Search results for: step load perturbations

Authors: V. Bastian Aguila, C. Diego Vasco, P. Paula Galvez, R. Paula Zapata

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The main results of an experimental study of the effect of temperature and nanoparticle concentration on thermal conductivity and viscosity of a nanofluid are shown. The nanofluid was made by using octadecane as a base fluid and CuO spherical nanoparticles of 75 nm (MkNano). Since the base fluid is a phase change material (PCM) to be used in thermal storage applications, the engineered nanofluid is referred as nanoPCM. Three nanoPCM were prepared through the two-step method (2.5, 5.0 and 10.0%wv). In order to increase the stability of the nanoPCM, the surface of the CuO nanoparticles was modified with sodium oleate, and it was verified by IR analysis. The modified CuO nanoparticles were dispersed by using an ultrasonic horn (Hielscher UP50H) during one hour (amplitude of 180 μm at 50 W). The thermal conductivity was measured by using a thermal properties analyzer (KD2-Pro) in the temperature range of 30ºC to 40ºC. The viscosity was measured by using a Brookfield DV2T-LV viscosimeter to 30 RPM in the temperature range of 30ºC to 55ºC. The obtained results for the nanoPCM showed that thermal conductivity is almost constant in the analyzed temperature range, and the viscosity decreases non-linearly with temperature. Respect to the effect of the nanoparticle concentration, both thermal conductivity and viscosity increased with nanoparticle concentration. The thermal conductivity raised up to 9% respect to the base fluid, and the viscosity increases up to 60%, in both cases for the higher concentration. Finally, the viscosity measurements for different rotation speeds (30 RPM - 80 RPM) exhibited that the addition of nanoparticles modifies the rheological behavior of the base fluid, from a Newtonian to a viscoplastic (Bingham) or shear thinning (power-law) non-Newtonian behavior.

Keywords: NanoPCM, thermal conductivity, viscosity, non-Newtonian fluid

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Authors: Abobaker Mohammed Qasem Farhan, Shangming Yang, Mohammed Al-Nehari

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Pneumonia is a kind of lung disease that creates congestion in the chest. Such pneumonic conditions lead to loss of life of the severity of high congestion. Pneumonic lung disease is caused by viral pneumonia, bacterial pneumonia, or Covidi-19 induced pneumonia. The early prediction and classification of such lung diseases help to reduce the mortality rate. We propose the automatic Computer-Aided Diagnosis (CAD) system in this paper using the deep learning approach. The proposed CAD system takes input from raw computerized tomography (CT) scans of the patient's chest and automatically predicts disease classification. We designed the Hybrid Deep Learning Algorithm (HDLA) to improve accuracy and reduce processing requirements. The raw CT scans have pre-processed first to enhance their quality for further analysis. We then applied a hybrid model that consists of automatic feature extraction and classification. We propose the robust 2D Convolutional Neural Network (CNN) model to extract the automatic features from the pre-processed CT image. This CNN model assures feature learning with extremely effective 1D feature extraction for each input CT image. The outcome of the 2D CNN model is then normalized using the Min-Max technique. The second step of the proposed hybrid model is related to training and classification using different classifiers. The simulation outcomes using the publically available dataset prove the robustness and efficiency of the proposed model compared to state-of-art algorithms.

Keywords: CT scan, Covid-19, deep learning, image processing, lung disease classification

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Authors: Gehan F. Abdel Raoof, Ataa A. Said, Khaled Y. Mohamed, Hala M. Mohammed

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Pleiogynium timorense(DC.) Leenh is one of the therapeutically active plants belonging to the family Anacardiaceae. The bark of Pleiogynium timorense needs further studies to investigate its phytochemical and biological activities. This work was carried out to investigate the chemical composition of petroleum ether extract of Pleiogynium timorense bark as well as to evaluate the analgesic and anti-inflammatory activities. The unsaponifiable matter and fatty acid methyl esters were analyzed by Gas chromatography–mass spectrometry (GC-MS). Moreover, analgesic and anti-inflammatory activities were evaluated using acetic acid-induced writhing test and carrageen hind paw oedema models in rats, respectively. The results showed that twenty one compounds in the unsaponifiable fraction were identified representing 92.54 % of the total beak area, the major compounds were 1-Heptene (35.32%), Butylated hydroxy toluene (19.42%) and phytol (12.53%), whereas fifteen compounds were identified in the fatty acid methyl esters fraction representing 94.15% of the total identified peak area. The major compounds were 9-Octadecenoic acid methyl ester (35.34%) and 9,12-Octadecadienoic acid methyl ester (29.32%). Moreover, petroleum ether extract showed a significant reduction in pain and inflammation in a dose dependent manner. This study aims to be the first step toward the use of petroleum ether extract of Pleiogynium timorense bark as analgesic and anti-inflammatory drug.

Keywords: analgesic, anti-inflammatory, bark, petroleum ether extract, Pleiogynium timorense

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Authors: Sayan Munshi, Subrajit Banerjee, Indrani Chakraborty

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Tourism is a prime sector in the economic development of many countries in particular the Indian sub-continent. Tourism is considered an integral pillar in the Make in India Program under the Government of India. The statistics of tourism in India had evolved from a past with the formation of History. The sector had shown dynamic changes in the statistics since 1980. With the evolving tourism along with destinations, this sector has been converted into the prime industry, as it not only impacts the destination but on the other hand supports the periphery of the destination. Tourism boost revenue and creates varied economic possibilities for the residents. Due to the influx of tourism in the cities, a load on the infrastructure and services can be observed, specifically in the Physical Infrastructure sectors. Due to the floating population in the designated tourism core of the Urban / Peri-Urban area, issues pertaining to Solid waste management and Transportation are highly observed. Thus, a need for capacity building arises for the infrastructure impacted by tourism, which may result in the upgradation of the lifestyle of the city and its permanent users. As tourism of a region has a dependency on the infrastructure, the paper here focuses on the relationship between tourism potential of a region and the infrastructural determinants of the city or region and hence to derive a structural equation supporting the relationship, further determine a coefficient and suggest the domain of in need of upgradation or retrofitting possibilities. The outcome of the paper is to suggest possible recommendations towards the formation of policies on an urban level to support the tourism potential of the region.

Keywords: urban planning, tourism planning, infrastructure, transportation, solid waste management

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Authors: Yoshinori Wakatake

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Many defects after the release of software packages are caused due to omissions of sufficient test items in test specifications. Poor test specifications are detected by manual review, which imposes a high human load. The prevention of omissions depends on the end-user awareness of test specification writers. If test specifications were written while envisioning the behavior of end-users, the number of omissions in test items would be greatly reduced. The paper pays attention to the point that writers who can achieve it differ from those who cannot in not only the description richness but also their gaze information. It proposes a method to estimate the degree of user-awareness of writers through the analysis of their gaze information when writing test specifications. We conduct an experiment to obtain the gaze information of a writer of the test specifications. Test specifications are automatically classified using gaze information. In this method, a Random Forest model is constructed for the classification. The classification is highly accurate. By looking at the explanatory variables which turn out to be important variables, we know behavioral features to distinguish test specifications of high quality from others. It is confirmed they are pupil diameter size and the number and the duration of blinks. The paper also investigates test specifications automatically classified with gaze information to discuss features in their writing ways in each quality level. The proposed method enables us to automatically classify test specifications. It also prevents test item omissions, because it reveals writing features that test specifications of high quality should satisfy.

Keywords: blink, eye tracking, gaze information, pupil diameter, quality improvement, specification document, user-awareness

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Authors: A. Majczak, G. Baranski, K. Pietrykowski

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Due to the growing popularity of light aircraft, it has become necessary to develop aircraft engines for this type of construction. One of engine system, designed to increase efficiency and reduce weight, is the engine with opposed pistons. In such an engine, the combustion chamber is formed by two pistons moving in one cylinder. Therefore, this type of engines run in a two-stroke cycle, so they have many advantages such as high power and torque, high efficiency, or a favorable power-to-weight ratio. Tests of one of the available aircraft engines with opposing piston system fueled with diesel oil were carried out on an engine dynamometer equipped with an eddy current brake and the necessary measuring and testing equipment. In order to get to know the basic parameters of the engine, the tests were carried out under partial load conditions for the following torque values: 40, 60, 80, 100 Nm. The rotational speed was changed from 1600 to 2500 rpm. Measurements were also taken for designated points of propeller characteristics. During the tests, the engine torque, engine power, fuel consumption, intake manifold pressure, and oil pressure were recorded. On the basis of the measurements carried out for particular loads, the power curve, hourly and specific fuel consumption curves were determined. Characteristics of charge pressure as a function of rotational speed as well as power, torque, hourly and specific fuel consumption curves for propeller characteristics were also prepared. The obtained characteristics make it possible to select the optimal points of engine operation.

Keywords: aircraft, diesel, engine testing, opposed piston

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Authors: Ayobami Adeyemo, Michael Chimonyo, Munyaradzi Marufu

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Gastrointestinal nematode (GNT) infection significantly hinder sustainable and profitable sheep production on rangelands. While vitamin E and protein supplementation have individually proven to improve host immunity to parasitism in lambs, to our knowledge, there is no information on the interaction of dietary vitamin E and protein supplementation on lamb growth and GIN faecal egg counts in naturally infected lambs. Therefore, the current study investigated the interaction of dietary protein and vitamin E supplementation on faecal egg counts (FEC) and growth performance of lambs. Twenty four Dohne Merino lambs aged 12 months were allocated equally to each of four treatment combinations, with six lambs in each treatment group for a period of eight weeks. Treatment one lambs received dietary protein and vitamin E (PE), treatment two lambs received dietary protein and no vitamin E (PNE), treatment three received dietary vitamin E and no protein (NPE), and treatment four received no dietary protein and vitamin E supplementation (NPNE). The lambs were allowed to graze on Pennisetum clandestinum contaminated with a heavy load of nematodes. Dietary protein supplementation increased (P < 0.01) average daily gain (ADG) and body condition scores (BCS). Dietary vitamin E supplementation had no effect (P > 0.05) on ADG and BCS. There was no interaction (P > 0.05) between dietary protein and vitamin E supplementation on ADG and BCS. Combined supplementation of dietary protein and vitamin E supplementation significantly reduced (P < 0.01) faecal egg counts and larval counts, respectively. Also, dietary protein and vitamin E supplementation reduced GNT faecal egg counts over the exposure period. The current findings support the hypothesis that the interaction of dietary protein and vitamin E supplementation reduced faecal egg counts and larval counts in lambs. This necessitates future findings on the interaction of dietary protein and vitamin E supplementation on blood associated profiles.

Keywords: gastrointestinal nematodes, nematode eggs, Haemonchus, Trichostrongylus

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Authors: Xi Gu, Guan Heng Yeoh, Victoria Timchenko

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In the current work, a three-dimensional geometry of a 75% stenosed blood vessel is analysed. Large eddy simulation (LES) with the help of a dynamic subgrid scale Smagorinsky model is applied to model the turbulent pulsatile flow. The geometry, the transmural pressure and the properties of the blood and the elastic boundary were based on clinical measurement data. For the flexible wall model, a thin solid region is constructed around the 75% stenosed blood vessel. The deformation of this solid region was modelled as a deforming boundary to reduce the computational cost of the solid model. Fluid-structure interaction is realised via a two-way coupling between the blood flow modelled via LES and the deforming vessel. The information of the flow pressure and the wall motion was exchanged continually during the cycle by an arbitrary lagrangian-eulerian method. The boundary condition of current time step depended on previous solutions. The fluctuation of the velocity in the post-stenotic region was analysed in the study. The axial velocity at normalised position Z=0.5 shows a negative value near the vessel wall. The displacement of the elastic boundary was concerned in this study. In particular, the wall displacement at the systole and the diastole were compared. The negative displacement at the stenosis indicates a collapse at the maximum velocity and the deceleration phase.

Keywords: Large Eddy Simulation, Fluid Structural Interaction, constricted artery, Computational Fluid Dynamics

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Authors: Oxana Vasilyeva

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This paper draws on research in progress focusing on independent art in the Russian Federation. I am using the concept of independent art to mean art free from state control and established restrictive narratives. The Russian state pursues its interests by supporting or forbidding certain forms of art, and art that promotes values in opposition to the official political course is often forbidden. Arguments presented below draw from fieldwork carried out in Russian cities of Moscow and Saint Petersburg in June – August 2019, which included in-depth interviews with artists. This research explores socially engaged artistic works and their effect on socio-political state of affairs. It argues that artistic works entering public places have a potential to challenge autocratic system and inspire civil society to be critically engaged and to be capable to resist state propaganda. I am focusing on those artists who have a critical stance towards the current Russian political regime and analyzing their works in terms of transgression. By using the framework of transgression I aim to demonstrate how artists step across existing norms with their art influencing political and social order. To show the connection between the factors mentioned above, I will turn to two examples of transgressive aesthetics; one is individual and another is collective. The first example is Konstantin Benkovich, an artist who makes his works out of steel rebar, which is considered to be a symbol of the lack of freedom, as it is usually encountered in prison settings. The second example is a collective art practice called Monstration. It combines techniques of a demonstration and a carnival atmosphere. In 2019 Monstration was held in 30 Russian cities, despite the dissatisfaction of the authorities.

Keywords: art, culture, resistance, Russia

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Authors: Pawit Tangviroon, Apichit Svang-Ariyaskul

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As the limited availability of petroleum-based fuel has been a major concern, biodiesel is one of the most attractive alternative fuels because it is renewable and it also has advantages over the conventional petroleum-base diesel. At Present, productions of biodiesel generally perform by transesterification of vegetable oils with low molecular weight alcohol, mainly methanol, using chemical catalysts. Methanol is petrochemical product that makes biodiesel producing from methanol to be not pure renewable energy source. Therefore, ethanol as a product produced by fermentation processes. It appears as a potential feed stock that makes biodiesel to be pure renewable alternative fuel. The research is conducted based on two biodiesel production processes by reacting soybean oils with methanol and ethanol. Life cycle assessment was carried out in order to evaluate the environmental impacts and to identify the process alternative. Nine mid-point impact categories are investigated. The results indicate that better performance on Abiotic Depletion Potential (ADP) and Acidification Potential (AP) are observed in biodiesel production from methanol when compared with biodiesel production from ethanol due to less energy consumption during the production processes. Except for ADP and AP, using methanol as feed stock does not show any advantages over biodiesel from ethanol. The single score method is also included in this study in order to identify the best option between two processes of biodiesel production. The global normalization and weighting factor based on eco-taxes are used and it shows that producing biodiesel form ethanol has less environmental load compare to biodiesel from methanol.

Keywords: biodiesel, ethanol, life cycle assessment, methanol, soybean oil

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Authors: Avinoam Rabinovich

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CO₂ geological storage is a proven technology for reducing anthropogenic carbon emissions, which is paramount for achieving the ambitious net zero emissions goal. Core flooding experiments are an important step in any CO₂ storage project, allowing us to gain information on the flow of CO₂ and brine in the porous rock extracted from the reservoir. This information is important for understanding basic mechanisms related to CO₂ geological storage as well as for reservoir modeling, which is an integral part of a field project. In this work, a different method for constructing accurate models of CO₂-brine core flooding will be presented. Results for synthetic cases and real experiments will be shown and compared with numerical models to exhibit their predictive capabilities. Furthermore, the various mechanisms which impact the CO₂ distribution and trapping in the rock samples will be discussed, and examples from models and experiments will be provided. The new method entails solving an inverse problem to obtain a three-dimensional permeability distribution which, along with the relative permeability and capillary pressure functions, constitutes a model of the flow experiments. The model is more accurate when data from a number of experiments are combined to solve the inverse problem. This model can then be used to test various other injection flow rates and fluid fractions which have not been tested in experiments. The models can also be used to bridge the gap between small-scale capillary heterogeneity effects (sub-core and core scale) and large-scale (reservoir scale) effects, known as the upscaling problem.

Keywords: CO₂ geological storage, residual trapping, capillary heterogeneity, core flooding, CO₂-brine flow

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Authors: Saveena Bogtapa, Jagbir Singh Kirti

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Himalaya is one of the most fascinating ranges in the world. In India, it comprises 18 percent of the land area. Lahoul valley which is a part of Trans-Himalaya region is well known for its unique, diverse flora and fauna. It lies in the North-Eastern corner of the state Himachal Pradesh where its altitude ranges between 2500m to 5000m. Vegetation of this region is dry-temperate to alpine type. The diversity of the area is very less, rare, unique and highly endemic. But today, as a lot of environmental degradation has taken place in this hot spot of biodiversity because of frequent developmental and commercial activities which lead to the diversity of this area comes under a real threat. Therefore, as part of the research, butterflies which are known for their attractiveness as well as usefulness to the ecosystem, are used for the study. The diversity of butterflies of a particular area not only provides a healthy environment but also serves as the first step of conservation to the biodiversity. Their distribution in different habitats and altitude type helps us to understand the species richness and abundance in an area. Moreover, different environmental parameters which affect the butterfly community has also recorded. Hence, the present study documents the butterfly diversity in an unexplored habitat and altitude types at Lahoul valley. The valley has been surveyed along with altitudinal gradients (from 2500m to 4500m) and in various habitats like agriculture land, grassland, scrubland, riverine and in different types of forests. Very rare species of butterflies have been explored, and these will be discussed along with different parameters during the presentation.

Keywords: butterflies, diversity, Lahoul valley, altitude, vegetation

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Authors: Fazıl Gökgöz, Fahrettin Filiz

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Electricity prices have sophisticated features such as high volatility, nonlinearity and high frequency that make forecasting quite difficult. Electricity price has a volatile and non-random character so that, it is possible to identify the patterns based on the historical data. Intelligent decision-making requires accurate price forecasting for market traders, retailers, and generation companies. So far, many shallow-ANN (artificial neural networks) models have been published in the literature and showed adequate forecasting results. During the last years, neural networks with many hidden layers, which are referred to as DNN (deep neural networks) have been using in the machine learning community. The goal of this study is to investigate electricity price forecasting performance of the shallow-ANN and DNN models for the Turkish day-ahead electricity market. The forecasting accuracy of the models has been evaluated with publicly available data from the Turkish day-ahead electricity market. Both shallow-ANN and DNN approach would give successful result in forecasting problems. Historical load, price and weather temperature data are used as the input variables for the models. The data set includes power consumption measurements gathered between January 2016 and December 2017 with one-hour resolution. In this regard, forecasting studies have been carried out comparatively with shallow-ANN and DNN models for Turkish electricity markets in the related time period. The main contribution of this study is the investigation of different shallow-ANN and DNN models in the field of electricity price forecast. All models are compared regarding their MAE (Mean Absolute Error) and MSE (Mean Square) results. DNN models give better forecasting performance compare to shallow-ANN. Best five MAE results for DNN models are 0.346, 0.372, 0.392, 0,402 and 0.409.

Keywords: deep learning, artificial neural networks, energy price forecasting, turkey

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Authors: S. Muogbo Uju, Akpunonu Uju,

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The prevailing harsh environment factors couple with poverty rate and unemployment propels a high rate of entrepreneurial activities in developing countries of the world. Women entrepreneurs operate within gender bias among other constraint that can constitute a threat or create opportunity for women entrepreneurs. This empirical paper investigates and critically examines women entrepreneurship as an inventive approach to sustainable development in Anambra State. The study used descriptive statistics (frequencies, mean, and percentages) to answer the three research questions posed. Hypotheses testing were done with person product moment correlation and multiple regressions were employed in data analysis. SPSS [statistical package for Social Science] software was used to run the analysis. Three hundred and fifty three (353) copies of questionnaires were administered, and one hundred and forty six (146) copies were returned. Consequently, the findings of this study portrayed a significant impact between women entrepreneurship activities, job creation, wealth creation, youth empowerment, poverty reduction, employment generation, and increase in standard of livings of people. Therefore, the findings prescribe that government should ensure that managerial lessons are accompanied with the skill acquisition programs in order for them to understand the rudiment of owing and sustaining a business. The study also recommends that women entrepreneurs that have overcome the inertia of starting a business should come together to create platforms that can help those women who are yet to take a step or kick-start such venture.

Keywords: women entrepreneurship, skill acquisition, sustainability, wealth creation

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Authors: Hichem Sassi

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Pneumonia, being a respiratory infection, has garnered global attention due to its rapid transmission and relatively high mortality rates. Timely detection and treatment play a crucial role in significantly reducing mortality associated with pneumonia. Presently, X-ray diagnosis stands out as a reasonably effective method. However, the manual scrutiny of a patient's X-ray chest radiograph by a proficient practitioner usually requires 5 to 15 minutes. In situations where cases are concentrated, this places immense pressure on clinicians for timely diagnosis. Relying solely on the visual acumen of imaging doctors proves to be inefficient, particularly given the low speed of manual analysis. Therefore, the integration of artificial intelligence into the clinical image diagnosis of pneumonia becomes imperative. Additionally, AI recognition is notably rapid, with convolutional neural networks (CNNs) demonstrating superior performance compared to human counterparts in image identification tasks. To conduct our study, we utilized a dataset comprising chest X-ray images obtained from Kaggle, encompassing a total of 5216 training images and 624 test images, categorized into two classes: normal and pneumonia. Employing five mainstream network algorithms, we undertook a comprehensive analysis to classify these diseases within the dataset, subsequently comparing the results. The integration of artificial intelligence, particularly through improved network architectures, stands as a transformative step towards more efficient and accurate clinical diagnoses across various medical domains.

Keywords: deep learning, computer vision, pneumonia, models, comparative study

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Authors: Hanifa Taher, Sulaiman Al-Zuhair, Ali H. Al-Marzouqi, Yousef Haik, Mohammed Farid

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Biodiesel, as an alternative renewable fuel, has been receiving increasing attention due to the limited supply of fossil fuels and the increasing need for energy. Microalgae is a promising source for lipids, which can be converted to biodiesel. The biodiesel production from microalgae lipids using lipase catalyzed reaction in supercritical CO2 medium has several advantages over conventional production processes. However, identifying the optimum microalgae lipid extraction and transesterification conditions is still a challenge. In this study, the lipids extracted from Scenedesmus sp. and their enzymatic transesterification using supercritical carbon dioxide have been investigated. The effect of extraction variables (temperature, pressure and solvent flow rate) and reaction variables (enzyme loading, incubation time, methanol to lipids molar ratio and temperature) were considered. Process parameters and their effects were studied using a full factorial analysis of both. Response Surface Methodology (RSM) and was used to determine the optimum conditions for the extraction and reaction steps. For extraction, the optimum conditions were 53 °C and 500 bar, whereas for the reaction the optimum conditions were 35% enzyme loading, 4 h reaction, 9:1 molar ratio and 50 oC. At these optimum conditions, the highest biodiesel production yield was found to be 82 %. The fuel properties of the produced biodiesel, at optimum reaction condition, were determined and compared to ASTM standards. The properties were found to comply with the limits, and showed a low glycerol content, without any separation step.

Keywords: biodiesel, lipase, supercritical CO2, standards

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Authors: Arnaldo G. de Oliveira, Jr, Matthieu Tubino

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The transesterification process of triglycerides with alcohols that occurs during the biodiesel synthesis causes continuous changes in several physical properties of the reaction mixture, such as refractive index, viscosity and density. Amongst them, density can be an useful parameter to monitor the reaction, in order to predict the composition of the reacting mixture and to verify the conversion of the oil into biodiesel. In this context, a system was constructed in order to continuously determine changes in the density of the reacting mixture containing soybean oil, methanol and sodium methoxide (30 % w/w solution in methanol), stirred at 620 rpm at room temperature (about 27 °C). A polyethylene pipe network connected to a peristaltic pump was used in order to collect the mixture and pump it through a coil fixed on the plate of an analytical balance. The collected mass values were used to trace a curve correlating the mass of the system to the reaction time. The density variation profile versus the time clearly shows three different steps: 1) the dispersion of methanol in oil causes a decrease in the system mass due to the lower alcohol density followed by stabilization; 2) the addition of the catalyst (sodium methoxide) causes a larger decrease in mass compared to the first step (dispersion of methanol in oil) because of the oil conversion into biodiesel; 3) the final stabilization, denoting the end of the reaction. This density variation profile provides information that was used to predict the composition of the mixture over the time and the reaction rate. The precise knowledge of the duration of the synthesis means saving time and resources on a scale production system. This kind of monitoring provides several interesting features such as continuous measurements without collecting aliquots.

Keywords: biodiesel, density measurements, online continuous monitoring, synthesis

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Authors: Robin Molinier

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Industrial symbiosis (I.S) is the realization of Industrial Ecology (I.E) principles in production systems in function. I.S consists in the use of waste materials, fatal energy, recirculated utilities and infrastructure/service sharing as resources for production. Environmental benefits can be achieved from resource conservation but economic profitability is required by the participating actors. I.S indeed involves several actors with their own objectives and resources so that each one must be satisfied by ex-ante arrangements to commit toward I.S execution (investments and transactions). Following the Resource-Based View of transactions we build a modular framework to assess global I.S profitability and to specify each actor’s contributions to costs and benefits in line with their resource endowments and performance requirements formulations. I.S projects specificities implied by the need for customization (asset specificity, non-homogeneity) induce the use of long-term contracts for transactions following Transaction costs economics arguments. Thus we propose first a taxonomy of costs and value drivers for I.S and an assignment to each actor of I.S specific risks that we identified as load profiles mismatch, quality problems and value fluctuations. Then appropriate contractual guidelines (pricing, cost sharing and warranties) that support mutual profitability are derived from the detailed identification of contributions by the cost-benefits model. This analytical framework helps identifying what points to focus on when bargaining over contracting for transactions and investments. Our methodology is applied to I.S archetypes raised from a literature survey on eco-industrial parks initiatives and practitioners interviews.

Keywords: contracts, cost-benefit analysis, industrial symbiosis, risks

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Authors: Farhad Salek, Shahaboddin Resalati

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The production of electric vehicles (EVs) featuring lithium-ion battery technology has substantially escalated over the past decade, demonstrating a steady and persistent upward trajectory. The imminent retirement of electric vehicle (EV) batteries after approximately eight years underscores the critical need for their redirection towards recycling, a task complicated by the current inadequacy of recycling infrastructures globally. A potential solution for such concerns involves extending the operational lifespan of electric vehicle (EV) batteries through their utilization in stationary energy storage systems during secondary applications. Such adoptions, however, require addressing the safety concerns associated with batteries’ knee points and thermal runaways. This paper develops an accurate mathematical model representative of the second-life battery packs from a cell-to-pack scale using an equivalent circuit model (ECM) methodology. Neural network algorithms are employed to forecast the degradation parameters based on the EV batteries' aging history to develop a degradation model. The degradation model is integrated with the ECM to reflect the impacts of the cycle aging mechanism on battery parameters during operation. The developed model is tested under real-life load profiles to evaluate the life span of the batteries in various operating conditions. The methodology and the algorithms introduced in this paper can be considered the basis for Battery Management System (BMS) design and techno-economic analysis of such technologies.

Keywords: second life battery, electric vehicles, degradation, neural network

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Authors: Seyed Mohamad Rasool Mirkarimi, David Chiaramonti, Samir Bensaid

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Catalytic methane decomposition (CMD, reaction 4) is a one-step process for hydrogen production where carbon in the methane molecule is sequestered in the form of stable and higher-value carbon materials. Metallic catalysts and carbon-based catalysts are two major types of catalysts utilized for the CDM process. Although carbon-based catalysts have lower activity compared to metallic ones, they are less expensive and offer high thermal stability and strong resistance to chemical impurities such as sulfur. Also, it would require less costly separation methods as some of the carbon-based catalysts may not have an active metal component in them. Since the regeneration of metallic catalysts requires burning of the C on their surfaces, which emits CO/CO2, in some cases, using carbon-based catalysts would be recommended because regeneration can be completely avoided, and the catalyst can be directly used in other processes. This work focuses on the effect of biochar as a carbon-based catalyst for the conversion of methane into hydrogen and carbon. Biochar produced from the pyrolysis of poplar wood and activated biochar are used as catalysts for this process. In order to observe the impact of carbon-based catalysts on methane conversion, methane cracking in the absence and presence of catalysts for a gas stream with different levels of methane concentration should be performed. The results of these experiments prove conversion of methane in the absence of catalysts at 900 °C is negligible, whereas in the presence of biochar and activated biochar, significant growth has been observed. Comparing the results of the tests related to using char and activated char shows the enhancement obtained in BET surface area of the catalyst through activation leads to more than 10 vol.% methane conversion.

Keywords: hydrogen production, catalytic methane decomposition, biochar, activated biochar, carbon-based catalyts

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Authors: A. Ameur Ameur, H. Boukherrouba

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In red meat slaughterhouses a significant number of organs and carcasses were seized because of the presence of lesions of various origins. The objective of this study is to characterize and evaluate the frequency of these lesions in the slaughterhouse of the Wilaya of BOUIRA. On cattle slaughtered in 2646 and inspected 72% of these carcasses have been no seizures against 28% who have undergone at least one entry. 325 lung (44%), 164 livers (22%), 149 hearts (21%) are the main saisis.38 kidneys members (5%), 33 breasts (4%) and 16 whole carcasses (2%) are less seizures parties. The main reasons are the input hydatid cyst for most seized organs such as the lungs (64.5%), livers (51.8%), hearts (23.2%), hydronephrosis for the kidneys (39.4%), and chronic mastitis (54%) for the breasts. Then we recorded second-degree pneumonia (16%) to the lungs, chronic fascioliasis (25%) for livers. A significant difference was observed (p < 0.0001) by sex, race, origin and age of all cattle having been saisie.une a specific input patterns and So pathology was recorded based on race. The local breed presented (75.2%) of hydatid cyst, (95%) and chronic fascioliasis (60%) pyelonephritis, for against the improved breed presented the entire respiratory lesions include pneumonia (64%) the chronic tuberculosis (64%) and mastitis (76%). These results are an important step in the implementation of the concept of risk assessment as the scientific basis of food legislation, by the identification and characterization of macroscopic damage leading withdrawals in meat and to establish the level of inclusion of these injuries within the recommended risk assessment systems (HACCP).

Keywords: slaughterhouses, meat safety, seizure patterns, HACCP

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Authors: Erin Curtis, Avraham Schwiger

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Neuropsychological testing and evaluation is a crucial step in providing patients with effective diagnoses and treatment while in clinical care. The variety of batteries used in these evaluations can help clinicians better understand the nuanced declivities in a patient’s cognitive, behavioral, or emotional functioning, consequently equipping clinicians with the insights to make intentional choices about a patient’s care. Despite the knowledge these batteries can yield, some aspects of neuropsychological testing remain largely inaccessible to certain patient groups as a result of fundamental cultural, educational, or social differences. One such battery includes the Dot Counting Test (DCT), during which patients are required to count a series of dots on a page as rapidly and accurately as possible. As the battery progresses, the dots appear in clusters that are designed to be easily multiplied. This task evaluates a patient’s cognitive functioning, attention, and level of effort exerted on the evaluation as a whole. However, there is evidence to suggest that certain social groups, particularly Latinx groups, may perform worse on this task as a result of cultural or educational differences, not reduced cognitive functioning or effort. As such, this battery fails to account for baseline differences among patient groups, thus creating questions surrounding the accuracy, generalizability, and value of its results. Accessibility and cultural sensitivity are critical considerations in the testing and treatment of marginalized groups, yet have been largely ignored in the literature and in clinical settings to date. Implications and improvements to applications are discussed.

Keywords: culture, latino, neuropsychological assessment, neuropsychology, accessibility

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Authors: Harvard Najoan, Sarwono Sutikno, Yusep Rosmansyah

Abstract:

Most enterprises are now using information technology services as their assets to support business objectives. These kinds of services are provided by the internal service provider (inside the enterprise) or external service provider (outside enterprise). To deliver quality information technology services, the service provider (which from now on will be called ‘organization’) either internal or external, must have a standard for service management system. At present, the standard that is recognized as best practice for service management system for the organization is international standard ISO/IEC 20000:2011. The most important part of this international standard is the first part or ISO/IEC 20000-1:2011-Service Management System Requirement, because it contains 22 for organization processes as a requirement to be implemented in an organizational environment in order to build, manage and deliver quality service to the customer. Assessing organization management processes is the first step to implementing ISO/IEC 20000:2011 into the organization management processes. This assessment needs Process Assessment Model (PAM) as an assessment instrument. PAM comprises two parts: Process Reference Model (PRM) and Measurement Framework (MF). PRM is built by transforming the 22 process of ISO/IEC 20000-1:2011 and MF is based on ISO/IEC 33020. This assessment instrument was designed to assess the capability of service management process in Divisi Teknologi dan Sistem Informasi (Information Systems and Technology Division) as an internal organization of PT Pos Indonesia. The result of this assessment model can be proposed to improve the capability of service management system.

Keywords: ISO/IEC 20000-1:2011, ISO/IEC 33020:2015, process assessment, process capability, service management system

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Authors: Iram Zahra

Abstract:

Friction and wear properties of multilayer graphene coatings (MLG) on nickel substrate were investigated at the macroscale, and different failure mechanisms working at the interface of nickel-graphene coatings were evaluated. Multilayer graphene coatings were produced on a nickel substrate using the atmospheric chemical vapour deposition (CVD) technique. Wear tests were performed on the pin-on-disk tribometer apparatus under dry air conditions, and using the saltwater solution, distilled water, and mineral oil lubricants and counterparts used in these wear tests were fabricated of stainless steel, chromium, and silicon nitride. The wear test parameters such as rotational speed, wear track diameter, temperature, relative humidity, and load were 60 rpm, 6 mm, 22˚C, 45%, and 2N, respectively. To analyse the friction and wear behaviour, coefficient of friction (COF) vs time curves were plotted, and the sliding surfaces of the samples and counterparts were examined using the optical microscope. Results indicated that graphene-coated nickel in mineral oil lubrication and dry conditions gave the minimum average value of COP (0.05) and wear track width ( ̴151 µm) against the three different types of counterparts. In contrast, uncoated nickel samples indicated a maximum wear track width ( ̴411 µm) and COF (0.5). Thorough investigation and analysis concluded that graphene-coated samples have two times lower COF and three times lower wear than the bare nickel samples. Furthermore, mechanical failures were significantly lower in the case of graphene-coated nickel. The overall findings suggested that multilayer graphene coatings have drastically decreased wear and friction on nickel substrate at the macroscale under various lubricating conditions and against different counterparts.

Keywords: friction, lubricity, multilayer graphene, sliding, wear

Procedia PDF Downloads 126

Authors: Yu-ding Du, Qi-lian Bao, Nassim Bessaad, Lin Liu

Abstract:

The Global Navigation Satellite System (GNSS) is regarded as an effective approach for the purpose of replacing the large amount used track-side balises in modern train localization systems. This paper describes a method based on the data fusion of a GNSS receiver sensor and an odometer sensor that can significantly improve the positioning accuracy. A digital track map is needed as another sensor to project two-dimensional GNSS position to one-dimensional along-track distance due to the fact that the train’s position can only be constrained on the track. A model trained by BP neural network is used to estimate the trend positioning error which is related to the specific location and proximate processing of the digital track map. Considering that in some conditions the satellite signal failure will lead to the increase of GNSS positioning error, a detection step for GNSS signal is applied. An adaptive weighted fusion algorithm is presented to reduce the standard deviation of train speed measurement. Finally an Extended Kalman Filter (EKF) is used for the fusion of the projected 1-D GNSS positioning data and the 1-D train speed data to get the estimate position. Experimental results suggest that the proposed method performs well, which can reduce positioning error notably.

Keywords: multi-sensor data fusion, train positioning, GNSS, odometer, digital track map, map matching, BP neural network, adaptive weighted fusion, Kalman filter

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Authors: Bhaven N. Tandel, Athira Rajeev

Abstract:

Sequencing batch reactor process is a suspended growth process operating under non-steady state conditions which utilizes a fill and draw reactor with complete mixing during the batch reaction step (after filling) and where the subsequent steps of aeration and clarification occur in the same tank. All sequencing batch reactor systems have five steps in common, which are carried out in sequence as follows, (1) fill (2) react (3) settle (sedimentation/clarification) (4) draw (decant) and (5) idle. The study was carried out in a sequencing batch reactor of dimensions 44cmx30cmx70cm with a working volume of 40 L. Mechanical stirrer of 100 rpm was used to provide continuous mixing in the react period and oxygen was supplied by fish tank aerators. The duration of a complete cycle of sequencing batch reactor was 8 hours. The cycle period was divided into different phases in sequence as follows-0.25 hours fill phase, 6 hours react period, 1 hour settling phase, 0.5 hours decant period and 0.25 hours idle phase. The study consisted of two runs, run 1 and run 2. Run 1 consisted of 6 hours aerobic react period and run 2 consisted of 3 hours aerobic react period followed by 3 hours anoxic react period. The influent wastewater used for the study had COD, BOD, NH3-N and TKN concentrations of 308.03±48.94 mg/L, 100.36±22.05 mg/L, 14.12±1.18 mg/L, and 24.72±2.21 mg/L respectively. Run 1 had an average COD removal efficiency of 41.28%, BOD removal efficiency of 56.25%, NH3-N removal efficiency of 86.19% and TKN removal efficiency of 54.4%. Run 2 had an average COD removal efficiency of 63.19%, BOD removal efficiency of 73.85%, NH3-N removal efficiency of 90.74% and TKN removal efficiency of 65.25%. It was observed that run 2 gave better performance than run 1 in the removal of COD, BOD and TKN.

Keywords: municipal waste water, aerobic, anoxic, sequencing batch reactor

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Authors: Gintarė Sauliutė, Gintaras Svecevičius

Abstract:

Landfill leachates contain a number of persistent pollutants, including heavy metals. They have the ability to spread in ecosystems and accumulate in fish which most of them are classified as top-consumers of trophic chains. Fish are freely swimming organisms; but perhaps, due to their species-specific ecological and behavioral properties, they often prefer the most suitable biotopes and therefore, did not avoid harmful substances or environments. That is why it is necessary to evaluate the persistent pollutant dispersion in hydroecosystem using fish tissue metal concentration. In hydroecosystems of hybrid type (e.g. river-pond-river) the distance from the pollution source could be a perfect indicator of such a kind of metal distribution. The studies were carried out in the Kairiai landfill neighboring hybrid-type ecosystem which is located 5 km east of the Šiauliai City. Fish tissue (gills, liver, and muscle) metal concentration measurements were performed on two types of ecologically-different fishes according to their feeding characteristics: benthophagous (Gibel carp, roach) and predatory (Northern pike, perch). A number of mathematical models (linear, non-linear, using log and other transformations) have been applied in order to identify the most satisfactorily description of the interdependence between fish tissue metal concentration and the distance from the pollution source. However, the only one log-multiple regression model revealed the pattern that the distance from the pollution source is closely and positively correlated with metal concentration in all predatory fish tissues studied (gills, liver, and muscle).

Keywords: bioaccumulation in fish, heavy metals, hydroecosystem, landfill leachate, mathematical model

Procedia PDF Downloads 276

Authors: Li Lin Ong, Duc Thinh Khong, Zaher M. A. Judeh

Abstract:

Phenylpropanoid sucrose esters (PSEs) are natural compounds found in various medicinal plants which exhibit important biological activities such as antiproliferation and α- and β-glucosidase inhibitory activities. Despite their potential as new therapeutics, total synthesis of PSEs has been very limited as their inherent structures contain one or more (substituted) cinnamoyl groups randomly allocated on the sucrose core via ester linkage. Since direct acylation of unprotected sucrose would be complex and tedious due to the presence of eight free hydroxyl groups, partially protected 2,1’:4,6-di-O-diisopropylidene sucrose was used as the starting material instead. However, similar reactivity between the remaining four hydroxyl groups still pose a challenge in the total synthesis of PSEs as the lack of selectivity can restrict customisation where acylation at specific OH is desired. To overcome this problem, a 4-step orthogonal protection scheme was developed. In this scheme, the remaining four hydroxyl groups on 2,1’:4,6-di-O-diisopropylidene sucrose, 6’-OH, 3’-OH, 4’-OH, and 3-OH, were protected with different protecting groups with an overall yield of > 40%. This orthogonally protected intermediate would provide a convenient and divergent access to a wider range of natural and synthetic PSEs as (substituted) cinnamoyl groups can be selectively introduced at desired positions. Using this scheme, three different series of monosubstituted PSEs were successfully synthesized where (substituted) cinnamoyl groups were introduced selectively at O-3, O-3’, and O-4’ positions, respectively. The expanded library of PSEs would aid in structural-activity relationship study of PSEs for identifying key components responsible for their biological activities.

Keywords: orthogonal protection, phenylpropanoid sucrose esters, selectivity, sucrose

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Authors: Sheikh Shams Azam, Manoj Raju, Venkatesh Pagidimarri, Vamsi Kasivajjala

Abstract:

Over the past decade, there has been a steep rise in the data-driven analysis in major areas of medicine, such as clinical decision support system, survival analysis, patient similarity analysis, image analytics etc. Most of the data in the field are well-structured and available in numerical or categorical formats which can be used for experiments directly. But on the opposite end of the spectrum, there exists a wide expanse of data that is intractable for direct analysis owing to its unstructured nature which can be found in the form of discharge summaries, clinical notes, procedural notes which are in human written narrative format and neither have any relational model nor any standard grammatical structure. An important step in the utilization of these texts for such studies is to transform and process the data to retrieve structured information from the haystack of irrelevant data using information retrieval and data mining techniques. To address this problem, the authors present Q-Map in this paper, which is a simple yet robust system that can sift through massive datasets with unregulated formats to retrieve structured information aggressively and efficiently. It is backed by an effective mining technique which is based on a string matching algorithm that is indexed on curated knowledge sources, that is both fast and configurable. The authors also briefly examine its comparative performance with MetaMap, one of the most reputed tools for medical concepts retrieval and present the advantages the former displays over the latter.

Keywords: information retrieval, unified medical language system, syntax based analysis, natural language processing, medical informatics

Procedia PDF Downloads 118

Authors: Wei Wang, Martin Chen

Abstract:

The reconstitution behaviours of nutritional products could impact user experience. Reconstitution issues such as lump formation and white flecks sticking to bottles surfaces could be very unappealing for the consumers in milk preparation. The controlling steps in dissolving instant milk powders include wetting, swelling, sinking, dispersing, and dissolution as in the literature. Each stage happens simultaneously with the others during milk preparation, and it is challenging to isolate and measure each step individually. This study characterized three adult nutritional products for different properties including particle size, density, dispersibility, stickiness, and capillary wetting to understand the relationship between powder physical properties and their reconstitution behaviours. From the results, the formation of clumps can be caused by different factors limiting the critical steps of powder reconstitution. It can be caused by small particle size distribution, light particle density limiting powder wetting, or the rapid swelling and dissolving of particle surface materials to impede water penetration in the capillary channels formed by powder agglomerates. For the grain or white flecks formation in milk preparation, it was believed to be controlled by dissolution speed of the particles after dispersion into water. By understanding those relationship between fundamental powder structure and their user experience in reconstitution, this information provides us new and multiple perspectives on how to improve the powder characteristics in the commercial manufacturing.

Keywords: characterization, dairy nutritional powder, physical property, reconstitution

Procedia PDF Downloads 93