRCCS Ca' Granda ""5permille"" ""COVID-19 Biobank"" (RC100017A). Andrea Biondi was supported by the grant from Fondazione Cariplo to Fondazione Tettamanti: "Biobanking of Covid-19 patient samples to support national and international research (Covid-Bank). This research was partly funded by a MIUR grant to the Department of Medical Sciences, under the program "Dipartimenti di Eccellenza 2018–2022". This study makes use of data generated by the GCAT-Genomes for Life. Cohort study of the Genomes of Catalonia, Fundació IGTP. IGTP is part of the CERCA Program / Generalitat de Catalunya. GCAT is supported by Acción de Dinamización del ISCIIIMINECO and the Ministry of Health of the Generalitat of Catalunya (ADE 10/00026); the Agència de Gestió d’Ajuts Universitaris i de Recerca (AGAUR) (2017-SGR 529). Marta Marquié received research funding from ant PI19/00335 Acción Estratégica en Salud, integrated in the Spanish National RDI Plan and financed by ISCIIISubdirección General de Evaluación and the Fondo Europeo de Desarrollo Regional (FEDER-Una manera de hacer Europa")., Beatriz Cortes is supported by national grants PI18/01512. Xavier Farre is supported by VEIS project (001-P-001647) (cofunded by European Regional Development Fund (ERDF), “A way to build Europe”). Additional data included in this study was obtained in part by the COVICAT Study Group (Cohort Covid de Catalunya) supported by IsGlobal and IGTP, EIT COVID-19 Rapid Response activity 73A and SR20-01024 La Caixa Foundation. Antonio Julià and Sara Marsal were supported by the Spanish Ministry of Economy and Competitiveness (grant numbers: PSE-010000-2006-6 and IPT-010000-2010-36). Antonio Julià was also supported the by national grant PI17/00019 from the Acción Estratégica en Salud (ISCIII) and the FEDER. The Basque Biobank is a hospitalrelated platform that also involves all Osakidetza health centres, the Basque government's Department of Health and Onkologikoa, is operated by the Basque Foundation for Health Innovation and Research-BIOEF. Mario Cáceres received Grants BFU2016-77244-R and PID2019-107836RB-I00 funded by the Agencia Estatal de Investigación (AEI, Spain) and the European Regional Development Fund (FEDER, EU). Manuel Romero Gómez, Javier Ampuero Herrojo, Rocío Gallego Durán and Douglas Maya Miles are supported by the “Spanish Ministry of Economy, Innovation and Competition, the Instituto de Salud Carlos III” (PI19/01404, PI16/01842, PI19/00589, PI17/00535 and GLD19/00100), and by the Andalussian government (Proyectos Estratégicos-Fondos Feder PE-0451-2018, COVID-Premed, COVID GWAs). The position held by Itziar de Rojas Salarich is funded by grant FI20/00215, PFIS Contratos Predoctorales de Formación en Investigación en Salud. Enrique Calderón's team is supported by CIBER of Epidemiology and Public Health (CIBERESP), "Instituto de Salud Carlos III". Jan Cato Holter reports grants from Research Council of Norway grant no 312780 during the conduct of the study. Dr. Solligård: reports grants from Research Council of Norway grant no 312769. The BioMaterialBank Nord is supported by the German Center for Lung Research (DZL), Airway Research Center North (ARCN). The BioMaterialBank Nord is member of popgen 2.0 network (P2N). Philipp Koehler has received non-financial scientific grants from Miltenyi Biotec GmbH, Bergisch Gladbach, Germany, and the Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases, University of Cologne, Cologne, Germany. He is supported by the German Federal Ministry of Education and Research (BMBF)., Oliver A. Cornely is supported by the German Federal Ministry of Research and Education and is funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy – CECAD, EXC 2030 – 390661388. The COMRI cohort is funded by Technical University of Munich, Munich, Germany. Genotyping was performed by the Genotyping laboratory of Institute for Molecular Medicine Finland FIMM Technology Centre, University of Helsinki. This work was supported by grants of the Rolf M. Schwiete Stiftung, the Saarland University, BMBF and The States of Saarland and Lower Saxony. Kerstin U. Ludwig is supported by the German Research Foundation (DFG, LU-1944/3-1). Genotyping for the BoSCO study is funded by the Institute of Human Genetics, University Hospital Bonn. Frank Hanses was supported by the Bavarian State Ministry for Science and Arts. Part of the genotyping was supported by a grant to Alfredo Ramirez from the German Federal Ministry of Education and Research (BMBF, grant: 01ED1619A, European Alzheimer DNA BioBank, EADB) within the context of the EU Joint Programme – Neurodegenerative Disease Research (JPND). Additional funding was derived from the German Research Foundation (DFG) grant: RA 1971/6-1 to Alfredo Ramirez. Philip Rosenstiel is supported by the DFG (CCGA Sequencing Centre and DFG ExC2167 PMI and by SH state funds for COVID19 research). Florian Tran is supported by the Clinician Scientist Program of the Deutsche Forschungsgemeinschaft Cluster of Excellence “Precision Medicine in Chronic Inflammation” (EXC2167). Christoph Lange and Jan Heyckendorf are supported by the German Center for Infection Research (DZIF). Thorsen Brenner, Marc M Berger, Oliver Witzke und Anke Hinney are supported by the Stiftung Universitätsmedizin Essen. Marialbert Acosta-Herrera was supported by Juan de la Cierva Incorporacion program, grant IJC2018-035131-I funded by MCIN/AEI/10.13039/501100011033. Eva C Schulte is supported by the Deutsche Forschungsgemeinschaft (DFG; SCHU 2419/2-1).

We present the design and implementation of DIO, a novel digital-physical construction toolkit to enable constructionist learning for children from age group 8-12 years. The toolkit comprises of dome-shaped (D) tangible modules with various attachments that allow suspension on the body of multiple children and/or in the environment to support a variety of sensing/input (I), actuation/output (O) functionalities. The modules are enabled for wireless communication and can be linked together using an Augmented Reality based programming interface running on a smartphone. The smartphone recognizes our hemispherical modules omnidirectionally through novel computer vision based 3D patterns; custom made to provide logical as well as semantic encoding. In this paper, we show how, owing to its unique form-factor, the toolkit enables multi-user constructions for the children and offers a shared learning experience. We further reflect on our learning from a one-year long iterative design process and contribute a social scaffolding based procedure to engage children with such constructionist toolkits effectively.

The quantitative and differential analysis of leukocytes present in human body provide conducive hematological information to physicians for diagnosis of various infections and ailments. This paper proposes an Optimized Binary Bat algorithm, an enhanced version of the original Binary Bat Algorithm, for classification of different types of leukocytes. It is used for the first time in this field of application to the best of our knowledge. A set of features are extracted from images of WBCs and then the optimized algorithm is used to obtain a subset of those features which are essential and more relevant from the high-dimensional dataset. Similar to the original BBA, the optimized BBA is an evolutionary algorithm inspired by the echolocation technique used by bats for locating a prey or an object. OBBA aims to reduce the dimensionality of the dataset by determining the features which are most discriminative. The proposed algorithm is implemented using four different classifiers, K-nearest neighbors (KNN), Logistic Regression, Random Forest and Decision Tree, and their performance is compared. The proposed OBBA can be used in classification of WBCs with an average accuracy of 97.3% and help in analysis of numerous hematological conditions. The optimized BBA is also compared with other nature inspired algorithms including Optimized Crow Search algorithm and Optimized Cuttlefish algorithm, and the results indicate that the suggested algorithm is sufficiently fast and accurate to be used in hematological analysis.

Multicore platforms are being increasingly adopted in Cyber -Physical Systems (CPS) due to their advantages over single-core processors, such as raw computing power and energy efficiency. Typically, multicore platforms use a shared system bus that connects the cores to the memory hierarchy (including caches and main memory). However, such hierarchy causes tasks running on different cores to compete for access to the shared system bus whenever data reads or writes need to be made. Such competition is problematic as it may cause variations in the execution time of tasks in a non-deterministic way. This paper presents a partitioned scheduling based approach that allows one to derive bus contention-aware worst-case response-time of tasks that follow the 3-phase task model. Experiments on synthetic task sets were performed to evaluate the effectiveness of the proposed analysis in comparison to a state-of-the-art approach. The experimental results reveal an increase of up to 34 percentage points of schedulable task sets in comparison to the compared approach.

Monocytes undergo phenotypic and functional changes in response to inflammatory cues, but the molecular signals that drive different monocyte states remain largely undefined. We show that monocytes acquire macrophage markers upon glomerulonephritis and may be derived from CCR2+CX3CR1+ double-positive monocytes, which are preferentially recruited, dwell within glomerular capillaries, and acquire proinflammatory characteristics in the nephritic kidney. Mechanistically, the transition to immature macrophages begins within the vasculature and relies on CCR2 in circulating cells and TNFR2 in parenchymal cells, findings that are recapitulated in vitro with monocytes cocultured with TNF-TNFR2–activated endothelial cells generating CCR2 ligands. Single-cell RNA sequencing of cocultures defines a CCR2-dependent monocyte differentiation path associated with the acquisition of immune effector functions and generation of CCR2 ligands. Immature macrophages are detected in the urine of lupus nephritis patients, and their frequency correlates with clinical disease. In conclusion, CCR2-dependent functional specialization of monocytes into macrophages begins within the TNF-TNFR2–activated vasculature and may establish a CCR2-based autocrine, feed-forward loop that amplifies renal inflammation.

The Internet is a vast collection of documents that are constantly evolving. Most of the data on the Internet is available through structured or semi-structured documents. XML is one of the semi-structured data exchange format used over the web. Therefore, understanding and detecting the changes occurring in XML documents becomes crucial. Due to the tree-structured and self-determined nature of the XML document, many change detection algorithms have been proposed. Most of these algorithms are based on comparing the entire XML trees of two versions of XML documents for identifying and locating the changes in them. We proposed an algorithm in this paper that uses the multiple digest scheme that helps in reducing the search space of locating the changes in the XML document. The approach used in this paper does not create any extra computation overhead for the processing of XML document which is justified by the results obtained.

Multicore platforms are being increasingly adopted in Cyber-Physical Systems (CPS) due to their advantages over single-core processors, such as raw computing power and energy efficiency. Typically, multicore platforms use a shared system bus that connects the cores to the memory hierarchy (including caches and main memory). However, such hierarchy causes tasks running on different cores to compete for access to the shared system bus whenever data reads or writes need to be made. Such competition is problematic as it may cause large variations in the execution time of tasks in a non-deterministic way. This paper presents an analysis that allows one to derive bus contention-aware worst-case response-time of tasks that follow the 3-phase task model executing under partitioned scheduling.

Pathogen-mediated balancing selection is regarded as a key driver of host immunogenetic diversity. A hallmark for balancing selection in humans is the heterozygote advantage at genes of the human leukocyte antigen (HLA), resulting in improved HIV-1 control. However, the actual mechanism of the observed heterozygote advantage is still elusive. HLA heterozygotes may present a broader array of antigenic viral peptides to immune cells, possibly resulting in a more efficient cytotoxic T-cell response. Alternatively, heterozygosity may simply increase the chance to carry the most protective HLA alleles, as individual HLA alleles are known to differ substantially in their association with HIV-1 control. Here, we used data from 6,311 HIV-1-infected individuals to explore the relative contribution of quantitative and qualitative aspects of peptide presentation in HLA heterozygote advantage against HIV. Screening the entire HIV-1 proteome, we observed that heterozygous individuals exhibited a broader array of HIV-1 peptides presented by their HLA class I alleles. In addition, viral load was negatively correlated with the breadth of the HIV-1 peptide repertoire bound by an individual’s HLA variants, particularly at HLA-B. This suggests that heterozygote advantage at HLA-B is at least in part mediated by quantitative peptide presentation. We also observed higher HIV-1 sequence diversity among HLA-B heterozygous individuals, suggesting stronger evolutionary pressure from HLA heterozygosity. However, HLA heterozygotes were also more likely to carry certain HLA alleles, including the highly protective HLA-B*57:01 variant, indicating that HLA heterozygote advantage ultimately results from a combination of quantitative and qualitative effects in antigen presentation.

We have already seen applications of nature-inspired algorithms to a wide variety of optimization problems. This chapter discusses another field of application which has not quite been explored to great depths yet. The problem of feature selection is approached by employing the bat algorithm on a medical dataset of white blood cells (WBCs). Feature selection, from a bird's eye view, is choosing an optimal subset of features from all features such that it does not hinder the classification accuracy. Since the differential count of WBCs is a key aspect for medical diagnostics and analysis, feature selection gives the advantage of faster processing and computing. The proposed methodology selects 11 features out of 35 features and has an accuracy of 97.69%. The chapter concludes with a detailed comparison with other recent nature-inspired algorithms, including the optimized crow search algorithm and the optimized cuttlefish algorithm.

Nature-inspired algorithms focus on many real-life applications, majority of which address different types of optimisation problems at a basic level. Feature selection, a type of optimisation problem, is an extremely important aspect of machine learning. This paper proposes an ensemble algorithm for feature selection using four recently developed evolutionary algorithms which are OCSA, OCFA, OBBA and MGWO. A ensemble set is created by combining the reduced feature set(s) obtained from the above-mentioned algorithms. The ensemble set so obtained represents a subset of features that are more robust and stable in nature. Ensemble creates a better composite global model by integrating various “differently biased” classifiers and thus reduces variance error by ensuring diverse “biasing”. The performance of this approach is validated using four classifiers, Decision Tree, Logistic Regression, K-nearest neighbours (KNN) and Random Forest. The application of the proposed method has been demonstrated using ten publicly available datasets. The suggested method shows promising results by either reducing the number of features with not much loss of accuracy or by including more relevant features and thereby increasing accuracy of predictions. Theoretical and empirical results presented in this paper validate the hypothesis that this method can help in finding a better feature subset.

Introduction Child abuse and neglect (CAN) is a significant global problem with a serious impact on the victims throughout their lives. Dentists have the unique opportunity to address this problem. However, reporting such cases has become a sensitive issue due to the uncertainty of the diagnosis. The authors are testing the knowledge of the dentists toward CAN and also trying to question the efforts of the educational institutions to improve this knowledge for the better future of the younger generation. Materials and methods Questionnaire data were distributed to 1,106 members regarding their knowledge, professional responsibilities, and behavior concerning child abuse. Results There were 762 responses to the questionnaire, yielding a response rate of 68.9%. Although dentists consider themselves able to identify suspicious cases, only a small percentage of the participants correctly identified all signs of abuse and 76.8% knew the indicators of child abuse. Most of them were willing to get involved in detecting a case and about 90% believed that it is their ethical duty to report child abuse. Only 7.2% suspected an abuse case in the past. The numbers indicate a lack of awareness about CAN in these participants. No differences were observed between sexes, year of graduation, types of license, frequency at which children were treated, and formal training already received. Conclusion A large proportion of child physical abuse cases go undocumented and unreported. The data showed that not all dental care providers and students were prepared to fulfill their legal and professional responsibilities in these situations. Clinical significance There should be modifications in the dental school curriculum focusing on educational experiences regarding child abuse to strengthen their capability to care and protect children. How to cite this article Malpani S, Arora J, Diwaker G, Kaleka PK, Parey A, Bontala P. Child Abuse and Neglect: Do We know enough? A Cross-sectional Study of Knowledge, Attitude, and Behavior of Dentists regarding Child Abuse and Neglect in Pune, India. J Contemp Dent Pract 2017;18(2):162-169.

In this paper, we propose the novel concept of manifesting the Choice Blindness paradigm in real-life scenarios through immersive Virtual Reality (VR). We designed a VR application wherein the participants encountered two-alternative choices regarding implicit racial bias. Our observations show that 92% of subjects failed to notice a mismatch in their choices, while 75% exhibited choice blindness, hence indicating a healthy scope for exploring choice blindness through virtual reality.

Given a Boolean formula F(X,Y), where X is a vector of outputs and Y is a vector of inputs, the Boolean functional synthesis problem requires us to compute a Skolem function vector G(Y)for X such that F(G(Y),Y) holds whenever \exists X F(X,Y) holds. In this paper, we investigate the relation between the representation of the specification F(X,Y) and the complexity of synthesis. We introduce a new normal form for Boolean formulas, called SynNNF, that guarantees polynomial-time synthesis and also polynomial-time existential quantification for some order of quantification of variables. We show that several normal forms studied in the knowledge compilation literature are subsumed by SynNNF, although SynNNFcan be super-polynomially more succinct than them. Motivated by these results, we propose an algorithm to convert a specification in CNF to SynNNF, with the intent of solving the Boolean functional synthesis problem. Experiments with a prototype implementation show that this approach solves several benchmarks beyond the reach of state-of-the-art tools., Full version of conference paper accepted at FMCAD 2019

We address the verification of concurrent programs running under the release-acquire (RA) semantics. We show that the reachability problem is undecidable even in the case where the input program is finite-state. Given this undecidability, we follow the spirit of the work on context-bounded analysis for detecting bugs in programs under the classical SC model, and propose an under-approximate reachability analysis for the case of RA. To this end, we propose a novel notion, called view-switching, and provide a code-to-code translation from an input program under RA to a program under SC. This leads to a reduction, in polynomial time, of the bounded view-switching reachability problem under RA to the bounded context-switching problem under SC. We have implemented a prototype tool VBMC and tested it on a set of benchmarks, demonstrating that many bugs in programs can be found using a small number of view switches.

Jewelry weaves into our everyday lives as no other wearable does. It comes in many wearable forms, is fashionable, and can adorn any part of the body. In this paper, through an exploratory, Research through Design (RtD) process, we tap into this vast potential space of input interaction that jewelry can enable. We do so by first identifying a small set of fundamental structural elements --- called Jewelements --- that any jewelry is composed of, and then defining their properties that enable the interaction. We leverage this synthesis along with observational data and literature to formulate a design space of jewelry-enabled input techniques. This work encapsulates both the extensions of common existing input methods (e.g., touch) as well as new ones inspired by jewelry. Furthermore, we discuss our prototypical sensor-based implementations. Through this work, we invite the community to engage in the conversation on how jewelry as a material can help shape wearable-based input.

Understanding how genetic regulatory variation affects gene expression in different T cell states is essential to deciphering autoimmunity. We conducted a high-resolution RNA-seq time course analysis of stimulated memory CD4+T cells from 24 healthy individuals. We identified 186 genes with dynamic allele-specific expression, where the balance of alleles changes over time. These genes were four fold enriched in autoimmune loci. We found pervasive dynamic regulatory effects within six HLA genes, particularly for a major autoimmune risk gene,HLA-DQB1. EachHLA-DQB1allele had one of three distinct transcriptional regulatory programs. Using CRISPR/Cas9 genomic editing we demonstrated that a single nucleotide variant at the promoter is causal for T cell-specific control ofHLA-DQB1expression. Our study in CD4+T cells shows that genetic variation incisregulatory elements may affect gene expression in a lymphocyte activation status-dependent manner contributing to the inter-individual complexity of immune responses.

Individual differences in HIV-1 control and progression to AIDS have been pinpointed to genetic variation in the HLA, coding for antigen-presenting molecules. However, our understanding of the corresponding antigens is still incomplete. Here we developed an approach that combines HLA genotypes and viral load data of HIV-infected individuals to screen the entire HIV-1 proteome for disease-relevant peptides. Our PepWAS approach identified a limited manageable core set of peptides, accounting for the entire variation in viral load previously associated with genetic variation in the HLA. This core set of disease-relevant antigens thus provides a functional link between HLA genetic variation and HIV-1 control, confirming several known antigens, but also prioritizing previously undescribed antigens as potential therapeutic targets.Genetic variation in the peptide-binding groove of the highly polymorphic HLA class I molecules has repeatedly been associated with HIV-1 control and progression to AIDS, accounting for up to 12% of the variation in HIV-1 set point viral load (spVL). This suggests a key role in disease control for HLA presentation of HIV-1 epitopes to cytotoxic T cells. However, a comprehensive understanding of the relevant HLA-bound HIV epitopes is still elusive. Here we describe a peptidome-wide association study (PepWAS) approach that integrates HLA genotypes and spVL data from 6,311 HIV-infected patients to interrogate the entire HIV-1 proteome (3,252 unique peptides) for disease-relevant peptides. This PepWAS approach predicts a core set of epitopes associated with spVL, including known epitopes but also several previously uncharacterized disease-relevant peptides. More important, each patient presents only a small subset of these predicted core epitopes through their individual HLA-A and HLA-B variants. Eventually, the individual differences in these patient-specific epitope repertoires account for the variation in spVL that was previously associated with HLA genetic variation. PepWAS thus enables a comprehensive functional interpretation of the robust but little-understood association between HLA and HIV-1 control, prioritizing a short list of disease-associated epitopes for the development of targeted therapy.

Sudden biotic pressures, such as those from novel diseases and pathogens, require populations to respond rapidly or face potential extinction. How this response process takes place remains poorly understood, particularly in natural environments. In this study we take advantage of unique decade-long data sets of two wild honey bee (Apis mellifera) populations in the United States to reconstruct the evolution of tolerance to a novel parasite, the ectoparasitic mite Varroa destructor. Upon the arrival of Varroa, the two geographically isolated populations simultaneously suffered massive Varroa-induced mortality, but stabilized within two years. Here we sequenced and phased genomes of 465 bees sampled from both populations annually over the decade that spanned Varroa's arrival. Remarkably, we found that genetic changes were strongly correlated between the populations, suggesting parallel selective responses to Varroa parasitization. The arrival of Varroa was also correlated with an influx of genes of African origin into both populations, though surprisingly it did not substantially contribute to the overall similarity of the evolutionary response between them. Genes involved in metabolic, protein processing and developmental pathways were under particularly strong selection. It is possible that interactions among highly connected gene groups in these pathways may help channelize selective responses to novel parasites, causing completely unrelated populations to exhibit parallel evolutionary trajectories when faced with the same biotic pressure. Our analyses illustrate that ecologically relevant traits emerge from highly polygenic selection involving thousands of genes contributing to complex patterns of evolutionary change.

This paper presents an IoT-enabled server device which is capable of authenticating a person by fingerprint recognition and grant access to the client application for making the attendance logging possible with the increased level of security. The ability of the device is to provide precise matching of fingerprints increases the possibility of error-free attendance logging. The impact of such approach is to provide the easier use of biometric attendance system in classrooms and offices with the Wi-Fi coverage. For security purpose, the client application provides the password to the device for protection from unauthorized access.

In this paper, an IoT-based smart home system is designed which consists of a number of subsystems required for a smart home. These subsystems are critical parameters monitoring with alert, home security systems, energy saving system, electrical appliance control and monitoring system. A detailed study has been done so as to find the appropriate hardware and software resources to fulfil the requirements of the smart home. Safety is one of the important concerns for IoT application which has been addressed using secure cloud platform which provides the authentication using login ID and password technique. A simple, efficient and robust architecture is proposed in the paper. The system is also implemented on the hardware set-up. The system is designed in such a way that consumes minimum power so simple sleep and wake up energy efficient algorithm is implemented along with ultra-low power MCU platform like MSP430.

systems are very inflexible towards modification of already existing functionalities such as security, dynamic re- configurability, robustness etc. In such functionalities if need arises for any enhancements then it affects large fractions of the code. Thus results in difficult to implement. Such functional enhancements in any component of the system that affect large fractions of the program code, are often called crosscutting concerns. Such cross-cutting concerns can be solved by the new emerging extension to object oriented paradigm i.e. Aspect Oriented Programming (AOP). The main idea in AOP is the programmer's ability to affect the execution of core code by writing aspects. Aspects are pieces of code that are run before, or after core function for which aspect is written. The quantification part means that programmer can define points in the main program. Aspects should affect the main program by using some definition language that is usually a declarative one. The obliviousness means that the affected code does not need to know anything about aspects.

This paper presents a deep learning based approach to extract product comparison information out of user reviews on various e-commerce websites. Any comparative product review has three major entities of information: the names of the products being compared, the user opinion (predicate) and the feature or aspect under comparison. All these informing entities are dependent on each other and bound by the rules of the language, in the review. We observe that their inter-dependencies can be captured well using LSTMs. We evaluate our system on existing manually labeled datasets and observe out-performance over the existing Semantic Role Labeling (SRL) framework popular for this task.

In the present scenario, it is essential to have an automatic billing system for shopping malls, supermarket and other wholesale & retail stores. Numerous billing systems like barcode scanning mechanism-based systems or tag-based systems are available in the market. It is important to replace such existing system with better and robust systems so hereby we proposed “Smart Goods Billing Management and Payment System for Shopping Malls”. In this system, the basic fundamental is barcode scanning for products, but we replace the conventional barcode scanner for faster and better results. In our prototype, the android phone is being used as a barcode scanner for simple, better and portable barcode scanner. This scanner is connected wirelessly to MCU via Bluetooth module. MCU is also connected to PC/Laptop for creating the database of all customers, their products, and bills. This database also tracks the total sale and number of goods sold per day. In addition, RFID technology is implemented in this system for payment through card-based system. Simulation and hardware-based results are proposed in this paper.

Whole genome duplications (WGD) have now been firmly established in all major eukaryotic kingdoms. In particular, all vertebrates descend from two rounds of WGDs, that occurred in their jawless ancestor some 500 MY ago. Paralogs retained from WGD, also coined ‘ohnologs’ after Susumu Ohno, have been shown to be typically associated with development, signaling and gene regulation. Ohnologs, which amount to about 20 to 35% of genes in the human genome, have also been shown to be prone to dominant deleterious mutations and frequently implicated in cancer and genetic diseases. Hence, identifying ohnologs is central to better understand the evolution of vertebrates and their susceptibility to genetic diseases. Early computational analyses to identify vertebrate ohnologs relied on content-based synteny comparisons between the human genome and a single invertebrate outgroup genome or within the human genome itself. These approaches are thus limited by lineage specific rearrangements in individual genomes. We report, in this study, the identification of vertebrate ohnologs based on the quantitative assessment and integration of synteny conservation between six amniote vertebrates and six invertebrate outgroups. Such a synteny comparison across multiple genomes is shown to enhance the statistical power of ohnolog identification in vertebrates compared to earlier approaches, by overcoming lineage specific genome rearrangements. Ohnolog gene families can be browsed and downloaded for three statistical confidence levels or recompiled for specific, user-defined, significance criteria at http://ohnologs.curie.fr/. In the light of the importance of WGD on the genetic makeup of vertebrates, our analysis provides a useful resource for researchers interested in gaining further insights on vertebrate evolution and genetic diseases., Author Summary Duplication of existing genes with subsequent divergence of duplicated copies has long been recognized as the primary source of genomic innovation. Gene duplication is thus at the root of the evolution and complexification of living organisms. However, gene duplicates have been retained differently depending on the genomic scale of their duplication and their implication in genetic diseases. The scale of genomic duplication spans from small scale segmental duplication to whole genome duplication (WGD), which corresponds to a dramatic doubling event of a species genome. In particular, all vertebrates, including human, descend from two rounds of WGDs, which occurred in their jawless ancestor some 500 MY ago. Interestingly, WGD gene duplicates, also called ‘ohnologs’, have be shown to be more frequently implicated in genetic diseases in human. Hence, identifying ohnologs appears central to better understand the evolution of vertebrates and their susceptibility to genetic diseases. In this study, we present a computational approach to predict ohnologs in six vertebrate genomes, including human, based on the comparison of their local gene content (i.e. synteny) with the genomes of six invertebrate outgroups. We show that such synteny comparisons across multiple genomes enhance the statistical power of ohnolog identification compared to earlier approaches.

Understanding genetic changes caused by novel pathogens and parasites can reveal mechanisms of adaptation and genetic robustness. Using whole-genome sequencing of museum and modern specimens, we describe the genomic changes in a wild population of honey bees in North America following the introduction of the ectoparasitic mite, Varroa destructor. Even though colony density in the study population is the same today as in the past, a major loss of haplotypic diversity occurred, indicative of a drastic mitochondrial bottleneck, caused by massive colony mortality. In contrast, nuclear genetic diversity did not change, though hundreds of genes show signs of selection. The genetic diversity within each bee colony, particularly as a consequence of polyandry by queens, may enable preservation of genetic diversity even during population bottlenecks. These findings suggest that genetically diverse honey bee populations can recover from introduced diseases by evolving rapid tolerance, while maintaining much of the standing genetic variation., Introduction of pathogens can cause colony collapse in honey bees. Here, the authors use museum specimens to show widespread colony mortality but unaffected nuclear genetic diversity in a wild population of honey bees in North America following the introduction of ectoparasitic Varroa mites.

Electrical measurement of quantities plays a crucial role in the real world. Measuring voltage is one of the main tasks for developing large number of applications. This paper is focused on design and development of digital voltmeter using different techniques. It has been shown how to develop a Digital Voltmeter (DVM) from simplest type to professional digital voltmeter. Different types of techniques are adopted for making a voltmeter and the result is compared for testing the accuracy. The simulation of all techniques is done on Proteus ISIS 7.10 and implemented on the hardware. The techniques used for developing the digital voltmeter is comparator based DVM, 8051 based DVM and PIC based DVM. The accuracy of DVMs is shown by simulation in Proteus ISIS and through hardware implementation.

The role of wireless sensor networks (WSNs) is essential to the present scenario. Numerous independent sensors exist in a WSN that cover the entire terrain and have the task of inspecting a specific phenomenon. For this reason, the sensors must work with minimal constraints, such as least energy consumption and data memory. To achieve the objective, many techniques are applied, one of which is clustering, where nodes are congregated into clusters and a head node is elected. Suitable cluster head selection is crucial for improving the energy management of a sensor network. In this paper, a technique based on a dominance based rough set is introduced for cluster head selection on the basis of attributes that have the capacity to augment the sustainability and lifetime of the sensor network. This method is far superior to the probabilistic approach of cluster head selection in a WSN.

This paper presents a prototype for the monitoring of Heartbeat rate. A Heart Beat (HB) sensor is being developed for acquainting the input signals using Light Dependent Resistance (LDR) and Light Emitting Diode (LED). It senses the heartbeat of a person and converts it in the form of electrical signals and pulses. The signals are amplified using a signal conditioning circuit and processed by a controller. The frequency of the signal depends on the heartbeat rate, this lays down the basic principle of the HB measuring system. The user needs to put his/her finger in the HB sensor for acquiring the input signals. Although number of methods has been proposed and implemented in this domain yet the proposed system in this text provides a simpler and robust method for measuring the heart rate. The proposed system is being implemented on the hardware and also simulated in Proteus ISIS 7.10 to prove its effectiveness. The proposed model is much more precise, straightforward and cheaper than other heartbeat rate measuring systems. This work has tried to make an easy and stout system for the monitoring of heart beat.