Search results for: forest conservation

Authors: Maryam Zarabian, Hector Guzman, Pedro Pereira-Almao, Abraham Fapojuwo

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Dry reforming of methane (DRM) has sparked significant industrial and scientific interest not only as a viable alternative for addressing the environmental concerns of two main contributors of the greenhouse effect, i.e., carbon dioxide (CO₂) and methane (CH₄), but also produces syngas, i.e., a mixture of hydrogen (H₂) and carbon monoxide (CO) utilized by a wide range of downstream processes as a feedstock for other chemical productions. In this study, we develop an AI-enable syngas production model to tackle the problem of achieving an equivalent H₂/CO ratio [1:1] with respect to the most efficient conversion. Firstly, the unsupervised density-based spatial clustering of applications with noise (DBSAN) algorithm removes outlier data points from the original experimental dataset. Then, random forest (RF) and deep neural network (DNN) models employ the error-free dataset to predict the DRM results. DNN models inherently would not be able to obtain accurate predictions without a huge dataset. To cope with this limitation, we employ reusing pre-trained layers’ approaches such as transfer learning and greedy layer-wise pretraining. Compared to the other deep models (i.e., pure deep model and transferred deep model), the greedy layer-wise pre-trained deep model provides the most accurate prediction as well as similar accuracy to the RF model with R² values 1.00, 0.999, 0.999, 0.999, 0.999, and 0.999 for the total outlet flow, H₂/CO ratio, H₂ yield, CO yield, CH₄ conversion, and CO₂ conversion outputs, respectively.

Keywords: artificial intelligence, dry reforming of methane, artificial neural network, deep learning, machine learning, transfer learning, greedy layer-wise pretraining

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Authors: Oseni Taiwo Amoo, Bloodless Dzwairo

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In this paper, we extend the versatility and usefulness of GIS as a methodology for any river basin hydrologic characteristics analysis (HCA). The Gurara River basin located in North-Central Nigeria is presented in this study. It is an on-going research using spatial Digital Elevation Model (DEM) and Arc-Hydro tools to take inventory of the basin characteristics in order to predict water abstraction quantification on streamflow regime. One of the main concerns of hydrological modelling is the quantification of runoff from rainstorm events. In practice, the soil conservation service curve (SCS) method and the Conventional procedure called rational technique are still generally used these traditional hydrological lumped models convert statistical properties of rainfall in river basin to observed runoff and hydrograph. However, the models give little or no information about spatially dispersed information on rainfall and basin physical characteristics. Therefore, this paper synthesizes morphometric parameters in generating runoff. The expected results of the basin characteristics such as size, area, shape, slope of the watershed and stream distribution network analysis could be useful in estimating streamflow discharge. Water resources managers and irrigation farmers could utilize the tool for determining net return from available scarce water resources, where past data records are sparse for the aspect of land and climate.

Keywords: hydrological characteristic, stream flow, runoff discharge, land and climate

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Authors: Tahmidul Islam

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Propensity Score Matching (PSM) technique has been widely used for estimating causal effect of treatment in observational studies. One major step of implementing PSM is estimating the propensity score (PS). Logistic regression model with additive linear terms of covariates is most used technique in many studies. Logistics regression model is also used with cubic splines for retaining flexibility in the model. However, choosing the functional form of the logistic regression model has been a question since the effectiveness of PSM depends on how accurately the PS been estimated. In many situations, the linearity assumption of linear logistic regression may not hold and non-linear relation between the logit and the covariates may be appropriate. One can estimate PS using machine learning techniques such as random forest, neural network etc for more accuracy in non-linear situation. In this study, an attempt has been made to compare the efficacy of Generalized Additive Model (GAM) in various linear and non-linear settings and compare its performance with usual logistic regression. GAM is a non-parametric technique where functional form of the covariates can be unspecified and a flexible regression model can be fitted. In this study various simple and complex models have been considered for treatment under several situations (small/large sample, low/high number of treatment units) and examined which method leads to more covariate balance in the matched dataset. It is found that logistic regression model is impressively robust against inclusion quadratic and interaction terms and reduces mean difference in treatment and control set equally efficiently as GAM does. GAM provided no significantly better covariate balance than logistic regression in both simple and complex models. The analysis also suggests that larger proportion of controls than treatment units leads to better balance for both of the methods.

Keywords: accuracy, covariate balances, generalized additive model, logistic regression, non-linearity, propensity score matching

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Authors: T. Hadj Sadok, R. Hattab Bey, K. Rebiha

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The valuation of juice from prickly pear of Opuntia ficus indica inermis as cocktails appears an attractive alternative because of their nutritional intake and functional compound has anti-radical activity (polyphenols, vitamin C, carotenoids, Betalaines, fiber and minerals). The juice from the fruit pulp is characterized by a high pH 5.85 which makes it difficult for its conservation and preservation requires a thermal treatment at high temperatures (over 100 °C) harmful for bioactive constituents compared to juice orange more acidic and processed at temperatures < 100 °C. The valuation as fig cocktails-orange is particularly interesting thanks to the contribution of polyph2nols, fiber, vitamin C, reducing sugar (sweetener) and betalaine, minerals while allowing lower temperature processing to decrease pH. The heat treatment of these juices: orange alone or in cocktails showed that the antioxidant power decreases by 12% in presence of 30% of juice treated by the heat and of 28 and 32% in the presence of 10 and 20% juice which shows the effect prickly pear juice of Opuntia. During storage for 4 weeks the loss of vitamin C is 40 and 38% in the presence of 10 and 20% juice and 33% in the presence of 30% pear juice parallel, a treatment of stabilization by heat affects relatively the polyphenols rate which decreases from 10.5% to 30% in the cocktail, and 6.11-6.71pour cocktails at 10% and 20%. Vitamin C decreases to 12 to 24 % after a heat treatment at 85°C for 30 minutes respectively for the orange juice and pear juice; this reduction is higher when the juice is in the form of cocktails composed of 10 to 30 % pear juice.

Keywords: prickly pear juice, orange cocktail, polyphenol, Opuntia ficus indica, vitamin

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Authors: Lorenza Abbracciavento, Valerio De Biagi

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Infrastructures are key elements to ensure the operational functionality of the transport system. The collapse of a single bridge or, equivalently, a tunnel can leads an entire motorway to be considered completely inaccessible. As a consequence, the paralysis of the communications network determines several important drawbacks for the community. Recent chronicle events have demonstrated that ensuring the functional continuity of the strategic infrastructures during and after a catastrophic event makes a significant difference in terms of life and economical losses. Moreover, it has been observed that RC structures located in mountain environments show a worst state of conservation compared to the same typology and aging structures located in temperate climates. Because of its morphology, in fact, the mountain environment is particularly exposed to severe collapse and deterioration phenomena, generally: natural hazards, e.g. rock falls, and meteorological hazards, e.g. freeze-thaw cycles or heavy snows. For these reasons, deep investigation on the characteristics of these processes becomes of fundamental importance to provide smart and sustainable solutions and make the infrastructure system more resilient. In this paper, the design of a monitoring system in mountainous environments is presented and analyzed in its parts. The method not only takes into account the peculiar climatic conditions, but it is integrated and interacts with the environment surrounding.

Keywords: structural health monitoring, resilience of bridges, mountain infrastructures, infrastructural network, maintenance

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Authors: Diptimayee Nayak

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Ecotourism has been recognised as a popular component of alternative tourism, which claims to guard host local environment and economy. This concept of ecological tourism (eco-tourism) has become more meaningful in evaluating the recreational function and services of any pristine ecosystem in context of ‘The Economics of Ecosystem and Biodiversity (TEEB)’. This ecotourism is said to be a local solution to the global problem of conserving ecosystems and optimising the utilisations of their services. This paper takes a case of recreational services of an Indian protected area ecosystems ‘Bhitarakanika mangrove protected area’ discussing how ecotourism is functioning taking the perspectives of different stakeholders. Specific stakeholders are taken for analysis, viz., tourists and local people, as they are believed to be the major beneficiaries of ecotourism. The stakeholders’ analysis is evaluated on the basis of travel cost techniques (by using truncated Poisson distribution model) for tourists and descriptive and analytical tools for local people. The evaluation of stakeholders’ analysis of ecotourism has gained its impetus after the formulation of Ecotourism guidelines by the Ministry of Environment and Forest (MoEF), Government of India. The paper concludes that ecotourism issues and challenges are site-specific and region-specific; without critically focussing challenges of ecotourism faced at local level the discourses of ecotourism at global level cannot be tackled. Mere integration and replication of policies at global level to be followed at local level will not be successful (top down policies). Rather mainstreaming the decision making process at local level with the global policy stature helps to solve global issues to a bigger extent (bottom up).

Keywords: ecosystem services, ecotourism, TEEB, economic valuation, stakeholders, travel cost techniques

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Authors: Sandor Levai, Valentin Juhasz, Miklos Gasz

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Rising damp is an extremely complex phenomenon that is of great practical interest to the field of building conservation due to the irreversible damages it can make to old and historic structures. The electrical effects occurring in damp masonry have been scarcely researched and are a largely unknown aspect of rising damp. Present paper describes the typical electrical patterns occurring in porous brickwork during a wetting and drying cycle. It has been found that in contrast with dry masonry, where electrical phenomena are virtually non-existent, damp masonry exhibits a wide array of electrical effects. Long-term real-time measurements performed in the lab on small-scale brick structures, using an array of embedded micro-sensors, revealed significant voltage, current, capacitance and resistance variations which can be linked to the movement of moisture inside porous materials. The same measurements performed on actual old buildings revealed a similar behaviour, the electrical effects being more significant in areas of the brickwork affected by rising damp. Understanding these electrical phenomena contributes to a better understanding of the driving mechanisms of rising damp, potentially opening new avenues of dealing with it in a less invasive manner.

Keywords: brick masonry, electrical phenomena in damp brickwork, porous building materials, rising damp, spontaneous electrical potential, wetting-drying cycle

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Authors: Matthew Olanrewaju Ibiyomi

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The study examined the abundance of free-range natural inhabitants of the Federal University of Agriculture, Abeokuta (FUNAAB) Zoo Park. A baseline data of free-ranging inhabitants of the Park is essential to monitor trends and institute conservation plans through unsustainable natural resources exploitation and habitat destruction. Four transects were selected across the study area. Each transect was traversed for a period of four months and observations was carried out twice a day. The Four existing tracks explored during the study were the aviary, reptile, carnivore and primate tracks. Data were analyzed using descriptive statistics. The findings from this study revealed that 8 species of natural inhabitants were identified, which were the Vervet monkey (Chlorocebuspygerythrus), Maxwell duiker(Philantombamaxwellii), Mongoose (Herpestidaespp), Bushbuck(Tragelaphusscriptus), Cobra (Najanaja), Ground squirrel (Marmotinispp), Senegal coucal(Centropus senegalensis), Black kite (Milvus migrans). The result further showed that a total of 115 animals were encountered in the primate transect, 77 animals in the carnivores transect, 46 animals in the aviary transect and 34 animals in the ungulates transect by the representative of 43.3%, 28.3%, 15.8% and 12.5% respectively. Human activities and level of disturbance were observed to have affected the abundance and distribution of animals at Funaab Zoo Park. Continuous field inventory is recommended to ascertain the dynamics of animals observed as free-range inhabitants in this study.

Keywords: abundance, ecosystem, extinction, free-range

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Authors: Bahareh Asefi, Fereidoun Farzaneh, Ghazaleh Asefi

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Continuous increasing food waste produced on a global as well as national scale may lead to burgeoning environmental and economic problems. Simultaneously, decreasing the use efficiencies of natural resources such as land, water, and energy is occurring. On the other hand, food waste has a high-energy content, which seems ideal to achieve dual benefits in terms of energy recovery and the improvement of resource use efficiencies. Therefore, to decrease the environmental impacts of food waste and resource conservation, the researcher has focused on traditional methods of using food waste as a resource through different approaches such as anaerobic digestion, composting, incineration, and landfill. The adverse environmental effects of growing food waste make it difficult for traditional food waste treatment and management methods to balance social, economic, and environmental benefits. The old technology does not need to develop, but several new technologies such as microbial fuel cells, food waste disposal, and bio-converting food waste technology still need to establish or appropriately considered. It is pointed out that some new technologies can take into account various benefits. Since the information about food waste and its management method is critical for executable policy, a review of the latest information regarding the source of food waste and its management technology in some counties is provided in this study.

Keywords: food waste, management technology, innovative method, bio converting food waste, microbial fuel cell

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Authors: L. Almulla

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Native plants are better adapted to the local environment providing a more natural effect on landscape projects; their use will both conserve natural resources and produce sustainable greenery. Continuation of evaluation of additional native plants is essential to increase diversity of plant resources for greenery projects. Therefore, in this project an effort was made to study the mass multiplication of further native plants for greenery applications. Standardization of vegetative propagation methods is essential for conservation and sustainable utilization of native plants in restoration projects. Moreover, these simple propagation methods can be readily adapted by the local nursery sector in Kuwait. In the present study, various treatments were used to mass multiply selected plants using vegetative parts to secure maximum rooting and initial growth. Soft or semi-hardwood cuttings of selected native plants were collected from mother plants and subjected to different treatments. Pennisetum divisum can be vegetatively propagated by cuttings/off-shoots. However, Tamarix aucheriana showed maximum number of rooted cuttings and stronger vigor seedlings with the lowest growth hormone concentration. Standardizing the propagation techniques for the native plant species will add to the rehabilitation and landscape revegetation projects in Kuwait.

Keywords: Kuwait desert, landscape, rooting percentage, vegetative propagation

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Authors: Arun Jyothi Bheemagani, Chakrapani Pullagummi, Anupalli Roja Rani

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Exploration of the chemical constituents of the plants and pharmacological screening may provide us the basis for the development of novel agents. Plants have provided us some of the very important life saving drugs used in the modern medicine. The aim of our work was to screen the phytochemical constituents and antimicrobial and antioxidant activities of methanol extract of leaves of Annona cherimola Mill plant from Tirumala forest, Tirupathi. It was originally called Chirimuya by the Inca people who lived where it was growing in the Andes of South America, is an edible fruit-bearing species of the genus Annona from the family Annonaceae. Annona cherimola Mill is a multipurpose tree with edible fruits and is one of the sources of the medicinal products. The antibacterial activity was measured by agar well diffusion method; the diameter of the zone of bacterial growth inhibition was measured after incubation of plates. The inhibitory effect was studied against the pathogenic bacteria (Klebsiella pneumonia, Bacillus subtilis, Staphylococcus aureus and Escherichia coli (E. coli). Antioxidant assays were also performed for the same extracts by spectrophotometric methods using known standard antioxidants as reference. The studied plant extracts were found to be very effective against the pathogenic microorganisms tested. The methanolic extract of Annona cherimola Mill from showed maximum activity against Escherichia coli and Staphylococcus aureus and the least concentration required showing the activity was 0.5mg/ml. Phytochemical screening of the plants revealed the presence of flavonoids, alkaloids, steroids and carbohydrates. Good presence of antioxidants was also found in the methanolic extracts.

Keywords: annona cherimola, phytochemicals, antioxidant and antibacterial activity, methanol extract

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Authors: Suelane Garcia Fontes, Silvio Luiz Stanzani, Pedro L. Pizzigatti Corrła Ronaldo G. Morato

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Environmental changes and major natural disasters are most prevalent in the world due to the damage that humanity has caused to nature and these damages directly affect the lives of animals. Thus, the study of animal behavior and their interactions with the environment can provide knowledge that guides researchers and public agencies in preservation and conservation actions. Exploratory analysis of animal movement can determine the patterns of animal behavior and with technological advances the ability of animals to be tracked and, consequently, behavioral studies have been expanded. There is a lot of research on animal movement and behavior, but we note that a proposal that combines resources and allows for exploratory analysis of animal movement and provide statistical measures on individual animal behavior and its interaction with the environment is missing. The contribution of this paper is to present the framework AniMoveMineR, a unified solution that aggregates trajectory analysis and data mining techniques to explore animal movement data and provide a first step in responding questions about the animal individual behavior and their interactions with other animals over time and space. We evaluated the framework through the use of monitored jaguar data in the city of Miranda Pantanal, Brazil, in order to verify if the use of AniMoveMineR allows to identify the interaction level between these jaguars. The results were positive and provided indications about the individual behavior of jaguars and about which jaguars have the highest or lowest correlation.

Keywords: data mining, data science, trajectory, animal behavior

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Authors: Jeana Cadby, Kae Miyazawa

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With rapidly expanding worldwide adoption of mobile technologies, Information and Communication Technology (ITC) is a major energy user and a contributor to global carbon emissions, due to infrastructure and operational energy consumption. The agricultural sector is also significantly responsible for contributing to global carbon emissions. However, ICT cloud computing using mobile technology can directly reduce environmental impacts in the agricultural sector through applications and mobile connectivity, such as precision fertilizer and pesticide applications, or access to weather data, for example. While direct impacts are easily calculated, indirect environmental impacts from ICT cloud computing usage have not been thoroughly investigated. For example, while women may be more poorly equipped for adaptation to environmentally sustainable agricultural practices due to resource constraints, this research concludes that indirect environmental benefits can be achieved by improving rural access to mobile technology for women. Women in advanced roles and secure land tenure are more likely to invest in long-term agricultural conservation strategies, which protect against environmental degradation. This study examines how ICT using mobile technology advances the role of women in rural agricultural systems and indirectly reduces environmental impacts from agricultural production, through literature examination from secondary sources. Increasing access for women to ICT mobile technology provides indirect environmental and social benefits in the rural agricultural sector.

Keywords: cloud computing, environmental benefits, mobile technology, women

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Authors: Goodman Conrad Kazoroa

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Among the most remarkable socioeconomic phenomena of the post-World War II era has been the expansion of the global tourism industry. Intensifying tourism activity is continuing to affect more and more places and there can no longer be any doubt as to the potential of this sector to affect fundamental economic, social-cultural and environmental change. A phenomenon with far reaching effects like this needs to be carefully controlled and planned so as not to compromise the chances for the future generations to enjoy this resource, therefore the issue of tourism sustainability, as a result, is unveiled. The concept of sustainable tourism remains vague in Uganda as the country has seen an increase in resorts, hotels and lodges especially in most of Uganda’s ecologically vulnerable areas National Parks. To many, sustainable tourism it is merely the application of the sustainable development idea to the sector of tourism. To others, it is the conservation of the environment and its natural resources, realising and appropriately using them to achieve sustainable built environments that promote tourism. Architecture and the built environment can be the first means to link the global dimension of this phenomenon of sustainable tourism to its local implications. The aim of this paper was to critically analyse the extent to which sustainability related considerations have been pursued in the built environments for Uganda’s national parks as means to achieving sustainable tourism. This was achieved by use of a sustainable architecture rating tool that was modified to fit Uganda’s context. The results of this are presented as the final results of the study. There are many examples of sustainable tourism resorts, or what tourism managers and developers claim are sustainable tourism resorts throughout the country. This paper reveals the truth, that is, true sustainable tourism resorts are very few and far between.

Keywords: sustainable tourism, tourism architecture, sustainable architecture, sustainable tourism resorts

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Authors: Megan Alkazoff, Charles Ruffner

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Tallgrass prairies and sand savannas, once covering northern to central Illinois, are ecosystems in need of restoration and conservation in the Midwestern United States. The Nature Conservancy manages five sites containing fragments of remaining tallgrass prairies and sand savannas within the Kankakee Sands using techniques such as prescribed burning and invasive species removal. The objective of this study was to conduct a ten-year resampling of transects established on these five sites during previous studies to assess whether the management tools applied there are helping maintain the tallgrass prairie and sand savannas. During the summer of 2020, permanent transect lines were sampled using a quadrat to determine the % Cover Class of each species rooted in the quadrat. Data gathered was analyzed using linear regression to illustrate the relationship between fire occurrence and species composition on the landscape. The fire frequency had a highly significant effect (P= 0.0025) on the species richness of all sites. The frequency of fire had a non-significant effect (P>0.05) on the Floristic Quality Index, percent C value 4-10, and bare-ground percentage of a site. These results suggest that fire on the landscape, both wild and prescribed, have increased biodiversity on all five sites but has not affected the Floristic Quality Index, percent C value 4-10, and the percentage of bare-ground on the sites.

Keywords: fire, floristic quality assessment, sand savanna, species richness, tallgrass prairie

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Authors: Sahil Patel

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Increasing urbanization leads to a concrete forest. The effects of new development practices occur in the natural hydrologic cycle. Here the concerns have been raised about the groundwater recharge in sufficient quantity. With further development, porous surfaces reduce rapidly. A city like Ahmedabad, with a non-perennial river, is 100% dependent on groundwater. The Ahmedabad city receives its domestic use water from the Narmada river, located about 200 km away. The expenses to bring water is much higher. Ahmedabad city receives annually 800 mm rainfall, and mostly this water increases the local level waterlogging problems; after that, water goes to the Sabarmati river and merges into the sea. The existing developed area of Ahmedabad city is very dense, and does not offer many chances to change the built form and increase porous surfaces to absorb storm-water. Therefore, there is a need to plan upcoming areas with more effective solutions to manage storm-water. This paper is focusing on the management of stormwater for new development by retaining natural hydrology. The Low Impact Development (LID) concept is used to manage storm-water efficiently. Ahmedabad city has a tool called the “Town Planning Scheme,” which helps the local body drive new development by land pooling mechanism. This paper gives a detailed analysis of the selected area (proposed Town Planning Scheme area by the local authority) in Ahmedabad. Here the development control regulations for individual developers and some physical elements for public places are presented to manage storm-water. There is a different solution for the Town Planning scheme than that of the conventional way. A local authority can use it for any area, but it can be site-specific. In the end, there are benefits to locals with some financial analysis and comparisons.

Keywords: water management, green field development, low impact development, town planning scheme

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Authors: S. Begum, T. Biswas, M. A. Islam

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The present research investigates the distribution and contamination of heavy metals in core sediments collected from three locations of the Sundarbans mangrove forest. In this research, quality of the analysis is evaluated by analyzing certified reference materials IAEA-SL-1 (lake sediment), IAEA-Soil-7, and NIST-1633b (coal fly ash). Total concentrations of 28 heavy metals (Na, Al, K, Ca, Sc, Ti, V, Cr, Mn, Fe, Co, Zn, Ga, As, Sb, Cs, La, Ce, Sm, Eu, Tb, Dy, Ho, Yb, Hf, Ta, Th, and U) have determined in core sediments of the Sundarbans mangrove by neutron activation analysis (NAA) technique. When compared with upper continental crustal (UCC) values, it is observed that mean concentrations of K, Ti, Zn, Cs, La, Ce, Sm, Hf, and Th show elevated values in the research area is high. In this research, the assessments of metal contamination levels using different environmental contamination indices (EF, Igeo, CF) indicate that Ti, Sb, Cs, REEs, and Th have minor enrichment of the sediments of the Sundarbans. The modified degree of contamination (mCd) of studied samples of the Sundarbans ecosystem show low contamination. The pollution load index (PLI) values for the cores suggested that sampling points are moderately polluted. The possible sources of the deterioration of the sediment quality can be attributed to the different chemical carrying cargo accidents, port activities, ship breaking, agricultural and aquaculture run-off of the area. Pearson correlation matrix (PCM) established relationships among elements. The PCM indicates that most of the metal's distributions have been controlled by the same factors such as Fe-oxy-hydroxides and clay minerals, and also they have a similar origin. The poor correlations of Ca with most of the elements in the sediment cores indicate that calcium carbonate has a less significant role in this mangrove sediment. Finally, the data from this research will be used as a benchmark for future research and help to quantify levels of metal pollutions, as well as to manage future ecological risks of the vulnerable mangrove ecosystem, the Sundarbans.

Keywords: contamination, core sediment, trace element, sundarbans, vulnerable

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Authors: Nico Rosamilia

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The study evaluates the importance of non-financial disclosure practices for regulators, investors, businesses, and markets. It aims to create a sector-specific set of indicators for environmental, social, and governance (ESG) performances alternative to the ratings of the agencies. The existing literature extensively studies the implementation of ESG rating systems. Conversely, this study has a twofold outcome. Firstly, it should generalize incentive systems and governance policies for ESG and sustainable principles. Therefore, it should contribute to the EU Sustainable Finance Disclosure Regulation. Secondly, it concerns the market and the investors by highlighting successful sustainable investing. Indeed, the study contemplates the effect of ESG adoption practices on corporate value. The research explores the asset pricing angle in order to shed light on the fragmented argument on the finance of ESG. Investors may be misguided about the positive or negative effects of ESG on performances. The paper proposes a different method to evaluate ESG performances. By comparing the results of a traditional econometric approach (Lasso) with a machine learning algorithm (Random Forest), the study establishes a set of indicators for ESG performance. Therefore, the research also empirically contributes to the theoretical strands of literature regarding model selection and variable importance in a finance framework. The algorithms will spit out sector-specific indicators. This set of indicators defines an alternative to the compounded scores of ESG rating agencies and avoids the possible offsetting effect of scores. With this approach, the paper defines a sector-specific set of indicators to standardize ESG disclosure. Additionally, it tries to shed light on the absence of a clear understanding of the direction of the ESG effect on corporate value (the problem of endogeneity).

Keywords: ESG ratings, non-financial information, value of firms, sustainable finance

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Authors: F. O. Danquah, F. Frimpong, E. Owusu Danquah, T. Frimpong, J. Adu, S. K. Amposah, P. Amankwaa-Yeboah, N. E. Amengor

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In the face of global concerns such as population increase, climate change, and limited natural resources, sustainable agriculture practices are critical for ensuring food security and environmental stewardship. The study was conducted in the Forest zones of Ghana during the major and minor seasons of 2023 cropping seasons to evaluate maize yield productivity improvement and profitability of integrating Cajanus cajan (pigeonpea) into a maize production system described as a pigeonpea-maize cropping system. This is towards an integrated soil fertility management (ISFM) with a legume shrub pigeonpea for sustainable maize production while improving smallholder farmers' resilience to climate change. A split-plot design with maize-pigeonpea (Pigeonpea-Maize intercrop – MPP and No pigeonpea/ Sole maize – NPP) and inorganic fertilizer rate (250 kg/ha of 15-15-15 N-P2O5-K2O + 250 kg/ha Sulphate of Ammonia (SoA) – Full rate (FR), 125 kg/ha of 15-15-15 N-P2O5-K2O + 125 kg/ha Sulphate of Ammonia (SoA) – Half rate (HR) and no inorganic fertilizer (NF) as control) was used as the main plot and subplot treatments respectively. The results indicated a significant interaction of the pigeonpea-maize cropping system and inorganic fertilizer rate on the growth and yield of the maize with better and similar maize productivity when HR and FR were used with pigeonpea biomass. Thus, the integration of pigeonpea and its biomass would result in the reduction of recommended fertiliser rate to half. This would improve farmers’ income and profitability for sustainable maize production in the face of climate change.

Keywords: agroforestry tree, climate change, integrated soil fertility management, resource use efficiency

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Authors: Li Hoon Lim, Nur Farhanah Said, Katie Simmons, Eric Pei Ping Pang, Sharon Mei Mei Wong

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Background and Purpose: Research regarding the sexual impact of breast cancer treatment on Asian women is both sensitive and scarce. This study aims to assess and evaluate the sexual health needs and concerns of breast cancer radiotherapy patients. It is hoped that awareness will be increased and an appropriate intervention can be developed to address the needs of future breast cancer patients. Methods: 110 consecutive unselected breast cancer patients were recruited prospectively. Questionnaires were administered once for patient undergoing radiotherapy to the breast. This study employed an anonymous questionnaire; any breast radiotherapy patient who can read English can voluntarily receive and complete the survey. The questionnaire consisted of items addressing demographics, potential informational needs, and educational preferences. Results: Patients’ interest to address sexual concerns decreases with age (p=0.024). Coherently, sexual concerns of patients are reported to decrease with age (p=0.015) where 70% of all respondents below age 50 [age 20-29 (60%); 30-39 (56.3%); 40-49(55.1%)] have started to have sexual concerns regarding their treatment effects on their sexual health. Patients who underwent breast conservation surgery (42.2%) and reconstruction surgery (83.3%) were more likely to have concerns about sexual health versus patients who underwent mastectomy (36.7%) (p=0.032). 74.2% of patients with sexual concern regardless of age would initiate conversation with their healthcare providers (p < 0.001). Conclusions: The results showed a staggering interest of female patients wanting information on this area which would not only boost their confidence and body image but also address concerns of the effect of breast radiotherapy on sexual health during their treatment.

Keywords: breast cancer, breast radiotherapy, sexual health, sexual impact

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Authors: Davit Shahnazaryan, Diogo Gomes, Mher Safaryan

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Many symbolic computations and manipulations required in the analysis of partial differential equations (PDE) or systems of PDEs are tedious and error-prone. These computations arise when determining conservation laws, entropies or integral identities, which are essential tools for the study of PDEs. Here, we discuss a new Mathematica package for the symbolic analysis of PDEs that automate multiple tasks, saving time and effort. Methodologies: During the research, we have used concepts of linear algebra and partial differential equations. We have been working on creating algorithms based on theoretical mathematics to find results mentioned below. Major Findings: Our package provides the following functionalities; finding symmetry group of different PDE systems, generation of polynomials invariant with respect to different symmetry groups; simplification of integral quantities by integration by parts and null Lagrangian cleaning, computing general forms of expressions by integration by parts; finding equivalent forms of an integral expression that are simpler or more symmetric form; determining necessary and sufficient conditions on the coefficients for the positivity of a given symbolic expression. Conclusion: Using this package, we can simplify integral identities, find conserved and dissipated quantities of time-dependent PDE or system of PDEs. Some examples in the theory of mean-field games and semiconductor equations are discussed.

Keywords: partial differential equations, symbolic computation, conserved and dissipated quantities, mathematica

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Authors: Ajai Singh

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Simulation of hydrological processes at the watershed outlet through modelling approach is essential for proper planning and implementation of appropriate soil conservation measures in Damodar Barakar catchment, Hazaribagh, India where soil erosion is a dominant problem. This study quantifies the parametric uncertainty involved in simulation of stream flow using Soil and Water Assessment Tool (SWAT), a watershed scale model and Radial Basis Neural Network (RBNN), an artificial neural network model. Both the models were calibrated and validated based on measured stream flow and quantification of the uncertainty in SWAT model output was assessed using ‘‘Sequential Uncertainty Fitting Algorithm’’ (SUFI-2). Though both the model predicted satisfactorily, but RBNN model performed better than SWAT with R2 and NSE values of 0.92 and 0.92 during training, and 0.71 and 0.70 during validation period, respectively. Comparison of the results of the two models also indicates a wider prediction interval for the results of the SWAT model. The values of P-factor related to each model shows that the percentage of observed stream flow values bracketed by the 95PPU in the RBNN model as 91% is higher than the P-factor in SWAT as 87%. In other words the RBNN model estimates the stream flow values more accurately and with less uncertainty. It could be stated that RBNN model based on simple input could be used for estimation of monthly stream flow, missing data, and testing the accuracy and performance of other models.

Keywords: SWAT, RBNN, SUFI 2, bootstrap technique, stream flow, simulation

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Authors: Işılay Tiarnagh Sheridan

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World EXPO, short version for the “exposition”, is a large universal public exhibition held since 1851. Within the 164 years, it was organized 34 times in 22 cities and as a result it has given birth to its very own culture unlike most of other international events. It has an outstanding power in transforming the places, in which it is held, into trademarks via changes in their urban tissues. For that, it is widely remembered with its cities instead of its countries. Within the scope of this change, some constructions were planned to be temporary, some planned to be permanent and some were thought to be temporary but kept afterwards becoming important monuments such as the Crystal Palace of London (though it was destroyed later by a fire) and the Eiffel Tower of Paris. These examples are the most prominent names upon considering World EXPOs. Yet, there are so many other legacies of these events within modern city fabric today that we don’t usually associate with its Expo history. Some of them are leading figures not only for the housing city but for other cities also, such as the first Metro line of Paris during 1900 World EXPO; some of them are listed as monuments of the cities such as Saint Louis Art Museum of 1904 World EXPO; some of them, like Melbourne Royal Exhibition Building of 1880 World’s EXPO, are among UNESCO World Heritage Sites and some of them are the masterpieces of modern architecture such as the famous Barcelona Pavilion, German pavilion of the 1929 World’s EXPO, of Ludwig Mies van der Rohe. Thus, the aim of this paper is to analyze the history of World’s EXPO and its eventual results in the birth of its own cultural heritage. Upon organizing these results, the paper aims to create a brief list of EXPO heritage monuments and sites so as to form a database for their further conservation needs.

Keywords: expo, heritage, world's fair, legacy

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Authors: Syed Asif Hassan, Syed Atif Hassan

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Multidrug-resistant Tuberculosis (MDR-TB) is an infection caused by the resistant strains of Mycobacterium tuberculosis that do not respond either to isoniazid or rifampicin, which are the most important anti-TB drugs. The increase in the occurrence of a drug-resistance strain of MTB calls for an intensive search of novel target-based therapeutics. In this context LprG (Rv1411c) a lipoprotein from MTB plays a pivotal role in the immune evasion of Mtb leading to survival and propagation of the bacterium within the host cell. Therefore, a machine learning method will be developed for generating a computational model that could predict for a potential anti LprG activity of the novel antituberculosis compound. The present study will utilize dataset from PubChem database maintained by National Center for Biotechnology Information (NCBI). The dataset involves compounds screened against MTB were categorized as active and inactive based upon PubChem activity score. PowerMV, a molecular descriptor generator, and visualization tool will be used to generate the 2D molecular descriptors for the actives and inactive compounds present in the dataset. The 2D molecular descriptors generated from PowerMV will be used as features. We feed these features into three different classifiers, namely, random forest, a deep neural network, and a recurring neural network, to build separate predictive models and choosing the best performing model based on the accuracy of predicting novel antituberculosis compound with an anti LprG activity. Additionally, the efficacy of predicted active compounds will be screened using SMARTS filter to choose molecule with drug-like features.

Keywords: antituberculosis drug, classifier, machine learning, molecular descriptors, prediction

Procedia PDF Downloads 387

Authors: Hakim Bachiri, Mohammed Znari, Moulay Abdeljalil Ait Baamranne

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Population characteristics of Atlas Barbary sheep (Ammotragus lervia lervia) were investigated 20 years following the 1999 introduction of 10 individuals into the fenced nature reserve of Amassine, High Atlas range, Morocco, for promoting wildlife watching and tourism. Population age-sex structure and density were determined in late winter-early spring during four consecutive years (2016-2019) by direct observation before the dispersal of the herd. In this latter case, the line transect distance sampling was successfully applied. Population size increased from 37 to 62 animals during the four-year study period; the maximal population size being 82 individuals recorded in 2006. An estimated population density ranged from 0.25 to 0.41 Barbary sheep/ha during the study period. The adult sex ratio varied from 91 to 67 per 100 females. The apparent birth rate was 14 to 73/100 females. Juveniles and subadults comprised 27-43% of the population, adult males 26-31% and adult females 29-45%. The survival rate from birth to 1 year of age approximated 35%, for adult males was estimated to average 69%/year. The obtained results would be helpful for developing sustainable population management and habitat restoration plan and assessing the feasibility of potential reintroduction/restocking in other areas of the Atlas range.

Keywords: atlas mountains, barbary sheep, demography, management

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Authors: Hongmei Gu, Shaobo Liang, Richard Bergman

Abstract:

With current worldwide trend in designs to have net-zero emission buildings to mitigate climate change, widespread use of mass timber products, such as Cross Laminated Timber (CLT), or Nail Laminated Timber (NLT) or Dowel Laminated Timber (DLT) in buildings have been proposed as one approach in reducing Greenhouse Gas (GHG) emissions. Consequentially, mass timber building designs are being adopted more and more by architectures in North America, especially for mid- to high-rise buildings where concrete and steel buildings are currently prevalent, but traditional light-frame wood buildings are not. Wood buildings and their associated wood products have tended to have lower environmental impacts than competing energy-intensive materials. It is common practice to conduct life cycle assessments (LCAs) and life cycle cost analyses on buildings with traditional structural materials like concrete and steel in the building design process. Mass timber buildings with lower environmental impacts, especially GHG emissions, can contribute to the Net Zero-emission goal for the world-building sector. However, the economic impacts from CLT mass timber buildings still vary from the life-cycle cost perspective and environmental trade-offs associated with GHG emissions. This paper quantified the Total Life Cycle Cost and cradle-to-grave GHG emissions of a pre-designed CLT mass timber building and compared it to a functionally-equivalent concrete building. The Total life cycle Eco-cost-efficiency is defined in this study and calculated to discuss the trade-offs for the net-zero emission buildings in a holistic view for both environmental and economic impacts. Mass timber used in buildings for the United States is targeted to the materials from the nation’s sustainable managed forest in order to benefit both national and global environments and economies.

Keywords: GHG, economic impact, eco-cost-efficiency, total life-cycle costs

Procedia PDF Downloads 132

Authors: Maria Luiza D. Ramiento, Maria Lissette D. Lucas

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Electricity is said to serve as the backbone of modern technology. Considering this, electricity consumption has dynamically grown due to the continuous demand. An alternative producer of energy concerning electricity must therefore be given focus. Microbial fuel cell wholly characterizes a new method of renewable energy recovery: the direct conversion of organic matter to electricity using bacteria. Electricity is produced as fuel or new food is given to the bacteria. The study concentrated in determining the feasibility of electricity production from local benthic zones. Microbial fuel cells were constructed to harvest the possible electricity and to test the presence of electricity producing microorganisms. Soil samples were gathered from Calumpang River, Palawan Mangrove Forest, Rosario River and Batangas Port. Eleven modules were constructed for the different trials of the soil samples. These modules were made of cathode and anode chambers connected by a salt bridge. For 85 days, the harvested voltage was measured daily. No parameter is added for the first 24 days. For the next 61 days, acetic acid was included in the first and second trials of the modules. Each of the trials of the soil samples gave a positive result in electricity production.There were electricity producing microbes in local benthic zones. It is observed that the higher the organic content of the soil sample, the higher the electricity harvested from it. It is recommended to identify the specific species of the electricity-producing microorganism present in the local benthic zone. Complement experiments are encouraged like determining the kind of soil particles to test its effect on the amount electricity that can be harvested. To pursue the development of microbial fuel cells by building a closed circuit in it is also suggested.

Keywords: microbial fuel cell, benthic zone, electricity, reduction-oxidation reaction, bacteria

Procedia PDF Downloads 393

Authors: Bhenjamin Jordan L. Ona

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Weather modification is an act of altering weather systems that catches interest on scientific studies. Cloud seeding is a common form of weather alteration. On the same principle, tropical cyclone mitigation experiment follows the methods of cloud seeding with intensity to account for. This study will present the effects of aerosol to tropical cyclone cloud microphysics and intensity. The framework of Weather Research and Forecasting (WRF) model incorporated with Thompson aerosol-aware scheme is the prime host to support the aerosol-cloud microphysics calculations of cloud condensation nuclei (CCN) ingested into the tropical cyclones before making landfall over the Philippine coast. The coupled microphysical and radiative effects of aerosols will be analyzed using numerical data conditions of Tropical Storm Ketsana (2009), Tropical Storm Washi (2011), and Typhoon Haiyan (2013) associated with varying CCN number concentrations per simulation per typhoon: clean maritime, polluted, and very polluted having 300 cm-3, 1000 cm-3, and 2000 cm-3 aerosol number initial concentrations, respectively. Aerosol species like sulphates, sea salts, black carbon, and organic carbon will be used as cloud nuclei and mineral dust as ice nuclei (IN). To make the study as realistic as possible, investigation during the biomass burning due to forest fire in Indonesia starting October 2015 as Typhoons Mujigae/Kabayan and Koppu/Lando had been seeded with aerosol emissions mainly comprises with black carbon and organic carbon, will be considered. Emission data that will be used is from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS). The physical mechanism/s of intensification or deintensification of tropical cyclones will be determined after the seeding experiment analyses.

Keywords: aerosol, CCN, IN, tropical cylone

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Authors: M. S. Wickramarachchi, L. S. Nawarathna, C. M. B. Dematawewa

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Hatchery performance is critical for the profitability of poultry breeder operations. Some extrinsic parameters of eggs and breeders cause to increase or decrease the hatchability. This study aims to identify the affecting extrinsic parameters on the commercial hatchability of local chicken's eggs and determine the most efficient classification model with a hatchability rate greater than 90%. In this study, seven extrinsic parameters were considered: egg weight, moisture loss, breeders age, number of fertilised eggs, shell width, shell length, and shell thickness. Multiple linear regression was performed to determine the most influencing variable on hatchability. First, the correlation between each parameter and hatchability were checked. Then a multiple regression model was developed, and the accuracy of the fitted model was evaluated. Linear Discriminant Analysis (LDA), Classification and Regression Trees (CART), k-Nearest Neighbors (kNN), Support Vector Machines (SVM) with a linear kernel, and Random Forest (RF) algorithms were applied to classify the hatchability. This grouping process was conducted using binary classification techniques. Hatchability was negatively correlated with egg weight, breeders' age, shell width, shell length, and positive correlations were identified with moisture loss, number of fertilised eggs, and shell thickness. Multiple linear regression models were more accurate than single linear models regarding the highest coefficient of determination (R²) with 94% and minimum AIC and BIC values. According to the classification results, RF, CART, and kNN had performed the highest accuracy values 0.99, 0.975, and 0.972, respectively, for the commercial hatchery process. Therefore, the RF is the most appropriate machine learning algorithm for classifying the breeder outcomes, which are economically profitable or not, in a commercial hatchery.

Keywords: classification models, egg weight, fertilised eggs, multiple linear regression

Procedia PDF Downloads 84

Authors: Kaiwen Zheng, Wanting Zhou, Nan Tang, Lei Li, Yuanhang He

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The integrated circuit industry has become a cornerstone of the information society, finding widespread application in areas such as industry, communication, medicine, and aerospace. However, with the increasing complexity of integrated circuits, Hardware Trojans (HTs) implanted by attackers have become a significant threat to their security. In this paper, we proposed a hardware trojan detection method for large-scale circuits. As HTs introduce physical characteristic changes such as structure, area, and power consumption as additional redundant circuits, we proposed a machine-learning-based hardware trojan detection method based on the physical characteristics of gate-level netlists. This method transforms the hardware trojan detection problem into a machine-learning binary classification problem based on physical characteristics, greatly improving detection speed. To address the problem of imbalanced data, where the number of pure circuit samples is far less than that of HTs circuit samples, we used the SMOTETomek algorithm to expand the dataset and further improve the performance of the classifier. We used three machine learning algorithms, K-Nearest Neighbors, Random Forest, and Support Vector Machine, to train and validate benchmark circuits on Trust-Hub, and all achieved good results. In our case studies based on AES encryption circuits provided by trust-hub, the test results showed the effectiveness of the proposed method. To further validate the method’s effectiveness for detecting variant HTs, we designed variant HTs using open-source HTs. The proposed method can guarantee robust detection accuracy in the millisecond level detection time for IC, and FPGA design flows and has good detection performance for library variant HTs.

Keywords: hardware trojans, physical properties, machine learning, hardware security

Procedia PDF Downloads 143