Search results for: demand estimate

Authors: Tariq Ahmad Dar, Moinuddin, M. Masroor A. Khan

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There is considerable need in enhancing the content and yield of active constituents of medicinal plants keeping in view their massive demand worldwide. Different strategies have been employed to enhance the active constituents of medicinal plants and the use of phytohormones has been proved effective in this regard. Gamma-irradiated Sodium alginate (ISA) is known to elicit an array of plant defense responses and biological activities in plants. Considering the medicinal importance, a pot experiment was conducted to explore the effect of ISA and phosphorus on growth, yield and quality of fenugreek (Trigonella foenum-graecum L.). ISA spray treatments (0, 40, 80 and 120 mg L-1) were applied alone and in combination with 40 kg P ha-1 (P40). Crop performance was assessed in terms of plant growth characteristics, physiological attributes, seed yield and the content of seed trigonelline. Of the ten-treatments, P40 + 80 mg L−1 of ISA proved the best. The results showed that foliar spray of ISA alone or in combination with P40 augmented the plant vegetative growth, enzymatic activities, trigonelline content, trigonelline yield and economic yield of fenugreek. Application of 80 mg L−1 of ISA applied with P40 gave the best results for almost all the parameters studied compared to control or to 80 mg L−1 of ISA applied alone. This treatment increased the total content of chlorophyll, carotenoids, leaf -N, -P and -K and trigonelline compared to the control by 24.85 and 27.40%, 15 and 23.52%, 18.70 and 16.84%, 15.88 and 18.92%, 12 and 14.44%, at 60 and 90 DAS respectively. The combined application of 80 mg L−1 of ISA along with P40 resulted in the maximum increase in seed yield, trigonelline content and trigonelline yield by146, 34 and 232.41%, respectively, over the control. Gel permeation chromatography revealed the formation of low molecular weight fractions in ISA samples, containing even less than 20,000 molecular weight oligomers, which might be responsible for plant growth promotion in this study. Trigonelline content was determined by reverse phase high performance liquid chromatography (HPLC) with C-18 column.

Keywords: gamma-irradiated sodium alginate, phosphorus, gel permeation chromatography, HPLC, trigonelline content, yield

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Authors: Sipho Mbatha, Anne Mastament-Mason

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South African manufacturing global competitiveness was ranked 22nd (out of 38 countries), dropped to 24th in 2013 and is expected to drop further to 25th by 2018. These impacts negatively on the industrialisation project of South Africa. For industrialization to be achieved through labour intensive industries like the Apparel Manufacturing Industries of South Africa (AMISA), South Africa needs to identify and respond to factors negatively impacting on the development of competitive advantage This paper applied factor conditions from Porter’s Diamond Model (1990) to understand the various challenges facing the AMISA. Factor conditions highlighted in Porter’s model are grouped into two groups namely, basic and advance factors. Two AMISA associations representing over 10 000 employees were interviewed. The largest Clothing, Textiles and Leather (CTL) apparel retail group was also interviewed with a government department implementing the industrialisation policy were interviewed The paper points out that while AMISA have basic factor conditions necessary for competitive advantage in the clothing and textiles industries, Advance factor coordination has proven to be a challenging task for the AMISA, Higher Education Institutions (HEIs) and government. Poor infrastructural maintenance has contributed to high manufacturing costs and poor quick response as a result of lack of advanced technologies. The use of Porter’s Factor Conditions as a tool to analyse the sector’s competitive advantage challenges and opportunities has increased knowledge regarding factors that limit the AMISA’s competitiveness. It is therefore argued that other studies on Porter’s Diamond model factors like Demand conditions, Firm strategy, structure and rivalry and Related and supporting industries can be used to analyse the situation of the AMISA for the purposes of improving competitive advantage.

Keywords: compliance rule, apparel manufacturing industry, factor conditions, advance skills and South African industrial policy

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Authors: Monika Foltyn-Zarychta

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Climate change mitigation investment activities are inevitably extended in time extremely. The project cycle does not last for decades – sometimes it stretches out for hundreds of years and the project outcomes impact several generations. The longevity of those activities raises multiple problems in the appraisal procedure. One of the pivotal issues is the choice of the discount rate, which affect tremendously the net present value criterion. The paper aims at estimating the value of social discount rate for intergenerational investment projects in Poland based on individual intertemporal preferences. The analysis is based on questionnaire surveying Polish citizens and designed as contingent valuation method. The analysis aimed at answering two questions: 1) whether the value of the individual discount rate decline with increased time of delay, and 2) whether the value of the individual discount rate changes with increased spatial distance toward the gainers of the project. The valuation questions were designed to identify respondent’s indifference point between lives saved today and in the future due to hypothetical project mitigating climate changes. Several project effects’ delays (of 10, 30, 90 and 150 years) were used to test the decline in value with time. The variability in regard to distance was tested by asking respondents to estimate their indifference point separately for gainers in Poland and in Latvia. The results show that as the time delay increases, the average discount rate value decreases from 15,32% for 10-year delay to 2,75% for 150-year delay. Similar values were estimated for Latvian beneficiaries. There should be also noticed that the average volatility measured by standard deviation also decreased with time delay. However, the results did not show any statistically significant difference in discount rate values for Polish and Latvian gainers. The results showing the decline of the discount rate with time prove the possible economic efficiency of the intergenerational effect of climate change mitigation projects and may induce the assumption of the altruistic behavior of present generation toward future people. Furthermore, it can be backed up by the same discount rate level declared by Polish for distant in space Latvian gainers. The climate change activities usually need significant outlays and the payback period is extremely long. The more precise the variables in the appraisal are, the more trustworthy and rational the investment decision is. The discount rate estimations for Poland add to the vivid discussion concerning the issue of climate change and intergenerational justice.

Keywords: climate change, social discount rate, investment appraisal, intergenerational justice

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Authors: Pelin Yılmaz Çetiner, Metin Mert İlgün, Nazlı Çetindağ, Emine Birci, Gizemnur Yıldız Uysal, Özcan Hatipoğlu, Ehsan Tuzcuoğlu, Gökhan Sır

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Water scarcity is an inevitable problem affecting more and more people day by day. It is a worldwide crisis and a consequence of rapid population growth, urbanization and overexploitation. Thus, the solutions providing the reclamation of the wastewater are the desired approach. Wastewater contains various substances such as organic, soaps and detergents, solvents, biological substances, and inorganic substances. The physical properties of the wastewater differs regarding to its origin such as commerical, domestic or hospital usage. Thus, the treatment strategy of this type of wastewater is should be comprehensively investigated and properly treated. The advanced oxidation process comes up as a hopeful method associated with the formation of reactive hydroxyl radicals that are highly reactive to oxidize of organic pollutants. This process has a priority on other methods such as coagulation, flocuation, sedimentation and filtration since it was not cause any undesirable by-products. In the present study, it was aimed to investigate the applicability of advanced oxidation process for the treatment of household appliances wastewater. For this purpose, the laboratory studies providing the effectively addressing of the formed radicals to organic pollutants were carried out. Then the effect of process parameters were comprehensively studied by using response surface methodology, Box-Benhken experimental desing. The final chemical oxygen demand (COD) was the main output to evaluate the optimum point providing the expected COD removal. The linear alkyl benzene sulfonate (LAS), total dissolved solids (TDS) and color were measured for the optimum point providing the expected COD removal. Finally, present study pointed out that advanced oxidation process might be efficiently preffered to treat of the household appliances wastewater and the optimum process parameters provided that expected removal of COD.

Keywords: advanced oxidation process, household appliances wastewater, modelling, water reuse

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Authors: Tessa Sellis, Marike A. Wierda, Elke Tichelman, Mirjam T. Van Lohuizen, Marjolein Berger, François Schellevis, Claudi Bockting, Lilian Peters, Huib Burger

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Introduction: Most women develop a healthy bond with their children, however, adequate mother-to-infant bonding cannot be taken for granted. Mother-to-infant bonding refers to the feelings and emotions experienced by the mother towards her child. It is an ongoing process that starts during pregnancy and develops during the first year postpartum and likely throughout early childhood. The prevalence of inadequate bonding ranges from 7 to 11% in the first weeks postpartum. An impaired mother-to-infant bond can cause long-term complications for both mother and child. Very little research has been conducted on the direct relationship between the personality of the mother and mother-to-infant bonding. This study explores the associations between maternal personality and postnatal mother-to-infant bonding. The main hypothesis is that there is a relationship between neuroticism and mother-to-infant bonding. Methods: Data for this study were used from the Pregnancy Anxiety and Depression Study (2010-2014), which examined symptoms of and risk factors for anxiety or depression during pregnancy and the first year postpartum of 6220 pregnant women who received primary, secondary or tertiary care in the Netherlands. The study was expanded in 2015 to investigate postnatal mother-to-infant bonding. For the current research 3836 participants were included. During the first trimester of gestation, baseline characteristics, as well as personality, were measured through online questionnaires. Personality was measured by the NEO Five Factor Inventory (NEO-FFI), which covers the big five of personality (neuroticism, extraversion, openness, altruism and conscientiousness). Mother-to-infant bonding was measured postpartum by the Postpartum Bonding Questionnaire (PBQ). Univariate linear regression analysis was performed to estimate the associations. Results: 5% of the PBQ-respondents reported impaired bonding. A statistically significant association was found between neuroticism and mother-to-infant bonding (p < .001): mothers scoring higher on neuroticism, reported a lower score on mother-to-infant bonding. In addition, a positive correlation was found between the personality traits extraversion (b: -.081), openness (b: -.014), altruism (b: -.067), conscientiousness (b: -.060) and mother-to-infant bonding. Discussion: This study is one of the first to demonstrate a direct association between the personality of the mother and mother-to-infant bonding. A statistically significant relationship has been found between neuroticism and mother-to-infant bonding, however, the percentage of variance predictable by a personality dimension is very small. This study has examined one part of the multi-factorial topic of mother-to-infant bonding and offers more insight into the rarely investigated and complex matter of mother-to-infant bonding. For midwives, it is important recognize the risks for impaired bonding and subsequently improve policy for women at risk.

Keywords: mother-to-infant bonding, personality, postpartum, pregnancy

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Authors: Mirian Graciella Dalla Porta, Humberto Jorge José, Danielle de Bem Luiz, Regina de F. P. M.Moreira

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Similar to most processing industries, fish processing produces large volumes of wastewater, which contains especially organic contaminants, salts and oils dispersed therein. Different processes have been used for the treatment of fishery wastewaters, but the most commonly used are chemical coagulation and flotation. These techniques are well known but sometimes the characteristics of the treated effluent do not comply with legal standards for discharge. Electrocoagulation (EC) is an electrochemical process that can be used to treat wastewaters in terms of both organic matter and nutrient removal. The process is based on the use of sacrificial electrodes such as aluminum, iron or zinc, that are oxidized to produce metal ions that can be used to coagulate and react with organic matter and nutrients in the wastewater. While EC processes are effective to treatment of several types of wastewaters, applications have been limited due to the high energy demands and high current densities. Generally, the for EC process can be performed without additional chemicals or pre-treatment, but the costs should be reduced for EC processes to become more applicable. In this work, we studied the treatment of a real wastewater from fishmeal industry by electrocoagulation process. Removal efficiencies for chemical oxygen demand (COD), total organic carbon (TOC) turbidity, phosphorous and nitrogen concentration were determined as a function of the operating conditions, such as pH, current density and operating time. The optimum operating conditions were determined to be operating time of 10 minutes, current density 100 A.m-2, and initial pH 4.0. COD, TOC, phosphorous concentration, and turbidity removal efficiencies at the optimum operating conditions were higher than 90% for aluminum electrode. Operating costs at the optimum conditions were calculated as US$ 0.37/m3 (US$ 0.038/kg COD) for Al electrode. These results demonstrate that the EC process is a promising technology to remove nutrients from fishery wastewaters, as the process has both a high efficiency of nutrient removal, and low energy requirements.

Keywords: electrocoagulation, fish, food industry, wastewater

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Authors: Dalma Varga, Nora Hubayne H.

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Nowadays, among the measures taken to offset the consequences of climate change, water resources management is one of the key tools, which can include excess water management. As a result of climate change’s effects and as a result of the frequent inappropriate landuse, more and more areas are affected by the excess water inundation. Hungary is located in the deepest part of the Pannonian Basin, which is exposed to water damage – especially lowland areas that are endangered by floods or excess waters. The periodical presence of excess water creates specific habitats in a given area, which have ecological, functional, and aesthetic values. Excess water inundation affects approximately 74% of Hungary’s lowland areas, of which about 46% is also under nature protection (such as national parks, protected landscape areas, nature conservation areas, Natura 2000 sites, etc.). These data prove that areas exposed to excess water inundation – which are predominantly characterized by agricultural land uses – have an important ecological role. Other research works have confirmed the presence of numerous rare and endangered plant species in drainage canals, on grasslands exposed to excess water, and on special agricultural fields with mud vegetation. The goal of this research is to define and analyze ecosystem services of areas exposed to excess water inundation. In addition to this, it is also important to determine the quantified indicators of these areas’ natural and landscape values besides the presence of protected species and the naturalness of habitats, so all in all, to analyze the various nature protections related to excess water. As a result, a practice-orientated assessment method has been developed that provides the ecological water demand, assimilates to ecological and habitat aspects, contributes to adaptive excess water management, and last but not least, increases or maintains the share of the green infrastructure network. In this way, it also contributes to reduce and mitigate the negative effects of climate change.

Keywords: ecosystem services, landscape architecture, excess water management, green infrastructure planning

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Authors: Soheila Sadeghi

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In the dynamic landscape of project management, scope changes are an inevitable reality that can significantly impact project performance. These changes, whether initiated by stakeholders, external factors, or internal project dynamics, can lead to cost overruns and schedule delays. Accurately predicting the consequences of these changes is crucial for effective project control and informed decision-making. This study aims to develop predictive models to estimate the impact of scope changes on project cost and schedule using machine learning techniques. The research utilizes a comprehensive dataset containing detailed information on project tasks, including the Work Breakdown Structure (WBS), task type, productivity rate, estimated cost, actual cost, duration, task dependencies, scope change magnitude, and scope change timing. Multiple machine learning models are developed and evaluated to predict the impact of scope changes on project cost and schedule. These models include Linear Regression, Decision Tree, Ridge Regression, Random Forest, Gradient Boosting, and XGBoost. The dataset is split into training and testing sets, and the models are trained using the preprocessed data. Cross-validation techniques are employed to assess the robustness and generalization ability of the models. The performance of the models is evaluated using metrics such as Mean Squared Error (MSE) and R-squared. Residual plots are generated to assess the goodness of fit and identify any patterns or outliers. Hyperparameter tuning is performed to optimize the XGBoost model and improve its predictive accuracy. The feature importance analysis reveals the relative significance of different project attributes in predicting the impact on cost and schedule. Key factors such as productivity rate, scope change magnitude, task dependencies, estimated cost, actual cost, duration, and specific WBS elements are identified as influential predictors. The study highlights the importance of considering both cost and schedule implications when managing scope changes. The developed predictive models provide project managers with a data-driven tool to proactively assess the potential impact of scope changes on project cost and schedule. By leveraging these insights, project managers can make informed decisions, optimize resource allocation, and develop effective mitigation strategies. The findings of this research contribute to improved project planning, risk management, and overall project success.

Keywords: cost impact, machine learning, predictive modeling, schedule impact, scope changes

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Authors: Lee A. Browne, K. Rumbold

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The first fluorinating enzyme, 5'-fluoro-5'-deoxyadenosine synthase (fluorinase) was isolated from the soil bacterium Streptomyces cattleya. Such an enzyme, with the ability to catalyze a C-F bond, presents great potential as a biocatalyst. Naturally fluorinated compounds are extremely rare in nature. As a result, the number of fluorinases identified remains relatively few. The field of fluorination is almost completely synthetic. However, with the increasing demand for fluorinated organic compounds of commercial value in the agrochemical, pharmaceutical and materials industries, it has become necessary to utilize biologically based methods such as biocatalysts. A key step in this crucial process is the large-scale production of the fluorinase enzyme in considerable quantities for industrial applications. Thus, this study aimed to optimize expression of the fluorinase enzyme in both prokaryotic and eukaryotic expression systems in order to obtain high protein yields. The fluorinase gene was cloned into the pET 41b(+) and pPinkα-HC vectors and used to transform the expression hosts, E.coli BL21(DE3) and Pichia pastoris (PichiaPink™ strains) respectively. Expression trials were conducted to select optimal conditions for expression in both expression systems. Fluorinase catalyses a reaction between S-adenosyl-L-Methionine (SAM) and fluoride ion to produce 5'-fluorodeoxyadenosine (5'FDA) and L-Methionine. The activity of the enzyme was determined using HPLC by measuring the product of the reaction 5'FDA. A gradient mobile phase of 95:5 v/v 50mM potassium phosphate buffer to a final mobile phase containing 80:20 v/v 50mM potassium phosphate buffer and acetonitrile were used. This resulted in the complete separation of SAM and 5’-FDA which eluted at 1.3 minutes and 3.4 minutes respectively. This proved that the fluorinase enzyme was active. Optimising expression of the fluorinase enzyme was successful in both E.coli and PichiaPink™ where high expression levels in both expression systems were achieved. Protein production will be scaled up in PichiaPink™ using fermentation to achieve large-scale protein production. High level expression of protein is essential in biocatalysis for the availability of enzymes for industrial applications.

Keywords: biocatalyst, expression, fluorinase, PichiaPink™

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Authors: Meshal M. Abdullah, Rusty A. Feagin, Layla Musawi

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When humans mismanage arid landscapes, soil erosion can become a primary mechanism that leads to desertification. This study focuses on applying soil erosion models to a disturbed landscape in Umm Nigga, Kuwait, and identifying its predicted change under restoration plans, The northern portion of Umm Nigga, containing both coastal and desert ecosystems, falls within the boundaries of the Demilitarized Zone (DMZ) adjacent to Iraq, and has been fenced off to restrict public access since 1994. The central objective of this project was to utilize GIS and remote sensing to compare the MPSIAC (Modified Pacific South West Inter Agency Committee), EMP (Erosion Potential Method), and USLE (Universal Soil Loss Equation) soil erosion models and determine their applicability for arid regions such as Kuwait. Spatial analysis was used to develop the necessary datasets for factors such as soil characteristics, vegetation cover, runoff, climate, and topography. Results showed that the MPSIAC and EMP models produced a similar spatial distribution of erosion, though the MPSIAC had more variability. For the MPSIAC model, approximately 45% of the land surface ranged from moderate to high soil loss, while 35% ranged from moderate to high for the EMP model. The USLE model had contrasting results and a different spatial distribution of the soil loss, with 25% of area ranging from moderate to high erosion, and 75% ranging from low to very low. We concluded that MPSIAC and EMP were the most suitable models for arid regions in general, with the MPSIAC model best. We then applied the MPSIAC model to identify the amount of soil loss between coastal and desert areas, and fenced and unfenced sites. In the desert area, soil loss was different between fenced and unfenced sites. In these desert fenced sites, 88% of the surface was covered with vegetation and soil loss was very low, while at the desert unfenced sites it was 3% and correspondingly higher. In the coastal areas, the amount of soil loss was nearly similar between fenced and unfenced sites. These results implied that vegetation cover played an important role in reducing soil erosion, and that fencing is much more important in the desert ecosystems to protect against overgrazing. When applying the MPSIAC model predictively, we found that vegetation cover could be increased from 3% to 37% in unfenced areas, and soil erosion could then decrease by 39%. We conclude that the MPSIAC model is best to predict soil erosion for arid regions such as Kuwait.

Keywords: soil erosion, GIS, modified pacific South west inter agency committee model (MPSIAC), erosion potential method (EMP), Universal soil loss equation (USLE)

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Authors: Vishal Pareek, Shubham Gupta, Sushil Chandra Jain

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With increasing high-speed computation demand the power consumption, heat dissipation and chip size issues are posing challenges for logic design with conventional technologies. Recovery of bit loss and bit errors is other issues that require reversibility and fault tolerance in the computation. The reversible computing is emerging as an alternative to conventional technologies to overcome the above problems and helpful in a diverse area such as low-power design, nanotechnology, quantum computing. Bit loss issue can be solved through unique input-output mapping which require reversibility and bit error issue require the capability of fault tolerance in design. In order to incorporate reversibility a number of combinational reversible logic based circuits have been developed. However, very few sequential reversible circuits have been reported in the literature. To make the circuit fault tolerant, a number of fault model and test approaches have been proposed for reversible logic. In this paper, we have attempted to incorporate fault tolerance in sequential reversible building blocks such as D flip-flop, T flip-flop, JK flip-flop, R-S flip-flop, Master-Slave D flip-flop, and double edge triggered D flip-flop by making them parity preserving. The importance of this proposed work lies in the fact that it provides the design of reversible sequential circuits completely testable for any stuck-at fault and single bit fault. In our opinion our design of reversible building blocks is superior to existing designs in term of quantum cost, hardware complexity, constant input, garbage output, number of gates and design of online testable D flip-flop have been proposed for the first time. We hope our work can be extended for building complex reversible sequential circuits.

Keywords: parity preserving gate, quantum computing, fault tolerance, flip-flop, sequential reversible logic

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Authors: Asma AlQahtani, Jumana AlHadad, Maryam AlQallaf, Shoug AlHasan

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New product development (NPD) is the complete process of bringing a new product to the customer by integrating the two broad divisions; one involving the idea generation, product design and detail engineering; and the other involving market research and marketing analysis. It is a common practice for companies to undertake some of these tasks simultaneously (concurrent engineering) and also consider them as an ongoing process (continuous development). The current study explores the framework and methodology for a new product development process utilizing the Quality Function Deployment (QFD) tool for bringing the customer opinion into the product development process. An elaborate customer survey with focus groups in the region was carried out to ensure that customer requirements are integrated into new products as early as the design stage including identifying the recognition of need for the new product. A QFD Matrix (House of Quality) was prepared that links customer requirements to product engineering requirements and a feasibility study and risk assessment exercise was carried out for a Small and Medium Enterprise (SME) in Kuwait for development of the new product. SMEs in Kuwait, particularly in manufacturing sector are mainly focused on serving the local demand, and often lack of product quality adversely affects the ability of the companies to compete on a regional/global basis. Further, lack of focus on identifying customer requirements often deters SMEs to envisage the idea of a New Product Development. The current study therefore focuses in utilizing QFD Matrix right from the conceptual design to detail design and to some extent, extending the link this to design of the manufacturing system. The outcome of the project resulted in a development of the prototype for a new molded product which can ensure consistency between the customer’s requirements and the measurable characteristics of the product. The Engineering Economics and Cost studies were also undertaken to analyse the viability of the new product, the results of which was also linked to the successful implementation of the initial QFD Matrix.

Keywords: Quality Function Deployment, QFD Matrix, new product development, NPD, Kuwait SMEs, prototype development

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Authors: Raj Chavan

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Currently, there are over 14,500 Water Resource Recovery Facilities (WRRFs) in the United States, with ~35% of them having some type of nutrient limits in place. These WRRFs account for about 1% of overall power demand and 2% of total greenhouse gas emissions (GHG) in the United States and contribute for 10 to 15% of the overall nutrient load to surface rivers in the United States. The evolution of densification technologies toward more compact and energy-efficient nutrient removal processes has been impacted by a number of factors. Existing facilities that require capacity expansion or biomass densification for higher treatability within the same footprint are being subjected to more stringent requirements relating to nutrient removal prior to surface water discharge. Densification of activated sludge has received recent widespread interest as a means for achieving process intensification and nutrient removal at WRRFs. At the core of the technology are the aerobic sludge granules where the biological processes occur. There is considerable interest in the prospect of producing granular sludge in continuous (or traditional) activated sludge processes (CAS) or densification of biomass by moving activated sludge flocs to a denser aggregate of biomass as a highly effective technique of intensification. This presentation will provide a fundamental understanding of densification by presenting insights and practical issues. The topics that will be discussed include methods used to generate and retain densified granules; the mechanisms that allow biological flocs to densify; the role that physical selectors play in the densification of biological flocs; some viable ways for managing biological flocs that have become densified; effects of physical selection design parameters on the retention of densified biological flocs and finally some operational solutions for customizing the flocs and granules required to meet performance and capacity targets. In addition, it will present some case studies where biological and physical parameters were used to generate aerobic granular sludge in the continuous flow system.

Keywords: densification, aerobic granular sludge, nutrient removal, intensification

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Authors: Cristian Soitu, Alexander Feuerborn, Cyril Deroy, Alfonso Castrejon-Pita, Peter R. Cook, Edmond J. Walsh

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Microfluidics now stands as an academically mature technology after a quarter of a century research activities have delivered a vast array of proof of concepts for many biological workflows. However, translation to industry remains poor, with only a handful of notable exceptions – e.g. digital PCR, DNA sequencing – mainly because of biocompatibility issues, limited range of readouts supported or complex operation required. This technology exploits the domination of interfacial forces over gravitational ones at the microscale, replacing solid walls with fluid ones as building blocks for cell micro-environments. By employing only materials used by biologists for decades, the system is shown to be biocompatible, and easy to manufacture and operate. The method consists in displacing a continuous fluid layer into a pattern of isolated chambers overlaid with an immiscible liquid to prevent evaporation. The resulting fluid arrangements can be arrays of micro-chambers with rectangular footprint, which use the maximum surface area available, or structures with irregular patterns. Pliant, self-healing fluid walls confine volumes as small as 1 nl. Such fluidic structures can be reconfigured during the assays, giving the platform an unprecedented level of flexibility. Common workflows in cell biology are demonstrated – e.g. cell growth and retrieval, cloning, cryopreservation, fixation and immunolabeling, CRISPR-Cas9 gene editing, and proof-of-concept drug tests. This fluid-shaping technology is shown to have potential for high-throughput cell- and organism-based assays. The ability to make and reconfigure on-demand microfluidic circuits on standard Petri dishes should find many applications in biology, and yield more relevant phenotypic and genotypic responses when compared to standard microfluidic assays.

Keywords: fluid walls, micro-chambers, reconfigurable, freestyle

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Authors: Ghufran Ahmed, Muhammad Osama Siddiqui, Shahbaz Siddiqui, Rauf Ahmad Shams Malick, Faisal Khan, Mubashir Khan

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In this paper, a machine learning-based approach for early prediction of diseases in cows is proposed. Different ML algos are applied to extract useful patterns from the available dataset. Technology has changed today’s world in every aspect of life. Similarly, advanced technologies have been developed in livestock and dairy farming to monitor dairy cows in various aspects. Dairy cattle monitoring is crucial as it plays a significant role in milk production around the globe. Moreover, it has become necessary for farmers to adopt the latest early prediction technologies as the food demand is increasing with population growth. This highlight the importance of state-ofthe-art technologies in analyzing how important technology is in analyzing dairy cows’ activities. It is not easy to predict the activities of a large number of cows on the farm, so, the system has made it very convenient for the farmers., as it provides all the solutions under one roof. The cattle industry’s productivity is boosted as the early diagnosis of any disease on a cattle farm is detected and hence it is treated early. It is done on behalf of the machine learning output received. The learning models are already set which interpret the data collected in a centralized system. Basically, we will run different algorithms on behalf of the data set received to analyze milk quality, and track cows’ health, location, and safety. This deep learning algorithm draws patterns from the data, which makes it easier for farmers to study any animal’s behavioral changes. With the emergence of machine learning algorithms and the Internet of Things, accurate tracking of animals is possible as the rate of error is minimized. As a result, milk productivity is increased. IoT with ML capability has given a new phase to the cattle farming industry by increasing the yield in the most cost-effective and time-saving manner.

Keywords: IoT, machine learning, health care, dairy cows

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Authors: Oluwafemi Samuel Oyamakin

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The forest in Nigeria is currently estimated to extend to around 9.6 million hectares, but used to expand over central and southern Nigeria decades ago. The forest estate is shrinking due to long-term human exploitation for agricultural development, fuel wood demand, uncontrolled forest harvesting and urbanization, amongst other factors, compounded by population growth in rural areas. Nigeria has lost more than 50% of its forest cover since 1990 and currently less than 10% of the country is forested. The current deforestation rate is estimated at 3.7%, which is one of the highest in the world. Reducing Emissions from Deforestation and forest Degradation plus conservation, sustainable management of forests and enhancement of forest carbon stocks constituted what is referred to as REDD+. This study evaluated some of the existing way of computing carbon stocks using eight indigenous tree species like Mansonia, Shorea, Bombax, Terminalia superba, Khaya grandifolia, Khaya senegalenses, Pines and Gmelina arborea. While these components are the essential elements of REDD+ programme, they can be brought under a broader framework of systems analysis designed to arrive at optimal solutions for future predictions through statistical distribution pattern of carbon sequestrated by various species of tree. Available data on height and diameter of trees in Ibadan were studied and their respective potentials of carbon sequestration level were assessed and subjected to tests so as to determine the best statistical distribution that would describe the carbon sequestration pattern of trees. The result of this study suggests a reasonable statistical distribution for carbons sequestered in simulation studies and hence, allow planners and government in determining resources forecast for sustainable development especially where experiments with real-life systems are infeasible. Sustainable management of forest can then be achieved by projecting future condition of forests under different management regimes thereby supporting conservation and REDD+ programmes in Nigeria.

Keywords: REDD+, carbon, climate change, height and diameter

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Authors: Young Nam Chun, Soo Hyuk Yun, Byeo Ri Jeong

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The recent gradual increase in the energy demand is mostly met by fossil fuel, but the research on and development of new alternative energy sources is drawing much attention due to the limited fossil fuel supply and the greenhouse gas problem. Biomass is an eco-friendly renewable energy that can achieve carbon neutrality. The conversion of the biomass sludge wastes discharged from a wastewater treatment plant to clean energy is an important green energy technology in an eco-friendly way. In this NRF study, a new type of microwave thermal treatment was developed to apply the biomass-CCS technology to sludge wastes. For this, the microwave dielectric heating characteristics were examined to investigate the energy conversion mechanism for the combined drying-pyrolysis/gasification of the dewatered wet sludge. The carbon dioxide gasification was tested using the CO2 captured from the pre-combustion capture process. In addition, the results of the pyrolysis and gasification test with the wet sludge were analyzed to compare the microwave energy conversion results with the results of the use of the conventional heating method. Gas was the largest component of the product of both pyrolysis and gasification, followed by sludge char and tar. In pyrolysis, the main components of the producer gas were hydrogen and carbon monoxide, and there were some methane and hydrocarbons. In gasification, however, the amount of carbon monoxide was greater than that of hydrogen. In microwave gasification, a large amount of heavy tar was produced. The largest amount of benzene among light tar was produced in both pyrolysis and gasification. NH3 and HCN which are the precursors of NOx, generated as well. In microwave heating, the sludge char had a smooth surface, like that of glass, and in the conventional heating method with an electric furnace, deep cracks were observed in the sludge char. This indicates that the gas obtained from the microwave pyrolysis and gasification of wet sewage sludge can be used as fuel, but the heavy tar and NOx precursors in the gas must be treated. Sludge char can be used as solid fuel or as a tar reduction adsorbent in the process if necessary. This work supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (No. 2015R1R1A2A2A03003044).

Keywords: microwave heating, pyrolysis gasification, precombustion CCS, sewage sludge, biomass energy

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Authors: Nattapol Pourprasert

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This research is to study qualitative research having two objectives: 1. to study comparison of private sector of government to compare with ASEAN Member States, 2. to study trend of private enterprise administration of ASEAN Member States. The results are: (1) Thai people focus on personal resource administrative system, (2) Indonesia focuses on official system by good administrative principles, (3) Malaysia focuses on technology development to service people, (4) Philippines focuses on operation system development, (5) Singapore focuses on public service development, (6) Brunei Darussalam focuses on equality in government service of people, (7) Vietnam focuses on creating government labor base and develop testing and administration of operation test, (8) Myanmar focuses on human resources development, (9) Laos focuses on form of local administration, (10) Cambodia focuses on policy revolution in personal resources. The result of the second part of the study are: (1) Thailand created government personnel to be power under qualitative official structural event, (2) Indonesia has Bureaucracy Reform Roadmap of Bureaucracy Reform and National Development Plan Medium Term, (3) Malaysia has database for people service, (4) Philippines follows up control of units operation by government policy, (5) Singapore created reliability, participation of people to set government policy people’s demand, (6) Brunei Darussalam has social welfare to people, (7) Vietnam revolved testing system and administration including manpower base construction of government effectively, (8) Myanmar creates high rank administrators to develop country, (9) Laos distributes power to locality, and (10) Cambodia revolved personnel resource policy.

Keywords: public administration development, ASEAN member states, private sector, government

Procedia PDF Downloads 238

Authors: Lancelot Boulet, Pierre Benard, Ghislain Lartigue, Vincent Moureau, Nicolas Chauvet, Sheddia Didorally

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International aeronautic standards demand a fire certification for engines that demonstrate their resistance. This demonstration relies on tests performed with prototype engines in the late stages of the development. Hardest tests require to place a kerosene standardized flame in front of the engine casing during a given time with imposed temperature and heat flux. The purpose of this work is to provide a better characterization of a kerosene/air certification burner in order to minimize the risks of test failure. A first Large-Eddy Simulation (LES) study of the certification burner permitted to model and simulate this burner, including both adiabatic and Conjugate Heat Transfer (CHT) computations. Carried out on unstructured grids with 40 million tetrahedral cells, using the finite-volume YALES2 code, spray combustion, forced convection on walls and conduction in the solid parts of the burner were coupled to achieve a detailed description of heat transfer. It highlighted the fact that conduction inside the solid has a real impact on the flame topology and the combustion regime. However, in the absence of radiative heat transfer, unrealistic temperature of the equipment was obtained. The aim of the present study is to include the radiative heat transfer in order to reach the same temperature given by experimental measurements. First, various test-cases are conducted to validate the coupling between the different heat solvers. Then, adiabatic case, CHT case, as well as CHT including radiative transfer are studied and compared. The LES model is finally applied to investigate the heat transfer in a flame impaction configuration. The aim is to progress on fire test modeling so as to reach a good confidence level as far as success of the certification test is concerned.

Keywords: conjugate heat transfer, fire resistance test, large-eddy simulation, radiative transfer, turbulent combustion

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Authors: Shaibu Baanni Azumah, William Adzawla

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Rice is an important staple crop, with current demand higher than the domestic supply in Ghana. This has led to a high and unfavourable import bill. Therefore, recent policies and interventions in the agricultural sub-sector aim at promoting various improved agricultural technologies in order to improve domestic production and reduce the importation of rice. In this study, we examined the effect of the adoption of Urea Deep Placement (UDP) technology by rice farmers on the position of the production frontier. This involved 200 farmers selected through a multi stage sampling technique in the Northern region of Ghana. A Cobb-Douglas stochastic frontier model was fitted. The result showed that the adoption of UDP technology shifts the output frontier outward and also move the farmers closer to the frontier. Farmers were also operating under diminishing returns to scale which calls for redress. Other factors that significantly influenced rice production were farm size, labour, use of certified seeds and NPK fertilizer. Although there was an opportunity for improvement, the farmers were highly efficient (92%), compared to previous studies. Farmers’ efficiency was improved through increased education, household size, experience, access to credit, and lack of extension service provision by MoFA. The study recommends the revision of Ghana’s agricultural policy to include the UDP technology. Agricultural Extension officers of the Ministry of Food and Agriculture (MoFA) should be trained on the UDP technology to support IFDC’s drive to improve adoption by rice farmers. Rice farmers are also encouraged to expand their farm lands, improve plant population, and also increase the usage of fertilizer to improve yields. Mechanisms through which credit can be made easily accessible and effectively utilised should be identified and promoted.

Keywords: efficiency, rice farmers, stochastic frontier, UDP technology

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Authors: Muhammad Kashif Fida

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In the bank, teller’s job (cash officer) is highly important and critical as at one end it requires soft and brisk customer services and on the other side, handling cash with integrity. It is always challenging for recruiters to hire competent and trustworthy tellers. According to author’s knowledge, there is no comprehensive test available that may provide assistance in recruitment in Pakistan. So there is a dire need of a psychometric battery that could provide support in recruitment of potential candidates for the teller’ position. So, the aim of the present study was to construct ABL-Teller Aptitude Test (ABL-TApT). Three major phases have been designed by following American Psychological Association’s guidelines. The first phase was qualitative, indicators of the test have been explored by content analysis of the a) teller’s job descriptions (n=3), b) interview with senior tellers (n=6) and c) interview with HR personals (n=4). Content analysis of above yielded three border constructs; i). Personality, ii). Integrity/honesty, iii). Professional Work Aptitude. Identified indicators operationalized and statements (k=170) were generated using verbatim. It was then forwarded to the five experts for review of content validity. They finalized 156 items. In the second phase; ABL-TApT (k=156) administered on 323 participants through a computer application. The overall reliability of the test shows significant alpha coefficient (α=.81). Reliability of subscales have also significant alpha coefficients. Confirmatory Factor Analysis (CFA) performed to estimate the construct validity, confirms four main factors comprising of eight personality traits (Confidence, Organized, Compliance, Goal-oriented, Persistent, Forecasting, Patience, Caution), one Integrity/honesty factor, four factors of professional work aptitude (basic numerical ability and perceptual accuracy of letters, numbers and signature) and two factors for customer services (customer services, emotional maturity). Values of GFI, AGFI, NNFI, CFI, RFI and RMSEA are in recommended range depicting significant model fit. In third phase concurrent validity evidences have been pursued. Personality and integrity part of this scale has significant correlations with ‘conscientiousness’ factor of NEO-PI-R, reflecting strong concurrent validity. Customer services and emotional maturity have significant correlations with ‘Bar-On EQI’ showing another evidence of strong concurrent validity. It is concluded that ABL-TAPT is significantly reliable and valid battery of tests, will assist in objective recruitment of tellers and help recruiters in finding a more suitable human resource.

Keywords: concurrent validity, construct validity, content validity, reliability, teller aptitude test, objective recruitment

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Authors: Guneet Saini, Uthej Vattipalli

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In a world with increased demand for sustainable construction, waste product of one industry could be a boon to the other in reducing the carbon footprint. Usage of industrial waste such as fly ash and ground granulated blast furnace slag have become the epicenter of curbing the use of cement, one of the major contributors of greenhouse gases. In this paper, empirical studies have been done to develop alkali activated self-compacting geopolymer concrete (GPC) using ground granulated blast furnace slag (GGBS), incorporated with 2% nano-silica by weight, through evaluation of its fresh and hardening properties. Experimental investigation on 6 mix designs of varying molarity of 10M, 12M and 16M of the alkaline solution and a binder content of 450 kg/m³ and 500 kg/m³ has been done and juxtaposed with GPC mix design composed of 16M alkaline solution concentration and 500 kg/m³ binder content without nano-silica. The sodium silicate to sodium hydroxide ratio (SS/SH), alkaline activator liquid to binder ratio (AAL/B) and water to binder ratio (W/B), which significantly affect the performance and mechanical properties of GPC, were fixed at 2.5, 0.45 and 0.4 respectively. To catalyze the early stage geopolymerisation, oven curing is done maintaining the temperature at 60˚C. This paper also elucidates the test results for fresh self-compacting concrete (SCC) done as per EFNARC guidelines. The mechanical properties tests conducted were: compressive strength test after 7 days, 28 days, 56 days and 90 days; flexure test; split tensile strength test after 28 days, 56 days and 90 days; X-ray diffraction test to analyze the mechanical performance and sorptivity test for testing of permeability. The study revealed that the sample of 16M concentration of alkaline solution with 500 Kg/m³ binder content containing 2% nano silica produced the highest compressive, flexural and split tensile strength of 81.33 MPa, 7.875 MPa, and 6.398 MPa respectively, at the end of 90 days.

Keywords: alkaline activator liquid, geopolymer concrete, ground granulated blast furnace slag, nano silica, self compacting

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Authors: Debabrata Biswas

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The current trend in the development of antibiotic resistance by multiple bacterial pathogens has resulted in a troubling loss of effective antibiotic options for human. The emergence of multi-drug-resistant pathogens has necessitated higher dosages and combinations of multiple antibiotics, further exacerbating the problem of antibiotic resistance. Zoonotic bacterial pathogens, such as Salmonella, Campylobacter, Shiga toxin-producing Escherichia coli (such as enterohaemorrhagic E. coli or EHEC), and Listeria are the most common and predominant foodborne enteric infectious agents. It was observed that these pathogens gained/developed their ability to survive in the presence of antibiotics either in farm animal gut or farm environment and researchers believe that therapeutic and sub-therapeutic antibiotic use in farm animal production might play an important role in it. The mechanism of action of antimicrobial components used in farm animal production in genomic interplay in the gut and farm environment, has not been fully characterized. Even the risk of promoting the exchange of mobile genetic elements between microbes specifically pathogens needs to be evaluated in depth, to ensure sustainable farm animal production, safety of our food and to mitigate/limit the enteric infection with multiple antibiotic resistant bacterial pathogens. Due to the consumer’s demand and considering the current emerging situation, many countries are in process to withdraw antibiotic use in farm animal production. Before withdrawing use of the sub-therapeutic antibiotic or restricting the use of therapeutic antibiotics in farm animal production, it is essential to find alternative natural antimicrobials for promoting the growth of farm animal and/or treating animal diseases. Further, it is also necessary to consider whether that compound(s) has the potential to trigger the acquisition or loss of genetic materials in zoonotic and any other bacterial pathogens. Development of alternative therapeutic and sub-therapeutic antimicrobials for farm animal production and food processing and preservation and their effective implementation for sustainable strategies for farm animal production as well as the possible risk for horizontal gene transfer in major enteric pathogens will be focus in the study.

Keywords: food safety, natural antimicrobial, sustainable farming, antibiotic resistance

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Authors: Xinhai Li, Huidong Tian, Yumin Guo

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Bird migration is fantastic natural phenomenon. In recent years, the use of GPS transmitters has generated a vast amount of data, and the Movebank platform has made these data publicly accessible. For researchers, what they need are data analysis tools. Although there are approximately 90 R packages dedicated to animal movement analysis, the capacity for comprehensive processing of bird migration data remains limited. Hence, we introduce a novel package called migrationR. This package enables the calculation of movement speed, direction, changes in direction, flight duration, daily and annual movement distances. Furthermore, it can pinpoint the starting and ending dates of migration, estimate nest site locations and stopovers, and visualize movement trajectories at various time scales. migrationR distinguishes individuals through NMDS (non-metric multidimensional scaling) coordinates based on movement variables such as speed, flight duration, path tortuosity, and migration timing. A distinctive aspect of the package is the development of a hetero-occurrences species distribution model that takes into account the daily rhythm of individual birds across different landcover types. Habitat use for foraging and roosting differs significantly for many waterbirds. For example, White-naped Cranes at Poyang Lake in China typically forage in croplands and roost in shallow water areas. Both of these occurrence types are of equal importance. Optimal habitats consist of a combination of crop lands and shallow waters, whereas suboptimal habitats lack both, which necessitates birds to fly extensively. With migrationR, we conduct species distribution modeling for foraging and roosting separately and utilize the moving distance between crop lands and shallow water areas as an index of overall habitat suitability. This approach offers a more nuanced understanding of the habitat requirements for migratory birds and enhances our ability to analyze and interpret their movement patterns effectively. The functions of migrationR are demonstrated using our own tracking data of 78 White-naped Crane individuals from 2014 to 2023, comprising over one million valid locations in total. migrationR can be installed from a GitHub repository by executing the following command: remotes::install_github("Xinhai-Li/migrationR").

Keywords: bird migration, hetero-occurrences species distribution model, migrationR, R package, satellite telemetry

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Authors: Taha Benarbia

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The advent of automated and connected vehicles has revolutionized the transportation industry, presenting new opportunities for enhancing the efficiency, safety, and sustainability of our transportation networks. This paper explores the integration of automated and connected vehicles into a smart transportation framework, leveraging the power of deep learning techniques to optimize the overall network performance. The first aspect addressed in this paper is the deployment of automated vehicles (AVs) within the transportation system. AVs offer numerous advantages, such as reduced congestion, improved fuel efficiency, and increased safety through advanced sensing and decisionmaking capabilities. The paper delves into the technical aspects of AVs, including their perception, planning, and control systems, highlighting the role of deep learning algorithms in enabling intelligent and reliable AV operations. Furthermore, the paper investigates the potential of connected vehicles (CVs) in creating a seamless communication network between vehicles, infrastructure, and traffic management systems. By harnessing real-time data exchange, CVs enable proactive traffic management, adaptive signal control, and effective route planning. Deep learning techniques play a pivotal role in extracting meaningful insights from the vast amount of data generated by CVs, empowering transportation authorities to make informed decisions for optimizing network performance. The integration of deep learning with automated and connected vehicles paves the way for advanced transportation network optimization. Deep learning algorithms can analyze complex transportation data, including traffic patterns, demand forecasting, and dynamic congestion scenarios, to optimize routing, reduce travel times, and enhance overall system efficiency. The paper presents case studies and simulations demonstrating the effectiveness of deep learning-based approaches in achieving significant improvements in network performance metrics

Keywords: automated vehicles, connected vehicles, deep learning, smart transportation network

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Authors: W. Jahouach-Rabai, J. Aribi, Z. Azzouz-Berriche, R. Lahsni, F. Hosni

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Gamma irradiation applied in removing pharmaceutical contaminants from wastewater is an effective advanced oxidation process (AOP), considered as an alternative to conventional water treatment technologies. In this purpose, the degradation efficiency of several detected contaminants under gamma irradiation was evaluated. In fact, radiolysis of organic pollutants in aqueous solutions produces powerful reactive species, essentially hydroxyl radical ( ·OH), able to destroy recalcitrant pollutants in water. Pharmaceuticals considered in this study are aqueous solutions of paracetamol, ibuprofen, and diclofenac at different concentrations 0.1-1 mmol/L, which were treated with irradiation doses from 3 to 15 kGy. The catalytic oxidation of these compounds by gamma irradiation was investigated using hydrogen peroxide (H₂O₂) as a convenient oxidant. Optimization of the main parameters influencing irradiation process, namely irradiation doses, initial concentration and oxidant volume (H₂O₂) were investigated, in the aim to release high degradation efficiency of considered pharmaceuticals. Significant modifications attributed to these parameters appeared in the variation of degradation efficiency, chemical oxygen demand removal (COD) and concentration of radio-induced radicals, confirming them synergistic effect to attempt total mineralization. Pseudo-first-order reaction kinetics could be used to depict the degradation process of these compounds. A sophisticated analytical study was released to quantify the detected radio-induced radicals (electron paramagnetic resonance spectroscopy (EPR) and high performance liquid chromatography (HPLC)). All results showed that this process is effective for the degradation of many pharmaceutical products in aqueous solutions due to strong oxidative properties of generated radicals mainly hydroxyl radical. Furthermore, the addition of an optimal amount of H₂O₂ was efficient to improve the oxidative degradation and contribute to the high performance of this process at very low doses (0.5 and 1 kGy).

Keywords: AOP, COD, hydroxyl radical, EPR, gamma irradiation, HPLC, pharmaceuticals

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Authors: Santimoy Khilari, Debabrata Pradhan

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Ever−increasing energy demand and growing energy crisis along with environmental issues emphasize the research on sustainable energy conversion and storage systems. Recently, supercapacitors or electrochemical capacitors emerge as a promising energy storage technology for future generation. The activity of supercapacitors generally depends on the efficiency of its electrode materials. So, the development of cost−effective efficient electrode materials for supercapacitors is one of the challenges to the scientific community. Transition metal oxides with spinel crystal structure receive much attention for different electrochemical applications in energy storage/conversion devices because of their improved performance as compared to simple oxides. In the present study, we have synthesized polypyrrole (PPy) supported manganese cobaltite nanorods (MnCo2O4 NRs) hybrid electrode material for supercapacitor application. The MnCo2O4 NRs were synthesized by a simple hydrothermal and calcination approach. The MnCo2O4 NRs/PPy hybrid was prepared by in situ impregnation of MnCo2O4 NRs during polymerization of pyrrole. The surface morphology and microstructure of as−synthesized samples was characterized by scanning electron microscopy and transmission electron microscopy, respectively. The crystallographic phase of MnCo2O4 NRs, PPy and hybrid was determined by X-ray diffraction. Electrochemical charge storage activity of MnCo2O4 NRs, PPy and MnCo2O4 NRs/PPy hybrid was evaluated from cyclic voltammetry, chronopotentiometry and electrochemical impedance spectroscopy. Significant improvement of specific capacitance was achieved in MnCo2O4 NRs/PPy hybrid as compared to the individual components. Furthermore, the mechanically mixed MnCo2O4 NRs, and PPy shows lower specific capacitance as compared to MnCo2O4 NRs/PPy hybrid suggesting the importance of in situ hybrid preparation. The stability of as prepared electrode materials was tested by cyclic charge-discharge measurement for 1000 cycles. Maximum 94% capacitance was retained with MnCo2O4 NRs/PPy hybrid electrode. This study suggests that MnCo2O4 NRs/PPy hybrid can be used as a low cost electrode material for charge storage in supercapacitors.

Keywords: supercapacitors, nanorods, spinel, MnCo2O4, polypyrrole

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Authors: Rajasekhar Reddy Poonuru, Anusha Parnem

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Purpose: To formulate proliposome powder of agomelatine, an antipsychotic drug, and to evaluate physicochemical, in vitro characters and effect of surface charge on ex vivo intestinal permeation. Methods: Film deposition technique was employed to develop proliposomal powders of agomelatin with varying molar ratios of lipid Hydro Soy PC L-α-phosphatidylcholine (HSPC) and cholesterol with fixed sum of drug. With the aim to derive free flowing and stable proliposome powder, fluid retention potential of various carriers was examined. Liposome formation and number of vesicles formed for per mm3 up on hydration, vesicle size, and entrapment efficiency was assessed to deduce an optimized formulation. Sodium cholate added to optimized formulation to induce surface charge on formed vesicles. Solid-state characterization (FTIR, DSC, and XRD) was performed with the intention to assess native crystalline and chemical behavior of drug. The in vitro dissolution test of optimized formulation along with pure drug was evaluated to estimate dissolution efficiency (DE) and relative dissolution rate (RDR). Effective permeability co-efficient (Peff(rat)) in rat and enhancement ratio (ER) of drug from formulation and pure drug dispersion were calculated from ex vivo permeation studies in rat ileum. Results: Proliposomal powder formulated with equimolar ratio of HSPC and cholesterol ensued in higher no. of vesicles (3.95) with 90% drug entrapment up on hydration. Neusilin UFL2 was elected as carrier because of its high fluid retention potential (4.5) and good flow properties. Proliposome powder exhibited augmentation in DE (60.3 ±3.34) and RDR (21.2±01.02) of agomelation over pure drug. Solid state characterization studies demonstrated the transformation of native crystalline form of drug to amorphous and/or molecular state, which was in correlation with results obtained from in vitro dissolution test. The elevated Peff(rat) of 46.5×10-4 cm/sec and ER of 2.65 of drug from charge induced proliposome formulation with respect to pure drug dispersion was assessed from ex vivo intestinal permeation studies executed in ileum of wistar rats. Conclusion: Improved physicochemical characters and ex vivo intestinal permeation of drug from charge induced proliposome powder with Neusilin UFL2 unravels the potentiality of this system in enhancing oral delivery of agomelatin.

Keywords: agomelatin, proliposome, sodium cholate, neusilin

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Authors: S. Gokul Prassad, S. Aakash, K. Malar Mohan

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In the process to cope with the challenges faced by the automobile industry in providing ride comfort, the electronics and control systems play a vital role. The control systems in an automobile monitor various parameters, controls the performances of the systems, thereby providing better handling characteristics. The automobile suspension system is one of the main systems that ensure the safety, stability and comfort of the passengers. The system is solely responsible for the isolation of the entire automobile from harmful road vibrations. Thus, integration of the control systems in the automobile suspension system would enhance its performance. The diverse road conditions of India demand the need of an efficient suspension system which can provide optimum ride comfort in all road conditions. For any passenger vehicle, the design of the suspension system plays a very important role in assuring the ride comfort and handling characteristics. In recent years, the air suspension system is preferred over the conventional suspension systems to ensure ride comfort. In this article, the ride comfort of the adaptive suspension system is compared with that of the passive suspension system. The schema is created in MATLAB/Simulink environment. The system is controlled by a proportional integral differential controller. Tuning of the controller was done with the Particle Swarm Optimization (PSO) algorithm, since it suited the problem best. Ziegler-Nichols and Modified Ziegler-Nichols tuning methods were also tried and compared. Both the static responses and dynamic responses of the systems were calculated. Various random road profiles as per ISO 8608 standard are modelled in the MATLAB environment and their responses plotted. Open-loop and closed loop responses of the random roads, various bumps and pot holes are also plotted. The simulation results of the proposed design are compared with the available passive suspension system. The obtained results show that the proposed adaptive suspension system is efficient in controlling the maximum over shoot and the settling time of the system is reduced enormously.

Keywords: automobile suspension, MATLAB, control system, PID, PSO

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Authors: Sultan Z. Mahmud, Emily C. Graff, Adil Bashir

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Phosphoprotein enriched in astrocytes 15 kDa (PEA-15) is a multifunctional adapter protein which is associated with the regulation of apoptotic cell death. Recently it has been discovered that PEA-15 is crucial in normal neurodevelopment of domestic cats, a gyrencephalic animal model, although the exact function of PEA-15 in neurodevelopment is unknown. This study investigates how PEA-15 affects the blood-brain barrier (BBB) permeability in cat brain, which can cause abnormalities in tissue metabolite and energy supplies. Severe polymicrogyria and microcephaly have been observed in cats with a loss of function PEA-15 mutation, affecting the normal neurodevelopment of the cat. This suggests that the vital role of PEA-15 in neurodevelopment is associated with gyrification. Neurodevelopment is a highly energy demanding process. The mammalian brain depends on glucose as its main energy source. PEA-15 plays a very important role in glucose uptake and utilization by interacting with phospholipase D1 (PLD1). Mitochondria also plays a critical role in bioenergetics and essential to supply adequate energy needed for neurodevelopment. Cerebral blood flow regulates adequate metabolite supply and recent findings also showed that blood plasma contains mitochondria as well. So the BBB can play a very important role in regulating metabolite and energy supply in the brain. In this study the blood-brain permeability in cat brain was measured using MRI magnetization transfer (MT) effect on the perfusion signal. Perfusion is the tissue mass normalized supply of blood to the capillary bed. Perfusion also accommodates the supply of oxygen and other metabolites to the tissue. A fraction of the arterial blood can diffuse to the tissue, which depends on the BBB permeability. This fraction is known as water extraction fraction (EF). MT is a process of saturating the macromolecules, which has an effect on the blood that has been diffused into the tissue while having minimal effect on intravascular blood water that has not been exchanged with the tissue. Measurement of perfusion signal with and without MT enables to estimate the microvascular blood flow, EF and permeability surface area product (PS) in the brain. All the experiments were performed with Siemens 7T Magnetom with 32 channel head coil. Three control cats and three PEA-15 mutant cats were used for the study. Average EF in white and gray matter was 0.9±0.1 and 0.86±0.15 respectively, perfusion in white and gray matter was 85±15 mL/100g/min and 97±20 mL/100g/min respectively, PS in white and gray matter was 201±25 mL/100g/min and 225±35 mL/100g/min respectively for control cats. For PEA-15 mutant cats, average EF in white and gray matter was 0.81±0.15 and 0.77±0.2 respectively, perfusion in white and gray matter was 140±25 mL/100g/min and 165±18 mL/100g/min respectively, PS in white and gray matter was 240±30 mL/100g/min and 259±21 mL/100g/min respectively. This results show that BBB is compromised in PEA-15 mutant cat brain, where EF is decreased and perfusion as well as PS are increased in the mutant cats compared to the control cats. This findings might further explain the function of PEA-15 in neurodevelopment.

Keywords: BBB, cat brain, magnetization transfer, PEA-15

Procedia PDF Downloads 122