Search results for: processing and manufacturing technologies

Authors: Yesim Sucullu Karadag, Pinar Kurt, Sule Bilen, Nese Subutay Oztekin, Fikri Ak

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Background: Primary cervical dystonia is thought to be a purely motor disorder. But recent studies revealed that patients with dystonia had additional non-motor features. Sensory and psychiatric disturbances could be included into the non-motor spectrum of dystonia. The Basal Ganglia receive inputs from all cortical areas and throughout the thalamus project to several cortical areas, thus participating to circuits that have been linked to motor as well as sensory, emotional and cognitive functions. However, there are limited studies indicating cognitive impairment in patients with cervical dystonia. More evidence is required regarding neurocognitive functioning in these patients. Objective: This study is aimed to investigate neurocognitive profile of cervical dystonia patients in comparison to healthy controls (HC) by employing a detailed set of neuropsychological tests in addition to self-reported instruments. Methods: Totally 29 (M/F: 7/22) cervical dystonia patients and 30 HC (M/F: 10/20) were included into the study. Exclusion criteria were depression and not given informed consent. Standard demographic, educational data and clinical reports (disease duration, disability index) were recorded for all patients. After a careful neurological evaluation, all subjects were given a comprehensive battery of neuropsychological tests: Self report of neuropsychological condition (by visual analogue scale-VAS, 0-100), RAVLT, STROOP, PASAT, TMT, SDMT, JLOT, DST, COWAT, ACTT, and FST. Patients and HC were compared regarding demographic, clinical features and neurocognitive tests. Also correlation between disease duration, disability index and self report -VAS were assessed. Results: There was no difference between patients and HCs regarding socio-demographic variables such as age, gender and years of education (p levels were 0.36, 0.436, 0.869; respectively). All of the patients were assessed at the peak of botulinum toxine effect and they were not taking an anticholinergic agent or benzodiazepine. Dystonia patients had significantly impaired verbal learning and memory (RAVLT, p<0.001), divided attention and working memory (ACTT, p<0.001), attention speed (TMT-A and B, p=0.008, 0.050), executive functions (PASAT, p<0.001; SDMT, p= 0.001; FST, p<0.001), verbal attention (DST, p=0.001), verbal fluency (COWAT, p<0.001), visio-spatial processing (JLOT, p<0.001) in comparison to healthy controls. But focused attention (STROOP-spontaneous correction) was not different between two groups (p>0.05). No relationship was found regarding disease duration and disability index with any neurocognitive tests. Conclusions: Our study showed that neurocognitive functions of dystonia patients were worse than control group with the similar age, sex, and education independently clinical expression like disease duration and disability index. This situation may be the result of possible cortical and subcortical changes in dystonia patients. Advanced neuroimaging techniques might be helpful to explain these changes in cervical dystonia patients.

Keywords: cervical dystonia, neurocognitive impairment, neuropsychological test, dystonia disability index

Procedia PDF Downloads 387

Authors: Bolysbek Utelbayev, Tasmagambetova Aigerim, Toktasyn Raila, Markayev Yergali, Myrzakhanov Maxat

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Intensive development of secondary processes of destructive processing of crude oil has led to the occurrence of oil refining factories resources of C2-C4 hydrocarbons. Except for oil gases also contain basically C2-C4 hydrocarbon gases where some of the amounts are burned. All these data has induced interest to the study of producing alkylate from hydrocarbons С2-С4 which being as components of motor fuels. The purpose of this work was studying transformation propane-propene, butane-butene fractions at the presence of the ruthenium-chromic support catalyst whereas the carrier is served pillar - structural montmorillonite containing in native bentonite clay. In this work is considered condition and structure of the bentonite clay from the South-Kazakhstan area of the Republic Kazakhstan. For preparation rhodium support catalyst (0,5-1,0 mass. % Rh) was used chloride of rhodium-RhCl3∙3H2O, as a carrier was used modified bentonite clay. For modifying natural clay to pillar structural form were used polyhydroxy complexes of chromium. To aqueous solution of chloride chromium gradually flowed the solution of sodium hydroxide at gradual hashing up to pH~3-4. The concentration of chloride chromium was paid off proceeding from calculation 5-30 mmole Cr3+ per gram clay. Suspension bentonite (~1,0 mass. %) received by intensive washing it in water during 4 h, pH-water extract of clay makes -8-9. The acidity of environment supervised by means of digital pH meter OP-208/1. In order to prevent coagulation of a solution polyhydroxy complexes of chromium, it was slowly added to a suspension of clay. "Reserve of basicity" Cr3+:/OH-allowing to prevent coagulation chloride of rhodium made 1/3. After endurance processed suspensions of clay during 24 h, a deposit was washed by water and condensed. The sample, after separate from a liquid phase, dried at first at the room temperature, and then at 110°C (2h) with the subsequent rise the temperature up to 180°C (4h). After cooling the firm mass was pounded to a powder, it was shifted infractions with the certain sizes of particles. Fractions of particles modifying clay in the further were impregnated with an aqueous solution with rhodium-RhCl3∙3H2O (0,5-1,0 mаss % Rh ). Obtained pillar structural bentonite approaches heat resistance and its porous structure above the 773K. Pillar structural bentonite was used for preparation 1.0% Ru/Carrier (modifying bentonite) support catalysts where is realised alkylation of C2-C4 hydrocarbons. The process of alkylation is carried out at a partial pressure of hydrogen 0.5-1.0MPa. Outcome 2.2.4 three methyl pentane and 2.2.3 trimethylpentane achieved 40%. At alkylation butane-butene mixture outcome of the isooctane is achieved 60%. In this condition of studying the ethene is not undergoing to alkylation.

Keywords: alkylation, butene, pillar structure, ruthenium catalyst

Procedia PDF Downloads 374

Authors: Kimberley Adamek

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According to the Council on Tall Buildings, there has been a rapid increase in the construction of tall or “megatall” buildings over the past two decades. Simultaneously, the New England Journal of Medicine has reported that there has been a steady increase in climate related natural disasters since the 1970s; the eastern expansion of the USA's infamous Tornado Alley being just one of many current issues. In the future, this could mean that tall buildings, which already guide high speed winds down to pedestrian levels would have to withstand stronger forces and protect pedestrians in more extreme ways. Although many projects are required to be verified within wind tunnels and a handful of cities such as San Francisco have included wind testing within building code standards, there are still many examples where wind is only considered for basic loading. This typically results in and an increase of structural expense and unwanted mitigation strategies that are proposed late within a project. When building cities, architects rarely consider how each building alters the invisible patterns of wind and how these alterations effect other areas in different ways later on. It is not until these forces move, overpower and even destroy cities that people take notice. For example, towers have caused winds to blow objects into people (Walkie-Talkie Tower, Leeds, England), cause building parts to vibrate and produce loud humming noises (Beetham Tower, Manchester), caused wind tunnels in streets as well as many other issues. Alternatively, there exist towers which have used their form to naturally draw in air and ventilate entire facilities in order to eliminate the needs for costly HVAC systems (The Met, Thailand) and used their form to increase wind speeds to generate electricity (Bahrain Tower, Dubai). Wind and weather exist and effect all parts of the world in ways such as: Science, health, war, infrastructure, catastrophes, tourism, shopping, media and materials. Working in partnership with a leading wind engineering company RWDI, a series of tests, images and animations documenting discovered interactions of different building forms with wind will be collected to emphasize the possibilities for wind use to architects. A site within San Francisco (due to its increasing tower development, consistently wind conditions and existing strict wind comfort criteria) will host a final design. Iterations of this design will be tested within the wind tunnel and computational fluid dynamic systems which will expose, utilize and manipulate wind flows to create new forms, technologies and experiences. Ultimately, this thesis aims to question the amount which the environment is allowed to permeate building enclosures, uncover new programmatic possibilities for wind in buildings, and push the boundaries of working with the wind to ensure the development and safety of future cities. This investigation will improve and expand upon the traditional understanding of wind in order to give architects, wind engineers as well as the general public the ability to broaden their scope in order to productively utilize this living phenomenon that everyone constantly feels but cannot see.

Keywords: wind engineering, climate, visualization, architectural aerodynamics

Procedia PDF Downloads 338

Authors: Faheema Khan

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To investigate the ability of sensitive and tolerant genotype of Glycine max to adapt to a saline environment in a field, we examined the growth performance, water relation and activities of antioxidant enzymes in relation to photosynthetic rate, chlorophyll a fluorescence, photosynthetic pigment concentration, protein and proline in plants exposed to salt stress. Ten soybean genotypes (Pusa-20, Pusa-40, Pusa-37, Pusa-16, Pusa-24, Pusa-22, BRAGG, PK-416, PK-1042, and DS-9712) were selected and grown hydroponically. After 3 days of proper germination, the seedlings were transferred to Hoagland’s solution (Hoagland and Arnon 1950). The growth chamber was maintained at a photosynthetic photon flux density of 430 μmol m−2 s−1, 14 h of light, 10 h of dark and a relative humidity of 60%. The nutrient solution was bubbled with sterile air and changed on alternate days. Ten-day-old seedlings were given seven levels of salt in the form of NaCl viz., T1 = 0 mM NaCl, T2=25 mM NaCl, T3=50 mM NaCl, T4=75 mM NaCl, T5=100 mM NaCl, T6=125 mM NaCl, T7=150 mM NaCl. The investigation showed that genotype Pusa-24, PK-416 and Pusa-20 appeared to be the most salt-sensitive. genotypes as inferred from their significantly reduced length, fresh weight and dry weight in response to the NaCl exposure. Pusa-37 appeared to be the most tolerant genotype since no significant effect of NaCl treatment on growth was found. We observed a greater decline in the photosynthetic variables like photosynthetic rate, chlorophyll fluorescence and chlorophyll content, in salt-sensitive (Pusa-24) genotype than in salt-tolerant Pusa-37 under high salinity. Numerous primers were verified on ten soybean genotypes obtained from Operon technologies among which 30 RAPD primers shown high polymorphism and genetic variation. The Jaccard’s similarity coefficient values for each pairwise comparison between cultivars were calculated and similarity coefficient matrix was constructed. The closer varieties in the cluster behaved similar in their response to salinity tolerance. Intra-clustering within the two clusters precisely grouped the 10 genotypes in sub-cluster as expected from their physiological findings.Salt tolerant genotype Pusa-37, was further analysed by 2-Dimensional gel electrophoresis to analyse the differential expression of proteins at high salt stress. In the Present study, 173 protein spots were identified. Of these, 40 proteins responsive to salinity were either up- or down-regulated in Pusa-37. Proteomic analysis in salt-tolerant genotype (Pusa-37) led to the detection of proteins involved in a variety of biological processes, such as protein synthesis (12 %), redox regulation (19 %), primary and secondary metabolism (25 %), or disease- and defence-related processes (32 %). In conclusion, the soybean plants in our study responded to salt stress by changing their protein expression pattern. The photosynthetic, biochemical and molecular study showed that there is variability in salt tolerance behaviour in soybean genotypes. Pusa-24 is the salt-sensitive and Pusa-37 is the salt-tolerant genotype. Moreover this study gives new insights into the salt-stress response in soybean and demonstrates the power of genomic and proteomic approach in plant biology studies which finally could help us in identifying the possible regulatory switches (gene/s) controlling the salt tolerant genotype of the crop plants and their possible role in defence mechanism.

Keywords: glycine max, salt stress, RAPD, genomic and proteomic variability

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Authors: M. Vezir Kahraman, Emre Basturk

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Energy storage technology offers new ways to meet the demand to obtain efficient and reliable energy storage materials. Thermal energy storage systems provide the potential to acquire energy savings, which in return decrease the environmental impact related to energy usage. For this purpose, phase change materials (PCMs) that work as 'latent heat storage units' which can store or release large amounts of energy are preferred. Phase change materials (PCMs) are being utilized to absorb, collect and discharge thermal energy during the cycle of melting and freezing, converting from one phase to another. Phase Change Materials (PCMs) can generally be arranged into three classes: organic materials, salt hydrates and eutectics. Many kinds of organic and inorganic PCMs and their blends have been examined as latent heat storage materials. PCMs have found different application areas such as solar energy storage and transfer, HVAC (Heating, Ventilating and Air Conditioning) systems, thermal comfort in vehicles, passive cooling, temperature controlled distributions, industrial waste heat recovery, under floor heating systems and modified fabrics in textiles. Ultraviolet (UV)-curing technology has many advantages, which made it applicable in many different fields. Low energy consumption, high speed, room-temperature operation, low processing costs, high chemical stability, and being environmental friendly are some of its main benefits. UV-curing technique has many applications. One of the many advantages of UV-cured PCMs is that they prevent the interior PCMs from leaking. Shape-stabilized PCM is prepared by blending the PCM with a supporting material, usually polymers. In our study, this problem is minimized by coating the fatty alcohols with a photo-cross-linked thiol-ene based polymeric system. Leakage is minimized because photo-cross-linked polymer acts a matrix. The aim of this study is to introduce a novel thiol-ene based shape-stabilized PCM. Photo-crosslinked thiol-ene based polymers containing fatty alcohols were prepared and characterized for the purpose of phase change materials (PCMs). Different types of fatty alcohols were used in order to investigate their properties as shape-stable PCMs. The structure of the PCMs was confirmed by ATR-FTIR techniques. The phase transition behaviors, thermal stability of the prepared photo-crosslinked PCMs were investigated by differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA). This work was supported by Marmara University, Commission of Scientific Research Project.

Keywords: differential scanning calorimetry (DSC), Polymeric phase change material, thermal energy storage, UV-curing

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Authors: Аndrey Marchenko, Oleg Linkov, Alexander Osetrov, Sergiy Kravchenko

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The low-calorie of gases include biogas, coal gas, coke oven gas, associated petroleum gas, gases sewage, etc. These gases are usually released into the atmosphere or burned on flares, causing substantial damage to the environment. However, with the right approach, low-calorie gas fuel can become a valuable source of energy. Specified determines the relevance of areas related to the development of low-calorific gas utilization technologies. As an example, in the work considered one of way of utilization of coalmine gas, because Ukraine ranks fourth in the world in terms of coal mine gas emission (4.7% of total global emissions, or 1.2 billion m³ per year). Experts estimate that coal mine gas is actively released in the 70-80 percent of existing mines in Ukraine. The main component of coal mine gas is methane (25-60%) Methane in 21 times has a greater impact on the greenhouse effect than carbon dioxide disposal problem has become increasingly important in the context of the increasing need to address the problems of climate, ecology and environmental protection. So marked causes negative effect of both local and global nature. The efforts of the United Nations and the World Bank led to the adoption of the program 'Zero Routine Flaring by 2030' dedicated to the cessation of these gases burn in flares and disposing them with the ability to generate heat and electricity. This study proposes to use coal gas as a fuel for gas engines to generate heat and electricity. Analyzed the physical-chemical properties of low-calorie gas fuels were allowed to choose a suitable engine, as well as estimate the influence of the composition of the fuel at its techno-economic indicators. Most suitable for low-calorie gas is engine with pre-combustion chamber jet ignition. In Ukraine is accumulated extensive experience in exploitation and production of gas engines with capacity of 1100 kW type GD100 (10GDN 207/2 * 254) fueled by natural gas. By using system pre- combustion chamber jet ignition and quality control in the engines type GD100 introduces the concept of burning depleted burn fuel mixtures, which in turn leads to decrease in the concentration of harmful substances of exhaust gases. The main problems of coal mine gas as a fuel for ICE is low calorific value, the presence of components that adversely affect combustion processes and terms of operation of the ICE, the instability of the composition, weak ignition. In some cases, these problems can be solved by adaptation engine design using coal mine gas as fuel (changing compression ratio, fuel injection quantity increases, change ignition time, increase energy plugs, etc.). It is shown that the use of coal mine gas engines with prechamber has not led to significant changes in the indicator parameters (ηi = 0.43 - 0.45). However, this significantly increases the volumetric fuel consumption, which requires increased fuel injection quantity to ensure constant nominal engine power. Thus, the utilization of low-calorie gas fuels in stationary gas engine type-based GD100 will significantly reduce emissions of harmful substances into the atmosphere when the generate cheap electricity and heat.

Keywords: gas engine, low-calorie gas, methane, pre-combustion chamber, utilization

Procedia PDF Downloads 240

Authors: Z. Nurzaireena, K. Azalea, T. Azirawaty, S. Jameela, G. Muralitharan

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The aim of this study is the review of the management practices of sickle cell disease patients during pregnancy, as well as the maternal and neonatal outcome at Ampang Hospital, Selangor. The study consisted of a review of pregnant patients with sickle cell disease under follow up at the Hematology Clinic, Ampang Hospital over the last seven years to assess their management and maternal-fetal outcome. The results of the review show that Ampang Hospital is considered the public hematology centre for sickle cell disease and had successfully managed three pregnancies throughout the last seven years. Patients’ presentations, managements and maternal-fetal outcome were compared and reviewed for academic improvements. All three patients were seen very early in their pregnancy and had been given a regime of folic acid, antibiotics and thrombo-prophylactic drugs. Close monitoring of maternal and fetal well being was done by the hematologists and obstetricians. Among the patients, there were multiple admissions during the pregnancy for either a painful sickle cell bone crisis, haemolysis following an infection and anemia requiring phenotype- matched blood and exchange transfusions. Broad spectrum antibiotics coverage during and infection, hydration, pain management and venous-thrombolism prophylaxis were mandatory. The pregnancies managed to reach near term in the third trimester but all required emergency caesarean section for obstetric indications. All pregnancies resulted in live births with good fetal outcome. During post partum all were nursed closely in the high dependency units for further complications and were discharged well. Post partum follow up and contraception counseling was comprehensively given for future pregnancies. Sickle cell disease is uncommonly seen in the East, especially in the South East Asian region, yet more cases are seen in the current decade due to improved medical expertise and advance medical laboratory technologies. Pregnancy itself is a risk factor for sickle cell patients as increased thrombosis event and risk of infections can lead to multiple crisis, haemolysis, anemia and vaso-occlusive complications including eclampsia, cerebrovasular accidents and acute bone pain. Patients mostly require multiple blood product transfusions thus phenotype-matched blood is required to reduce the risk of alloimmunozation. Emphasizing the risks and complications in preconception counseling and establishing an ultimate pregnancy plan would probably reduce the risk of morbidity and mortality to the mother and unborn child. Early management for risk of infection, thromboembolic events and adequate hydration is mandatory. A holistic approach involving multidisciplinary team care between the hematologist, obstetricians, anesthetist, neonatologist and close nursing care for both mother and baby would ensure the best outcome. In conclusion, sickle cell disease by itself is a high risk medical condition and pregnancy would further amplify the risk. Thus, close monitoring with combine multidisciplinary care, counseling and educating the patients are crucial in achieving the safe outcome.

Keywords: anaemia, haemoglobinopathies, pregnancy, sickle cell disease

Procedia PDF Downloads 234

Authors: K. Power, M. White, B. Dunleavey, E. Comerford, C. Doherty, N. Delanty, R. Corbridge, M. Fitzsimons

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Introduction: Providing people with access to their own healthcare information and engaging them as co-authors of their health record can promote better transparency, trust, and inclusivity in the healthcare system. With the advent of electronic health records, there is a move towards involving patients as partners in their healthcare by providing them with access to their own health data via electronic patient portals (ePortal). For example, a recently developed ePortal to the Irish National Epilepsy Electronic Patient Record (EPR) provides access to summary medical records, tools for Patient Reported Outcomes (PROM), health goal-setting and preparation for clinical appointments. Aim: To determine what people with epilepsy (their families/carers) value about the Irish epilepsy ePortal. Methods: A socio-technical process was employed recruiting 30 families of people with epilepsy who also have an intellectual disability (ID). Family members who are a care partner of the person with epilepsy (PWE) were invited to co-design, develop and implement the ePortal. Family members engaged in usability and utility testing which involved a face to face meeting to learn about the ePortal, register for a user account and evaluate its structure and content. Family members were instructed to login to the portal on at least two separate occasions following the meeting and to complete a self-report evaluation tool during this time. The evaluation tool, based on a Usability Questionnaire (Lewis, 1993), consists of a short assessment of comfort using technology, instructions for using the ePortal and some tasks to complete. Tasks included validating summary record details, assessing ePortal ease of use, evaluation of information presented. Participants were asked for suggestions on how to improve the portal and make it more applicable to PWE who also have an ID. Results: Family members responded positively to the ePortal and valued the ability to share information between clinicians and care partners; use the ePortal as a passport between different healthcare settings (e.g., primary care to hospital). In the context of elderly parents of PWE, the ePortal is valued as a tool for supporting shared care between family members. Participants welcomed the facility to log lists of questions and goals to discuss with the clinician at the next clinical appointment as a means of improving quality of care. Participants also suggested further enhancements to the ePortal such as access to clinic letters which can provide an aide memoir in terms of the careplan agreed with the clinical team. For example, through the ePortal, people could see what investigations or therapies are scheduled. Conclusion: The Epilepsy Patient Portal is accessible via a range of devices such as smartphones and tablets. ePortals have the potential to help personalise care, improve patient involvement in clinical decision making, engage them as quality and safety partners, and help clinicians be more responsive to patient needs. Acknowledgement: The epilepsy ePortal project is part of PISCES, a Lighthouse Project funded by eHealth Ireland and HSE to help build an understanding of the benefits of eHealth technologies in the Irish Healthcare System.

Keywords: electronic patient portal, electronic patient record, epilepsy, intellectual disability, usability testing

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Authors: Niharika Kaushal, Minni Singh

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Fruit crops are widely cultivated throughout the World, with citrus being one of the most common. Mandarins, oranges, grapefruits, lemons, and limes are among the most frequently grown varieties. Citrus cultivars are industrially processed into juice, resulting in approx. 25-40% by wt. of biomass in the form of peels and seeds, generally considered as waste. In consequence, a significant amount of this nutraceutical-enriched biomass goes to waste, which, if utilized wisely, could revolutionize the functional food industry, as this biomass possesses a wide range of bioactive compounds, mainly within the class of polyphenols and terpenoids, making them an abundant source of functional bioactive. Mandarin is a potential source of bioflavonoids with putative antioxidative properties, and its potential application for developing value-added products is obvious. In this study, ‘kinnow’ mandarin (Citrus nobilis X Citrus deliciosa) biomass was studied for its flavonoid profile. For this, dried and pulverized peels were subjected to green and sustainable extraction techniques, namely, supercritical fluid extraction carried out under conditions pressure: 330 bar, temperature: 40 ̊ C and co-solvent: 10% ethanol. The obtained extract was observed to contain 47.3±1.06 mg/ml rutin equivalents as total flavonoids. Mass spectral analysis revealed the prevalence of polymethoxyflavones (PMFs), chiefly tangeretin and nobiletin. Furthermore, the antioxidant potential was analyzed by the 2,2-diphenyl-1-picrylhydrazyl (DPPH) method, which was estimated to be at an IC₅₀ of 0.55μg/ml. The pre-systemic metabolism of flavonoids limits their functionality, as was observed in this study through in vitro gastrointestinal studies where nearly 50.0% of the flavonoids were degraded within 2 hours of gastric exposure. We proposed nanoencapsulation as a means to overcome this problem, and flavonoids-laden polylactic-co-glycolic acid (PLGA) nano encapsulates were bioengineered using solvent evaporation method, and these were furnished to a particle size between 200-250nm, which exhibited protection of flavonoids in the gastric environment, allowing only 20% to be released in 2h. A further step involved impregnating the nano encapsulates within alginate hydrogels which were fabricated by ionic cross-linking, which would act as delivery vehicles within the gastrointestinal (GI) tract. As a result, 100% protection was achieved from the pre-systemic release of bioflavonoids. These alginate hydrogels had key significant features, i.e., less porosity of nearly 20.0%, and Cryo-SEM (Cryo-scanning electron microscopy) images of the composite corroborate the packing ability of the alginate hydrogel. As a result of this work, it is concluded that the waste can be used to develop functional biomaterials while retaining the functionality of the bioactive itself.

Keywords: bioflavonoids, gastrointestinal, hydrogels, mandarins

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Authors: Ngoc Nguyen

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There is large plantation of Eucalyptus globulus established which has been grown to produce pulpwood. This resource is not suitable for the production of decorative products, principally due to low grades of wood and “dull” appearance but many trials have been already undertaken for the production of veneer and veneer-based engineered wood products, such as plywood and laminated veneer lumber (LVL). The manufacture of veneer-based products has been recently identified as an unprecedented opportunity to promote higher value utilisation of plantation resources. However, many uncertainties remain regarding the impacts of inferior wood quality of young plantation trees on product recovery and value, and with respect to optimal processing techniques. Moreover, the quality of veneer and veneer-based products is far from optimal as trees are young and have small diameters; and the veneers have the significant colour variation which affects to the added value of final products. Developing production methods which would enhance appearance of low-quality veneer would provide a great potential for the production of high-value wood products such as furniture, joinery, flooring and other appearance products. One of the methods of enhancing appearance of low quality veneer, developed in Italy, involves the production of multilaminar veneer, also named “reconstructed veneer”. An important stage of the multilaminar production is colouring the veneer which can be achieved by dyeing veneer with dyes of different colours depending on the type of appearance products, their design and market demand. Although veneer dyeing technology has been well advanced in Italy, it has been focused on poplar veneer from plantation which wood is characterized by low density, even colour, small amount of defects and high permeability. Conversely, the majority of plantation eucalypts have medium to high density, have a lot of defects, uneven colour and low permeability. Therefore, detailed study is required to develop dyeing methods suitable for colouring eucalypt veneers. Brown reactive dye is used for veneer colouring process. Veneers from sapwood and heartwood of two moisture content levels are used to conduct colouring experiments: green veneer and veneer dried to 12% MC. Prior to dyeing, all samples are treated. Both soaking (dipping) and vacuum pressure methods are used in the study to compare the results and select most efficient method for veneer dyeing. To date, the results of colour measurements by CIELAB colour system showed significant differences in the colour of the undyed veneers produced from heartwood part. The colour became moderately darker with increasing of Sodium chloride, compared to control samples according to the colour measurements. It is difficult to conclude a suitable dye solution used in the experiments at this stage as the variables such as dye concentration, dyeing temperature or dyeing time have not been done. The dye will be used with and without UV absorbent after all trials are completed using optimal parameters in colouring veneers.

Keywords: Eucalyptus globulus, veneer colouring/dyeing, multilaminar veneer, reactive dye

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Authors: Mylena McCoggle, Shyra Wilson, Andrea Rivera, Rocio Alba-Flores

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This work introduces the use of EMGs (electromyography) from muscle sensors to develop an Artificial Neural Network (ANN) for pattern recognition to control a small unmanned aerial vehicle. The objective of this endeavor exhibits interfacing drone applications beyond manual control directly. MyoWare Muscle sensor contains three EMG electrodes (dual and single type) used to collect signals from the posterior (extensor) and anterior (flexor) forearm and the bicep. Collection of raw voltages from each sensor were connected to an Arduino Uno and a data processing algorithm was developed with the purpose of interpreting the voltage signals given when performing flexing, resting, and motion of the arm. Each sensor collected eight values over a two-second period for the duration of one minute, per assessment. During each two-second interval, the movements were alternating between a resting reference class and an active motion class, resulting in controlling the motion of the drone with left and right movements. This paper further investigated adding up to three sensors to differentiate between hand gestures to control the principal motions of the drone (left, right, up, and land). The hand gestures chosen to execute these movements were: a resting position, a thumbs up, a hand swipe right motion, and a flexing position. The MATLAB software was utilized to collect, process, and analyze the signals from the sensors. The protocol (machine learning tool) was used to classify the hand gestures. To generate the input vector to the ANN, the mean, root means squared, and standard deviation was processed for every two-second interval of the hand gestures. The neuromuscular information was then trained using an artificial neural network with one hidden layer of 10 neurons to categorize the four targets, one for each hand gesture. Once the machine learning training was completed, the resulting network interpreted the processed inputs and returned the probabilities of each class. Based on the resultant probability of the application process, once an output was greater or equal to 80% of matching a specific target class, the drone would perform the motion expected. Afterward, each movement was sent from the computer to the drone through a Wi-Fi network connection. These procedures have been successfully tested and integrated into trial flights, where the drone has responded successfully in real-time to predefined command inputs with the machine learning algorithm through the MyoWare sensor interface. The full paper will describe in detail the database of the hand gestures, the details of the ANN architecture, and confusion matrices results.

Keywords: artificial neural network, biosensors, electromyography, machine learning, MyoWare muscle sensors, Arduino

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Authors: Taif Rocky, Uttam Saha, Mahobul Islam

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With a rapid urbanisation in Bangladesh, waste management remains one of the core challenges. Turning municipal waste into biogas for mass usage is a solution that Bangladesh needs to adopt urgently. Practical Action with its commitment to challenging poverty with technological justice has piloted such idea in Gaibandha. The initiative received immense success and drew the attention of policy makers and practitioners. We believe, biogas from waste can highly contribute to meet the growing demand for energy in the country at present and in the future. Practical Action has field based experience in promoting small scale and innovative technologies. We have proven track record in integrated solid waste management. We further utilized this experience to promote waste to biogas at end users’ level. In 2011, we have piloted a project on waste to biogas in Gaibandha, a northern secondary town of Bangladesh. With resource and support from UNICEF and with our own innovative funds we have established a complete chain of utilizing waste to the renewable energy source and organic fertilizer. Biogas is produced from municipal solid waste, which is properly collected, transported and segregated by private entrepreneurs. The project has two major focuses, diversification of biogas end use and establishing a public-private partnership business model. The project benefits include Recycling of Wastes, Improved institutional (municipal) capacity, Livelihood from improved services and Direct Income from the project. Project risks include Change of municipal leadership, Traditional mindset, Access to decision making, Land availability. We have observed several outcomes from the initiative. Up scaling such an initiative will certainly contribute for sustainable cleaner and healthier urban environment and urban poverty reduction. - It reduces the unsafe disposal of wastes which improve the cleanliness and environment of the town. -Make drainage system effective reducing the adverse impact of water logging or flooding. -Improve public health from better management of wastes. -Promotes usage of biogas replacing the use of firewood/coal which creates smoke and indoor air pollution in kitchens which have long term impact on health of women and children. -Reduce the greenhouse gas emission from the anaerobic recycling of wastes and contributes to sustainable urban environment. -Promote the concept of agroecology from the uses of bio slurry/compost which contributes to food security. -Creates green jobs from waste value chain which impacts on poverty alleviation of urban extreme poor. -Improve municipal governance from inclusive waste services and functional partnership with private sectors. -Contribute to the implementation of 3R (Reduce, Reuse, Recycle) Strategy and Employment Creation of extreme poor to achieve the target set in Vision 2021 by Government of Bangladesh.

Keywords: kitchen waste, secondary town, biogas, segregation

Procedia PDF Downloads 188

Authors: K. H. Reeta, Bhavana Prasher, Mitali Mukerji, Dhwani Dholakia, Sangeeta Khanna, Archana Vats, Shivam Pandey, Sandeep Seth, Subir Kumar Maulik

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Introduction Research has demonstrated a connection between coronary artery disease (CAD) and genetics. We did a deep literature mining using both bioinformatics and manual efforts to identify the susceptible polymorphisms in coronary artery disease. Further, the study sought to validate these findings in an Asian population. Methodology In first phase, we used an automated pipeline which organizes and presents structured information on SNPs, Population and Diseases. The information was obtained by applying Natural Language Processing (NLP) techniques to approximately 28 million PubMed abstracts. To accomplish this, we utilized Python scripts to extract and curate disease-related data, filter out false positives, and categorize them into 24 hierarchical groups using named Entity Recognition (NER) algorithms. From the extensive research conducted, a total of 466 unique PubMed Identifiers (PMIDs) and 694 Single Nucleotide Polymorphisms (SNPs) related to coronary artery disease (CAD) were identified. To refine the selection process, a thorough manual examination of all the studies was carried out. Specifically, SNPs that demonstrated susceptibility to CAD and exhibited a positive Odds Ratio (OR) were selected, and a final pool of 324 SNPs was compiled. The next phase involved validating the identified SNPs in DNA samples of 96 CAD patients and 37 healthy controls from Indian population using Global Screening Array. ResultsThe results exhibited out of 324, only 108 SNPs were expressed, further 4 SNPs showed significant difference of minor allele frequency in cases and controls. These were rs187238 of IL-18 gene, rs731236 of VDR gene, rs11556218 of IL16 gene and rs5882 of CETP gene. Prior researches have reported association of these SNPs with various pathways like endothelial damage, susceptibility of vitamin D receptor (VDR) polymorphisms, and reduction of HDL-cholesterol levels, ultimately leading to the development of CAD. Among these, only rs731236 had been studied in Indian population and that too in diabetes and vitamin D deficiency. For the first time, these SNPs were reported to be associated with CAD in Indian population. Conclusion: This pool of 324 SNP s is a unique kind of resource that can help to uncover risk associations in CAD. Here, we validated in Indian population. Further, validation in different populations may offer valuable insights and contribute to the development of a screening tool and may help in enabling the implementation of primary prevention strategies targeted at the vulnerable population.

Keywords: coronary artery disease, single nucleotide polymorphism, susceptible SNP, bioinformatics

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Authors: Rabbia Idrees, Ananda Maiti, Saurabh Garg, Muhammad Bilal Amin

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IoT devices are the basic building blocks of IoT network that generate enormous volume of real-time and high-speed data to help organizations and companies to take intelligent decisions. To integrate this enormous data from multisource and transfer it to the appropriate client is the fundamental of IoT development. The handling of this huge quantity of devices along with the huge volume of data is very challenging. The IoT devices are battery-powered and resource-constrained and to provide energy efficient communication, these IoT devices go sleep or online/wakeup periodically and a-periodically depending on the traffic loads to reduce energy consumption. Sometime these devices get disconnected due to device battery depletion. If the node is not available in the network, then the IoT network provides incomplete, missing, and inaccurate data. Moreover, many IoT applications, like vehicle tracking and patient tracking require the IoT devices to be mobile. Due to this mobility, If the distance of the device from the sink node become greater than required, the connection is lost. Due to this disconnection other devices join the network for replacing the broken-down and left devices. This make IoT devices dynamic in nature which brings uncertainty and unreliability in the IoT network and hence produce bad quality of data. Due to this dynamic nature of IoT devices we do not know the actual reason of abnormal data. If data are of poor-quality decisions are likely to be unsound. It is highly important to process data and estimate data quality before bringing it to use in IoT applications. In the past many researchers tried to estimate data quality and provided several Machine Learning (ML), stochastic and statistical methods to perform analysis on stored data in the data processing layer, without focusing the challenges and issues arises from the dynamic nature of IoT devices and how it is impacting data quality. A comprehensive review on determining the impact of dynamic nature of IoT devices on data quality is done in this research and presented a data quality model that can deal with this challenge and produce good quality of data. This research presents the data quality model for the sensors monitoring water quality. DBSCAN clustering and weather sensors are used in this research to make data quality model for the sensors monitoring water quality. An extensive study has been done in this research on finding the relationship between the data of weather sensors and sensors monitoring water quality of the lakes and beaches. The detailed theoretical analysis has been presented in this research mentioning correlation between independent data streams of the two sets of sensors. With the help of the analysis and DBSCAN, a data quality model is prepared. This model encompasses five dimensions of data quality: outliers’ detection and removal, completeness, patterns of missing values and checks the accuracy of the data with the help of cluster’s position. At the end, the statistical analysis has been done on the clusters formed as the result of DBSCAN, and consistency is evaluated through Coefficient of Variation (CoV).

Keywords: clustering, data quality, DBSCAN, and Internet of things (IoT)

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Authors: E. Fabre, C. Vale, E. Pereira, C. M. Silva

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Introduction: Mercury is one of the most troublesome toxic metals responsible for the contamination of the aquatic systems due to its accumulation and bioamplification along the food chain. The 2030 agenda for sustainable development of United Nations promotes the improving of water quality by reducing water pollution and foments an enhance in wastewater treatment, encouraging their recycling and safe water reuse globally. Sorption processes are widely used in wastewater treatments due to their many advantages such as high efficiency and low operational costs. In these processes the target contaminant is removed from the solution by a solid sorbent. The more selective and low cost is the biosorbent the more attractive becomes the process. Agricultural wastes are especially attractive approaches for sorption. They are largely available, have no commercial value and require little or no processing. In this work, banana peels were tested for mercury removal from low concentrated solutions. In order to investigate the applicability of this solid, six water matrices were used increasing the complexity from natural waters to a real wastewater. Studies of kinetics and equilibrium were also performed using the most known models to evaluate the viability of the process In line with the concept of circular economy, this study adds value to this by-product as well as contributes to liquid waste management. Experimental: The solutions were prepared with Hg(II) initial concentration of 50 µg L-1 in natural waters, at 22 ± 1 ºC, pH 6, magnetically stirring at 650 rpm and biosorbent mass of 0.5 g L-1. NaCl was added to obtain the salt solutions, seawater was collected from the Portuguese coast and the real wastewater was kindly provided by ISQ - Instituto de Soldadura e qualidade (Welding and Quality Institute) and diluted until the same concentration of 50 µg L-1. Banana peels were previously freeze-drying, milled, sieved and the particles < 1 mm were used. Results: Banana peels removed more than 90% of Hg(II) from all the synthetic solutions studied. In these cases, the enhance in the complexity of the water type promoted a higher mercury removal. In salt waters, the biosorbent showed removals of 96%, 95% and 98 % for 3, 15 and 30 g L-1 of NaCl, respectively. The residual concentration of Hg(II) in solution achieved the level of drinking water regulation (1 µg L-1). For real matrices, the lower Hg(II) elimination (93 % for seawater and 81 % for the real wastewaters), can be explained by the competition between the Hg(II) ions and the other elements present in these solutions for the sorption sites. Regarding the equilibrium study, the experimental data are better described by the Freundlich isotherm (R ^ 2=0.991). The Elovich equation provided the best fit to the kinetic points. Conclusions: The results exhibited the great ability of the banana peels to remove mercury. The environmental realist conditions studied in this work, highlight their potential usage as biosorbents in water remediation processes.

Keywords: banana peels, mercury removal, sorption, water treatment

Procedia PDF Downloads 132

Authors: Aisha Ijaz

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The paper focuses on the impact of Muslim religiosity on convenience food purchases and involvement experienced in a non-Muslim culture. There is a scarcity of research on the purchasing patterns of Muslim diaspora communities residing in risk societies, particularly in contexts where there is an increasing inclination toward industrialized food items alongside a renewed interest in the concept of natural foods. The United Kingdom serves as an appropriate setting for this study due to the increasing Muslim population in the country, paralleled by the expanding Halal Food Market. A multi-dimensional framework is proposed, testing for five forms of involvement, specifically Purchase Decision Involvement, Product Involvement, Behavioural Involvement, Intrinsic Risk and Extrinsic Risk. Quantitative cross-sectional consumer data were collected through a face-to-face survey contact method with 141 Muslims during the summer of 2020 in Liverpool located in the Northwest of England. proportion formula was utilitsed, and the population of interest was stratified by gender and age before recruitment took place through local mosques and community centers. Six input variables were used (intrinsic religiosity and involvement dimensions), dividing the sample into 4 clusters using the Two-Step Cluster Analysis procedure in SPSS. Nuanced variances were observed in the type of involvement experienced by religiosity group, which influences behaviour when purchasing convenience food. Four distinct market segments were identified: highly religious ego-involving (39.7%), less religious active (26.2%), highly religious unaware (16.3%), less religious concerned (17.7%). These segments differ significantly with respects to their involvement, behavioural variables (place of purchase and information sources used), socio-cultural (acculturation and social class), and individual characteristics. Choosing the appropriate convenience food is centrally related to the value system of highly religious ego-involving first-generation Muslims, which explains their preference for shopping at ethnic food stores. Less religious active consumers are older and highly alert in information processing to make the optimal food choice, relying heavily on product label sources. Highly religious unaware Muslims are less dietary acculturated to the UK diet and tend to rely on digital and expert advice sources. The less-religious concerned segment, who are typified by younger age and third generation, are engaged with the purchase process because they are worried about making unsuitable food choices. Research implications are outlined and potential avenues for further explorations are identified.

Keywords: consumer behaviour, consumption, convenience food, religion, muslims, UK

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Authors: S. Toufigh Bararpour, Davood Karami, Nader Mahinpey

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Dependence of global economics on fossil fuels has led to a large growth in the emission of greenhouse gases (GHGs). Among the various GHGs, carbon dioxide is the main contributor to the greenhouse effect due to its huge emission amount. To mitigate the threatening effect of CO₂, carbon capture and sequestration (CCS) technologies have been studied widely in recent years. For the combustion processes, three main CO₂ capture techniques have been proposed such as post-combustion, pre-combustion and oxyfuel combustion. Post-combustion is the most commonly used CO₂ capture process as it can be readily retrofit into the existing power plants. Multiple advantages have been reported for the post-combustion by solid sorbents such as high CO₂ selectivity, high adsorption capacity, and low required regeneration energy. Chemical adsorption of CO₂ over alkali-metal-based solid sorbents such as K₂CO₃ is a promising method for the selective capture of diluted CO₂ from the huge amount of nitrogen existing in the flue gas. To improve the CO₂ capture performance, K₂CO₃ is supported by a stable and porous material. Al₂O₃ has been employed commonly as the support and enhanced the cyclic CO₂ capture efficiency of K₂CO₃. Different phases of alumina can be obtained by setting the calcination temperature of boehmite at 300, 600 (γ-alumina), 950 (δ-alumina) and 1200 °C (α-alumina). By increasing the calcination temperature, the regeneration capacity of alumina increases, while the surface area reduces. However, sorbents with lower surface areas have lower CO₂ capture capacity as well (except for the sorbents prepared by hydrophilic support materials). To resolve this issue, a highly efficient alumina-aerogel support was synthesized with a BET surface area of over 2000 m²/g and then calcined at a high temperature. The synthesized alumina-aerogel was impregnated on K₂CO₃ based on 50 wt% support/K₂CO₃, which resulted in the preparation of a sorbent with remarkable CO₂ capture performance. The effect of synthesis conditions such as types of alcohols, solvent-to-co-solvent ratios, and aging times was investigated on the performance of the support. The best support was synthesized using methanol as the solvent, after five days of aging time, and at a solvent-to-co-solvent (methanol-to-toluene) ratio (v/v) of 1/5. Response surface methodology was used to investigate the effect of operating parameters such as carbonation temperature and H₂O-to-CO₂ flowrate ratio on the CO₂ capture capacity. The maximum CO₂ capture capacity, at the optimum amounts of operating parameters, was 7.2 mmol CO₂ per gram K₂CO₃. Cyclic behavior of the sorbent was examined over 20 carbonation and regenerations cycles. The alumina-aerogel-supported K₂CO₃ showed a great performance compared to unsupported K₂CO₃ and γ-alumina-supported K₂CO₃. Fundamental performance analyses and long-term thermal and chemical stability test will be performed on the sorbent in the future. The applicability of the sorbent for a bench-scale process will be evaluated, and a corresponding process model will be established. The fundamental material knowledge and respective process development will be delivered to industrial partners for the design of a pilot-scale testing unit, thereby facilitating the industrial application of alumina-aerogel.

Keywords: alumina-aerogel, CO₂ capture, K₂CO₃, optimization

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Authors: Carlos Tapia Cortez, Serkan Saydam, Jeff Coulton, Claude Sammut

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Strategic mineral commodities (SMC) both energetic and metals have long been fundamental for human beings. There is a strong and long-run relation between the mineral resources industry and society's evolution, with the provision of primary raw materials, becoming one of the most significant drivers of economic growth. Due to mineral resources’ relevance for the entire economy and society, an understanding of the SMC market behaviour to simulate price fluctuations has become crucial for governments and firms. For any human activity, SMC price fluctuations are affected by economic, geopolitical, environmental, technological and psychological issues, where cognition has a major role. Cognition is defined as the capacity to store information in memory, processing and decision making for problem-solving or human adaptation. Thus, it has a significant role in those systems that exhibit dynamic equilibrium through time, such as economic growth. Cognition allows not only understanding past behaviours and trends in SCM markets but also supports future expectations of demand/supply levels and prices, although speculations are unavoidable. Technological developments may also be defined as a cognitive system. Since the Industrial Revolution, technological developments have had a significant influence on SMC production costs and prices, likewise allowing co-integration between commodities and market locations. It suggests a close relation between structural breaks, technology and prices evolution. SCM prices forecasting have been commonly addressed by econometrics and Gaussian-probabilistic models. Econometrics models may incorporate the relationship between variables; however, they are statics that leads to an incomplete approach of prices evolution through time. Gaussian-probabilistic models may evolve through time; however, price fluctuations are addressed by the assumption of random behaviour and normal distribution which seems to be far from the real behaviour of both market and prices. Random fluctuation ignores the evolution of market events and the technical and temporal relation between variables, giving the illusion of controlled future events. Normal distribution underestimates price fluctuations by using restricted ranges, curtailing decisions making into a pre-established space. A proper understanding of SMC's price dynamics taking into account the historical-cognitive relation between economic, technological and psychological factors over time is fundamental in attempting to simulate prices. The aim of this paper is to discuss the SMC market cognition hypothesis and empirically demonstrate its dynamic-cognitive capacity. Three of the largest and traded SMC's: oil, copper and gold, will be assessed to examine the economic, technological and psychological cognition respectively.

Keywords: commodity price simulation, commodity price uncertainties, dynamic-cognition, dynamic systems

Procedia PDF Downloads 435

Authors: Danny Alexander R. Moreno, Gustavo L. Sartorello, Yuli Andrea P. Bermudez, Richard R. Lobo, Ives Claudio S. Bueno, Augusto H. Gameiro

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Meat production is a significant sector for Brazil's economy; however, the agricultural segment has suffered censure regarding the negative impacts on the environment, which consequently results in climate change. Therefore, it is essential the implementation of nutritional strategies that can improve the environmental performance of livestock. This research aimed to estimate the environmental impact and profitability of the use of yerba mate extract (Ilex paraguariensis) as an additive in the feeding of feedlot lamb. Thirty-six castrated male lambs (average weight of 23.90 ± 3.67 kg and average age of 75 days) were randomly assigned to four experimental diets with different levels of inclusion of yerba mate extract (0, 1, 2, and 4 %) based on dry matter. The animals were confined for fifty-three days and fed with 60:40 corn silage to concentrate ratio. As an indicator of environmental impact, the carbon footprint (CF) was measured as kg of CO₂ equivalent (CO₂-eq) per kg of body weight produced (BWP). The greenhouse gas (GHG) emissions such as methane (CH₄) generated from enteric fermentation, were calculated using the sulfur hexafluoride gas tracer (SF₆) technique; while the CH₄, nitrous oxide (N₂O - emissions generated by feces and urine), and carbon dioxide (CO₂ - emissions generated by concentrate and silage processing) were estimated using the Intergovernmental Panel on Climate Change (IPCC) methodology. To estimate profitability, the gross margin was used, which is the total revenue minus the total cost; the latter is composed of the purchase of animals and food. The boundaries of this study considered only the lamb fattening system. The enteric CH₄ emission from the lamb was the largest source of on-farm GHG emissions (47%-50%), followed by CH₄ and N₂O emissions from manure (10%-20%) and CO₂ emission from the concentrate, silage, and fossil energy (17%-5%). The treatment that generated the least environmental impact was the group with 4% of yerba mate extract (YME), which showed a 3% reduction in total GHG emissions in relation to the control (1462.5 and 1505.5 kg CO₂-eq, respectively). However, the scenario with 1% YME showed an increase in emissions of 7% compared to the control group. In relation to CF, the treatment with 4% YME had the lowest value (4.1 kg CO₂-eq/kg LW) compared with the other groups. Nevertheless, although the 4% YME inclusion scenario showed the lowest CF, the gross margin decreased by 36% compared to the control group (0% YME), due to the cost of YME as a food additive. The results showed that the extract has the potential for use in reducing GHG. However, the cost of implementing this input as a mitigation strategy increased the production cost. Therefore, it is important to develop political strategies that help reduce the acquisition costs of input that contribute to the search for the environmental and economic benefit of the livestock sector.

Keywords: meat production, natural additives, profitability, sheep

Procedia PDF Downloads 104

Authors: Aura Alejandra Burbano Patino, Mariela Agotegaray, Veronica Lassalle, Fernanda Horst

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Water pollution is of worldwide concern due to its importance as an essential resource for life. Industrial and urbanistic growth are anthropogenic activities that have caused an increase of undesirable compounds in water. In the last decade, emerging pollutants have become of great interest since, at very low concentrations (µg/L and ng/L), they exhibit a hazardous effect on wildlife, aquatic ecosystems, and human organisms. One group of emerging pollutants that are a matter of study are pharmaceuticals. Their high consumption rate and their inappropriate disposal have led to their detection in wastewater treatment plant influent, effluent, surface water, and drinking water. In consequence, numerous technologies have been developed to efficiently treat these pollutants. Adsorption appears like an easy and cost-effective technology. One of the most used adsorbents of emerging pollutants removal is carbon-based materials such as hydrochars. This study aims to use a magnetic hydrochar nanocomposite to be employed as an adsorbent for diclofenac removal. Kinetics models and the adsorption efficiency in real water samples were analyzed. For this purpose, a magnetic hydrochar nanocomposite was synthesized through the hydrothermal carbonization (HTC) technique hybridized to co-precipitation to add the magnetic component into the hydrochar, based on iron oxide nanoparticles. The hydrochar was obtained from sunflower husk residue as the precursor. TEM, TGA, FTIR, Zeta potential as a function of pH, DLS, BET technique, and elemental analysis were employed to characterize the material in terms of composition and chemical structure. Adsorption kinetics were carried out in distilled water and real water at room temperature, pH of 5.5 for distilled water and natural pH for real water samples, 1:1 adsorbent: adsorbate dosage ratio, contact times from 10-120 minutes, and 50% dosage concentration of DCF. Results have demonstrated that magnetic hydrochar presents superparamagnetic properties with a saturation magnetization value of 55.28 emu/g. Besides, it is mesoporous with a surface area of 55.52 m²/g. It is composed of magnetite nanoparticles incorporated into the hydrochar matrix, as can be proven by TEM micrographs, FTIR spectra, and zeta potential. On the other hand, kinetic studies were carried out using DCF models, finding percent removal efficiencies up to 85.34% after 80 minutes of contact time. In addition, after 120 minutes of contact time, desorption of emerging pollutants from active sites took place, which indicated that the material got saturated after that t time. In real water samples, percent removal efficiencies decrease up to 57.39%, ascribable to a possible mechanism of competitive adsorption of organic or inorganic compounds, ions for active sites of the magnetic hydrochar. The main suggested adsorption mechanism between the magnetic hydrochar and diclofenac include hydrophobic and electrostatic interactions as well as hydrogen bonds. It can be concluded that the magnetic hydrochar nanocomposite could be valorized into a by-product which appears as an efficient adsorbent for DCF removal as a model emerging pollutant. These results are being complemented by modifying experimental variables such as pollutant’s initial concentration, adsorbent: adsorbate dosage ratio, and temperature. Currently, adsorption assays of other emerging pollutants are being been carried out.

Keywords: environmental remediation, emerging pollutants, hydrochar, magnetite nanoparticles

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Authors: S.V. Kleyn, S.Yu. Zagorodnov, А.А. Kokoulina

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Technogenic emissions of the mining and processing complex are characterized by a high content of chemical components and solid dust particles. However, each industrial enterprise and the surrounding area have features that require refinement and parameterization. Numerous studies have shown the negative impact of fine dust PM10 and PM2.5 on the health, as well as the possibility of toxic components absorption, including heavy metals by dust particles. The target of the study was the quantitative assessment of the fractional and particle size composition of ambient air dust in the area of impact by primary magnesium production complex. Also, we tried to describe the morphology features of dust particles. Study methods. To identify the dust emission sources, the analysis of the production process has been carried out. The particulate composition of the emissions was measured using laser particle analyzer Microtrac S3500 (covered range of particle size is 20 nm to 2000 km). Particle morphology and the component composition were established by electron microscopy by scanning microscope of high resolution (magnification rate - 5 to 300 000 times) with X-ray fluorescence device S3400N ‘HITACHI’. The chemical composition was identified by X-ray analysis of the samples using an X-ray diffractometer XRD-700 ‘Shimadzu’. Determination of the dust pollution level was carried out using model calculations of emissions in the atmosphere dispersion. The calculations were verified by instrumental studies. Results of the study. The results demonstrated that the dust emissions of different technical processes are heterogeneous and fractional structure is complicated. The percentage of particle sizes up to 2.5 micrometres inclusive was ranged from 0.00 to 56.70%; particle sizes less than 10 microns inclusive – 0.00 - 85.60%; particle sizes greater than 10 microns - 14.40% -100.00%. During microscopy, the presence of nanoscale size particles has been detected. Studied dust particles are round, irregular, cubic and integral shapes. The composition of the dust includes magnesium, sodium, potassium, calcium, iron, chlorine. On the base of obtained results, it was performed the model calculations of dust emissions dispersion and establishment of the areas of fine dust РМ 10 and РМ 2.5 distribution. It was found that the dust emissions of fine powder fractions PM10 and PM2.5 are dispersed over large distances and beyond the border of the industrial site of the enterprise. The population living near the enterprise is exposed to the risk of diseases associated with dust exposure. Data are transferred to the economic entity to make decisions on the measures to minimize the risks. Exposure and risks indicators on the health are used to provide named patient health and preventive care to the citizens living in the area of negative impact of the facility.

Keywords: dust emissions, еxposure assessment, PM 10, PM 2.5

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Authors: Chen Jiang, Eric Jordan, Maurice Gell, Balakrishnan Nair

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Nuclear fusion, one of the most promising options for reliably generating large amounts of carbon-free energy in the future, has seen a plethora of ground-breaking technological advances in recent years. An efficient and durable “breeding blanket”, needed to ensure a reactor’s self-sufficiency by maintaining the optimal coolant temperature as well as by minimizing radiation dosage behind the blanket, still remains a technological challenge for the various reactor designs for commercial fusion power plants. A relatively new dual-coolant lead-lithium (DCLL) breeder design has exhibited great potential for high-temperature (>700oC), high-thermal-efficiency (>40%) fusion reactor operation. However, the structural material, namely reduced activation ferritic-martensitic (RAFM) steel, is not chemically stable in contact with molten Pb-17%Li coolant. Thus, to utilize this new promising reactor design, the demand for effective corrosion-resistant coatings on RAFM steels represents a pressing need. Solution Spray Technologies LLC (SST) is developing a double-layer ceramic coating design to address the corrosion protection of RAFM steels, using a novel solution and solution/suspension plasma spray technology through a US Department of Energy-funded project. Plasma spray is a coating deposition method widely used in many energy applications. Novel derivatives of the conventional powder plasma spray process, known as the solution-precursor and solution/suspension-hybrid plasma spray process, are powerful methods to fabricate thin, dense ceramic coatings with complex compositions necessary for the corrosion protection in DCLL breeders. These processes can be used to produce ultra-fine molten splats and to allow fine adjustment of coating chemistry. Thin, dense ceramic coatings with chosen chemistry for superior chemical stability in molten Pb-Li, low activation properties, and good radiation tolerance, is ideal for corrosion-protection of RAFM steels. A key challenge is to accommodate its CTE mismatch with the RAFM substrate through the selection and incorporation of appropriate bond layers, thus allowing for enhanced coating durability and robustness. Systematic process optimization is being used to define the optimal plasma spray conditions for both the topcoat and bond-layer, and X-ray diffraction and SEM-EDS are applied to successfully validate the chemistry and phase composition of the coatings. The plasma-sprayed double-layer corrosion resistant coatings were also deposited onto simulated RAFM steel substrates, which are being tested separately under thermal cycling, high-temperature moist air oxidation as well as molten Pb-Li capsule corrosion conditions. Results from this testing on coated samples, and comparisons with bare RAFM reference samples will be presented and conclusions will be presented assessing the viability of the new ceramic coatings to be viable corrosion prevention systems for DCLL breeders in commercial nuclear fusion reactors.

Keywords: breeding blanket, corrosion protection, coating, plasma spray

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Authors: Manaranjan Pradhan, Shailaja Grover, U. Dinesh Kumar

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Farming community in India, as well as other parts of the world, is one of the highly stressed communities due to reasons such as increasing input costs (cost of seeds, fertilizers, pesticide), droughts, reduced revenue leading to farmer suicides. Lack of integrated farm advisory system in India adds to the farmers problems. Farmers need right information during the early stages of crop’s lifecycle to prevent damage and loss in revenue. In this paper, we use deep learning techniques to develop an early warning system for detection of crop diseases using images taken by farmers using their smart phone. The research work leads to building a smart assistant using analytics and big data which could help the farmers with early diagnosis of the crop diseases and corrective actions. The classical approach for crop disease management has been to identify diseases at crop level. Recently, ImageNet Classification using the convolutional neural network (CNN) has been successfully used to identify diseases at individual plant level. Our model uses convolution filters, max pooling, dense layers and dropouts (to avoid overfitting). The models are built for binary classification (healthy or not healthy) and multi class classification (identifying which disease). Transfer learning is used to modify the weights of parameters learnt through ImageNet dataset and apply them on crop diseases, which reduces number of epochs to learn. One shot learning is used to learn from very few images, while data augmentation techniques are used to improve accuracy with images taken from farms by using techniques such as rotation, zoom, shift and blurred images. Models built using combination of these techniques are more robust for deploying in the real world. Our model is validated using tomato crop. In India, tomato is affected by 10 different diseases. Our model achieves an accuracy of more than 95% in correctly classifying the diseases. The main contribution of our research is to create a personal assistant for farmers for managing plant disease, although the model was validated using tomato crop, it can be easily extended to other crops. The advancement of technology in computing and availability of large data has made possible the success of deep learning applications in computer vision, natural language processing, image recognition, etc. With these robust models and huge smartphone penetration, feasibility of implementation of these models is high resulting in timely advise to the farmers and thus increasing the farmers' income and reducing the input costs.

Keywords: analytics in agriculture, CNN, crop disease detection, data augmentation, image recognition, one shot learning, transfer learning

Procedia PDF Downloads 97

Authors: Jaeyoung Lee

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Autonomous driving systems require high reliability to provide people with a safe and comfortable driving experience. However, despite the development of a number of vehicle sensors, it is difficult to always provide high perceived performance in driving environments that vary from time to season. The image segmentation method using deep learning, which has recently evolved rapidly, provides high recognition performance in various road environments stably. However, since the system controls a vehicle in real time, a highly complex deep learning network cannot be used due to time and memory constraints. Moreover, efficient networks are optimized for GPU environments, which degrade performance in embedded processor environments equipped simple hardware accelerators. In this paper, a semantic segmentation network, matrix multiplication accelerator network (MMANet), optimized for matrix multiplication accelerator (MMA) on Texas instrument digital signal processors (TI DSP) is proposed to improve the recognition performance of autonomous driving system. The proposed method is designed to maximize the number of layers that can be performed in a limited time to provide reliable driving environment information in real time. First, the number of channels in the activation map is fixed to fit the structure of MMA. By increasing the number of parallel branches, the lack of information caused by fixing the number of channels is resolved. Second, an efficient convolution is selected depending on the size of the activation. Since MMA is a fixed, it may be more efficient for normal convolution than depthwise separable convolution depending on memory access overhead. Thus, a convolution type is decided according to output stride to increase network depth. In addition, memory access time is minimized by processing operations only in L3 cache. Lastly, reliable contexts are extracted using the extended atrous spatial pyramid pooling (ASPP). The suggested method gets stable features from an extended path by increasing the kernel size and accessing consecutive data. In addition, it consists of two ASPPs to obtain high quality contexts using the restored shape without global average pooling paths since the layer uses MMA as a simple adder. To verify the proposed method, an experiment is conducted using perfsim, a timing simulator, and the Cityscapes validation sets. The proposed network can process an image with 640 x 480 resolution for 6.67 ms, so six cameras can be used to identify the surroundings of the vehicle as 20 frame per second (FPS). In addition, it achieves 73.1% mean intersection over union (mIoU) which is the highest recognition rate among embedded networks on the Cityscapes validation set.

Keywords: edge network, embedded network, MMA, matrix multiplication accelerator, semantic segmentation network

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Authors: Christopher Thornton, Niina Kolehmainen, Kianoush Nazarpour

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Background: Accelerometers are widely used to measure physical activity behavior, including in children. The traditional method for processing acceleration data uses cut points, relying on calibration studies that relate the quantity of acceleration to energy expenditure. As these relationships do not generalise across diverse populations, they must be parametrised for each subpopulation, including different age groups, which is costly and makes studies across diverse populations difficult. A data-driven approach that allows physical activity intensity states to emerge from the data under study without relying on parameters derived from external populations offers a new perspective on this problem and potentially improved results. We evaluated the data-driven approach in a diverse population with a range of rapidly evolving physical and mental capabilities, namely very young children (9-38 months old), where this new approach may be particularly appropriate. Methods: We applied an unsupervised machine learning approach (a hidden semi-Markov model - HSMM) to segment and cluster the accelerometer data recorded from 275 children with a diverse range of physical and cognitive abilities. The HSMM was configured to identify a maximum of six physical activity intensity states and the output of the model was the time spent by each child in each of the states. For comparison, we also processed the accelerometer data using published cut points with available thresholds for the population. This provided us with time estimates for each child’s sedentary (SED), light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA). Data on the children’s physical and cognitive abilities were collected using the Paediatric Evaluation of Disability Inventory (PEDI-CAT). Results: The HSMM identified two inactive states (INS, comparable to SED), two lightly active long duration states (LAS, comparable to LPA), and two short-duration high-intensity states (HIS, comparable to MVPA). Overall, the children spent on average 237/392 minutes per day in INS/SED, 211/129 minutes per day in LAS/LPA, and 178/168 minutes in HIS/MVPA. We found that INS overlapped with 53% of SED, LAS overlapped with 37% of LPA and HIS overlapped with 60% of MVPA. We also looked at the correlation between the time spent by a child in either HIS or MVPA and their physical and cognitive abilities. We found that HIS was more strongly correlated with physical mobility (R²HIS =0.5, R²MVPA= 0.28), cognitive ability (R²HIS =0.31, R²MVPA= 0.15), and age (R²HIS =0.15, R²MVPA= 0.09), indicating increased sensitivity to key attributes associated with a child’s mobility. Conclusion: An unsupervised machine learning technique can segment and cluster accelerometer data according to the intensity of movement at a given time. It provides a potentially more sensitive, appropriate, and cost-effective approach to analysing physical activity behavior in diverse populations, compared to the current cut points approach. This, in turn, supports research that is more inclusive across diverse populations.

Keywords: physical activity, machine learning, under 5s, disability, accelerometer

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Authors: Solanki Ravirajsinh, Kudo Kuniaki, Sharma Ankit, Devi Sherine, Kuboshima Misaki, Tachi Shuntaro

Abstract:

In software development life cycles, the absence of scalable CI/CD significantly impacts organizations, leading to increased overall maintenance costs, prolonged release delivery times, heightened manual efforts, and difficulties in meeting tight deadlines. Implementing CI/CD with standard serverless technologies using cloud services overcomes all the above-mentioned issues and helps organizations improve efficiency and faster delivery without the need to manage server maintenance and capacity. By integrating scalable CI/CD with scalable automation testing, productivity, quality, and agility are enhanced while reducing the need for repetitive work and manual efforts. Implementing scalable CI/CD for development using cloud services like ECS (Container Management Service), AWS Fargate, ECR (to store Docker images with all dependencies), Serverless Computing (serverless virtual machines), Cloud Log (for monitoring errors and logs), Security Groups (for inside/outside access to the application), Docker Containerization (Docker-based images and container techniques), Jenkins (CI/CD build management tool), and code management tools (GitHub, Bitbucket, AWS CodeCommit) can efficiently handle the demands of diverse development environments and are capable of accommodating dynamic workloads, increasing efficiency for faster delivery with good quality. CI/CD pipelines encourage collaboration among development, operations, and quality assurance teams by providing a centralized platform for automated testing, deployment, and monitoring. Scalable CI/CD streamlines the development process by automatically fetching the latest code from the repository every time the process starts, building the application based on the branches, testing the application using a scalable automation testing framework, and deploying the builds. Developers can focus more on writing code and less on managing infrastructure as it scales based on the need. Serverless CI/CD eliminates the need to manage and maintain traditional CI/CD infrastructure, such as servers and build agents, reducing operational overhead and allowing teams to allocate resources more efficiently. Scalable CI/CD adjusts the application's scale according to usage, thereby alleviating concerns about scalability, maintenance costs, and resource needs. Creating scalable automation testing using cloud services (ECR, ECS Fargate, Docker, EFS, Serverless Computing) helps organizations run more than 500 test cases in parallel, aiding in the detection of race conditions, performance issues, and reducing execution time. Scalable CI/CD offers flexibility, dynamically adjusting to varying workloads and demands, allowing teams to scale resources up or down as needed. It optimizes costs by only paying for the resources as they are used and increases reliability. Scalable CI/CD pipelines employ automated testing and validation processes to detect and prevent errors early in the development cycle.

Keywords: achieve parallel execution, cloud services, scalable automation testing, scalable continuous integration and deployment

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Authors: Praniil Nagaraj

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This paper proposes a method to collect homeless data using crowdsourcing and presents an approach to analyze the data, demonstrating its potential to strengthen existing and future policies aimed at promoting socio-economic equilibrium. The 2022 Annual Homeless Assessment Report (AHAR) to Congress highlighted alarming statistics, emphasizing the need for effective decision-making and budget allocation within local planning bodies known as Continuums of Care (CoC). This paper's contributions can be categorized into three main areas. Firstly, a unique method for collecting homeless data is introduced, utilizing a user-friendly smartphone app (currently available for Android). The app enables the general public to quickly record information about homeless individuals, including the number of people and details about their living conditions. The collected data, including date, time, and location, is anonymized and securely transmitted to the cloud. It is anticipated that an increasing number of users motivated to contribute to society will adopt the app, thus expanding the data collection efforts. Duplicate data is addressed through simple classification methods, and historical data is utilized to fill in missing information. The second contribution of this paper is the description of data analysis techniques applied to the collected data. By combining this new data with existing information, statistical regression analysis is employed to gain insights into various aspects, such as distinguishing between unsheltered and sheltered homeless populations, as well as examining their correlation with factors like unemployment rates, housing affordability, and labor demand. Initial data is collected in San Francisco, while pre-existing information is drawn from three cities: San Francisco, New York City, and Washington D.C., facilitating the conduction of simulations. The third contribution focuses on demonstrating the practical implications of the data processing results. The challenges faced by key stakeholders, including charitable organizations and local city governments, are taken into consideration. Two case studies are presented as examples. The first case study explores improving the efficiency of food and necessities distribution, as well as medical assistance, driven by charitable organizations. The second case study examines the correlation between micro-geographic budget expenditure by local city governments and homeless information to justify budget allocation and expenditures. The ultimate objective of this endeavor is to enable the continuous enhancement of the quality of life for the underprivileged. It is hoped that through increased crowdsourcing of data from the public, the Generosity Curve and the Need Curve will intersect, leading to a better world for all.

Keywords: crowdsourcing, homelessness, socio-economic policies, statistical analysis

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Authors: Antonio Martín-Pardo

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With regard to the context in which this paper is inserted, it is noteworthy that the current criminal policy model in which we find immersed, denominated by some doctrine sector as the citizen security model, is characterized by a marked tendency towards the discredit of expert knowledge. This type of technic knowledge has been displaced by the common sense and by the daily experience of the people at the time of legislative drafting, as well as by excessive attention to the short-term political effects of the law. Despite this criminal-political adverse scene, we still find valuable efforts in the side of experts to bring some rationality to the legislative development. This is the case of the proposal for a new cannabis regulation model in Spain carried out by the Cannabis Policy Studies Group (hereinafter referred as ‘GEPCA’). The GEPCA is a multidisciplinary group composed by authors with multiple/different orientations, trajectories and interests, but with a common minimum objective: the conviction that the current situation regarding cannabis is unsustainable and, that a rational legislative solution must be given to the growing social pressure for the regulation of their consumption and production. This paper details the main lines through which this technical proposal is developed with the purpose of its dissemination and discussion in the Congress. The basic methodology of the proposal is inductive-expository. In that way, firstly, we will offer a brief, but solid contextualization of the situation of cannabis in Spain. This contextualization will touch on issues such as the national regulatory situation and its relationship with the international context; the criminal, judicial and penitentiary impact of the offer and consumption of cannabis, or the therapeutic use of the substance, among others. In second place, we will get down to the business properly by detailing the minutia of the three main cannabis access channels that are proposed. Namely: the regulated market, the associations of cannabis users and personal self-cultivation. In each of these options, especially in the first two, special attention will be paid to both, the production and processing of the substance and the necessary administrative control of the activity. Finally, in a third block, some notes will be given on a series of subjects that surround the different access options just mentioned above and that give fullness and coherence to the proposal outlined. Among those related issues we find some such as consumption and tenure of the substance; the issue of advertising and promotion of cannabis; consumption in areas of special risk (work or driving v. g.); the tax regime; the need to articulate evaluation instruments for the entire process; etc. The main conclusion drawn from the analysis of the proposal is the unsustainability of the current repressive system, clearly unsuccessful, and the need to develop new access routes to cannabis that guarantee both public health and the rights of people who have freely chosen to consume it.

Keywords: cannabis regulation proposal, cannabis policies studies group, criminal policy, expertise participation

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Authors: Roberto M. G. Velásquez, Jonas R. Gazoli, Nelson Ponce Jr, Valério L. Borges, Alessandro Sete, Fernanda M. C. Tomé, Julian D. Hunt, Heitor C. Lira, Cristiano L. de Souza, Fabio T. Bindemann, Wilmar Wounnsoscky

Abstract:

Nowadays, society is working toward reducing energy losses and greenhouse gas emissions, as well as seeking clean energy sources, as a result of the constant increase in energy demand and emissions. Energy loss occurs in the gas pressure reduction stations at the delivery points in natural gas distribution systems (city gates). Installing pressure reduction turbines (PRT) parallel to the static reduction valves at the city gates enhances the energy efficiency of the system by recovering the enthalpy of the pressurized natural gas, obtaining in the pressure-lowering process shaft work and generating electrical power. Currently, the Brazilian natural gas transportation network has 9,409 km in extension, while the system has 16 national and 3 international natural gas processing plants, including more than 143 delivery points to final consumers. Thus, the potential of installing PRT in Brazil is 66 MW of power, which could yearly avoid the emission of 235,800 tons of CO2 and generate 333 GWh/year of electricity. On the other hand, an economic viability analysis of these energy efficiency projects is commonly carried out based on estimates of the project's cash flow obtained from several variables forecast. Usually, the cash flow analysis is performed using representative values of these variables, obtaining a deterministic set of financial indicators associated with the project. However, in most cases, these variables cannot be predicted with sufficient accuracy, resulting in the need to consider, to a greater or lesser degree, the risk associated with the calculated financial return. This paper presents an approach applied to the technical-economic viability analysis of PRTs projects that explicitly considers the uncertainties associated with the input parameters for the financial model, such as gas pressure at the delivery point, amount of energy generated by TRP, the future price of energy, among others, using sensitivity analysis techniques, scenario analysis, and Monte Carlo methods. In the latter case, estimates of several financial risk indicators, as well as their empirical probability distributions, can be obtained. This is a methodology for the financial risk analysis of PRT projects. The results of this paper allow a more accurate assessment of the potential PRT project's financial feasibility in Brazil. This methodology will be tested at the Cuiabá thermoelectric plant, located in the state of Mato Grosso, Brazil, and can be applied to study the potential in other countries.

Keywords: pressure reduction turbine, natural gas pressure drop station, energy efficiency, electricity generation, monte carlo methods

Procedia PDF Downloads 82

Authors: Ertuğrul Ferhat Yilmaz, Ali Riza Perçin

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In the business enterprises implemented modern business enterprise principles, the most important issues are increasing the performance of workers and getting maximum income. Through the twentieth century, rapid development of the sectors of data processing and communication and because of the free trade politics arising of multilateral business enterprises have canceled the economical borders and changed the local rivalry into the spherical rivalry. In this rivalry conditions, the business enterprises have to work active and productive in order to continue their existences. The employees worked at business enterprises have formed the most important factor of product. Therefore, the business enterprises inferring the importance of the human factors in order to increase the profit have used “the performance evolution system” to increase the success and development of the employees. The evolution of the performance is aimed to increase the manpower productive by using the employees in an active way. Furthermore, this system assists the wage politics implemented in business enterprise, determining the strategically plans in business enterprises through the short and long terms, being promoted and determining the educational needs of employees, making decisions as dismissing and work rotation. It requires a great deal of effort to catch the pace of change in the working realm and to keep up ourselves up-to-date. To get the quality in people,to have an effect in workplace depends largely on the knowledge and competence of managers and prospective managers. Therefore,managers need to use the performance evaluation systems in order to base their managerial decisions on sound data. This study aims at finding whether the organizations effectively use performance evaluation systms,how much importance is put on this issue and how much the results of the evaulations have an effect on employees. Whether the organizations have the advantage of competition and can keep on their activities depend to a large extent on how they effectively and efficiently use their employees.Therefore,it is of vital importance to evaluate employees' performance and to make them better according to the results of that evaluation. The performance evaluation system which evaluates the employees according to the criteria related to that organization has become one of the most important topics for management. By means of those important ends mentioned above,performance evaluation system seems to be a tool that can be used to improve the efficiency and effectiveness of organization. Because of its contribution to organizational success, thinking performance evaluation on the axis of efficiency shows the importance of this study on a different angle. In this study, we have explained performance evaluation system ,efficiency and the relation between those two concepts. We have also analyzed the results of questionnaires conducted on the textile workers in Edirne city.We have got positive answers from the questions about the effects of performance evaluation on efficiency.After factor analysis ,the efficiency and motivation which are determined as factors of performance evaluation system have the biggest variance (%19.703) in our sample. Thus, this study shows that objective performance evaluation increases the efficiency and motivation of employees.

Keywords: performance, performance evolution system, productivity, Edirne region

Procedia PDF Downloads 280