Search results for: forest fire hazard

Authors: Nion Sirimongkonlertkun, Vivard Phonekeo

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This research focused on open burning occurrence in Greater Mekong Sub-Region countries that influences the increase of PM10concentrations. Thailand, Myanmar, and Laos were chosen as a case study, and 2009, 2010, and 2012 were chosen as the year for case study. Hotspot detected by MODIS (Moderate Resolution Imaging Specto radiometer) sensor on board of Terra/Aqua satellites and provided by Rapid Response System was used to represent open burning location in the region. Hotspot was selected through fire confidence with confidence levels of 80-100%. The spatial analysis by GIS was used as the main tool for analyzing and defining the location of open burning at study sites as hotspot with the pixel size of 1 km by 1 km. The total hotspot counts in the study period of four years (2007, 2009, 2010, and January-April 2012) at the regional level, including Thailand, Laos, and Myanmar were 255,177 hotspots or a very high yearly average of 63,795 hotspots. The highest amount was seen in Myanmar (50%), followed by Laos (36%), and Thailand (14%). For Thailand, the majority of burning or 64% occurred in the northern region with the density of 5 hotspots per 100 km2. According to statistics of the 4 years, the increasing rate of hotspot from January to February was 10 times and from February to March was 4 times. After that period, the hotspot started to decline by 2 times from March to April. Therefore, in order to develop a policy which aims to lessen open burning conduction, the government should seriously focus on this problem during the peak period—February to March in every year when hotspot and open burning area is significantly increased.

Keywords: PM10, hotspot, greater mekong sub-region, open burning

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Authors: Romeo Malik, Yashraj Tripathy, Anup Barai

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Transportation safety is a major concern for vehicle electrification on a large-scale. The failure cost of lithium-ion batteries is substantial and is significantly impacted by higher liability and replacement cost. With continuous advancement on the material front in terms of higher energy density, upgrading safety characteristics are becoming more crucial for broader integration of lithium-ion batteries. Understanding and impeding thermal runaway is the prime issue for battery safety researchers. In this study, a comprehensive comparison of thermal runaway mechanisms for two different cathode types, Li(Ni₀.₃Co₀.₃Mn₀.₃)O₂ and Li(Ni₀.₈Co₀.₁₅Al₀.₀₅)O₂ is explored. Both the chemistries were studied for different states of charge, and the various abuse scenarios that lead to thermal runaway is investigated. Abuse tests include mechanical abuse, electrical abuse, and thermal abuse. Batteries undergo thermal runaway due to a series of combustible reactions taking place internally; this is observed as multiple jets of flame reaching temperatures of the order of 1000ºC. The physicochemical characterisation was performed on cells, prior to and after abuse. Battery’s state of charge and chemistry have a significant effect on the flame temperature profiles which is otherwise quantified as heat released. Majority of the failures during transportation is due to these external short circuit. Finally, a mitigation approach is proposed to impede the thermal runaway hazard. Transporting lithium-ion batteries under low states of charge is proposed as a way forward. Batteries at low states of charge have demonstrated minimal heat release under thermal runaway reducing the risk of secondary hazards such as thermal runaway propagation.

Keywords: battery reliability, lithium-ion batteries, thermal runaway characterisation, tomography

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Authors: A. A. Adebayo, A. O. Ogunkeyede, A. O. Adeigbe

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Digital globalisation and yarn of Nigeria society to overcome the digital divide have resulted in contamination of soil by heavy metals (HMs) from e-waste activities at Alaba international market, Lagos, Nigeria. The aim of this research was to determine the concentration of various metals {Cadmium (Cd), Chromium (Cr), Copper (Cu), and Lead (Pb)} and identify their ecological and health risks for the people within the study area. A total of 60 soil samples were collected at Alaba market study area. Two types of samples were collected from each sampling points: topsoil (0-15 cm), subsoil (15 -30 cm). The metal concentration results showed that the soils were heavily contaminated by HMs at topsoil and subsoil. The geoaccummulation and ecological risk indices revealed high pollution level from all studied site. The health risk assessment results suggested that there is high possibility of carcinogenic risk to humans because the carcinogenic risk via corresponding exposure pathways exceeded the safety limit of 10-6 (the acceptable level of carcinogenic risk for human). Furthermore, inhalation of soil particles is the main exposure pathway for Cr to enter the human body for all ages. Children in the vicinity are exposed more to ingestion of Pb since they tend to eat earth (pica) and repeatedly suck their fingers. This study provides basic information to create awareness for a need to introduce pollution control measures and the need to protect the ecosystem and human health within the study area at Alaba international market.

Keywords: contaminated soil, ecological risk, hazard index, risk factor, exposure pathways, heavy metals

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Authors: Minakshi Jain, I. P. Singh

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The mountain system makes the one fifth of the world’s landscape and is the home to the 600 million people. Though hills and mountains contain about 10 percent of the total population of the country, yet almost half of the country’s population living in or adjacent to the mountain areas depend directly or indirectly on the resources of the hills. Mountain environments are essential to the survival of the global ecosystems, as they sustain the economy of India through its perennial river system and precious forest wealth. Hill areas, with distinct climate, diverse vegetation and valuable flora & fauna are distinguished primarily by unique eco-system, rich both in bio-diversity and visual resources. These areas have special significance in terms of environment and economy. Still the irony is that these mountain ecosystems are fragile and highly susceptible to disturbance, with a low ability to rebound and heal after damage. Hills are home to endangered species, biological diversity and an essential part of the ecosystem. They are extremely sensitive to any human related development. Natural systems are the most ignored in the hills. The way the cities and towns have encroached them today has the serious repercussions on the climate. Amidst immense resources and constraints of nature, the town had a fantastic diversity of cultural and ethnic characteristics nurtured through ages along river basin and valley strung across the length and breadth of this Himalayan setting.

Keywords: eco-system, bio-diversity, urban sprawl, vernacular landscape

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Authors: Lingxia Li, Frédéric Schnell, Shuzhe Ding, Solène Le Douairon Lahaye

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Background: The prevalence of cardiovascular diseases (CVD) in different triathlon sports disciplines has not been determined. Purpose: The present study aimed to determine the prevalence of CVD in world-class triathletes according to their sex, sports disciplines (aquathlon, duathlon, triathlon…), and formats (short/medium, long, and ultra-long distance). Methods: Male and female elite athletes from eleven triathlon sport disciplines, ranked in the internationally yearly top 10 between 2006 and 2019, were included. The athlete’s name was associated in a Google search with selected key terms related to heart disease and/or cardiac abnormalities. The prevalence and the hazard function of the variation were calculated, and the differences were then compared. Results: From 1329 athletes (male 639, female 690), 13 cases of CVD (0.98%, 95% CI: [0.45-1.51]) were identified, and the mean age of their occurrence was 29±6 years. Although no sex differences were found in each sport discipline/format (p > 0.05), severe outcomes (sudden cardiac arrest/death and those who had to stop their sports practice) were only observed in males. Short-distance triathlon (5.08%, 95% CI: [1.12-9.05]) was more affected than other disciplines in short/medium, long, and ultra-long formats. The prevalence of CVD in athletes who participated in multi-type of sports disciplines (4.14%, 95% CI: [1.14-7.15]) was higher than in those who participated in one type (0.52%, 95% CI: [0.10-0.93]) (p = 0.0004). Conclusion: Athletes in short-distance triathlon were more affected than other disciplines in short/medium, long and ultra-long formats. Athletes who participate in short/medium distances and those who participate in multi-type of sports disciplines should be closely monitored regardless of sex.

Keywords: cardiovascular diseases, sudden cardiac death, triathlon sport disciplines, world-class athletes

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Authors: Ansong Richard Omari, Yosei Oikawa, Yoshiharu Fujii, Dorothea Sonoko Bellingrath-Kimura

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Renewed interest in soil management aimed at improving the productive capacity of Sub Saharan Africa (SSA) soils has called for the need to analyse the long term effect of different fertilization systems on soil. This study was conducted in two agroecological zones (i.e., Guinea Savannah (GS) and Deciduous forest (DF)) of Ghana to evaluate the impacts of long term (> 5 years) fertilization schemes on soil chemical and microbial properties. Soil samples under four different fertilization schemes (inorganic, inorganic and organic, organic, and no fertilization) were collected from 20 farmers` field in both agroecological zones. Soil analyses were conducted using standard procedures. All average soil quality parameters except extractable C, potential mineralizable nitrogen and CEC were significantly higher in DF sites compared to GS. Inorganic fertilization proved superior in soil chemical and microbial biomass especially in GS zone. In GS, soil deterioration index (DI) revealed that soil quality deteriorated significantly (−26%) under only organic fertilization system whereas soil improvement was observed under inorganic and no fertilization sites. In DF, either inorganic or organic and inorganic fertilization showed significant positive effects on soil quality. The high soil chemical composition and enhanced microbial biomass in DF were associated with the high rate of inorganic fertilization.

Keywords: deterioration index, fertilization scheme, microbial biomass, tropical agroecological zone

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Authors: Y. Sarı Nayim, B. N. Nayim

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This research proposal includes the defining and evaluation of the semi-natural and cultural ecosystems at Bartın University main campus in Turkey in terms of landscape mosaics. The ecosystem mosaic of the main campus was divided into zones based on ecological classification technique. Based on the results from the study, it was found that 6 different ecosystem mosaics should be used as a base in the planning and design of the existing and future landscape planning of Kutlubeyyazıcılar campus. The first landscape zone involves the 'social areas'. These areas include yards, dining areas, recreational areas and lawn areas. The second landscape zone is 'main vehicle and pedestrian areas'. These areas include vehicle access to the campus landscape, moving in the campus with vehicles, parking and pedestrian walk ways. The third zone is 'landscape areas with high visual landscape quality'. These areas will be the places where attractive structural and plant landscape elements will be used. Fourth zone will be 'landscapes of building borders and their surroundings.' The fifth and important zone that should be survived in the future is 'Actual semi-natural forest and bush areas'. And the last zone is 'water landscape' which brings ecological value to landscape areas. While determining the most convenient areas in the planning and design of the campus, these landscape mosaics should be taken into consideration. This zoning will ensure that the campus landscape is protected and living spaces in the campus apart from the areas where human activities are carried out will be used properly.

Keywords: campus landscape planning and design, landscape ecology, landscape mosaics, Bartın

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Authors: Revoti Prasad Bora, Nikita Katyal

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Promotion is a key element in the retail business. Thus, analysis of promotions to quantify their effectiveness in terms of Revenue and/or Margin is an essential activity in the retail industry. However, measuring the sales/revenue uplift is based on estimations, as the actual sales/revenue without the promotion is not present. Further, the presence of Halo and Cannibalization in a multiple parallel promotions’ scenario complicates the problem. Calculating Baseline by considering inter-brand/competitor items or using Halo and Cannibalization's impact on Revenue calculations by considering Baseline as an interpretation of items’ unit sales in neighboring nonpromotional weeks individually may not capture the overall Revenue uplift in the case of multiple parallel promotions. Hence, this paper proposes a Machine Learning based method for calculating the Revenue uplift by considering the Halo and Cannibalization impact on the Baseline and the Revenue. In the first section of the proposed methodology, Baseline of an item is calculated by incorporating the impact of the promotions on its related items. In the later section, the Revenue of an item is calculated by considering both Halo and Cannibalization impacts. Hence, this methodology enables correct calculation of the overall Revenue uplift due a given promotion.

Keywords: Halo, Cannibalization, promotion, Baseline, temporary price reduction, retail, elasticity, cross price elasticity, machine learning, random forest, linear regression

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Authors: Emmanuel Osaze Oshoiribhor, Adetokunbo MacGregor John-Otumu

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In recent years, there has been a desire to forecast student academic achievement prior to graduation. This is to help them improve their grades, particularly for individuals with poor performance. The goal of this study is to employ supervised learning techniques to construct a predictive model for student academic achievement. Many academics have already constructed models that predict student academic achievement based on factors such as smoking, demography, culture, social media, parent educational background, parent finances, and family background, to name a few. This feature and the model employed may not have correctly classified the students in terms of their academic performance. This model is built using a logistic regression classifier with basic features such as the previous semester's course score, attendance to class, class participation, and the total number of course materials or resources the student is able to cover per semester as a prerequisite to predict if the student will perform well in future on related courses. The model outperformed other classifiers such as Naive bayes, Support vector machine (SVM), Decision Tree, Random forest, and Adaboost, returning a 96.7% accuracy. This model is available as a desktop application, allowing both instructors and students to benefit from user-friendly interfaces for predicting student academic achievement. As a result, it is recommended that both students and professors use this tool to better forecast outcomes.

Keywords: artificial intelligence, ML, logistic regression, performance, prediction

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Authors: Pamir Gogoi, Ratree Wayland

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This study investigates the acoustic measures of breathiness when coarticulated with nasality. The acoustic correlates of breathiness and nasality that has already been well established after years of empirical research. Some of these acoustic parameters - like low frequency peaks and wider bandwidths- are common for both nasal and breathy voice. Therefore, it is likely that these parameters interact when a sound is coarticulated with breathiness and nasality. This leads to the hypothesis that the acoustic parameters, which usually act as robust cues in differentiating between breathy and modal voice, might not be reliable cues for differentiating between breathy and modal voice when breathiness is coarticulated with nasality. The effect of nasality on the perception of breathiness has been explored in earlier studies using synthesized speech. The results showed that perceptually, nasality and breathiness do interact. The current study investigates if a similar pattern is observed in natural speech. The study is conducted on Marathi, an Indo-Aryan language which has a three-way contrast between nasality and breathiness. That is, there is a phonemic distinction between nasals, breathy voice and breathy-nasals. Voice quality parameters like – H1-H2 (Difference between the amplitude of first and second harmonic), H1-A3 (Difference between the amplitude of first harmonic and third formant, CPP (Cepstral Peak Prominence), HNR (Harmonics to Noise ratio) and B1 (Bandwidth of first formant) were extracted. Statistical models like linear mixed effects regression and Random Forest classifiers show that measures that capture the noise component in the signal- like CPP and HNR- can classify breathy voice from modal voice better than spectral measures when breathy voice is coarticulated with nasality.

Keywords: breathiness, marathi, nasality, voice quality

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Authors: Kavita Bodke

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Structural health monitoring (SHM) is experiencing growth, necessitating the development of distinct methodologies to address its expanding scope effectively. In this study, we developed automatic structure damage identification, which incorporates three unique types of a building’s structural integrity. The first pertains to the presence of fractures within the structure, the second relates to the issue of dampness within the structure, and the third involves corrosion inside the structure. This study employs image classification techniques to discern between intact and impaired structures within structural data. The aim of this research is to find automatic damage detection with the probability of each damage class being present in one image. Based on this probability, we know which class has a higher probability or is more affected than the other classes. Utilizing photographs captured by a mobile camera serves as the input for an image classification system. Image classification was employed in our study to perform multi-class and multi-label classification. The objective was to categorize structural data based on the presence of cracks, moisture, and corrosion. In the context of multi-class image classification, our study employed three distinct methodologies: Random Forest, Multilayer Perceptron, and CNN. For the task of multi-label image classification, the models employed were Rasnet, Xceptionet, and Inception.

Keywords: SHM, CNN, deep learning, multi-class classification, multi-label classification

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Authors: Sarpong Boateng, Rohit Balasundaram, Akua Afrah Amoah

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Introduction: Racial and Gender disparities have been found to be independently associated with Salivary Gland Cancers (SGCs) survival; however, to our best knowledge, there are no previous studies on the interplay of these social determinants on the prognosis of SGCs. The objective of this study was to examine the joint effect of race and gender on the survival of SGCs. Methods: We analyzed survival outcomes of 13,547 histologically confirmed cases of SGCs using the Surveillance Epidemiology and End Results (SEER) database (2004 to 2015). Multivariable Cox regression analysis and Kaplan-Meier curves were used to estimate hazard ratios (HR) after controlling for age, tumor characteristics, treatment type and year of diagnosis. Results: 73.5% of the participants were whites, 8.5% were blacks, 10.1% were Hispanics and 58.5% were males. Overall, males had poorer survival than females (HR = 1.16, p=0.003). In the adjusted multivariable model, there were no significant differences in survival by race. However, the interaction of gender and race was statistically significant (p=0.01) in Hispanic males. Thus, compared to White females (reference), Hispanic females had significantly better survival (HR=0.53), whiles Hispanic males had worse survival outcomes (HR=1.82) for SGCs. Conclusions: Our results show significant interactions between race and gender, with racial disparities varying across the different genders for SGCs survival. This study indicates that racial and gender differences are crucial factors to be considered in the prognostic counseling and management of patients with SGCs. Biologic factors, tumor genetic characteristics, chemotherapy, lifestyle, environmental exposures, and socioeconomic and dietary factors are potential yet proven reasons that could account for racial and gender differences in the survival of SGCs.

Keywords: salivary, cancer, survival, disparity, race, gender, SEER

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Authors: Raymond Xu, Cindy Jingru Wang

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Social media has become a globally connected and influencing platform. Social media data, such as tweets, can help predict the spread of pandemics and provide individuals and healthcare providers early warnings. Public psychological reactions and opinions can be efficiently monitored by AI models on the progression of dominant topics on Twitter. However, statistics show that as the coronavirus spreads, so does an infodemic of misinformation due to pandemic-related factors such as unemployment and lockdowns. Social media algorithms are often biased toward outrage by promoting content that people have an emotional reaction to and are likely to engage with. This can influence users’ attitudes and cause confusion. Therefore, social media is a double-edged sword. Combating fake news and biased content has become one of the essential tasks. This research analyzes the variety of methods used for fake news detection covering random forest, logistic regression, support vector machines, decision tree, naive Bayes, BoW, TF-IDF, LDA, CNN, RNN, LSTM, DeepFake, and hierarchical attention network. The performance of each method is analyzed. Based on these models’ achievements and limitations, a multi-dimensional AI framework is proposed to achieve higher accuracy in infodemic detection, especially pandemic-related news. The model is trained on contextual content, images, and news metadata.

Keywords: artificial intelligence, fake news detection, infodemic detection, image recognition, sentiment analysis

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Authors: Aree Thongpukdee, Chockpisit Thepsithar, Chuthalak Thammaso

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Use of plants grown in local area for edible has a long tradition in different culture. The indigenous knowledge such as usage of plants as vegetables by local people is risk to disappear when no records are done. In order to conserve and transfer this valuable heritage to the new generation, ethnobotanical study should be investigated and documented. The survey of vegetable plants traditionally used was carried out in the year 2012. Information was accumulated via questionnaires and oral interviewing from 100 people living in 36 villages of 9 districts in Amphoe Huai Mek, Kalasin, Thailand. Local plant names, utilized parts and preparation methods of the plants were recorded. Each mentioned plant species were collected and voucher specimens were prepared. A total of 55 vegetable plant species belonging to 34 families and 54 genera were identified. The plant habits were tree, shrub, herb, climber, and shrubby fern at 21.82%, 18.18%, 38.18%, 20.00% and 1.82% respectively. The most encountered vegetable plant families were Leguminosae (20%), Cucurbitaceae (7.27%), Apiaceae (5.45%), whereas families with 3.64% uses were Araceae, Bignoniaceae, Lamiaceae, Passifloraceae, Piperaceae and Solanaceae. The most common consumptions were fresh or brief boiled young shoot or young leaf as side dishes of ‘jaeo, laab, namprik, pon’ or curries. Most locally known vegetables included 45% of the studied plants which grow along road side, backyard garden, hedgerow, open forest and rice field.

Keywords: vegetable plants, ethnobotanical survey, Kalasin, Thailand

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Authors: Muhammad Ali

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Cyber-attacks and anomaly detection on the Internet of Things (IoT) infrastructure is emerging concern in the domain of data-driven intrusion. Rapidly increasing IoT risk is now making headlines around the world. denial of service, malicious control, data type probing, malicious operation, DDos, scan, spying, and wrong setup are attacks and anomalies that can affect an IoT system failure. Everyone talks about cyber security, connectivity, smart devices, and real-time data extraction. IoT devices expose a wide variety of new cyber security attack vectors in network traffic. For further than IoT development, and mainly for smart and IoT applications, there is a necessity for intelligent processing and analysis of data. So, our approach is too secure. We train several machine learning models that have been compared to accurately predicting attacks and anomalies on IoT systems, considering IoT applications, with ANOVA-based feature selection with fewer prediction models to evaluate network traffic to help prevent IoT devices. The machine learning (ML) algorithms that have been used here are KNN, SVM, NB, D.T., and R.F., with the most satisfactory test accuracy with fast detection. The evaluation of ML metrics includes precision, recall, F1 score, FPR, NPV, G.M., MCC, and AUC & ROC. The Random Forest algorithm achieved the best results with less prediction time, with an accuracy of 99.98%.

Keywords: machine learning, analysis of variance, Internet of Thing, network security, intrusion detection

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Authors: Walid Moudani

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The healthcare environment is generally perceived as being information rich yet knowledge poor. However, there is a lack of effective analysis tools to discover hidden relationships and trends in data. In fact, valuable knowledge can be discovered from application of data mining techniques in healthcare system. In this study, a proficient methodology for the extraction of significant patterns from the coronary heart disease warehouses for heart attack prediction, which unfortunately continues to be a leading cause of mortality in the whole world, has been presented. For this purpose, we propose to enumerate dynamically the optimal subsets of the reduced features of high interest by using rough sets technique associated to dynamic programming. Therefore, we propose to validate the classification using Random Forest (RF) decision tree to identify the risky heart disease cases. This work is based on a large amount of data collected from several clinical institutions based on the medical profile of patient. Moreover, the experts’ knowledge in this field has been taken into consideration in order to define the disease, its risk factors, and to establish significant knowledge relationships among the medical factors. A computer-aided system is developed for this purpose based on a population of 525 adults. The performance of the proposed model is analyzed and evaluated based on set of benchmark techniques applied in this classification problem.

Keywords: multi-classifier decisions tree, features reduction, dynamic programming, rough sets

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Authors: Marco Vinicio Félix Lerma, Efrain Rubio Rosas, Fernando Ricardez Rueda, Victor Manuel Castaño Meneses

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This paper reports a spectral analysis of the exposure levels of radiofrequency electromagnetic fields originating from a wide variety of telecommunications sources present in an urban area of Lagos de Moreno, Jalisco, Mexico. The electromagnetic characterization of the urban zone under study was carried out by measurements in 118 sites. Measurements of TETRA,ISM434, LTE800, ISM868, GSM900, GSM1800, 3G UMTS,4G UMTS, Wlan2.4, LTE2.6, DECT, VHF Television and FM radio signals were performed at distances ranging over 10 to 1000m from 87 broadcasting towers concentrated in an urban area of about 3 hectares. The aim of these measurements is the evaluation of the electromagnetic fields power levels generated by communication systems because of their interaction with the human body. We found that in certain regions the general public exposure limits determined by ICNIRP (International Commission of Non Ionizing Radiation Protection) are overpassed from 5% up to 61% of the upper values, indicating an imminent health public hazard, whereas in other regions we found that these limits are not overpassed. This work proposes an electromagnetic pollution classification for urban zones according with ICNIRP standards. We conclude that the urban zone under study presents diverse levels of pollution and that in certain regions an electromagnetic shielding solution is needed in order to safeguard the health of the population that lives there. A practical solution in the form of paint coatings and fiber curtains for the buildings present in this zone is also proposed.

Keywords: electromagnetic field, telecommunication systems, electropollution, health hazards

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Authors: Gatot Dwi Hendro, Hayyan ul Haq

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This work aims to explore the strategy in embodying the ecological validity in creating the sustainability of public policy, particularly in strengthening the green economy in Indonesia. This green economy plays an important role in supporting the national development in Indonesia, as it is a part of the national policy that posits the primary priority in Indonesian governance. The green economy refers to the national development covering strategic natural resources, such as mining, gold, oil, coal, forest, water, marine, and the other supporting infrastructure for products and distribution, such as fabrics, roads, bridges, and so forth. Thus, all activities in those national development should consider the sustainability. This sustainability requires the strong commitment of the national and regional government, as well as the local governments to put the ecology as the main requirement for issuing any policy, such as licence in mining production, and developing and building new production and supporting infrastructures for optimising the national resources. For that reason this work will focus on the strategy how to embody the ecological values and norms in the public policy. In detail, this work will offer the method, i.e. legal techniques, in visualising and embodying the norms and public policy that valid ecologically. This ecological validity is required in order to maintain and sustain our collective life.

Keywords: ecological validity, sustainable development, coherence, Indonesian Pancasila values, environment, marine

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Authors: Mohsen Masoomi, Fazel Asadi Amjad, Monireh Arvin

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According to Naturalistic principles, human destiny in the form of blind chance and determinism, entraps the individual, so man is a defenceless creature unable to escape from the ruthless paws of a stoical universe. In Naturalism; nonetheless, melodrama mirrors a conscious alternative with a peculiar function. A typical American Naturalistic character thus cannot be a subject for social criticism of American society since they are not victims of the ongoing virtual slavery, capitalist system, nor of a ruined milieu, but of their own volition, and more importantly, their character frailty. Through a Postmodern viewpoint, each Naturalistic work can encompass some entropic trends and changes culminating in an entire failure and devastation. Frank Norris in McTeague displays the futile struggles of ordinary men and how they end up brutes. McTeague encompasses intoxication, abuse, violation, and ruthless homicides. Norris’ depictions of the falling individual as a demon represent the entropic dimension of Naturalistic novels. McTeague’s defeat is somewhat his own fault, the result of his own blunders and resolution, not the result of sheer accident. Throughout the novel, each character is a kind of insane quester indicating McTeague’s decadence and, by inference, the decadence of Western civilisation. McTeague seems to designate Norris’ solicitude for a community fabricated by the elements of human negative demeanours and conducts hauling acute symptoms of infectious dehumanisation. The aim of this article is to illustrate how one specific negative human disposition gradually, like a running fire, can spread everywhere and burn everything in itself. The author applies the concept of entropy metaphorically to describe the individual devolutions that necessarily comprise community entropy in McTeague, a dying universe.

Keywords: animal imagery, entropy, Gypsy, melodrama

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Authors: Simon Mensah Ofosu

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Illicit surface mining activities pollutes agricultural lands and water bodies and results in accumulation of heavy metals in vegetables cultivated in such areas. Heavy metal (HM) accumulation in vegetables is a serious food safety issues due to the adverse effects of metal toxicities, hence the need to investigate the levels of these metals in cultivated vegetables in the eastern region. Cocoyam leaves, cabbage and cucumber were sampled from selected farms in mining areas (Atiwa District) and non -mining areas (Yilo Krobo and East Akim District) of the region for the study. Levels of Cadmium, Lead, Mercury and Arsenic were investigated in the vegetables with Atomic Absorption Spectrometer, and the results statistically analyzed with Microsoft Office Excel (2013) Spread Sheet and ANOVA. Cadmium (Cd) and arsenic (As) were the highest and least concentrated HM in the vegetables sampled, respectively. The mean concentrations of Cd and Pb in cabbage (0.564 mg/kg, 0.470 mg/kg), cucumber (0.389 mg/kg, 0.190 mg/kg), cocoyam leaves (0.410 mg/kg, 0.256 mg/kg) respectively from the mining areas exceeded the permissible limits set by Joint FAO/WHO. The mean concentrations of the metals in vegetables from the mining and non-mining areas varied significantly (P<0.05). The Target Hazard Quotient (THQ) was used to assess the health risk posed to the human population via vegetable consumption. The THQ values of cadmium, mercury, and lead in adults and children through vegetable consumption in the mining areas were greater than 1 (THQ >1). This indicates the potential health risk that the children and adults may be facing. The THQ values of adults and children in the non-mining areas were less than the safe limit of 1 (THQ<1), hence no significant health risk posed to the population from such areas.

Keywords: food safety, risk assessment, illicit mining, public health, contaminated vegetables

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Authors: Julia DeVoy, Olivia Berlin

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The United States exports over 1.6 billion pounds of post-consumer textiles every year, primarily to countries in the Global South. These textiles make their way to landfills and open-air dumps where they decompose, contaminating water systems and releasing harmful greenhouse gases. Through this inequitable system of waste disposal, countries with less political and economic power are coerced into accepting the environmental and health consequences of over-consumption in the Global North. Thus, the global trade of post-consumer textile waste represents a serious issue of environmental justice and a public health hazard. Our research located, characterizes, and quantifies the environmental and human health risks that occur when post-consumer textiles are left to decompose in landfills and open-air dumps in the Global South. In our work, we make use of United Nations International Trade Statistics data to map the global distribution of post-consumer textiles exported from the United States. Next, we present our landfill simulating reactor designed to measure toxicity of leachate resulting from the decomposition of textiles in developing countries and to quantify the related greenhouse gas emissions. This design makes use of low-cost and sustainable materials to promote frugal innovation and make landfill reactors more accessible. Finally, we describe how the data generated from these tools can be leveraged to inform individual consumer behaviors, local policies around textile waste disposal, and global advocacy efforts to mitigate the environmental harms caused by textile waste.

Keywords: sustainability, textile design, public health, built environment

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Authors: Salwa M. Almomen, Mona A. Almaghrabi, Saja M. Alhabardi, Adel A. Alrwisan

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Background: Hepatotoxicity is a major reason for medication withdrawal from the markets. Unfortunately, serious adverse hepatic effects can occur after marketing with limited indicators during clinical development. Therefore, finding possible predictors for hepatotoxicity might guide the monitoring program of various stakeholders. Methods: We examined the clinical review documents for drugs approved in the US from 2011 to 2016 to evaluate their hepatic safety profile. Predictors: we assessed whether these medications meet Hy’s Law with hepatotoxicity grade ≥ 3, labeled hepatic adverse effects at approval, or accelerated approval status. Outcome: post-marketing regulatory action related to hepatotoxicity, including product withdrawal or updates to warning, precaution, or adverse effects sections. Statistical analysis: drugs were included in the analysis from the time of approval until the end of 2019 or the first post-marketing regulatory action related to hepatotoxicity, whichever occurred first. The hazard ratio (HR) was estimated using Cox-regression analysis. Results: We included 192 medications in the study. We classified 48 drugs as having grade ≥ 3 hepatotoxicities, 43 had accelerated approval status, and 74 had labeled information about hepatotoxicity prior to marketing. The adjusted HRs for post-marketing regulatory action for products with grade ≥ 3 hepatotoxicity was 0.61 (95% confidence interval [CI], 0.17-2.23), 0.92 (95%CI, 0.29-2.93) for a drug approved via accelerated approval program, and was 0.91 (95%CI, 0.33-2.56) for drugs with labeled hepatotoxicity information at approval time. Conclusion: This study does not provide conclusive evidence on the association between post-marketing regulatory action and grade ≥ 3 hepatotoxicity, accelerated approval status, or availability of labeled information at approval due to sampling size and channeling bias.

Keywords: accelerated approvals, hepatic adverse effects, drug-induced liver injury, hepatotoxicity predictors, post-marketing withdrawal

Procedia PDF Downloads 139

Authors: Fasil Wagnew, Kerri Viney, Kefyalew Addis Alene, Matthew Kelly, Darren Gray

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Background: Undernutrition is a risk factor for tuberculosis (TB), including poor treatment outcomes. However, evidence regarding the effect of undernutrition on TB treatment outcomes is not well understood. We aimed to evaluate the effect of undernutrition on sputum culture conversion and treatment outcomes among people with multi-drug resistance (MDR)-TB. Methods: We searched for publications in the Medline, Embase, Scopus, and Web of Science databases without restrictions on geography or year of publication. We conducted a random-effect meta-analysis to estimate the effects of undernutrition on sputum culture conversion and treatment outcomes. Two reviewers independently assessed the study eligibility, extracted the necessary information, and assessed the risk of bias. Depending on the nature of the data, odds ratio (OR) and hazard ratio (HR) with 95% confidence intervals (CIs) were used to summarize the effect estimates. Potential publication bias was checked using funnel plots and Egger’s tests. Results: Of 2358 records screened, 59 studies comprising a total of 31,254 people with MDR-TB were included. Undernutrition was significantly associated with a lower sputum culture conversion rate (HR 0·7, 95% CI 0·6–0·9, I2=67·1%) and a higher rate of mortality (OR 2·9, 95%CI 2·1–3·8, I2=23·7%) and unfavourable treatment outcomes (OR 1·8, 95%CI 1·5–2·0, I2=72·7%). There was no statistically significant publication bias in the included studies. Three studies were low, forty-two studies were moderate, and fourteen studies were high quality. Interpretations: Undernutrition was significantly associated with unfavourable treatment outcomes, including mortality and lower sputum culture conversion among people with MDR-TB. These findings have implications for supporting targeted nutritional interventions alongside standardised second-line TB drugs.

Keywords: undernutrition, MDR-TB, sputum culture conversion, treatment outcomes, meta-analysis

Procedia PDF Downloads 132

Authors: Anjali Kanagali, Astha Sinha

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Climate change is the greatest threat being faced by mankind in the 21st century. It no longer is merely an environmental, scientific or economic issue but is a humanitarian issue as well. Paris Agreement put great pressure on the businesses to reduce carbon emissions and mitigate the impact of climate change. However, the already increased climate variability and extreme weather are aggravating emergency humanitarian needs. According to the Intergovernmental Panel on Climate Change (IPCC), if efficient policy changes are not made in time to combat the climate change issues, the situation will deteriorate with an estimated global temperature rise of 4 degrees. The existing international network of Humanitarian system is not adequately structured to handle the projected natural disasters and climate change crisis. The 2030 Agenda which embraces the 17 Sustainable Development Goals (SGDs) discussed the relationship between the climate change and humanitarian assistance. The Humanitarian law aims to protect, amongst other things, ‘internally displaced persons’ which includes people displaced due to natural hazard related disasters engulfing the hazards of climate change. ‘Legal protection’ of displaced people to protect their rights is becoming a pressing need in such times. In this paper, attempts will be made to analyze the causes of the displacement, identify areas where the effect of the climate change is most likely to occur and to examine the character of forced displacement triggering population movement. We shall discuss the pressure on the Humanitarian system and assistance due to climate change issues and the need for vesting powers to the local communities or local government players to deal with the climate changes. We shall also discuss the possibility of setting up a new framework where non-state actors could be set up for climate change impact and its governance.

Keywords: humanitarian assistance to climate change, humanitarian crisis, internally displaced person, legal framework for climate migrants, non-state actors

Procedia PDF Downloads 301

Authors: Raquel Amanda Villamizar Gallardo, Oscar Orlando Ortíz Rodríguez

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Enteric viruses are cosmopolitan agents present in several environments including water. These viruses can cause different diseases including gastroenteritis, hepatitis, conjunctivitis, respiratory problems among others. Although in Colombia there are not regulations concerning to routine viral analysis of drinking water, an enhanced understanding of viral pollution and resistance to treatments is desired in order to assure pure water to the population. Viral detection is often complex due to the need of specialized and time-consuming procedures. In addition, viruses are highly diluted in water which is a drawback from the analytical point of view. To this end, a fast and selective detection method for detection enteric viruses (i.e. Hepatitis A and Rotavirus) were applied. Micro- magnetic particles were functionalized with monoclonal antibodies anti-Hepatitis and anti-Rotavirus and they were used to capture, concentrate and separate whole viral particles in raw water and drinking water samples from four treatment plants identified as CAR-01, MON-02, POR-03, TON-04 and located in the Northeastern Colombia. Viruses were molecularly by using RT-PCR One Step Superscript III. Each plant was analyzed at the entry and exit points, in order to determine the initial presence and eventual reduction of Hepatitis A and Rotavirus after disinfection. The results revealed the presence of both enteric viruses in a 100 % of raw water analyzed in all plants. This represents a potential health hazard, especially for those people whose use this water for agricultural purposes. However, in drinking water analysis, enteric viruses was only positive in CAR-01, where was found the presence of Rotavirus. As a conclusion, the results confirm Rotavirus as the best indicator to evaluate the efficacy of potable treatment plant in eliminating viruses. CAR potable water plant should improve their disinfection process in order to remove efficiently enteric viruses.

Keywords: drinking water, hepatitis A, rotavirus, virus removal

Procedia PDF Downloads 207

Authors: Noah G. Akhimien, Eshrar Latif

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The natural environment is in need for an urgent rescue due to dilapidation and recession of resources. Passive design strategies have proven to be one of the effective ways to reduce CO₂ emissions and to improve building performance. On the other hand, there is a huge drop in material availability due to poor recycling culture. Consequently, building waste pose environmental hazard due to unrecycled building materials from construction and deconstruction. Buildings are seen to be material banks for a circular economy, therefore incorporating circular economy into passive housing will not only safe guide the climate but also improve resource efficiency. The study focuses on incorporating a circular economy in passive design strategies for an affordable energy and resource efficient residential building in Nigeria. Carbon dioxide (CO₂) concentration is still on the increase as buildings are responsible for a significant amount of this emission globally. Therefore, prompt measures need to be taken to combat the effect of global warming and associated threats. Nigeria is rapidly growing in human population, resources on the other hand have receded greatly, and there is an abrupt need for recycling even in the built environment. It is necessary that Nigeria responds to these challenges effectively and efficiently considering building resource and energy. Passive design strategies were assessed using simulations to obtain qualitative and quantitative data which were inferred to case studies as it relates to the Nigeria climate. Building materials were analysed using the ReSOLVE model in order to explore possible recycling phase. This provided relevant information and strategies to illustrate the possibility of circular economy in passive buildings. The study offers an alternative approach, as it is the general principle for the reworking of an economy on ecological lines in passive housing and by closing material loops in circular economy.

Keywords: building, circular, efficiency, environment, sustainability

Procedia PDF Downloads 235

Authors: Abdullahi Jibrin, Aishetu Abdulkadir

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The development of allometric models is crucial to accurate forest biomass/carbon stock assessment. The aim of this study was to develop a set of biomass prediction models that will enable the determination of total tree aboveground biomass for savannah woodland area in Niger State, Nigeria. Based on the data collected through biometric measurements of 1816 trees and destructive sampling of 36 trees, five species specific and one site specific models were developed. The sample size was distributed equally between the five most dominant species in the study site (Vitellaria paradoxa, Irvingia gabonensis, Parkia biglobosa, Anogeissus leiocarpus, Pterocarpus erinaceous). Firstly, the equations were developed for five individual species. Secondly these five species were mixed and were used to develop an allometric equation of mixed species. Overall, there was a strong positive relationship between total tree biomass and the stem diameter. The coefficient of determination (R2 values) ranging from 0.93 to 0.99 P < 0.001 were realised for the models; with considerable low standard error of the estimates (SEE) which confirms that the total tree above ground biomass has a significant relationship with the dbh. The F-test value for the biomass prediction models were also significant at p < 0.001 which indicates that the biomass prediction models are valid. This study recommends that for improved biomass estimates in the study site, the site specific biomass models should preferably be used instead of using generic models.

Keywords: allometriy, biomass, carbon stock , model, regression equation, woodland, inventory

Procedia PDF Downloads 430

Authors: K. Rumchev, S. Gilbey

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Airborne particulate matter is a known hazard to human health, with a considerable body of evidence linking agricultural dust exposures to adverse human health effects in exposed populations. It is also known that agricultural workers are exposed to high levels of soil dust and other types of airborne particulate matter within the farming environment. The aim of this study was to examine exposure to agricultural dust among farm workers during the seeding season. Twenty-one wheat-belt farms consented to participate in the study with 30 workers being monitored for dust exposure whilst seeding or undertaking seeding associated tasks. Each farm was visited once and farmers’ were asked to wear a personal air sampler for a 4-hour sampling period. Simultaneous, real-time, tractor cabin air quality monitoring was also undertaken. Data for this study was collected using real-time aerosol dust monitors to determine in-tractor cabin PM exposure to five size fractions (total, PM10, respirable, PM2.5 and PM1), and personal sampling was undertaken to establish individual exposure to inhalable and respirable dust concentrations. The study established a significant difference between personal exposures and simultaneous real-time in-cabin exposures for both inhalable and respirable fractions. No significant difference was shown between in-cabin and personal inhalable dust concentrations during seeding and spraying tasks, although both in-cabin and personal concentrations were two times greater for seeding than spraying. Future research should focus on educating and providing farm owners and workers with more information on adopting safe work practices to minimise harmful exposures to agricultural dust.

Keywords: agriculture, air quality, Australia, particulate matter

Procedia PDF Downloads 201

Authors: Levylee Bautista, Dawn Grace Santos, Aishwarya Veluchamy, Jesusa Santos, Ghafoor, Jr. I Haque, Rodolfo Rafael

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The booming interest in using natural compounds as an alternative to conventional medications has paved way to focus the attention on plants that provide rich sources of bioactive phytochemicals. For regulatory purposes, evaluation of the genotoxic effects of such alternatives is therefore empirical as part of the plant’s hazard assessment. Sesbania grandiflora is among the plants used as a traditional remedy in folk medicine and a subject of research for its medicinal benefits. This study aimed to evaluate the genotoxic potential induced by S. grandiflora flower methanol extract (SGFME) in terms of the frequency of micronucleus (MN) in polychromatic erythrocyte (PCE) (MNPCE) and PCE ratio employing the micronucleus assay. The frequency of MN was examined in bone marrow cells (BMCs) obtained from male Swiss albino mice exposed in vivo to four different concentrations (11.25, 22.5, 40, and 90 mg/kg) of SGFME and MMC (70 mg/kg; positive control) and sacrificed 24 hours post-intraperitoneal injection. Results showed a significant (p < 0.01) rate of MNPCEs for 11.25 and 22.5 tested concentrations of SGFME and is comparable with the MMC-treated mice. Although PCE ratio values in all doses of SGFME-treated mice were over 0.20, it is worth noting that 40 and 90 tested concentrations of SGFME-treated mice exhibited the lowest value, i.e., 0.22 and 0.28, respectively. The present study has demonstrated that S. grandiflora possesses genotoxic potential for murine BMCs. Such activity could be ascribed from the bioactive compounds present in S. grandiflora that require further isolation and characterization of the active molecules. Likewise, findings of this study warrant a caution of the use of S. grandiflora insomuch as further investigations do not demonstrate their safety.

Keywords: genotoxicity, micronucleus, phytochemicals, Sesbania grandiflora

Procedia PDF Downloads 122

Authors: Kanchan Mondal, Dasharath Koulage, Dattatray Manerikar, Asmita Ghate

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This paper presents an additive reliability model using warranty data and Finite Element Analysis (FEA) data. Warranty data for any product gives insight to its underlying issues. This is often used by Reliability Engineers to build prediction model to forecast failure rate of parts. But there is one major limitation in using warranty data for prediction. Warranty periods constitute only a small fraction of total lifetime of a product, most of the time it covers only the infant mortality and useful life zone of a bathtub curve. Predicting with warranty data alone in these cases is not generally provide results with desired accuracy. Failure rate of a mechanical part is driven by random issues initially and wear-out or usage related issues at later stages of the lifetime. For better predictability of failure rate, one need to explore the failure rate behavior at wear out zone of a bathtub curve. Due to cost and time constraints, it is not always possible to test samples till failure, but FEA-Fatigue analysis can provide the failure rate behavior of a part much beyond warranty period in a quicker time and at lesser cost. In this work, the authors proposed an Additive Weibull Model, which make use of both warranty and FEA fatigue analysis data for predicting failure rates. It involves modeling of two data sets of a part, one with existing warranty claims and other with fatigue life data. Hazard rate base Weibull estimation has been used for the modeling the warranty data whereas S-N curved based Weibull parameter estimation is used for FEA data. Two separate Weibull models’ parameters are estimated and combined to form the proposed Additive Weibull Model for prediction.

Keywords: bathtub curve, fatigue, FEA, reliability, warranty, Weibull

Procedia PDF Downloads 55