Search results for: waste classification

Authors: Wei Wen Yang, Emily Chia Yu Su

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Dengue fever is a mosquito-borne tropical infectious disease caused by the dengue virus. After infection, symptoms usually start from three to fourteen days. Dengue virus may cause a high fever and at least two of the following symptoms, severe headache, severe eye pain, joint pains, muscle or bone pain, vomiting, feature skin rash, and mild bleeding manifestation. In addition, recovery will take at least two to seven days. Dengue fever has rapidly spread in tropical and subtropical areas in recent years. Several phenomena around the world such as global warming, urbanization, and international travel are the main reasons in boosting the spread of dengue. In Taiwan, epidemics occur annually, especially during summer and fall seasons. On the other side, Singapore government also has announced the amounts number of dengue cases spreading in Singapore. As the serious epidemic of dengue fever outbreaks in Taiwan and Singapore, countries around the Asia-Pacific region are becoming high risks of susceptible to the outbreaks and local hub of spreading the virus. To improve public safety and public health issues, firstly, we are going to use Microsoft Excel and SAS EG to do data preprocessing. Secondly, using support vector machines and decision trees builds predict model, and analyzes the infectious cases between Taiwan and Singapore. By comparing different factors causing vector mosquito from model classification and regression, we can find similar spreading patterns where the disease occurred most frequently. The result can provide sufficient information to predict the future dengue infection outbreaks and control the diffusion of dengue fever among countries.

Keywords: dengue fever, Taiwan, Singapore, Aedes aegypti

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Authors: Shamsulhaq Amin

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Drought can arise from several hydrometeorological phenomena that result in insufficient precipitation, soil moisture, and surface and groundwater flow, leading to conditions that are considerably drier than the usual water content or availability. Drought is often assessed using indices that are associated with meteorological, agricultural, and hydrological phenomena. In order to effectively handle drought disasters, it is essential to accurately determine the kind, intensity, and extent of the drought using drought characterization. This information is critical for managing the drought before, during, and after the rehabilitation process. Over a hundred drought assessments have been created in literature to evaluate drought disasters, encompassing a range of factors and variables. Some models utilise solely hydrometeorological drivers, while others employ remote sensing technology, and some incorporate a combination of both. Comprehending the entire notion of drought and taking into account drought indices along with their calculation processes are crucial for researchers in this discipline. Examining several drought metrics in different studies requires additional time and concentration. Hence, it is crucial to conduct a thorough examination of approaches used in drought indices in order to identify the most straightforward approach to avoid any discrepancies in numerous scientific studies. In case of practical application in real-world, categorizing indices relative to their usage in meteorological, agricultural, and hydrological phenomena might help researchers maximize their efficiency. Users have the ability to explore different indexes at the same time, allowing them to compare the convenience of use and evaluate the benefits and drawbacks of each. Moreover, certain indices exhibit interdependence, which enhances comprehension of their connections and assists in making informed decisions about their suitability in various scenarios. This study provides a comprehensive assessment of various drought indices, analysing their types and computation methodologies in a detailed and systematic manner.

Keywords: drought classification, drought severity, drought indices, agricultur, hydrological

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Authors: Brindha Senthil Kumar, Payel Chakraborty, Senthil Kumar Nachimuthu, Arindam Maitra, Prem Nath

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Gastric cancer is predominantly caused by demographic and diet factors as compared to other cancer types. The aim of the study is to predict Early Gastric Cancer (ECG) from diet and lifestyle factors using supervised machine learning algorithms. For this study, 160 healthy individual and 80 cases were selected who had been followed for 3 years (2016-2019), at Civil Hospital, Aizawl, Mizoram. A dataset containing 11 features that are core risk factors for the gastric cancer were extracted. Supervised machine algorithms: Logistic Regression, Naive Bayes, Support Vector Machine (SVM), Multilayer perceptron, and Random Forest were used to analyze the dataset using Python Jupyter Notebook Version 3. The obtained classified results had been evaluated using metrics parameters: minimum_false_positives, brier_score, accuracy, precision, recall, F1_score, and Receiver Operating Characteristics (ROC) curve. Data analysis results showed Naive Bayes - 88, 0.11; Random Forest - 83, 0.16; SVM - 77, 0.22; Logistic Regression - 75, 0.25 and Multilayer perceptron - 72, 0.27 with respect to accuracy and brier_score in percent. Naive Bayes algorithm out performs with very low false positive rates as well as brier_score and good accuracy. Naive Bayes algorithm classification results in predicting ECG showed very satisfactory results using only diet cum lifestyle factors which will be very helpful for the physicians to educate the patients and public, thereby mortality of gastric cancer can be reduced/avoided with this knowledge mining work.

Keywords: Early Gastric cancer, Machine Learning, Diet, Lifestyle Characteristics

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Authors: Julius Ilawe Osayi, Peter Osifo

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Solid waste disposal, such as used tires is a global challenge as well as energy crisis due to rising energy demand amidst price uncertainty and depleting fossil fuel reserves. Therefore, the effectiveness of pyrolysis as a disposal method that can transform used tires into liquid fuel and other end-products has made the process attractive to researchers. Although used tires have been converted to liquid fuel using pyrolysis, there is the need to improve on the liquid fuel properties. Hence, this paper reports the investigation of zeolite NaY synthesized from kaolin, a locally abundant soil material in the Benin metropolis as a suitable catalyst and its effect on the properties of pyrolytic oil produced from used tires. The pyrolysis process was conducted for a range of 1 to 10 wt.% of catalyst concentration to used tire at a temperature of 600 oC, a heating rate of 15oC/min and particle size of 6mm. Although no significant increase in pyrolytic oil yield was observed compared to the previously investigated non-catalytic pyrolysis of a used tire. However, the Fourier transform infrared (FTIR), Nuclear Magnetic Resonance (NMR); and Gas chromatography-mass spectrometry (GC-MS) characterization results revealed the pyrolytic oil to possess an improved physicochemical and fuel properties alongside valuable industrial chemical species. This confirms the possibility of transforming kaolin into a catalyst suitable for improved fuel properties of the liquid fraction obtainable from thermal cracking of hydrocarbon materials.

Keywords: catalytic pyrolysis, fossil fuel, kaolin, pyrolytic oil, used tyres, Zeolite NaY

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Authors: E. Lacasa, J. L. Santolaya, I. Millán

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The progress toward sustainability implies maintaining and preferably improving both, human and ecosystem well-being, according to a triple bottom line that includes the environmental, economic and social dimensions. The life cycle assessment (LCA) is a method applicable to all production sectors that aims to quantify the environmental pressures and the benefits related to goods and services, as well as the trade-offs and the scope for improving areas of the production process. While using LCA to measure the environmental dimension of sustainability is widespread, similar approaches for the economic and the social dimensions still have limited application worldwide and there is a need for consistent and robust methods and indicators. This paper focuses on the milk production process and presents the analysis of the flows exchanged by an industrial installation through accounting all the energy and material inputs and the associated emissions and waste outputs at this stage of its life cycle. The functional unit is one litre of milk produced. Different metrics and indicators are used to assess the three dimensions of sustainability. Metrics considered useful to assess the production activities are the total water and energy consumptions and the milk production volume of each cow. The global warming, the value added and the working hours are indicators used to measure each sustainability dimension. The study is performed with two types of feeding of the cows, which includes a change in percentages of components as well. Nutritional composition of the milk obtained is almost kept. It is observed that environmental and social improvements involve high economic costs.

Keywords: milk production, sustainability, indicators, life cycle assessment

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Authors: Aldrin Avergas, Quennie Mariel Peñaranda, Niña Karen San Miguel, Alexis Katrina Agustin, Peralta Xusha Mae, Maria Luisa Sison

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The research is entitled “The Relationship of Socioeconomic Status and Levels of Delinquency among Senior High School Students with Secured Attachment to their Mothers”. The researchers had explored the relationship between socioeconomic status and delinquent tendencies among grade 11 students. The objective of the research is to discover if delinquent behavior will have a relationship with the current socio-economic status of an adolescent student having a warm relationship with their mothers. The researchers utilized three questionnaires that would measure the three variables of the study, namely: (1) 1SEC 2012: The New Philippines Socioeconomic Classification System was used to show the current socioeconomic status of the respondents, (2) Self-Reported Delinquency – Problem Behavior Frequency Scale was utilized to determine the individual's frequency in engaging to delinquent behavior, and (3) Inventory of Parent and Peer Attachment Revised (IPPA-R) was used to determine the attachment style of the respondents. The researchers utilized a quantitative research design, specifically correlation research. The study concluded that there is no significant relationship between socioeconomic status and academic delinquency despite the fact that these participants had secured attachment to their mother hence this research implies that delinquency is not just a problem for students belonging in the lower socio-economic status and that even having a warm and close relationship with their mothers is not sufficient enough for these students to completely be free from engaging in delinquent acts. There must be other factors (such as peer pressure, emotional quotient, self-esteem or etc.) that are might be contributing to delinquent behaviors.

Keywords: adolescents, delinquency, high school students, secured attachment style, socioeconomic status

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Authors: Dike Felix Okechukwu

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Studies and reports from authoritative sources such as the Intergovernmental Panel on Climate Change (IPCC) have stated that to effectively solve environmental sustainability challenges such as pollution, inappropriate waste disposal, and unsustainable consumption, there is a need for more research to seek solutions towards environmentally sustainable behavior. However, literature thus far reports only sporadic developments of TL in Environmental Sustainability because there are scarce reports showing the reliable process(es) to produce TL - for sustainability projects or otherwise. Nonetheless, a recently published article demonstrates how TL can be used to help young adults gain transformed mindsets and habits toward environmental sustainability behaviors and practices. This study, however, does not demonstrate, on a repeated basis, the dependability of the method or reliability of the procedures in using its proposed methodology to help young adults achieve transformed habits towards environmental sustainability behaviors, especially in diverse contexts. In this study, it is demonstrated, through repeated measures, a reliable process that can be used to achieve transformations in habits and mindsets toward environmental sustainability behaviors. To achieve this, the design adopted is multiple case studies and a thematic analysis techniques. Five cases in diverse contexts were used to analyze pieces of evidence of Transformative Learning Outcomes toward environmentally sustainable behaviors. Results from the study offer fresh perspectives on a reliable methodology that can be adopted to achieve Transformations in Habits and mindsets toward environmental sustainability behaviors.

Keywords: environmental sustainability, transformative learning, behaviour, learning, education

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Authors: Atour Taghipour

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In the real world each manufacturing company is an independent business unit. These business units are linked to each other through upstream and downstream linkages. The management of these linkages is called coordination which, could be considered as a difficult engineering task. The degree of difficulty of coordination depends on the type and the nature of information exchanged between partners as well as the structure of relationship from mutual to the network structure. The literature of manufacturing systems comprises a wide range of varieties of methods and approaches of coordination. In fact, two main streams of research can be distinguished: central coordination versus decentralized coordination. In the centralized systems a high degree of information exchanges is required. The high degree of information exchanges sometimes leads to difficulties when independent members do not want to share information. In order to address these difficulties, decentralized approaches of coordination of operations planning decisions based on some minimal information sharing have been proposed in many academic disciplines. This paper first proposes a framework of analysis in order to analyze the proposed approaches in the literature, based on this framework which includes the similarities between approaches we categorize the existing approaches. This classification can be used as a research map for future researches. The result of our paper highlights several opportunities for future research. First, it is proposed to develop more dynamic and stochastic mechanisms of planning coordination of manufacturing units. Second, in order to exploit the complementarities of approaches proposed by diverse science discipline, we propose to integrate the techniques of coordination. Finally, based on our approach we proposed to develop coordination standards to guaranty both the complementarity of these approaches as well as the freedom of companies to adopt any planning tools.

Keywords: network coordination, manufacturing, operations planning, supply chain

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Authors: Ethan James

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Over one billion people worldwide suffer from some level of vision loss or blindness as a result of progressive retinal diseases. Many patients, particularly in developing areas, are incorrectly diagnosed or undiagnosed whatsoever due to unconventional diagnostic tools and screening methods. Artificial intelligence (AI) based on deep learning (DL) convolutional neural networks (CNN) have recently gained a high interest in ophthalmology for its computer-imaging diagnosis, disease prognosis, and risk assessment. Optical coherence tomography (OCT) is a popular imaging technique used to capture high-resolution cross-sections of retinas. In ophthalmology, DL has been applied to fundus photographs, optical coherence tomography, and visual fields, achieving robust classification performance in the detection of various retinal diseases including macular degeneration, diabetic retinopathy, and retinitis pigmentosa. However, there is no complete diagnostic model to analyze these retinal images that provide a diagnostic accuracy above 90%. Thus, the purpose of this project was to develop an AI model that utilizes machine learning techniques to automatically diagnose specific retinal diseases from OCT scans. The algorithm consists of neural network architecture that was trained from a dataset of over 20,000 real-world OCT images to train the robust model to utilize residual neural networks with cyclic pooling. This DL model can ultimately aid ophthalmologists in diagnosing patients with these retinal diseases more quickly and more accurately, therefore facilitating earlier treatment, which results in improved post-treatment outcomes.

Keywords: artificial intelligence, deep learning, imaging, medical devices, ophthalmic devices, ophthalmology, retina

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Authors: Mohammad Saber Eslamlou

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Morphology of Islamic cities has been extensively studied by researchers of Islamic cities and different theories could be found about it. In this regard, there exist much difference in method of analysis, classification, recognition, confrontation and comparative method of urban morphology. The present paper aims to examine the previous methods, approaches and insights and that how Dr. Giulia Annalinda Neglia dealt with the analysis of morphology of Islamic cities. Neglia is assistant professor in University of Bari, Italy (UNIBA) who has published numerous papers and books on Islamic cities. I introduce her works in the field of morphology of Islamic cities. And then, her thoughts, insights and research methodologies are presented and analyzed in critical perspective. This is a qualitative research on her written works, which have been classified in three major categories. The first category consists mainly of her works on morphology and physical shape of Islamic cities. The results of her works’ review suggest that she has used Moratoria typology in investigating morphology of Islamic cities. Moreover, overall structure of the cities under investigation is often described linear; however, she’s against to define a single framework for the recognition of morphology in Islamic cities. She states that ‘to understand the physical complexity and irregularities in Islamic cities, it is necessary to study the urban fabric by typology method, focusing on transformation processes of the buildings’ form and their surrounding open spaces’ and she believes that fabric of each region in the city follows from the principles of an specific period or urban pattern, in particular, Hellenistic and Roman structures. Furthermore, she believes that it is impossible to understand the morphology of a city without taking into account the obvious and hidden developments associated with it, because form of building and their surrounding open spaces are written history of the city.

Keywords: city, Islamic city, Giulia Annalinda Neglia, morphology

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Authors: Javier Delgado-Gonzaga, Wilfrido Rivera, David Juárez-Romero

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Cooling and water purification are processes that have contributed to the economic and social development of the modern world. However, these processes require a significant amount of energy globally. Nowadays, absorption heat pumps have been studied with great interest since they are capable of producing cooling and/or purifying water from low-temperature energy sources such as industrial waste heat or renewable energy. In addition, absorption heat pumps require negligible amounts of electricity for their operation and generally use working fluids that do not represent a risk to the environment. The objective of this work is to evaluate a system that integrates an absorption heat transformer and an absorption cooling system to produce fresh water and cooling from a low-temperature heat source. Both cycles operate with the working pair LiBr-H2O. The integration is possible through the interaction of the LiBr-H2O solution streams between both cycles and also by recycling heat from the absorption heat transformer to the absorption cooling system. Mathematical models were developed to compare the performance of four different configurations. The results showed that the configuration in which the hottest streams of LiBr-H2O solution preheated the coldest streams in the economizers of both cycles was one that achieved the best performance. The interaction of the solution currents and the heat recycling analyzed in this work serves as a record of the possibilities of integration between absorption cycles for cogeneration.

Keywords: absorption heat transformer, absorption cooling system, water desalination, integrated system

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Authors: Qingsong Xiong, Cheng Yuan, Qingzhao Kong, Haibei Xiong

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Deep-learning-driven approaches based on vibration responses have attracted larger attention in rapid structural condition assessment while obtaining sufficient measured training data with corresponding labels is relevantly costly and even inaccessible in practical engineering. This study proposes an integrated label propagation network for structural condition assessment, which is able to diffuse the labels from continuously-generating measurements by intact structure to those of missing labels of damage scenarios. The integrated network is embedded with damage-sensitive features extraction by deep autoencoder and pseudo-labels propagation by optimized fuzzy clustering, the architecture and mechanism which are elaborated. With a sophisticated network design and specified strategies for improving performance, the present network achieves to extends the superiority of self-supervised representation learning, unsupervised fuzzy clustering and supervised classification algorithms into an integration aiming at assessing damage conditions. Both numerical simulations and full-scale laboratory shaking table tests of a two-story building structure were conducted to validate its capability of detecting post-earthquake damage. The identifying accuracy of a present network was 0.95 in numerical validations and an average 0.86 in laboratory case studies, respectively. It should be noted that the whole training procedure of all involved models in the network stringently doesn’t rely upon any labeled data of damage scenarios but only several samples of intact structure, which indicates a significant superiority in model adaptability and feasible applicability in practice.

Keywords: autoencoder, condition assessment, fuzzy clustering, label propagation

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Authors: Ayu Dwi Hardiyanti, Bernardus Anggit Winahyu, I. Gusti Agung Ayu Sugita Sari, Lestari Sutra Simamora, I. Wayan Warmada

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The Penosogan Formation sandstone, that has Middle Miosen age, has been deemed as a reservoir potential based on sample data from sandstone outcrop in Kebakalan and Kedawung villages, Karangsambung sub-district, Kebumen Regency, Central Java. This research employs the following analytical methods; petrography, X-ray diffraction (XRD), and porosity test. Based on the presence of micritic sandstone, muddy micrite, and muddy sandstone, the Penosogan Formation sandstone has a fine-coarse granular size and middle-to-fine sorting. The composition of the sandstone is mostly made up of plagioclase, skeletal grain, and traces of micrite. The percentage of clay minerals based on petrographic analysis is 10% and appears to envelop grain, resulting enveloping grain which reduces the porosity of rocks. The porosity types as follows: interparticle, vuggy, channel, and shelter, with an equant form of cement. Moreover, the diagenesis process involves compaction, cementation, authigenic mineral growth, and dissolving due to feldspar alteration. The maturity of the reservoir can be seen through the X-ray diffraction analysis results, using ethylene glycol solution for clay minerals fraction transformed from smectite–illite. Porosity test analysis showed that the Penosogan Formation sandstones has a porosity value of 22% based on the Koeseomadinata classification, 1980. That shows high maturity is very influential for the quality of reservoirs sandstone of the Penosogan Formation.

Keywords: sandstone reservoir, Penosogan Formation, smectite, XRD

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Authors: Abdul Walusansa

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The aim of this study was to assess the level of microbial pollution along Nakibiso stream. The study was carried out in polluted waters of Nakibiso stream, originating from Mbale municipality and running through ADRA Estates to Namatala Wetlands in Eastern Uganda. Four sites along the stream were selected basing on the activities of their vicinity. A total of 120 samples were collected in sterile bottles from the four sampling locations of the stream during the wet and dry seasons of the year 2011. The samples were taken to the National water and Sewerage Cooperation Laboratory for Analysis. Membrane filter technique was used to test for Erischerichia coli. Nitrogen, Phosphorus, pH, dissolved oxygen, electrical conductivity, total suspended solids, turbidity and temperature were also measured. Results for Nitrogen and Phosphorus for sites; 1, 2, 3 and 4 were 1.8, 8.8, 7.7 and 13.8 NH4-N mg/L; and 1.8, 2.1, 1.8 and 2.3 PO4-P mg/L respectively. Basing on these results, it was estimated that farmers use 115 and 24 Kg/acre of Nitrogen and Phosphorus respectively per month. Taking results for Nitrogen, the same amount of Nutrients in artificial fertilizers would cost $ 88. This shows that reuse of wastewater has a potential in terms of nutrients. The results for E. coli for sites 1, 2, 3 and 4 were 1.1 X 107, 9.1 X 105, 7.4 X 105, and 3.4 X 105 respectively. E. coli hence decreased downstream with statistically significant variations between sites 1 and 4. Site 1 had the highest mean E.coli counts. The bacterial contamination was significantly higher during the dry season when more water was needed for irrigation. Although the water had the potential for reuse in farming, bacterial contamination during both seasons was higher than 103 FC/100ml recommended by WHO for unrestricted Agriculture.

Keywords: E. coli, nitrogen, phosphorus, water reuse, waste water

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Authors: S. Abdi Goudazri, R. Ziaie Moayed, A. Nazeri

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Loose soils normally are of weak bearing capacity due to their structural nature. Being exposed to heavy traffic loads, they would fail in most cases. To tackle the aforementioned issue, geotechnical engineers have come up with different approaches; one of which is making use of geosynthetic-reinforced soil-aggregate systems. As these polymeric reinforcements have highlighted economic and environmentally-friendly features, they have become widespread in practice during the last decades. The present research investigates the efficiency of four different types of these reinforcements in increasing the bearing capacity of two-layered soil sections using a series California Bearing Ratio (CBR) test. The studied sections are comprised of a 10 cm-thick layer of no. 161 Firouzkooh sand (weak subgrade) and a 10 cm-thick layer of compacted aggregate materials (base course) classified as SP and GW according to the United Soil Classification System (USCS), respectively. The aggregate layer was compacted to the relative density (Dr) of 95% at the optimum water content (Wopt) of 6.5%. The applied reinforcements were including two kinds of geocomposites (type A and B), a geotextile, and a geogrid that were embedded at the interface of the lower and the upper layers of the soil-aggregate system. As the standard CBR mold was not appropriate in height for this study, the mold used for soaked CBR tests were utilized. To make a comparison between the results of stress-settlement behavior in the studied specimens, CBR values pertinent to the penetrations of 2.5 mm and 5 mm were considered. The obtained results demonstrated 21% and 24.5% increments in the amount of CBR value in the presence of geocomposite type A and geogrid, respectively. On the other hand, the effect of both geotextile and geocomposite type B on CBR values was generally insignificant in this research.

Keywords: geosynthetics, geogrid, geotextile, CBR test, increasing bearing capacity

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Authors: Parul Johri, Mala Trivedi

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Major Intrinsic proteins (MIPs), actively involved in the passive transport of small polar molecules across the membranes of almost all living organisms. MIPs that specifically transport water molecules are named aquaporins (AQPs). The permeability of membranes is actively controlled by the regulation of the amount of different MIPs present but also in some cases by phosphorylation and dephosphorylation of the channel. Based on sequence similarity, MIPs have been classified into many categories. All of the proteins are made up of the 20 amino acids, the only difference is there in their orientations. Again all the 20 amino acids are made up of the basic five elements namely: carbon, hydrogen, oxygen, sulphur and nitrogen. These elements are responsible for giving the amino acids the properties of hydrophilicity/hydrophobicity which play an important role in protein interactions. The hydrophobic amino acids characteristically have greater number of carbon atoms as carbon is the main element which contributes to hydrophobic interactions in proteins. It is observed that the carbon level of proteins in different species is different. In the present work, we have taken a sample set of 150 aquaporins proteins from Uniprot database and a dynamic programming code was written to calculate the carbon percentage for each sequence. This carbon percentage was further used to barcode the aqauporins of animals and plants. The protein taken from Oryza sativa, Zea mays and Arabidopsis thaliana preferred to have carbon percentage of 31.8 to 35, whereas on the other hand sequences taken from Mus musculus, Saccharomyces cerevisiae, Homo sapiens, Bos Taurus, and Rattus norvegicus preferred to have carbon percentage of 31 to 33.7. This clearly demarks the carbon range in the aquaporin proteins from plant and animal origin. Hence the atom level analysis of protein sequences can provide us with better results as compared to the residue level comparison.

Keywords: aquaporins, carbon, dynamic prgramming, MIPs

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Authors: Ahmed Negm, George Aggidis, Xiandong Ma

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With the diverse nature of urban cities, customer demand patterns, landscape topologies or even seasonal weather trends; managing our water distribution networks (WDNs) has proved a complex task. These unpredictable circumstances manifest as pipe failures, intermittent supply and burst events thus adding to water loss, energy waste and increased carbon emissions. Whilst these events are unavoidable, advanced pressure management has proved an effective tool to control and mitigate them. Henceforth, water utilities have struggled with developing a real-time control method that is resilient when confronting the challenges of water distribution. In this paper we use deep reinforcement learning (DRL) algorithms as a novel pressure control strategy to minimise pressure violations and leakage under both burst and background leakage conditions. Agents based on asynchronous actor critic (A2C) and recurrent proximal policy optimisation (Recurrent PPO) were trained and compared to benchmarked optimisation algorithms (differential evolution, particle swarm optimisation. A2C manages to minimise leakage by 32.48% under burst conditions and 67.17% under background conditions which was the highest performance in the DRL algorithms. A2C and Recurrent PPO performed well in comparison to the benchmarks with higher processing speed and lower computational effort.

Keywords: deep reinforcement learning, pressure management, water distribution networks, leakage management

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Authors: Şevket Evci, Mehmet Akif Karsli

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The aim of this study is to determine nutrient contents, in situ ruminal degradation kinetics and protein fractions of screenings bean (B), chick pea (ChP), red lentil (RL) and green lentil (GL) that is used as residue in grain legume packing industry. For this purpose, four samples of each legumes species-a total of 16 samples, collected from different parts of our country were utilized. Feedstuffs used in the experiment were incubated for 0, 2 4, 8, 12, 24, and 48 hours in the rumen of 3 ruminally cannulated Akkaraman rams as duplicate. The nutrient contents, in situ ruminal dry matter (DM), organic matter (OM) and crude protein (CP) degradabilities and fractions, and escape protein contents were evaluated. The highest OM and CP contents were observed in RL (P<0.05). Chick pea had the highest ether extract (EE) content and EE values were 3.47, 6.72, 2.26, 8.66 % for RL, B, GL and ChP, respectively (P<0.05). Crude fiber (CF), ADF, and NDF contents were the highest in RL and the lowest in ChP. CF values were 24.03, 10.80, 4.09 and 3.57 % for RL, GL, B and ChP (P<0.05). Acid detergent insoluble nitrogen content of samples did not differ. Escape protein content was the highest in RL and the lowest in B (P<0.05). After 48 h incubation, the lowest OM and CP degradabilities were observed in RL. While the highest OM degradability was seen in ChP the highest CP degradability was observed in B (P<0.05). The lowest water soluble OM and CP contents were observed in RL whereas the highest potentially degradable OM and CP contents were seen in B and ChP (P<0.05). Both rate of OM and CP degradations (k-1) did not differ among samples (P>0.05). In conclusion, it was noted that feedstuffs (GL, ChP and B) used in the experiment except RL had a greater ruminal degradibilities of both OM and CP and moreover, had a higher escape protein contents, except B. It was thought that these feedstuffs can be substituted with some of common protein sources used in animal nutrition.

Keywords: in situ, nutrient contents, ruminant, subsieve

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Authors: A. Sivakumar, S. S. Darun Prakash, P. Navaneethakrishnan

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In and around Erode District, it is estimated that more than 1250 chemical and allied textile processing fabric industries are affected, partially closed and shut off for various reasons such as poor management, poor supplier performance, lack of planning for productivity, fluctuation of output, poor investment, waste analysis, labor problems, capital/labor ratio, accumulation of stocks, poor maintenance of resources, deficiencies in the quality of fabric, low capacity utilization, age of plant and equipment, high investment and input but low throughput, poor research and development, lack of energy, workers’ fear of loss of jobs, work force mix and work ethic. The main objective of this work is to analyze the existing conditions in textile fabric sector, validate the break even of Total Productivity (TP), analyze, design and implement fuzzy sets and mathematical programming for improvement of productivity and quality dimensions in the fabric processing industry. It needs to be compatible with the reality of textile and fabric processing industries. The highly risk events from productivity and quality dimension were found by fuzzy systems and results are wrapped up among the textile fabric processing industry.

Keywords: break even point, fuzzy crisp data, fuzzy sets, productivity, productivity cycle, total productive maintenance

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Authors: S. A. H. Feghhi, Z. Gholamzadeh, Z. Alipoor, C. Tenreiro

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Currently, thorium fuel has been especially noticed because of its proliferation resistance than long half-life alpha emitter minor actinides, breeding capability in fast and thermal neutron flux and mono-isotopic naturally abundant. In recent years, efficiency of minor actinide burning up in PWRs has been investigated. Hence, a minor actinide-contained thorium based fuel matrix can confront both proliferation resistance and nuclear waste depletion aims. In the present work, minor actinide depletion rate in a CANDU-type nuclear core modeled using MCNP code has been investigated. The obtained effects of minor actinide load as mixture of thorium fuel matrix on the core neutronics has been studiedwith comparingpresence and non-presence of minor actinide component in the fuel matrix.Depletion rate of minor actinides in the MA-contained fuel has been calculated using different power loads.According to the obtained computational data, minor actinide loading in the modeled core results in more negative reactivity coefficients. The MA-contained fuel achieves less radial peaking factor in the modeled core. The obtained computational results showed 140 kg of 464 kg initial load of minor actinide has been depleted in during a 6-year burn up in 10 MW power.

Keywords: minor actinide burning, CANDU-type reactor, MCNPX code, neutronic parameters

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Authors: Magdalena Blachnio, Viktor Bogatyrov, Mariia Galaburda, Anna Derylo-Marczewska

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Agricultural waste materials from traditional oil mill and after extraction of natural raw materials in supercritical conditions were used for the preparation of carbon nanomaterials (activated carbons) by two various methods. Chemical activation using acetic acid and physical activation with a gaseous agent (carbon dioxide) were chosen as mild and environmentally friendly ones. The effect of influential factors: type of raw material, temperature and activation agent on the porous structure characteristics of the materials was discussed by using N₂ adsorption/desorption isotherms at 77 K. Furthermore scanning electron microscope (SEM), transmission electron microscope (TEM), X-ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS) were employed to examine the physicochemical properties of the obtained sorbents. Selection of a raw material and an optimization of the conditions of the synthesis process, allowed to obtain the cheap sorbents with a targeted distribution of pores enabling effective adsorption of the model organic pollutants carried out in the multicomponent systems. Adsorption behavior (capacity and rate) of the chosen activated carbons was estimated by utilizing Crystal violet (CV), 4-chlorophenoxyacetic acid (4-CPA), 2.4-dichlorophenoxyacetic acid (2.4-D) as the adsorbates. Both rate and adsorption capacity of the organics on the sorbents evidenced that the activated carbons could be effectively used in sewage treatment plants. The mechanisms of organics adsorption were studied and correlated with activated carbons properties.

Keywords: activated carbon, adsorption equilibrium, adsorption kinetics, organics adsorption

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Authors: Silvija Šiljeg, Ivan Marić, Ante Šiljeg

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The accessibility of urban green spaces (UGS) is an integral element in the quality of life. Due to rapid urbanization, UGS studies have become a key element in urban planning. The potential benefits of space for its inhabitants are frequently analysed. A functional transport network system and the optimal spatial distribution of urban green surfaces are the prerequisites for maintaining the environmental equilibrium of the urban landscape. An accessibility analysis was conducted as part of the Urban Green Belts Project (UGB). The development of a GIS database for Zadar was the first step in generating the UGS accessibility indicator. Data were collected using the supervised classification method of multispectral LANDSAT images and manual vectorization of digital orthophoto images (DOF). An analysis of UGS accessibility according to the ANGst standard was conducted in the first phase of research. The accessibility indicator was generated on the basis of seven objective measurements, which included average UGS surface per capita and accessibility according to six functional levels of green surfaces. The generated indicator was compared with subjective measurements obtained by conducting a survey (718 respondents) within statistical units. The collected data reflected individual assessments and subjective evaluations of UGS accessibility. This study highlighted the importance of using objective and subjective measures in the process of understanding the accessibility of urban green surfaces. It may be concluded that when evaluating UGS accessibility, residents emphasize the immediate residential environment, ignoring higher UGS functional levels. It was also concluded that large areas of UGS within a city do not necessarily generate similar satisfaction with accessibility. The heterogeneity of output results may serve as guidelines for the further development of a functional UGS city network.

Keywords: urban green spaces (UGS), accessibility indicator, subjective and objective measurements, Zadar

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Authors: K. P. Ganesh, T. Gomathi, L. Arul Pragasan

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Degradation of lake water quality is one of the serious environmental threats for the last few decades, particularly, the lakes situated in and around urban and industrial areas. The present study aimed to analyze the physicochemical and biological parameters, and metal elements to determine the water quality of Krishnampathi, Ukkadam, Kurichi, Sulur and Singanallur Lakes. Of the 23 physicochemical parameters analyzed in the five lakes, except TDS, Chloride and Total hardness values all the 20 parameters were found within the prescribed limit as recommended by World Health Organization (WHO) and Bureau of Indian Standards (BIS). In case of biological parameter, both Total Coliform and Fecal Coliform bacteria (Escherichia coli) were identified. This indicates the contamination of lakes by fecal matter, and warns of potential of disease causing by viruses, bacteria and other organisms. Among the twelve metal elements (Al, Cr, Mn, Fe, Ni, Cu, Zn, As, Se, Mo, Cd and Pb) determined by inductively coupled plasma-mass spectroscopy, except Cd (for all lakes), and Pb (for Ukkadam, Kurichi, Sulur & Singanallur), all the elements were found above the prescribed limits of BIS. The results of the present study revealed that all the five major lakes of Coimbatore were contaminated. It is recommended that proper implementation of the new wetland waste management system and monitoring of water quality be of the urgent need to sustain the water bodies for future generations.

Keywords: heavy metals, inductively coupled plasma-mass spectroscopy, physicochemical and biological parameters, water quality

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Authors: Morteza Haghi, Cigdem Yilmazbas, Ayse Zeynep Uysal, Melisa Tepedelen, Gozde Turkoz Bakirci

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Today, the increase in plastic waste accumulation is an inescapable consequence of environmental pollution; the disposal of these wastes has caused a significant problem. Variable methods have been utilized; however, biodegradation is the most environmentally friendly and low-cost method. Accordingly, the present study aimed to isolate the bacteria capable of biodegradation of plastics. In doing so, we applied the liquid carbon-free basal medium (LCFBM) prepared with deionized water for the isolation of bacterial species obtained from soil samples taken from the Izmir Menemen region. Isolates forming biofilms on plastic were selected and named (PLB3, PLF1, PLB1B) and subjected to a degradation test. FTIR analysis, 16s rDNA amplification, sequencing, identification of isolates were performed. Finally, at the end of the process, a mass loss of 16.6% in PLB3 isolate and 25% in PLF1 isolate was observed, while no mass loss was detected in PLB1B isolate. Only PLF1 and PLB1B created transparent zones on plastic texture. Considering the FTIR result, PLB3 changed plastic structure by 13.6% and PLF1 by 17%, while PLB1B did not change the plastic texture. According to the 16s rDNA sequence analysis, FLP1, PLB1B, and PLB3 isolates were identified as Streptomyces albogriseolus, Enterobacter cloacae, and Klebsiella pneumoniae, respectively.

Keywords: polyethylene, biodegradation, bacteria, 16s rDNA, FTIR

Procedia PDF Downloads 183

Authors: Li Chin Law, Epaminondas Mastorakos, Mohd Roslee Othman, Antonis Trakakis

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The paper introduces an alternative concept of carbon capture for shipping by using pre-combustion carbon capture technology (Pre-CCS), which was proven to be less energy intensive than post-combustion carbon capture from the engine exhaust. Energy assessment on amine-based post-combustion CCS on LNG-fuelled ships showed that the energy efficiency of CCS ships reduced from 48% to 36.6%. Then, an energy assessment was carried out to compare the power and heat requirements of the most used hydrogen production methods and carbon capture technologies. Steam methane reformer (SMR) was found to be 20% more energy efficient and achieved a higher methane conversion than auto thermal reaction and methane decomposition. Next, pressure swing adsorber (PSA) has shown a lower energy requirement than membrane separation, cryogenic separation, and amine absorption in pre-combustion carbon capture. Hence, an integrated system combining SMR and PSA (SMR-PSA) with waste heat integration (WHR) was proposed. This optimized SMR-based integrated system has achieved 65% of CO₂ reduction with less than 7-percentage point of energy penalty (41.7% of energy efficiency). Further integration of post-combustion CCS with the SMR-PSA integrated system improved carbon capture rate to 86.3% with 9-percentage points of energy penalty (39% energy efficiency). The proposed system was shown to be able to meet the carbon reduction targets set by International Maritime Organization (IMO) with certain energy penalties.

Keywords: shipping, decarbonisation, alternative fuels, low carbon, hydrogen, carbon capture

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Authors: A. Ribeiro, N. Pacheco, M. Soares, N. Valério, L. Nascimento, A. Silva, C. Vilarinho, J. Carvalho

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Hydrogen will play a key role in changing the current global energy paradigm, associated with the high use of fossil fuels and the release of greenhouse gases. This work intended to identify and quantify the potential of Solid Recovered Fuels (SFR) existing in Portugal and project the cost of hydrogen, produced through its steam gasification in different scenarios, associated with the size or capacity of the plant and the existence of carbon capture and storage (CCS) systems. Therefore, it was performed a techno-economic analysis simulation using an ASPEN base model, the H2A Hydrogen Production Model Version 3.2018. Regarding the production of SRF, it was possible to verify the annual production of more than 200 thousand tons of SRF in Portugal in 2019. The results of the techno-economic analysis simulations showed that in the scenarios containing a high (200,000 tons/year) and medium (40,000 tons/year) amount of SFR, the cost of hydrogen production was competitive concerning the current prices of hydrogen. The results indicate that scenarios 1 and 2, which use 200,000 tons of SRF per year, have lower hydrogen production values, 1.22 USD/kg H2 and 1.63 USD/kg H2, respectively. The cost of producing hydrogen without carbon capture and storage (CCS) systems in an average amount of SFR (40,000 tons/year) was 1.70 USD/kg H2. In turn, scenarios 5 (without CCS) and 6 (with CCS), which use only 683 tons of SFR from urban sources, have the highest costs, 6.54 USD/kg H2 and 908.97 USD/kg H2, respectively. Therefore, it was possible to conclude that there is a huge potential for the use of SRF for the production of hydrogen through steam gasification in Portugal.

Keywords: gasification, hydrogen, solid recovered fuels, techno-economic analysis, waste-to-energy

Procedia PDF Downloads 107

Authors: Opeyemi Atiba-Oyewo, Maurice S. Onyango, Christian Wolkersdorfer

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Characterization and nanostructure formation of banana peels as sorbent material are described in this paper. The transformation of this agricultural waste via mechanical milling to enhance its properties such as changed in microstructure and surface area for water pollution control and other applications were studied. Mechanical milling was employed using planetary continuous milling machine with ethanol as a milling solvent and the samples were taken at time intervals between 10 h to 30 h to examine the structural changes. The samples were characterised by X-ray diffraction (XRD), scanning electron microscopy (SEM), Fourier transform infra-red (FTIR), Transmission electron microscopy (TEM) and Brunauer Emmett and teller (BET). Results revealed three typical structures with different deformation mechanisms and the grain-sizes within the range of (71-12 nm), nanostructure of the particles and fibres. The particle size decreased from 65µm to 15 nm as the milling progressed for a period of 30 h. The morphological properties of the materials indicated that the particle shapes becomes regular and uniform as the milling progresses. Furthermore, particles fracturing resulted in surface area increment from 1.0694-4.5547 m2/g. The functional groups responsible for the banana peels capacity to coordinate and remove metal ions, such as the carboxylic and amine groups were identified at absorption bands of 1730 and 889 cm-1, respectively. However, the choice of this sorbent material for the sorption or any application will depend on the composition of the pollutant to be eradicated.

Keywords: characterization, nanostructure, nanosorbent, eco-friendly, banana peels, mechanical milling, water quality

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Authors: Abbas Ghahremani

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One of the most fundamental management issues in organizations and companies is the recruiting of efficient staff and compiling exact and perfect criteria for testing the applicants,which is guided and practiced by the manager of human resources of the organization. Obviously, each part of the organization seeks special features and abilities in the people apart from common features among all the staff in all units,which are called principal duties and abilities,and we will study them more. This article is trying to find out how we can identify the most efficient people among the applicants of employment by using proper methods of testing appropriate for the needs of different of employment by using proper methods of testing appropriate for the needs of different units of the organization and recruit efficient staff. Acceptable method for recruiting is to closely identify their characters from various aspects such as ability to communicate, flexibility, stress management, risk acceptance, tolerance, vision to future, familiarity with the art, amount of creativity and different thinking and by raising proper questions related with the above named features and presenting a questionnaire, evaluate them from various aspect in order to gain the proper result. According to the above explanations, it can be concluded which aspects of abilities and characteristics of a person must be evaluated in order to reduce any mistake in recruitment and approach an ideal result and ultimately gain an organized system according to the standards and avoid waste of energy for unprofessional personnel which is a marginal issue in the organizations.

Keywords: human resources management, staff recuiting, employment factors, efficient staff

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Authors: Vinay Kumar, M. Kishor, Sathyanarayana Rao Ts

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Background: Growth of elderly people in the general population in recent years is termed as ‘greying of the world’ where there is a shift from high mortality & fertility to low mortality and fertility, resulting in an increased proportion of older people as seen in India. Improved health care promises longevity but socio-economic factors like poverty, joint families and poor services pose a psychological threat. Epidemiological data regarding the prevalence of mental disorders in geriatric population with physical illness is required for proper health planning. Methods: Sixty consecutive elderly patients aged 60 years or above of both sexes, reporting with physical illness to general outpatient registration counter of JSS Medical College and Hospital, Mysore, India, were considered for the Study. With informed consent, they were screened with General Health Questionnaire (GHQ-12) and were further evaluated for diagnosing mental disorders according to WHO International Classification of Diseases (ICD-10) criteria. Results: Mental disorders were detected in 48.3%, predominantly depressive disorders, nicotine dependence, generalized anxiety disorder, alcohol dependence and least was dementia. Most common physical illness was cardiovascular disease followed by metabolic, respiratory and other diseases. Depressive disorders, substance dependence and dementia were more associated with cardiovascular disease compared to metabolic disease and respiratory diseases were more associated with nicotine dependence. Conclusions: Depression and Substance use disorders among elderly population is of concern, which needs to be further studied with larger population. Psychiatric morbidity will adversely have an impact on physical illness which needs proper assessment and management. This will enhance our understanding and prioritize our planning for future.

Keywords: Geriatric, mental disorders, physical illness, psychiatry

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Authors: Elina Brahma Hazarika, Jeuti Basumatary, Deepanka Saikia, Jaydeep Das, Micky Moni D'mary, Fungkha Basumatary

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This study includes development of two varieties of biscuits incorporated with: the seeds of Jack fruit (Artocarpus heterophyllus), which post-consumption of it’s pulp, is discarded as a waste, and Cassava (Manihot esculenta) tubers.The jack fruit seeds and cassava were first ground into flour and its proximate and physiochemical properties were studied. The biscuits that were developed incorporating them had 50% wheat flour and 50% jackfruit seed flour and 50% cassava flours as the major composition, apart from the other general ingredients use in making biscuits. Various trials of compositions were made for baking to get the overall desirable acceptability in biscuits through sensory evaluation. Finally, the best composition of ingredients was selected to make the biscuits, and hence studies were done accordingly to compare it with the properties of their respective raw flours. The results showed that the proximate composition of the biscuits fared better than that of their respective flours: There was a decrease in the Moisture content of both Jackfruit Seed Biscuits and Cassava Biscuits to 4.5% and 6.7% than that of their respective raw flours (8 and 12%). Post-baking, there is increase in the percentages of ash, protein, and fibre contents in both Jackfruit Seed Biscuits and Cassava Biscuits; the values being 3% and 3.8%, 13.2% and 3.3%, and 3.2 and 4.1% respectively. Also the total carbohydrate content in Jackfruit Seed Biscuits and Cassava Biscuits were 66.7% and 71.7% respectively. Their sensory evaluation and texture study also yielded a clear review that they have an overall good acceptability.

Keywords: baking, proximate, sensory, texture

Procedia PDF Downloads 300