Search results for: digital dynamic pulse-frequency control systems

Authors: Taghrid Asfar, Olusanya J. Oluwole, Michael Schmidt, Alejandra Casas, Zoran Bursac, Wasim Maziak.

Abstract:

Waterpipe (WP) smoking (a.k.a. hookah) has increased dramatically in the US mainly due to the misperception that it is safer than cigarette smoking. Mounting evidence show that WP smoking is addictive and harmful. Health warning labels (HWLs) are effective in communicating smoking-related risks. Currently, the FDA requires that WP tobacco packages have a textual HWL about nicotine. While this represents a good step, it is inadequate given the established harm of WP smoking beyond addiction and the superior performance of pictorial HWLs over text-only ones. We developed 24 WP pictorial HWLs in a Delphi study among international expert panel. HWLs were grouped into 6 themes: addiction, harm compared to cigarettes, harm to others, health effects, quitting, and specific harms. This study aims to compare the effect of the pictorial HWLs compared to the FDA HWL, and 2) the effect of pictorial HWLs between the 6 themes. A 2x7 between/within subject online factorial experimental study was conducted among a national convenience sample of 300 (50% current WP smokers; 50% nonsmokers) US adults (females 71.1%; mean age of 31.1±3.41 years) in March 2022. The first factor varied WP smoking status (smokers, nonsmokers). The second factor varied the HWL theme and type (text, pictorial). Participants were randomized to view and rate 7 HWLs: 1 FDA text HWL (control) and 6 HWLs, one from each of the 6 themes, all presented in random order. HWLs were rated based on the message impact framework into five categories: attention, reaction (believability, relevance, fear), perceived effectiveness, intentions to quit WP among current smokers, and intention to not initiate WP among nonsmokers. measures were assessed on a 5-point Likert scale (1=not at all to 5=very much) for attention and reaction and on a 7-point Likert scale (1=not at all to 7=very much) for the perceived effectiveness and intentions to quit or not initiate WP smoking. Means and SDs of outcome measures for each HWL type and theme were calculated. Planned comparisons using Friedman test followed by pairwise Wilcoxon signed-rank test for multiple comparisons were used to examine distributional differences of outcomes between the HWL type and themes. Approximately 74.4 % of participants were non-Hispanic Whites, 68.4% had college degrees, and 41.5% were under the poverty level. Participants reported starting WTS on average at 20.3±8.19 years. Compared with the FDA text HWL, pictorial HWLs elicited higher attention (p<0.0001), fear (p<0.0001), harm perception (p<0.0003), perceived effectiveness (p<0.0001), and intentions to quit (p=0.0014) and not initiate WP smoking (p<0.0003). HWLs in theme 3 (harm to others) achieved the highest rating in attention (4.14±1), believability (4.15±0.95), overall perceived effectiveness (7.60±2.35), harm perception (7.53±2.43), and intentions to quit (7.35±2.57). HWLs in theme 2 (WP harm compared to cigarettes) achieved the highest rating in discouraging WP smoking initiation (7.32±2.54). Pictorial HWLs were superior to the FDA text-only for several communication outcomes. Pictorial HWLs related to WP harm to others and WP harm compared to cigarette are promising. These findings provide strong evidence for the potential implementation of WP-specific pictorial HWLs.

Keywords: health communication, waterpipe smoking, factorial experiment, reaction, harm perception, tobacco regulations

Procedia PDF Downloads 107

Authors: Jérémy Philippe, Lucien Baldas, Batoul Attar, Jean-Charles Mare

Abstract:

The proposed communication deals with the research and development of a rotary direct-drive servo valve for aerospace applications. A key challenge of the project is to downsize the electromagnetic torque motor by reducing the torque required to drive the rotary spool. It is intended to optimize the spool and the sleeve geometries by combining a Computational Fluid Dynamics (CFD) approach with commercial optimization software. The present communication addresses an important phase of the project, which consists firstly of gaining confidence in the simulation results. It is well known that the force needed to pilot a sliding spool valve comes from several physical effects: hydraulic forces, friction and inertia/mass of the moving assembly. Among them, the flow force is usually a major contributor to the steady-state (or Root Mean Square) driving torque. In recent decades, CFD has gradually become a standard simulation tool for studying fluid-structure interactions. However, in the particular case of high-pressure valve design, the authors have experienced that the calculated overall hydraulic force depends on the parameterization and options used to build and run the CFD model. To solve this issue, the authors have selected the standard case of the linear spool valve, which is addressed in detail in numerous scientific references (analytical models, experiments, CFD simulations). The first CFD simulations run by the authors have shown that the evolution of the equivalent discharge coefficient vs. Reynolds number at the metering orifice corresponds well to the values that can be predicted by the classical analytical models. Oppositely, the simulated flow force was found to be quite different from the value calculated analytically. This drove the authors to investigate minutely the influence of the studied domain and the setting of the CFD simulation. It was firstly shown that the flow recirculates in the inlet and outlet channels if their length is not sufficient regarding their hydraulic diameter. The dead volume on the uncontrolled orifice side also plays a significant role. These examples highlight the influence of the geometry of the fluid domain considered. The second action was to investigate the influence of the type of mesh, the turbulence models and near-wall approaches, and the numerical solver and discretization scheme order. Two approaches were used to determine the overall hydraulic force acting on the moving spool. First, the force was deduced from the momentum balance on a control domain delimited by the valve inlet and outlet and the spool walls. Second, the overall hydraulic force was calculated from the integral of pressure and shear forces acting at the boundaries of the fluid domain. This underlined the significant contribution of the viscous forces acting on the spool between the inlet and outlet orifices, which are generally not considered in the literature. This also emphasized the influence of the choices made for the implementation of CFD calculation and results analysis. With the step-by-step process adopted to increase confidence in the CFD simulations, the authors propose a set of best practices and recommendations for the efficient use of CFD to design high-pressure spool valves.

Keywords: computational fluid dynamics, hydraulic forces, servovalve, rotary servovalve

Procedia PDF Downloads 37

Authors: Shraddha Chaudhary, Raksha Agarwal, Niladri Chatterjee

Abstract:

This work demonstrates a web crawler-based generalized end-to-end open domain Question Answering (QA) system. An efficient QA system requires a significant amount of domain knowledge to answer any question with the aim to find an exact and correct answer in the form of a number, a noun, a short phrase, or a brief piece of text for the user's questions. Analysis of the question, searching the relevant document, and choosing an answer are three important steps in a QA system. This work uses a web scraper (Beautiful Soup) to extract K-documents from the web. The value of K can be calibrated on the basis of a trade-off between time and accuracy. This is followed by a passage ranking process using the MS-Marco dataset trained on 500K queries to extract the most relevant text passage, to shorten the lengthy documents. Further, a QA system is used to extract the answers from the shortened documents based on the query and return the top 3 answers. For evaluation of such systems, accuracy is judged by the exact match between predicted answers and gold answers. But automatic evaluation methods fail due to the linguistic ambiguities inherent in the questions. Moreover, reference answers are often not exhaustive or are out of date. Hence correct answers predicted by the system are often judged incorrect according to the automated metrics. One such scenario arises from the original Google Natural Question (GNQ) dataset which was collected and made available in the year 2016. Use of any such dataset proves to be inefficient with respect to any questions that have time-varying answers. For illustration, if the query is where will be the next Olympics? Gold Answer for the above query as given in the GNQ dataset is “Tokyo”. Since the dataset was collected in the year 2016, and the next Olympics after 2016 were in 2020 that was in Tokyo which is absolutely correct. But if the same question is asked in 2022 then the answer is “Paris, 2024”. Consequently, any evaluation based on the GNQ dataset will be incorrect. Such erroneous predictions are usually given to human evaluators for further validation which is quite expensive and time-consuming. To address this erroneous evaluation, the present work proposes an automated approach for evaluating time-dependent question-answer pairs. In particular, it proposes a metric using the current timestamp along with top-n predicted answers from a given QA system. To test the proposed approach GNQ dataset has been used and the system achieved an accuracy of 78% for a test dataset comprising 100 QA pairs. This test data was automatically extracted using an analysis-based approach from 10K QA pairs of the GNQ dataset. The results obtained are encouraging. The proposed technique appears to have the possibility of developing into a useful scheme for gathering precise, reliable, and specific information in a real-time and efficient manner. Our subsequent experiments will be guided towards establishing the efficacy of the above system for a larger set of time-dependent QA pairs.

Keywords: web-based information retrieval, open domain question answering system, time-varying QA, QA evaluation

Procedia PDF Downloads 99

Authors: Lubos Rojka

Abstract:

The common perception of morally responsible behavior is that it presupposes freedom of choice, and that free decisions and actions are not determined by natural events, but by a person. In other words, the moral agent has the ability and the possibility of doing otherwise when making morally responsible decisions, and natural causal determinism cannot fully account for morally significant freedom. The incompatibility between a person’s morally significant freedom and causal determinism appears to be a natural position. Nevertheless, some of the most influential philosophical theories on moral responsibility are compatibilist or semi-compatibilist, and they exclude the requirement of alternative possibilities, which contradicts the claims of classical incompatibilism. The compatibilists often employ Frankfurt-style thought experiments to prove their theory. The goal of this paper is to examine the role of imaginary Frankfurt-style examples in compatibilist accounts. More specifically, the compatibilist accounts defended by John Martin Fischer and Michael McKenna will be inserted into the broader understanding of a person elaborated by Harry Frankfurt, Robert Kane and Walter Glannon. Deeper analysis reveals that the exclusion of alternative possibilities based on Frankfurt-style examples is problematic and misleading. A more comprehensive account of moral responsibility and morally significant (source) freedom requires higher order complex theories of human will and consciousness, in which rational and self-creative abilities and a real possibility to choose otherwise, at least on some occasions during a lifetime, are necessary. Theoretical moral reasons and their logical relations seem to require a sort of higher-order agent-causal incompatibilism. The ability of theoretical or abstract moral reasoning requires complex (strongly emergent) mental and conscious properties, among which an effective free will, together with first and second-order desires. Such a hierarchical theoretical model unifies reasons-responsiveness, mesh theory and emergentism. It is incompatible with physical causal determinism, because such determinism only allows non-systematic processes that may be hard to predict, but not complex (strongly) emergent systems. An agent’s effective will and conscious reflectivity is the starting point of a morally responsible action, which explains why a decision is 'up to the subject'. A free decision does not always have a complete causal history. This kind of an emergentist source hyper-incompatibilism seems to be the best direction of the search for an adequate explanation of moral responsibility in the traditional (merit-based) sense. Physical causal determinism as a universal theory would exclude morally significant freedom and responsibility in the traditional sense because it would exclude the emergence of and supervenience by the essential complex properties of human consciousness.

Keywords: consciousness, free will, determinism, emergence, moral responsibility

Procedia PDF Downloads 163

Authors: Agnieszka Markowska-Radomska, Ewa Dluska

Abstract:

Maintaining a bioactive substances dense diet is important for the elderly, especially to prevent diseases and to support healthy ageing. Adequate bioactive substances intake can reduce the risk of developing chronic diseases (e.g. cardiovascular, osteoporosis, neurodegenerative syndromes, diseases of the oral cavity, gastrointestinal (GI) disorders, diabetes, and cancer). This can be achieved by introducing a comprehensive supplementation of components necessary for the proper functioning of the ageing body. The paper proposes the multiple emulsions of the W1/O/W2 (water-in-oil-in-water) type as carriers for effective co-encapsulation and co-delivery of bioactive substances in supplementation of the elderly. Multiple emulsions are complex structured systems ("drops in drops"). The functional structure of the W1/O/W2 emulsion enables (i) incorporation of one or more bioactive components (lipophilic and hydrophilic); (ii) enhancement of stability and bioavailability of encapsulated substances; (iii) prevention of interactions between substances, as well as with the external environment, delivery to a specific location; and (iv) release in a controlled manner. The multiple emulsions were prepared by a one-step method in the Couette-Taylor flow (CTF) contactor in a continuous manner. In general, a two-step emulsification process is used to obtain multiple emulsions. The paper contains a proposal of emulsion functionalization by introducing pH-responsive biopolymer—carboxymethylcellulose sodium salt (CMC-Na) to the external phase, which made it possible to achieve a release of components controlled by the pH of the gastrointestinal environment. The membrane phase of emulsions was soybean oil. The W1/O/W2 emulsions were evaluated for their characteristics (drops size/drop size distribution, volume packing fraction), encapsulation efficiency and stability during storage (to 30 days) at 4ºC and 25ºC. Also, the in vitro multi-substance co-release process were investigated in a simulated gastrointestinal environment (different pH and composition of release medium). Three groups of stable multiple emulsions were obtained: emulsions I with co-encapsulated vitamins B12, B6 and resveratrol; emulsions II with vitamin A and β-carotene; and emulsions III with vitamins C, E and D3. The substances were encapsulated in the appropriate emulsion phases depending on the solubility. For all emulsions, high encapsulation efficience (over 95%) and high volume packing fraction of internal droplets (0.54-0.76) were reached. In addition, due to the presence of a polymer (CMC-Na) with adhesive properties, high encapsulation stability during emulsions storage were achieved. The co-release study of encapsulated bioactive substances confirmed the possibility to modify the release profiles. It was found that the releasing process can be controlled through the composition, structure, physicochemical parameters of emulsions and pH of the release medium. The results showed that the obtained multiple emulsions might be used as potential liquid complex carriers for controlled/modified/site-specific co-delivery of bioactive substances in dietary supplementation in the elderly.

Keywords: bioactive substance co-release, co-encapsulation, elderly supplementation, multiple emulsion

Procedia PDF Downloads 193

Authors: David Bakker, Nikki Rickard

Abstract:

Smartphone apps hold immense potential as mental health and wellbeing tools. Support can be made easily accessible and can be used in real-time while users are experiencing distress. Furthermore, data can be collected to enable machine learning and automated tailoring of support to users. While many apps have been developed for mental health purposes, few have adhered to evidence-based recommendations and even fewer have pursued experimental validation. This paper details the development and experimental evaluation of an app, MoodMission, that aims to provide support for low moods and anxiety, help prevent clinical depression and anxiety disorders, and serve as an adjunct to professional clinical supports. MoodMission was designed to deliver cognitive behavioural therapy for specifically reported problems in real-time, momentary interactions. Users report their low moods or anxious feelings to the app along with a subjective units of distress scale (SUDS) rating. MoodMission then provides a choice of 5-10 short, evidence-based mental health strategies called Missions. Users choose a Mission, complete it, and report their distress again. Automated tailoring, gamification, and in-built data collection for analysis of effectiveness was also included in the app’s design. The development process involved construction of an evidence-based behavioural plan, designing of the app, building and testing procedures, feedback-informed changes, and a public launch. A randomized controlled trial (RCT) was conducted comparing MoodMission to two other apps and a waitlist control condition. Participants completed measures of anxiety, depression, well-being, emotional self-awareness, coping self-efficacy and mental health literacy at the start of their app use and 30 days later. At the time of submission (November 2016) over 300 participants have participated in the RCT. Data analysis will begin in January 2017. At the time of this submission, MoodMission has over 4000 users. A repeated-measures ANOVA of 1390 completed Missions reveals that SUDS (0-10) ratings were significantly reduced between pre-Mission ratings (M=6.20, SD=2.39) and post-Mission ratings (M=4.93, SD=2.25), F(1,1389)=585.86, p < .001, np2=.30. This effect was consistent across both low moods and anxiety. Preliminary analyses of the data from the outcome measures surveys reveal improvements across mental health and wellbeing measures as a result of using the app over 30 days. This includes a significant increase in coping self-efficacy, F(1,22)=5.91, p=.024, np2=.21. Complete results from the RCT in which MoodMission was evaluated will be presented. Results will also be presented from the continuous outcome data being recorded by MoodMission. MoodMission was successfully developed and launched, and preliminary analysis suggest that it is an effective mental health and wellbeing tool. In addition to the clinical applications of MoodMission, the app holds promise as a research tool to conduct component analysis of psychological therapies and overcome restraints of laboratory based studies. The support provided by the app is discrete, tailored, evidence-based, and transcends barriers of stigma, geographic isolation, financial limitations, and low health literacy.

Keywords: anxiety, app, CBT, cognitive behavioural therapy, depression, eHealth, mission, mobile, mood, MoodMission

Procedia PDF Downloads 267

Authors: Halina Veloso e Zarate, Manuela Triggianese

Abstract:

The urban challenges posed by rapid population growth, climate adaptation, and sustainable living have compelled Dutch cities to reimagine their built environment and transportation systems. As a pivotal contributor to CO₂ emissions, the transportation sector in the Netherlands demands innovative solutions for transitioning to low-carbon mobility. This study investigates the potential of transit oriented development (TOD) as a strategy for achieving carbon reduction and sustainable urban transformation. Focusing on the Lombardijen station area in Rotterdam, which is targeted for significant densification, this paper presents a design-oriented exploration of a low-carbon transport node. By employing a research-by-design methodology, this study delves into multifaceted factors and scales, aiming to propose future scenarios for Lombardijen. Drawing from a synthesis of existing literature, applied research, and practical insights, a robust design framework emerges. To inform this framework, governmental data concerning the built environment and material embodied carbon are harnessed. However, the restricted access to crucial datasets, such as property ownership information from the cadastre and embodied carbon data from De Nationale Milieudatabase, underscores the need for improved data accessibility, especially during the concept design phase. The findings of this research contribute fundamental insights not only to the Lombardijen case but also to TOD studies across Rotterdam's 13 nodes and similar global contexts. Spatial data related to property ownership facilitated the identification of potential densification sites, underscoring its importance for informed urban design decisions. Additionally, the paper highlights the disparity between the essential role of embodied carbon data in environmental assessments for building permits and its limited accessibility due to proprietary barriers. Although this study lays the groundwork for sustainable urbanization through TOD-based design, it acknowledges an area of future research worthy of exploration: the socio-economic dimension. Given the complex socio-economic challenges inherent in the Lombardijen area, extending beyond spatial constraints, a comprehensive approach demands integration of mobility infrastructure expansion, land-use diversification, programmatic enhancements, and climate adaptation. While the paper adopts a TOD lens, it refrains from an in-depth examination of issues concerning equity and inclusivity, opening doors for subsequent research to address these aspects crucial for holistic urban development.

Keywords: Rotterdam zuid, transport oriented development, carbon emissions, low-carbon design, cross-scale design, data-supported design

Procedia PDF Downloads 77

Authors: Dorottya Guban, Irina Borbath, Istvan Bakos, Peter Nemeth, Andras Tompos

Abstract:

One of the greatest challenges of the implementation of polymer electrolyte membrane fuel cells (PEMFCs) is to find active and durable electrocatalysts. The cell performance is always limited by the oxygen reduction reaction (ORR) on the cathode since it is at least 6 orders of magnitude slower than the hydrogen oxidation on the anode. Therefore high loading of Pt is required. Catalyst corrosion is also more significant on the cathode, especially in case of mobile applications, where rapid changes of loading have to be tolerated. Pt-Sn bulk alloys and SnO2-decorated Pt3Sn nanostructures are among the most studied bimetallic systems for fuel cell applications. Exclusive formation of supported Sn-Pt alloy phases with different Pt/Sn ratios can be achieved by using controlled surface reactions (CSRs) between hydrogen adsorbed on Pt sites and tetraethyl tin. In this contribution our results for commercial and a home-made 20 wt.% Pt/C catalysts modified by tin anchoring via CSRs are presented. The parent Pt/C catalysts were synthesized by modified NaBH4-assisted ethylene-glycol reduction method using ethanol as a solvent, which resulted either in dispersed and highly stable Pt nanoparticles or evenly distributed raspberry-like agglomerates according to the chosen synthesis parameters. The 20 wt.% Pt/C catalysts prepared that way showed improved electrocatalytic performance in the ORR and stability in comparison to the commercial 20 wt.% Pt/C catalysts. Then, in order to obtain Sn-Pt/C catalysts with Pt/Sn= 3 ratio, the Pt/C catalysts were modified with tetraethyl tin (SnEt4) using three and five consecutive tin anchoring periods. According to in situ XPS studies in case of catalysts with highly dispersed Pt nanoparticles, pre-treatment in hydrogen even at 170°C resulted in complete reduction of the ionic tin to Sn0. No evidence of the presence of SnO2 phase was found by means of the XRD and EDS analysis. These results demonstrate that the method of CSRs is a powerful tool to create Pt-Sn bimetallic nanoparticles exclusively, without tin deposition onto the carbon support. On the contrary, the XPS results revealed that the tin-modified catalysts with raspberry-like Pt agglomerates always contained a fraction of non-reducible tin oxide. At the same time, they showed increased activity and long-term stability in the ORR than Pt/C, which was assigned to the presence of SnO2 in close proximity/contact with Pt-Sn alloy phase. It has been demonstrated that the content and dispersion of the fcc Pt3Sn phase within the electrocatalysts can be controlled by tuning the reaction conditions of CSRs. The bimetallic catalysts displayed an outstanding performance in the ORR. The preparation of a highly dispersed 20Pt/C catalyst permits to decrease the Pt content without relevant decline in the electrocatalytic performance of the catalysts.

Keywords: anode catalyst, cathode catalyst, controlled surface reactions, oxygen reduction reaction, PtSn/C electrocatalyst

Procedia PDF Downloads 226

Authors: Loveline Ambo Angwah

Abstract:

The processing of cassava from tubers or roots into food using crude and rudimentary method (hand peeling, grating, frying and to sun drying) is a very cumbersome and difficult process. The crude methods are time consuming and labour intensive. While on the other hand, modern processing method, that is using machines to perform the various processes as washing, peeling, grinding, oven drying, fermentation and frying is easier, less time consuming, and less labour intensive. Rudimentarily, cassava roots are processed into numerous products and utilized in various ways according to local customs and preferences. For the people of Ngwo village, cassava is transformed locally into flour or powder form called ‘cumcum’. It is also sucked into water to give a kind of food call ‘water fufu’ and fried to give ‘garri’. The leaves are consumed as vegetables. Added to these, its relative high yields; ability to stay underground after maturity for long periods give cassava considerable advantage as a commodity that is being used by poor rural folks in the community, to fight poverty. It plays a major role in efforts to alleviate the food crisis because of its efficient production of food energy, year-round availability, tolerance to extreme stress conditions, and suitability to present farming and food systems in Africa. Improvement of cassava processing and utilization techniques would greatly increase labor efficiency, incomes, and living standards of cassava farmers and the rural poor, as well as enhance the-shelf life of products, facilitate their transportation, increase marketing opportunities, and help improve human and livestock nutrition. This paper presents a general overview of crude ways in cassava processing and utilization methods now used by subsistence and small-scale farmers in Ngwo village of the North West region in Cameroon, and examine the opportunities of improving processing technologies. Cassava needs processing because the roots cannot be stored for long because they rot within 3-4 days of harvest. They are bulky with about 70% moisture content, and therefore transportation of the tubers to markets is difficult and expensive. The roots and leaves contain varying amounts of cyanide which is toxic to humans and animals, while the raw cassava roots and uncooked leaves are not palatable. Therefore, cassava must be processed into various forms in order to increase the shelf life of the products, facilitate transportation and marketing, reduce cyanide content and improve palatability.

Keywords: cassava roots, crude ways, food system, poverty

Procedia PDF Downloads 163

Authors: Rahel Birhanu Kassaye, Ralf Otterpohl, Kumelachew Yeshitila

Abstract:

Water resource management and land degradation are among the critical issues threatening the suitable livability of many cities in developing countries such as Ethiopia. Rapid expansion of urban areas and fast growing population has increased the pressure on water security. On the other hand, the large transformation of natural green cover and agricultural land loss to settlement and industrial activities such as quarrying is contributing to environmental concerns. Integrated water harvesting is considered to play a crucial role in terms of providing alternative water source to insure water security and helping to improve soil condition, agricultural productivity and regeneration of ecosystem. Moreover, it helps to control stormwater runoff, thus reducing flood risks and pollution, thereby improving the quality of receiving water bodies and the health of inhabitants. The aim of this research was to investigate the potential of applying integrated water harvesting approaches as a provision for water source and enabling land restoration in Jemo river catchment consisting of abandoned quarry site adjacent to a settlement area that is facing serious water shortage in western hilly part of Addis Ababa city, Ethiopia. The abandoned quarry site, apart from its contribution to the loss of aesthetics, has resulted in poor water infiltration and increase in stormwater runoff leading to land degradation and flooding in the downstream. Application of GIS and multi-criteria based analysis are used for the assessment of potential water harvesting technologies considering the technology features and site characteristics of the case study area. Biophysical parameters including precipitation, surrounding land use, surface gradient, soil characteristics and geological aspects are used as site characteristic indicators and water harvesting technologies including retention pond, check dam, agro-forestation employing contour trench system were considered for evaluation with technical and socio-economic factors used as parameters in the assessment. The assessment results indicate the different suitability potential among the analyzed water harvesting and restoration techniques with respect to the abandoned quarry site characteristics. Application of agro-forestation with contour trench system with the revegetation of indigenous plants is found to be the most suitable option for reclamation and restoration of the quarry site. Successful application of the selected technologies and strategies for water harvesting and restoration is considered to play a significant role to provide additional water source, maintain good water quality, increase agricultural productivity at urban peri-urban interface scale and improve biodiversity in the catchment. The results of the study provide guideline for decision makers and contribute to the integration of decentralized water harvesting and restoration techniques in the water management and planning of the case study area.

Keywords: abandoned quarry site, land reclamation and restoration, multi-criteria assessment, water harvesting

Procedia PDF Downloads 212

Authors: Soheila Sadeghi

Abstract:

Accurate cost prediction is essential for effective project management and decision-making in the construction industry. This study aims to develop a cost prediction model for construction projects using Machine Learning techniques and Particle Swarm Optimization (PSO). The research utilizes a comprehensive dataset containing project cost estimates, actual costs, resource details, and project performance metrics from a road reconstruction project. The methodology involves data preprocessing, feature selection, and the development of an Artificial Neural Network (ANN) model optimized using PSO. The study investigates the impact of various input features, including cost estimates, resource allocation, and project progress, on the accuracy of cost predictions. The performance of the optimized ANN model is evaluated using metrics such as Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and R-squared. The results demonstrate the effectiveness of the proposed approach in predicting project costs, outperforming traditional benchmark models. The feature selection process identifies the most influential variables contributing to cost variations, providing valuable insights for project managers. However, this study has several limitations. Firstly, the model's performance may be influenced by the quality and quantity of the dataset used. A larger and more diverse dataset covering different types of construction projects would enhance the model's generalizability. Secondly, the study focuses on a specific optimization technique (PSO) and a single Machine Learning algorithm (ANN). Exploring other optimization methods and comparing the performance of various ML algorithms could provide a more comprehensive understanding of the cost prediction problem. Future research should focus on several key areas. Firstly, expanding the dataset to include a wider range of construction projects, such as residential buildings, commercial complexes, and infrastructure projects, would improve the model's applicability. Secondly, investigating the integration of additional data sources, such as economic indicators, weather data, and supplier information, could enhance the predictive power of the model. Thirdly, exploring the potential of ensemble learning techniques, which combine multiple ML algorithms, may further improve cost prediction accuracy. Additionally, developing user-friendly interfaces and tools to facilitate the adoption of the proposed cost prediction model in real-world construction projects would be a valuable contribution to the industry. The findings of this study have significant implications for construction project management, enabling proactive cost estimation, resource allocation, budget planning, and risk assessment, ultimately leading to improved project performance and cost control. This research contributes to the advancement of cost prediction techniques in the construction industry and highlights the potential of Machine Learning and PSO in addressing this critical challenge. However, further research is needed to address the limitations and explore the identified future research directions to fully realize the potential of ML-based cost prediction models in the construction domain.

Keywords: cost prediction, construction projects, machine learning, artificial neural networks, particle swarm optimization, project management, feature selection, road reconstruction

Procedia PDF Downloads 51

Authors: Gianluca Castelnuovo, Giada Pietrabissa, Gian Mauro Manzoni, Margherita Novelli, Emanuele Maria Giusti, Roberto Cattivelli, Enrico Molinari

Abstract:

Diabesity could be defined as a new global epidemic of obesity and being overweight with many complications and chronic conditions. Such conditions include not only type 2 diabetes, but also cardiovascular diseases, hypertension, dyslipidemia, hypercholesterolemia, cancer, and various psychosocial and psychopathological disorders. The financial direct and indirect burden (considering also the clinical resources involved and the loss of productivity) is a real challenge in many Western health-care systems. Recently the Lancet journal defined diabetes as a 21st-century challenge. In order to promote patient compliance in diabesity treatment reducing costs, evidence-based interventions to improve weight-loss, maintain a healthy weight, and reduce related comorbidities combine different treatment approaches: dietetic, nutritional, physical, behavioral, psychological, and, in some situations, pharmacological and surgical. Moreover, new technologies can provide useful solutions in this multidisciplinary approach, above all in maintaining long-term compliance and adherence in order to ensure clinical efficacy. Psychological therapies with diet and exercise plans could better help patients in achieving weight loss outcomes, both inside hospitals and clinical centers and during out-patient follow-up sessions. In the management of chronic diseases clinical psychology play a key role due to the need of working on psychological conditions of patients, their families and their caregivers. mHealth approach could overcome limitations linked with the traditional, restricted and highly expensive in-patient treatment of many chronic pathologies: one of the best up-to-date application is the management of obesity with type 2 diabetes, where mHealth solutions can provide remote opportunities for enhancing weight reduction and reducing complications from clinical, organizational and economic perspectives. A stepped care mHealth-based approach is an interesting perspective in chronic care management of obesity with type 2 diabetes. One promising future direction could be treating obesity, considered as a chronic multifactorial disease, using a stepped-care approach: -mhealth or traditional based lifestyle psychoeducational and nutritional approach. -health professionals-driven multidisciplinary protocols tailored for each patient. -inpatient approach with the inclusion of drug therapies and other multidisciplinary treatments. -bariatric surgery with psychological and medical follow-up In the chronic care management of globesity mhealth solutions cannot substitute traditional approaches, but they can supplement some steps in clinical psychology and medicine both for obesity prevention and for weight loss management.

Keywords: clinical health psychology, mhealth, obesity, type 2 diabetes, stepped care, chronic care management

Procedia PDF Downloads 341

Authors: Elena Cangelosi, Wayne Beyea

Abstract:

This research expands the resilience planning literature by exploring the barriers and enablers to climate and health adaptation planning for small urban, coastal Great Lakes communities. With funding from the United States Centers for Disease Control and Prevention (CDC) Climate Ready City and States Initiative, this research took place during a 3-year pilot intervention project which integrates urban planning and public health. The project used the CDC’s Building Resilience Against Climate Effects (BRACE) framework to prevent or reduce the human health impacts from climate change in Marquette County, Michigan. Using a deliberation with the analysis planning process, interviews, focus groups, and community meetings with over 25 stakeholder groups and over 100 participants identified the area’s climate-related health concerns and adaptation interventions to address those concerns. Marquette County, on the shores of Lake Superior, the largest of the Great Lakes, was selected for the project based on their existing adaptive capacity and proactive approach to climate adaptation planning. With Marquette County as the context, this study fills a gap in the adaptation literature, which currently heavily emphasizes large-urban or agriculturally-based rural areas, and largely neglects small urban areas. This research builds on the qualitative case-study, survey, and interview approach established by previous researchers on contextual barriers and enablers for adaptation planning. This research uses a case study approach, including surveys and interviews of public officials, to identify the barriers and enablers for climate and health adaptation planning for small-urban areas within a large, non-agricultural, Great Lakes county. The researchers hypothesize that the barriers and enablers will, in some cases, overlap those found in other contexts, but in many cases, will be unique to a rural setting. The study reveals that funding, staff capacity, and communication across a large, rural geography act as the main barriers, while strong networks and collaboration, interested leaders, and community interest through a strong human-land connection act as the primary enablers. Challenges unique to rural areas are revealed, including weak opportunities for grant funding, large geographical distances, communication challenges with an aging and remote population, and the out-migration of education residents. Enablers that may be unique to rural contexts include strong collaborative relationships across jurisdictions for regional work and strong connections between residents and the land. As the factors that enable and prevent climate change planning are highly contextual, understanding, and appropriately addressing the unique factors at play for small-urban communities is key for effective planning in those areas. By identifying and addressing the barriers and enablers to climate and health adaptation planning for small-urban, coastal areas, this study can help Great Lakes communities appropriately build resilience to the adverse impacts of climate change. In addition, this research expands the breadth of research and understanding of the challenges and opportunities planners confront in the face of climate change.

Keywords: climate adaptation and resilience, climate change adaptation, climate change and urban resilience, governance and urban resilience

Procedia PDF Downloads 118

Authors: Takeru Furuawa, Kohei Takizawa, Daisuke Kuwahara, Shunjiro Shinohara

Abstract:

In the field of a space propulsion, an electric propulsion system has been developed because its fuel efficiency is much higher than a conventional chemical one. However, the practical electric propulsion systems, e.g., an ion engine, have a problem of short lifetime due to a damage of generation and acceleration electrodes of the plasma. A helicon plasma thruster is proposed as a long-lifetime electric thruster which has non-direct contact electrodes. In this system, both generation and acceleration methods of a dense plasma are executed by antennas from the outside of a discharge tube. Development of the helicon plasma thruster has been conducting under the Helicon Electrodeless Advanced Thruster (HEAT) project. Our helicon plasma thruster has two important processes. First, we generate a dense source plasma using a helicon wave with an excitation frequency between an ion and an electron cyclotron frequencies, fci and fce, respectively, applied from the outside of a discharge using a radio frequency (RF) antenna. The helicon plasma source can provide a high-density (~1019 m-3), a high-ionization ratio (up to several tens of percent), and a high particle generation efficiency. Second, in order to achieve high thrust and specific impulse, we accelerate the dense plasma by the axial Lorentz force fz using the product of the induced azimuthal current jθ and the static radial magnetic field Br, shown as fz = jθ × Br. The HEAT project has proposed several kinds of electrodeless acceleration schemes, and in our particular case, a Rotating Magnetic Field (RMF) method has been extensively studied. The RMF scheme was originally developed as a concept to maintain the Field Reversed Configuration (FRC) in a magnetically confined fusion research. Here, RMF coils are expected to generate jθ due to a nonlinear effect shown below. First, the rotating magnetic field Bω is generated by two pairs of RMF coils with AC currents, which have a phase difference of 90 degrees between the pairs. Due to the Faraday’s law, an axial electric field is induced. Second, an axial current is generated by the effects of an electron-ion and an electron-neutral collisions through the Ohm’s law. Third, the azimuthal electric field is generated by the nonlinear term, and the retarding torque generated by the collision effects again. Then, azimuthal current jθ is generated as jθ = - nₑ er ∙ 2π fRMF. Finally, the axial Lorentz force fz for plasma acceleration is generated. Here, jθ is proportional to nₑ and frequency of RMF coil current fRMF, when Bω is fully penetrated into the plasma. Our previous study has achieved 19 % increase of ion velocity using the 5 MHz and 50 A of the RMF coil power supply. In this presentation, we will show the improvement of the ion velocity using the lower frequency and higher current supplied by RMF power supply. In conclusion, helicon high-density plasma production and electromagnetic acceleration by the RMF scheme with a concept of electrodeless condition have been successfully executed.

Keywords: electric propulsion, electrodeless thruster, helicon plasma, rotating magnetic field

Procedia PDF Downloads 258

Authors: J. Martin Leal-Graciano, Juan J. Pérez-Gavilán, A. Reyes-Salazar, J. H. Castorena, J. L. Rivera-Salas

Abstract:

The experimental results about the global behavior of twelve 1:2 scaled reinforced concrete frame subject to in-plane lateral load are presented. The main objective was to generate experimental evidence about the use of steel bars within mortar bed-joints as shear reinforcement in infill walls. Similar to the Canadian and New Zealand standards, the Mexican code includes specifications for this type of reinforcement. However, these specifications were obtained through experimental studies of load-bearing walls, mainly confined walls. Little information is found in the existing literature about the effects of joint reinforcement on the seismic behavior of infill masonry walls. Consequently, the Mexican code establishes the same equations to estimate the contribution of joint reinforcement for both confined walls and infill walls. A confined masonry construction and a reinforced concrete frame infilled with masonry walls have similar appearances. However, substantial differences exist between these two construction systems, which are mainly related to the sequence of construction and to how these structures support vertical and lateral loads. To achieve the objective established, ten reinforced concrete frames with masonry infill walls were built and tested in pairs, having both specimens in the pair identical characteristics except that one of them included joint reinforcement. The variables between pairs were the type of units, the size of the columns of the frame and the aspect ratio of the wall. All cases included tie-columns and tie-beams on the perimeter of the wall to anchor the joint reinforcement. Also, two bare frame with identical characteristic to the infilled frames were tested. The purpose was to investigate the effects of the infill wall on the behavior of the system to in-plane lateral load. In addition, the experimental results were compared with the prediction of the Mexican code. All the specimens were tested in cantilever under reversible cyclic lateral load. To simulate gravity load, constant vertical load was applied on the top of the columns. The results indicate that the contribution of the joint reinforcement to lateral strength depends on the size of the columns of the frame. Larger size columns produce a failure mode that is predominantly a sliding mode. Sliding inhibits the production of new inclined cracks, which are necessary to activate (deform) the joint reinforcement. Regarding the effects of joint reinforcement in the performance of confined masonry walls, many facts were confirmed for infill walls: this type of reinforcement increases the lateral strength of the wall, produces a more distributed cracking and reduces the width of the cracks. Moreover, it reduces the ductility demand of the system at maximum strength. The prediction of the lateral strength provided by the Mexican code is property in some cases; however, the effect of the size of the columns on the contribution of joint reinforcement needs to be better understood.

Keywords: experimental study, Infill wall, Infilled frame, masonry wall

Procedia PDF Downloads 74

Authors: C. A. Barros, Ana P. Barroso

Abstract:

Any industrial company needs to determine the amount of variation that exists within its measurement process and guarantee the reliability of their data, studying the performance of their measurement system, in terms of linearity, bias, repeatability and reproducibility and stability. This issue is critical for automotive industry suppliers, who are required to be certified by the 16949:2016 standard (replaces the ISO/TS 16949) of International Automotive Task Force, defining the requirements of a quality management system for companies in the automotive industry. Measurement System Analysis (MSA) is one of the mandatory tools. Frequently, the measurement system in companies is not connected to the equipment and do not incorporate the methods proposed by the Automotive Industry Action Group (AIAG). To address these constraints, an R&D project is in progress, whose objective is to develop a web and cloud-based MSA tool. This MSA tool incorporates Industry 4.0 concepts, such as, Internet of Things (IoT) protocols to assure the connection with the measuring equipment, cloud computing, artificial intelligence, statistical tools, and advanced mathematical algorithms. This paper presents the preliminary findings of the project. The web and cloud-based MSA tool is innovative because it implements all statistical tests proposed in the MSA-4 reference manual from AIAG as well as other emerging methods and techniques. As it is integrated with the measuring devices, it reduces the manual input of data and therefore the errors. The tool ensures traceability of all performed tests and can be used in quality laboratories and in the production lines. Besides, it monitors MSAs over time, allowing both the analysis of deviations from the variation of the measurements performed and the management of measurement equipment and calibrations. To develop the MSA tool a ten-step approach was implemented. Firstly, it was performed a benchmarking analysis of the current competitors and commercial solutions linked to MSA, concerning Industry 4.0 paradigm. Next, an analysis of the size of the target market for the MSA tool was done. Afterwards, data flow and traceability requirements were analysed in order to implement an IoT data network that interconnects with the equipment, preferably via wireless. The MSA web solution was designed under UI/UX principles and an API in python language was developed to perform the algorithms and the statistical analysis. Continuous validation of the tool by companies is being performed to assure real time management of the ‘big data’. The main results of this R&D project are: MSA Tool, web and cloud-based; Python API; New Algorithms to the market; and Style Guide of UI/UX of the tool. The MSA tool proposed adds value to the state of the art as it ensures an effective response to the new challenges of measurement systems, which are increasingly critical in production processes. Although the automotive industry has triggered the development of this innovative MSA tool, other industries would also benefit from it. Currently, companies from molds and plastics, chemical and food industry are already validating it.

Keywords: automotive Industry, industry 4.0, Internet of Things, IATF 16949:2016, measurement system analysis

Procedia PDF Downloads 212

Authors: Julio Jesus Salazar, Julio Jesus De Lama

Abstract:

the fundamental objective of hydrological studies applied to the engineering field is to determine the statistically consistent volumes or water flows that, in each case, allow us to size or design a series of elements or structures to effectively manage and develop a river basin. To determine these values, there are several ways of working within the framework of traditional hydrology: (1) Study each of the factors that influence the hydrological cycle, (2) Study the historical behavior of the hydrology of the area, (3) Study the historical behavior of hydrologically similar zones, and (4) Other studies (rain simulators or experimental basins). Of course, this range of studies in a certain basin is very varied and complex and presents the difficulty of collecting the data in real time. In this complex space, the study of variables can only be overcome by collecting and transmitting data to decision centers through the Internet of things and artificial intelligence. Thus, this research work implemented the learning project of the sub-basin of the Shullcas river in the Andean basin of the Mantaro river in Peru. The sensor firmware to collect and communicate hydrological parameter data was programmed and tested in similar basins of the European Union. The Machine Learning applications was programmed to choose the algorithms that direct the best solution to the determination of the rainfall-runoff relationship captured in the different polygons of the sub-basin. Tests were carried out in the mountains of Europe, and in the sub-basins of the Shullcas river (Huancayo) and the Yauli river (Jauja) with heights close to 5000 m.a.s.l., giving the following conclusions: to guarantee a correct communication, the distance between devices should not pass the 15 km. It is advisable to minimize the energy consumption of the devices and avoid collisions between packages, the distances oscillate between 5 and 10 km, in this way the transmission power can be reduced and a higher bitrate can be used. In case the communication elements of the devices of the network (internet of things) installed in the basin do not have good visibility between them, the distance should be reduced to the range of 1-3 km. The energy efficiency of the Atmel microcontrollers present in Arduino is not adequate to meet the requirements of system autonomy. To increase the autonomy of the system, it is recommended to use low consumption systems, such as the Ashton Raggatt McDougall or ARM Cortex L (Ultra Low Power) microcontrollers or even the Cortex M; and high-performance direct current (DC) to direct current (DC) converters. The Machine Learning System has initiated the learning of the Shullcas system to generate the best hydrology of the sub-basin. This will improve as machine learning and the data entered in the big data coincide every second. This will provide services to each of the applications of the complex system to return the best data of determined flows.

Keywords: hydrology, internet of things, machine learning, river basin

Procedia PDF Downloads 155

Authors: Devin Doos, Ashley Hughes, Trang Pham, Paul Barach, Rami Ahmed

Abstract:

Over 115,000 Health Care Workers (HCWs) have died from COVID-19, and millions have been infected while caring for patients. HCWs have filed thousands of safety complaints surrounding safety concerns due to Personal Protective Equipment (PPE) shortages, which included concerns around inadequate and PPE reuse. Protocols for donning and doffing PPE remain ambiguous, lacking an evidence-base, and often result in wide deviations in practice. PPE donning and doffing protocol deviations commonly result in self-contamination but have not been thoroughly addressed. No evidence-driven protocols provide guidance on protecting HCW during periods of PPE reuse. Objective: The aim of this study was to examine safety-related threats and risks to Health Care Workers (HCWs) due to the reuse of PPE among Emergency Department personnel. Method: We conducted a prospective observational study to examine the risks of reusing PPE. First, ED personnel were asked to don and doff PPE in a simulation lab. Each participant was asked to don and doff PPE five times, according to the maximum reuse recommendation set by the Centers for Disease Control and Prevention (CDC). Each participant was videorecorded; video recordings were reviewed and coded independently by at least 2 of the 3trained coders for safety behaviors and riskiness of actions. A third coder was brought in when the agreement between the 2 coders could not be reached. Agreement between coders was high (81.9%), and all disagreements (100%) were resolved via consensus. A bowtie risk assessment chart was constructed analyzing the factors that contribute to increased risks HCW are faced with due to PPE use and reuse. Agreement amongst content experts in the field of Emergency Medicine, Human Factors, and Anesthesiology was used to select aspects of health care that both contribute and mitigate risks associated with PPE reuse. Findings: Twenty-eight clinician participants completed five rounds of donning/doffing PPE, yielding 140 PPE donning/doffing sequences. Two emerging threats were associated with behaviors in donning, doffing, and re-using PPE: (i) direct exposure to contaminant, and (ii) transmission/spread of contaminant. Protective behaviors included: hand hygiene, not touching the patient-facing surface of PPE, and ensuring a proper fit and closure of all PPE materials. 100% of participants (n= 28) deviated from the CDC recommended order, and most participants (92.85%, n=26) self-contaminated at least once during reuse. Other frequent errors included failure to tie all ties on the PPE (92.85%, n=26) and failure to wash hands after a contamination event occurred (39.28%, n=11). Conclusions: There is wide variation and regular errors in how HCW don and doffPPE while including in reusing PPE that led to self-contamination. Some errors were deemed “recoverable”, such as hand washing after touching a patient-facing surface to remove the contaminant. Other errors, such as using a contaminated mask and accidentally spreading to the neck and face, can lead to compound risks that are unique to repeated PPE use. A more comprehensive understanding of the contributing threats to HCW safety and complete approach to mitigating underlying risks, including visualizing with risk management toolsmay, aid future PPE designand workflow and space solutions.

Keywords: bowtie analysis, health care, PPE reuse, risk management

Procedia PDF Downloads 85

Authors: M. Arun, A. Kannan

Abstract:

Textile industries cater to varied customer preferences and contribute substantially to the economy. However, these textile industries also produce a considerable amount of effluents. Prominent among these are the azo dyes which impart considerable color and toxicity even at low concentrations. Azo dyes are also used as coloring agents in food and pharmaceutical industry. Despite their applications, azo dyes are also notorious pollutants and carcinogens. Popular techniques like photo-degradation, biodegradation and the use of oxidizing agents are not applicable for all kinds of dyes, as most of them are stable to these techniques. Chemical coagulation produces a large amount of toxic sludge which is undesirable and is also ineffective towards a number of dyes. Most of the azo dyes are stable to UV-visible light irradiation and may even resist aerobic degradation. Adsorption has been the most preferred technique owing to its less cost, high capacity and process efficiency and the possibility of regenerating and recycling the adsorbent. Adsorption is also most preferred because it may produce high quality of the treated effluent and it is able to remove different kinds of dyes. However, the adsorption process is influenced by many variables whose inter-dependence makes it difficult to identify optimum conditions. The variables include stirring speed, temperature, initial concentration and adsorbent dosage. Further, the internal diffusional resistance inside the adsorbent particle leads to slow uptake of the solute within the adsorbent. Hence, it is necessary to identify optimum conditions that lead to high capacity and uptake rate of these pollutants. In this work, commercially available activated carbon was chosen as the adsorbent owing to its high surface area. A typical azo dye found in textile effluent waters, viz. the monoazo Acid Orange 10 dye (CAS: 1936-15-8) has been chosen as the representative pollutant. Adsorption studies were mainly focused at obtaining equilibrium and kinetic data for the batch adsorption process at different process conditions. Studies were conducted at different stirring speed, temperature, adsorbent dosage and initial dye concentration settings. The Full Factorial Design was the chosen statistical design framework for carrying out the experiments and identifying the important factors and their interactions. The optimum conditions identified from the experimental model were validated with actual experiments at the recommended settings. The equilibrium and kinetic data obtained were fitted to different models and the model parameters were estimated. This gives more details about the nature of adsorption taking place. Critical data required to design batch adsorption systems for removal of Acid Orange 10 dye and identification of factors that critically influence the separation efficiency are the key outcomes from this research.

Keywords: acid orange 10, activated carbon, optimum adsorption conditions, statistical design

Procedia PDF Downloads 168

Authors: Norbert Magyar, Jozsef Kovacs, Peter Tanos, Balazs Trasy, Tamas Garamhegyi, Istvan Gabor Hatvani

Abstract:

Water is one of the most important common resources, and as a result of urbanization, agriculture, and industry it is becoming more and more exposed to potential pollutants. The prevention of the deterioration of water quality is a crucial role for environmental scientist. To achieve this aim, the operation of monitoring networks is necessary. In general, these networks have to meet many important requirements, such as representativeness and cost efficiency. However, existing monitoring networks often include sampling sites which are unnecessary. With the elimination of these sites the monitoring network can be optimized, and it can operate more economically. The aim of this study is to illustrate the applicability of the CCDA (Combined Cluster and Discriminant Analysis) to the field of water quality monitoring and optimize the monitoring networks of a river (the Danube), a wetland-lake system (Kis-Balaton & Lake Balaton), and two surface-subsurface water systems on the watershed of Lake Neusiedl/Lake Fertő and on the Szigetköz area over a period of approximately two decades. CCDA combines two multivariate data analysis methods: hierarchical cluster analysis and linear discriminant analysis. Its goal is to determine homogeneous groups of observations, in our case sampling sites, by comparing the goodness of preconceived classifications obtained from hierarchical cluster analysis with random classifications. The main idea behind CCDA is that if the ratio of correctly classified cases for a grouping is higher than at least 95% of the ratios for the random classifications, then at the level of significance (α=0.05) the given sampling sites don’t form a homogeneous group. Due to the fact that the sampling on the Lake Neusiedl/Lake Fertő was conducted at the same time at all sampling sites, it was possible to visualize the differences between the sampling sites belonging to the same or different groups on scatterplots. Based on the results, the monitoring network of the Danube yields redundant information over certain sections, so that of 12 sampling sites, 3 could be eliminated without loss of information. In the case of the wetland (Kis-Balaton) one pair of sampling sites out of 12, and in the case of Lake Balaton, 5 out of 10 could be discarded. For the groundwater system of the catchment area of Lake Neusiedl/Lake Fertő all 50 monitoring wells are necessary, there is no redundant information in the system. The number of the sampling sites on the Lake Neusiedl/Lake Fertő can decrease to approximately the half of the original number of the sites. Furthermore, neighbouring sampling sites were compared pairwise using CCDA and the results were plotted on diagrams or isoline maps showing the location of the greatest differences. These results can help researchers decide where to place new sampling sites. The application of CCDA proved to be a useful tool in the optimization of the monitoring networks regarding different types of water bodies. Based on the results obtained, the monitoring networks can be operated more economically.

Keywords: combined cluster and discriminant analysis, cost efficiency, monitoring network optimization, water quality

Procedia PDF Downloads 346

Authors: Loganathan Kumaresan, Velusamy Chidambaram, Arumugam Velayutham Karthikeyani, Alex Cheru Pulikottil, Madhusudan Sau, Gurpreet Singh Kapur, Sankara Sri Venkata Ramakumar

Abstract:

Environmentally driven regulations throughout the world stipulate dramatic improvements in the quality of transportation fuels and refining operations. The exhaust gases like CO, NOx, and SOx from stationary sources (e.g., refinery) and motor vehicles contribute to a large extent for air pollution. The refining industry is under constant environmental pressure to achieve more rigorous standards on sulphur content in the fuel used in the transportation sector and other off-gas emissions. Fluid catalytic cracking unit (FCCU) is a major secondary process in refinery for gasoline and diesel production. CO-combustion promoter additive and gasoline sulphur reduction (GSR) additive are catalytic systems used in FCCU to assist the combustion of CO to CO₂ in the regenerator and regulate sulphur in gasoline faction respectively along with main FCC catalyst. Effectiveness of these catalysts is governed by the active metal used, its dispersion, the type of base material employed, and retention characteristics of additive in FCCU such as attrition resistance and density. The challenge is to have a high-density microsphere catalyst support for its retention and high activity of the active metals as these catalyst additives are used in low concentration compare to the main FCC catalyst. The present paper discusses in the first part development of high dense microsphere of nanocrystalline alumina by hydro-thermal method for CO combustion promoter application. Performance evaluation of additive was conducted under simulated regenerator conditions and shows CO combustion efficiency above 90%. The second part discusses the efficacy of a co-precipitation method for the generation of the active crystalline spinels of Zn, Mg, and Cu with aluminium oxides as an additive. The characterization and micro activity test using heavy combined hydrocarbon feedstock at FCC unit conditions for evaluating gasoline sulphur reduction activity are studied. These additives were characterized by X-Ray Diffraction, NH₃-TPD & N₂ sorption analysis, TPR analysis to establish structure-activity relationship. The reaction of sulphur removal mechanisms involving hydrogen transfer reaction, aromatization and alkylation functionalities are established to rank GSR additives for their activity, selectivity, and gasoline sulphur removal efficiency. The sulphur shifting in other liquid products such as heavy naphtha, light cycle oil, and clarified oil were also studied. PIONA analysis of liquid product reveals 20-40% reduction of sulphur in gasoline without compromising research octane number (RON) of gasoline and olefins content.

Keywords: hydrothermal, nanocrystalline, spinel, sulphur reduction

Procedia PDF Downloads 95

Authors: Ellana Boada, Eric Santos-Clotas, Alba Cabrera-Codony, Maria Martin, Lluis Baneras, Frederic Gich

Abstract:

Volatile methylsiloxanes (VMS) are a group of manmade silicone compounds widely used in household and industrial applications that end up on the biogas produced through the anaerobic digestion of organic matter in landfills and wastewater treatment plants. The presence of VMS during the biogas energy conversion can cause damage on the engines, reducing the efficiency of this renewable energy source. Non regenerative adsorption onto activated carbon is the most widely used technology to remove siloxanes from biogas, while new trends point out that biotechnology offers a low-cost and environmentally friendly alternative to conventional technologies. The first objective of this research was to enrich, isolate and identify bacterial species able to grow using siloxane molecules as a sole carbon source: anoxic wastewater sludge was used as initial inoculum in liquid anoxic enrichments, adding D4 (as representative siloxane compound) previously adsorbed on activated carbon. After several months of acclimatization, liquid enrichments were plated onto solid media containing D4 and thirty-four bacterial isolates were obtained. 16S rRNA gene sequencing allowed the identification of strains belonging to the following species: Ciceribacter lividus, Alicycliphilus denitrificans, Pseudomonas aeruginosa and Pseudomonas citronellolis which are described to be capable to degrade toxic volatile organic compounds. Kinetic assays with 8 representative strains revealed higher cell growth in the presence of D4 compared to the control. Our second objective was to characterize the community composition and diversity of the microbial community present in the enrichments and to elucidate whether the isolated strains were representative members of the community or not. DNA samples were extracted, the 16S rRNA gene was amplified (515F & 806R primer pair), and the microbiome analyzed from sequences obtained with a MiSeq PE250 platform. Results showed that the retrieved isolates only represented a minor fraction of the microorganisms present in the enrichment samples, which were represented by Alpha, Beta, and Gamma proteobacteria as dominant groups in the category class thus suggesting that other microbial species and/or consortia may be important for D4 biodegradation. These results highlight the need of additional protocols for the isolation of relevant D4 degraders. Currently, we are developing molecular tools targeting key genes involved in siloxane biodegradation to identify and quantify the capacity of the isolates to metabolize D4 in batch cultures supplied with a synthetic gas stream of air containing 60 mg m⁻³ of D4 together with other volatile organic compounds found in the biogas mixture (i.e. toluene, hexane and limonene). The isolates were used as inoculum in a biotrickling filter containing lava rocks and activated carbon to assess their capacity for siloxane removal. Preliminary results of biotrickling filter performance showed 35% of siloxane biodegradation in a contact time of 14 minutes, denoting that biological siloxane removal is a promising technology for biogas upgrading.

Keywords: bacterial cultivation, biogas upgrading, microbiome, siloxanes

Procedia PDF Downloads 256

Authors: A. F. Jaber, E. Dean, M. Liu, J. He, D. Sabata, J. Radel

Abstract:

Background: Stroke is a serious health care concern and a major cause of disability in the United States. This condition impacts the individual’s functional ability to perform daily activities. Predicting functional performance of people with stroke assists health care professionals in optimizing the delivery of health services to the affected individuals. The purpose of this study was to identify significant predictors of Motor FIM and of Cognitive FIM subscores among individuals with stroke after discharge from inpatient rehabilitation (typically 4-6 weeks after stroke onset). A second purpose is to explore the relation among personal characteristics, health status, and functional performance of daily activities within 2 weeks of stroke onset. Methods: This study used a retrospective chart review to conduct a secondary analysis of data obtained from the Healthcare Enterprise Repository for Ontological Narration (HERON) database. The HERON database integrates de-identified clinical data from seven different regional sources including hospital electronic medical record systems of the University of Kansas Health System. The initial HERON data extract encompassed 1192 records and the final sample consisted of 207 participants who were mostly white (74%) males (55%) with a diagnosis of ischemic stroke (77%). The outcome measures collected from HERON included performance scores on the National Institute of Health Stroke Scale (NIHSS), the Glasgow Coma Scale (GCS), and the Functional Independence Measure (FIM). The data analysis plan included descriptive statistics, Pearson correlation analysis, and Stepwise regression analysis. Results: significant predictors of discharge Motor FIM subscores included age, baseline Motor FIM subscores, discharge NIHSS scores, and comorbid electrolyte disorder (R2 = 0.57, p <0.026). Significant predictors of discharge Cognitive FIM subscores were age, baseline cognitive FIM subscores, client cooperative behavior, comorbid obesity, and the total number of comorbidities (R2 = 0.67, p <0.020). Functional performance on admission was significantly associated with age (p < 0.01), stroke severity (p < 0.01), and length of hospital stay (p < 0.05). Conclusions: our findings show that younger age, good motor and cognitive abilities on admission, mild stroke severity, fewer comorbidities, and positive client attitude all predict favorable functional outcomes after inpatient stroke rehabilitation. This study provides health care professionals with evidence to evaluate predictors of favorable functional outcomes early at stroke rehabilitation, to tailor individualized interventions based on their client’s anticipated prognosis, and to educate clients about the benefits of making lifestyle changes to improve their anticipated rate of functional recovery.

Keywords: functional performance, predictors, stroke, recovery

Procedia PDF Downloads 142

Authors: Douglas E. Mainhart, Alejandro Fierro-Cabo, Bradley Christoffersen, Charlotte Reemts

Abstract:

Semi-arid ecosystems across the globe have faced land conversion for agriculture and resource extraction activities, posing a threat to the important ecosystem services they provide. Revegetation-centered restoration efforts in these regions face low success rates due to limited soil water availability and high temperatures leading to elevated seedling mortality after planting. Typical methods to alleviate these stresses require costly post-planting interventions aimed at improving soil moisture status. We set out to evaluate the efficacy of applying in-nursery treatments to address transplant shock. Four native Tamaulipan thornscrub species were compared. Three treatments were applied: elevated CO2, drought hardening (four-week exposure each), and antitranspirant foliar spray (the day prior to planting). Our goal was to answer two primary questions: (1) Do treatments improve survival and growth of seedlings in the early period post-planting? (2) If so, what underlying physiological changes are associated with this improved performance? To this end, we measured leaf gas exchange (stomatal conductance, light saturated photosynthetic rate, water use efficiency), leaf morphology (specific leaf area), and osmolality before and upon the conclusion of treatments. A subset of seedlings from all treatments have been planted, which will be monitored in coming months for in-field survival and growth.First month field survival for all treatment groups were high due to ample rainfall following planting (>85%). Growth data was unreliable due to high herbivory (68% of all sampled plants). While elevated CO2 had infrequent or no detectable influence on all aspects of leaf gas exchange, drought hardening reduced stomatal conductance in three of the four species measured without negatively impacting photosynthesis. Both CO2 and drought hardening elevated leaf osmolality in two species. Antitranspirant application significantly reduced conductance in all species for up to four days and reduced photosynthesis in two species. Antitranspirants also increased the variability of water use efficiency compared to controls. Collectively, these results suggest that antitranspirants and drought hardening are viable treatments for reducing short-term water loss during the transplant shock period. Elevated CO2, while not effective at reducing water loss, may be useful for promoting more favorable water status via osmotic adjustment. These practices could improve restoration outcomes in Tamaulipan thornscrub and other semi-arid systems. Further research should focus on evaluating combinations of these treatments and their species-specific viability.

Keywords: conservation, drought conditioning, semi-arid restoration, plant physiology

Procedia PDF Downloads 84

Authors: Soraia V. M. de Sá, Miguel A. Faria, José O. Fernandes, Sara C. Cunha

Abstract:

Cereals play a vital role in fulfilling the nutritional needs of children, supplying essential nutrients crucial for their growth and development. However, concerns arise due to children's heightened vulnerability due to their unique physiology, specific dietary requirements, and relatively higher intake in relation to their body weight. This vulnerability exposes them to harmful food contaminants, particularly mycotoxins, prevalent in cereals. Because of the thermal stability of mycotoxins, conventional industrial food processing often falls short of eliminating them. Children, especially those aged 4 months to 12 years, frequently encounter mycotoxins through the consumption of specialized food products, such as instant foods, breakfast cereals, bars, cookie snacks, fruit puree, and various dairy items. A close monitoring of this demographic group's exposure to mycotoxins is essential, as toxins ingestion may weaken children’s immune systems, reduce their resistance to infectious diseases, and potentially lead to cognitive impairments. The severe toxicity of mycotoxins, some of which are classified as carcinogenic, has spurred the establishment and ongoing revision of legislative limits on mycotoxin levels in food and feed globally. While EU Commission Regulation 1881/2006 addresses well-known mycotoxins in processed cereal-based foods and infant foods, the absence of regulations specifically addressing emerging mycotoxins underscores a glaring gap in the regulatory framework, necessitating immediate attention. Emerging mycotoxins have gained mounting scrutiny in recent years due to their pervasive presence in various foodstuffs, notably cereals and cereal-based products. Alarmingly, exposure to multiple mycotoxins is hypothesized to exhibit higher toxicity than isolated effects, raising particular concerns for products primarily aimed at children. This study scrutinizes the presence of 22 mycotoxins of the diverse range of chemical classes in 148 processed cereal-based foods, including 39 breakfast cereals, 25 infant formulas, 27 snacks, 25 cereal bars, and 32 cookies commercially available in Portugal. The analytical approach employed a modified QuEChERS procedure followed by ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) analysis. Given the paucity of information on the risk assessment of children to multiple mycotoxins in cereal and cereal-based products consumed by children of Portugal pioneers the evaluation of this critical aspect. Overall, aflatoxin B1 (AFB1) and aflatoxin G2 (AFG2) emerged as the most prevalent regulated mycotoxins, while enniatin B (ENNB) and sterigmatocystin (STG) were the most frequently detected emerging mycotoxins.

Keywords: cereal-based products, children´s nutrition, food safety, UPLC-MS/MS analysis

Procedia PDF Downloads 66

Authors: Amarachukwu B. Isiaka, Vivian N. Anakwenze, Chinyere C. Ezemba, Chiamaka R. Ilodinso, Chikodili G. Anaukwu, Chukwuebuka M. Ezeokoli, Ugonna H. Uzoka

Abstract:

Infectious diseases continue to pose significant threats to global public health, necessitating advanced and timely detection methods for effective outbreak management. This study explores the integration of artificial intelligence (AI) in the early detection and management of infectious disease outbreaks. Leveraging vast datasets from diverse sources, including electronic health records, social media, and environmental monitoring, AI-driven algorithms are employed to analyze patterns and anomalies indicative of potential outbreaks. Machine learning models, trained on historical data and continuously updated with real-time information, contribute to the identification of emerging threats. The implementation of AI extends beyond detection, encompassing predictive analytics for disease spread and severity assessment. Furthermore, the paper discusses the role of AI in predictive modeling, enabling public health officials to anticipate the spread of infectious diseases and allocate resources proactively. Machine learning algorithms can analyze historical data, climatic conditions, and human mobility patterns to predict potential hotspots and optimize intervention strategies. The study evaluates the current landscape of AI applications in infectious disease surveillance and proposes a comprehensive framework for their integration into existing public health infrastructures. The implementation of an AI-driven early detection system requires collaboration between public health agencies, healthcare providers, and technology experts. Ethical considerations, privacy protection, and data security are paramount in developing a framework that balances the benefits of AI with the protection of individual rights. The synergistic collaboration between AI technologies and traditional epidemiological methods is emphasized, highlighting the potential to enhance a nation's ability to detect, respond to, and manage infectious disease outbreaks in a proactive and data-driven manner. The findings of this research underscore the transformative impact of harnessing AI for early detection and management, offering a promising avenue for strengthening the resilience of public health systems in the face of evolving infectious disease challenges. This paper advocates for the integration of artificial intelligence into the existing public health infrastructure for early detection and management of infectious disease outbreaks. The proposed AI-driven system has the potential to revolutionize the way we approach infectious disease surveillance, providing a more proactive and effective response to safeguard public health.

Keywords: artificial intelligence, early detection, disease surveillance, infectious diseases, outbreak management

Procedia PDF Downloads 60

Authors: Ivana Cabarkapa, Zorica Tomicic, Olivera Duragic

Abstract:

Antimicrobial resistance represents one of the major challenges facing humanity in the last decades. Increasing antibiotic-resistant pathogens indicates the need for the development of alternative antibacterial drugs and new treatment strategies. One of the innovative emerging treatments in overcoming multidrug-resistant pathogens certainly represents the inhibition anti-quorum sensing system. For most of the food-borne pathogens, the expression of the virulence depends on their capability communication with other members of the population by means of quorum sensing (QS). QS represents a specific way of bacterial intercellular communication, which enabled owing to their ability to detect and to respond to cell population density by gene regulation. QS mechanisms are responsible for controls the pathogenesis, virulence luminescence, motility, sporulation and biofilm formation of many organisms by regulating gene expression. Therefore, research in this field is being an attractive target for the development of new natural antibacterial agents. Anti-QS compounds are known to have the ability to prohibit bacterial pathogenicity. Considering the importance of quorum sensing during bacterial pathogenesis, this research has been focused on evaluation anti - QS properties of four essential oils (EOs) Origanum heracleoticum, Origanum vulgare, Thymus vulgare, and Thymus serpyllum, using biomonitor strain of Chromobacterium violaceum CV026. Tests conducted on Luria Bertani agar supplemented with N hexanol DL homoserine lacton (HHL) 10µl/50ml of agar. The anti-QS potential of the EOs was assayed in a range of concentrations of 200 – 0.39 µl/ml using the disc diffusion method. EOs of Th. vulgaris and T. serpyllum were exhibited anti-QS activity indicated by a non- pigmented ring with a dilution-dependent manner. The lowest dilution of EOs T. vulgaris and T. serpyllum in which they exhibited visually detectable inhibition of violacein synthesis was 6.25 µl/ml for both tested EOs. EOs of O. heracleoticum and O. vulgare were displayed different active principles, i.e., antimicrobial activity indicated by the inner clear ring and anti-QS activity indicated by the outer non-pigmented ring, in a concentration-dependent manner. The lowest dilution of EOs of O. heracleoticum and O. vulgare in which exhibited visually detectable inhibition of violacein synthesis was 1.56 and 3.25 µl/ml, respectively. Considering that, the main constituents of the tested EOs represented by monoterpenes (carvacrol, thymol, γ-terpinene, and p-cymene), anti - QS properties of tested EOs can be mainly attributed to their activity. In particular, from the scientific literature, carvacrol and thymol show a sub-inhibitory effect against foodborne pathogens. Previous studies indicated that sub-lethal concentrations of carvacrol reduced the mobility of bacteria due to the ability of interference using QS mechanism between the bacterial cells, and thereby reducing the ability of biofilm formation The precise mechanism by which carvacrol inhibits biofilm formation is still not fully understood. Our results indicated that EOs displayed different active principles, i.e., antimicrobial activity indicated by the inner clear ring and anti-QS activity indicated by an outer non- pigmented ring with visually detectable inhibition of violacein. Preliminary results suggest that EOs represent a promising alternative for effective control of the emergence and spread of resistant pathogens.

Keywords: anti-quorum sensing activity, Chromobacterium violaceum, essential oils, violacein

Procedia PDF Downloads 130

Authors: Winnie Kung, Xinhua Liu, Debbie Huang, Patricia Kim, Keon Kim, Xiaoran Wang, Lawrence Yang

Abstract:

Considerable Asian Americans were exposed to the World Trade Center attack due to the proximity of the site to Chinatown and a sizeable number of South Asians working in the collapsed and damaged buildings nearby. Few studies focused on Asians in examining the disaster’s mental health impact, and even less longitudinal studies were reported beyond the first couple of years after the event. Based on the World Trade Center Health Registry, this study examined the trajectory of PTSD of individuals directly exposed to the attack from 2-3 to 5-6 years after the attack, comparing Asians against the non-Hispanic White group. Participants included 2,431 Asians and 31,455 Whites. Trajectories were delineated into the resilient, chronic, delayed-onset and remitted groups using PTSD checklist cut-off score at 44 at the 2 waves. Logistic regression analyses were conducted to compare the poorer trajectories against the resilient as a reference group, using predictors of baseline sociodemographic, exposure to the disaster, lower respiratory symptoms and previous depression/anxiety disorder diagnosis, and recruitment source as the control variable. Asians had significant lower socioeconomic status in terms of income, education and employment status compared to Whites. Over 3/4 of participants from both races were resilient, though slightly less for Asians than Whites (76.5% vs 79.8%). Asians had a higher proportion with chronic PTSD (8.6% vs 7.4%) and remission (5.9% vs 3.4%) than Whites. A considerable proportion of participants had delayed-onset in both races (9.1% Asians vs 9.4% Whites). The distribution of trajectories differed significantly by race (p<0.0001) with Asians faring poorer. For Asians, in the chronic vs resilient group, significant protective factors included age >65, annual household income >$50,000, and never married vs married/cohabiting; risk factors were direct disaster exposure, job loss due to 9/11, lost someone, and tangible loss; lower respiratory symptoms and previous mental disorder diagnoses. Similar protective and risk factors were noted for the delayed-onset group, except education being protective; and being an immigrant a risk. Between the 2 comparisons, the chronic group was more vulnerable than the delayed-onset as expected. It should also be noted that in both comparisons, Asians’ current employment status had no significant impact on their PTSD trajectory. Comparing between Asians against Whites, the direction of the relationships between the predictors and the PTSD trajectories were mostly the same, although more factors were significant for Whites than for Asians. A few factors showed significant racial difference: Higher risk for lower respiratory symptoms for Whites than Asians, higher risk for pre-9/11 mental disorder diagnosis for Asians than Whites, and immigrant a risk factor for the remitted vs resilient groups for Whites but not for Asians. Over 17% Asians still suffered from PTSD 5-6 years after the WTC attack signified its persistent impact which incurred substantial human, social and economic costs. The more disadvantaged socioeconomic status of Asians rendered them more vulnerable in their mental health trajectories relative to Whites. Together with their well-documented low tendency to seek mental health help, outreach effort to this population is needed to ensure follow-up treatment and prevention.

Keywords: PTSD, Asian Americans, World Trade Center Attack, racial differences

Procedia PDF Downloads 260

Authors: Milu T. Cherian, Sergio C. Chai, Morgan A. Casal, Taosheng Chen

Abstract:

This study aims to use CINPA1, a recently discovered small-molecule inhibitor of the xenobiotic receptor CAR (constitutive androstane receptor) for understanding the binding modes of CAR and to guide CAR-mediated gene expression profiling studies in human primary hepatocytes. CAR and PXR are xenobiotic sensors that respond to drugs and endobiotics by modulating the expression of metabolic genes that enhance detoxification and elimination. Elevated levels of drug metabolizing enzymes and efflux transporters resulting from CAR activation promote the elimination of chemotherapeutic agents leading to reduced therapeutic effectiveness. Multidrug resistance in tumors after chemotherapy could be associated with errant CAR activity, as shown in the case of neuroblastoma. CAR inhibitors used in combination with existing chemotherapeutics could be utilized to attenuate multidrug resistance and resensitize chemo-resistant cancer cells. CAR and PXR have many overlapping modulating ligands as well as many overlapping target genes which confounded attempts to understand and regulate receptor-specific activity. Through a directed screening approach we previously identified a new CAR inhibitor, CINPA1, which is novel in its ability to inhibit CAR function without activating PXR. The cellular mechanisms by which CINPA1 inhibits CAR function were also extensively examined along with its pharmacokinetic properties. CINPA1 binding was shown to change CAR-coregulator interactions as well as modify CAR recruitment at DNA response elements of regulated genes. CINPA1 was shown to be broken down in the liver to form two, mostly inactive, metabolites. The structure-activity differences of CINPA1 and its metabolites were used to guide computational modeling using the CAR-LBD structure. To rationalize how ligand binding may lead to different CAR pharmacology, an analysis of the docked poses of human CAR bound to CITCO (a CAR activator) vs. CINPA1 or the metabolites was conducted. From our modeling, strong hydrogen bonding of CINPA1 with N165 and H203 in the CAR-LBD was predicted. These residues were validated to be important for CINPA1 binding using single amino-acid CAR mutants in a CAR-mediated functional reporter assay. Also predicted were residues making key hydrophobic interactions with CINPA1 but not the inactive metabolites. Some of these hydrophobic amino acids were also identified and additionally, the differential coregulator interactions of these mutants were determined in mammalian two-hybrid systems. CINPA1 represents an excellent starting point for future optimization into highly relevant probe molecules to study the function of the CAR receptor in normal- and pathophysiology, and possible development of therapeutics (for e.g. use for resensitizing chemoresistant neuroblastoma cells).

Keywords: antagonist, chemoresistance, constitutive androstane receptor (CAR), multi-drug resistance, structure activity relationship (SAR), xenobiotic resistance

Procedia PDF Downloads 279

Authors: A. V. Samokhin, A. A. Fadeev, M. A. Sinaiskii, N. V. Alekseev, A. V. Kolesnikov

Abstract:

Composite materials where metal matrix is reinforced by ceramic or metal particles are of great interest for use in the manufacturing of electrical contacts. Significant improvement of the composite physical and mechanical properties as well as increase of the performance parameters of composite-based products can be achieved if the nanoscale structure in the composite materials is obtained by using nanosized powders as starting components. The results of nanosized composite powders synthesis (Ag-SnO2, W-Cu and Cu-C) in the DC thermal plasma flows are presented in this paper. The investigations included the following processes: - Recondensation of micron powder mixture Ag + SnO2 in a nitrogen plasma; - The reduction of the oxide powders mixture (WO3 + CuO) in a hydrogen-nitrogen plasma; - Decomposition of the copper formate and copper acetate powders in nitrogen plasma. The calculations of equilibrium compositions of multicomponent systems Ag-Sn-O-N, W-Cu-O-H-N and Cu-O-C-H-N in the temperature range of 400-5000 K were carried to estimate basic process characteristics. Experimental studies of the processes were performed using a plasma reactor with a confined jet flow. The plasma jet net power was in the range of 2 - 13 kW, and the feedstock flow rate was up to 0.35 kg/h. The obtained powders were characterized by TEM, HR-TEM, SEM, EDS, ED-XRF, XRD, BET and QEA methods. Nanocomposite Ag-SnO2 (12 wt. %). Processing of the initial powder mixture (Ag-SnO2) in nitrogen thermal plasma stream allowed to produce nanopowders with a specific surface area up to 24 m2/g, consisting predominantly of particles with size less than 100 nm. According to XRD results, tin was present in the obtained products as SnO2 phase, and also as intermetallic phases AgxSn. Nanocomposite W-Cu (20 wt .%). Reduction of (WO3+CuO) mixture in the hydrogen-nitrogen plasma provides W-Cu nanopowder with particle sizes in the range of 10-150 nm. The particles have mainly spherical shape and structure tungsten core - copper shell. The thickness of the shell is about several nanometers, the shell is composed of copper and its oxides (Cu2O, CuO). The nanopowders had 1.5 wt. % oxygen impurity. Heat treatment in a hydrogen atmosphere allows to reduce the oxygen content to less than 0.1 wt. %. Nanocomposite Cu-C. Copper nanopowders were found as products of the starting copper compounds decomposition. The nanopowders primarily had a spherical shape with a particle size of less than 100 nm. The main phase was copper, with small amount of Cu2O and CuO oxides. Copper formate decomposition products had a specific surface area 2.5-7 m2/g and contained 0.15 - 4 wt. % carbon; and copper acetate decomposition products had the specific surface area 5-35 m2/g, and carbon content of 0.3 - 5 wt. %. Compacting of nanocomposites (sintering in hydrogen for Ag-SnO2 and electric spark sintering (SPS) for W-Cu) showed that the samples having a relative density of 97-98 % can be obtained with a submicron structure. The studies indicate the possibility of using high-intensity plasma processes to create new technologies to produce nanocomposite materials for electric contacts.

Keywords: electrical contact, material, nanocomposite, plasma, synthesis

Procedia PDF Downloads 230