Search results for: chain drive

Authors: Saheli Mitra, Ramesh Karri, Praveen K. Mylapalli, Arka. B. Dey, Gourav Bhattacharya, Gouriprasanna Roy, Syed M. Kamil, Surajit Dhara, Sunil K. Sinha, Sajal K. Ghosh

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The most well-known structures of lyotropic liquid crystalline systems are the two dimensional hexagonal phase of cylindrical micelles with a positive interfacial curvature and the lamellar phase of flat bilayers with zero interfacial curvature. In aqueous solution of surfactants, the concentration dependent phase transitions have been investigated extensively. However, instead of changing the surfactant concentrations, the local curvature of an aggregate can be altered by tuning the electrostatic interactions among the constituent molecules. Intermediate phases with non-uniform interfacial curvature are still unexplored steps to understand the route of phase transition from hexagonal to lamellar. Understanding such structural evolution in lyotropic liquid crystalline systems is important as it decides the complex rheological behavior of the system, which is one of the main interests of the soft matter industry. Sodium dodecyl sulfate (SDS) is an anionic surfactant and can be considered as a unique system to tune the electrostatics by cationic additives. In present study, imidazolium-based ionic liquids (ILs) with different number of carbon atoms in their single hydrocarbon chain were used as the additive in the aqueous solution of SDS. At a fixed concentration of total non-aqueous components (SDS and IL), the molar ratio of these components was changed, which effectively altered the electrostatic interactions between the SDS molecules. As a result, the local curvature is observed to modify, and correspondingly, the structure of the hexagonal liquid crystalline phases are transformed into other phases. Polarizing optical microscopy of SDS and imidazole-based-IL systems have exhibited different textures of the liquid crystalline phases as a function of increasing concentration of the ILs. The small angle synchrotron x-ray diffraction (SAXD) study has indicated the hexagonal phase of direct cylindrical micelles to transform to a rectangular phase at the presence of short (two hydrocarbons) chain IL. However, the hexagonal phase is transformed to a lamellar phase at the presence of long (ten hydrocarbons) chain IL. Interestingly, at the presence of a medium (four hydrocarbons) chain IL, the hexagonal phase is transformed to another hexagonal phase of direct cylindrical micelles through the lamellar phase. To the best of our knowledge, such a phase sequence has not been reported earlier. Even though the small angle x-ray diffraction study has revealed the lattice parameters of these phases to be similar to each other, their rheological behavior has been distinctly different. These rheological studies have shed lights on how these phases differ in their viscoelastic behavior. Finally, the packing parameters, calculated for these phases based on the geometry of the aggregates, have explained the formation of the self-assembled aggregates.

Keywords: lyotropic liquid crystals, polarizing optical microscopy, rheology, surfactants, small angle x-ray diffraction

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Authors: Miguel García-Ferrús, Ana González, María A. Ferrús

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The most demanded organic foods worldwide are those that are consumed fresh, such as fruits and vegetables. However, there is a knowledge gap about some aspects of organic food microbiological quality and safety. Organic fruits and vegetables are more exposed to pathogenic microorganisms due to surface contact with natural fertilizers such as animal manure, wastes and vermicompost used during farming. It has been suggested that some emergent pathogens, such as Helicobacter pylori or Arcobacter spp., could reach humans through the consumption of raw or minimally processed vegetables. Therefore, the objective of this work was to study the contamination of organic fresh green leafy vegetables by Arcobacter spp. and Helicobacter pylori. For this purpose, a total of 24 vegetable samples, 13 lettuce and 11 spinach were acquired from 10 different ecological supermarkets and greengroceries and analyzed by culture and PCR. Arcobacter spp. was detected in 5 samples (20%) by PCR, 4 spinach and one lettuce. One spinach sample was found to be also positive by culture. For H. pylori, the H. pylori VacA gene-specific band was detected in 12 vegetable samples (50%), 10 lettuces and 2 spinach. Isolation in the selective medium did not yield any positive result, possibly because of low contamination levels together with the presence of the organism in its viable but non-culturable form. Results showed significant levels of H. pylori and Arcobacter contamination in organic vegetables that are generally consumed raw, which seems to confirm that these foods can act as transmission vehicles to humans.

Keywords: Arcobacter sp., Helicobacter pylori, Organic Vegetables, Polymerase Chain Reaction (PCR)

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Authors: Ezekiel Olukayode Akintunde

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There is a high level of inadequate methods at all levels of food supply in the global food industry. The inadequacies have led to vast wastages of food. Hence there is a need to curb the wastages that can later affect natural resources, water resources, and energy to avoid negative impacts on the climate and the environment. There is a need to engage multifaceted engineering packaging approaches for a sustainable food chain to ensure active packaging, intelligent packaging, new packaging materials, and a sustainable packaging system. Packaging can be regarded as an indispensable component approach that can be applied to solve major problems of sustainable food consumption globally; this is about controlling the environmental impact of packed food. The creative innovation will ensure that packaged foods are free from food-borne diseases and food chemical pollution. This paper evaluates the key shortcomings that must be addressed by innovative food packaging to ensure a safe, natural environment that will preserve energy and sustain water resources. Certain solutions, including fabricating microbial biodegradable chemical compounds/polymers from agro-food waste remnants, appear a bright path to ensure a strong and innovative waste-based food packaging system. Over the years, depletion in the petroleum reserves has brought about the emergence of biodegradable polymers as a proper replacement for traditional plastics; moreover, the increase in the production of traditional plastics has raised serious concerns about environmental threats. Biodegradable polymers have proven to be biocompatible, which can also be processed for other useful applications. Therefore, this study will showcase a workable guiding framework for designing a sustainable food packaging system that will not constitute a danger to our present society and that will surely preserve natural water resources. Various assessment methods will be deployed at different stages of the packaging design to enhance the package's sustainability. Every decision that will be made must be facilitated with methods that will be engaged per stage to allow for corrective measures throughout the cycle of the design process. Basic performance appraisal of packaging innovations. Food wastage can result in inimical environmental impacts, and ethical practices must be carried out for food loss at home. An examination in West Africa quantified preventable food wastage over the entire food value chain at almost 180kg per person per year. That is preventable food wastage, 35% of which originated at the household level. Many food losses reported, which happened at the harvesting, storage, transportation, and processing stages, are not preventable and are without much environmental impact because such wastage can be used for feeding. Other surveys have shown that 15%-20% of household food losses can be traced to food packaging. Therefore, new innovative packaging systems can lessen the environmental effect of food wastage to extend shelf‐life to lower food loss in the process distribution chain and at the household level.

Keywords: food packaging, biodegradable polymer, intelligent packaging, shelf-life

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Authors: Indika Fernando, Jiangang Fei, Roger Stanley, Hossein Enshaei

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Delicate produce such as fresh fruits are increasingly susceptible to physiological damage during the essential post-harvest operations such as transport and handling. Vibration and shock during the distribution are identified factors for produce damage within post-harvest supply chains. Mechanical damages caused during transit may significantly diminish the quality of fresh produce which may also result in a substantial wastage. Bananas are one of the staple fruit crops and the most sold supermarket produce in Australia. It is also the largest horticultural industry in the state of Queensland where 95% of the total production of bananas are cultivated. This results in significantly lengthy interstate supply chains where fruits are exposed to prolonged vibration and shocks. This paper is focused on determining the shock and vibration levels experienced by packaged bananas during transit from the farm gate to the retail market. Tri-axis acceleration data were captured by custom made accelerometer based data loggers which were set to a predetermined sampling rate of 400 Hz. The devices recorded data continuously for 96 Hours in the interstate journey of nearly 3000 Km from the growing fields in far north Queensland to the central distribution centre in Melbourne in Victoria. After the bananas were ripened at the ripening facility in Melbourne, the data loggers were used to capture the transport and handling conditions from the central distribution centre to three retail outlets within the outskirts of Melbourne. The quality of bananas were assessed before and after transport at each location along the supply chain. Time series vibration and shock data were used to determine the frequency and the severity of the transient shocks experienced by the packages. Frequency spectrogram was generated to determine the dominant frequencies within each segment of the post-harvest supply chain. Root Mean Square (RMS) acceleration levels were calculated to characterise the vibration intensity during transport. Data were further analysed by Fast Fourier Transform (FFT) and the Power Spectral Density (PSD) profiles were generated to determine the critical frequency ranges. It revealed the frequency range in which the escalated energy levels were transferred to the packages. It was found that the vertical vibration was the highest and the acceleration levels mostly oscillated between ± 1g during transport. Several shock responses were recorded exceeding this range which were mostly attributed to package handling. These detrimental high impact shocks may eventually lead to mechanical damages in bananas such as impact bruising, compression bruising and neck injuries which affect their freshness and visual quality. It was revealed that the frequency range between 0-5 Hz and 15-20 Hz exert an escalated level of vibration energy to the packaged bananas which may result in abrasion damages such as scuffing, fruit rub and blackened rub. Further research is indicated specially in the identified critical frequency ranges to minimise exposure of fruits to the harmful effects of vibration. Improving the handling conditions and also further study on package failure mechanisms when exposed to transient shock excitation will be crucial to improve the visual quality of bananas within the post-harvest supply chain in Australia.

Keywords: bananas, handling, post-harvest, supply chain, shocks, transport, vibration

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Authors: Shirin Jalili, Sadegh Hasannia, Hadi Shirzad, Afshin Khara

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Morphine is one of the most medicinally important analgesics and narcotics. Structurally, it is classified as an alkaloid because of the presence of nitrogen. Its structure is similar to that of codeine, thebaine, and heroin. An immunoassay to accurately discriminate between these analogous alkaloids would be highly beneficial. A key factor for such an assay is specificity with high sensitivity, which is totally dependent on the antibody employed. However, most antibodies against haptens are polyclonal serum antibodies that exhibit significant cross-reactivities with closely related compounds. The camel-derived single-chain antibody fragments (VHH) are the smallest molecules with antigen-binding capacity, possessing unique properties compared to other conventional antibodies. In this study, a library containing the VHH genes of a camel immunized with with morphine conjugated BSA following phage display technology was generated. By screening the camel-derived variable region of the heavy chain cDNA phage display library with the ability to bind the desired hapten, we obtained some nanobodies that recognize this hapten. Phage display expression of the Nbs from this library and pannings against this hapten resulted in a clear enrichment of four distinct Nb-displaying phages with specificity for morphine that could be a potential target site for the development of new strategies for the development of a biosensor for detecting illicit drug.

Keywords: phage display, nanobody, Morphine-3, glucuronide, ELISA, biosensor

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Authors: Yena Lee, Vassilis M. Charitopoulos, Karthik Thyagarajan, Ian Morris, Jose M. Pinto, Lazaros G. Papageorgiou

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With globalisation, the need to have better coordination of production and distribution decisions has become increasingly important for industrial gas companies in order to remain competitive in the marketplace. In this work, we investigate a problem that integrates production, inventory, and routing decisions in a liquid oxygen supply chain. The oxygen supply chain consists of production facilities, external third-party suppliers, and multiple customers, including hospitals and industrial customers. The product produced by the plants or sourced from the competitors, i.e., third-party suppliers, is distributed by a fleet of heterogenous vehicles to satisfy customer demands. The objective is to minimise the total operating cost involving production, third-party, and transportation costs. The key decisions for production include production and inventory levels and product amount from third-party suppliers. In contrast, the distribution decisions involve customer allocation, delivery timing, delivery amount, and vehicle routing. The optimisation of the coordinated production, inventory, and routing decisions is a challenging problem, especially when dealing with large-size problems. Thus, we present a two-stage procedure to solve the integrated problem efficiently. First, the problem is formulated as a mixed-integer linear programming (MILP) model by simplifying the routing component. The solution from the first-stage MILP model yields the optimal customer allocation, production and inventory levels, and delivery timing and amount. Then, we fix the previous decisions and solve a detailed routing. In the second stage, we propose a column generation scheme to address the computational complexity of the resulting detailed routing problem. A case study considering a real-life oxygen supply chain in the UK is presented to illustrate the capability of the proposed models and solution method. Furthermore, a comparison of the solutions from the proposed approach with the corresponding solutions provided by existing metaheuristic techniques (e.g., guided local search and tabu search algorithms) is presented to evaluate the efficiency.

Keywords: production planning, inventory routing, column generation, mixed-integer linear programming

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Authors: N. Singh, A. Khullar, R. Shrivastava, I. Singh, A. S. Kumar

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Steel forms the basis of any modern society and is essential to economic growth. India’s annual crude steel production has seen a consistent increase over the past years and is poised to grow to 300 million tons per annum by 2030-31 from current level of 110-120 million tons per annum. Steel industry is highly capital-intensive industry and to remain competitive, it is imperative that it invests in operational excellence. Due to inherent nature of the industry, there is large amount of variability in its supply chain both internally and externally. Production and productivity of a steel plant is greatly affected by the bottlenecks present in material flow logistics. The internal logistics constituting of transport of liquid metal within a steel melting shop (SMS) presents an opportunity in increasing the throughput with marginal capital investment. The study was carried out at one of the SMS of an integrated steel plant located in the eastern part of India. The plant has three SMS’s and the study was carried out at one of them. The objective of this study was to identify means to optimize SMS hot metal logistics through application of industrial engineering techniques. The study also covered the identification of non-value-added activities and proposed methods to eliminate the delays and improve the throughput of the SMS.

Keywords: optimization, steel making, supply chain, throughput enhancement, workforce productivity

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Authors: Jana Abu Ahmada, Zaineb Mohamed, Ilyasse Aksikas

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The linear quadratic control system of hyperbolic first order partial differential equations (PDEs) are presented. The aim of this research is to control chemical reactions. This is achieved by converting the PDEs system to ordinary differential equations (ODEs) using the method of characteristics to reduce the system to control it by using the integral reinforcement learning. The designed controller is applied to a catalytic cracking reactor. Background—Transport-Reaction systems cover a large chemical and bio-chemical processes. They are best described by nonlinear PDEs derived from mass and energy balances. As a main application to be considered in this work is the catalytic cracking reactor. Indeed, the cracking reactor is widely used to convert high-boiling, high-molecular weight hydrocarbon fractions of petroleum crude oils into more valuable gasoline, olefinic gases, and others. On the other hand, control of PDEs systems is an important and rich area of research. One of the main control techniques is feedback control. This type of control utilizes information coming from the system to correct its trajectories and drive it to a desired state. Moreover, feedback control rejects disturbances and reduces the variation effects on the plant parameters. Linear-quadratic control is a feedback control since the developed optimal input is expressed as feedback on the system state to exponentially stabilize and drive a linear plant to the steady-state while minimizing a cost criterion. The integral reinforcement learning policy iteration technique is a strong method that solves the linear quadratic regulator problem for continuous-time systems online in real time, using only partial information about the system dynamics (i.e. the drift dynamics A of the system need not be known), and without requiring measurements of the state derivative. This is, in effect, a direct (i.e. no system identification procedure is employed) adaptive control scheme for partially unknown linear systems that converges to the optimal control solution. Contribution—The goal of this research is to Develop a characteristics-based optimal controller for a class of hyperbolic PDEs and apply the developed controller to a catalytic cracking reactor model. In the first part, developing an algorithm to control a class of hyperbolic PDEs system will be investigated. The method of characteristics will be employed to convert the PDEs system into a system of ODEs. Then, the control problem will be solved along the characteristic curves. The reinforcement technique is implemented to find the state-feedback matrix. In the other half, applying the developed algorithm to the important application of a catalytic cracking reactor. The main objective is to use the inlet fraction of gas oil as a manipulated variable to drive the process state towards desired trajectories. The outcome of this challenging research would yield the potential to provide a significant technological innovation for the gas industries since the catalytic cracking reactor is one of the most important conversion processes in petroleum refineries.

Keywords: PDEs, reinforcement iteration, method of characteristics, riccati equation, cracking reactor

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Authors: Gaurav Kumar Sinha

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As the world grapples with climate challenges, this study highlights the instrumental role of AWS services in amplifying the impact of LCVs. Their ability to harness the cloud, data analytics, and scalable infrastructure offered by AWS empowers LCVs to innovate, scale, and drive meaningful change in the quest for a sustainable future. This study serves as a rallying cry, urging stakeholders to recognize, embrace, and maximize the potential of AWS-powered solutions in advancing sustainable and resilient global initiatives.

Keywords: low carbon ventures, sustainability solutions, AWS services, data analytics

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Authors: Rudzani Manafe, Ezekiel Green

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Brucella, has many different virulence factors that act as a causative agent of brucellosis, depending on the environment and other factors, some factors may play a role more than others during infection and as a result, play a role in becoming a causative agent for pathogenesis. Brucella melitensis and Brucella abortus are considered to be pathogenic to humans. The genetic regularity of nine potential causes of virulence of two Brucella species in Eastern Cape livestock have been examined. A hundred and twenty isolates obtained from Molecular Pathogenesis and Molecular Epidemiology Research Group (MPMERG) were used for this study. All isolates were grown on Brucella agar medium. Nine primer pairs were used for the detection of virB2, virB5, vceC, btpA, btpB, prpA, betB, bpe275, and bspB virulence factors using Polymerase chain reaction (PCR). Approximately 100% was observed for genes BecC and BetB from B. arbotus. While the lowest gene observed was PrpA at 4.6% from B. arbotus. BetB was detected in 34.7%, while virB2 and prpA (0%) were not detected in B. melitensis. The results from this research suggest that most isolates of Brucella have virulence-related genes associated with disease pathogenesis. Finally, our findings showed that Brucella strains in the Eastern Cape Province are extremely virulent as virulence characteristics exist in most strains investigated.

Keywords: putative virulence genes, brucella, polymerase chain reaction, milk

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Authors: Varshith Kotagiri, Lei Li

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Fluorescent sensors are organic fluorophores that detect specific analytes with quantitative fluorescence intensity changes. They have offered impressive benefits compared with instrumental techniques, such as low cost, high selectivity, and rapid responses. One issue that limits the fluorescent sensors for further application is their poor solubility in the aqueous medium, where most targeted analytes, including metal ions, inorganic anions, and neutral biomolecules, are readily soluble. When fluorescent sensors are utilized to detect these analytes, a heterogeneous phase is formed. In most cases, an extra water-miscible organic solvent is needed as an additive to facilitate the sensing process, which complicates the measurement operations and produces more organic waste. We aim to resolve this issue by skillful molecular design to introduce a hydrophilic side chain to the fluorescent sensor, increasing its water solubility and facilitating its sensing process to analytes, like various protons, fluoride ions, and copper ions, in an aqueous medium. Simultaneously, its sensitivity and selectivity will be retained. This work will simplify the sensing operations and reduce the amount of organic waste produced during the measurement. This strategy will additionally be of broad interest to the chemistry community, as it introduces the idea of modifying the molecular structure to apply an initial hydrophobic compound under hydrophilic conditions in a feasible way.

Keywords: organic fluorescent sensor, analytes, sensing, aqueous medium, phenanthroimidazole, hydrophilic side chain

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Authors: A. Douka, S. Vouyiouka, L. M. Papaspyridi, D. Korres, C. Papaspyrides

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A "green" process was studied for the preparation of partially renewable aliphatic polyesters based on 1,4-butanediol and 1,8-octanediol with various diacids and derivatives, namely diethyl succinate, adipic acid, sebacic acid, 1,12-dodecanedioic acid and 1,14-tetradecanedioic acid. A first step of enzymatic prepolymerization was carried out in the presence of two different solvents, toluene and diphenylether, applying molecular sieves and vacuum, respectively, to remove polycondensation by-products. Poly(octylene adipate) (PE 8.6), poly(octylene dodecanate)(PE 8.12) and poly(octylene tetradecanate) (PE 8.14) were firstly enzymatically produced in toluene using molecular sieves giving however, low-molecular-weight products. Thereafter, the synthesis of PE 8.12 and PE 8.14 was examined under optimized conditions using diphenylether as solvent and a more vigorous by-product removal step, such as application of vacuum. Apart from these polyesters, the optimized process was also implemented for the production of another long-chain polyester-poly(octylene sebacate) (PE 8.10) and a short-chain polyester-poly(butylene succinate) (PE 4.4). Subsequently, bulk post-polymerization in the melt or solid state was performed. SSP runs involved absence of biocatalyst and reaction temperatures (T) in the vicinity of the prepolymer melting point (Tm-T varied between 15.5 up to 4oC). Focusing on PE 4.4 and PE 8.12, SSP took place under vacuum or flowing nitrogen leading to increase of the molecular weight and improvement of the end product physical appearance and thermal properties.

Keywords: aliphatic polyester, enzymatic polymerization, solid state polymerization, Novozym 435

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Authors: Boris G. German, Edward Jiménez, Sebastián Espinoza, Andrés G. Chico, Ricardo A. Narváez

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The unique flora and fauna of The Galapagos Islands has leveraged a tourism-driven growth in the islands. Nonetheless, such development is energy-intensive and requires thousands of gallons of diesel each year for thermoelectric electricity generation. The needed transport of fossil fuels from the continent has generated oil spillages and affectations to the fragile ecosystem of the islands. The Zero Fossil Fuels initiative for The Galapagos proposed by the Ecuadorian government as an alternative to reduce the use of fossil fuels in the islands, considers the replacement of diesel in thermoelectric generators, by Jatropha curcas vegetable oil. However, the Jatropha oil supply cannot entirely cover yet the demand for electricity generation in Galapagos. Within this context, the present work aims to provide an optimization model that can be used as a selection criterion for approving new Jatropha Curcas collection points in rural areas of Manabi-Ecuador. For this purpose, existing Jatropha collection points in Manabi were grouped under three regions: north (7 collection points), center (4 collection points) and south (9 collection points). Field work was carried out in every region in order to characterize the collection points, to establish local Jatropha supply and to determine transportation costs. Data collection was complemented using GIS software and an objective function was defined in order to determine the profit associated to Jatropha oil production. The market price of both Jatropha oil and residual cake, were considered for the total revenue; whereas Jatropha price, transportation and oil extraction costs were considered for the total cost. The tonnes of Jatropha fruit and seed, transported from collection points to the extraction plant, were considered as variables. The maximum and minimum amount of the collected Jatropha from each region constrained the optimization problem. The supply chain was optimized using linear programming in order to maximize the profits. Finally, a sensitivity analysis was performed in order to find a profit-based criterion for the acceptance of future collection points in Manabi. The maximum profit reached a value of $ 4,616.93 per year, which represented a total Jatropha collection of 62.3 tonnes Jatropha per year. The northern region of Manabi had the biggest collection share (69%), followed by the southern region (17%). The criteria for accepting new Jatropha collection points in the rural areas of Manabi can be defined by the current maximum profit of the zone and by the variation in the profit when collection points are removed one at a time. The definition of new feasible collection points plays a key role in the supply chain associated to Jatropha oil production. Therefore, a mathematical model that assists decision makers in establishing new collection points while assuring profitability, contributes to guarantee a continued Jatropha oil supply for Galapagos and a sustained economic growth in the rural areas of Ecuador.

Keywords: collection points, Jatropha curcas, linear programming, supply chain

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Authors: Ali Alavi, Hong-Oanh Nguyen, ‎Jiangang Fei, Jafar Sayareh

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The recent competitive market in the port sector highly depend on logistics practices, functions ‎and activities and seaports play a key role in port logistics chains. Despite the well-articulated importance of ports and terminals in integrated logistics, the role of success factors in port logistics integration has been rarely mentioned‎. The objective of this paper is to ‎fill this gap in the literature and provide an insight into how seaports and terminals may improve their logistics integration. First, a literature review of studies on logistics integration in seaports and terminals is conducted. Second, a new conceptual framework for port logistics integration is proposed to incorporate the role of the new variables emerging from the recent developments in the global business environment. Third, the model tested in Iranian port and maritime sector using self-administered and online survey among logistics chain actors in Iranian seaports such shipping line operators, logistics service providers, port authorities, logistics companies and other related actors. The results have found the logistics process and operations, information integration, ‎value-added services, and logistics practices being influential to logistics integration. A proposed conceptual framework is developed to extend the existing ‎framework and incorporates the variables namely organizational activities, resource ‎sharing, and institutional support.‎ Further examination of the proposed model across multiple contexts is necessary for the validity of the findings. The framework could be more detailed on each factor and consider actors perspective.

Keywords: maritime logistics‎, port integration‎, logistics integration‎, supply chain integration

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Authors: Aravind G., Arshinder Kaur, Pushpavanam S.

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There is a strong emphasis on shifting to electric vehicles (EVs) throughout the globe for reducing the impact on global warming following the Paris climate accord. Lithium-ion batteries (LIBs) are predominantly used in EVs, and these can be a significant threat to the environment if not disposed of safely. Lithium is also a valuable resource not widely available. There are several research groups working on developing an efficient recycling process for LIBs. Two routes - pyrometallurgical and hydrometallurgical processes have been proposed for recycling LIBs. In this paper, we focus on life cycle assessment (LCA) as a tool to quantify the environmental impact of these recycling processes. We have defined the boundary of the LCA to include only the recycling phase of the end-of-life (EoL) of the battery life cycle. The analysis is done assuming ideal conditions for the hydrometallurgical and a combined hydrometallurgical and pyrometallurgical process in the inventory analysis. CML-IA method is used for quantifying the impact assessment across eleven indicators. Our results show that cathode, anode, and foil contribute significantly to the impact. The environmental impacts of both hydrometallurgical and combined recycling processes are similar across all the indicators. Further, the results of LCA are used in developing a multi-objective optimization model for the design of lithium-ion battery recycling network. Greenhouse gas emissions and cost are the two parameters minimized for the optimization study.

Keywords: life cycle assessment, lithium-ion battery recycling, multi-objective optimization, network design, reverse supply chain

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Authors: Ahmad Afif, Teuku Yuri M. Zagloel

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Sustainable supply chain management is a new pattern that has emerged recently in industry and companies. The procurement process is one of the key factors for efficiency in supply chain management practices. Partnership is one of the procurement strategies for strategic items. The success factors of the partnership must be determined to avoid things that endanger the financial and operational status of the company. The current supplier partnership research focuses on the selection of general criteria and sustainable supplier selection. Currently, there is still limited research on the success factors of supplier partnerships that focus on strategic items in the coal mining industry. Meanwhile, the procurement of coal mining has its own characteristics, and there are regulations related to the procurement of goods. Therefore, this research was conducted to determine the categories of goods that are included in the strategic items and to design the success factors of supplier partnerships. The main factors studied are general, financial, production, reputation, synergies, and sustainable. The research was conducted using the Kraljic method to determine the categories of goods that are included in the strategic items. To design a supplier partnership success factor using the Hybrid Multi Criteria Decision Making method. Integrated Fuzzy AHP-Fuzzy TOPSIS is used to determine the weight of the success factors of supplier partnerships and to rank suppliers on the factors used.

Keywords: supplier, partnership, strategic item, success factors, and coal mining industry

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Authors: Seyed Esmail Seyedi Bariran, Khairul Salleh Mohamed Sahari

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In multi-echelon supply chain networks, optimal supplier selection significantly depends on the accuracy of suppliers’ performance prediction. Different methods of multi criteria decision making such as ANN, GA, Fuzzy, AHP, etc have been previously used to predict the supplier performance but the “black-box” characteristic of these methods is yet a major concern to be resolved. Therefore, the primary objective in this paper is to implement an artificial intelligence-based gene expression programming (GEP) model to compare the prediction accuracy with that of ANN. A full factorial design with %95 confidence interval is initially applied to determine the appropriate set of criteria for supplier performance evaluation. A test-train approach is then utilized for the ANN and GEP exclusively. The training results are used to find the optimal network architecture and the testing data will determine the prediction accuracy of each method based on measures of root mean square error (RMSE) and correlation coefficient (R2). The results of a case study conducted in Supplying Automotive Parts Co. (SAPCO) with more than 100 local and foreign supply chain members revealed that, in comparison with ANN, gene expression programming has a significant preference in predicting supplier performance by referring to the respective RMSE and R-squared values. Moreover, using GEP, a mathematical function was also derived to solve the issue of ANN black-box structure in modeling the performance prediction.

Keywords: Supplier Performance Prediction, ANN, GEP, Automotive, SAPCO

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Authors: Hai Hoang, Thanh Xuan Nguyen Thi, Guillaume Galliero

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Coarse-Grained (CG) molecular simulations have shown to be an efficient way to estimate thermophysical (static and dynamic) properties of fluids. Several strategies have been developed and reported in the literature for defining CG molecular models. Among them, those based on a top-down strategy (i.e. CG molecular models related to macroscopic observables), despite being heuristic, have increasingly gained attention. This is probably due to its simplicity in implementation and its ability to provide reasonable results for not only simple but also complex systems. Regarding simple Force-Fields associated with these CG molecular models, it has been found that the four parameters Mie chain model is one of the best compromises to describe thermophysical static properties (e.g. phase diagram, saturation pressure). However, parameterization procedures of these Mie-chain GC molecular models given in literature are generally insufficient to simultaneously provide static and dynamic (e.g. viscosity) properties. To deal with such situations, we have extended the corresponding states by using a quantity associated with the liquid viscosity. Results obtained from molecular simulations have shown that our approach is able to yield good estimates for both static and dynamic thermophysical properties for various real non-associating fluids. In addition, we will show that on simple (e.g. phase diagram, saturation pressure) and complex (e.g. thermodynamic response functions, thermodynamic energy potentials) static properties, results of our scheme generally provides improved results compared to existing approaches.

Keywords: coarse-grained model, mie potential, molecular simulations, thermophysical properties, phase equilibria

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Authors: Sidra Suleman, Maliha Suleman, Jinesh Shah

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Maxillary canines play a crucial role in occlusion and aesthetics. Successful management of impacted canines requires early identification and intervention to prevent complications such as resorption of adjacent teeth and cystic changes. Although removal of the deciduous canine can encourage normal eruption of its successor, this is not always successful. Some patients may require surgical exposure and bonding of a gold chain to mobilise and align the canine, which can take up to 3 years. As this procedure has various risks, patients need to be appropriately consented to. Failure of such treatment commonly occurs due to inadequate anchorage or failure of the gold chain attachment, but in some cases, this is due to ankylosis. Aim: The aim of this study was to determine the incidence of ankylosis of unerupted maxillary ectopic canines following surgical exposure and orthodontic alignment at the Maxillofacial and Orthodontic Department, Royal Stoke University Hospital (RSUH), United Kingdom. Methodology: Patients treated from January 1, 2017, to December 31, 2019, were retrospectively studied. Electronic records with post-treatment follow-up at 3-6 months and 12-15 months were extracted and analysed. Patients were excluded based on three criteria, non-compliance with orthodontic treatment post-surgery, presence of canine transposition, and external orthodontic treatment. Sample: Overall, 159 suitable patients were selected from the 171 patients identified. Surgical exposure and gold chain bonding was carried out for a total of 206 maxillary canines, with the pattern of impaction being 159 (77.2 %) palatal, 46 (22.3%) buccal, and 1 (0.49%) in line of the arch. The sample consisted of 57 (35.8%) males and 102 (64.2%) females between the age range of 10 to 32 years, with the mean age being 15 years. The procedures were carried out under general anaesthesia for all but three patients, with two cases being repeats. Closed exposure was carried out for 189 (91.7%) canines. Results: The incidence of ankylosis from this study was 0.97%. In total, two patients had upper left canine ankylosis, which was identified at their 12-15 months orthodontic follow-up. Both patients were males, one having closed exposure at age 15 and the other having open exposure at age 19. Conclusions: Although this data shows that there is a low risk of ankylosis (0.97%), it highlights the difficulty in predicting which patients may be affected, and thus, a thorough pre-treatment assessment and careful observation during treatment is necessary. Future studies involving larger cohorts are warranted to further analyse factors affecting outcomes.

Keywords: ankylosis, ectopic, maxillary canines, orthodontics

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Authors: Migena Mana, Ahmed Khalid Syed, Abdul Malik, Nikhil Cherian

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In recent years, advancements in deep learning enabled researchers to tackle the problem of self-driving cars. Car companies use huge datasets to train their deep learning models to make autonomous cars a reality. However, this approach has certain drawbacks in that the state space of possible actions for a car is so huge that there cannot be a dataset for every possible road scenario. To overcome this problem, the concept of reinforcement learning (RL) is being investigated in this research. Since the problem of autonomous driving can be modeled in a simulation, it lends itself naturally to the domain of reinforcement learning. The advantage of this approach is that we can model different and complex road scenarios in a simulation without having to deploy in the real world. The autonomous agent can learn to drive by finding the optimal policy. This learned model can then be easily deployed in a real-world setting. In this project, we focus on three RL algorithms: Q-learning, Deep Deterministic Policy Gradient (DDPG), and Proximal Policy Optimization (PPO). To model the environment, we have used TORCS (The Open Racing Car Simulator), which provides us with a strong foundation to test our model. The inputs to the algorithms are the sensor data provided by the simulator such as velocity, distance from side pavement, etc. The outcome of this research project is a comparative analysis of these algorithms. Based on the comparison, the PPO algorithm gives the best results. When using PPO algorithm, the reward is greater, and the acceleration, steering angle and braking are more stable compared to the other algorithms, which means that the agent learns to drive in a better and more efficient way in this case. Additionally, we have come up with a dataset taken from the training of the agent with DDPG and PPO algorithms. It contains all the steps of the agent during one full training in the form: (all input values, acceleration, steering angle, break, loss, reward). This study can serve as a base for further complex road scenarios. Furthermore, it can be enlarged in the field of computer vision, using the images to find the best policy.

Keywords: autonomous driving, DDPG (deep deterministic policy gradient), PPO (proximal policy optimization), reinforcement learning

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Authors: Asma Poursoroush

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Solid-supported lipid bilayers are often used as a simple model for studies of biological membranes. The presence of a solid substrate that interacts attractively with lipid head-groups is expected to affect the phase behavior of the supported bilayer. Molecular dynamics simulations of a coarse-grained model are thus performed to investigate the phase behavior of supported one-component lipid bilayer membranes. Our results show that the attraction of the lipid head groups to the substrate leads to a phase behavior that is different from that of a free standing lipid bilayer. In particular, we found that the phase behaviors of the two leaflets are decoupled in the presence of a substrate. The proximal leaflet undergoes a clear gel-to-fluid phase transition at a temperature lower than that of a free standing bilayer, and that decreases with increasing strength of the substrate-lipid attraction. The distal leaflet, however, undergoes a change from a homogeneous liquid phase at high temperatures to a heterogeneous state consisting of small liquid and gel domains, with the average size of the gel domains that increases with decreasing temperature. While the chain order parameter of the proximal leaflet clearly shows a gel-fluid phase transition, the chain order parameter of the distal leaflet does not exhibit a clear phase transition. The decoupling in the phase behavior of the two leaflets is due to a non-symmteric lipid distribution in the two leaflets resulting from the presence of the substrate.

Keywords: membrane, substrate, molecular dynamics, simulation

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Authors: Yuan-Jye Tseng, Shin-Han Lin

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In this research, a mathematical model for integrated evaluation of green design and green manufacturing processes is presented. To design a product, there can be alternative options to design the detailed components to fulfill the same product requirement. In the design alternative cases, the components of the product can be designed with different materials and detailed specifications. If several design alternative cases are proposed, the different materials and specifications can affect the manufacturing processes. In this paper, a new concept for integrating green design and green manufacturing processes is presented. A green design can be determined based the manufacturing processes of the designed product by evaluating the green criteria including energy usage and environmental impact, in addition to the traditional criteria of manufacturing cost. With this concept, a mathematical model is developed to find the green design and the associated green manufacturing processes. In the mathematical model, the cost items include material cost, manufacturing cost, and green related cost. The green related cost items include energy cost and environmental cost. The objective is to find the decisions of green design and green manufacturing processes to achieve the minimized total cost. In practical applications, the decision-making can be made to select a good green design case and its green manufacturing processes. In this presentation, an example product is illustrated. It shows that the model is practical and useful for integrated evaluation of green design and green manufacturing processes.

Keywords: supply chain management, green supply chain, green design, green manufacturing, mathematical model

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Authors: Ana Paula S. Horodenski, Priscila Pelegrini, Salli Baggenstoss

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The brewing industry with artisanal concepts seeks to serve a specific market, with diversified production that has been gaining ground in the national environment, also in the Amazon region. This growth is due to the more demanding consumer, with a diversified taste that wants to try new types of beer, enjoying products with new aromas, flavors, as a differential of what is so widely spread through the big industrial brands. Thus, through qualitative research methods, the study aimed to investigate how is the process of managing the production of a craft brewery in a city in the northern State of Mato Grosso (BRAZIL), providing knowledge of production processes and strategies in the industry. With the efficient use of resources, it is possible to obtain the necessary quality and provide better performance and differentiation of the company, besides analyzing the best management model. The research is descriptive with a qualitative approach through a case study. For the data collection, a semi-structured interview was elaborated, composed of the areas: microbrewery characterization, artisan beer production process, and the company supply chain management. Also, production processes were observed during technical visits. With the study, it was verified that the artisan brewery researched develops preventive maintenance strategies with the inputs, machines, and equipment, so that the quality of the product and the production process are achieved. It was observed that the distance from the supplying centers makes the management of processes and the supply chain be carried out with a longer planning time so that the delivery of the final product is satisfactory. The production process of the brewery is composed of machines and equipment that allows the control and quality of the product, which the manager states that for the productive capacity of the industry and its consumer market, the available equipment meets the demand. This study also contributes to highlight one of the challenges for the development of small breweries in front of the market giants, that is, the legislation, which fits the microbreweries as producers of alcoholic beverages. This makes the micro and small business segment to be taxed as a major, who has advantages in purchasing large batches of raw materials and tax incentives because they are large employers and tax pickers. It was possible to observe that the supply chain management system relies on spreadsheets and notes that are done manually, which could be simplified with a computer program to streamline procedures and reduce risks and failures of the manual process. In relation to the control of waste and effluents affected by the industry is outsourced and meets the needs. Finally, the results showed that the industry uses preventive maintenance as a productive strategy, which allows better conditions for the production and quality of artisanal beer. The quality is directly related to the satisfaction of the final consumer, being prized and performed throughout the production process, with the selection of better inputs, the effectiveness of the production processes and the relationship with the commercial partners.

Keywords: artisanal brewery, production management, production processes, supply chain

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Authors: Abdulatif Abdulsalam Mohamed Shaban

Abstract:

A.C motors, in general, have superior performance characteristics to their d.c. counterparts. However, despite these advantage a.c. motors lack the controllability and simplicity and so d.c. motors retain a competitive edge where precise control is required. As part of an overall project to develop an improved cycloconverter control strategy for induction motors. Simulation and modelling techniques have been developed. This contribution describes a method used to simulate an induction motor drive using the SIMULINK toolbox within MATLAB software. The cycloconverter fed induction motor is principally modelled using the d-q axis equations. Results of the simulation for a given set of induction motor parameters are also presented.

Keywords: simulation, converter, motor, cycloconverter

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Authors: Min-Pei Ling

Abstract:

Aflatoxin is a fungal secondary metabolite with high toxicity capable of contaminating various types of food crops. It has been identified as a Group 1 human carcinogen by the International Agency for Research on Cancer. Chronic aflatoxin exposure has caused a worldwide public food safety concern. Peanuts and peanut products are the major sources of aflatoxin exposure. Therefore, some reduction interventions have been developed to minimize contamination through the peanut production chain. The purpose of this study is to estimate the efficacy of interventions in reducing the health impact of hepatocellular carcinoma caused by aflatoxin contamination in peanuts. The estimated total disability-adjusted life-years (DALYs) was calculated using FDA-iRISK online software. Six aflatoxin reduction strategies were evaluated, including good agricultural practice (GAP), biocontrol, Purdue Improved Crop Storage packaging, basic processing, ozonolysis, and ultraviolet irradiation. The results indicated that basic processing could prevent huge public health loss of 4,079.7–21,833 total DALYs per year, which accounted for 39.6% of all decreased total DALYs. GAP and biocontrol were both effective strategies in the farm field, while the other three interventions were limited in reducing total DALYs. In conclusion, this study could help farmers, processing plants, and government policymakers to alleviate aflatoxin contamination issues in the peanut production chain.

Keywords: aflatoxin, health burden, disability-adjusted life-years, peanuts

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Authors: Zunnu Raen Akhtar, U. Irshad, M. Majid

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Due to the widespread cultivation of transgenic cotton, intense selection pressure resulted in resistant allele in pink bollworm, Pectinophora gossypiella (Gelechiidae: Lepidoptera). A resistant strain of pink bollworm against transgenic cotton has become a challenge to Integrated Resistance Management (IRM) in the World. Laboratory and field studies were conducted to determine the resistant strains of pink bollworm by performing bioassay, extracting the DNA, conducting PCR of both laboratory as well as field collected pink bollworms to observe the developed resistance. In all of the studies, two Bt varieties FH-142 and FH-118 expressing Cry1Ac compared to non-Bt (Control) were tested against pink bollworm. In the laboratory, bioassay results showed that there was no significant mortality difference between Bt and non-Bt varieties. Similar mortality percentage was observed in transgenic and non-transgenic (control) variety. Insects which were survived after bioassay, as well as those collected from the Bt cotton fields, were selected for further molecular studies. DNA extraction followed by PCR was conducted to check the resistant strains in pink bollworm. In field studies, we also observed the population dynamics of pink boll worms on Bt as compared to non-Bt varieties. Laboratory and field studies confirmed that resistant strains occurs in Pakistani Bt cotton fields. Different strategies should be adopted to combat that serious prevailing resistance issues.

Keywords: transgenic cotton, resistance, pectinophora gossypiella, , integrated resistance management (IRM), polymerase chain reaction (PCR)

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Authors: Ässia Boukhatmi, Roger Nyffenegger

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The expansion of solar energy as a means to address the climate crisis is undisputed, but the increasing number of new photovoltaic (PV) modules being put on the market is simultaneously leading to increased challenges in terms of managing the growing waste stream. Many of the discarded modules are still fully functional but are often damaged by improper handling after disassembly or not properly tested to be considered for a second life. In addition, the collection rate for dismantled PV modules in several European countries is only a fraction of previous projections, partly due to the increased number of illegal exports. The underlying problem for those market imperfections is an insufficient data exchange between the different actors along the PV value chain, as well as the limited traceability of PV panels during their lifetime. As part of the Horizon 2020 project CIRCUSOL, an asset database prototype was developed to tackle the described problems. In an iterative process applying the design science research methodology, different business models, as well as the technical implementation of the database, were established and evaluated. To explore the requirements of different stakeholders for the development of the database, surveys and in-depth interviews were conducted with various representatives of the solar industry. The proposed database prototype maps the entire value chain of PV modules, beginning with the digital product passport, which provides information about materials and components contained in every module. Product-related information can then be expanded with performance data of existing installations. This information forms the basis for the application of data analysis methods to forecast the appropriate end-of-life strategy, as well as the circular economy potential of PV modules, already before they arrive at the recycling facility. The database prototype could already be enriched with data from different data sources along the value chain. From a business model perspective, the database offers opportunities both in the area of reuse as well as with regard to the certification of sustainable modules. Here, participating actors have the opportunity to differentiate their business and exploit new revenue streams. Future research can apply this approach to further industry and product sectors, validate the database prototype in a practical context, and can serve as a basis for standardization efforts to strengthen the circular economy.

Keywords: business model, circular economy, database, design science research, solar industry

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Authors: Emad Al-Abdallat, Faris G. Bakri, Azmi Mahafza, Rayyan Al Ali, Nidaa Ababneh, Ahmed Idhair

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Background: Morgues are high-risk areas for the spread of infection from the cadavers to the staff during the postmortem examination. Infection can spread from corpses to workers by the airborne route, by direct contact, or from needle and sharp object injuries. Objective: Knowledge about the prevalence of these infections among autopsies is prudent to appreciate any risk of transmission and to further enforce safety measures. Method: A total of 242 autopsies were tested. Age ranged from 3 days to 94 years (median 75.5 years, mean 45.3 (21.9 ± SD)). There were 172 (71%) males. Results: The cause of death was considered natural in 137 (56.6%) cases, accidental in 89 (36.8%), homicidal in 9 (3.7%), suicidal in 4 (1.7%), and unknown in 3 (1.2%). Hepatitis B surface antigen was positive in 5 (2.1%) cases. Hepatitis C virus antibody was detected in 5 (2.1%) cases and the hepatitis C virus polymerase chain reaction was positive in 2 of them (0.8%). HIV antibody was not detected in any of the cases. Conclusions: Autopsies can be associated with exposure to blood borne viruses. Autopsies performed during the study period were tested for hepatitis B surface antigen, hepatitis C virus antibody, and human immunodeficiency virus antibody. Positive tests were subsequently confirmed by polymerase chain reaction. There is low prevalence of infections with these viruses in our autopsy cases. However, the risk of transmission remains a threat. Healthcare workers in the forensic departments should adhere to standard precautions.

Keywords: autopsy, hepatitis B virus, hepatitis C virus, human immunodeficiency virus, Jordan

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Authors: Attila Kiss, Erzsébet Némedi, Zoltán Naár

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As natural prebiotic (non-digestible) carbohydrates stimulate the growth of colon microflora and contribute to maintain the health of the host, analytical studies aiming at revealing the chemical behavior of these beneficial food components came to the forefront of interest. Food processing (especially baking) may lead to a significant conversion of the parent compounds, hence it is of utmost importance to characterize the transformation patterns and the plausible decomposition products formed by thermal degradation. The relevance of this work is confirmed by the wide-spread use of these carbohydrates (fructo-oligosaccharides, cyclodextrins, raffinose and resistant starch) in the food industry. More and more functional foodstuffs are being developed based on prebiotics as bioactive components. 12 different types of oligosaccharides have been investigated in order to reveal their thermal degradation characteristics. Different carbohydrate derivatives (D-fructose and D-glucose oligomers and polymers) have been exposed to elevated temperatures (150 °C 170 °C, 190 °C, 210 °C, and 220 °C) for 10 min. An advanced HPLC method was developed and used to identify the decomposition products of carbohydrates formed as a consequence of thermal treatment. Gradient elution was applied with binary solvent elution (acetonitrile, water) through amine based carbohydrate column. Evaporative light scattering (ELS) proved to be suitable for the reliable detection of the UV/VIS inactive carbohydrate degradation products. These experimental conditions and applied advanced techniques made it possible to survey all the formed intermediers. Change in oligomer distribution was established in cases of all studied prebiotics throughout the thermal treatments. The obtained results indicate increased extent of chain degradation of the carbohydrate moiety at elevated temperatures. Prevalence of oligomers with shorter chain length and even the formation of monomer sugars (D-glucose and D-fructose) might be observed at higher temperatures. Unique oligomer distributions, which have not been described previously are revealed in the case of each studied, specific carbohydrate, which might result in various prebiotic activities. Resistant starches exhibited high stability when being thermal treated. The degradation process has been modeled by a plausible reaction mechanism, in which proton catalyzed degradation and chain cleavage take place.

Keywords: prebiotics, thermal degradation, fructo-oligosaccharide, HPLC, ELS detection

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Authors: Baker Ssekitto, Ambrose Mbogo

Abstract:

The study reveals that indeed agriculture employs over 70% of Uganda’s population, of which majority are youth and women. The study further reveals that over 70% of the farmers are smallholder farmers based in rural areas, whose operations are greatly affected by; climate change, weak digital skills, limited access to productivity knowledge along value chains, limited access to quality farm inputs, weak logistics systems, limited access to quality extension services, weak business intelligence, limited access to quality markets among others. It finds that the emerging 4th industrial revolution powered by artificial intelligence, 5G and data science will provide possibilities of addressing some of these challenges. Furthermore, the study finds that despite rapid development of ICT4Agric Innovation, their uptake is constrained by a number of factors including; limited awareness of these innovations, low internet and smart phone penetration especially in rural areas, lack of appropriate digital skills, inappropriate programmes implementation models which are project and donor driven, limited articulation of value addition to various stakeholders among others. Majority of farmers and other value chain actors lacked knowledge and skills to harness the power of ICTs, especially their application of ICTs in monitoring and evaluation on quality of service in the extension system and farm level processes.

Keywords: artificial intelligence, productivity, ICT4agriculture, value chain, logistics

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