Search results for: dynamic algorithm

Authors: Delphine Mukaneza, Lin Qiao, Wang Pengxin, Li Yan, Chen Yingyi

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Human activities on land use make the land-cover gradually change or transit. In this study, we examined the use of Landsat TM data to detect the land use change of Kigali between 1987 and 2009 using remote sensing techniques and analysis of data using ENVI and ArcGIS, a GIS software. Six different categories of land use were distinguished: bare soil, built up land, wetland, water, vegetation, and others. With remote sensing techniques, we analyzed land use data in 1987, 1999 and 2009, changed areas were found and a dynamic situation of land use in Kigali city was found during the 22 years studied. According to relevant Landsat data, the research focused on land use change in accordance with the role of remote sensing in the process of urbanization. The result of the work has shown the rapid increase of built up land between 1987 and 1999 and a big decrease of vegetation caused by the rebuild of the city after the 1994 genocide, while in the period of 1999 to 2009 there was a reduction in built up land and vegetation, after the authority of Kigali city established, a Master Plan where all constructions which were not in the range of the master Plan were destroyed. Rwanda's capital, Kigali City, through the expansion of the urban area, it is increasing the internal employment rate and attracts business investors and the service sector to improve their economy, which will increase the population growth and provide a better life. The overall planning of the city of Kigali considers the environment, land use, infrastructure, cultural and socio-economic factors, the economic development and population forecast, urban development, and constraints specification. To achieve the above purpose, the Government has set for the overall planning of city Kigali, different stages of the detailed description of the design, strategy and action plan that would guide Kigali planners and members of the public in the future to have more detailed regional plans and practical measures. Thus, land use change is significantly the performance of Kigali active human area, which plays an important role for the country to take certain decisions. Another area to take into account is the natural situation of Kigali city. Agriculture in the region does not occupy a dominant position, and with the population growth and socio-economic development, the construction area will gradually rise and speed up the process of urbanization. Thus, as a developing country, Rwanda's population continues to grow and there is low rate of utilization of land, where urbanization remains low. As mentioned earlier, the 1994 genocide massacres, population growth and urbanization processes, have been the factors driving the dramatic changes in land use. The focus on further research would be on analysis of Rwanda’s natural resources, social and economic factors that could be, the driving force of land use change.

Keywords: land use change, urbanization, Kigali City, Landsat

Procedia PDF Downloads 287

Authors: Niraimathi Kesavan, Sangeeta Sharma, Deepa Jagan, Sridhar Sukumar, Mohan Ramachandran, Vidhubala Elangovan

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Background: Childhood is a dynamic period for growth and development. Optimum nutrition during this period forms a strong foundation for growth, development, resistance to infections, long-term good health, cognition, educational achievements, and work productivity in a later phase of life. Underprivileged children living in a resource constraint settings like shelter homes are at high risk of malnutrition due to poor quality diet and nutritional inadequacy. In low-income countries, underprivileged children are vulnerable to being deprived of nutritious food, which stands as a major challenge in the health sector. The present aims to assess the dietary intake, nutritional status, and nutritional inadequacy and their association with malnutrition among children residing in shelter homes in rural Tamil Nadu. Methods: The study was a descriptive survey conducted among all the children aged between 8-18 years residing in two selected shelter homes (Anbu illam, a home for female children, and Amaidhi illam, a home for male children), rural Tirunelveli, Tamil Nadu, India. A total of 57 children were recruited, including 18 boys and 39 girls, for the study. Dietary intake was measured using seven days 24 hours recall. The average nutrient intake was considered for further analysis. Results: Of the 57 children, about 60% (n=35) were undernutrition. The mean daily energy intake was 1298 (SD 180) kcal for boys and 952 (SD155) kcal for girls. The total calorie intake was 55-60% below the estimated average requirement (EAR) for adolescent boys and girls in the age group 13-15 years and 16-18 years. Carbohydrates were the major source of energy (boys 53% and girls 51%), followed by fat (boys 31.5% and girls 34.5%) and protein (boys 14% and girls 12.9%). Dairy intake (<200ml/day) was less than the recommendation (500ml/day). Micro-nutrient-rich foods such as fruits, vegetables, and green leafy vegetables in the diet were <200g/day, which was far less than the recommended dietary guidelines of 400g- 600g/day for the age group of 7-18 years. Nearly 26% of girls reported experiencing menstrual problems. The majority (76.9%) of the children exhibited nutrient deficiency-related signs and symptoms. Conclusion: The total energy, minerals, and micro-nutrient intake were inadequate and below the Recommended Dietary Allowance for children and adolescents. The diet predominantly consists of refined cereals, rice, semolina, and vermicelli. Consumption of whole grains, milk, fruits, vegetables, and leafy vegetables was far below the recommended dietary guidelines. Dietary inadequacies among these children pose a serious concern for their overall health status and its consequences in the later phase of life.

Keywords: adolescents, children, dietary intake, malnutrition, nutritional inadequacy, shelter home

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Authors: L. P. Gomes, G. F. Araújo, Y. M. L. Cordeiro, C. T. Andrade, E. M. Del Aguila, V. M. F. Paschoalin

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The application of nanoscale materials and nanostructures is an emerging area, these since materials may provide solutions to technological and environmental challenges in order to preserve the environment and natural resources. To reach this goal, the increasing demand must be accompanied by 'green' synthesis methods. Chitosan is a natural, nontoxic, biopolymer derived by the deacetylation of chitin and has great potential for a wide range of applications in the biological and biomedical areas, due to its biodegradability, biocompatibility, non-toxicity and versatile chemical and physical properties. Chitosan also presents high antimicrobial activities against a wide variety of pathogenic and spoilage microorganisms. Ultrasonication is a common tool for the preparation and processing of polymer nanoparticles. It is particularly effective in breaking up aggregates and in reducing the size and polydispersity of nanoparticles. High-intensity ultrasonication has the potential to modify chitosan molecular weight and, thus, alter or improve chitosan functional properties. The aim of this study was to evaluate the influence of sonication intensity and time on the changes of commercial chitosan characteristics, such as molecular weight and its potential antibacterial activity against Gram-negative bacteria. The nanoparticles (NPs) were produced from two commercial chitosans, of medium molecular weight (CS-MMW) and low molecular weight (CS-LMW) from Sigma-Aldrich®. These samples (2%) were solubilized in 100 mM sodium acetate pH 4.0, placed on ice and irradiated with an ultrasound SONIC ultrasonic probe (model 750 W), equipped with a 1/2" microtip during 30 min at 4°C. It was used on constant duty cycle and 40% amplitude with 1/1s intervals. The ultrasonic degradation of CS-MMW and CS-LMW were followed up by means of ζ-potential (Brookhaven Instruments, model 90Plus) and dynamic light scattering (DLS) measurements. After sonication, the concentrated samples were diluted 100 times and placed in fluorescence quartz cuvettes (Hellma 111-QS, 10 mm light path). The distributions of the colloidal particles were calculated from the DLS and ζ-potential are measurements taken for the CS-MMW and CS-LMW solutions before and after (CS-MMW30 and CS-LMW30) sonication for 30 min. Regarding the results for the chitosan sample, the major bands can be distinguished centered at Radius hydrodynamic (Rh), showed different distributions for CS-MMW (Rh=690.0 nm, ζ=26.52±2.4), CS-LMW (Rh=607.4 and 2805.4 nm, ζ=24.51±1.29), CS-MMW30 (Rh=201.5 and 1064.1 nm, ζ=24.78±2.4) and CS-LMW30 (Rh=492.5, ζ=26.12±0.85). The minimal inhibitory concentration (MIC) was determined using different chitosan samples concentrations. MIC values were determined against to E. coli (106 cells) harvested from an LB medium (Luria-Bertani BD™) after 18h growth at 37 ºC. Subsequently, the cell suspension was serially diluted in saline solution (0.8% NaCl) and plated on solid LB at 37°C for 18 h. Colony-forming units were counted. The samples showed different MICs against E. coli for CS-LMW (1.5mg), CS-MMW30 (1.5 mg/mL) and CS-LMW30 (1.0 mg/mL). The results demonstrate that the production of nanoparticles by modification of their molecular weight by ultrasonication is simple to be performed and dispense acid solvent addition. Molecular weight modifications are enough to provoke changes in the antimicrobial potential of the nanoparticles produced in this way.

Keywords: antimicrobial agent, chitosan, green production, nanoparticles

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Authors: Jollen Dai, Truman You, Xinyun Du, Katrina Liu

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Transportation is one of the leading sources of greenhouse gas emissions (GHG). Thus, to meet the Paris Agreement 2015, all countries must adopt a different and more sustainable transportation system. From bikes to Maglev, the world is slowly shifting to sustainable transportation. To develop a utility public transit system, a sustainable web of buses must be implemented. As of now, only a handful of cities have adopted a detailed plan to implement a full fleet of e-buses by the 2030s, with Shenzhen in the lead. Every change requires a detailed plan and a focused analysis of the impacts of the change. In this report, the economic implications and financial implications have been taken into consideration to develop a well-rounded 10-year plan for New York City. We also apply the same financial model to the other cities, LA and Chicago. We picked NYC, Chicago, and LA to conduct the comparative NPB analysis since they are all big metropolitan cities and have complex transportation systems. All three cities have started an action plan to achieve a full fleet of e-bus in the decades. Plus, their energy carbon footprint and their energy price are very different, which are the key factors to the benefits of electric buses. Using TCO (Total Cost Ownership) financial analysis, we developed a model to calculate NPB (Net Present Benefit) /and compare EBS (electric buses) to DBS (diesel buses). We have considered all essential aspects in our model: initial investment, including the cost of a bus, charger, and installation, government fund (federal, state, local), labor cost, energy (electricity or diesel) cost, maintenance cost, insurance cost, health and environment benefit, and V2G (vehicle to grid) benefit. We see about $1,400,000 in benefits for a 12-year lifetime of an EBS compared to DBS provided the government fund to offset 50% of EBS purchase cost. With the government subsidy, an EBS starts to make positive cash flow in 5th year and can pay back its investment in 5 years. Please remember that in our model, we consider environmental and health benefits, and every year, $50,000 is counted as health benefits per bus. Besides health benefits, the significant benefits come from the energy cost savings and maintenance savings, which are about $600,000 and $200,000 in 12-year life cycle. Using linear regression, given certain budget limitations, we then designed an optimal three-phase process to replace all NYC electric buses in 10 years, i.e., by 2033. The linear regression process is to minimize the total cost over the years and have the lowest environmental cost. The overall benefits to replace all DBS with EBS for NYC is over $2.1 billion by the year of 2033. For LA, and Chicago, the benefits for electrification of the current bus fleet are $1.04 billion and $634 million by 2033. All NPB analyses and the algorithm to optimize the electrification phase process are implemented in Python code and can be shared.

Keywords: financial modeling, total cost ownership, net present benefits, electric bus, diesel bus, NYC, LA, Chicago

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Authors: Alireza Barari, Ahmad Abdi

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Introduction: Plyometric training (PT) is popular among individuals involved in dynamic sports, and is executed with a goal to improve muscular performance. Cytokines are considered as immunoregulatory molecules for regulation of immune function and other body responses. In addition, the pro-inflammatory cytokines, TNF-α andIL-1β, have been reported to be increased during and after exercises. If some of the cytokines which cause responses such as inflammation of cells in skeletal muscles, with manipulating of training program or optimizing nutrition, it can be avoided or limited from those injuries caused by cytokines release. Its shows that mistletoe extracts show immune-modulating effects. Materials and methods: present study was to investigate the effect of six weeks PT with or without mistletoe supplementation (MS)(10 mg/kg) on cytokine responses and performance in male basketball players. This study is semi-experimental. Statistic society of this study was basketball player’s male students of Mahmoud Abad city. Statistic samples are concluded of 32 basketball players with an age range of 14–17 years was selected from randomly. Selection of samples in four groups of 8 individuals Participants were randomly assigned to either an experimental group (E, n=16) that performed plyometric exercises with (n=8) or without (n=8) MS, or a control group that rested (C, n=16) with (n=8) or without (n=8) MS. Plants were collected in June from the Mazandaran forest in north of Iran. Then they dried in exposure to air without any exposition to sunlight, on a clean textile. For better drying the plants were high and down until they lost their water. Each subject consumed 10 mg/kg/day of extract for six weeks of intervention. Pre and post-testing was performed in the afternoon of the same day. Blood samples (10 ml) were collected from the intermediate cubital vein of the subjects. Serum concentration of IL-1β and TNF-α were measured by ELISA method. Data analysis was performed using pretest to posttest changes that assessed by t-test for paired samples. After the last plyometric training program, the second blood samples were in the next day. Group differences at baseline were evaluated using One-way ANOVA (post-hock Tukey) test is used for analysis and comparison of three group’s variables. Results: PT with or without MS improved the one repetition maximum leg and chest press, Sargeant test and power in RAST (P < 0.05). However there were no statistically significant differences between groups in Vo2max measures (P > 0.05). PT resulted in a significant increase in plasma IL-1β concentration from 1.08±0.4 mg/ml in pre-training to 1.68±0.18 mg/ml in post-training (P=0.006). While the MS significantly decreased the training-induced increment of IL-1β (P=0.007). In contrast, neither PT nor MS had any effect on TNF-α levels (P > 0.05). Discussion: The results of this investigation indicate that PT improved muscular performance and increases the IL-1β concentration. Increasing of IL-1β after exercise in damaged skeletal muscle has shown of the role of this cytokine in inflammation processes and damaged skeletal muscle repair. However mistletoe supplementation ameliorates the increment of IL-1β levels, indicating the beneficial effect of mistletoe on immune response following plyometric training.

Keywords: mistletoe supplementation, training, IL-1β, TNF-α

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Authors: Sanjeev Kumar Appicharla

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This paper presents the results of the modelling and analysis of the European Railway Traffic Management (ERTMS) safety-critical incident to raise awareness of biases in the systems engineering process on the Cambrian Railway in the UK using the RAIB 17/2019 as a primary input. The RAIB, the UK independent accident investigator, published the Report- RAIB 17/2019 giving the details of their investigation of the focal event in the form of immediate cause, causal factors, and underlying factors and recommendations to prevent a repeat of the safety-critical incident on the Cambrian Line. The Systems for Investigation of Railway Interfaces (SIRI) is the methodology used to model and analyze the safety-critical incident. The SIRI methodology uses the Swiss Cheese Model to model the incident and identify latent failure conditions (potentially less than adequate conditions) by means of the management oversight and risk tree technique. The benefits of the systems for investigation of railway interfaces methodology (SIRI) are threefold: first is that it incorporates the “Heuristics and Biases” approach advanced by 2002 Nobel laureate in Economic Sciences, Prof Daniel Kahneman, in the management oversight and risk tree technique to identify systematic errors. Civil engineering and programme management railway professionals are aware of the role “optimism bias” plays in programme cost overruns and are aware of bow tie (fault and event tree) model-based safety risk modelling techniques. However, the role of systematic errors due to “Heuristics and Biases” is not appreciated as yet. This overcomes the problems of omission of human and organizational factors from accident analysis. Second, the scope of the investigation includes all levels of the socio-technical system, including government, regulatory, railway safety bodies, duty holders, signaling firms and transport planners, and front-line staff such that lessons are learned at the decision making and implementation level as well. Third, the author’s past accident case studies are supplemented with research pieces of evidence drawn from the practitioner's and academic researchers’ publications as well. This is to discuss the role of system thinking to improve the decision-making and risk management processes and practices in the IEC 15288 systems engineering standard and in the industrial context such as the GB railways and artificial intelligence (AI) contexts as well.

Keywords: accident analysis, AI algorithm internal audit, bounded rationality, Byzantine failures, heuristics and biases approach

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Authors: Masoud Mirzaee, Ghobad Behzadi Pour

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An aircraft tire is designed to tolerate extremely heavy loads for a short duration. The number of tires increases with the weight of the aircraft, as it is needed to be distributed more evenly. Generally, aircraft tires work at high pressure, up to 200 psi (14 bar; 1,400 kPa) for airliners and higher for business jets. Tire assemblies for most aircraft categories provide a recommendation of compressed nitrogen that supports the aircraft’s weight on the ground, including a mechanism for controlling the aircraft during taxi, takeoff; landing; and traction for braking. Accurate tire pressure is a key factor that enables tire assemblies to perform reliably under high static and dynamic loads. Concerning ambient temperature change, considering the condition in which the temperature between the origin and destination airport was different, tire pressure should be adjusted and inflated to the specified operating pressure at the colder airport. This adjustment superseding the normal tire over an inflation limit of 5 percent at constant ambient temperature is required because the inflation pressure remains constant to support the load of a specified aircraft configuration. On the other hand, without this adjustment, a tire assembly would be significantly under/over-inflated at the destination. Due to an increase of human errors in the aviation industry, exorbitant costs are imposed on the airlines for providing consumable parts such as aircraft tires. The existence of an intelligent system to adjust the aircraft tire pressure based on weight, load, temperature, and weather conditions of origin and destination airports, could have a significant effect on reducing the aircraft maintenance costs, aircraft fuel and further improving the environmental issues related to the air pollution. An intelligent tire pressure regulation system (ITPRS) contains a processing computer, a nitrogen bottle with 1800 psi, and distribution lines. Nitrogen bottle’s inlet and outlet valves are installed in the main wheel landing gear’s area and are connected through nitrogen lines to main wheels and nose wheels assy. Controlling and monitoring of nitrogen will be performed by a computer, which is adjusted according to the calculations of received parameters, including the temperature of origin and destination airport, the weight of cargo loads and passengers, fuel quantity, and wind direction. Correct tire inflation and deflation are essential in assuring that tires can withstand the centrifugal forces and heat of normal operations, with an adequate margin of safety for unusual operating conditions such as rejected takeoff and hard landings. ITPRS will increase the performance of the aircraft in all phases of takeoff, landing, and taxi. Moreover, this system will reduce human errors, consumption materials, and stresses imposed on the aircraft body.

Keywords: avionic system, improve efficiency, ITPRS, human error, reduced cost, tire pressure

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Authors: Federico Capra, Emanuele Martelli, Matteo Gazzani, Marco Mazzotti, Maurizio Notaro

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Natural gas is a major energy source in the current global economy, contributing to roughly 21% of the total primary energy consumption. Production of natural gas starting from renewable energy sources is key to limit the related CO2 emissions, especially for those sectors that heavily rely on natural gas use. In this context, biomethane produced via biogas upgrading represents a good candidate for partial substitution of fossil natural gas. The upgrading process of biogas to biomethane consists in (i) the removal of pollutants and impurities (e.g. H2S, siloxanes, ammonia, water), and (ii) the separation of carbon dioxide from methane. Focusing on the CO2 removal process, several technologies can be considered: chemical or physical absorption with solvents (e.g. water, amines), membranes, adsorption-based systems (PSA). However, none emerged as the leading technology, because of (i) the heterogeneity in plant size, ii) the heterogeneity in biogas composition, which is strongly related to the feedstock type (animal manure, sewage treatment, landfill products), (iii) the case-sensitive optimal tradeoff between purity and recovery of biomethane, and iv) the destination of the produced biomethane (grid injection, CHP applications, transportation sector). With this contribution, we explore the use of a technology for biogas upgrading and we compare the resulting performance with benchmark technologies. The proposed technology makes use of a chemical sorbent, which is engineered by RSE and consists of Di-Ethanol-Amine deposited on a solid support made of γ-Alumina, to chemically adsorb the CO2 contained in the gas. The material is packed into fixed beds that cyclically undergo adsorption and regeneration steps. CO2 is adsorbed at low temperature and ambient pressure (or slightly above) while the regeneration is carried out by pulling vacuum and increasing the temperature of the bed (vacuum-temperature swing adsorption - VTSA). Dynamic adsorption tests were performed by RSE and were used to tune the mathematical model of the process, including material and transport parameters (i.e. Langmuir isotherms data and heat and mass transport). Based on this set of data, an optimal VTSA cycle was designed. The results enabled a better understanding of the interplay between material and cycle tuning. As exemplary application, the upgrading of biogas for grid injection, produced by an anaerobic digester (60-70% CO2, 30-40% CH4), for an equivalent size of 1 MWel was selected. A plant configuration is proposed to maximize heat recovery and minimize the energy consumption of the process. The resulting performances are very promising compared to benchmark solutions, which make the VTSA configuration a valuable alternative for biomethane production starting from biogas.

Keywords: biogas upgrading, biogas upgrading energetic cost, CO2 adsorption, VTSA process modelling

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Authors: Razieh Karimi Aghcheh, Christian Kubicek, Joseph Strauss, Gerhard Braus

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Filamentous fungi are of considerable economic and social significance for human health, nutrition and in white biotechnology. These organisms are dominant producers of a range of primary metabolites such as citric acid, microbial lipids (biodiesel) and higher unsaturated fatty acids (HUFAs). In particular, they produce also important but structurally complex secondary metabolites with enormous therapeutic applications in pharmaceutical industry, for example: cephalosporin, penicillin, taxol, zeranol and ergot alkaloids. Several fungal secondary metabolites, which are significantly relevant to human health do not only include antibiotics, but also e.g. lovastatin, a well-known antihypercholesterolemic agent produced by Aspergillus. terreus, or aflatoxin, a carcinogen produced by A. flavus. In addition to their roles for human health and agriculture, some fungi are industrially and commercially important: Species of the ascomycete genus Hypocrea spp. (teleomorph of Trichoderma) have been demonstrated as efficient producer of highly active cellulolytic enzymes. This trait makes them effective in disrupting and depolymerization of lignocellulosic materials and thus applicable tools in number of biotechnological areas as diverse as clothes-washing detergent, animal feed, and pulp and fuel productions. Fungal LaeA/LAE1 (Loss of aflR Expression A) homologs their gene products act at the interphase between secondary metabolisms, cellulase production and development. Lack of the corresponding genes results in significant physiological changes including loss of secondary metabolite and lignocellulose degrading enzymes production. At the molecular level, the encoded proteins are presumably methyltransferases or demethylases which act directly or indirectly at heterochromatin and interact with velvet domain proteins. Velvet proteins bind to DNA and affect expression of secondary metabolites (SMs) genes and cellulases. The dynamic interplay between LaeA/LAE1, velvet proteins and additional interaction partners is the key for an understanding of the coordination of metabolic and morphological functions of fungi and is required for a biotechnological control of the formation of desired bioactive products. Aspergilli and Trichoderma represent different biotechnologically significant species with significant differences in the LaeA/LAE1-Velvet protein machinery and their target proteins. We, therefore, performed a comparative study of the interaction partners of this machinery and the dynamics of the various protein-protein interactions using our robust proteomic and mass spectrometry techniques. This enhances our knowledge about the fungal coordination of secondary metabolism, cellulase production and development and thereby will certainly improve recombinant fungal strain construction for the production of industrial secondary metabolite or lignocellulose hydrolytic enzymes.

Keywords: cellulases, LaeA/1, proteomics, secondary metabolites

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Authors: Heiko Jessen, Laura Tanus, Slobodan Ruzicic

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Objectives: The efficacy of Stribild®, an integrase strand transfer inhibitor (INSTI) -based STR, has been evaluated in randomized clinical trials and it has demonstrated durable capability in terms of achieving sustained suppression of HIV-1 RNA-levels. However, differences in monitoring frequency, existing selection bias and profile of patients enrolled in the trials, may all result in divergent efficacy of this regimen in routine clinical settings. The aim of this study was to assess the virologic outcomes, safety and tolerability profile of Stribild® in a routine clinical setting. Methods: This was a retrospective monocentric analysis on HIV-1-infected patients, who started with or were switched to Stribild®. Virological failure (VF) was defined as confirmed HIV-RNA>50 copies/ml. The minimum time of follow-up was 24 weeks. The percentage of patients remaining free of therapeutic failure was estimated using the time-to-loss-of-virologic-response (TLOVR) algorithm, by intent-to-treat analysis. Results: We analyzed the data of 197 patients (56 ART-naïve and 141 treatment-experienced patients), who fulfilled the inclusion criteria. Majority (95.9%) of patients were male. The median time of HIV-infection at baseline was 2 months in treatment-naïve and 70 months in treatment-experienced patients. Median time [IQR] under ART in treatment-experienced patients was 37 months. Among the treatment-experienced patients 27.0% had already been treated with a regimen consisting of two NRTIs and one INSTI, whereas 18.4% of them experienced a VF. The median time [IQR] of virological suppression prior to therapy with Stribild® in the treatment-experienced patients was 10 months [0-27]. At the end of follow-up (median 33 months), 87.3% (95% CI, 83.5-91.2) of treatment-naïve and 80.3% (95% CI, 75.8-84.8) of treatment-experienced patients remained free of therapeutic failure. Considering only treatment-experienced patients with baseline VL<50 copies/ml, 83.0% (95% CI, 78.5-87.5) remained free of therapeutic failure. A total of 17 patients stopped treatment with Stribild®, 5.4% (3/56) of them were treatment-naïve and 9.9% (14/141) were treatment-experienced patients. The Stribild® therapy was discontinued in 2 (1.0%) because of VF, loss to follow-up in 4 (2.0%), and drug-drug interactions in 2 (1.0%) patients. Adverse events were in 7 (3.6%) patients the reason to switch from therapy with Stribild® and further 2 (1.0%) patients decided personally to switch. The most frequently observed adverse events were gastrointestinal side effects (20.0%), headache (8%), rash events (7%) and dizziness (6%). In two patients we observed an emergence of novel resistances in integrase-gene. The N155H evolved in one patient and resulted in VF. In another patient S119R evolved either during or shortly upon switch from therapy with Stribild®. In one further patient with VF two novel mutations in the RT-gene were observed when compared to historical genotypic test result (V106I/M and M184V), whereby it is not clear whether they evolved during or already before the switch to Stribild®. Conclusions: Effectiveness of Stribild® for treatment-naïve patients was consistent with data obtained in clinical trials. The safety and tolerability profile as well as resistance development confirmed clinical efficacy of Stribild® in a daily practice setting.

Keywords: ART, HIV, integrase inhibitor, stribild

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Authors: Ichiro Takahashi

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One conundrum that macroeconomic theory faces is to explain how an economy can revive from depression, in which the aggregate demand has fallen substantially below its productive capacity. This paper examines an autonomous stabilizing mechanism using an agent-based Wicksell-Keynes macroeconomic model. This paper focuses on the effects of the number of firms and the length of the gestation period for investment that are often assumed to be one in a mainstream macroeconomic model. The simulations found the virtual economy was highly unstable, or more precisely, collapsing when these parameters are fixed at one. This finding may even suggest us to question the legitimacy of these common assumptions. A perpetual decline in capital stock will eventually encourage investment if the capital stock is short-lived because an inactive investment will result in insufficient productive capacity. However, for an economy characterized by a roundabout production method, a gradual decline in productive capacity may not be able to fall below the aggregate demand that is also shrinking. Naturally, one would then ask if our economy cannot rely on an external stimulus such as population growth and technological progress to revive investment, what factors would provide such a buoyancy for stimulating investments? The current paper attempts to answer this question by employing the artificial macroeconomic model mentioned above. The baseline model has the following three features: (1) the multi-period gestation for investment, (2) a large number of heterogeneous firms, (3) demand-constrained firms. The instability is a consequence of the following dynamic interactions. (a) A multiple-period gestation period means that once a firm starts a new investment, it continues to invest over some subsequent periods. During these gestation periods, the excess demand created by the investing firm will spill over to ignite new investment of other firms that are supplying investment goods: the presence of multi-period gestation for investment provides a field for investment interactions. Conversely, the excess demand for investment goods tends to fade away before it develops into a full-fledged boom if the gestation period of investment is short. (b) A strong demand in the goods market tends to raise the price level, thereby lowering real wages. This reduction of real wages creates two opposing effects on the aggregate demand through the following two channels: (1) a reduction in the real labor income, and (2) an increase in the labor demand due to the principle of equality between the marginal labor productivity and real wage (referred as the Walrasian labor demand). If there is only a single firm, a lower real wage will increase its Walrasian labor demand, thereby an actual labor demand tends to be determined by the derived labor demand. Thus, the second positive effect would not work effectively. In contrast, for an economy with a large number of firms, Walrasian firms will increase employment. This interaction among heterogeneous firms is a key for stability. A single firm cannot expect the benefit of such an increased aggregate demand from other firms.

Keywords: agent-based macroeconomic model, business cycle, demand constraint, gestation period, representative agent model, stability

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Authors: Shelley Zion

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This study examines the longitudinal impact (10 years) of a course for education leaders designed to encourage the development of critical consciousness surrounding issues of equity, oppression, power, and privilege. The ability to resist and challenge oppression across social and cultural contexts can be acquired through the use of transformative pedagogies that create spaces that use the practice of exploration to make connections between pervasive structural and institutional practices and race and ethnicity. This study seeks to extend this understanding by exploring the longitudinal influence of participating in a course that utilizes transformative pedagogies, course materials, exercises, and activities to encourage the practice of exploration of student experiences with racial and ethnic discrimination with the end goal of providing them with the necessary knowledge and skills that foster their ability to resist and challenge oppression and discrimination -critical action- in their lives. To this end, we use the explanatory power of the theories of critical consciousness development, sociopolitical development, and social identity construction that view exploration as a crucial practice in understanding the role ethnic and racial differences play in creating opportunities or barriers in the lives of individuals. When educators use transformative pedagogies, they create a space where students collectively explore their experiences with racial and ethnic discrimination through course readings, in-class activities, and discussions. The end goal of this exploration is twofold: first, to encourage the student’s ability to understand how differences are identified, given meaning to, and used to position them in specific places and spaces in their world; second, to scaffold students’ ability to make connections between their individual and collective differences and particular institutional and structural practices that create opportunities or barriers in their lives. Studies have found the formal exploration of students’ individual and collective differences in relation to their experiences with racial and ethnic discrimination results in developing an understanding of the roles race and ethnicity play in their lives. To trace the role played by exploration in identity construction, we utilize an integrative approach to identity construction informed by multiple theoretical frameworks grounded in cultural studies, social psychology, and sociology that understand social-cultural, racial, and ethnic -identities as dynamic and ever-changing based on context-specific environments. Stuart Hall refers to this practice as taking “symbolic detours through the past” while reflecting on the different ways individuals have been positioned based on their roots (group membership) and also how they, in turn, chose to position themselves through collective sense-making of the various meanings their differences carried through the routes they have taken. The practice of exploration in the construction of ethnic-racial identities has been found to be beneficial to sociopolitical development.

Keywords: political polarization, civic participation, democracy, education

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Authors: Ali Ahmed Ali Al-Juboori, H. Zhu, D. Wexler, H. Li, C. Lu, J. McLeod, S. Pannila, J. Barnes

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A number of studies have focused on the formation mechanics of white etching layer and its origin in the railway operation. Until recently, the following hypotheses consider the precise mechanics of WELs formation: (i) WELs are the result of thermal process caused by wheel slip; (ii) WELs are mechanically induced by severe plastic deformation; (iii) WELs are caused by a combination of thermo-mechanical process. The mechanisms discussed above lead to occurrence of white etching layers on the area of wheel and rail contact. This is because the contact patch which is the active point of the wheel on the rail is exposed to highest shear stresses which result in localised severe plastic deformation; and highest rate of heat caused by wheel slipe during excessive traction or braking effort. However, if the WELs are not on the running band area, it would suggest that there is another cause of WELs formation. In railway system, particularly electrified railway, arcing phenomenon has been occurring more often and regularly on the rails. In electrified railway, the current is delivered to the train traction motor via contact wires and then returned to the station via the contact between the wheel and the rail. If the contact between the wheel and the rail is temporarily losing, due to dynamic vibration, entrapped dirt or water, lubricant effect or oxidation occurrences, high current can jump through the gap and results in arcing. The other resources of arcing also include the wheel passage the insulated joint and lightning on a train during bad weather. During the arcing, an extensive heat is generated and speared over a large area of top surface of rail. Thus, arcing is considered another heat source in the rail head (rather than wheel slipe) that results in microstructural changes and white etching layer formation. A head hardened (HH) rail steel, cut from a curved rail truck was used for the investigation. Samples were sectioned from a depth of 10 mm below the rail surface, where the material is considered to be still within the hardened layer but away from any microstructural changes on the top surface layer caused by train passage. These samples were subjected to electrical discharges by using Gas Tungsten Arc Welding (GTAW) machine. The arc current was controlled and moved along the samples surface in the direction of travel, as indicated by an arrow. Five different conditions were applied on the surface of the samples. Samples containing pre-existed WELs, taken from ex-service rail surface, were also considered in this study for comparison. Both simulated and ex-serviced WELs were characterised by advanced methods including SEM, TEM, TKD, EDS, XRD. Samples for TEM and TKFD were prepared by Focused Ion Beam (FIB) milling. The results showed that both simulated WELs by electrical arcing and ex-service WEL comprise similar microstructure. Brown etching layer was found with WELs and likely induced by a concurrent tempering process. This study provided a clear understanding of new formation mechanics of WELs which contributes to track maintenance procedure.

Keywords: white etching layer, arcing, brown etching layer, material characterisation

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Authors: A. P. Mikhailovich, V. V. Fomin, E. M. Agapitov, V. E. Rogachev, E. A. Kostousova, E. S. Perekhodova

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Woody vegetation among the upper limit of its habitat is a sensitive indicator of biota reaction to regional climate changes. Quantitative assessment of temporal and spatial changes in the distribution of trees and plant biocenoses calls for the development of new modeling approaches based upon selected data from measurements on the ground level and ultra-resolution aerial photography. Statistical models were developed for the study area located in the Polar Urals. These models allow obtaining probabilistic estimates for placing Siberian Larch trees into one of the three age intervals, namely 1-10, 11-40 and over 40 years, based on the Weilbull distribution of the maximum horizontal crown projection. Authors developed the distribution map for larch trees with crown diameters exceeding twenty centimeters by deciphering aerial photographs made by a UAV from an altitude equal to fifty meters. The total number of larches was equal to 88608, forming the following distribution row across the abovementioned intervals: 16980, 51740, and 19889 trees. The results demonstrate that two processes can be observed in the course of recent decades: first is the intensive forestation of previously barren or lightly wooded fragments of the study area located within the patches of wood, woodlands, and sparse stand, and second, expansion into mountain tundra. The current expansion of the Siberian Larch in the region replaced the depopulation process that occurred in the course of the Little Ice Age from the late 13ᵗʰ to the end of the 20ᵗʰ century. Using data from field measurements of Siberian larch specimen biometric parameters (including height, diameter at root collar and at 1.3 meters, and maximum projection of the crown in two orthogonal directions) and data on tree ages obtained at nine circular test sites, authors developed a model for artificial neural network including two layers with three and two neurons, respectively. The model allows quantitative assessment of a specimen's age based on height and maximum crone projection values. Tree height and crown diameters can be quantitatively assessed using data from aerial photographs and lidar scans. The resulting model can be used to assess the age of all Siberian larch trees. The proposed approach, after validation, can be applied to assessing the age of other tree species growing near the upper tree boundaries in other mountainous regions. This research was collaboratively funded by the Russian Ministry for Science and Education (project No. FEUG-2023-0002) and Russian Science Foundation (project No. 24-24-00235) in the field of data modeling on the basis of artificial neural network.

Keywords: treeline, dynamic, climate, modeling

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Authors: Domenico Carmelo Mongelli

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The context is that of great uncertainty in the 27 countries belonging to the European Union which has adopted an epochal measure: the elimination of internal combustion engines for the traction of road vehicles starting from 2035 with complete replacement with electric vehicles. If on the one hand there is great concern at various levels for the unpreparedness for this change, on the other the Scientific Community is not preparing accurate studies on the problem, as the scientific literature deals with single aspects of the issue, moreover addressing the issue at the level of individual countries, losing sight of the global implications of the issue for the entire EU. The aim of the research is to fill these gaps: the technological, plant engineering, environmental, economic and employment aspects of the energy transition in question are addressed and connected to each other, comparing the current situation with the different scenarios that could exist in 2035 and in the following years until total disposal of the internal combustion engine vehicle fleet for the entire EU. The methodologies adopted by the research consist in the analysis of the entire life cycle of electric vehicles and batteries, through the use of specific databases, and in the dynamic simulation, using specific calculation codes, of the application of the results of this analysis to the entire EU electric vehicle fleet from 2035 onwards. Energy balance sheets will be drawn up (to evaluate the net energy saved), plant balance sheets (to determine the surplus demand for power and electrical energy required and the sizing of new plants from renewable sources to cover electricity needs), economic balance sheets (to determine the investment costs for this transition, the savings during the operation phase and the payback times of the initial investments), the environmental balances (with the different energy mix scenarios in anticipation of 2035, the reductions in CO2eq and the environmental effects are determined resulting from the increase in the production of lithium for batteries), the employment balances (it is estimated how many jobs will be lost and recovered in the reconversion of the automotive industry, related industries and in the refining, distribution and sale of petroleum products and how many will be products for technological innovation, the increase in demand for electricity, the construction and management of street electric columns). New algorithms for forecast optimization are developed, tested and validated. Compared to other published material, the research adds an overall picture of the energy transition, capturing the advantages and disadvantages of the different aspects, evaluating the entities and improvement solutions in an organic overall picture of the topic. The results achieved allow us to identify the strengths and weaknesses of the energy transition, to determine the possible solutions to mitigate these weaknesses and to simulate and then evaluate their effects, establishing the most suitable solutions to make this transition feasible.

Keywords: engines, Europe, mobility, transition

Procedia PDF Downloads 36

Authors: Alexander Harrison Greer, Edward King, Elijah Lee, Safa Obuz, Ruhao Sun, Aditya Sardesai, Toby Ma, Daniel Chow, Bryce Broadus, Calvin Costner, Troy Barnes, Biagio DeSimone, Yeshwin Sankuratri, Yiheng Chen, Holly Golecki

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Although a relatively new field, soft robotics is experiencing a rise in applicability in the secondary school setting through The Soft Robotics Toolkit, shared fabrication resources and a design competition. Exposing students outside of university research groups to this rapidly growing field allows for development of the soft robotics industry in new and imaginative ways. Soft robotic actuators have remained difficult to implement in classrooms because of their relative cost or difficulty of fabrication. Traditionally, a two-part molding system is used; however, this configuration often results in delamination. In an effort to make soft robotics more accessible to young students, we aim to develop a simple, single-mold method of fabricating soft robotic actuators from common household materials. These actuators are made by embedding a soluble polymer insert into silicone. These inserts can be made from hand-cut polystyrene, 3D-printed polyvinyl alcohol (PVA) or acrylonitrile butadiene styrene (ABS), or molded sugar. The insert is then dissolved using an appropriate solvent such as water or acetone, leaving behind a negative form which can be pneumatically actuated. The resulting actuators are seamless, eliminating the instability of adhering multiple layers together. The benefit of this approach is twofold: it simplifies the process of creating a soft robotic actuator, and in turn, increases its effectiveness and durability. To quantify the increased durability of the single-mold actuator, it was tested against the traditional two-part mold. The single-mold actuator could withstand actuation at 20psi for 20 times the duration when compared to the traditional method. The ease of fabrication of these actuators makes them more accessible to hobbyists and students in classrooms. After developing these actuators, they were applied, in collaboration with a ceramics teacher at our school, to a glove used to transfer nuanced hand motions used to throw pottery from an expert artist to a novice. We quantified the improvement in the users’ pottery-making skill when wearing the glove using image analysis software. The seamless actuators proved to be robust in this dynamic environment. Seamless soft robotic actuators created by high school students show the applicability of the Soft Robotics Toolkit for secondary STEM education and outreach. Making students aware of what is possible through projects like this will inspire the next generation of innovators in materials science and robotics.

Keywords: pneumatic actuator fabrication, soft robotic glove, soluble polymers, STEM outreach

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Authors: Elias Jemal Abdella

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The Blue Nile River is an important shared resource of Ethiopia, Sudan and also, because it is the major contributor of water to the main Nile River, Egypt. Despite the potential benefits of regional cooperation and integrated joint basin management, all three countries continue to pursue unilateral plans for development. Besides, there is great uncertainty about the likely impacts of climate change in water availability for existing as well as proposed irrigation and hydropower projects in the Blue Nile Basin. The main objective of this study is to quantitatively assess the impact of climate change on the hydrological regime of the upper Blue Nile basin, western Ethiopia. Three models were combined, a dynamic Coordinated Regional Climate Downscaling Experiment (CORDEX) regional climate model (RCM) that is used to determine climate projections for the Upper Blue Nile basin for Representative Concentration Pathways (RCPs) 4.5 and 8.5 greenhouse gas emissions scenarios for the period 2021-2050. The outputs generated from multimodel ensemble of four (4) CORDEX-RCMs (i.e., rainfall and temperature) were used as input to a Soil and Water Assessment Tool (SWAT) hydrological model which was setup, calibrated and validated with observed climate and hydrological data. The outputs from the SWAT model (i.e., projections in river flow) were used as input to a Water Evaluation and Planning (WEAP) water resources model which was used to determine the water resources implications of the changes in climate. The WEAP model was set-up to simulate three development scenarios. Current Development scenario was the existing water resource development situation, Medium-term Development scenario was planned water resource development that is expected to be commissioned (i.e. before 2025) and Long-term full Development scenario were all planned water resource development likely to be commissioned (i.e. before 2050). The projected change of mean annual temperature for period (2021 – 2050) in most of the basin are warmer than the baseline (1982 -2005) average in the range of 1 to 1.4oC, implying that an increase in evapotranspiration loss. Subbasins which already distressed from drought may endure to face even greater challenges in the future. Projected mean annual precipitation varies from subbasin to subbasin; in the Eastern, North Eastern and South western highland of the basin a likely increase of mean annual precipitation up to 7% whereas in the western lowland part of the basin mean annual precipitation projected to decrease by 3%. The water use simulation indicates that currently irrigation demand in the basin is 1.29 Bm3y-1 for 122,765 ha of irrigation area. By 2025, with new schemes being developed, irrigation demand is estimated to increase to 2.5 Bm3y-1 for 277,779 ha. By 2050, irrigation demand in the basin is estimated to increase to 3.4 Bm3y-1 for 372,779 ha. The hydropower generation simulation indicates that 98 % of hydroelectricity potential could be produced if all planned dams are constructed.

Keywords: Blue Nile River, climate change, hydropower, SWAT, WEAP

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Authors: Massimo Ferrari, Maria Sole Pagliari

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Pollution is a classic example of economic externality: agents who produce it do not face direct costs from emissions. Therefore, there are no direct economic incentives for reducing pollution. One way to address this market failure would be directly taxing emissions. However, because emissions are global, governments might as well find it optimal to wait let foreign countries to tax emissions so that they can enjoy the benefits of lower pollution without facing its direct costs. In this paper, we first document the empirical relation between pollution and economic output with static and dynamic regression methods. We show that there is a negative relation between aggregate output and the stock of pollution (measured as the stock of CO₂ emissions). This relationship is also highly non-linear, increasing at an exponential rate. In the second part of the paper, we develop and estimate a two-country, two-sector model for the US and the euro area. With this model, we aim at analyzing how the public sector should respond to higher emissions and what are the direct costs that these policies might have. In the model, there are two types of firms, brown firms (which produce a polluting technology) and green firms. Brown firms also produce an externality, CO₂ emissions, which has detrimental effects on aggregate output. As brown firms do not face direct costs from polluting, they do not have incentives to reduce emissions. Notably, emissions in our model are global: the stock of CO₂ in the economy affects all countries, independently from where it is produced. This simplified economy captures the main trade-off between emissions and production, generating a classic market failure. According to our results, the current level of emission reduces output by between 0.4 and 0.75%. Notably, these estimates lay in the upper bound of the distribution of those delivered by studies in the early 2000s. To address market failure, governments should step in introducing taxes on emissions. With the tax, brown firms pay a cost for polluting hence facing the incentive to move to green technologies. Governments, however, might also adopt a beggar-thy-neighbour strategy. Reducing emissions is costly, as moves production away from the 'optimal' production mix of brown and green technology. Because emissions are global, a government could just wait for the other country to tackle climate change, ripping the benefits without facing any costs. We study how this strategic game unfolds and show three important results: first, cooperation is first-best optimal from a global prospective; second, countries face incentives to deviate from the cooperating equilibria; third, tariffs on imported brown goods (the only retaliation policy in case of deviation from the cooperation equilibrium) are ineffective because the exchange rate would move to compensate. We finally study monetary policy under when costs for climate change rise and show that the monetary authority should react stronger to deviations of inflation from its target.

Keywords: climate change, general equilibrium, optimal taxation, monetary policy

Procedia PDF Downloads 132

Authors: Brittany Richardson, Ying Wang

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For physical therapy, exercise prescription, athlete training, and regular fitness training, it is crucial to perform health assessments or fitness assessments periodically. An accurate assessment is propitious for tracking recovery progress, preventing potential injury and making long-range training plans. Assessments include necessary measurements, height, weight, blood pressure, heart rate, body fat, etc. and advanced evaluation, muscle group strength, stability-mobility, and movement evaluation, etc. In the current standard assessment procedures, the accuracy of assessments, especially advanced evaluations, largely depends on the experience of physicians, coaches, and personal trainers. And it is challenging to track clients’ progress in the current assessment. Unlike the tradition assessment, in this paper, we present a deep learning based face recognition algorithm for accurate, comprehensive and trackable assessment. Based on the result from our assessment, physicians, coaches, and personal trainers are able to adjust the training targets and methods. The system categorizes the difficulty levels of the current activity for the client or user, furthermore make more comprehensive assessments based on tracking muscle group over time using a designed landmark detection method. The system also includes the function of grading and correcting the form of the clients during exercise. Experienced coaches and personal trainer can tell the clients' limit based on their facial expression and muscle group movements, even during the first several sessions. Similar to this, using a convolution neural network, the system is trained with people’s facial expression to differentiate challenge levels for clients. It uses landmark detection for subtle changes in muscle groups movements. It measures the proximal mobility of the hips and thoracic spine, the proximal stability of the scapulothoracic region and distal mobility of the glenohumeral joint, as well as distal mobility, and its effect on the kinetic chain. This system integrates data from other fitness assistant devices, including but not limited to Apple Watch, Fitbit, etc. for a improved training and testing performance. The system itself doesn’t require history data for an individual client, but the history data of a client can be used to create a more effective exercise plan. In order to validate the performance of the proposed work, an experimental design is presented. The results show that the proposed work contributes towards improving the quality of exercise plan, execution, progress tracking, and performance.

Keywords: exercise prescription, facial recognition, landmark detection, fitness assessments

Procedia PDF Downloads 102

Authors: Kai Warsoenke, Maik Mackiewicz

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To achieve a high quality of assembled car body structures, tolerancing is used to ensure a geometric accuracy of the single car body parts. There are two main techniques to determine the required tolerances. The first is tolerance analysis which describes the influence of individually tolerated input values on a required target value. Second is tolerance synthesis to determine the location of individual tolerances to achieve a target value. Both techniques are based on classical statistical methods, which assume certain probability distributions. To ensure competitiveness in both saturated and dynamic markets, production processes in vehicle manufacturing must be flexible and efficient. The dimensional specifications selected for the individual body components and the resulting assemblies have a major influence of the quality of the process. For example, in the manufacturing of forming tools as operating equipment or in the higher level of car body assembly. As part of the metrological process monitoring, manufactured individual parts and assemblies are recorded and the measurement results are stored in databases. They serve as information for the temporary adjustment of the production processes and are interpreted by experts in order to derive suitable adjustments measures. In the production of forming tools, this means that time-consuming and costly changes of the tool surface have to be made, while in the body shop, uncertainties that are difficult to control result in cost-intensive rework. The stored measurement results are not used to intelligently design tolerances in future processes or to support temporary decisions based on real-world geometric data. They offer potential to extend the tolerancing methods through data analysis and machine learning models. The purpose of this paper is to examine real-world measurement data from individual car body components, as well as assemblies, in order to develop an approach for using the data in short-term actions and future projects. For this reason, the measurement data will be analyzed descriptively in the first step in order to characterize their behavior and to determine possible correlations. In the following, a database is created that is suitable for developing machine learning models. The objective is to create an intelligent way to determine the position and number of measurement points as well as the local tolerance range. For this a number of different model types are compared and evaluated. The models with the best result are used to optimize equally distributed measuring points on unknown car body part geometries and to assign tolerance ranges to them. The current results of this investigation are still in progress. However, there are areas of the car body parts which behave more sensitively compared to the overall part and indicate that intelligent tolerancing is useful here in order to design and control preceding and succeeding processes more efficiently.

Keywords: automotive production, machine learning, process optimization, smart tolerancing

Procedia PDF Downloads 89

Authors: Ignitia Motjolopane

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Small and medium enterprises (SMEs) play an important role in economies by contributing to economic growth and employment. In the fourth industrial revolution, the convergence of technologies and the changing nature of work created pressures on economies globally. Generative artificial intelligence (AI) may support SMEs in exploring, exploiting, and transforming business models to align with their growth aspirations. SMEs' growth aspirations fall into four categories: subsistence, income, growth, and speculative. Subsistence-oriented firms focus on meeting basic financial obligations and show less motivation for business model innovation. SMEs focused on income, growth, and speculation are more likely to pursue business model innovation to support growth strategies. SMEs' strategic goals link to distinct business model innovation paths depending on whether SMEs are starting a new business, pursuing growth, or seeking profitability. Integrating generative artificial intelligence in start-up SME business model innovation enhances value creation, user-oriented innovation, and SMEs' ability to adapt to dynamic changes in the business environment. The existing literature may lack comprehensive frameworks and guidelines for effectively integrating generative AI in start-up reiterative business model innovation paths. This paper examines start-up business model innovation path with generative artificial intelligence. A theoretical approach is used to examine start-up-focused SME reiterative business model innovation path with generative AI. Articulating how generative AI may be used to support SMEs to systematically and cyclically build the business model covering most or all business model components and analyse and test the BM's viability throughout the process. As such, the paper explores generative AI usage in market exploration. Moreover, market exploration poses unique challenges for start-ups compared to established companies due to a lack of extensive customer data, sales history, and market knowledge. Furthermore, the paper examines the use of generative AI in developing and testing viable value propositions and business models. In addition, the paper looks into identifying and selecting partners with generative AI support. Selecting the right partners is crucial for start-ups and may significantly impact success. The paper will examine generative AI usage in choosing the right information technology, funding process, revenue model determination, and stress testing business models. Stress testing business models validate strong and weak points by applying scenarios and evaluating the robustness of individual business model components and the interrelation between components. Thus, the stress testing business model may address these uncertainties, as misalignment between an organisation and its environment has been recognised as the leading cause of company failure. Generative AI may be used to generate business model stress-testing scenarios. The paper is expected to make a theoretical and practical contribution to theory and approaches in crafting a robust business model innovation path with generative artificial intelligence in start-up SMEs.

Keywords: business models, innovation, generative AI, small medium enterprises

Procedia PDF Downloads 43

Authors: Aliya K. Salahova

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Scientific thinking, characterized by purposeful knowledge-seeking and the harmonization of theory and facts, holds a crucial role in preparing young minds for an increasingly complex and technologically advanced world. This abstract presents a research study aimed at fostering scientific thinking in early childhood, focusing on children aged 5 to 9 years, through experiential learning in Kids Science Labs (STEM). The study utilized a longitudinal exploration design, spanning 240 weeks from September 2018 to April 2023, to evaluate the effectiveness of the Kids Science Labs program in developing scientific thinking skills. Participants in the research comprised 72 children drawn from local schools and community organizations. Through a formative psychology-pedagogical experiment, the experimental group engaged in weekly STEM activities carefully designed to stimulate scientific thinking, while the control group participated in daily art classes for comparison. To assess the scientific thinking abilities of the participants, a registration table with evaluation criteria was developed. This table included indicators such as depth of questioning, resource utilization in research, logical reasoning in hypotheses, procedural accuracy in experiments, and reflection on research processes. The data analysis revealed dynamic fluctuations in the number of children at different levels of scientific thinking proficiency. While the development was not uniform across all participants, a main leading factor emerged, indicating that the Kids Science Labs program and formative experiment exerted a positive impact on enhancing scientific thinking skills in children within this age range. The study's findings support the hypothesis that systematic implementation of STEM activities effectively promotes and nurtures scientific thinking in children aged 5-9 years. Enriching education with a specially planned STEM program, tailoring scientific activities to children's psychological development, and implementing well-planned diagnostic and corrective measures emerged as essential pedagogical conditions for enhancing scientific thinking abilities in this age group. The results highlight the significant and positive impact of the systematic-activity approach in developing scientific thinking, leading to notable progress and growth in children's scientific thinking abilities over time. These findings have promising implications for educators and researchers, emphasizing the importance of incorporating STEM activities into educational curricula to foster scientific thinking from an early age. This study contributes valuable insights to the field of science education and underscores the potential of STEM-based interventions in shaping the future scientific minds of young children.

Keywords: Scientific thinking, education, STEM, intervention, Psychology, Pedagogy, collaborative learning, longitudinal study

Procedia PDF Downloads 40

Authors: Soma Kanta Baral

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Background: Since 1981, when the first AIDS case was reported, worldwide, more than 34 million people have been infected with HIV. Almost 95 percent of the people infected with HIV live in developing countries. As HBV & HIV share similar routes of transmission by sexual intercourse or drug use by parenteral injection, co-infection is common. Because of the limited access to healthcare & HIV treatment in developing countries, HIV-infected individuals are present late for care. Enumeration of CD4+ T cell count at the time of diagnosis has been useful to initiate the therapy in HIV infected individuals. The baseline CD4+ T cell count shows high immunological variability among patients. Methods: This prospective study was done in the serology section of the Department of Microbiology over a period of one year from august 2012 to July 2013. A total of 13037 individuals subjected for HIV test were included in the study comprising of 4982 males & 8055 females. Blood sample was collected by vein puncture aseptically with standard operational procedure in clean & dry test-tube. All blood samples were screened for HIV as described by WHO algorithm by Immuno-chromatography rapid kits. Further confirmation was done by biokit ELISA method as per the manufacturer’s guidelines. After informed consent, HIV positive individuals were screened for HBsAg by Immuno-chromatography rapid kits (Hepacard). Further confirmation was done by biokit ELISA method as per the manufacturer’s guidelines. EDTA blood samples were collected from the HIV sero-positive individuals for baseline CD4+ T count. Then, CD4+ T cells count was determined by using FACS Calibur Flow Cytometer (BD). Results: Among 13037 individuals screened for HIV, 104 (0.8%) were found to be infected comprising of 69(66.34%) males & 35 (33.65%) females. The study showed that the high infection was noted in housewives (28.7%), active age group (30.76%), rural area (56.7%) & in heterosexual route (80.9%) of transmission. Out of total HIV infected individuals, distribution of HBV co-infection was found to be 6(5.7%). All co- infected individuals were married, male, above the age of 25 years & heterosexual route of transmission. Baseline CD4+ T cell count of HIV infected patient was found higher (mean CD4+ T cell count; 283cells/cu.mm) than HBV co-infected patients (mean CD4+ T cell count; 91 cells/cu.mm). Majority (77.2%) of HIV infected & all co-infected individuals were presented in our center late (CD4+ T cell count;< 350/cu. mm) for diagnosis and care. Majority of co- infected 4 (80%) were late presented with advanced AIDS stage (CD4+ count; <200/cu.mm). Conclusions: The study showed a high percentage of HIV sero-positive & co- infected individuals. Baseline CD4+ T cell count of majority of HIV infected individuals was found to be low. Hence, more sustained and vigorous awareness campaigns & counseling still need to be done in order to promote early diagnosis and management.

Keywords: HIV/AIDS, HBsAg, co-infection, CD4+

Procedia PDF Downloads 192

Authors: Farzan Gity, Lida Ansari, Ian M. Povey, Roger E. Nagle, James C. Greer

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Titanium nitride (TiN) films have been widely used in variety of fields, due to its unique electrical, chemical, physical and mechanical properties, including low electrical resistivity, chemical stability, and high thermal conductivity. In microelectronic devices, thin continuous TiN films are commonly used as diffusion barrier and metal gate material. However, as the film thickness decreases below a few nanometers, electrical properties of the film alter considerably. In this study, the physical and electrical characteristics of 1.5nm to 22nm thin films deposited by Plasma-Enhanced Atomic Layer Deposition (PE-ALD) using Tetrakis(dimethylamino)titanium(IV), (TDMAT) chemistry and Ar/N2 plasma on 80nm SiO2 capped in-situ by 2nm Al2O3 are investigated. ALD technique allows uniformly-thick films at monolayer level in a highly controlled manner. The chemistry incorporates low level of oxygen into the TiN films forming titanium oxynitride (TiON). Thickness of the films is characterized by Transmission Electron Microscopy (TEM) which confirms the uniformity of the films. Surface morphology of the films is investigated by Atomic Force Microscopy (AFM) indicating sub-nanometer surface roughness. Hall measurements are performed to determine the parameters such as carrier mobility, type and concentration, as well as resistivity. The >5nm-thick films exhibit metallic behavior; however, we have observed that thin film resistivity is modulated significantly by film thickness such that there are more than 5 orders of magnitude increment in the sheet resistance at room temperature when comparing 5nm and 1.5nm films. Scattering effects at interfaces and grain boundaries could play a role in thickness-dependent resistivity in addition to quantum confinement effect that could occur at ultra-thin films: based on our measurements the carrier concentration is decreased from 1.5E22 1/cm3 to 5.5E17 1/cm3, while the mobility is increased from < 0.1 cm2/V.s to ~4 cm2/V.s for the 5nm and 1.5nm films, respectively. Also, measurements at different temperatures indicate that the resistivity is relatively constant for the 5nm film, while for the 1.5nm film more than 2 orders of magnitude reduction has been observed over the range of 220K to 400K. The activation energy of the 2.5nm and 1.5nm films is 30meV and 125meV, respectively, indicating that the TiON ultra-thin films are exhibiting semiconducting behaviour attributing this effect to a metal-semiconductor transition. By the same token, the contact is no longer Ohmic for the thinnest film (i.e., 1.5nm-thick film); hence, a modified lift-off process was developed to selectively deposit thicker films allowing us to perform electrical measurements with low contact resistance on the raised contact regions. Our atomic scale simulations based on molecular dynamic-generated amorphous TiON structures with low oxygen content confirm our experimental observations indicating highly n-type thin films.

Keywords: activation energy, ALD, metal-semiconductor transition, resistivity, titanium oxynitride, ultra-thin film

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Authors: Yan Torres, Fernanda Simoes, Francisco Petrucci-Fonseca, Freddie-Jeanne Richard

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The non-invasive samples are an alternative of collecting genetic samples directly. Non-invasive samples are collected without the manipulation of the animal (e.g., scats, feathers and hairs). Nevertheless, the use of non-invasive samples has some limitations. The main issue is degraded DNA, leading to poorer extraction efficiency and genotyping. Those errors delayed for some years a widespread use of non-invasive genetic information. Possibilities to limit genotyping errors can be done using analysis methods that can assimilate the errors and singularities of non-invasive samples. Genotype matching and population estimation algorithms can be highlighted as important analysis tools that have been adapted to deal with those errors. Although, this recent development of analysis methods there is still a lack of empirical performance comparison of them. A comparison of methods with dataset different in size and structure can be useful for future studies since non-invasive samples are a powerful tool for getting information specially for endangered and rare populations. To compare the analysis methods, four different datasets used were obtained from the Dryad digital repository were used. Three different matching algorithms (Cervus, Colony and Error Tolerant Likelihood Matching - ETLM) are used for matching genotypes and two different ones for population estimation (Capwire and BayesN). The three matching algorithms showed different patterns of results. The ETLM produced less number of unique individuals and recaptures. A similarity in the matched genotypes between Colony and Cervus was observed. That is not a surprise since the similarity between those methods on the likelihood pairwise and clustering algorithms. The matching of ETLM showed almost no similarity with the genotypes that were matched with the other methods. The different cluster algorithm system and error model of ETLM seems to lead to a more criterious selection, although the processing time and interface friendly of ETLM were the worst between the compared methods. The population estimators performed differently regarding the datasets. There was a consensus between the different estimators only for the one dataset. The BayesN showed higher and lower estimations when compared with Capwire. The BayesN does not consider the total number of recaptures like Capwire only the recapture events. So, this makes the estimator sensitive to data heterogeneity. Heterogeneity in the sense means different capture rates between individuals. In those examples, the tolerance for homogeneity seems to be crucial for BayesN work properly. Both methods are user-friendly and have reasonable processing time. An amplified analysis with simulated genotype data can clarify the sensibility of the algorithms. The present comparison of the matching methods indicates that Colony seems to be more appropriated for general use considering a time/interface/robustness balance. The heterogeneity of the recaptures affected strongly the BayesN estimations, leading to over and underestimations population numbers. Capwire is then advisable to general use since it performs better in a wide range of situations.

Keywords: algorithms, genetics, matching, population

Procedia PDF Downloads 117

Authors: F. Infante, W. Kaal, S. Perfetto, S. Herold

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In the last decade the demand of wireless sensors and low-power electric devices for condition monitoring in mechanical structures has been strongly increased. Networks of wireless sensors can potentially be applied in a huge variety of applications. Due to the reduction of both size and power consumption of the electric components and the increasing complexity of mechanical systems, the interest of creating dense nodes sensor networks has become very salient. Nevertheless, with the development of large sensor networks with numerous nodes, the critical problem of powering them is drawing more and more attention. Batteries are not a valid alternative for consideration regarding lifetime, size and effort in replacing them. Between possible alternative solutions for durable power sources useable in mechanical components, vibrations represent a suitable source for the amount of power required to feed a wireless sensor network. For this purpose, energy harvesting from structural vibrations has received much attention in the past few years. Suitable vibrations can be found in numerous mechanical environments including automotive moving structures, household applications, but also civil engineering structures like buildings and bridges. Similarly, a dynamic vibration absorber (DVA) is one of the most used devices to mitigate unwanted vibration of structures. This device is used to transfer the primary structural vibration to the auxiliary system. Thus, the related energy is effectively localized in the secondary less sensitive structure. Then, the additional benefit of harvesting part of the energy can be obtained by implementing dedicated components. This paper describes the design process of an energy harvesting tuned vibration absorber (EHTVA) for rotating systems using piezoelectric elements. The energy of the vibration is converted into electricity rather than dissipated. The device proposed is indeed designed to mitigate torsional vibrations as with a conventional rotational TVA, while harvesting energy as a power source for immediate use or storage. The resultant rotational multi degree of freedom (MDOF) system is initially reduced in an equivalent single degree of freedom (SDOF) system. The Den Hartog’s theory is used for evaluating the optimal mechanical parameters of the initial DVA for the SDOF systems defined. The performance of the TVA is operationally assessed and the vibration reduction at the original resonance frequency is measured. Then, the design is modified for the integration of active piezoelectric patches without detuning the TVA. In order to estimate the real power generated, a complex storage circuit is implemented. A DC-DC step-down converter is connected to the device through a rectifier to return a fixed output voltage. Introducing a big capacitor, the energy stored is measured at different frequencies. Finally, the electromechanical prototype is tested and validated achieving simultaneously reduction and harvesting functions.

Keywords: energy harvesting, piezoelectricity, torsional vibration, vibration absorber

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Authors: Kseniya Gladun

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Tactile stimulation of a dorsal side of the wrist can have a strong impact on our attitude toward physical objects such as pleasant and unpleasant impact. This study explored different aspects of tactile perception to investigate atypical touch sensitivity in children with autism spectrum disorder (ASD). This study included 40 children with ASD and 40 healthy children aged 5 to 9 years. We recorded rsEEG (sampling rate of 250 Hz) during 20 min using EEG amplifier “Encephalan” (Medicom MTD, Taganrog, Russian Federation) with 19 AgCl electrodes placed according to the International 10–20 System. The electrodes placed on the left, and right mastoids served as joint references under unipolar montage. The registration of EEG v19 assignments was carried out: frontal (Fp1-Fp2; F3-F4), temporal anterior (T3-T4), temporal posterior (T5-T6), parietal (P3-P4), occipital (O1-O2). Subjects were passively touched by 4 types of tactile stimuli on the left wrist. Our stimuli were presented with a velocity of about 3–5 cm per sec. The stimuli materials and procedure were chosen for being the most "pleasant," "rough," "prickly" and "recognizable". Type of tactile stimulation: Soft cosmetic brush - "pleasant" , Rough shoe brush - "rough", Wartenberg pin wheel roller - "prickly", and the cognitive tactile stimulation included letters by finger (most of the patient’s name ) "recognizable". To designate the moments of the stimuli onset-offset, we marked the moment when the moment of the touch began and ended; the stimulation was manual, and synchronization was not precise enough for event-related measures. EEG epochs were cleaned from eye movements by ICA-based algorithm in EEGLAB plugin for MatLab 7.11.0 (Mathwork Inc.). Muscle artifacts were cut out by manual data inspection. The response to tactile stimuli was significantly different in the group of children with ASD and healthy children, which was also depended on type of tactile stimuli and the severity of ASD. Amplitude of Alpha rhythm increased in parietal region to response for only pleasant stimulus, for another type of stimulus ("rough," "thorny", "recognizable") distinction of amplitude was not observed. Correlation dimension D2 was higher in healthy children compared to children with ASD (main effect ANOVA). In ASD group D2 was lower for pleasant and unpleasant compared to the background in the right parietal area. Hilbert transform changes in the frequency of the theta rhythm found only for a rough tactile stimulation compared with healthy participants only in the right parietal area. Children with autism spectrum disorders and healthy children were responded to tactile stimulation differently with specific frequency distribution alpha and theta band in the right parietal area. Thus, our data supports the hypothesis that rsEEG may serve as a sensitive index of altered neural activity caused by ASD. Children with autism have difficulty in distinguishing the emotional stimuli ("pleasant," "rough," "prickly" and "recognizable").

Keywords: autism, tactile stimulation, Hilbert transform, pediatric electroencephalography

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Authors: A. Rahim Baharudin, Nor Arinee binti Mat Saaud, Muhammad Afiq Azman, Farah Adiba A. Sani

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Objectives: This paper shares the case study on the engineering analysis, data analysis, and real-time data comparison for qualifying the stand wires' minimum breaking load and safe working load upon loadout operation for a new project and, at the same time, eliminate the risk due to discrepancies and unalignment of COMPANY Technical Standards to Industry Standards and Practices. This paper demonstrates “Lean Construction” for COMPANY’s Project by sustaining fit-for-purpose Technical Requirements of Loadout Strand Wire Factor of Safety (F.S). The case study utilizes historical engineering data from a few loadout operations by skidding methods from different projects. It is also demonstrating and qualifying the skidding wires' minimum breaking load and safe working load used for loadout operation for substructure and other facilities for the future. Methods: Engineering analysis and comparison of data were taken as referred to the international standard and internal COMPANY standard requirements. Data was taken from nine (9) previous projects for both topsides and jacket facilities executed at the several local fabrication yards where load out was conducted by three (3) different service providers with emphasis on four (4) basic elements: i) Industry Standards for Loadout Engineering and Operation Reference: COMPANY internal standard was referred to superseded documents of DNV-OS-H201 and DNV/GL 0013/ND. DNV/GL 0013/ND and DNVGL-ST-N001 do not mention any requirements of Strand Wire F.S of 4.0 for Skidding / Pulling Operations. ii) Reference to past Loadout Engineering and Execution Package: Reference was made to projects delivered by three (3) major offshore facilities operators. Strand Wire F.S observed ranges from 2.0 MBL (Min) to 2.5 MBL (Max). No Loadout Operation using the requirements of 4.0 MBL was sighted from the reference. iii) Strand Jack Equipment Manufacturer Datasheet Reference: Referring to Strand Jack Equipment Manufactured Datasheet by different loadout service providers, it is shown that the Designed F.S for the equipment is also ranging between 2.0 ~ 2.5. Eight (8) Strand Jack Datasheet Model was referred to, ranging from 15 Mt to 850 Mt Capacity; however, there are NO observations of designed F.S 4.0 sighted. iv) Site Monitoring on Actual Loadout Data and Parameter: Max Load on Strand Wire was captured during 2nd Breakout, which is during Static Condition of 12.9 MT / Strand Wire (67.9% Utilization). Max Load on Strand Wire for Dynamic Conditions during Step 8 and Step 12 is 9.4 Mt / Strand Wire (49.5% Utilization). Conclusion: This analysis and study demonstrated the adequacy of strand wires supplied by the service provider were technically sufficient in terms of strength, and via engineering analysis conducted, the minimum breaking load and safe working load utilized and calculated for the projects were satisfied and operated safely for the projects. It is recommended from this study that COMPANY’s technical requirements are to be revised for future projects’ utilization.

Keywords: construction, load out, minimum breaking load, safe working load, strand jacking, skidding

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Authors: Marlon Gallo, Eduardo Miguel, Laura Oca, Eneko Gonzalez, Unai Iraola

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The heat generation of an energy storage system is an essential topic when designing a battery pack and its cooling system. Heat generation estimation is used together with thermal models to predict battery temperature in operation and adapt the design of the battery pack and the cooling system to these thermal needs guaranteeing its safety and correct operation. In the present work, a comparison between the use of a heat flux sensor (HFS) for indirect measurement of heat losses in a cell and the widely used and simplified version of Bernardi’s equation for estimation is presented. First, a Li-ion cell is thermally characterized with an HFS to measure the thermal parameters that are used in a first-order lumped thermal model. These parameters are the equivalent thermal capacity and the thermal equivalent resistance of a single Li-ion cell. Static (when no current is flowing through the cell) and dynamic (making current flow through the cell) tests are conducted in which HFS is used to measure heat between the cell and the ambient, so thermal capacity and resistances respectively can be calculated. An experimental platform records current, voltage, ambient temperature, surface temperature, and HFS output voltage. Second, an equivalent circuit model is built in a Matlab-Simulink environment. This allows the comparison between the generated heat predicted by Bernardi’s equation and the HFS measurements. Data post-processing is required to extrapolate the heat generation from the HFS measurements, as the sensor records the heat released to the ambient and not the one generated within the cell. Finally, the cell temperature evolution is estimated with the lumped thermal model (using both HFS and Bernardi’s equation total heat generation) and compared towards experimental temperature data (measured with a T-type thermocouple). At the end of this work, a critical review of the results obtained and the possible mismatch reasons are reported. The results show that indirectly measuring the heat generation with HFS gives a more precise estimation than Bernardi’s simplified equation. On the one hand, when using Bernardi’s simplified equation, estimated heat generation differs from cell temperature measurements during charges at high current rates. Additionally, for low capacity cells where a small change in capacity has a great influence on the terminal voltage, the estimated heat generation shows high dependency on the State of Charge (SoC) estimation, and therefore open circuit voltage calculation (as it is SoC dependent). On the other hand, with indirect measuring the heat generation with HFS, the resulting error is a maximum of 0.28ºC in the temperature prediction, in contrast with 1.38ºC with Bernardi’s simplified equation. This illustrates the limitations of Bernardi’s simplified equation for applications where precise heat monitoring is required. For higher current rates, Bernardi’s equation estimates more heat generation and consequently, a higher predicted temperature. Bernardi´s equation accounts for no losses after cutting the charging or discharging current. However, HFS measurement shows that after cutting the current the cell continues generating heat for some time, increasing the error of Bernardi´s equation.

Keywords: lithium-ion battery, heat flux sensor, heat generation, thermal characterization

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Authors: Animesh Pan, Geoffrey D. Bothun

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With the development of nanotechnology, research in multifunctional delivery systems has a new pace and dimension. An incipient challenge is to design an all-in-one delivery system that can be used for multiple purposes, including tumor targeting therapy, radio-frequency (RF-), near-infrared (NIR-), light-, or pH-induced controlled release, photothermal therapy (PTT), photodynamic therapy (PDT), and medical diagnosis. In this regard, various inorganic nanoparticles (NPs) are known to show great potential as the 'functional components' because of their fascinating and tunable physicochemical properties and the possibility of multiple theranostic modalities from individual NPs. Magnetic, luminescent, and plasmonic properties are the three most extensively studied and, more importantly biomedically exploitable properties of inorganic NPs. Although successful attempts of combining any two of them above mentioned functionalities have been made, integrating them in one system has remained challenge. Keeping those in mind, controlled designs of complex colloidal nanoparticle system are one of the most significant challenges in nanoscience and nanotechnology. Therefore, systematic and planned studies providing better revelation are demanded. We report a multifunctional delivery platform-based liposome loaded with drug, iron-oxide magnetic nanoparticles (MNPs), and a gold shell on the surface of liposomes, were synthesized using a lipid with polyelectrolyte (layersomes) templating technique. MNPs and the anti-cancer drug doxorubicin (DOX) were co-encapsulated inside liposomes composed by zwitterionic phophatidylcholine and anionic phosphatidylglycerol using reverse phase evaporation (REV) method. The liposomes were coated with positively charge polyelectrolyte (poly-L-lysine) to enrich the interface with gold anion, exposed to a reducing agent to form a gold nanoshell, and then capped with thio-terminated polyethylene glycol (SH-PEG2000). The core-shell nanostructures were characterized by different techniques like; UV-Vis/NIR scanning spectrophotometer, dynamic light scattering (DLS), transmission electron microscope (TEM). This multifunctional system achieves a variety of functions, such as radiofrequency (RF)-triggered release, chemo-hyperthermia, and NIR laser-triggered for photothermal therapy. Herein, we highlight some of the remaining major design challenges in combination with preliminary studies assessing therapeutic objectives. We demonstrate an efficient loading and delivery system to significant cell death of human cancer cells (A549) with therapeutic capabilities. Coupled with RF and NIR excitation to the doxorubicin-loaded core-shell nanostructure helped in securing targeted and controlled drug release to the cancer cells. The present core-shell multifunctional system with their multimodal imaging and therapeutic capabilities would be eminent candidates for cancer theranostics.

Keywords: cancer thernostics, multifunctional nanostructure, photothermal therapy, radiofrequency targeting

Procedia PDF Downloads 106