Search results for: Membrane stability index (MSI)

Authors: Johns Paul, Santhosh J. Nalluveettil, P. Purushothaman, M. Premdas

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Lunar landing is one of the most critical phases of lunar mission. The lander is provided with a soft landing system to prevent structural damage of lunar module by absorbing the landing shock and also assure stability during landing. Presently available software are not capable to simulate the rigid body dynamics coupled with contact simulation and elastic/plastic deformation analysis. Hence a separate mathematical model has been generated for studying the dynamics of a typical lunar soft lander. Parameters used in the analysis includes lunar surface slope, coefficient of friction, initial touchdown velocity (vertical and horizontal), mass and moment of inertia of lander, crushing force due to energy absorbing material in the legs, number of legs and geometry of lander. The mathematical model is capable to simulate plastic and elastic deformation of honey comb, frictional force between landing leg and lunar soil, surface contact simulation, lunar gravitational force, rigid body dynamics and linkage dynamics of inverted tripod landing gear. The non linear differential equations generated for studying the dynamics of lunar lander is solved by numerical method. Matlab programme has been used as a computer tool for solving the numerical equations. The position of each kinematic joint is defined by mathematical equations for the generation of equation of motion. All hinged locations are defined by position vectors with respect to body fixed coordinate. The vehicle rigid body rotations and motions about body coordinate are only due to the external forces and moments arise from footpad reaction force due to impact, footpad frictional force and weight of vehicle. All these force are mathematically simulated for the generation of equation of motion. The validation of mathematical model is done by two different phases. First phase is the validation of plastic deformation of crushable elements by employing conservation of energy principle. The second phase is the validation of rigid body dynamics of model by simulating a lander model in ADAMS software after replacing the crushable elements to elastic spring element. Simulation of plastic deformation along with rigid body dynamics and contact force cannot be modeled in ADAMS. Hence plastic element of primary strut is replaced with a spring element and analysis is carried out in ADAMS software. The same analysis is also carried out using the mathematical model where the simulation of honeycomb crushing is replaced by elastic spring deformation and compared the results with ADAMS analysis. The rotational motion of linkages and 6 degree of freedom motion of lunar Lander about its CG can be validated by ADAMS software by replacing crushing element to spring element. The model is also validated by the drop test results of 4 leg lunar lander. This paper presents the details of mathematical model generated and its validation.

Keywords: honeycomb, landing leg tripod, lunar lander, primary link, secondary link

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Authors: Jungyeol Hong, Dongjoo Park

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The urban transit system is a critical part of a solution to the economic, energy, and environmental challenges. Furthermore, it ultimately contributes the improvement of people’s quality of lives. For taking these kinds of advantages, the city of Seoul has tried to construct an integrated transit system including both subway and buses. The effort led to the fact that approximately 6.9 million citizens use the integrated transit system every day for their trips. Diagnosing the current transit network is a significant task to provide more convenient and pleasant transit environment. Therefore, the critical objective of this study is to establish a methodological framework for the analysis of an integrated bus-subway network and to examine the relationship between subway ridership and parameters such as network topology measures, bus demand, and a variety of commercial business facilities. Regarding a statistical approach to estimate subway ridership at a station level, many previous studies relied on Ordinary Least Square regression, but there was lack of studies considering the endogeneity issues which might show in the subway ridership prediction model. This study focused on both discovering the impacts of integrated transit network topology measures and endogenous effect of bus demand on subway ridership. It could ultimately contribute to developing more accurate subway ridership estimation accounting for its statistical bias. The spatial scope of the study covers Seoul city in South Korea, and it includes 243 subway stations and 10,120 bus stops with the temporal scope set during twenty-four hours with one-hour interval time panels each. The subway and bus ridership information in detail was collected from the Seoul Smart Card data in 2015 and 2016. First, integrated subway-bus network topology measures which have characteristics regarding connectivity, centrality, transitivity, and reciprocity were estimated based on the complex network theory. The results of integrated transit network topology analysis were compared to subway-only network topology. Also, the non-recursive approach which is Three-Stage Least Square was applied to develop the daily subway ridership model as capturing the endogeneity between bus and subway demands. Independent variables included roadway geometry, commercial business characteristics, social-economic characteristics, safety index, transit facility attributes, and dummies for seasons and time zone. Consequently, it was found that network topology measures were significant size effect. Especially, centrality measures showed that the elasticity was a change of 4.88% for closeness centrality, 24.48% for betweenness centrality while the elasticity of bus ridership was 8.85%. Moreover, it was proved that bus demand and subway ridership were endogenous in a non-recursive manner as showing that predicted bus ridership and predicted subway ridership is statistically significant in OLS regression models. Therefore, it shows that three-stage least square model appears to be a plausible model for efficient subway ridership estimation. It is expected that the proposed approach provides a reliable guideline that can be used as part of the spectrum of tools for evaluating a city-wide integrated transit network.

Keywords: integrated transit system, network topology measures, three-stage least squared, endogeneity, subway ridership

Procedia PDF Downloads 179

Authors: K. Yu Vlasova, M. A. Abakumov, H. Wishwarsao, M. Sokolsky, N. V. Nukolova, A. G. Majouga, Y. I. Golovin, N. L. Klyachko, A. V. Kabanov

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Introduction:Nowadays pharmaceutical medicine is aimed to create systems for combined therapy, diagnostic, drug delivery and controlled release of active molecules to target cells. Magnetic nanoparticles (MNPs) are used to achieve this aim. MNPs can be applied in molecular diagnostics, magnetic resonance imaging (T1/T2 contrast agents), drug delivery, hyperthermia and could improve therapeutic effect of drugs. The most common drug containers, containing MNPs, are liposomes, micelles and polymeric molecules bonded to the MNPs surface. Usually superparamagnetic nanoparticles are used (the general diameter is about 5-6 nm) and all effects of high frequency magnetic field (MF) application are based on Neel relaxation resulting in heating of surrounded media. In this work we try to develop a new method to improve drug release from MNPs under super low frequency MF. We suppose that under low frequency MF exposures the Brown’s relaxation dominates and MNPs rotation could occur leading to conformation changes and release of bioactive molecules immobilized on MNPs surface.The aim of this work was to synthesize different systems with active drug (biopolymers coated MNPs nanoclusters with immobilized enzymes and doxorubicin (Dox) loaded magnetic liposomes/micelles) and investigate the effect of super low frequency MF on these drug containers. Methods: We have synthesized MNPs of magnetite with magnetic core diameter 7-12 nm . The MNPs were coated with block-copolymer of polylysine and polyethylene glycol. Superoxide dismutase 1 (SOD1) was electrostatically adsorbed on the surface of the clusters. Liposomes were prepared as follow: MNPs, phosphatidylcholine and cholesterol were dispersed in chloroform, dried to get film and then dispersed in distillated water, sonicated. Dox was added to the solution, pH was adjusted to 7.4 and excess of drug was removed by centrifugation through 3 kDa filters. Results: Polylysine coated MNPs formed nanosized clusters (as observed by TEM) with intensity average diameter of 112±5 nm and zeta potential 12±3 mV. After low frequency AC MF exposure we observed change of immobilized enzyme activity and hydrodynamic size of clusters. We suppose that the biomolecules (enzymes) are released from the MNPs surface followed with additional aggregation of complexes at the MF in medium. Centrifugation of the nanosuspension after AC MF exposures resulted in increase of positive charge of clusters and change in enzyme concentration in comparison with control sample without MF, thus confirming desorption of negatively charged enzyme from the positively charged surface of MNPs. Dox loaded magnetic liposomes had average diameter of 160±8 nm and polydispersity index (PDI) 0.25±0.07. Liposomes were stable in DW and PBS at pH=7.4 at 370C during a week. After MF application (10 min of exposure, 50 Hz, 230 mT) diameter of liposomes raised to 190±10 nm and PDI was 0.38±0.05. We explain this by destroying and/or reorganization of lipid bilayer, that leads to changes in release of drug in comparison with control without MF exposure. Conclusion: A new application of low frequency AC MF for drug delivery and controlled drug release was shown. Investigation was supported by RSF-14-13-00731 grant, K1-2014-022 grant.

Keywords: magnetic nanoparticles, low frequency magnetic field, drug delivery, controlled drug release

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Authors: Zahra Shakoori, Farid Salmanpour

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Pollination services are a vital service for the ecosystem to maintain environmental stability. The decline of pollinators can disrupt the ecological balance by affecting components of biodiversity. Bumble bees are crucial pollinators, playing a vital role in maintaining plant diversity. This study investigated the temporal patterns of their visitation to flowers in Kiasar National Park, Iran. Observations were conducted in Jun 2024, totaling 442 person-minutes of observation. Five species of bumble bees were identified. The study revealed that they consistently visited an average of 12-15 flowers per minute, regardless of species. The findings highlight the importance of protecting natural habitats, where their populations are thriving in the absence of human-induced stressors. This study was conducted in Kiasar National Park, located in the southeast of Mazandaran, northern Iran. The surveyed area, at an altitude of 1800-2200 meters, includes both forest and pasture. Bumble bee surveys were carried out on sunny days from June 2024, starting at dawn and ending at sunset. To avoid double-counting, we systematically searched for foraging habitats on low-sloping ridges with high mud density, frequently moving between patches. We recorded bumble bee visits to flowers and plant species per minute using direct observation, a stopwatch, and a pre-prepared form. We used statistical analysis of variance (ANOVA) with a confidence level of 95% to examine potential differences in foraging rates across different bumble bee species, flowers, plant bases, and plant species visited. Bumble bee identification relied on morphological indicators. A total of 442 person-minutes of bumble bee observations were recorded. Five species of bumble bees (Bombus fragrans, Bombus haematurus, Bombus lucorum, Bombus melanurus, Bombus terrestris) were identified during the study. The results of this study showed that the visits of bumble bees to flower sources were not different from each other. In general, bumble bees visit an average of 12-15 flowers every 60 seconds. In addition, at the same time they visit between 3-5 plant bases. Finally, they visit an average of 1 to 3 plant species per minute. While many taxa contribute to pollination, insects—especially bees—are crucial for maintaining plant diversity and ecosystem functions. As plant diversity increases, the stopping rate of pollinating insects rises, which reduces their foraging activity. Bumble bees, therefore, stop more frequently in natural areas than in agricultural fields due to higher plant diversity. Our findings emphasize the need to protect natural habitats like Kiasar National Park, where bumble bees thrive without human-induced stressors like pesticides, livestock grazing, and pollution. With bumble bee populations declining globally, further research is essential to understand their behavior in different environments and develop effective conservation strategies to protect them.

Keywords: bumble bees, pollination, pollinator, plant diversity, Iran

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Authors: S. Gustafsson

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The aim of this paper is to explore the connection between gender, agency, and health on personal and social levels over time. The use of gender as an analytical tool for health research has been shown to be useful to explore thoughts and ideas that are taken for granted, which have relevance for health. The paper highlights the following three issues. There are multiple forms of femininity and masculinity. Agency and social structure are closely related and referred to in this paper as 'gender agency'. Gender is illuminated as a product of history but also treated as a social factor and a producer of history. As a prominent social factor in the process of shaping living conditions, gender is highlighted as being significant for understanding health. To make health explicit as a dynamic and complex concept and not merely the opposite of disease requires a broader alliance with feminist theory and a post-Bourdieusian framework. A personal story, included with other ethnographic material about women’s networking in rural Sweden, is used as an empirical illustration. Ethnographic material was chosen for its ability to illustrate historical, local, and cultural ways of doing gendered and capitalized health. New concepts characterize ethnography, exemplified in this study by 'processes of transformation'. The semi-structured interviews followed an interview guide drafted with reference to the background theory of gender. The interviews lasted about an hour and were recorded and transcribed verbatim. The transcribed interviews and the author’s field notes formed the basis for the writing up of this paper. Initially, the participants' interests in weaving, sewing, and various handicrafts became obvious foci for networking activities and seemed at first to shape compliance with patriarchy, which generally does the opposite of promoting health. However, a significant event disrupted the stability of this phenomenon. What was permissible for the women began to crack and new spaces opened up. By exploiting these new spaces, the participants found opportunities to try out alternatives to emphasized femininity. Over time, they began combining feminized activities with degrees of masculinity, as leadership became part of the activities. In response to this, masculine enactment was gradually transformed and became increasingly gender neutral. As the tasks became more gender neutral the activities assumed a more formal character and the women stretched the limits of their capacity by enacting gender agency, a process the participants referred to as 'personal growth' and described as health promotion. What was described in terms of 'personal growth' can be interpreted as the effects of a raised status. Participation in women’s networking strengthened the participants’ structural position. More specifically, it was the gender-neutral position that was rewarded. To clarify the connection between gender, agency, and health on personal and social levels over time the concept processes of transformation is used. This concept is suggested as a dynamic equivalent to habitus. Health is thus seen as resulting from situational access to social recognition, prestige, capital assets and not least, meanings of gender.

Keywords: a cross-gender bodily hexis, gender agency, gender as analytical tool, processes of transformation

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Authors: Yichao Liu, Peter Fransson, Julian Heidecke, Jonas Wallin, Joacim Rockloev

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Dengue, a mosquito-borne viral disease, poses a significant public health challenge in endemic tropical or subtropical countries, including Sri Lanka. To reveal insights into the complexity of the dynamics of this disease and study the drivers, a comprehensive model capable of both robust forecasting and insightful inference of drivers while capturing the co-circulating of several virus strains is essential. However, existing studies mostly focus on only one aspect at a time and do not integrate and carry insights across the siloed approach. While mechanistic models are developed to capture immunity dynamics, they are often oversimplified and lack integration of all the diverse drivers of disease transmission. On the other hand, purely data-driven methods lack constraints imposed by immuno-epidemiological processes, making them prone to overfitting and inference bias. This research presents a hybrid model that combines machine learning techniques with mechanistic modelling to overcome the limitations of existing approaches. Leveraging eight years of newly reported dengue case data, along with socioeconomic factors, such as human mobility, weekly climate data from 2011 to 2018, genetic data detecting the introduction and presence of new strains, and estimates of seropositivity for different districts in Sri Lanka, we derive a data-driven vector (SEI) to human (SEIR) model across 16 regions in Sri Lanka at the weekly time scale. By conducting ablation studies, the lag effects allowing delays up to 12 weeks of time-varying climate factors were determined. The model demonstrates superior predictive performance over a pure machine learning approach when considering lead times of 5 and 10 weeks on data withheld from model fitting. It further reveals several interesting interpretable findings of drivers while adjusting for the dynamics and influences of immunity and introduction of a new strain. The study uncovers strong influences of socioeconomic variables: population density, mobility, household income and rural vs. urban population. The study reveals substantial sensitivity to the diurnal temperature range and precipitation, while mean temperature and humidity appear less important in the study location. Additionally, the model indicated sensitivity to vegetation index, both max and average. Predictions on testing data reveal high model accuracy. Overall, this study advances the knowledge of dengue transmission in Sri Lanka and demonstrates the importance of incorporating hybrid modelling techniques to use biologically informed model structures with flexible data-driven estimates of model parameters. The findings show the potential to both inference of drivers in situations of complex disease dynamics and robust forecasting models.

Keywords: compartmental model, climate, dengue, machine learning, social-economic

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Authors: Same Noel Ngando, Yakub Abdulfatai Olatunji

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Renewable energy micro-grids, such as those powered by solar or wind energy, are often intermittent in nature. This means that the amount of energy generated by these systems can vary depending on weather conditions or other factors, which can make it difficult to ensure a steady supply of power. To address this issue, energy storage systems have been developed to increase the reliability of renewable energy micro-grids. Battery systems have been the dominant energy storage technology for renewable energy micro-grids. Batteries can store large amounts of energy in a relatively small and compact package, making them easy to install and maintain in a micro-grid setting. Additionally, batteries can be quickly charged and discharged, allowing them to respond quickly to changes in energy demand. However, the process involved in recycling batteries is quite costly and difficult. An alternative energy storage system that is gaining popularity is hydrogen storage. Hydrogen is a versatile energy carrier that can be produced from renewable energy sources such as solar or wind. It can be stored in large quantities at low cost, making it suitable for long-distance mass storage. Unlike batteries, hydrogen does not degrade over time, so it can be stored for extended periods without the need for frequent maintenance or replacement, allowing it to be used as a backup power source when the micro-grid is not generating enough energy to meet demand. When hydrogen is needed, it can be converted back into electricity through a fuel cell. Energy consumption data is got from a particular residential area in Daegu, South Korea, and the data is processed and analyzed. From the analysis, the total energy demand is calculated, and different hybrid energy system configurations are designed using HOMER Pro (Hybrid Optimization for Multiple Energy Resources) and MATLAB software. A techno-economic and environmental comparison and life cycle assessment (LCA) of the different configurations using battery and hydrogen as storage systems are carried out. The various scenarios included PV-hydrogen-grid system, PV-hydrogen-grid-wind, PV-hydrogen-grid-biomass, PV-hydrogen-wind, PV-hydrogen-biomass, biomass-hydrogen, wind-hydrogen, PV-battery-grid-wind, PV- battery -grid-biomass, PV- battery -wind, PV- battery -biomass, and biomass- battery. From the analysis, the least cost system for the location was the PV-hydrogen-grid system, with a net present cost of about USD 9,529,161. Even though all scenarios were environmentally friendly, taking into account the recycling cost and pollution involved in battery systems, all systems with hydrogen as a storage system produced better results. In conclusion, hydrogen is becoming a very prominent energy storage solution for renewable energy micro-grids. It is easier to store compared with electric power, so it is suitable for long-distance mass storage. Hydrogen storage systems have several advantages over battery systems, including flexibility, long-term stability, and low environmental impact. The cost of hydrogen storage is still relatively high, but it is expected to decrease as more hydrogen production, and storage infrastructure is built. With the growing focus on renewable energy and the need to reduce greenhouse gas emissions, hydrogen is expected to play an increasingly important role in the energy storage landscape.

Keywords: renewable energy systems, microgrid, hydrogen production, energy storage systems

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Authors: Jing (Claire) LI

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More than two decades from 2000 to 2020 of economic reforms have brought China unprecedented economic growth. There is an urgent call of research towards corporate social responsibility (CSR) in the context of China because while China continues to develop into a global trading market, it suffers from various serious problems relating to CSR. This study analyses the factors affecting the adoption of CSR practices by Chinese listed companies. The author proposes a new framework of factors of CSR adoption. Following common organisational factors and external factors in the literature (including organisational support, company size, shareholder pressures, and government support), this study introduces two additional factors, dynamic capability and regional culture. A survey questionnaire was conducted on the CSR adoption of Chinese listed companies in Shen Zhen and Shang Hai index from December 2019 to March 2020. The survey was conducted to collect data on the factors that affect the adoption of CSR. After collection of data, this study performed factor analysis to reduce the number of measurement items to several main factors. This procedure is to confirm the proposed framework and ensure the significant factors. Through analysis, this study identifies four grouped factors as determinants of the CSR adoption. The first factor loading includes dynamic capability and organisational support. The study finds that they are positively related to the first factor, so the first factor mainly reflects the capabilities of companies, which is one component in internal factors. In the second factor, measurement items of stakeholder pressures mainly are from regulatory bodies, customer and supplier, employees and community, and shareholders. In sum, they are positively related to the second factor and they reflect stakeholder pressures, which is one component of external factors. The third factor reflects organisational characteristics. Variables include company size and cultural score. Among these variables, company size is negatively related to the third factor. The resulted factor loading of the third factor implies that organisational factor is an important determinant of CSR adoption. Cultural consistency, the variable in the fourth factor, is positively related to the factor. It represents the difference between perception of managers and actual culture of the organisations in terms of cultural dimensions, which is one component in internal factors. It implies that regional culture is an important factor of CSR adoption. Overall, the results are consistent with previous literature. This study is of significance from both theoretical and empirical perspectives. First, from the significance of theoretical perspective, this research combines stakeholder theory, dynamic capability view of a firm, and neo-institutional theory in CSR research. Based on association of these three theories, this study introduces two new factors (dynamic capability and regional culture) to have a better framework for CSR adoption. Second, this study contributes to empirical literature of CSR in the context of China. Extant Chinese companies lack recognition of the importance of CSR practices adoption. This study built a framework and may help companies to design resource allocation strategies and evaluate future CSR and management practices in an early stage.

Keywords: China, corporate social responsibility, CSR adoption, dynamic capability, regional culture

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Authors: Ramez F. Saad, Ahmad Kobaissi, Bernard Amiaud, Julien Ruelle, Emile Benizri

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Agromining is a new technology that establishes agricultural systems on ultramafic soils in order to produce valuable metal compounds such as nickel (Ni), with the final aim of restoring a soil's agricultural functions. But ultramafic soils are characterized by low fertility levels and this can limit yields of hyperaccumulators and metal phytoextraction. The objectives of the present work were to test if the association of a hyperaccumulating plant (Alyssum murale) and a Fabaceae (Vicia sativa var. Prontivesa) could induce changes in physicochemical characteristics of a serpentine soil and in root architecture of a hyperaccumulating plant then lead to efficient agromining practices through soil quality improvement. Based on standard agricultural systems, consisting in the association of legumes and another crop such as wheat or rape, a three-month rhizobox experiment was carried out to study the effect of the co-cropping (Co) or rotation (Ro) of a hyperaccumulating plant (Alyssum murale) with a legume (Vicia sativa) and incorporating legume biomass to soil, in comparison with mineral fertilization (FMo), on the structure and physicochemical properties of an ultramafic soil and on root architecture. All parameters measured (biomass, C and N contents, and taken-up Ni) on Alyssum murale conducted in co-cropping system showed the highest values followed by the mineral fertilization and rotation (Co > FMo > Ro), except for root nickel yield for which rotation was better than the mineral fertilization (Ro > FMo). The rhizosphere soil of Alyssum murale in co-cropping had larger soil particles size and better aggregates stability than other treatments. Using geostatistics, co-cropped Alyssum murale showed a greater root surface area spatial distribution. Moreover, co-cropping and rotation-induced lower soil DTPA-extractable nickel concentrations than other treatments, but higher pH values. Alyssum murale co-cropped with a legume showed a higher biomass production, improved soil physical characteristics and enhanced nickel phytoextraction. This study showed that the introduction of a legume into Ni agromining systems could improve yields of dry biomass of the hyperaccumulating plant used and consequently, the yields of Ni. Our strategy can decrease the need to apply fertilizers and thus minimizes the risk of nitrogen leaching and underground water pollution. Co-cropping of Alyssum murale with the legume showed a clear tendency to increase nickel phytoextraction and plant biomass in comparison to rotation treatment and fertilized mono-culture. In addition, co-cropping improved soil physical characteristics and soil structure through larger and more stabilized aggregates. It is, therefore, reasonable to conclude that the use of legumes in Ni-agromining systems could be a good strategy to reduce chemical inputs and to restore soil agricultural functions. Improving the agromining system by the replacement of inorganic fertilizers could simultaneously be a safe way of rehabilitating degraded soils and a method to restore soil quality and functions leading to the recovery of ecosystem services.

Keywords: plant association, legumes, hyperaccumulating plants, ultramafic soil physicochemical properties

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Authors: Ruth Hegarty, Noel Connaughton

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

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

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Authors: Sunil Chandra, Himanshu Rawat, Vikas Gusain, Triparna Barman

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Forest fires are a recurrent phenomenon in the Himalayan region owing to the presence of vulnerable forest types, topographical gradients, climatic weather conditions, and anthropogenic pressure. The present study focuses on the identification of forest fire-affected areas in a small part of the West Himalayan region using a differential normalized burnt ratio method and spectral unmixing methods. The study area has a rugged terrain with the presence of sub-tropical pine forest, montane temperate forest, and sub-alpine forest and scrub. The major reason for fires in this region is anthropogenic in nature, with the practice of human-induced fires for getting fresh leaves, scaring wild animals to protect agricultural crops, grazing practices within reserved forests, and igniting fires for cooking and other reasons. The fires caused by the above reasons affect a large area on the ground, necessitating its precise estimation for further management and policy making. In the present study, two approaches have been used for carrying out a burnt area analysis. The first approach followed for burnt area analysis uses a differenced normalized burnt ratio (dNBR) index approach that uses the burnt ratio values generated using the Short-Wave Infrared (SWIR) band and Near Infrared (NIR) bands of the Sentinel-2 image. The results of the dNBR have been compared with the outputs of the spectral mixing methods. It has been found that the dNBR is able to create good results in fire-affected areas having homogenous forest stratum and with slope degree <5 degrees. However, in a rugged terrain where the landscape is largely influenced by the topographical variations, vegetation types, tree density, the results may be largely influenced by the effects of topography, complexity in tree composition, fuel load composition, and soil moisture. Hence, such variations in the factors influencing burnt area assessment may not be effectively carried out using a dNBR approach which is commonly followed for burnt area assessment over a large area. Hence, another approach that has been attempted in the present study utilizes a spectral mixing method where the individual pixel is tested before assigning an information class to it. The method uses a neural network approach utilizing Sentinel-2 bands. The training and testing data are generated from the Sentinel-2 data and the national field inventory, which is further used for generating outputs using ML tools. The analysis of the results indicates that the fire-affected regions and their severity can be better estimated using spectral unmixing methods, which have the capability to resolve the noise in the data and can classify the individual pixel to the precise burnt/unburnt class.

Keywords: categorical data, log linear modeling, neural network, shifting cultivation

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Authors: Vladimir Berezin, Aizhan Turmagambetova, Andrey Bogoyavlenskiy, Pavel Alexyuk, Madina Alexyuk, Irina Zaitceva, Nadezhda Sokolova

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Introduction: Influenza viruses could infect approximately 5% to 10% of the global human population annually, resulting in serious social and economic damage. Vaccination and etiotropic antiviral drugs are used for the prevention and treatment of influenza. Vaccination is important; however, antiviral drugs represent the second line of defense against new emerging influenza virus strains for which vaccines may be unsuccessful. However, the significant drawback of commercial synthetic anti-flu drugs is the appearance of drug-resistant influenza virus strains. Therefore, the search and development of new anti-flu drugs efficient against drug-resistant strains is an important medical problem for today. The aim of this work was a study of four phenolic acids of plant origin (Gallic, Syringic, Vanillic, and Protocatechuic acids) as a possible tool for treatment against influenza virus. Methods: Phenolic acids; gallic, syringic, vanillic, and protocatechuic have been prepared by extraction from plant tissues and purified using high-performance liquid chromatography fractionation. Avian influenza virus, strain A/Tern/South Africa/1/1961 (H5N3) and human epidemic influenza virus, strain A/Almaty/8/98 (H3N2) resistant to commercial anti-flu drugs (Rimantadine, Oseltamivir) were used for testing antiviral activity. Viruses were grown in the allantoic cavity of 10 days old chicken embryos. The chemotherapeutic index (CTI), determined as the ratio of an average toxic concentration of the tested compound (TC₅₀) to the average effective virus-inhibition concentration (EC₅₀), has been used as a criteria of specific antiviral action. Results: The results of study have shown that the structure of phenolic acids significantly affected their ability to suppress the reproduction of tested influenza virus strains. The highest antiviral activity among tested phenolic acids was detected for gallic acid, which contains three hydroxyl groups in the molecule at C3, C4, and C5 positions. Antiviral activity of gallic acid against A/H5N3 and A/H3N2 influenza virus strains was higher than antiviral activity of Oseltamivir and Rimantadine. gallic acid inhibited almost 100% of the infection activity of both tested viruses. Protocatechuic acid, which possesses 2 hydroxyl groups (C3 and C4) have shown weaker antiviral activity in comparison with gallic acid and inhibited less than 10% of virus infection activity. Syringic acid, which contains two hydroxyl groups (C3 and C5), was able to suppress up to 12% of infection activity. Substitution of two hydroxyl groups by methoxy groups resulted in the complete loss of antiviral activity. Vanillic acid, which is different from protocatechuic acid by replacing of C3 hydroxyl group to methoxy group, was able to suppress about 30% of infection activity of tested influenza viruses. Conclusion: For pronounced antiviral activity, the molecular of phenolic acid must have at least two hydroxyl groups. Replacement of hydroxyl groups to methoxy group leads to a reduction of antiviral properties. Gallic acid demonstrated high antiviral activity against influenza viruses, including Rimantadine and Oseltamivir resistant strains, and could be used as a potential candidate for the development of antiviral drug against influenza virus.

Keywords: antiviral activity, influenza virus, drug resistance, phenolic acids

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Authors: Sandy Elsayed, Aya Mohamed, Noha Nassar

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Introduction: Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by social deficits and repetitive behavior. Multiple studies suggest that oxidative stress and neuroinflammation are key factors in the etiology of ASD and often associated with worsening of ASD-related behaviors. Nuclear factor erythroid 2-related factor 2 (NRF-2) is a transcription factor that promotes expression of antioxidant response element genes in oxidative stress. In ASD subjects, decreased expression of NRF-2 in frontal cortex shifted the redox homeostasis towards oxidative stress, and resulted in inflammation evidenced by elevation of nuclear factor kappa B (NF-κB) transcriptional activity. Dimethyl fumarate (DMF) is a NRF-2 activator that is used in the treatment of psoriasis and multiple sclerosis. It participates in the transcriptional control of inflammatory factors via inhibition of NF-κB and its downstream targets. This study aimed to investigate the role of DMF in alleviating the cognitive impairments and behavior deficits associated with ASD through mitigation of oxidative stress and inflammation in prenatal valproic acid (VPA) rat model of autism. Methods: Pregnant female Wistar rats received a single intraperitoneal injection of VPA (600 mg/kg) to induce autistic-like-behavioral and neurobiological alterations in their offspring. Chronic oral gavage of DMF (150mg/kg/day) started from postnatal day (PND) 24 till PND62 (39 days). Prenatal VPA exposure elicited autistic behaviors including decreased social interaction and stereotyped behavior. Social interaction was evaluated using three-chamber sociability test and calculation of sociability index (SI), while stereotyped repetitive behavior and anxiety associated with ASD were assessed using marble burying test (MBT). Biochemical analyses were done on prefrontal cortex homogenates including NRF-2, and NF-κB expression. Moreover, inducible nitric oxide synthase (iNOS) gene expression and tumor necrosis factor (TNF-) protein expression were evaluated as markers of inflammation. Results: Prenatal VPA elicited decreased social interaction shown by decreased SI compared to control group (p < 0.001) and DMF enhanced SI (p < 0.05). In MBT, prenatal injection of VPA manifested stereotyped behavior and enhanced number of buried marbles compared to control (p < 0.05) and DMF reduced the anxiety-related behavior in rats exhibiting ASD-like behaviors (p < 0.05). In prefrontal cortex, NRF-2 expression was downregulated in prenatal VPA model (p < 0.0001) and DMF reversed this effect (p < 0.0001). The inflammatory transcription factor NF-κB was elevated in prenatal VPA model (p < 0.0001) and reduced (p < 0.0001) upon NRF-2 activation by DMF. Prenatal VPA expressed higher levels of proinflammatory cytokine TNF- compared to control group (p < 0.0001) and DMF reduced it (p < 0.0001). Finally, the gene expression of iNOS was downregulated upon NRF-2 activation by DMF (p < 0.01). Conclusion: This study proposes that DMF is a potential agent that can be used to ameliorate autistic-like-changes through NRF-2 activation along with NF-κB downregulation and therefore, it is a promising novel therapy for ASD.

Keywords: autism spectrum disorders, dimethyl fumarate, neuroinflammation, NRF-2

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Authors: Abha Gupta, Deepak K. Mishra

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Food security issue in India has surrounded over availability and accessibility of cereal which is regarded as the only food group to check hunger and improve nutrition. Significance of fruits, vegetables, meat and other food products have totally been neglected given the fact that they provide essential nutrients to the body. There is a need to shift the emphasis from cereal-based approach to a more diverse diet so that aim of achieving food security may change from just reducing hunger to an overall health. This paper attempts to analyse how far dietary diversity level has been achieved across different socio-economic groups in India. For this purpose, present paper sets objectives to determine (a) percentage share of different food groups to total food expenditure and consumption by background characteristics (b) source of and preference for all food items and, (c) diversity of diet across socio-economic groups. A cross sectional survey covering 304 households selected through proportional stratified random sampling was conducted in six villages of Aligarh district of Uttar Pradesh, India. Information on amount of food consumed, source of consumption and expenditure on food (74 food items grouped into 10 major food groups) was collected with a recall period of seven days. Per capita per day food consumption/expenditure was calculated through dividing consumption/expenditure by household size and number seven. Food variety score was estimated by giving 0 values to those food groups/items which had not been eaten and 1 to those which had been taken by households in last seven days. Addition of all food group/item score gave result of food variety score. Diversity of diet was computed using Herfindahl-Hirschman index. Findings of the paper show that cereal, milk, roots and tuber food groups contribute a major share in total consumption/expenditure. Consumption of these food groups vary across socio-economic groups whereas fruit, vegetables, meat and other food consumption remain low and same. Estimation of dietary diversity show higher concentration of diet due to higher consumption of cereals, milk, root and tuber products and dietary diversity slightly varies across background groups. Muslims, Scheduled caste, small farmers, lower income class, food insecure, below poverty line and labour families show higher concentration of diet as compared to their counterpart groups. These groups also evince lower mean intake of number of food item in a week due to poor economic constraints and resultant lower accessibility to number of expensive food items. Results advocate to make a shift from cereal based diet to dietary diversity which not only includes cereal and milk products but also nutrition rich food items such as fruits, vegetables, meat and other products. Integrating a dietary diversity approach in food security programmes of the country would help to achieve nutrition security as hidden hunger is widespread among the Indian population.

Keywords: dietary diversity, food Security, India, socio-economic groups

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Authors: Oibar Martinez, Clara Oliver, Jose Miguel Miranda

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In this paper, we discuss the standard improvements which can be made to reduce the earth resistance in difficult terrains for optimum lightning protection, what are the practical limitations, and how the modeling can be refined for accurate diagnostics and ground resistance minimization. Ground resistance minimization can be made via three different approaches: burying vertical electrodes connected in parallel, burying horizontal conductive plates or meshes, or modifying the own terrain, either by changing the entire terrain material in a large volume or by adding earth-enhancing compounds. The use of vertical electrodes connected in parallel pose several practical limitations. In order to prevent loss of effectiveness, it is necessary to keep a minimum distance between each electrode, which is typically around five times larger than the electrode length. Otherwise, the overlapping of the local equipotential lines around each electrode reduces the efficiency of the configuration. The addition of parallel electrodes reduces the resistance and facilitates the measurement, but the basic parallel resistor formula of circuit theory will always underestimate the final resistance. Numerical simulation of equipotential lines around the electrodes overcomes this limitation. The resistance of a single electrode will always be proportional to the soil resistivity. The electrodes are usually installed with a backfilling material of high conductivity, which increases the effective diameter. However, the improvement is marginal, since the electrode diameter counts in the estimation of the ground resistance via a logarithmic function. Substances that are used for efficient chemical treatment must be environmentally friendly and must feature stability, high hygroscopicity, low corrosivity, and high electrical conductivity. A number of earth enhancement materials are commercially available. Many are comprised of carbon-based materials or clays like bentonite. These materials can also be used as backfilling materials to reduce the resistance of an electrode. Chemical treatment of soil has environmental issues. Some products contain copper sulfate or other copper-based compounds, which may not be environmentally friendly. Carbon-based compounds are relatively inexpensive and they do have very low resistivities, but they also feature corrosion issues. Typically, the carbon can corrode and destroy a copper electrode in around five years. These compounds also have potential environmental concerns. Some earthing enhancement materials contain cement, which, after installation acquire properties that are very close to concrete. This prevents the earthing enhancement material from leaching into the soil. After analyzing different configurations, we conclude that a buried conductive ring with vertical electrodes connected periodically should be the optimum baseline solution for the grounding of a large size structure installed on a large resistivity terrain. In order to show this, a practical example is explained here where we simulate the ground resistance of a conductive ring buried in a terrain with a resistivity in the range of 1 kOhm·m.

Keywords: grounding improvements, large scale scientific instrument, lightning risk assessment, lightning standards

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Authors: Bensaid A., Mostephaoui T., Nedjai R.

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A considerable area of Algerian lands are threatened by the phenomenon of wind erosion. For a long time, wind erosion and its associated harmful effects on the natural environment have posed a serious threat, especially in the arid regions of the country. In recent years, as a result of increases in the irrational exploitation of natural resources (fodder) and extensive land clearing, wind erosion has particularly accentuated. The extent of degradation in the arid region of the Algerian Mécheriadepartment generated a new situation characterized by the reduction of vegetation cover, the decrease of land productivity, as well as sand encroachment on urban development zones. In this study, we attempt to investigate the potential of remote sensing and geographic information systems for detecting the spatial dynamics of the ancient dune cords based on the numerical processing of PlanetScope PSB.SB sensors images by September 29, 2021. As a second step, we prospect the use of a multi-scale geographic object-based image analysis (GEOBIA) approach to segment the high spatial resolution images acquired on heterogeneous surfaces that vary according to human influence on the environment. We have used the fractal net evolution approach (FNEA) algorithm to segment images (Baatz&Schäpe, 2000). Multispectral data, a digital terrain model layer, ground truth data, a normalized difference vegetation index (NDVI) layer, and a first-order texture (entropy) layer were used to segment the multispectral images at three segmentation scales, with an emphasis on accurately delineating the boundaries and components of the sand accumulation areas (Dune, dunes fields, nebka, and barkhane). It is important to note that each auxiliary data contributed to improve the segmentation at different scales. The silted areas were classified using a nearest neighbor approach over the Naâma area using imagery. The classification of silted areas was successfully achieved over all study areas with an accuracy greater than 85%, although the results suggest that, overall, a higher degree of landscape heterogeneity may have a negative effect on segmentation and classification. Some areas suffered from the greatest over-segmentation and lowest mapping accuracy (Kappa: 0.79), which was partially attributed to confounding a greater proportion of mixed siltation classes from both sandy areas and bare ground patches. This research has demonstrated a technique based on very high-resolution images for mapping sanded and degraded areas using GEOBIA, which can be applied to the study of other lands in the steppe areas of the northern countries of the African continent.

Keywords: land development, GIS, sand dunes, segmentation, remote sensing

Procedia PDF Downloads 109

Authors: Aungkana Kmonpetch

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Protection of trafficked victims and partnership among stakeholders are established as core principles in 5P’ strategies in international and national anti-human trafficking policies. In this article, it is of interest to discuss how the role of public-private partnerships in promoting the occupation development for employment in wage will enhance the better protection for victims of trafficking who affirmatively decide they want a criminal justice intervention, using Thailand as a case. Most of the victims who have accepted to be witness in the criminal justice system have lost income during their absence from work. The analysis of Thailand case is based on two methodological approaches: 1) interview with victims of trafficking, protection authorities, service providers, trainers and teachers, social workers, NGOs, police, prosecutors, business owners and enterprises, ILO, UNDP etc.; 2) create collaborative effort through workshops/consultation meetings in participation of all stakeholders – governmental agencies, private organizations, UN and international agencies. The linking of protection and partnership is anchored in international conventions and human trafficking directives. While this is actually framed as a responsive advantage for 5P strategies of anti-human trafficking – prevention, protection, persecution, punishment, and partnership, in reality, there might have more practical requirements of care and support. The article addresses how the partnership between governmental agencies and private organizations provide opportunities for trafficked victims to engage in high-skilled occupational development such as Silk-Sewing and Tailoring. The discussion is also focused how this approach of capacity building of the trainer for trainee, be enable the trafficked victims to cultivate the practices of high-skilled training to engage them into the business of social enterprise with employment in wage. The partnership coordination draws specifically to two aspects: firstly, to formulate appropriate assistance for promotion and protection of human rights of the trafficked victims in response to the 5P’ strategies of anti-human trafficking policy; secondly, to empower them to settle some economic stability for livelihood opportunity in the country of origin on their return and reintegration. Therefore, they can define how they want to move forward to prevent them at risk of vulnerable situations where they might being trafficked again or going on to work in exploitative conditions. It strengthens proper access to protection and assistance, depending on how the incentive of protection for cooperation is perceived to be and how useful the capacity building in occupation development for employment in wage will be implemented practically both in the host country and in the country of origin. This also brings into question how the victim of trafficking are able to access to the trade of market and are supported the employment opportunity according to the concept of decent work as they are constituted as witnesses. We discuss these issues in the area of a broader literature on social protection, economic security, gender, law, and victimhood.

Keywords: employment opportunity, occupation development, protection for victim of trafficking, public-private partnership

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Authors: Sunitha Sampathi, Pankaj Kumar Tiriya, Sonia Gera, Sravanthi Reddy Pailla, V. Likhitha, A. J. Maruthi

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Surgical site infections (SSIs) are the most common nosocomial infections localized at the incision site. With an estimated 27 million surgical procedures each year in USA, approximately 2-5% rate of SSIs are predicted to occur annually. SSIs are treated with antibiotic medication. Current trend suggest that the direct drug delivery from the suture to the scared tissue can improve patient comfort and wound recovery. For that reason coating the surface of the medical device such as suture and catguts with broad spectrum antibiotics can prevent the formation of bactierial colonies with out comprimising the mechanical properties of the sutures.Hence, the present study was aimed to develop and evaluate a surgical suture coated with an antibiotic Ciprofloxacin hydrochloride loaded on gold nanoparticles. Gold nanoparticles were synthesized by chemical reduction method and conjugated with ciprofloxacin using Polyvinylpyrolidone as stabilizer and gold as carrier. Ciprofloxacin conjugated gold nanoparticles were coated over an absorbable surgical suture made of Polyglactan using sodium alginate as an immobilising agent by slurry dipping technique. The average particle size and Polydispersity Index of drug conjugated gold NPs were found to be 129±2.35 nm and 0.243±0.36 respectively. Gold nanoparticles are characterized by UV-Vis absorption spectroscopy, Fourier Transform Infrared Spectroscopy (FT-IR), Scanning electron microscopy and Transmission electron microscopy. FT-IR revealed that there is no chemical interaction between drug and polymer. Antimicrobial activity for coated sutures was evaluated by disc diffusion method on culture plates of both gram negative (E-coli) and gram positive bacteria (Staphylococcus aureus) and results found to be satisfactory. In vivo studies for coated sutures was performed on Swiss albino mice and histological evaluation of intestinal wound healing parameters such as wound edges in mucosa, muscularis, presence of necrosis, exudates, granulation tissue, granulocytes, macrophages, restoration, and repair of mucosal epithelium and muscularis propria on day 7 after surgery were studied. The control animal group, sutured with plain suture (uncoated suture) showed signs of restoration and repair, but presence of necrosis, heamorraghic infiltration and granulation tissue was still noticed. Whereas the animal group treated with ciprofloxacin and ciprofloxacin gold nanoparticle coated sutures has shown promising decrease in terms of haemorraghic infiltration, granulation tissue, necrosis and better repaired muscularis layers on comparision with plain coated sutures indicating faster rate of repair and less chance of sepsis. Hence coating of sutures with broad spectrum antibiotics can be an alternate technique to reduce SSIs.

Keywords: ciprofloxacin hydrochloride, gold nanoparticles, surgical site infections, sutures

Procedia PDF Downloads 256

Authors: Elena Samarsky

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According to German national records and willingness to migrate surveys, emigration is much more attractive for better educated citizens employed in white-collar positions, with academics displaying the highest migration rate. The case study of academic migration from Germany is furthermore intriguing due to the country's financial power, competitive labour market and relatively good life-standards, working conditions and high wage rates. Investigation of such mobility challenges traditional economic view on migration, as it raises the question of why people chose to leave their highly-industrialized countries known for their high life-standards, stable political scene and prosperous economy. Within the regional domain, examining mobility of Germans contributes to the ongoing debate over the extent of influence of the EU mobility principle on migration decision. The latter is of particular interest, as it may shed the light on the extent to which it frames individual migration path, defines motivations and colours the experiences of migration action itself. The paper is based on the analysis of the migration decisions obtained through in-depth interviews with German academics employed in the UK. These retrospective interviews were conducted with German academies across selected universities in the UK, employed in a variety of academic fields, and different career stages. Interviews provide a detailed description of what motivated people to search for a post in another country, which attributes of such job are needed to be satisfied in order to facilitate migration, as well as general information on particularities of an academic career and institutions involved. In the course of the project, it became evident that although securing financial stability was non-negotiable factor in migration (e.g., work contract singed before relocation) non-pecuniary motivations played significant role as well. Migration narratives of this group - the highly skilled, whose human capital is transferable, and whose expertise is positively evaluated by countries, is mainly characterised by search for personal development and career advancement, rather than a direct increase in their income. Such records are also consistent in showing that in case of academics, scientific freedom and independence are the main attributes of a perfect job and are a substantial motivator. On the micro level, migration is rather depicted as an opportunistic action addressed in terms of voluntary and rather imposed decision. However, on the macro level, findings allow suggesting that such opportunities are rather an outcome embedded in the peculiarities of academia and its historical and structural developments. This, in turn, contributes significantly to emergence of a scene in which migration action takes place. The paper suggest further comparative research on the intersection of the macro and micro level, and in particular how both national academic institutions and the EU mobility principle shape migration of academics. In light of continuous attempts to make the European labour market more mobile and attractive such findings ought to have direct implications on policy.

Keywords: migration, EU, academics, highly skilled labour

Procedia PDF Downloads 257

Authors: Zhao Gao, Eran Edirisinghe

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The production of an accurate sketch of a suspect based on a verbal description obtained from a witness is an essential task for most criminal investigations. The criminal investigation system employs specifically trained professional artists to manually draw a facial image of the suspect according to the descriptions of an eyewitness for subsequent identification. Within the advancement of Deep Learning, Recurrent Neural Networks (RNN) have shown great promise in Natural Language Processing (NLP) tasks. Additionally, Generative Adversarial Networks (GAN) have also proven to be very effective in image generation. In this study, a trained GAN conditioned on textual features such as keywords automatically encoded from a verbal description of a human face using an RNN is used to generate photo-realistic facial images for criminal investigations. The intention of the proposed system is to map corresponding features into text generated from verbal descriptions. With this, it becomes possible to generate many reasonably accurate alternatives to which the witness can use to hopefully identify a suspect from. This reduces subjectivity in decision making both by the eyewitness and the artist while giving an opportunity for the witness to evaluate and reconsider decisions. Furthermore, the proposed approach benefits law enforcement agencies by reducing the time taken to physically draw each potential sketch, thus increasing response times and mitigating potentially malicious human intervention. With publically available 'CelebFaces Attributes Dataset' (CelebA) and additionally providing verbal description as training data, the proposed architecture is able to effectively produce facial structures from given text. Word Embeddings are learnt by applying the RNN architecture in order to perform semantic parsing, the output of which is fed into the GAN for synthesizing photo-realistic images. Rather than the grid search method, a metaheuristic search based on genetic algorithms is applied to evolve the network with the intent of achieving optimal hyperparameters in a fraction the time of a typical brute force approach. With the exception of the ‘CelebA’ training database, further novel test cases are supplied to the network for evaluation. Witness reports detailing criminals from Interpol or other law enforcement agencies are sampled on the network. Using the descriptions provided, samples are generated and compared with the ground truth images of a criminal in order to calculate the similarities. Two factors are used for performance evaluation: The Structural Similarity Index (SSIM) and the Peak Signal-to-Noise Ratio (PSNR). A high percentile output from this performance matrix should attribute to demonstrating the accuracy, in hope of proving that the proposed approach can be an effective tool for law enforcement agencies. The proposed approach to criminal facial image generation has potential to increase the ratio of criminal cases that can be ultimately resolved using eyewitness information gathering.

Keywords: RNN, GAN, NLP, facial composition, criminal investigation

Procedia PDF Downloads 164

Authors: Eda Ozkara San

Abstract:

Nurse educators have been charged by several nursing organizations and accrediting bodies to provide innovative and evidence-based educational experiences, both didactic and clinical, to help students to develop the knowledge, skills, and attitudes needed to provide culturally competent nursing care to patients. Clinical simulation, which offers the opportunity for students to practice nursing skills in a risk-free, controlled environment and helps develop self-efficacy (confidence) within the nursing role. As one simulation method, the standardized patients (SPs) simulation helps educators to teach nursing students variety of skills in nursing, medicine, and other health professions. It can be a helpful tool for nurse educators to enhance cultural competence of nursing students. An alarming gap exists within the literature concerning the effectiveness of SP strategy to enhance cultural competence development of diverse student groups, who must work with patients from various backgrounds. This grant-supported, longitudinal, one-group, pretest and post-test educational intervention study aimed to examine the effect of the Diverse Standardized Patient Simulation (DSPS) cultural competence education strategy on students’ (n = 53) transcultural self-efficacy (TSE). The researcher-developed multidimensional DSPS strategy involved careful integration of transcultural nursing skills guided by the Cultural Competence and Confidence (CCC) model. As a carefully orchestrated teaching and learning strategy by specifically utilizing the SP pedagogy, the DSPS also followed international guidelines and standards for the design, implementation, evaluation, and SP training; and had content validity review. The DSPS strategy involved two simulation scenarios targeting underrepresented patient populations (Muslim immigrant woman with limited English proficiency and Irish-Italian American gay man with his partner (Puerto Rican) to be utilized in a second-semester, nine-credit, 15-week medical-surgical nursing course at an urban public US university. Five doctorally prepared content experts reviewed the DSPS strategy for content validity. The item-level content validity index (I-CVI) score was calculated between .80-1.0 on the evaluation forms. Jeffreys’ Transcultural Self-Efficacy Tool (TSET) was administered as a pretest and post-test to assess students’ changes in cognitive, practical, and affective dimensions of TSE. Results gained from this study support that the DSPS cultural competence education strategy assisted students to develop cultural competence and caused statistically significant changes (increase) in students’ TSE perceptions. Results also supported that all students, regardless of their background, benefit (and require) well designed cultural competence education strategies. The multidimensional DSPS strategy is found to be an effective way to foster nursing students’ cultural competence development. Step-by-step description of the DSPS provides an easy adaptation of this strategy with different student populations and settings.

Keywords: cultural competence development, the cultural competence and confidence model, CCC model, educational intervention, transcultural self-efficacy, TSE, transcultural self-efficacy tool, TSET

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Authors: Sonia A. Stoica, Lexi Frankel, Amalia Ardeljan, Selena Rashid, Ali Yasback, Omar Rashid

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Introduction Enterococcus is a vast genus of lactic acid bacteria, gram-positivecocci species. They are common commensal organisms in the intestines of humans: E. faecalis (90–95%) and E. faecium (5–10%). Rare groups of infections can occur with other species, including E. casseliflavus, E. gallinarum, and E. raffinosus. The most common infections caused by Enterococcus include urinary tract infections, biliary tract infections, subacute endocarditis, diverticulitis, meningitis, septicemia, and spontaneous bacterial peritonitis. The treatment for sensitive strains of these bacteria includes ampicillin, penicillin, cephalosporins, or vancomycin, while the treatment for resistant strains includes daptomycin, linezolid, tygecycline, or streptogramine. Enterococcus faecalis CECT7121 is an encouraging nominee for being considered as a probiotic strain. E. faecalis CECT7121 enhances and skews the profile of cytokines to the Th1 phenotype in situations such as vaccination, anti-tumoral immunity, and allergic reactions. It also enhances the secretion of high levels of IL-12, IL-6, TNF alpha, and IL-10. Cytokines have been previously associated with the development of cancer. The intention of this study was to therefore evaluate the correlation between Enterococcus infections and incidence of bone carcinoma. Methods A retrospective cohort study (2010-2019) was conducted through a Health Insurance Portability and Accountability Act (HIPAA) compliant national database and conducted using International Classification of Disease (ICD) 9th and 10th codes for bone carcinoma diagnosis in a previously Enterococcus infected population. Patients were matched for age range and Charlson Comorbidity Index (CCI). Access to the database was granted by Holy Cross Health for academic research. Chi-squared test was used to assess statistical significance. Results A total number of 17,056 patients was obtained in Enterococcus infected group as well as in the control population (matched by Age range and CCI score). Subsequent bone carcinoma development was seen at a rate of 1.07% (184) in the Enterococcal infectious group and 3.42% (584) in the control group, respectively. The difference was statistically significant by p= 2.2x10-¹⁶, Odds Ratio = 0.355 (95% CI 0.311 - 0.404) Treatment for enterococcus infection was analyzed and controlled for in both enterococcus infected and noninfected populations. 78 out of 6,624 (1.17%) patients with a prior enterococcus infection and treated with antibiotics were compared to 202 out of 6,624 (3.04%) patients with no history of enterococcus infection (control) and received antibiotic treatment. Both populations subsequently developed bone carcinoma. Results remained statistically significant (p<2.2x10-), Odds Ratio=0.456 (95% CI 0.396-0.525). Conclusion This study shows a statistically significant correlation between Enterococcus infection and a decreased incidence of bone carcinoma. The immunologic response of the organism to Enterococcus infection may exert a protecting mechanism from developing bone carcinoma. Further exploration is needed to identify the potential mechanism of Enterococcus in reducing bone carcinoma incidence.

Keywords: anti-tumoral immunity, bone carcinoma, enterococcus, immunologic response

Procedia PDF Downloads 181

Authors: Zenaida Chitu, Roxana Bojariu, Liliana Velea, Roxana Burcea

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A number of studies show that extreme air temperature affects mortality related to cardiovascular diseases, particularly among elderly people. In Romania, the summer thermal discomfort expressed by Universal Thermal Climate Index (UTCI) is highest in the Southern part of the country, where Bucharest, the largest Romanian urban agglomeration, is also located. The urban characteristics such as high building density and reduced green areas enhance the increase of the air temperature during summer. In Bucharest, as in many other large cities, the effect of heat urban island is present and determines an increase of air temperature compared to surrounding areas. This increase is particularly important during heat wave periods in summer. In this context, the researchers performed a temperature-mortality analysis based on daily deaths related to cardiovascular diseases, recorded between 2010 and 2019 in Bucharest. The temperature-mortality relationship was modeled by applying distributed lag non-linear model (DLNM) that includes a bi-dimensional cross-basis function and flexible natural cubic spline functions with three internal knots in the 10th, 75th and 90th percentiles of the temperature distribution, for modelling both exposure-response and lagged-response dimensions. Firstly, this study applied this analysis for the present climate. Extrapolation of the exposure-response associations beyond the observed data allowed us to estimate future effects on mortality due to temperature changes under climate change scenarios and specific assumptions. We used future projections of air temperature from five numerical experiments with regional climate models included in the EURO-CORDEX initiative under the relatively moderate (RCP 4.5) and pessimistic (RCP 8.5) concentration scenarios. The results of this analysis show for RCP 8.5 an ensemble-averaged increase with 6.1% of heat-attributable mortality fraction in future in comparison with present climate (2090-2100 vs. 2010-219), corresponding to an increase of 640 deaths/year, while mortality fraction due to the cold conditions will be reduced by 2.76%, corresponding to a decrease by 288 deaths/year. When mortality data is stratified according to the age, the ensemble-averaged increase of heat-attributable mortality fraction for elderly people (> 75 years) in the future is even higher (6.5 %). These findings reveal the necessity to carefully plan urban development in Bucharest to face the public health challenges raised by the climate change. Paper Details: This work is financed by the project URCLIM which is part of ERA4CS, an ERA-NET initiated by JPI Climate, and funded by Ministry of Environment, Romania with co-funding by the European Union (Grant 690462). A part of this work performed by one of the authors has received funding from the European Union’s Horizon 2020 research and innovation programme from the project EXHAUSTION under grant agreement No 820655.

Keywords: cardiovascular diseases, climate change, extreme air temperature, mortality

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Authors: Riadh Zorgati, Thomas Triboulet

Abstract:

In quite diverse application areas such as astronomy, medical imaging, geophysics or nondestructive evaluation, many problems related to calibration, fitting or estimation of a large number of input parameters of a model from a small amount of output noisy data, can be cast as inverse problems. Due to noisy data corruption, insufficient data and model errors, most inverse problems are ill-posed in a Hadamard sense, i.e. existence, uniqueness and stability of the solution are not guaranteed. A wide class of inverse problems in physics relates to the Fredholm equation of the first kind. The ill-posedness of such inverse problem results, after discretization, in a very ill-conditioned linear system of equations, the condition number of the associated matrix can typically range from 109 to 1018. This condition number plays the role of an amplifier of uncertainties on data during inversion and then, renders the inverse problem difficult to handle numerically. Similar problems appear in other areas such as numerical optimization when using interior points algorithms for solving linear programs leads to face ill-conditioned systems of linear equations. Devising efficient solution approaches for such system of equations is therefore of great practical interest. Efficient iterative algorithms are proposed for solving a system of linear equations. The approach is based on a preconditioning of the initial matrix of the system with an approximation of a generalized inverse leading to a stochastic preconditioned matrix. This approach, valid for non-negative matrices, is first extended to hermitian, semi-definite positive matrices and then generalized to any complex rectangular matrices. The main results obtained are as follows: 1) We are able to build a generalized inverse of any complex rectangular matrix which satisfies the convergence condition requested in iterative algorithms for solving a system of linear equations. This completes the (short) list of generalized inverse having this property, after Kaczmarz and Cimmino matrices. Theoretical results on both the characterization of the type of generalized inverse obtained and the convergence are derived. 2) Thanks to its properties, this matrix can be efficiently used in different solving schemes as Richardson-Tanabe or preconditioned conjugate gradients. 3) By using Lp norms, we propose generalized Kaczmarz’s type matrices. We also show how Cimmino's matrix can be considered as a particular case consisting in choosing the Euclidian norm in an asymmetrical structure. 4) Regarding numerical results obtained on some pathological well-known test-cases (Hilbert, Nakasaka, …), some of the proposed algorithms are empirically shown to be more efficient on ill-conditioned problems and more robust to error propagation than the known classical techniques we have tested (Gauss, Moore-Penrose inverse, minimum residue, conjugate gradients, Kaczmarz, Cimmino). We end on a very early prospective application of our approach based on stochastic matrices aiming at computing some parameters (such as the extreme values, the mean, the variance, …) of the solution of a linear system prior to its resolution. Such an approach, if it were to be efficient, would be a source of information on the solution of a system of linear equations.

Keywords: conditioning, generalized inverse, linear system, norms, stochastic matrix

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Authors: Ana L. M. Pavan, Guilherme Giacomini, Allan F. F. Alves, Marcela De Oliveira, Fernando A. B. Neto, Maria E. D. Rosa, Andre P. Trindade, Diana R. De Pina

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Mammography is a worldwide image modality used to diagnose breast cancer, even in asymptomatic women. Due to its large availability, mammograms can be used to measure breast density and to predict cancer development. Women with increased mammographic density have a four- to sixfold increase in their risk of developing breast cancer. Therefore, studies have been made to accurately quantify mammographic breast density. In clinical routine, radiologists perform image evaluations through BIRADS (Breast Imaging Reporting and Data System) assessment. However, this method has inter and intraindividual variability. An automatic objective method to measure breast density could relieve radiologist’s workload by providing a first aid opinion. However, pectoral muscle is a high density tissue, with similar characteristics of fibroglandular tissues. It is consequently hard to automatically quantify mammographic breast density. Therefore, a pre-processing is needed to segment the pectoral muscle which may erroneously be quantified as fibroglandular tissue. The aim of this work was to develop an automatic algorithm to segment and extract pectoral muscle in digital mammograms. The database consisted of thirty medio-lateral oblique incidence digital mammography from São Paulo Medical School. This study was developed with ethical approval from the authors’ institutions and national review panels under protocol number 3720-2010. An algorithm was developed, in Matlab® platform, for the pre-processing of images. The algorithm uses image processing tools to automatically segment and extract the pectoral muscle of mammograms. Firstly, it was applied thresholding technique to remove non-biological information from image. Then, the Hough transform is applied, to find the limit of the pectoral muscle, followed by active contour method. Seed of active contour is applied in the limit of pectoral muscle found by Hough transform. An experienced radiologist also manually performed the pectoral muscle segmentation. Both methods, manual and automatic, were compared using the Jaccard index and Bland-Altman statistics. The comparison between manual and the developed automatic method presented a Jaccard similarity coefficient greater than 90% for all analyzed images, showing the efficiency and accuracy of segmentation of the proposed method. The Bland-Altman statistics compared both methods in relation to area (mm²) of segmented pectoral muscle. The statistic showed data within the 95% confidence interval, enhancing the accuracy of segmentation compared to the manual method. Thus, the method proved to be accurate and robust, segmenting rapidly and freely from intra and inter-observer variability. It is concluded that the proposed method may be used reliably to segment pectoral muscle in digital mammography in clinical routine. The segmentation of the pectoral muscle is very important for further quantifications of fibroglandular tissue volume present in the breast.

Keywords: active contour, fibroglandular tissue, hough transform, pectoral muscle

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Authors: Zihan Geng, L. Quentin Dixon

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It has been proposed that early bilingual experience confers a number of advantages in the development of executive control mechanisms. Although the literature provides empirical evidence for bilingual benefits, some studies also reported null or mixed results. To make sense of these contradictory findings, the current review synthesize recent empirical studies investigating bilingual effects on children’s executive function and attention control. The publication time of the studies included in the review ranges from 2010 to 2017. The key searching terms are bilingual, bilingualism, children, executive control, executive function, and attention. The key terms were combined within each of the following databases: ERIC (EBSCO), Education Source, PsycINFO, and Social Science Citation Index. Studies involving both children and adults were also included but the analysis was based on the data generated only by the children group. The initial search yielded 137 distinct articles. Twenty-eight studies from 27 articles with a total of 3367 participants were finally included based on the selection criteria. The selective studies were then coded in terms of (a) the setting (i.e., the country where the data was collected), (b) the participants (i.e., age and languages), (c) sample size (i.e., the number of children in each group), (d) cognitive outcomes measured, (e) data collection instruments (i.e., cognitive tasks and tests), and (f) statistic analysis models (e.g., t-test, ANOVA). The results show that the majority of the studies were undertaken in western countries, mainly in the U.S., Canada, and the UK. A variety of languages such as Arabic, French, Dutch, Welsh, German, Spanish, Korean, and Cantonese were involved. In relation to cognitive outcomes, the studies examined children’s overall planning and problem-solving abilities, inhibition, cognitive complexity, working memory (WM), and sustained and selective attention. The results indicate that though bilingualism is associated with several cognitive benefits, the advantages seem to be weak, at least, for children. Additionally, the nature of the cognitive measures was found to greatly moderate the results. No significant differences are observed between bilinguals and monolinguals in overall planning and problem-solving ability, indicating that there is no bilingual benefit in the cooperation of executive function components at an early age. In terms of inhibition, the mixed results suggest that bilingual children, especially young children, may have better conceptual inhibition measured in conflict tasks, but not better response inhibition measured by delay tasks. Further, bilingual children showed better inhibitory control to bivalent displays, which resembles the process of maintaining two language systems. The null results were obtained for both cognitive complexity and WM, suggesting no bilingual advantage in these two cognitive components. Finally, findings on children’s attention system associate bilingualism with heightened attention control. Together, these findings support the hypothesis of cognitive benefits for bilingual children. Nevertheless, whether these advantages are observable appears to highly depend on the cognitive assessments. Therefore, future research should be more specific about the cognitive outcomes (e.g., the type of inhibition) and should report the validity of the cognitive measures consistently.

Keywords: attention, bilingual advantage, children, executive function

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Authors: Alberto Veses, Olga Sanhauja, María Soledad Callén, Tomás García

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The appropriate use of renewable sources emerges as a decisive point to minimize the environmental impact caused by fossil fuels use. Particularly, the use of lignocellulosic biomass becomes one of the best promising alternatives since it is the only carbon-containing renewable source that can produce bioproducts similar to fossil fuels and it does not compete with food market. Among all the processes that can valorize lignocellulosic biomass, pyrolysis is an attractive alternative because it is the only thermochemical process that can produce a liquid biofuel (bio-oil) in a simple way and solid and gas fractions that can be used as energy sources to support the process. However, in order to incorporate bio-oils in current infrastructures and further process in future biorefineries, their quality needs to be improved. Introducing different low-cost catalysts and/or incorporating different polymer residues to the process are some of the new, simple and low-cost strategies that allow the user to directly obtain advanced bio-oils to be used in future biorefineries in an economic way. In this manner, from previous thermogravimetric analyses, local agricultural wastes such as grape seeds (GS) were selected as lignocellulosic biomass while, waste tires (WT) were selected as polymer residue. On the other hand, CaO was selected as low-cost catalyst based on previous experiences by the group. To reach this aim, a specially-designed fixed bed reactor using N₂ as a carrier gas was used. This reactor has the peculiarity to incorporate a vertical mobile liner that allows the user to introduce the feedstock in the oven once the selected temperature (550 ºC) is reached, ensuring higher heating rates needed for the process. Obtaining a well-defined phase distribution in the resulting bio-oil is crucial to ensure the viability to the process. Thus, once experiments were carried out, not only a well-defined two layers was observed introducing several mixtures (reaching values up to 40 wt.% of WT) but also, an upgraded organic phase, which is the one considered to be processed in further biorefineries. Radical interactions between GS and WT released during the pyrolysis process and dehydration reactions enhanced by CaO can promote the formation of better-quality bio-oils. The latter was reflected in a reduction of water and oxygen content of bio-oil and hence, a substantial increase of its heating value and its stability. Moreover, not only sulphur content was reduced from solely WT pyrolysis but also potential and negative issues related to a strong acidic environment of conventional bio-oils were minimized due to its basic pH and lower total acid numbers. Therefore, acidic compounds obtained in the pyrolysis such as CO₂-like substances can react with the CaO and minimize acidic problems related to lignocellulosic bio-oils. Moreover, this CO₂ capture promotes H₂ production from water gas shift reaction favoring hydrogen-transfer reactions, improving the final quality of the bio-oil. These results show the great potential of grapes seeds to carry out the catalytic co-pyrolysis process with different plastic residues in order to produce a liquid bio-oil that can be considered as a high-quality renewable vector.

Keywords: advanced bio-oils, biorefinery, catalytic co-pyrolysis of biomass and waste tires, lignocellulosic biomass

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Authors: M. E. Semenov, U. Zh. Mirzakimov, A. S. Stoporev, R. S. Pavelev, M. A. Varfolomeev

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Gas hydrates are host-guest compounds. Guest molecules can be low molecular weight components of associated petroleum gas (C1-C4 hydrocarbons), carbon dioxide, hydrogen sulfide, nitrogen. Gas hydrates have a number of unique properties that make them interesting from a technological point of view, for example, for storing hydrocarbon gases in solid form under moderate thermobaric conditions. Currently, the possibility of storing and transporting hydrocarbon gases in the form of solid hydrate is being actively explored throughout the world. The hydrate form of gas has a number of advantages, including a significant gas content in the hydrate, relative safety and environmental friendliness of the process. Recently, new developments have been proposed that seek to reduce the number of steps to obtain the finished hydrate, for example, using a pressing device/screw inside the reactor. However, the energy consumption required for the hydrate formation process remains a challenge. Thus, the goal of the current work is to study the patterns and mechanisms of the hydrate formation process using small additions of hydrate formation promoters under static conditions. The study of these aspects will help solve the problem of accelerated production of gas hydrates with minimal energy consumption. New compounds have been developed at Kazan Federal University that can accelerate the formation of methane hydrate with a small amount of promoter in water, not exceeding 0.1% by weight. These promoters were synthesized based on available natural compounds and showed high efficiency in accelerating the growth of methane hydrate. To test the influence of promoters on the process of hydrate formation, standard experiments are carried out under dynamic conditions with stirring. During such experiments, the time at which hydrate formation begins (induction period), the temperature at which formation begins (supercooling), the rate of hydrate formation, and the degree of conversion of water to hydrate are assessed. This approach helps to determine the most effective compound in comparative experiments with different promoters and select their optimal concentration. These experimental studies made it possible to study the features of the formation of associated petroleum gas hydrate from promoter solutions under static conditions. Phase transformations were studied using high-pressure micro-differential scanning calorimetry under various experimental conditions. Visual studies of the growth mode of methane hydrate depending on the type of promoter were also carried out. The work is an extension of the methodology for studying the effect of promoters on the process of associated petroleum gas hydrate formation in order to identify new ways to accelerate the formation of gas hydrates without the use of mixing. This work presents the results of a study of the process of associated petroleum gas hydrate formation using high-pressure differential scanning micro-calorimetry, visual investigation, gas chromatography, autoclave study, and stability data. It was found that the synthesized compounds multiply the conversion of water into hydrate under static conditions up to 96% due to a change in the growth mechanism of associated petroleum gas hydrate. This work was carried out in the framework of the program Priority-2030.

Keywords: gas hydrate, gas storage, promotor, associated petroleum gas

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Authors: Wanchalerm Patanacharoenwong, Panaya Sudta, Prachya Bumrungkun

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The paper focuses on the development of a system that combines Internet of Things (IoT) technologies and deep learning algorithms for anomaly detection in residential Electric Vehicle (EV) charging in smart cities. With the increasing number of EVs, ensuring efficient and reliable charging systems has become crucial. The aim of this research is to develop an integrated IoT and deep learning system for detecting anomalies in residential EV charging and enhancing EV load profiling and event detection in smart cities. This approach utilizes IoT devices equipped with infrared cameras to collect thermal images and household EV charging profiles from the database of Thailand utility, subsequently transmitting this data to a cloud database for comprehensive analysis. The methodology includes the use of advanced deep learning techniques such as Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM) algorithms. IoT devices equipped with infrared cameras are used to collect thermal images and EV charging profiles. The data is transmitted to a cloud database for comprehensive analysis. The researchers also utilize feature-based Gaussian mixture models for EV load profiling and event detection. Moreover, the research findings demonstrate the effectiveness of the developed system in detecting anomalies and critical profiles in EV charging behavior. The system provides timely alarms to users regarding potential issues and categorizes the severity of detected problems based on a health index for each charging device. The system also outperforms existing models in event detection accuracy. This research contributes to the field by showcasing the potential of integrating IoT and deep learning techniques in managing residential EV charging in smart cities. The system ensures operational safety and efficiency while also promoting sustainable energy management. The data is collected using IoT devices equipped with infrared cameras and is stored in a cloud database for analysis. The collected data is then analyzed using RNN, LSTM, and feature-based Gaussian mixture models. The approach includes both EV load profiling and event detection, utilizing a feature-based Gaussian mixture model. This comprehensive method aids in identifying unique power consumption patterns among EV owners and outperforms existing models in event detection accuracy. In summary, the research concludes that integrating IoT and deep learning techniques can effectively detect anomalies in residential EV charging and enhance EV load profiling and event detection accuracy. The developed system ensures operational safety and efficiency, contributing to sustainable energy management in smart cities.

Keywords: cloud computing framework, recurrent neural networks, long short-term memory, Iot, EV charging, smart grids

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Authors: Wendy De Gomez

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The University of Waterloo is situated in central Canada in the Province of Ontario- one hour from the metropolitan city of Toronto. For over 30 years, it has held Canada’s top spot as the most innovative university; and has been consistently ranked in the top 25 computer science and top 50 engineering schools in the world. Waterloo benefits from the federal government’s over 100 domestic innovation policies which have assisted in the country’s 15th place global ranking in the World Intellectual Property Organization’s (WIPO) 2022 Global Innovation Index. Yet undoubtedly, the University of Waterloo’s unique characteristics are what propels its innovative creativeness forward. This paper will provide a contextual definition of innovation in higher education and then demonstrate the five operational attributes that contribute to the University of Waterloo’s innovative reputation. The methodology is based on statistical analyses obtained from ranking bodies such as the QS World University Rankings, a secondary literature review related to higher education innovation in Canada, and case studies that exhibit the operationalization of the attributes outlined below. The first attribute is geography. Specifically, the paper investigates the network structure effect of the Toronto-Waterloo high-tech corridor and the resultant industrial relationships built there. The second attribute is University Policy 73-Intellectal Property Rights. This creator-owned policy grants all ownership to the creator/inventor regardless of the use of the University of Waterloo property or funding. Essentially, through the incentivization of IP ownership by all researchers, further commercialization and entrepreneurship are formed. Third, this IP policy works hand in hand with world-renowned business incubators such as the Accelerator Centre in the dedicated research and technology park and velocity, a 14-year-old facility that equips and guides founders to build and scale companies. Communitech, a 25-year-old provincially backed facility in the region, also works closely with the University of Waterloo to build strong teams, access capital, and commercialize products. Fourth, Waterloo’s co-operative education program contributes 31% of all co-op participants to the Canadian economy. Home to the world’s largest co-operative education program, data shows that over 7,000 from around the world recruit Waterloo students for short- and long-term placements- directly contributing to the student’s ability to learn and optimize essential employment skills when they graduate. Finally, the students themselves at Waterloo are exceptional. The entrance average ranges from the low 80s to the mid-90s depending on the program. In computer, electrical, mechanical, mechatronics, and systems design engineering, to have a 66% chance of acceptance, the applicant’s average must be 95% or above. Singularly, none of these five attributes could lead to the university’s outstanding track record of innovative creativity, but when bundled up into a 1000 acre- 100 building main campus with 6 academic faculties, 40,000+ students, and over 1300 world-class faculty, the recipe for success becomes quite evident.

Keywords: IP policy, higher education, economy, innovation

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