484 research outputs found

    Efficiency Concepts and Models that Evaluates the Strength of Concretes Containing Different Supplementary Cementitious Materials

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    The usage of Supplementary Cementitious Materials (SCM) is very much acknowledged due to the several improvements possible in the concrete composites, and because of the general economy. Research work till date suggests that utilization of SCMs enhance a significant number of the performance characteristics of the hardened concrete. The idea of efficiency can be utilized for comparing the relative performance of different pozzolans when incorporated into concrete. The efficiency concept, which was initially developed for fly ash, can be effortlessly connected to other advantageous s as well, such as silica fume, slag and natural pozzolans. A quantitative understanding of the efficiency of SCMs as a mineral admixture in concrete is essential for its effective utilization. The paper reviews the literature pertaining to the different efficiency concepts and models present to date that evaluates the strength of concretes containing different SCMs. This short survey demonstrates that there is a need for a superior comprehension of the SCMs in concrete for its powerful usage. Also, it is an effort directed towards a specific understanding of the efficiency of SCMs in concrete

    A Product Life Cycle Ontology for Additive Manufacturing

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    The manufacturing industry is evolving rapidly, becoming more complex, more interconnected, and more geographically distributed. Competitive pressure and diversity of consumer demand are driving manufacturing companies to rely more and more on improved knowledge management practices. As a result, multiple software systems are being created to support the integration of data across the product life cycle. Unfortunately, these systems manifest a low degree of interoperability, and this creates problems, for instance when different enterprises or different branches of an enterprise interact. Common ontologies (consensus-based controlled vocabularies) have proved themselves in various domains as a valuable tool for solving such problems. In this paper, we present a consensus-based Additive Manufacturing Ontology (AMO) and illustrate its application in promoting re-usability in the field of dentistry product manufacturing

    Physico–chemical analysis and Management of different combinations of sugar mill and distillery effluents with different animal dungs during vermicomposting by earthworm Eisenia fetida

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    Sugar mill effluents and distillery effluents are harmful for human health and environment. These effluents are having higher amount of suspended solids, dissolved solids, chloride, sulphate, nitrate, and calcium etc. The vermicomposting is suitable way for proper management of these wastes with the help of earthworm Eisenia fetida. After treatment of different combination of these wastes are uses as initial feed mixture for E. fetida during vermicomposting. The physico-chemical property of different combinations of effluents of sugar mill and distillery with animal dungs was observed before and after vermicomposting. There was significant increase in total kjeldhal nitrogen (TKN) 5.8±0.18 g/kg in cow dung, total available phosphorous (TAP) 12.2±0.16 g/kg in DE, total potassium (TK) 16.3±0.36 g/kg in DE, total calcium (TCa) 3.2±0.2 g/kg in SME+BD level and significant decreased in C:N ratio 76.2±1.26 in DE+CD, total organic carbon (TOC) 139.1.13 g/kg in SME (sugar mill effluents), electrical conductivity (EC) 1.3±0.04 and moisture 52.3±1.26 % relative humidity in CD of final vermicompost with respect to initial feed mixture. The temperature of initial feed mixture was significantly decreased after vermicomposting. The pH of initial feed mixture in all the combinations tends to acidic/ neutral nature. The aim of present study to management of sugar mill effluents and distillery effluents as well as determined the chemical compositions of the different combination beds before and after vermicomposting. Keywords: Sugar mill effluents, Distillery effluents, Animal dungs, Vermicomposting, Eisenia fetida, Physico-chemical analysi

    Combination Photodynamic Therapy and Chemotherapy for Temozolomide-Resistant Glioblastoma

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    Polymer based nanoparticles (NPs) are useful vehicles for drug therapy in treating glioblastoma because of their ideal characteristics such as small size, to cross the blood-brain barrier, and bind to overexpressed transferrin receptors via peptide conjugation and surface modification of NPs. The use of a photosensitizer drug such as verteporfin, or BPD, in combination with a repurposed drug, Cediranib (CED), prepared as a nanoparticle therapy will provide the medical field with new research on the possible ways to treat glioblastoma. BPD-CED-loaded NPs have the potential to induce cytotoxicity in glioblastoma cells by 1) remotely triggering BPD through photodynamic therapy by irradiating laser at 690 nm and subsequent production of reactive oxygen species and 2) anti-angiogenesis mechanisms which may allow for longer progression free survival in patients and fewer systemic side effects due to the nanoparticle drug delivery. The specific aims of this research were to synthesize, using nanoprecipitation, and characterize pegylated and transferrin-peptide conjugated PLGA-CED NPs, PLGA-BPD NPs, and PLGA-BPD-CED NPs which were less than 100 nm in size for enhanced permeation and retention effects. NPs were characterized using dynamic light scatter (DLS) to determine particle size, PDI, and zeta potential, while absorbance spectroscopy was used to find encapsulation efficiency of loaded drugs. Transmission electron microscopy (TEM) and scanning electron microscopy (SEM) were used to obtain topographical and 3-D structural imaging of NPs. The cytotoxicity of the free drugs, targeted and non-targeted single and dual-drug-loaded NPs was evaluated using MTT assay in the U87-MG cell line. MTT assay results showed increased cell death by combination nanoparticles. The size, PDI, zeta potential and encapsulation efficiency of synthesized nanoparticles were acceptable. The major goal of this research was to investigate a new combination of photodynamic-chemotherapy drugs in NP formulation to provide for a more effective targeted cell therapy in glioblastoma patients

    Machine Learning in Manufacturing: Review, Synthesis, and Theoretical Framework

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    There has been a paradigmatic shift in manufacturing as computing has transitioned from the programmable to the cognitive computing era. In this paper we present a theoretical framework for understanding this paradigmatic shift in manufacturing and the fast evolving role of artificial intelligence. Policy, Strategic and Operational implications are discussed. Implications for the future of strategy and operations in manufacturing are also discussed. Future research directions are presented
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