Search results for: mean paltelets volume (MPV)
124 Localized Recharge Modeling of a Coastal Aquifer from a Dam Reservoir (Korba, Tunisia)
Authors: Nejmeddine Ouhichi, Fethi Lachaal, Radhouane Hamdi, Olivier Grunberger
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Located in Cap Bon peninsula (Tunisia), the Lebna dam was built in 1987 to balance local water salt intrusion taking place in the coastal aquifer of Korba. The first intention was to reduce coastal groundwater over-pumping by supplying surface water to a large irrigation system. The unpredicted beneficial effect was recorded with the occurrence of a direct localized recharge to the coastal aquifer by leakage through the geological material of the southern bank of the lake. The hydrological balance of the reservoir dam gave an estimation of the annual leakage volume, but dynamic processes and sound quantification of recharge inputs are still required to understand the localized effect of the recharge in terms of piezometry and quality. Present work focused on simulating the recharge process to confirm the hypothesis, and established a sound quantification of the water supply to the coastal aquifer and extend it to multi-annual effects. A spatial frame of 30km² was used for modeling. Intensive outcrops and geophysical surveys based on 68 electrical resistivity soundings were used to characterize the aquifer 3D geometry and the limit of the Plio-quaternary geological material concerned by the underground flow paths. Permeabilities were determined using 17 pumping tests on wells and piezometers. Six seasonal piezometric surveys on 71 wells around southern reservoir dam banks were performed during the 2019-2021 period. Eight monitoring boreholes of high frequency (15min) piezometric data were used to examine dynamical aspects. Model boundary conditions were specified using the geophysics interpretations coupled with the piezometric maps. The dam-groundwater flow model was performed using Visual MODFLOW software. Firstly, permanent state calibration based on the first piezometric map of February 2019 was established to estimate the permanent flow related to the different reservoir levels. Secondly, piezometric data for the 2019-2021 period were used for transient state calibration and to confirm the robustness of the model. Preliminary results confirmed the temporal link between the reservoir level and the localized recharge flow with a strong threshold effect for levels below 16 m.a.s.l. The good agreement of computed flow through recharge cells on the southern banks and hydrological budget of the reservoir open the path to future simulation scenarios of the dilution plume imposed by the localized recharge. The dam reservoir-groundwater flow-model simulation results approve a potential for storage of up to 17mm/year in existing wells, under gravity-feed conditions during level increases on the reservoir into the three years of operation. The Lebna dam groundwater flow model characterized a spatiotemporal relation between groundwater and surface water.Keywords: leakage, MODFLOW, saltwater intrusion, surface water-groundwater interaction
Procedia PDF Downloads 136123 Mathematical Modeling of Avascular Tumor Growth and Invasion
Authors: Meitham Amereh, Mohsen Akbari, Ben Nadler
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Cancer has been recognized as one of the most challenging problems in biology and medicine. Aggressive tumors are a lethal type of cancers characterized by high genomic instability, rapid progression, invasiveness, and therapeutic resistance. Their behavior involves complicated molecular biology and consequential dynamics. Although tremendous effort has been devoted to developing therapeutic approaches, there is still a huge need for new insights into the dark aspects of tumors. As one of the key requirements in better understanding the complex behavior of tumors, mathematical modeling and continuum physics, in particular, play a pivotal role. Mathematical modeling can provide a quantitative prediction on biological processes and help interpret complicated physiological interactions in tumors microenvironment. The pathophysiology of aggressive tumors is strongly affected by the extracellular cues such as stresses produced by mechanical forces between the tumor and the host tissue. During the tumor progression, the growing mass displaces the surrounding extracellular matrix (ECM), and due to the level of tissue stiffness, stress accumulates inside the tumor. The produced stress can influence the tumor by breaking adherent junctions. During this process, the tumor stops the rapid proliferation and begins to remodel its shape to preserve the homeostatic equilibrium state. To reach this, the tumor, in turn, upregulates epithelial to mesenchymal transit-inducing transcription factors (EMT-TFs). These EMT-TFs are involved in various signaling cascades, which are often associated with tumor invasiveness and malignancy. In this work, we modeled the tumor as a growing hyperplastic mass and investigated the effects of mechanical stress from surrounding ECM on tumor invasion. The invasion is modeled as volume-preserving inelastic evolution. In this framework, principal balance laws are considered for tumor mass, linear momentum, and diffusion of nutrients. Also, mechanical interactions between the tumor and ECM is modeled using Ciarlet constitutive strain energy function, and dissipation inequality is utilized to model the volumetric growth rate. System parameters, such as rate of nutrient uptake and cell proliferation, are obtained experimentally. To validate the model, human Glioblastoma multiforme (hGBM) tumor spheroids were incorporated inside Matrigel/Alginate composite hydrogel and was injected into a microfluidic chip to mimic the tumor’s natural microenvironment. The invasion structure was analyzed by imaging the spheroid over time. Also, the expression of transcriptional factors involved in invasion was measured by immune-staining the tumor. The volumetric growth, stress distribution, and inelastic evolution of tumors were predicted by the model. Results showed that the level of invasion is in direct correlation with the level of predicted stress within the tumor. Moreover, the invasion length measured by fluorescent imaging was shown to be related to the inelastic evolution of tumors obtained by the model.Keywords: cancer, invasion, mathematical modeling, microfluidic chip, tumor spheroids
Procedia PDF Downloads 105122 E-Governance: A Key for Improved Public Service Delivery
Authors: Ayesha Akbar
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Public service delivery has witnessed a significant improvement with the integration of information communication technology (ICT). It not only improves management structure with advanced technology for surveillance of service delivery but also provides evidence for informed decisions and policy. Pakistan’s public sector organizations have not been able to produce some good results to ensure service delivery. Notwithstanding, some of the public sector organizations in Pakistan has diffused modern technology and proved their credence by providing better service delivery standards. These good indicators provide sound basis to integrate technology in public sector organizations and shift of policy towards evidence based policy making. Rescue-1122 is a public sector organization which provides emergency services and proved to be a successful model for the provision of service delivery to save human lives and to ensure human development in Pakistan. The information about the organization has been received by employing qualitative research methodology. The information is broadly based on primary and secondary sources which includes Rescue-1122 website, official reports of organizations; UNDP (United Nation Development Program), WHO (World Health Organization) and by conducting 10 in-depth interviews with the high administrative staff of organizations who work in the Lahore offices. The information received has been incorporated with the study for the better understanding of the organization and their management procedures. Rescue-1122 represents a successful model in delivering the services in an efficient way to deal with the disaster management. The management of Rescue has strategized the policies and procedures in such a way to develop a comprehensive model with the integration of technology. This model provides efficient service delivery as well as maintains the standards of the organization. The service delivery model of rescue-1122 works on two fronts; front-office interface and the back-office interface. Back-office defines the procedures of operations and assures the compliance of the staff whereas, front-office equipped with the latest technology and good infrastructure handles the emergency calls. Both ends are integrated with satellite based vehicle tracking, wireless system, fleet monitoring system and IP camera which monitors every move of the staff to provide better services and to pinpoint the distortions in the services. The standard time of reaching to the emergency spot is 7 minutes, and during entertaining the case; driver‘s behavior, traffic volume and the technical assistance being provided to the emergency case is being monitored by front-office. Then the whole information get uploaded to the main dashboard of Lahore headquarter from the provincial offices. The latest technology is being materialized by Rescue-1122 for delivering the efficient services, investigating the flaws; if found, and to develop data to make informed decision making. The other public sector organizations of Pakistan can also develop such models to integrate technology for improving service delivery and to develop evidence for informed decisions and policy making.Keywords: data, e-governance, evidence, policy
Procedia PDF Downloads 237121 Analyzing the Investment Decision and Financing Method of the French Small and Medium-Sized Enterprises
Authors: Eliane Abdo, Olivier Colot
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SMEs are always considered as a national priority due to their contribution to job creation, innovation and growth. Once the start-up phase is crossed with encouraging results, the company enters the phase of growth. In order to improve its competitiveness, maintain and increase its market share, the company is in the necessity even the obligation to develop its tangible and intangible investments. SMEs are generally closed companies with special and critical financial situation, limited resources and difficulty to access the capital markets; their shareholders are always living in a conflict between their independence and their need to increase capital that leads to the entry of new shareholder. The capital structure was always considered the core of research in corporate finance; moreover, the financial crisis and its repercussions on the credit’s availability, especially for SMEs make SME financing a hot topic. On the other hand, financial theories do not provide answers to capital structure’s questions; they offer tools and mode of financing that are more accessible to larger companies. Yet, SME’s capital structure can’t be independent of their governance structure. The classic financial theory supposes independence between the investment decision and the financing decision. Thus, investment determines the volume of funding, but not the split between internal or external funds. In this context, we find interesting to study the hypothesis that SMEs respond positively to the financial theories applied to large firms and to check if they are constrained by conventional solutions used by large companies. In this context, this research focuses on the analysis of the resource’s structure of SME in parallel with their investments’ structure, in order to highlight a link between their assets and liabilities structure. We founded our conceptual model based on two main theoretical frameworks: the Pecking order theory, and the Trade Off theory taking into consideration the SME’s characteristics. Our data were generated from DIANE database. Five hypotheses were tested via a panel regression to understand the type of dependence between the financing methods of 3,244 French SMEs and the development of their investment over a period of 10 years (2007-2016). The results show dependence between equity and internal financing in case of intangible investments development. Moreover, this type of business is constraint to financial debts since the guarantees provided are not sufficient to meet the banks' requirements. However, for tangible investments development, SMEs count sequentially on internal financing, bank borrowing, and new shares issuance or hybrid financing. This is compliant to the Pecking Order Theory. We, therefore, conclude that unlisted SMEs incur more financial debts to finance their tangible investments more than their intangible. However, they always prefer internal financing as a first choice. This seems to be confirmed by the assumption that the profitability of the company is negatively related to the increase of the financial debt. Thus, the Pecking Order Theory predictions seem to be the most plausible. Consequently, SMEs primarily rely on self-financing and then go, into debt as a priority to finance their financial deficit.Keywords: capital structure, investments, life cycle, pecking order theory, trade off theory
Procedia PDF Downloads 104120 Low Cost LiDAR-GNSS-UAV Technology Development for PT Garam’s Three Dimensional Stockpile Modeling Needs
Authors: Mohkammad Nur Cahyadi, Imam Wahyu Farid, Ronny Mardianto, Agung Budi Cahyono, Eko Yuli Handoko, Daud Wahyu Imani, Arizal Bawazir, Luki Adi Triawan
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Unmanned aerial vehicle (UAV) technology has cost efficiency and data retrieval time advantages. Using technologies such as UAV, GNSS, and LiDAR will later be combined into one of the newest technologies to cover each other's deficiencies. This integration system aims to increase the accuracy of calculating the volume of the land stockpile of PT. Garam (Salt Company). The use of UAV applications to obtain geometric data and capture textures that characterize the structure of objects. This study uses the Taror 650 Iron Man drone with four propellers, which can fly for 15 minutes. LiDAR can classify based on the number of image acquisitions processed in the software, utilizing photogrammetry and structural science principles from Motion point cloud technology. LiDAR can perform data acquisition that enables the creation of point clouds, three-dimensional models, Digital Surface Models, Contours, and orthomosaics with high accuracy. LiDAR has a drawback in the form of coordinate data positions that have local references. Therefore, researchers use GNSS, LiDAR, and drone multi-sensor technology to map the stockpile of salt on open land and warehouses every year, carried out by PT. Garam twice, where the previous process used terrestrial methods and manual calculations with sacks. Research with LiDAR needs to be combined with UAV to overcome data acquisition limitations because it only passes through the right and left sides of the object, mainly when applied to a salt stockpile. The UAV is flown to assist data acquisition with a wide coverage with the help of integration of the 200-gram LiDAR system so that the flying angle taken can be optimal during the flight process. Using LiDAR for low-cost mapping surveys will make it easier for surveyors and academics to obtain pretty accurate data at a more economical price. As a survey tool, LiDAR is included in a tool with a low price, around 999 USD; this device can produce detailed data. Therefore, to minimize the operational costs of using LiDAR, surveyors can use Low-Cost LiDAR, GNSS, and UAV at a price of around 638 USD. The data generated by this sensor is in the form of a visualization of an object shape made in three dimensions. This study aims to combine Low-Cost GPS measurements with Low-Cost LiDAR, which are processed using free user software. GPS Low Cost generates data in the form of position-determining latitude and longitude coordinates. The data generates X, Y, and Z values to help georeferencing process the detected object. This research will also produce LiDAR, which can detect objects, including the height of the entire environment in that location. The results of the data obtained are calibrated with pitch, roll, and yaw to get the vertical height of the existing contours. This study conducted an experimental process on the roof of a building with a radius of approximately 30 meters.Keywords: LiDAR, unmanned aerial vehicle, low-cost GNSS, contour
Procedia PDF Downloads 84119 Strategies for the Optimization of Ground Resistance in Large Scale Foundations for Optimum Lightning Protection
Authors: Oibar Martinez, Clara Oliver, Jose Miguel Miranda
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In this paper, we discuss the standard improvements which can be made to reduce the earth resistance in difficult terrains for optimum lightning protection, what are the practical limitations, and how the modeling can be refined for accurate diagnostics and ground resistance minimization. Ground resistance minimization can be made via three different approaches: burying vertical electrodes connected in parallel, burying horizontal conductive plates or meshes, or modifying the own terrain, either by changing the entire terrain material in a large volume or by adding earth-enhancing compounds. The use of vertical electrodes connected in parallel pose several practical limitations. In order to prevent loss of effectiveness, it is necessary to keep a minimum distance between each electrode, which is typically around five times larger than the electrode length. Otherwise, the overlapping of the local equipotential lines around each electrode reduces the efficiency of the configuration. The addition of parallel electrodes reduces the resistance and facilitates the measurement, but the basic parallel resistor formula of circuit theory will always underestimate the final resistance. Numerical simulation of equipotential lines around the electrodes overcomes this limitation. The resistance of a single electrode will always be proportional to the soil resistivity. The electrodes are usually installed with a backfilling material of high conductivity, which increases the effective diameter. However, the improvement is marginal, since the electrode diameter counts in the estimation of the ground resistance via a logarithmic function. Substances that are used for efficient chemical treatment must be environmentally friendly and must feature stability, high hygroscopicity, low corrosivity, and high electrical conductivity. A number of earth enhancement materials are commercially available. Many are comprised of carbon-based materials or clays like bentonite. These materials can also be used as backfilling materials to reduce the resistance of an electrode. Chemical treatment of soil has environmental issues. Some products contain copper sulfate or other copper-based compounds, which may not be environmentally friendly. Carbon-based compounds are relatively inexpensive and they do have very low resistivities, but they also feature corrosion issues. Typically, the carbon can corrode and destroy a copper electrode in around five years. These compounds also have potential environmental concerns. Some earthing enhancement materials contain cement, which, after installation acquire properties that are very close to concrete. This prevents the earthing enhancement material from leaching into the soil. After analyzing different configurations, we conclude that a buried conductive ring with vertical electrodes connected periodically should be the optimum baseline solution for the grounding of a large size structure installed on a large resistivity terrain. In order to show this, a practical example is explained here where we simulate the ground resistance of a conductive ring buried in a terrain with a resistivity in the range of 1 kOhm·m.Keywords: grounding improvements, large scale scientific instrument, lightning risk assessment, lightning standards
Procedia PDF Downloads 130118 Assessing the Severity of Traffic Related Air Pollution in South-East London to School Pupils
Authors: Ho Yin Wickson Cheung, Liora Malki-Epshtein
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Outdoor air pollution presents a significant challenge for public health globally, especially in urban areas, with road traffic acting as the primary contributor to air pollution. Several studies have documented the antagonistic relation between traffic-related air pollution (TRAP) and the impact on health, especially to the vulnerable group of population, particularly young pupils. Generally, TRAP could cause damage to their brain, restricting the ability of children to learn and, more importantly, causing detrimental respiratory issues in later life. Butlittle is known about the specific exposure of children at school during the school day and the impact this may have on their overall exposure to pollution at a crucial time in their development. This project has set out to examine the air quality across primary schools in South-East London and assesses the variability of data found based on their geographic location and surroundings. Nitrogen dioxide, PM contaminants, and carbon dioxide were collected with diffusion tubes and portable monitoring equipment for eight schools across three local areas, that are Greenwich, Lewisham, and Tower Hamlets. This study first examines the geographical features of the schools surrounding (E.g., coverage of urban road structure and green infrastructure), then utilize three different methods to capture pollutants data. Moreover, comparing the obtained results with existing data from monitoring stations to understand the differences in air quality before and during the pandemic. Furthermore, most studies in this field have unfortunately neglected human exposure to pollutants and calculated based on values from fixed monitoring stations. Therefore, this paper introduces an alternative approach by calculating human exposure to air pollution from real-time data obtained when commuting within related areas (Driving routes and field walking). It is found that schools located highly close to motorways are generally not suffering from the most air pollution contaminants. Instead, one with the worst traffic congested routes nearby might also result in poor air quality. Monitored results also indicate that the annual air pollution values have slightly decreased during the pandemic. However, the majority of the data is currently still exceeding the WHO guidelines. Finally, the total human exposures for NO2 during commuting in the two selected routes were calculated. Results illustrated the total exposure for route 1 were 21,730 μm/m3 and 28,378.32 μm/m3, and for route 2 were 30,672 μm/m3 and 16,473 μm/m3. The variance that occurred might be due to the difference in traffic volume that requires further research. Exposure for NO2 during commuting was plotted with detailed timesteps that have shown their peak usually occurred while commuting. These have consolidated the initial assumption to the extremeness of TRAP. To conclude, this paper has yielded significant benefits to understanding air quality across schools in London with the new approach of capturing human exposure (Driving routes). Confirming the severity of air pollution and promoting the necessity of considering environmental sustainability for policymakers during decision making to protect society's future pillars.Keywords: air pollution, schools, pupils, congestion
Procedia PDF Downloads 112117 Leveraging Advanced Technologies and Data to Eliminate Abandoned, Lost, or Otherwise Discarded Fishing Gear and Derelict Fishing Gear
Authors: Grant Bifolchi
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As global environmental problems continue to have highly adverse effects, finding long-term, sustainable solutions to combat ecological distress are of growing paramount concern. Ghost Gear—also known as abandoned, lost or otherwise discarded fishing gear (ALDFG) and derelict fishing gear (DFG)—represents one of the greatest threats to the world’s oceans, posing a significant hazard to human health, livelihoods, and global food security. In fact, according to the UN Food and Agriculture Organization (FAO), abandoned, lost and discarded fishing gear represents approximately 10% of marine debris by volume. Around the world, many governments, governmental and non-profit organizations are doing their best to manage the reporting and retrieval of nets, lines, ropes, traps, floats and more from their respective bodies of water. However, these organizations’ ability to effectively manage files and documents about the environmental problem further complicates matters. In Ghost Gear monitoring and management, organizations face additional complexities. Whether it’s data ingest, industry regulations and standards, garnering actionable insights into the location, security, and management of data, or the application of enforcement due to disparate data—all of these factors are placing massive strains on organizations struggling to save the planet from the dangers of Ghost Gear. In this 90-minute educational session, globally recognized Ghost Gear technology expert Grant Bifolchi CET, BBA, Bcom, will provide real-world insight into how governments currently manage Ghost Gear and the technology that can accelerate success in combatting ALDFG and DFG. In this session, attendees will learn how to: • Identify specific technologies to solve the ingest and management of Ghost Gear data categories, including type, geo-location, size, ownership, regional assignment, collection and disposal. • Provide enhanced access to authorities, fisheries, independent fishing vessels, individuals, etc., while securely controlling confidential and privileged data to globally recognized standards. • Create and maintain processing accuracy to effectively track ALDFG/DFG reporting progress—including acknowledging receipt of the report and sharing it with all pertinent stakeholders to ensure approvals are secured. • Enable and utilize Business Intelligence (BI) and Analytics to store and analyze data to optimize organizational performance, maintain anytime-visibility of report status, user accountability, scheduling, management, and foster governmental transparency. • Maintain Compliance Reporting through highly defined, detailed and automated reports—enabling all stakeholders to share critical insights with internal colleagues, regulatory agencies, and national and international partners.Keywords: ghost gear, ALDFG, DFG, abandoned, lost or otherwise discarded fishing gear, data, technology
Procedia PDF Downloads 88116 Phycoremiadation of Heavy Metals by Marine Macroalgae Collected from Olaikuda, Rameswaram, Southeast Coast of India
Authors: Suparna Roy, Anatharaman Perumal
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The industrial effluent with high amount of heavy metals is known to have adverse effects on the environment. For the removal of heavy metals from aqueous environment, different conventional treatment technologies had been applied gradually which are not economically beneficial and also produce huge quantity of toxic chemical sludge. So, bio-sorption of heavy metals by marine plant is an eco-friendly innovative and alternative technology for removal of these pollutants from aqueous environment. The aim of this study is to evaluate the capacity of heavy metals accumulation and removal by some selected marine macroalgae (seaweeds) from marine environment. Methods: Seaweeds Acanthophora spicifera (Vahl.) Boergesen, Codium tomentosum Stackhouse, Halimeda gracilis Harvey ex. J. Agardh, Gracilaria opuntia Durairatnam.nom. inval. Valoniopsis pachynema (Martens) Boergesen, Caulerpa racemosa var. macrophysa (Sonder ex Kutzing) W. R. Taylor and Hydroclathrus clathratus (C. Agardh) Howe were collected from Olaikuda (09°17.526'N-079°19.662'E), Rameshwaram, south east coast of India during post monsoon period (April’2016). Seaweeds were washed with sterilized and filtered in-situ seawater repeatedly to remove all the epiphytes and debris and clean seaweeds were kept for shade drying for one week. The dried seaweeds were grinded to powder, and one gm powder seaweeds were taken in a 250ml conical flask, and 8 ml of 10 % HNO3 (70 % pure) was added to each sample and kept in room temperature (28 ̊C) for 24 hours and then samples were heated in hotplate at 120 ̊C, boiled to evaporate up to dryness and 20 ml of Nitric acid: Percholoric acid in 4:1 were added to it and again heated to hotplate at 90 ̊C up to evaporate to dryness, then samples were kept in room temperature for few minutes to cool and 10ml 10 % HNO3 were added to it and kept for 24 hours in cool and dark place and filtered with Whatman (589/2) filter paper and the filtrates were collected in 250ml clean conical flask and diluted accurately to 25 ml volume with double deionised water and triplicate of each sample were analysed with Inductively-Coupled plasma analysis (ICP-OES) to analyse total eleven heavy metals (Ag, Cd, B, Cu, Mn, Co, Ni, Cr, Pb, Zn, and Al content of the specified species and data were statistically evaluated for standard deviation. Results: Acanthophora spicifera contains highest amount of Ag (0.1± 0.2 mg/mg) followed by Cu (0.16±0.01 mg/mg), Mn (1.86±0.02 mg/mg), B (3.59±0.2 mg/mg), Halimeda gracilis showed highest accumulation of Al (384.75±0.12mg/mg), Valoniopsis pachynema accumulates maximum amount of Co (0.12±0.01 mg/mg), Zn (0.64±0.02 mg/mg), Caulerpa racemosa var. macrophysa contains Zn (0.63±0.01), Cr (0.26±0.01 mg/mg ), Ni (0.21±0.05), Pb (0.16±0.03 ) and Cd ( 0.02±00 ). Hydroclathrus clathratus, Codium tomentosum and Gracilaria opuntia also contain adequate amount of heavy metals. Conclusions: The mentioned species of seaweeds are contributing important role for decreasing the heavy metals pollution in marine environment by bioaccumulation. So, we can utilise this species to remove excess amount of heavy metals from polluted area.Keywords: heavy metals pollution, seaweeds, bioaccumulation, eco-friendly, phyco-remediation
Procedia PDF Downloads 228115 The Effect of Photochemical Smog on Respiratory Health Patients in Abuja Nigeria
Authors: Christabel Ihedike, John Mooney, Monica Price
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Summary: This study aims to critically evaluate effect of photochemical smog on respiratory health in Nigeria. Cohort of chronic obstructive pulmonary disease (COPD) patients was recruited from two large hospitals in Abuja Nigeria. Respiratory health questionnaires, daily diaries, dyspnoea scale and lung function measurement were used to obtain health data and investigate the relationship with air quality data (principally ozone, NOx and particulate pollution). Concentrations of air pollutants were higher than WHO and Nigerian air quality standard. The result suggests a correlation between measured air quality and exacerbation of respiratory illness. Introduction: Photochemical smog is a significant health challenge in most cities and its effect on respiratory health is well acknowledged. This type of pollution is most harmful to the elderly, children and those with underlying respiratory disease. This study aims to investigate impact of increasing temperature and photo-chemically generated secondary air pollutants on respiratory health in Abuja Nigeria. Method and Result: Health data was collected using spirometry to measure lung function on routine attendance at the clinic, daily diaries kept by patients and information obtained using respiratory questionnaire. Questionnaire responses (obtained using an adapted and internally validated version of St George’s Hospital Respiratory Questionnaire), shows that ‘time of wheeze’ showed an association with participants activities: 30% had worse wheeze in the morning: 10% cannot shop, 15% take long-time to get washed, 25% walk slower, 15% if hurry have to stop and 5% cannot take-bath. There was also a decrease in Forced expiratory volume in the first second and Forced Vital Capacity, and daily change in the afternoon–morning may be associated with the concentration level of pollutants. Also, dyspnoea symptoms recorded that 60% of patients were on grade 3, 25% grade 2 and 15% grade 1. Daily frequency of the number of patients in the cohort that cough /brought sputum is 78%. Air pollution in the city is higher than Nigerian and WHO standards with NOx and PM10 concentrations of 693.59ug/m-3 and 748ugm-3 being measured respectively. The result shows that air pollution may increase occurrence and exacerbation of respiratory disease. Conclusion: High temperature and local climatic conditions in urban Nigeria encourages formation of Ozone, the major constituent of photochemical smog, resulting also in the formation of secondary air pollutants associated with health challenges. In this study we confirm the likely potency of the pattern of secondary air pollution in exacerbating COPD symptoms in vulnerable patient group in urban Nigeria. There is need for better regulation and measures to reduce ozone, particularly when local climatic conditions favour development of photochemical smog in such settings. Climate change and likely increasing temperatures add impetus and urgency for better air quality standards and measures (traffic-restrictions and emissions standards) in developing world settings such as Nigeria.Keywords: Abuja-Nigeria, effect, photochemical smog, respiratory health
Procedia PDF Downloads 218114 Endometrial Biopsy Curettage vs Endometrial Aspiration: Better Modality in Female Genital Tuberculosis
Authors: Rupali Bhatia, Deepthi Nair, Geetika Khanna, Seema Singhal
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Introduction: Genital tract tuberculosis is a chronic disease (caused by reactivation of organisms from systemic distribution of Mycobacterium tuberculosis) that often presents with low grade symptoms and non-specific complaints. Patients with genital tuberculosis are usually young women seeking workup and treatment for infertility. Infertility is the commonest presentation due to involvement of the fallopian tubes, endometrium and ovarian damage with poor ovarian volume and reserve. The diagnosis of genital tuberculosis is difficult because of the fact that it is a silent invader of genital tract. Since tissue cannot be obtained from fallopian tubes, the diagnosis is made by isolation of bacilli from endometrial tissue obtained by endometrial biopsy curettage and/or aspiration. Problems are associated with sampling technique as well as diagnostic modality due to lack of adequate sample volumes and the segregation of the sample for various diagnostic tests resulting in non-uniform distribution of microorganisms. Moreover, lack of an efficient sampling technique universally applicable for all specific diagnostic tests contributes to the diagnostic challenges. Endometrial sampling plays a key role in accurate diagnosis of female genital tuberculosis. It may be done by 2 methods viz. endometrial curettage and endometrial aspiration. Both endometrial curettage and aspirate have their own limitations as curettage picks up strip of the endometrium from one of the walls of the uterine cavity including tubal osteal areas whereas aspirate obtains total tissue with exfoliated cells present in the secretory fluid of the endometrial cavity. Further, sparse and uneven distribution of the bacilli remains a major factor contributing to the limitations of the techniques. The sample that is obtained by either technique is subjected to histopathological examination, AFB staining, culture and PCR. Aim: Comparison of the sampling techniques viz. endometrial biopsy curettage and endometrial aspiration using different laboratory methods of histopathology, cytology, microbiology and molecular biology. Method: In a hospital based observational study, 75 Indian females suspected of genital tuberculosis were selected on the basis of inclusion criteria. The women underwent endometrial tissue sampling using Novaks biopsy curette and Karmans cannula. One part of the specimen obtained was sent in formalin solution for histopathological testing and another part was sent in normal saline for acid fast bacilli smear, culture and polymerase chain reaction. The results so obtained were correlated using coefficient of correlation and chi square test. Result: Concordance of results showed moderate agreement between both the sampling techniques. Among HPE, AFB and PCR, maximum sensitivity was observed for PCR, though the specificity was not as high as other techniques. Conclusion: Statistically no significant difference was observed between the results obtained by the two sampling techniques. Therefore, one may use either EA or EB to obtain endometrial samples and avoid multiple sampling as both the techniques are equally efficient in diagnosing genital tuberculosis by HPE, AFB, culture or PCR.Keywords: acid fast bacilli (AFB), histopatholgy examination (HPE), polymerase chain reaction (PCR), endometrial biopsy curettage
Procedia PDF Downloads 322113 Detection and Quantification of Viable but Not Culturable Vibrio Parahaemolyticus in Frozen Bivalve Molluscs
Authors: Eleonora Di Salvo, Antonio Panebianco, Graziella Ziino
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Background: Vibrio parahaemolyticus is a human pathogen that is widely distributed in marine environments. It is frequently isolated from raw seafood, particularly shellfish. Consumption of raw or undercooked seafood contaminated with V. parahaemolyticus may lead to acute gastroenteritis. Vibrio spp. has excellent resistance to low temperatures so it can be found in frozen products for a long time. Recently, the viable but non-culturable state (VBNC) of bacteria has attracted great attention, and more than 85 species of bacteria have been demonstrated to be capable of entering this state. VBNC cells cannot grow in conventional culture medium but are viable and maintain metabolic activity, which may constitute an unrecognized source of food contamination and infection. Also V. parahaemolyticus could exist in VBNC state under nutrient starvation or low-temperature conditions. Aim: The aim of the present study was to optimize methods and investigate V. parahaemolyticus VBNC cells and their presence in frozen bivalve molluscs, regularly marketed. Materials and Methods: propidium monoazide (PMA) was integrated with real-time polymerase chain reaction (qPCR) targeting the tl gene to detect and quantify V. parahaemolyticus in the VBNC state. PMA-qPCR resulted highly specific to V. parahaemolyticus with a limit of detection (LOD) of 10-1 log CFU/mL in pure bacterial culture. A standard curve for V. parahaemolyticus cell concentrations was established with the correlation coefficient of 0.9999 at the linear range of 1.0 to 8.0 log CFU/mL. A total of 77 samples of frozen bivalve molluscs (35 mussels; 42 clams) were subsequently subjected to the qualitative (on alkaline phosphate buffer solution) and quantitative research of V. parahaemolyticus on thiosulfate-citrate-bile salts-sucrose (TCBS) agar (DIFCO) NaCl 2.5%, and incubation at 30°C for 24-48 hours. Real-time PCR was conducted on homogenate samples, in duplicate, with and without propidium monoazide (PMA) dye, and exposed for 45 min under halogen lights (650 W). Total DNA was extracted from cell suspension in homogenate samples according to bolliture protocol. The Real-time PCR was conducted with species-specific primers for V. parahaemolitycus. The RT-PCR was performed in a final volume of 20 µL, containing 10 µL of SYBR Green Mixture (Applied Biosystems), 2 µL of template DNA, 2 µL of each primer (final concentration 0.6 mM), and H2O 4 µL. The qPCR was carried out on CFX96 TouchTM (Bio-Rad, USA). Results: All samples were negative both to the quantitative and qualitative detection of V. parahaemolyticus by the classical culturing technique. The PMA-qPCR let us individuating VBNC V. parahaemolyticus in the 20,78% of the samples evaluated with a value between the Log 10-1 and Log 10-3 CFU/g. Only clams samples were positive for PMA-qPCR detection. Conclusion: The present research is the first evaluating PMA-qPCR assay for detection of VBNC V. parahaemolyticus in bivalve molluscs samples, and the used method was applicable to the rapid control of marketed bivalve molluscs. We strongly recommend to use of PMA-qPCR in order to identify VBNC forms, undetectable by the classic microbiological methods. A precise knowledge of the V.parahaemolyticus in a VBNC form is fundamental for the correct risk assessment not only in bivalve molluscs but also in other seafood.Keywords: food safety, frozen bivalve molluscs, PMA dye, Real-time PCR, VBNC state, Vibrio parahaemolyticus
Procedia PDF Downloads 128112 Determination of Slope of Hilly Terrain by Using Proposed Method of Resolution of Forces
Authors: Reshma Raskar-Phule, Makarand Landge, Saurabh Singh, Vijay Singh, Jash Saparia, Shivam Tripathi
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For any construction project, slope calculations are necessary in order to evaluate constructability on the site, such as the slope of parking lots, sidewalks, and ramps, the slope of sanitary sewer lines, slope of roads and highways. When slopes and grades are to be determined, designers are concerned with establishing proper slopes and grades for their projects to assess cut and fill volume calculations and determine inverts of pipes. There are several established instruments commonly used to determine slopes, such as Dumpy level, Abney level or Hand Level, Inclinometer, Tacheometer, Henry method, etc., and surveyors are very familiar with the use of these instruments to calculate slopes. However, they have some other drawbacks which cannot be neglected while major surveying works. Firstly, it requires expert surveyors and skilled staff. The accessibility, visibility, and accommodation to remote hilly terrain with these instruments and surveying teams are difficult. Also, determination of gentle slopes in case of road and sewer drainage constructions in congested urban places with these instruments is not easy. This paper aims to develop a method that requires minimum field work, minimum instruments, no high-end technology or instruments or software, and low cost. It requires basic and handy surveying accessories like a plane table with a fixed weighing machine, standard weights, alidade, tripod, and ranging rods should be able to determine the terrain slope in congested areas as well as in remote hilly terrain. Also, being simple and easy to understand and perform the people of that local rural area can be easily trained for the proposed method. The idea for the proposed method is based on the principle of resolution of weight components. When any object of standard weight ‘W’ is placed on an inclined surface with a weighing machine below it, then its cosine component of weight is presently measured by that weighing machine. The slope can be determined from the relation between the true or actual weight and the apparent weight. A proper procedure is to be followed, which includes site location, centering and sighting work, fixing the whole set at the identified station, and finally taking the readings. A set of experiments for slope determination, mild and moderate slopes, are carried out by the proposed method and by the theodolite instrument in a controlled environment, on the college campus, and uncontrolled environment actual site. The slopes determined by the proposed method were compared with those determined by the established instruments. For example, it was observed that for the same distances for mild slope, the difference in the slope obtained by the proposed method and by the established method ranges from 4’ for a distance of 8m to 2o15’20” for a distance of 16m for an uncontrolled environment. Thus, for mild slopes, the proposed method is suitable for a distance of 8m to 10m. The correlation between the proposed method and the established method shows a good correlation of 0.91 to 0.99 for various combinations, mild and moderate slope, with the controlled and uncontrolled environment.Keywords: surveying, plane table, weight component, slope determination, hilly terrain, construction
Procedia PDF Downloads 86111 Interdisciplinary Method Development - A Way to Realize the Full Potential of Textile Resources
Authors: Nynne Nørup, Julie Helles Eriksen, Rikke M. Moalem, Else Skjold
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Despite a growing focus on the high environmental impact of textiles, textile waste is only recently considered as part of the waste field. Consequently, there is a general lack of knowledge and data within this field. Particularly the lack of a common perception of textiles generates several problems e.g., to recognize the full material potential the fraction contains, which is cruel if the textile must enter the circular economy. This study aims to qualify a method to make the resources in textile waste visible in a way that makes it possible to move them as high up in the waste hierarchy as possible. Textiles are complex and cover many different types of products, fibers and combinations of fibers and production methods. In garments alone, there is a great variety, even when narrowing it to only undergarments. However, textile waste is often reduced to one fraction, assessed solely by quantity, and compared to quantities of other waste fractions. Disregarding the complexity and reducing textiles to a single fraction that covers everything made of textiles increase the risk of neglecting the value of the materials, both with regards to their properties and economical. Instead of trying to fit textile waste into the current primarily linear waste system where volume is a key part of the business models, this study focused on integrating textile waste as a resource in the design and production phase. The study combined interdisciplinary methods for determining replacement rates used in Life Cycle Assessments and Mass Flow Analysis methods with the designer’s toolbox to hereby activate the properties of textile waste in a way that can unleash its potential optimally. It was hypothesized that by activating Denmark's tradition for design and high level of craftsmanship, it is possible to find solutions that can be used today and create circular resource models that reduce the use of virgin fibers. Through waste samples, case studies, and testing of various design approaches, this study explored how to functionalize the method so that the product after the end-use is kept as a material and only then processed at fiber level to obtain the best environmental utilization. The study showed that the designers' ability to decode the properties of the materials and understanding of craftsmanship were decisive for how well the materials could be utilized today. The later in the life cycle the textiles appeared as waste, the more demanding the description of the materials to be sufficient, especially if to achieve the best possible use of the resources and thus a higher replacement rate. In addition, it also required adaptation in relation to the current production because the materials often varied more. The study found good indications that part of the solution is to use geodata i.e., where in the life cycle the materials were discarded. An important conclusion is that a fully developed method can help support better utilization of textile resources. However, it stills requires a better understanding of materials by the designers, as well as structural changes in business and society.Keywords: circular economy, development of sustainable processes, environmental impacts, environmental management of textiles, environmental sustainability through textile recycling, interdisciplinary method development, resource optimization, recycled textile materials and the evaluation of recycling, sustainability and recycling opportunities in the textile and apparel sector
Procedia PDF Downloads 89110 Portable Environmental Parameter Monitor Based on STM32
Authors: Liang Zhao, Chongquan Zhong
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Introduction: According to statistics, people spend 80% to 90% of time indoor, so indoor air quality, either at home or in the office, greatly impacts the quality of life, health and work efficiency. Therefore, indoor air quality is very important to human activities. With the acceleration of urbanization, people are spending more time in indoor activity. The time in indoor environment, the living space, and the frequency interior decoration are all increasingly increased. However, housing decoration materials contain formaldehyde and other harmful substances, causing environmental and air quality problems, which have brought serious damage to countless families and attracted growing attention. According to World Health Organization statistics, the indoor environments in more than 30% of buildings in China are polluted by poisonous and harmful gases. Indoor pollution has caused various health problems, and these widespread public health problems can lead to respiratory diseases. Long-term inhalation of low-concentration formaldehyde would cause persistent headache, insomnia, weakness, palpitation, weight loss and vomiting, which are serious impacts on human health and safety. On the other hand, as for offices, some surveys show that good indoor air quality helps to enthuse the staff and improve the work efficiency by 2%-16%. Therefore, people need to further understand the living and working environments. There is a need for easy-to-use indoor environment monitoring instruments, with which users only have to power up and monitor the environmental parameters. The corresponding real-time data can be displayed on the screen for analysis. Environment monitoring should have the sensitive signal alarm function and send alarm when harmful gases such as formaldehyde, CO, SO2, are excessive to human body. System design: According to the monitoring requirements of various gases, temperature and humidity, we designed a portable, light, real-time and accurate monitor for various environmental parameters, including temperature, humidity, formaldehyde, methane, and CO. This monitor will generate an alarm signal when a target is beyond the standard. It can conveniently measure a variety of harmful gases and provide the alarm function. It also has the advantages of small volume, convenience to carry and use. It has a real-time display function, outputting the parameters on the LCD screen, and a real-time alarm function. Conclusions: This study is focused on the research and development of a portable parameter monitoring instrument for indoor environment. On the platform of an STM32 development board, the monitored data are collected through an external sensor. The STM32 platform is for data acquisition and processing procedures, and successfully monitors the real-time temperature, humidity, formaldehyde, CO, methane and other environmental parameters. Real-time data are displayed on the LCD screen. The system is stable and can be used in different indoor places such as family, hospital, and office. Meanwhile, the system adopts the idea of modular design and is superior in transplanting. The scheme is slightly modified and can be used similarly as the function of a monitoring system. This monitor has very high research and application values.Keywords: indoor air quality, gas concentration detection, embedded system, sensor
Procedia PDF Downloads 247109 Permeable Asphalt Pavement as a Measure of Urban Green Infrastructure in the Extreme Events Mitigation
Authors: Márcia Afonso, Cristina Fael, Marisa Dinis-Almeida
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Population growth in cities has led to an increase in the infrastructures construction, including buildings and roadways. This aspect leads directly to the soils waterproofing. In turn, changes in precipitation patterns are developing into higher and more frequent intensities. Thus, these two conjugated aspects decrease the rainwater infiltration into soils and increase the volume of surface runoff. The practice of green and sustainable urban solutions has encouraged research in these areas. The porous asphalt pavement, as a green infrastructure, is part of practical solutions set to address urban challenges related to land use and adaptation to climate change. In this field, permeable pavements with porous asphalt mixtures (PA) have several advantages in terms of reducing the runoff generated by the floods. The porous structure of these pavements, compared to a conventional asphalt pavement, allows the rainwater infiltration in the subsoil, and consequently, the water quality improvement. This green infrastructure solution can be applied in cities, particularly in streets or parking lots to mitigate the floods effects. Over the years, the pores of these pavements can be filled by sediment, reducing their function in the rainwater infiltration. Thus, double layer porous asphalt (DLPA) was developed to mitigate the clogging effect and facilitate the water infiltration into the lower layers. This study intends to deepen the knowledge of the performance of DLPA when subjected to clogging. The experimental methodology consisted on four evaluation phases of the DLPA infiltration capacity submitted to three precipitation events (100, 200 and 300 mm/h) in each phase. The evaluation first phase determined the behavior after DLPA construction. In phases two and three, two 500 g/m2 clogging cycles were performed, totaling a 1000 g/m2 final simulation. Sand with gradation accented in fine particles was used as clogging material. In the last phase, the DLPA was subjected to simple sweeping and vacuuming maintenance. A precipitation simulator, type sprinkler, capable of simulating the real precipitation was developed for this purpose. The main conclusions show that the DLPA has the capacity to drain the water, even after two clogging cycles. The infiltration results of flows lead to an efficient performance of the DPLA in the surface runoff attenuation, since this was not observed in any of the evaluation phases, even at intensities of 200 and 300 mm/h, simulating intense precipitation events. The infiltration capacity under clogging conditions decreased about 7% on average in the three intensities relative to the initial performance that is after construction. However, this was restored when subjected to simple maintenance, recovering the DLPA hydraulic functionality. In summary, the study proved the efficacy of using a DLPA when it retains thicker surface sediments and limits the fine sediments entry to the remaining layers. At the same time, it is guaranteed the rainwater infiltration and the surface runoff reduction and is therefore a viable solution to put into practice in permeable pavements.Keywords: clogging, double layer porous asphalt, infiltration capacity, rainfall intensity
Procedia PDF Downloads 486108 Optimizing Data Transfer and Processing in Multi-Cloud Environments for Big Data Workloads
Authors: Gaurav Kumar Sinha
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In an era defined by the proliferation of data and the utilization of cloud computing environments, the efficient transfer and processing of big data workloads across multi-cloud platforms have emerged as critical challenges. This research paper embarks on a comprehensive exploration of the complexities associated with managing and optimizing big data in a multi-cloud ecosystem.The foundation of this study is rooted in the recognition that modern enterprises increasingly rely on multiple cloud providers to meet diverse business needs, enhance redundancy, and reduce vendor lock-in. As a consequence, managing data across these heterogeneous cloud environments has become intricate, necessitating innovative approaches to ensure data integrity, security, and performance.The primary objective of this research is to investigate strategies and techniques for enhancing the efficiency of data transfer and processing in multi-cloud scenarios. It recognizes that big data workloads are characterized by their sheer volume, variety, velocity, and complexity, making traditional data management solutions insufficient for harnessing the full potential of multi-cloud architectures.The study commences by elucidating the challenges posed by multi-cloud environments in the context of big data. These challenges encompass data fragmentation, latency, security concerns, and cost optimization. To address these challenges, the research explores a range of methodologies and solutions. One of the key areas of focus is data transfer optimization. The paper delves into techniques for minimizing data movement latency, optimizing bandwidth utilization, and ensuring secure data transmission between different cloud providers. It evaluates the applicability of dedicated data transfer protocols, intelligent data routing algorithms, and edge computing approaches in reducing transfer times.Furthermore, the study examines strategies for efficient data processing across multi-cloud environments. It acknowledges that big data processing requires distributed and parallel computing capabilities that span across cloud boundaries. The research investigates containerization and orchestration technologies, serverless computing models, and interoperability standards that facilitate seamless data processing workflows.Security and data governance are paramount concerns in multi-cloud environments. The paper explores methods for ensuring data security, access control, and compliance with regulatory frameworks. It considers encryption techniques, identity and access management, and auditing mechanisms as essential components of a robust multi-cloud data security strategy.The research also evaluates cost optimization strategies, recognizing that the dynamic nature of multi-cloud pricing models can impact the overall cost of data transfer and processing. It examines approaches for workload placement, resource allocation, and predictive cost modeling to minimize operational expenses while maximizing performance.Moreover, this study provides insights into real-world case studies and best practices adopted by organizations that have successfully navigated the challenges of multi-cloud big data management. It presents a comparative analysis of various multi-cloud management platforms and tools available in the market.Keywords: multi-cloud environments, big data workloads, data transfer optimization, data processing strategies
Procedia PDF Downloads 60107 Estimating Poverty Levels from Satellite Imagery: A Comparison of Human Readers and an Artificial Intelligence Model
Authors: Ola Hall, Ibrahim Wahab, Thorsteinn Rognvaldsson, Mattias Ohlsson
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The subfield of poverty and welfare estimation that applies machine learning tools and methods on satellite imagery is a nascent but rapidly growing one. This is in part driven by the sustainable development goal, whose overarching principle is that no region is left behind. Among other things, this requires that welfare levels can be accurately and rapidly estimated at different spatial scales and resolutions. Conventional tools of household surveys and interviews do not suffice in this regard. While they are useful for gaining a longitudinal understanding of the welfare levels of populations, they do not offer adequate spatial coverage for the accuracy that is needed, nor are their implementation sufficiently swift to gain an accurate insight into people and places. It is this void that satellite imagery fills. Previously, this was near-impossible to implement due to the sheer volume of data that needed processing. Recent advances in machine learning, especially the deep learning subtype, such as deep neural networks, have made this a rapidly growing area of scholarship. Despite their unprecedented levels of performance, such models lack transparency and explainability and thus have seen limited downstream applications as humans generally are apprehensive of techniques that are not inherently interpretable and trustworthy. While several studies have demonstrated the superhuman performance of AI models, none has directly compared the performance of such models and human readers in the domain of poverty studies. In the present study, we directly compare the performance of human readers and a DL model using different resolutions of satellite imagery to estimate the welfare levels of demographic and health survey clusters in Tanzania, using the wealth quintile ratings from the same survey as the ground truth data. The cluster-level imagery covers all 608 cluster locations, of which 428 were classified as rural. The imagery for the human readers was sourced from the Google Maps Platform at an ultra-high resolution of 0.6m per pixel at zoom level 18, while that of the machine learning model was sourced from the comparatively lower resolution Sentinel-2 10m per pixel data for the same cluster locations. Rank correlation coefficients of between 0.31 and 0.32 achieved by the human readers were much lower when compared to those attained by the machine learning model – 0.69-0.79. This superhuman performance by the model is even more significant given that it was trained on the relatively lower 10-meter resolution satellite data while the human readers estimated welfare levels from the higher 0.6m spatial resolution data from which key markers of poverty and slums – roofing and road quality – are discernible. It is important to note, however, that the human readers did not receive any training before ratings, and had this been done, their performance might have improved. The stellar performance of the model also comes with the inevitable shortfall relating to limited transparency and explainability. The findings have significant implications for attaining the objective of the current frontier of deep learning models in this domain of scholarship – eXplainable Artificial Intelligence through a collaborative rather than a comparative framework.Keywords: poverty prediction, satellite imagery, human readers, machine learning, Tanzania
Procedia PDF Downloads 98106 Characterization of Platelet Mitochondrial Metabolism in COVID-19 Caused Acute Respiratory Distress Syndrome (ARDS)
Authors: Anna Höfer, Johannes Herrmann, Patrick Meybohm, Christopher Lotz
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Mitochondria are pivotal for energy supply and regulation of cellular functions. Deficiencies of mitochondrial metabolism have been implicated in diverse stressful conditions including infections. Platelets are key mediators for thrombo-inflammation during development and resolution of acute respiratory distress syndrome (ARDS). Previous data point to an exhausted platelet phenotype in critically-ill patients with coronavirus 19 disease (COVID-19) impacting the course of disease. The objective of this work was to characterize platelet mitochondrial metabolism in patients suffering from COVID-19 ARDSA longitudinal analysis of platelet mitochondrial metabolism in 24 patients with COVID-19 induced ARDS compared to 35 healthy controls (ctrl) was performed. Blood samples were analyzed at two time points (t1=day 1; t2=day 5-7 after study inclusion). The activity of mitochondrial citrate synthase was photometrically measured. The impact of oxidative stress on mitochondrial permeability was assessed by a photometric calcium-induced swelling assay and the activity of superoxide dismutase (SOD) by a SOD assay kit. The amount of protein carbonylation and the activity of mitochondria complexes I-IV were photometrically determined. Levels of interleukins (IL)-1α, IL-1β and tumor necrosis factor (TNF-) α were measured by a Multiplex assay kit. Median age was 54 years, 63 % were male and BMI was 29.8 kg/m2. SOFA (12; IQR: 10-15) and APACHE II (27; IQR: 24-30) indicated critical illness. Median Murray Score was 3.4 (IQR: 2.8-3.4), 21/24 (88%) required mechanical ventilation and V-V ECMO support in 14/24 (58%). Platelet counts in ARDS did not change during ICU stay (t1: 212 vs. t2: 209 x109/L). However, mean platelet volume (MPV) significantly increased (t1: 10.6 vs. t2: 11.9 fL; p<0.0001). Citrate synthase activity showed no significant differences between ctrl and ARDS patients. Calcium induced swelling was more pronounced in patients at t1 compared to t2 and to ctrl (50µM; t1: 0.006 vs. ctrl: 0.016 ΔOD; p=0.001). The amount of protein carbonylation as marker for irreversible proteomic modification constantly increased during ICU stay and compared to ctrl., without reaching significance. In parallel, superoxid dismutase activity gradually declined during ICU treatment vs. ctrl (t2: - 29 vs. ctrl.: - 17 %; p=0.0464). Complex I analysis revealed significantly stronger activity in ARDS vs. ctrl. (t1: 0.633 vs. ctrl.: 0.415 ΔOD; p=0.0086). There were no significant differences in complex II, III or IV activity in platelets from ARDS patients compared to ctrl. IL-18 constantly increased during the observation period without reaching significance. IL-1α and TNF-α did not differ from ctrl. However, IL-1β levels were significantly elevated in ARDS (t1: 16.8; t2: 16.6 vs. ctrl.: 12.4 pg/mL; p1=0.0335, p2=0.0032). This study reveals new insights in platelet mitochondrial metabolism during COVID-19 caused ARDS. it data point towards enhanced platelet activity with a pronounced turnover rate. We found increased activity of mitochondria complex I and evidence for enhanced oxidative stress. In parallel, protective mechanisms against oxidative stress were narrowed with elevated levels of IL-1β likely causing a pro-apoptotic environment. These mechanisms may contribute to platelet exhaustion in ARDS.Keywords: acute respiratory distress syndrome (ARDS), coronavirus 19 disease (COVID-19), oxidative stress, platelet mitochondrial metabolism
Procedia PDF Downloads 48105 Use of Sewage Sludge Ash as Partial Cement Replacement in the Production of Mortars
Authors: Domagoj Nakic, Drazen Vouk, Nina Stirmer, Mario Siljeg, Ana Baricevic
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Wastewater treatment processes generate significant quantities of sewage sludge that need to be adequately treated and disposed. In many EU countries, the problem of adequate disposal of sewage sludge has not been solved, nor is determined by the unique rules, instructions or guidelines. Disposal of sewage sludge is important not only in terms of satisfying the regulations, but the aspect of choosing the optimal wastewater and sludge treatment technology. Among the solutions that seem reasonable, recycling of sewage sludge and its byproducts reaches the top recommendation. Within the framework of sustainable development, recycling of sludge almost completely closes the cycle of wastewater treatment in which only negligible amounts of waste that requires landfilling are being generated. In many EU countries, significant amounts of sewage sludge are incinerated, resulting in a new byproduct in the form of ash. Sewage sludge ash is three to five times less in volume compared to stabilized and dehydrated sludge, but it also requires further management. The combustion process also destroys hazardous organic components in the sludge and minimizes unpleasant odors. The basic objective of the presented research is to explore the possibilities of recycling of the sewage sludge ash as a supplementary cementitious material. This is because of the main oxides present in the sewage sludge ash (SiO2, Al2O3 and Cao, which is similar to cement), so it can be considered as latent hydraulic and pozzolanic material. Physical and chemical characteristics of ashes, generated by sludge collected from different wastewater treatment plants, and incinerated in laboratory conditions at different temperatures, are investigated since it is a prerequisite of its subsequent recycling and the eventual use in other industries. Research was carried out by replacing up to 20% of cement by mass in cement mortar mixes with different obtained ashes and examining characteristics of created mixes in fresh and hardened condition. The mixtures with the highest ash content (20%) showed an average drop in workability of about 15% which is attributed to the increased water requirements when ash was used. Although some mixes containing added ash showed compressive and flexural strengths equivalent to those of reference mixes, generally slight decrease in strength was observed. However, it is important to point out that the compressive strengths always remained above 85% compared to the reference mix, while flexural strengths remained above 75%. Ecological impact of innovative construction products containing sewage sludge ash was determined by analyzing leaching concentrations of heavy metals. Results demonstrate that sewage sludge ash can satisfy technical and environmental criteria for use in cementitious materials which represents a new recycling application for an increasingly important waste material that is normally landfilled. Particular emphasis is placed on linking the composition of generated ashes depending on its origin and applied treatment processes (stage of wastewater treatment, sludge treatment technology, incineration temperature) with the characteristics of the final products. Acknowledgement: This work has been fully supported by Croatian Science Foundation under the project '7927 - Reuse of sewage sludge in concrete industry – from infrastructure to innovative construction products'.Keywords: cement mortar, recycling, sewage sludge ash, sludge disposal
Procedia PDF Downloads 242104 Nanoparticle Supported, Magnetically Separable Metalloporphyrin as an Efficient Retrievable Heterogeneous Nanocatalyst in Oxidation Reactions
Authors: Anahita Mortazavi Manesh, Mojtaba Bagherzadeh
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Metalloporphyrins are well known to mimic the activity of monooxygenase enzymes. In this regard, metalloporphyrin complexes have been largely employed as valuable biomimetic catalysts, owing to the critical roles they play in oxygen transfer processes in catalytic oxidation reactions. Investigating in this area is based on different strategies to design selective, stable and high turnover catalytic systems. Immobilization of expensive metalloporphyrin catalysts onto supports appears to be a good way to improve their stability, selectivity and the catalytic performance because of the support environment and other advantages with respect to recovery, reuse. In other words, supporting metalloporphyrins provides a physical separation of active sites, thus minimizing catalyst self-destruction and dimerization of unhindered metalloporphyrins. Furthermore, heterogeneous catalytic oxidations have become an important target since their process are used in industry, helping to minimize the problems of industrial waste treatment. Hence, the immobilization of these biomimetic catalysts is much desired. An attractive approach is the preparation of the heterogeneous catalyst involves immobilization of complexes on silica coated magnetic nano-particles. Fe3O4@SiO2 magnetic nanoparticles have been studied extensively due to their superparamagnetism property, large surface area to volume ratio and easy functionalization. Using heterogenized homogeneous catalysts is an attractive option to facile separation of catalyst, simplified product work-up and continuity of catalytic system. Homogeneous catalysts immobilized on magnetic nanoparticles (MNPs) surface occupy a unique position due to combining the advantages of both homogeneous and heterogeneous catalysts. In addition, superparamagnetic nature of MNPs enable very simple separation of the immobilized catalysts from the reaction mixture using an external magnet. In the present work, an efficient heterogeneous catalyst was prepared by immobilizing manganese porphyrin on functionalized magnetic nanoparticles through the amino propyl linkage. The prepared catalyst was characterized by elemental analysis, FT-IR spectroscopy, X-ray powder diffraction, atomic absorption spectroscopy, UV-Vis spectroscopy, and scanning electron microscopy. Application of immobilized metalloporphyrin in the oxidation of various organic substrates was explored using Gas chromatographic (GC) analyses. The results showed that the supported Mn-porphyrin catalyst (Fe3O4@SiO2-NH2@MnPor) is an efficient and reusable catalyst in oxidation reactions. Our catalytic system exhibits high catalytic activity in terms of turnover number (TON) and reaction conditions. Leaching and recycling experiments revealed that nanocatalyst can be recovered several times without loss of activity and magnetic properties. The most important advantage of this heterogenized catalytic system is the simplicity of the catalyst separation in which the catalyst can be separated from the reaction mixture by applying a magnet. Furthermore, the separation and reuse of the magnetic Fe3O4 nanoparticles were very effective and economical.Keywords: Fe3O4 nanoparticle, immobilized metalloporphyrin, magnetically separable nanocatalyst, oxidation reactions
Procedia PDF Downloads 295103 Production of Medicinal Bio-active Amino Acid Gamma-Aminobutyric Acid In Dairy Sludge Medium
Authors: Farideh Tabatabaee Yazdi, Fereshteh Falah, Alireza Vasiee
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Introduction: Gamma-aminobutyric acid (GABA) is a non-protein amino acid that is widely present in organisms. GABA is a kind of pharmacological and biological component and its application is wide and useful. Several important physiological functions of GABA have been characterized, such as neurotransmission and induction of hypotension. GABA is also a strong secretagogue of insulin from the pancreas and effectively inhibits small airway-derived lung adenocarcinoma and tranquilizer. Many microorganisms can produce GABA, and lactic acid bacteria have been a focus of research in recent years because lactic acid bacteria possess special physiological activities and are generally regarded as safe. Among them, the Lb. Brevis produced the highest amount of GABA. The major factors affecting GABA production have been characterized, including carbon sources and glutamate concentration. The use of food industry waste to produce valuable products such as amino acids seems to be a good way to reduce production costs and prevent the waste of food resources. In a dairy factory, a high volume of sludge is produced from a separator that contains useful compounds such as growth factors, carbon, nitrogen, and organic matter that can be used by different microorganisms such as Lb.brevis as carbon and nitrogen sources. Therefore, it is a good source of GABA production. GABA is primarily formed by the irreversible α-decarboxylation reaction of L-glutamic acid or its salts, catalysed by the GAD enzyme. In the present study, this aim was achieved for the fast-growing of Lb.brevis and producing GABA, using the dairy industry sludge as a suitable growth medium. Lactobacillus Brevis strains obtained from Microbial Type Culture Collection (MTCC) were used as model strains. In order to prepare dairy sludge as a medium, sterilization should be done at 121 ° C for 15 minutes. Lb. Brevis was inoculated to the sludge media at pH=6 and incubated for 120 hours at 30 ° C. After fermentation, the supernatant solution is centrifuged and then, the GABA produced was analyzed by the Thin Layer chromatography (TLC) method qualitatively and by the high-performance liquid chromatography (HPLC) method quantitatively. By increasing the percentage of dairy sludge in the culture medium, the amount of GABA increased. Also, evaluated the growth of bacteria in this medium showed the positive effect of dairy sludge on the growth of Lb.brevis, which resulted in the production of more GABA. GABA-producing LAB offers the opportunity of developing naturally fermented health-oriented products. Although some GABA-producing LAB has been isolated to find strains suitable for different fermentations, further screening of various GABA-producing strains from LAB, especially high-yielding strains, is necessary. The production of lactic acid, bacterial gamma-aminobutyric acid, is safe and eco-friendly. The use of dairy industry waste causes enhanced environmental safety. Also provides the possibility of producing valuable compounds such as GABA. In general, dairy sludge is a suitable medium for the growth of Lactic Acid Bacteria and produce this amino acid that can reduce the final cost of it by providing carbon and nitrogen source.Keywords: GABA, Lactobacillus, HPLC, dairy sludge
Procedia PDF Downloads 131102 Treatment Process of Sludge from Leachate with an Activated Sludge System and Extended Aeration System
Authors: A. Chávez, A. Rodríguez, F. Pinzón
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Society is concerned about measures of environmental, economic and social impacts generated in the solid waste disposal. These places of confinement, also known as landfills, are locations where problems of pollution and damage to human health are reduced. They are technically designed and operated, using engineering principles, storing the residue in a small area, compact it to reduce volume and covering them with soil layers. Problems preventing liquid (leachate) and gases produced by the decomposition of organic matter. Despite planning and site selection for disposal, monitoring and control of selected processes, remains the dilemma of the leachate as extreme concentration of pollutants, devastating soil, flora and fauna; aggressive processes requiring priority attention. A biological technology is the activated sludge system, used for tributaries with high pollutant loads. Since transforms biodegradable dissolved and particulate matter into CO2, H2O and sludge; transform suspended and no Settleable solids; change nutrients as nitrogen and phosphorous; and degrades heavy metals. The microorganisms that remove organic matter in the processes are in generally facultative heterotrophic bacteria, forming heterogeneous populations. Is possible to find unicellular fungi, algae, protozoa and rotifers, that process the organic carbon source and oxygen, as well as the nitrogen and phosphorus because are vital for cell synthesis. The mixture of the substrate, in this case sludge leachate, molasses and wastewater is maintained ventilated by mechanical aeration diffusers. Considering as the biological processes work to remove dissolved material (< 45 microns), generating biomass, easily obtained by decantation processes. The design consists of an artificial support and aeration pumps, favoring develop microorganisms (denitrifying) using oxygen (O) with nitrate, resulting in nitrogen (N) in the gas phase. Thus, avoiding negative effects of the presence of ammonia or phosphorus. Overall the activated sludge system includes about 8 hours of hydraulic retention time, which does not prevent the demand for nitrification, which occurs on average in a value of MLSS 3,000 mg/L. The extended aeration works with times greater than 24 hours detention; with ratio of organic load/biomass inventory under 0.1; and average stay time (sludge age) more than 8 days. This project developed a pilot system with sludge leachate from Doña Juana landfill - RSDJ –, located in Bogota, Colombia, where they will be subjected to a process of activated sludge and extended aeration through a sequential Bach reactor - SBR, to be dump in hydric sources, avoiding ecological collapse. The system worked with a dwell time of 8 days, 30 L capacity, mainly by removing values of BOD and COD above 90%, with initial data of 1720 mg/L and 6500 mg/L respectively. Motivating the deliberate nitrification is expected to be possible commercial use diffused aeration systems for sludge leachate from landfills.Keywords: sludge, landfill, leachate, SBR
Procedia PDF Downloads 264101 Automatic Identification of Pectoral Muscle
Authors: Ana L. M. Pavan, Guilherme Giacomini, Allan F. F. Alves, Marcela De Oliveira, Fernando A. B. Neto, Maria E. D. Rosa, Andre P. Trindade, Diana R. De Pina
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Mammography is a worldwide image modality used to diagnose breast cancer, even in asymptomatic women. Due to its large availability, mammograms can be used to measure breast density and to predict cancer development. Women with increased mammographic density have a four- to sixfold increase in their risk of developing breast cancer. Therefore, studies have been made to accurately quantify mammographic breast density. In clinical routine, radiologists perform image evaluations through BIRADS (Breast Imaging Reporting and Data System) assessment. However, this method has inter and intraindividual variability. An automatic objective method to measure breast density could relieve radiologist’s workload by providing a first aid opinion. However, pectoral muscle is a high density tissue, with similar characteristics of fibroglandular tissues. It is consequently hard to automatically quantify mammographic breast density. Therefore, a pre-processing is needed to segment the pectoral muscle which may erroneously be quantified as fibroglandular tissue. The aim of this work was to develop an automatic algorithm to segment and extract pectoral muscle in digital mammograms. The database consisted of thirty medio-lateral oblique incidence digital mammography from São Paulo Medical School. This study was developed with ethical approval from the authors’ institutions and national review panels under protocol number 3720-2010. An algorithm was developed, in Matlab® platform, for the pre-processing of images. The algorithm uses image processing tools to automatically segment and extract the pectoral muscle of mammograms. Firstly, it was applied thresholding technique to remove non-biological information from image. Then, the Hough transform is applied, to find the limit of the pectoral muscle, followed by active contour method. Seed of active contour is applied in the limit of pectoral muscle found by Hough transform. An experienced radiologist also manually performed the pectoral muscle segmentation. Both methods, manual and automatic, were compared using the Jaccard index and Bland-Altman statistics. The comparison between manual and the developed automatic method presented a Jaccard similarity coefficient greater than 90% for all analyzed images, showing the efficiency and accuracy of segmentation of the proposed method. The Bland-Altman statistics compared both methods in relation to area (mm²) of segmented pectoral muscle. The statistic showed data within the 95% confidence interval, enhancing the accuracy of segmentation compared to the manual method. Thus, the method proved to be accurate and robust, segmenting rapidly and freely from intra and inter-observer variability. It is concluded that the proposed method may be used reliably to segment pectoral muscle in digital mammography in clinical routine. The segmentation of the pectoral muscle is very important for further quantifications of fibroglandular tissue volume present in the breast.Keywords: active contour, fibroglandular tissue, hough transform, pectoral muscle
Procedia PDF Downloads 345100 The Monitor for Neutron Dose in Hadrontherapy Project: Secondary Neutron Measurement in Particle Therapy
Authors: V. Giacometti, R. Mirabelli, V. Patera, D. Pinci, A. Sarti, A. Sciubba, G. Traini, M. Marafini
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The particle therapy (PT) is a very modern technique of non invasive radiotherapy mainly devoted to the treatment of tumours untreatable with surgery or conventional radiotherapy, because localised closely to organ at risk (OaR). Nowadays, PT is available in about 55 centres in the word and only the 20\% of them are able to treat with carbon ion beam. However, the efficiency of the ion-beam treatments is so impressive that many new centres are in construction. The interest in this powerful technology lies to the main characteristic of PT: the high irradiation precision and conformity of the dose released to the tumour with the simultaneous preservation of the adjacent healthy tissue. However, the beam interactions with the patient produce a large component of secondary particles whose additional dose has to be taken into account during the definition of the treatment planning. Despite, the largest fraction of the dose is released to the tumour volume, a non-negligible amount is deposed in other body regions, mainly due to the scattering and nuclear interactions of the neutrons within the patient body. One of the main concerns in PT treatments is the possible occurrence of secondary malignant neoplasm (SMN). While SMNs can be developed up to decades after the treatments, their incidence impacts directly life quality of the cancer survivors, in particular in pediatric patients. Dedicated Treatment Planning Systems (TPS) are used to predict the normal tissue toxicity including the risk of late complications induced by the additional dose released by secondary neutrons. However, no precise measurement of secondary neutrons flux is available, as well as their energy and angular distributions: an accurate characterization is needed in order to improve TPS and reduce safety margins. The project MONDO (MOnitor for Neutron Dose in hadrOntherapy) is devoted to the construction of a secondary neutron tracker tailored to the characterization of that secondary neutron component. The detector, based on the tracking of the recoil protons produced in double-elastic scattering interactions, is a matrix of thin scintillating fibres, arranged in layer x-y oriented. The final size of the object is 10 x 10 x 20 cm3 (squared 250µm scint. fibres, double cladding). The readout of the fibres is carried out with a dedicated SPAD Array Sensor (SBAM) realised in CMOS technology by FBK (Fondazione Bruno Kessler). The detector is under development as well as the SBAM sensor and it is expected to be fully constructed for the end of the year. MONDO will make data tacking campaigns at the TIFPA Proton Therapy Center of Trento, at the CNAO (Pavia) and at HIT (Heidelberg) with carbon ion in order to characterize the neutron component and predict the additional dose delivered on the patients with much more precision and to drastically reduce the actual safety margins. Preliminary measurements with charged particles beams and MonteCarlo FLUKA simulation will be presented.Keywords: secondary neutrons, particle therapy, tracking detector, elastic scattering
Procedia PDF Downloads 22199 Ordered Mesoporous Carbons of Different Morphology for Loading and Controlled Release of Active Pharmaceutical Ingredients
Authors: Aleksander Ejsmont, Aleksandra Galarda, Joanna Goscianska
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Smart porous carriers with defined structure and physicochemical properties are required for releasing the therapeutic drug with precise control of delivery time and location in the body. Due to their non-toxicity, ordered structure, chemical, and thermal stability, mesoporous carbons can be considered as modern carriers for active pharmaceutical ingredients (APIs) whose effectiveness needs frequent dosing algorithms. Such an API-carrier system, if programmed precisely, may stabilize the pharmaceutical and increase its dissolution leading to enhanced bioavailability. The substance conjugated with the material, through its prior adsorption, can later be successfully applied internally to the organism, as well as externally if the API release is feasible under these conditions. In the present study, ordered mesoporous carbons of different morphologies and structures, prepared by hard template method, were applied as carriers in the adsorption and controlled release of active pharmaceutical ingredients. In the first stage, the carbon materials were synthesized and functionalized with carboxylic groups by chemical oxidation using ammonium persulfate solution and then with amine groups. Materials obtained were thoroughly characterized with respect to morphology (scanning electron microscopy), structure (X-ray diffraction, transmission electron microscopy), characteristic functional groups (FT-IR spectroscopy), acid-base nature of surface groups (Boehm titration), parameters of the porous structure (low-temperature nitrogen adsorption) and thermal stability (TG analysis). This was followed by a series of tests of adsorption and release of paracetamol, benzocaine, and losartan potassium. Drug release experiments were performed in the simulated gastric fluid of pH 1.2 and phosphate buffer of pH 7.2 or 6.8 at 37.0 °C. The XRD patterns in the small-angle range and TEM images revealed that functionalization of mesoporous carbons with carboxylic or amine groups leads to the decreased ordering of their structure. Moreover, the modification caused a considerable reduction of the carbon-specific surface area and pore volume, but it simultaneously resulted in changing their acid-base properties. Mesoporous carbon materials exhibit different morphologies, which affect the host-guest interactions during the adsorption process of active pharmaceutical ingredients. All mesoporous carbons show high adsorption capacity towards drugs. The sorption capacity of materials is mainly affected by BET surface area and the structure/size matching between adsorbent and adsorbate. Selected APIs are linked to the surface of carbon materials mainly by hydrogen bonds, van der Waals forces, and electrostatic interactions. The release behavior of API is highly dependent on the physicochemical properties of mesoporous carbons. The release rate of APIs could be regulated by the introduction of functional groups and by changing the pH of the receptor medium. Acknowledgments—This research was supported by the National Science Centre, Poland (project SONATA-12 no: 2016/23/D/NZ7/01347).Keywords: ordered mesoporous carbons, sorption capacity, drug delivery, carbon nanocarriers
Procedia PDF Downloads 17098 Rapid Building Detection in Population-Dense Regions with Overfitted Machine Learning Models
Authors: V. Mantey, N. Findlay, I. Maddox
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The quality and quantity of global satellite data have been increasing exponentially in recent years as spaceborne systems become more affordable and the sensors themselves become more sophisticated. This is a valuable resource for many applications, including disaster management and relief. However, while more information can be valuable, the volume of data available is impossible to manually examine. Therefore, the question becomes how to extract as much information as possible from the data with limited manpower. Buildings are a key feature of interest in satellite imagery with applications including telecommunications, population models, and disaster relief. Machine learning tools are fast becoming one of the key resources to solve this problem, and models have been developed to detect buildings in optical satellite imagery. However, by and large, most models focus on affluent regions where buildings are generally larger and constructed further apart. This work is focused on the more difficult problem of detection in populated regions. The primary challenge with detecting small buildings in densely populated regions is both the spatial and spectral resolution of the optical sensor. Densely packed buildings with similar construction materials will be difficult to separate due to a similarity in color and because the physical separation between structures is either non-existent or smaller than the spatial resolution. This study finds that training models until they are overfitting the input sample can perform better in these areas than a more robust, generalized model. An overfitted model takes less time to fine-tune from a generalized pre-trained model and requires fewer input data. The model developed for this study has also been fine-tuned using existing, open-source, building vector datasets. This is particularly valuable in the context of disaster relief, where information is required in a very short time span. Leveraging existing datasets means that little to no manpower or time is required to collect data in the region of interest. The training period itself is also shorter for smaller datasets. Requiring less data means that only a few quality areas are necessary, and so any weaknesses or underpopulated regions in the data can be skipped over in favor of areas with higher quality vectors. In this study, a landcover classification model was developed in conjunction with the building detection tool to provide a secondary source to quality check the detected buildings. This has greatly reduced the false positive rate. The proposed methodologies have been implemented and integrated into a configurable production environment and have been employed for a number of large-scale commercial projects, including continent-wide DEM production, where the extracted building footprints are being used to enhance digital elevation models. Overfitted machine learning models are often considered too specific to have any predictive capacity. However, this study demonstrates that, in cases where input data is scarce, overfitted models can be judiciously applied to solve time-sensitive problems.Keywords: building detection, disaster relief, mask-RCNN, satellite mapping
Procedia PDF Downloads 16697 Improved Elastoplastic Bounding Surface Model for the Mathematical Modeling of Geomaterials
Authors: Andres Nieto-Leal, Victor N. Kaliakin, Tania P. Molina
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The nature of most engineering materials is quite complex. It is, therefore, difficult to devise a general mathematical model that will cover all possible ranges and types of excitation and behavior of a given material. As a result, the development of mathematical models is based upon simplifying assumptions regarding material behavior. Such simplifications result in some material idealization; for example, one of the simplest material idealization is to assume that the material behavior obeys the elasticity. However, soils are nonhomogeneous, anisotropic, path-dependent materials that exhibit nonlinear stress-strain relationships, changes in volume under shear, dilatancy, as well as time-, rate- and temperature-dependent behavior. Over the years, many constitutive models, possessing different levels of sophistication, have been developed to simulate the behavior geomaterials, particularly cohesive soils. Early in the development of constitutive models, it became evident that elastic or standard elastoplastic formulations, employing purely isotropic hardening and predicated in the existence of a yield surface surrounding a purely elastic domain, were incapable of realistically simulating the behavior of geomaterials. Accordingly, more sophisticated constitutive models have been developed; for example, the bounding surface elastoplasticity. The essence of the bounding surface concept is the hypothesis that plastic deformations can occur for stress states either within or on the bounding surface. Thus, unlike classical yield surface elastoplasticity, the plastic states are not restricted only to those lying on a surface. Elastoplastic bounding surface models have been improved; however, there is still need to improve their capabilities in simulating the response of anisotropically consolidated cohesive soils, especially the response in extension tests. Thus, in this work an improved constitutive model that can more accurately predict diverse stress-strain phenomena exhibited by cohesive soils was developed. Particularly, an improved rotational hardening rule that better simulate the response of cohesive soils in extension. The generalized definition of the bounding surface model provides a convenient and elegant framework for unifying various previous versions of the model for anisotropically consolidated cohesive soils. The Generalized Bounding Surface Model for cohesive soils is a fully three-dimensional, time-dependent model that accounts for both inherent and stress induced anisotropy employing a non-associative flow rule. The model numerical implementation in a computer code followed an adaptive multistep integration scheme in conjunction with local iteration and radial return. The one-step trapezoidal rule was used to get the stiffness matrix that defines the relationship between the stress increment and the strain increment. After testing the model in simulating the response of cohesive soils through extensive comparisons of model simulations to experimental data, it has been shown to give quite good simulations. The new model successfully simulates the response of different cohesive soils; for example, Cardiff Kaolin, Spestone Kaolin, and Lower Cromer Till. The simulated undrained stress paths, stress-strain response, and excess pore pressures are in very good agreement with the experimental values, especially in extension.Keywords: bounding surface elastoplasticity, cohesive soils, constitutive model, modeling of geomaterials
Procedia PDF Downloads 31096 Sustainable Recycling Practices to Reduce Health Hazards of Municipal Solid Waste in Patna, India
Authors: Anupama Singh, Papia Raj
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Though Municipal Solid Waste (MSW) is a worldwide problem, yet its implications are enormous in developing countries, as they are unable to provide proper Municipal Solid Waste Management (MSWM) for the large volume of MSW. As a result, the collected wastes are dumped in open dumping at landfilling sites while the uncollected wastes remain strewn on the roadside, many-a-time clogging drainage. Such unsafe and inadequate management of MSW causes various public health hazards. For example, MSW directly on contact or by leachate contaminate the soil, surface water, and ground water; open burning causes air pollution; anaerobic digestion between the piles of MSW enhance the greenhouse gases i.e., carbon dioxide and methane (CO2 and CH4) into the atmosphere. Moreover, open dumping can cause spread of vector borne disease like cholera, typhoid, dysentery, and so on. Patna, the capital city of Bihar, one of the most underdeveloped provinces in India, is a unique representation of this situation. Patna has been identified as the ‘garbage city’. Over the last decade there has been an exponential increase in the quantity of MSW generation in Patna. Though a large proportion of such MSW is recyclable in nature, only a negligible portion is recycled. Plastic constitutes the major chunk of the recyclable waste. The chemical composition of plastic is versatile consisting of toxic compounds, such as, plasticizers, like adipates and phthalates. Pigmented plastic is highly toxic and it contains harmful metals such as copper, lead, chromium, cobalt, selenium, and cadmium. Human population becomes vulnerable to an array of health problems as they are exposed to these toxic chemicals multiple times a day through air, water, dust, and food. Based on analysis of health data it can be emphasized that in Patna there has been an increase in the incidence of specific diseases, such as, diarrhoea, dysentry, acute respiratory infection (ARI), asthma, and other chronic respiratory diseases (CRD). This trend can be attributed to improper MSWM. The results were reiterated through a survey (N=127) conducted during 2014-15 in selected areas of Patna. Random sampling method of data collection was used to better understand the relationship between different variables affecting public health due to exposure to MSW and lack of MSWM. The results derived through bivariate and logistic regression analysis of the survey data indicate that segregation of wastes at source, segregation behavior, collection bins in the area, distance of collection bins from residential area, and transportation of MSW are the major determinants of public health issues. Sustainable recycling is a robust method for MSWM with its pioneer concerns being environment, society, and economy. It thus ensures minimal threat to environment and ecology consequently improving public health conditions. Hence, this paper concludes that sustainable recycling would be the most viable approach to manage MSW in Patna and would eventually reduce public health hazards.Keywords: municipal solid waste, Patna, public health, sustainable recycling
Procedia PDF Downloads 31795 A Semi-supervised Classification Approach for Trend Following Investment Strategy
Authors: Rodrigo Arnaldo Scarpel
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Trend following is a widely accepted investment strategy that adopts a rule-based trading mechanism that rather than striving to predict market direction or on information gathering to decide when to buy and when to sell a stock. Thus, in trend following one must respond to market’s movements that has recently happen and what is currently happening, rather than on what will happen. Optimally, in trend following strategy, is to catch a bull market at its early stage, ride the trend, and liquidate the position at the first evidence of the subsequent bear market. For applying the trend following strategy one needs to find the trend and identify trade signals. In order to avoid false signals, i.e., identify fluctuations of short, mid and long terms and to separate noise from real changes in the trend, most academic works rely on moving averages and other technical analysis indicators, such as the moving average convergence divergence (MACD) and the relative strength index (RSI) to uncover intelligible stock trading rules following trend following strategy philosophy. Recently, some works has applied machine learning techniques for trade rules discovery. In those works, the process of rule construction is based on evolutionary learning which aims to adapt the rules to the current environment and searches for the global optimum rules in the search space. In this work, instead of focusing on the usage of machine learning techniques for creating trading rules, a time series trend classification employing a semi-supervised approach was used to early identify both the beginning and the end of upward and downward trends. Such classification model can be employed to identify trade signals and the decision-making procedure is that if an up-trend (down-trend) is identified, a buy (sell) signal is generated. Semi-supervised learning is used for model training when only part of the data is labeled and Semi-supervised classification aims to train a classifier from both the labeled and unlabeled data, such that it is better than the supervised classifier trained only on the labeled data. For illustrating the proposed approach, it was employed daily trade information, including the open, high, low and closing values and volume from January 1, 2000 to December 31, 2022, of the São Paulo Exchange Composite index (IBOVESPA). Through this time period it was visually identified consistent changes in price, upwards or downwards, for assigning labels and leaving the rest of the days (when there is not a consistent change in price) unlabeled. For training the classification model, a pseudo-label semi-supervised learning strategy was used employing different technical analysis indicators. In this learning strategy, the core is to use unlabeled data to generate a pseudo-label for supervised training. For evaluating the achieved results, it was considered the annualized return and excess return, the Sortino and the Sharpe indicators. Through the evaluated time period, the obtained results were very consistent and can be considered promising for generating the intended trading signals.Keywords: evolutionary learning, semi-supervised classification, time series data, trading signals generation
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