Search results for: adaptive and non-adaptive spectral estimation

Authors: Pragati Sirohi, Vivek Singh Rana

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Brand is a name, term, sign, symbol or design or a combination of all these which is intended to identify the goods or services of one seller or a group of sellers and to differentiate them from those of the competitors and perception influences purchase decisions here and so building that perception is critical. The FMCG industry is a low margin business. Volumes hold the key to success in this industry. Therefore, the industry has a strong emphasis on marketing. Creating strong brands is important for FMCG companies and they devote considerable money and effort in developing brands. Brand loyalty is fickle. Companies know this and that is why they relentlessly work towards brand building. The purpose of the study is a comparison between Indian and Multinational companies with regard to FMCG sector in India. It has been hypothesized that after liberalization the Indian companies has taken up the challenge of globalization and some of these are giving a stiff competition to MNCs. There is an existence of strong brand image of MNCs compared to Indian companies. Advertisement expenditures of MNCs are proportionately higher compared to Indian counterparts. The operational area of the study is the country as a whole. Continuous time series data is available from 1996-2014 for the selected 8 companies. The selection of these companies is done on the basis of their large market share, brand equity and prominence in the market. Research methodology focuses on finding trend growth rates of market capitalization, net worth, and brand values through regression analysis by the usage of secondary data from prowess database developed by CMIE (Centre for monitoring Indian Economy). Estimation of brand values of selected FMCG companies is being attempted, which can be taken to be the excess of market capitalization over the net worth of a company. Brand value indices are calculated. Correlation between brand values and advertising expenditure is also measured to assess the effect of advertising on branding. Major results indicate that although MNCs enjoy stronger brand image but few Indian companies like ITC is the outstanding leader in terms of its market capitalization and brand values. Dabur and Tata Global Beverages Ltd are competing equally well on these values. Advertisement expenditures are the highest for HUL followed by ITC, Colgate and Dabur which shows that Indian companies are not behind in the race. Although advertisement expenditures are playing a role in brand building process there are many other factors which affect the process. Also, brand values are decreasing over the years for FMCG companies in India which show that competition is intense with aggressive price wars and brand clutter. Implications for Indian companies are that they have to consistently put in proactive and relentless efforts in their brand building process. Brands need focus and consistency. Brand longevity without innovation leads to brand respect but does not create brand value.

Keywords: brand value, FMCG, market capitalization, net worth

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Authors: Alexander K. Guo

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PM2.5 poses a large threat to people’s health and the environment and is an issue of large concern in Beijing, brought to the attention of the government by the media. In addition, both the United States Embassy in Beijing and the government of China have increased monitoring of PM2.5 in recent years, and have made real-time data available to the public. This report utilizes hourly historical data (2008-2016) from the U.S. Embassy in Beijing for the first time. The first objective was to attempt to fit probability distributions to the data to better predict a number of days exceeding the standard, and the second was to uncover any yearly, seasonal, monthly, daily, and hourly patterns and trends that may arise to better understand of air control policy. In these data, 66,650 hours and 2687 days provided valid data. Lognormal, gamma, and Weibull distributions were fit to the data through an estimation of parameters. The Chi-squared test was employed to compare the actual data with the fitted distributions. The data were used to uncover trends, patterns, and improvements in PM2.5 concentration over the period of time with valid data in addition to specific periods of time that received large amounts of media attention, analyzed to gain a better understanding of causes of air pollution. The data show a clear indication that Beijing’s air quality is unhealthy, with an average of 94.07µg/m3 across all 66,650 hours with valid data. It was found that no distribution fit the entire dataset of all 2687 days well, but each of the three above distribution types was optimal in at least one of the yearly data sets, with the lognormal distribution found to fit recent years better. An improvement in air quality beginning in 2014 was discovered, with the first five months of 2016 reporting an average PM2.5 concentration that is 23.8% lower than the average of the same period in all years, perhaps the result of various new pollution-control policies. It was also found that the winter and fall months contained more days in both good and extremely polluted categories, leading to a higher average but a comparable median in these months. Additionally, the evening hours, especially in the winter, reported much higher PM2.5 concentrations than the afternoon hours, possibly due to the prohibition of trucks in the city in the daytime and the increased use of coal for heating in the colder months when residents are home in the evening. Lastly, through analysis of special intervals that attracted media attention for either unnaturally good or bad air quality, the government’s temporary pollution control measures, such as more intensive road-space rationing and factory closures, are shown to be effective. In summary, air quality in Beijing is improving steadily and do follow standard probability distributions to an extent, but still needs improvement. Analysis will be updated when new data become available.

Keywords: Beijing, distribution, patterns, pm2.5, trends

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Authors: V. Jayanthi

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Urbanization and pace of urbanization have increased tremendously in last few decades. More towns are now getting converted into cities. Urbanization trend is seen all over the world but is becoming most dominant in Asia. Today, the scale of urbanization in India is so huge that Indian cities are among the fastest-growing in the world, including Bangalore, Hyderabad, Pune, Chennai, Delhi, and Mumbai. Urbanization remains a single predominant factor that is continuously linked to the destruction of urban green spaces. With reference to Chennai as a case study, which is suffering from rapid deterioration of its green spaces, this paper sought to fill this gap by exploring key factors aside urbanization that is responsible for the destruction of green spaces. The paper relied on a research approach and triangulated data collection techniques such as interviews, focus group discussion, personal observation and retrieval of archival data. It was observed that apart from urbanization, problem of ownership of green space lands, low priority to green spaces, poor maintenance, enforcement of development controls, wastage of underpass spaces, and uncooperative attitudes of the general public, play a critical role in the destruction of urban green spaces. Therefore the paper narrows down to a point, that for a city to have a proper sustainable urban green space, broader city development plans are essential. Though rapid urbanization is an indicator of positive development, it is also accompanied by a host of challenges. Chennai lost a lot of greenery, as the city urbanized rapidly that led to a steep fall in vegetation cover. Environmental deterioration will be the big price we pay if Chennai continues to grow at the expense of greenery. Soaring skyscrapers, multistoried complexes, gated communities, and villas, frame the iconic skyline of today’s Chennai city which reveals that we overlook the importance of our green cover, which is important to balance our urban and lung spaces. Chennai, with a clumped landscape at the center of the city, is predicted to convert 36% of its total area into urban areas by 2026. One major issue is that a city designed and planned in isolation creates underused spaces all around the cities which are of negligence. These urban voids are dead, underused, unused spaces in the cities that are formed due to inefficient decision making, poor land management, and poor coordination. Urban voids have huge potential of creating a stronger urban fabric, exploited as public gathering spaces, pocket parks or plazas or just enhance public realm, rather than dumping of debris and encroachments. Flyovers need to justify their existence themselves by being more than just traffic and transport solutions. The vast, unused space below the Kathipara flyover is a case in point. This flyover connects three major routes: Tambaram, Koyambedu, and Adyar. This research will focus on the concept of urban voids, how these voids under the flyovers, can be used for place making process, how this space beneath flyovers which are neglected, can be a part of the urban realm through urban design and landscaping.

Keywords: landscape design, flyovers, public spaces, reclaiming lost spaces, urban voids

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Authors: Diana F. Lopes, Jorge Simoes, José Martins, Eduardo Castro

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Health professionals are the keystone of any health system, by delivering health services to the population. Given the time and cost involved in training new health professionals, the planning process of the health workforce is particularly important as it ensures a proper balance between the supply and demand of these professionals and it plays a central role on the Health 2020 policy. In the past 40 years, the planning of the health workforce in Portugal has been conducted in a reactive way lacking a prospective vision based on an integrated, comprehensive and valid analysis. This situation may compromise not only the productivity and the overall socio-economic development but the quality of the healthcare services delivered to patients. This is even more critical given the expected shortage of the health workforce in the future. Furthermore, Portugal is facing an aging context of some professional classes (physicians and nurses). In 2015, 54% of physicians in Portugal were over 50 years old, and 30% of all members were over 60 years old. This phenomenon associated to an increasing emigration of young health professionals and a change in the citizens’ illness profiles and expectations must be considered when planning resources in healthcare. The perspective of sudden retirement of large groups of professionals in a short time is also a major problem to address. Another challenge to embrace is the health workforce imbalances, in which Portugal has one of the lowest nurse to physician ratio, 1.5, below the European Region and the OECD averages (2.2 and 2.8, respectively). Within the scope of the HEALTH 2040 project – which aims to estimate the ‘Future needs of human health resources in Portugal till 2040’ – the present study intends to get a comprehensive dynamic approach of the problem, by (i) estimating the needs of physicians and nurses in Portugal, by specialties and by quinquenium till 2040; (ii) identifying the training needs of physicians and nurses, in medium and long term, till 2040, and (iii) estimating the number of students that must be admitted into medicine and nursing training systems, each year, considering the different categories of specialties. The development of such approach is significantly more critical in the context of limited budget resources and changing health care needs. In this context, this study presents the drivers of the healthcare needs’ evolution (such as the demographic and technological evolution, the future expectations of the users of the health systems) and it proposes a Bayesian methodology, combining the best available data with experts opinion, to model such evolution. Preliminary results considering different plausible scenarios are presented. The proposed methodology will be integrated in a user-friendly decision support system so it can be used by politicians, with the potential to measure the impact of health policies, both at the regional and the national level.

Keywords: bayesian estimation, health economics, health workforce planning, human health resources planning

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Authors: Ivo Zution Goncalves, Christopher M. U. Neale, Hiran Medeiros, Everardo Mantovani, Natalia Souza

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Multispectral and thermal infrared imagery from satellite sensors coupled with climate and soil datasets were used to estimate evapotranspiration and biomass in center pivots planted to maize in Brazil during the 2016 season. The hybrid remote sensing based model named Spatial EvapoTranspiration Modelling Interface (SETMI) was applied using multispectral and thermal infrared imagery from the Landsat Thematic Mapper instrument. Field data collected by the IRRIGER center pivot management company included daily weather information such as maximum and minimum temperature, precipitation, relative humidity for estimating reference evapotranspiration. In addition, soil water content data were obtained every 0.20 m in the soil profile down to 0.60 m depth throughout the season. Early season soil samples were used to obtain water-holding capacity, wilting point, saturated hydraulic conductivity, initial volumetric soil water content, layer thickness, and saturated volumetric water content. Crop canopy development parameters and irrigation application depths were also inputs of the model. The modeling approach is based on the reflectance-based crop coefficient approach contained within the SETMI hybrid ET model using relationships developed in Nebraska. The model was applied to several fields located in Minas Gerais State in Brazil with approximate latitude: -16.630434 and longitude: -47.192876. The model provides estimates of real crop evapotranspiration (ET), crop irrigation requirements and all soil water balance outputs, including biomass estimation using multi-temporal satellite image inputs. An interpolation scheme based on the growing degree-day concept was used to model the periods between satellite inputs, filling the gaps between image dates and obtaining daily data. Actual and accumulated ET, accumulated cold temperature and water stress and crop water requirements estimated by the model were compared with data measured at the experimental fields. Results indicate that the SETMI modeling approach using data assimilation, showed reliable daily ET and crop water requirements for maize, interpolated between remote sensing observations, confirming the applicability of the SETMI model using new relationships developed in Nebraska for estimating mainly ET and water requirements in Brazil under tropical conditions.

Keywords: basal crop coefficient, irrigation, remote sensing, SETMI

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Authors: Juliane Toce, Steven Holochwost

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A substantial and growing literature has demonstrated that arts education benefits young children’s socioemotional and cognitive development. Less is known about the capacity of arts-integrated instruction to yield benefits to similar domains, particularly among demographically and socioeconomically diverse groups of young children. However, the small literature on this topic suggests that arts-integrated instruction may foster young children’s socioemotional and cognitive development by presenting opportunities to 1) engage in instructional content in diverse ways, 2) experience and regulate strong emotions, 3) experience growth-oriented feedback, and 4) engage in collaborative work with peers. Start with the Art is a new program of arts-integrated instruction currently being implemented in four schools in a school district that serves students from a diverse range of backgrounds. The program employs a co-teaching model in which teaching artists and classroom teachers engage in collaborative lesson planning and instruction over the course of the academic year and is currently the focus of an impact study featuring a randomized-control design, as well as an implementation study, both of which are funded through an Educational Innovation and Research grant from the United States Department of Education. The paper will present the early results from the Start with the Art implementation study. These results will provide an overview of the extent to which the program was implemented in accordance with design, with a particular emphasis on the degree to which the four opportunities enumerated above (e.g., opportunities to engage in instructional content in diverse ways) were presented to students. There will be a review key factors that may influence the fidelity of implementation, including classroom teachers’ reception of the program and the extent to which extant conditions in the classroom (e.g., the overall level of classroom organization) may have impacted implementation fidelity. With the explicit purpose of creating a program that values and meets the needs of the teachers and students, Start with the Art incorporates the feedback from individuals participating in the intervention. Tracing its trajectory from inception to ongoing development and examining the adaptive changes made in response to teachers' transformative experiences in the post-pandemic classroom, Start with the Art continues to solicit input from experts in integrating artistic content into core curricula within educational settings catering to students from under-represented backgrounds in the arts. Leveraging the input from this rich consortium of experts has allowed for a comprehensive evaluation of the program’s implementation. The early findings derived from the implementation study emphasize the potential of arts-integrated instruction to incorporate restorative practices. Such practices serve as a crucial support system for both students and educators, providing avenues for children to express themselves, heal emotionally, and foster social development, while empowering teachers to create more empathetic, inclusive, and supportive learning environments. This all-encompassing analysis spotlights Start with the Art’s adaptability to any learning environment through the program’s effectiveness, resilience, and its capacity to transform - through art - the classroom experience within the ever-evolving landscape of education.

Keywords: arts-integration, social emotional learning, diverse learners, co-teaching, teaching artists, post-pandemic teaching

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Authors: Beatriz González-rodrigo, Diego Hidalgo-leiva, Omar Flores, Claudia Germoso, Maribel Jiménez-martínez, Laura Navas-sánchez, Belén Orta, Nicola Tarque, Orlando Hernández- Rubio, Miguel Marchamalo, Juan Gregorio Rejas, Belén Benito-oterino

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Cities facing seismic hazard necessitate detailed risk assessments for effective urban planning and vulnerability identification, ensuring the safety and sustainability of urban infrastructure. Comprehensive studies involving seismic hazard, vulnerability, and exposure evaluations are pivotal for estimating potential losses and guiding proactive measures against seismic events. However, broad-scale traditional risk studies limit consideration of specific local threats and identify vulnerable housing within a structural typology. Achieving precise results at neighbourhood levels demands higher resolution seismic hazard exposure, and vulnerability studies. This research aims to bolster sustainability and safety against seismic disasters in three Central American and Caribbean capitals. It integrates geospatial techniques and artificial intelligence into seismic risk studies, proposing cost-effective methods for exposure data collection and damage prediction. The methodology relies on prior seismic threat studies in pilot zones, utilizing existing exposure and vulnerability data in the region. Emphasizing detailed building attributes enables the consideration of behaviour modifiers affecting seismic response. The approach aims to generate detailed risk scenarios, facilitating prioritization of preventive actions pre-, during, and post-seismic events, enhancing decision-making certainty. Detailed risk scenarios necessitate substantial investment in fieldwork, training, research, and methodology development. Regional cooperation becomes crucial given similar seismic threats, urban planning, and construction systems among involved countries. The outcomes hold significance for emergency planning and national and regional construction regulations. The success of this methodology depends on cooperation, investment, and innovative approaches, offering insights and lessons applicable to regions facing moderate seismic threats with vulnerable constructions. Thus, this framework aims to fortify resilience in seismic-prone areas and serves as a reference for global urban planning and disaster management strategies. In conclusion, this research proposes a comprehensive framework for seismic risk assessment in high-risk urban areas, emphasizing detailed studies at finer resolutions for precise vulnerability evaluations. The approach integrates regional cooperation, geospatial technologies, and adaptive fragility curve adjustments to enhance risk assessment accuracy, guiding effective mitigation strategies and emergency management plans.

Keywords: assessment, behaviour modifiers, emergency management, mitigation strategies, resilience, vulnerability

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Authors: Alisawi Alaa T., Collins P. E. F.

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The analysis and evaluation of slope stability and landslide hazards are landslide hazards are critically important in civil engineering projects and broader considerations of safety. The level of slope stability risk should be identified due to its significant and direct financial and safety effects. Slope stability hazard analysis is performed considering static and/or dynamic loading circumstances. To reduce and/or prevent the failure hazard caused by landslides, a sophisticated and practical hazard analysis method using advanced constitutive modeling should be developed and linked to an effective solution that corresponds to the specific type of slope stability and landslides failure risk. Previous studies on slope stability analysis methods identify the failure mechanism and its corresponding solution. The commonly used approaches include used approaches include limit equilibrium methods, empirical approaches for rock slopes (e.g., slope mass rating and Q-slope), finite element or finite difference methods, and district element codes. This study presents an overview and evaluation of these analysis techniques. Contemporary source materials are used to examine these various methods on the basis of hypotheses, the factor of safety estimation, soil types, load conditions, and analysis conditions and limitations. Limit equilibrium methods play a key role in assessing the level of slope stability hazard. The slope stability safety level can be defined by identifying the equilibrium of the shear stress and shear strength. The slope is considered stable when the movement resistance forces are greater than those that drive the movement with a factor of safety (ratio of the resistance of the resistance of the driving forces) that is greater than 1.00. However, popular and practical methods, including limit equilibrium approaches, are not effective when the slope experiences complex failure mechanisms, such as progressive failure, liquefaction, internal deformation, or creep. The present study represents the first episode of an ongoing project that involves the identification of the types of landslides hazards, assessment of the level of slope stability hazard, development of a sophisticated and practical hazard analysis method, linkage of the failure type of specific landslides conditions to the appropriate solution and application of an advanced computational method for mapping the slope stability properties in the United Kingdom, and elsewhere through geographical information system (GIS) and inverse distance weighted spatial interpolation(IDW) technique. This study investigates and assesses the different assesses the different analysis and solution techniques to enhance the knowledge on the mechanism of slope stability and landslides hazard analysis and determine the available solutions for each potential landslide failure risk.

Keywords: slope stability, finite element analysis, hazard analysis, landslides hazard

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Authors: Marcos Silva Tavares, Jamile Raquel Regazzo, Edson José de Souza Sardinha, Murilo Mesquita Baesso

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Common beans are a widely cultivated and consumed legume globally, serving as a staple food for humans, especially in developing countries, due to their nutritional characteristics. Nitrogen (N) is the most limiting nutrient for productivity, and foliar analysis is crucial to ensure balanced nitrogen fertilization. Excessive N applications can cause, either isolated or cumulatively, soil and water contamination, plant toxicity, and increase their susceptibility to diseases and pests. However, the quantification of N using conventional methods is time-consuming and costly, demanding new technologies to optimize the adequate supply of N to plants. Thus, it becomes necessary to establish constant monitoring of the foliar content of this macronutrient in plants, mainly at the V4 stage, aiming at precision management of nitrogen fertilization. In this work, the objective was to evaluate the performance of a deep learning model, Resnet-50, in the classification of foliar nitrogen in common beans using RGB images. The BRS Estilo cultivar was sown in a greenhouse in a completely randomized design with four nitrogen doses (T1 = 0 kg N ha-1, T2 = 25 kg N ha-1, T3 = 75 kg N ha-1, and T4 = 100 kg N ha-1) and 12 replications. Pots with 5L capacity were used with a substrate composed of 43% soil (Neossolo Quartzarênico), 28.5% crushed sugarcane bagasse, and 28.5% cured bovine manure. The water supply of the plants was done with 5mm of water per day. The application of urea (45% N) and the acquisition of images occurred 14 and 32 days after sowing, respectively. A code developed in Matlab© R2022b was used to cut the original images into smaller blocks, originating an image bank composed of 4 folders representing the four classes and labeled as T1, T2, T3, and T4, each containing 500 images of 224x224 pixels obtained from plants cultivated under different N doses. The Matlab© R2022b software was used for the implementation and performance analysis of the model. The evaluation of the efficiency was done by a set of metrics, including accuracy (AC), F1-score (F1), specificity (SP), area under the curve (AUC), and precision (P). The ResNet-50 showed high performance in the classification of foliar N levels in common beans, with AC values of 85.6%. The F1 for classes T1, T2, T3, and T4 was 76, 72, 74, and 77%, respectively. This study revealed that the use of RGB images combined with deep learning can be a promising alternative to slow laboratory analyses, capable of optimizing the estimation of foliar N. This can allow rapid intervention by the producer to achieve higher productivity and less fertilizer waste. Future approaches are encouraged to develop mobile devices capable of handling images using deep learning for the classification of the nutritional status of plants in situ.

Keywords: convolutional neural network, residual network 50, nutritional status, artificial intelligence

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Authors: R. Simide, T. Miard

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Integrated multi-trophic aquaculture (IMTA) is used to reduce waste from aquaculture and increase productivity by co-cultured species. In this study, we designed a recirculating multi-trophic aquaculture system which requires low energy consumption, low water renewal and easy-care. European seabass (Dicentrarchus labrax) were raised with co-cultured sea urchin (Paracentrotus lividus), deteritivorous polychaete fed on settled particulate matter, mussels (Mytilus galloprovincialis) used to extract suspended matters, macroalgae (Ulva sp.) used to uptake dissolved nutrients and gastropod (Phorcus turbinatus) used to clean the series of 4 tanks from fouling. Experiment was performed in triplicate during one month in autumn under an experimental greenhouse at the Institute Océanographique Paul Ricard (IOPR). Thanks to the absence of a physical filter, any pomp was needed to pressure water and the water flow was carried out by a single air-lift followed by gravity flow.Total suspended solids (TSS), biochemical oxygen demand (BOD5), turbidity, phytoplankton estimation and dissolved nutrients (ammonium NH₄, nitrite NO₂⁻, nitrate NO₃⁻ and phosphorus PO₄³⁻) were measured weekly while dissolved oxygen and pH were continuously recorded. Dissolved nutrients stay under the detectable threshold during the experiment. BOD5 decreased between fish and macroalgae tanks. TSS highly increased after 2 weeks and then decreased at the end of the experiment. Those results show that bioremediation can be well used for aquaculture system to keep optimum growing conditions. Fish were the only feeding species by an external product (commercial fish pellet) in the system. The others species (extractive species) were fed from waste streams from the tank above or from Ulva produced by the system for the sea urchin. In this way, between the fish aquaculture only and the addition of the extractive species, the biomass productivity increase by 5.7. In other words, the food conversion ratio dropped from 1.08 with fish only to 0.189 including all species. This experimental recirculating multi-trophic aquaculture system was efficient enough to reduce waste and increase productivity. In a second time, this technology has been reproduced at a commercial scale. The IOPR in collaboration with Les 4 Marais company run for 6 month a recirculating IMTA in 8000 m² of water allocate between 4 marsh ponds. A similar air-lift and gravity recirculating system was design and only one feeding species of shrimp (Palaemon sp.) was growth for 3 extractive species. Thanks to this joint work at the laboratory and commercial scales we will be able to challenge IMTA system and discuss about this sustainable aquaculture technology.

Keywords: bioremediation, integrated multi-trophic aquaculture (IMTA), laboratory and commercial scales, recirculating aquaculture, sustainable

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Authors: Moien Mojabi, Aurelien Hospital, Daniel Potts, Chris Young, Albert Leung

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The wave analysis is an integral part of the hydrotechnical assessment carried out during the permitting and design phases for coastal structures, such as marinas. This analysis aims in quantifying: i) the Suitability of the coastal structure design against Small Craft Harbour wave tranquility safety criterion; ii) Potential environmental impacts of the structure (e.g., effect on wave, flow, and sediment transport); iii) Mooring and dock design and iv) Requirements set by regulatory agency’s (e.g., WSA section 11 application). While a complex three-dimensional hydrodynamic modelling approach can be applied on large-scale projects, the need for an efficient and reliable wave analysis method suitable for smaller scale marina projects was identified. As a result, Tetra Tech has developed and applied an integrated analysis framework (hereafter TT approach), which takes the advantage of the state-of-the-art numerical models while preserving the level of simplicity that fits smaller scale projects. The present paper aims to describe the TT approach and highlight the key advantages of using this integrated framework in lake marina projects. The core of this methodology is made by integrating wind, water level, bathymetry, and structure geometry data. To respond to the needs of specific projects, several add-on modules have been added to the core of the TT approach. The main advantages of this method over the simplified analytical approaches are i) Accounting for the proper physics of the lake through the modelling of the entire lake (capturing real lake geometry) instead of a simplified fetch approach; ii) Providing a more realistic representation of the waves by modelling random waves instead of monochromatic waves; iii) Modelling wave-structure interaction (e.g. wave transmission/reflection application for floating structures and piles amongst others); iv) Accounting for wave interaction with the lakebed (e.g. bottom friction, refraction, and breaking); v) Providing the inputs for flow and sediment transport assessment at the project site; vi) Taking in consideration historical and geographical variations of the wind field; and vii) Independence of the scale of the reservoir under study. Overall, in comparison with simplified analytical approaches, this integrated framework provides a more realistic and reliable estimation of wave parameters (and its spatial distribution) in lake marinas, leading to a realistic hydrotechnical assessment accessible to any project size, from the development of a new marina to marina expansion and pile replacement. Tetra Tech has successfully utilized this approach since many years in the Okanagan area.

Keywords: wave modelling, wind-wave, extreme value analysis, marina

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Authors: Zheng Wang, Zhenhong Li, Jon Mills

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Ground-based synthetic aperture radar (GBSAR) represents a powerful remote sensing tool for deformation monitoring towards various geohazards, e.g. landslides, mudflows, avalanches, infrastructure failures, and the subsidence of residential areas. Unlike spaceborne SAR with a fixed revisit period, GBSAR data can be acquired with an adjustable temporal resolution through either continuous or discontinuous operation. However, challenges arise from processing high temporal-resolution continuous GBSAR data, including the extreme cost of computational random-access-memory (RAM), the delay of displacement maps, and the loss of temporal evolution. Moreover, repositioning errors between discontinuous campaigns impede the accurate measurement of surface displacements. Therefore, a versatile package with two complete chains is developed in this study in order to process both continuous and discontinuous GBSAR data and address the aforementioned issues. The first chain is based on a small-baseline subset concept and it processes continuous GBSAR images unit by unit. Images within a window form a basic unit. By taking this strategy, the RAM requirement is reduced to only one unit of images and the chain can theoretically process an infinite number of images. The evolution of surface displacements can be detected as it keeps temporarily-coherent pixels which are present only in some certain units but not in the whole observation period. The chain supports real-time processing of the continuous data and the delay of creating displacement maps can be shortened without waiting for the entire dataset. The other chain aims to measure deformation between discontinuous campaigns. Temporal averaging is carried out on a stack of images in a single campaign in order to improve the signal-to-noise ratio of discontinuous data and minimise the loss of coherence. The temporal-averaged images are then processed by a particular interferometry procedure integrated with advanced interferometric SAR algorithms such as robust coherence estimation, non-local filtering, and selection of partially-coherent pixels. Experiments are conducted using both synthetic and real-world GBSAR data. Displacement time series at the level of a few sub-millimetres are achieved in several applications (e.g. a coastal cliff, a sand dune, a bridge, and a residential area), indicating the feasibility of the developed GBSAR data processing package for deformation monitoring of a wide range of scientific and practical applications.

Keywords: ground-based synthetic aperture radar, interferometry, small baseline subset algorithm, deformation monitoring

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Authors: Sunil Sangwan, Narayan Chandra Nayak

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Over the last few decades, Indian banking system has achieved remarkable growth in its credit volume. However, one of the most disturbing facts about this growth is the uneven distribution of financial services across regions. Having witnessed limited success from all the earlier efforts towards financial inclusion targeting the rural poor and the underprivileged, provision of microfinance, of late, has emerged as a supplementary mechanism. There are two prominent modes of microfinance distribution in India namely Bank-SHG linkage (SBLP) and private Microfinance Institutions (MFIs). Ironically, such efforts also seem to have failed to achieve the desired targets as the microfinance services have witnessed skewed distribution across the states of the country. This study attempts to make a comparative analysis of the geographical skew of the SBLP and MFI in India and examine the factors influencing their regional distribution. The results indicate that microfinance services are largely concentrated in the southern region, accounting for about 50% of all microfinance clients and 49% of all microfinance loan portfolios. This is distantly followed by an eastern region where client outreach is close to 25% only. The north-eastern, northern, central, and western regions lag far behind in microfinance sectors, accounting for only 4%, 4%, 10%, and 7 % client outreach respectively. The penetration of SHGs is equally skewed, with the southern region accounting for 46% of client outreach and 70% of loan portfolios followed by an eastern region with 21% of client outreach and 13% of the loan portfolio. Contrarily, north-eastern, northern, central, western and eastern regions account for 5%, 5%, 10%, and 13% of client outreach and 3%, 3%, 7%, and 4% of loan portfolios respectively. The study examines the impact of literacy rate, rural poverty, population density, primary sector share, non-farm activities, loan default behavior and bank penetration on the microfinance penetration. The study is limited to 17 major states of the country over the period 2008-2014. The results of the GMM estimation indicate the significant positive impact of literacy rate, non-farm activities and population density on microfinance penetration across the states, while the rise in loan default seems to deter it. Rural poverty shows the significant negative impact on the spread of SBLP, while it has a positive impact on MFI penetration, hence indicating the policy of exclusion being adhered to by the formal financial system especially towards the poor. However, MFIs seem to be working as substitute mechanisms to banks to fill the gap. The findings of the study are a pointer towards enhancing financial literacy, non-farm activities, rural bank penetration and containing loan default for achieving greater microfinance prevalence.

Keywords: bank penetration, literacy rate, microfinance, primary sector share, rural non-farm activities, rural poverty

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Authors: Prachi Buche Marathe

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Karanja Laad is a city located in the Vidarbha region in the state of Maharashtra, India. It has a huge amount of tangible and intangible heritage in the form of monuments, precincts, a group of structures, festivals and procession route, which is neglected and lost with time. Three different religions Hinduism, Islam and Jainism along with associations of being a birthplace of Swami Nrusinha Saraswati, an exponent of Datta Sampradaya sect and the British colonial layer have shaped the culture and society of the place over the period. The architecture of the town Karanja Laad has enhanced its unique historic and cultural value with a combination of all these historic layers. Karanja Laad is also a traditional trading historic town with unique hybrid architectural style and has a good potential for developing as a tourist place along with the present image of a pilgrim destination of Datta Sampradaya. The aim of the research is to prepare a conservation proposal for the historic town along with the management framework. Objectives of the research are to study the evolution of Karanja town, to identify the cultural resources along with issues of the historic core of the city, to understand Datta sampradaya, and contribution of Saint Nrusinha Saraswati in the religious sect and his association as an important personality with Karanja. The methodology of the research is site visits to the Karanja city, making field surveys for documentation and discussions and questionnaires with the residents to establish heritage and identify potential and issues within the historic core thereby establishing a case for conservation. Field surveys are conducted for town level study of land use, open spaces, occupancy, ownership, traditional commodity and community, infrastructure, streetscapes, and precinct activities during the festival and non-festival period. Building level study includes establishing various typologies like residential, institutional commercial, religious, and traditional infrastructure from the mythological references like waterbodies (kund), lake and wells. One of the main issues is that the loss of the traditional footprint as well as the traditional open spaces which are getting lost due to the new illegal encroachments and lack of guidelines for the new additions to conserve the original fabric of the structures. Traditional commodities are getting lost since there is no promotion of these skills like pottery and painting. Lavish bungalows like Kannava mansion, main temple Wada (birthplace of the saint) have a huge potential to be developed as a museum by adaptive re-use which will, in turn, attract many visitors during festivals which will boost the economy. Festival procession routes can be identified and a heritage walk can be developed so as to highlight the traditional features of the town. Overall study has resulted in establishing a heritage map with 137 heritage structures identified as potential. Conservation proposal is worked out on the town level, precinct level and building level with interventions such as developing construction guidelines for further development and establishing a heritage cell consisting architects and engineers for the upliftment of the existing rich heritage of the Karanja city.

Keywords: built heritage, conservation, Datta Sampradaya, Karanja Laad, Swami Nrusinha Saraswati, procession route

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Authors: Elena Cangelosi, Wayne Beyea

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This research expands the resilience planning literature by exploring the barriers and enablers to climate and health adaptation planning for small urban, coastal Great Lakes communities. With funding from the United States Centers for Disease Control and Prevention (CDC) Climate Ready City and States Initiative, this research took place during a 3-year pilot intervention project which integrates urban planning and public health. The project used the CDC’s Building Resilience Against Climate Effects (BRACE) framework to prevent or reduce the human health impacts from climate change in Marquette County, Michigan. Using a deliberation with the analysis planning process, interviews, focus groups, and community meetings with over 25 stakeholder groups and over 100 participants identified the area’s climate-related health concerns and adaptation interventions to address those concerns. Marquette County, on the shores of Lake Superior, the largest of the Great Lakes, was selected for the project based on their existing adaptive capacity and proactive approach to climate adaptation planning. With Marquette County as the context, this study fills a gap in the adaptation literature, which currently heavily emphasizes large-urban or agriculturally-based rural areas, and largely neglects small urban areas. This research builds on the qualitative case-study, survey, and interview approach established by previous researchers on contextual barriers and enablers for adaptation planning. This research uses a case study approach, including surveys and interviews of public officials, to identify the barriers and enablers for climate and health adaptation planning for small-urban areas within a large, non-agricultural, Great Lakes county. The researchers hypothesize that the barriers and enablers will, in some cases, overlap those found in other contexts, but in many cases, will be unique to a rural setting. The study reveals that funding, staff capacity, and communication across a large, rural geography act as the main barriers, while strong networks and collaboration, interested leaders, and community interest through a strong human-land connection act as the primary enablers. Challenges unique to rural areas are revealed, including weak opportunities for grant funding, large geographical distances, communication challenges with an aging and remote population, and the out-migration of education residents. Enablers that may be unique to rural contexts include strong collaborative relationships across jurisdictions for regional work and strong connections between residents and the land. As the factors that enable and prevent climate change planning are highly contextual, understanding, and appropriately addressing the unique factors at play for small-urban communities is key for effective planning in those areas. By identifying and addressing the barriers and enablers to climate and health adaptation planning for small-urban, coastal areas, this study can help Great Lakes communities appropriately build resilience to the adverse impacts of climate change. In addition, this research expands the breadth of research and understanding of the challenges and opportunities planners confront in the face of climate change.

Keywords: climate adaptation and resilience, climate change adaptation, climate change and urban resilience, governance and urban resilience

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Authors: Monika Soni, Chandra Bhattacharya, Siraj Ahmed Ahmed, Prafulla Dutta

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Dengue is now a globally important arboviral disease. Extensive vector surveillance has already established A.aegypti as a primary vector, but A.albopictus is now accelerating the situation through gradual adaptation to human surroundings. Global destabilization and gradual climatic shift with rising in temperature have significantly expanded the geographic range of these species These versatile vectors also host Chikungunya, Zika, and yellow fever virus. Biggest challenge faced by endemic countries now is upsurge in co-infection reported with multiple serotypes and virus co-circulation. To foster vector control interventions and mitigate disease burden, there is surge for knowledge on vector susceptibility and viral tolerance in response to multiple infections. To address our understanding on transmission dynamics and reproductive fitness, both the vectors were exposed to single and dual combinations of all four dengue serotypes by artificial feeding and followed up to third generation. Artificial feeding observed significant difference in feeding rate for both the species where A.albopictus was poor artificial feeder (35-50%) compared to A.aegypti (95-97%) Robust sequential screening of viral antigen in mosquitoes was followed by Dengue NS1 ELISA, RT-PCR and Quantitative PCR. To observe viral dissemination in different mosquito tissues Indirect immunofluorescence assay was performed. Result showed that both the vectors were infected initially with all dengue(1-4)serotypes and its co-infection (D1 and D2, D1 and D3, D1 and D4, D2 and D4) combinations. In case of DENV-2 there was significant difference in the peak titer observed at 16th day post infection. But when exposed to dual infections A.aegypti supported all combinations of virus where A.albopictus only continued single infections in successive days. There was a significant negative effect on the fecundity and fertility of both the vectors compared to control (PANOVA < 0.001). In case of dengue 2 infected mosquito, fecundity in parent generation was significantly higher (PBonferroni < 0.001) for A.albopicus compare to A.aegypti but there was a complete loss of fecundity from second to third generation for A.albopictus. It was observed that A.aegypti becomes infected with multiple serotypes frequently even at low viral titres compared to A.albopictus. Possible reason for this could be the presence of wolbachia infection in A.albopictus or mosquito innate immune response, small RNA interference etc. Based on the observations it could be anticipated that transovarial transmission may not be an important phenomenon for clinical disease outcome, due to the absence of viral positivity by third generation. Also, Dengue NS1 ELISA can be used for preliminary viral detection in mosquitoes as more than 90% of the samples were found positive compared to RT-PCR and viral load estimation.

Keywords: co-infection, dengue, reproductive fitness, viral quantification

Procedia PDF Downloads 201

Authors: Supria Sarkar, Vasit Sagan, Sourav Bhadra, Meghnath Pokharel, Felix B.Fritschi

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Soybean and their derivatives are very important agricultural commodities around the world because of their wide applicability in human food, animal feed, biofuel, and industries. However, the significance of soybean production depends on the quality of the soybean seeds rather than the yield alone. Seed composition is widely dependent on plant physiological properties, aerobic and anaerobic environmental conditions, nutrient content, and plant phenological characteristics, which can be captured by high temporal resolution remote sensing datasets. Planet scope (PS) satellite images have high potential in sequential information of crop growth due to their frequent revisit throughout the world. In this study, we estimate soybean seed composition while the plants are in the field by utilizing PlanetScope (PS) satellite images and different machine learning algorithms. Several experimental fields were established with varying genotypes and different seed compositions were measured from the samples as ground truth data. The PS images were processed to extract 462 hand-crafted vegetative and textural features. Four machine learning algorithms, i.e., partial least squares (PLSR), random forest (RFR), gradient boosting machine (GBM), support vector machine (SVM), and two recurrent neural network architectures, i.e., long short-term memory (LSTM) and gated recurrent unit (GRU) were used in this study to predict oil, protein, sucrose, ash, starch, and fiber of soybean seed samples. The GRU and LSTM architectures had two separate branches, one for vegetative features and the other for textures features, which were later concatenated together to predict seed composition. The results show that sucrose, ash, protein, and oil yielded comparable prediction results. Machine learning algorithms that best predicted the six seed composition traits differed. GRU worked well for oil (R-Squared: of 0.53) and protein (R-Squared: 0.36), whereas SVR and PLSR showed the best result for sucrose (R-Squared: 0.74) and ash (R-Squared: 0.60), respectively. Although, the RFR and GBM provided comparable performance, the models tended to extremely overfit. Among the features, vegetative features were found as the most important variables compared to texture features. It is suggested to utilize many vegetation indices for machine learning training and select the best ones by using feature selection methods. Overall, the study reveals the feasibility and efficiency of PS images and machine learning for plot-level seed composition estimation. However, special care should be given while designing the plot size in the experiments to avoid mixed pixel issues.

Keywords: agriculture, computer vision, data science, geospatial technology

Procedia PDF Downloads 137

Authors: Waleed Omri

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With the growth of the small business sector in emerging markets, developing a better understanding of what drives 'day-to-day' entrepreneurial activities has become an important issue for academicians and practitioners. Innovation, as an entrepreneurial behavior, revolves around individuals who creatively engage in new organizational efforts. In a similar vein, the innovation behaviors and processes at the organizational member level are central to any corporate entrepreneurship strategy. Despite the broadly acknowledged importance of entrepreneurship and innovation at the individual level in the establishment of successful ventures, the literature lacks evidence on how entrepreneurs can effectively harness their skills and knowledge in the workplace. The existing literature illustrates that religion can impact the day-to-day work behavior of entrepreneurs, managers, and employees. Religious beliefs and practices could affect daily entrepreneurial activities by fostering mental abilities and traits such as creativity, intelligence, and self-efficacy. In the present study, we define religious capital as a set of personal and intangible resources, skills, and competencies that emanate from an individual’s religious values, beliefs, practices, and experiences and may be used to increase the quality of economic activities. Religious beliefs and practices give individuals a religious satisfaction, which can lead them to perform better in the workplace. In addition, religious ethics and practices have been linked to various positive employee outcomes in terms of organizational change, job satisfaction, and entrepreneurial intensity. As investigations of their consequences beyond direct task performance are still scarce, we explore if religious capital plays a role in entrepreneurs’ innovative behavior. In sum, this study explores the determinants of individual entrepreneurial behavior by investigating the relationship between religious capital and entrepreneurs’ innovative behavior in the context of small businesses. To further explain and clarify the religious capital-innovative behavior link, the present study proposes a model to examine the mediating role of entrepreneurial creativity. We use both Islamic work ethics (IWE) and Islamic religious practices (IRP) to measure Islamic religious capital. We use structural equation modeling with a robust maximum likelihood estimation to analyze data gathered from 289 Tunisian small businesses and to explore the relationships among the above-described variables. In line with the theory of planned behavior, only religious work ethics are found to increase the innovative behavior of small businesses’ owner-managers. Our findings also clearly demonstrate that the connection between religious capital-related variables and innovative behavior is better understood if the influence of entrepreneurial creativity, as a mediating variable of the aforementioned relationship, is taken into account. By incorporating both religious capital and entrepreneurial creativity into the innovative behavior analysis, this study provides several important practical implications for promoting innovation process in small businesses.

Keywords: entrepreneurial behavior, small business, religion, creativity

Procedia PDF Downloads 243

Authors: Natalia Buderatskaya, Igor Ilyin, Julia Gontar, Sergey Lavrynenko, Olga Parnitskaya, Ekaterina Ilyina, Eduard Kapustin, Yana Lakhno

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Introduction: It is known that cryopreservation of oocytes has peculiar features due to the complex structure of the oocyte. One of the most important features is that mature oocytes contain meiotic division spindle which is very sensitive even to the slightest variation in temperature. Thus, the main objective of this study is to analyse the resulting euploid embryos obtained from thawed oocytes in comparison with the data of preimplantation genetic screening (PGS) in fresh embryo cycles. Material and Methods: The study was conducted at 'Medical Centre IGR' from January to July 2016. Data were analysed for 908 donor oocytes obtained in 67 cycles of assisted reproductive technologies (ART), of which 693 oocytes were used in the 51 'fresh' cycles (group A), and 215 oocytes - 16 ART programs with vitrification female gametes (group B). The average age of donors in the groups match 27.3±2.9 and 27.8±6.6 years. Stimulation of superovulation was conducted the standard way. Vitrification was performed in 1-2 hours after transvaginal puncture and thawing of oocytes were carried out in accordance with the standard protocol of Cryotech (Japan). Manipulation ICSI was performed 4-5 hours after transvaginal follicle puncture for fresh oocytes, or after defrosting - for vitrified female gametes. For the PGS, an embryonic biopsy was done on the third or on the fifth day after fertilization. Diagnostic procedures were performed using fluorescence in situ hybridization with the study of such chromosomes as 13, 16, 18, 21, 22, X, Y. Only morphologically quality blastocysts were used for the transfer, the estimation of which corresponded to the Gardner criteria. The statistical hypotheses were done using the criteria t, x^2 at a significance levels p<0.05, p<0.01, p<0.001. Results: The mean number of mature oocytes per cycle in group A was 13.58±6.65 and in group B - 13.44±6.68 oocytes for patient. The survival of oocytes after thawing totaled 95.3% (n=205), which indicates a highly effective quality of performed vitrification. The proportion of zygotes in the group A corresponded to 91.1%(n=631), in the group B – 80.5%(n=165), which shows statistically significant difference between the groups (p<0.001) and explained by non-viable oocytes elimination after vitrification. This is confirmed by the fact that on the fifth day of embryos development a statistically significant difference in the number of blastocysts was absent (p>0.05), and constituted respectively 61.6%(n=389) and 63.0%(n=104) in the groups. For the PGS performing 250 embryos analyzed in the group A and 72 embryos - in the group B. The results showed that euploidy in the studied chromosomes were 40.0%(n=100) embryos in the group A and 41.7% (n=30) - in the group B, which shows no statistical significant difference (p>0.05). The indicators of clinical pregnancies in the groups amounted to 64.7% (22 pregnancies per 34 embryo transfers) and 61.5% (8 pregnancies per 13 embryo transfers) respectively, and also had no significant difference between the groups (p>0.05). Conclusions: The results showed that the vitrification does not affect the resulting euploid embryos in assisted reproductive technologies and are not reflected in their morphological characteristics in ART programs.

Keywords: euploid embryos, preimplantation genetic screening, thawing oocytes, vitrification

Procedia PDF Downloads 334

Authors: Sadeem Aljamaan, Reem Hariri, Rahaf Alghamdi, Batool Alotaibi, Batool Alsenan, Lama Althunayyan, Areej Alnemer

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The aim of this study is to correlate between radiological findings and histopathological results in regard to the breast imaging-reporting and data system scores, size of breast masses, molecular subtypes and suspicious radiological features, as well as to assess the concordance rate in histological grade between core biopsy and surgical excision among breast cancer patients, followed by analyzing the change of concordance rate in relation to neoadjuvant chemotherapy in a Saudi population. A retrospective review was conducted over 6-year period (2017-2022) on all breast core biopsies of women preceded by radiological investigation. Chi-squared test (χ2) was performed on qualitative data, the Mann-Whitney test for quantitative non-parametric variables, and the Kappa test for grade agreement. A total of 641 cases were included. Ultrasound, mammography, and magnetic resonance imaging demonstrated diagnostic accuracies of 85%, 77.9% and 86.9%; respectively. magnetic resonance imaging manifested the highest sensitivity (72.2%), and the lowest was for ultrasound (61%). Concordance in tumor size with final excisions was best in magnetic resonance imaging, while mammography demonstrated a higher tendency of overestimation (41.9%), and ultrasound showed the highest underestimation (67.7%). The association between basal-like molecular subtypes and the breast imaging-reporting and data system score 5 classifications was statistically significant only for magnetic resonance imaging (p=0.04). Luminal subtypes demonstrated a significantly higher percentage of speculation in mammography. Breast imaging-reporting and data system score 4 manifested a substantial number of benign pathologies in all the 3 modalities. A fair concordance rate (k= 0.212 & 0.379) was demonstrated between excision and the preceding core biopsy grading with and without neoadjuvant therapy, respectively. The results demonstrated a down-grading in cases post-neoadjuvant therapy. In cases who did not receive neoadjuvant therapy, underestimation of tumor grade in biopsy was evident. In summary, magnetic resonance imaging had the highest sensitivity, specificity, positive predictive value and accuracy of both diagnosis and estimation of tumor size. Mammography demonstrated better sensitivity than ultrasound and had the highest negative predictive value, but ultrasound had better specificity, positive predictive value and accuracy. Therefore, the combination of different modalities is advantageous. The concordance rate of core biopsy grading with excision was not impacted by neoadjuvant therapy.

Keywords: breast cancer, mammography, MRI, neoadjuvant, pathology, US

Procedia PDF Downloads 82

Authors: Nurlan Smagulov, Aiman Konkabayeva, Akerke Sadykova, Arailym Serik

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Introduction. Adverse environmental factors do not immediately lead to pathological changes in the body. They can exert the growth of pre-pathology characterized by shifts in physiological, biochemical, immunological and other indicators of the body state. These disorders are unstable, reversible and indicative of body reactions. There is an opportunity to objectively judge the internal structure of the adaptive body reactions at the level of individual organs and systems. In order to obtain a stable response of the body to the chronic effects of unfavorable environmental factors of low intensity (compared to production environment factors), a time called the «lag time» is needed. The obtained results without considering this factor distort reality and, for the most part, cannot be a reliable statement of the main conclusions in any work. A technique is needed to reduce methodological errors and combine mathematical logic using statistical methods and a medical point of view, which ultimately will affect the obtained results and avoid a false correlation. Objective. Development of a methodology for assessing and predicting the environmental factors impact on the population health considering the «lag time.» Methods. Research objects: environmental and population morbidity indicators. The database on the environmental state was compiled from the monthly newsletters of Kazhydromet. Data on population morbidity were obtained from regional statistical yearbooks. When processing static data, a time interval (lag) was determined for each «argument-function» pair. That is the required interval, after which the harmful factor effect (argument) will fully manifest itself in the indicators of the organism's state (function). The lag value was determined by cross-correlation functions of arguments (environmental indicators) with functions (morbidity). Correlation coefficients (r) and their reliability (t), Fisher's criterion (F) and the influence share (R2) of the main factor (argument) per indicator (function) were calculated as a percentage. Results. The ecological situation of an industrially developed region has an impact on health indicators, but it has some nuances. Fundamentally opposite results were obtained in the mathematical data processing, considering the «lag time». Namely, an expressed correlation was revealed after two databases (ecology-morbidity) shifted. For example, the lag period was 4 years for dust concentration, general morbidity, and 3 years – for childhood morbidity. These periods accounted for the maximum values of the correlation coefficients and the largest percentage of the influencing factor. Similar results were observed in relation to the concentration of soot, dioxide, etc. The comprehensive statistical processing using multiple correlation-regression variance analysis confirms the correctness of the above statement. This method provided the integrated approach to predicting the degree of pollution of the main environmental components to identify the most dangerous combinations of concentrations of leading negative environmental factors. Conclusion. The method of assessing the «environment-public health» system (considering the «lag time») is qualitatively different from the traditional (without considering the «lag time»). The results significantly differ and are more amenable to a logical explanation of the obtained dependencies. The method allows presenting the quantitative and qualitative dependence in a different way within the «environment-public health» system.

Keywords: ecology, morbidity, population, lag time

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Authors: Zakia Hbellaq

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The Mediterranean region is considered a hotbed for climate change. Morocco is a semi-arid Mediterranean country facing water shortages and poor water quality. Its limited water resources limit the activities of various economic sectors. Most of Morocco's territory is in arid and desert areas. The potential water resources are estimated at 22 billion m3, which is equivalent to about 700 m3/inhabitant/year, and Morocco is in a state of structural water stress. Strictly speaking, the Kingdom of Morocco is one of the “very riskiest” countries, according to the World Resources Institute (WRI), which oversees the calculation of water stress risk in 167 countries. The surprising results of the Institute (WRI) rank Morocco as one of the riskiest countries in terms of water scarcity, ranking 3.89 out of 5, thus occupying the 23rd place out of a total of 167 countries, which indicates that the demand for water exceeds the available resources. Agriculture with a score of 3.89 is most affected by water stress from irrigation and places a heavy burden on the water table. Irrigation is an unavoidable technical need and has undeniable economic and social benefits given the available resources and climatic conditions. Irrigation, and therefore the agricultural sector, currently uses 86% of its water resources, while industry uses 5.5%. Although its development has undeniable economic and social benefits, it also contributes to the overfishing of most groundwater resources and the surprising decline in levels and deterioration of water quality in some aquifers. In this context, REUSE is one of the proposed solutions to reduce the water footprint of the agricultural sector and alleviate the shortage of water resources. Indeed, wastewater reuse, also known as REUSE (reuse of treated wastewater), is a step forward not only for the circular economy but also for the future, especially in the context of climate change. In particular, water reuse provides an alternative to existing water supplies and can be used to improve water security, sustainability, and resilience. However, given the introduction of organic trace pollutants or, organic micro-pollutants, the absorption of emerging contaminants, and decreasing salinity, it is possible to tackle innovative capabilities to overcome these problems and ensure food and health safety. To this end, attention will be paid to the adoption of an integrated and attractive approach, based on the reinforcement and optimization of the treatments proposed for the elimination of the organic load with particular attention to the elimination of emerging pollutants, to achieve this goal. , membrane bioreactors (MBR) as stand-alone technologies are not able to meet the requirements of WHO guidelines. They will be combined with heterogeneous Fenton processes using persulfate or hydrogen peroxide oxidants. Similarly, adsorption and filtration are applied as tertiary treatment In addition, the evaluation of crop performance in terms of yield, productivity, quality, and safety, through the optimization of Trichoderma sp strains that will be used to increase crop resistance to abiotic stresses, as well as the use of modern omics tools such as transcriptomic analysis using RNA sequencing and methylation to identify adaptive traits and associated genetic diversity that is tolerant/resistant/resilient to biotic and abiotic stresses. Hence, ensuring this approach will undoubtedly alleviate water scarcity and, likewise, increase the negative and harmful impact of wastewater irrigation on the condition of crops and the health of their consumers.

Keywords: water scarcity, food security, irrigation, agricultural water footprint, reuse, emerging contaminants

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Authors: K. Nazan Turhan, Tuğçe Ersan

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The population of the world is approximately 8 billion, and it increases uncontrollably and irrepressibly, leading to an increase in consumption. This situation causes crucial problems, and food waste is one of these. The Food and Agriculture Organization of the United Nations (FAO) defines food waste as the discarding or alternative utilization of food that is safe and nutritious for the consumption of humans along the entire food supply chain, from primary production to end household consumer level. In addition, according to the estimation of FAO, one-third of all food produced for human consumption is lost or wasted worldwide every year. Wasting food endangers natural resources and causes hunger. For instance, excessive amounts of food waste cause greenhouse gas emissions, contributing to global warming. Therefore, waste management has been gaining significance in the last few decades at both local and global levels due to the expected scarcity of resources for the increasing population of the world. There are several ways to recover food waste. According to the United States Environmental Protection Agency’s Food Recovery Hierarchy, food waste recovery ways are source reduction, feeding hungry people, feeding animals, industrial uses, composting, and landfill/incineration from the most preferred to the least preferred, respectively. Bioethanol, biodiesel, biogas, agricultural fertilizer and animal feed can be obtained from food waste that is generated by different food industries. In this project, feeding animals was selected as a food waste recovery method and food waste of a plant was used to provide ingredient uniformity. Grasshoppers were used as a protein source. In other words, the project was performed to develop a dog food product by recovery of the plant’s food waste after following some steps. The collected food waste and purchased grasshoppers were sterilized, dried and pulverized. Then, they were all mixed with 60 g agar-agar solution (4%w/v). 3 different aromas were added, separately to the samples to enhance flavour quality. Since there are differences in the required amounts of different species of dogs, fulfilling all nutritional needs is one of the problems. In other words, there is a wide range of nutritional needs in terms of carbohydrates, protein, fat, sodium, calcium, and so on. Furthermore, the requirements differ depending on age, gender, weight, height, and species. Therefore, the product that was developed contains average amounts of each substance so as not to cause any deficiency or surplus. On the other hand, it contains more protein than similar products in the market. The product was evaluated in terms of contamination and nutritional content. For contamination risk, detection of E. coli and Salmonella experiments were performed, and the results were negative. For the nutritional value test, protein content analysis was done. The protein contents of different samples vary between 33.68% and 26.07%. In addition, water activity analysis was performed, and the water activity (aw) values of different samples ranged between 0.2456 and 0.4145.

Keywords: food waste, dog food, animal nutrition, food waste recovery

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Authors: Nadarajah I. Ramesh

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Much of the research on stochastic point process models for rainfall has focused on Poisson cluster models constructed from either the Neyman-Scott or Bartlett-Lewis processes. The doubly stochastic Poisson process provides a rich class of point process models, especially for fine-scale rainfall modelling. This paper provides an account of recent development on this topic and presents the results based on some of the fine-scale rainfall models constructed from this class of stochastic point processes. Amongst the literature on stochastic models for rainfall, greater emphasis has been placed on modelling rainfall data recorded at hourly or daily aggregation levels. Stochastic models for sub-hourly rainfall are equally important, as there is a need to reproduce rainfall time series at fine temporal resolutions in some hydrological applications. For example, the study of climate change impacts on hydrology and water management initiatives requires the availability of data at fine temporal resolutions. One approach to generating such rainfall data relies on the combination of an hourly stochastic rainfall simulator, together with a disaggregator making use of downscaling techniques. Recent work on this topic adopted a different approach by developing specialist stochastic point process models for fine-scale rainfall aimed at generating synthetic precipitation time series directly from the proposed stochastic model. One strand of this approach focused on developing a class of doubly stochastic Poisson process (DSPP) models for fine-scale rainfall to analyse data collected in the form of rainfall bucket tip time series. In this context, the arrival pattern of rain gauge bucket tip times N(t) is viewed as a DSPP whose rate of occurrence varies according to an unobserved finite state irreducible Markov process X(t). Since the likelihood function of this process can be obtained, by conditioning on the underlying Markov process X(t), the models were fitted with maximum likelihood methods. The proposed models were applied directly to the raw data collected by tipping-bucket rain gauges, thus avoiding the need to convert tip-times to rainfall depths prior to fitting the models. One advantage of this approach was that the use of maximum likelihood methods enables a more straightforward estimation of parameter uncertainty and comparison of sub-models of interest. Another strand of this approach employed the DSPP model for the arrivals of rain cells and attached a pulse or a cluster of pulses to each rain cell. Different mechanisms for the pattern of the pulse process were used to construct variants of this model. We present the results of these models when they were fitted to hourly and sub-hourly rainfall data. The results of our analysis suggest that the proposed class of stochastic models is capable of reproducing the fine-scale structure of the rainfall process, and hence provides a useful tool in hydrological modelling.

Keywords: fine-scale rainfall, maximum likelihood, point process, stochastic model

Procedia PDF Downloads 278

Authors: Rowan Moore, Kai Scheffler, Eugen Damoc, Jennifer Sutton, Aaron Bailey, Stephane Houel, Simon Cubbon, Jonathan Josephs

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Purpose: MS analysis of monoclonal antibodies (mAbs) at the protein and peptide levels is critical during development and production of biopharmaceuticals. The compositions of current generation therapeutic proteins are often complex due to various modifications which may affect efficacy. Intact proteins analyzed by MS are detected in higher charge states that also provide more complexity in mass spectra. Protein analysis in native or native-like conditions with zero or minimal organic solvent and neutral or weakly acidic pH decreases charge state value resulting in mAb detection at higher m/z ranges with more spatial resolution. Methods: Three commercially available mAbs were used for all experiments. Intact proteins were desalted online using size exclusion chromatography (SEC) or reversed phase chromatography coupled on-line with a mass spectrometer. For streamlined use of the LC- MS platform we used a single SEC column and alternately selected specific mobile phases to perform separations in either denaturing or native-like conditions: buffer A (20 % ACN, 0.1 % FA) with Buffer B (100 mM ammonium acetate). For peptide analysis mAbs were proteolytically digested with and without prior reduction and alkylation. The mass spectrometer used for all experiments was a commercially available Thermo Scientific™ hybrid Quadrupole-Orbitrap™ mass spectrometer, equipped with the new BioPharma option which includes a new High Mass Range (HMR) mode that allows for improved high mass transmission and mass detection up to 8000 m/z. Results: We have analyzed the profiles of three mAbs under reducing and native conditions by direct infusion with offline desalting and with on-line desalting via size exclusion and reversed phase type columns. The presence of high salt under denaturing conditions was found to influence the observed charge state envelope and impact mass accuracy after spectral deconvolution. The significantly lower charge states observed under native conditions improves the spatial resolution of protein signals and has significant benefits for the analysis of antibody mixtures, e.g. lysine variants, degradants or sequence variants. This type of analysis requires the detection of masses beyond the standard mass range ranging up to 6000 m/z requiring the extended capabilities available in the new HMR mode. We have compared each antibody sample that was analyzed individually with mixtures in various relative concentrations. For this type of analysis, we observed that apparent native structures persist and ESI is benefited by the addition of low amounts of acetonitrile and formic acid in combination with the ammonium acetate-buffered mobile phase. For analyses on the peptide level we analyzed reduced/alkylated, and non-reduced proteolytic digests of the individual antibodies separated via reversed phase chromatography aiming to retrieve as much information as possible regarding sequence coverage, disulfide bridges, post-translational modifications such as various glycans, sequence variants, and their relative quantification. All data acquired were submitted to a single software package for analysis aiming to obtain a complete picture of the molecules analyzed. Here we demonstrate the capabilities of the mass spectrometer to fully characterize homogeneous and heterogeneous therapeutic proteins on one single platform. Conclusion: Full characterization of heterogeneous intact protein mixtures by improved mass separation on a quadrupole-Orbitrap™ mass spectrometer with extended capabilities has been demonstrated.

Keywords: disulfide bond analysis, intact analysis, native analysis, mass spectrometry, monoclonal antibodies, peptide mapping, post-translational modifications, sequence variants, size exclusion chromatography, therapeutic protein analysis, UHPLC

Procedia PDF Downloads 361

Authors: Bharti Garg, Ashleigh Cousins, Pauline Pearson, Vincent Verheyen, Paul Feron

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The presence of SO₂ in power plant flue gases makes flue gas desulfurization (FGD) an essential requirement prior to post combustion CO₂ (PCC) removal facilities. Although most of the power plants worldwide deploy FGD in order to comply with environmental regulations, generally the achieved SO₂ levels are not sufficiently low for the flue gases to enter the PCC unit. The SO₂ level in the flue gases needs to be less than 10 ppm to effectively operate the PCC installation. The existing FGD units alone cannot bring down the SO₂ levels to or below 10 ppm as required for CO₂ capture. It might require an additional scrubber along with the existing FGD unit to bring the SO₂ to the desired levels. The absence of FGD units in Australian power plants brings an additional challenge. SO₂ concentrations in Australian power station flue gas emissions are in the range of 100-600 ppm. This imposes a serious barrier on the implementation of standard PCC technologies in Australia. CSIRO’s developed CS-Cap process is a unique solution to capture SO₂ and CO₂ in a single column with single absorbent which can potentially bring cost-effectiveness to the commercial deployment of carbon capture in Australia, by removing the need for FGD. Estimated savings of removing SO₂ through a similar process as CS-Cap is around 200 MMUSD for a 500 MW Australian power plant. Pilot plant trials conducted to generate the proof of concept resulted in 100% removal of SO₂ from flue gas without utilising standard limestone-based FGD. In this work, removal of absorbed sulfur from aqueous amine absorbents generated in the pilot plant trials has been investigated by reactive crystallisation and thermal reclamation. More than 95% of the aqueous amines can be reclaimed back from the sulfur loaded absorbent via reactive crystallisation. However, the recovery of amines through thermal reclamation is limited and depends on the sulfur loading on the spent absorbent. The initial experimental work revealed that reactive crystallisation is a better fit for CS-Cap’s sulfur-rich absorbent especially when it is also capable of generating K₂SO₄ crystals of highly saleable quality ~ 99%. Initial cost estimation carried on both the technologies resulted in almost similar capital expenditure; however, the operating cost is considerably higher in thermal reclaimer than that in crystalliser. The experimental data generated in the laboratory from both the regeneration techniques have been used to generate the simulation model in Aspen Plus. The simulation model illustrates the economic benefits which could be gained by removing flue gas desulfurization prior to standard PCC unit and replacing it with a CS-Cap absorber column co-capturing CO₂ and SO₂, and it's absorbent regeneration system which would be either reactive crystallisation or thermal reclamation.

Keywords: combined capture, cost analysis, crystallisation, CS-Cap, flue gas desulfurisation, regeneration, sulfur, thermal reclamation

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Authors: Georgi Y. Georgiev, Matthew Brouillet

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This research applies the power of agent-based modeling to a pivotal question at the intersection of biology, computer science, physics, and complex systems theory about the self-organization processes in open, complex, non-equilibrium thermodynamic systems. Central to this investigation is the principle of Maximum Entropy Production (MEP). This principle suggests that such systems evolve toward states that optimize entropy production, leading to the formation of structured environments. It is hypothesized that guided by the least action principle, open thermodynamic systems identify and follow the shortest paths to transmit energy and matter, resulting in maximal entropy production, internal structure formation, and a decrease in internal entropy. Concurrently, it is predicted that there will be an increase in system information as more information is required to describe the developing structure. To test this, an agent-based model is developed simulating an ant colony's formation of a path between a food source and its nest. Utilizing the Netlogo software for modeling and Python for data analysis and visualization, self-organization is quantified by calculating the decrease in system entropy based on the potential states and distribution of the ants within the simulated environment. External entropy production is also evaluated for information increase and efficiency improvements in the system's action. Simulations demonstrated that the system begins at maximal entropy, which decreases as the ants form paths over time. A range of system behaviors contingent upon the number of ants are observed. Notably, no path formation occurred with fewer than five ants, whereas clear paths were established by 200 ants, and saturation of path formation and entropy state was reached at populations exceeding 1000 ants. This analytical approach identified the inflection point marking the transition from disorder to order and computed the slope at this point. Combined with extrapolation to the final path entropy, these parameters yield important insights into the eventual entropy state of the system and the timeframe for its establishment, enabling the estimation of the self-organization rate. This study provides a novel perspective on the exploration of self-organization in thermodynamic systems, establishing a correlation between internal entropy decrease rate and external entropy production rate. Moreover, it presents a flexible framework for assessing the impact of external factors like changes in world size, path obstacles, and friction. Overall, this research offers a robust, replicable model for studying self-organization processes in any open thermodynamic system. As such, it provides a foundation for further in-depth exploration of the complex behaviors of these systems and contributes to the development of more efficient self-organizing systems across various scientific fields.

Keywords: complexity, self-organization, agent based modelling, efficiency

Procedia PDF Downloads 68

Authors: Divya Palaniappan

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Early Childhood assessment tools must measure the quality and the appropriateness of a curriculum with respect to culture and age of the children. Preschool assessment tools lack psychometric properties and were developed to measure only few areas of development such as specific skills in music, art and adaptive behavior. Existing preschool assessment tools in India are predominantly informal and are fraught with judgmental bias of observers. The World of Discovery TM curriculum focuses on accelerating the physical, cognitive, language, social and emotional development of pre-schoolers in India through various activities. The curriculum caters to every child irrespective of their dominant intelligence as per Gardner’s Theory of Multiple Intelligence which concluded "even students as young as four years old present quite distinctive sets and configurations of intelligences". The curriculum introduces a new theme every week where, concepts are explained through various activities so that children with different dominant intelligences could understand it. For example: The ‘Insects’ theme is explained through rhymes, craft and counting corner, and hence children with one of these dominant intelligences: Musical, bodily-kinesthetic and logical-mathematical could grasp the concept. The child’s progress is evaluated using an assessment tool that measures a cluster of inter-dependent developmental areas: physical, cognitive, language, social and emotional development, which for the first time renders a multi-domain approach. The assessment tool is a 5-point rating scale that measures these Developmental aspects: Cognitive, Language, Physical, Social and Emotional. Each activity strengthens one or more of the developmental aspects. During cognitive corner, the child’s perceptual reasoning, pre-math abilities, hand-eye co-ordination and fine motor skills could be observed and evaluated. The tool differs from traditional assessment methodologies by providing a framework that allows teachers to assess a child’s continuous development with respect to specific activities in real time objectively. A pilot study of the tool was done with a sample data of 100 children in the age group 2.5 to 3.5 years. The data was collected over a period of 3 months across 10 centers in Chennai, India, scored by the class teacher once a week. The teachers were trained by psychologists on age-appropriate developmental milestones to minimize observer’s bias. The norms were calculated from the mean and standard deviation of the observed data. The results indicated high internal consistency among parameters and that cognitive development improved with physical development. A significant positive relationship between physical and cognitive development has been observed among children in a study conducted by Sibley and Etnier. In Children, the ‘Comprehension’ ability was found to be greater than ‘Reasoning’ and pre-math abilities as indicated by the preoperational stage of Piaget’s theory of cognitive development. The average scores of various parameters obtained through the tool corroborates the psychological theories on child development, offering strong face validity. The study provides a comprehensive mechanism to assess a child’s development and differentiate high performers from the rest. Based on the average scores, the difficulty level of activities could be increased or decreased to nurture the development of pre-schoolers and also appropriate teaching methodologies could be devised.

Keywords: child development, early childhood assessment, early childhood curriculum, quantitative assessment of preschool curriculum

Procedia PDF Downloads 362

Authors: S. Maniruzzaman, N. Ramanujam, Qazi Akhter Rasool, Swapan Kumar Biswas, P. Prasad, Chandrakanta Ojha

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Landslide is one of the major natural disasters in South Asian countries. Applying 2D Electrical Resistivity Tomographic Imaging estimation of geometry, thickness, and depth of failure zone of the landslide can be made. Landslide is a pertinent problem in Nilgris plateau next to Himalaya. Nilgris range consists of hard Archean metamorphic rocks. Intense weathering prevailed during the Pre-Cambrian time had deformed the rocks up to 45m depth. The landslides are dominant in the southern and eastern part of plateau of is comparatively smaller than the northern drainage basins, as it has low density of drainage; coarse texture permitted the more of infiltration of rainwater, whereas in the northern part of the plateau entombed with high density of drainage pattern and fine texture with less infiltration than run off, and low to the susceptible to landslide. To get comprehensive information about the landslide zone 2D Electrical Resistivity Tomographic imaging study with CRM 500 Resistivity meter are used in Coonoor– Mettupalyam sector of Nilgiris plateau. To calculate Factor of Safety the infinite slope model of Brunsden and Prior is used. Factor of Safety can be expressed (FS) as the ratio of resisting forces to disturbing forces. If FS < 1 disturbing forces are larger than resisting forces and failure may occur. The geotechnical parameters of soil samples are calculated on the basis upon the apparent resistivity values for litho units of measured from 2D ERT image of the landslide zone. Relationship between friction angles for various soil properties is established by simple regression analysis from apparent resistivity data. Increase of water content in slide zone reduces the effectiveness of the shearing resistance and increase the sliding movement. Time-lapse resistivity changes to slope failure is determined through geophysical Factor of Safety which depends on resistivity and site topography. This ERT technique infers soil property at variable depths in wider areas. This approach to retrieve the soil property and overcomes the limit of the point of information provided by rain gauges and porous probes. Monitoring of slope stability without altering soil structure through the ERT technique is non-invasive with low cost. In landslide prone area an automated Electrical Resistivity Tomographic Imaging system should be installed permanently with electrode networks to monitor the hydraulic precursors to monitor landslide movement.

Keywords: 2D ERT, landslide, safety factor, slope stability

Procedia PDF Downloads 317

Authors: Merve Uzuner Sahin, Kumru D. Atalay, Berna Dengiz

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In today’s competitive market, there are many alternative products that can be used in similar manner and purpose. Therefore, the utility of the product is an important issue for the preferability of the brand. This utility could be measured in terms of its functionality, durability, reliability. These all are affected by the system capabilities. Reliability is an important system design criteria for the manufacturers to be able to have high availability. Availability is the probability that a system (or a component) is operating properly to its function at a specific point in time or a specific period of times. System availability provides valuable input to estimate the production rate for the company to realize the production plan. When considering only the corrective maintenance downtime of the system, mean time between failure (MTBF) and mean time to repair (MTTR) are used to obtain system availability. Also, the MTBF and MTTR values are important measures to improve system performance by adopting suitable maintenance strategies for reliability engineers and practitioners working in a system. Failure and repair time probability distributions of each component in the system should be known for the conventional availability analysis. However, generally, companies do not have statistics or quality control departments to store such a large amount of data. Real events or situations are defined deterministically instead of using stochastic data for the complete description of real systems. A fuzzy set is an alternative theory which is used to analyze the uncertainty and vagueness in real systems. The aim of this study is to present a novel approach to compute system availability using representation of MTBF and MTTR in fuzzy numbers. Based on the experience in the system, it is decided to choose 3 different spread of MTBF and MTTR such as 15%, 20% and 25% to obtain lower and upper limits of the fuzzy numbers. To the best of our knowledge, the proposed method is the first application that is used fuzzy MTBF and fuzzy MTTR for fuzzy system availability estimation. This method is easy to apply in any repairable production system by practitioners working in industry. It is provided that the reliability engineers/managers/practitioners could analyze the system performance in a more consistent and logical manner based on fuzzy availability. This paper presents a real case study of a repairable multi-stage production line in lead-acid battery production factory in Turkey. The following is focusing on the considered wet-charging battery process which has a higher production level than the other types of battery. In this system, system components could exist only in two states, working or failed, and it is assumed that when a component in the system fails, it becomes as good as new after repair. Instead of classical methods, using fuzzy set theory and obtaining intervals for these measures would be very useful for system managers, practitioners to analyze system qualifications to find better results for their working conditions. Thus, much more detailed information about system characteristics is obtained.

Keywords: availability analysis, battery production system, fuzzy sets, triangular fuzzy numbers (TFNs)

Procedia PDF Downloads 224