Search results for: numerical solutions
Commenced in January 2007
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Paper Count: 6887

Search results for: numerical solutions

227 Numerical Optimization of Cooling System Parameters for Multilayer Lithium Ion Cell and Battery Packs

Authors: Mohammad Alipour, Ekin Esen, Riza Kizilel

Abstract:

Lithium-ion batteries are a commonly used type of rechargeable batteries because of their high specific energy and specific power. With the growing popularity of electric vehicles and hybrid electric vehicles, increasing attentions have been paid to rechargeable Lithium-ion batteries. However, safety problems, high cost and poor performance in low ambient temperatures and high current rates, are big obstacles for commercial utilization of these batteries. By proper thermal management, most of the mentioned limitations could be eliminated. Temperature profile of the Li-ion cells has a significant role in the performance, safety, and cycle life of the battery. That is why little temperature gradient can lead to great loss in the performances of the battery packs. In recent years, numerous researchers are working on new techniques to imply a better thermal management on Li-ion batteries. Keeping the battery cells within an optimum range is the main objective of battery thermal management. Commercial Li-ion cells are composed of several electrochemical layers each consisting negative-current collector, negative electrode, separator, positive electrode, and positive current collector. However, many researchers have adopted a single-layer cell to save in computing time. Their hypothesis is that thermal conductivity of the layer elements is so high and heat transfer rate is so fast. Therefore, instead of several thin layers, they model the cell as one thick layer unit. In previous work, we showed that single-layer model is insufficient to simulate the thermal behavior and temperature nonuniformity of the high-capacity Li-ion cells. We also studied the effects of the number of layers on thermal behavior of the Li-ion batteries. In this work, first thermal and electrochemical behavior of the LiFePO₄ battery is modeled with 3D multilayer cell. The model is validated with the experimental measurements at different current rates and ambient temperatures. Real time heat generation rate is also studied at different discharge rates. Results showed non-uniform temperature distribution along the cell which requires thermal management system. Therefore, aluminum plates with mini-channel system were designed to control the temperature uniformity. Design parameters such as channel number and widths, inlet flow rate, and cooling fluids are optimized. As cooling fluids, water and air are compared. Pressure drop and velocity profiles inside the channels are illustrated. Both surface and internal temperature profiles of single cell and battery packs are investigated with and without cooling systems. Our results show that using optimized Mini-channel cooling plates effectively controls the temperature rise and uniformity of the single cells and battery packs. With increasing the inlet flow rate, cooling efficiency could be reached up to 60%.

Keywords: lithium ion battery, 3D multilayer model, mini-channel cooling plates, thermal management

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226 The Effect of Rheological Properties and Spun/Meltblown Fiber Characteristics on “Hotmelt Bleed through” Behavior in High Speed Textile Backsheet Lamination Process

Authors: Kinyas Aydin, Fatih Erguney, Tolga Ceper, Serap Ozay, Ipar N. Uzun, Sebnem Kemaloglu Dogan, Deniz Tunc

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In order to meet high growth rates in baby diaper industry worldwide, the high-speed textile backsheet lamination lines have recently been introduced to the market for non-woven/film lamination applications. It is a process where two substrates are bonded to each other via hotmelt adhesive (HMA). Nonwoven (NW) lamination system basically consists of 4 components; polypropylene (PP) nonwoven, polyethylene (PE) film, HMA and applicator system. Each component has a substantial effect on the process efficiency of continuous line and final product properties. However, for a precise subject cover, we will be addressing only the main challenges and possible solutions in this paper. The NW is often produced by spunbond method (SSS or SMS configuration) and has a 10-12 gsm (g/m²) basis weight. The NW rolls can have a width and length up to 2.060 mm and 30.000 linear meters, respectively. The PE film is the 2ⁿᵈ component in TBS lamination, which is usually a 12-14 gsm blown or cast breathable film. HMA is a thermoplastic glue (mostly rubber based) that can be applied in a large range of viscosity ranges. The main HMA application technology in TBS lamination is the slot die application in which HMA is spread on the top of the NW along the whole width at high temperatures in the melt form. Then, the NW is passed over chiller rolls with a certain open time depending on the line speed. HMAs are applied at certain levels in order to provide a proper de-lamination strength in cross and machine directions to the entire structure. Current TBS lamination line speed and width can be as high as 800 m/min and 2100 mm, respectively. They also feature an automated web control tension system for winders and unwinders. In order to run a continuous trouble-free mass production campaign on the fast industrial TBS lines, rheological properties of HMAs and micro-properties of NWs can have adverse effects on the line efficiency and continuity. NW fiber orientation and fineness, as well as spun/melt blown composition fabric micro-level properties, are the significant factors to affect the degree of “HMA bleed through.” As a result of this problem, frequent line stops are observed to clean the glue that is being accumulated on the chiller rolls, which significantly reduces the line efficiency. HMA rheology is also important and to eliminate any bleed through the problem; one should have a good understanding of rheology driven potential complications. So, the applied viscosity/temperature should be optimized in accordance with the line speed, line width, NW characteristics and the required open time for a given HMA formulation. In this study, we will show practical aspects of potential preventative actions to minimize the HMA bleed through the problem, which may stem from both HMA rheological properties and NW spun melt/melt blown fiber characteristics.

Keywords: breathable, hotmelt, nonwoven, textile backsheet lamination, spun/melt blown

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225 Improving the Efficiency of a High Pressure Turbine by Using Non-Axisymmetric Endwall: A Comparison of Two Optimization Algorithms

Authors: Abdul Rehman, Bo Liu

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Axial flow turbines are commonly designed with high loads that generate strong secondary flows and result in high secondary losses. These losses contribute to almost 30% to 50% of the total losses. Non-axisymmetric endwall profiling is one of the passive control technique to reduce the secondary flow loss. In this paper, the non-axisymmetric endwall profile construction and optimization for the stator endwalls are presented to improve the efficiency of a high pressure turbine. The commercial code NUMECA Fine/ Design3D coupled with Fine/Turbo was used for the numerical investigation, design of experiments and the optimization. All the flow simulations were conducted by using steady RANS and Spalart-Allmaras as a turbulence model. The non-axisymmetric endwalls of stator hub and shroud were created by using the perturbation law based on Bezier Curves. Each cut having multiple control points was supposed to be created along the virtual streamlines in the blade channel. For the design of experiments, each sample was arbitrarily generated based on values automatically chosen for the control points defined during parameterization. The Optimization was achieved by using two algorithms i.e. the stochastic algorithm and gradient-based algorithm. For the stochastic algorithm, a genetic algorithm based on the artificial neural network was used as an optimization method in order to achieve the global optimum. The evaluation of the successive design iterations was performed using artificial neural network prior to the flow solver. For the second case, the conjugate gradient algorithm with a three dimensional CFD flow solver was used to systematically vary a free-form parameterization of the endwall. This method is efficient and less time to consume as it requires derivative information of the objective function. The objective function was to maximize the isentropic efficiency of the turbine by keeping the mass flow rate as constant. The performance was quantified by using a multi-objective function. Other than these two classifications of the optimization methods, there were four optimizations cases i.e. the hub only, the shroud only, and the combination of hub and shroud. For the fourth case, the shroud endwall was optimized by using the optimized hub endwall geometry. The hub optimization resulted in an increase in the efficiency due to more homogenous inlet conditions for the rotor. The adverse pressure gradient was reduced but the total pressure loss in the vicinity of the hub was increased. The shroud optimization resulted in an increase in efficiency, total pressure loss and entropy were reduced. The combination of hub and shroud did not show overwhelming results which were achieved for the individual cases of the hub and the shroud. This may be caused by fact that there were too many control variables. The fourth case of optimization showed the best result because optimized hub was used as an initial geometry to optimize the shroud. The efficiency was increased more than the individual cases of optimization with a mass flow rate equal to the baseline design of the turbine. The results of artificial neural network and conjugate gradient method were compared.

Keywords: artificial neural network, axial turbine, conjugate gradient method, non-axisymmetric endwall, optimization

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224 Supercritical Water Gasification of Organic Wastes for Hydrogen Production and Waste Valorization

Authors: Laura Alvarez-Alonso, Francisco Garcia-Carro, Jorge Loredo

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Population growth and industrial development imply an increase in the energy demands and the problems caused by emissions of greenhouse effect gases, which has inspired the search for clean sources of energy. Hydrogen (H₂) is expected to play a key role in the world’s energy future by replacing fossil fuels. The properties of H₂ make it a green fuel that does not generate pollutants and supplies sufficient energy for power generation, transportation, and other applications. Supercritical Water Gasification (SCWG) represents an attractive alternative for the recovery of energy from wastes. SCWG allows conversion of a wide range of raw materials into a fuel gas with a high content of hydrogen and light hydrocarbons through their treatment at conditions higher than those that define the critical point of water (temperature of 374°C and pressure of 221 bar). Methane used as a transport fuel is another important gasification product. The number of different uses of gas and energy forms that can be produced depending on the kind of material gasified and type of technology used to process it, shows the flexibility of SCWG. This feature allows it to be integrated with several industrial processes, as well as power generation systems or waste-to-energy production systems. The final aim of this work is to study which conditions and equipment are the most efficient and advantageous to explore the possibilities to obtain streams rich in H₂ from oily wastes, which represent a major problem both for the environment and human health throughout the world. In this paper, the relative complexity of technology needed for feasible gasification process cycles is discussed with particular reference to the different feedstocks that can be used as raw material, different reactors, and energy recovery systems. For this purpose, a review of the current status of SCWG technologies has been carried out, by means of different classifications based on key features as the feed treated or the type of reactor and other apparatus. This analysis allows to improve the technology efficiency through the study of model calculations and its comparison with experimental data, the establishment of kinetics for chemical reactions, the analysis of how the main reaction parameters affect the yield and composition of products, or the determination of the most common problems and risks that can occur. The results of this work show that SCWG is a promising method for the production of both hydrogen and methane. The most significant choices of design are the reactor type and process cycle, which can be conveniently adopted according to waste characteristics. Regarding the future of the technology, the design of SCWG plants is still to be optimized to include energy recovery systems in order to reduce costs of equipment and operation derived from the high temperature and pressure conditions that are necessary to convert water to the SC state, as well as to find solutions to remove corrosion and clogging of components of the reactor.

Keywords: hydrogen production, organic wastes, supercritical water gasification, system integration, waste-to-energy

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223 The Effect of Post Spinal Hypotension on Cerebral Oxygenation Using Near-Infrared Spectroscopy and Neonatal Outcomes in Full Term Parturient Undergoing Lower Segment Caesarean Section: A Prospective Observational Study

Authors: Shailendra Kumar, Lokesh Kashyap, Puneet Khanna, Nishant Patel, Rakesh Kumar, Arshad Ayub, Kelika Prakash, Yudhyavir Singh, Krithikabrindha V.

Abstract:

Introduction: Spinal anesthesia is considered a standard anesthesia technique for caesarean delivery. The incidence of spinal hypotension during caesarean delivery is 70 -80%. Spinal hypotension may cause cerebral hypoperfusion in the mother, but physiologically cerebral autoregulatory mechanisms accordingly prevent cerebral hypoxia. Cerebral blood flow remains constant in the 50-150 mmHg of Cerebral Perfusion Pressure (CPP) range. Near-infrared spectroscopy (NIRS) is a non-invasive technology that is used to detect Cerebral Desaturation Events (CDEs) immediately compared to other conventional intraoperative monitoring techniques. Objective: The primary aim of the study is to correlate the change in cerebral oxygen saturation using NIRS with respect to a fall in mean blood pressure after spinal anaesthesia and to find out the effects of spinal hypotension on neonatal APGAR score, neonatal acid-base variations, and presence of Postoperative Delirium (POD). Methodology: NIRS sensors were attached to the forehead of all the patients, and their baseline readings of cerebral oxygenation on the right and left frontal regions and mean blood pressure were noted. Subarachnoid block was given with hyperbaric 0.5% bupivacaine plus fentanyl, the dose being determined by the individual anaesthesiologist. Co-loading of IV crystalloid solutions was given to the patient. Blood pressure reading and cerebral saturation were recorded every 1 minute till 30min. Hypotension was a fall in MAP less than 20% of the baseline values. Patients going for hypotension were treated with an IV Bolus of phenylephrine/ephedrine. Umbilical cord blood samples were taken for blood gas analysis, and neonatal APGAR was noted by a neonatologist. Study design: A prospective observational study conducted in a population of Thirty ASA 2 and 3 parturients scheduled for lower segment caesarean section (LSCS). Results: Mean fall in regional cerebral saturation is 28.48 ± 14.7% with respect to the mean fall in blood pressure 38.92 ± 8.44 mm Hg. The correlation coefficient between fall in saturation and fall in mean blood pressure is 0.057, and p-value {0.7} after subarachnoid block. A fall in regional cerebral saturation occurred 2±1 min before a fall in mean blood pressure. Twenty-nine out of thirty patients required vasopressors during hypotension. The first dose of vasopressor requirement is needed at 6.02±2 min after the block. The mean APGAR score was 7.86 and 9.74 at 1 and 5 min of birth, respectively, and the mean umbilical arterial pH of 7.3±0.1. According to DRS-98 (Delirium Rating Scale), the mean delirium rating score on postoperative day 1 and day 2 were 0.1 and 0.7, respectively. Discussion: There was a fall in regional cerebral oxygen saturation, which started before with respect to a significant fall in mean blood pressure readings but was statistically not significant. Maximal fall in blood pressure requiring vasopressors occurs within 10 min of SAB. Neonatal APGAR scores and acid-base variations were in the normal range with maternal hypotension, and there was no incidence of postoperative delirium in patients with post-spinal hypotension.

Keywords: cerebral oxygenation, LSCS, NIRS, spinal hypotension

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222 Strategies for the Optimization of Ground Resistance in Large Scale Foundations for Optimum Lightning Protection

Authors: Oibar Martinez, Clara Oliver, Jose Miguel Miranda

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In this paper, we discuss the standard improvements which can be made to reduce the earth resistance in difficult terrains for optimum lightning protection, what are the practical limitations, and how the modeling can be refined for accurate diagnostics and ground resistance minimization. Ground resistance minimization can be made via three different approaches: burying vertical electrodes connected in parallel, burying horizontal conductive plates or meshes, or modifying the own terrain, either by changing the entire terrain material in a large volume or by adding earth-enhancing compounds. The use of vertical electrodes connected in parallel pose several practical limitations. In order to prevent loss of effectiveness, it is necessary to keep a minimum distance between each electrode, which is typically around five times larger than the electrode length. Otherwise, the overlapping of the local equipotential lines around each electrode reduces the efficiency of the configuration. The addition of parallel electrodes reduces the resistance and facilitates the measurement, but the basic parallel resistor formula of circuit theory will always underestimate the final resistance. Numerical simulation of equipotential lines around the electrodes overcomes this limitation. The resistance of a single electrode will always be proportional to the soil resistivity. The electrodes are usually installed with a backfilling material of high conductivity, which increases the effective diameter. However, the improvement is marginal, since the electrode diameter counts in the estimation of the ground resistance via a logarithmic function. Substances that are used for efficient chemical treatment must be environmentally friendly and must feature stability, high hygroscopicity, low corrosivity, and high electrical conductivity. A number of earth enhancement materials are commercially available. Many are comprised of carbon-based materials or clays like bentonite. These materials can also be used as backfilling materials to reduce the resistance of an electrode. Chemical treatment of soil has environmental issues. Some products contain copper sulfate or other copper-based compounds, which may not be environmentally friendly. Carbon-based compounds are relatively inexpensive and they do have very low resistivities, but they also feature corrosion issues. Typically, the carbon can corrode and destroy a copper electrode in around five years. These compounds also have potential environmental concerns. Some earthing enhancement materials contain cement, which, after installation acquire properties that are very close to concrete. This prevents the earthing enhancement material from leaching into the soil. After analyzing different configurations, we conclude that a buried conductive ring with vertical electrodes connected periodically should be the optimum baseline solution for the grounding of a large size structure installed on a large resistivity terrain. In order to show this, a practical example is explained here where we simulate the ground resistance of a conductive ring buried in a terrain with a resistivity in the range of 1 kOhm·m.

Keywords: grounding improvements, large scale scientific instrument, lightning risk assessment, lightning standards

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221 The Product Innovation Using Nutraceutical Delivery System on Improving Growth Performance of Broiler

Authors: Kitti Supchukun, Kris Angkanaporn, Teerapong Yata

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The product innovation using a nutraceutical delivery system on improving the growth performance of broilers is the product planning and development to solve the antibiotics banning policy incurred in the local and global livestock production system. Restricting the use of antibiotics can reduce the quality of chicken meat and increase pathogenic bacterial contamination. Although other alternatives were used to replace antibiotics, the efficacy was inconsistent, reflecting on low chicken growth performance and contaminated products. The product innovation aims to effectively deliver the selected active ingredients into the body. This product is tested on the pharmaceutical lab scale and on the farm-scale for market feasibility in order to create product innovation using the nutraceutical delivery system model. The model establishes the product standardization and traceable quality control process for farmers. The study is performed using mixed methods. Starting with a qualitative method to find the farmers' (consumers) demands and the product standard, then the researcher used the quantitative research method to develop and conclude the findings regarding the acceptance of the technology and product performance. The survey has been sent to different organizations by random sampling among the entrepreneur’s population including integrated broiler farm, broiler farm, and other related organizations. The mixed-method results, both qualitative and quantitative, verify the user and lead users' demands since they provide information about the industry standard, technology preference, developing the right product according to the market, and solutions for the industry problems. The product innovation selected nutraceutical ingredients that can solve the following problems in livestock; bactericidal, anti-inflammation, gut health, antioxidant. The combinations of the selected nutraceutical and nanostructured lipid carriers (NLC) technology aim to improve chemical and pharmaceutical components by changing the structure of active ingredients into nanoparticle, which will be released in the targeted location with accurate concentration. The active ingredients in nanoparticle form are more stable, elicit antibacterial activity against pathogenic Salmonella spp and E.coli, balance gut health, have antioxidant and anti-inflammation activity. The experiment results have proven that the nutraceuticals have an antioxidant and antibacterial activity which also increases the average daily gain (ADG), reduces feed conversion ratio (FCR). The results also show a significant impact on the higher European Performance Index that can increase the farmers' profit when exporting. The product innovation will be tested in technology acceptance management methods from farmers and industry. The production of broiler and commercialization analyses are useful to reduce the importation of animal supplements. Most importantly, product innovation is protected by intellectual property.

Keywords: nutraceutical, nano structure lipid carrier, anti-microbial drug resistance, broiler, Salmonella

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220 Thermal Securing of Electrical Contacts inside Oil Power Transformers

Authors: Ioan Rusu

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In the operation of power transformers of 110 kV/MV from substations, these are traveled by fault current resulting from MV line damage. Defect electrical contacts are heated when they are travelled from fault currents. In the case of high temperatures when 135 °C is reached, the electrical insulating oil in the vicinity of the electrical faults comes into contact with these contacts releases gases, and activates the electrical protection. To avoid auto-flammability of electro-insulating oil, we designed a security system thermal of electrical contact defects by pouring fire-resistant polyurethane foam, mastic or mortar fire inside a cardboard electro-insulating cylinder. From practical experience, in the exploitation of power transformers of 110 kV/MT in oil electro-insulating were recorded some passing disconnecting commanded by the gas protection at internal defects. In normal operation and in the optimal load, nominal currents do not require thermal secure contacts inside electrical transformers, contacts are made at the fabrication according to the projects or to repair by solder. In the case of external short circuits close to the substation, the contacts inside electrical transformers, even if they are well made in sizes of Rcontact = 10‑6 Ω, are subjected to short-circuit currents of the order of 10 kA-20 kA which lead to the dissipation of some significant second-order electric powers, 100 W-400 W, on contact. At some internal or external factors which action on electrical contacts, including electrodynamic efforts at short-circuits, these factors could be degraded over time to values in the range of 10-4 Ω to 10-5 Ω and if the action time of protection is great, on the order of seconds, power dissipation on electrical contacts achieve high values of 1,0 kW to 40,0 kW. This power leads to strong local heating, hundreds of degrees Celsius and can initiate self-ignition and burning oil in the vicinity of electro-insulating contacts with action the gas relay. Degradation of electrical contacts inside power transformers may not be limited for the duration of their operation. In order to avoid oil burn with gas release near electrical contacts, at short-circuit currents 10 kA-20 kA, we have outlined the following solutions: covering electrical contacts in fireproof materials that would avoid direct burn oil at short circuit and transmission of heat from electrical contact along the conductors with heat dissipation gradually over time, in a large volume of cooling. Flame retardant materials are: polyurethane foam, mastic, cement (concrete). In the normal condition of operation of transformer, insulating of conductors coils is with paper and insulating oil. Ignition points of its two components respectively are approximated: 135 °C heat for oil and 200 0C for paper. In the case of a faulty electrical contact, about 10-3 Ω, at short-circuit; the temperature can reach for a short time, a value of 300 °C-400 °C, which ignite the paper and also the oil. By burning oil, there are local gases that disconnect the power transformer. Securing thermal electrical contacts inside the transformer, in cardboard tube with polyurethane foams, mastik or cement, ensures avoiding gas release and also gas protection working.

Keywords: power transformer, oil insulatation, electric contacts, Bucholtz relay

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219 Concentration and Stability of Fatty Acids and Ammonium in the Samples from Mesophilic Anaerobic Digestion

Authors: Mari Jaakkola, Jasmiina Haverinen, Tiina Tolonen, Vesa Virtanen

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These process monitoring of biogas plant gives valuable information of the function of the process and help to maintain a stable process. The costs of basic monitoring are often much lower than the costs associated with re-establishing a biologically destabilised plant. Reactor acidification through reactor overload is one of the most common reasons for process deterioration in anaerobic digesters. This occurs because of a build-up of volatile fatty acids (VFAs) produced by acidogenic and acetogenic bacteria. VFAs cause pH values to decrease, and result in toxic conditions in the reactor. Ammonia ensures an adequate supply of nitrogen as a nutrient substance for anaerobic biomass and increases system's buffer capacity, counteracting acidification lead by VFA production. However, elevated ammonia concentration is detrimental to the process due to its toxic effect. VFAs are considered the most reliable analytes for process monitoring. To obtain accurate results, sample storage and transportation need to be carefully controlled. This may be a challenge for off-line laboratory analyses especially when the plant is located far away from the laboratory. The aim of this study was to investigate the correlation between fatty acids, ammonium, and bacteria in the anaerobic digestion samples obtained from an industrial biogas factory. The stability of the analytes was studied comparing the results of the on-site analyses performed in the factory site to the results of the samples stored at room temperature and -18°C (up to 30 days) after sampling. Samples were collected in the biogas plant consisting of three separate mesofilic AD reactors (4000 m³ each) where the main feedstock was swine slurry together with a complex mixture of agricultural plant and animal wastes. Individual VFAs, ammonium, and nutrients (K, Ca, Mg) were studied by capillary electrophoresis (CE). Longer chain fatty acids (oleic, hexadecanoic, and stearic acids) and bacterial profiles were studied by GC-MSD (Gas Chromatography-Mass Selective Detector) and 16S rDNA, respectively. On-site monitoring of the analytes was performed by CE. The main VFA in all samples was acetic acid. However, in one reactor sample elevated levels of several individual VFAs and long chain fatty acids were detected. Also bacterial profile of this sample differed from the profiles of other samples. Acetic acid decomposed fast when the sample was stored in a room temperature. All analytes were stable when stored in a freezer. Ammonium was stable even at a room temperature for the whole testing period. One reactor sample had higher concentration of VFAs and long chain fatty acids than other samples. CE was utilized successfully in the on-site analysis of separate VFAs and NH₄ in the biogas production site. Samples should be analysed in the sampling day if stored in RT or freezed for longer storage time. Fermentation reject can be stored (and transported) at ambient temperature at least for one month without loss of NH₄. This gives flexibility to the logistic solutions when reject is used as a fertilizer.

Keywords: anaerobic digestion, capillary electrophoresis, ammonium, bacteria

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218 Adaptation of Retrofit Strategies for the Housing Sector in Northern Cyprus

Authors: B. Ozarisoy, E. Ampatzi, G. Z. Lancaster

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This research project is undertaken in the Turkish Republic of Northern Cyprus (T.R.N.C). The study focuses on identifying refurbishment activities capable of diagnosing and detecting the underlying problems alongside the challenges offered by the buildings’ typology in addition to identifying the correct construction materials in the refurbishment process which allow for the maximisation of expected energy savings. Attention is drawn to, the level of awareness and understanding of refurbishment activity that needs to be raised in the current construction process alongside factors that include the positive environmental impact and the saving of energy. The approach here is to look at buildings that have been built by private construction companies that have already been refurbished by occupants and to suggest additional control mechanisms for retrofitting that can further enhance the process of renewal. The objective of the research is to investigate the occupants’ behaviour and role in the refurbishment activity; to explore how and why occupants decide to change building components and to understand why and how occupants consider using energy-efficient materials. The present work is based on data from this researcher’s first-hand experience and incorporates the preliminary data collection on recent housing sector statistics, including the year in which housing estates were built, an examination of the characteristics that define the construction industry in the T.R.N.C., building typology and the demographic structure of house owners. The housing estates are chosen from 16 different projects in four different regions of the T.R.N.C. that include urban and suburban areas. There is, therefore, a broad representation of the common drivers in the property market, each with different levels of refurbishment activity and this is coupled with different samplings from different climatic regions within the T.R.N.C. The study is conducted through semi-structured interviews to identify occupants’ behaviour as it is associated with refurbishment activity. The interviews provide all the occupants’ demographic information, needs and intentions as they relate to various aspects of the refurbishment process. This research paper presents the results of semi-structured interviews with 70 homeowners in a selected group of 16 housing estates in five different parts of the T.R.N.C. The people who agreed to be interviewed in this study are all residents of single or multi-family housing units. Alongside the construction process and its impact on the environment, the results point out the need for control mechanisms in the housing sector to promote and support the adoption of retrofit strategies and minimize non-controlled refurbishment activities, in line with diagnostic information of the selected buildings. The expected solutions should be effective, environmentally acceptable and feasible given the type of housing projects under review, with due regard for their location, the climatic conditions within which they were undertaken, the socio-economic standing of the house owners and their attitudes, local resources and legislative constraints. Furthermore, the study goes on to insist on the practical and long-term economic benefits of refurbishment under the proper conditions and why this should be fully understood by the householders.

Keywords: construction process, energy-efficiency, refurbishment activity, retrofitting

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217 Examining Litter Distributions in Lethbridge, Alberta, Canada, Using Citizen Science and GIS Methods: OpenLitterMap App and Story Maps

Authors: Tali Neta

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Humans’ impact on the environment has been incredibly brutal, with enormous plastic- and other pollutants (e.g., cigarette buds, paper cups, tires) worldwide. On land, litter costs taxpayers a fortune. Most of the litter pollution comes from the land, yet it is one of the greatest hazards to marine environments. Due to spatial and temporal limitations, previous litter data covered very small areas. Currently, smartphones can be used to obtain information on various pollutants (through citizen science), and they can greatly assist in acknowledging and mitigating the environmental impact of litter. Litter app data, such as the Litterati, are available for study through a global map only; these data are not available for download, and it is not clear whether irrelevant hashtags have been eliminated. Instagram and Twitter open-source geospatial data are available for download; however, these are considered inaccurate, computationally challenging, and impossible to quantify. Therefore, the resulting data are of poor quality. Other downloadable geospatial data (e.g., Marine Debris Tracker8 and Clean Swell10) are focused on marine- rather than terrestrial litter. Therefore, accurate terrestrial geospatial documentation of litter distribution is needed to improve environmental awareness. The current research employed citizen science to examine litter distribution in Lethbridge, Alberta, Canada, using the OpenLitterMap (OLM) app. The OLM app is an application used to track litter worldwide, and it can mark litter locations through photo georeferencing, which can be presented through GIS-designed maps. The OLM app provides open-source data that can be downloaded. It also offers information on various litter types and “hot-spots” areas where litter accumulates. In this study, Lethbridge College students collected litter data with the OLM app. The students produced GIS Story Maps (interactive web GIS illustrations) and presented these to school children to improve awareness of litter's impact on environmental health. Preliminary results indicate that towards the Lethbridge Coulees’ (valleys) East edges, the amount of litter significantly increased due to shrubs’ presence, that acted as litter catches. As wind generally travels from west to east in Lethbridge, litter in West-Lethbridge often finds its way down in the east part of the coulees. The students’ documented various litter types, while the majority (75%) included plastic and paper food packaging. The students also found metal wires, broken glass, plastic bottles, golf balls, and tires. Presentations of the Story Maps to school children had a significant impact, as the children voluntarily collected litter during school recess, and they were looking into solutions to reduce litter. Further litter distribution documentation through Citizen Science is needed to improve public awareness. Additionally, future research will be focused on Drone imagery of highly concentrated litter areas. Finally, a time series analysis of litter distribution will help us determine whether public education through Citizen Science and Story Maps can assist in reducing litter and reaching a cleaner and healthier environment.

Keywords: citizen science, litter pollution, Open Litter Map, GIS Story Map

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216 Destruction of History and the Syrian Conflict: Upholding the Cultural Integrity of Dura Europos

Authors: Justine A. Lloyd

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Since the onset of the Syrian Civil War in 2011, the ancient city of Dura-Europos has faced widespread destruction and looting. The site is one of many places in the country the terrorist group ISIS has specifically targeted, allegedly due to its particular representations of Syrian history and culture. However, looted art and artifacts are the extremist group’s second largest source of income, only after oil. The protection of this site is important to both academics and the millions who have called Syria a home, as it aids in the nation’s sense of identity, reveals developments in the arts, and contributes to humanity’s collective history. At a time when Syria’s culture is being flattened, this sense of cultural expression is especially important to maintain. Creating an awareness of the magnitude of the issue at hand begins with an examination of the rich history of the ancient fortress city. Located on the western bank of the Euphrates River, Dura-Europos contains artifacts dating back to the Hellenistic, Parthian, and Roman periods. Though a great deal of the art and artifacts have remained safe in institutions such as the National Museum of Damascus and the Yale University Art Gallery, hundreds of looting pits and use of heavy machinery on the site has severely set back the investigative progress made by archaeologists over the last century, as well as the prospect of future excavation. Further research draws on the current destruction of the site by both ISIS and opportunists involved with the black market. Because Dura-Europos is located in a war stricken region, the acquisition of data and possibility of immediate action is particularly challenging. Resources gained from local reports, in addition to technology such as satellite imagery, however, have provided a firm starting point for the evaluation of the state of the site. The Syrian Ministry of Culture, UNESCO, and numerous Syrian and global organizations provide insight into the historic city’s past, present issues, and future plans to ensure that the cultural integrity of the site is upheld. Though over seventy percent of Dura-Europos has been completely decimated, this research challenges the notion that physically destroyed sites are lost forever. This paper assesses preventative measures that can take place to ensure the preservation of the site’s art and architecture, including examining possible solutions to the damage, such as digital reconstruction, replication, and distribution of information through exhibitions and other forms of publically accessible information. In order to investigate any possible retribution, research also includes the necessary information pertaining the global laws and regulations dealing with cultural heritage, as it directly affects the ways in which this situation can be dealt with. With the countless experts and citizens dedicated to the importance of cultural heritage, the prospect of honoring and valuing elements of Dura-Europos is possible—whether physically preserved or otherwise.

Keywords: antiquities law, archaeological sites, restitution, Syrian Civil War

Procedia PDF Downloads 149
215 A Convolution Neural Network PM-10 Prediction System Based on a Dense Measurement Sensor Network in Poland

Authors: Piotr A. Kowalski, Kasper Sapala, Wiktor Warchalowski

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PM10 is a suspended dust that primarily has a negative effect on the respiratory system. PM10 is responsible for attacks of coughing and wheezing, asthma or acute, violent bronchitis. Indirectly, PM10 also negatively affects the rest of the body, including increasing the risk of heart attack and stroke. Unfortunately, Poland is a country that cannot boast of good air quality, in particular, due to large PM concentration levels. Therefore, based on the dense network of Airly sensors, it was decided to deal with the problem of prediction of suspended particulate matter concentration. Due to the very complicated nature of this issue, the Machine Learning approach was used. For this purpose, Convolution Neural Network (CNN) neural networks have been adopted, these currently being the leading information processing methods in the field of computational intelligence. The aim of this research is to show the influence of particular CNN network parameters on the quality of the obtained forecast. The forecast itself is made on the basis of parameters measured by Airly sensors and is carried out for the subsequent day, hour after hour. The evaluation of learning process for the investigated models was mostly based upon the mean square error criterion; however, during the model validation, a number of other methods of quantitative evaluation were taken into account. The presented model of pollution prediction has been verified by way of real weather and air pollution data taken from the Airly sensor network. The dense and distributed network of Airly measurement devices enables access to current and archival data on air pollution, temperature, suspended particulate matter PM1.0, PM2.5, and PM10, CAQI levels, as well as atmospheric pressure and air humidity. In this investigation, PM2.5, and PM10, temperature and wind information, as well as external forecasts of temperature and wind for next 24h served as inputted data. Due to the specificity of the CNN type network, this data is transformed into tensors and then processed. This network consists of an input layer, an output layer, and many hidden layers. In the hidden layers, convolutional and pooling operations are performed. The output of this system is a vector containing 24 elements that contain prediction of PM10 concentration for the upcoming 24 hour period. Over 1000 models based on CNN methodology were tested during the study. During the research, several were selected out that give the best results, and then a comparison was made with the other models based on linear regression. The numerical tests carried out fully confirmed the positive properties of the presented method. These were carried out using real ‘big’ data. Models based on the CNN technique allow prediction of PM10 dust concentration with a much smaller mean square error than currently used methods based on linear regression. What's more, the use of neural networks increased Pearson's correlation coefficient (R²) by about 5 percent compared to the linear model. During the simulation, the R² coefficient was 0.92, 0.76, 0.75, 0.73, and 0.73 for 1st, 6th, 12th, 18th, and 24th hour of prediction respectively.

Keywords: air pollution prediction (forecasting), machine learning, regression task, convolution neural networks

Procedia PDF Downloads 122
214 Superparamagnetic Core Shell Catalysts for the Environmental Production of Fuels from Renewable Lignin

Authors: Cristina Opris, Bogdan Cojocaru, Madalina Tudorache, Simona M. Coman, Vasile I. Parvulescu, Camelia Bala, Bahir Duraki, Jeroen A. Van Bokhoven

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The tremendous achievements in the development of the society concretized by more sophisticated materials and systems are merely based on non-renewable resources. Consequently, after more than two centuries of intensive development, among others, we are faced with the decrease of the fossil fuel reserves, an increased impact of the greenhouse gases on the environment, and economic effects caused by the fluctuations in oil and mineral resource prices. The use of biomass may solve part of these problems, and recent analyses demonstrated that from the perspective of the reduction of the emissions of carbon dioxide, its valorization may bring important advantages conditioned by the usage of genetic modified fast growing trees or wastes, as primary sources. In this context, the abundance and complex structure of lignin may offer various possibilities of exploitation. However, its transformation in fuels or chemicals supposes a complex chemistry involving the cleavage of C-O and C-C bonds and altering of the functional groups. Chemistry offered various solutions in this sense. However, despite the intense work, there are still many drawbacks limiting the industrial application. Thus, the proposed technologies considered mainly homogeneous catalysts meaning expensive noble metals based systems that are hard to be recovered at the end of the reaction. Also, the reactions were carried out in organic solvents that are not acceptable today from the environmental point of view. To avoid these problems, the concept of this work was to investigate the synthesis of superparamagnetic core shell catalysts for the fragmentation of lignin directly in the aqueous phase. The magnetic nanoparticles were covered with a nanoshell of an oxide (niobia) with a double role: to protect the magnetic nanoparticles and to generate a proper (acidic) catalytic function and, on this composite, cobalt nanoparticles were deposed in order to catalyze the C-C bond splitting. With this purpose, we developed a protocol to prepare multifunctional and magnetic separable nano-composite Co@Nb2O5@Fe3O4 catalysts. We have also established an analytic protocol for the identification and quantification of the fragments resulted from lignin depolymerization in both liquid and solid phase. The fragmentation of various lignins occurred on the prepared materials in high yields and with very good selectivity in the desired fragments. The optimization of the catalyst composition indicated a cobalt loading of 4wt% as optimal. Working at 180 oC and 10 atm H2 this catalyst allowed a conversion of lignin up to 60% leading to a mixture containing over 96% in C20-C28 and C29-C37 fragments that were then completely fragmented to C12-C16 in a second stage. The investigated catalysts were completely recyclable, and no leaching of the elements included in the composition was determined by inductively coupled plasma optical emission spectrometry (ICP-OES).

Keywords: superparamagnetic core-shell catalysts, environmental production of fuels, renewable lignin, recyclable catalysts

Procedia PDF Downloads 314
213 Assessing Sustainability of Bike Sharing Projects Using Envision™ Rating System

Authors: Tamar Trop

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Bike sharing systems can be important elements of smart cities as they have the potential for impact on multiple levels. These systems can add a significant alternative to other modes of mass transit in cities that are continuously looking for measures to become more livable and maintain their attractiveness for citizens, businesses and tourism. Bike-sharing began in Europe in 1965, and a viable format emerged in the mid-2000s thanks to the introduction of information technology. The rate of growth in bike-sharing schemes and fleets has been very rapid since 2008 and has probably outstripped growth in every other form of urban transport. Today, public bike-sharing systems are available on five continents, including over 700 cities, operating more than 800,000 bicycles at approximately 40,000 docking stations. Since modern bike sharing systems have become prevalent only in the last decade, the existing literature analyzing these systems and their sustainability is relatively new. The purpose of the presented study is to assess the sustainability of these newly emerging transportation systems, by using the Envision™ rating system as a methodological framework and the Israeli 'Tel -O-Fun' – bike sharing project as a case study. The assessment was conducted by project team members. Envision™ is a new guidance and rating system used to assess and improve the sustainability of all types and sizes of infrastructure projects. This tool provides a holistic framework for evaluating and rating the community, environmental, and economic benefits of infrastructure projects over the course of their life cycle. This evaluation method has 60 sustainability criteria divided into five categories: Quality of life, leadership, resource allocation, natural world, and climate and risk. 'Tel -O-Fun' project was launched in Tel Aviv-Yafo on 2011 and today provides about 1,800 bikes for rent, at 180 rental stations across the city. The system is based on a complex computer terminal that is located in the docking stations. The highest-rated sustainable features that the project scored include: (a) Improving quality of life by: offering a low cost and efficient form of public transit, improving community mobility and access, enabling the flexibility of travel within a multimodal transportation system, saving commuters time and money, enhancing public health and reducing air and noise pollution; (b) improving resource allocation by: offering inexpensive and flexible last-mile connectivity, reducing space, materials and energy consumption, reducing wear and tear on public roads, and maximizing the utility of existing infrastructure, and (c) reducing of greenhouse gas emissions from transportation. Overall, 'Tel -O-Fun' project was highly scored as an environmentally sustainable and socially equitable infrastructure. The use of this practical framework for evaluation also yielded various interesting insights on the shortcoming of the system and the characteristics of good solutions. This can contribute to the improvement of the project and may assist planners and operators of bike sharing systems to develop a sustainable, efficient and reliable transportation infrastructure within smart cities.

Keywords: bike sharing, Envision™, sustainability rating system, sustainable infrastructure

Procedia PDF Downloads 318
212 Design and Development of Graphene Oxide Modified by Chitosan Nanosheets Showing pH-Sensitive Surface as a Smart Drug Delivery System for Control Release of Doxorubicin

Authors: Parisa Shirzadeh

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Drug delivery systems in which drugs are traditionally used, multi-stage and at specified intervals by patients, do not meet the needs of the world's up-to-date drug delivery. In today's world, we are dealing with a huge number of recombinant peptide and protean drugs and analogues of hormones in the body, most of which are made with genetic engineering techniques. Most of these drugs are used to treat critical diseases such as cancer. Due to the limitations of the traditional method, researchers sought to find ways to solve the problems of the traditional method to a large extent. Following these efforts, controlled drug release systems were introduced, which have many advantages. Using controlled release of the drug in the body, the concentration of the drug is kept at a certain level, and in a short time, it is done at a higher rate. Graphene is a natural material that is biodegradable, non-toxic, and natural compared to carbon nanotubes; its price is lower than carbon nanotubes and is cost-effective for industrialization. On the other hand, the presence of highly effective surfaces and wide surfaces of graphene plates makes it more effective to modify graphene than carbon nanotubes. Graphene oxide is often synthesized using concentrated oxidizers such as sulfuric acid, nitric acid, and potassium permanganate based on Hummer 1 method. In comparison with the initial graphene, the resulting graphene oxide is heavier and has carboxyl, hydroxyl, and epoxy groups. Therefore, graphene oxide is very hydrophilic and easily dissolves in water and creates a stable solution. On the other hand, because the hydroxyl, carboxyl, and epoxy groups created on the surface are highly reactive, they have the ability to work with other functional groups such as amines, esters, polymers, etc. Connect and bring new features to the surface of graphene. In fact, it can be concluded that the creation of hydroxyl groups, Carboxyl, and epoxy and in fact graphene oxidation is the first step and step in creating other functional groups on the surface of graphene. Chitosan is a natural polymer and does not cause toxicity in the body. Due to its chemical structure and having OH and NH groups, it is suitable for binding to graphene oxide and increasing its solubility in aqueous solutions. Graphene oxide (GO) has been modified by chitosan (CS) covalently, developed for control release of doxorubicin (DOX). In this study, GO is produced by the hummer method under acidic conditions. Then, it is chlorinated by oxalyl chloride to increase its reactivity against amine. After that, in the presence of chitosan, the amino reaction was performed to form amide transplantation, and the doxorubicin was connected to the carrier surface by π-π interaction in buffer phosphate. GO, GO-CS, and GO-CS-DOX characterized by FT-IR, RAMAN, TGA, and SEM. The ability to load and release is determined by UV-Visible spectroscopy. The loading result showed a high capacity of DOX absorption (99%) and pH dependence identified as a result of DOX release from GO-CS nanosheet at pH 5.3 and 7.4, which show a fast release rate in acidic conditions.

Keywords: graphene oxide, chitosan, nanosheet, controlled drug release, doxorubicin

Procedia PDF Downloads 104
211 Polarization as a Proxy of Misinformation Spreading

Authors: Michela Del Vicario, Walter Quattrociocchi, Antonio Scala, Ana Lucía Schmidt, Fabiana Zollo

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Information, rumors, and debates may shape and impact public opinion heavily. In the latest years, several concerns have been expressed about social influence on the Internet and the outcome that online debates might have on real-world processes. Indeed, on online social networks users tend to select information that is coherent to their system of beliefs and to form groups of like-minded people –i.e., echo chambers– where they reinforce and polarize their opinions. In this way, the potential benefits coming from the exposure to different points of view may be reduced dramatically, and individuals' views may become more and more extreme. Such a context fosters misinformation spreading, which has always represented a socio-political and economic risk. The persistence of unsubstantiated rumors –e.g., the hypothetical and hazardous link between vaccines and autism– suggests that social media do have the power to misinform, manipulate, or control public opinion. As an example, current approaches such as debunking efforts or algorithmic-driven solutions based on the reputation of the source seem to prove ineffective against collective superstition. Indeed, experimental evidence shows that confirmatory information gets accepted even when containing deliberately false claims while dissenting information is mainly ignored, influences users’ emotions negatively and may even increase group polarization. Moreover, confirmation bias has been shown to play a pivotal role in information cascades, posing serious warnings about the efficacy of current debunking efforts. Nevertheless, mitigation strategies have to be adopted. To generalize the problem and to better understand social dynamics behind information spreading, in this work we rely on a tight quantitative analysis to investigate the behavior of more than 300M users w.r.t. news consumption on Facebook over a time span of six years (2010-2015). Through a massive analysis on 920 news outlets pages, we are able to characterize the anatomy of news consumption on a global and international scale. We show that users tend to focus on a limited set of pages (selective exposure) eliciting a sharp and polarized community structure among news outlets. Moreover, we find similar patterns around the Brexit –the British referendum to leave the European Union– debate, where we observe the spontaneous emergence of two well segregated and polarized groups of users around news outlets. Our findings provide interesting insights into the determinants of polarization and the evolution of core narratives on online debating. Our main aim is to understand and map the information space on online social media by identifying non-trivial proxies for the early detection of massive informational cascades. Furthermore, by combining users traces, we are finally able to draft the main concepts and beliefs of the core narrative of an echo chamber and its related perceptions.

Keywords: information spreading, misinformation, narratives, online social networks, polarization

Procedia PDF Downloads 270
210 Monitoring the Production of Large Composite Structures Using Dielectric Tool Embedded Capacitors

Authors: Galatee Levadoux, Trevor Benson, Chris Worrall

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With the rise of public awareness on climate change comes an increasing demand for renewable sources of energy. As a result, the wind power sector is striving to manufacture longer, more efficient and reliable wind turbine blades. Currently, one of the leading causes of blade failure in service is improper cure of the resin during manufacture. The infusion process creating the main part of the composite blade structure remains a critical step that is yet to be monitored in real time. This stage consists of a viscous resin being drawn into a mould under vacuum, then undergoing a curing reaction until solidification. Successful infusion assumes the resin fills all the voids and cures completely. Given that the electrical properties of the resin change significantly during its solidification, both the filling of the mould and the curing reaction are susceptible to be followed using dieletrometry. However, industrially available dielectrics sensors are currently too small to monitor the entire surface of a wind turbine blade. The aim of the present research project is to scale up the dielectric sensor technology and develop a device able to monitor the manufacturing process of large composite structures, assessing the conformity of the blade before it even comes out of the mould. An array of flat copper wires acting as electrodes are embedded in a polymer matrix fixed in an infusion mould. A multi-frequency analysis from 1 Hz to 10 kHz is performed during the filling of the mould with an epoxy resin and the hardening of the said resin. By following the variations of the complex admittance Y*, the filling of the mould and curing process are monitored. Results are compared to numerical simulations of the sensor in order to validate a virtual cure-monitoring system. The results obtained by drawing glycerol on top of the copper sensor displayed a linear relation between the wetted length of the sensor and the complex admittance measured. Drawing epoxy resin on top of the sensor and letting it cure at room temperature for 24 hours has provided characteristic curves obtained when conventional interdigitated sensor are used to follow the same reaction. The response from the developed sensor has shown the different stages of the polymerization of the resin, validating the geometry of the prototype. The model created and analysed using COMSOL has shown that the dielectric cure process can be simulated, so long as a sufficient time and temperature dependent material properties can be determined. The model can be used to help design larger sensors suitable for use with full-sized blades. The preliminary results obtained with the sensor prototype indicate that the infusion and curing process of an epoxy resin can be followed with the chosen configuration on a scale of several decimeters. Further work is to be devoted to studying the influence of the sensor geometry and the infusion parameters on the results obtained. Ultimately, the aim is to develop a larger scale sensor able to monitor the flow and cure of large composite panels industrially.

Keywords: composite manufacture, dieletrometry, epoxy, resin infusion, wind turbine blades

Procedia PDF Downloads 143
209 Analyzing the Investment Decision and Financing Method of the French Small and Medium-Sized Enterprises

Authors: Eliane Abdo, Olivier Colot

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SMEs are always considered as a national priority due to their contribution to job creation, innovation and growth. Once the start-up phase is crossed with encouraging results, the company enters the phase of growth. In order to improve its competitiveness, maintain and increase its market share, the company is in the necessity even the obligation to develop its tangible and intangible investments. SMEs are generally closed companies with special and critical financial situation, limited resources and difficulty to access the capital markets; their shareholders are always living in a conflict between their independence and their need to increase capital that leads to the entry of new shareholder. The capital structure was always considered the core of research in corporate finance; moreover, the financial crisis and its repercussions on the credit’s availability, especially for SMEs make SME financing a hot topic. On the other hand, financial theories do not provide answers to capital structure’s questions; they offer tools and mode of financing that are more accessible to larger companies. Yet, SME’s capital structure can’t be independent of their governance structure. The classic financial theory supposes independence between the investment decision and the financing decision. Thus, investment determines the volume of funding, but not the split between internal or external funds. In this context, we find interesting to study the hypothesis that SMEs respond positively to the financial theories applied to large firms and to check if they are constrained by conventional solutions used by large companies. In this context, this research focuses on the analysis of the resource’s structure of SME in parallel with their investments’ structure, in order to highlight a link between their assets and liabilities structure. We founded our conceptual model based on two main theoretical frameworks: the Pecking order theory, and the Trade Off theory taking into consideration the SME’s characteristics. Our data were generated from DIANE database. Five hypotheses were tested via a panel regression to understand the type of dependence between the financing methods of 3,244 French SMEs and the development of their investment over a period of 10 years (2007-2016). The results show dependence between equity and internal financing in case of intangible investments development. Moreover, this type of business is constraint to financial debts since the guarantees provided are not sufficient to meet the banks' requirements. However, for tangible investments development, SMEs count sequentially on internal financing, bank borrowing, and new shares issuance or hybrid financing. This is compliant to the Pecking Order Theory. We, therefore, conclude that unlisted SMEs incur more financial debts to finance their tangible investments more than their intangible. However, they always prefer internal financing as a first choice. This seems to be confirmed by the assumption that the profitability of the company is negatively related to the increase of the financial debt. Thus, the Pecking Order Theory predictions seem to be the most plausible. Consequently, SMEs primarily rely on self-financing and then go, into debt as a priority to finance their financial deficit.

Keywords: capital structure, investments, life cycle, pecking order theory, trade off theory

Procedia PDF Downloads 91
208 A Taxonomy of Professional Engineering Attributes for Tackling Global Humanitarian Challenges

Authors: Georgia Kremmyda, Angelos Georgoulas, Yiannis Koumpouros, James T. Mottram

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There is a growing interest in enhancing the creativity and problem-solving ability of engineering students by expanding their engagement to complex, interdisciplinary problems such as environmental issues, resilience to man-made and natural disasters, global health matters, water needs, increased energy demands, and other global humanitarian challenges. Tackling societal challenges requires knowledgeable and erudite engineers who can handle, combine, transform and create innovative, affordable and sustainable solutions. This view simultaneously complements and challenges current conceptions of an emerging educational movement that, almost without exception, are underpinned by calls for competitive economic growth and technological development. This article reveals a taxonomy of humanitarian attributes to be enabled to professional engineers, through reformed curricula and innovative pedagogies, which once implemented and integrated efficiently in higher engineering education, they will provide students and educators with opportunities to explore interdependencies and connections between resources, sustainable design, societal needs, and the natural environment and to critically engage with implicit and explicit facets of disciplinary identity. The research involves carrying out a study on (a) current practices, best practices and barriers in knowledge organisation, content, and hierarchy in graduate engineering programmes, (b) best practices associated with teaching and research in engineering education around the world, (c) opportunities inherent in general reforms of graduate engineering education and inherent in integrating the humanitarian context throughout engineering education programmes, and, (d) an overarching taxonomy of professional attributes for tackling humanitarian challenges. Research methods involve state-of-the-art literature review on engineering education and pedagogy to resource thematic findings on current status in engineering education worldwide, and qualitative research through three practice dialogue workshops, run in Asia (Vietnam, Indonesia and Bangladesh) involving a variety of national, international and local stakeholders (industries; NGOs, governmental organisations). Findings from this study provide evidence on: (a) what are the professional engineering attributes (skills, experience, knowledge) needed for tackling humanitarian challenges; (b) how we can integrate other disciplines and professions to engineering while defining the professional attributes of engineers who are capable of tackling humanitarian challenges. The attributes will be linked to those discipline(s) and profession(s) that are more likely to enforce the attributes (removing the assumption that engineering education as it stands at the moment can provide all attributes), and; (c) how these attributes shall be supplied; what kind of pedagogies or training shall take place beyond current practices. Acknowledgment: The study is currently in progress and is being undertaken in the framework of the project ENHANCE - ENabling Humanitarian Attributes for Nurturing Community-based Engineering (project No: 598502-EEP-1-2018-1-UK-EPPKA2-CBHE-JP (2018-2582/001-001), funded by the Erasmus + KA2 Cooperation for innovation and the exchange of good practices – Capacity building in the field of Higher Education.

Keywords: professional engineering attributes, engineering education, taxonomy, humanitarian challenges, humanitarian engineering

Procedia PDF Downloads 165
207 Multi-scale Geographic Object-Based Image Analysis (GEOBIA) Approach to Segment a Very High Resolution Images for Extraction of New Degraded Zones. Application to The Region of Mécheria in The South-West of Algeria

Authors: Bensaid A., Mostephaoui T., Nedjai R.

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A considerable area of Algerian lands are threatened by the phenomenon of wind erosion. For a long time, wind erosion and its associated harmful effects on the natural environment have posed a serious threat, especially in the arid regions of the country. In recent years, as a result of increases in the irrational exploitation of natural resources (fodder) and extensive land clearing, wind erosion has particularly accentuated. The extent of degradation in the arid region of the Algerian Mécheriadepartment generated a new situation characterized by the reduction of vegetation cover, the decrease of land productivity, as well as sand encroachment on urban development zones. In this study, we attempt to investigate the potential of remote sensing and geographic information systems for detecting the spatial dynamics of the ancient dune cords based on the numerical processing of PlanetScope PSB.SB sensors images by September 29, 2021. As a second step, we prospect the use of a multi-scale geographic object-based image analysis (GEOBIA) approach to segment the high spatial resolution images acquired on heterogeneous surfaces that vary according to human influence on the environment. We have used the fractal net evolution approach (FNEA) algorithm to segment images (Baatz&Schäpe, 2000). Multispectral data, a digital terrain model layer, ground truth data, a normalized difference vegetation index (NDVI) layer, and a first-order texture (entropy) layer were used to segment the multispectral images at three segmentation scales, with an emphasis on accurately delineating the boundaries and components of the sand accumulation areas (Dune, dunes fields, nebka, and barkhane). It is important to note that each auxiliary data contributed to improve the segmentation at different scales. The silted areas were classified using a nearest neighbor approach over the Naâma area using imagery. The classification of silted areas was successfully achieved over all study areas with an accuracy greater than 85%, although the results suggest that, overall, a higher degree of landscape heterogeneity may have a negative effect on segmentation and classification. Some areas suffered from the greatest over-segmentation and lowest mapping accuracy (Kappa: 0.79), which was partially attributed to confounding a greater proportion of mixed siltation classes from both sandy areas and bare ground patches. This research has demonstrated a technique based on very high-resolution images for mapping sanded and degraded areas using GEOBIA, which can be applied to the study of other lands in the steppe areas of the northern countries of the African continent.

Keywords: land development, GIS, sand dunes, segmentation, remote sensing

Procedia PDF Downloads 85
206 Sustainability in Space: Implementation of Circular Economy and Material Efficiency Strategies in Space Missions

Authors: Hamda M. Al-Ali

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The ultimate aim of space exploration has been centralized around the possibility of life on other planets in the solar system. This aim is driven by the detrimental effects that climate change could potentially have on human survival on Earth in the future. This drives humans to search for feasible solutions to increase environmental and economical sustainability on Earth and to evaluate and explore the ability of human survival on other planets such as Mars. To do that, frequent space missions are required to meet the ambitious human goals. This means that reliable and affordable access to space is required, which could be largely achieved through the use of reusable spacecrafts. Therefore, materials and resources must be used wisely to meet the increasing demand. Space missions are currently extremely expensive to operate. However, reusing materials hence spacecrafts, can potentially reduce overall mission costs as well as the negative impact on both space and Earth environments. This is because reusing materials leads to less waste generated per mission, and therefore fewer landfill sites are required. Reusing materials reduces resource consumption, material production, and the need for processing new and replacement spacecraft and launch vehicle parts. Consequently, this will ease and facilitate human access to outer space as it will reduce the demand for scarce resources, which will boost material efficiency in the space industry. Material efficiency expresses the extent to which resources are consumed in the production cycle and how the waste produced by the industrial process is minimized. The strategies proposed in this paper to boost material efficiency in the space sector are the introduction of key performance indicators that are able to measure material efficiency as well as the introduction of clearly defined policies and legislation that can be easily implemented within the general practices in the space industry. Another strategy to improve material efficiency is by amplifying energy and resource efficiency through reusing materials. The circularity of various spacecraft materials such as Kevlar, steel, and aluminum alloys could be maximized through reusing them directly or after galvanizing them with another layer of material to act as a protective coat. This research paper has an aim to investigate and discuss how to improve material efficiency in space missions considering circular economy concepts so that space and Earth become more economically and environmentally sustainable. The circular economy is a transition from a make-use-waste linear model to a closed-loop socio-economic model, which is regenerative and restorative in nature. The implementation of a circular economy will reduce waste and pollution through maximizing material efficiency, ensuring that businesses can thrive and sustain. Further research into the extent to which reusable launch vehicles reduce space mission costs have been discussed, along with the environmental and economic implications it could have on the space sector and the environment. This has been examined through research and in-depth literature review of published reports, books, scientific articles, and journals. Keywords such as material efficiency, circular economy, reusable launch vehicles and spacecraft materials were used to search for relevant literature.

Keywords: circular economy, key performance indicator, material efficiency, reusable launch vehicles, spacecraft materials

Procedia PDF Downloads 102
205 Statistical Models and Time Series Forecasting on Crime Data in Nepal

Authors: Dila Ram Bhandari

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Throughout the 20th century, new governments were created where identities such as ethnic, religious, linguistic, caste, communal, tribal, and others played a part in the development of constitutions and the legal system of victim and criminal justice. Acute issues with extremism, poverty, environmental degradation, cybercrimes, human rights violations, crime against, and victimization of both individuals and groups have recently plagued South Asian nations. Everyday massive number of crimes are steadfast, these frequent crimes have made the lives of common citizens restless. Crimes are one of the major threats to society and also for civilization. Crime is a bone of contention that can create a societal disturbance. The old-style crime solving practices are unable to live up to the requirement of existing crime situations. Crime analysis is one of the most important activities of the majority of intelligent and law enforcement organizations all over the world. The South Asia region lacks such a regional coordination mechanism, unlike central Asia of Asia Pacific regions, to facilitate criminal intelligence sharing and operational coordination related to organized crime, including illicit drug trafficking and money laundering. There have been numerous conversations in recent years about using data mining technology to combat crime and terrorism. The Data Detective program from Sentient as a software company, uses data mining techniques to support the police (Sentient, 2017). The goals of this internship are to test out several predictive model solutions and choose the most effective and promising one. First, extensive literature reviews on data mining, crime analysis, and crime data mining were conducted. Sentient offered a 7-year archive of crime statistics that were daily aggregated to produce a univariate dataset. Moreover, a daily incidence type aggregation was performed to produce a multivariate dataset. Each solution's forecast period lasted seven days. Statistical models and neural network models were the two main groups into which the experiments were split. For the crime data, neural networks fared better than statistical models. This study gives a general review of the applied statistics and neural network models. A detailed image of each model's performance on the available data and generalizability is provided by a comparative analysis of all the models on a comparable dataset. Obviously, the studies demonstrated that, in comparison to other models, Gated Recurrent Units (GRU) produced greater prediction. The crime records of 2005-2019 which was collected from Nepal Police headquarter and analysed by R programming. In conclusion, gated recurrent unit implementation could give benefit to police in predicting crime. Hence, time series analysis using GRU could be a prospective additional feature in Data Detective.

Keywords: time series analysis, forecasting, ARIMA, machine learning

Procedia PDF Downloads 145
204 Visco-Hyperelastic Finite Element Analysis for Diagnosis of Knee Joint Injury Caused by Meniscal Tearing

Authors: Eiji Nakamachi, Tsuyoshi Eguchi, Sayo Yamamoto, Yusuke Morita, H. Sakamoto

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In this study, we aim to reveal the relationship between the meniscal tearing and the articular cartilage injury of knee joint by using the dynamic explicit finite element (FE) method. Meniscal injuries reduce its functional ability and consequently increase the load on the articular cartilage of knee joint. In order to prevent the induction of osteoarthritis (OA) caused by meniscal injuries, many medical treatment techniques, such as artificial meniscus replacement and meniscal regeneration, have been developed. However, it is reported that these treatments are not the comprehensive methods. In order to reveal the fundamental mechanism of OA induction, the mechanical characterization of meniscus under the condition of normal and injured states is carried out by using FE analyses. At first, a FE model of the human knee joint in the case of normal state – ‘intact’ - was constructed by using the magnetron resonance (MR) tomography images and the image construction code, Materialize Mimics. Next, two types of meniscal injury models with the radial tears of medial and lateral menisci were constructed. In FE analyses, the linear elastic constitutive law was adopted for the femur and tibia bones, the visco-hyperelastic constitutive law for the articular cartilage, and the visco-anisotropic hyperelastic constitutive law for the meniscus, respectively. Material properties of articular cartilage and meniscus were identified using the stress-strain curves obtained by our compressive and the tensile tests. The numerical results under the normal walking condition revealed how and where the maximum compressive stress occurred on the articular cartilage. The maximum compressive stress and its occurrence point were varied in the intact and two meniscal tear models. These compressive stress values can be used to establish the threshold value to cause the pathological change for the diagnosis. In this study, FE analyses of knee joint were carried out to reveal the influence of meniscal injuries on the cartilage injury. The following conclusions are obtained. 1. 3D FE model, which consists femur, tibia, articular cartilage and meniscus was constructed based on MR images of human knee joint. The image processing code, Materialize Mimics was used by using the tetrahedral FE elements. 2. Visco-anisotropic hyperelastic constitutive equation was formulated by adopting the generalized Kelvin model. The material properties of meniscus and articular cartilage were determined by curve fitting with experimental results. 3. Stresses on the articular cartilage and menisci were obtained in cases of the intact and two radial tears of medial and lateral menisci. Through comparison with the case of intact knee joint, two tear models show almost same stress value and higher value than the intact one. It was shown that both meniscal tears induce the stress localization in both medial and lateral regions. It is confirmed that our newly developed FE analysis code has a potential to be a new diagnostic system to evaluate the meniscal damage on the articular cartilage through the mechanical functional assessment.

Keywords: finite element analysis, hyperelastic constitutive law, knee joint injury, meniscal tear, stress concentration

Procedia PDF Downloads 222
203 Leveraging Advanced Technologies and Data to Eliminate Abandoned, Lost, or Otherwise Discarded Fishing Gear and Derelict Fishing Gear

Authors: Grant Bifolchi

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As global environmental problems continue to have highly adverse effects, finding long-term, sustainable solutions to combat ecological distress are of growing paramount concern. Ghost Gear—also known as abandoned, lost or otherwise discarded fishing gear (ALDFG) and derelict fishing gear (DFG)—represents one of the greatest threats to the world’s oceans, posing a significant hazard to human health, livelihoods, and global food security. In fact, according to the UN Food and Agriculture Organization (FAO), abandoned, lost and discarded fishing gear represents approximately 10% of marine debris by volume. Around the world, many governments, governmental and non-profit organizations are doing their best to manage the reporting and retrieval of nets, lines, ropes, traps, floats and more from their respective bodies of water. However, these organizations’ ability to effectively manage files and documents about the environmental problem further complicates matters. In Ghost Gear monitoring and management, organizations face additional complexities. Whether it’s data ingest, industry regulations and standards, garnering actionable insights into the location, security, and management of data, or the application of enforcement due to disparate data—all of these factors are placing massive strains on organizations struggling to save the planet from the dangers of Ghost Gear. In this 90-minute educational session, globally recognized Ghost Gear technology expert Grant Bifolchi CET, BBA, Bcom, will provide real-world insight into how governments currently manage Ghost Gear and the technology that can accelerate success in combatting ALDFG and DFG. In this session, attendees will learn how to: • Identify specific technologies to solve the ingest and management of Ghost Gear data categories, including type, geo-location, size, ownership, regional assignment, collection and disposal. • Provide enhanced access to authorities, fisheries, independent fishing vessels, individuals, etc., while securely controlling confidential and privileged data to globally recognized standards. • Create and maintain processing accuracy to effectively track ALDFG/DFG reporting progress—including acknowledging receipt of the report and sharing it with all pertinent stakeholders to ensure approvals are secured. • Enable and utilize Business Intelligence (BI) and Analytics to store and analyze data to optimize organizational performance, maintain anytime-visibility of report status, user accountability, scheduling, management, and foster governmental transparency. • Maintain Compliance Reporting through highly defined, detailed and automated reports—enabling all stakeholders to share critical insights with internal colleagues, regulatory agencies, and national and international partners.

Keywords: ghost gear, ALDFG, DFG, abandoned, lost or otherwise discarded fishing gear, data, technology

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202 Convolutional Neural Network Based on Random Kernels for Analyzing Visual Imagery

Authors: Ja-Keoung Koo, Kensuke Nakamura, Hyohun Kim, Dongwha Shin, Yeonseok Kim, Ji-Su Ahn, Byung-Woo Hong

Abstract:

The machine learning techniques based on a convolutional neural network (CNN) have been actively developed and successfully applied to a variety of image analysis tasks including reconstruction, noise reduction, resolution enhancement, segmentation, motion estimation, object recognition. The classical visual information processing that ranges from low level tasks to high level ones has been widely developed in the deep learning framework. It is generally considered as a challenging problem to derive visual interpretation from high dimensional imagery data. A CNN is a class of feed-forward artificial neural network that usually consists of deep layers the connections of which are established by a series of non-linear operations. The CNN architecture is known to be shift invariant due to its shared weights and translation invariance characteristics. However, it is often computationally intractable to optimize the network in particular with a large number of convolution layers due to a large number of unknowns to be optimized with respect to the training set that is generally required to be large enough to effectively generalize the model under consideration. It is also necessary to limit the size of convolution kernels due to the computational expense despite of the recent development of effective parallel processing machinery, which leads to the use of the constantly small size of the convolution kernels throughout the deep CNN architecture. However, it is often desired to consider different scales in the analysis of visual features at different layers in the network. Thus, we propose a CNN model where different sizes of the convolution kernels are applied at each layer based on the random projection. We apply random filters with varying sizes and associate the filter responses with scalar weights that correspond to the standard deviation of the random filters. We are allowed to use large number of random filters with the cost of one scalar unknown for each filter. The computational cost in the back-propagation procedure does not increase with the larger size of the filters even though the additional computational cost is required in the computation of convolution in the feed-forward procedure. The use of random kernels with varying sizes allows to effectively analyze image features at multiple scales leading to a better generalization. The robustness and effectiveness of the proposed CNN based on random kernels are demonstrated by numerical experiments where the quantitative comparison of the well-known CNN architectures and our models that simply replace the convolution kernels with the random filters is performed. The experimental results indicate that our model achieves better performance with less number of unknown weights. The proposed algorithm has a high potential in the application of a variety of visual tasks based on the CNN framework. Acknowledgement—This work was supported by the MISP (Ministry of Science and ICT), Korea, under the National Program for Excellence in SW (20170001000011001) supervised by IITP, and NRF-2014R1A2A1A11051941, NRF2017R1A2B4006023.

Keywords: deep learning, convolutional neural network, random kernel, random projection, dimensionality reduction, object recognition

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201 Sustainable Urbanism: Model for Social Equity through Sustainable Development

Authors: Ruchira Das

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The major Metropolises of India are resultant of Colonial manifestation of Production, Consumption and Sustenance. These cities grew, survived, and sustained on the basic whims of Colonial Power and Administrative Agendas. They were symbols of power, authority and administration. Within them some Colonial Towns remained as small towns within the close vicinity of the major metropolises and functioned as self–sufficient units until peripheral development due to tremendous pressure occurred in the metropolises. After independence huge expansion in Judiciary and Administration system resulted City Oriented Employment. A large number of people started residing within the city or within commutable distance of the city and it accelerated expansion of the cities. Since then Budgetary and Planning expenditure brought a new pace in Economic Activities. Investment in Industry and Agriculture sector generated opportunity of employment which further led towards urbanization. After two decades of Budgetary and Planning economic activities in India, a new era started in metropolitan expansion. Four major metropolises started further expansion rapidly towards its suburbs. A concept of large Metropolitan Area developed. Cities became nucleus of suburbs and rural areas. In most of the cases such expansion was not favorable to the relationship between City and its hinterland due to absence of visualization of Compact Sustainable Development. The search for solutions needs to weigh the choices between Rural and Urban based development initiatives. Policymakers need to focus on areas which will give the greatest impact. The impact of development initiatives will spread the significant benefit to all. There is an assumption that development integrates Economic, Social and Environmental considerations with equal weighing. The traditional narrower and almost exclusive focus on economic criteria as the determinant of the level of development is thus re–described and expanded. The Social and Environmental aspects are equally important as Economic aspect to achieve Sustainable Development. The arrangement of opportunities for Public, Semi – Public facilities for its citizen is very much relevant to development. It is responsibility of the administration to provide opportunities for the basic requirement of its inhabitants. Development should be in terms of both Industrial and Agricultural to maintain a balance between city and its hinterland. Thus, policy is to formulate shifting the emphasis away from Economic growth towards Sustainable Human Development. The goal of Policymaker should aim at creating environments in which people’s capabilities can be enhanced by the effective dynamic and adaptable policy. The poverty could not be eradicated simply by increasing income. The improvement of the condition of the people would have to lead to an expansion of basic human capabilities. In this scenario the suburbs/rural areas are considered as environmental burden to the metropolises. A new living has to be encouraged in the suburban or rural. We tend to segregate agriculture from the city and city life, this leads to over consumption, but this urbanism model attempts both these to co–exists and hence create an interesting overlapping of production and consumption network towards sustainable Rurbanism.

Keywords: socio–economic progress, sustainability, social equity, urbanism

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200 A Distributed Smart Battery Management System – sBMS, for Stationary Energy Storage Applications

Authors: António J. Gano, Carmen Rangel

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Currently, electric energy storage systems for stationary applications have known an increasing interest, namely with the integration of local renewable energy power sources into energy communities. Li-ion batteries are considered the leading electric storage devices to achieve this integration, and Battery Management Systems (BMS) are decisive for their control and optimum performance. In this work, the advancement of a smart BMS (sBMS) prototype with a modular distributed topology is described. The system, still under development, has a distributed architecture with modular characteristics to operate with different battery pack topologies and charge capacities, integrating adaptive algorithms for functional state real-time monitoring and management of multicellular Li-ion batteries, and is intended for application in the context of a local energy community fed by renewable energy sources. This sBMS system includes different developed hardware units: (1) Cell monitoring units (CMUs) for interfacing with each individual cell or module monitoring within the battery pack; (2) Battery monitoring and switching unit (BMU) for global battery pack monitoring, thermal control and functional operating state switching; (3) Main management and local control unit (MCU) for local sBMS’s management and control, also serving as a communications gateway to external systems and devices. This architecture is fully expandable to battery packs with a large number of cells, or modules, interconnected in series, as the several units have local data acquisition and processing capabilities, communicating over a standard CAN bus and will be able to operate almost autonomously. The CMU units are intended to be used with Li-ion cells but can be used with other cell chemistries, with output voltages within the 2.5 to 5 V range. The different unit’s characteristics and specifications are described, including the different implemented hardware solutions. The developed hardware supports both passive and active methods for charge equalization, considered fundamental functionalities for optimizing the performance and the useful lifetime of a Li-ion battery package. The functional characteristics of the different units of this sBMS system, including different process variables data acquisition using a flexible set of sensors, can support the development of custom algorithms for estimating the parameters defining the functional states of the battery pack (State-of-Charge, State-of-Health, etc.) as well as different charge equalizing strategies and algorithms. This sBMS system is intended to interface with other systems and devices using standard communication protocols, like those used by the Internet of Things. In the future, this sBMS architecture can evolve to a fully decentralized topology, with all the units using Wi-Fi protocols and integrating a mesh network, making unnecessary the MCU unit. The status of the work in progress is reported, leading to conclusions on the system already executed, considering the implemented hardware solution, not only as fully functional advanced and configurable battery management system but also as a platform for developing custom algorithms and optimizing strategies to achieve better performance of electric energy stationary storage devices.

Keywords: Li-ion battery, smart BMS, stationary electric storage, distributed BMS

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199 Climate Change Impact on Mortality from Cardiovascular Diseases: Case Study of Bucharest, Romania

Authors: Zenaida Chitu, Roxana Bojariu, Liliana Velea, Roxana Burcea

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A number of studies show that extreme air temperature affects mortality related to cardiovascular diseases, particularly among elderly people. In Romania, the summer thermal discomfort expressed by Universal Thermal Climate Index (UTCI) is highest in the Southern part of the country, where Bucharest, the largest Romanian urban agglomeration, is also located. The urban characteristics such as high building density and reduced green areas enhance the increase of the air temperature during summer. In Bucharest, as in many other large cities, the effect of heat urban island is present and determines an increase of air temperature compared to surrounding areas. This increase is particularly important during heat wave periods in summer. In this context, the researchers performed a temperature-mortality analysis based on daily deaths related to cardiovascular diseases, recorded between 2010 and 2019 in Bucharest. The temperature-mortality relationship was modeled by applying distributed lag non-linear model (DLNM) that includes a bi-dimensional cross-basis function and flexible natural cubic spline functions with three internal knots in the 10th, 75th and 90th percentiles of the temperature distribution, for modelling both exposure-response and lagged-response dimensions. Firstly, this study applied this analysis for the present climate. Extrapolation of the exposure-response associations beyond the observed data allowed us to estimate future effects on mortality due to temperature changes under climate change scenarios and specific assumptions. We used future projections of air temperature from five numerical experiments with regional climate models included in the EURO-CORDEX initiative under the relatively moderate (RCP 4.5) and pessimistic (RCP 8.5) concentration scenarios. The results of this analysis show for RCP 8.5 an ensemble-averaged increase with 6.1% of heat-attributable mortality fraction in future in comparison with present climate (2090-2100 vs. 2010-219), corresponding to an increase of 640 deaths/year, while mortality fraction due to the cold conditions will be reduced by 2.76%, corresponding to a decrease by 288 deaths/year. When mortality data is stratified according to the age, the ensemble-averaged increase of heat-attributable mortality fraction for elderly people (> 75 years) in the future is even higher (6.5 %). These findings reveal the necessity to carefully plan urban development in Bucharest to face the public health challenges raised by the climate change. Paper Details: This work is financed by the project URCLIM which is part of ERA4CS, an ERA-NET initiated by JPI Climate, and funded by Ministry of Environment, Romania with co-funding by the European Union (Grant 690462). A part of this work performed by one of the authors has received funding from the European Union’s Horizon 2020 research and innovation programme from the project EXHAUSTION under grant agreement No 820655.

Keywords: cardiovascular diseases, climate change, extreme air temperature, mortality

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198 Biochemical Effects of Low Dose Dimethyl Sulfoxide on HepG2 Liver Cancer Cell Line

Authors: Esra Sengul, R. G. Aktas, M. E. Sitar, H. Isan

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Hepatocellular carcinoma (HCC) is a hepatocellular tumor commonly found on the surface of the chronic liver. HepG2 is the most commonly used cell type in HCC studies. The main proteins remaining in the blood serum after separation of plasma fibrinogen are albumin and globulin. The fact that the albumin showed hepatocellular damage and reflect the synthesis capacity of the liver was the main reason for our use. Alpha-Fetoprotein (AFP) is an albumin-like structural embryonic globulin found in the embryonic cortex, cord blood, and fetal liver. It has been used as a marker in the follow-up of tumor growth in various malign tumors and in the efficacy of surgical-medical treatments, so it is a good protein to look at with albumins. We have seen the morphological changes of dimethyl sulfoxide (DMSO) on HepG2 and decided to investigate its biochemical effects. We examined the effects of DMSO, which is used in cell cultures, on albumin, AFP and total protein at low doses. Material Method: Cell Culture: Medium was prepared in cell culture using Dulbecco's Modified Eagle Media (DMEM), Fetal Bovine Serum Dulbecco's (FBS), Phosphate Buffered Saline and trypsin maintained at -20 ° C. Fixation of Cells: HepG2 cells, which have been appropriately developed at the end of the first week, were fixed with acetone. We stored our cells in PBS at + 4 ° C until the fixation was completed. Area Calculation: The areas of the cells are calculated in the ImageJ (IJ). Microscope examination: The examination was performed with a Zeiss Inverted Microscope. Daytime photographs were taken at 40x, 100x 200x and 400x. Biochemical Tests: Protein (Total): Serum sample was analyzed by a spectrophotometric method in autoanalyzer. Albumin: Serum sample was analyzed by a spectrophotometric method in autoanalyzer. Alpha-fetoprotein: Serum sample was analyzed by ECLIA method. Results: When liver cancer cells were cultured in medium with 1% DMSO for 4 weeks, a significant difference was observed when compared with the control group. As a result, we have seen that DMSO can be used as an important agent in the treatment of liver cancer. Cell areas were reduced in the DMSO group compared to the control group and the confluency ratio increased. The ability to form spheroids was also significantly higher in the DMSO group. Alpha-fetoprotein was lower than the values of an ordinary liver cancer patient and the total protein amount increased to the reference range of the normal individual. Because the albumin sample was below the specimen value, the numerical results could not be obtained on biochemical examinations. We interpret all these results as making DMSO a caretaking aid. Since each one was not enough alone we used 3 parameters and the results were positive when we refer to the values of a normal healthy individual in parallel. We hope to extend the study further by adding new parameters and genetic analyzes, by increasing the number of samples, and by using DMSO as an adjunct agent in the treatment of liver cancer.

Keywords: hepatocellular carcinoma, HepG2, dimethyl sulfoxide, cell culture, ELISA

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