Survey Paper on Emotion Recognition

Facial expressions give important information about emotions of a person. Understanding facial expressions accurately is one of the challenging tasks for interpersonal relationships. Automatic emotion detection using facial expressions recognition is now a main area of interest within various fields such as computer science, medicine, and psychology. HCI research communities also use automated facial expression recognition system for better results. Various feature extraction techniques have been developed for recognition of expressions from static images as well as real time videos. This paper provides a review of research work carried out and published in the field of facial expression recognition and various techniques used for facial expression recognition

Design of ECG Acquisition System and Noise Removal Using MSP 430 Controller

In today’s world, electrocardiography (ECG) is very important to detect heart related problems. Many technologies have been developed for medical monitoring. In this study, we are developing monitoring system using 3 leads. This system takes input as an analog signal processes and conditions it and converts it into digital signal. After converting, it processes the digital signal with MSP430 controller

NIST Interlaboratory Study on Glycosylation Analysis of Monoclonal Antibodies: Comparison of Results from Diverse Analytical Methods

Glycosylation is a topic of intense current interest in the development of biopharmaceuticals because it is related to drug safety and efficacy. This work describes results of an interlaboratory study on the glycosylation of the Primary Sample (PS) of NISTmAb, a monoclonal antibody reference material. Seventy-six laboratories from industry, university, research, government, and hospital sectors in Europe, North America, Asia, and Australia submit- Avenue, Silver Spring, Maryland 20993; 22Glycoscience Research Laboratory, Genos, Borongajska cesta 83h, 10 000 Zagreb, Croatia; 23Faculty of Pharmacy and Biochemistry, University of Zagreb, A. Kovacˇ ic´ a 1, 10 000 Zagreb, Croatia; 24Department of Chemistry, Georgia State University, 100 Piedmont Avenue, Atlanta, Georgia 30303; 25glyXera GmbH, Brenneckestrasse 20 * ZENIT / 39120 Magdeburg, Germany; 26Health Products and Foods Branch, Health Canada, AL 2201E, 251 Sir Frederick Banting Driveway, Ottawa, Ontario, K1A 0K9 Canada; 27Graduate School of Advanced Sciences of Matter, Hiroshima University, 1-3-1 Kagamiyama Higashi-Hiroshima 739–8530 Japan; 28ImmunoGen, 830 Winter Street, Waltham, Massachusetts 02451; 29Department of Medical Physiology, Jagiellonian University Medical College, ul. Michalowskiego 12, 31–126 Krakow, Poland; 30Department of Pathology, Johns Hopkins University, 400 N. Broadway Street Baltimore, Maryland 21287; 31Mass Spec Core Facility, KBI Biopharma, 1101 Hamlin Road Durham, North Carolina 27704; 32Division of Mass Spectrometry, Korea Basic Science Institute, 162 YeonGuDanji-Ro, Ochang-eup, Cheongwon-gu, Cheongju Chungbuk, 363–883 Korea (South); 33Advanced Therapy Products Research Division, Korea National Institute of Food and Drug Safety, 187 Osongsaengmyeong 2-ro Osong-eup, Heungdeok-gu, Cheongju-si, Chungcheongbuk-do, 363–700, Korea (South); 34Center for Proteomics and Metabolomics, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands; 35Ludger Limited, Culham Science Centre, Abingdon, Oxfordshire, OX14 3EB, United Kingdom; 36Biomolecular Discovery and Design Research Centre and ARC Centre of Excellence for Nanoscale BioPhotonics (CNBP), Macquarie University, North Ryde, Australia; 37Proteomics, Central European Institute for Technology, Masaryk University, Kamenice 5, A26, 625 00 BRNO, Czech Republic; 38Max Planck Institute for Dynamics of Complex Technical Systems, Sandtorstrasse 1, 39106 Magdeburg, Germany; 39Department of Biomolecular Sciences, Max Planck Institute of Colloids and Interfaces, 14424 Potsdam, Germany; 40AstraZeneca, Granta Park, Cambridgeshire, CB21 6GH United Kingdom; 41Merck, 2015 Galloping Hill Rd, Kenilworth, New Jersey 07033; 42Analytical R&D, MilliporeSigma, 2909 Laclede Ave. St. Louis, Missouri 63103; 43MS Bioworks, LLC, 3950 Varsity Drive Ann Arbor, Michigan 48108; 44MSD, Molenstraat 110, 5342 CC Oss, The Netherlands; 45Exploratory Research Center on Life and Living Systems (ExCELLS), National Institutes of Natural Sciences, 5–1 Higashiyama, Myodaiji, Okazaki 444–8787 Japan; 46Graduate School of Pharmaceutical Sciences, Nagoya City University, 3–1 Tanabe-dori, Mizuhoku, Nagoya 467–8603 Japan; 47Medical & Biological Laboratories Co., Ltd, 2-22-8 Chikusa, Chikusa-ku, Nagoya 464–0858 Japan; 48National Institute for Biological Standards and Control, Blanche Lane, South Mimms, Potters Bar, Hertfordshire EN6 3QG United Kingdom; 49Division of Biological Chemistry & Biologicals, National Institute of Health Sciences, 1-18-1 Kamiyoga, Setagaya-ku, Tokyo 158–8501 Japan; 50New England Biolabs, Inc., 240 County Road, Ipswich, Massachusetts 01938; 51New York University, 100 Washington Square East New York City, New York 10003; 52Target Discovery Institute, Nuffield Department of Medicine, University of Oxford, Roosevelt Drive, Oxford, OX3 7FZ, United Kingdom; 53GlycoScience Group, The National Institute for Bioprocessing Research and Training, Fosters Avenue, Mount Merrion, Blackrock, Co. Dublin, Ireland; 54Department of Chemistry, North Carolina State University, 2620 Yarborough Drive Raleigh, North Carolina 27695; 55Pantheon, 201 College Road East Princeton, New Jersey 08540; 56Pfizer Inc., 1 Burtt Road Andover, Massachusetts 01810; 57Proteodynamics, ZI La Varenne 20–22 rue Henri et Gilberte Goudier 63200 RIOM, France; 58ProZyme, Inc., 3832 Bay Center Place Hayward, California 94545; 59Koichi Tanaka Mass Spectrometry Research Laboratory, Shimadzu Corporation, 1 Nishinokyo Kuwabara-cho Nakagyo-ku, Kyoto, 604 8511 Japan; 60Children’s GMP LLC, St. Jude Children’s Research Hospital, 262 Danny Thomas Place Memphis, Tennessee 38105; 61Sumitomo Bakelite Co., Ltd., 1–5 Muromati 1-Chome, Nishiku, Kobe, 651–2241 Japan; 62Synthon Biopharmaceuticals, Microweg 22 P.O. Box 7071, 6503 GN Nijmegen, The Netherlands; 63Takeda Pharmaceuticals International Co., 40 Landsdowne Street Cambridge, Massachusetts 02139; 64Department of Chemistry and Biochemistry, Texas Tech University, 2500 Broadway, Lubbock, Texas 79409; 65Thermo Fisher Scientific, 1214 Oakmead Parkway Sunnyvale, California 94085; 66United States Pharmacopeia India Pvt. Ltd. IKP Knowledge Park, Genome Valley, Shamirpet, Turkapally Village, Medchal District, Hyderabad 500 101 Telangana, India; 67Alberta Glycomics Centre, University of Alberta, Edmonton, Alberta T6G 2G2 Canada; 68Department of Chemistry, University of Alberta, Edmonton, Alberta T6G 2G2 Canada; 69Department of Chemistry, University of California, One Shields Ave, Davis, California 95616; 70Horva´ th Csaba Memorial Laboratory for Bioseparation Sciences, Research Center for Molecular Medicine, Doctoral School of Molecular Medicine, Faculty of Medicine, University of Debrecen, Debrecen, Egyetem ter 1, Hungary; 71Translational Glycomics Research Group, Research Institute of Biomolecular and Chemical Engineering, University of Pannonia, Veszprem, Egyetem ut 10, Hungary; 72Delaware Biotechnology Institute, University of Delaware, 15 Innovation Way Newark, Delaware 19711; 73Proteomics Core Facility, University of Gothenburg, Medicinaregatan 1G SE 41390 Gothenburg, Sweden; 74Department of Medical Biochemistry and Cell Biology, University of Gothenburg, Institute of Biomedicine, Sahlgrenska Academy, Medicinaregatan 9A, Box 440, 405 30, Gothenburg, Sweden; 75Department of Clinical Chemistry and Transfusion Medicine, Sahlgrenska Academy at the University of Gothenburg, Bruna Straket 16, 41345 Gothenburg, Sweden; 76Department of Chemistry, University of Hamburg, Martin Luther King Pl. 6 20146 Hamburg, Germany; 77Department of Chemistry, University of Manitoba, 144 Dysart Road, Winnipeg, Manitoba, Canada R3T 2N2; 78Laboratory of Mass Spectrometry of Interactions and Systems, University of Strasbourg, UMR Unistra-CNRS 7140, France; 79Natural and Medical Sciences Institute, University of Tu¨ bingen, Markwiesenstrae 55, 72770 Reutlingen, Germany; 80Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Padualaan 8, 3584 CH Utrecht, The Netherlands; 81Division of Bioanalytical Chemistry, Amsterdam Institute for Molecules, Medicines and Systems, Vrije Universiteit Amsterdam, de Boelelaan 1085, 1081 HV Amsterdam, The Netherlands; 82Department of Chemistry, Waters Corporation, 34 Maple Street Milford, Massachusetts 01757; 83Zoetis, 333 Portage St. Kalamazoo, Michigan 49007 Author’s Choice—Final version open access under the terms of the Creative Commons CC-BY license. Received July 24, 2019, and in revised form, August 26, 2019 Published, MCP Papers in Press, October 7, 2019, DOI 10.1074/mcp.RA119.001677 ER: NISTmAb Glycosylation Interlaboratory Study 12 Molecular & Cellular Proteomics 19.1 Downloaded from https://www.mcponline.org by guest on January 20, 2020 ted a total of 103 reports on glycan distributions. The principal objective of this study was to report and compare results for the full range of analytical methods presently used in the glycosylation analysis of mAbs. Therefore, participation was unrestricted, with laboratories choosing their own measurement techniques. Protein glycosylation was determined in various ways, including at the level of intact mAb, protein fragments, glycopeptides, or released glycans, using a wide variety of methods for derivatization, separation, identification, and quantification. Consequently, the diversity of results was enormous, with the number of glycan compositions identified by each laboratory ranging from 4 to 48. In total, one hundred sixteen glycan compositions were reported, of which 57 compositions could be assigned consensus abundance values. These consensus medians provide communityderived values for NISTmAb PS. Agreement with the consensus medians did not depend on the specific method or laboratory type. The study provides a view of the current state-of-the-art for biologic glycosylation measurement and suggests a clear need for harmonization of glycosylation analysis methods. Molecular & Cellular Proteomics 19: 11–30, 2020. DOI: 10.1074/mcp.RA119.001677.L

ONTOLOGY EXTRACTION FOR AGRICULTURE DOMAIN IN MARATHI LANGUAGE USING NLP TECHNIQUES

Ontology is defined as shared specification of conceptual vocabulary used for formulating knowledge-level theories about a domain of discourse. Dataset is created by manually collecting information about different diseases related to crops. Ontology modeling is used for knowledge representation of various domains. India is an agricultural based economic country. Majority of Indian population relies on farming but the technologies are sparsely used for the aid of farmers. Ontology based modeling for agricultural knowledge can change this scenario. The farmers can understand it easily in their native language. We proposed a system which will model and extract knowledge in Marathi language. In this paper, we review various existing agriculture ontology’s along with some of Natural Language Processing (NLP) models. Model ontology for agriculture domain system aims to retrieve relevant answers to the farmer’s query. We explored Rule-Based and Conditional Random Fields based models for Ontology extraction. The extraction methods and preprocessing phases of proposed system is discussed

Comparison of effect of ethylenediaminetetraacetic acid solution and ethylenediaminetetraacetic acid paste on canal transportation using cone beam computed tomography: An in vitro study

Aims: The aim of the present study was to compare the effect of saline, ethylenediaminetetraacetic acid (EDTA) 17% solution and EDTA paste on root canal transportation. Subjects and Methods: Moderately curved mesiobuccal roots of 24 maxillary molars were standardized in length and randomized into one control and two experimental groups. All teeth were scanned by cone beam computed tomography (CBCT) to determine the root canal shape and measure the parameters required for comparison before instrumentation. The canals were instrumented with 0.06 taper rotary files to size #25. All groups were irrigated with saline. Group 1 was prepared with RC-Prep (Premier Dental, Philadelphia, PA, USA) and in Group 2, EDTA 17% solution (Pulpdent Corp., Watertown, MA, USA) was used. After preparation, postinstrumentation scan was performed. Pre- and post-instrumentation images were obtained at three levels, 3 mm from the apical end of the root (apical level) and 3 mm below the orifice from the coronal level (15 mm from the apex) and the mid-root level (8 mm from the apex) were compared using CBCT software. The amount of canal transportation was assessed. Statistical Analysis Used: The data were analyzed with one-way analysis of variance (α = 0.05) and the Tukey post hoc test. Results: Less canal transportation was observed in experimental groups than the control group. Group 1 showed significantly less canal transportation than Group 2 and control group. Conclusions: EDTA preparation had a significant effect on canal transportation

Evaluation of salivary nitric oxide levels in caries-free children and children with early childhood caries: An in vivo study

Background and Objectives: Early childhood caries (ECC) is one of the most prevalent diseases of childhood. Pediatric dentists must make conscious efforts to prevent this condition for optimal oral health. Normal salivary function is considered critical for the maintenance of a healthy oral cavity. Saliva provides an easily available, noninvasive medium for the diagnosis of wide range of diseases and clinical conditions. The objective of the present study was to estimate and compare salivary nitric oxide (NO) levels in caries-free children and children with ECC. Methodology: The children were divided into two groups. Group I comprised thirty caries-free children and Group II comprised thirty children with ECC. Saliva was collected by suction method. Griess reaction was used to estimate the NO levels. Unpaired t-test was used for comparing and evaluating the NO levels in both the groups. Results: Mean salivary Nitric Oxide level is significantly higher in caries free children as compared to that of children with early childhood caries (ECC). Interpretation and Conclusion: The present study clearly indicates a significant increase in salivary NO levels in caries-free children as compared to children with caries. This may be attributed to the antimicrobial action of NO

Hydrothermal synthesis of WO3 film on rough surface to analyze methanol gas at room temperature

In this paper, we synthesized WO _3 thick films on a rough and smooth glass substrate by hydrothermal method and then heated to a temperature of 400-degree Celcius. Characteristic techniques such as XRD and SEM analysis were sequenced to determine the crystallite size and grain composition of the finished samples, respectively. We have discussed the results of the Rietveld refinement made using MAUD to determine useful information regarding the atomic sites, mesh parameters, and micro-stresses in the sample. Subsequently, FTIR analysis has been performed to note the critical bond vibrations associated with the material. AFM studies have also been included to determine the pore sizes and understand the surface-level differences between WO _3 films on rough and smooth substrates. The room temperature gas sensing mechanism was then discussed in the presence of humidity with methanol, ethanol, and benzene along with most of the targeted gases with different selective parameters at atmospheric pressure. We have tried to develop a theory incorporating the anomalous observation for the methanol gas sensing experiment and explained the future scope of this work

A Model Linked to E. Coli Related to Electrostrictive Energy in Cancer Cell

The paper has focused on a new concept in respect of the status of oxidant/antioxidant in cancer cell following radiation therapy. And in this respect a model has been developed linked with an environment of E.Coli in which TrpRS II is induced after radiation damage. It is interesting to note that Electrostrictive energy is the input to the model the output of which is the oxidant/antioxidant ratio. This ratio is related to the status of Electrostrictive energy derived from capacitance relaxation phenomenon (US patent No. US Patent No. TK Basak 5691178, 1997) in cancer cell. The oxidant/antioxidant ratio is linked to Electrostrictive energy with increasing pH. This paper discusses about the status of phosphorylation and dephosphorylation after radiation therapy linked to E.Coli environment against the pH gradient is indicative for the treatment of cancer