Search results for: allele mining

Authors: Olaniyi Awe, Adelana R. Adetunji, Abraham Adeleke

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Field observation revealed a lot of artisanal gold mining activities in Ilesa gold belt of southwestern Nigeria. The possibility of alluvial and lode gold deposits in commercial quantities around this location is very high, as there are many resident artisanal gold miners who have been mining and trading alluvial gold ore for decades and to date in the area. Their major process of solid gold recovery from its ore is by gravity concentration using the convectional panning method. This method is simple to learn and fast to recover gold from its alluvial ore, but its effectiveness is based on rules of thumb and the artisanal miners' experience in handling gold ore panning tool while processing the ore. Research samples from five alluvial gold ore tailings dumps were collected and studied. Samples were subjected to particle size analysis and mineralogical and elemental characterization using X-Ray Diffraction (XRD) and Particle-Induced X-ray Emission (PIXE) methods, respectively. The results showed that the tailings were of major quartz in association with albite, plagioclase, mica, gold, calcite and sulphide minerals. The elemental composition analysis revealed a 15ppm of gold concentration in particle size fraction of -90 microns in one of the tailings dumps investigated. These results are significant. It is recommended that heaps of panning tailings should be further reprocessed using other gold recovery methods such as shaking tables, flotation and controlled cyanidation that can efficiently recover fine gold particles that were previously lost into the gold panning tailings. The tailings site should also be well controlled and monitored so that these heavy minerals do not find their way into surrounding water streams and rivers, thereby causing health hazards.

Keywords: gold ore, panning, PIXE, tailings, XRD

Procedia PDF Downloads 90

Authors: Wei-Chih Huang, Pei-Lung Chung, Ching-Heng Lin, Hsuan-Chia Yang, Der-Ming Liou

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Background: In-Hospital Cardiac Arrest (IHCA) threaten life of the inpatients, cause serious effect to patient safety, quality of inpatients care and hospital service. Health providers must identify the signs of IHCA early to avoid the occurrence of IHCA. This study will consider the potential association between early signs of IHCA and the essence of patient care provided by nurses and other professionals before an IHCA occurs. The aim of this study is to identify significant associations between nursing interventions and abnormal early evaluation results of IHCA that can assist health care providers in monitoring inpatients at risk of IHCA to increase opportunities of IHCA early detection and prevention. Materials and Methods: This study used one of the data mining techniques called association rules mining to compute associations between nursing interventions and abnormal early evaluation results of IHCA. The nursing interventions and abnormal early evaluation results of IHCA were considered to be co-occurring if nursing interventions were provided within 24 hours of last being observed in abnormal early evaluation results of IHCA. The rule based methods were utilized 23.6 million electronic medical records (EMR) from a medical center in Taipei, Taiwan. This dataset includes 733 concepts of nursing interventions that coded by clinical care classification (CCC) codes and 13 early evaluation results of IHCA with binary codes. The values of interestingness and lift were computed as Q values to measure the co-occurrence and associations’ strength between all in-hospital patient care measures and abnormal early evaluation results of IHCA. The associations were evaluated by comparing the results of Q values and verified by medical experts. Results and Conclusions: The results show that there are 4195 pairs of associations between nursing interventions and abnormal early evaluation results of IHCA with their Q values. The indication of positive association is 203 pairs with Q values greater than 5. Inpatients with high blood sugar level (hyperglycemia) have positive association with having heart rate lower than 50 beats per minute or higher than 120 beats per minute, Q value is 6.636. Inpatients with temporary pacemaker (TPM) have significant association with high risk of IHCA, Q value is 47.403. There is significant positive correlation between inpatients with hypovolemia and happened abnormal heart rhythms (arrhythmias), Q value is 127.49. The results of this study can help to prevent IHCA from occurring by making health care providers early recognition of inpatients at risk of IHCA, assist with monitoring patients for providing quality of care to patients, improve IHCA surveillance and quality of in-hospital care.

Keywords: in-hospital cardiac arrest, patient safety, nursing intervention, association rule mining

Procedia PDF Downloads 271

Authors: Ami Fadhillah Amir Abdul Nasir, Amanda C. Niehaus, Skye F. Cameron, Frank A. Von Hippel, John Postlethwait​, Robbie S. Wilson

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For suicidal breeders, the physiological stresses and energetic costs of breeding are fatal. Environmental stressors such as pollution should compound these costs, yet suicidal breeding is so rare among mammals that this is unknown. Here, we explored the consequences of metal contamination to the health, aging and performance of endangered, suicidally-breeding northern quolls (Dasyurus hallucatus) living near an active manganese mine on Groote Eylandt, Northern Territory, Australia. We found respirable manganese dust at levels exceeding international recommendations even 20km from mining sites and substantial accumulation of manganese within quolls’ hair, testes, and in two brain regions—the neocortex and cerebellum, responsible for sensory perception and motor function, respectively. Though quolls did not differ in sprint speeds, motor skill, or manoeuvrability, those with higher accumulation of manganese crashed at lower speeds during manoeuvrability tests, indicating a potential effect on sight or cognition. Immune function and telomere length declined over the breeding season, as expected with ageing, but manganese contamination exacerbated immune declines and suppressed cortisol. Unexpectedly, male quolls with higher levels of manganese had longer telomeres, supporting evidence of unusual telomere dynamics among Dasyurids—though whether this affects their lifespan is unknown. We posit that sublethal contamination via pollution, mining, or urbanisation imposes physiological costs on wildlife that may diminish reproductive success or survival.

Keywords: ecotoxicology, heavy metal, manganese, telomere length, cortisol, locomotor

Procedia PDF Downloads 317

Authors: Roman Graf, Sergiu Gordea, Heather M. Ryan

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This paper presents an approach for easy creation and classification of institutional risk profiles supporting endangerment analysis of file formats. The main contribution of this work is the employment of data mining techniques to support set up of the most important risk factors. Subsequently, risk profiles employ risk factors classifier and associated configurations to support digital preservation experts with a semi-automatic estimation of endangerment group for file format risk profiles. Our goal is to make use of an expert knowledge base, accuired through a digital preservation survey in order to detect preservation risks for a particular institution. Another contribution is support for visualisation of risk factors for a requried dimension for analysis. Using the naive Bayes method, the decision support system recommends to an expert the matching risk profile group for the previously selected institutional risk profile. The proposed methods improve the visibility of risk factor values and the quality of a digital preservation process. The presented approach is designed to facilitate decision making for the preservation of digital content in libraries and archives using domain expert knowledge and values of file format risk profiles. To facilitate decision-making, the aggregated information about the risk factors is presented as a multidimensional vector. The goal is to visualise particular dimensions of this vector for analysis by an expert and to define its profile group. The sample risk profile calculation and the visualisation of some risk factor dimensions is presented in the evaluation section.

Keywords: linked open data, information integration, digital libraries, data mining

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Authors: A. Anastasiou, K. S. Tingay

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Background: Discovering suitable datasets is an important part of health research, particularly for projects working with clinical data from patients organized in cohorts (cohort data), but with the proliferation of so many national and international initiatives, it is becoming increasingly difficult for research teams to locate real world datasets that are most relevant to their project objectives. We present a method for identifying healthcare institutes in the European Union (EU) which may hold haemato-oncology (HO) data. A key enabler of this research was the bibInsight platform, a scientometric data management and analysis system developed by the authors at Swansea University. Method: A PubMed search was conducted using HO clinical terms taken from previous work. The resulting XML file was processed using the bibInsight platform, linking affiliations to the Global Research Identifier Database (GRID). GRID is an international, standardized list of institutions, including the city and country in which the institution exists, as well as a category of the main business type, e.g., Academic, Healthcare, Government, Company. Countries were limited to the 28 current EU members, and institute type to 'Healthcare'. An article was considered valid if at least one author was affiliated with an EU-based healthcare institute. Results: The PubMed search produced 21,310 articles, consisting of 9,885 distinct affiliations with correspondence in GRID. Of these articles, 760 were from EU countries, and 390 of these were healthcare institutes. One affiliation was excluded as being a veterinary hospital. Two EU countries did not have any publications in our analysis dataset. The results were analysed by country and by individual healthcare institute. Networks both within the EU and internationally show institutional collaborations, which may suggest a willingness to share data for research purposes. Geographical mapping can ensure that data has broad population coverage. Collaborations with industry or government may exclude healthcare institutes that may have embargos or additional costs associated with data access. Conclusions: Data reuse is becoming increasingly important both for ensuring the validity of results, and economy of available resources. The ability to identify potential, specific data sources from over twenty thousand articles in less than an hour could assist in improving knowledge of, and access to, data sources. As our method has not yet specified if these healthcare institutes are holding data, or merely publishing on that topic, future work will involve text mining of data-specific concordant terms to identify numbers of participants, demographics, study methodologies, and sub-topics of interest.

Keywords: data reuse, data discovery, data linkage, journal articles, text mining

Procedia PDF Downloads 115

Authors: Remy Mpulumba Badiambile, Paul Musa Obadia, Malick Useni Mutayo, Jeef Numbi Mukanya, Patient Nkulu Banza, Tony Kayembe Kitenge, Erik Smolders, Jean-François Picron, Vincent Haufroid, Célestin Banza Lubaba Nkulu, Benoit Nemery

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Background: In July 2021, the Tshikapa river became heavily polluted by mining wastes from a diamond mine in neighboring Angola, leading to massive killing of fish, as well as disease and even deaths among residents living along the Tshikapa and Kasai rivers, a major contributory of the Congo river. The exact nature of the pollutants was unknown. Methods: In a cross-sectional study conducted in the city of Tshikapa in August 2021, we enrolled by opportunistic sampling 65 residents (11 children < 16y) living alongside the polluted rivers and 65 control residents (5 children) living alongside a non-affected portion of the Kasai river (upstream from the Tshikapa-Kasai confluence). We administered a questionnaire and obtained spot urine samples for measurements of thiocyanate (a metabolite of cyanide) and 26 trace metals (by ICP-MS). Metals (and pH) were also measured in samples of river water. Results: Participants from both groups consumed river water. In the area affected by the pollution, most participants had eaten dead fish. Prevalences of reported health symptoms were higher in the exposed group than among controls: skin rashes (52% vs 0%), diarrhea (40% vs 8%), abdominal pain (8% vs 3%), nausea (3% vs 0%). In polluted water, concentrations [median (range)] were only higher for nickel [(2.2(1.4–3.5)µg/L] and uranium [78(71–91)ng/L] than in non-polluted water [0.8(0.6–1.9)µg/L; 9(7–19)ng/L]. In urine, concentrations [µg/g creatinine, median(IQR)] were significantly higher in the exposed group than in controls for lithium [19.5(12.4–27.3) vs 6.9(5.9–12.1)], thallium [0.41(0.31–0.57) vs 0.19(0.16–0.39)], and uranium [0.026(0.013–0.037)] vs 0.012(0.006–0.024)]. Other elements did not differ between the groups, but levels were higher than reference values for several metals (including manganese, cobalt, nickel, and lead). Urinary thiocyanate concentrations did not differ. Conclusion: This study, after an ecological disaster in the DRC, has documented contamination of river water by nickel and uranium and high urinary levels of some trace metals among affected riverine populations. However, the exact cause of the massive fish kill and disease among residents remains elusive. The capacity to rapidly investigate toxic pollution events must be increased in the area.

Keywords: metal contaminants, river water and human urine, pollution by mining wastes, DR Congo

Procedia PDF Downloads 157

Authors: Fabiana Franceschi, Martha Cobo, Manuel Figueredo

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Bogotá, the capital of Colombia, is its largest city and one of the most polluted in Latin America due to the fast economic growth over the last ten years. Bogotá has been affected by high pollution events which led to the high concentration of PM10 and NO2, exceeding the local 24-hour legal limits (100 and 150 g/m3 each). The most important pollutants in the city are PM10 and PM2.5 (which are associated with respiratory and cardiovascular problems) and it is known that their concentrations in the atmosphere depend on the local meteorological factors. Therefore, it is necessary to establish a relationship between the meteorological variables and the concentrations of the atmospheric pollutants such as PM10, PM2.5, CO, SO2, NO2 and O3. This study aims to determine the interrelations between meteorological variables and air pollutants in Bogotá, using data mining techniques. Data from 13 monitoring stations were collected from the Bogotá Air Quality Monitoring Network within the period 2010-2015. The Principal Component Analysis (PCA) algorithm was applied to obtain primary relations between all the parameters, and afterwards, the K-means clustering technique was implemented to corroborate those relations found previously and to find patterns in the data. PCA was also used on a per shift basis (morning, afternoon, night and early morning) to validate possible variation of the previous trends and a per year basis to verify that the identified trends have remained throughout the study time. Results demonstrated that wind speed, wind direction, temperature, and NO2 are the most influencing factors on PM10 concentrations. Furthermore, it was confirmed that high humidity episodes increased PM2,5 levels. It was also found that there are direct proportional relationships between O3 levels and wind speed and radiation, while there is an inverse relationship between O3 levels and humidity. Concentrations of SO2 increases with the presence of PM10 and decreases with the wind speed and wind direction. They proved as well that there is a decreasing trend of pollutant concentrations over the last five years. Also, in rainy periods (March-June and September-December) some trends regarding precipitations were stronger. Results obtained with K-means demonstrated that it was possible to find patterns on the data, and they also showed similar conditions and data distribution among Carvajal, Tunal and Puente Aranda stations, and also between Parque Simon Bolivar and las Ferias. It was verified that the aforementioned trends prevailed during the study period by applying the same technique per year. It was concluded that PCA algorithm is useful to establish preliminary relationships among variables, and K-means clustering to find patterns in the data and understanding its distribution. The discovery of patterns in the data allows using these clusters as an input to an Artificial Neural Network prediction model.

Keywords: air pollution, air quality modelling, data mining, particulate matter

Procedia PDF Downloads 258

Authors: Rusudan Chagelishvili, Nino Sulava, Tamar Beridze, Nana Rezesidze, Nikoloz Tatuashvili

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The South Caucasus is one of the most important centers of prehistoric metallurgy, known for its Colchian bronze culture. Modern Lechkhumi – historical Mountainous Colchis where the existence of prehistoric metallurgy is confirmed by the discovery of many artifacts is a part of this area. Studies focused on prehistoric smelting sites, related artefacts, and ore deposits have been conducted during last ten years in Lechkhumi. More than 20 prehistoric smelting sites and artefacts associated with metallurgical activities (ore roasting furnaces, slags, crucible, and tuyères fragments) have been identified so far. Within the framework of integrated studies was established that these sites were operating in 13-9 centuries B.C. and used for copper smelting. Palynological studies of slags revealed that chestnut (Castanea sativa) and hornbeam (Carpinus sp.) wood were used as smelting fuel. Geological exploration-analytical studies revealed that copper ore mining, processing, and smelting sites were distributed close to each other. Despite recent complex data, the signs of prehistoric mines (trenches) haven’t been found in this part of the study area so far. Since 2018 the archaeological-geological exploration has been focused on the southern part of Lechkhumi and covered the areas of villages Okureshi and Opitara. Several copper smelting sites (Okureshi 1 and 2, Opitara 1), as well as a Colchian Bronze culture settlement, have been identified here. Three mine workings have been found in the narrow gorge of the river Rtkhmelebisgele in the vicinities of the village Opitara. In order to establish a link between the Opitara-Okureshi archaeometallurgical sites, Late Bronze Age settlements, and mines, various scientific analytical methods -mineralized rock and slags petrography and atomic absorption spectrophotometry (AAS) analysis have been applied. The careful examination of Opitara mine workings revealed that there is a striking difference between the mine #1 on the right bank of the river and mines #2 and #3 on the left bank. The first one has all characteristic features of the Soviet period mine working (e. g. high portal with angular ribs and roof showing signs of blasting). In contrast, mines #2 and #3, which are located very close to each other, have round-shaped portals/entrances, low roofs, and fairly smooth ribs and are filled with thick layers of river sediments and collapsed weathered rock mass. A thorough review of the publications related to prehistoric mine workings revealed some striking similarities between mines #2 and #3 with their worldwide analogues. Apparently, the ore extraction from these mines was conducted by fire-setting applying primitive tools. It was also established that mines are cut in Jurassic mineralized volcanic rocks. Ore minerals (chalcopyrite, pyrite, galena) are related to calcite and quartz veins. The results obtained through the petrochemical and petrography studies of mineralized rock samples from Opitara mines and prehistoric slags are in complete correlation with each other, establishing the direct link between copper mining and smelting within the study area. Acknowledgment: This work was supported by the Shota Rustaveli National Science Foundation of Georgia (grant # FR-19-13022).

Keywords: archaeometallurgy, Mountainous Colchis, mining, ore minerals

Procedia PDF Downloads 181

Authors: A. Clementking, C. Jothi Venkateswaran

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Mathematical and computational functionalities such as descriptive mining, optimization, and predictions are espoused to resolve natural resource planning. The water quality prediction and its attributes influence determinations are adopted optimization techniques. The water properties are tainted while merging water resource one with another. This work aimed to predict influencing water resource distribution connectivity in accordance to water quality and sediment using an innovative proposed master-slave neural network back-propagation model. The experiment results are arrived through collecting water quality attributes, computation of water quality index, design and development of neural network model to determine water quality and sediment, master–slave back propagation neural network back-propagation model to determine variations on water quality and sediment attributes between the water resources and the recommendation for connectivity. The homogeneous and parallel biochemical reactions are influences water quality and sediment while distributing water from one location to another. Therefore, an innovative master-slave neural network model [M (9:9:2)::S(9:9:2)] designed and developed to predict the attribute variations. The result of training dataset given as an input to master model and its maximum weights are assigned as an input to the slave model to predict the water quality. The developed master-slave model is predicted physicochemical attributes weight variations for 85 % to 90% of water quality as a target values.The sediment level variations also predicated from 0.01 to 0.05% of each water quality percentage. The model produced the significant variations on physiochemical attribute weights. According to the predicated experimental weight variation on training data set, effective recommendations are made to connect different resources.

Keywords: master-slave back propagation neural network model(MSBPNNM), water quality analysis, multivariate analysis, environmental mining

Procedia PDF Downloads 477

Authors: Farhood Rismanchian, Seong Hyeon Park, Young Hoon Lee

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This paper proposes a method to optimize the layout of an emergency department (ED) based on real executions of care processes by considering several planning objectives simultaneously. Recently, demand for healthcare services has been dramatically increased. As the demand for healthcare services increases, so do the need for new healthcare buildings as well as the need for redesign and renovating existing ones. The importance of implementation of a standard set of engineering facilities planning and design techniques has been already proved in both manufacturing and service industry with many significant functional efficiencies. However, high complexity of care processes remains a major challenge to apply these methods in healthcare environments. Process mining techniques applied in this study to tackle the problem of complexity and to enhance care process analysis. Process related information such as clinical pathways extracted from the information system of an ED. A 0-1 goal programming approach is then proposed to find a single layout that simultaneously satisfies several goals. The proposed model solved by optimization software CPLEX 12. The solution reached using the proposed method has 42.2% improvement in terms of walking distance of normal patients and 47.6% improvement in walking distance of critical patients at minimum cost of relocation. It has been observed that lots of patients must unnecessarily walk long distances during their visit to the emergency department because of an inefficient design. A carefully designed layout can significantly decrease patient walking distance and related complications.

Keywords: healthcare operation management, goal programming, facility layout problem, process mining, clinical processes

Procedia PDF Downloads 296

Authors: Hang Yang, Jichao Li, Kewei Yang, Tianyang Lei

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Multivariate time series anomaly detection is a significant research topic in the field of data mining, encompassing a wide range of applications across various industrial sectors such as traffic roads, financial logistics, and corporate production. The inherent spatial dependencies and temporal characteristics present in multivariate time series introduce challenges to the anomaly detection task. Previous studies have typically been based on the assumption that all variables belong to the same spatial hierarchy, neglecting the multi-level spatial relationships. To address this challenge, this paper proposes a multi-scale spatial and unified temporal feature fusion network, denoted as MSUT-Net, for multivariate time series anomaly detection. The proposed model employs a multi-level modeling approach, incorporating both temporal and spatial modules. The spatial module is designed to capture the spatial characteristics of multivariate time series data, utilizing an adaptive graph structure learning model to identify the multi-level spatial relationships between data variables and their attributes. The temporal module consists of a unified temporal processing module, which is tasked with capturing the temporal features of multivariate time series. This module is capable of simultaneously identifying temporal dependencies among different variables. Extensive testing on multiple publicly available datasets confirms that MSUT-Net achieves superior performance on the majority of datasets. Our method is able to model and accurately detect systems data with multi-level spatial relationships from a spatial-temporal perspective, providing a novel perspective for anomaly detection analysis.

Keywords: data mining, industrial system, multivariate time series, anomaly detection

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Authors: Aguasanta Miguel Sarmiento, José Miguel Dávila, María Luisa de la Torre

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Acid mine drainage (AMD) is an acidic leachate with high levels of metals and sulphates in solution, which seriously affects the durability and strength of metallic materials used in the construction of structural and mechanical components. This paper presents the results of the evolution over time of the reduction in tensile strength and defects in AISI 304 stainless steel in contact with acid mine drainage. For this purpose, a total of 30 bars with a diameter of 8 mm and a length of 14 cm were placed transversely in the course of a stream contaminated by AMD from the sulphide mines of the Iberian Pyritic Belt (SW Spain). This stream has average pH values of 2.6, a potential of 660 mV, and average concentrations of 12 g/L of sulphates, 1.2 g/L of Fe, 191 mg/L of Zn, etc. Every two months of exposure, 6 stainless steel bars were extracted from the acid stream. They were subjected to surface roughness analysis carried out with the help of Mitutoyo Surftest SJ-210 surface roughness tester. The analysis was carried out at three different points on 5 specimens from each series. The average reading of each parameter is calculated in order to ensure the accuracy of the measurements and the surface coverage. Arithmetic mean roughness value (Ra), mean roughness depth (Rz), and root mean square roughness (Rq) were measured. Five specimens from each series were statically tensile tested using universal equipment (Servosis ME 403 of 200kN). The specimens were clamped at their ends with two grips for cylindrical sections, and the tensile force was applied at a constant speed of 0.5 kN/s, according to the requirements of standard UNE-EN ISO 6892-1: 2020. To determine the modulus of elasticity, limits close to 15% and 55% of the maximum load were used, depending on the course of each test. Field Emission Scanning Electron Microscopy (FESEM) was used to observe corrosion products and defects generated by exposure to AMD. Energy dispersive X-ray spectrometry (EDS) was used to analyse the chemical composition of the corrosion products formed. For this purpose, small pieces were cut from the resulting specimens, cleaned, and embedded in epoxy resin. The results show that after only 5 months of exposure of AISI 304 stainless steel to the mining environment, the surface roughness increases significantly, with average depths almost 6 times greater than the initial one. Cracks are observed on the surface of the material, which increases in size with the time of exposure. A large number of grains with a composition of more than 57% Pb and 16% Sn can be observed inside these cracks. Tensile tests show a reduction in the resistance of this material after only two months of exposure. The results show the serious problems that would result from the use of this material for the use of mechanical components in a sulphide mining environment, not only because of the significant reduction in the lifetime of such components, but also because of the implications for human safety.

Keywords: acid mine drainage, corrosion, mechanical properties, stainless steel

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Authors: Aguasanta M. Sarmiento, Jose Miguel Davila, Juan Carlos Fortes, Maria Luisa de la Torre

Abstract:

Acid mine drainage (AMD) is an acidic leachate with high levels of metals and sulphates in solution, which seriously affects the durability and strength of metallic materials used in the construction of structural and mechanical components. This paper presents the results of the evolution over time of the reduction in tensile strength and defects in AISI 304 stainless steel in contact with acid mine drainage. For this purpose, a total of 30 bars with a diameter of 8 mm and a length of 14 cm were placed transversely in the course of a stream contaminated by AMD from the sulphide mines of the Iberian Pyritic Belt (SW Spain). This stream has average pH values of 2.6, a potential of 660 mV and average concentrations of 12 g/L of sulphates, 1.2 g/L of Fe, 191 mg/L of Zn, etc. Every two months of exposure, 6 stainless steel bars were extracted from the acid stream. They were subjected to surface roughness analysis carried out with the help of Mitutoyo Surftest SJ-210 surface roughness tester. The analysis was carried out at three different points on 5 specimens from each series. The average reading of each parameter is calculated in order to ensure the accuracy of the measurements and the surface coverage. Arithmetic mean roughness value (Ra), mean roughness depth (Rz) and root mean square roughness (Rq) were measured. Five specimens from each series were statically tensile tested using universal equipment (Servosis ME 403 of 200kN). The specimens were clamped at their ends with two grips for cylindrical sections, and the tensile force was applied at a constant speed of 0.5 kN/s, according to the requirements of standard UNE-EN ISO 6892-1: 2020. To determine the modulus of elasticity, limits close to 15% and 55% of the maximum load were used, depending on the course of each test. Field Emission Scanning Electron Microscopy (FESEM) was used to observe corrosion products and defects generated by exposure to AMD. Energy dispersive X-ray spectrometry (EDS) was used to analyze the chemical composition of the corrosion products formed. For this purpose, small pieces were cut from the resulting specimens, cleaned and embedded in epoxy resin. The results show that after only 5 months of exposure of AISI 304 stainless steel to the mining environment, the surface roughness increases significantly, with average depths almost 6 times greater than the initial one. Cracks are observed on the surface of the material, which increases in size with the time of exposure. A large number of grains with a composition of more than 57% Pb and 16% Sn can be observed inside these cracks. Tensile tests show a reduction in the resistance of this material after only two months of exposure. The results show the serious problems that would result from the use of this material for the use of mechanical components in a sulphide mining environment, not only because of the significant reduction in the lifetime of such components but also because of the implications for human safety.

Keywords: Acid mine drainage, Corrosion, Mechanical properties, Stainless steel

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Authors: Mona T. Kashef, Omneya M. Helmy

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Multidrug resistant (MDR) bacteria have become a significant public health threat. The prevalence rates, of Gram negative MDR bacteria, are in continuous increase. However, few data are available about these resistant strains. Since, third generation cephalosporins are one of the most commonly used antimicrobials, we set out to investigate the prevalence, different mechanisms and clonal relatedness of multidrug resistance among third generation resistant Gram negative clinical isolates. A total of 114 Gram negative clinical isolates, previously characterized as being resistant to at least one of 3rd generation cephalosporins, were included in this study. Each isolate was tested, using Kirby Bauer disk diffusion method, against its assigned categories of antimicrobials. The role of efflux pump in resistance development was tested by the efflux pump inhibitor-based microplate assay using chloropromazine as an inhibitor. Detecting different aminoglycosides, β-lactams and quinolones resistance genes was done using polymerase chain reaction. The genetic diversity of MDR isolates was investigated using Random Amplification of Polymorphic DNA technique. MDR phenotype was detected in 101 isolates (89%). Efflux pump mediated resistance was detected in 49/101 isolates. Aminoglycosides resistance genes; armA and aac(6)-Ib were detected in one and 53 isolates, respectively. The aac(6)-Ib-cr allele, that also confers resistance to floroquinolones, was detected in 28/53 isolates. β-lactam resistance genes; blaTEM, blaSHV, blaCTX-M group 1 and group 9 were detected in 52, 29, 61 and 35 isolates, respectively. Quinolone resistance genes; qnrA, qnrB and qnrS were detectable in 2, 14, 8 isolates respectively, while qepA was not detectable at all. High diversity was observed among tested MDR isolates. MDR is common among 3rd generation cephalosporins resistant Gram negative bacteria, in Egypt. In most cases, resistance was caused by different mechanisms. Therefore, new treatment strategies should be implemented.

Keywords: gram negative, multidrug resistance, RAPD typing, resistance genes

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Authors: Patompong Satapornpong, Therdpong Tempark, Pawinee Rerknimitr, Jettanong Klaewsongkram, Chonlaphat Sukasem

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Dapsone (4, 4’-diaminodiphenyl sulfone, DDS) is broadly used for the treatment of inflammatory diseases and infections such as; leprosy, Pneumocystis jiroveci pneumonia in patients with HIV infection, neutrophilic dermatoses, dermatitis herpetiformis and autoimmune bullous disease. The severe cutaneous adverse drug reactions (SCARs) including, Stevens-Johnson syndrome (SJS), toxic epidermal necrolysis (TEN) and drug reaction with eosinophilia and systemic symptoms (DRESS) are rare but severe life-threatening adverse drug reactions. Dapsone is one of many culprit drugs induced SJS, TEN and DRESS. Notwithstanding, to our knowledge, there are no studies of the association of HLA class I alleles and dapsone-induced SCARs in non-leprosy Thai patients. This investigation was a prospective cohort study, which performed in a total of 45 non-leprosy patients. Fifteen patients of dapsone-induced SCARs were classified as following the RegiSCAR criteria, and 30 dapsone-tolerant controls were exposed to dapsone more than 6 months without any evidence of cutaneous reactions. The genotyping of HLA-A, -B and –C were performed using sequence-specific oligonucleotides (PCR-SSOs). The Ethics Committee of Ramathibodi hospital, Mahidol University, approved this study. Among all HLA class I alleles, HLA-A*24:07, HLA-B*13:01, HLA-B*15:02, HLA-C*03:04 and HLA-C*03:09 were significantly associated with dapsone-induced SCARs (OR = 10.55, 95% CI = 1.06 – 105.04, p = 0.0360; OR = 56.00, 95% CI = 8.27 – 379.22, p = 0.0001; OR = 7.00, 95% CI = 1.17 – 42.00, p = 0.0322; OR = 6.00, 95% CI = 1.24 – 29.07, p = 0.0425 and OR = 17.08, 95% CI = 0.82 – 355.45, p = 0.0321, respectively). Furthermore, HLA-B*13:01 allele had strong association with dapsone-induced SJS-TEN and DRESS when compared with dapsone-tolerant controls (OR = 42.00, 95% CI = 2.88 – 612.31, p = 0.0064 and OR = 63.00, 95% CI = 7.72 – 513.94 and p = 0.0001, respectively). Consequently, HLA-B*13:01 might serve as a pharmacogenetic marker for screening before initiating the therapy with dapsone for prevention of dapsone-induced SCARs.

Keywords: dapsone-induced SCARs, HLA-B*13:01, HLA class I alleles, severe cutaneous adverse reactions, Thai

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Authors: N. Gharbi

Abstract:

Constraint Satisfaction problems are mathematical problems that are often used to model many real-world problems for which we look if there exists a solution satisfying all its constraints. Table constraints are important for modeling parts of many problems since they list all combinations of allowed or forbidden values. However, they admit practical limitations because they are sometimes too large to be represented in a direct way. In this paper, we present a survey of the different categories of the proposed approaches to compress table constraints in order to reduce both space and time complexities.

Keywords: constraint programming, compression, data mining, table constraints

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Authors: Vibha Venkataramu, B. V. Venkatarama Reddy

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Natural river sand is the most preferred choice as fine aggregate in masonry mortars. Uncontrolled mining of sand from riverbeds for several decades has had detrimental effects on the environment. Several countries across the world have put strict restrictions on sand mining from riverbeds. However, in countries like India, the huge infrastructural boom has made the local construction industry to look for alternative materials to sand. This study aims at understanding the suitability of granulated blast furnace slag (GBS) as fine aggregates in masonry mortars. Apart from characterising the material properties of GBS, such as particle size distribution, pH, chemical composition, etc., of GBS, tests were performed on the mortars with GBS as fine aggregate. Additionally, the properties of five brick tall, stack bonded masonry prisms with various types of GBS mortars were studied. The mortars with mix proportions 1: 0: 6 (cement: lime: fine aggregate), 1: 1: 6, and 1: 0: 3 were considered for the study. Fresh and hardened properties of mortar, such as flow and compressive strength, were studied. To understand the behaviour of GBS mortars on masonry, tests such as compressive strength and flexure bond strength were performed on masonry prisms made with a different type of GBS mortars. Furthermore, the elastic properties of masonry with GBS mortars were also studied under compression. For comparison purposes, the properties of corresponding control mortars with natural sand as fine aggregate and masonry prisms with sand mortars were also studied under similar testing conditions. From the study, it was observed the addition of GBS negatively influenced the flow of mortars and positively influenced the compressive strength. The GBS mortars showed 20 to 25 % higher compressive strength at 28 days of age, compared to corresponding control mortars. Furthermore, masonry made with GBS mortars showed nearly 10 % higher compressive strengths compared to control specimens. But, the impact of GBS on the flexural strength of masonry was marginal.

Keywords: building materials, fine aggregate, granulated blast furnace slag in mortars, masonry properties

Procedia PDF Downloads 121

Authors: Halkiopoulos Constantinos, Gkintoni Evgenia, Koutsopoulou Ioanna, Antonopoulou Hera

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E-sports and e-gaming have emerged in recent years since the increase in internet use have become universal and e-gamers are the new reality in our homes. The excessive involvement of young adults with e-sports has already been revealed and the adverse consequences have been reported in researches in the past few years, but the issue has not been fully studied yet. The present research is conducted in Greece and studies the psychological profile of video game players and provides information on personality traits, habits and emotional status that affect online gamers’ behaviors in order to help professionals and policy makers address the problem. Three standardized self-report questionnaires were administered to participants who were young male and female adults aged from 19-26 years old. The Profile of Mood States (POMS) scale was used to evaluate people’s perceptions of their everyday life mood; the personality features that can trace back to people’s habits and anticipated reactions were measured by Eysenck Personality Questionnaire (EPQ), and the Trait Emotional Intelligence Questionnaire (TEIQue) was used to measure which cognitive (gamers’ beliefs) and emotional parameters (gamers’ emotional abilities) mainly affected/ predicted gamers’ behaviors and leisure time activities?/ gaming behaviors. Data mining techniques were used to analyze the data, which resulted in machine learning algorithms that were included in the software package R. The research findings attempt to designate the effect of personality traits, emotional status and emotional intelligence influence and correlation with e-sports, gamers’ behaviors and help policy makers and stakeholders take action, shape social policy and prevent the adverse consequences on young adults. The need for further research, prevention and treatment strategies is also addressed.

Keywords: e-sports, e-gamers, personality traits, POMS, emotional intelligence, data mining, R

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Authors: Andrew R. Beatty

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The exploitation of Australia’s vast mineral wealth is regulated by a matrix of planning, environment and heritage legislation, and despite the desire for a ‘balance’ between economic, environmental and heritage values, Aboriginal objects and places are often detrimentally impacted by mining approvals. The Australian experience is not novel. There are other cases of clashes between the rights of traditional landowners and businesses seeking to exploit mineral or other resources on or beneath those lands, including in the United States, Canada, and Brazil. How one reconciles the rights of traditional owners with those of resource companies is an ongoing legal problem of general interest. In Australia, planning and environmental approvals for resource projects are ordinarily issued by State or Territory governments. Federal legislation such as the Aboriginal and Torres Strait Islander Heritage Protection Act 1984 (Cth) is intended to act as a safety net when State or Territory legislation is incapable of protecting Indigenous objects or places in the context of approvals for resource projects. This paper will analyse the context and effectiveness of legislation enacted to protect Indigenous heritage in the planning process. In particular, the paper will analyse how the statutory objects of such legislation need to be weighed against the statutory objects of competing legislation designed to facilitate and control resource exploitation. Using a current claim in the Federal Court of Australia for the protection of a culturally significant landscape as a case study, this paper will examine the challenges faced in ascribing value to cultural heritage within the wider context of environmental and planning laws. Our findings will reveal that there is an inherent difficulty in defining and weighing competing economic, environmental and heritage considerations. An alternative framework will be proposed to guide regulators towards making decisions that result in better protection of Indigenous heritage in the context of resource management.

Keywords: environmental law, heritage law, indigenous rights, mining

Procedia PDF Downloads 96

Authors: Purevdolgor Luvsantseren, Ajnai Luvsan-Ish, Oyuntsetseg Sandag, Javzmaa Tsend, Akhit Tileubai, Baasandorj Chilhaasuren, Jargalbat Puntsagdash, Galbadrakh Chuluunbaatar

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One of the indicators of the quality of university services is student satisfaction. Aim: We aimed to study the level of satisfaction of students in the first year of premedical courses in the course of Medical Physics using the cluster method. Materials and Methods: In the framework of this goal, a questionnaire was collected from a total of 324 students who studied the medical physics course of the 1st course of the premedical course at the Mongolian National University of Medical Sciences. When determining the level of satisfaction, the answers were obtained on five levels of satisfaction: "excellent", "good", "medium", "bad" and "very bad". A total of 39 questionnaires were collected from students: 8 for course evaluation, 19 for teacher evaluation, and 12 for student evaluation. From the research, a database with 39 fields and 324 records was created. Results: In this database, cluster analysis was performed in MATLAB and R programs using the k-means method of data mining. Calculated the Hopkins statistic in the created database, the values are 0.88, 0.87, and 0.97. This shows that cluster analysis methods can be used. The course evaluation sub-fund is divided into three clusters. Among them, cluster I has 150 objects with a "good" rating of 46.2%, cluster II has 119 objects with a "medium" rating of 36.7%, and Cluster III has 54 objects with a "good" rating of 16.6%. The teacher evaluation sub-base into three clusters, there are 179 objects with a "good" rating of 55.2% in cluster II, 108 objects with an "average" rating of 33.3% in cluster III, and 36 objects with an "excellent" rating in cluster I of 11.1%. The sub-base of student evaluations is divided into two clusters: cluster II has 215 objects with an "excellent" rating of 66.3%, and cluster I has 108 objects with an "excellent" rating of 33.3%. Evaluating the resulting clusters with the Silhouette coefficient, 0.32 for the course evaluation cluster, 0.31 for the teacher evaluation cluster, and 0.30 for student evaluation show statistical significance. Conclusion: Finally, to conclude, cluster analysis in the model of the medical physics lesson “good” - 46.2%, “middle” - 36.7%, “bad” - 16.6%; 55.2% - “good”, 33.3% - “middle”, 11.1% - “bad” in the teacher evaluation model; 66.3% - “good” and 33.3% of “bad” in the student evaluation model.

Keywords: questionnaire, data mining, k-means method, silhouette coefficient

Procedia PDF Downloads 50

Authors: S. Mondal, L. M. Olsen-Kettle, L. Gross

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Fracture propagation and damage evolution are extremely important for many industrial applications including mining industry, composite materials, earthquake simulations, hydraulic fracturing. The influence of pre-existing flaws and rock heterogeneity on the processes and mechanisms of rock fracture has important ramifications in many mining and reservoir engineering applications. We simulate the damage evolution and fracture propagation in an isotropic sandstone specimen containing a pre-existing 3-D surface flaw in different configurations under uniaxial compression. We apply a damage model based on the unified strength theory and solve the solid deformation and damage evolution equations using the Finite Element Method (FEM) with tetrahedron elements on unstructured meshes through the simulation software, eScript. Unstructured meshes provide higher geometrical flexibility and allow a more accurate way to model the varying flaw depth, angle, and length through locally adapted FEM meshes. The heterogeneity of rock is considered by initializing material properties using a Weibull distribution sampled over a cubic grid. In our model, we introduce a length scale related to the rock heterogeneity which is independent of the mesh size. We investigate the effect of parameters including the heterogeneity of the elastic moduli and geometry of the single flaw in the stress strain response. The generation of three typical surface cracking patterns, called wing cracks, anti-wing cracks and far-field cracks were identified, and these depend on the geometry of the pre-existing surface flaw. This model results help to advance our understanding of fracture and damage growth in heterogeneous rock with the aim to develop fracture simulators for different industry applications.

Keywords: finite element method, heterogeneity, isotropic damage, uniaxial compression

Procedia PDF Downloads 218

Authors: Gary Pattemore, Michael Edgar, Andrew Job, Marina Auad, Kathryn Job

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As critical commodities become more scarce, significant time and resources have been used to better understand complicated ore bodies and extract their full potential. These challenging ore bodies provide several pain points for geologists and engineers to overcome, poor handling of these issues flows downs stream to the processing plant affecting throughput rates and recovery. Many open cut mines utilise blast hole drilling to extract additional information to feed back into the modelling process. This method requires samples to be collected during or after blast hole drilling. Samples are then sent for assay with turnaround times varying from 1 to 12 days. This method is time consuming, costly, requires human exposure on the bench and collects elemental data only. To address this challenge, research has been undertaken to utilise hyperspectral imaging across a broad spectrum to scan samples, collars or take down hole measurements for minerals and moisture content and grade abundances. Automation of this process using unmanned vehicles and on-board processing reduces human in pit exposure to ensure ongoing safety. On-board processing allows data to be integrated into modelling workflows with immediacy. The preliminary results demonstrate numerous direct and indirect benefits from this new technology, including rapid and accurate grade estimates, moisture content and mineralogy. These benefits allow for faster geo modelling updates, better informed mine scheduling and improved downstream blending and processing practices. The paper presents recommendations for implementation of the technology in open cut mining environments.

Keywords: grade control, hyperspectral scanning, artificial intelligence, autonomous mining, machine learning

Procedia PDF Downloads 113

Authors: Juliana A. Galhardi, Daniel M. Bonotto

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Coal is an important non-renewable energy source of and can be associated with radioactive elements. In Figueira city, Paraná state, Brazil, it was recorded high uranium activity near the coal mine that supplies a local thermoelectric power plant. In this context, the radon activity (Rn-222, produced by the Ra-226 decay in the U-238 natural series) was evaluated in groundwater, river water and effluents produced from the acid mine drainage in the coal reject dumps. The samples were collected in August 2013 and in February 2014 and analyzed at LABIDRO (Laboratory of Isotope and Hydrochemistry), UNESP, Rio Claro city, Brazil, using an alpha spectrometer (AlphaGuard) adjusted to evaluate the mean radon activity concentration in five cycles of 10 minutes. No radon activity concentration above 100 Bq.L-1, which was a previous critic value established by the World Health Organization. The average radon activity concentration in groundwater was higher than in surface water and in effluent samples, possibly due to the accumulation of uranium and radium in the aquifer layers that favors the radon trapping. The lower value in the river waters can indicate dilution and the intermediate value in the effluents may indicate radon absorption in the coal particles of the reject dumps. The results also indicate that the radon activities in the effluents increase with the sample acidification, possibly due to the higher radium leaching and the subsequent radon transport to the drainage flow. The water samples of Laranjinha River and Ribeirão das Pedras stream, which, respectively, supply Figueira city and receive the mining effluent, exhibited higher pH values upstream the mine, reflecting the acid mine drainage discharge. The radionuclides transport indicates the importance of monitoring their activity concentration in natural waters due to the risks that the radioactivity can represent to human health.

Keywords: radon, radium, acid mine drainage, coal

Procedia PDF Downloads 432

Authors: Saloni Khandelwal

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The Aravalli hills are one of the oldest and most distinctive mountain chains of peninsular India spanning in around 692 Km. More than 60% of it falls in the state of Rajasthan and influences ecological equilibrium in about 30% of the state. Because of natural and human-induced activities, physical gaps in the Aravallis are increasing, new gaps are coming up, and its physical structure is changing. There are no strict regulations to protect and monitor the Aravallis and no comprehensive research and study has been done for the enhancement of ecosystem functions of these ranges. Through this study, various factors leading to Aravalli’s degradation are identified and its impacts on selected areas are analyzed. A literature study is done to identify factors responsible for the degradation. To understand the severity of the problem at the lowest level, two tehsils from different districts in Rajasthan, which are the most affected due to illegal mining and increasing physical gaps are selected for the study. Case-1 of three-gram panchayats in Kishangarh Tehsil of Ajmer district focuses on the expanding physical gaps in the Aravalli range, and case-2 of three-gram panchayats in Tijara Tehsil of Alwar district focuses on increasing illegal mining in the Aravalli range. For measuring the degradation, physical, biological and social indicators are identified through literature review and for both the cases analysis is done on the basis of these indicators. Primary survey and focus group discussions are done with villagers, mining owners, illegal miners, and various government officials to understand dependency of people on the Aravalli and its importance to them along with the impact of degradation on their livelihood and environment. From the analysis, it has been found that green cover is continuously decreasing in both cases, dense forest areas do not exist now, the groundwater table is depleting at a very fast rate, soil is losing its moisture resulting in low yield and shift in agriculture. Wild animals which were easily seen earlier are now extinct. Cattles of villagers are dependent on the forest area in the Aravalli range for food, but with a decrease in fodder, their cattle numbers are decreasing. There is a decrease in agricultural land and an increase in scrub and salt-affected land. Analysis of various national and state programmes, acts which were passed to conserve biodiversity has been done showing that none of them is helping much to protect the Aravalli. For conserving the Aravalli and its forest areas, regional level and local level initiatives are required and are proposed in this study. This study is an attempt to formulate conservation and management strategies for the Aravalli range. These strategies will help in improving biodiversity which can lead to the revival of its ecosystem functions. It will also help in curbing the pollution at the regional and local level. All this will lead to the sustainable development of the region.

Keywords: Aravalli, ecosystem, LULC, Rajasthan

Procedia PDF Downloads 137

Authors: Manish Pandey, Gurinderjit Kaur, Meenu Talwar, Sachin Chauhan, Jagbir Gill

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Health-care management systems are a unit of nice connection as a result of the supply a straightforward and fast management of all aspects relating to a patient, not essentially medical. What is more, there are unit additional and additional cases of pathologies during which diagnosing and treatment may be solely allotted by victimization medical imaging techniques. With associate ever-increasing prevalence, medical pictures area unit directly acquired in or regenerate into digital type, for his or her storage additionally as sequent retrieval and process. Data Mining is the process of extracting information from large data sets through using algorithms and Techniques drawn from the field of Statistics, Machine Learning and Data Base Management Systems. Forecasting may be a prediction of what's going to occur within the future, associated it's an unsure method. Owing to the uncertainty, the accuracy of a forecast is as vital because the outcome foretold by foretelling the freelance variables. A forecast management should be wont to establish if the accuracy of the forecast is within satisfactory limits. Fuzzy regression strategies have normally been wont to develop shopper preferences models that correlate the engineering characteristics with shopper preferences relating to a replacement product; the patron preference models offer a platform, wherever by product developers will decide the engineering characteristics so as to satisfy shopper preferences before developing the merchandise. Recent analysis shows that these fuzzy regression strategies area units normally will not to model client preferences. We tend to propose a Testing the strength of Exponential Regression Model over regression toward the mean Model.

Keywords: health-care management systems, fuzzy regression, data mining, forecasting, fuzzy membership function

Procedia PDF Downloads 279

Authors: Wade Ghribi, Abdelmoty M. Ahmed, Ahmed Said Badawy, Belgacem Bouallegue

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In higher education institutions, the most pressing priority is to improve student performance and retention. Large volumes of student data are used in Educational Data Mining techniques to find new hidden information from students' learning behavior, particularly to uncover the early symptom of at-risk pupils. On the other hand, data with noise, outliers, and irrelevant information may provide incorrect conclusions. By identifying features of students' data that have the potential to improve performance prediction results, comparing and identifying the most appropriate ensemble learning technique after preprocessing the data, and optimizing the hyperparameters, this paper aims to develop a reliable students' performance prediction model for Higher Education Institutions. Data was gathered from two different systems: a student information system and an e-learning system for undergraduate students in the College of Computer Science of a Saudi Arabian State University. The cases of 4413 students were used in this article. The process includes data collection, data integration, data preprocessing (such as cleaning, normalization, and transformation), feature selection, pattern extraction, and, finally, model optimization and assessment. Random Forest, Bagging, Stacking, Majority Vote, and two types of Boosting techniques, AdaBoost and XGBoost, are ensemble learning approaches, whereas Decision Tree, Support Vector Machine, and Artificial Neural Network are supervised learning techniques. Hyperparameters for ensemble learning systems will be fine-tuned to provide enhanced performance and optimal output. The findings imply that combining features of students' behavior from e-learning and students' information systems using Majority Vote produced better outcomes than the other ensemble techniques.

Keywords: educational data mining, student performance prediction, e-learning, classification, ensemble learning, higher education

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Authors: Sarah Niklas, Lynne Chester, Mark Diesendorf

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Geopolitical tensions, climate change and recent movements favouring a transformative shift in institutional power structures have influenced the economics of conventional energy supply for decades. This study takes a multi-dimensional approach to illustrate the potential of renewable energy (RE) technology to provide a pathway to a low-carbon economy driven by ecologically sustainable, independent and socially just energy. This comparative analysis identifies economic, political and social drivers that shaped the adoption of RE policy in two significantly different economies, Germany and Australia, with strong and weak commitments to RE respectively. Two complementary political-economy theories frame the document-based analysis. Régulation Theory, inspired by Marxist ideas and strongly influenced by contemporary economic problems, provides the background to explore the social relationships contributing the adoption of RE within the macro-economy. Varieties of Capitalism theory, a more recently developed micro-economic approach, examines the nature of state-firm relationships. Together these approaches provide a comprehensive lens of analysis. Germany’s energy policy transformed substantially over the second half of the last century. The development is characterised by the coordination of societal, environmental and industrial demands throughout the advancement of capitalist regimes. In the Fordist regime, mass production based on coal drove Germany’s astounding economic recovery during the post-war period. Economic depression and the instability of institutional arrangements necessitated the impulsive seeking of national security and energy independence. During the postwar Flexi-Fordist period, quality-based production, innovation and technology-based competition schemes, particularly with regard to political power structures in and across Europe, favoured the adoption of RE. Innovation, knowledge and education were institutionalized, leading to the legislation of environmental concerns. Lastly the establishment of government-industry-based coordinative programs supported the phase out of nuclear power and the increased adoption of RE during the last decade. Australia’s energy policy is shaped by the country’s richness in mineral resources. Energy policy largely served coal mining, historically and currently one of the most capital-intense industry. Assisted by the macro-economic dimensions of institutional arrangements, social and financial capital is orientated towards the export-led and strongly demand-oriented economy. Here energy policy serves the maintenance of capital accumulation in the mining sector and the emerging Asian economies. The adoption of supportive renewable energy policy would challenge the distinct role of the mining industry within the (neo)-liberal market economy. The state’s protective role of the mining sector has resulted in weak commitment to RE policy and investment uncertainty in the energy sector. Recent developments, driven by strong public support for RE, emphasize the sense of community in urban and rural areas and the emergence of a bottom-up approach to adopt renewables. Thus, political economy frameworks on both the macro-economic (Regulation Theory) and micro-economic (Varieties of Capitalism theory) scales can together explain the strong commitment to RE in Germany vis-à-vis the weak commitment in Australia.

Keywords: political economy, regulation theory, renewable energy, social relationships, energy transitions

Procedia PDF Downloads 381

Authors: Özlem Ateş Sönmezoğlu, Begüm Terzi, Ahmet Yıldırım, Leyla Gündüz

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Durum wheat quality is defined as its suitability for pasta processing, that is pasta making quality. Another factor that determines the quality of durum wheat is the nutritional value of wheat or its final products. Wheat is a basic source of calories, proteins and minerals for humans in many countries of the world. For this reason, improvement of wheat nutritional value is of great importance. In recent years, deficiencies in protein and micronutrients, particularly in iron and zinc, have seriously increased. Therefore, basic foods such as wheat must be improved for micronutrient content. The effects of some major genes for grain quality established. Gpc-B1 locus is one of the genes increased protein and micronutrients content, and used in improvement studies of durum wheat nutritional value. The aim of this study was to increase the protein content and the micronutrient (Fe, Zn ve Mn) contents of an advanced durum wheat line (TMB 1) that was previously improved for its protein quality. For this purpose, TMB1 advanced durum wheat line were used as the recurrent parent and also, UC1113-Gpc-B1 line containing the Gpc-B1 gene was used as the gene source. In all of the generations, backcrossed plants carrying the targeted gene region were selected by marker assisted selection (MAS). BC4F1 plants MAS method was employed in combination with embryo culture and rapid plant growth in a controlled greenhouse conditions in order to shorten the duration of the transition between generations in backcross breeding. The Gpc-B1 gene was selected specific molecular markers. Since Yr-36 gene associated with Gpc-B1 allele, it was also transferred to the Gpc-B1 transferred lines. Thus, the backcrossed plants selected by MAS are resistance to yellow rust disease. This research has been financially supported by TÜBİTAK (112T910).

Keywords: Durum wheat, Gpc-B1, MAS, Triticum durum, Yr-36

Procedia PDF Downloads 277

Authors: Branci Sarra, Branci Saadia

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Because of the multiplied data growth, many computer science tools have been developed to process and analyze these Big Data. High-performance computing architectures have been designed to meet the treatment needs of Big Data (view transaction processing standpoint, strategic, and tactical analytics). The purpose of this article is to provide a historical and global perspective on the recent trend of high-performance computing architectures especially what has a relation with Analytics and Data Mining.

Keywords: high performance computing, HPC, big data, data analysis

Procedia PDF Downloads 520

Authors: Kristýna Weissová

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This study is focused on two selected model taxa of invertebrates - Hymenoptera: Aculeata and Lepidopterawithnocturnalactivity, recordedatthesitesof lignite dumps and their surroundings in the North Bohemian Lignite Basin, Czech Republic. There search was conducted on 10 landfills, 3 study areas were determined on each landfill - primary and secondary succession and recultivation. A total of 3,202 individuals belonging to 232 species and 17 families of sagebrushinsects were collected. died, 74%of the species occurred on the primary succes sionare as, that is 2x more species than on the reclaimed areas. Of the total number of species and on all areas, 60 rare species were recorded - 29 vulnerable, 21 endangered, 8 critically endangered, and 2 extinct The areas of primary succession were again confirmed to be the richest in terms of rare species, hosting 39 rare species of Hymenoptera: Aculeata. In addition, bothextinct species were represented only on plots of primary succession. The family Crabronidae had the largestre presentation of species on theareasofleft primary succession, the family Halictidae was the most represented on the reclaimed areas and areas of secondary succession. A total of 3,634 moths were collected, assigned to 262 species and 10 families. A similar number of species occurred on the primary succession and reclaimed areas, but the reclaimed area had a greater abundance. Secondary successionsiteshostedha lf as many species and alsocontainedlow abundance compared to other management types. The results show that there claimed areas host a numerically larger group and more species of moths than the successionalareas. Rare species did not occur at any site. A higher number of days in locations without water bodies, wetland vegetation, and locations with a highre presentation of woody species. It is advisable to combine individual types of landscape management in such a way as to create a colorfulmosaic that supports biodiversity. In particular, we recommend incorporating natural successionintoreclamation plans, which is a refuge for many rare species of invertebrates, which has not yetbeenroutinely and purposefully practiced.

Keywords: hymenoptera: aculeata, lepidoptera, reclamation, succession, post-mining ara

Procedia PDF Downloads 117