Search results for: adverse weather

Authors: Zahra Jandaghian, Mehdi Ghobadi, Michal Bartko, Alex Hayes, Marianne Armstrong, Alexandra Thompson, Michael Lacasse

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The Intergovernmental Panel on Climate Change (IPCC) report stated the urgent need to cut greenhouse gas emissions to avoid the adverse impacts of climatic changes. The United Nations has forecasted that nearly 70 percent of people will live in urban areas by 2050 resulting in a doubling of the global building stock. Given that buildings are currently recognised as emitting 40 percent of global carbon emissions, there is thus an urgent incentive to decarbonize existing buildings and to build net-zero carbon buildings. To attain net zero carbon emissions in communities in the future requires action in two directions: I) reduction of emissions; and II) removal of on-going emissions from the atmosphere once de-carbonization measures have been implemented. Nature-based solutions (NBS) have a significant role to play in achieving net zero carbon communities, spanning both emission reductions and removal of on-going emissions. NBS for the decarbonisation of buildings can be achieved by using green roofs and green walls – increasing vertical and horizontal vegetation on the building envelopes – and using nature-based materials that either emit less heat to the atmosphere thus decreasing photochemical reaction rates, or store substantial amount of carbon during the whole building service life within their structure. The NBS approach can also mitigate urban flooding and overheating, improve urban climate and air quality, and provide better living conditions for the urban population. For existing buildings, de-carbonization mostly requires retrofitting existing envelopes efficiently to use NBS techniques whereas for future construction, de-carbonization involves designing new buildings with low carbon materials as well as having the integrity and system capacity to effectively employ NBS. This paper presents the opportunities and challenges in respect to the de-carbonization of buildings using NBS for both building retrofits and new construction. This review documents the effectiveness of NBS to de-carbonize Canadian buildings, identifies the missing links to implement these techniques in cold climatic conditions, and determine a road map and immediate approaches to mitigate the adverse impacts of climate change such as urban heat islanding. Recommendations are drafted for possible inclusion in the Canadian building and energy codes.

Keywords: decarbonization, nature-based solutions, GHG emissions, greenery enhancement, buildings

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Authors: Raj Kumar Kama, Rajshree Kamat

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Traffic congestion is a serious problem that is to be considered, and it is increasing day-by-day in urban areas that is seriously affecting the urban society. From the study, it is understood that increased urbanization and growth of population are the principal causes of congestion. It has adverse effects on society, economy, environment, and health. This study mainly focussed on studying and understanding the causes of congestion, consequences faced by urban society, and planning solutions to mitigate congestion. Techniques like transit oriented development (TOD) and integrated transport systems are more effective in mitigating traffic congestion.

Keywords: traffic congestion, transit oriented development, integrated transport system, urbanization

Procedia PDF Downloads 284

Authors: Francisco Toledo-Castillo, María Josefa Sospedra-Baeza, Sergio Hidalgo-Fuentes

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Motorcycles constitute about 9% of all motorized vehicles in Spain and are generally overrepresented in traffic accidents, accounting for 21% of total accidents. Six years of motorcycle accident data were obtained through the national accident database of Spain (Dirección General de Tráfico). Some of the studied factors are age, gender, helmet wearing, alcohol consumption, speeding, subject’s driving license and for how long it has been held, the trip purpose, and the presence of a passenger on the vehicle. Key findings show helmet use, unsafe speed, the trip purpose, weather, distraction, collision type and other variables play significant roles in crash-injury outcomes. Finally, we examine evolution of mortality and severity from 2006 to 2011.

Keywords: motorcycle accidents, risk factors, statistics, Spain

Procedia PDF Downloads 346

Authors: Getachew Demesa Bexa

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Building resilience to withstand extreme weather events through reduction and mitigation measures towards predicted disasters with appropriate contingency plans complemented by timely and effective emergency response demands committed and integrated/coordinated efforts. The 2006 flood disaster that claimed more than 200 people in Dire Dawa town shifted the paradigm from reactive to proactive engagement among government, NGOs and communities to contain future disasters through resilience building. Dire Dawa CMDRR Association is a model community organization that demonstrated the basic minimum and turning adversity into opportunity by mobilizing vulnerable community members. Meanwhile the birth of African Centre for Disaster Risk Management is a milestone in changing the image of the country and beyond in resilience building while linking relief and development.

Keywords: Dire Dawa, disaster, resilience, risk management

Procedia PDF Downloads 356

Authors: Preeyaphorn Kosa, Thanutch Sukwimolseree

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The climate change is a main parameter which affects the element of hydrological cycle especially runoff. Then, the purpose of this study is to determine the impact of the climate change on surface runoff using land use map on 2008 and daily weather data during January 1, 1979 to September 30, 2010 for SWAT model. SWAT continuously simulate time model and operates on a daily time step at basin scale. The results present that the effect of temperature change cannot be clearly presented on the change of runoff while the rainfall, relative humidity and evaporation are the parameters for the considering of runoff change. If there are the increasing of rainfall and relative humidity, there is also the increasing of runoff. On the other hand, if there is the increasing of evaporation, there is the decreasing of runoff.

Keywords: climate, runoff, SWAT, upper Mun River basin

Procedia PDF Downloads 376

Authors: N. H. D. P. Fonseka, I. H. Rajapakse, A. S. Dissanayake

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Background: Problem drinking, namely alcohol dependence (AD) and alcohol abuse (AA) are associated with major medical, social and economic adverse consequences. Problem drinking behavior is noted among those admitted to hospitals due to alcohol-related medical/surgical complaints as well as those with unrelated complaints. Literature shows an association between alcohol consumption and depression. Aims of this study were to determine the frequency of problem drinking and depression among males with a history of alcohol consumption tertiary care setting in Southern Sri Lanka. Method: Two-hundred male patients who consumed alcohol, receiving care in medical and surgical wards in Teaching Hospital Galle, were assessed. A validated J12 questionnaire of the Mini International Neuropsychiatric Interview was administered to determine frequency AA and AD. A validated PHQ 9 questionnaire to determine the prevalence and severity of depression. Results: Sixty-three participants (31%) had problem drinking. Of them, 61% had AD, and 39% had AA. Depression was noted in 39 (19%) subjects. In those who reported alcohol consumption not amounting to problem drinking, depression was noted in 23 (16%) participants. Mild depression was seen in 17, moderate in five and moderately severe in one. Among those who had problem drinking, 16 (25%) had depression. Mild depression was seen in four, moderate in seven, moderately severe in three and severe in two. Conclusions: A high proportion alcohol users had problem drinking. Adverse consequences associated with problem drinking places a major strain on the health system especially in a low resource setting where healthcare spending is limited and alcohol cessation support services are not well organised. Thus alcohol consumption and problem drinking behaviour need to be inquired into all medical consultations. Community prevalence of depression in Sri Lanka is approximately 10%. Depression among those consuming alcohol was two times higher compared to the general population. The rates of depression among those with problem drinking were especially high being 2.5 times more common than in the general population. A substantial proportion of these patients with depression had moderately severe or severe depression. When depression coexists with problem drinking, it may increase the tendency to consume alcohol as well as act as a barrier to the success of alcohol cessation interventions. Thus screening all patients who consume alcohol for depression, especially those who are problem drinkers becomes an important step in their clinical evaluation. In addition, in view of the high prevalence of problem drinking and coexistent depression, the need to organize a structured alcohol cessation support service in Sri Lanka as well as the need for increasing access to psychological evaluation and treatment of those with problem drinking are highlighted.

Keywords: alcohol abuse, alcohol, depression, problem drinking

Procedia PDF Downloads 143

Authors: Neelam Kadyan

Abstract:

Global environmental change is happening at an alarming rate in the present world. Floods, Tsunamis’, Avalanches, Change in Weather patterns, Rise in sea temperature, Landslides, are only few evidences of this change. To regulate such alarming growth of global change in environment certain regulatory system or mechanism is required. Nuisance,negligence,absolute liability,strict liability and trespass are some of the effective common law principles which are helpful in environmental problems. What we need today is sufficient law and adequate machinery to enforce the legal standards. Without law environmental standards cannot be enforced and once again there is need to adopt the common law approach in solving the problem of environmental change as through this approach the affected person can get compensation and as the same time it puts check on wrongdoer.

Keywords: global environmental problems, nuisance, negligence, trespass, strict liability, absolute liability

Procedia PDF Downloads 547

Authors: Norimichi Nagano, Yoshio Hirano, Tsutomu Yasukawa

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Mesenchymal stem cells are thought to confer neuroprotection, facilitate tissue regeneration and exert their effects on retinal degenerative diseases, however, adverse events such as proliferative vitreoretinopathy and preretinal membrane disease associated with cell suspension transplantation have also been reported. We have recently developed human (allogeneic) adipose tissue-derived mesenchymal stem cell (adMSC) sheets through our proprietary sheet transformation technique, which could potentially mitigate these adverse events. To clarify the properties of our adMSC sheets named PAL-222, we performed in vitro studies such as viability testing, cytokine secretions by ELISA, immunohistochemical study, and migration assay. The viability of the cells exceeded 70%. Vascular Endothelial Growth Factor (VEGF) and Pigment Epithelium-Derived Factor (PEDF), which are quite important cytokines for the retinal area, were observed. PAL-222 expressed type I collagen, a strength marker, type IV collagen, a marker of the basement membrane, and elastin, an elasticity marker. Finally, the migration assay was performed and showed negative, which means that PAL-222 is stably kept in the topical area and does not come to pieces. Next, to evaluate the efficacy in vivo, we transplanted PAL-222 into the subretinal space of the eye of Royal College of Surgeons rats with congenital retinal degeneration and assessed it for three weeks after transplantation. We confirmed that PAL-222 suppressed the decrease in the thickness of the outer nuclear layer, which means that the photoreceptor protective effect treated with PAL-222 was significantly higher than that in the sham group. (p < 0.01). This finding demonstrates that PAL-222 showed their retinoprotective effect in a model of congenital retinal degeneration. As the study suggested the efficacy of PAL-222 in both in vitro and in vivo studies, we are presently engaged in clinical trials of PAL-222 for myopic chorioretinal atrophy, which is one of the retinal degenerative diseases, for the purpose of regenerative medicine.

Keywords: cell sheet, clinical trial, mesenchymal stem cell, myopic chorioretinal atrophy

Procedia PDF Downloads 62

Authors: Hyung Joo Lee, Jin Young Choi, Gun Soo Park, Kyo Sun Oh, Dong Jun Won

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The fluctuation of the output of the renewable generator caused by weather conditions must be mitigated because it imposes strain on the system and adversely affects power quality. In this paper, we focus on mitigating the output fluctuation of the photovoltaic (PV) using battery energy storage system (BESS). To satisfy tight conditions of system, proposed algorithm is developed. This algorithm focuses on adjusting the integrated output curve considering state of capacity (SOC) of the battery. In this paper, the simulation model is PSCAD / EMTDC software. SOC of the battery and the overall output curve are shown using the simulation results. We also considered losses and battery efficiency.

Keywords: photovoltaic generation, battery energy storage system, renewable integration, power smoothing

Procedia PDF Downloads 259

Authors: N. K. Bhute, B. B. Bhosle, D. G. More, B. V. Bhede

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The field experiments were conducted during kharif season of the year 2007-08 at the experimental farm of the Department of Agricultural Entomology, Vasantrao Naik Marathwada Krishi Vidyapeeth, Studies on evaluation of different IPM modules for Bt cotton in relation to yield economics and ICBR revealed that MAU and CICR IPM modules proved superior. It was, however, on par with chemical control. Considering the ICBR and safety to natural enemies, an inference can be drawn that Bt cotton with IPM module is the most ideal combination. Besides reduction in insecticide use, it is also expected to ensure favourable ecological and economic returns in contrast to the adverse effects due to conventional insecticides. The IPM approach, which takes care of varying pest situation, appears to be essential for gaining higher advantage from Bt cotton.

Keywords: yield, economics, ICBR, IPM Modules, Bt cotton

Procedia PDF Downloads 246

Authors: Kamalpreet Kaur, Renu Dhir

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Climate prediction is an essential component of climate research, which helps evaluate possible effects on economies, communities, and ecosystems. Climate prediction involves short-term weather prediction, seasonal prediction, and long-term climate change prediction. Climate prediction can use the information gathered from satellites, ground-based stations, and ocean buoys, among other sources. The paper's four architectures, such as ResNet50, VGG19, Inception-v3, and Xception, have been combined using an ensemble approach for overall performance and robustness. An ensemble of different models makes a prediction, and the majority vote determines the final prediction. The various architectures such as ResNet50, VGG19, Inception-v3, and Xception efficiently classify the dataset RSI-CB256, which contains satellite images into cloudy and non-cloudy. The generated ensembled S-E model (Sar-ensembled model) provides an accuracy of 99.25%.

Keywords: climate, satellite images, prediction, classification

Procedia PDF Downloads 46

Authors: I. Muslih, A. Alkhalailah, A. Merdji

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Photovoltaic efficiency is highly affected by dust accumulation; the dust particles prevent direct solar radiation from reaching the panel surface; therefore a reduction in output power will occur. A study of dust and soiling accumulation effect on the output power of PV panels was conducted for different periods of time from May to October in three countries of the MENA region, Jordan, Egypt, and Algeria, under local weather conditions. This study leads to build a more realistic equation to estimate the power reduction as a function of time. This logarithmic function shows the high reduction in power in the first days with 10% reduction in output power compared to the reference system, where it reaches a steady state value after 60 days to reach a maximum value of 30%.

Keywords: dust effect, MENA, solar energy, PV system

Procedia PDF Downloads 198

Authors: A. Alyaaria, b, J. P. Wignerona, A. Ducharneb, Y. Kerrc, P. de Rosnayd, R. de Jeue, A. Govinda, A. Al Bitarc, C. Albergeld, J. Sabaterd, C. Moisya, P. Richaumec, A. Mialonc

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Global Level-3 surface soil moisture (SSM) maps from the passive microwave soil moisture and Ocean Salinity satellite (SMOSL3) have been released. To further improve the Level-3 retrieval algorithm, evaluation of the accuracy of the spatio-temporal variability of the SMOS Level 3 products (referred to here as SMOSL3) is necessary. In this study, a comparative analysis of SMOSL3 with a SSM product derived from the observations of the Advanced Microwave Scanning Radiometer (AMSR-E) computed by implementing the Land Parameter Retrieval Model (LPRM) algorithm, referred to here as AMSRM, is presented. The comparison of both products (SMSL3 and AMSRM) were made against SSM products produced by a numerical weather prediction system (SM-DAS-2) at ECMWF (European Centre for Medium-Range Weather Forecasts) for the 03/2010-09/2011 period at global scale. The latter product was considered here a 'reference' product for the inter-comparison of the SMOSL3 and AMSRM products. Three statistical criteria were used for the evaluation, the correlation coefficient (R), the root-mean-squared difference (RMSD), and the bias. Global maps of these criteria were computed, taking into account vegetation information in terms of biome types and Leaf Area Index (LAI). We found that both the SMOSL3 and AMSRM products captured well the spatio-temporal variability of the SM-DAS-2 SSM products in most of the biomes. In general, the AMSRM products overestimated (i.e., wet bias) while the SMOSL3 products underestimated (i.e., dry bias) SSM in comparison to the SM-DAS-2 SSM products. In term of correlation values, the SMOSL3 products were found to better capture the SSM temporal dynamics in highly vegetated biomes ('Tropical humid', 'Temperate Humid', etc.) while best results for AMSRM were obtained over arid and semi-arid biomes ('Desert temperate', 'Desert tropical', etc.). When removing the seasonal cycles in the SSM time variations to compute anomaly values, better correlation with the SM-DAS-2 SSM anomalies were obtained with SMOSL3 than with AMSRM, in most of the biomes with the exception of desert regions. Eventually, we showed that the accuracy of the remotely sensed SSM products is strongly related to LAI. Both the SMOSL3 and AMSRM (slightly better) SSM products correlate well with the SM-DAS2 products over regions with sparse vegetation for values of LAI < 1 (these regions represent almost 50% of the pixels considered in this global study). In regions where LAI>1, SMOSL3 outperformed AMSRM with respect to SM-DAS-2: SMOSL3 had almost consistent performances up to LAI = 6, whereas AMSRM performance deteriorated rapidly with increasing values of LAI.

Keywords: remote sensing, microwave, soil moisture, AMSR-E, SMOS

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Authors: Hyeongju Jeon, Yonghyun Kim, Yongil Kim

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Synthetic Aperture Radar (SAR) is an effective tool for damage assessment induced by disasters due to its all-weather and night/day acquisition capability. In this paper, the 2017 Colombia landslide was observed using full-polarimetric ALOS/PALSAR-2 data. Polarimetric decompositions, including the Freeman-Durden decomposition and the Cloude decomposition, are utilized to analyze the scattering mechanisms changes before and after-landslide. These analyses are used to detect the damaged areas induced by the landslide. Experimental results validate the efficiency of the full polarimetric SAR data since the damaged areas can be well discriminated. Thus, we can conclude the proposed method using full polarimetric data has great potential for damage assessment of landslides.

Keywords: Synthetic Aperture Radar (SAR), polarimetric decomposition, damage assessment, landslide

Procedia PDF Downloads 370

Authors: John Hang Leung, Shyh-Yau Wang, Hei-Tung Yip, Fion, Ho Tsung-chin, Agnes LF Chan

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Objectives: Platinum-resistant ovarian cancer has a short overall survival of 9–12 months and limited treatment options. The combination of immunotherapy and targeted therapy appears to be a promising treatment option for patients with ovarian cancer, particularly to patients with platinum-resistant recurrent ovarian cancer (PRrOC). However, there are no direct head-to-head clinical trials comparing their efficacy and toxicity. We, therefore, used a network to directly and indirectly compare seven newer immunotherapies or targeted therapies combined with chemotherapy in platinum-resistant relapsed ovarian cancer, including antibody-drug conjugates, PD-1 (Programmed death-1) and PD-L1 (Programmed death-ligand 1), PARP (Poly ADP-ribose polymerase) inhibitors, TKIs (Tyrosine kinase inhibitors), and antiangiogenic agents. Methods: We searched PubMed (Public/Publisher MEDLINE), EMBASE (Excerpta Medica Database), and the Cochrane Library electronic databases for phase II and III trials involving PRrOC patients treated with immunotherapy or targeted therapy plus chemotherapy. The quality of included trials was assessed using the GRADE method. The primary outcomes compared were progression-free survival, the secondary outcomes were overall survival and safety. Results: Seven randomized controlled trials involving a total of 2058 PRrOC patients were included in this analysis. Bevacizumab plus chemotherapy showed statistically significant differences in PFS (Progression-free survival) but not OS (Overall survival) for all interested targets and immunotherapy regimens; however, according to the heatmap analysis, bevacizumab plus chemotherapy had a statistically significant risk of ≥grade 3 SAEs (Severe adverse effects), particularly hematological severe adverse events (neutropenia, anemia, leukopenia, and thrombocytopenia). Conclusions: Bevacizumab plus chemotherapy resulted in better PFS as compared with all interested regimens for the treatment of PRrOC. However, statistical differences in SAEs as bevacizumab plus chemotherapy is associated with a greater risk for hematological SAE.

Keywords: platinum-resistant recurrent ovarian cancer, network meta-analysis, immune checkpoint inhibitors, target therapy, antiangiogenic agents

Procedia PDF Downloads 52

Authors: Shahab Khan, Damiya Saghir

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With the advent of space technology, a new era began where space, considered the new ‘High ground,’ is used for a variety of commercial (communications, weather and navigational information, Earth resources monitoring and imagery) and military applications (surveillance, tracking, reconnaissance and espionage of adversaries). With the ever-evolving geo-political environment, where now the US foreseeing India as a counterbalance to China’s economic and military rise, significant growth in strategic collaboration between US and India has been witnessed, particularly in the space domain. This is creating a strategic imbalance in South Asia with implications for all regional countries. This research explores the present and future of Indo-US strategic collaboration in the space domain with envisaged effects and challenges for countries in the South Asian region.

Keywords: space, satellites, Indo-US strategic agreements in space domain, balance of power in South Asian region

Procedia PDF Downloads 93

Authors: Ana Hol

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Technological inventions such as websites, blogs, smartphone applications are on a daily basis influencing our decision making, are improving our productivity and are shaping futures of many consumer and service/product providers. This research identifies that these days both customers and providers heavily rely on smart phone applications. With this in mind, iTunes mobile applications store has been studies. It was identified that food related applications used by consumers can broadly be categorized into purchase apps, diaries, tracking health apps, trip farm location apps and cooking apps. On the other hand, apps used by farmers can be classified as: weather apps, pests / fertilizer app and general Facebook apps. With the aim to blur this farmer-consumer divide our research utilizes Context Specific eTransformation Framework and based on it identifies characteristic of the app that would allow this to happen.

Keywords: smart phone applications, SME - farmers, consumer, technology, business innovation

Procedia PDF Downloads 363

Authors: Ankush, Harshit Sosan Lakra, Rachita Kuthial

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Climate change poses significant challenges to vulnerable communities, particularly indigenous populations in ecologically sensitive regions. Jharkhand, located in the heart of India, is home to several indigenous communities, including the Particularly Vulnerable Tribal Groups (PVTGs). The Indigenous architecture of the region functions as a significant reservoir of climate adaptation wisdom. It explores the architectural analysis encompassing the construction materials, construction techniques, design principles, climate responsiveness, cultural relevance, adaptation, integration with the environment and traditional wisdom that has evolved through generations, rooted in cultural and socioeconomic traditions, and has allowed these communities to thrive in a variety of climatic zones, including hot and dry, humid, and hilly terrains to withstand the test of time. Despite their historical resilience to adverse climatic conditions, PVTG tribal communities face new and amplified challenges due to the accelerating pace of climate change. There is a significant research void that exists in assimilating their traditional practices and local wisdom into contemporary climate resilience initiatives. Most of the studies place emphasis on technologically advanced solutions, often ignoring the invaluable Indigenous Local knowledge that can complement and enhance these efforts. This research gap highlights the need to bridge the disconnect between indigenous knowledge and contemporary climate adaptation strategies. The study aims to explore and leverage indigenous knowledge of vernacular architecture as a strategic tool for enhancing climatic resilience among PVTGs of the region. The first objective is to understand the traditional wisdom of vernacular architecture by analyzing and documenting distinct architectural practices and cultural significance of PVTG communities, emphasizing construction techniques, materials and spatial planning. The second objective is to develop culturally sensitive climatic resilience strategies based on findings of vernacular architecture by employing a multidisciplinary research approach that encompasses ethnographic fieldwork climate data assessment considering multiple variables such as temperature variations, precipitation patterns, extreme weather events and climate change reports. This will be a tailor-made solution integrating indigenous knowledge with modern technology and sustainable practices. With the involvement of indigenous communities in the process, the research aims to ensure that the developed strategies are practical, culturally appropriate, and accepted. To foster long-term resilience against the global issue of climate change, we can bridge the gap between present needs and future aspirations with Traditional wisdom, offering sustainable solutions that will empower PVTG communities. Moreover, the study emphasizes the significance of preserving and reviving traditional Architectural wisdom for enhancing climatic resilience. It also highlights the need for cooperative endeavors of communities, stakeholders, policymakers, and researchers to encourage integrating traditional Knowledge into Modern sustainable design methods. Through these efforts, this research will contribute not only to the well-being of PVTG communities but also to the broader global effort to build a more resilient and sustainable future. Also, the Indigenous communities like PVTG in the state of Jharkhand can achieve climatic resilience while respecting and safeguarding the cultural heritage and peculiar characteristics of its native population.

Keywords: vernacular architecture, climate change, resilience, PVTGs, Jharkhand, indigenous people, India

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Authors: Allagui Mohamed

Abstract:

The study of the temporal variation of the PM10 and the SO₂ in the area of Sfax during the year of 2008, showed very significant fluctuations of the contents. They depend on the transmitting sources and the weather conditions. The study of the evolutionary behavior of the PM10 and the SO₂ in a situation of the Sirocco revealed the determining influence of the Sahara which was confirmed by its strong enrichment of the atmosphere with particulate matter. The analysis of a situation of breeze of sea highlighted the increase in the contents of the PM10 of agreement with the increase the speed of the marine wind, in particular for the diurnal period, possibly testifying to the enrichment of the aerosol in a considerable maritime component. A situation of anticyclonic winter examined when with it the accumulation of the contents of the PM10 at a rate of 70 μg/m³ showed such concentrations remained weak by comparison with other studies which show contents of about 300 μg/m³.

Keywords: PM10, sea breeze, SO₂, sirocco, anticyclone

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Authors: Pitchayanin Sukholthaman

Abstract:

Gradually accumulated, the enormous amount of waste has caused tremendous adverse impacts to the world. Bangkok, Thailand, is chosen as an urban city of a developing country having coped with serious MSW problems due to the vast amount of waste generated, ineffective and improper waste management problems. Waste generation is the most important factor for successful planning of MSW management system. Thus, the prediction of MSW is a very important role to understand MSW distribution and characteristic; to be used for strategic planning issues. This study aims to find influencing variables that affect the amount of Bangkok MSW generation quantity.

Keywords: MSW generation, MSW quantity prediction, MSW management, multiple regression, Bangkok

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Authors: Abderrahmane Diaf, Kamel Benabdellaziz

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Remote arid areas of the vast expanses of the African deserts hold huge subterranean reserves of brackish water resources waiting for economic development. This work presents design guidelines as well as initial performance data of new autonomous solar desalination equipment which could help local communities produce their own fresh water using solar energy only and, why not, contribute to transforming desert lands into lush gardens. The output of solar distillation equipment is typically low and in the range of 3 l/m2/day on the average. This new design with an integrated, water-based, environmentally-friendly solar heat storage system produced 5 l/m2/day in early spring weather. Equipment output during summer exceeded 9 liters per m2 per day.

Keywords: multiple trough distillation, solar desalination, solar distillation with heat storage, water based heat storage system

Procedia PDF Downloads 416

Authors: Jongho Park, Taekyun Kim, Jungbhin You, Sungnam Hong, Sun-Kyu Park

Abstract:

Due to the aging of bridges, increasing of maintenance costs and decreasing of structural safety is occurred. The steel corrosion of reinforced concrete bridge is the most common problem and this phenomenon is accelerating due to abnormal weather and increasing CO₂ concentration due to climate change. To solve these problems, composite members using textile have been studied. A textile reinforced concrete can reduce carbon emissions by reduced concrete and without steel bars, so a lot of structural behavior studies are needed. Therefore, in this study, textile reinforced concrete beam was made and flexural test was performed. Also, the change of flexural strength according to the prestressing was conducted. As a result, flexural strength of TRC with prestressing was increased compared and flexural behavior was shown as reinforced concrete.

Keywords: AR-glass, flexural strength, prestressing, textile reinforced concrete

Procedia PDF Downloads 309

Authors: Richard Ren

Abstract:

Air pollution is a serious danger to international well-being and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.

Keywords: air quality prediction, air pollution, artificial intelligence, machine learning algorithms

Procedia PDF Downloads 97

Authors: Kalyan S. Ghosh, B. L. Dhananjaya

Abstract:

Snake bite causes fatal injuries in multi-organs and even many deaths due to several adverse physiological effects of various phospholipases (PLA2s) present in snake venom. Though these PLA2s bear highly homologues sequences and also structure but exhibit a different extent of those pharmacological effects. In this study, we have explored the difference in the neurotoxicity of two PLA2 namely PLA2-V, PLA2-VIIIa present in the venom from Vipera russellii. Bioinformatics studies on sequences of these two proteins along with detailed structural comparison enable us to explore the differences unambiguously. The identification of the residues involved in neurotoxicity will further lead towards proper designing of inhibitors against such killing effects of the venom.

Keywords: electrostatic potential, homology modeling, hydrophobicity, neurotoxicity, Phospholipase A2

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Authors: S. M. Yasir Arafat

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Driving models are needed by many researchers to improve traffic safety and to advance autonomous vehicle design. To be most useful, a driving model must state specifically what information is needed and how it is processed. So we developed an “Obstacle Avoidance and Detection Autonomous Car” based on sensor application. The ever increasing technological demands of today call for very complex systems, which in turn require highly sophisticated controllers to ensure that high performance can be achieved and maintained under adverse conditions. Based on a developed model of brakes operation, the controller of braking system operation has been designed. It has a task to enable solution to the problem of the better controlling of braking system operation in a more accurate way then it was the case now a day.

Keywords: automobile, obstacle, safety, sensing

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Authors: Anne-Loes K. Warps, Rob A. E. M. Tollenaar, Pieter J. Tanis, Jan Willem T. Dekker

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Anastomotic leakage after colorectal cancer surgery remains a severe complication. Early diagnosis and treatment are essential to prevent further adverse outcomes. In the literature, it has been suggested that earlier reintervention is associated with better survival, but anastomotic leakage can occur with a highly variable time interval to index surgery. This study aims to evaluate the time-interval between rectal cancer resection with primary anastomosis creation and reoperation, in relation to short-term outcomes, stratified for the use of a defunctioning stoma. Methods: Data of all primary rectal cancer patients that underwent elective resection with primary anastomosis during 2013-2019 were extracted from the Dutch ColoRectal Audit. Analyses were stratified for defunctioning stoma. Anastomotic leakage was defined as a defect of the intestinal wall or abscess at the site of the colorectal anastomosis for which a reintervention was required within 30 days. Primary outcomes were new stoma construction, mortality, ICU admission, prolonged hospital stay and readmission. The association between time to reoperation and outcome was evaluated in three ways: Per 2 days, before versus on or after postoperative day 5 and during primary versus readmission. Results: In total 10,772 rectal cancer patients underwent resection with primary anastomosis. A defunctioning stoma was made in 46.6% of patients. These patients had a lower anastomotic leakage rate (8.2% vs. 11.6%, p < 0.001) and less often underwent a reoperation (45.3% vs. 88.7%, p < 0.001). Early reoperations (< 5 days) had the highest complication and mortality rate. Thereafter the distribution of adverse outcomes was more spread over the 30-day postoperative period for patients with a defunctioning stoma. Median time-interval from primary resection to reoperation for defunctioning stoma patients was 7 days (IQR 4-14) versus 5 days (IQR 3-13 days) for no-defunctioning stoma patients. The mortality rate after primary resection and reoperation were comparable (resp. for defunctioning vs. no-defunctioning stoma 1.0% vs. 0.7%, P=0.106 and 5.0% vs. 2.3%, P=0.107). Conclusion: This study demonstrated that early reinterventions after anastomotic leakage are associated with worse outcomes (i.e. mortality). Maybe the combination of a physiological dip in the cellular immune response and release of cytokines following surgery, as well as a release of endotoxins caused by the bacteremia originating from the leakage, leads to a more profound sepsis. Another explanation might be that early leaks are not contained to the pelvis, leading to a more profound sepsis requiring early reoperations. Leakage with or without defunctioning stoma resulted in a different type of reinterventions and time-interval between surgery and reoperation.

Keywords: rectal cancer surgery, defunctioning stoma, anastomotic leakage, time-interval to reoperation

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Authors: Abdullah Al Mohiuddin

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Bangladesh is one of the poorest countries in the world, and ranks low on almost all measures of economic development, thus leaving the population extremely vulnerable to natural disasters and climate events. 20% of GDP come from agriculture but more than 60% of the population relies on agriculture as their main source of income making the entire economy vulnerable to climate change and natural disasters. High population density exacerbates the exposure to and effect of climate events, and increases the levels of vulnerability, as does the poor institutional development of the country. The most vulnerable sectors to climate change impacts in Bangladesh are agriculture, coastal zones, water resources, forestry, fishery, health, biomass, and energy. High temperatures, heavy rainfall, high humidity and fairly marked seasonal variations characterize the climate in Bangladesh: Mild winter, hot humid summer and humid, warm rainy monsoon. Much of the country is flooded during the summer monsoon. The Department of Environment (DOE) under the Ministry of Environment and Forestry (MoEF) is the focal point for the United Nations Framework Convention on Climate Change (UNFCCC) and coordinates climate related activities in the country. Recently, a Climate Change Cell (CCC) has been established to address several issues including adaptation to climate change. The climate change focus started with The National Environmental Management Action Plan (NEMAP) which was prepared in 1995 in order to initiate the process to address environmental and climate change issues as long-term environmental problems for Bangladesh. Bangladesh was one of the first countries to finalise a NAPA (Preparation of a National Adaptation Plan of Action) which addresses climate change issues. The NAPA was completed in 2005, and is the first official initiative for mainstreaming adaptation to national policies and actions to cope with climate change and vulnerability. The NAPA suggests a number of adaptation strategies, for example: - Providing drinking water to coastal communities to fight the enhanced salinity caused by sea level rise, - Integrating climate change in planning and design of infrastructure, - Including climate change issues in education, - Supporting adaptation of agricultural systems to new weather extremes, - Mainstreaming CCA into policies and programmes in different sectors, e.g. disaster management, water and health, - Dissemination of CCA information and awareness raising on enhanced climate disasters, especially in vulnerable communities. Bangladesh has geared up its environment conservation steps to save the world’s poorest countries from the adverse effects of global warming. Now it is turning towards green economy policies to save the degrading ecosystem. Bangladesh is a developing country and always fights against Natural Disaster. At the same time we also fight for establishing ecological environment through promoting Green Economy/Energy by Youth Networking. ANTAR is coordinating a big Youth Network in the southern part of Bangladesh where 30 Youth group involved. It can be explained as the economic development based on sustainable development which generates growth and improvement in human’s lives while significantly reducing environmental risks and ecological scarcities. Green economy in Bangladesh promotes three bottom lines – sustaining economic, environment and social well-being.

Keywords: resilience, networking, mobilizing, resource

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Authors: Rabbia Idrees, Ananda Maiti, Saurabh Garg, Muhammad Bilal Amin

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IoT devices are the basic building blocks of IoT network that generate enormous volume of real-time and high-speed data to help organizations and companies to take intelligent decisions. To integrate this enormous data from multisource and transfer it to the appropriate client is the fundamental of IoT development. The handling of this huge quantity of devices along with the huge volume of data is very challenging. The IoT devices are battery-powered and resource-constrained and to provide energy efficient communication, these IoT devices go sleep or online/wakeup periodically and a-periodically depending on the traffic loads to reduce energy consumption. Sometime these devices get disconnected due to device battery depletion. If the node is not available in the network, then the IoT network provides incomplete, missing, and inaccurate data. Moreover, many IoT applications, like vehicle tracking and patient tracking require the IoT devices to be mobile. Due to this mobility, If the distance of the device from the sink node become greater than required, the connection is lost. Due to this disconnection other devices join the network for replacing the broken-down and left devices. This make IoT devices dynamic in nature which brings uncertainty and unreliability in the IoT network and hence produce bad quality of data. Due to this dynamic nature of IoT devices we do not know the actual reason of abnormal data. If data are of poor-quality decisions are likely to be unsound. It is highly important to process data and estimate data quality before bringing it to use in IoT applications. In the past many researchers tried to estimate data quality and provided several Machine Learning (ML), stochastic and statistical methods to perform analysis on stored data in the data processing layer, without focusing the challenges and issues arises from the dynamic nature of IoT devices and how it is impacting data quality. A comprehensive review on determining the impact of dynamic nature of IoT devices on data quality is done in this research and presented a data quality model that can deal with this challenge and produce good quality of data. This research presents the data quality model for the sensors monitoring water quality. DBSCAN clustering and weather sensors are used in this research to make data quality model for the sensors monitoring water quality. An extensive study has been done in this research on finding the relationship between the data of weather sensors and sensors monitoring water quality of the lakes and beaches. The detailed theoretical analysis has been presented in this research mentioning correlation between independent data streams of the two sets of sensors. With the help of the analysis and DBSCAN, a data quality model is prepared. This model encompasses five dimensions of data quality: outliers’ detection and removal, completeness, patterns of missing values and checks the accuracy of the data with the help of cluster’s position. At the end, the statistical analysis has been done on the clusters formed as the result of DBSCAN, and consistency is evaluated through Coefficient of Variation (CoV).

Keywords: clustering, data quality, DBSCAN, and Internet of things (IoT)

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Authors: Kwei Huan Liw, Sashi B. Darshan

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Background: Double eyelid surgery has become one of the most sought-after aesthetic procedures among Asians. Many surgeons perform surgical blepharoplasty and various other methods of non-incisional blepharoplasty. Face-Q is a validated method of measuring patient satisfaction for facial aesthetic procedures. Here we have analyzed the overall eye satisfaction score, the upper eyelid appraisal score and the adverse effect on eyes score Methods: 274 patients (548 eyes), aged between 18 to 40 years old, were recruited from 2015-2018. Each patient underwent a non-incisional double-eyelid blepharoplasty using a single-knotted continuous buried suture. 3 – 5 stab incisions were made depending on the upper eyelid size. A needle loaded with 7-0 nylon is passed from the lateral most wound through the dermis and the conjunctiva in an alternate fashion into the remaining stab wounds. The suture is then tunneled back laterally in the deeper dermis and knotted securely with the suture end. The knot is then buried within the orbicularis oculi muscle. Each patient was required to fill the Face-Q questionnaire before the procedure and 2 weeks post procedure. The results are described based on the percentage of the maximum achievable score. Patients were reviewed after 12 to 18 months to assess the long-term outcome. Results: The overall eye satisfaction score demonstrated a high level of post-operative satisfaction (97.85%), compared to 27.32% pre-operatively. The appraisal of upper eyelid scores showed drastic improvement in perception post-operatively (95.31%) compared to 21.44% pre-operatively. Adverse effect on eyes score showed a very low post-operative complication rate (0.4%) The long-term follow-up showed 6 cases that had developed asymmetrical folds. Only 1 patient agreed for revision surgery. The other 5 patients were still satisfied with the outcome and were not keen for revision surgery. None of the cases had loosening of knots. Conclusion: Modified single-knot continuous buried suture technique is a simple and non-invasive method to create aesthetically pleasing non-surgical double-eyelids, which has long-term effects. Proper patient selection is crucial and good surgical technique is required to achieve a desirable outcome.

Keywords: blepharoplasty, double-eyelid, face-Q, non-incisional

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Authors: Claire Williams

Abstract:

Randomised controlled Trials (RCTs) of efficacy are still perceived as the gold standard for the generation of evidence, and whilst advances in data collection methods are well developed, this progress has not been matched for the reporting of adverse events (AEs). Assessment and reporting of AEs in clinical trials are fraught with human error and inefficiency and are extremely time and resource intensive. Recent research conducted into the quality of reporting of AEs during clinical trials concluded it is substandard and reporting is inconsistent. Investigators commonly send reports to sponsors who are incorrectly categorised and lacking in critical information, which can complicate the detection of valid safety signals. In our presentation, we will describe an electronic data capture system, which has been designed to support clinical trial processes by reducing the resource burden on investigators, improving overall trial efficiencies, and making trials safer for patients. This proprietary technology was developed using expertise proven in the delivery of the world’s first prospective, phase 3b real-world trial, ‘The Salford Lung Study, ’ which enabled robust safety monitoring and reporting processes to be accomplished by the remote monitoring of patients’ EHRs. This technology enables safety alerts that are pre-defined by the protocol to be detected from the data extracted directly from the patients EHR. Based on study-specific criteria, which are created from the standard definition of a serious adverse event (SAE) and the safety profile of the medicinal product, the system alerts the investigator or study team to the safety alert. Each safety alert will require a clinical review by the investigator or delegate; examples of the types of alerts include hospital admission, death, hepatotoxicity, neutropenia, and acute renal failure. This is achieved in near real-time; safety alerts can be reviewed along with any additional information available to determine whether they meet the protocol-defined criteria for reporting or withdrawal. This active surveillance technology helps reduce the resource burden of the more traditional methods of AE detection for the investigators and study teams and can help eliminate reporting bias. Integration of multiple healthcare data sources enables much more complete and accurate safety data to be collected as part of a trial and can also provide an opportunity to evaluate a drug’s safety profile long-term, in post-trial follow-up. By utilising this robust and proven method for safety monitoring and reporting, a much higher risk of patient cohorts can be enrolled into trials, thus promoting inclusivity and diversity. Broadening eligibility criteria and adopting more inclusive recruitment practices in the later stages of drug development will increase the ability to understand the medicinal products risk-benefit profile across the patient population that is likely to use the product in clinical practice. Furthermore, this ground-breaking approach to AE detection not only provides sponsors with better-quality safety data for their products, but it reduces the resource burden on the investigator and study teams. With the data taken directly from the source, trial costs are reduced, with minimal data validation required and near real-time reporting enables safety concerns and signals to be detected more quickly than in a traditional RCT.

Keywords: more comprehensive and accurate safety data, near real-time safety alerts, reduced resource burden, safer trials

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