Search results for: deep soil mixing column

Authors: Priya Tomar, Pallavi Mittal

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As industrialization is inevitable and progress with rapid acceleration, the need for innovative ways to get rid of waste has increased. Recent advancement in bioresource technology paves novel ideas for recycling of factory waste that has been polluting the agro-industry, soil and water bodies. Paper industries in India are in a considerable number, where molasses and impure alcohol are still being used as raw materials for manufacturing of paper. Paper mills based on nonconventional agro residues are being encouraged due to increased demand of paper and acute shortage of forest-based raw materials. The colouring body present in the wastewater from pulp and paper mill is organic in nature and is comprised of wood extractives, tannin, resins, synthetic dyes, lignin and its degradation products formed by the action of chlorine on lignin which imparts an offensive colour to the water. These mills use different chemical process for paper manufacturing due to which lignified chemicals are released into the environment. Therefore, the chemical oxygen demand (COD) of the emanating stream is quite high. This paper presents some new techniques that were developed for the efficiency of bioremediation on paper industry. A short introduction to paper industry and a variety of presently available methods of bioremediation on paper industry and different strategies are also discussed here. For solving the above problem, two bacterial strains (Pseudomonas aeruginosa and Bacillus subtilis) and their consortia (Pseudomonas aeruginosa and Bacillus subtilis) were utilized for the pulp and paper mill effluent. Pseudomonas aeruginosa and Bacillus subtilis named as T–1, T–2, T–3, T–4, T–5, T–6, for the decolourisation of paper industry effluent. The results indicated that a maximum colour reduction is (60.5%) achieved by Pseudomonas aeruginosa and COD reduction is (88.8%) achieved by Bacillus subtilis, maximum pH changes is (4.23) achieved by Pseudomonas aeruginosa, TSS reduction is (2.09 %) achieved by Bacillus subtilis, and TDS reduction is (0.95 %) achieved by Bacillus subtilis. When the wastewater was supplemented with carbon (glucose) and nitrogen (yeast extract) source and data revealed the efficiency of Bacillus subtilis, having more with glucose than Pseudomonas aeruginosa.

Keywords: bioremediation, paper and pulp mill effluent, treated effluent, lignin

Procedia PDF Downloads 240

Authors: Dheyaa W. Abbood, Rafa H. AL-Suhaili, May S. Saleh

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A model using the artificial neural networks and genetic algorithm technique is developed for obtaining optimum dimensions of the foundation length and protections of small hydraulic structures. The procedure involves optimizing an objective function comprising a weighted summation of the state variables. The decision variables considered in the optimization are the upstream and downstream cutoffs length sand their angles of inclination, the foundation length, and the length of the downstream soil protection. These were obtained for a given maximum difference in head, depth of impervious layer and degree of anisotropy.The optimization carried out subjected to constraints that ensure a safe structure against the uplift pressure force and sufficient protection length at the downstream side of the structure to overcome an excessive exit gradient. The Geo-studios oft ware, was used to analyze 1200 different cases. For each case the length of protection and volume of structure required to satisfy the safety factors mentioned previously were estimated. An ANN model was developed and verified using these cases input-output sets as its data base. A MatLAB code was written to perform a genetic algorithm optimization modeling coupled with this ANN model using a formulated optimization model. A sensitivity analysis was done for selecting the cross-over probability, the mutation probability and level ,the number of population, the position of the crossover and the weights distribution for all the terms of the objective function. Results indicate that the most factor that affects the optimum solution is the number of population required. The minimum value that gives stable global optimum solution of this parameters is (30000) while other variables have little effect on the optimum solution.

Keywords: inclined cutoff, optimization, genetic algorithm, artificial neural networks, geo-studio, uplift pressure, exit gradient, factor of safety

Procedia PDF Downloads 312

Authors: Yangzhi Li

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Network transfer of information and performance customization is now a viable method of digital industrial production in the era of Industry 4.0. Robot platforms and network platforms have grown more important in digital design and construction. The pressing need for novel building techniques is driven by the growing labor scarcity problem and increased awareness of construction safety. Robotic approaches in construction research are regarded as an extension of operational and production tools. Several technological theories related to robot autonomous recognition, which include high-performance computing, physical system modeling, extensive sensor coordination, and dataset deep learning, have not been explored using intelligent construction. Relevant transdisciplinary theory and practice research still has specific gaps. Optimizing high-performance computing and autonomous recognition visual guidance technologies improves the robot's grasp of the scene and capacity for autonomous operation. Intelligent vision guidance technology for industrial robots has a serious issue with camera calibration, and the use of intelligent visual guiding and identification technologies for industrial robots in industrial production has strict accuracy requirements. It can be considered that visual recognition systems have challenges with precision issues. In such a situation, it will directly impact the effectiveness and standard of industrial production, necessitating a strengthening of the visual guiding study on positioning precision in recognition technology. To best facilitate the handling of complicated components, an approach for the visual recognition of parts utilizing machine learning algorithms is proposed. This study will identify the position of target components by detecting the information at the boundary and corner of a dense point cloud and determining the aspect ratio in accordance with the guidelines for the modularization of building components. To collect and use components, operational processing systems assign them to the same coordinate system based on their locations and postures. The RGB image's inclination detection and the depth image's verification will be used to determine the component's present posture. Finally, a virtual environment model for the robot's obstacle-avoidance route will be constructed using the point cloud information.

Keywords: robotic construction, robotic assembly, visual guidance, machine learning

Procedia PDF Downloads 75

Authors: Aishi Kundu, Elhan Raza

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"Necessity is the mother of invention" - Rapid increase in the global human population has directed the agricultural domain toward machine learning. The basic need of human beings is considered to be food which can be satisfied through farming. Farming is one of the major revenue generators for the Indian economy. Agriculture is not only considered a source of employment but also fulfils humans’ basic needs. So, agriculture is considered to be the source of employment and a pillar of the economy in developing countries like India. This paper provides a brief review of the progress made in implementing Machine Learning in the agricultural sector. Accurate predictions are necessary at the right time to boost production and to aid the timely and systematic distribution of agricultural commodities to make their availability in the market faster and more effective. This paper includes a thorough analysis of various machine learning algorithms applied in different aspects of agriculture (crop management, soil management, water management, yield tracking, livestock management, etc.).Due to climate changes, crop production is affected. Machine learning can analyse the changing patterns and come up with a suitable approach to minimize loss and maximize yield. Machine Learning algorithms/ models (regression, support vector machines, bayesian models, artificial neural networks, decision trees, etc.) are used in smart agriculture to analyze and predict specific outcomes which can be vital in increasing the productivity of the Agricultural Food Industry. It is to demonstrate vividly agricultural works under machine learning to sensor data. Machine Learning is the ongoing technology benefitting farmers to improve gains in agriculture and minimize losses. This paper discusses how the irrigation and farming management systems evolve in real-time efficiently. Artificial Intelligence (AI) enabled programs to emerge with rich apprehension for the support of farmers with an immense examination of data.

Keywords: machine Learning, artificial intelligence, crop management, precision farming, smart farming, pre-harvesting, harvesting, post-harvesting

Procedia PDF Downloads 91

Authors: Soheila Sadeghi

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Construction projects are complex and often subject to significant cost overruns due to the multifaceted nature of the activities involved. Accurate cost estimation is crucial for effective budget planning and resource allocation. Traditional methods for predicting overruns often rely on expert judgment or analysis of historical data, which can be time-consuming, subjective, and may fail to consider important factors. However, with the increasing availability of data from construction projects, machine learning techniques can be leveraged to improve the accuracy of overrun predictions. This study applied machine learning algorithms to enhance the prediction of cost overruns in a case study of a construction project. The methodology involved the development and evaluation of two machine learning models: Random Forest and Neural Networks. Random Forest can handle high-dimensional data, capture complex relationships, and provide feature importance estimates. Neural Networks, particularly Deep Neural Networks (DNNs), are capable of automatically learning and modeling complex, non-linear relationships between input features and the target variable. These models can adapt to new data, reduce human bias, and uncover hidden patterns in the dataset. The findings of this study demonstrate that both Random Forest and Neural Networks can significantly improve the accuracy of cost overrun predictions compared to traditional methods. The Random Forest model also identified key cost drivers and risk factors, such as changes in the scope of work and delays in material delivery, which can inform better project risk management. However, the study acknowledges several limitations. First, the findings are based on a single construction project, which may limit the generalizability of the results to other projects or contexts. Second, the dataset, although comprehensive, may not capture all relevant factors influencing cost overruns, such as external economic conditions or political factors. Third, the study focuses primarily on cost overruns, while schedule overruns are not explicitly addressed. Future research should explore the application of machine learning techniques to a broader range of projects, incorporate additional data sources, and investigate the prediction of both cost and schedule overruns simultaneously.

Keywords: cost prediction, machine learning, project management, random forest, neural networks

Procedia PDF Downloads 26

Authors: Vishwanath Mali, Hemant Warhatkar, Raju Pawade

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Drilling of bone has been always challenging for surgeons due to the adverse effect it may impart to bone tissues. Force has to be applied manually by the surgeon while performing conventional bone drilling which may lead to permanent death of bone tissues and nerves. During bone drilling the temperature of the bone tissues increases to higher values above 47 ⁰C that causes thermal osteonecrosis resulting into screw loosening and subsequent implant failures. An attempt has been made here to study the input drilling parameters and surgical drill bit geometry affecting bone health during bone drilling. A One Factor At a Time (OFAT) method is used to plan the experiments. Input drilling parameters studied include spindle speed and feed rate. The drill bit geometry parameter studied include point angle and helix angle. The output variables are drilling thrust force and bone temperature. The experiments were conducted on goat femur bone at room temperature 30 ⁰C. For measurement of thrust forces KISTLER cutting force dynamometer Type 9257BA was used. For continuous data acquisition of temperature NI LabVIEW software was used. Fixture was made on RPT machine for holding the bone specimen while performing drilling operation. Bone specimen were preserved in deep freezer (LABTOP make) under -40 ⁰C. In case of drilling parameters, it is observed that at constant feed rate when spindle speed increases, thrust force as well as temperature decreases and at constant spindle speed when feed rate increases thrust force as well as temperature increases. The effect of drill bit geometry shows that at constant helix angle when point angle increases thrust force as well as temperature increases and at constant point angle when helix angle increase thrust force as well as temperature decreases. Hence it is concluded that as the thrust force increases temperature increases. In case of drilling parameter, the lowest thrust force and temperature i.e. 35.55 N and 36.04 ⁰C respectively were recorded at spindle speed 2000 rpm and feed rate 0.04 mm/rev. In case of drill bit geometry parameter, the lowest thrust force and temperature i.e. 40.81 N and 34 ⁰C respectively were recorded at point angle 70⁰ and helix angle 25⁰ Hence to avoid thermal necrosis of bone it is recommended to use higher spindle speed, lower feed rate, low point angle and high helix angle. The hard nature of cortical bone contributes to a greater rise in temperature whereas a considerable drop in temperature is observed during cancellous bone drilling.

Keywords: bone drilling, helix angle, point angle, thrust force, temperature, thermal necrosis

Procedia PDF Downloads 303

Authors: Ebrahim Izadi-Darbandi, Masoud Azad, Masumeh Dehghan

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In order to study the effects of nitrogen and phosphoruse management and wheat sowing method on wheat yield, two experiments was performed as factorial, based on completely randomized design with three replications at Research Farm, Faculty of Agriculture, Ferdowsi University of Mashhad, Iran in 2009. In the first experiment nitrogen application rates (100kg ha-1, 200 kg ha-1, 300 kg ha-1), phosphorus application rates (100 kg ha-1, 200 kg ha-1) and two levels of their application methods (Broadcast and Band) were studied. The second experiment treatments included of wheat sowing methods (single-row with 30 cm distance and twine row on 60 cm width ridges), as main plots and nitrogen and phosphorus application methods (Broadcast and Band) as sub plots (150 kg ha-1). Phosphorus and nitrogen sources for fertilization at both experiment were respectively super phosphate, applied before wheat sowing and incorporated with soil and urea, applied in two phases (50% pre plant) and (50%) near wheat shooting. Results from first experiment showed that the effect of fertilizers application methods were significant (p≤0.01) on wheat yield increasing. Band application of phosphorus and nitrogen were increased biomass and seed yield of wheat with nine and 15% respectively compared to their broadcast application. The interaction between the effects of nitrogen and phosphorus application rate with phosphorus and nitrogen application methods, showed that band application of fertilizers and the rate of application of 200kg/ha phosphorus and 300kg/ha nitrogen were the best methods in wheat yield improvement. The second experiment also showed that the effect of wheat sowing method and fertilizers application methods were significant (p≤0.01) on wheat seed and biomass yield improvement. Wheat twine row on 60 cm width ridges sowing method, increased its biomass and seed yield for 22% and 30% respectively compared to single-row with 30 cm. Wheat sowing method and fertilizers application methods interaction indicated that band application of fertilizers and wheat twine row on 60 cm width ridges sowing method was the best treatment on winter wheat yield improvement. In conclusion these results indicated that nitrogen and phosphorus management in wheat and modifying wheat sowing method have important role in increasing fertilizers use efficiency.

Keywords: band application, broadcast application, rate of fertilizer application, wheat seed yield, wheat biomass yield

Procedia PDF Downloads 449

Authors: Trieu Anh Ngoc, Nguyen Quang Kim

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Located at the downstream of the Mekong Delta, the Vietnamese Mekong Delta is well-known as 'rice bowl' of Vietnam. The Vietnamese Mekong Delta experiences widespread flooding annually where is habitat for about 17 million people. The economy of this region mainly depends on the agricultural productivities. The suspended sediment load in the Mekong River plays an important role in carrying contaminants and nutrients to the delta and changing the geomorphology of the delta river system. In many past decades, flooding and suspended sediment were considered as indispensable factors in agricultural cultivations. Although flooding in the wet season caused serious inundation in paddy field and affected livelihoods, it is an effective facility for flushing acid and saline to this area - alluvial soil heavily contaminated with acid and salt intrusion. In addition, sediment delivery to this delta contained rich-nutrients distributed and deposited on the fields through flooding process. In recent decades, the changing of flow and sediment transport have been strongly and clearly occurring due to upstream dam development and climate change. However, effects of sediment delivery on agricultural cultivations were less attention. This study investigated the impacts of upstream flow on sediment distribution in the Vietnamese Mekong Delta. Flow fluctuation and sediment distribution were simulated by the Mike 11 model, including hydrodynamics model and advection-dispersion model. Various scenarios were simulated based on anticipated upstream discharges. Our findings indicated that sediment delivery into the Vietnamese Mekong Delta come from not only Tien River but also border of Cambodia floodplains. Sediment distribution in the Vietnamese Mekong Delta is dramatically changed by the distance from the main rivers and the secondary channels. The dam development in the upstream is one of the major factors leading a decrease in sediment discharge as well as sediment deposition. Moreover, sea level rise partially contributed to decrease in sediment transport and change of sediment distribution between upstream and downstream of the Vietnamese Mekong Delta.

Keywords: sediment transport, sea level rise, climate change, Mike Model

Procedia PDF Downloads 263

Authors: Nanh Lovanh, John Loughrin, Kimberly Cook, Phil Silva, Byung-Taek Oh

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In the era of sustainability, utilization of livestock wastes as soil amendment to provide micronutrients for crops is very economical and sustainable. It is well understood that livestock wastes are comparable, if not better, nutrient sources for crops as chemical fertilizers. However, the large concentrated volumes of animal manure produced from livestock operations and the limited amount of available nearby agricultural land areas necessitated the need for volume reduction of these animal wastes. Composting of these animal manures is a viable option for biomass and pathogenic reduction in the environment. Nevertheless, composting also increases the potential loss of available nutrients for crop production as well as unwanted emission of anthropogenic air pollutants due to the loss of ammonia and other compounds via volatilization. In this study, we examine the emission of ammonia and nitrous oxide from swine manure windrows to evaluate the benefit of biomass reduction in conjunction with the potential loss of available nutrients. The feedstock for the windrows was obtained from swine farm in Kentucky where swine manure was mixed with wood shaving as absorbent material. Static flux chambers along with photoacoustic gas analyzer were used to monitor ammonia and nitrous oxide concentrations during the composting process. The results show that ammonia and nitrous oxide fluxes were quite high during the initial composting process and after the turning of each compost pile. Over the period of roughly three months of composting, the biochemical oxygen demand (BOD) decreased by about 90%. Although composting of animal waste is quite beneficial for biomass reduction, composting may not be economically feasible from an agronomical point of view due to time, nutrient loss (N loss), and potential environmental pollution (ammonia and greenhouse gas emissions). Therefore, additional studies are needed to assess and validate the economics and environmental impact of animal (swine) manure composting (e.g., crop yield or impact on climate change).

Keywords: windrow, swine manure, ammonia, nitrous oxide, fluxes, management

Procedia PDF Downloads 346

Authors: Soheila Sadeghi

Abstract:

Construction projects are complex and often subject to significant cost overruns due to the multifaceted nature of the activities involved. Accurate cost estimation is crucial for effective budget planning and resource allocation. Traditional methods for predicting overruns often rely on expert judgment or analysis of historical data, which can be time-consuming, subjective, and may fail to consider important factors. However, with the increasing availability of data from construction projects, machine learning techniques can be leveraged to improve the accuracy of overrun predictions. This study applied machine learning algorithms to enhance the prediction of cost overruns in a case study of a construction project. The methodology involved the development and evaluation of two machine learning models: Random Forest and Neural Networks. Random Forest can handle high-dimensional data, capture complex relationships, and provide feature importance estimates. Neural Networks, particularly Deep Neural Networks (DNNs), are capable of automatically learning and modeling complex, non-linear relationships between input features and the target variable. These models can adapt to new data, reduce human bias, and uncover hidden patterns in the dataset. The findings of this study demonstrate that both Random Forest and Neural Networks can significantly improve the accuracy of cost overrun predictions compared to traditional methods. The Random Forest model also identified key cost drivers and risk factors, such as changes in the scope of work and delays in material delivery, which can inform better project risk management. However, the study acknowledges several limitations. First, the findings are based on a single construction project, which may limit the generalizability of the results to other projects or contexts. Second, the dataset, although comprehensive, may not capture all relevant factors influencing cost overruns, such as external economic conditions or political factors. Third, the study focuses primarily on cost overruns, while schedule overruns are not explicitly addressed. Future research should explore the application of machine learning techniques to a broader range of projects, incorporate additional data sources, and investigate the prediction of both cost and schedule overruns simultaneously.

Keywords: resource allocation, machine learning, optimization, data-driven decision-making, project management

Procedia PDF Downloads 23

Authors: Wissal Ben Arfi, Jean-Michel Sahut

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The purpose of this paper is to provide a deeper understanding of the succession process from a knowledge management perspective. By doing that, succession process in family businesses, as an environment for creating and sharing knowledge, was explored. Design/Methodology/Approach: To support our reasoning, we collected qualitative data through 16 in-depth interviews conducted with all decision makers involved in the family businesses succession process in France. These open-ended responses were subsequently exposed to thematic discourse analysis. Findings: Central to this exhibit is the nature and magnitude of knowledge creation and sharing among the actors within the family succession context and how can tacit knowledge sharing facilitate the succession process. We also identified factors that inhibit down the knowledge creation and sharing processes. The sharing and creation of knowledge among members of a family business appear to be a complex process that must be part of a strategy for change. This implies that it requests trust and takes a certain amount of time because it requires organizational change and a clear and coherent strategic vision that is accepted and assimilated by all the members. Professional and leadership skills are of particular importance in knowledge sharing and creation processes. In most cases, tacit knowledge is crucial when it is shared and accumulated collectively. Our findings reveal that managers should find ways of implementing knowledge sharing and creation processes while acknowledging the succession process within family firms. This study highlights the importance of generating knowledge strategies in order to enhance the performance and the success of intergenerational succession. The empirical outcomes contribute to enrich the field of succession management process and enhance the role of knowledge in shaping family performance and longevity. To a large extent, the lessons learned from the study of succession processes in family-owned businesses are that when there is a deliberate effort to introduce a knowledge-based approach, this action becomes a seminal event in the life of the organization. Originality/Value: The paper contributes to the deep understanding of interactions among actors by examining the knowledge creation and sharing processes since current researches in family succession focused on aspects such as personal development of potential, intra-family succession intention, decision-making processes in family businesses. Besides, as succession is one of the key factors that determine the longevity and the performance of family businesses, it also contributes to literature by examining how tacit knowledge is transferred, shared and created in family businesses and how this can facilitate the intergenerational succession process.

Keywords: family-owned businesses, succession process, knowledge, performance

Procedia PDF Downloads 199

Authors: Bojana Horvat, Barbara Karleusa, Goran Volf, Nevenka Ozanic, Ivica Kisic

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Forest fire is a major threat in many regions in Croatia, especially in coastal areas. Although they are often caused by natural processes, the most common cause is the human factor, intentional or unintentional. Forest fires drastically transform landscapes and influence natural processes. The main goal of the presented research is to analyse and quantify the impact of the forest fire on hydrological processes and propose the model that best describes changes in hydrological patterns in the analysed catchments. Keeping in mind the spatial component of the processes, geospatial analysis is performed to gain better insight into the spatial variability of the hydrological response to disastrous events. In that respect, two catchments that experienced severe forest fire were delineated, and various hydrological and meteorological data were collected both attribute and spatial. The major drawback is certainly the lack of hydrological data, common in small torrential karstic streams; hence modelling results should be validated with the data collected in the catchment that has similar characteristics and established hydrological monitoring. The event chosen for the modelling is the forest fire that occurred in July 2019 and burned nearly 10% of the analysed area. Surface (land use/land cover) conditions before and after the event were derived from the two Sentinel-2 images. The mapping of the burnt area is based on a comparison of the Normalized Burn Index (NBR) computed from both images. To estimate and compare hydrological behaviour before and after the event, curve number (CN) values are assigned to the land use/land cover classes derived from the satellite images. Hydrological modelling resulted in surface runoff generation and hence prediction of hydrological responses in the catchments to a forest fire event. The research was supported by the Croatian Science Foundation through the project 'Influence of Open Fires on Water and Soil Quality' (IP-2018-01-1645).

Keywords: Croatia, forest fire, geospatial analysis, hydrological response

Procedia PDF Downloads 122

Authors: Timothy Adam Boleratzky

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The goal of this transformative endeavour lies in the repurposing of textile scraps, heralding a renaissance in the creation of wearable art. Through a judicious fusion of Life Cycle Assessment (LCA) methodologies and cutting-edge techniques, this research embarks upon a voyage of exploration, unraveling the intricate tapestry of environmental implications woven into the fabric of textile waste. Delving deep into the annals of empirical evidence and scholarly discourse, the study not only elucidates the urgent imperative for waste reduction strategies but also unveils the transformative potential inherent in embracing circular economy principles within the hallowed halls of fashion. As the research unfurls its sails, guided by the compass of sustainability, it traverses uncharted territories, charting a course toward a more enlightened and responsible fashion ecosystem. The canvas upon which this journey unfolds is richly adorned with insights gleaned from the crucible of experimentation, laying bare the myriad pathways toward waste minimisation and resource optimisation. From the adoption of recycling strategies to the cultivation of eco-friendly production techniques, the research endeavours to sculpt a blueprint for a more sustainable future, one stitch at a time. In this unfolding narrative, the role of wearable art emerges as a potent catalyst for change, transcending the boundaries of conventional fashion to embrace a more holistic ethos of sustainability. Through the alchemy of creativity and craftsmanship, discarded textile scraps are imbued with new life, morphing into exquisite creations that serve as both a testament to human ingenuity and a rallying cry for environmental preservation. Each thread, each stitch, becomes a silent harbinger of change, weaving together a tapestry of hope in a world besieged by ecological uncertainty. As the research journey culminates, its echoes resonate far beyond the confines of academia, reverberating through the corridors of industry and beyond. In its wake, it leaves a legacy of empowerment and enlightenment, inspiring a generation of designers, entrepreneurs, and consumers to embrace a more sustainable vision of fashion. For in the intricate interplay of threads and textiles lies the promise of a brighter, more resilient future, where beauty coexists harmoniously with responsibility and where fashion becomes not merely an expression of style but a celebration of sustainability.

Keywords: fabric-manipulation, sustainability, textiles, waste, wearable-art

Procedia PDF Downloads 24

Authors: Afshin Kadri

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Using Renewable Energy Resources (RES) as a type of DG unit is developing in distribution systems. The connection of these generation units to existing AC distribution systems changes the structure and some of the operational aspects of these grids. Most of the RES requires to power electronic-based interfaces for connection to AC systems. These interfaces consist of at least one DC/AC conversion unit. Nowadays, grid-connected inverters must have the required feature to support the grid under sag voltage conditions. There are two curves in these conditions that show the magnitude of the reactive component of current as a function of voltage drop value and the required minimum time value, which must be connected to the grid. This feature is named low voltage ride-through (LVRT). Implementing this feature causes problems in the operation of the inverter that increases the amplitude of high-frequency components of the injected current and working out of maximum power point in the photovoltaic panel connected inverters are some of them. The important phenomenon in these conditions is ripples in the DC bus voltage that affects the operation of the inverter directly and indirectly. The losses of DC bus capacitors which are electrolytic capacitors, cause increasing their temperature and decreasing its lifespan. In addition, if the inverter is connected to the photovoltaic panels directly and has the duty of maximum power point tracking, these ripples cause oscillations around the operating point and decrease the generating energy. Using a bidirectional converter in the DC bus, which works as a buck and boost converter and transfers the ripples to its DC bus, is the traditional method to eliminate these ripples. In spite of eliminating the ripples in the DC bus, this method cannot solve the problem of reliability because it uses an electrolytic capacitor in its DC bus. In this work, a control method is proposed which uses the bidirectional converter as the fourth leg of the inverter and eliminates the DC bus ripples using an injection of unbalanced currents into the grid. Moreover, the proposed method works based on constant power control. In this way, in addition, to supporting the amplitude of grid voltage, it stabilizes its frequency by injecting active power. Also, the proposed method can eliminate the DC bus ripples in deep voltage drops, which cause increasing the amplitude of the reference current more than the nominal current of the inverter. The amplitude of the injected current for the faulty phases in these conditions is kept at the nominal value and its phase, together with the phase and amplitude of the other phases, are adjusted, which at the end, the ripples in the DC bus are eliminated, however, the generated power decreases.

Keywords: renewable energy resources, voltage drop value, DC bus ripples, bidirectional converter

Procedia PDF Downloads 61

Authors: Omar Qaftan

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Earthquakes can cause tremendous loss of human life and can result in severe damage to a several of civil engineering structures especially the tall buildings. The response of a multistory structure subjected to earthquake loading is a complex task, and it requires to be studied by physical and numerical modelling. For many circumstances, the scale models on shaking table may be a more economical option than the similar full-scale tests. A shaking table apparatus is a powerful tool that offers a possibility of understanding the actual behaviour of structural systems under earthquake loading. It is required to use a set of scaling relations to predict the behaviour of the full-scale structure. Selecting the scale factors is the most important steps in the simulation of the prototype into the scaled model. In this paper, the principles of scaling modelling procedure are explained in details, and the simulation of scaled multi-storey concrete structure for dynamic studies is investigated. A procedure for a complete dynamic simulation analysis is investigated experimentally and numerically with a scale factor of 1/50. The frequency domain accounting and lateral displacement for both numerical and experimental scaled models are determined. The procedure allows accounting for the actual dynamic behave of actual size porotype structure and scaled model. The procedure is adapted to determine the effects of the tall multi-storey structure on a raft foundation. Four generated accelerograms were used as inputs for the time history motions which are in complying with EC8. The output results of experimental works expressed regarding displacements and accelerations are compared with those obtained from a conventional fixed-base numerical model. Four-time history was applied in both experimental and numerical models, and they concluded that the experimental has an acceptable output accuracy in compare with the numerical model output. Therefore this modelling methodology is valid and qualified for different shaking table experiments tests.

Keywords: structure, raft, soil, interaction

Procedia PDF Downloads 124

Authors: Alessandro Suardi, Rodolfo Picchio, Domenico Coaloa, Maria Bonaventura Forleo, Nadia Palmieri, Luigi Pari

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The reconversion process of the Italian sugar supply chain to bio-energy supply chains, as a result of the 2006 Sugar CMO reform, have involved research to define the best logistics, the most adapted energy crops for the Italian territory and their sustainability. Rapeseed (Brassica napus L.), Giant reed (Arundo donax L.) and Poplar (Poplar ssp.) are energy crops considered strategic for the development of Italian energy supply-chains. This study analyzed the environmental and the economic impacts on the farm level of these three energy crops. The environmental assessment included six farming units, two per crop, which were extracted from a sample of 251 rapeseed farm units (2751 ha), 7 giant reed farm units (7.8 ha), and 91 poplar farm units (440 ha) using a statistical multivariate analysis. Life Cycle Assessment (LCA) research method has been used to evaluate and compare the sustainability of the agricultural phases of the crops studied. The impact analyses have been performed at mid-point and end-point levels. The results of the analysis shown that the fertilization, is the major source of environmental impact of the agricultural phase due to the production of the fertilizers and the soil emissions of GHG following the treatment. The perennial energy crops studied (Arundo donax L., Poplar ssp.) were environmentally more sustainable if compared with the annual crop (Brassica napus L.) for all the impact categories at mid-point and end-point levels analyzed. The most relevant impact category influenced by the agricultural process result the fossil depletion, mainly due to the fossil fuels consumed during the mineral fertilizers production (urea). Human health was the most affected damage category at the end point level. Poplar result the energy crop with the best environmental performance for the Italian territory, in the distribution areas most suitable for its cultivation.

Keywords: LCA, energy crops, rapeseed, giant reed, poplar

Procedia PDF Downloads 469

Authors: Ignacio W. Loor

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In the context of informal settlements in Quito, this paper provides evidence that slopes and deep ravines typical of Andean cities, around which marginalized urban communities sit, constitute a platform for green infrastructure that supports mobility for pedestrians in an incremental fashion. This is informally shaped green infrastructure that provides connectivity to other mobility infrastructures such as roads and public transport, which permits relegated dwellers reach their daily destinations and reclaim their rights to the city. This is relevant in that walking has been increasingly neglected as a viable mean of transport in Latin American cities, in favor of rather motorized means, for which the mobility benefits of green infrastructure have remained invisible to policymakers, contributing to the progressive isolation of informal settlements. This research leverages greatly on an ecological rejuvenation programme led by the municipality of Quito and the Andean Corporation for Development (CAN) intended for rehabilitating the ecological functionalities of ravines. Accordingly, four ravines in different stages of rejuvenation were chosen, in order to through ethnographic methods, capture the practices they support to dwellers of informal settlements across different stages, particularly in terms of issues of mobility. Then, by presenting fragments of interviews, description of observed phenomena, photographs and narratives published in institutional reports and media, the production process of mobility infrastructure over unoccupied slopes and ravines, and the roles that this infrastructure plays in the mobility of dwellers and their quotidian practices are explained. For informal settlements, which normally feature scant urban infrastructure, mobility embodies an unfavourable driver for the possibilities of dwellers to actively participate in the social, economic and political dimensions of the city, for which their rights to the city are widely neglected. Nevertheless, informal green infrastructure for mobility provides some alleviation. This infrastructure is incremental, since its features and usability gradually evolves as users put into it knowledge, labour, devices, and connectivity to other infrastructures in different dimensions which increment its dependability. This is evidenced in the diffusion of knowledge of trails and routes of footpaths among users, the implementation of linking stairs and bridges, the improved access by producing public spaces adjacent to the ravines, the illuminating of surrounding roads, and ultimately, the restoring of ecological functions of ravines. However, the perpetuity of this type of infrastructure is also fragile and vulnerable to the course of urbanisation, densification, and expansion of gated privatised spaces.

Keywords: green infrastructure, informal settlements, urban mobility, walkability

Procedia PDF Downloads 145

Authors: S. Jayalakshmi, Gayathri S., Subiksa V., Nithyasri P., Agasthiya

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Paleochannels are the buried part of an active river system which was separated from the active river channel by the process of cutoff or abandonment during the dynamic evolution of the active river. Over time, they are filled by young unconsolidated or semi-consolidated sediments. Additionally, it is impacted by geo morphological influences, lineament alterations, and other factors. The primary goal of this study is to identify the paleochannels in Periyar river basin for the year 2023. Those channels has a high probability in the presence of natural resources, including gold, platinum,tin,an duranium. Numerous techniques are used to map the paleochannel. Using the optical data, Satellite images were collected from various sources, which comprises multispectral satellite images from which indices such as Normalized Difference Vegetation Index (NDVI),Normalized Difference Water Index (NDWI), Soil Adjusted Vegetative Index (SAVI) and thematic layers such as Lithology, Stream Network, Lineament were prepared. Weights are assigned to each layer based on its importance, and overlay analysis has done, which concluded that the northwest region of the area has shown some paleochannel patterns. The results were cross-verified using the results obtained using microwave data. Using Sentinel data, Synthetic Aperture Radar (SAR) Image was extracted from European Space Agency (ESA) portal, pre-processed it using SNAP 6.0. In addition to that, Polarimetric decomposition technique has incorporated to detect the paleochannels based on its scattering property. Further, Principal component analysis has done for enhanced output imagery. Results obtained from optical and microwave radar data were compared and the location of paleochannels were detected. It resulted six paleochannels in the study area out of which three paleochannels were validated with the existing data published by Department of Geology and Environmental Science, Kerala. The other three paleochannels were newly detected with the help of SAR image.

Keywords: paleochannels, optical data, SAR image, SNAP

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Authors: Marcio Freire Cruz, Naoaki Ono, Shigehiko Kanaya, Carlos Arthur Mattos Teixeira Cavalcante

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The systems that record patient care information, known as Electronic Medical Record (EMR) and those that monitor vital signs of patients, such as heart rate, body temperature, and blood pressure have been extremely valuable for the effectiveness of the patient’s treatment. Several kinds of research have been using data from EMRs and vital signs of patients to predict illnesses. Among them, we highlight those that intend to predict, classify, or, at least identify patterns, of sepsis illness in patients under vital signs monitoring. Sepsis is an organic dysfunction caused by a dysregulated patient's response to an infection that affects millions of people worldwide. Early detection of sepsis is expected to provide a significant improvement in its treatment. Preceding works usually combined medical, statistical, mathematical and computational models to develop detection methods for early prediction, getting higher accuracies, and using the smallest number of variables. Among other techniques, we could find researches using survival analysis, specialist systems, machine learning and deep learning that reached great results. In our research, patients are modeled as points moving each hour in an n-dimensional space where n is the number of vital signs (variables). These points can reach a sepsis target point after some time. For now, the sepsis target point was calculated using the median of all patients’ variables on the sepsis onset. From these points, we calculate for each hour the position vector, the first derivative (velocity vector) and the second derivative (acceleration vector) of the variables to evaluate their behavior. And we construct a prediction model based on a Long Short-Term Memory (LSTM) Network, including these derivatives as explanatory variables. The accuracy of the prediction 6 hours before the time of sepsis, considering only the vital signs reached 83.24% and by including the vectors position, speed, and acceleration, we obtained 94.96%. The data are being collected from Medical Information Mart for Intensive Care (MIMIC) Database, a public database that contains vital signs, laboratory test results, observations, notes, and so on, from more than 60.000 patients.

Keywords: dynamic analysis, long short-term memory, prediction, sepsis

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Authors: Mohamed Trigui, Fatma Masmoudi, Imen Zouari

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Massive utilizations of chemical fertilizer and chemical pesticides in agriculture sector to improve the farming productivity have created increasing environmental damages. Then, agriculture must become sustainable, focusing on production systems that respect the environment and help to reduce climate change. Isolation and microbial identification of new bacterial strains from naturally saline habitats and compost extracts could be a prominent way in pest management and crop production under saline conditions. In this study, potential mechanisms involved in plant growth promotion and suppressive activity against fungal diseases of a compost extract produced from poultry manure/olive husk compost and halotolerant and halophilic bacterial strains under saline stress were investigated. On the basis of the antimicrobial tests, different strains isolated from Sfax solar saltern (Tunisia) and from compost extracts were selected and tested for their plant growth promoting traits, such as siderophores production, nitrogen fixation, phosphate solubilization and the production of extracellular hydrolytic enzymes (protease and lipase) under in-vitro conditions. Among 450 isolated bacterial strains, 16 isolates showed potent antifungal activity against the tested plant pathogenic fungi. Their identification based on 16S rRNA gene sequence revealed they belonged to different species. Some of these strains were also characterized for their plant growth promoting capacities. Obtained results showed the ability of four strains belonging to Bacillus genesis to ameliorate germination rate and root elongation compared to the untreated positive controls. Combinatorial capacity of halotolerant bacteria with antimicrobial activity and plant growth promoting traits could be promising sources of interesting bioactive substances under saline stress.

Keywords: abiotic stress, biofertilizer, biotic stress, compost extract, halobacteria, plant growth promoting (PGP), soil fertility

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Authors: Huinan Zhang, Wenjie Jiang

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Accurate estimation of tropical cyclone intensity is of great importance for disaster prevention and mitigation. Existing techniques are largely based on satellite imagery data, and research and utilization of the inner thermal core structure characteristics of tropical cyclones still pose challenges. This paper presents a two-stage tropical cyclone intensity estimation network based on the fusion of coarse and fine-grained features from microwave brightness temperature data. The data used in this network are obtained from the thermal core structure of tropical cyclones through the Advanced Technology Microwave Sounder (ATMS) inversion. Firstly, the thermal core information in the pressure direction is comprehensively expressed through the maximal intensity projection (MIP) method, constructing coarse-grained thermal core images that represent the tropical cyclone. These images provide a coarse-grained feature range wind speed estimation result in the first stage. Then, based on this result, fine-grained features are extracted by combining thermal core information from multiple view profiles with a distributed network and fused with coarse-grained features from the first stage to obtain the final two-stage network wind speed estimation. Furthermore, to better capture the long-tail distribution characteristics of tropical cyclones, focal loss is used in the coarse-grained loss function of the first stage, and ordinal regression loss is adopted in the second stage to replace traditional single-value regression. The selection of tropical cyclones spans from 2012 to 2021, distributed in the North Atlantic (NA) regions. The training set includes 2012 to 2017, the validation set includes 2018 to 2019, and the test set includes 2020 to 2021. Based on the Saffir-Simpson Hurricane Wind Scale (SSHS), this paper categorizes tropical cyclone levels into three major categories: pre-hurricane, minor hurricane, and major hurricane, with a classification accuracy rate of 86.18% and an intensity estimation error of 4.01m/s for NA based on this accuracy. The results indicate that thermal core data can effectively represent the level and intensity of tropical cyclones, warranting further exploration of tropical cyclone attributes under this data.

Keywords: Artificial intelligence, deep learning, data mining, remote sensing

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Authors: Noura El-Ahmady El-Naggar

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Among the antitumour drugs, bacterial enzyme L-asparaginase has been employed as the most effective chemotherapeutic agent in pediatric oncotherapy especially for acute lymphoblastic leukemia. Glutaminase free L-asparaginase producing actinomycetes were isolated from soil samples collected from Egypt. Among them, a potential culture, strain NEAE-119, was selected and identified on the basis of morphological, cultural, physiological and biochemical properties, together with 16S rDNA sequence as Streptomyces olivaceus NEAE-119 and sequencing product(1509 bp) was deposited in the GenBank database under accession number KJ200342. The optimization of different process parameters for L-asparaginase production by Streptomyces olivaceus NEAE-119 using Plackett–Burman experimental design and response surface methodology was carried out. Fifteen nutritional variables (temperature, pH, incubation time, inoculum size, inoculum age, agitation speed, dextrose, starch, L-asparagine, KNO3, yeast extract, K2HPO4, MgSO4.7H2O, NaCl and FeSO4. 7H2O) were screened using Plackett–Burman experimental design. The most positive significant independent variables affecting enzyme production (temperature, inoculum age and agitation speed) were further optimized by the central composite face-centered design -response surface methodology. As a result, a medium of the following formula is the optimum for producing an extracellular L-asparaginase in the culture filtrate of Streptomyces olivaceus NEAE-119: Dextrose 3g, starch 20g, L-asparagine 10g, KNO3 1g, K2HPO4 1g, MgSO4.7H2O 0.1g, NaCl 0.1g, pH 7, temperature 37°C, agitation speed 200 rpm/min, inoculum size 4%, v/v, inoculum age 72 h and fermentation period 5 days.

Keywords: Streptomyces olivaceus NEAE-119, glutaminase free L-asparaginase, production, Plackett-Burman design, central composite face-centered design, 16S rRNA, scanning electron microscope

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Authors: Amina Beldjazia, Djamel Alatou, Khaled Missaoui

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The forest of Mahouna is a part of the mountain range of the Tell Atlas in the northeast of Algeria. It is characterized by a significant biodiversity. The management of this resource requires thorough the understanding of the current state of the vegetation (inventories), degradation factors and ongoing monitoring of the various long-term ecological changes. Digital mapping is a very effective way to in-depth knowledge of natural resources. The realization of a vegetation map based on satellite images, aerial photographs and the use of geographic information system (GIS), shows large values results of the vegetation of the massif in the scientific view point (the development of a database of the different formations that exist on the site, ecological conditions) and economic (GIS facilitate our task of managing the various resources and diversity of the forest). The methodology is divided into three stages: the first involves an analysis of climate data (1988 to 2013); the second is to conduct field surveys (soil and phytoecological) during the months of June and July 2013 (10 readings), the third is based on the development of different themes and synthetic cards by software of GIS (ENVI 4.6 and 10 ARCMAP). The results show: cork oak covers an area of 1147 ha. Depending on the environmental conditions, it rests on sandstone and individualizes between 3 layers of vegetation from thermo-mediterranean (the North East part with 40ha), meso-Mediterranean (1061 ha) and finally the supra-Mediterranean (46ha ). The map shows the current actual state of the cork oak forest massif of Mahouna, it is an older forest (>150 years) where regeneration is absent because of several factors (fires, overgrazing, leaching, erosion, etc.). The cork oak is in the form of dense forest with Laburnum and heather as the dominant species. It may also present in open forest dominated by scrub species: Daphne gniduim, Erica arborea, Calycotome spinosa, Phillyrea angustifolia, Lavandula stoechas, Cistus salvifolius.

Keywords: biodiversity, environmental, Mahouna, Cork oak

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Authors: Yamma Rose, Kone Martine, Yonli Arsène, Wanko Ngnien Adrien

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Soil pollution and, consequently, water resources by micropollutants from gold mine tailings constitute a major threat in developing countries due to the lack of waste treatment. Phytoremediation is an alternative for extracting or trapping micropollutants from contaminated soils by mining residues. The potentialities of Chrysopogon zizanioides (acclimated plant) and Andropogon gayanus (native plant) to accumulate arsenic (As), mercury (Hg), iron (Fe) and zinc (Zn) were studied in artisanal gold mine in Ouagadougou, Burkina Faso. The phytoremediation effectiveness of two plant species was studied in 75 pots of 30 liters each, containing mining residues from the artisanal gold processing site in the rural commune of Nimbrogo. The experiments cover three modalities: Tn - planted unpolluted soils; To – unplanted mine tailings and Tp – planted mine tailings arranged in a randomized manner. The pots were amended quarterly with compost to provide nutrients to the plants. The phytoremediation assessment consists of comparing the growth, biomass and capacity of these two herbaceous plants to extract or to trap Hg, Fe, Zn and As in mining residues in a controlled environment. The analysis of plant species parameters cultivated in mine tailings shows indices of relative growth of A. gayanus very significantly high (34.38%) compared to 20.37% for C.zizanioides. While biomass analysis reveals that C. zizanioides has greater foliage and root system growth than A. gayanus. The results after a culture time of 6 months showed that C. zizanioides and A. gayanus have the potential to accumulate Hg, Fe, Zn and As. Root biomass has a more significant accumulation than aboveground biomass for both herbaceous species. Although the BCF bioaccumulation factor values for both plants together are low (<1), the removal efficiency of Hg, Fe, Zn and As is 45.13%, 42.26%, 21.5% and 2.87% respectively in 24 weeks of culture with C. zizanioides. However, pots grown with A. gayanus gives an effectiveness rate of 43.55%; 41.52%; 2.87% and 1.35% respectively for Fe, Zn, Hg and As. The results indicate that the plant species studied have a strong phytoremediation potential, although that of A. gayanus is relatively less than C. zizanioides.

Keywords: artisanal gold mine tailings, andropogon gayanus, chrysopogon zizanioides, phytoremediation

Procedia PDF Downloads 52

Authors: Mahendran Ganesan, Sanjeet Kumar Verma, Zafar Iqbal, Ashish Chandran, Zakir Husain, Shama Afroz, Sana Shahid, Laiq Ur Rahman

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Highly efficient in vitro regeneration system has been developed for Swertia chirayita (Roxb. ex Fleming) H. Karst, a high prized traditional medicinal plant to treat numerous ailments such as liver disorders, malaria and diabetes and are reported to have a wide spectrum of pharmacological properties. Its medicinal usage is well-documented in Indian pharmaceutical codex, the British and the American pharmacopeias, and in different traditional medicine such as the Ayurveda, Unani and Siddha medical systems. Nodal explants were cultured on MS medium supplemented with various phytohormones for multiple shoot induction. The nodal segments failed to respond in growth regulator free medium. All the concentrations of BAP, Kin and TDZ facilitated shoot bud break and multiple shoot induction. Among the various cytokinins tested, BAP was found to be more effective with respect to initiation and subsequent development of shoots. Of the various concentrations BAP tested, BAP at 4.0 mg/L showed the higher average number of shoot regeneration (10.80 shoots per explant). Kin at 4 mg/L and TDZ at 4 mg/L induced 5.70 and 04.5+0 shoots per explant, respectively. Further increase in concentration did not favour an increase in the number of shoots. However, these shoots failed to elongate further. Hence, addition of GA₃ (1 mg/L) was added to the above medium. This treatment resulted in the elongation of shoots (2.50 cm) and a further increase in the number of microshoots (34.20 shoots/explant). Roots were also induced in the same medium containing BAP (4 mg/L) + GA₃ (1 mg/L) + NAA (0.5 mg/L). In vitro derived plantlets with well-developed roots were transferred to the potting media containing garden soil: sand: vermicompost (2:1:1). Plantlets were covered with a polyethylene bag and irrigated with water. The pots were maintained at 25 ± 2ºC, and then the polyethylene cover was gradually loosened, thus dropping the humidity (65–70%). This procedure subsequently resulted in in vitro hardening of the plantlet.

Keywords: micropropagation, nodal explant, plant growth regulators, Swertia chirayita

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Authors: Ujala, Diksha Sharma, Mahinder Partap, Ashish R. Warghat, Bhavya Bhargava

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In soil-less agriculture, hydroponic is considered a potential farming system for the production of uniform quality plant material in significantly less time. Therefore, for the first time, the current investigation corroborates the effect of different cultivation conditions (open-field, poly-house, and hydroponic) on morpho-physiological traits, phenolic content, and essential oil components analysis in three flower color variants (yellow, scarlet red, and orange) of Tagetes patula. The results revealed that the maximum plant height, number of secondary branches, number of flowers, photosynthesis, stomatal conductance, and transpiration rate were observed under the hydroponic system as compared to other conditions. However, the maximum content of gallic acid (0.82 mg/g DW), syringic acid (3.98 mg/g DW), epicatechin (0.48 mg/g DW), p-coumaric acid (7.28 mg/g DW), protocatechuic acid (0.59 mg/g DW), ferulic acid (2.58 mg/g DW), and luteolin (8.24 mg/g DW) were quantified maximally under open-field conditions. However, under hydroponic conditions, the higher content of vanillic acid (0.43 mg/g DW), caffeic acid (0.49 mg/g DW), and quercetin (0.92 mg/g DW) were quantified. Moreover, a total of nineteen volatile components were identified in the essential oil of different flower color variants of T. patula cultivated under different conditions. The major reported volatile components in essential oil were (-)-caryophyllene oxide, trans-β-caryophyllene, trans-geraniol, 3 methyl-benzyl alcohol, and 2,2’:5’,2”-terthiophene. It has also been observed that the volatile component percentage range in all variants was observed in open-field (70.85 % to 90.54 %), poly-house (59.03 % to 77.93 %), and hydroponic (68.78 % to 89.41 %). In conclusion, the research highlighted that morpho-physiological performance with flower production was enhanced in the hydroponic system. However, phenolic content and volatile components were maximally observed in open-field conditions. However, significant results have been reported under hydroponic conditions in all studied parameters, so it could be a potential strategy for quality biomass production in T. patula.

Keywords: Tagetes patula, cultivation conditions, hydroponic, morpho-physiology

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Authors: Cheryl-Ann Sarita Boodram

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Historically, the movement of people has been the subject of socio-political and economic regulatory policies which congeal to regulate human mobility and establish geopolitical and spatial identities and borderlands. As migratory practices evolved, so too has the problematization associated with movement, migration and citizenship. The emerging trends have led to active development of immigration technology governing human mobility and the naming of migratory practices. One such named phenomenon is ‘deportation’ or the forced removal of individuals from their adopted country. Deportation, has gained much attention within the human mobility landscape in the past twenty years following the September 2001 terrorist attack on the World Trade Centre in New York. In a reactionary move, several metropolitan countries, including Canada and the United Kingdom enacted or reviewed immigration laws which further enabled the removal of foreign born criminals to the land of their birth in the global south. Existing studies fall short of understanding the multiple textures of the forced returned migration experiences and the social injustices resulting from deportation displacement. This study brings together indigenous research methodologies through the use of participatory action research and social work with returned migrants in Trinidad and Tobago to uncover the experiences of displacement of deported nationals. The study explores the experiences of negotiating life as a ‘stranger’ and how return has influenced the construction of identities of returned nationals. Findings from this study reveal that deportation has led to inequalities and facilitated ‘othering’ of this group within their own country of birth. The study further highlighted that deportation leads to circuits of dispossession, and perpetuates inequalities. This study provides original insights into the way returned migrants negotiate, map and embody ‘strangeness’ and manage their return to a soil they consider unfamiliar and alien.

Keywords: stranger, alien geographies, displacement, deportation, negotiating strangeness, identity, otherness, alien landscapes

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Authors: Vathanachannbo Veth, Ilan Ich, Sophea Rom Phy, Ty Sok, Layheang Song, Sophal Try, Chantha Oeurng

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Climate change is one of the major global challenges inducing disaster risks and threatening livelihoods and communities through adverse impacts on food and water security, ecosystems, and services. Prek Thnot River Basin of Cambodia is one of the largest tributaries in the Lower Mekong that has been exposed to hazards and disasters, particularly floods and is said to be the effect of climate change. Therefore, the assessment of precipitation and streamflow changes under the effect of climate change was proposed in this river basin using Soil Water Assessment Tool (SWAT) model and different flow indices under baseline (1997 to 2011) and climate change scenarios (RCP2.6 and RCP8.5 with three General Circulation Models (GCMs): GFDL, GISS, and IPSL) in two time-horizons: near future (the 2030s: 2021 to 2040) and medium future (2060s: 2051 to 2070). Both intensity and frequency indices compared with the historical extreme rainfall indices significantly change in the GFDL under the RCP8.5 for both 2030s and 2060s. The average rate change of Rx1day, Rx10day, SDII, and R20mm in the 2030s and 2060s of both RCP2.6 and RCP8.5 was found to increase in GFDL and decrease in both GISS and IPSL. The mean percentage change of the flow analyzed in the IHA tool (Group1) indicated that the flow in the Prek Thnot River increased in GFDL for both RCP2.6 and RCP8.5 in both 2030s and 2060s, oppositely in GISS, the flow decreases. Moreover, the IPSL affected the flow by increasing in five months (January, February, October, November, and December), and in the other seven months, the flow decreased accordingly. This study provides water resources managers and policymakers with a wide range of precipitation and water flow projections within the Prek Thnot River Basin in the context of plausible climate change scenarios.

Keywords: IHA, climate change, disaster risk, Prek Thnot River Basin, Cambodia

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Authors: Joana Mourão

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Transition to a low carbon economy requires changes in consumption and production patterns, including the improvement of existing buildings’ environmental performance. Urban rehabilitation is a top policy priority in Europe, creating an opportunity to increase this performance. However, urban rehabilitation comprises different typologies of interventions with distinct levels of consideration for cultural urban heritage values and for environmental values, thus with different impacts. Cities rely on both material and non-material forms of heritage that are deep-rooted and resilient. One of the most relevant parts of that urban heritage is the historical pre-industrial housing stock, with an extensive presence in many European cities, as Lisbon. This stock is rehabilitated and transformed at the framework of urban management and local governance traditions, as well as the framework of the global economy, and in that context, faces opportunities and threats that need evaluation and control. The scope of this article is to define methodological bases and research lines for the assessment of impacts that urban rehabilitation initiatives set on the vulnerable and historical pre-industrial urban housing stock, considering it as an environmental and cultural unreplaceable material value and resource. As a framework, this article reviews the concepts of urban regeneration, urban renewal, current buildings conservation and refurbishment, and energy refurbishment of buildings, seeking to define key typologies of urban rehabilitation that represent different approaches to the urban fabric, in terms of scope, actors, and priorities. Moreover, main types of interventions - basing on a case-study in a XVIII century neighborhood in Lisbon - are defined and analyzed in terms of the elements lost in each type of intervention, and relating those to urbanistic, architectonic and constructive values of urban heritage, as well as to environmental and energy efficiency. Further, the article overviews environmental cultural heritage assessment and life-cycle assessment tools, selecting relevant and feasible impact assessment criteria for urban buildings rehabilitation regulation, focusing on multi-level urban heritage integrity. Urbanistic, architectonic, constructive and energetic integrity are studied as criteria for impact assessment and specific indicators are proposed. The role of these criteria in sustainable urban management is discussed. Throughout this article, the key challenges for urban rehabilitation planning and management, concerning urban built heritage as a resource for sustainability, are discussed and clarified.

Keywords: urban rehabilitation, impact assessment criteria, buildings integrity, embodied energy

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Authors: Oluwatosin M. A. Jesuyon

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In order to propose a simpler tool that eliminates the age-long problems associated with the traditional index method for selection of multiple traits in broilers, the Barttlet factor regression equation is being proposed as an alternative selection tool. 100 day-old chicks each of Arbor Acres (AA) and Annak (AN) broiler strains were obtained from two rival hatcheries in Ibadan Nigeria. These were raised in deep litter system in a 56-day feeding trial at the University of Ibadan Teaching and Research Farm, located in South-west Tropical Nigeria. The body weight and body dimensions were measured and recorded during the trial period. Eight (8) zoometric measurements namely live weight (g), abdominal circumference, abdominal length, breast width, leg length, height, wing length and thigh circumference (all in cm) were recorded randomly from 20 birds within strain, at a fixed time on the first day of the new week respectively with a 5-kg capacity Camry scale. These records were analyzed and compared using completely randomized design (CRD) of SPSS analytical software, with the means procedure, Factor Scores (FS) in stepwise Multiple Linear Regression (MLR) procedure for initial live weight equations. Bartlett Factor Score (BFS) analysis extracted 2 factors for each strain, termed Body-length and Thigh-meatiness Factors for AA, and; Breast Size and Height Factors for AN. These derived orthogonal factors assisted in deducing and comparing trait-combinations that best describe body conformation and Meatiness in experimental broilers. BFS procedure yielded different body conformational traits for the two strains, thus indicating the different economic traits and advantages of strains. These factors could be useful as selection criteria for improving desired economic traits. The final Bartlett Factor Regression equations for prediction of body weight were highly significant with P < 0.0001, R2 of 0.92 and above, VIF of 1.00, and DW of 1.90 and 1.47 for Arbor Acres and Annak respectively. These FSR equations could be used as a simple and potent tool for selection during poultry flock improvement, it could also be used to estimate selection index of flocks in order to discriminate between strains, and evaluate consumer preference traits in broilers.

Keywords: alternative selection tool, Bartlet factor regression model, consumer preference trait, linear and body measurements, live body weight

Procedia PDF Downloads 196