Search results for: degree of efficiency

Authors: Mahabub Alam, Mohammad Mahmudul Hassan, M. Hasanuzzaman, M. Ahasanul Hoque

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Animals are transported from one place to another for different purposes in Bangladesh. However, the potential effect of long-distance transport on cattle health has not frequently been studied. Therefore, this study was conducted to assess health conditions of cattle transported from a long distance to Chittagong in Bangladesh. A total of 100 adult cattle, regardless of breed and sex, were selected at Benapole live cattle market in Jessore between August and September 2015 for the study. Blood samples were taken from 50 randomly selected cattle at 0 hours before transportation, just after transportation, at 12-16 hours post-conclusion of transportation, and 24 hours after transportation. The external health conditions and injuries of the cattle were assessed by close inspection, and the trader was interviewed using the structured questionnaire. Images of cattle injuries were taken with a camera. The basic internal health of the cattle was evaluated using standard hemato-biochemical tests. Animals were fasted and remained standing within a small space allocation (8-10 sq feet/animal) in the vehicle during transportation. Animals were provided only with paddy straw and water prior to selling at the destination market. The overall frequency of cattle injuries varied significantly (26% before vs. 47% after transportation; p < 0.001). The frequency of different cattle injuries also significantly varied by types such as abrasion (11% vs. 21%; p < 0.05) and barbed wire injury (9% vs. 18%; p < 0.05). Single cattle injury differed significantly (21% vs. 36%; p < 0.001). Cattle health conditions varied significantly (nasal discharge: 15% vs. 28%; p < 0.05; diarrhea: 15% vs. 23%; p < 0.05 and severe dehydration: 8% vs. 20%; p < 0.001). The values of hemoglobin (Hb), total erythrocyte count (TEC), total leukocyte count (TLC), lymphocyte (L), neutrophil (N) and eosinophil (E) varied significantly (p ≤ 0.01) (Hb: 11.1mg/dl vs. 12.3mg/dl; TEC: 4.7 million/ml vs. 5.7million/ml; TLC: 6.2 thousand/ml vs. 7.3 thousand/ml; L: 61.7% vs. 58.1%; N: 29.7% vs. 32.8%; E: 3.8% vs. 4.7%). The values of serum total protein (TP), creatine kinase (CK), triglyceride (TG), calcium (Ca), phosphorus (P) and alkaline phosphatase (ALP) significantly differed (p ≤ 0.05) (TP: 6.8g/dl vs. 8.2g/dl; CK:574.9u/l vs. 1288u/l; TG: 104.7mg/dl vs. 127.7mg/dl; Ca: 11.3mg/dl vs. 13mg/dl; P: 7.3mg/dl vs. 7.6mg/dl; ALP: 303u/l vs. 363u/l). The identified status of external and internal health conditions of the cattle for trading purpose due to long-distance transportation in the present study indicates a high degree of transport stress and poor animal welfare.

Keywords: animal welfare, cattle, external and internal health conditions, transportation

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Authors: Babak Safaei, A. M. Fattahi

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In the present study we have investigated axial buckling characteristics of nanocomposite beams reinforced by single-walled carbon nanotubes (SWCNTs). Various types of beam theories including Euler-Bernoulli beam theory, Timoshenko beam theory and Reddy beam theory were used to analyze the buckling behavior of carbon nanotube-reinforced composite beams. Generalized differential quadrature (GDQ) method was utilized to discretize the governing differential equations along with four commonly used boundary conditions. The material properties of the nanocomposite beams were obtained using molecular dynamic (MD) simulation corresponding to both short-(10,10) SWCNT and long-(10,10) SWCNT composites which were embedded by amorphous polyethylene matrix. Then the results obtained directly from MD simulations were matched with those calculated by the mixture rule to extract appropriate values of carbon nanotube efficiency parameters accounting for the scale-dependent material properties. The selected numerical results were presented to indicate the influences of nanotube volume fractions and end supports on the critical axial buckling loads of nanocomposite beams relevant to long- and short-nanotube composites.

Keywords: nanocomposites, molecular dynamics simulation, axial buckling, generalized differential quadrature (GDQ)

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Authors: Dimassi Wissem

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In this work, we investigate the effect of combination between the porous silicon (PS) layer passivized with Lithium Bromide (LiBr) and grooving of grain boundaries (GB) in multi crystalline silicon. The grain boundaries were grooved in order to reduce the area of these highly recombining regions. Using optimized conditions, grooved GB's enable deep phosphorus diffusion and deep metallic contacts. We have evaluated the effects of LiBr on the surface properties of porous silicon on the performance of silicon solar cells. The results show a significant improvement of the internal quantum efficiency, which is strongly related to the photo-generated current. We have also shown a reduction of the surface recombination velocity and an improvement of the diffusion length after the LiBr process. As a result, the I–V characteristics under the dark and AM1.5 illumination were improved. It was also observed a reduction of the GB recombination velocity, which was deduced from light-beam-induced-current (LBIC) measurements. Such grooving in multi crystalline silicon enables passivization of GB-related defects. These results are discussed and compared to solar cells based on untreated multi crystalline silicon wafers.

Keywords: Multicrystalline silicon, LiBr, porous silicon, passivation

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Authors: Kwame B. O. Amoah

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This paper focuses on retrofitting an old existing office building to a net-zero energy building (NZEB). An existing small office building in Melbourne, Florida, was chosen as a case study to integrate state-of-the-art design strategies and energy-efficient building systems to improve building performance and reduce energy consumption. The study aimed to explore possible ways to maximize energy savings and renewable energy generation sources to cover the building's remaining energy needs necessary to achieve net-zero energy goals. A series of retrofit options were reviewed and adopted with some significant additional decision considerations. Detailed processes and considerations leading to zero energy are well documented in this study, with lessons learned adequately outlined. Based on building energy simulations, multiple design considerations were investigated, such as emerging state-of-the-art technologies, material selection, improvements to the building envelope, optimization of the HVAC, lighting systems, and occupancy loads analysis, as well as the application of renewable energy sources. The comparative analysis of simulation results was used to determine how specific techniques led to energy saving and cost reductions. The research results indicate this small office building can meet net-zero energy use after appropriate design manipulations and renewable energy sources.

Keywords: energy consumption, building energy analysis, energy retrofits, energy-efficiency

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Authors: Cheng-Jhe Lee, Chiun-Chieh Hsu

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Due to the rapid development of the Internet and the increased availability of digital documents, the excessive information on the Internet has led to information overflow problem. In order to solve these problems for effective information retrieval, document clustering in text mining becomes a popular research topic. Clustering is the unsupervised classification of data items into groups without the need of training data. Many conventional document clustering methods perform inefficiently for large document collections because they were originally designed for relational database. Therefore they are impractical in real-world document clustering and require special handling for high dimensionality and high volume. We propose the FIHC (Frequent Itemset-based Hierarchical Clustering) method, which is a hierarchical clustering method developed for document clustering, where the intuition of FIHC is that there exist some common words for each cluster. FIHC uses such words to cluster documents and builds hierarchical topic tree. In this paper, we combine FIHC algorithm with ontology to solve the semantic problem and mine the meaning behind the words in documents. Furthermore, we use the closed frequent itemsets instead of only use frequent itemsets, which increases efficiency and scalability. The experimental results show that our method is more accurate than those of well-known document clustering algorithms.

Keywords: FIHC, documents clustering, ontology, closed frequent itemset

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Authors: Artur Tyliszczak, Ewa Szymanek, Maciej Marek

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Flow through granular materials is important to a vast array of industries, for instance in construction industry where granular layers are used for bulkheads and isolators, in chemical engineering and catalytic reactors where large surfaces of packed granular beds intensify chemical reactions, or in energy production systems, where granulates are promising materials for heat storage and heat transfer media. Despite the common usage of granulates and extensive research performed in this field, phenomena occurring between granular solid elements or between solids and fluid are still not fully understood. In the present work we analyze the heat exchange process between the flowing medium (gas, liquid) and solid material inside the granular layers. We consider them as a composite of isolated solid elements and inter-granular spaces in which a gas or liquid can flow. The structure of the layer is controlled by shapes of particular granular elements (e.g., spheres, cylinders, cubes, Raschig rings), its spatial distribution or effective characteristic dimension (total volume or surface area). We will analyze to what extent alteration of these parameters influences on flow characteristics (turbulent intensity, mixing efficiency, heat transfer) inside the layer and behind it. Analysis of flow inside granular layers is very complicated because the use of classical experimental techniques (LDA, PIV, fibber probes) inside the layers is practically impossible, whereas the use of probes (e.g. thermocouples, Pitot tubes) requires drilling of holes inside the solid material. Hence, measurements of the flow inside granular layers are usually performed using for instance advanced X-ray tomography. In this respect, theoretical or numerical analyses of flow inside granulates seem crucial. Application of discrete element methods in combination with the classical finite volume/finite difference approaches is problematic as a mesh generation process for complex granular material can be very arduous. A good alternative for simulation of flow in complex domains is an immersed boundary-volume penalization (IB-VP) in which the computational meshes have simple Cartesian structure and impact of solid objects on the fluid is mimicked by source terms added to the Navier-Stokes and energy equations. The present paper focuses on application of the IB-VP method combined with large eddy simulation (LES). The flow solver used in this work is a high-order code (SAILOR), which was used previously in various studies, including laminar/turbulent transition in free flows and also for flows in wavy channels, wavy pipes and over various shape obstacles. In these cases a formal order of approximation turned out to be in between 1 and 2, depending on the test case. The current research concentrates on analyses of the flows in dense granular layers with elements distributed in a deterministic regular manner and validation of the results obtained using LES-IB method and body-fitted approach. The comparisons are very promising and show very good agreement. It is found that the size, number of elements and their distribution have huge impact on the obtained results. Ordering of the granular elements (or lack of it) affects both the pressure drop and efficiency of the heat transfer as it significantly changes mixing process.

Keywords: granular layers, heat transfer, immersed boundary method, numerical simulations

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Authors: Mengjie Zhou

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Under the rapid promotion of digital logistics, the old consumption space in cities is undergoing profound transformation and reconstruction. This article systematically analyzes the impact of digital logistics on existing consumer spaces in cities and how these spaces can adapt to and lead this change through distinct ‘spatial production’ models. The digital transformation of the logistics industry has significantly improved logistics efficiency and service quality while also putting forward new requirements for the form and function of consumer space. In this process, the old consumption space in cities not only faces the trend of material consumption transforming into spiritual consumption but also needs to face profound changes in consumer behavior patterns. Taking Fengying Xili in Changsha as an empirical case, this article explores in detail how it successfully transformed from a traditional consumption space to a modern cultural consumption space by introducing new business formats, optimizing spatial layout, and improving service quality while preserving its historical heritage. This case not only provides valuable practical experience for the transformation of old urban consumption spaces but also demonstrates the feasibility and potential of the new model of ‘spatial production’.

Keywords: digital logistics, urban consumption space, space production, urban renewal

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Authors: Olayinka Oduwole, Steve Sheard

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The magnetic separation of biological cells using super-magnetic beads has been used widely for various bioassays. These bioassays can further be integrated with other laboratory components to form a biosensor which can be used for cell sorting, mixing, purification, transport, manipulation etc. These bio-sensing applications have also been facilitated by the wide availability of magnetic beads which range in size and magnetic properties produced by different manufacturers. In order to improve the efficiency and separation capabilities of these biosensors, it is important to determine the magnetic force induced velocities and interaction of beads within the magnetic field; this will help biosensor users choose the desired magnetic bead for their specific application. This study presents for the first time the interaction between a pair of different sized super-paramagnetic beads suspended in a static fluid moving within a uniform magnetic field using a modified finite-time-finite-difference scheme. A captured video was used to record the trajectory pattern and a good agreement was obtained between the simulated trajectories and the video data. The model is, therefore, a good approximation for predicting the velocities as well as the interaction between various magnetic particles which differ in size and magnetic properties for bio-sensing applications requiring a low concentration of magnetic beads.

Keywords: biosensor, magnetic field, magnetic separation, super-paramagnetic bead

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Authors: Aniket Ganvir, Ritarani Sahu, Suchismita Chinara

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The rapid digitization of various aspects of life is leading to the creation of smart IoT ecosystems, where interconnected devices generate significant amounts of valuable data. However, these IoT devices face constraints such as limited computational resources and bandwidth. Cloud computing emerges as a solution by offering ample resources for offloading tasks efficiently despite introducing latency issues, especially for time-sensitive applications like fog computing. Fog computing (FC) addresses latency concerns by bringing computation and storage closer to the network edge, minimizing data travel distance, and enhancing efficiency. Offloading tasks to fog nodes or the cloud can conserve energy and extend IoT device lifespan. The offloading process is intricate, with tasks categorized as full or partial, and its optimization presents an NP-hard problem. Traditional greedy search methods struggle to address the complexity of task offloading efficiently. To overcome this, the efficient crow search algorithm (ECSA) has been proposed as a meta-heuristic optimization algorithm. ECSA aims to effectively optimize computation offloading, providing solutions to this challenging problem.

Keywords: IoT, fog computing, task offloading, efficient crow search algorithm

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Authors: Djaafar Fatiha, Ghalem Bachir, Hadri Bagdad

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We studied mainly the influence of temperature, thickness, molar fraction and the doping of the various layers (emitter, base, BSF and window) on the performances of a photovoltaic solar cell. In a first stage, we optimized the performances of the InGaP/GaAs dual-junction solar cell while varying its operation temperature from 275°K to 375 °K with an increment of 25°C using a virtual wafer fabrication TCAD Silvaco. The optimization at 300 °K led to the following result: Icc =14.22 mA/cm2, Voc =2.42V, FF=91.32 %, η= 22.76 % which is close with those found in the literature. In a second stage ,we have varied the molar fraction of different layers as well their thickness and the doping of both emitters and bases and we have registered the result of each variation until obtaining an optimal efficiency of the proposed solar cell at 300°K which was of Icc=14.35mA/cm2,Voc=2.47V,FF=91.34,and η=23.33% for In(1-x)Ga(x)P molar fraction( x=0.5).The elimination of a layer BSF on the back face of our cell, enabled us to make a remarkable improvement of the short-circuit current (Icc=14.70 mA/cm2) and a decrease in open circuit voltage Voc and output η which reached 1.46V and 11.97% respectively. Therefore, we could determine the critical parameters of the cell and optimize its various technological parameters to obtain the best performance for a dual junction solar cell .This work opens the way with new prospects in the field of the photovoltaic one. Such structures will thus simplify the manufacturing processes of the cells; will thus reduce the costs while producing high outputs of photovoltaic conversion.

Keywords: modeling, simulation, multijunction, optimization, Silvaco ATLAS

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Authors: Hyun-Ju Oh, Soon-Rim Suh, Mihan Kim

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The steady and rapid increase of the older population is a global phenomenon. Chronic diseases and disabilities are increased due to aging. In general, exercise has been known to be most effective in preventing and managing chronic back pain. However, it is hard for the older women to initiate and maintain the exercise. Transtheoretical model (TTM) is one of the theories explain behavioral changes such as exercise. The application of the program considering the stage of behavior change is effective for the elderly woman to start and maintain the exercise. The purpose of this study was to develop TTM based exercise program and to examine its effect for elderly women with chronic back-pain. For the program evaluation, the non-equivalent control pre-posttest design was applied. The independent variable of this study is exercise intervention program. The contents of the program were constructed considering the characteristics of the elderly women with chronic low back pain, focusing on the process of change, the stage of change by the previous studies. The developed exercise program was applied to the elderly women with chronic low back pain in the planning stage and the preparation stage. The subjects were 50 older women over 65 years of age with chronic back-pain who did not practice regular exercise. The experimental group (n=25) received the 8weeks TTM based exercise program. The control group received the book which named low back pain management. Data were collected at three times: before the exercise intervention, right after the intervention, and 4weeks after the intervention. The dependent variables were the processes of change, decisional balance, exercise self-efficacy, back-pain, depression and muscle strength. The results of this study were as follows. Processes of change (<.001), pros of decisional balance (<.001), exercise self-efficacy (<.001), back pain (<.001), depression (<.001), muscle strength (<.001) were higher in the experimental group than in the control group right after the program and 4weeks after the programs. The results of this study show that applying the TTM based exercise program increases the use of the change process, increases the exercise self-efficacy, increases the stage of changing the exercise behavior and strengthens the muscular strength by lowering the degree of pain and depression Respectively. The significance of the study was to confirm the effect of continuous exercise by maintaining regular exercise habits by applying exercise program of the transtheoretical model to the chronic low back pain elderly with exercise intention.

Keywords: chronic back pain, elderly, exercise, women

Procedia PDF Downloads 252

Authors: Muhammad Bilal Shaikh

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Mineral processing plants play a pivotal role in extracting valuable minerals from raw ores, contributing significantly to various industries. However, the optimization of plant throughput remains a complex challenge, necessitating innovative approaches for increased efficiency and productivity. This research paper investigates the application of Multimodal Artificial Intelligence (MAI) techniques to address this challenge, aiming to improve overall plant throughput in mineral processing operations. The integration of multimodal AI leverages a combination of diverse data sources, including sensor data, images, and textual information, to provide a holistic understanding of the complex processes involved in mineral extraction. The paper explores the synergies between various AI modalities, such as machine learning, computer vision, and natural language processing, to create a comprehensive and adaptive system for optimizing mineral processing plants. The primary focus of the research is on developing advanced predictive models that can accurately forecast various parameters affecting plant throughput. Utilizing historical process data, machine learning algorithms are trained to identify patterns, correlations, and dependencies within the intricate network of mineral processing operations. This enables real-time decision-making and process optimization, ultimately leading to enhanced plant throughput. Incorporating computer vision into the multimodal AI framework allows for the analysis of visual data from sensors and cameras positioned throughout the plant. This visual input aids in monitoring equipment conditions, identifying anomalies, and optimizing the flow of raw materials. The combination of machine learning and computer vision enables the creation of predictive maintenance strategies, reducing downtime and improving the overall reliability of mineral processing plants. Furthermore, the integration of natural language processing facilitates the extraction of valuable insights from unstructured textual data, such as maintenance logs, research papers, and operator reports. By understanding and analyzing this textual information, the multimodal AI system can identify trends, potential bottlenecks, and areas for improvement in plant operations. This comprehensive approach enables a more nuanced understanding of the factors influencing throughput and allows for targeted interventions. The research also explores the challenges associated with implementing multimodal AI in mineral processing plants, including data integration, model interpretability, and scalability. Addressing these challenges is crucial for the successful deployment of AI solutions in real-world industrial settings. To validate the effectiveness of the proposed multimodal AI framework, the research conducts case studies in collaboration with mineral processing plants. The results demonstrate tangible improvements in plant throughput, efficiency, and cost-effectiveness. The paper concludes with insights into the broader implications of implementing multimodal AI in mineral processing and its potential to revolutionize the industry by providing a robust, adaptive, and data-driven approach to optimizing plant operations. In summary, this research contributes to the evolving field of mineral processing by showcasing the transformative potential of multimodal artificial intelligence in enhancing plant throughput. The proposed framework offers a holistic solution that integrates machine learning, computer vision, and natural language processing to address the intricacies of mineral extraction processes, paving the way for a more efficient and sustainable future in the mineral processing industry.

Keywords: multimodal AI, computer vision, NLP, mineral processing, mining

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Authors: Youcef Amir

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The consumption of beverages continues to grow worldwide due to increasing demography, but pure fruit juices and high-quality nectars can induce protective effects on human health because of their natural bioactive components. In contrast, sodas and gaseous drinks containing synthetic food additives are considered as responsible for consumers of several pathologies such as obesity, diabetes, and non-alcoholic fatty liver disease. The nutritional and therapeutic virtues of fruit juices are generally a remarkable antioxidant power, anti-cancer activity linked to their richness of indigestible and indigestible sugars, vitamins, mineral salts, carotenoids and phenolic compounds. The main reasons, which led us to produce these fruit derivatives, are the non-availability of the fresh fruits mentioned above all along the year and also the existence of variations in the chemical composition of these different fruits as well as for the major or minor components. We tested, therefore, the physicochemical characteristics of each fruit juice and pulp apart and afterward those of the cocktails formulated. The fresh juices used during our experiments were obtained from the following fruits from north-central Algeria: prickly pear, pomegranate, melon, red oranges. The formulations of these fruit juices were tested after several trials comprising sensorial analysis, physicochemical factors (pH, titratable acidity, Brix degree, formal index, water content, total ash, total and reducing sugars, vitamin C, carotenoids, phenolic compounds) and microbial analysis after a storage period. To the pure juices proportions, citric acid E330, sucrose, and water were added followed by pasteurisation. These products were analysed from the physicochemical, microbial and sensorial viewpoints after a storage period of one month according to national legislation to evaluate their stability. The results of the physicochemical parameters of the prepared beverages had shown good physicochemical results, acceptable sensorial characteristics and microbial stability and safety before and after a storage period. We measured appreciable amounts of minor compounds with health properties.

Keywords: fruit juices, microbial analyses, nectars, physico chemical characteristics, sensorial analysis, storage period

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Authors: Muhammad Awais, Wei Li, Anjum Munir

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Biomass gasification is a process of converting solid biomass ingredients into a combustible gas which can be used in electricity generation. Regardless of their applications in many fields, biomass gasification technology is still facing many cleaning issues of syngas. Tar production in biomass gasification process is one of the biggest challenges for this technology. The aimed of this study is to evaluate the tar contents in syngas produced from wood chips, corn cobs, coconut shells and mixture of corn cobs and wood chips as biomass fuel and tar removal efficiency of different cleaning units integrated with gassifier. Performance of different cleaning units, i.e., cyclone separator, wet scrubber, biomass filter, and auxiliary filter was tested under two biomass fuels. Results of this study indicate that wood chips produced less tar of 1736 mg/Nm³ as compared to corn cobs which produced tor 2489 mg/Nm³. It is also observed that coconut shells produced a high amount of tar. It was observed that when wood chips were used as a fuel, syngas tar contents were reduced from 6600 to 112 mg/Nm³ while in case of corn cob, they were reduced from 7500 mg/Nm³ to 220 mg/Nm³. Overall tar removal efficiencies of cyclone separator, wet scrubber, biomass filter, and auxiliary filter was 72%, 63%, 74%, 35% respectively.

Keywords: biomass, gasification, tar, cleaning system, biomass filter

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Authors: Christine K. Ormsbee, Jeremy S. Robinson

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Teacher quality is important for United States universities. It impacts student achievement, program and degree progress, and even retention. While course instructors are still the primary designers and deliverers of instruction in U.S. higher education classrooms, students have become better and more vocal consumers of instruction. They are capable of identifying what instructors do that facilitates their learning or, conversely, what instructors do that makes learning more difficult. Instructors can use students as resources as they design and implement their courses. Students have become more aware of their own learning preferences and processes and can articulate those. While it is not necessarily possible or likely that an instructor can address the widely varying differences in learning preferences represented by a large class of students, it is possible for them to employ general instructional supports that help students understand clearly the instructor's study expectations, identify critical content, efficiently commit content to memory, and develop new skills. Those learning supports include reading guides, test study guides, and other instructor-developed tasks that organize learning for students, hold them accountable for the content, and prepare them to use that material in simulated and real situations. When U.S. university teaching and learning support staff work with instructors to help them identify areas of their teaching to improve, a key part of that assistance includes talking to the instructor member's students. Students are asked to explain what the instructor does that helps them learn, what the instructor does that impedes their learning, and what they wish the instructor would do. Not surprisingly, students are very specific in what they see as helpful learning supports for them. Moreover, they also identify impediments to their success, viewing those as the instructor creating unnecessary barriers to learning. A qualitative survey was developed to provide undergraduate students the opportunity to identify instructor behaviors and/or practices that they thought helped students learn and those behaviors and practices that were perceived as hindrances to student success. That information is used to help instructors implement more student-focused learning supports that facilitate student achievement. In this session, data shared from the survey will focus on supportive instructor behaviors identified by undergraduate students in an institution located in the southwest United States and those behaviors that students perceive as creating unnecessary barriers to their academic success.

Keywords: effective teaching, pedagogy, student engagement, instructional design

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Authors: Arifa Batool, Ghulam Hussain Bhatti, Syed Mujtaba Shah

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Inorganic n-type (TiO2, CdO) and p-type (NiO, CuO) metal oxide nanoparticles were synthesized by a facile wet chemical method at room temperature. The morphological, compositional, structural and optical properties were investigated by scanning electron microscopy, energy dispersive X-ray spectroscopy, FT-IR, XRD analysis, UV/Visible and fluorescence spectroscopy. All semiconducting nanoparticles were photosensitized with Ru (II) based Z907 dye in ethanol solvent by grafting. Grafting of dye on the surface of nanoparticles was confirmed by UV/Visible and FT-IR spectroscopy. The synthesized photo-active nanohybrid was thoroughly blended with P3HT, a solid electrolyte and I-V measurements under solar stimulated radiations 1000 W/m2 (AM 1.5) were recorded. Maximum incident photon to current conversion efficiency (IPCE) of 0.9% was achieved with dye functionalized Z907-TiO2 hybrid, IPCE of 0.72% was achieved with bulk-heterojunction of TiO2-Z907-CuO and IPCE of 0.68% was attained with nanocomposite of TiO2-CdO. TiO2 based Solar cells have maximum Jscvalue i.e.4.63 mA/cm2. Dye-functionalized TiO2-based photovoltaic devices were found more efficient than the reference device but the morphology of the device was a major check in progress.

Keywords: solar cell, bulk heterojunction, nanocomposites, photosensitization, dye sensitized solar cell

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Authors: Polycarpe Feussi

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Globalization, technological and customer increasing changes, amongst other drivers, result in higher levels of uncertainty and unpredictability for organizations. In order for organizations to cope with the uncertain and fast-changing economic and business environment, these organizations need to innovate in order to achieve flexibility. In simple terms, the organizations must develop strategies leading to the ability of these organizations to provide horizontal information connections across the supply chain to create and deliver products that meet customer needs by synchronization of customer demands with product creation. The generated information will create efficiency and effectiveness throughout the whole supply chain regarding production, storage, and distribution, as well as eliminating redundant activities and reduction in response time. In an integrated supply chain, spanning activities include coordination with distributors and suppliers. This paper explains how through postponement strategies, flexibility can be achieved in an organization. In order to achieve the above, a thorough literature review was conducted via the search of online websites that contains material from scientific journal data-bases, articles, and textbooks on the subject of postponement and flexibility. The findings of the research are found in the last part of the paper. The first part introduces the concept of postponement and its importance in supply chain management. The second part of the paper provides the methodology used in the process of writing the paper.

Keywords: postponement strategies, supply chain management, flexibility, logistics

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Authors: Lukman Andi Priyatna, Vivi Fauzia, Ferry Anggoro Ardy Nugroho

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Zinc oxide (ZnO) based nanostructures are ubiquitous in applications due to their favourable physicochemical properties and ease of fabrication. One widely accessible route to synthesize ZnO nanorods, which show promising performance in e.g. photoelectrochemical water splitting, is hydrothermal growth of ZnO seeds, obtained via an atomic nebulizer. Despite its popularity, study on the impact of the synthesis parameters in atomic nebulizer on the performance of the synthesized ZnO nanostructures is lacking. This study presents an investigation on the impact of the distance between substrates and atomic nebulizer nozzle on the photoelectrochemical water splitting performance of ZnO nanorods. Adjusting such a distance reveals an optimum separation which results in nanostructures with highest absorbance. Such high absorbance translates into improved photoelectrochemistry, as evaluated by higher photocurrent density, from 0.11 mA/cm² to 0.14 mA/cm² and higher Applied Bias Photon-to-Current Efficiency (ABPE) from 0.12% to 0.14%. These results underscore the importance of understanding and optimizing the experimental parameters during ZnO nanostructure synthesis. In a broader context, it advertises the need to carefully assess the corresponding fabrication parameters to optimize the performance of the obtained nanostructures.

Keywords: atomic nebulizer, photocurrent density, photoelectrochemical water splitting, ZnO nanorods

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Authors: Han Longxiang

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In the process of treating industrial oily wastewater with complex components, the traditional treatment methods (flotation, coagulation, microwave heating, etc.) often produce high operating costs, secondary pollution, and other problems. In order to solve these problems, the materials with high flux and stability applied to surfactant-stabilized emulsions separation have gained huge attention in the treatment of oily wastewater. Nevertheless, four stable oil-in-water emulsions can be formed due to different surfactants (surfactant-free, anionic surfactant, cationic surfactant, and non-ionic surfactant), and the previous advanced materials can only separate one or several of them, cannot effectively separate in one step. Herein, a facile synthesis method of graphene-based multilevel filter materials (GMFM) which can efficiently separate the oil-in-water emulsions stabilized with different surfactants only through its gravity. The prepared materials with high stability of 20 cycles show a high flux of ~ 5000 L m-2 h-1 with a high separation efficiency of > 99.9 %. GMFM can effectively separate the emulsion stabilized by mixed surfactants and oily wastewater from factories. The results indicate that the GMFM have a wide range of applications in oil-in-water emulsions separation in industry and environmental science.

Keywords: emulsion, filtration, graphene, one-step

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Authors: V. E. Messerle, A. L. Mosse, O. A. Lavrichshev, A. N. Nikonchuk, A. B. Ustimenko

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One of the most serious environmental problems today is pollution by biomedical waste (BMW), which in most cases has undesirable properties such as toxicity, carcinogenicity, mutagenicity, fire. Sanitary and hygienic survey of typical solid BMW, made in Belarus, Kazakhstan, Russia and other countries shows that their risk to the environment is significantly higher than that of most chemical wastes. Utilization of toxic BMW requires use of the most universal methods to ensure disinfection and disposal of any of their components. Such technology is a plasma technology of BMW processing. To implement this technology a thermodynamic analysis of the plasma processing of BMW was fulfilled and plasma-box furnace was developed. The studies have been conducted on the example of the processing of bone. To perform thermodynamic calculations software package Terra was used. Calculations were carried out in the temperature range 300 - 3000 K and a pressure of 0.1 MPa. It is shown that the final products do not contain toxic substances. From the organic mass of BMW synthesis gas containing combustible components 77.4-84.6% was basically produced, and mineral part consists mainly of calcium oxide and contains no carbon. Degree of gasification of carbon reaches 100% by the temperature 1250 K. Specific power consumption for BMW processing increases with the temperature throughout its range and reaches 1 kWh/kg. To realize plasma processing of BMW experimental installation with DC plasma torch of 30 kW power was developed. The experiments allowed verifying the thermodynamic calculations. Wastes are packed in boxes weighing 5-7 kg. They are placed in the box furnace. Under the influence of air plasma flame average temperature in the box reaches 1800 OC, the organic part of the waste is gasified and inorganic part of the waste is melted. The resulting synthesis gas is continuously withdrawn from the unit through the cooling and cleaning system. Molten mineral part of the waste is removed from the furnace after it has been stopped. Experimental studies allowed determining operating modes of the plasma box furnace, the exhaust gases was analyzed, samples of condensed products were assembled and their chemical composition was determined. Gas at the outlet of the plasma box furnace has the following composition (vol.%): CO - 63.4, H2 - 6.2, N2 - 29.6, S - 0.8. The total concentration of synthesis gas (CO + H2) is 69.6%, which agrees well with the thermodynamic calculation. Experiments confirmed absence of the toxic substances in the final products.

Keywords: biomedical waste, box furnace, plasma torch, processing, synthesis gas

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Authors: M. Merabet-Khelassi, Z. Houiene, L. Aribi-Zouioueche, O. Riant

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Lipases (EC.3.1.1.3) are efficient biotools widely used for their remarkable chemo-, regio- and enantio-selectivity, especially, in kinetic resolution of racemates. They offer access to a large panel of enantiopure building blocks, such as secondary benzylic alcohols, commonly used as synthetic intermediates in pharmaceutical and agrochemical industries. Due to the stability of lipases in both water and organic solvents poor in water, they are able to catalyze both transesterifications of arylalkylcarbinols and hydrolysis of their corresponding acetates. The use of enzymatic hydrolysis in aqueous media still limited. In this presentation, we expose a practical methodology for the preparation of optically enriched acetates using a Candida antarctica lipase B-catalyzed hydrolysis in non-aqueous media in the presence of alkaline carbonate salts. The influence of several parameters which can intervene on the enzymatic efficiency such as the impact of the introduction of the carbonates salts, its amount and the nature of the alkaline earth metal are discussed. The obtained results show that the use of sodium carbonate with CAL-B enhances drastically both reactivity and selectivity of this immobilized lipase. In all cases, the resulting alcohols and remaining acetates are obtained in high ee values (up to > 99 %), and the selectivities reach (E > 500).

Keywords: alkaline-hydrolysis, enzymatic kinetic resolution, lipases, arylalkylcarbinol, non-aqueous media

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Authors: Awatef Chniguir, Tarek Farah, Zouhair Ben Jemaa, Safya Belguith

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Optimal routing allows minimizing energy consumption in wireless sensor networks (WSN). Clustering has proven its effectiveness in organizing WSN by reducing channel contention and packet collision and enhancing network throughput under heavy load. Therefore, nowadays, with the emergence of the Internet of Things, heterogeneity is essential. Stable election protocol (SEP) that has increased the network stability period and lifetime is the first clustering protocol for heterogeneous WSN. SEP and its descendants, namely SEP, Threshold Sensitive SEP (TSEP), Enhanced TSEP (ETSSEP) and Current Energy Allotted TSEP (CEATSEP), were studied. These algorithms’ performance was evaluated based on different metrics, especially first node death (FND), to compare their stability. Simulations were conducted on the MATLAB tool considering two scenarios: The first one demonstrates the fraction variation of advanced nodes by setting the number of total nodes. The second considers the interpretation of the number of nodes while keeping the number of advanced nodes permanent. CEATSEP outperforms its antecedents by increasing stability and, at the same time, keeping a low throughput. It also operates very well in a large-scale network. Consequently, CEATSEP has a useful lifespan and energy efficiency compared to the other routing protocol for heterogeneous WSN.

Keywords: clustering, heterogeneous, stability, scalability, IoT, WSN

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Authors: M. Zake, I. Barmina, R. Valdmanis, A. Kolmickovs

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Experimental investigations of the DC electric field effect on thermal decomposition of biomass, formation of the axial flow of volatiles (CO, H2, CxHy), mixing of volatiles with swirling airflow at low swirl intensity (S ≈ 0.2-0.35), their ignition and on formation of combustion dynamics are carried out with the aim to understand the mechanism of electric field influence on biomass gasification, combustion of volatiles and heat energy production. The DC electric field effect on combustion dynamics was studied by varying the positive bias voltage of the central electrode from 0.6 kV to 3 kV, whereas the ion current was limited to 2 mA. The results of experimental investigations confirm the field-enhanced biomass gasification with enhanced release of volatiles and the development of endothermic processes at the primary stage of thermochemical conversion of biomass determining the field-enhanced heat energy consumption with the correlating decrease of the flame temperature and heat energy production at this stage of flame formation. Further, the field-enhanced radial expansion of the flame reaction zone correlates with a more complete combustion of volatiles increasing the combustion efficiency by 3 % and decreasing the mass fraction of CO, H2 and CxHy in the products, whereas by 10 % increases the average volume fraction of CO2 and the heat energy production downstream the combustor increases by 5-10 %

Keywords: biomass, combustion, electrodynamic control, gasification

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Authors: Jeffrey Siphiwe Mkhize

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Twelve years of schooling for most South African children, particularly those children from disadvantaged past, are confronted with numerous and diverse challenges. These challenges range from infrastructural limitations, language of teaching, poor resources and varying family backgrounds. Likewise, schools are categorized to signify schools’ geographic location, poverty lines, societal class and type of students that the school are likely to enroll. Such categorization perpetuates particular lines of identities that are indirectly reinforced by the same system that seeks to redress. South African universities prefer point systems to determine students’ suitability to gain access to their programmes. Once students are admitted based on the qualifying points there is an assumed equity in the manner in which they receive tuition. They are assumed as equal; noting the widened access to South African universities as means to redress past inequalities. Given the challenges, inequalities, it is necessary to view higher education as a site for knowledge construction that is accessible to all students. Epistemological access is key to all students irrespective of their socio-economic status. This paper seeks to contribute to the discourse of student engagement using lecturer-student relationship as a lens to understand this phenomenon. Data were generated using South African Survey of Student Engagement, focus group interviews, semi-structured one-on-one-interviews as well as document analysis. The focus was on students registered for the first year of a Bachelor of Education degree as well as lecturers that teach high risk modules in this qualification at the same level. The findings suggest that lecturers are challenged by overcrowded classrooms and over-enrolled modules; this challenge hampers their good intentions to become more efficient and innovative in their teaching. Students lack confidence in approaching lecturers for assistance. Collaborative learning has stronger results and students believe in self-support to deal with their challenges based on their individual strengths. Collaborative learning is key to student academic performance.

Keywords: collaborative learning, consultations, student engagement, student performance

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Authors: Mahdi Motahari, Mojtaba Farzaneh, Ebrahim Sepidbar

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Tracking of moving and flying targets is one of the most important issues in image processing topic. Estimating of trajectory of desired object in short-term and long-term scale is more important than tracking of moving and flying targets. In this paper, a new way of identifying and estimating of future trajectory of a moving ball in long-term scale is estimated by using synthesis and interaction of image processing algorithms including noise removal and image segmentation, Kalman filter algorithm in order to estimating of trajectory of ball in football game in short-term scale and intelligent adaptive neuro-fuzzy algorithm based on time series of traverse distance. The proposed system attain more than 96% identify accuracy by using aforesaid methods and relaying on aforesaid algorithms and data base video in format of synthesis and interaction. Although the present method has high precision, it is time consuming. By comparing this method with other methods we realize the accuracy and efficiency of that.

Keywords: tracking, signal processing, moving targets and flying, artificial intelligent systems, estimating of trajectory, Kalman filter

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Authors: Erico R. Carmona, Lucas Hernandez-Saravia, Aliro Villacorta, Felipe Carevic

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Tailings and electronic waste (e-waste) are an important source of global contamination. Chile is one of Organisation for Economic Co-operation and Development (OECD) member countries that least recycled this kind of industrial waste, reaching only 3% of the total. Tailings and e-waste recycling offers a valuable tool to minimize the increasing accumulation of waste, supplement the scarcity of some raw materials and to obtain economic benefits through the commercialization of these. It should be noted that this type of industrial waste is an important source of valuable metals, such as copper, which allow generating new business and added value through its transformation into new materials with advanced physical and biological properties. In this sense, the development of nanotechnology has led to the creation of nanomaterials with multiple applications given their unique physicochemical properties. Among others, copper nanoparticles (CuNPs) have gained great interest due to their optical, catalytic, conductive properties, and particularly because of their broad-spectrum antimicrobial activity. There are different synthesis methods of copper nanoparticles; however, green synthesis is one of the most promising methodologies, since it is simple, low-cost, ecological, and generates stable nanoparticles, which makes it a promising methodology for scaling up. Currently, there are few initiatives that involve the development of methods for the recovery and transformation of copper from waste to produce nanoparticles with new properties and better technological benefits. Thus, the objective of this work is to show preliminary data about the develop a sustainable transformation process of tailings and e-waste that allows obtaining a copper-based nanotechnological product with potential antimicrobial applications. For this, samples of tailings and e-waste collected from Tarapacá and Antofagasta region of northern Chile were used to recover copper through efficient, ecological, and low-cost alkaline hydrometallurgical treatments, which to allow obtaining copper with a high degree of purity. On the other hand, the transformation process from recycled copper to a nanomaterial was carried out through a green synthesis approach by using vegetal organic residue extracts that allows obtaining CuNPs following methodologies previously reported by authors. Initial physical characterization with UV-Vis, FTIR, AFM, and TEM methodologies will be reported for CuNPs synthesized.

Keywords: nanomaterials, industrial waste, chile, recycling

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Authors: Andrew R. Winters, Gregor J. Gassner

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A high-order numerical magentohydrodynamics (MHD) solver built upon a non-linear entropy stable numerical flux function that supports eight traveling wave solutions will be described. The method is designed to treat the divergence-free constraint on the magnetic field in a similar fashion to a hyperbolic divergence cleaning technique. The solver is especially well-suited for flows involving strong discontinuities due to its strong stability without the need to enforce artificial low density or energy limits. Furthermore, a new formulation of the numerical algorithm to guarantee positivity of the pressure during the simulation is described and presented. By construction, the solver conserves mass, momentum, and energy and is entropy stable. High spatial order is obtained through the use of a third order limiting technique. High temporal order is achieved by utilizing the family of strong stability preserving (SSP) Runge-Kutta methods. Main attributes of the solver are presented as well as details on an implementation of the new solver into the multi-physics, multi-scale simulation code FLASH. The accuracy, robustness, and computational efficiency is demonstrated with a variety of numerical tests. Comparisons are also made between the new solver and existing methods already present in FLASH framework.

Keywords: entropy stability, finite volume scheme, magnetohydrodynamics, pressure positivity

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Authors: Wu Defu, Kiefer Chiam, Yang Kin Seng

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The planning of geological survey works is an iterative process which involves planner, geologist, civil engineer and other stakeholders, who perform different roles and have different points of view. Traditionally, the team used paper maps or CAD drawings to present the proposal which is not an efficient way to present and share idea on the site investigation proposal such as sitting of borehole location or seismic survey lines. This paper focuses on how a GIS approach can be utilised to develop a web-based system to support decision making process in the planning of geological survey works and also to plan site activities carried out by Singapore Geological Office (SGO). The authors design a framework of building an interactive web-based GIS system, and develop a prototype, which enables the users to obtain rapidly existing geological information and also to plan interactively borehole locations and seismic survey lines via a web browser. This prototype system is used daily by SGO and has shown to be effective in increasing efficiency and productivity as the time taken in the planning of geological survey works is shortened. The prototype system has been developed using the ESRI ArcGIS API 3.7 for Flex which is based on the ArcGIS 10.2.1 platform.

Keywords: engineering geology, flex, geological survey planning, geoscience, GIS, site investigation, WebGIS

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Authors: Bitan Kumar Sarkar, Akashdeep Agarwal, Rajib Dey, Gopes Chandra Das

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The rapid depletion of high-grade iron ore (Fe₂O₃) has gained attention on the use of other sources of iron ore. Titaniferous magnetite ore (TMO) is a special type of magnetite ore having high titania content (23.23% TiO₂ present in this case). Due to high TiO₂ content and high density, TMO cannot be treated by the conventional smelting reduction. In this present work, the TMO has been collected from high-grade metamorphic terrain of the Precambrian Chotanagpur gneissic complex situated in the eastern part of India (Shaltora area, Bankura district, West Bengal) and the hematite ore has been collected from Visakhapatnam Steel Plant (VSP), Visakhapatnam. At VSP, iron ore is received from Bailadila mines, Chattisgarh of M/s. National Mineral Development Corporation. The preliminary characterization of TMO and hematite ore (HMO) has been investigated by WDXRF, XRD and FESEM analyses. Similarly, good quality of coal (mainly coking coal) is also getting depleted fast. The basic purpose of this work is to find how lean grade coal can be utilised along with TMO for smelting to produce pig iron. Lean grade coal has been characterised by using TG/DTA, proximate and ultimate analyses. The boiler grade coal has been found to contain 28.08% of fixed carbon and 28.31% of volatile matter. TMO fines (below 75 μm) and HMO fines (below 75 μm) have been separately agglomerated with lean grade coal fines (below 75 μm) in the form of briquettes using binders like bentonite and molasses. These green briquettes are dried first in oven at 423 K for 30 min and then reduced isothermally in tube furnace over the temperature range of 1323 K, 1373 K and 1423 K for 30 min & 60 min. After reduction, the reduced briquettes are characterized by XRD and FESEM analyses. The best reduced TMO and HMO samples are taken and blended in three different weight percentage ratios of 1:4, 1:8 and 1:12 of TMO:HMO. The chemical analysis of three blended samples is carried out and degree of metallisation of iron is found to contain 89.38%, 92.12% and 93.12%, respectively. These three blended samples are briquetted using binder like bentonite and lime. Thereafter these blended briquettes are separately smelted in raising hearth furnace at 1773 K for 30 min. The pig iron formed is characterized using XRD, microscopic analysis. It can be concluded that 90% yield of pig iron can be achieved when the blend ratio of TMO:HMO is 1:4.5. This means for 90% yield, the maximum TMO that could be used in the blend is about 18%.

Keywords: briquetting reduction, lean grade coal, smelting reduction, TMO

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Authors: S. Koppikar, P. Kulkarni, D. Ingale , N. Wagh, S. Deshpande, A. Mahajan, A. Harsulkar

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Crucial role of reactive oxygen species (ROS) in the progression Osteoarthritis (OA) pathogenesis has been endorsed several times though its exact mechanism remains unclear. Oxidative stress is known to instigate classical stress factors such as cytokines, chemokines and ROS, which hampers cartilage remodelling process and ultimately results in worsening the disease. Synovial fluid (SF) is a biological communicator between cartilage and synovium that accumulates redox and biochemical signalling mediators. The present work attempts to measure several oxidative stress markers in the synovial fluid obtained from knee OA patients with varying degree of disease severity. Thirty OA and five Meniscal-tear (MT) patients were graded using Kellgren-Lawrence scale and assessed for Nitric oxide (NO), Nitrate-Nitrite (NN), 2,2-diphenyl-1-picrylhydrazyl (DPPH), Ferric Reducing Antioxidant Potential (FRAP), Catalase (CAT), Superoxide dismutase (SOD) and Malondialdehyde (MDA) levels for comparison. Out of various oxidative markers studied, NO and SOD showed significant difference between moderate and severe OA (p= 0.007 and p= 0.08, respectively), whereas CAT demonstrated significant difference between MT and mild group (p= 0.07). Interestingly, NN revealed statistically positive correlation with OA severity (p= 0.001 and p= 0.003). MDA, a lipid peroxidation by-product was estimated maximum in early OA when compared to MT (p= 0.06). However, FRAP did not show any correlation with OA severity or MT control. NO is an essential bio-regulatory molecule essential for several physiological processes, and inflammatory conditions. However, due to its short life, exact estimation of NO becomes difficult. NO and its measurable stable products are still it is considered as one of the important biomarker of oxidative damage. Levels of NO and nitrite-nitrate in SF of patients with OA indicated its involvement in the disease progression. When SF groups were compared, a significant correlation among moderate, mild and MT groups was established. To summarize, present data illustrated higher levels of NO, SOD, CAT, DPPH and MDA in early OA in comparison with MT, as a control group. NN had emerged as a prognostic bio marker in knee OA patients, which may act as futuristic targets in OA treatment.

Keywords: antioxidant, knee osteoarthritis, oxidative stress, synovial fluid

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