407 research outputs found
Determining the consumer perception on perishable food wastage in Texas, United States
No full textCurrently, 9 million people die every year from hunger-related issues worldwide while one-third of the produced food is wasted. It is a global as well as a regional problem. Among the different states of the United States, one-eighth of the Texans are vulnerable to food insecurity. The changing demographics, driven by the recent population influx, have not only affected consumption and wastage pattern but have also influenced environmental, resource, and social concerns. Water scarcity and drought further exacerbate its impact. With agriculture being a crucial contributor to the Texas economy, food wastage disrupts the entire supply chain globally. To address this issue, this study aims to identify the current pattern of food wastage, factors affecting food wastage, and finally to propose sustainable solutions. Also, this study identifies the consumer food shopping behavior, perceptions, knowledge, and motivations of the consumers towards reducing this problem. To fulfill these objectives, an online questionnaire survey using Qualtrics was conducted. The stratified random sampling method was employed matching the diversity of Texas in terms of age, educational level, household income, and race. Multinomial logistic regression was used to find the factors affecting food wastage and binomial logistic regression was used to find the determinants of the consumers’ willingness to accept the proposed solution. MS Excel and STATA were used for data analysis. Among the different foods, fruits and vegetables were most wasted followed by homemade meals, packaged foods, milk, bread, and meat. The major cause of food waste was identified as a change in plan followed by buying too much/too little, lack of a plan, unforeseen schedule conflict, and dislike of leftovers. Multinomial logistic regression revealed that the number of family members, race, frequency of purchase, number of children, food handling training, income level, education level, favorable shopping behavior, knowledge score, and engagement in waste reduction strategies were the significant determinants of food wastage. Further, three solutions were proposed which include packaging bags near the restaurant table, sharing the leftovers through mobile applications, and incentives via discounts for making and adhering to the shopping list. Binomial logistic regression found that the number of family members, knowledge score, and preferred shopping behavior score were the predictors of willingness to accept these proposed solutions. These overall findings will help the future researchers by providing guidelines about the consumers behavior. The policymakers benefit from this study by knowing the resent scenario and implementing these solutions to mitigate the food waste problem.Agricultural Science
Computer vision methods for large-scale online clustering and quantitative dermatology
No full textIn modern computer vision applications where datasets are large and updates with new data may be ongoing, methods of online clustering are extremely important. Online clustering algorithms incrementally cluster the data points, use a fraction of the dataset memory, and update the clustering decisions when new data comes in. In this thesis we adapt a classic online clustering algorithm called Balanced Iterative Reducing and Clustering using Hierarchies (BIRCH) to incrementally cluster large datasets of features commonly used in computer vision, e.g., 840K color SIFT descriptors, 1.09 million color patches, 60K outlier corrupted grayscale patches, and 700K grayscale SIFT descriptors. We use the algorithm to cluster datasets consisting of non-convex clusters, e.g., Hopkins 155 3-D motion segmentation dataset. We call the adapted version modified-BIRCH (m-BIRCH). BIRCH was originally developed by the database management community. Modifications made in m-BIRCH enable data driven parameter selection and effectively handle varying density regions in the feature space. Data driven parameter selection automatically controls the level of coarseness of the data summarization. Effective handling of varying density regions is necessary to well represent the different density regions in the data summarization. Our implementation of the algorithm provides a useful clustering tool and is made publicly available. In the second part of the thesis, we present a micro-level feature based approach to register time-lapse skin images acquired over an extended period of time and multimodal skin images acquired in quick succession. Misregistration between the images makes it difficult to perform quantitative analysis and track the progression of skin disease. We demonstrate the utility of both types of registration, by employing the results for two quantitative dermatology tasks: 1) automatic detection of acne-like regions, and 2) separation of surface and subsurface reflection. Additionally, we have created a time-lapse video showing the registered time-lapse images, which clearly brings out the evolution of acne lesions with time.Ph. D.Includes bibliographical referencesby Siddharth K. Mada
An unstructured Tablulated Method for the computation of Thermo-physical fluid properties
No full textIn various propulsion and power systems, modeling of non-ideal fluid flows (fluids that depart from ideal gas behaviour), presents a great challenge. For example, in organic rankine cycle (ORC) turbines, where a part of the expansion process occurs close to the vapour saturation curve, the flow deviates highly from ideal behavior. A branch of fluid dynamics called the Non-ideal compressible fluid dynamics (NICFD) deals with the modeling and analysis of such non ideal fluid flows. As a consequence of the need for accurate thermo-physical property computation, various models have recently been developed for non ideal flows and a number of libraries are available to accurately predict the thermo-physical properties. However, the available thermodynamic libraries are often computationally costly since they require solving of complex equations of state (EoS) to obtain thermo-physical properties. When these libraries are coupled with existing simulation codes, (for example in computational fluid-dynamics), the simulation process is computationally inefficient.This thesis is an endeavor towards enhancing the computational efficiency of the process of thermodynamic property calculation with the use of the Look up table (LUT) approach.The LUT method aims at computing thermodynamic properties of a fluid with the help of array indexing operations applied on pre calculated or existing thermodynamic tables. These tables are initially obtained from a thermodynamic library FluidProp. A binary search algorithm helps in accurately locating the query point(s) on the thermodynamic domain. A data interpolation algorithm is then used to predict the thermodynamic properties of interest. The presented LUT method ensures inherently high accuracy with a very small computational cost, as demonstrated later in the thesis.To check the applicability of the LUT method, it is used to obtain the pressure variation across a control volume with subsonic flow conditions. As a second and a much larger application, the LUT tool is coupled with an in house MOC (Method of Characteristics) tool to design the geometry of a supersonic nozzle. A comprehensive analysis of this method is presented by comparing the accuracies and computational cost with the results from FluidProp. Both interpolation methods implemented in the proposed LUT method prove to be computationally efficient and accurate. The method is successfully applied to the MOC tool to design the geometry of the diverging section of a supersonic nozzle.Aerospace Engineerin
Human surfactant protein D alters oxidative stress and HMGA1 expression to induce p53 apoptotic pathway in eosinophil leukemic cell line
Get PDFThis article is made available through the Brunel Open Access Publishing Fund. Copyright: © 2013 Mahajan et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Surfactant protein D (SP-D), an innate immune molecule, has an indispensable role in host defense and regulation of
inflammation. Immune related functions regulated by SP-D include agglutination of pathogens, phagocytosis,
oxidative burst, antigen presentation, T lymphocyte proliferation, cytokine secretion, induction of apoptosis and
clearance of apoptotic cells. The present study unravels a novel ability of SP-D to reduce the viability of leukemic
cells (eosinophilic leukemic cell line, AML14.3D10; acute myeloid leukemia cell line, THP-1; acute lymphoid leukemia
cell lines, Jurkat, Raji; and human breast epithelial cell line, MCF-7), and explains the underlying mechanisms. SP-D
and a recombinant fragment of human SP-D (rhSP-D) induced G2/M phase cell cycle arrest, and dose and timedependent
apoptosis in the AML14.3D10 eosinophilic leukemia cell line. Levels of various apoptotic markers viz.
activated p53, cleaved caspase-9 and PARP, along with G2/M checkpoints (p21 and Tyr15 phosphorylation of cdc2)
showed significant increase in these cells. We further attempted to elucidate the underlying mechanisms of rhSP-D
induced apoptosis using proteomic analysis. This approach identified large scale molecular changes initiated by SPD
in a human cell for the first time. Among others, the proteomics analysis highlighted a decreased expression of
survival related proteins such as HMGA1, overexpression of proteins to protect the cells from oxidative burst, while a
drastic decrease in mitochondrial antioxidant defense system. rhSP-D mediated enhanced oxidative burst in
AML14.3D10 cells was confirmed, while antioxidant, N-acetyl-L-cysteine, abrogated the rhSP-D induced apoptosis.
The rhSP-D mediated reduced viability was specific to the cancer cell lines and viability of human PBMCs from
healthy controls was not affected. The study suggests involvement of SP-D in host’s immunosurveillance and
therapeutic potential of rhSP-D in the eosinophilic leukemia and cancers of other origins.Department of Biotechnology, Indi
Dataset of miRNA-disease relations extracted from textual data using transformer-based neural networks
No full textMadan S, Kühnel L, Frohlich H, Hofmann-Apitius M, Fluck J. Dataset of miRNA-disease relations extracted from textual data using transformer-based neural networks. Database : the journal of biological databases and curation. 2024;2024.MicroRNAs (miRNAs) play important roles in post-transcriptional processes and regulate major cellular functions. The abnormal regulation of expression of miRNAs has been linked to numerous human diseases such as respiratory diseases, cancer, and neurodegenerative diseases. Latest miRNA-disease associations are predominantly found in unstructured biomedical literature. Retrieving these associations manually can be cumbersome and time-consuming due to the continuously expanding number of publications. We propose a deep learning-based text mining approach that extracts normalized miRNA-disease associations from biomedical literature. To train the deep learning models, we build a new training corpus that is extended by distant supervision utilizing multiple external databases. A quantitative evaluation shows that the workflow achieves an area under receiver operator characteristic curve of 98% on a holdout test set for the detection of miRNA-disease associations. We demonstrate the applicability of the approach by extracting new miRNA-disease associations from biomedical literature (PubMed and PubMed Central). We have shown through quantitative analysis and evaluation on three different neurodegenerative diseases that our approach can effectively extract miRNA-disease associations not yet available in public databases. Database URL: https://zenodo.org/records/10523046. © The Author(s) 2024. Published by Oxford University Press
The Eccentric Connectivity Polynomial of some Graph Operations
Get PDFThe eccentric connectivity index of a graph G, ξ^C, was proposed
by Sharma, Goswami and Madan. It is defined as ξ^C(G) =
∑ u ∈ V(G) degG(u)εG(u), where degG(u) denotes the degree of the vertex x
in G and εG(u) = Max{d(u, x) | x ∈ V (G)}. The eccentric connectivity
polynomial is a polynomial version of this topological index. In this paper,
exact formulas for the eccentric connectivity polynomial of Cartesian
product, symmetric difference, disjunction and join of graphs are presented.* The work of this author was supported in part by a grant from IPM (No. 89050111)
Testimony by DMMR re: H.R. 644, Grand Canyon Watersheds Protection Act
Get PDFabstract: Testimony for The Subcommittee on National Parks, Forests and Public Lands of the Committee on Natural Resources presented against the withdrawal of the uranium-bearing lands around the Grand Canyon National Park.Open-file report (Arizona Department of Mines and Mineral Resources) ; 09-2
Impact of vesicular stomatitis virus M proteins on different cellular functions
Get PDFThis is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Three different matrix (M) proteins termed M1, M2 and M3 have been described in cells infected with vesicular stomatitis virus (VSV). Individual expression of VSV M proteins induces an evident cytopathic effect including cell rounding and detachment, in addition to a partial inhibition of cellular protein synthesis, likely mediated by an indirect mechanism. Analogous to viroporins, M1 promotes the budding of new virus particles; however, this process does not produce an increase in plasma membrane permeability. In contrast to M1, M2 and M3 neither interact with the cellular membrane nor promote the budding of double membrane vesicles at the cell surface. Nonetheless, all three species of M protein interfere with the transport of cellular mRNAs from the nucleus to the cytoplasm and also modulate the redistribution of the splicing factor. The present findings indicate that all three VSV M proteins share some activities that interfere with host cell functions.This study was supported by a DGICYT (Dirección General de Investigación Científica y Técnica). Ministerio de Economía y Competitividad, Spain grant (BFU2012-31861). The Institutional Grant awarded to the Centro de Biología Molecular “Severo Ochoa” (CSIC-UAM) by the Fundación Ramón Areces is acknowledged.Peer Reviewe
Scientometric Portrait of Homi Jehangir Bhabha: The Father of Indian Nuclear Research Programme
Get PDFQuantitative and qualitative analysis with graphic representation of the publication productivity of a scientist facilitates easy and clear perception about the work of a scientist. Bhabha’s scientific work spanned over more than three decades (1933-1967) during which he published 104 publications, which could be classified into nine fields: Interaction of Radiation with Matter (4), Quantum Electrodynamics (5), Mathematical Physics (2), Cosmic Ray Physics (18), Elementary Particle Physics (14), Field Theory (15), General Physics (2), Nuclear Physics (4) and General (40). The highest number of publications (6) were published in 1941, 1945 and 1964 respectively. The average number of publications published per year was 3.05. His productivity coefficient was 0.05 which is a clear indicates that his publication productivity was quite consistent throughout his scientific career. He was single author in 79 of his publications and the main author in 24 publications indicates that he always preferred to work himself and lead the team as ‘mentor’. Bhabha had 22 collaborators during the period. Team of research collaborators working with a successful scientist documents the sociological aspect of history of science while generating knowledge by a leader in a domain.
Bhabha became a citable author in 1937. Bhabha received 1211 citations to his 30 publications out of 104 publications. Out of 104, 74 publications did not receive any citations. Out of 74 publications, 40 publications dealt subjects mainly of general interest. Bhabha’s 86.66 percent of cited publications received their first citations within four years of their publication indicates that his publications were noticed immediately and had direct impact among the fellow researchers working all over the world. His overall citation rate was 11.64 per cited publication. The highest citations 389 were received to the domain ‘Cosmic ray physics’. The highest number of citations received were 45 in 1938. His self-citations were only 24 (1.98%) and citations by others were 1187 (98.02%). The highest self citations were six in 1946. Bhabha’s mean diachronous self-citation rate was 1.98. The highest citation rate 28.4 was to the domain ‘Quantum electrodynamics. His single authored publications have received the highest number 863 (71.26%) of citations. Bhabha’s five publications have been cited more than 100 times each. His publications have been cited by the authors working in various diverse fields like nuclear physics, mathematical physics, instrumentation, optics, geophysics and geochemistry, condensed matter physics, applied physics, electrical and electronic engineering, mechanical engineering etc., indicating a very diverse influence and impact of Bhabha’s publications. Bhabha’s publications have also been cited by the Nobel laureates like V. L. Ginzberg, Wolfgang Pauli, H. A. Bethe, M. Born, W. Bothe, E. P. Wigner, H. Yukawa, P. M. S. Blackett and C. N. Yang which is an indication of his originality of ideas and high quality of publications
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