Search results for: natural hazard detection

Authors: Lucille Alonso, Florent Renard

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The characterizations of urban heat island (UHI) and their interactions with climate change and urban climates are the main research and public health issue, due to the increasing urbanization of the population. These solutions require a better knowledge of the UHI and micro-climate in urban areas, by combining measurements and modelling. This study is part of this topic by evaluating microclimatic conditions in dense urban areas in the Lyon Metropolitan Area (France) using a combination of data traditionally used such as topography, but also from LiDAR (Light Detection And Ranging) data, Landsat 8 satellite observation and Sentinel and ground measurements by bike. These bicycle-dependent weather data collections are used to build the database of the variable to be modelled, the air temperature, over Lyon’s hyper-center. This study aims to model the air temperature, measured during 6 mobile campaigns in Lyon in clear weather, using multiple linear regressions based on 33 explanatory variables. They are of various categories such as meteorological parameters from remote sensing, topographic variables, vegetation indices, the presence of water, humidity, bare soil, buildings, radiation, urban morphology or proximity and density to various land uses (water surfaces, vegetation, bare soil, etc.). The acquisition sources are multiple and come from the Landsat 8 and Sentinel satellites, LiDAR points, and cartographic products downloaded from an open data platform in Greater Lyon. Regarding the presence of low, medium, and high vegetation, the presence of buildings and ground, several buffers close to these factors were tested (5, 10, 20, 25, 50, 100, 200 and 500m). The buffers with the best linear correlations with air temperature for ground are 5m around the measurement points, for low and medium vegetation, and for building 50m and for high vegetation is 100m. The explanatory model of the dependent variable is obtained by multiple linear regression of the remaining explanatory variables (Pearson correlation matrix with a |r| < 0.7 and VIF with < 5) by integrating a stepwise sorting algorithm. Moreover, holdout cross-validation is performed, due to its ability to detect over-fitting of multiple regression, although multiple regression provides internal validation and randomization (80% training, 20% testing). Multiple linear regression explained, on average, 72% of the variance for the study days, with an average RMSE of only 0.20°C. The impact on the model of surface temperature in the estimation of air temperature is the most important variable. Other variables are recurrent such as distance to subway stations, distance to water areas, NDVI, digital elevation model, sky view factor, average vegetation density, or building density. Changing urban morphology influences the city's thermal patterns. The thermal atmosphere in dense urban areas can only be analysed on a microscale to be able to consider the local impact of trees, streets, and buildings. There is currently no network of fixed weather stations sufficiently deployed in central Lyon and most major urban areas. Therefore, it is necessary to use mobile measurements, followed by modelling to characterize the city's multiple thermal environments.

Keywords: air temperature, LIDAR, multiple linear regression, surface temperature, urban heat island

Procedia PDF Downloads 113

Authors: Stephen Osakue Amiandamhen, Schwaller Andreas, Martina Meincken, Luvuyo Tyhoda

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Invasive alien tree species are currently being cleared in South Africa as a result of the forest and water imbalances. These species grow wildly constituting about 40% of total forest area. They compete with the ecosystem for natural resources and are considered as ecosystem engineers by rapidly changing disturbance regimes. As such, they are harvested for commercial uses but much of it is wasted because of their form and structure. The waste is being sold to local communities as fuel wood. These species can be considered as potential feedstock for the production of phosphate bonded composites. The presence of bark in wood-based composites leads to undesirable properties, and debarking as an option can be cost implicative. This study investigates the potentials of these invasive species processed without debarking on some fundamental properties of wood-based panels. Some invasive alien tree species were collected from EC Biomass, Port Elizabeth, South Africa. They include Acacia mearnsii (Black wattle), A. longifolia (Long-leaved wattle), A. cyclops (Red-eyed wattle), A. saligna (Golden-wreath wattle) and Eucalyptus globulus (Blue gum). The logs were chipped as received. The chips were hammer-milled and screened through a 1 mm sieve. The wood particles were conditioned and the quantity of bark in the wood was determined. The binding matrix was prepared using a reactive magnesia, phosphoric acid and class S fly ash. The materials were mixed and poured into a metallic mould. The composite within the mould was compressed at room temperature at a pressure of 200 KPa. After initial setting which took about 5 minutes, the composite board was demoulded and air-cured for 72 h. The cured product was thereafter conditioned at 20°C and 70% relative humidity for 48 h. Test of physical and strength properties were conducted on the composite boards. The effect of binder formulation and fly ash content on the properties of the boards was studied using fitted response surface technology, according to a central composite experimental design (CCD) at a fixed wood loading of 75% (w/w) of total inorganic contents. The results showed that phosphate/magnesia ratio of 3:1 and fly ash content of 10% was required to obtain a product of good properties and sufficient strength for intended applications. The proposed products can be used for ceilings, partitioning and insulating wall panels.

Keywords: invasive alien tree species, phosphate bonded composites, physical properties, strength

Procedia PDF Downloads 272

Authors: Zakia Hammouni

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Healthcare professionals’ well-being is becoming a priority during this Covid-19 pandemic due to stress, fatigue, and workload. Well before this pandemic, contemporary hospitals are endowed with environmental attributes that contribute to achieving well-being within their environment with the emphasis on the patient. The patient-centered care approach has been followed by the patient-centered design approach. Studies that have focused on the physical environment in hospitals have dealt with the patient's recovery process and his well-being. Prior scientific literature has placed less emphasis on the healthcare professionals’ interactions within the physical environment and to guide hospital designers to make evidence-based design choices to meet the needs and expectations of hospital users by considering, in addition to patients, healthcare professionals. This paper examines these issues related to the daily stress of professionals who provide care in a hospital environment. In this exploratory study, the interest was to grasp the issues related to this environment and explores the current realities of newly built hospitals based on design approaches and what attributes of the physical setting support healthcare professional’s well-being. Within a constructivist approach, this study was conducted in two care units in a new hospital in a big city in Canada before the Covid-19 pandemic (august 2nd to November 2nd 2018). A spatial evaluation of these care units allowed us to understand the interaction of health professionals in their work environment, to understand the spatial behavior of these professionals, and the narratives from 44 interviews of various healthcare professionals. The mental images validated the salient components of the hospital environment as perceived by these healthcare professionals. Thematic analysis and triangulation of the data set were conducted. Among the key attributes promoting the healthcare professionals’ well-being as revealed by the healthcare professionals are the overall light-color atmosphere in the hospital and care unit, particularly in the corridors and public areas of the hospital, the maintenance and cleanliness. The presence of the art elements also brings well-being to the health professionals as well as panoramic views from the staff lounge and corridors of the care units or elevator lobbies. Despite the overall positive assessment of this environment, some attributes need to be improved to ensure the well-being of healthcare professionals and to provide them with a restructuring environment. These are the supply of natural light, softer colors, sufficient furniture, comfortable seating in the restroom, and views, which are important in allowing these healthcare professionals to recover from their work stress. Noise is another attribute that needs to be further improved in the hospital work environment, especially in the nursing workstations and consultant's room. In conclusion, this study highlights the importance of providing healthcare professionals with work and rest areas that allow them to resist the stress they face, particularly during periods of extreme stress and fatigue such as a Covid-19 pandemic.

Keywords: healthcare facilities, healthcare professionals, physical environment, well-being

Procedia PDF Downloads 107

Authors: Antonella Falanga, Armando Cartenì

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Today, an unprecedented amount of data coming from several sources, including mobile devices, sensors, tracking systems, and online platforms, characterizes our lives. The term “big data” not only refers to the quantity of data but also to the variety and speed of data generation. These data hold valuable insights that, when extracted and analyzed, facilitate informed decision-making. The 4Vs of big data - velocity, volume, variety, and value - highlight essential aspects, showcasing the rapid generation, vast quantities, diverse sources, and potential value addition of these kinds of data. This surge of information has revolutionized many sectors, such as business for improving decision-making processes, healthcare for clinical record analysis and medical research, education for enhancing teaching methodologies, agriculture for optimizing crop management, finance for risk assessment and fraud detection, media and entertainment for personalized content recommendations, emergency for a real-time response during crisis/events, and also mobility for the urban planning and for the design/management of public and private transport services. Big data's pervasive impact enhances societal aspects, elevating the quality of life, service efficiency, and problem-solving capacities. However, during this transformative era, new challenges arise, including data quality, privacy, data security, cybersecurity, interoperability, the need for advanced infrastructures, and staff training. Within the transportation sector (the one investigated in this research), applications span planning, designing, and managing systems and mobility services. Among the most common big data applications within the transport sector are, for example, real-time traffic monitoring, bus/freight vehicle route optimization, vehicle maintenance, road safety and all the autonomous and connected vehicles applications. Benefits include a reduction in travel times, road accidents and pollutant emissions. Within these issues, the proper transport demand estimation is crucial for sustainable transportation planning. Evaluating the impact of sustainable mobility policies starts with a quantitative analysis of travel demand. Achieving transportation decarbonization goals hinges on precise estimations of demand for individual transport modes. Emerging technologies, offering substantial big data at lower costs than traditional methods, play a pivotal role in this context. Starting from these considerations, this study explores the usefulness impact of big data within transport demand estimation. This research focuses on leveraging (big) data collected during the COVID-19 pandemic to estimate the evolution of the mobility demand in Italy. Estimation results reveal in the post-COVID-19 era, more than 96 million national daily trips, about 2.6 trips per capita, with a mobile population of more than 37.6 million Italian travelers per day. Overall, this research allows us to conclude that big data better enhances rational decision-making for mobility demand estimation, which is imperative for adeptly planning and allocating investments in transportation infrastructures and services.

Keywords: big data, cloud computing, decision-making, mobility demand, transportation

Procedia PDF Downloads 44

Authors: Despoina Mouratidis, Katia Lida Kermanidis

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Machine translation (MT) is a very important task in Natural Language Processing (NLP). MT evaluation is crucial in MT development, as it constitutes the means to assess the success of an MT system, and also helps improve its performance. Several methods have been proposed for the evaluation of (MT) systems. Some of the most popular ones in automatic MT evaluation are score-based, such as the BLEU score, and others are based on lexical similarity or syntactic similarity between the MT outputs and the reference involving higher-level information like part of speech tagging (POS). This paper presents a language-independent machine learning framework for classifying pairwise translations. This framework uses vector representations of two machine-produced translations, one from a statistical machine translation model (SMT) and one from a neural machine translation model (NMT). The vector representations consist of automatically extracted word embeddings and string-like language-independent features. These vector representations used as an input to a multi-layer neural network (NN) that models the similarity between each MT output and the reference, as well as between the two MT outputs. To evaluate the proposed approach, a professional translation and a "ground-truth" annotation are used. The parallel corpora used are English-Greek (EN-GR) and English-Italian (EN-IT), in the educational domain and of informal genres (video lecture subtitles, course forum text, etc.) that are difficult to be reliably translated. They have tested three basic deep learning (DL) architectures to this schema: (i) fully-connected dense, (ii) Convolutional Neural Network (CNN), and (iii) Long Short-Term Memory (LSTM). Experiments show that all tested architectures achieved better results when compared against those of some of the well-known basic approaches, such as Random Forest (RF) and Support Vector Machine (SVM). Better accuracy results are obtained when LSTM layers are used in our schema. In terms of a balance between the results, better accuracy results are obtained when dense layers are used. The reason for this is that the model correctly classifies more sentences of the minority class (SMT). For a more integrated analysis of the accuracy results, a qualitative linguistic analysis is carried out. In this context, problems have been identified about some figures of speech, as the metaphors, or about certain linguistic phenomena, such as per etymology: paronyms. It is quite interesting to find out why all the classifiers led to worse accuracy results in Italian as compared to Greek, taking into account that the linguistic features employed are language independent.

Keywords: machine learning, machine translation evaluation, neural network architecture, pairwise classification

Procedia PDF Downloads 111

Authors: Jayahar Sivasubramanian

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Understanding laminar-turbulent transition process in hyper-sonic boundary layers is crucial for designing viable high speed flight vehicles. The study of transition becomes particularly important in the high speed regime due to the effect of transition on aerodynamic performance and heat transfer. However, even after many years of research, the transition process in hyper-sonic boundary layers is still not understood. This lack of understanding of the physics of the transition process is a major impediment to the development of reliable transition prediction methods. Towards this end, spatial Direct Numerical Simulations are conducted to investigate the instability waves generated by a localized disturbance in a hyper-sonic flat plate boundary layer. In order to model a natural transition scenario, the boundary layer was forced by a short duration (localized) pulse through a hole on the surface of the flat plate. The pulse disturbance developed into a three-dimensional instability wave packet which consisted of a wide range of disturbance frequencies and wave numbers. First, the linear development of the wave packet was studied by forcing the flow with low amplitude (0.001% of the free-stream velocity). The dominant waves within the resulting wave packet were identified as two-dimensional second mode disturbance waves. Hence the wall-pressure disturbance spectrum exhibited a maximum at the span wise mode number k = 0. The spectrum broadened in downstream direction and the lower frequency first mode oblique waves were also identified in the spectrum. However, the peak amplitude remained at k = 0 which shifted to lower frequencies in the downstream direction. In order to investigate the nonlinear transition regime, the flow was forced with a higher amplitude disturbance (5% of the free-stream velocity). The developing wave packet grows linearly at first before reaching the nonlinear regime. The wall pressure disturbance spectrum confirmed that the wave packet developed linearly at first. The response of the flow to the high amplitude pulse disturbance indicated the presence of a fundamental resonance mechanism. Lower amplitude secondary peaks were also identified in the disturbance wave spectrum at approximately half the frequency of the high amplitude frequency band, which would be an indication of a sub-harmonic resonance mechanism. The disturbance spectrum indicates, however, that fundamental resonance is much stronger than sub-harmonic resonance.

Keywords: boundary layer, DNS, hyper sonic flow, instability waves, wave packet

Procedia PDF Downloads 166

Authors: Rangrong Yoksan, Amporn Sane, Nattaporn Khanoonkon, Chanakorn Yokesahachart, Narumol Noivoil, Khanh Minh Dang

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Polylactic acid (PLA) is the most commercially available bio-based and biodegradable plastic at present. PLA has been used in plastic related industries including single-used containers, disposable and environmentally friendly packaging owing to its renewability, compostability, biodegradability, and safety. Although PLA demonstrates reasonably good optical, physical, mechanical, and barrier properties comparable to the existing petroleum-based plastics, its brittleness and mold shrinkage as well as its price are the points to be concerned for the production of rigid and semi-rigid packaging. Blending PLA with other bio-based polymers including thermoplastic starch (TPS) is an alternative not only to achieve a complete bio-based plastic, but also to reduce the brittleness, shrinkage during molding and production cost of the PLA-based products. TPS is a material produced mainly from starch which is cheap, renewable, biodegradable, compostable, and non-toxic. It is commonly prepared by a plasticization of starch under applying heat and shear force. Although glycerol has been reported as one of the most plasticizers used for preparing TPS, its migration caused the surface stickiness of the TPS products. In some cases, mixed plasticizers or natural fibers have been applied to impede the retrogradation of starch or reduce the migration of glycerol. The introduction of fibers into TPS-based materials could reinforce the polymer matrix as well. Therefore, the objective of the present research is to study the effect of starch type (i.e. native starch and phosphate starch), plasticizer type (i.e. glycerol and xylitol with a weight ratio of glycerol to xylitol of 100:0, 75:25, 50:50, 25:75, and 0:100), and fiber content (i.e. in the range of 1-25 % wt) on properties of PLA/TPS blend and composite. PLA/TPS blends and composites were prepared using a twin-screw extruder and then converted into dumbbell-shaped specimens using an injection molding machine. The PLA/TPS blends prepared by using phosphate starch showed higher tensile strength and stiffness than the blends prepared by using the native one. In contrast, the blends from native starch exhibited higher extensibility and heat distortion temperature (HDT) than those from the modified starch. Increasing xylitol content resulted in enhanced tensile strength, stiffness, and water resistance, but decreased extensibility and HDT of the PLA/TPS blend. Tensile properties and hydrophobicity of the blend could be improved by incorporating silane treated-jute fibers.

Keywords: polylactic acid, thermoplastic starch, Jute fiber, composite, blend

Procedia PDF Downloads 406

Authors: Kien Vu, Jien Min Soh, Mohamed Jahangir Abubacker, Piyawut Pattamanon, Soojin Lee, Suvro Banerjee

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Recent advances in Generative Artificial Intelligence (GenAI), in particular Large Language Models (LLMs) have shown promise to disrupt multiple industries at scale. However, LLMs also present unique challenges, notably, these so-called "hallucination" which is the generation of outputs that are not grounded in the input data that hinders its adoption into production. Common practice to mitigate hallucination problem is utilizing Retrieval Agmented Generation (RAG) system to ground LLMs'response to ground truth. RAG converts the grounding documents into embeddings, retrieve the relevant parts with vector similarity between user's query and documents, then generates a response that is not only based on its pre-trained knowledge but also on the specific information from the retrieved documents. However, the RAG system is not suitable for tabular data and subsequent data analysis tasks due to multiple reasons such as information loss, data format, and retrieval mechanism. In this study, we have explored a novel methodology that combines planning-and-execution and code generation agents to enhance LLMs' data analysis capabilities. The approach enables LLMs to autonomously dissect a complex analytical task into simpler sub-tasks and requirements, then convert them into executable segments of code. In the final step, it generates the complete response from output of the executed code. When deployed beta version on DataSense, the property insight tool of PropertyGuru, the approach yielded promising results, as it was able to provide market insights and data visualization needs with high accuracy and extensive coverage by abstracting the complexities for real-estate agents and developers from non-programming background. In essence, the methodology not only refines the analytical process but also serves as a strategic tool for real estate professionals, aiding in market understanding and enhancement without the need for programming skills. The implication extends beyond immediate analytics, paving the way for a new era in the real estate industry characterized by efficiency and advanced data utilization.

Keywords: large language model, reasoning, planning and execution, code generation, natural language processing, prompt engineering, data analysis, real estate, data sense, PropertyGuru

Procedia PDF Downloads 53

Authors: S. K. Appiah, E. N. Aidoo, D. Asamoah Owusu, M. W. Nuonabuor

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Urbanization remains one of the unique predominant factors which is linked to the destruction of urban environment and its associated cases of soil contamination by heavy metals through the natural and anthropogenic activities. These activities are important sources of toxic heavy metals such as arsenic (As), cadmium (Cd), chromium (Cr), copper (Cu), iron (Fe), manganese (Mn), and lead (Pb), nickel (Ni) and zinc (Zn). Often, these heavy metals lead to increased levels in some areas due to the impact of atmospheric deposition caused by their proximity to industrial plants or the indiscriminately burning of substances. Information gathered on potentially hazardous levels of these heavy metals in soils leads to establish serious health and urban agriculture implications. However, characterization of spatial variations of soil contamination by heavy metals in Ghana is limited. Kumasi is a Metropolitan city in Ghana, West Africa and is challenged with the recent spate of deteriorating soil quality due to rapid economic development and other human activities such as “Galamsey”, illegal mining operations within the metropolis. The paper seeks to use both univariate and multivariate geostatistical techniques to assess the spatial distribution of heavy metals in soils and the potential risk associated with ingestion of sources of soil contamination in the Metropolis. Geostatistical tools have the ability to detect changes in correlation structure and how a good knowledge of the study area can help to explain the different scales of variation detected. To achieve this task, point referenced data on heavy metals measured from topsoil samples in a previous study, were collected at various locations. Linear models of regionalisation and coregionalisation were fitted to all experimental semivariograms to describe the spatial dependence between the topsoil heavy metals at different spatial scales, which led to ordinary kriging and cokriging at unsampled locations and production of risk maps of soil contamination by these heavy metals. Results obtained from both the univariate and multivariate semivariogram models showed strong spatial dependence with range of autocorrelations ranging from 100 to 300 meters. The risk maps produced show strong spatial heterogeneity for almost all the soil heavy metals with extremely risk of contamination found close to areas with commercial and industrial activities. Hence, ongoing pollution interventions should be geared towards these highly risk areas for efficient management of soil contamination to avert further pollution in the metropolis.

Keywords: coregionalization, heavy metals, multivariate geostatistical analysis, soil contamination, spatial distribution

Procedia PDF Downloads 279

Authors: Sugandha Asthana, Geetika Vajpayee, Pratibha Kumari, Shanthy Sundaram

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An economically important disease of wheat in North Western region of India is Karnal Bunt caused by smut fungus Tilletia indica. This fungal pathogen spreads by air, soil and seed borne sporodia at the time of flowering, which ultimately leads to partial bunting of wheat kernels with fishy odor and taste to wheat flour. It has very serious effects due to quarantine measures which have to be applied for grain exports. Chemical fungicides such as mercurial compounds and Propiconazole applied to the control of Karnal bunt have been only partially successful. Considering the harmful effects of chemical fungicides on man as well as environment, many countries are developing biological control as the superior substitute to chemical control. Repeated use of fungicides can be responsible for the development of resistance in fungal pathogens against certain chemical compounds. The present investigation is based on the isolation and evaluation of antifungal properties of some isolated (from natural manure) and commercial bacterial strains against Tilletia indica. Total 23 bacterial isolates were obtained and antagonistic activity of all isolates and commercial bacterial strains (Bacillus subtilis MTCC8601, Bacillus pumilus MTCC 8743, Pseudomonas aeruginosa) were tested against T. indica by dual culture plate assay (pour plate and streak plate). Test for the production of antifungal volatile organic compounds (VOCs) by antagonistic bacteria was done by sealed plate method. Amongst all s1, s3, s5, and B. subtilis showed more than 80% inhibition. Production of extracellular hydrolytic enzymes such as protease, beta 1, 4 glucanase, HCN and ammonia was studied for confirmation of antifungal activity. s1, s3, s5 and B. subtilis were found to be the best for protease activity and s5 and B. subtilis for beta 1, 4 glucanase activity. Bacillus subtilis was significantly effective for HCN whereas s3, s5 and Bacillus subtilis for ammonia production. Isolates were identified as Pseudomonas aeruginosa (s1) and B. licheniformis (s3, s5) by various biochemical assays and confirmed by16s rRNA sequencing. Use of microorganisms or their secretions as biocontrol agents to avoid plant diseases is ecologically safe and may offer long term of protection to crop. The above study reports the promising effects of these strains in better pathogen free crop production and quality maintenance as well as prevention of the excessive use of synthetic fungicides.

Keywords: antagonistic, antifungal, biocontrol, Karnal bunt

Procedia PDF Downloads 262

Authors: Bolawole F. Ogunbodede, Mokolade Johnson, Adetunji Adejumo

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High population growth rate, reactive infrastructure provision, inability of physical planning to cope with developmental pace are responsible for waste water crisis in the Lagos Metropolis. Septic tank is still the most prevalent waste-water holding system. Unfortunately, there is a dearth of septage treatment infrastructure. Public waste-water treatment system statistics relative to the 23 million people in Lagos State is worrisome. 1.85 billion Cubic meters of wastewater is generated on daily basis and only 5% of the 26 million population is connected to public sewerage system. This is compounded by inadequate budgetary allocation and erratic power supply in the last two decades. This paper explored community participatory waste-water management alternative at Oworonshoki Municipality in Lagos. The study is underpinned by decentralized Waste-water Management systems in built-up areas. The initiative accommodates 5 step waste-water issue including generation, storage, collection, processing and disposal through participatory decision making in two Oworonshoki Community Development Association (CDA) areas. Drone assisted mapping highlighted building footage. Structured interviews and focused group discussion of land lord associations in the CDA areas provided collaborator platform for decision-making. Water stagnation in primary open drainage channels and natural retention ponds in framing wetlands is traceable to frequent of climate change induced tidal influences in recent decades. Rise in water table resulting in septic-tank leakage and water pollution is reported to be responsible for the increase in the water born infirmities documented in primary health centers. This is in addition to unhealthy dumping of solid wastes in the drainage channels. The effect of uncontrolled disposal system renders surface waters and underground water systems unsafe for human and recreational use; destroys biotic life; and poisons the fragile sand barrier-lagoon urban ecosystems. Cluster decentralized system was conceptualized to service 255 households. Stakeholders agreed on public-private partnership initiative for efficient wastewater service delivery.

Keywords: health, infrastructure, management, septage, well-being

Procedia PDF Downloads 150

Authors: Nana Bolashvili, Vakhtang Geladze, Tamazi Karalashvili, Nino Machavariani, George Geladze, Davit Kartvelishvili, Ana Karalashvili

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Fresh water is the major natural resource of Georgia. The average perennial sum of the rivers' runoff in Georgia is 52,77 km³, out of which 9,30 km³ inflows from abroad. The major volume of transit river runoff is ascribed to the Chorokhi river. Average perennial runoff in Western Georgia is 41,52 km³, in Eastern Georgia 11,25 km³. The indices of Eastern and Western Georgia were calculated with 50% and 90% river runoff respectively, while the same index calculation for other countries is based on a 50% river runoff. Out of total volume of resources, 133,2 m³/sec (4,21 km³) has been geologically prospected by the State Commission on Reserves and Acknowledged as reserves available for exploitation, 48% (2,02 km³) of which is in Western Georgia and 2,19 km³ in Eastern Georgia. Considering acknowledged water reserves of all categories per capita water resources accounts to 2,2 m³/day, whereas high industrial category -0. 88 m³ /day fresh drinking water. According to accepted norms, the possibility of using underground water reserves is 2,5 times higher than the long-term requirements of the country. The volume of abundant fresh-water reserves in Georgia is about 150 m³/sec (4,74 km³). Water in Georgia is consumed mostly in agriculture for irrigation purposes. It makes 66,4% around Georgia, in Eastern Georgia 72,4% and 38% in Western Georgia. According to the long-term forecast provision of population and the territory with water resources in Eastern Georgia will be quite normal. A bit different is the situation in the lower reaches of the Khrami and Iori rivers which could be easily overcome by corresponding financing. The present day irrigation system in Georgia does not meet the modern technical requirements. The overall efficiency of their majority varies between 0,4-0,6. Similar is the situation in the fresh water and public service water consumption. Organization of the mentioned systems, installation of water meters, introduction of new methods of irrigation without water loss will substantially increase efficiency of water use. Besides new irrigation norms developed from agro-climatic, geographical and hydrological angle will significantly reduce water waste. Taking all this into account we assume that for irrigation agricultural lands in Georgia is necessary 6,0 km³ water, 5,5 km³ of which goes to Eastern Georgia on irrigation arable areas. To increase water supply in Eastern Georgian territory and its population is possible by means of new water reservoirs as the runoff of every river considerably exceeds the consumption volume. In conclusion, we should say that fresh water resources by which Georgia is that rich could be significant source for barter exchange and investment attraction. Certain volume of fresh water can be exported from Western Georgia quite trouble free, without bringing any damage to population and hydroecosystems. The precise volume of exported water per region/time and method/place of water consumption should be defined after the estimation of different hydroecosystems and detailed analyses of water balance of the corresponding territories.

Keywords: GIS, management, rivers, water resources

Procedia PDF Downloads 350

Authors: Tamar Arieli

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Cross-border cooperation has long been hailed as a means for stabilizing and normalizing relations between former enemies. Cooperation in problem-solving and realizing of local interests in post-conflict environments can indeed serve as a basis for developing dialogue and meaningful relations between neighbors across borders. Hence the potential for formerly sealed borders to serve as a basis for generating local and national perceptions of interdependence and as a buffer against the resume of conflict. Central questions which arise for policy-makers and third parties are how to facilitate cross-border cooperation and which areas of cooperation best serve to normalize post-conflict border regions. The Israel-Jordan border functions as a post-conflict border, in that it is a peaceful border since the 1994 Israel-Jordan peace treaty yet cross-border relations are defined but the highly securitized nature of the border region and the ongoing Arab-Israel regional conflict. This case study is based on long term qualitative research carried out in the border regions of both Israel and Jordan, which mapped and analyzed cross-border in a wide range of activities – social interactions sponsored by peace-facilitating NGOs, government sponsored agricultural cooperation, municipal initiated emergency planning in cross-border continuous urban settings, private cross-border business ventures and various environmental cooperative initiatives. These cooperative initiatives are evaluated through multiple interviews carried out with initiators and partners in cross-border cooperation as well as analysis of documentation, funding and media. These cooperative interactions are compared based on levels of cross-border local and official awareness and involvement as well as sustainability over time. This research identifies environmental cooperation as the most sustainable area of cross- border cooperation and as most conducive to generating perceptions of regional interdependence. This is a variation to the ‘New Middle East’ vision of business-based cooperation leading to conflict amelioration and regional stability. Environmental cooperation serving the public good rather than personal profit enjoys social legitimization even in the face of widespread anti-normalization sentiments common in the post-conflict environment. This insight is examined in light of philosophical and social aspects of the natural environment and its social perceptions. This research has theoretical implications for better understanding dynamics of cooperation and conflict, as well as practical ramifications for practitioners in border region policy and management.

Keywords: borders, cooperation, post-conflict, security

Procedia PDF Downloads 291

Authors: Xinhai Li, Huidong Tian, Yumin Guo

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Bird migration is fantastic natural phenomenon. In recent years, the use of GPS transmitters has generated a vast amount of data, and the Movebank platform has made these data publicly accessible. For researchers, what they need are data analysis tools. Although there are approximately 90 R packages dedicated to animal movement analysis, the capacity for comprehensive processing of bird migration data remains limited. Hence, we introduce a novel package called migrationR. This package enables the calculation of movement speed, direction, changes in direction, flight duration, daily and annual movement distances. Furthermore, it can pinpoint the starting and ending dates of migration, estimate nest site locations and stopovers, and visualize movement trajectories at various time scales. migrationR distinguishes individuals through NMDS (non-metric multidimensional scaling) coordinates based on movement variables such as speed, flight duration, path tortuosity, and migration timing. A distinctive aspect of the package is the development of a hetero-occurrences species distribution model that takes into account the daily rhythm of individual birds across different landcover types. Habitat use for foraging and roosting differs significantly for many waterbirds. For example, White-naped Cranes at Poyang Lake in China typically forage in croplands and roost in shallow water areas. Both of these occurrence types are of equal importance. Optimal habitats consist of a combination of crop lands and shallow waters, whereas suboptimal habitats lack both, which necessitates birds to fly extensively. With migrationR, we conduct species distribution modeling for foraging and roosting separately and utilize the moving distance between crop lands and shallow water areas as an index of overall habitat suitability. This approach offers a more nuanced understanding of the habitat requirements for migratory birds and enhances our ability to analyze and interpret their movement patterns effectively. The functions of migrationR are demonstrated using our own tracking data of 78 White-naped Crane individuals from 2014 to 2023, comprising over one million valid locations in total. migrationR can be installed from a GitHub repository by executing the following command: remotes::install_github("Xinhai-Li/migrationR").

Keywords: bird migration, hetero-occurrences species distribution model, migrationR, R package, satellite telemetry

Procedia PDF Downloads 43

Authors: Amani Tahat, Serdal Kirmizialtin

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Trajectory fragment methods such as Markov State Models (MSM), Milestoning (MS) and Transition Path sampling are the prime choice of extending the timescale of all atom Molecular Dynamics simulations. In these approaches, a set of structures that covers the accessible phase space has to be chosen a priori using cluster analysis. Structural clustering serves to partition the conformational state into natural subgroups based on their similarity, an essential statistical methodology that is used for analyzing numerous sets of empirical data produced by Molecular Dynamics (MD) simulations. Local transition kernel among these clusters later used to connect the metastable states using a Markovian kinetic model in MSM and a non-Markovian model in MS. The choice of clustering approach in constructing such kernel is crucial since the high dimensionality of the biomolecular structures might easily confuse the identification of clusters when using the traditional hierarchical clustering methodology. Of particular interest, in the case of MS where the milestones are very close to each other, accurate determination of the milestone identity of the trajectory becomes a challenging issue. Throughout this work we present two cluster analysis methods applied to the cis–trans isomerism of dinucleotide AA. The choice of nucleic acids to commonly used proteins to study the cluster analysis is two fold: i) the energy landscape is rugged; hence transitions are more complex, enabling a more realistic model to study conformational transitions, ii) Nucleic acids conformational space is high dimensional. A diverse set of internal coordinates is necessary to describe the metastable states in nucleic acids, posing a challenge in studying the conformational transitions. Herein, we need improved clustering methods that accurately identify the AA structure in its metastable states in a robust way for a wide range of confused data conditions. The single linkage approach of the hierarchical clustering available in GROMACS MD-package is the first clustering methodology applied to our data. Self Organizing Map (SOM) neural network, that also known as a Kohonen network, is the second data clustering methodology. The performance comparison of the neural network as well as hierarchical clustering method is studied by means of computing the mean first passage times for the cis-trans conformational rates. Our hope is that this study provides insight into the complexities and need in determining the appropriate clustering algorithm for kinetic analysis. Our results can improve the effectiveness of decisions based on clustering confused empirical data in studying conformational transitions in biomolecules.

Keywords: milestoning, self organizing map, single linkage, structure clustering

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Authors: Guerich Mohamed, Assaf Samir

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The application of viscoelastic materials in the form of constrained layers in mechanical structures is an efficient and cost-effective technique for solving noise and vibration problems. This technique requires a design tool to select the best location, type, and thickness of the damping treatment. This paper presents a finite element model for the vibration of beams partially or fully covered with a constrained viscoelastic damping material. The model is based on Bernoulli-Euler theory for the faces and Timoshenko beam theory for the core. It uses four variables: the through-thickness constant deflection, the axial displacements of the faces, and the bending rotation of the beam. The sandwich beam finite element is compatible with the conventional C1 finite element for homogenous beams. To validate the proposed model, several free vibration analyses of fully or partially covered beams, with different locations of the damping patches and different percent coverage, are studied. The results show that the proposed approach can be used as an effective tool to study the influence of the location and treatment size on the natural frequencies and the associated modal loss factors. Then, a parametric study regarding the variation in the damping characteristics of partially covered beams has been conducted. In these studies, the effect of core shear modulus value, the effect of patch size variation, the thickness of constraining layer, and the core and the locations of the patches are considered. In partial coverage, the spatial distribution of additive damping by using viscoelastic material is as important as the thickness and material properties of the viscoelastic layer and the constraining layer. Indeed, to limit added mass and to attain maximum damping, the damping patches should be placed at optimum locations. These locations are often selected using the modal strain energy indicator. Following this approach, the damping patches are applied over regions of the base structure with the highest modal strain energy to target specific modes of vibration. In the present study, a more efficient indicator is proposed, which consists of placing the damping patches over regions of high energy dissipation through the viscoelastic layer of the fully covered sandwich beam. The presented approach is used in an optimization method to select the best location for the damping patches as well as the material thicknesses and material properties of the layers that will yield optimal damping with the minimum area of coverage.

Keywords: finite element model, damping treatment, viscoelastic materials, sandwich beam

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Authors: Dhouha Laribi Galalou, Najla Allani Bouhoula, Atef Hammouda

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This research delves into the fundamental question of the morphological restitution of built archaeology in order to place it in its paradigmatic context and to seek answers to it. Indeed, the understanding of the object of the study, its analysis, and the methodology of solving the morphological problem posed, are manageable aspects only by means of a thoughtful strategy that draws on well-defined epistemological scaffolding. In this stream, the crisis of natural reasoning in archaeology has generated multiple changes in this field, ranging from the use of new tools to the integration of an archaeological information system where urbanization involves the interplay of several disciplines. The built archaeological topic is also an architectural and morphological object. It is also a set of articulated elementary data, the understanding of which is about to be approached from a logicist point of view. Morphological restitution is no exception to the rule, and the inter-exchange between the different disciplines uses the capacity of each to frame the reflection on the incomplete elements of a given architecture or on its different phases and multiple states of existence. The logicist sequence is furnished by the set of scattered or destroyed elements found, but also by what can be called a rule base which contains the set of rules for the architectural construction of the object. The knowledge base built from the archaeological literature also provides a reference that enters into the game of searching for forms and articulations. The choice of the Roman Forum in North Africa is justified by the great urban and architectural characteristics of this entity. The research on the forum involves both a fairly large knowledge base but also provides the researcher with material to study - from a morphological and architectural point of view - starting from the scale of the city down to the architectural detail. The experimentation of the knowledge deduced on the paradigmatic level, as well as the deduction of an analysis model, is then carried out on the basis of a well-defined context which contextualises the experimentation from the elaboration of the morphological information container attached to the rule base and the knowledge base. The use of logicist analysis and artificial intelligence has allowed us to first question the aspects already known in order to measure the credibility of our system, which remains above all a decision support tool for the morphological restitution of Roman Fora in North Africa. This paper presents a first experimentation of the model elaborated during this research, a model framed by a paradigmatic discussion and thus trying to position the research in relation to the existing paradigmatic and experimental knowledge on the issue.

Keywords: classical reasoning, logicist reasoning, archaeology, architecture, roman forum, morphology, calculation

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Authors: Merina Islam

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There are many environmental problems. Various counter measures have been taken for environmental problems. Philosophy is an important contributor to environmental studies as it takes deep interest in meaning analysis of the concept environment and other related concepts. The Buddhist frame, which is virtue ethical, remains a better alternative to the traditional environmental outlook. Granting the unique role of man in immoral deliberations, the Buddhist approach, however, maintains a holistic concept of ecological harmony. Buddhist environmental ethics is more concerned about the complete moral community, the total ecosystem, than any particular species within the community. The moral reorientation proposed here has resemblance to the concept of 'deep ecology. Given the present day prominence of virtue ethics, we need to explore further into the Buddhist virtue theory, so that a better framework to treat the natural world would be ensured. Environment has turned out to be one of the most widely discussed issues in the recent times. Buddhist concepts such as Pratityasamutpadavada, Samvrit Satya, Paramartha Satya, Shunyata, Sanghatvada, Bodhisattva, Santanvada and others deal with interdependence in terms of both internal as well external ecology. The internal ecology aims at mental well-being whereas external ecology deals with physical well-being. The fundamental Buddhist concepts for dealing with environmental Problems are where the environment has the same value as humans as from the two Buddhist doctrines of the Non-duality of Life and its Environment and the Origination in Dependence; and the inevitability of overcoming environmental problems through the practice of the way of the Bodhisattva, because environmental problems are evil for people and nature. Buddhism establishes that there is a relationship among all the constituents of the world. There is nothing in the world which is independent from any other thing. Everything is dependent on others. The realization that everything in the universe is mutually interdependent also shows that the man cannot keep itself unaffected from ecology. This paper would like to focus how the Buddhist’s identification of nature and the Dhamma can contribute toward transforming our understanding, attitudes, and actions regarding the care of the earth. Environmental Ethics in Buddhism presents a logical and thorough examination of the metaphysical and ethical dimensions of early Buddhist literature. From the Buddhist viewpoint, humans are not in a category that is distinct and separate from other sentient beings, nor are they intrinsically superior. All sentient beings are considered to have the Buddha-nature, that is, the potential to become fully enlightened. Buddhists do not believe in treating of non-human sentient beings as objects for human consumption. The significance of Buddhist theory of interdependence can be understood from the fact that it shows that one’s happiness or suffering originates from ones realization or non-realization respectively of the dependent nature of everything. It is obvious, even without emphasis, which in the context of deep ecological crisis of today there is a need to infuse the consciousness of interdependence.

Keywords: Buddhism, deep ecology, environmental problems, Pratityasamutpadavada

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Authors: Turin Datta, Kisor K. Sahu

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Structural materials used in today’s oil and gas exploration and drilling of both onshore and offshore oil and gas wells must possess superior tensile properties, excellent resistance to corrosive degradation that includes general, localized (pitting and crevice) and environment assisted cracking such as stress corrosion cracking and hydrogen embrittlement. The High Pressure and High Temperature (HPHT) wells are typically operated at temperature and pressure that can exceed 300-3500F and 10,000psi (69MPa) respectively which necessitates the use of exotic materials in these exotic sources of natural resources. This research investigation is focussed on the evaluation of tensile properties and corrosion behavior of AISI 4140 High-Strength Low Alloy Steel (HSLA) possessing tempered martensitic microstructure and Duplex 2205 Stainless Steel (DSS) having austenitic and ferritic phase. The selection of this two alloys are primarily based on economic considerations as 4140 HSLA is cheaper when compared to DSS 2205. Due to the harsh aggressive chemical species encountered in deep oil and gas wells like chloride ions (Cl-), carbon dioxide (CO2), hydrogen sulphide (H2S) along with other mineral organic acids, DSS 2205, having a dual-phase microstructure can mitigate the degradation resulting from the presence of both chloride ions (Cl-) and hydrogen simultaneously. Tensile properties evaluation indicates a ductile failure of DSS 2205 whereas 4140 HSLA exhibit quasi-cleavage fracture due to the phenomenon of ‘tempered martensitic embrittlement’. From the potentiodynamic polarization testing, it is observed that DSS 2205 has higher corrosion resistance than 4140 HSLA; the former exhibits passivity signifying resistance to localized corrosion while the latter exhibits active dissolution in all the environmental parameters space that was tested. From the Scanning Electron Microscopy (SEM) evaluation, it is understood that stable pits appear in DSS 2205 only when the temperature exceeds the critical pitting temperature (CPT). SEM observation of the corroded 4140 HSLA specimen tested in aqueous 3.5 wt.% NaCl solution reveals intergranular cracking which appears due to the adsorption and diffusion of hydrogen during polarization, thus, causing hydrogen-induced cracking/hydrogen embrittlement. General corrosion testing of DSS 2205 in acidic brine (pH~3.0) solution at ambient temperature using coupons indicate no weight loss even after three months whereas the corrosion rate of AISI 4140 HSLA is significantly higher after one month of testing.

Keywords: DSS 2205, polarization, pitting, SEM

Procedia PDF Downloads 247

Authors: Hsiao-Lin Fang

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The Patient Self-Determination Act is based on the belief that each life is unique. The act regards each patient as an autonomous entity and explicitly protects the patient’s rights to know and make decisions and choices while ensuring that the patient’s wish for a peaceful end is granted. Even when the patient is unconscious and unable to express himself/herself, the patient’s self-determination and its exercise are still protected under the law. The act also ensures that healthcare professionals (HCPs) have a specific set of rules to follow and complete legal protection when their patients are unable to express themselves clearly. This report is about a 55-year-old female patient who weighed 110 kg and was diagnosed with acute type A aortic dissection. The case was that the patient suddenly felt backache and nausea during sleep before daybreak and was therefore transferred to this hospital from the original one. After the doctor explained the patient’s conditions, it was concluded that surgery was necessary. However, the patient’s family was immediately against the surgery after having heard its possible complications. Nevertheless, the patient was still willing to receive the surgery. Being at odds with her family, the patient decided to sign the surgery agreement herself and agreed to receive the two surgical procedures: (1) ascending aorta replacement and (2) innominate artery debranching. After the surgery, the patient did not regain consciousness and therefore received computed tomography scanning of the brain, which revealed false lumen involving proximal left common carotid artery, left subclavian artery and innominate artery, and severe compression of the true lumen with total/subtotal occlusion in the left common carotid artery. On the following day, the doctor discussed two further surgical procedures: (1) endografting for descending aorta and (2) endografting for left common carotid artery and subclavian artery with the family. However, as the patient’s postoperative recovery of consciousness only reached the level of stupor and her family had no intention of subsequent healthcare for the patient, the family made the joint decision three days later to have the endotracheal tube removed from the patient and let her die a natural death. Suggestion: An advance directive (AD) can be created beforehand. Once the patient is in a special clinical state (e.g., terminal illness, permanent vegetative state, etc.), the AD can determine whether to sustain the patient’s life through ‘medical intervention’ or to respect the patient’s rights to choose a peaceful end and receive palliative care. Through the expression of self-determination, it is possible to respect the patient’s medical practice autonomy and protect the patient’s dignity and right to a peaceful end, thereby respecting and supporting the patient’s decision. This also allows the three sides: the patient, the family and the medical team to understand the patient’s true wish in the process of advance care planning (ACP) and thereby promote harmony in the HCP-patient relationship.

Keywords: intensive care unit patient, cardiovascular surgery, self-determination, advance directive

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Authors: Sonja Giese, Tess N. Peacock

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South African based Innovation Edge is experimenting with technology to drive positive behavior change, enable data-driven decision making, and scale quality early years services. This paper uses five case studies to illustrate how technology can be used in resource-constrained environments to first, encourage parenting practices that build early language development (using a stage-based mobile messaging pilot, ChildConnect), secondly, to improve the quality of ECD programs (using a mobile application, CareUp), thirdly, how to affordably scale services for the early detection of visual and hearing impairments (using a mobile tool, HearX), fourthly, how to build a transparent and accountable system for the registration and funding of ECD (using a blockchain enabled platform, Amply), and finally enable rapid data collection and feedback to facilitate quality enhancement of programs at scale (the Early Learning Outcomes Measure). ChildConnect and CareUp were both developed using a design based iterative research approach. The usage and uptake of ChildConnect and CareUp was evaluated with qualitative and quantitative methods. Actual child outcomes were not measured in the initial pilots. Although parents who used and engaged on either platform felt more supported and informed, parent engagement and usage remains a challenge. This is contrast to ECD practitioners whose usage and knowledge with CareUp showed both sustained engagement and knowledge improvement. HearX is an easy-to-use tool to identify hearing loss and visual impairment. The tool was tested with 10000 children in an informal settlement. The feasibility of cost-effectively decentralising screening services was demonstrated. Practical and financial barriers remain with respect to parental consent and for successful referrals. Amply uses mobile and blockchain technology to increase impact and accountability of public services. In the pilot project, Amply is being used to replace an existing paper-based system to register children for a government-funded pre-school subsidy in South Africa. Early Learning Outcomes Measure defines what it means for a child to be developmentally ‘on track’ at aged 50-69 months. ELOM administration is enabled via a tablet which allows for easy and accurate data collection, transfer, analysis, and feedback. ELOM is being used extensively to drive quality enhancement of ECD programs across multiple modalities. The nature of ECD services in South Africa is that they are in large part provided by disconnected private individuals or Non-Governmental Organizations (in contrast to basic education which is publicly provided by the government). It is a disparate sector which means that scaling successful interventions is that much harder. All five interventions show the potential of technology to support and enhance a range of ECD services, but pathways to scale are still being tested.

Keywords: assessment, behavior change, communication, data, disabilities, mobile, scale, technology, quality

Procedia PDF Downloads 117

Authors: Man Fung Ho, Lap So, Jiaqi Zhang, Yuheng Zhao, Huiyang Lu, Tat Shing Choi, K. Y. Michael Wong

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Nowadays, a tremendous amount of data is available in the transportation system, enabling the development of various machine learning approaches to make short-term latency predictions. A natural question is then the choice of relevant information to enable accurate predictions. Using traffic data collected from the Taiwan Freeway System, we consider the prediction of short-term latency of a freeway segment with a length of 17 km covering 5 measurement points, each collecting vehicle-by-vehicle data through the electronic toll collection system. The processed data include the past latencies of the freeway segment with different time lags, the traffic conditions of the individual segments (the accumulations, the traffic fluxes, the entrance and exit rates), the total accumulations, and the weekday latency profiles obtained by Gaussian process regression of past data. We arrive at several important conclusions about how data should be refined to obtain accurate predictions, which have implications for future system-wide latency predictions. (1) We find that the prediction of median latency is much more accurate and meaningful than the prediction of average latency, as the latter is plagued by outliers. This is verified by machine-learning prediction using XGBoost that yields a 35% improvement in the mean square error of the 5-minute averaged latencies. (2) We find that the median latency of the segment 15 minutes ago is a very good baseline for performance comparison, and we have evidence that further improvement is achieved by machine learning approaches such as XGBoost and Long Short-Term Memory (LSTM). (3) By analyzing the feature importance score in XGBoost and calculating the mutual information between the inputs and the latencies to be predicted, we identify a sequence of inputs ranked in importance. It confirms that the past latencies are most informative of the predicted latencies, followed by the total accumulation, whereas inputs such as the entrance and exit rates are uninformative. It also confirms that the inputs are much less informative of the average latencies than the median latencies. (4) For predicting the latencies of segments composed of two or three sub-segments, summing up the predicted latencies of each sub-segment is more accurate than the one-step prediction of the whole segment, especially with the latency prediction of the downstream sub-segments trained to anticipate latencies several minutes ahead. The duration of the anticipation time is an increasing function of the traveling time of the upstream segment. The above findings have important implications to predicting the full set of latencies among the various locations in the freeway system.

Keywords: data refinement, machine learning, mutual information, short-term latency prediction

Procedia PDF Downloads 153

Authors: Swati Gautam, Salman Akhtar, S. P. Jaiswar, Amita Jain

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Background: FGTB is now a major global health problem mostly in developing countries including India. In humans, Mycobacterium Tuberculosis (M.tb) is a causating agent of infection. High index of suspicion is required for early diagnosis due to asymptomatic presentation of FGTB disease. In macrophages Toll Like Receptor-2 (TLR-2) is one which mediated host’s immune response to M.tb. The expression of TLR-2 on macrophages is important to determine the fate of innate immune responses to M.tb. TLR-2 have two work. First its high expression on macrophages worsen the outer of infection and another side, it maintains M.tb to its dormant stage avoids activation of M.tb from latent phase. Single Nucleotide Polymorphism (SNP) of TLR-2 gene plays an important role in susceptibility to TB among different populations and subsequently, in the development of infertility. Methodology: This Case-Control study was done in the Department of Obs and Gynae and Department of Microbiology at King George’s Medical University, U.P, Lucknow, India. Total 300 subjects (150 Cases and 150 Controls) were enrolled in the study. All subjects were enrolled only after fulfilling the given inclusion and exclusion criteria. Inclusion criteria: Age 20-35 years, menstrual-irregularities, positive on Acid-Fast Bacilli (AFB), TB-PCR, (LJ/MGIT) culture in Endometrial Aspiration (EA). Exclusion criteria: Koch’s active, on ATT, PCOS, and Endometriosis fibroid women, positive on Gonococal and Chlamydia. Blood samples were collected in EDTA tubes from cases and healthy control women (HCW) and genomic DNA extraction was carried out by salting-out method. Genotyping of TLR2 genetic variants (Arg753Gln and Arg677Trp) were performed by using single amplification refractory mutation system (ARMS) PCR technique. PCR products were analyzed by electrophoresis on 1.2% agarose gel and visualized by gel-doc. Statistical analysis of the data was performed using the SPSS 16.3 software and computing odds ratio (OR) with 95% CI. Linkage Disequiliribium (LD) analysis was done by SNP stats online software. Results: In TLR-2 (Arg753Gln) polymorphism significant risk of FGTB observed with GG homozygous mutant genotype (OR=13, CI=0.71-237.7, p=0.05), AG heterozygous mutant genotype (OR=13.7, CI=0.76-248.06, p=0.03) however, G allele (OR=1.09, CI=0.78-1.52, p=0.67) individually was not associated with FGTB. In TLR-2 (Arg677Trp) polymorphism a significant risk of FGTB observed with TT homozygous mutant genotype (OR= 0.020, CI=0.001-0.341, p < 0.001), CT heterozygous mutant genotype (OR=0.53, CI=0.33-0.86, p=0.014) and T allele (OR=0.463, CI=0.32-0.66, p < 0.001). TT mutant genotype was only found in FGTB cases and frequency of CT heterozygous more in control group as compared to FGTB group. So, CT genotype worked as protective mutation for FGTB susceptibility group. In haplotype analysis of TLR-2 genetic variants, four possible combinations, i.e. (G-T, A-C, G-C, and A-T) were obtained. The frequency of haplotype A-C was significantly higher in FGTB cases (0.32). Control group did not show A-C haplotype and only found in FGTB cases. Conclusion: In conclusion, study showed a significant association with both genetic variants of TLR-2 of FGTB disease. Moreover, the presence of specific associated genotype/alleles suggest the possibility of disease severity and clinical approach aimed to prevent extensive damage by disease and also helpful for early detection of disease.

Keywords: ARMS, EDTA, FGTB, TLR

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Authors: Fereydoon Bondarian, Samira Shaygan

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Today, many nutritionists recommend the consumption of plants, fruits, and vegetables to provide the antioxidants needed by the body because the use of plant antioxidants usually causes fewer side effects and better treatment. Natural antioxidants increase the power of plasma antioxidants and reduce the incidence of some diseases, such as cancer. Bad lifestyles and environmental factors play an important role in increasing the incidence of cancer. In this study, different extracts of white teas taken from two types of tea available in Iran (clone 100 and Chinese hybrid) due to the presence of a hydroxyl functional group in their structure to inhibit free radicals and anticancer properties, using 3 aqueous, methanolic and aqueous-methanolic methods were used. The total polyphenolic content was calculated using the Folin-Ciocalcu method, and the percentage of inhibition and trapping of free radicals in each of the extracts was calculated using the DPPH method. With the help of high-performance liquid chromatography, a small amount of each catechin in the tea samples was obtained. Clone 100 white tea was found to be the best sample of tea in terms of all the examined attributes (total polyphenol content, antioxidant properties, and individual amount of each catechin). The results showed that aqueous and aqueous-methanolic extracts of Clone 100 white tea have the highest total polyphenol content with 27.59±0.08 and 36.67±0.54 (equivalent gallic acid per gram dry weight of leaves), respectively. Due to having the highest level of different groups of catechin compounds, these extracts have the highest property of inhibiting and trapping free radicals with 66.61±0.27 and 71.74±0.27% (mg/l) of the extracted sample against ascorbic acid). Using the MTT test, the inhibitory effect of clone 100 white tea extract in inhibiting the growth of HCT-116 colon cancer cells was investigated and the best time and concentration treatments were 500, 150 and 1000 micrograms in 8, 16 and 24 hours, respectively. To investigate gene expression changes, selected genes, including tumorigenic genes, proto-oncogenes, tumor suppressors, and genes involved in apoptosis, were selected and analyzed using the real-time PCR method and in the presence of concentrations obtained for white tea. White tea extract at a concentration of 1000 μg/ml 3 times 16, 8, and 24 hours showed the highest growth inhibition in cancer cells with 53.27, 55.8, and 86.06%. The concentration of 1000 μg/ml aqueous extract of white tea under 24-hour treatment increased the expression of tumor suppressor genes compared to the normal sample.

Keywords: catechin, gene expression, suppressor genes, colon cell line

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Authors: Aylin W Sahin, Alice Jaeger, Laura Nyhan, Gregory Belt, Steffen Münch, Elke K. Arendt

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Our current food systems cause an increase in malnutrition resulting in more people being overweight or obese in the Western World. Additionally, our natural resources are under enormous pressure and the greenhouse gas emission increases yearly with a significant contribution to climate change. Hence, transforming our food systems is of highest priority. Plant-based food products have a lower environmental impact compared to their animal-based counterpart, representing a more sustainable protein source. However, most plant-based protein ingredients, such as soy and pea, are lacking indispensable amino acids and extremely limited in their functionality and, thus, in their food application potential. They are known to have a low solubility in water and change their properties during processing. The low solubility displays the biggest challenge in the development of milk alternatives leading to inferior protein content and protein quality in dairy alternatives on the market. Moreover, plant-based protein ingredients often possess an off-flavour, which makes them less attractive to consumers. EverPro, a plant-protein isolate originated from Brewer’s Spent Grain, the most abundant by-product in the brewing industry, represents the missing piece in the plant protein portfolio. With a protein content of >85%, it is of high nutritional value, including all indispensable amino acids which allows closing the protein quality gap of plant proteins. Moreover, it possesses high techno-functional properties. It is fully soluble in water (101.7 ± 2.9%), has a high fat absorption capacity (182.4 ± 1.9%), and a foaming capacity which is superior to soy protein or pea protein. This makes EverPro suitable for a vast range of food applications. Furthermore, it does not cause changes in viscosity during heating and cooling of dispersions, such as beverages. Besides its outstanding nutritional and functional characteristics, the production of EverPro has a much lower environmental impact compared to dairy or other plant protein ingredients. Life cycle assessment analysis showed that EverPro has the lowest impact on global warming compared to soy protein isolate, pea protein isolate, whey protein isolate, and egg white powder. It also contributes significantly less to freshwater eutrophication, marine eutrophication and land use compared the protein sources mentioned above. EverPro is the prime example of sustainable ingredients, and the type of plant protein the food industry was waiting for: nutritious, multi-functional, and environmentally friendly.

Keywords: plant-based protein, upcycled, brewers' spent grain, low environmental impact, highly functional ingredient

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Authors: África Vicario, Fernando J. Álvarez, Felipe Parralejo, Fernando Aranda

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The irrigation systems of traditional agriculture, such as gravity-fed irrigation, produce a great waste of water because, generally, there is no control over the amount of water supplied in relation to the water needed. The AIRON Project tries to solve this problem by implementing an IoT-based system to sensor the irrigation plots so that the state of the crops and the amount of water used for irrigation can be known remotely. The IoT system consists of a sensor network that measures the humidity of the soil, the weather conditions (temperature, relative humidity, wind and solar radiation) and the irrigation water flow. The communication between this network and a central gateway is conducted by means of long-range wireless communication that depends on the characteristics of the irrigation plot. The main objective of the AIRON project is to deploy an IoT sensor network in two different plots of the irrigation community of Aranjuez in the Spanish region of Madrid. The first plot is 2 km away from the central gateway, so LoRa has been used as the base communication technology. The problem with this plot is the absence of mains electric power, so devices with energy-saving modes have had to be used to maximize the external batteries' use time. An ESP32 SOC board with a LoRa module is employed in this case to gather data from the sensor network and send them to a gateway consisting of a Raspberry Pi with a LoRa hat. The second plot is located 18 km away from the gateway, a range that hampers the use of LoRa technology. In order to establish reliable communication in this case, the long-term evolution (LTE) standard is used, which makes it possible to reach much greater distances by using the cellular network. As mains electric power is available in this plot, a Raspberry Pi has been used instead of the ESP32 board to collect sensor data. All data received from the two plots are stored on a proprietary server located at the irrigation management company's headquarters. The analysis of these data by means of machine learning algorithms that are currently under development should allow a short-term prediction of the irrigation water demand that would significantly reduce the waste of this increasingly valuable natural resource. The major finding of this work is the real possibility of deploying a remote sensing system for irrigated plots by using Commercial-Off-The-Shelf (COTS) devices, easily scalable and adaptable to design requirements such as the distance to the control center or the availability of mains electrical power at the site.

Keywords: internet of things, irrigation water control, LoRa, LTE, smart farming

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Authors: Chiyoung Kim, Jaegeol Yim

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Bus service is often either main or the only public transportation available in cities. In metropolitan areas, both subways and buses are available whereas in the medium sized cities buses are usually the only type of public transportation available. Bus Information Systems (BIS) provide current locations of running buses, efficient routes to travel from one place to another, points of interests around a given bus stop, a series of bus stops consisting of a given bus route, and so on to users. Thanks to BIS, people do not have to waste time at a bus stop waiting for a bus because BIS provides exact information on bus arrival times at a given bus stop. Therefore, BIS does a lot to promote the use of buses contributing to pollution reduction and saving natural resources. BIS implementation costs a huge amount of budget as it requires a lot of special equipment such as road side equipment, automatic vehicle identification and location systems, trunked radio systems, and so on. Consequently, medium and small sized cities with a low budget cannot afford to install BIS even though people in these cities need BIS service more desperately than people in metropolitan areas. It is possible to provide BIS service at virtually no cost under the assumption that everybody carries a smartphone and there is at least one person with a smartphone in a running bus who is willing to reveal his/her location details while he/she is sitting in a bus. This assumption is usually true in the real world. The smartphone penetration rate is greater than 100% in the developed countries and there is no reason for a bus driver to refuse to reveal his/her location details while driving. We have developed a mobile app that periodically reads values of sensors including GPS and sends GPS data to the server when the bus stops or when the elapsed time from the last send attempt is greater than a threshold. This app detects the bus stop state by investigating the sensor values. The server that receives GPS data from this app has also been developed. Under the assumption that the current locations of all running buses collected by the mobile app are recorded in a database, we have also developed a web site that provides all kinds of information that most BISs provide to users through the Internet. The development environment is: OS: Windows 7 64bit, IDE: Eclipse Luna 4.4.1, Spring IDE 3.7.0, Database: MySQL 5.1.7, Web Server: Apache Tomcat 7.0, Programming Language: Java 1.7.0_79. Given a start and a destination bus stop, it finds a shortest path from the start to the destination using the Dijkstra algorithm. Then, it finds a convenient route considering number of transits. For the user interface, we use the Google map. Template classes that are used by the Controller, DAO, Service and Utils classes include BUS, BusStop, BusListInfo, BusStopOrder, RouteResult, WalkingDist, Location, and so on. We are now integrating the mobile app system and the web app system.

Keywords: bus information system, GPS, mobile app, web site

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Authors: Mukul Sharma, Madhusmita Das, Sundeep Chaitanya Vedithi

Abstract:

Leprosy is a chronic human disease caused by Mycobacterium leprae, that cannot be cultured in vitro. Though treatable with multidrug therapy (MDT), recently, bacteria reported resistance to multiple antibiotics. Targeting DNA replication and repair pathways can serve as the foundation of developing new anti-leprosy drugs. Due to the absence of an axenic culture medium for the propagation of M. leprae, studying cellular processes, especially those belonging to DNA repair pathways, is challenging. Genomic understanding of M. Leprae harbors several protein-coding genes with no previously assigned function known as 'hypothetical proteins'. Here, we report identification and expression of known and hypothetical DNA repair genes from a human skin biopsy and mouse footpads that are involved in base excision repair, direct reversal repair, and SOS response. Initially, a bioinformatics approach was employed based on sequence similarity, identification of known protein domains to screen the hypothetical proteins in the genome of M. leprae, that are potentially related to DNA repair mechanisms. Before testing on clinical samples, pure stocks of bacterial reference DNA of M. leprae (NHDP63 strain) was used to construct standard graphs to validate and identify lower detection limit in the qPCR experiments. Primers were designed to amplify the respective transcripts, and PCR products of the predicted size were obtained. Later, excisional skin biopsies of newly diagnosed untreated, treated, and drug resistance leprosy cases from SIHR & LC hospital, Vellore, India were taken for the extraction of RNA. To determine the presence of the predicted transcripts, cDNA was generated from M. leprae mRNA isolated from clinically confirmed leprosy skin biopsy specimen across all the study groups. Melting curve analysis was performed to determine the integrity of the amplification and to rule out primer‑dimer formation. The Ct values obtained from qPCR were fitted to standard curve to determine transcript copy number. Same procedure was applied for M. leprae extracted after processing a footpad of nude mice of drug sensitive and drug resistant strains. 16S rRNA was used as positive control. Of all the 16 genes involved in BER, DR, and SOS, differential expression pattern of the genes was observed in terms of Ct values when compared to human samples; this was because of the different host and its immune response. However, no drastic variation in gene expression levels was observed in human samples except the nth gene. The higher expression of nth gene could be because of the mutations that may be associated with sequence diversity and drug resistance which suggests an important role in the repair mechanism and remains to be explored. In both human and mouse samples, SOS system – lexA and RecA, and BER genes AlkB and Ogt were expressing efficiently to deal with possible DNA damage. Together, the results of the present study suggest that DNA repair genes are constitutively expressed and may provide a reference for molecular diagnosis, therapeutic target selection, determination of treatment and prognostic judgment in M. leprae pathogenesis.

Keywords: DNA repair, human biopsy, hypothetical proteins, mouse footpads, Mycobacterium leprae, qPCR

Procedia PDF Downloads 87

Authors: Ila Thakur, Atul Srivastava, Shyamprasad Karagadde

Abstract:

The phenomenon of double-diffusive convection is driven by density gradients created by two different components (e.g., temperature and concentration) having different molecular diffusivities. The evolution of horizontal double-diffusive layers (DDLs) is one of the outcomes of double-diffusive convection occurring in a laterally/vertically cooled rectangular cavity having a pre-existing vertically stable composition field. The present work mainly focuses on different characteristics of the formation and merging of double-diffusive layers by imposing lateral/vertical thermal gradients in a vertically stable compositional field. A CFD-based twodimensional fluent model has been developed for the investigation of the aforesaid phenomena. The configuration containing vertical thermal gradients shows the evolution and merging of DDLs, where, elements from the same horizontal plane move vertically and mix with surroundings, creating a horizontal layer. In the configuration of lateral thermal gradients, a specially oriented convective roll was found inside each DDL and each roll was driven by the competing density change due to the already existing composition field and imposed thermal field. When the thermal boundary layer near the vertical wall penetrates the salinity interface, it can disrupt the compositional interface and can lead to layer merging. Different analytical scales were quantified and compared for both configurations. Various combinations of solutal and thermal Rayleigh numbers were investigated to get three different regimes, namely; stagnant regime, layered regime and unicellular regime. For a particular solutal Rayleigh number, a layered structure can originate only for a range of thermal Rayleigh numbers. Lower thermal Rayleigh numbers correspond to a diffusion-dominated stagnant regime. Very high thermal Rayleigh corresponds to a unicellular regime with high convective mixing. Different plots identifying these three regimes, number, thickness and time of existence of DDLs have been studied and plotted. For a given solutal Rayleigh number, an increase in thermal Rayleigh number increases the width but decreases both the number and time of existence of DDLs in the fluid domain. Sudden peaks in the velocity and heat transfer coefficient have also been observed and discussed at the time of merging. The present study is expected to be useful in correlating the double-diffusive convection in many large-scale applications including oceanography, metallurgy, geology, etc. The model has also been developed for three-dimensional geometry, but the results were quite similar to that of 2-D simulations.

Keywords: double diffusive layers, natural convection, Rayleigh number, thermal gradients, compositional gradients

Procedia PDF Downloads 70

Authors: Aiman Mazhar Qureshi, Ahmed Rachid

Abstract:

Extreme heat events are emerging human environmental health concerns in dense urban areas due to anthropogenic activities. High spatial and temporal resolution heat maps are important for urban heat adaptation and mitigation, helping to indicate hotspots that are required for the attention of city planners. The Heat Vulnerability Index (HVI) is the important approach used by decision-makers and urban planners to identify heat-vulnerable communities and areas that require heat stress mitigation strategies. Amiens is a medium-sized French city, where the average temperature has been increasing since the year 2000 by +1°C. Extreme heat events are recorded in the month of July for the last three consecutive years, 2018, 2019 and 2020. Poor air quality, especially ground-level ozone, has been observed mainly during the same hot period. In this study, we evaluated the HVI in Amiens during extreme heat days recorded last three years (2018,2019,2020). The Principal Component Analysis (PCA) technique is used for fine-scale vulnerability mapping. The main data we considered for this study to develop the HVI model are (a) socio-economic and demographic data; (b) Air pollution; (c) Land use and cover; (d) Elderly heat-illness; (e) socially vulnerable; (f) Remote sensing data (Land surface temperature (LST), mean elevation, NDVI and NDWI). The output maps identified the hot zones through comprehensive GIS analysis. The resultant map shows that high HVI exists in three typical areas: (1) where the population density is quite high and the vegetation cover is small (2) the artificial surfaces (built-in areas) (3) industrial zones that release thermal energy and ground-level ozone while those with low HVI are located in natural landscapes such as rivers and grasslands. The study also illustrates the system theory with a causal diagram after data analysis where anthropogenic activities and air pollution appear in correspondence with extreme heat events in the city. Our suggested index can be a useful tool to guide urban planners and municipalities, decision-makers and public health professionals in targeting areas at high risk of extreme heat and air pollution for future interventions adaptation and mitigation measures.

Keywords: heat vulnerability index, heat mapping, heat health-illness, remote sensing, urban heat mitigation

Procedia PDF Downloads 124