Search results for: consumption patterns

Authors: Danlei Yang, Luofeng Huang

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The integration of digital twin technology with renewable energy systems offers an innovative approach to predicting and optimising performance throughout the entire lifecycle. A digital twin is a continuously updated virtual replica of a real-world entity, synchronised with data from its physical counterpart and environment. Many digital twin companies today claim to have mature digital twin products, but their focus is primarily on equipment visualisation. However, the core of a digital twin should be its model, which can mirror, shadow, and thread with the real-world entity, which is still underdeveloped. For a floating solar energy system, a digital twin model can be defined in three aspects: (a) the physical floating solar energy system along with environmental factors such as solar irradiance and wave dynamics, (b) a digital model powered by artificial intelligence (AI) algorithms, and (c) the integration of real system data with the AI-driven model and a user interface. The experimental setup for the floating solar energy system, is designed to replicate real-ocean conditions of floating solar installations within a controlled laboratory environment. The system consists of a water tank that simulates an aquatic surface, where a floating catamaran structure supports a solar panel. The solar simulator is set up in three positions: one directly above and two inclined at a 45° angle in front and behind the solar panel. This arrangement allows the simulation of different sun angles, such as sunrise, midday, and sunset. The solar simulator is positioned 400 mm away from the solar panel to maintain consistent solar irradiance on its surface. Stability for the floating structure is achieved through ropes attached to anchors at the bottom of the tank, which simulates the mooring systems used in real-world floating solar applications. The floating solar energy system's sensor setup includes various devices to monitor environmental and operational parameters. An irradiance sensor measures solar irradiance on the photovoltaic (PV) panel. Temperature sensors monitor ambient air and water temperatures, as well as the PV panel temperature. Wave gauges measure wave height, while load cells capture mooring force. Inclinometers and ultrasonic sensors record heave and pitch amplitudes of the floating system’s motions. An electric load measures the voltage and current output from the solar panel. All sensors collect data simultaneously. Artificial neural network (ANN) algorithms are central to developing the digital model, which processes historical and real-time data, identifies patterns, and predicts the system’s performance in real time. The data collected from various sensors are partly used to train the digital model, with the remaining data reserved for validation and testing. The digital twin model combines the experimental setup with the ANN model, enabling monitoring, analysis, and prediction of the floating solar energy system's operation. The digital model mirrors the functionality of the physical setup, running in sync with the experiment to provide real-time insights and predictions. It provides useful industrial benefits, such as informing maintenance plans as well as design and control strategies for optimal energy efficiency. In long term, this digital twin will help improve overall solar energy yield whilst minimising the operational costs and risks.

Keywords: digital twin, floating solar energy system, experiment setup, artificial intelligence

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Authors: Marina Nechayeva, Malgorzata Marciniak, Vladimir Przhebelskiy, A. Dragutan, S. Lamichhane, S. Oikawa

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This presentation is a progress report on a faculty-student research collaboration at CUNY LaGuardia Community College (LaGCC) aimed at designing a small horizontal axis wind turbine optimized for the wind patterns on the roof of our campus. Our project combines statistical and engineering research. Our wind modeling protocol is based upon a recent wind study by a faculty-student research group at MIT, and some of our blade design methods are adopted from a senior engineering project at CUNY City College. Our use of genetic algorithms has been inspired by the work on small wind turbines’ design by David Wood. We combine these diverse approaches in our interdisciplinary project in a way that has not been done before and improve upon certain techniques used by our predecessors. We employ several estimation methods to determine the best fitting parametric probability distribution model for the local wind speed data obtained through correlating short-term on-site measurements with a long-term time series at the nearby airport. The model serves as a foundation for engineering research that focuses on adapting and implementing genetic algorithms (GAs) to engineering optimization of the wind turbine design using Blade Element Momentum Theory. GAs are used to create new airfoils with desirable aerodynamic specifications. Small scale models of best performing designs are 3D printed and tested in the wind tunnel to verify the accuracy of relevant calculations. Genetic algorithms are applied to selected airfoils to determine the blade design (radial cord and pitch distribution) that would optimize the coefficient of power profile of the turbine. Our approach improves upon the traditional blade design methods in that it lets us dispense with assumptions necessary to simplify the system of Blade Element Momentum Theory equations, thus resulting in more accurate aerodynamic performance calculations. Furthermore, it enables us to design blades optimized for a whole range of wind speeds rather than a single value. Lastly, we improve upon known GA-based methods in that our algorithms are constructed to work with XFoil generated airfoils data which enables us to optimize blades using our own high glide ratio airfoil designs, without having to rely upon available empirical data from existing airfoils, such as NACA series. Beyond its immediate goal, this ongoing project serves as a training and selection platform for CUNY Research Scholars Program (CRSP) through its annual Aerodynamics and Wind Energy Research Seminar (AWERS), an undergraduate summer research boot camp, designed to introduce prospective researchers to the relevant theoretical background and methodology, get them up to speed with the current state of our research, and test their abilities and commitment to the program. Furthermore, several aspects of the research (e.g., writing code for 3D printing of airfoils) are adapted in the form of classroom research activities to enhance Calculus sequence instruction at LaGCC.

Keywords: engineering design optimization, genetic algorithms, horizontal axis wind turbine, wind modeling

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Authors: Mohammad Hossein Pazandeh, Monir Doudi, Sona Rostampour Yasouri

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Irregular consumption of current antibiotic makes increases of antibiotic resistance between urin pathogens on all worlds. This study selected based on this great community problem. The aim of this study was the biosynthesis of silver nanoparticles from Zataria multiflora extract and then to investigate its antibacterial effect on gram-negative bacilli common in Urinary Tract Infections (UTI) and MDR. The plant used in the present research was Zataria multiflora whose extract was prepared through Soxhlet extraction method. Green synthesis condition of silver nanoparticles was investigated in terms of three parameters including the extract amount, concentration of silver nitrate salt, and temperature. The seizes of nanoparticles were determined by Zetasizer. In order to identify synthesized silver nanoparticles Transmission Electron Microscopy (TEM) and X-ray Diffraction (XRD) methods were used. For evaluating the antibacterial effects of nanoparticles synthesized through biological method different concentrations of silver nanoparticles were studied on 140 cases of Muliple Drug Resistance (MDR) bacteria strains Escherichia coli, Klebsiella pneumoniae, Enterobacter aerogenes, Proteus vulgaris,Citrobacter freundii, Acinetobacter bumanii and Pseudomonas aeruginosa, (each genus of bacteria, 20 samples), which all were MDR and cause urinary tract infections , for identification of bacteria were used of Polymerase Chain Reaction (PCR) test and laboratory methods (Agar well diffusion and Microdilution methods) to assess their sensitivity to Nanoparticles. The data were analyzed using SPSS software by nonparametric Kruskal-Wallis and Mann-Whitney tests. Significant results were found about the effects of silver nitrate concentration, different amounts of Zataria multiflora extract, and temperature on nanoparticles; that is, by increasing the concentration of silver nitrate, extract amount, and temperature, the sizes of synthesized nanoparticles declined. However, the effect of above mentioned factors on particles diffusion index was not significant. Based on the TEM results, particles were mainly spherical shape with a diameter range of 25 to 50 nm. The results of XRD Analysis indicated the formation of Nanostructures and Nanocrystals of silver.. The obtained results of antibacterial effects of different concentrations of silver nanoparticles on according to agar well diffusion and microdilution method, biologically synthesized nanoparticles showed 1000 mg /ml highest and lowest mean inhibition zone diameter in E.coli , Acinetobacter bumanii 23 and 15mm, respectively. MIC was observed for all of bacteria 125mg/ml and for Acinetobacter bumanii 250mg/ml.Comparing the growth inhibitory effect of chemically synthesized Nanoparticles and biologically synthesized Nanoparticles showed that in the chemical method the highest growth inhibition belonged to the concentration of 62.5 mg /ml. The inhibitory effect on the growth all of bacteria causes of urine infection and MDR was observed and by increasing silver ion concentration in Nanoparticles, antibacterial activity increased. Generally, the biological synthesis can be considered an efficient way not only in making Nanoparticles but also for having anti-bacterial properties. It is more biocompatible and may be possess less toxicity than the Nanoparticles synthesized chemically.

Keywords: biosynthesis, MDR bacteria, silver nanoparticles, UTI

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Authors: Joao Ferreira Do Rosario, Maria De Lurdes Calisto, Ana Teresa Machado, Nuno Gustavo, Rui Gonçalves

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The tourism sector is increasingly important to the economic performance of countries and a relevant theme to academic research, increasing the importance of understanding how and why tourists evaluate tourism locations. The city of Lisbon is currently a tourist destination of excellence in the European and world-wide panorama, registering a significant growth of the economic weight of its tourist activities in the Gross Added Value of the region. Although there is research on the feedback of those who visit tourist sites and different methodologies for studying tourist sites have been applied, this research seeks to be innovative in the objective of obtaining insights on the competitiveness in terms of attractiveness of the city of Lisbon as a tourist destination, based the feedback of tourists in the Facebook pages of the most visited museums and monuments of Lisbon, an interpretation that is relevant in the development of strategies of tourist attraction. The intangible dimension of the tourism offer, due to its unique condition of simultaneous production and consumption, makes eWOM particularly relevant. The testimony of consumers is thus a decisive factor in the decision-making and buying process in tourism. Online social networks are one of the most used platforms for tourists to evaluate the attractiveness's points of a tourism destination (e.g. cultural and historical heritage), with this user-generated feedback enabling relevant information about the customer-tourists. This information is related to the tourist experience representing the true voice of the customer. Furthermore, this voice perceived by others as genuine, opposite to marketing messages, may have a powerful word-of-mouth influence on other potential tourists. The relevance of online reviews sharing, however, becomes particularly complex, considering social media users’ different profiles or the possible and different sources of information available, as well as their associated reputation associated with each source. In the light of these trends, our research focuses on the tourists’ feedback on Facebook pages of the most visited museums and monuments of Lisbon that contribute to its attractiveness as a tourism destination. Sentiment Analysis is the methodology selected for this research, using public available information in the online context, which was deemed as an appropriate non-participatory observation method. Data will be collected from two museums (Museu dos Coches and Museu de Arte Antiga) and three monuments ((Mosteiro dos Jerónimos, Torre de Belém and Panteão Nacional) Facebook pages during a period of one year. The research results will help in the evaluation of the considered places by the tourists, their contribution to the city attractiveness and present insights helpful for the management decisions regarding this museums and monuments. The results of this study will also contribute to a better knowledge of the tourism sector, namely the identification of attributes in the evaluation and choice of the city of Lisbon as a tourist destination. Further research will evaluate the Lisbon attraction points for tourists in different categories beyond museums and monuments, will also evaluate the tourist feedback from other sources like TripAdvisor and apply the same methodology in other cities and country regions.

Keywords: Lisbon tourism, opinion mining, sentiment analysis, tourism location attractiveness evaluation

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Authors: Dirk Bruland, Paulo Pinheiro, Ullrich Bauer

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Introduction: Over 3 million children, about one quarter of all students, experience at least one parent with mental disorder in Germany every year. Children of mentally-ill parents are at considerably higher risk of developing serious mental health problems. The different burden patterns and coping attempts often become manifest in children's school lives. In this context, schools can have an important protective function, but can also create risk potentials. In reference to Jorm, pupil-related teachers’ mental health literacy (Teacher-MHL) includes the ability to recognize change behaviour, the knowledge of risk factors, the implementation of first aid intervention, and seeking professional help (teacher as gatekeeper). Although teachers’ knowledge and increased awareness of this topic is essential, the literature provides little information on the extent of teachers' abilities. As part of a German-wide research consortium on health literacy, this project, launched in March for 3 years, will conduct evidence-based mental health literacy research. The primary objective is to measure Teacher-MHL in the context of pupil-related psychosocial factors at primary and secondary schools (grades 5 & 6), while also focussing on children’s social living conditions. Methods: (1) A systematic literature review in different databases to identify papers with regard to Teacher-MHL (completed). (2) Based on these results, an interview guide was developed. This research step includes a qualitative pre-study to inductively survey the general profiles of teachers (n=24). The evaluation will be presented on the conference. (3) These findings will be translated into a quantitative teacher survey (n=2500) in order to assess the extent of socio-analytical skills of teachers as well as in relation to institutional and individual characteristics. (4) Based on results 1 – 3, developing a training program for teachers. Results: The review highlights a lack of information for Teacher-MHL and their skills, especially related to high-risk-groups like children of mentally ill parents. The literature is limited to a few studies only. According to these, teacher are not good at identifying burdened children and if they identify those children they do not know how to handle the situations in school. They are not sufficiently trained to deal with these children, especially there are great uncertainties in dealing with the teaching situation. Institutional means and resources are missing as well. Such a mismatch can result in insufficient support and use of opportunities for children at risk. First impressions from the interviews confirm these results and allow a greater insight in the everyday school-life according to critical life events in families. Conclusions: For the first time schools will be addressed as a setting where children are especially "accessible" for measures of health promotion. Addressing Teacher-MHL gives reason to expect high effectiveness. Targeting professionals' abilities for dealing with this high-risk-group leads to a discharge for teacher themselves to handle those situations and increases school health promotion. In view of the fact that only 10-30% of such high-risk families accept offers of therapy and assistance, this will be the first primary preventive and health-promoting approach to protect the health of a yet unaffected, but particularly burdened, high-risk group.

Keywords: children of mentally ill parents, health promotion, mental health literacy, school

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Authors: Kiran Baldavoo, Mishelle Doorasamy

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Universities have a role to play in the preservation of the environment, and the study attempted to evaluate the environmental management accounting (EMA) processes at UKZN. UKZN, a South African university, generates the same direct and indirect environmental impacts as the higher education sector worldwide. This is significant within the context of the South African environment which is constantly plagued by having to effectively manage the already scarce resources of water and energy, evident through the imposition of water and energy restrictions over the recent years. The study’s aim is to increase awareness of having a structured approach to environmental management in order to achieve the strategic environmental goals of the university. The research studied the experiences of key managers within UKZN, with the purpose of exploring the potential factors which influence the decision to adopt and apply EMA within the higher education sector. The study comprised two objectives, namely understanding the current state of accounting practices for managing major environmental costs and identifying factors influencing EMA adoption within the university. The study adopted a case study approach, comprising semi-structured interviews of key personnel involved in Management Accounting, Environmental Management, and Academic Schools within the university. Content analysis was performed on the transcribed interview data. A Theoretical Framework derived from literature was adopted to guide data collection and focus the study. Contingency and Institutional theory was the resultant basis of the derived framework. The findings of the first objective revealed that there was a distinct lack of EMA utilization within the university. There was no distinct policy on EMA, resulting in minimal environmental cost information being brought to the attention of senior management. The university embraced the principles of environmental sustainability; however, efforts to improve internal environmental accountability primarily from an accounting perspective was absent. The findings of the second objective revealed that five key barriers contributed to the lack of EMA utilization within the university. The barriers being attitudinal, informational, institutional, technological, and lack of incentives (financial). The results and findings of this study supported the use and application of EMA within the higher education sector. Participants concurred that EMA was underutilized and if implemented, would realize significant benefits for both the university and environment. Environmental management accounting is being widely acknowledged as a key management tool that can facilitate improved financial and environmental performance via the concept of enhanced environmental accountability. Historically research has been concentrated primarily on the manufacturing industry, due to it generating the greatest proportion of environmental impacts. Service industries are also an integral component of environmental management as they contribute significant environmental impacts, both direct and indirect. Educational institutions such as universities form part of the service sector and directly impact on the environment through the consumption of paper, energy, and water and solid waste generated, with the associated demands.

Keywords: environmental management accounting, environmental impacts, higher education, Southern Africa

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Authors: H. I. Obadiah, S. N. Wieser, E. A. Omudu, B. O. Atu, O. Byanet, L. Schnittger, M. Florin-Christensen

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Sarcocystis sp. are Apicomplexan protozoan parasites with a life cycle that involves a predator and a prey as final and intermediate hosts, respectively. In tissues of the intermediate hosts, the parasites produce sarcocysts that vary in size and morphology according to the species. When a suitable predator ingests sarcocyst-containing meat, the parasites are released in the intestine and undergo sexual reproduction producing infective sporocysts, which are excreted with the feces into the environment. The cycle is closed when a prey ingests sporocyst-contaminated water or pasture; the parasites gain access to the circulation, and eventually invade tissues and reproduce asexually yielding sarcocysts. Pig farming is a common practice in Nigeria as well as in many countries around the world. In addition to its importance as protein source, pork is also a source of several pathogens relevant to humans. In the case of Sarcocystis, three species have been described both in domestic and wild pigs, namely, S. miescheriana, S. porcifelis and S. suihominis. Humans can act both as final and aberrant intermediate hosts of S. suihominis, after ingesting undercooked sarcocyst-infested pork. Infections are usually asymptomatic but can be associated with inappetence, nausea, vomiting and diarrhea, or with muscle pain, fever, eosinophilia and bronchospasm, in humans acting as final or intermediate hosts, respectively. Moreover, excretion of infective forms with human feces leads to further dissemination of the infection. In this study, macroscopic sarcocysts of white color, oval shape and a size range of approximately 3-5 mm were observed in the skeletal muscle of a slaughtered pig in an abattoir in Makurdi, Benue State, Nigeria, destined to human consumption. Sarcocysts were excised and washed in distilled water, and genomic DNA was extracted using a commercial kit. The near-complete length of the 18S rRNA gene was analyzed after PCR amplification of two overlapping fragments, each of which were submitted to direct sequencing. In addition, the mitochondrial cytochrome oxidase (cox-1) gene was PCR-amplified and directly sequenced. Two phylogenetic trees containing the obtained sequences along with available relevant 18S rRNA and cox-1 sequences were constructed by neighbor joining after alignment, using the corresponding sequences of Toxoplasma gondii as outgroup. The results showed in both cases that the analyzed sequences grouped with S. suihominis with high bootstrap value, confirming the identity of this macroscopic sarcocyst-forming parasite as S. suihominis. To the best of our knowledge, these results represent the first demonstration of this parasite in pigs of Nigeria and the largest sarcocysts described so far for S. suihominis. The close proximity between pigs and humans in pig farms, and the frequent poor sanitary conditions in human dwellings strongly suggest that the parasite undergoes the sexual stages of its life cycle in humans as final hosts. These findings provide an important reference for the examination and control of Sarcocystis species in pigs of Nigeria.

Keywords: nigeria, pork, sarcocystis suihominis, zoonotic parasite

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Authors: Osman Adiguzel

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Shape memory alloys take place in a class of smart materials by exhibiting a peculiar property called the shape memory effect. This property is characterized by the recoverability of two certain shapes of material at different temperatures. These materials are often called smart materials due to their functionality and their capacity of responding to changes in the environment. Shape memory materials are used as shape memory devices in many interdisciplinary fields such as medicine, bioengineering, metallurgy, building industry and many engineering fields. The shape memory effect is performed thermally by heating and cooling after first cooling and stressing treatments, and this behavior is called thermoelasticity. This effect is based on martensitic transformations characterized by changes in the crystal structure of the material. The shape memory effect is the result of successive thermally and stress-induced martensitic transformations. Shape memory alloys exhibit thermoelasticity and superelasticity by means of deformation in the low-temperature product phase and high-temperature parent phase region, respectively. Superelasticity is performed by stressing and releasing the material in the parent phase region. Loading and unloading paths are different in the stress-strain diagram, and the cycling loop reveals energy dissipation. The strain energy is stored after releasing, and these alloys are mainly used as deformation absorbent materials in control of civil structures subjected to seismic events, due to the absorbance of strain energy during any disaster or earthquake. Thermal-induced martensitic transformation occurs thermally on cooling, along with lattice twinning with cooperative movements of atoms by means of lattice invariant shears, and ordered parent phase structures turn into twinned martensite structures, and twinned structures turn into the detwinned structures by means of stress-induced martensitic transformation by stressing the material in the martensitic condition. Thermal induced transformation occurs with the cooperative movements of atoms in two opposite directions, <110 > -type directions on the {110} - type planes of austenite matrix which is the basal plane of martensite. Copper-based alloys exhibit this property in the metastable β-phase region, which has bcc-based structures at high-temperature parent phase field. Lattice invariant shear and twinning is not uniform in copper-based ternary alloys and gives rise to the formation of complex layered structures, depending on the stacking sequences on the close-packed planes of the ordered parent phase lattice. In the present contribution, x-ray diffraction and transmission electron microscopy (TEM) studies were carried out on two copper-based CuAlMn and CuZnAl alloys. X-ray diffraction profiles and electron diffraction patterns reveal that both alloys exhibit superlattice reflections inherited from the parent phase due to the displacive character of martensitic transformation. X-ray diffractograms taken in a long time interval show that diffraction angles and intensities of diffraction peaks change with the aging duration at room temperature. In particular, some of the successive peak pairs providing a special relation between Miller indices come close to each other. This result refers to the rearrangement of atoms in a diffusive manner.

Keywords: shape memory effect, martensitic transformation, reversibility, superelasticity, twinning, detwinning

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Authors: Guillaume Soubeyran, Fabrice Micoud, Benoit Morin, Jean-Philippe Poirot-Crouvezier, Magali Reytier

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Proton Exchange Membrane Fuel Cell (PEMFC) technology is considered as a solution for the reduction of CO2 emissions. However, this technology still meets several challenges for high-scale industrialization. In this context, the increase of durability remains a critical aspect for competitiveness of this technology. Fortunately, performance degradations in nominal operating conditions is partially reversible, meaning that if specific conditions are applied, a partial recovery of fuel cell performance can be achieved, while irreversible degradations can only be mitigated. Thus, it is worth studying the optimal conditions to rejuvenate these reversible degradations and assessing the long-term impact of such procedures on the performance of the cell. Reversible degradations consist mainly of anode Pt active sites poisoning by carbon monoxide at the anode, heterogeneities in water management during use, and oxidation/deactivation of Pt active sites at the cathode. The latter is identified as a major source of reversible performance loss caused by the presence oxygen, high temperature and high cathode potential that favor platinum oxidation, especially in high efficiency operating points. Hence, we studied here a recovery procedure aiming at reducing the platinum oxides by decreasing cathode potential during operation. Indeed, the application of short air starvation phase leads to a drop of cathode potential. Cell performances are temporarily increased afterwards. Nevertheless, local temperature and current heterogeneities within the cells are favored and shall be minimized. The consumption of fuel during the recovery phase shall also be considered to evaluate the global efficiency. Consequently, the purpose of this work is to find an optimal compromise between the recovery of reversible degradations by air starvation, the increase of global cell efficiency and the mitigation of irreversible degradations effects. Different operating parameters have first been studied such as cell voltage, temperature and humidity in single cell set-up. Considering the global PEMFC system efficiency, tests showed that reducing duration of recovery phase and reducing cell voltage was the key to ensure an efficient recovery. Recovery phase frequency was a major factor as well. A specific method was established to find the optimal frequency depending on the duration and voltage of the recovery phase. Then, long-term degradations have also been studied by applying FC-DLC cycles based on NEDC cycles on a 4-cell short stack by alternating test sequences with and without recovery phases. Depending on recovery phase timing, cell efficiency during the cycle was increased up to 2% thanks to a mean voltage increase of 10 mV during test sequences with recovery phases. However, cyclic voltammetry tests results suggest that the implementation of recovery phases causes an acceleration of the decrease of platinum active areas that could be due to the high potential variations applied to the cathode electrode during operation.

Keywords: durability, PEMFC, recovery procedure, reversible degradation

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Authors: Linmin Zhang

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Entrained-flow gasification technology is considered the most promising gasification technology because of its clean and efficient utilization characteristics. The stable fluidity of slag at high temperatures is the key to affecting the long-period operation of the gasifier. The diversity and differences of coal ash-slag systems make it difficult to meet the requirements for stable slagging in entrained-flow gasifiers. Therefore, coal blending or adding fluxes has been used in industry for a long time to improve the flow behavior of coal ash. As a by-product of the indirect coal liquefaction process, indirect coal liquefaction residue (ICLR) is a kind of industrial solid waste that is usually disposed of by stacking or landfilling. However, this disposal method will not only occupy land resources but also cause serious pollution to soil and water bodies by leachate containing toxic and harmful metals. As a carbon-containing matrix, ICLR is not only a kind of waste but also a kind of energy substance. Utilizing existing industrial gasifiers to blend combustion ICLR can not only transform industrial solid waste into fuel but also save coal resources. Moreover, the ICLR usually contains a unique ash chemical composition different from coal, which will affect the slagging performance of the gasifier. Therefore, exploring the effect of the ash addition in ICLR on the coal ash flow behavior can not only improve the slagging performance and gasification efficiency of entrained-flow gasifier by using the unique ash chemical composition of ICLR but also provide some theoretical support for the large-scale consumption of industrial solid waste. Combining molecular dynamics simulation with Raman spectroscopy experiment, the effect of ICLR addition on slag structure and fluidity was explained, and the relationship between the evolution law of slag short/medium range microstructure and macroscopic flow behavior was discussed. The research found that the high silicon and aluminum content in coal ash led to the formation of complex [SiO₄]⁴- tetrahedron and [AlO₄]⁵- tetrahedron structures at high temperature, and the [SiO₄]⁴- tetrahedron and [AlO₄]⁵- tetrahedron were connected by oxygen atoms to form a multi-membered ring structure with high polymerization degree. Due to the action of the multi-membered ring structure, the internal friction in the slag increased, and the viscosity value was higher on the macro-level. As a network-modified ion, Fe2+ could replace Si4+ and Al3+ in the multi-membered ring structure and combine with O2-, which will destroy the bridge oxygen (BO) structure and transform more complex tri cluster oxygen (TO) and bridge oxygen (BO) into simple non-bridge oxygen (NBO) structure. As a result, a large number of multi-membered rings with high polymerization degrees were depolymerized into low-membered rings with low polymerization degrees. The evolution of oxygen types and ring structures in slag reduced the structure complexity and polymerization degree of coal ash slag, resulting in a decrease in the viscosity of coal ash slag.

Keywords: ash slag, coal gasification, fluidity, industrial solid waste, slag structure

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Authors: Ruth Leitch, Joanne Hughes

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This paper presents the findings of a three-year government-funded study (ILiAD) that aimed to understand the reasons for differential educational achievement within and between socially and economically deprived areas in Northern Ireland. Previous international studies have concluded that there is a positive correlation between deprivation and underachievement. Our preliminary secondary data analysis suggested that the factors involved in educational achievement within multiple deprived areas may be more complex than this, with some areas of high multiple deprivation having high levels of student attainment, whereas other less deprived areas demonstrated much lower levels of student attainment, as measured by outcomes on high stakes national tests. The study proposed that no single explanation or disparate set of explanations could easily account for the linkage between levels of deprivation and patterns of educational achievement. Using a social capital perspective that centralizes the connections within and between individuals and social networks in a community as a valuable resource for educational achievement, the ILiAD study involved a multi-level case study analysis of seven community sites in Northern Ireland, selected on the basis of religious composition (housing areas are largely segregated by religious affiliation), measures of multiple deprivation and differentials in educational achievement. The case study approach involved three (interconnecting) levels of qualitative data collection and analysis - what we have termed Micro (or community/grassroots level) understandings, Meso (or school level) explanations and Macro (or policy/structural) factors. The analysis combines a statistical mapping of factors with qualitative, in-depth data interpretation which, together, allow for deeper understandings of the dynamics and contributory factors within and between the case study sites. Thematic analysis of the qualitative data reveals both cross-cutting factors (e.g. demographic shifts and loss of community, place of the school in the community, parental capacity) and analytic case studies of explanatory factors associated with each of the community sites also permit a comparative element. Issues arising from the qualitative analysis are classified either as drivers or inhibitors of educational achievement within and between communities. Key issues that are emerging as inhibitors/drivers to attainment include: the legacy of the community conflict in Northern Ireland, not least in terms of inter-generational stress, related with substance abuse and mental health issues; differing discourses on notions of ‘community’ and ‘achievement’ within/between community sites; inter-agency and intra-agency levels of collaboration and joined-up working; relationship between the home/school/community triad and; school leadership and school ethos. At this stage, the balance of these factors can be conceptualized in terms of bonding social capital (or lack of it) within families, within schools, within each community, within agencies and also bridging social capital between the home/school/community, between different communities and between key statutory and voluntary organisations. The presentation will outline the study rationale, its methodology, present some cross-cutting findings and use an illustrative case study of the findings from a community site to underscore the importance of attending to community differences when trying to engage in research to understand and improve educational attainment for all.

Keywords: educational achievement, multiple deprivation, community case studies, social capital

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Authors: Saeed Abbas, Rahilla Tabassum, Haider Abbas, Babar Khan, Shahid Hussain, Muhammad Zafar Khan, Fazal Karim, Yawar Abbas, Rizwan Karim

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Human–carnivore conflict is considered to be a major conservation and rural livelihood concern because many carnivore species have been heavily victimized due to elevated conflict levels with communities. Like other snow leopard range countries, this situation prevails in Pakistan, where WWF is currently working under Asia High Mountain Project (AHMP) in Gilgit-Baltistan of Pakistan. To mitigate such conflicts requires a firm understanding of grazing and predation pattern including human-carnivore interaction. For this purpose we conducted a survey in Hoper valley (one of the AHMP project sites in Pakistan), during August, 2013 through a questionnaire based survey and unstructured interviews covering 647 households, permanently residing in the project area out of the total 900 households. The valley, spread over 409 km2 between 36°7'46" N and 74°49'2"E, at 2900m asl in Karakoram ranges is considered to be one of an important habitat of snow leopard and associated prey species such as Himalayan ibex. The valley is home of 8100 Brusho people (ancient tribe of Northern Pakistan) dependent on agro-pastoral livelihoods including farming and livestock rearing. The total number of livestock reported were (N=15,481) out of which 8346 (53.91%) were sheep, 3546 (22.91%) goats, 2193 (14.16%) cows, 903 (5.83%) yaks, 508 (3.28%) bulls, 28 (0.18%) donkeys, 27 (0.17%) zo/zomo (cross breed of yak and cow), and 4 (0.03%) horses. 83 percent respondent (n=542 households) confirmed loss of their livestock during the last one year July, 2012 to June, 2013 which account for 2246 (14.51%) animals. The major reason of livestock loss include predation by large carnivores such as snow leopards and wolf (1710, 76.14%) followed by diseases (536, 23.86%). Of the total predation cases snow leopard is suspected to kill 1478 animals (86.43%). Among livestock sheep were found to be the major prey of snow leopard (810, 55%) followed by goats (484, 32.7%) cows (151, 10.21%), yaks (15, 1.015%), zo/zomo (7, 0.5%) and donkey (1, 0.07%). The reason for the mass depredation of sheep and goats is that they tend to browse on twigs of bushes and graze on soft grass near cliffs. They are also considered to be very active as compared to other species in moving quickly and covering more grazing area. This makes them more vulnerable to snow leopard attack. The majority (1283, 75%) of livestock killed by predators occurred during the warm season (May-September) in alpine and sub-alpine pastures and remaining (427, 25%) occurred in the winter season near settlements in valley. It was evident from the recent study that Snow leopard kills outside the pen were (1351, 79.76%) as compared to inside pen (359, 20.24%). Assessing the economic loss of livestock predation we found that the total loss of livestock predation in the study area is equal to PKR 11,230,000 (USD 105,797), which is about PRK 17, 357 (USD 163.51) per household per year. Economic loss incurred by the locals due to predation is quite significant where the average cash income per household per year is PKR 85,000 (USD 800.75).

Keywords: carnivores, conflict, predation, livelihood, conservation, rural, snow leopard, livestock

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Authors: Tshimangadzo Jeanette Raedani, Edgar Musie, Afsatou Traore

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Background: Street-vended meats, including chicken, pork, and beef, are popular in urban areas worldwide due to their convenience and affordability. However, these meats often pose a significant risk of foodborne diseases. The high water activity, protein content, and nearly neutral pH of meat create conditions conducive to the growth of pathogenic bacteria. Street foods, particularly meats, are frequently linked to outbreaks of foodborne illnesses due to potential contamination from improper handling and preparation. This study aimed to assess the microbial quality and safety of street-vended ready-to-eat meat sold in the Thohoyandou area. Method: The study involved collecting 168 samples of street-vended meat, split evenly between chicken (n=84) and beef (n=84), from various vendors around Thohoyandou. The samples were randomly selected and transported in sterile conditions to the Department of Food Microbiology at the University of Venda for analysis. Each 10-gram sample was cultured in selective media: MSA for Staphylococcus aureus, EMB for E. coli O157, XLD agar for Salmonella, and Sorbitol McConkey for Shigella. After initial culturing, the presumptive colonies were sub-cultured for purification and identified through Gram staining and biochemical tests, including Catalase, API 20E, Klingler Iron Agar Test, and Vitek 2 system. Antibiotic susceptibility was tested using agents such as Ampicillin, Chloramphenicol, Penicillin, Neomycin, Tetracycline, Streptomycin, and Amoxicillin. Molecular characterization was performed to identify E. coli pathotypes using multiplex PCR. Results: Out of 168 samples tested, 32 (19%) were positive for Staphylococcus spp., with the highest prevalence found in cooked chicken meat. The most common staphylococcus species identified were S. xylosus (13.2%) and S. saprophyticus (10.5%). E. coli was present in 29 (19.3%) of the samples, with the highest prevalence in fried chicken. Antibiotic susceptibility testing showed that 100% of E. coli isolates were resistant to Ampicillin, Tetracycline, and Penicillin, but 100% were susceptible to Neomycin. Staphylococcus spp. isolates were also 100% resistant to Ampicillin and 100% susceptible to Neomycin. The study detected a range of virulence genes in E. coli, with prevalence rates from 13.33% to 86.67%. The identified pathotypes included EPEC, EHEC, ETEC, EAEC, and EIEC, with many isolates showing mixed pathotypes. Conclusion: The study highlighted that the microbial quality and safety of street-vended meats in Thohoyandou are inadequate, rendering them unsafe for consumption. The presence of pathogenic microorganisms in both beef and chicken samples indicates significant risks associated with poor personal hygiene and food preparation practices. This underscores the need for improved monitoring and stricter food safety measures to prevent foodborne diseases and ensure consumer safety.

Keywords: meat, microbial analysis, street vendors, E. coli

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Authors: Mazaher Yarmohamadi-Vasel, Ali Reza Modarresi-Alama, Sahar Shabzendedara

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Purpose/Objectives: The first purpose was synthesize Poly(N-(sulfophenyl)aniline) nanoflowers (PSANFLs) and Poly(N-(sulfophenyl)aniline) nanofibers/titanium dioxide nanoparticles ((PSANFs/TiO2NPs) by a solid-state mechano-chemical reaction and template-free method and use them in hybrid solar cell. Also, our second aim was to increase the solubility and the processability of conjugated nanomaterials in water through polar functionalized materials. poly[N-(4-sulfophenyl)aniline] is easily soluble in water because of the presence of polar groups of sulfonic acid in the polymer chain. Materials/Methods: Iron (III) chloride hexahydrate (FeCl3∙6H2O) were bought from Merck Millipore Company. Titanium oxide nanoparticles (TiO2, <20 nm, anatase) and Sodium diphenylamine-4-sulfonate (99%) were bought from Sigma-Aldrich Company. Titanium dioxide nanoparticles paste (PST-20T) was prepared from Sharifsolar Co. Conductive glasses coated with indium tin oxide (ITO) were bought from Xinyan Technology Co (China). For the first time we used the solid-state mechano-chemical reaction and template-free method to synthesize Poly(N-(sulfophenyl)aniline) nanoflowers. Moreover, for the first time we used the same technique to synthesize nanocomposite of Poly(N-(sulfophenyl)aniline) nanofibers and titanium dioxide nanoparticles (PSANFs/TiO2NPs) also for the first time this nanocomposite was synthesized. Examining the results of electrochemical calculations energy gap obtained by CV curves and UV–vis spectra demonstrate that PSANFs/TiO2NPs nanocomposite is a p-n type material that can be used in photovoltaic cells. Doctor blade method was used to creat films for three kinds of hybrid solar cells in terms of different patterns like ITO│TiO2NPs│Semiconductor sample│Al. In the following, hybrid photovoltaic cells in bilayer and bulk heterojunction structures were fabricated as ITO│TiO2NPs│PSANFLs│Al and ITO│TiO2NPs│PSANFs /TiO2NPs│Al, respectively. Fourier-transform infrared spectra, field emission scanning electron microscopy (FE-SEM), ultraviolet-visible spectra, cyclic voltammetry (CV) and electrical conductivity were the analysis that used to characterize the synthesized samples. Results and Conclusions: FE-SEM images clearly demonstrate that the morphology of the synthesized samples are nanostructured (nanoflowers and nanofibers). Electrochemical calculations of band gap from CV curves demonstrated that the forbidden band gap of the PSANFLs and PSANFs/TiO2NPs nanocomposite are 2.95 and 2.23 eV, respectively. I–V characteristics of hybrid solar cells and their power conversion efficiency (PCE) under 100 mWcm−2 irradiation (AM 1.5 global conditions) were measured that The PCE of the samples were 0.30 and 0.62%, respectively. At the end, all the results of solar cell analysis were discussed. To sum up, PSANFLs and PSANFLs/TiO2NPs were successfully synthesized by an affordable and straightforward mechanochemical reaction in solid-state under the green condition. The solubility and processability of the synthesized compounds have been improved compared to the previous work. We successfully fabricated hybrid photovoltaic cells of synthesized semiconductor nanostructured polymers and TiO2NPs as different architectures. We believe that the synthesized compounds can open inventive pathways for the development of other Poly(N-(sulfophenyl)aniline based hybrid materials (nanocomposites) proper for preparing new generation solar cells.

Keywords: mechanochemical synthesis, PSANFLs, PSANFs/TiO2NPs, solar cell

Procedia PDF Downloads 67

Authors: I. Stathopoulos, V. Syrgiamiotis, E. Karavasilis, A. Ploussi, I. Nikas, C. Hatzigiorgi, K. Platoni, E. P. Efstathopoulos

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Introduction: Brain and central nervous system (CNS) tumors form the second most common group of cancer in children, accounting for 30% of all childhood cancers. MRI is the key imaging technique used for the visualization and management of pediatric brain tumors. Initial characterization of tumors from MRI scans is usually performed via a radiologist’s visual assessment. However, different brain tumor types do not always demonstrate clear differences in visual appearance. Using only conventional MRI to provide a definite diagnosis could potentially lead to inaccurate results, and so histopathological examination of biopsy samples is currently considered to be the gold standard for obtaining definite diagnoses. Machine learning is defined as the study of computational algorithms that can use, complex or not, mathematical relationships and patterns from empirical and scientific data to make reliable decisions. Concerning the above, machine learning techniques could provide effective and accurate ways to automate and speed up the analysis and diagnosis for medical images. Machine learning applications in radiology are or could potentially be useful in practice for medical image segmentation and registration, computer-aided detection and diagnosis systems for CT, MR or radiography images and functional MR (fMRI) images for brain activity analysis and neurological disease diagnosis. Purpose: The objective of this study is to provide an automated tool, which may assist in the imaging evaluation and classification of brain neoplasms in pediatric patients by determining the glioma type, grade and differentiating between different brain tissue types. Moreover, a future purpose is to present an alternative way of quick and accurate diagnosis in order to save time and resources in the daily medical workflow. Materials and Methods: A cohort, of 80 pediatric patients with a diagnosis of posterior fossa tumor, was used: 20 ependymomas, 20 astrocytomas, 20 medulloblastomas and 20 healthy children. The MR sequences used, for every single patient, were the following: axial T1-weighted (T1), axial T2-weighted (T2), FluidAttenuated Inversion Recovery (FLAIR), axial diffusion weighted images (DWI), axial contrast-enhanced T1-weighted (T1ce). From every sequence only a principal slice was used that manually traced by two expert radiologists. Image acquisition was carried out on a GE HDxt 1.5-T scanner. The images were preprocessed following a number of steps including noise reduction, bias-field correction, thresholding, coregistration of all sequences (T1, T2, T1ce, FLAIR, DWI), skull stripping, and histogram matching. A large number of features for investigation were chosen, which included age, tumor shape characteristics, image intensity characteristics and texture features. After selecting the features for achieving the highest accuracy using the least number of variables, four machine learning classification algorithms were used: k-Nearest Neighbour, Support-Vector Machines, C4.5 Decision Tree and Convolutional Neural Network. The machine learning schemes and the image analysis are implemented in the WEKA platform and MatLab platform respectively. Results-Conclusions: The results and the accuracy of images classification for each type of glioma by the four different algorithms are still on process.

Keywords: image classification, machine learning algorithms, pediatric MRI, pediatric oncology

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Authors: S. Dalvi, N. Sane, V. Patil, D. Bansode, A. Tharakan, V. Mathur

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Measurement of routine clinical electrolyte tests is common in labs worldwide for screening of illness or diseases. All the analyzers for the measurement of electrolyte parameters have sensors, reagents, sampler, pump tubing, valve, other tubing’s separate that are either expensive, require heavy maintenance and have a short shelf-life. Moreover, the costs required to maintain such Lab instrumentation is high and this limits the use of the device to only highly specialized personnel and sophisticated labs. In order to provide Healthcare Diagnostics to ALL at affordable costs, there is a need for an All-in-one Universal Modular Cartridge that contains sensors, reagents, sampler, valve, pump tubing, and other tubing’s in one single integrated module-in-module cartridge that is affordable, reliable, easy-to-use, requires very low sample volume and is truly modular and maintenance-free. DiaSys India has developed a World’s first, Patent Pending, Versatile All-in-one Universal Module-in-Module Cartridge based Electrolyte Analyzer (QDx InstaLyte) that can perform sodium, potassium, chloride, calcium, pH, lithium tests. QDx InstaLyte incorporates High Performance, Inexpensive All-in-one Universal Cartridge for rapid quantitative measurement of electrolytes in body fluids. Our proposed methodology utilizes Advanced & Improved long life ISE sensors to provide a sensitive and accurate result in 120 sec with just 100 µl of sample volume. The All-in-One Universal Cartridge has a very low reagent consumption capable of maximum of 1000 tests with a Use-life of 3-4 months and a long Shelf life of 12-18 months at 4-25°C making it very cost-effective. Methods: QDx InstaLyte analyzers with All-in-one Universal Modular Cartridges were independently evaluated with three R&D lots for Method Performance (Linearity, Precision, Method Comparison, Cartridge Stability) to measure Sodium, Potassium, Chloride. Method Comparison was done against Medica EasyLyte Plus Na/K/Cl Electrolyte Analyzer, a mid-size lab based clinical chemistry analyzer with N = 100 samples run over 10 days. Within-run precision study was done using modified CLSI guidelines with N = 20 samples and day-to-day precision study was done for 7 consecutive days using Trulab N & P Quality Control Samples. Accelerated stability testing was done at 45oC for 4 weeks with Production Lots. Results: Data analysis indicates that the CV for within-run precision for Na is ≤ 1%, for K is ≤2%, and for Cl is ≤2% and with R2 ≥ 0.95 for Method Comparison. Further, the All-in-One Universal Cartridge is stable up to 12-18 months at 4-25oC storage temperature based on preliminary extrapolated data. Conclusion: The Developed Technology Platform of All-in-One Universal Module-in-Module Cartridge based QDx InstaLyte is Reliable and meets all the performance specifications of the lab and is Truly Modular and Maintenance-Free. Hence, it can be easily adapted for low cost, sensitive and rapid measurement of electrolyte tests in low resource settings such as in urban, semi-urban and rural areas in the developing countries and can be used as a Point-of-care testing system for worldwide applications.

Keywords: all-in-one modular catridge, electrolytes, maintenance free, QDx instalyte

Procedia PDF Downloads 31

Authors: Hamda M. Al-Ali

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The ultimate aim of space exploration has been centralized around the possibility of life on other planets in the solar system. This aim is driven by the detrimental effects that climate change could potentially have on human survival on Earth in the future. This drives humans to search for feasible solutions to increase environmental and economical sustainability on Earth and to evaluate and explore the ability of human survival on other planets such as Mars. To do that, frequent space missions are required to meet the ambitious human goals. This means that reliable and affordable access to space is required, which could be largely achieved through the use of reusable spacecrafts. Therefore, materials and resources must be used wisely to meet the increasing demand. Space missions are currently extremely expensive to operate. However, reusing materials hence spacecrafts, can potentially reduce overall mission costs as well as the negative impact on both space and Earth environments. This is because reusing materials leads to less waste generated per mission, and therefore fewer landfill sites are required. Reusing materials reduces resource consumption, material production, and the need for processing new and replacement spacecraft and launch vehicle parts. Consequently, this will ease and facilitate human access to outer space as it will reduce the demand for scarce resources, which will boost material efficiency in the space industry. Material efficiency expresses the extent to which resources are consumed in the production cycle and how the waste produced by the industrial process is minimized. The strategies proposed in this paper to boost material efficiency in the space sector are the introduction of key performance indicators that are able to measure material efficiency as well as the introduction of clearly defined policies and legislation that can be easily implemented within the general practices in the space industry. Another strategy to improve material efficiency is by amplifying energy and resource efficiency through reusing materials. The circularity of various spacecraft materials such as Kevlar, steel, and aluminum alloys could be maximized through reusing them directly or after galvanizing them with another layer of material to act as a protective coat. This research paper has an aim to investigate and discuss how to improve material efficiency in space missions considering circular economy concepts so that space and Earth become more economically and environmentally sustainable. The circular economy is a transition from a make-use-waste linear model to a closed-loop socio-economic model, which is regenerative and restorative in nature. The implementation of a circular economy will reduce waste and pollution through maximizing material efficiency, ensuring that businesses can thrive and sustain. Further research into the extent to which reusable launch vehicles reduce space mission costs have been discussed, along with the environmental and economic implications it could have on the space sector and the environment. This has been examined through research and in-depth literature review of published reports, books, scientific articles, and journals. Keywords such as material efficiency, circular economy, reusable launch vehicles and spacecraft materials were used to search for relevant literature.

Keywords: circular economy, key performance indicator, material efficiency, reusable launch vehicles, spacecraft materials

Procedia PDF Downloads 125

Authors: K. S. Poutanen, P. Dussort, A. Erkner, S. Fiszman, K. Karnik, M. Kristensen, C. F. M. Marsaux, S. Miquel-Kergoat, S. Pentikäinen, P. Putz, R. E. Steinert, J. Slavin, D. J. Mela

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Dietary fiber (DF) intake has been associated with lower body weight or less weight gain. These effects are generally attributed to putative effects of DF on appetite. Many intervention studies have tested the effect of DFs on appetite-related measures, with inconsistent results. However, DF includes a wide category of different compounds with diverse chemical and physical characteristics, and correspondingly diverse effects in human digestion. Thus, inconsistent results between DF consumption and appetite are not surprising. The specific contribution of different compounds with varying physico-chemical properties to appetite control and the mediating mechanisms are not well characterized. This systematic review aimed to assess the influence of specific DF characteristics, including viscosity, gel forming capacity, fermentability, and molecular weight, on appetite-related outcomes in healthy humans. Medline and FSTA databases were searched for controlled human intervention trials, testing the effects of well-characterized DFs on subjective satiety/appetite or energy intake outcomes. Studies were included only if they reported: 1) fiber name and origin, and 2) data on viscosity, gelling properties, fermentability, or molecular weight of the DF materials tested. The search generated 3001 unique records, 322 of which were selected for further consideration from title and abstract screening. Of these, 149 were excluded due to insufficient fiber characterization and 124 for other reasons (not original article, not randomized controlled trial, or no appetite related outcome), leaving 49 papers meeting all the inclusion criteria, most of which reported results from acute testing (<1 day). The eligible 49 papers described 90 comparisons of DFs in foods, beverages or supplements. DF-containing material of interest was efficacious for at least one appetite-related outcome in 51/90 comparisons. Gel-forming DF sources were most consistently efficacious but there were no clear associations between viscosity, MW or fermentability and appetite-related outcomes. A considerable number of papers had to be excluded from the review due to shortcomings in fiber characterization. To build understanding about the impact of DF on satiety/appetite specifically there should be clear hypotheses about the mechanisms behind the proposed beneficial effect of DF material on appetite, and sufficient data about the DF properties relevant for the hypothesized mechanisms to justify clinical testing. The hypothesized mechanisms should also guide the decision about relevant duration of exposure in studies, i.e. are the effects expected to occur during acute time frame (related to stomach emptying, digestion rate, etc.) or develop from sustained exposure (gut fermentation mediated mechanisms). More consistent measurement methods and reporting of fiber specifications and characterization are needed to establish reliable structure-function relationships for DF and health outcomes.

Keywords: appetite, dietary fiber, physico-chemical properties, satiety

Procedia PDF Downloads 235

Authors: A. Shahriari, M. Khalatbari Jafari, M. Faridi

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Abstract The Muradlu volcanic area is located in Azerbaijan province, NW Iran. The studied area exposed in a vast region includes lesser Caucasus, Southeastern Turkey, and northwestern Iran, comprising Cenozoic volcanic and plutonic massifs. The geology of this extended region was under the influence of the Alpine-Himalayan orogeny. Cenozoic magmatic activities in this vast region evolved through the northward subduction of the Neotethyan subducted slab and subsequence collision of the Arabian and Eurasian plates. Based on stratigraphy and paleontology data, most of the volcanic activities in the Muradlu area occurred in the Eocene period. The Studied volcanic rocks overly late Cretaceous limestone with disconformity. The volcanic sequence includes thick epiclastic and hyaloclastite breccia at the base, laterally changed to pillow lava and continued by hyaloclastite and lave flows at the top of the series. The lava flows display different textures from megaporphyric-phyric to fluidal and microlithic textures. The studied samples comprise picrobasalt basalt, tephrite basanite, trachybasalt, basaltic trachyandesite, phonotephrite, tephrophonolite, trachyandesite, and trachyte in compositions. Some xenoliths with lherzolitic composition are found in picrobasalt. These xenoliths are made of olivine, cpx (diopside), and opx (enstatite), probably the remain of mantle origin. Some feldspathoid minerals such as sodalite presence in the phonotephrite confirm an alkaline trend. Two types of augite phenocrysts are found in picrobasalt, basalt and trachybasalt. The first types are shapeless, with disharmony zoning and sponge texture with reaction edges probably resulted from sodic magma, which is affected by a potassic magma. The second shows a glomerocryst shape. In discriminative diagrams, the volcanic rocks show alkaline-shoshonitic trends. They contain (0.5-7.7) k2O values and plot in the shoshonitic field. Most of the samples display transitional to potassic alkaline trends, and some samples reveal sodic alkaline trends. The transitional trend probably results from the mixing of the sodic alkaline and potassic magmas. The Rare Earth Elements (REE) patterns and spider diagrams indicate enrichment of Large-Ione Lithophile Element (LILE) and depletion of High Field Strength Elements (HFSE) relative to Heavy Rare Earth Elements (HREE). Enrichment of K, Rb, Sr, Ba, Zr, Th, and U and the enrichment of Light Rare Earth Elements (LREE) relative to Heavy Rare Earth Elements (HREE) indicate the effect of subduction-related fluids over the mantle source, which has been reported in the arc and continental collision zones. The studied samples show low Nb/La ratios. Our studied samples plot in the lithosphere and lithosphere-asthenosphere fields in the Nb/La versus La/Yb ratios diagram. These geochemical characters allow us to conclude that a lithospheric mantle source previously metasomatized by subduction components was the origin of the Muradlu volcanic rocks.

Keywords: alkaline, asthenosphere, lherzolite, lithosphere, Muradlu, potassic, shoshonitic, sodic, volcanism

Procedia PDF Downloads 171

Authors: Inese Trusina, Elita Jermolajeva, Viktors Gopejenko, Viktor Abramov

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Global challenges require a transition from the existing linear economic model to a model that will consider nature as a life support system for the development of the way to social well-being in the frame of the ecological economics paradigm. The objective of the article is to present the results of the analysis of socio-economic systems in the context of sustainable development using the systems power (energy flows) changes analyzing method and structural Kaldor's model of GDP. In accordance with the principles of life's development and the ecological concept was formalized the tasks of sustainable development of the open, non-equilibrium, stable socio-economic systems were formalized using the energy flows analysis method. The methodology of monitoring sustainable development and level of life were considered during the research of interactions in the system ‘human - society - nature’ and using the theory of a unified system of space-time measurements. Based on the results of the analysis, the time series consumption energy and economic structural model were formulated for the level, degree and tendencies of sustainable development of the system and formalized the conditions of growth, degrowth and stationarity. In order to design the future state of socio-economic systems, a concept was formulated, and the first models of energy flows in systems were created using the tools of system dynamics. During the research, the authors calculated and used a system of universal indicators of sustainable development in the invariant coordinate system in energy units. In order to design the future state of socio-economic systems, a concept was formulated, and the first models of energy flows in systems were created using the tools of system dynamics. In the context of the proposed approach and methods, universal sustainable development indicators were calculated as models of development for the USA and China. The calculations used data from the World Bank database for the period from 1960 to 2019. Main results: 1) In accordance with the proposed approach, the heterogeneous energy resources of countries were reduced to universal power units, summarized and expressed as a unified number. 2) The values of universal indicators of the life’s level were obtained and compared with generally accepted similar indicators.3) The system of indicators in accordance with the requirements of sustainable development can be considered as a basis for monitoring development trends. This work can make a significant contribution to overcoming the difficulties of forming socio-economic policy, which is largely due to the lack of information that allows one to have an idea of the course and trends of socio-economic processes. The existing methods for the monitoring of the change do not fully meet this requirement since indicators have different units of measurement from different areas and, as a rule, are the reaction of socio-economic systems to actions already taken and, moreover, with a time shift. Currently, the inconsistency or inconsistency of measures of heterogeneous social, economic, environmental, and other systems is the reason that social systems are managed in isolation from the general laws of living systems, which can ultimately lead to a systemic crisis.

Keywords: sustainability, system dynamic, power, energy flows, development

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Authors: Zachary Blanks, Solomon Sonya

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Poaching presents a serious threat to endangered animal species, environment conservations, and human life. Additionally, some poaching activity has even been linked to supplying funds to support terrorist networks elsewhere around the world. Consequently, agencies dedicated to protecting wildlife habitats have a near intractable task of adequately patrolling an entire area (spanning several thousand kilometers) given limited resources, funds, and personnel at their disposal. Thus, agencies need predictive tools that are both high-performing and easily implementable by the user to help in learning how the significant features (e.g. animal population densities, topography, behavior patterns of the criminals within the area, etc) interact with each other in hopes of abating poaching. This research develops a classification model using machine learning algorithms to aid in forecasting future attacks that is both easy to train and performs well when compared to other models. In this research, we demonstrate how data imputation methods (specifically predictive mean matching, gradient boosting, and random forest multiple imputation) can be applied to analyze data and create significant predictions across a varied data set. Specifically, we apply these methods to improve the accuracy of adopted prediction models (Logistic Regression, Support Vector Machine, etc). Finally, we assess the performance of the model and the accuracy of our data imputation methods by learning on a real-world data set constituting four years of imputed data and testing on one year of non-imputed data. This paper provides three main contributions. First, we extend work done by the Teamcore and CREATE (Center for Risk and Economic Analysis of Terrorism Events) research group at the University of Southern California (USC) working in conjunction with the Department of Homeland Security to apply game theory and machine learning algorithms to develop more efficient ways of reducing poaching. This research introduces ensemble methods (Random Forests and Stochastic Gradient Boosting) and applies it to real-world poaching data gathered from the Ugandan rain forest park rangers. Next, we consider the effect of data imputation on both the performance of various algorithms and the general accuracy of the method itself when applied to a dependent variable where a large number of observations are missing. Third, we provide an alternate approach to predict the probability of observing poaching both by season and by month. The results from this research are very promising. We conclude that by using Stochastic Gradient Boosting to predict observations for non-commercial poaching by season, we are able to produce statistically equivalent results while being orders of magnitude faster in computation time and complexity. Additionally, when predicting potential poaching incidents by individual month vice entire seasons, boosting techniques produce a mean area under the curve increase of approximately 3% relative to previous prediction schedules by entire seasons.

Keywords: ensemble methods, imputation, machine learning, random forests, statistical analysis, stochastic gradient boosting, wildlife protection

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Authors: Rosimeire Araújo Silva, Philip Martin Fearnside

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Extreme droughts and floods in the Amazon have serious consequences for natural ecosystems and the human population in the region. The frequency of these events has increased in recent years, and projections of climate change predict greater frequency and intensity of these events. Understanding the links between these extreme events and different patterns of sea surface temperature in the Atlantic and Pacific Oceans is essential, both to improve the modeling of climate change and its consequences and to support efforts of adaptation in the region. The relationship between sea temperatures and events in the Amazon is much more complex than is usually assumed in climatic models. Warming and cooling of different parts of the oceans, as well as the interaction between simultaneous temperature changes in different parts of each ocean and between the two oceans, have specific consequences for the Amazon, with effects on precipitation that vary in different parts of the region. Simplistic generalities, such as the association between El Niño events and droughts in the Amazon, do not capture this complexity. We investigated the variability of Sea Surface Temperature (SST) in the Tropical Pacific Ocean during the period 1950-2022, using Empirical Orthogonal Functions (FOE), spectral analysis coherence and wavelet phase. The two were identified as the main modes of variability, which explain about 53,9% and 13,3%, respectively, of the total variance of the data. The spectral and coherence analysis and wavelets phase showed that the first selected mode represents the warming in the central part of the Pacific Ocean (the “Central El Niño”), while the second mode represents warming in the eastern part of the Pacific (the “Eastern El Niño The effects of the 1982-1983 and 1976-1977 El Niño events in the Amazon, although both events were characterized by an increase in sea surface temperatures in the Equatorial Pacific, the impact on rainfall in the Amazon was distinct. In the rainy season, from December to March, the sub-basins of the Japurá, Jutaí, Jatapu, Tapajós, Trombetas and Xingu rivers were the regions that showed the greatest reductions in rainfall associated with El Niño Central (1982-1983), while the sub-basins of the Javari, Purus, Negro and Madeira rivers had the most pronounced reductions in the year of Eastern El Niño (1976-1977). In the transition to the dry season, in April, the greatest reductions were associated with the Eastern El Niño year for the majority of the study region, with the exception only of the sub-basins of the Madeira, Trombetas and Xingu rivers, which had their associated reductions to Central El Niño. In the dry season from July to September, the sub-basins of the Japurá Jutaí Jatapu Javari Trombetas and Madeira rivers were the rivers that showed the greatest reductions in rainfall associated with El Niño Central, while the sub-basins of the Tapajós Purus Negro and Xingu rivers had the most pronounced reductions. In the Eastern El Niño year this season. In this way, it is possible to conclude that the Central (Eastern) El Niño controlled the reductions in soil moisture in the dry (rainy) season for all sub-basins shown in this study. Extreme drought events associated with these meteorological phenomena can lead to a significant increase in the occurrence of forest fires. These fires have a devastating impact on Amazonian vegetation, resulting in the irreparable loss of biodiversity and the release of large amounts of carbon stored in the forest, contributing to the increase in the greenhouse effect and global climate change.

Keywords: sea surface temperature, variability, climate, Amazon

Procedia PDF Downloads 63

Authors: Esmael Makarian, Ayub Elyasi, Fatemeh Saberi, Olusegun Stanley Tomomewo

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Rock mechanical investigation is one of the most crucial activities in underground operations, especially in surveys related to hydrocarbon exploration and production, geothermal reservoirs, energy storage, mining, and geotechnics. There is a wide range of traditional methods for driving, collecting, and analyzing rock mechanics data. However, these approaches may not be suitable or work perfectly in some situations, such as fractured zones. Cutting-edge technologies have been provided to solve and optimize the mentioned issues. Internet of Things (IoT), Edge, and Cloud Computing technologies (ECt & CCt, respectively) are among the most widely used and new artificial intelligence methods employed for geomechanical studies. IoT devices act as sensors and cameras for real-time monitoring and mechanical-geological data collection of rocks, such as temperature, movement, pressure, or stress levels. Structural integrity, especially for cap rocks within hydrocarbon systems, and rock mass behavior assessment, to further activities such as enhanced oil recovery (EOR) and underground gas storage (UGS), or to improve safety risk management (SRM) and potential hazards identification (P.H.I), are other benefits from IoT technologies. EC techniques can process, aggregate, and analyze data immediately collected by IoT on a real-time scale, providing detailed insights into the behavior of rocks in various situations (e.g., stress, temperature, and pressure), establishing patterns quickly, and detecting trends. Therefore, this state-of-the-art and useful technology can adopt autonomous systems in rock mechanical surveys, such as drilling and production (in hydrocarbon wells) or excavation (in mining and geotechnics industries). Besides, ECt allows all rock-related operations to be controlled remotely and enables operators to apply changes or make adjustments. It must be mentioned that this feature is very important in environmental goals. More often than not, rock mechanical studies consist of different data, such as laboratory tests, field operations, and indirect information like seismic or well-logging data. CCt provides a useful platform for storing and managing a great deal of volume and different information, which can be very useful in fractured zones. Additionally, CCt supplies powerful tools for predicting, modeling, and simulating rock mechanical information, especially in fractured zones within vast areas. Also, it is a suitable source for sharing extensive information on rock mechanics, such as the direction and size of fractures in a large oil field or mine. The comprehensive review findings demonstrate that digital transformation through integrated IoT, Edge, and Cloud solutions is revolutionizing traditional rock mechanical investigation. These advanced technologies have empowered real-time monitoring, predictive analysis, and data-driven decision-making, culminating in noteworthy enhancements in safety, efficiency, and sustainability. Therefore, by employing IoT, CCt, and ECt, underground operations have experienced a significant boost, allowing for timely and informed actions using real-time data insights. The successful implementation of IoT, CCt, and ECt has led to optimized and safer operations, optimized processes, and environmentally conscious approaches in underground geological endeavors.

Keywords: rock mechanical studies, internet of things, edge computing, cloud computing, underground surveys, geological operations

Procedia PDF Downloads 62

Authors: Oibar Martinez, Clara Oliver

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The Cherenkov Telescope Array Project (CTA) aims to build two different observatories of Cherenkov Telescopes, located in Cerro del Paranal, Chile, and La Palma, Spain. These facilities are used in this paper as a case study to investigate how to apply standard Directives on Electromagnetic Compatibility to astronomical observatories. Cherenkov Telescopes are able to provide valuable information from both Galactic and Extragalactic sources by measuring Cherenkov radiation, which is produced by particles which travel faster than light in the atmosphere. The construction requirements demand compliance with the European Electromagnetic Compatibility Directive. The largest telescopes of these observatories, called Large Scale Telescopes (LSTs), are high precision instruments with advanced photomultipliers able to detect the faint sub-nanosecond blue light pulses produced by Cherenkov Radiation. They have a 23-meter parabolic reflective surface. This surface focuses the radiation on a camera composed of an array of high-speed photosensors which are highly sensitive to the radio spectrum pollution. The camera has a field of view of about 4.5 degrees and has been designed for maximum compactness and lowest weight, cost and power consumption. Each pixel incorporates a photo-sensor able to discriminate single photons and the corresponding readout electronics. The first LST is already commissioned and intends to be operated as a service to Scientific Community. Because of this, it must comply with a series of reliability and functional requirements and must have a Conformité Européen (CE) marking. This demands compliance with Directive 2014/30/EU on electromagnetic compatibility. The main difficulty of accomplishing this goal resides on the fact that Conformité Européen marking setups and procedures were implemented for industrial products, whereas no clear protocols have been defined for scientific installations. In this paper, we aim to give an answer to the question on how the directive should be applied to our installation to guarantee the fulfillment of all the requirements and the proper functioning of the telescope itself. Experts in Optics and Electromagnetism were both needed to make these kinds of decisions and match tests which were designed to be made over the equipment of limited dimensions on large scientific plants. An analysis of the elements and configurations most likely to be affected by external interferences and those that are most likely to cause the maximum disturbances was also performed. Obtaining the Conformité Européen mark requires knowing what the harmonized standards are and how the elaboration of the specific requirement is defined. For this type of large installations, one needs to adapt and develop the tests to be carried out. In addition, throughout this process, certification entities and notified bodies play a key role in preparing and agreeing the required technical documentation. We have focused our attention mostly on the technical aspects of each point. We believe that this contribution will be of interest for other scientists involved in applying industrial quality assurance standards to large scientific plant.

Keywords: CE marking, electromagnetic compatibility, european directive, scientific installations

Procedia PDF Downloads 110

Authors: R. Yuan, S. Sivasankaran, N. Dutta, K. Ebrahimi

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This paper investigates the software capability and computer-aided engineering (CAE) method of modelling transient heat transfer process occurred in the vehicle underhood region during vehicle thermal soak phase. The heat retention from the soak period will be beneficial to the cold start with reduced friction loss for the second 14°C worldwide harmonized light-duty vehicle test procedure (WLTP) cycle, therefore provides benefits on both CO₂ emission reduction and fuel economy. When vehicle undergoes soak stage, the airflow and the associated convective heat transfer around and inside the engine bay is driven by the buoyancy effect. This effect along with thermal radiation and conduction are the key factors to the thermal simulation of the engine bay to obtain the accurate fluids and metal temperature cool-down trajectories and to predict the temperatures at the end of the soak period. Method development has been investigated in this study on a light-duty passenger vehicle using coupled aerodynamic-heat transfer thermal transient modelling method for the full vehicle under 9 hours of thermal soak. The 3D underhood flow dynamics were solved inherently transient by the Lattice-Boltzmann Method (LBM) method using the PowerFlow software. This was further coupled with heat transfer modelling using the PowerTHERM software provided by Exa Corporation. The particle-based LBM method was capable of accurately handling extremely complicated transient flow behavior on complex surface geometries. The detailed thermal modelling, including heat conduction, radiation, and buoyancy-driven heat convection, were integrated solved by PowerTHERM. The 9 hours cool-down period was simulated and compared with the vehicle testing data of the key fluid (coolant, oil) and metal temperatures. The developed CAE method was able to predict the cool-down behaviour of the key fluids and components in agreement with the experimental data and also visualised the air leakage paths and thermal retention around the engine bay. The cool-down trajectories of the key components obtained for the 9 hours thermal soak period provide vital information and a basis for the further development of reduced-order modelling studies in future work. This allows a fast-running model to be developed and be further imbedded with the holistic study of vehicle energy modelling and thermal management. It is also found that the buoyancy effect plays an important part at the first stage of the 9 hours soak and the flow development during this stage is vital to accurately predict the heat transfer coefficients for the heat retention modelling. The developed method has demonstrated the software integration for simulating buoyancy-driven heat transfer in a vehicle underhood region during thermal soak with satisfying accuracy and efficient computing time. The CAE method developed will allow integration of the design of engine encapsulations for improving fuel consumption and reducing CO₂ emissions in a timely and robust manner, aiding the development of low-carbon transport technologies.

Keywords: ATCT/WLTC driving cycle, buoyancy-driven heat transfer, CAE method, heat retention, underhood modeling, vehicle thermal soak

Procedia PDF Downloads 153

Authors: Alessandra Panico, Francesco Bagordo, Tiziana Grassi, Adele Idolo, Marcello Guido, Francesca Serio, Mattia De Giorgi, Antonella De Donno

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In the Province of Lecce (Southeastern Italy) an area with unusual high incidence of chronic respiratory diseases, including lung cancer, was recently identified. The causes of this health emergency are still not entirely clear. In order to determine the risk profile of children living in five municipalities included in this area an epidemiological-molecular study was performed in the years 2014-2016: the IMP.AIR. (Impact of air quality on health of residents in the Municipalities of Sternatia, Galatina, Cutrofiano, Sogliano Cavour and Soleto) study. 122 children aged 6-8 years attending primary school in the study area were enrolled to evaluate the frequency of micronuclei (MNs) in their buccal exfoliated cells. The samples were collected in May 2015 by rubbing the oral mucosa with a soft bristle disposable toothbrush. At the same time, a validated questionnaire was administered to parents to obtain information about health, lifestyle and eating habits of the children. In addition, information on airborne pollutants, routinely detected by the Regional Environmental Agency (ARPA Puglia) in the study area, was acquired. A multivariate analysis was performed to detect any significant association between frequency of MNs (dependent variable) and behavioral factors (independent variables). The presence of MNs was highlighted in the buccal exfoliated cells of about 42% of recruited children with a mean frequency of 0.49 MN/1000 cells, greater than in other areas of Salento. The survey on individual characteristics and lifestyles showed that one in three children was overweight and that most of them had unhealthy eating habits with frequent consumption of foods considered ‘risky’. Moreover many parents (40% of fathers and 12% of mothers) were smokers and about 20% of them admitted to smoking in the house where the children lived. Information regarding atmospheric contaminants was poor. Of the few substances routinely detected by the only one monitoring station located in the study area (PM2.5, SO2, NO2, CO, O3) only ozone showed high concentrations exceeding the limits set by the legislation for 67 times in the year 2015. The study showed that the level of early biological effect markers in children was not negligible. This critical condition could be related to some individual factors and lifestyles such as overweight, unhealthy eating habits and exposure to passive smoking. At present, no relationship with airborne pollutants can be established due to the lack of information on many substances. Therefore, it would be advisable to modify incorrect behaviors and to intensify the monitoring of airborne pollutants (e.g. including detection of PM10, heavy metals, aromatic polycyclic hydrocarbons, benzene) given the epidemiology of chronic respiratory diseases registered in this area.

Keywords: chronic respiratory diseases, environmental pollution, lifestyle, micronuclei

Procedia PDF Downloads 202

Authors: Muhammad Haris, Syed Kamran Ali, Mubeen Islam, Tariq Mehmood, Faisal Shah

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Jacobabad Khairpur High, part of a Sukkur rift zone, is the separating boundary between Central and Southern Indus Basin, formed as a result of Post-Jurassic uplift after the deposition of Middle Jurassic Chiltan Formation. Habib Rahi Formation of Middle to Late Eocene outcrops in the vicinity of Jacobabad Khairpur High, a section at Rohri near Sukkur is measured in detail for lithofacies, microfacies, diagenetic analysis and sequence stratigraphy. Habib Rahi Formation is richly fossiliferous and consists of mostly limestone with subordinate clays and marl. The total thickness of the formation in this section is 28.8m. The bottom of the formation is not exposed, while the upper contact with the Sirki Shale of the Middle Eocene age is unconformable in some places. A section is measured using Jacob’s Staff method, and traverses were made perpendicular to the strike. Four different lithofacies were identified based on outcrop geology which includes coarse-grained limestone facies (HR-1 to HR-5), massive bedded limestone facies (HR-6 HR-7), and micritic limestone facies (HR-8 to HR-13) and algal dolomitic limestone facie (HR-14). Total 14 rock samples were collected from outcrop for detailed petrographic studies, and thin sections of respective samples were prepared and analyzed under the microscope. On the basis of Dunham’s (1962) classification systems after studying textures, grain size, and fossil content and using Folk’s (1959) classification system after reviewing Allochems type, four microfacies were identified. These microfacies include HR-MF 1: Benthonic Foraminiferal Wackstone/Biomicrite Microfacies, HR-MF 2: Foramineral Nummulites Wackstone-Packstone/Biomicrite Microfacies HR-MF 3: Benthonic Foraminiferal Packstone/Biomicrite Microfacies, HR-MF 4: Bioclasts Carbonate Mudstone/Micrite Microfacies. The abundance of larger benthic Foraminifera’s (LBF), including Assilina sp., A. spiral abrade, A. granulosa, A. dandotica, A. laminosa, Nummulite sp., N. fabiani, N. stratus, N. globulus, Textularia, Bioclasts, and Red algae indicates shallow marine (Tidal Flat) environment of deposition. Based on variations in rock types, grain size, and marina fauna Habib Rahi Formation shows progradational stacking patterns, which indicates coarsening upward cycles. The second order of sea-level rise is identified (spanning from Y-Persian to Bartonian age) that represents the Transgressive System Tract (TST) and a third-order Regressive System Tract (RST) (spanning from Bartonian to Priabonian age). Diagenetic processes include fossils replacement by mud, dolomitization, pressure dissolution associated stylolites features and filling with dark organic matter. The presence of the microfossils includes Nummulite. striatus, N. fabiani, and Assilina. dandotica, signify Bartonian to Priabonian age of Habib Rahi Formation.

Keywords: Jacobabad Khairpur High, Habib Rahi Formation, lithofacies, microfacies, sequence stratigraphy, diagenetic history

Procedia PDF Downloads 472

Authors: Karen L. Lindsay, Sonja Entringer, Claudia Buss, Pathik D. Wadhwa

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Maternal nutrition and stress are independently recognized as among the most important factors that influence prenatal biology, with implications for fetal development and poor pregnancy outcomes. While there is substantial evidence from non-pregnancy human and animal studies that a complex, bi-directional relationship exists between nutrition and stress, to the author’s best knowledge, their interaction in the context of pregnancy has been significantly understudied. The aim of this study is to assess the interaction between maternal psychological stress and diet quality across pregnancy and its effects on biomarkers of prenatal insulin resistance and inflammation. This is a prospective longitudinal study of N=235 women carrying a healthy, singleton pregnancy, recruited from prenatal clinics of the University of California, Irvine Medical Center. Participants completed a 4-day ambulatory assessment in early, middle and late pregnancy, which included multiple daily electronic diary entries using Ecological Momentary Assessment (EMA) technology on a dedicated study smartphone. The EMA diaries gathered moment-level data on maternal perceived stress, negative mood, positive mood and quality of social interactions. The numerical scores for these variables were averaged across each study time-point and converted to Z-scores. A single composite variable for 'STRESS' was computed as follows: (Negative mood+Perceived stress)–(Positive mood+Social interaction quality). Dietary intakes were assessed by three 24-hour dietary recalls conducted within two weeks of each 4-day assessment. Daily nutrient and food group intakes were averaged across each study time-point. The Alternative Healthy Eating Index adapted for pregnancy (AHEI-P) was computed for early, middle and late pregnancy as a validated summary measure of diet quality. At the end of each 4-day ambulatory assessment, women provided a fasting blood sample, which was assayed for levels of glucose, insulin, Interleukin (IL)-6 and Tumor Necrosis Factor (TNF)-α. Homeostasis Model Assessment of Insulin Resistance (HOMA-IR) was computed. Pearson’s correlation was used to explore the relationship between maternal STRESS and AHEI-P within and between each study time-point. Linear regression was employed to test the association of the stress-diet interaction (STRESS*AHEI-P) with the biological markers HOMA-IR, IL-6 and TNF-α at each study time-point, adjusting for key covariates (pre-pregnancy body mass index, maternal education level, race/ethnicity). Maternal STRESS and AHEI-P were significantly inversely correlated in early (r=-0.164, p=0.018) and mid-pregnancy (-0.160, p=0.019), and AHEI-P from earlier gestational time-points correlated with later STRESS (early AHEI-P x mid STRESS: r=-0.168, p=0.017; mid AHEI-P x late STRESS: r=-0.142, p=0.041). In regression models, the interaction term was not associated with HOMA-IR or IL-6 at any gestational time-point. The stress-diet interaction term was significantly associated with TNF-α according to the following patterns: early AHEI-P*early STRESS vs early TNF-α (p=0.005); early AHEI-P*early STRESS vs mid TNF-α (p=0.002); early AHEI-P*mid STRESS vs mid TNF-α (p=0.005); mid AHEI-P*mid STRESS vs mid TNF-α (p=0.070); mid AHEI-P*late STRESS vs late TNF-α (p=0.011). Poor diet quality is significantly related to higher psychosocial stress levels in pregnant women across gestation, which may promote inflammation via TNF-α. Future prenatal studies should consider the combined effects of maternal stress and diet when evaluating either one of these factors on pregnancy or infant outcomes.

Keywords: diet quality, inflammation, insulin resistance, nutrition, pregnancy, stress, tumor necrosis factor-alpha

Procedia PDF Downloads 200

Authors: James Cairns, Marco Vezza, Richard Green, Donald MacVicar

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Significant legislative changes are set to revolutionise the commercial shipping industry. Upcoming emissions restrictions will force operators to look at technologies that can improve the efficiency of their vessels -reducing fuel consumption and emissions. A device which may help in this challenge is the Ship Wind-Assisted Propulsion system (SWAP), an actively controlled aerofoil mounted vertically on the deck of a ship. The device functions in a similar manner to a sail on a yacht, whereby the aerodynamic forces generated by the sail reach an equilibrium with the hydrodynamic forces on the hull and a forward velocity results. Numerical and experimental testing of the SWAP device is presented in this study. Circulation control takes the form of a co-flow jet aerofoil, utilising both blowing from the leading edge and suction from the trailing edge. A jet at the leading edge uses the Coanda effect to energise the boundary layer in order to delay flow separation and create high lift with low drag. The SWAP concept has been originated by the research and development team at SMAR Azure Ltd. The device will be retrofitted to existing ships so that a component of the aerodynamic forces acts forward and partially reduces the reliance on existing propulsion systems. Wind tunnel tests have been carried out at the de Havilland wind tunnel at the University of Glasgow on a 1:20 scale model of this system. The tests aim to understand the airflow characteristics around the aerofoil and investigate the approximate lift and drag coefficients that an early iteration of the SWAP device may produce. The data exhibits clear trends of increasing lift as injection momentum increases, with critical flow attachment points being identified at specific combinations of jet momentum coefficient, Cµ, and angle of attack, AOA. Various combinations of flow conditions were tested, with the jet momentum coefficient ranging from 0 to 0.7 and the AOA ranging from 0° to 35°. The Reynolds number across the tested conditions ranged from 80,000 to 240,000. Comparisons between 2D computational fluid dynamics (CFD) simulations and the experimental data are presented for multiple Reynolds-Averaged Navier-Stokes (RANS) turbulence models in the form of normalised surface pressure comparisons. These show good agreement for most of the tested cases. However, certain simulation conditions exhibited a well-documented shortcoming of RANS-based turbulence models for circulation control flows and over-predicted surface pressures and lift coefficient for fully attached flow cases. Work must be continued in finding an all-encompassing modelling approach which predicts surface pressures well for all combinations of jet injection momentum and AOA.

Keywords: CFD, circulation control, Coanda, turbo wing sail, wind tunnel

Procedia PDF Downloads 135

Authors: Ruth Hegarty, Noel Connaughton

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Sustainability reporting has become a priority for many global multinational companies. This is associated with ever-increasing expectations from key stakeholders for companies to be transparent about their strategies, activities and management with regard to sustainability issues. The Global Reporting Initiative (GRI) encourages reporters to only provide information on the issues that are really critical in order to achieve the organisation’s goals for sustainability and manage its impact on environment and society. A key challenge for most reporting organisations is how to identify relevant issues for sustainability reporting and prioritise those material issues in accordance with company and stakeholder needs. A recent study indicates that most of the largest companies listed on the world’s stock exchanges are failing to provide data on key sustainability indicators such as employee turnover, energy, greenhouse gas emissions (GHGs), injury rate, pay equity, waste and water. This paper takes an indepth look at the approaches used by a select number of international sustainability leader corporates to identify key sustainability issues. The research methodology involves performing a detailed analysis of the sustainability report content of up to 50 companies listed on the 2014 Dow Jones Sustainability Indices (DJSI). The most recent sustainability report content found on the GRI Sustainability Disclosure Database is then compared with 91 GRI Specific Standard Disclosures and a small number of GRI Standard Disclosures. Preliminary research indicates significant gaps in the information disclosed in corporate sustainability reports versus the indicator content specified in the GRI Content Index. The following outlines some of the key findings to date: Most companies made a partial disclosure with regard to the Economic indicators of climate change risks and infrastructure investments, but did not focus on the associated negative impacts. The top Environmental indicators disclosed were energy consumption and reductions, GHG emissions, water withdrawals, waste and compliance. The lowest rates of indicator disclosure included biodiversity, water discharge, mitigation of environmental impacts of products and services, transport, environmental investments, screening of new suppliers and supply chain impacts. The top Social indicators disclosed were new employee hires, rates of injury, freedom of association in operations, child labour and forced labour. Lesser disclosure rates were reported for employee training, composition of governance bodies and employees, political contributions, corruption and fines for non-compliance. The reporting on most other Social indicators was found to be poor. In addition, most companies give only a brief explanation on how material issues are defined, identified and ranked. Data on the identification of key stakeholders and the degree and nature of engagement for determining issues and their weightings is also lacking. Generally, little to no data is provided on the algorithms used to score an issue. Research indicates that most companies lack a rigorous and thorough methodology to systematically determine the material issues of sustainability reporting in accordance with company and stakeholder needs.

Keywords: identification of key stakeholders, material issues, sustainability reporting, transparency

Procedia PDF Downloads 306