Search results for: effort estimation

Authors: Heewon Jeong, Seongpyo Kim, Joon Ha Kim

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Over the last few tens of years, the coastal regions of Korea have experienced red tide algal blooms, which are harmful and toxic to both humans and marine organisms due to their potential threat. It was accelerated owing to eutrophication by human activities, certain oceanic processes, and climate change. Previous studies have tried to monitoring and predicting the algae concentration of the ocean with the bio-optical algorithms applied to color images of the satellite. However, the accurate estimation of algal blooms remains problems to challenges because of the complexity of coastal waters. Therefore, this study suggests a new method to identify the concentration of red tide algal bloom from images of geostationary ocean color imager (GOCI) which are representing the water environment of the sea in Korea. The method employed GOCI images, which took the water leaving radiances centered at 443nm, 490nm and 660nm respectively, as well as observed weather data (i.e., humidity, temperature and atmospheric pressure) for the database to apply optical characteristics of algae and train deep learning algorithm. Convolution neural network (CNN) was used to extract the significant features from the images. And then artificial neural network (ANN) was used to estimate the concentration of algae from the extracted features. For training of the deep learning model, backpropagation learning strategy is developed. The established methods were tested and compared with the performances of GOCI data processing system (GDPS), which is based on standard image processing algorithms and optical algorithms. The model had better performance to estimate algae concentration than the GDPS which is impossible to estimate greater than 5mg/m³. Thus, deep learning model trained successfully to assess algae concentration in spite of the complexity of water environment. Furthermore, the results of this system and methodology can be used to improve the performances of remote sensing. Acknowledgement: This work was supported by the 'Climate Technology Development and Application' research project (#K07731) through a grant provided by GIST in 2017.

Keywords: deep learning, algae concentration, remote sensing, satellite

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Authors: Fikru Fentaw Abera

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Climate changes alter regional hydrologic conditions and results in a variety of impacts on water resource systems. Such hydrologic changes will affect almost every aspect of human well-being. The goal of this paper is to assess the impact of climate change on the hydrology of Upper Guder catchment located in northwest of Ethiopia. The GCM derived scenarios (HadCM3 A2a & B2a SRES emission scenarios) experiments were used for the climate projection. The statistical downscaling model (SDSM) was used to generate future possible local meteorological variables in the study area. The down-scaled data were then used as input to the soil and water assessment tool (SWAT) model to simulate the corresponding future stream flow regime in Upper Guder catchment of the Abay River Basin. A semi distributed hydrological model, SWAT was developed and Generalized Likelihood Uncertainty Estimation (GLUE) was utilized for uncertainty analysis. GLUE is linked with SWAT in the Calibration and Uncertainty Program known as SWAT-CUP. Three benchmark periods simulated for this study were 2020s, 2050s and 2080s. The time series generated by GCM of HadCM3 A2a and B2a and Statistical Downscaling Model (SDSM) indicate a significant increasing trend in maximum and minimum temperature values and a slight increasing trend in precipitation for both A2a and B2a emission scenarios in both Gedo and Tikur Inch stations for all three bench mark periods. The hydrologic impact analysis made with the downscaled temperature and precipitation time series as input to the hydrological model SWAT suggested for both A2a and B2a emission scenarios. The model output shows that there may be an annual increase in flow volume up to 35% for both emission scenarios in three benchmark periods in the future. All seasons show an increase in flow volume for both A2a and B2a emission scenarios for all time horizons. Potential evapotranspiration in the catchment also will increase annually on average 3-15% for the 2020s and 7-25% for the 2050s and 2080s for both A2a and B2a emissions scenarios.

Keywords: climate change, Guder sub-basin, GCM, SDSM, SWAT, SWAT-CUP, GLUE

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Authors: Maria Miranda-Medina, Sara Salopek, Andras Vernes, Martin Jech

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Sliding lubricated surfaces induce the formation of tribofilms that reduce friction, wear and prevent large-scale damage of contact parts. Engine oils and lubricants use antiwear and antioxidant additives such as zinc dialkyldithiophosphate (ZDDP) from where protective tribofilms are formed by degradation. The ZDDP tribofilms are described as a two-layer structure composed of inorganic polymer material. On the top surface, the long chain polyphosphate is a zinc phosphate and in the bulk, the short chain polyphosphate is a mixed Fe/Zn phosphate with a gradient concentration. The polyphosphate chains are partially adherent to steel surface through a sulfide and work as anti-wear pads. In this contribution, ZDDP tribofilms formed on gray cast iron surfaces are studied. The tribofilms were generated in a reciprocating sliding tribometer with a piston ring-cylinder liner configuration. Fully formulated oil of SAE grade 5W-30 was used as lubricant during two tests at 40Hz and 50Hz. For the estimation of the tribofilm thicknesses, spectroscopic ellipsometry was used due to its high accuracy and non-destructive nature. Ellipsometry works under an optical principle where the change in polarisation of light reflected by the surface, is associated with the refractive index of the surface material or to the thickness of the layer deposited on top. Ellipsometrical responses derived from tribofilms are modelled by effective medium approximation (EMA), which includes the refractive index of involved materials, homogeneity of the film and thickness. The materials composition was obtained from x-ray photoelectron spectroscopic studies, where the presence of ZDDP, O and C was confirmed. From EMA models it was concluded that tribofilms formed at 40 Hz are thicker and more homogeneous than the ones formed at 50 Hz. In addition, the refractive index of each material is mixed to derive an effective refractive index that describes the optical composition of the tribofilm and exhibits a maximum response in the UV range, being a characteristic of glassy semitransparent films.

Keywords: effective medium approximation, reciprocating sliding tribometer, spectroscopic ellipsometry, zinc dialkyldithiophosphate

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Authors: Sara Tokhi Arab, Rozo Noguchi, Tofeal Ahamed

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Drought is a natural disaster that occurs in a region due to a lack of precipitation and high temperatures over a continuous period or in a single season as a consequence of climate change. Precipitation deficits and prolonged high temperatures mostly affect the agricultural sector, water resources, socioeconomics, and the environment. Consequently, it causes agricultural product loss, food shortage, famines, migration, and natural resources degradation in a region. Agriculture is the first sector affected by drought. Therefore, it is important to develop an agricultural drought risk and loss assessment to mitigate the drought impact in the agriculture sector. In this context, the main purpose of this study was to assess yield loss using composite drought indices in the drought-affected vineyards. In this study, the CDI was developed for the years 2016 to 2020 by comprising five indices: the vegetation condition index (VCI), temperature condition index (TCI), deviation of NDVI from the long-term mean (NDVI DEV), normalized difference moisture index (NDMI) and precipitation condition index (PCI). Moreover, the quantitative principal component analysis (PCA) approach was used to assign a weight for each input parameter, and then the weights of all the indices were combined into one composite drought index. Finally, Bayesian regularized artificial neural networks (BRANNs) were used to evaluate the yield variation in each affected vineyard. The composite drought index result indicated the moderate to severe droughts were observed across the Kabul Province during 2016 and 2018. Moreover, the results showed that there was no vineyard in extreme drought conditions. Therefore, we only considered the severe and moderated condition. According to the BRANNs results R=0.87 and R=0.94 in severe drought conditions for the years of 2016 and 2018 and the R= 0.85 and R=0.91 in moderate drought conditions for the years of 2016 and 2018, respectively. In the Kabul Province within the two years drought periods, there was a significate deficit in the vineyards. According to the findings, 2018 had the highest rate of loss almost -7 ton/ha. However, in 2016 the loss rates were about – 1.2 ton/ha. This research will support stakeholders to identify drought affect vineyards and support farmers during severe drought.

Keywords: grapes, composite drought index, yield loss, satellite remote sensing

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Authors: Ashu Rastogi, Uttam Thakur, Jimmy Pathak, Rajesh Gupta, Anil Bhansali

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Introduction: Liraglutide is known to induce weight loss and metabolic benefits in obese individuals. However, its effect after sleeve gastrectomy are not known. Methods: People with obesity (BMI>27.5 kg/m2) underwent LSG. Subsequently, participants were randomized to receive either 0.6mg liraglutide subcutaneously daily from 6 week post to be continued till 24 week (L-L group) or placebo (L-P group). Patients were assessed before surgery (baseline) and 6 weeks, 12weeks, 18weeks and 24weeks after surgery for height, weight, waist and hip circumference, BMI, body fat percentage, HbA1c, fasting C-peptide, fasting insulin, HOMA-IR, HOMA-β, GLP-1 levels (after standard OGTT). MRI abdomen was performed prior to surgery and at 24weeks post operatively for the estimation of intrapancreatic and intrahepatic fat content. Outcome measures: Primary outcomes were changes in metabolic variables of fasting and stimulated GLP-1 levels, insulin, c-peptide, plasma glucose levels. Secondary variables were indices of insulin resistance HOMA-IR, Matsuda index; and pancreatic and hepatic steatosis. Results: Thirty-eight patients undergoing LSG were screened and 29 participants were enrolled. Two patients withdrew consent and one patient died of acute coronary event. 26 patients were randomized and data analysed. Median BMI was 40.73±3.66 and 46.25±6.51; EBW of 49.225±11.14 and 651.48±4.85 in the L-P and L-L group, respectively. Baseline FPG was 132±51.48, 125±39.68; fasting insulin 21.5±13.99, 13.15±9.20, fasting GLP-1 2.4± .37, 2.4± .32, AUC GLP-1 340.78± 44 and 332.32 ± 44.1, HOMA-IR 7.0±4.2 and 4.42±4.5 in the L-P and L-L group, respectively. EBW loss was 47± 13.20 and 65.59± 24.20 (p<0.05) in the placebo versus liraglutide group. However, we did not observe inter-group difference in metabolic parameters between the groups in spite of significant intra-group changes after 6 months of LSG. Intra-pancreatic fat prior to surgery was 3.21±1.7 and 2.2±0.9 (p=0.38) that decreased to 2.14±1.8 and 1.06±0.8 (p=0.25) at 6 months in L-P and L-L group, respectively. Similarly, intra-pancreatic fat was 1.97±0.27 and 1.88±0.36 (p=0.361) at baseline that decreased to 1.14±0.44 and 1.36±0.47 (p=0.465) at 6 months in L-P and L-L group, respectively. Conclusion: Liraglutide augments extra body weight loss after sleeve gastrectomy. A decrease in intra-pancreatic and intra-hepatic fat is noticed after bariatric surgery without additive benefit of liraglutide administration.

Keywords: sleeve gastrectomy, liraglutide, intra-pancreatic fat, insulin

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Authors: Joel Thomas, Alexa Squirini

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The key argument of this research is that every element of systems interoperability is an enabler of regional disaster resilience, and arguably should become a focal point for standardized measurement of communities’ ability to work together. Few resilience research efforts have focused on the development and application of solutions that measurably improve communities’ ability to work together at a regional level, yet a majority of the most devastating and disruptive disasters are those that have had a regional impact. The key findings of the research include a unique theoretical, mathematical, and operational approach to tangibly and defensibly measure and assess systems interoperability required to support crisis information management activities performed by governments, the private sector, and humanitarian organizations. A most effective way for communities to measurably improve regional disaster resilience is through deliberately executed disaster preparedness activities. Developing interoperable crisis information management capabilities is a crosscutting preparedness activity that greatly affects a community’s readiness and ability to work together in times of crisis. Thus, improving communities’ human and technical posture to work together in advance of a crisis, with the ultimate goal of enabling information sharing to support coordination and the careful management of available resources, is a primary means by which communities may improve regional disaster resilience. This model describes how systems interoperability can be qualitatively and quantitatively assessed when characterized as five forms of capital: governance; standard operating procedures; technology; training and exercises; and usage. The unique measurement framework presented defines the relationships between systems interoperability, information sharing and safeguarding, operational coordination, community preparedness and regional disaster resilience, and offers a means by which to implement real-world solutions and measure progress over the course of a multi-year program. The model is being developed and piloted in partnership with the U.S. Department of Homeland Security (DHS) Science and Technology Directorate (S&T) and the North Atlantic Treaty Organization (NATO) Advanced Regional Civil Emergency Coordination Pilot (ARCECP) with twenty-three organizations in Bosnia and Herzegovina, Croatia, Macedonia, and Montenegro. The intended effect of the model implementation is to enable communities to answer two key questions: 'Have we measurably improved crisis information management capabilities as a result of this effort?' and, 'As a result, are we more resilient?'

Keywords: disaster, interoperability, measurement, resilience

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Authors: Xiaobo Liu, Rakesh Mishra, Yun Zhang

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Continuous monitoring of forest canopy height with large coverage is essential for obtaining forest carbon stocks and emissions, quantifying biomass estimation, analyzing vegetation coverage, and determining biodiversity. LiDAR can be used to collect accurate woody vegetation structure such as canopy height. However, LiDAR’s coverage is usually limited because of its high cost and limited maneuverability, which constrains its use for dynamic and large area forest canopy monitoring. On the other hand, optical satellite images, like Sentinel-2, have the ability to cover large forest areas with a high repeat rate, but they do not have height information. Hence, exploring the solution of integrating LiDAR data and Sentinel-2 images to enlarge the coverage of forest canopy height prediction and increase the prediction repeat rate has been an active research topic in the environmental remote sensing community. In this study, we explore the potential of training a Random Forest Regression (RFR) model and a Convolutional Neural Network (CNN) model, respectively, to develop two predictive models for predicting and validating the forest canopy height of the Acadia Forest in New Brunswick, Canada, with a 10m ground sampling distance (GSD), for the year 2018 and 2021. Two 10m airborne LiDAR-derived canopy height models, one for 2018 and one for 2021, are used as ground truth to train and validate the RFR and CNN predictive models. To evaluate the prediction performance of the trained RFR and CNN models, two new predicted canopy height maps (CHMs), one for 2018 and one for 2021, are generated using the trained RFR and CNN models and 10m Sentinel-2 images of 2018 and 2021, respectively. The two 10m predicted CHMs from Sentinel-2 images are then compared with the two 10m airborne LiDAR-derived canopy height models for accuracy assessment. The validation results show that the mean absolute error (MAE) for year 2018 of the RFR model is 2.93m, CNN model is 1.71m; while the MAE for year 2021 of the RFR model is 3.35m, and the CNN model is 3.78m. These demonstrate the feasibility of using the RFR and CNN models developed in this research for predicting large-coverage forest canopy height at 10m spatial resolution and a high revisit rate.

Keywords: remote sensing, forest canopy height, LiDAR, Sentinel-2, artificial intelligence, random forest regression, convolutional neural network

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Authors: Esther Yin-Nei Cho

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There is inconsistency among studies about whether there is an association between poverty and the subjective wellbeing of children. Some have found a positive association, though its magnitude could be limited, others have shown no association. One possible explanation for this inconsistency is that household income, an often-adopted measure of child poverty, may not accurately and stably reflect the actual life experience of children. Some studies have suggested, however, that material deprivation covering various dimensions of children’s lives could be a better measure of child poverty. Another possible explanation for the inconsistency is that the link between poverty and subjective wellbeing of children may not be that straightforward, as there could be underlying mechanisms, such as mediation and moderation, influencing its direction or strength. While a mediator refers to the mechanism through which an independent variable affects a dependent variable, a moderator changes the direction or strength of the relationship between an independent variable and a dependent variable. As suggested by empirical evidence, family relationships and friendships could be potential mediators or moderators of the link between poverty and subjective well-being: poverty affects relationships; relationships are an important element in children’s subjective well-being; and economic status affects child outcomes, though not necessarily subjective wellbeing, through relationships. Since the potential links have not been adequately understood, this study fills this gap by examining the possible role of family relationships and friendships as mediators or moderators between poverty (using child-derived material deprivation as measure) and the subjective wellbeing of children. Improving subjective wellbeing is increasingly considered as a policy goal. The finding of no or a limited association between poverty and subjective wellbeing of children could be a justification for less effort to improve poverty in this regard. But if the observed magnitude of that association is due to some underlying mechanisms at work, the effect of poverty may be underestimated and the potentially useful strategies that take into account both poverty and other mediators or moderators for improving children’s subjective well-being may be overlooked. Multiple mediation, and multiple moderation models, based on regression analyses, are performed to a sample of approximately 1,600 children, who are aged 10 to 15, from the wellbeing survey conducted by The Children’s Society in England from 2010 to 2011. Results show that the effect of children’s material deprivation on their subjective well-being is mediated by their family relationships and friendships. Moreover, family relationships are a significant moderator. It is found that the negative impact of child deprivation on subjective wellbeing could be exacerbated if family relationships are not going well, while good family relationships may prevent the further decline in subjective well-being. Policy implications of the findings are discussed. In particular, policy measures that focus on strengthening the family relationships or nurturing home environment through supporting household’s economic security and parental time with children could promote the subjective wellbeing of children.

Keywords: child poverty, mediation, moderation, subjective well-being of children

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Authors: Woldegerima G. Medhin, Tadele Araya

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Background: Rabies is acute viral encephalitis affecting mainly carnivores and insectivorous but can affect any mammal. Case fatality rate is 100% once clinical signs appear. Rabies has a worldwide distribution in continental regions of Asia and Africa. Globally, rabies is responsible for more than 61000 human deaths annually. An estimation of human mortality rabies in Asia and Africa annually exceed 35172 and 21476 respectively. Ethiopia approximately 2900 people were estimated to die of rabies annually, Tigary region approximately 98 people were estimated to die annually. The aim of this study is to analyze trends, describe, and evaluate the ten years rabies data in Tigray, Ethiopia. Methods: We conducted descriptive epidemiological study from 15-30 February, 2023 of rabies exposure and death in humans by reviewing the health management information system report from Tigray Regional Health Bureau and vaccination coverage of dog population from 2013 to 2022. We used case definition, suspected cases are those bitten by the dogs displaying clinical signs consistent with rabies and confirmed cases were deaths from rabies at time of the exposure. Results: A total 21031 dog bites and 375 deaths report of rabies and 18222 post exposure treatments for humans in Tigray region were used. A suspected rabies patients had shown an increasing trend from 2013 to 2015 and 2018 to 2019. Overall mortality rate was 19/1000 in Tigray. Majority of suspected patients (45%) were age <15 years old. An estimated by Agriculture Bureau of Tigray Region about 12000 owned and 2500 stray dogs are available in the region, but yearly dog vaccination remains low (50%). Conclusion: Rabies is a public health problem in Tigray region. It is highly recommended to vaccinate individually owned dogs and concerned sectors should eliminate stray dogs. Surveillance system should strengthen for estimating the real magnitude, launch preventive and control measures.

Keywords: rabies, Virus, transmision, prevalence

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Authors: G. Amariei, K. Boltes, R. Rosal, P. Leton

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Wastewater treatment plants (WWTPs) are supposed to hold an important place in the reduction of emerging contaminants, but provide an environment that has potential for the development and/or spread of adaptation, as bacteria are continuously mixed with contaminants at sub-inhibitory concentrations. Reviewing the literature, there are little data available regarding the use of adapted bacteria forming activated sludge community for toxicity assessment, and only individual validations have been performed. Therefore, the aim of this work was to study the toxicity of Triclosan (TCS) and Ibuprofen (IBU), individually and in binary combination, on adapted activated sludge (AS). For this purpose a battery of biomarkers were assessed, involving oxidative stress and cytotoxicity responses: glutation-S-transferase (GST), catalase (CAT) and viable cells with FDA. In addition, we compared the toxic effects on adapted bacteria with unadapted bacteria, from a previous research. Adapted AS comes from three continuous-flow AS laboratory systems; two systems received IBU and TCS, individually; while the other received the binary combination, for 14 days. After adaptation, each bacterial culture condition was exposure to IBU, TCS and the combination, at 12 h. The concentration of IBU and TCS ranged 0.5-4mg/L and 0.012-0.1 mg/L, respectively. Batch toxicity experiments were performed using Oxygraph system (Hansatech), for determining the activity of CAT enzyme based on the quantification of oxygen production rate. Fluorimetric technique was applied as well, using a Fluoroskan Ascent Fl (Thermo) for determining the activity of GST enzyme, using monochlorobimane-GSH as substrate, and to the estimation of viable cell of the sludge, by fluorescence staining using Fluorescein Diacetate (FDA). For IBU adapted sludge, CAT activity it was increased at low concentration of IBU, TCS and mixture. However, increasing the concentration the behavior was different: while IBU tends to stabilize the CAT activity, TCS and the mixture decreased this one. GST activity was significantly increased by TCS and mixture. For IBU, no variations it was observed. For TCS adapted sludge, no significant variations on CAT activity it was observed. GST activity it was significant decreased for all contaminants. For mixture adapted sludge the behaviour of CAT activity it was similar to IBU adapted sludge. GST activity it was decreased at all concentration of IBU. While the presence of TCS and mixture, respectively, increased the GST activity. These findings were consistent with the viability cells evaluation, which clearly showed a variation of sludge viability. Our results suggest that, compared with unadapted bacteria, the adapted bacteria conditions plays a relevant role in the toxicity behaviour towards activated sludge communities.

Keywords: adapted sludge community, mixture, PPCPs, toxicity

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Authors: Dávid Kovács, Bálint Csanády, Dániel Boros, Iván Ivkovic, Lóránt Nagy, Dalma Tóth-Lakits, László Márkus, András Lukács

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The modeling practice of financial instruments has seen significant change over the last decade due to the recognition of time-dependent and stochastically changing correlations among the market prices or the prices and market characteristics. To represent this phenomenon, the Stochastic Correlation Process (SCP) has come to the fore in the joint modeling of prices, offering a more nuanced description of their interdependence. This approach has allowed for the attainment of realistic tail dependencies, highlighting that prices tend to synchronize more during intense or volatile trading periods, resulting in stronger correlations. Evidence in statistical literature suggests that, similarly to the volatility, the SCP of certain stock prices follows rough paths, which can be described using fractional differential equations. However, estimating parameters for these equations often involves complex and computation-intensive algorithms, creating a necessity for alternative solutions. In this regard, the Fractional Ornstein-Uhlenbeck (fOU) process from the family of fractional processes offers a promising path. We can effectively describe the rough SCP by utilizing certain transformations of the fOU. We employed neural networks to understand the behavior of these processes. We had to develop a fast algorithm to generate a valid and suitably large sample from the appropriate process to train the network. With an extensive training set, the neural network can estimate the process parameters accurately and efficiently. Although the initial focus was the fOU, the resulting model displayed broader applicability, thus paving the way for further investigation of other processes in the realm of financial mathematics. The utility of SCP extends beyond its immediate application. It also serves as a springboard for a deeper exploration of fractional processes and for extending existing models that use ordinary Wiener processes to fractional scenarios. In essence, deploying both SCP and fractional processes in financial models provides new, more accurate ways to depict market dynamics.

Keywords: fractional Ornstein-Uhlenbeck process, fractional stochastic processes, Heston model, neural networks, stochastic correlation, stochastic differential equations, stochastic volatility

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Authors: Sultan Ahmad Azizi, Gaurang J. Joshi

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Urban transportation has come to lime light in recent times due to deteriorating travel quality. The economic growth of India has boosted significant rise in private vehicle ownership in cities, whereas public transport systems have largely been ignored in metropolitan cities. Even though there is latent demand for public transport systems like organized bus services, most of the metropolitan cities have unsustainably low share of public transport. Unfortunately, Indian metropolitan cities have failed to maintain balance in mode share of various travel modes in absence of timely introduction of mass transit system of required capacity and quality. As a result, personalized travel modes like two wheelers have become principal modes of travel, which cause significant environmental, safety and health hazard to the citizens. Of late, the policy makers have realized the need to improve public transport system in metro cities for sustaining the development. However, the challenge to the transit planning authorities is to design a transit system for cities that may attract people to switch over from their existing and rather convenient mode of travel to the transit system under the influence of household socio-economic characteristics and the given travel pattern. In this context, the fast-growing industrial city of Surat is taken up as a case for the study of likely shift to bus transit. Deterioration of public transport system of bus after 1998, has led to tremendous growth in two-wheeler traffic on city roads. The inadequate and poor service quality of present bus transit has failed to attract the riders and correct the mode use balance in the city. The disaggregate travel behavior for trip generations and the travel mode choice has been studied for the West Adajan residential sector of city. Mode specific utility functions are calibrated under multi-nominal logit environment for two-wheeler, cars and auto rickshaws with respect to bus transit using SPSS. Estimation of shift to bus transit is carried indicate an average 30% of auto rickshaw users and nearly 5% of 2W users are likely to shift to bus transit if service quality is improved. However, car users are not expected to shift to bus transit system.

Keywords: bus transit, disaggregate travel nehavior, mode choice Behavior, public transport

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Authors: Pesaru Vigneshwar Reddy, Parvathaneni Pavan

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Green organic chemistry which is the latest and one of the most researched topics now-a- days has been in demand since 1990’s. Majority of the research in green organic chemistry chemicals are some of the important starting materials for greater number of major chemical industries. The production of organic chemicals has raw materials (or) reagents for other application is major sector of manufacturing polymers, pharmaceuticals, pesticides, paints, artificial fibers, food additives etc. organic synthesis on a large scale compound to the labratory scale, involves the use of energy, basic chemical ingredients from the petro chemical sectors, catalyst and after the end of the reaction, seperation, purification, storage, packing distribution etc. During these processes there are many problems of health and safety for workers in addition to the environmental problems caused there by use and deposition as waste. Green chemistry with its 12 principles would like to see changes in conventional way that were used for decades to make synthetic organic chemical and the use of less toxic starting materials. Green chemistry would like to increase the efficiency of synthetic methods, to use less toxic solvents, reduce the stage of synthetic routes and minimize waste as far as practically possible. In this way, organic synthesis will be part of the effort for sustainable development Green chemistry is also interested for research and alternatives innovations on many practical aspects of organic synthesis in the university and research labaratory of institutions. By changing the methodologies of organic synthesis, health and safety will be advanced in the small scale laboratory level but also will be extended to the industrial large scale production a process through new techniques. The three key developments in green chemistry include the use of super critical carbondioxide as green solvent, aqueous hydrogen peroxide as an oxidising agent and use of hydrogen in asymmetric synthesis. It also focuses on replacing traditional methods of heating with that of modern methods of heating like microwaves traditions, so that carbon foot print should reduces as far as possible. Another beneficiary of this green chemistry is that it will reduce environmental pollution through the use of less toxic reagents, minimizing of waste and more bio-degradable biproducts. In this present paper some of the basic principles, approaches, and early achievements of green chemistry has a branch of chemistry that studies the laws of passing of chemical reactions is also considered, with the summarization of green chemistry principles. A discussion about E-factor, old and new synthesis of ibuprofen, microwave techniques, and some of the recent advancements also considered.

Keywords: energy, e-factor, carbon foot print, micro-wave, sono-chemistry, advancement

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Authors: Fazıl Gökgöz, Fahrettin Filiz

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Load forecasting has become crucial in recent years and become popular in forecasting area. Many different power forecasting models have been tried out for this purpose. Electricity load forecasting is necessary for energy policies, healthy and reliable grid systems. Effective power forecasting of renewable energy load leads the decision makers to minimize the costs of electric utilities and power plants. Forecasting tools are required that can be used to predict how much renewable energy can be utilized. The purpose of this study is to explore the effectiveness of LSTM-based neural networks for estimating renewable energy loads. In this study, we present models for predicting renewable energy loads based on deep neural networks, especially the Long Term Memory (LSTM) algorithms. Deep learning allows multiple layers of models to learn representation of data. LSTM algorithms are able to store information for long periods of time. Deep learning models have recently been used to forecast the renewable energy sources such as predicting wind and solar energy power. Historical load and weather information represent the most important variables for the inputs within the power forecasting models. The dataset contained power consumption measurements are gathered between January 2016 and December 2017 with one-hour resolution. Models use publicly available data from the Turkish Renewable Energy Resources Support Mechanism. Forecasting studies have been carried out with these data via deep neural networks approach including LSTM technique for Turkish electricity markets. 432 different models are created by changing layers cell count and dropout. The adaptive moment estimation (ADAM) algorithm is used for training as a gradient-based optimizer instead of SGD (stochastic gradient). ADAM performed better than SGD in terms of faster convergence and lower error rates. Models performance is compared according to MAE (Mean Absolute Error) and MSE (Mean Squared Error). Best five MAE results out of 432 tested models are 0.66, 0.74, 0.85 and 1.09. The forecasting performance of the proposed LSTM models gives successful results compared to literature searches.

Keywords: deep learning, long short term memory, energy, renewable energy load forecasting

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Authors: Eva L. Suarez, Daniel E. Meeroff, Yan Yong

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Current flooding risk modeling focuses on resilience, defined as the probability of recovery from a severe flooding event. However, the long-term damage to property and well-being by nuisance flooding and its long-term effects on communities are not typically included in risk assessments. An approach was developed to address the probability of recovering from a severe flooding event combined with the probability of community performance during a nuisance event. A consolidated model, namely the conflation flooding recovery (&FR) model, evaluates risk-coping mitigation strategies for communities based on the recovery time from catastrophic events, such as hurricanes or extreme surges, and from everyday nuisance flooding events. The &FR model assesses the variation contribution of each independent input and generates a weighted output that favors the distribution with minimum variation. This approach is especially useful if the input distributions have dissimilar variances. The &FR is defined as a single distribution resulting from the product of the individual probability density functions. The resulting conflated distribution resides between the parent distributions, and it infers the recovery time required by a community to return to basic functions, such as power, utilities, transportation, and civil order, after a flooding event. The &FR model is more accurate than averaging individual observations before calculating the mean and variance or averaging the probabilities evaluated at the input values, which assigns the same weighted variation to each input distribution. The main disadvantage of these traditional methods is that the resulting measure of central tendency is exactly equal to the average of the input distribution’s means without the additional information provided by each individual distribution variance. When dealing with exponential distributions, such as resilience from severe flooding events and from nuisance flooding events, conflation results are equivalent to the weighted least squares method or best linear unbiased estimation. The combination of severe flooding risk with nuisance flooding improves flood risk management for highly populated coastal communities, such as in South Florida, USA, and provides a method to estimate community flood recovery time more accurately from two different sources, severe flooding events and nuisance flooding events.

Keywords: community resilience, conflation, flood risk, nuisance flooding

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Authors: Kyomin Lee, Joohee Kim, Sangho Kang

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The commercial nuclear power reactor in South Korea, Kori Unit 1, which was a 587 MWe pressurized water reactor that started operation since 1978, was permanently shut down in June 2017 without an additional operating license extension. The Kori 1 Unit is scheduled to become the nuclear power unit to enter the decommissioning phase. In this study, the preliminary evaluation of the decommissioning wastes for the Kori Unit 1 was performed based on the following series of process: firstly, the plant inventory is investigated based on various documents (i.e., equipment/ component list, construction records, general arrangement drawings). Secondly, the radiological conditions of systems, structures and components (SSCs) are established to estimate the amount of radioactive waste by waste classification. Third, the waste management strategies for Kori Unit 1 including waste packaging are established. Forth, selection of the proper decontamination and dismantling (D&D) technologies is made considering the various factors. Finally, the amount of decommissioning waste by classification for Kori 1 is estimated using the DeCAT program, which was developed by KEPCO-E&C for a decommissioning cost estimation. The preliminary evaluation results have shown that the expected amounts of decommissioning wastes were less than about 2% and 8% of the total wastes generated (i.e., sum of clean wastes and radwastes) before/after waste processing, respectively, and it was found that the majority of contaminated material was carbon or alloy steel and stainless steel. In addition, within the range of availability of information, the results of the evaluation were compared with the results from the various decommissioning experiences data or international/national decommissioning study. The comparison results have shown that the radioactive waste amount from Kori Unit 1 decommissioning were much less than those from the plants decommissioned in U.S. and were comparable to those from the plants in Europe. This result comes from the difference of disposal cost and clearance criteria (i.e., free release level) between U.S. and non-U.S. The preliminary evaluation performed using the methodology established in this study will be useful as a important information in establishing the decommissioning planning for the decommissioning schedule and waste management strategy establishment including the transportation, packaging, handling, and disposal of radioactive wastes.

Keywords: characterization, classification, decommissioning, decontamination and dismantling, Kori 1, radioactive waste

Procedia PDF Downloads 206

Authors: Mohammed Abdullah Alshahrani

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The research focuses on investigating the use of partial least squares (PLS) methodology for addressing challenges associated with high-dimensional correlated data. Recent technological advancements have led to experiments producing data characterized by a large number of variables compared to observations, with substantial inter-variable correlations. Such data patterns are common in chemometrics, where near-infrared (NIR) spectrometer calibrations record chemical absorbance levels across hundreds of wavelengths, and in genomics, where thousands of genomic regions' copy number alterations (CNA) are recorded from cancer patients. PLS serves as a widely used method for analyzing high-dimensional data, functioning as a regression tool in chemometrics and a classification method in genomics. It handles data complexity by creating latent variables (components) from original variables. However, applying PLS can present challenges. The study investigates key areas to address these challenges, including unifying interpretations across three main PLS algorithms and exploring unusual negative shrinkage factors encountered during model fitting. The research presents an alternative approach to addressing the interpretation challenge of predictor weights associated with PLS. Sparse estimation of predictor weights is employed using a penalty function combining a lasso penalty for sparsity and a Cauchy distribution-based penalty to account for variable dependencies. The results demonstrate sparse and grouped weight estimates, aiding interpretation and prediction tasks in genomic data analysis. High-dimensional data scenarios, where predictors outnumber observations, are common in regression analysis applications. Ordinary least squares regression (OLS), the standard method, performs inadequately with high-dimensional and highly correlated data. Copy number alterations (CNA) in key genes have been linked to disease phenotypes, highlighting the importance of accurate classification of gene expression data in bioinformatics and biology using regularized methods like PLS for regression and classification.

Keywords: partial least square regression, genetics data, negative filter factors, high dimensional data, high correlated data

Procedia PDF Downloads 44

Authors: Michael N. O'Sullivan, Con Sheahan

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Researchers have spent decades developing tools and techniques to aid teams in the new product development (NPD) process. Despite this, it is evident that there is a huge gap between their academic prevalence and their industry adoption. For the fuzzy front-end, in particular, there is a wide range of tools to choose from, including the Kano Model, the House of Quality, and many others. In fact, there are so many tools that it can often be difficult for teams to know which ones to use and how they interact with one another. Moreover, while the benefits of using these tools are obvious to industrialists, they are rarely used as they carry a learning curve that is too steep and they become too complex to manage over time. In essence, it is commonly believed that they are simply not worth the effort required to learn and use them. This research explores a streamlined process for the fuzzy front-end, assembling the most effective tools and making them accessible to everyone. The process was developed iteratively over the course of 3 years, following over 80 final year NPD teams from engineering, design, technology, and construction as they carried a product from concept through to production specification. Questionnaires, focus groups, and observations were used to understand the usability issues with the tools involved, and a human-centred design approach was adopted to produce a solution to these issues. The solution takes the form of physical toolkit, similar to a board game, which allows the team to play through an example of a new product development in order to understand the process and the tools, before using it for their own product development efforts. A complimentary website is used to enhance the physical toolkit, and it provides more examples of the tools being used, as well as deeper discussions on each of the topics, allowing teams to adapt the process to their skills, preferences and product type. Teams found the solution very useful and intuitive and experienced significantly less confusion and mistakes with the process than teams who did not use it. Those with a design background found it especially useful for the engineering principles like Quality Function Deployment, while those with an engineering or technology background found it especially useful for design and customer requirements acquisition principles, like Voice of the Customer. Products developed using the toolkit are added to the website as more examples of how it can be used, creating a loop which helps future teams understand how the toolkit can be adapted to their project, whether it be a small consumer product or a large B2B service. The toolkit unlocks the potential of these beneficial tools to those in industry, both for large, experienced teams and for inexperienced start-ups. It allows users to assess the market potential of their product concept faster and more effectively, arriving at the product design stage with technical requirements prioritized according to their customers’ needs and wants.

Keywords: new product development, fuzzy front-end, usability, Kano model, quality function deployment, voice of customer

Procedia PDF Downloads 106

Authors: M. R. Aher, R. B. Laware, G. S. Asane, B. S. Kuchekar

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Objective: Studies have shown that a new combination therapy with Artemisinin derivatives and curcumin is unique, with potential advantages over known ACTs. In present study an attempt was made to prepare microparticulate drug delivery system of Curcumin-Zn complex and evaluate it in combination with artemether for antimalarial activity. Material and method: Curcumin Zn complex was prepared and encapsulated using sodium alginate. Microparticles thus obtained are further coated with various enteric polymers at different coating thickness to control the release. Microparticles are evaluated for encapsulation efficiency, drug loading and in vitro drug release. Roentgenographic Studies was conducted in rabbits with BaSO 4 tagged formulation. Optimized formulation was screened for antimalarial activity using P. berghei-infected mice survival test and % paracetemia inhibition, alone (three oral dose of 5mg/day) and in combination with arthemether (i.p. 500, 1000 and 1500µg). Curcumin-Zn(II) was estimated in serum after oral administration to rats by using spectroflurometry. Result: Microparticles coated with Cellulose acetate phthalate showed most satisfactory and controlled release with 479 min time for 60% drug release. X-ray images taken at different time intervals confirmed the retention of formulation in GI tract. Estimation of curcumin in serum by spectroflurometry showed that drug concentration is maintained in the blood for longer time with tmax of 6 hours. The survival time (40 days post treatment) of mice infected with P. berghei was compared to survival after treatment with either Curcumin-Zn(II) microparticles artemether combination, curcumin-Zn complex and artemether. Oral administration of Curcumin-Zn(II)-artemether prolonged the survival of P.berghei-infected mice. All the mice treated with Curcumin-Zn(II) microparticles (5mg/day) artemether (1000µg) survived for more than 40 days and recovered with no detectable parasitemia. Administration of Curcumin-Zn(II) artemether combination reduced the parasitemia in mice by more than 90% compared to that in control mice for the first 3 days after treatment. Conclusion: Antimalarial activity of the curcumin Zn-artemether combination was more pronounced than mono therapy. A single dose of 1000µg of artemether in curcumin-Zn combination gives complete protection in P. berghei-infected mice. This may reduce the chances of drug resistance in malaria management.

Keywords: formulation, microparticulate drug delivery, antimalarial, pharmaceutics

Procedia PDF Downloads 388

Authors: Edward R. Moad

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Al-Ghazali’s Tahāfat al Falāsifa is widely construed as an attack on philosophy in favor of theological fideism. Consequently, he has been blamed for ‘death of philosophy’ in the Muslim world. ‘Falsifa’ however is not philosophy itself, but rather a range of philosophical doctrines mainly influenced by or inherited form Greek thought. In these terms, this work represents a defense of philosophy against what we could call ‘falsifical’ fideism. In the introduction, Ghazali describes his target audience as, not the falasifa, but a group of pretenders engaged in taqlid to a misconceived understanding of falasifa, including the belief that they were capable of demonstrative certainty in the field of metaphysics. He promises to use falsifa standards of logic (with which he independently agrees), to show that that the falasifa failed to demonstratively prove many of their positions. Whether or not he succeeds in that, the exercise of subjecting alleged proofs to critical scrutiny is quintessentially philosophical, while uncritical adherence to a doctrine, in the name of its being ‘philosophical’, is decidedly unphilosophical. If we are to blame the intellectual decline of the Muslim world on someone’s ‘bad’ way of thinking, rather than more material historical circumstances (which is already a mistake), then blame more appropriately rests with modernist Muslim thinkers who, under the influence of orientalism (and like Ghazali’s philosophical pretenders) mistook taqlid to the falasifa as philosophy itself. The discussion of the Tahāfut takes place in the context of an epistemic (and related social) hierarchy envisioned by the falasifa, corresponding to the faculties of the sense, the ‘estimative imagination’ (wahm), and the pure intellect, along with the respective forms of discourse – rhetoric, dialectic, and demonstration – appropriate to each category of that order. Al-Farabi in his Book of Letters describes a relation between dialectic and demonstration on the one hand, and theology and philosophy on the other. The latter two are distinguished by method rather than subject matter. Theology is that which proceeds dialectically, while philosophy is (or aims to be?) demonstrative. Yet, Al-Farabi tells us, dialectic precedes philosophy like ‘nourishment for the tree precedes its fruit.’ That is, dialectic is part of the process, by which we interrogate common and imaginative notions in the pursuit of clearly understood first principles that we can then deploy in the demonstrative argument. Philosophy is, therefore, something we aspire to through, and from a discursive condition of, dialectic. This stands in apparent contrast to the understanding of Ibn Sina, for whom one arrives at the knowledge of first principles through contact with the Active Intellect. It also stands in contrast to that of Ibn Rushd, who seems to think our knowledge of first principles can only come through reading Aristotle. In conclusion, based on Al-Farabi’s framework, Ghazali’s Tahafut is a truly an exercise in philosophy, and an effort to keep the door open for true philosophy in the Muslim mind, against the threat of a kind of developing theology going by the name of falsifa.

Keywords: philosophy, incoherence, theology, Tahafut

Procedia PDF Downloads 155

Authors: Priyanka Sharma, Manoj Jais, Poonam Gupta, Suraiya K. Ansari, Ravinder Kaur

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Introduction: As much as the Health Care is necessary for the population, so is the management of the Biomedical waste produced. Biomedical waste is a wide terminology used for the waste material produced during the diagnosis, treatment or immunization of human beings and animals, in research or in the production or testing of biological products. Biomedical waste management is a chain of processes from the point of generation of Biomedical waste to its final disposal in the correct and proper way, assigned for that particular type of waste. Any deviation from the said processes leads to improper disposal of Biomedical waste which itself is a major health hazard. Proper segregation of Biomedical waste is the key for Biomedical Waste management. Improper disposal of BMW can cause sharp injuries which may lead to HIV, Hepatitis-B virus, Hepatitis-C virus infections. Therefore, proper disposal of BMW is of upmost importance. Health care establishments segregate the Biomedical waste and dispose it as per the Biomedical waste management rules in India. Objectives: This study was done to observe the current trends of Biomedical waste generated in a tertiary care Hospital in Delhi. Methodology: Biomedical waste management rounds were conducted in the hospital wards. Relevant details were collected and analysed and sites with maximum Biomedical waste generation were identified. All the data was cross checked with the commons collection site. Results: The total amount of waste generated in the hospital during January 2014 till December 2014 was 6,39,547 kg, of which 70.5% was General (non-hazardous) waste and the rest 29.5% was BMW which consisted highly infectious waste (12.2%), disposable plastic waste (16.3%) and sharps (1%). The maximum quantity of Biomedical waste producing sites were Obstetrics and Gynaecology wards with a total Biomedical waste production of 45.8%, followed by Paediatrics, Surgery and Medicine wards with 21.2 %, 4.6% and 4.3% respectively. The maximum average Biomedical waste generated was by Obstetrics and Gynaecology ward with 0.7 kg/bed/day, followed by Paediatrics, Surgery and Medicine wards with 0.29, 0.28 and 0.18 kg/bed/day respectively. Conclusions: Hospitals should pay attention to the sites which produce a large amount of BMW to avoid improper segregation of Biomedical waste. Also, induction and refresher training Program of Biomedical waste management should be conducted to avoid improper management of Biomedical waste. Healthcare workers should be made aware of risks of poor Biomedical waste management.

Keywords: biomedical waste, biomedical waste management, hospital-tertiary care, New Delhi

Procedia PDF Downloads 241

Authors: Erick R. Bandala, Kebret Kebede, Nicole Johnson, Rebecca Murray, Destiny Green, John Mejia, Polioptro Martinez-Austria

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Summertemperature data from Clark County was collected and used to estimate two different heat-related indexes: the heat index (HI) and excess heat factor (EHF). These two indexes were used jointly with data of health-related deaths in Clark County to assess the effect of extreme heat on the exposed population. The trends of the heat indexes were then analyzed for the 2007-2016 decadeandthe correlation between heat wave episodes and the number of heat-related deaths in the area was estimated. The HI showed that this value has increased significantly in June, July, and August over the last ten years. The same trend was found for the EHF, which showed a clear increase in the severity and number of these events per year. The number of heat wave episodes increased from 1.4 per year during the 1980-2016 period to 1.66 per yearduring the 2007-2016 period. However, a different trend was found for heat-wave-event duration, which decreasedfrom an average of 20.4 days during the trans-decadal period (1980-2016) to 18.1 days during the most recent decade(2007-2016). The number of heat-related deaths was also found to increase from 2007 to 2016, with 2016 with the highest number of heat-related deaths. Both HI and the number of deaths showeda normal-like distribution for June, July, and August, with the peak values reached in late July and early August. The average maximum HI values better correlated with the number of deaths registered in Clark County than the EHF, probably because HI uses the maximum temperature and humidity in its estimation,whereas EHF uses the average medium temperature. However, it is worth testing the EHF of the study zone because it was reported to fit properly in the case of heat-related morbidity. For the overall period, 437 heat-related deaths were registered in Clark County, with 20% of the deaths occurring in June, 52% occurring in July, 18% occurring in August,and the remaining 10% occurring in the other months of the year. The most vulnerable subpopulation was people over 50 years old, for which 76% of the heat-related deaths were registered.Most of the cases were associated with heart disease preconditions. The second most vulnerable subpopulation was young adults (20-50), which accounted for 23% of the heat-related deaths. These deathswere associated with alcoholic/illegal drug intoxication.

Keywords: heat, health, hazards, workforce

Procedia PDF Downloads 102

Authors: Mohd Harun, Cini Varghese, Eldho Varghese, Seema Jaggi

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Hybridization crosses find a vital role in breeding experiments to evaluate the combining abilities of individual parental lines or crosses for creation of lines with desirable qualities. There are various ways of obtaining progenies and further studying the combining ability effects of the lines taken in a breeding programme. Some of the most common methods are diallel or two-way cross, triallel or three-way cross, tetra-allele or four-way cross. These techniques help the breeders to improve the quantitative traits which are of economical as well as nutritional importance in crops and animals. Amongst these methods, tetra-allele cross provides extra information in terms of the higher specific combining ability (sca) effects and the hybrids thus produced exhibit individual as well as population buffering mechanism because of the broad genetic base. Most of the common commercial hybrids in corn are either three-way or four-way cross hybrids. Tetra-allele cross came out as the most practical and acceptable scheme for the production of slaughter pigs having fast growth rate, good feed efficiency, and carcass quality. Tetra-allele crosses are mostly used for exploitation of heterosis in case of commercial silkworm production. Experimental designs involving tetra-allele crosses have been studied extensively in literature. Optimality of designs has also been considered as a researchable issue. In practical situations, it is advisable to include sca effects in the model as this information is needed by the breeder to improve economically and nutritionally important quantitative traits. Thus, a model that provides information regarding the specific traits by utilizing sca effects along with general combining ability (gca) effects may help the breeders to deal with the problem of various stresses. In this paper, a model for experimental designs involving tetra-allele crosses that incorporates both gca and sca has been defined. Optimality aspects of such designs have been discussed incorporating sca effects in the model. Orthogonality conditions have been derived for block designs ensuring estimation of contrasts among the gca effects, after eliminating the nuisance factors, independently from sca effects. User friendly SAS macro and web solution (webPTC) have been developed for the generation and analysis of such designs.

Keywords: general combining ability, optimality, specific combining ability, tetra-allele cross, webPTC

Procedia PDF Downloads 130

Authors: Andrea Giacomelli, Luciano Massetti, Elena Maggi, Antonio Raschi

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The presentation will report the activities managed during the Summer of 2017 by a team composed by staff from a University Department, a National Research Council Institute, and an outreach NGO, collecting measurements of night sky brightness and other information on artificial lighting, in order to characterize light pollution issues on portions of the Tuscan coast, in Central Italy. These activities combine measurements collected by the principal scientists, citizen science observations led by students, and outreach events targeting a broad audience. This campaign aggregates the efforts of three actors: the BuioMetria Partecipativa project, which started collecting light pollution data on a national scale in 2008 with an environmental engineering and free/open source GIS core team; the Institute of Biometeorology from the National Research Council, with ongoing studies on light and urban vegetation and a consolidated track record in environmental education and citizen science; the Department of Biology from the University of Pisa, which started experiments to assess the impact of light pollution in coastal environments in 2015. While the core of the activities concerns in situ data, the campaign will account also for remote sensing data, thus considering heterogeneous data sources. The aim of the campaign is twofold: (1) To test actions of citizen and student engagement in monitoring sky brightness (2) To collect night sky brightness data and test a protocol for applications to studies on the ecological impact of light pollution, with a special focus on marine coastal ecosystems. The collaboration of an interdisciplinary team in the study of artificial lighting issues is not a common case in Italy, and the possibility of undertaking the campaign in Tuscany has the added value of operating in one of the territories where it is possible to observe both sites with extremely high lighting levels, and areas with extremely low light pollution, especially in the Southern part of the region. Combining environmental monitoring and communication actions in the context of the campaign, this effort will contribute to the promotion of night skies with a good quality as an important asset for the sustainability of coastal ecosystems, as well as to increase citizen awareness through star gazing, night photography and actively participating in field campaign measurements.

Keywords: citizen science, light pollution, marine coastal biodiversity, environmental education

Procedia PDF Downloads 169

Authors: Karitikeya Sonker

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Religion as a discrete system through its lawful internal working produces an output in the form of realised spatial order with its social logic and a social order with its spatial logic. Thus, it appears to exhibit its duality of spatial and trans-spatial. The components of this system share a relevance forming a collective. This shared relevance creates meaning forming a group where all collectives share one identity. This group with its new social order and its spatial logic revive the already existing spatial order. These religious groups do so having a tendency to expand resulting in the production of space in a situation of encounter where they have found relevance. But an encounter without a lawful internal working of a discrete system results in anomaly because groups do not find relevance due to the absence of collective identity. Events happen all around. One of the main reasons we could say that something became an event is because of conflict. Conflict not in its definitive sense but any occurrence that happens because of an intervention that creates an event worth remembering. The unfolding of such events creates Cities and Urban spaces which exhibit their duality of spatial and trans-spatial by behaving as a discrete system. This system through its lawful internal working produces an output in the form of realized spatial order with its social logic and a social order with spatial logic. The components of this system form a collective through a shared a relevance. This shared relevance creates meaning forming a group where all collectives share one identity. This group with its new social order and its spatial logic revives the already existing spatial order. These groups do so having a tendency to expand resulting in the production of space in a situation of encounter where they have found relevance. But an encounter without a lawful internal working of the discrete system results in anomaly because groups do not find relevance due to the absence of collective identity. This paper makes an effort to explore one such even in the case of Babri Mosque and Ramjanmabhumi, Ayodhya to explain the anomaly as transposition of social and spatial. The paper through the case studies makes an attempt to generate an equation explaining the two different situations of religious encounters, former reviving the social and spatial order and the other resulting in anomaly. Through the case study, it makes an attempt to generate an equation explaining the two different situations of religious encounters, former reviving the social and spatial order and the other resulting in anomaly.

Keywords: Babri Masjid, Ayodhya, conflict, religion

Procedia PDF Downloads 272

Authors: S. Koppikar, P. Kulkarni, D. Ingale , N. Wagh, S. Deshpande, A. Mahajan, A. Harsulkar

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Crucial role of reactive oxygen species (ROS) in the progression Osteoarthritis (OA) pathogenesis has been endorsed several times though its exact mechanism remains unclear. Oxidative stress is known to instigate classical stress factors such as cytokines, chemokines and ROS, which hampers cartilage remodelling process and ultimately results in worsening the disease. Synovial fluid (SF) is a biological communicator between cartilage and synovium that accumulates redox and biochemical signalling mediators. The present work attempts to measure several oxidative stress markers in the synovial fluid obtained from knee OA patients with varying degree of disease severity. Thirty OA and five Meniscal-tear (MT) patients were graded using Kellgren-Lawrence scale and assessed for Nitric oxide (NO), Nitrate-Nitrite (NN), 2,2-diphenyl-1-picrylhydrazyl (DPPH), Ferric Reducing Antioxidant Potential (FRAP), Catalase (CAT), Superoxide dismutase (SOD) and Malondialdehyde (MDA) levels for comparison. Out of various oxidative markers studied, NO and SOD showed significant difference between moderate and severe OA (p= 0.007 and p= 0.08, respectively), whereas CAT demonstrated significant difference between MT and mild group (p= 0.07). Interestingly, NN revealed statistically positive correlation with OA severity (p= 0.001 and p= 0.003). MDA, a lipid peroxidation by-product was estimated maximum in early OA when compared to MT (p= 0.06). However, FRAP did not show any correlation with OA severity or MT control. NO is an essential bio-regulatory molecule essential for several physiological processes, and inflammatory conditions. However, due to its short life, exact estimation of NO becomes difficult. NO and its measurable stable products are still it is considered as one of the important biomarker of oxidative damage. Levels of NO and nitrite-nitrate in SF of patients with OA indicated its involvement in the disease progression. When SF groups were compared, a significant correlation among moderate, mild and MT groups was established. To summarize, present data illustrated higher levels of NO, SOD, CAT, DPPH and MDA in early OA in comparison with MT, as a control group. NN had emerged as a prognostic bio marker in knee OA patients, which may act as futuristic targets in OA treatment.

Keywords: antioxidant, knee osteoarthritis, oxidative stress, synovial fluid

Procedia PDF Downloads 471

Authors: Olusegun F. Adebowale

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Research has confirmed that the emergence of information technology is significantly reflected in the field of psychology and its related disciplines due to its widespread use at reasonable price and its user-friendliness. It is consequently affecting ordinary life in many areas like shopping, advertising, corresponding and educating. Specifically the innovations of computer technology led to several new forms of communication, all with implications and applicability for counselling and psychotherapy practices. This is premise on which online counselling is based. Most institutions of higher learning in Nigeria have established their presence on the Internet and have deployed a variety of applications through ICT. Some are currently attempting to include counselling services in such applications with the belief that many counselling needs of students are likely to be met. This study therefore explored different challenges and preferences students present in online counselling interaction in a given Nigerian university with the view to guide new universities that may want to invest into these areas as to necessary preparations and referral requirements. The study is a mixed method research incorporating qualitative and quantitative methodologies to sample the preferences and concerns students express in online interaction. The sample comprised all the 876 students who visited the university online counselling platform either voluntarily, by invitation or by referral. The instrument for data collection was the online counselling platform of the university 'OAU Online counsellors'. The period of data collection spanned between January 2011 and October 2012. Data were analysed quantitatively (using percentages and Mann-Whitney U test) and qualitatively (using Interpretative Phenomenological Analysis (IPA)). The results showed that the students seem to prefer real-time chatting as their online medium of communicating with the online counsellor. The majority of students resorted to e-mail when their effort to use real-time chatting were becoming thwarted. Also, students preferred to enter into online counselling relationships voluntarily to other modes of entry. The results further showed that the prevalent counselling needs presented by students during online counselling sessions were mainly in the areas of social interaction and academic/educational concerns. Academic concerns were found to be prevalent, in form of course offerings, studentship matters and academic finance matters. The personal/social concerns were in form of students’ welfare, career related concerns and relationship matters. The study concludes students’ preferences include voluntary entry into online counselling, communication by real-time chatting and a specific focus on their academic concerns. It also recommends that all efforts should be made to encourage students’ voluntary entry into online counselling through reliable and stable internet infrastructure that will be able to support real-time chatting.

Keywords: online, counselling, needs, preferences

Procedia PDF Downloads 285

Authors: Aldona Kluczek

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Energy efficient process have become a pressing research field in manufacturing. The arguments for having an effective industrial energy efficiency processes are interacted with factors: economic and environmental impact, and energy security. Improvements in energy efficiency are most often achieved by implementation of more efficient technology or manufacturing process. Current processes of electricity production represents the biggest consumption of energy and the greatest amount of emissions to the environment. The goal of this study is to improve the potential energy-savings and reduce greenhouse emissions related to improvement scenarios for the treatment of hardwood lumber produced by an industrial plant operating in the U.S. through the application of green balancing procedure, in order to find the preferable efficient technology. The green procedure for energy is based on analysis of energy efficiency data. Three alternative scenarios of the cogeneration systems plant (CHP) construction are considered: generation of fresh steam, the purchase of a new boiler with the operating pressure 300 pounds per square inch gauge (PSIG), an installation of a new boiler with a 600 PSIG pressure. In this paper, the application of a bottom-down modelling for energy flow to devise a streamlined Energy and Emission Flow Analyze method for the technology of producing electricity is illustrated. It will identify efficiency or technology of a given process to be reached, through the effective use of energy, or energy management. Results have shown that the third scenario seem to be the efficient alternative scenario considered from the environmental and economic concerns for treating hardwood lumber. The energy conservation evaluation options could save an estimated 6,215.78 MMBtu/yr in each year, which represents 9.5% of the total annual energy usage. The total annual potential cost savings from all recommendations is $143,523/yr, which represents 30.1% of the total annual energy costs. Estimation have presented that energy cost savings are possible up to 43% (US$ 143,337.85), representing 18.6% of the total annual energy costs.

Keywords: alternative scenario improvements, cogeneration system, energy and emission flow analyze, energy balancing, green procedure, hardwood lumber manufacturing process

Procedia PDF Downloads 201

Authors: Juan C. Gutierrez-Estrada, Inmaculada Pulido-Calvo, Ignacio De La Rosa, Antonio Peregrin, Fernando Gomez-Bravo, Samuel Lopez-Dominguez, Alejandro Garrocho-Cruz, Jairo Castro-Gutierrez

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The semi-intensive aquaculture in traditional earth ponds is the main rearing system in Southern Spain. These fish rearing systems are approximately two thirds of aquatic production in this area which has made a significant contribution to the regional economy in recent years. In this type of rearing system, a crucial aspect is the correct quantification and control of the fish abundance in the ponds because the fish farmer knows how many fishes he puts in the ponds but doesn’t know how many fishes will harvest at the end of the rear period. This is a consequence of the mortality induced by different causes as pathogen agents as parasites, viruses and bacteria and other factors as predation of fish-eating birds and poaching. Track the fish abundance in these installations is very difficult because usually the ponds take up a large area of land and the management of the water flow is not automatized. Therefore, there is a very high degree of uncertainty on the abundance fishes which strongly hinders the management and planning of the sales. A novel and non-invasive procedure to count fishes in the ponds is by the means of imaging sonars, particularly fixed systems and/or linked to aquatic vehicles as Remotely Operated Vehicles (ROVs). In this work, a method based on census stations procedures is proposed to evaluate the fish abundance estimation accuracy using images obtained of multibeam sonars. The results indicate that it is possible to obtain a realistic approach about the number of fishes, sizes and therefore the biomass contained in the ponds. This research is included in the framework of the KTTSeaDrones Project (‘Conocimiento y transferencia de tecnología sobre vehículos aéreos y acuáticos para el desarrollo transfronterizo de ciencias marinas y pesqueras 0622-KTTSEADRONES-5-E’) financed by the European Regional Development Fund (ERDF) through the Interreg V-A Spain-Portugal Programme (POCTEP) 2014-2020.

Keywords: census station procedure, fish biomass, semi-intensive aquaculture, multibeam sonars

Procedia PDF Downloads 216

Authors: George Pavlidis, Ana Vivas

Abstract:

The demographic change into an aging population has stimulated the examination of seniors’ mental health and ability to live independently. The corresponding literature depicts the relation between cognitive decline and everyday functionality with aging, focusing largely in individuals that are reaching or have bridged the threshold of various forms of neuropathology and disability. In this context, recent meta-analysis depicts a moderate relation between cognitive performance and everyday functionality in AD sufferers. However, there has not been an analogous effort for the examination of this relation in the healthy spectrum of aging (i.e, in samples that are not challenged from a neurodegenerative disease). There is a consensus that the assessment tools designed to detect neuropathology with those that assess cognitive performance in healthy adults are distinct, thus their universal use in cognitively challenged and in healthy adults is not always valid. The same accounts for the assessment of everyday functionality. In addition, it is argued that everyday functionality should be examined with cultural adjusted assessment tools, since many vital everyday tasks are heterotypical among distinct cultures. Therefore, this study was set out to examine the relation between cognitive performance and everyday functionality a) in the healthy spectrum of aging and b) by adjusting the everyday functionality tools EPT and OTDL-R in the Greek cultural context. In Greece, 107 cognitively healthy seniors ( Mage = 62.24) completed a battery of neuropsychological tests and everyday functionality tests. Both were carefully chosen to be sensitive in fluctuations of performance in the healthy spectrum of cognitive performance and everyday functionality. The everyday functionality assessment tools were modified to reflect the local cultural context (i.e., EPT-G and OTDL-G). The results depicted that performance in all everyday functionality measures decline with age (.197 < r > .509). Statistically significant correlations emerged between cognitive performance and everyday functionality assessments that range from r =0.202 to r=0.510. A series of independent regression analysis including the scores of cognitive assessments has yield statistical significant models that explained 20.9 < AR2 > 32.4 of the variance in everyday functionality scored indexes. All everyday functionality measures were independently predicted by the TMT B-A index, and indicator of executive function. Stepwise regression analyses depicted that TMT B-A and age were statistically significant independent predictors of EPT-G and OTDL-G. It was concluded that everyday functionality is declining with age and that cognitive performance and everyday functional may be related in the healthy spectrum of aging. Age seems not to be the sole contributing factor in everyday functionality decline, rather executive control as well. Moreover, it was concluded that the EPT-G and OTDL-G are valuable tools to assess everyday functionality in Greek seniors that are not cognitively challenged, especially for research purposes. Future research should examine the contributing factors of a better cognitive vitality especially in executive control, as vital for the maintenance of independent living capacity with aging.

Keywords: cognition, everyday functionality, aging, cognitive decline, healthy aging, Greece

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