Search results for: collaborative problem solving

Authors: Kevin W. Zobrist, Patricia A. Townsend, Nora M. Haider

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Advanced Hardwood Biofuels Northwest (AHB) is a consortium funded by the United States Department of Agriculture (USDA) to research the potential for a system to produce advanced biofuels (jet fuel, diesel, and gasoline) from hybrid poplar in the Pacific Northwest region of the U.S. An Extension team was established as part of the project to examine community readiness and willingness to adopt hybrid as a purpose-grown bioenergy crop. The Extension team surveyed key stakeholder groups, including growers, Extension professionals, policy makers, and environmental groups, to examine attitudes and concerns about growing hybrid poplar for biofuels. The surveys found broad skepticism about the viability of such a system. The top concern for most stakeholder groups was economic viability and the availability of predictable markets. Growers had additional concerns stemming from negative past experience with hybrid poplar as an unprofitable endeavor for pulp and paper production. Additional barriers identified included overall land availability and the availability of water and water rights for irrigation in dry areas of the region. Since the beginning of the project, oil and natural gas prices have plummeted due to rapid increases in domestic production. This has exacerbated the problem with economic viability by making biofuels even less competitive than fossil fuels. However, the AHB project has identified intermediate market opportunities to use poplar as a renewable source for other biochemicals produced by petroleum refineries, such as acetic acid, ethyl acetate, ethanol, and ethylene. These chemicals can be produced at a lower cost with higher yields and higher, more-stable prices. Despite these promising market opportunities, the survey results suggest that it will still be challenging to induce growers to adopt hybrid poplar. Early adopters will be needed to establish an initial feedstock supply for a budding industry. Through demonstration sites and outreach events to various stakeholder groups, the project attracted interest from wastewater treatment facilities, since these facilities are already growing hybrid poplar plantations for applying biosolids and treated wastewater for further purification, clarification, and nutrient control through hybrid poplar’s phytoremediation capabilities. Since these facilities are already using hybrid poplar, selling the wood as feedstock for a biorefinery would be an added bonus rather than something requiring a high rate of return to compete with other crops and land uses. By holding regional workshops and conferences with wastewater professionals, AHB Extension has found strong interest from wastewater treatment operators. In conclusion, there are several significant barriers to developing a successful system for producing biofuels from hybrid poplar, with the largest barrier being economic viability. However, there is potential for wastewater treatment facilities to serve as early adopters for hybrid poplar production for intermediate biochemicals and eventually biofuels.

Keywords: hybrid poplar, biofuels, biochemicals, wastewater treatment

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Authors: Grant Bifolchi

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

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

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Authors: Gabriel Malgaresi, Sara Borazjani, Hadi Madani, Pavel Bedrikovetsky

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Suspension-Colloidal flow in porous media occurs in numerous engineering fields, such as industrial water treatment, the disposal of industrial wastes into aquifers with the propagation of contaminants and low salinity water injection into petroleum reservoirs. The main effects are particle mobilization and captured by the porous rock, which can cause pore plugging and permeability reduction which is known as formation damage. Various factors such as fluid salinity, pH, temperature, and rock properties affect particle detachment. Formation damage is unfavorable specifically near injection and production wells. One way to control formation damage is pre-treatment of the rock with nanoparticles. Adsorption of nanoparticles on fines and rock surfaces alters zeta-potential of the surfaces and enhances the attachment force between the rock and fine particles. The main objective of this study is to develop a two-stage mathematical model for (1) flow and adsorption of nanoparticles on the rock in the pre-treatment stage and (2) fines migration and permeability reduction during the water production after the pre-treatment. The model accounts for adsorption and desorption of nanoparticles, fines migration, and kinetics of particle capture. The system of equations allows for the exact solution. The non-self-similar wave-interaction problem was solved by the Method of Characteristics. The analytical model is new in two ways: First, it accounts for the specific boundary and initial condition describing the injection of nanoparticle and production from the pre-treated porous media; second, it contains the effect of nanoparticle sorption hysteresis. The derived analytical model contains explicit formulae for the concentration fronts along with pressure drop. The solution is used to determine the optimal injection concentration of nanoparticle to avoid formation damage. The mathematical model was validated via an innovative laboratory program. The laboratory study includes two sets of core-flood experiments: (1) production of water without nanoparticle pre-treatment; (2) pre-treatment of a similar core with nanoparticles followed by water production. Positively-charged Alumina nanoparticles with the average particle size of 100 nm were used for the rock pre-treatment. The core was saturated with the nanoparticles and then flushed with low salinity water; pressure drop across the core and the outlet fine concentration was monitored and used for model validation. The results of the analytical modeling showed a significant reduction in the fine outlet concentration and formation damage. This observation was in great agreement with the results of core-flood data. The exact solution accurately describes fines particle breakthroughs and evaluates the positive effect of nanoparticles in formation damage. We show that the adsorbed concentration of nanoparticle highly affects the permeability of the porous media. For the laboratory case presented, the reduction of permeability after 1 PVI production in the pre-treated scenario is 50% lower than the reference case. The main outcome of this study is to provide a validated mathematical model to evaluate the effect of nanoparticles on formation damage.

Keywords: nano-particles, formation damage, permeability, fines migration

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Authors: Jiri Cecrdle

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This paper describes the concept of the W-WING whirl flutter aeroelastic demonstrator. Whirl flutter is the specific case of flutter that accounts for the additional dynamic and aerodynamic influences of the engine rotating parts. The instability is driven by motion-induced unsteady aerodynamic propeller forces and moments acting in the propeller plane. Whirl flutter instability is a serious problem that may cause the unstable vibration of a propeller mounting, leading to the failure of an engine installation or an entire wing. The complicated physical principle of whirl flutter required the experimental validation of the analytically gained results. W-WING aeroelastic demonstrator has been designed and developed at Czech Aerospace Research Centre (VZLU) Prague, Czechia. The demonstrator represents the wing and engine of the twin turboprop commuter aircraft. Contrary to the most of past demonstrators, it includes a powered motor and thrusting propeller. It allows the changes of the main structural parameters influencing the whirl flutter stability characteristics. Propeller blades are adjustable at standstill. The demonstrator is instrumented by strain gauges, accelerometers, revolution-counting impulse sensor, sensor of airflow velocity, and the thrust measurement unit. Measurement is supported by the in house program providing the data storage and real-time depiction in the time domain as well as pre-processing into the form of the power spectral densities. The engine is linked with a servo-drive unit, which enables maintaining of the propeller revolutions (constant or controlled rate ramp) and monitoring of immediate revolutions and power. Furthermore, the program manages the aerodynamic excitation of the demonstrator by the aileron flapping (constant, sweep, impulse). Finally, it provides the safety guard to prevent any structural failure of the demonstrator hardware. In addition, LMS TestLab system is used for the measurement of the structure response and for the data assessment by means of the FFT- and OMA-based methods. The demonstrator is intended for the experimental investigations in the VZLU 3m-diameter low-speed wind tunnel. The measurement variant of the model is defined by the structural parameters: pitch and yaw attachment stiffness, pitch and yaw hinge stations, balance weight station, propeller type (duralumin or steel blades), and finally, angle of attack of the propeller blade 75% section (). The excitation is provided either by the airflow turbulence or by means of the aerodynamic excitation by the aileron flapping using a frequency harmonic sweep. The experimental results are planned to be utilized for validation of analytical methods and software tools in the frame of development of the new complex multi-blade twin-rotor propulsion system for the new generation regional aircraft. Experimental campaigns will include measurements of aerodynamic derivatives and measurements of stability boundaries for various configurations of the demonstrator.

Keywords: aeroelasticity, flutter, whirl flutter, W WING demonstrator

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Authors: G. Kiran Kumar, K. Padmaja

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The rise of urban and peri-urban agriculture (UPA) is an important urban phenomenon that needs to be well understood before we pronounce a verdict whether it is beneficial or not. The challenge of supply of safe and nutritious food is faced by urban inhabitants. The definition of urban and peri-urban varies from city to city depending on the local policies framed with a view to bring regulated urban habitations as part of governance. Expansion of cities and the blurring of boundaries between urban and rural areas make it difficult to define peri-urban agriculture. The problem is further exacerbated by the fact that definition adopted in one region may not fit in the other. On the other hand the proportion of urban population is on the rise vis-à-vis rural. The rise of UPA does not promise that the food requirements of cities can be entirely met from this practice, since availability of enormous amounts of spaces on rooftops and vacant plots is impossible for raising crops. However, UPA reduces impact of price volatility, particularly for vegetables, which relatively have a longer shelf life. UPA improves access to fresh, nutritious and safe food for the urban poor. UPA provides employment to food handlers and traders in the supply chain. UPA can pose environmental and health risks from inappropriate agricultural practices; increased competition for land, water and energy; alter the ecological landscape and make it vulnerable to increased pollution. The present work is based on case studies in peri-urban agriculture in Hyderabad, India and relies on secondary data. This paper tries to analyze the need for more intensive production technologies without affecting the environment. An optimal solution in terms of urban-rural linkages has to be devised. There is a need to develop a spatial vision and integrate UPA in urban planning in a harmonious manner. Zoning of peri-urban areas for agriculture, milk and poultry production is an essential step to preserve the traditional nurturing character of these areas. Urban local bodies in conjunction with Departments of Agriculture and Horticulture can provide uplift to existing UPA models, without which the UPA can develop into a haphazard phenomenon and add to the increasing list of urban challenges. Land to be diverted for peri-urban agriculture may render the concept of urban and peri-urban forestry ineffective. This paper suggests that UPA may be practiced for high value vegetables which can be cultivated under protected conditions and are better resilient to climate change. UPA can provide models for climate resilient agriculture in urban areas which can be replicated in rural areas. Production of organic farm produce is another option for promote UPA owing to the proximity to informed consumers and access to markets within close range. Waste lands in peri-urban areas can be allotted to unemployed rural youth with the support of Urban Local Bodies (ULBs) and used for UPA. This can serve the purposes of putting wastelands to food production, enhancing employment opportunities and enhancing access to fresh produce for urban consumers.

Keywords: environment, food security, urban and peri-urban agriculture, zoning

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Authors: Breanna Wright, Peter Bragge

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Diagnostic error rates in healthcare are approximately 10% of cases. Diagnostic errors can cause patient harm due to inappropriate, inadequate or delayed treatment, and such errors contribute heavily to medical liability claims globally. Therefore, addressing diagnostic error is a high priority. In most cases, diagnostic errors are the result of faulty information synthesis rather than lack of knowledge. Specifically, the majority of diagnostic errors involve cognitive factors, and in particular, cognitive biases. Emergency Departments are an environment with heightened risk of diagnostic error due to time and resource pressures, a frequently chaotic environment, and patients arriving undifferentiated and with minimal context. This project aimed to develop a behavioural, evidence-informed intervention to reduce diagnostic error in Emergency Departments through co-design with emergency physicians, insurers, researchers, hospital managers, citizens and consumer representatives. The Forum Process was utilised to address this aim. This involves convening a small (4 – 6 member) expert panel to guide a focused literature and practice review; convening of a 10 – 12 person citizens panel to gather perspectives of laypeople, including those affected by misdiagnoses; and a 18 – 22 person structured stakeholder dialogue bringing together representatives of the aforementioned stakeholder groups. The process not only provides in-depth analysis of the problem and associated behaviours, but brings together expertise and insight to facilitate identification of a behaviour change intervention. Informed by the literature and practice review, the Citizens Panel focused on eliciting the values and concerns of those affected or potentially affected by diagnostic error. Citizens were comfortable with diagnostic uncertainty if doctors were honest with them. They also emphasised the importance of open communication between doctors and patients and their families. Citizens expect more consistent standards across the state and better access for both patients and their doctors to patient health information to avoid time-consuming re-taking of long patient histories and medication regimes when re-presenting at Emergency Departments and to reduce the risk of unintentional omissions. The structured Stakeholder Dialogue focused on identifying a feasible behavioural intervention to review diagnoses in Emergency Departments. This needed to consider the role of cognitive bias in medical decision-making; contextual factors (in Victoria, there is a legislated 4-hour maximum time between ED triage and discharge / hospital admission); resource availability; and the need to ensure the intervention could work in large metropolitan as well as small rural and regional ED settings across Victoria. The identified behavioural intervention will be piloted in approximately ten hospital EDs across Victoria, Australia. This presentation will detail the findings of all review and consultation activities, describe the behavioural intervention developed and present results of the pilot trial.

Keywords: behavioural intervention, cognitive bias, decision-making, diagnostic error

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Authors: Eduardo Martínez González, Mousumi Dey, Pekka Peljo

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Transitioning to a renewable energy model is inevitable owing to the effects of climate change. These energies are aimed at sustainability and a positive impact on the environment, but they are intermittent energies; their connection to the electrical grid depends on creating long-term, efficient, and low-cost energy storage devices. Redox flow batteries are attractive technologies to address this problem, as they store energy in solution through external tanks known as posolyte (solution to storage positive charge) and negolyte (solution to storage negative charge). During the charging process of the device, the posolyte and negolyte solutions are pumped into an electrochemical cell (which has the anode and cathode separated by an ionic membrane), where they undergo oxidation and reduction reactions at electrodes, respectively. The electrogenerated species should be stable and diffuse into the bulk solution. It has been possible to connect gigantic redox flow batteries to the electrical grid. However, the devices created do not fit with the sustainability criteria since their electroactive material consists of vanadium (material scarce and expensive) solutions dissolved in an acidic medium (e.g., 9 mol L-1 of H₂SO₄) that is highly corrosive; so, work is being done on the design of organic-electroactive electrolytes (posolytes and nogolytes) for their operation at different pH values, including neutral medium. As a main characteristic, negolyte species should have low reduction potential values, while the reverse is true for the oxidation process of posolytes. A wide variety of negolytes that store 1 and up to 2 electrons per molecule (in aqueous medium) have been publised. Gallocyanine compound was recently introduced as an electroactive material for developing alkaline flow battery negolytes. The system can storage two electrons per molecule, but its unexpectedly low water solubility was improved with an amino sulphonic acid additive. The cycling stability of and improved gallocyanine electrolyte was demonstrated by operating a flow battery cell (pairing the system to a posolyte composed of ferri/ferrocyanide solution) outside a glovebox. We also discovered that the additive improves the solubility of gallocyanine, but there is a kinetic price to pay for this advantage. Therefore, in this work, the effect of different amino sulphonic acid derivatives on the kinetics and solubility of gallocyanine compound was studied at alkaline solutions. The additive providing a faster electron transfer rate and high solubility was tested in a flow battery cell. An aqueous organic flow battery electrolyte working outside a glovebox with 15 mAhL-1 will be discussed. Acknowledgments: To Bi3BoostFlowBat Project (2021-2025), funded by the European Research Concil. For support with infrastructure, reagents, and a postdoctoral fellowship to Dr. Martínez-González.

Keywords: alkaline flow battery, gallocyanine electroactive material, amine-sulphonic acid additives, improved solubility

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Authors: Sarah Elshahat, Tina Moffat

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Suboptimal mental health is a considerable global public health challenge that leads to considerable inequalities worldwide. Newcomers are at elevated risk for developing mental health issues as a result of social exclusion, stigmatization, racism, unequal employment opportunities, and discrimination. The problem can be especially serious amongst Arabic-speaking immigrants and refugees (ASIR) whose mental wellness may have already been affected by exposure to political violence, persecution, hunger or war in their countries of origin. A scoping review was conducted to investigate pre- and post-migration mental health determinants amongst ASIR in North America (the U.S. and Canada), who are a rapidly growing population in both regions. Pertinent peer-reviewed papers and grey literature were located through a systematic search of five electronic databases (Medline, Embase, PsycINFO, Anthropology Plus, and Sociology Database). A stakeholder consultation was implemented to validate the analyzed findings of the included 44 studies. About 80% of the studies were carried out in the US, underscoring a lack of Canadian ASIR-mental health research. A gap in qualitative, mixed-method, and longitudinal research was detected, where approximately two-thirds of the studies adopted a cross-sectional method. Pre-migration determinants of mental health were related to the political unrest, violence and armed conflict in the Arab world, increasing post-traumatic stress disorder and psychological distress levels among ASIR. English language illiteracy and generational variations in acculturation patterns were major post-migration mental health triggering factors. Exposure to domestic violence, stigmatization, poverty, racialization, and harassment were significant post-migration mental health determinants that stem from social inequalities, triggering depression, and distress amongst ASIR. Family conflicts linked to child-rearing and gendered norms were considered as both pre- and post-migration mental health triggering factors. Most post-migration mental health protective factors were socio-culturally related and included the maintenance of positive ethnic identity, faith, family support, and community cohesion. Individual resilience, articulated as self-esteem and hope, was a significant negative predictor of depression and psychological distress among ASIR. Community-engaged, mixed-methods, and longitudinal studies are required to address the current gap in mental health research among ASIR in North America. A more thorough determination of potential mental health triggers and protective factors would help inform the development of mental wellness and resilience-promoting programs that are culturally sensitive to ASIR. On the policy level, the Health in All Policies framework of the World Health Organization can be potentially useful for addressing social and health inequalities among ASIR, reducing mental health challenges.

Keywords: depression, post-traumatic stress disorder, psychological distress, resilience

Procedia PDF Downloads 136

Authors: Srijata Mitra, Mobina Parveen, Pranab Roy, Narayan Chandra Chattopadhyay

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Chlorinated hydrocarbon can be a major pollution problem in groundwater as well as soil. Many people interact with these chemicals on daily accidentally or by professionally in the laboratory. One of the most common sources for Chlorinated hydrocarbon contamination of soil and groundwater are industrial effluents. The wide use and discharge of Trichloroethylene (TCE), a volatile chlorohydrocarbon from chemical industry, led to major water pollution in rural areas. TCE is an mainly used as an industrial metal degreaser in industries. Biotransformation of TCE to the potent carcinogen vinyl chloride (VC) by consortia of anaerobic bacteria might have role for the above purpose. For these reasons, the aim of current study was to isolate and characterized the genes involved in TCE metabolism and also to investigate the in silico study of those genes. To our knowledge, only one aromatic dioxygenase system, the toluene dioxygenase in Pseudomonas putida F1 has been shown to be involved in TCE degradation. This is first instance where Bacillus cereus group being used in biodegradation of trichloroethylene. A novel bacterial strain 2479 was isolated from oil depot site at Rajbandh, Durgapur (West Bengal, India) by enrichment culture technique. It was identified based on polyphasic approach and ribotyping. The bacterium was gram positive, rod shaped, endospore forming and capable of degrading trichloroethylene as the sole carbon source. On the basis of phylogenetic data and Fatty Acid Methyl Ester Analysis, strain 2479 should be placed within the genus Bacillus and species cereus. However, the present isolate (strain 2479) is unique and sharply different from the usual Bacillus strains in its biodegrading nature. Fujiwara test was done to estimate that the strain 2479 could degrade TCE efficiently. The gene for TCE biodegradation was PCR amplified from genomic DNA of Bacillus cereus 2479 by using todC1 gene specific primers. The 600bp amplicon was cloned into expression vector pUC I8 in the E. coli host XL1-Blue and expressed under the control of lac promoter and nucleotide sequence was determined. The gene sequence was deposited at NCBI under the Accession no. GU183105. In Silico approach involved predicting the physico-chemical properties of deduced Tce1 protein by using ProtParam tool. The tce1 gene contained 342 bp long ORF encoding 114 amino acids with a predicted molecular weight 12.6 kDa and the theoretical pI value of the polypeptide was 5.17, molecular formula: C559H886N152O165S8, total number of atoms: 1770, aliphatic index: 101.93, instability index: 28.60, Grand Average of Hydropathicity (GRAVY): 0.152. Three differentially expressed proteins (97.1, 40 and 30 kDa) were directly involved in TCE biodegradation, found to react immunologically to the antibodies raised against TCE inducible proteins in Western blot analysis. The present study suggested that cloned gene product (TCE1) was capable of degrading TCE as verified chemically.

Keywords: cloning, Bacillus cereus, in silico analysis, TCE

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

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

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

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Authors: Seyed Reza Aghili, Tahereh Shokohi, Shirin Sadat Hashemi Fesharaki, Mohammad Ali Boroumand, Bahar Salmanian

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Introduction: Intravenous catheter-associated fungal infection as nosocomial infection continue to be a deep problem among hospitalized patients, decreasing quality of life and adding healthcare costs. The capacity of catheters in the spread of candidemia in heart failure patients is obvious. The aim of this study was to evaluate the prevalence and genetic identification of Candida species in heart disorder patients. Material and Methods: This study was conducted in Tehran Hospital of Cardiology Center (Tehran, Iran, 2014) during 1.5 years on the patients hospitalized for at least 7 days and who had central or peripheral vein catheter. Culture of catheters, blood and skin of the location of catheter insertion were applied for detecting Candida colonies in 223 patients. Identification of Candida species was made on the basis of a combination of various phenotypic methods and confirmed by sequencing the ITS1-5.8S-ITS2 region amplified from the genomic DNA using PCR and the NCBI BLAST. Results: Of the 223 patients samples tested, we identified totally 15 Candida isolates obtained from 9 (4.04%) catheter cultures, 3 (1.35%) blood cultures and 2 (0.90%) skin cultures of the catheter insertion areas. On the base of ITS region sequencing, out of nine Candida isolates from catheter, 5(55.6%) C. albicans, 2(22.2%) C. glabrata, 1(11.1%) C. membranifiaciens and 1 (11.1%) C. tropicalis were identified. Among three Candida isolates from blood culture, C. tropicalis, C. carpophila and C. membranifiaciens were identified. Non-candida yeast isolated from one blood culture was Cryptococcus albidus. One case of C. glabrata and one case of Candida albicans were isolated from skin culture of the catheter insertion areas in patients with positive catheter culture. In these patients, ITS region of rDNA sequence showed a similarity between Candida isolated from the skin and catheter. However, the blood samples of these patients were negative for fungal growth. We report two cases of catheter-related candidemia caused by C. membranifiaciens and C. tropicalis on the base of genetic similarity of species isolated from blood and catheter which were treated successfully with intravenous fluconazole and catheter removal. In phenotypic identification methods, we could only identify C. albicans and C. tropicalis and other yeast isolates were diagnosed as Candida sp. Discussion: Although more than 200 species of Candida have been identified, only a few cause diseases in humans. There is some evidence that non-albicans infections are increasing. Many risk factors, including prior antibiotic therapy, use of a central venous catheter, surgery, and parenteral nutrition are considered to be associated with candidemia in hospitalized heart failure patients. Identifying the route of infection in candidemia is difficult. Non-albicans candida as the cause of candidemia is increasing dramatically. By using conventional method, many non-albicans isolates remain unidentified. So, using more sensitive and specific molecular genetic sequencing to clarify the aspects of epidemiology of the unknown candida species infections is essential. The positive blood and catheter cultures for candida isolates and high percentage of similarity of their ITS region of rDNA sequence in these two patients confirmed the diagnosis of intravenous catheter-associated candidemia.

Keywords: catheter-associated infections, heart failure patient, molecular genetic sequencing, ITS region of rDNA, Candidemia

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Authors: Fouzia Khanam, Belal Hossain, Kaosar Afsana, Mahfuzar Rahman

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Aim: Although cardiovascular diseases (CVD) has already been recognized as a major cause of death in developed countries, its prevalence is rising in developing countries as well, and engendering a challenge for the health sector. Bangladesh has experienced an epidemiological transition from communicable to non-communicable diseases over the last few decades. So, the rising prevalence of CVD and its risk factors are imposing a major problem for the country. We aimed to examine the prevalence of CVDs and socioeconomic and lifestyle factors related to it from a population-based survey. Methods: The data used for this study were collected as a part of a large-scale cross-sectional study conducted to explore the overall health status of children, mothers and senior citizens of Bangladesh. Multistage cluster random sampling procedure was applied by considering unions as clusters and households as the primary sampling unit to select a total of 11,428 households for the base survey. Present analysis encompassed 12338 respondents of ≥ 35 years, selected from both rural areas and urban slums of the country. Socio-economic, demographic and lifestyle information were obtained through individual by a face-to-face interview which was noted in ODK platform. And height, weight, blood pressure and glycosuria were measured using standardized methods. Chi-square test, Univariate modified Poisson regression model, and multivariate modified Poisson regression model were done using STATA software (version 13.0) for analysis. Results: Overall, the prevalence of CVD was 4.51%, of which 1.78% had stroke and 3.17% suffered from heart diseases. Male had higher prevalence of stroke (2.20%) than their counterparts (1.37%). Notably, thirty percent of respondents had high blood pressure and 5% population had diabetes and more than half of the population was pre-hypertensive. Additionally, 20% were overweight, 77% were smoker or consumed smokeless tobacco and 28% of respondents were physically inactive. Eighty-two percent of respondents took extra salt while eating and 29% of respondents had deprived sleep. Furthermore, the prevalence of risk factor of CVD varied according to gender. Women had a higher prevalence of overweight, obesity and diabetes. Women were also less physically active compared to men and took more extra salt. Smoking was lower in women compared to men. Moreover, women slept less compared to their counterpart. After adjusting confounders in modified Poisson regression model, age, gender, occupation, wealth quintile, BMI, extra salt intake, daily sleep, tiredness, diabetes, and hypertension remained as risk factors for CVD. Conclusion: The prevalence of CVD is significant in Bangladesh, and there is an evidence of rising trend for its risk factors such as hypertension, diabetes especially in older population, women and high-income groups. Therefore, in this current epidemiological transition, immediate public health intervention is warranted to address the overwhelming CVD risk.

Keywords: cardiovascular diseases, diabetes, hypertension, stroke

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Authors: Akeel A. Shah, Tong Zhang

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Computational approaches to learning the properties of materials are commonplace, motivated by the need to screen or design materials for a given application, e.g., semiconductors and energy storage. Experimental approaches can be both time consuming and costly. Unfortunately, computational approaches such as ab-initio electronic structure calculations and classical or ab-initio molecular dynamics are themselves can be too slow for the rapid evaluation of materials, often involving thousands to hundreds of thousands of candidates. Machine learning assisted approaches have been developed to overcome the time limitations of purely physics-based approaches. These approaches, on the other hand, require large volumes of data for training (hundreds of thousands on many standard data sets such as QM7b). This means that they are limited by how quickly such a large data set of physics-based simulations can be established. At high fidelity, such as configuration interaction, composite methods such as G4, and coupled cluster theory, gathering such a large data set can become infeasible, which can compromise the accuracy of the predictions - many applications require high accuracy, for example band structures and energy levels in semiconductor materials and the energetics of charge transfer in energy storage materials. In order to circumvent this problem, multi-fidelity approaches can be adopted, for example the Δ-ML method, which learns a high-fidelity output from a low-fidelity result such as Hartree-Fock or density functional theory (DFT). The general strategy is to learn a map between the low and high fidelity outputs, so that the high-fidelity output is obtained a simple sum of the physics-based low-fidelity and correction, Although this requires a low-fidelity calculation, it typically requires far fewer high-fidelity results to learn the correction map, and furthermore, the low-fidelity result, such as Hartree-Fock or semi-empirical ZINDO, is typically quick to obtain, For high-fidelity outputs the result can be an order of magnitude or more in speed up. In this work, a new multi-fidelity approach is developed, based on a graph convolutional network (GCN) combined with semi-supervised learning. The GCN allows for the material or molecule to be represented as a graph, which is known to improve accuracy, for example SchNet and MEGNET. The graph incorporates information regarding the numbers of, types and properties of atoms; the types of bonds; and bond angles. They key to the accuracy in multi-fidelity methods, however, is the incorporation of low-fidelity output to learn the high-fidelity equivalent, in this case by learning their difference. Semi-supervised learning is employed to allow for different numbers of low and high-fidelity training points, by using an additional GCN-based low-fidelity map to predict high fidelity outputs. It is shown on 4 different data sets that a significant (at least one order of magnitude) increase in accuracy is obtained, using one to two orders of magnitude fewer low and high fidelity training points. One of the data sets is developed in this work, pertaining to 1000 simulations of quinone molecules (up to 24 atoms) at 5 different levels of fidelity, furnishing the energy, dipole moment and HOMO/LUMO.

Keywords: .materials screening, computational materials, machine learning, multi-fidelity, graph convolutional network, semi-supervised learning

Procedia PDF Downloads 41

Authors: Vladimir Berezin, Aizhan Turmagambetova, Andrey Bogoyavlenskiy, Pavel Alexyuk, Madina Alexyuk, Irina Zaitceva, Nadezhda Sokolova

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Introduction: Influenza viruses could infect approximately 5% to 10% of the global human population annually, resulting in serious social and economic damage. Vaccination and etiotropic antiviral drugs are used for the prevention and treatment of influenza. Vaccination is important; however, antiviral drugs represent the second line of defense against new emerging influenza virus strains for which vaccines may be unsuccessful. However, the significant drawback of commercial synthetic anti-flu drugs is the appearance of drug-resistant influenza virus strains. Therefore, the search and development of new anti-flu drugs efficient against drug-resistant strains is an important medical problem for today. The aim of this work was a study of four phenolic acids of plant origin (Gallic, Syringic, Vanillic, and Protocatechuic acids) as a possible tool for treatment against influenza virus. Methods: Phenolic acids; gallic, syringic, vanillic, and protocatechuic have been prepared by extraction from plant tissues and purified using high-performance liquid chromatography fractionation. Avian influenza virus, strain A/Tern/South Africa/1/1961 (H5N3) and human epidemic influenza virus, strain A/Almaty/8/98 (H3N2) resistant to commercial anti-flu drugs (Rimantadine, Oseltamivir) were used for testing antiviral activity. Viruses were grown in the allantoic cavity of 10 days old chicken embryos. The chemotherapeutic index (CTI), determined as the ratio of an average toxic concentration of the tested compound (TC₅₀) to the average effective virus-inhibition concentration (EC₅₀), has been used as a criteria of specific antiviral action. Results: The results of study have shown that the structure of phenolic acids significantly affected their ability to suppress the reproduction of tested influenza virus strains. The highest antiviral activity among tested phenolic acids was detected for gallic acid, which contains three hydroxyl groups in the molecule at C3, C4, and C5 positions. Antiviral activity of gallic acid against A/H5N3 and A/H3N2 influenza virus strains was higher than antiviral activity of Oseltamivir and Rimantadine. gallic acid inhibited almost 100% of the infection activity of both tested viruses. Protocatechuic acid, which possesses 2 hydroxyl groups (C3 and C4) have shown weaker antiviral activity in comparison with gallic acid and inhibited less than 10% of virus infection activity. Syringic acid, which contains two hydroxyl groups (C3 and C5), was able to suppress up to 12% of infection activity. Substitution of two hydroxyl groups by methoxy groups resulted in the complete loss of antiviral activity. Vanillic acid, which is different from protocatechuic acid by replacing of C3 hydroxyl group to methoxy group, was able to suppress about 30% of infection activity of tested influenza viruses. Conclusion: For pronounced antiviral activity, the molecular of phenolic acid must have at least two hydroxyl groups. Replacement of hydroxyl groups to methoxy group leads to a reduction of antiviral properties. Gallic acid demonstrated high antiviral activity against influenza viruses, including Rimantadine and Oseltamivir resistant strains, and could be used as a potential candidate for the development of antiviral drug against influenza virus.

Keywords: antiviral activity, influenza virus, drug resistance, phenolic acids

Procedia PDF Downloads 141

Authors: Isabela S. Gonçalves, Vitor G. P. Lima, Tiago M. B. Campos, Marcos Jacobovitz, Luana M. R. Vasconcellos, Ivone R. Oliveira

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Periodontitis is an infectious disease of multifactorial origin, which originates from a periodontogenic bacterial biofilm that colonizes the surfaces of the teeth, resulting in an inflammatory reaction to microbial aggression. In the absence of adequate treatment, it can lead to the gradual destruction of the periodontal ligaments, cementum and alveolar bone. In guided tissue/bone regeneration therapy (GTR/GBR), a barrier membrane is placed between the fibrous tissues and the bone defect to prevent unwanted incursions of fibrous tissues into the bone defect, thus allowing the regeneration of quality bone. Currently, there are a significant number of biodegradable barrier membranes available on the market. However, a very common problem is that the membranes are not bioactive/osteogenic, that is, they are incapable of inducing a favorable osteogenic response and integration with the host tissue, resulting in many cases in displacement/expulsion of the membrane, requiring a new surgical procedure and replacement of the implant. Aiming to improve the bioactive and osteogenic properties of the membrane, this work evaluated the production of membranes that integrate the biocompatibility of the hydrophilic synthetic polymer (polyvinyl alcohol - PVA) with the osteogenic effects of chlorinated bioactive glasses (BG58S-Cl), using the electrospinning equipment (AeroSpinner L1.0 from Areka) which allows the execution of spinning by high voltage and/or blowing in solution and with a high production rate, enabling development on an industrial scale. In the formulation of bioactive glasses, the replacement of nitrates by chlorinated molecules has shown to be a promising alternative, since the chloride ion is naturally present in the body and, with its presence in the bioactive glass, the biocompatibility of the material increases. Thus, in this work, chlorinated bioactive glasses were synthesized by the sol-gel route using the compounds tetraethyl orthosilicate (TEOS), calcium chloride dihydrate and monobasic ammonium phosphate with pH adjustments with 37% HCl (1.5 or 2.5) and different calcination temperatures (500, 600 and 700 °C) were evaluated. The BG-58S-Cl powders obtained were characterized by pH, conductivity and zeta potential x time curves and by SEM/FEG, FTIR-ATR and Raman tests. The material produced under the selected conditions was evaluated in relation to the milling procedure, obtaining particles suitable for incorporation into PVA polymer solutions to be electrospun (D50 = 22 µm). Membranes were produced and evaluated regarding the influence of the crosslinking agent content as well as the crosslinking treatment temperature (3, 5 and 10 wt% citric acid) and (130 or 175 oC) and were characterized by SEM/FEG, FTIR, TG and DSC. From the optimization of the crosslinking conditions, membranes were prepared by adding BG58S-Cl powder (5 and 10 wt%) to the PVA solutions and were characterized by SEM-FEG, DSC, bioactivity in SBF and behavior in cell culture (cell viability, total protein content, alkaline phosphatase, mineralization nodules). The micrographs showed homogeneity of the distribution of BG58S-Cl particles throughout the sample, favoring cell differentiation.

Keywords: barrier membranes, chlorinated bioactive glasses, polyvinyl alcohol, tissue regeneration.

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Authors: Gyu-Dong Kim, Wuk-Jae Yoo, Sang-Youl Lee

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Composite structures offer numerous advantages over conventional structural systems in the form of higher specific stiffness and strength, lower life-cycle costs, and benefits such as easy installation and improved safety. Recently, there has been a considerable increase in the use of composites in engineering applications and as wraps for seismic upgrading and repairs. However, these composites deteriorate with time because of outdated materials, excessive use, repetitive loading, climatic conditions, manufacturing errors, and deficiencies in inspection methods. In particular, damaged fibers in a composite result in significant degradation of structural performance. In order to reduce the failure probability of composites in service, techniques to assess the condition of the composites to prevent continual growth of fiber damage are required. Condition assessment technology and nondestructive evaluation (NDE) techniques have provided various solutions for the safety of structures by means of detecting damage or defects from static or dynamic responses induced by external loading. A variety of techniques based on detecting the changes in static or dynamic behavior of isotropic structures has been developed in the last two decades. These methods, based on analytical approaches, are limited in their capabilities in dealing with complex systems, primarily because of their limitations in handling different loading and boundary conditions. Recently, investigators have introduced direct search methods based on metaheuristics techniques and artificial intelligence, such as genetic algorithms (GA), simulated annealing (SA) methods, and neural networks (NN), and have promisingly applied these methods to the field of structural identification. Among them, GAs attract our attention because they do not require a considerable amount of data in advance in dealing with complex problems and can make a global solution search possible as opposed to classical gradient-based optimization techniques. In this study, we propose an alternative damage-detection technique that can determine the degraded stiffness distribution of vibrating laminated composites made of Glass Fiber-reinforced Polymer (GFRP). The proposed method uses a modified form of the bivariate Gaussian distribution function to detect degraded stiffness characteristics. In addition, this study presents a method to detect the fiber property variation of laminated composite plates from the micromechanical point of view. The finite element model is used to study free vibrations of laminated composite plates for fiber stiffness degradation. In order to solve the inverse problem using the combined method, this study uses only first mode shapes in a structure for the measured frequency data. In particular, this study focuses on the effect of the interaction among various parameters, such as fiber angles, layup sequences, and damage distributions, on fiber-stiffness damage detection.

Keywords: stiffness detection, fiber damage, genetic algorithm, layup sequences

Procedia PDF Downloads 272

Authors: M. E. Semenov, U. Zh. Mirzakimov, A. S. Stoporev, R. S. Pavelev, M. A. Varfolomeev

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Gas hydrates are host-guest compounds. Guest molecules can be low molecular weight components of associated petroleum gas (C1-C4 hydrocarbons), carbon dioxide, hydrogen sulfide, nitrogen. Gas hydrates have a number of unique properties that make them interesting from a technological point of view, for example, for storing hydrocarbon gases in solid form under moderate thermobaric conditions. Currently, the possibility of storing and transporting hydrocarbon gases in the form of solid hydrate is being actively explored throughout the world. The hydrate form of gas has a number of advantages, including a significant gas content in the hydrate, relative safety and environmental friendliness of the process. Recently, new developments have been proposed that seek to reduce the number of steps to obtain the finished hydrate, for example, using a pressing device/screw inside the reactor. However, the energy consumption required for the hydrate formation process remains a challenge. Thus, the goal of the current work is to study the patterns and mechanisms of the hydrate formation process using small additions of hydrate formation promoters under static conditions. The study of these aspects will help solve the problem of accelerated production of gas hydrates with minimal energy consumption. New compounds have been developed at Kazan Federal University that can accelerate the formation of methane hydrate with a small amount of promoter in water, not exceeding 0.1% by weight. These promoters were synthesized based on available natural compounds and showed high efficiency in accelerating the growth of methane hydrate. To test the influence of promoters on the process of hydrate formation, standard experiments are carried out under dynamic conditions with stirring. During such experiments, the time at which hydrate formation begins (induction period), the temperature at which formation begins (supercooling), the rate of hydrate formation, and the degree of conversion of water to hydrate are assessed. This approach helps to determine the most effective compound in comparative experiments with different promoters and select their optimal concentration. These experimental studies made it possible to study the features of the formation of associated petroleum gas hydrate from promoter solutions under static conditions. Phase transformations were studied using high-pressure micro-differential scanning calorimetry under various experimental conditions. Visual studies of the growth mode of methane hydrate depending on the type of promoter were also carried out. The work is an extension of the methodology for studying the effect of promoters on the process of associated petroleum gas hydrate formation in order to identify new ways to accelerate the formation of gas hydrates without the use of mixing. This work presents the results of a study of the process of associated petroleum gas hydrate formation using high-pressure differential scanning micro-calorimetry, visual investigation, gas chromatography, autoclave study, and stability data. It was found that the synthesized compounds multiply the conversion of water into hydrate under static conditions up to 96% due to a change in the growth mechanism of associated petroleum gas hydrate. This work was carried out in the framework of the program Priority-2030.

Keywords: gas hydrate, gas storage, promotor, associated petroleum gas

Procedia PDF Downloads 70

Authors: Mohsina Aktar, Bishawjit Mallick

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Bangladesh faces the multidimensional manifestations of climate change e.g. flood, cyclone, sea level rise, drainage congestion, salinity, etc. This study aimed at to find out the community’s perception of the perceived impact of climate change on their wetland resource based livelihood, to analyze their present livelihood scenario and to find out required institutional setup to strengthen present livelihood scenario. Therefore, this study required both quantitative analysis like quantification of wetland resources, occupation, etc. and also exploratory information like policy and institutional reform. For quantitative information 200 questionnaire survey and in some cases observation survey and for socially shareable qualitative and quantitative issues case study and focus group discussion were conducted. In-Depth interview was conducted for socially non-shareable qualitative issues. The overall findings of this study have been presented maintaining a sequence- perception about climate change effect, livelihood scenario and required institutional support of the wetland community. Flood has been ranked where cyclone effect is comparatively less disastrous in this area. Heavy rainfall comes after the cyclone. Female members responded almost same about the ranking and effects of frequently occurred and devastating effects of climate change. People are much more aware of the impact of climate change. Training of Care in RVCC project helps to increase their knowledge level. If the level of education can be increased, people can fight against calamity and poverty with more confidence. People seem to overcome the problems of water logging and thus besides involving in Hydroponics (33.3%) as prime occupation in monsoon; they are also engaged in other business related activities. January to May is the low-income season for the farmers. But some people don’t want to change their traditional occupation and their age is above 45. The young earning member wants to utilize their lean income period by alternative occupation. People who do not have own land and performing water transportation or other types of occupation are now interested about Hydroponics. People who give their land on rent are now thinking about renting their land in monsoon as through that they can earn a sound amount rather than get nothing. What they require is just seed, training, and capital. Present marketing system faces the problem of communication. So this sector needed to be developed. Involvement of women in income earning activity is very low (5.1%), and 100% women are housewives. They became inferior due to their educational level and dominance of their husband. Only one NGO named BCAS (Bangladesh Center for Advanced Studies) has been found engage training facilities and advocacy for this purpose. Upazilla agricultural extension office like other GO remains inactive to give support the community for extension and improvement of Hydroponics agriculture. If the community gets proper support and inspiration, they can fight against crisis of low-income and climate change, with the Hydroponics cultivation system successfully.

Keywords: wetland community, hydroponics, climate change adaptation, livelihood

Procedia PDF Downloads 274

Authors: U. S. Putro, L. Mayangsari, M. Siallagan, N. P. Tjahyani

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National Collective Management Institute (LKMN) in Indonesia stated that legal music products were about 77.552.008 unit while illegal music products were about 22.0688.225 unit in 1996 and this number keeps getting worse every year. Consequently, Indonesia named as one of the countries with high piracy levels in 2005. This study models people decision toward unlawful behavior, music content piracy in particular, using agent-based modeling and simulation (ABMS). The classification of actors in the model constructed in this study are legal consumer, illegal consumer, and neutral consumer. The decision toward piracy among the actors is a manifestation of the social norm which attributes are social pressure, peer pressure, social approval, and perceived prevalence of piracy. The influencing attributes fluctuate depending on the majority of surrounding behavior called social network. There are two main interventions undertaken in the model, campaign and peer influence, which leads to scenarios in the simulation: positively-framed descriptive norm message, negatively-framed descriptive norm message, positively-framed injunctive norm with benefits message, and negatively-framed injunctive norm with costs message. Using NetLogo, the model is simulated in 30 runs with 10.000 iteration for each run. The initial number of agent was set 100 proportion of 95:5 for illegal consumption. The assumption of proportion is based on the data stated that 95% sales of music industry are pirated. The finding of this study is that negatively-framed descriptive norm message has a worse reversed effect toward music piracy. The study discovers that selecting the context-based campaign is the key process to reduce the level of intention toward music piracy as unlawful behavior by increasing the compliance awareness. The context of Indonesia reveals that that majority of people has actively engaged in music piracy as unlawful behavior, so that people think that this illegal act is common behavior. Therefore, providing the information about how widespread and big this problem is could make people do the illegal consumption behavior instead. The positively-framed descriptive norm message scenario works best to reduce music piracy numbers as it focuses on supporting positive behavior and subject to the right perception on this phenomenon. Music piracy is not merely economical, but rather social phenomenon due to the underlying motivation of the actors which has shifted toward community sharing. The indication of misconception of value co-creation in the context of music piracy in Indonesia is also discussed. This study contributes theoretically that understanding how social norm configures the behavior of decision-making process is essential to breakdown the phenomenon of unlawful behavior in music industry. In practice, this study proposes that reward-based and context-based strategy is the most relevant strategy for stakeholders in music industry. Furthermore, this study provides an opportunity that findings may generalize well beyond music piracy context. As an emerging body of work that systematically constructs the backstage of law and social affect decision-making process, it is interesting to see how the model is implemented in other decision-behavior related situation.

Keywords: music piracy, social norm, behavioral decision-making, agent-based model, value co-creation

Procedia PDF Downloads 187

Authors: Nataliya G. Olkhovik

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Nowadays in the system of Russian higher medical education there have been undertaken initiatives that resulted in focusing on the resources of e-learning in teaching foreign languages. Obviously, the face-to-face communication in foreign languages bears much more advantages in terms of effectiveness in comparison with the potential of e-learning. Thus, we’ve faced the necessity of strengthening the capacity of e-learning via integration of active methods into the process of teaching foreign languages, such as project activity of students. Successful project activity of students should involve the following components: monitoring, control, methods of organizing the student’s activity in foreign languages, stimulating their interest in the chosen project, approaches to self-assessment and methods of raising their self-esteem. The contemporary methodology assumes the project as a specific method, which activates potential of a student’s cognitive function, emotional reaction, ability to work in the team, commitment, skills of cooperation and, consequently, their readiness to verbalize ideas, thoughts and attitudes. Verbal activity in the foreign language is a complex conception that consolidates both cognitive (involving speech) capacity and individual traits and attitudes such as initiative, empathy, devotion, responsibility etc. Once we organize the project activity by the means of e-learning within the ‘Foreign language’ discipline we have to take into consideration all mentioned above characteristics and work out an effective way to implement it into the teaching practice to boost its educational potential. We have integrated into the e-platform Moodle the module of project activity consisting of the following blocks of tasks that lead students to research, cooperate, strive to leadership, chase the goal and finally verbalize their intentions. Firstly, we introduce the project through activating self-activity of students by the tasks of the phase ‘Preparation of the project’: choose the topic and justify it; find out the problematic situation and its components; set the goals; create your team, choose the leader, distribute the roles in your team; make a written report on grounding the validity of your choices. Secondly, in the ‘Planning the project’ phase we ask students to represent the analysis of the problem in terms of reasons, ways and methods of solution and define the structure of their project (here students may choose oral or written presentation by drawing up the claim in the e-platform about their wish, whereas the teacher decides what form of presentation to prefer). Thirdly, the students have to design the visual aids, speech samples (functional phrases, introductory words, keywords, synonyms, opposites, attributive constructions) and then after checking, discussing and correcting with a teacher via the means of Moodle present it in front of the audience. And finally, we introduce the phase of self-reflection that aims to awake the inner desire of students to improve their verbal activity in a foreign language. As a result, by implementing the project activity into the e-platform and project activity, we try to widen the frameworks of a traditional lesson of foreign languages through tapping the potential of personal traits and attitudes of students.

Keywords: active methods, e-learning, improving verbal activity in foreign languages, personal traits and attitudes

Procedia PDF Downloads 105

Authors: Nino Kupatadze, Mzevinar Bedinashvili, Tamar Memanishvili, Manana Gurielidze, David Tugushi, Ramaz Katsarava

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Bacteria easily colonize the surfaces of tissues, surgical devices (implants, orthopedics, catheters, etc.), and instruments causing surgical device related infections. Therefore, the battle against bacteria and the prevention of surgical devices from biofilm formation is one of the main challenges of biomedicine today. Our strategy to the solution of this problem consists in using antimicrobial polymeric coatings as effective “shields” to protect surfaces from bacteria’s colonization and biofilm formation. As one of the most promising approaches look be the use of antimicrobial bioerodible polymeric nanocomposites containing silver nanoparticles (AgNPs). We assume that the combination of an erodible polymer with a strong bactericide should put obstacles to bacteria to occupy the surface and to form biofilm. It has to be noted that this kind of nanocomposites are also promising as wound dressing materials to treat infected superficial wounds. Various synthetic and natural polymers were used for creating biocomposites containing AgNPs as both particles' stabilizers and matrices forming elastic films at surfaces. One of the most effective systems to fabricate AgNPs is an ethanol solution of polyvinylpyrrolidone(PVP) with dissolved AgNO3–ethanol serves as a AgNO3 reductant and PVP as AgNPs stabilizer (through the interaction of nanoparticles with nitrogen atom of the amide group). Though PVP is biocompatible and film-forming polymer, it is not a good candidate to design either "biofilm shield" or wound dressing material because of a high solubility in water – though the solubility of PVP provides the desirable release of AgNPs from the matrix, but the coating is easily washable away from the surfaces. More promising as matrices look water insoluble but bioerodible polymers that can provide the release of AgNPs and form long-lasting coatings at the surfaces. For creating bioerodible water-insoluble antimicrobial coatings containing AgNPs, we selected amino acid based biodegradable polymers(AABBPs)–poly(ester amide)s, poly(ester urea)s, their copolymers containing amide and related groups capable to stabilize AgNPs. Among a huge variety of AABBPs reported we selected the polymers soluble in ethanol. For preparing AgNPs containing nanocompositions AABBPs and AgNO3 were dissolved in ethanol and subjected to photochemical reduction using daylight-irradiation. The formation of AgNPs was observed visually by coloring the solutions in brownish-red. The obtained AgNPs were characterized by UV-spectroscopy, transmission electron microscopy(TEM), and dynamic light scattering(DLS). According to the UV and TEM data, the photochemical reduction resulted presumably in spherical AgNPs with rather high contribution of the particles below 10 nm that are known as responsible for the antimicrobial activity. DLS study showed that average size of nanoparticles formed after photo-reduction in ethanol solution ranged within 50 nm. The in vitro antimicrobial activity study of the new nanocomposite material is in progress now.

Keywords: nanocomposites, silver nanoparticles, polymer, biodegradable

Procedia PDF Downloads 396

Authors: Zuhal Eltayeb Awad

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Alryad neighborhood is located in Khartoum town– the administrative center of the Capital of Sudan. The neighborhood is one of the high-income residential areas with villa type development of low-density. It was planned and developed in 1972 with large plots (600-875m²), wide crossing roads and balanced environment. Recently the area transformed into more compact urban form of high density, mixed-use integrated development with more intensive use of land; multi-storied apartments. The most important socio-economic process in the neighborhood has been the commercialization and deinitialization of the area in connect with the displacement of the residential function. This transformation affected the quality of the neighborhood and the inter-related features of the built environment. A case study approach was chosen to gather the necessary qualitative and quantitative data. A detailed survey on existing development pattern was carried out over the whole area of Alryad. Data on the built and social environment of the neighborhoods were collected through observations, interviews and secondary data sources. The paper reflected a theoretical and empirical interest in the particular characteristics of compact neighborhood with high density, and mixed land uses and their effect on social wellbeing of the residents all in the context of the sustainable development. The research problem is focused on the challenges of transformation that associated with compact neighborhood that created multiple urban problems, e.g., stress of essential services (water supply, electricity, and drainage), congestion of streets and demand for parking. The main objective of the study is to analyze the transformation of this area from residential use to commercial and administrative use. The study analyzed the current situation of the neighborhood compared to the five principles of sustainable neighborhood prepared by UN Habitat. The study found that the neighborhood is experienced changes that occur to inner-city residential areas and the process of change of the neighborhood was originated by external forces due to the declining economic situation of the whole country. It is evident that non-residential uses have taken place uncontrolled, unregulated and haphazardly that led to damage the residential environment and deficiency in infrastructure. The quality of urban life and in particular on levels of privacy was reduced, the neighborhood changed gradually to be a central business district that provides services to the whole Khartoum town. The change of house type may be attributed to a demand-led housing market and absence of policy. The results showed that Alryad is not fully sustainable and self-contained, street network characteristics and mixed land-uses development are compatible with the principles of sustainability. The area of streets represents 27.4% of the total area of the neighborhood. Residential density is 4,620 people/ km², that is lower than the recommendations, and the limited block land-use specialization is higher than 10% of the blocks. Most inhabitants have a high income so that there is no social mix in the neighborhood. The study recommended revision of the current zoning regulations in order to control and regulate undesirable development in the neighborhood and provide new solutions which allow promoting the neighborhood sustainable development.

Keywords: compact neighborhood, land uses, mixed use, residential area, transformation

Procedia PDF Downloads 129

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

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

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

Procedia PDF Downloads 290

Authors: A. K. Tekile, I. L. Kim, J. Y. Lee

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Human activities put freshwater quality under risk, mainly due to expansion of agriculture and industries, damming, diversion and discharge of inadequately treated wastewaters. The rapid human population growth and climate change escalated the problem. External controlling actions on point and non-point pollution sources are long-term solution to manage water quality. To have a holistic approach, these mechanisms should be coupled with the in-water control strategies. The available in-lake or river methods are either costly or they have some adverse effect on the ecological system that the search for an alternative and effective solution with a reasonable balance is still going on. This study aimed at the physical and chemical water quality improvement in a stagnant Yeo-cheon River reach (Korea), which has recently shown sign of water quality problems such as scum formation and fish death. The river water quality was monitored, for the duration of three months by operating only water flow generator in the first two weeks and then ultrasonic irradiation device was coupled to the flow unit for the remaining duration of the experiment. In addition to assessing the water quality improvement, the correlation among the parameters was analyzed to explain the contribution of the ultra-sonication. Generally, the combined strategy showed localized improvement of water quality in terms of dissolved oxygen, Chlorophyll-a and dissolved reactive phosphate. At locations under limited influence of the system operation, chlorophyll-a was highly increased, but within 25 m of operation the low initial value was maintained. The inverse correlation coefficient between dissolved oxygen and chlorophyll-a decreased from 0.51 to 0.37 when ultrasonic irradiation unit was used with the flow, showing that ultrasonic treatment reduced chlorophyll-a concentration and it inhibited photosynthesis. The relationship between dissolved oxygen and reactive phosphate also indicated that influence of ultra-sonication was higher than flow on the reactive phosphate concentration. Even though flow increased turbidity by suspending sediments, ultrasonic waves canceled out the effect due to the agglomeration of suspended particles and the follow-up settling out. There has also been variation of interaction in the water column as the decrease of pH and dissolved oxygen from surface to the bottom played a role in phosphorus release into the water column. The variation of nitrogen and dissolved organic carbon concentrations showed mixed trend probably due to the complex chemical reactions subsequent to the operation. Besides, the intensive rainfall and strong wind around the end of the field trial had apparent impact on the result. The combined effect of water flow and ultrasonic irradiation was a cumulative water quality improvement and it maintained the dissolved oxygen and chlorophyll-a requirement of the river for healthy ecological interaction. However, the overall improvement of water quality is not guaranteed as effectiveness of ultrasonic technology requires long-term monitoring of water quality before, during and after treatment. Even though, the short duration of the study conducted here has limited nutrient pattern realization, the use of ultrasound at field scale to improve water quality is promising.

Keywords: stagnant, ultrasonic irradiation, water flow, water quality

Procedia PDF Downloads 193

Authors: Domagoj Nakic, Drazen Vouk, Nina Stirmer, Mario Siljeg, Ana Baricevic

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Wastewater treatment processes generate significant quantities of sewage sludge that need to be adequately treated and disposed. In many EU countries, the problem of adequate disposal of sewage sludge has not been solved, nor is determined by the unique rules, instructions or guidelines. Disposal of sewage sludge is important not only in terms of satisfying the regulations, but the aspect of choosing the optimal wastewater and sludge treatment technology. Among the solutions that seem reasonable, recycling of sewage sludge and its byproducts reaches the top recommendation. Within the framework of sustainable development, recycling of sludge almost completely closes the cycle of wastewater treatment in which only negligible amounts of waste that requires landfilling are being generated. In many EU countries, significant amounts of sewage sludge are incinerated, resulting in a new byproduct in the form of ash. Sewage sludge ash is three to five times less in volume compared to stabilized and dehydrated sludge, but it also requires further management. The combustion process also destroys hazardous organic components in the sludge and minimizes unpleasant odors. The basic objective of the presented research is to explore the possibilities of recycling of the sewage sludge ash as a supplementary cementitious material. This is because of the main oxides present in the sewage sludge ash (SiO2, Al2O3 and Cao, which is similar to cement), so it can be considered as latent hydraulic and pozzolanic material. Physical and chemical characteristics of ashes, generated by sludge collected from different wastewater treatment plants, and incinerated in laboratory conditions at different temperatures, are investigated since it is a prerequisite of its subsequent recycling and the eventual use in other industries. Research was carried out by replacing up to 20% of cement by mass in cement mortar mixes with different obtained ashes and examining characteristics of created mixes in fresh and hardened condition. The mixtures with the highest ash content (20%) showed an average drop in workability of about 15% which is attributed to the increased water requirements when ash was used. Although some mixes containing added ash showed compressive and flexural strengths equivalent to those of reference mixes, generally slight decrease in strength was observed. However, it is important to point out that the compressive strengths always remained above 85% compared to the reference mix, while flexural strengths remained above 75%. Ecological impact of innovative construction products containing sewage sludge ash was determined by analyzing leaching concentrations of heavy metals. Results demonstrate that sewage sludge ash can satisfy technical and environmental criteria for use in cementitious materials which represents a new recycling application for an increasingly important waste material that is normally landfilled. Particular emphasis is placed on linking the composition of generated ashes depending on its origin and applied treatment processes (stage of wastewater treatment, sludge treatment technology, incineration temperature) with the characteristics of the final products. Acknowledgement: This work has been fully supported by Croatian Science Foundation under the project '7927 - Reuse of sewage sludge in concrete industry – from infrastructure to innovative construction products'.

Keywords: cement mortar, recycling, sewage sludge ash, sludge disposal

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Authors: Duncan Wallace, M-Tahar Kechadi

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In recent years, Machine Learning (ML) approaches have been successfully applied to an analysis of patient symptom data in the context of disease diagnosis, at least where such data is well codified. However, much of the data present in Electronic Health Records (EHR) are unlikely to prove suitable for classic ML approaches. Furthermore, as scores of data are widely spread across both hospitals and individuals, a decentralized, computationally scalable methodology is a priority. The focus of this paper is to develop a method to predict outliers in an out-of-hours healthcare provision center (OOHC). In particular, our research is based upon the early identification of patients who have underlying conditions which will cause them to repeatedly require medical attention. OOHC act as an ad-hoc delivery of triage and treatment, where interactions occur without recourse to a full medical history of the patient in question. Medical histories, relating to patients contacting an OOHC, may reside in several distinct EHR systems in multiple hospitals or surgeries, which are unavailable to the OOHC in question. As such, although a local solution is optimal for this problem, it follows that the data under investigation is incomplete, heterogeneous, and comprised mostly of noisy textual notes compiled during routine OOHC activities. Through the use of Deep Learning methodologies, the aim of this paper is to provide the means to identify patient cases, upon initial contact, which are likely to relate to such outliers. To this end, we compare the performance of Long Short-Term Memory, Gated Recurrent Units, and combinations of both with Convolutional Neural Networks. A further aim of this paper is to elucidate the discovery of such outliers by examining the exact terms which provide a strong indication of positive and negative case entries. While free-text is the principal data extracted from EHRs for classification, EHRs also contain normalized features. Although the specific demographical features treated within our corpus are relatively limited in scope, we examine whether it is beneficial to include such features among the inputs to our neural network, or whether these features are more successfully exploited in conjunction with a different form of a classifier. In this section, we compare the performance of randomly generated regression trees and support vector machines and determine the extent to which our classification program can be improved upon by using either of these machine learning approaches in conjunction with the output of our Recurrent Neural Network application. The output of our neural network is also used to help determine the most significant lexemes present within the corpus for determining high-risk patients. By combining the confidence of our classification program in relation to lexemes within true positive and true negative cases, with an inverse document frequency of the lexemes related to these cases, we can determine what features act as the primary indicators of frequent-attender and non-frequent-attender cases, providing a human interpretable appreciation of how our program classifies cases.

Keywords: artificial neural networks, data-mining, machine learning, medical informatics

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Authors: Seyed Hossein Hosseini, Seyed Majid Hashemzadeh

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Solar energy is one of the remarkable renewable energy sources that have particular characteristics such as unlimited, no environmental pollution, and free access. Generally, solar energy can be used in thermal and photovoltaic (PV) types. The cost of installation of the PV system is very high. Additionally, due to dependence on environmental situations such as solar radiation and ambient temperature, electrical power generation of this system is unpredictable and without power electronics devices, there is no guarantee to maximum power delivery at the output of this system. Maximum power point tracking (MPPT) should be used to achieve the maximum power of a PV string. MPPT is one of the essential parts of the PV system which without this section, it would be impossible to reach the maximum amount of the PV string power and high losses are caused in the PV system. One of the noticeable challenges in the problem of MPPT is the partial shading conditions (PSC). In PSC, the output photocurrent of the PV module under the shadow is less than the PV string current. The difference between the mentioned currents passes from the module's internal parallel resistance and creates a large negative voltage across shaded modules. This significant negative voltage damages the PV module under the shadow. This condition is called hot-spot phenomenon. An anti-paralleled diode is inserted across the PV module to prevent the happening of this phenomenon. This diode is known as the bypass diode. Due to the performance of the bypass diode under PSC, the P-V curve of the PV string has several peaks. One of the P-V curve peaks that makes the maximum available power is the global peak. Model-based Global MPPT (GMPPT) methods can estimate the optimal point with higher speed than other GMPPT approaches. Centralized, modular, and interleaved DC-DC converter topologies are the significant structures that can be used for GMPPT at a PV string. there are some problems in the centralized structure such as current mismatch losses at PV sting, loss of power of the shaded modules because of bypassing by bypass diodes under PSC, needing to series connection of many PV modules to reach the desired voltage level. In the modular structure, each PV module is connected to a DC-DC converter. In this structure, by increasing the amount of demanded power from the PV string, the number of DC-DC converters that are used at the PV system will increase. As a result, the cost of the modular structure is very high. We can implement the model-based GMPPT through the multi-input interleaved boost DC-DC converter to increase the power extraction from the PV string and reduce hot-spot and current mismatch error in a PV string under different environmental condition and variable load circumstances. The interleaved boost DC-DC converter has many privileges than other mentioned structures, such as high reliability and efficiency, better regulation of DC voltage at DC link, overcome the notable errors such as module's current mismatch and hot spot phenomenon, and power switches voltage stress reduction.

Keywords: solar energy, photovoltaic systems, interleaved boost converter, maximum power point tracking, model-based method, partial shading conditions

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Authors: Carlu Van Der Westhuizen

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The South African Agricultural Sector is of major socio-economic importance to the country due to its contribution in maintaining stability in food production and food security, providing labour opportunities, eradicating poverty and earning foreign currency. Against this reality, this paper investigates within the Agricultural Sector in South Africa the changes in Land Policies that the new democratically elected government (African National Congress) brought about since their takeover in 1994. The change in the agricultural environment is decidedly dualistic, with 1) a commercial sector, and 2) a subsistence and emerging farmer sector. The future demands and challenges are mostly identified as those of land redistribution and social upliftment. Opportunities that arose from the challenge of change are, among others, the small-holder participation in the value chain, while the challenge of change in Agriculture and the opportunities that were identified could serve as a yardstick against which the Sectors’ (Agriculture) Performance could be measured in future. Unfortunately, despite all Governments’ Policies, Programmes and Projects and inputs of the Private Sector, the outcomes are, to a large extend, unsuccessful. The urgency with the Land Redistribution Programme is that, for the period 1994 – 2014, only 7.5% of the 30% aim in the redistribution of land was achieved. Another serious aspect of concern is that 90% of the Land Redistribution Projects are not in a state of productive use by emerging farmers. Several reasons may be offered for these failures, amongst others the uncoordinated way in which different stakeholders are involved in a specific farming project. These stakeholders could generally in most cases be identified as: - The Government as the policy maker; - The Private Sector that has the potential to contribute to the sustainable pre- and post-settlement stages of the Programme by cooperating the supporting services to Government; - Inputs from the communities in rural areas where the settlement takes place; - The landowners as sellers of land (e.g. a Traditional Council); and - The emerging beneficiaries as the receivers of land. Mentorship is mostly the medium with which the support are coordinated. In this paper focus will be on three scenarios of different types of mentorship (or management support) namely: - The Taung Irrigation Scheme (TIS) where multiple new land beneficiaries were established by sharing irrigation pivots and receiving mentorship support from commodity organisations within a traditional land sharing system; - Projects whereby the mentor is a strategic partner (mostly a major agricultural 'cooperative' which is also providing inputs to the farmer and responsible for purchasing/marketing all commodities produced); and - An individual mentor who is a private person focussing mainly on farm management mentorship without direct gain other than a monthly stipend paid to the mentor by Government. Against this introduction the focus of the study is investigating the process for the sustainable implementation of Governments’ Land Redistribution in South African Agriculture. To achieve this, the research paper is presented under the themes of problem statement, objectives, methodology and limitations, outline of the research process, as well as proposing possible solutions.

Keywords: land reform, role-players, failures, mentorship, management models

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Authors: Samrat Paul, Satyajit Pahari, Krishnendu Basak, Amitava Roy

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Fishing is one of the pivotal livelihood activities, especially in developing countries. Today it is considered an important occupation for human society from the era of human settlement began. In simple terms, non-target catches of any species during fishing can be considered as ‘bycatch,’ and fishing bycatch is neither a new fishery management issue nor a new problem. Sundarban is one of the world’s largest mangrove land expanding up to 10,200 sq. km in India and Bangladesh. This largest mangrove biome resource is used by the local inhabitants commercially to run their livelihood, especially by forest fringe villagers (FFVs). In Sundarban, over-fishing, especially post larvae collection of wild Penaeus monodon, is one of the major concerns, as during the collection of P. monodon, different aquatic species are destroyed as a result of bycatch mortality which changes in productivity and may negatively impact entire biodiversity, of the ecosystem. Wild prawn seed collection gear like a small mesh sized net poses a serious threat to aquatic stocks, where the collection isn’t only limited to prawn seed larvae. As prawn seed collection processes are inexpensive, require less monetary investment, and are lucrative; people are easily engaged here as their source of income. Wildlife Trust of India’s (WTI) intervention in selected forest fringe villages of Sundarban Tiger Reserve (STR) was to estimate and reduce the mortality of aquatic bycatches by involving local communities in newly developed release method and their time engagement in prawn seed collection (PSC) by involving them in Alternate Income Generation (AIG). The study was conducted for their taxonomic identification during the period of March to October 2019. Collected samples were preserved in 70% ethyl alcohol for identification, and all the preserved bycatch samples were identified morphologically by the expertise of the Zoological Survey of India (ZSI), Kolkata. Around 74 different aquatic species, where 11 different species are molluscs, 41 fish species, out of which 31 species were identified, and 22 species of crustacean collected, out of which 18 species were identified. Around 13 different species belong to a different order, and families were unable to identify them morphologically as they were collected in the juvenile stage. The study reveals that for collecting one single prawn seed, eight individual life of associated faunas are being lost. Zero bycatch mortality is not practical; rather, collectors should focus on bycatch reduction by avoiding capturing, allowing escaping, and mortality reduction, and must make changes in their fishing method by increasing net mesh size, which will avoid non-target captures. But as the prawns are small in size (generally 1-1.5 inches in length), thus increase net size making economically less or no profit for collectors if they do so. In this case, returning bycatches is considered one of the best ways to a reduction in bycatch mortality which is a more sustainable practice.

Keywords: bycatch mortality, biodiversity, mangrove biome resource, sustainable practice, Alternate Income Generation (AIG)

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Authors: Aamir Shahzad, Mao-Gang He

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Currently, dusty plasmas motivated the researchers' widespread interest. Since the last two decades, substantial efforts have been made by the scientific and technological community to investigate the transport properties and their nonlinear behavior of three-dimensional and two-dimensional nonideal complex (dusty plasma) liquids (NICDPLs). Different calculations have been made to sustain and utilize strongly coupled NICDPLs because of their remarkable scientific and industrial applications. Understanding of the thermophysical properties of complex liquids under various conditions is of practical interest in the field of science and technology. The determination of thermal conductivity is also a demanding question for thermophysical researchers, due to some reasons; very few results are offered for this significant property. Lack of information of the thermal conductivity of dense and complex liquids at different parameters related to the industrial developments is a major barrier to quantitative knowledge of the heat flux flow from one medium to another medium or surface. The exact numerical investigation of transport properties of complex liquids is a fundamental research task in the field of thermophysics, as various transport data are closely related with the setup and confirmation of equations of state. A reliable knowledge of transport data is also important for an optimized design of processes and apparatus in various engineering and science fields (thermoelectric devices), and, in particular, the provision of precise data for the parameters of heat, mass, and momentum transport is required. One of the promising computational techniques, the homogenous nonequilibrium molecular dynamics (HNEMD) simulation, is over viewed with a special importance on the application to transport problems of complex liquids. This proposed work is particularly motivated by the FIRST TIME to modify the problem of heat conduction equations leads to polynomial velocity and temperature profiles algorithm for the investigation of transport properties with their nonlinear behaviors in the NICDPLs. The aim of proposed work is to implement a NEMDS algorithm (Poiseuille flow) and to delve the understanding of thermal conductivity behaviors in Yukawa liquids. The Yukawa system is equilibrated through the Gaussian thermostat in order to maintain the constant system temperature (canonical ensemble ≡ NVT)). The output steps will be developed between 3.0×105/ωp and 1.5×105/ωp simulation time steps for the computation of λ data. The HNEMD algorithm shows that the thermal conductivity is dependent on plasma parameters and the minimum value of lmin shifts toward higher G with an increase in k, as expected. New investigations give more reliable simulated data for the plasma conductivity than earlier known simulation data and generally the plasma λ0 by 2%-20%, depending on Γ and κ. It has been shown that the obtained results at normalized force field are in satisfactory agreement with various earlier simulation results. This algorithm shows that the new technique provides more accurate results with fast convergence and small size effects over a wide range of plasma states.

Keywords: molecular dynamics simulation, thermal conductivity, nonideal complex plasma, Poiseuille flow

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