Search results for: subfilter scale modeling
Commenced in January 2007
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Edition: International
Paper Count: 9310

Search results for: subfilter scale modeling

340 Microbiological and Physicochemical Evaluation of Traditional Greek Kopanisti Cheese Produced by Different Starter Cultures

Authors: M. Kazou, A. Gavriil, O. Kalagkatsi, T. Paschos, E. Tsakalidou

Abstract:

Kopanisti cheese is a Greek soft Protected Designation of Origin (PDO) cheese made of raw cow, sheep or goat milk, or mixtures of them, with similar organoleptic characteristics to that of Roquefort cheese. Traditional manufacturing of Kopanisti cheese is limited in small-scale dairies, without the addition of starter cultures. Instead, an amount of over-mature Kopanisti cheese, called Mana Kopanisti, is used to initiate ripening. Therefore, the selection of proper starter cultures and the understanding of the contribution of various microbial groups to its overall quality is crucial for the production of a high-quality final product with standardized organoleptic and physicochemical characteristics. Taking the above into account, the aim of the present study was the investigation of Kopanisti cheese microbiota and its role in cheese quality. For this purpose, four different types of Kopanisti were produced in triplicates, all with pasteurized cow milk, with the addition of (A) the typical mesophilic species Lactococcus lactis and Lactobacillus paracasei used as starters in the production of soft spread cheeses, (B) strains of Lactobacillus acidipiscis and Lactobacillus rennini previously isolated from Kopanisti and Mana Kopanisti, (C) all the species from (A) and (B) as inoculum, and finally (D) the species from (A) and Mana Kopanisti. Physicochemical and microbiological analysis was performed for milk and cheese samples during ripening. Enumeration was performed for major groups of lactic acid bacteria (LAB), total mesophilic bacteria, yeasts as well as hygiene indicator microorganisms. Bacterial isolates from all the different LAB groups, apart from enterococci, alongside yeasts isolates, were initially grouped using repetitive sequence-based polymerase chain reaction (rep-PCR) and then identified at the species level using 16S rRNA gene and internal transcribed spacer (ITS) DNA region sequencing, respectively. Sensory evaluation was also performed for final cheese samples at the end of the ripening period (35 days). Based on the results of the classical microbiological analysis, the average counts of the total mesophilic bacteria and LAB, apart from enterococci, ranged between 7 and 10 log colony forming unit (CFU) g⁻¹, phychrotrophic bacteria, and yeast extract glucose chloramphenicol (YGC) isolates between 4 and 8 log CFU g⁻¹, while coliforms and enterococci up to 2 log CFU g⁻¹ throughout ripening in cheese samples A, C and D. In contrast, in cheese sample B, the average counts of the total mesophilic bacteria and LAB, apart from enterococci, phychrotrophic bacteria, and YGC isolates ranged between 0 and 10 log CFU g⁻¹ and coliforms and enterococci up to 2 log CFU g⁻¹. Although the microbial counts were not that different among samples, identification of the bacterial and yeasts isolates revealed the complex microbial community structure present in each cheese sample. Differences in the physicochemical characteristics among the cheese samples were also observed, with pH ranging from 4.3 to 5.3 and moisture from 49.6 to 58.0 % in the final cheese products. Interestingly, the sensory evaluation also revealed differences among samples, with cheese sample B ranking first based on the total score. Overall, the combination of these analyses highlighted the impact of different starter cultures on the Kopanisti microbiota as well as on the physicochemical and sensory characteristics of the final product.

Keywords: Kopanisti cheese, microbiota, classical microbiological analysis, physicochemical analysis

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339 Fermented Fruit and Vegetable Discard as a Source of Feeding Ingredients and Functional Additives

Authors: Jone Ibarruri, Mikel Manso, Marta Cebrián

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A high amount of food is lost or discarded in the World every year. In addition, in the last decades, an increasing demand of new alternative and sustainable sources of proteins and other valuable compounds is being observed in the food and feeding sectors and, therefore, the use of food by-products as nutrients for these purposes sounds very interesting from the environmental and economical point of view. However, the direct use of discarded fruit and vegetables that present, in general, a low protein content is not interesting as feeding ingredient except if they are used as a source of fiber for ruminants. Especially in the case of aquaculture, several alternatives to the use of fish meal and other vegetable protein sources have been extensively explored due to the scarcity of fish stocks and the unsustainability of fishing for these purposes. Fish mortality is also of great concern in this sector as this problem highly reduces their economic feasibility. So, the development of new functional and natural ingredients that could reduce the need for vaccination is also of great interest. In this work, several fermentation tests were developed at lab scale using a selected mixture of fruit and vegetable discards from a wholesale market located in the Basque Country to increase their protein content and also to produce some bioactive extracts that could be used as additives in aquaculture. Fruit and vegetable mixtures (60/40 ww) were centrifugated for humidity reduction and crushed to 2-5 mm particle size. Samples were inoculated with a selected Rhizopus oryzae strain and fermented for 7 days in controlled conditions (humidity between 65 and 75% and 28ºC) in Petri plates (120 mm) by triplicate. Obtained results indicated that the final fermented product presented a twofold protein content (from 13 to 28% d.w). Fermented product was further processed to determine their possible functionality as a feed additive. Extraction tests were carried out to obtain an ethanolic extract (60:40 ethanol: water, v.v) and remaining biomass that also could present applications in food or feed sectors. The extract presented a polyphenol content of about 27 mg GAE/gr d.w with antioxidant activity of 8.4 mg TEAC/g d.w. Remining biomass is mainly composed of fiber (51%), protein (24%) and fat (10%). Extracts also presented antibacterial activity according to the results obtained in Agar Diffusion and to the Minimum Inhibitory Concentration (MIC) tests determined against several food and fish pathogen strains. In vitro, digestibility was also assessed to obtain preliminary information about the expected effect of extraction procedure on fermented product digestibility. First results indicated that remaining biomass after extraction doesn´t seem to improve digestibility in comparison to the initial fermented product. These preliminary results show that fermented fruit and vegetables can be a useful source of functional ingredients for aquaculture applications and a substitute of other protein sources in the feeding sector. Further validation will be also carried out through “in vivo” tests with trout and bass.

Keywords: fungal solid state fermentation, protein increase, functional extracts, feed ingredients

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338 Destructive and Nondestructive Characterization of Advanced High Strength Steels DP1000/1200

Authors: Carla M. Machado, André A. Silva, Armando Bastos, Telmo G. Santos, J. Pamies Teixeira

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Advanced high-strength steels (AHSS) are increasingly being used in automotive components. The use of AHSS sheets plays an important role in reducing weight, as well as increasing the resistance to impact in vehicle components. However, the large-scale use of these sheets becomes more difficult due to the limitations during the forming process. Such limitations are due to the elastically driven change of shape of a metal sheet during unloading and following forming, known as the springback effect. As the magnitude of the springback tends to increase with the strength of the material, it is among the most worrisome problems in the use of AHSS steels. The prediction of strain hardening, especially under non-proportional loading conditions, is very limited due to the lack of constitutive models and mainly due to very limited experimental tests. It is very clear from the literature that in experimental terms there is not much work to evaluate deformation behavior under real conditions, which implies a very limited and scarce development of mathematical models for these conditions. The Bauschinger effect is also fundamental to the difference between kinematic and isotropic hardening models used to predict springback in sheet metal forming. It is of major importance to deepen the phenomenological knowledge of the mechanical and microstructural behavior of the materials, in order to be able to reproduce with high fidelity the behavior of extension of the materials by means of computational simulation. For this, a multi phenomenological analysis and characterization are necessary to understand the various aspects involved in plastic deformation, namely the stress-strain relations and also the variations of electrical conductivity and magnetic permeability associated with the metallurgical changes due to plastic deformation. Aiming a complete mechanical-microstructural characterization, uniaxial tensile tests involving successive cycles of loading and unloading were performed, as well as biaxial tests such as the Erichsen test. Also, nondestructive evaluation comprising eddy currents to verify microstructural changes due to plastic deformation and ultrasonic tests to evaluate the local variations of thickness were made. The material parameters for the stable yield function and the monotonic strain hardening were obtained using uniaxial tension tests in different material directions and balanced biaxial tests. Both the decrease of the modulus of elasticity and Bauschinger effect were determined through the load-unload tensile tests. By means of the eddy currents tests, it was possible to verify changes in the magnetic permeability of the material according to the different plastically deformed areas. The ultrasonic tests were an important aid to quantify the local plastic extension. With these data, it is possible to parameterize the different models of kinematic hardening to better approximate the results obtained by simulation with the experimental results, which are fundamental for the springback prediction of the stamped parts.

Keywords: advanced high strength steel, Bauschinger effect, sheet metal forming, springback

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337 Effects of an Online Positive Psychology Program on Stress, Depression, and Anxiety Symptoms of Emerging Adults

Authors: Gabriela R. Silveira, Claudia S. Rocha, Lais S. Vitti, Jeane L. Borges, Helen B. Durgante

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Emerging adulthood occurs after adolescence in a period that maybe be marked by experimentation, identity reconfigurations, labor life demands, and insertion in the work environment, which tends to generate stress and emotional instability. Health promotion programs for the development of strengths and virtues, based on Positive Psychology, for emerging adults are sparse in Brazil. The aim of this study was to evaluate the preliminary effects of an online multi-component Positive Psychology program for the health promotion of emerging adults based on Cognitive Behavioural Therapy and Positive Psychology. The program included six online (synchronous) weekly group sessions of approximately two hours each and homework (asynchronous) activities. The themes worked were Values and self-care/Prudence, Optimism, Empathy, Gratitude, Forgiveness, and Meaning of life and work. This study presents data from a longitudinal, pre-experimental design with pre (T1) and post-test (T2) evaluation in the intervention group. 47 individuals aged between 19-30 years old participated, mean age of 24.53 years (SD=3.13), 37 females (78.7%). 42 (89.4%) self-defined as heterosexual, four (8.5%) as homosexual, and one (2.5%) as bisexual. 33 (70.2%) had incomplete higher education, four (8.5%) completed higher education, and seven (14.9%) had a graduate level of education. 27 participants worked (57.4%), out of which 25 were health workers (53.2%). 14 (29.8%) were caregivers, 27 (57.4%) had a spiritual belief, 36 (76.6%) had access to leisure, and 38 (80.9%) had perceived social support. The instruments used were a sociodemographic questionnaire, the 10-item Perceived Stress Scale, and the 12-item General Health Questionnaire. The program was advertised on social networks and interested participants filled out the Consent Form and the evaluation protocol at T1 and T2 via Google Docs form. The main research was approved (CEP n.1,899,368; 4,143,219; CAAE: 61997516.5.0000.5334) and complied with sanitary and Ethics criteria in research with human beings. Wilcoxon statistics revealed significant improvements in indicators of perceived stress between T1 (X=22.21, SD=6.79) and T2 (X=15.10, SD=5.82); (Z=-4.353; p=0.001) as well as depression and anxiety symptoms (T1:X=26.72, SD=8.84; T2: X=19.23, SD=4.68); (Z=-3.945, p=0.001) of the emerging adults after their participation in the programme. The programme has an innovative character not only for presenting an online Positive Psychology approach but also for being based on an intervention developed, evaluated, and manualized in Brazil. By focusing on emerging adults, this study contributes to advancing research on a relatively new field in developmental studies. As a limitation, this is a pre-experimental and pilot study, requiring an increase in sample size for greater statistical robustness, also qualitative data analysis is crucial for methodological complementarity. The importance of investing efforts to accompany this age group and provide advances in longitudinal research in the area of health promotion and disease prevention is highlighted.

Keywords: emerging adults, disease prevention, health promotion, online program

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336 Numerical Modeling of Phase Change Materials Walls under Reunion Island's Tropical Weather

Authors: Lionel Trovalet, Lisa Liu, Dimitri Bigot, Nadia Hammami, Jean-Pierre Habas, Bruno Malet-Damour

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The MCP-iBAT1 project is carried out to study the behavior of Phase Change Materials (PCM) integrated in building envelopes in a tropical environment. Through the phase transitions (melting and freezing) of the material, thermal energy can be absorbed or released. This process enables the regulation of indoor temperatures and the improvement of thermal comfort for the occupants. Most of the commercially available PCMs are more suitable to temperate climates than to tropical climates. The case of Reunion Island is noteworthy as there are multiple micro-climates. This leads to our key question: developing one or multiple bio-based PCMs that cover the thermal needs of the different locations of the island. The present paper focuses on the numerical approach to select the PCM properties relevant to tropical areas. Numerical simulations have been carried out with two softwares: EnergyPlusTM and Isolab. The latter has been developed in the laboratory, with the implicit Finite Difference Method, in order to evaluate different physical models. Both are Thermal Dynamic Simulation (TDS) softwares that predict the building’s thermal behavior with one-dimensional heat transfers. The parameters used in this study are the construction’s characteristics (dimensions and materials) and the environment’s description (meteorological data and building surroundings). The building is modeled in accordance with the experimental setup. It is divided into two rooms, cells A and B, with same dimensions. Cell A is the reference, while in cell B, a layer of commercial PCM (Thermo Confort of MCI Technologies) has been applied to the inner surface of the North wall. Sensors are installed in each room to retrieve temperatures, heat flows, and humidity rates. The collected data are used for the comparison with the numerical results. Our strategy is to implement two similar buildings at different altitudes (Saint-Pierre: 70m and Le Tampon: 520m) to measure different temperature ranges. Therefore, we are able to collect data for various seasons during a condensed time period. The following methodology is used to validate the numerical models: calibration of the thermal and PCM models in EnergyPlusTM and Isolab based on experimental measures, then numerical testing with a sensitivity analysis of the parameters to reach the targeted indoor temperatures. The calibration relies on the past ten months’ measures (from September 2020 to June 2021), with a focus on one-week study on November (beginning of summer) when the effect of PCM on inner surface temperatures is more visible. A first simulation with the PCM model of EnergyPlus gave results approaching the measurements with a mean error of 5%. The studied property in this paper is the melting temperature of the PCM. By determining the representative temperature of winter, summer and inter-seasons with past annual’s weather data, it is possible to build a numerical model of multi-layered PCM. Hence, the combined properties of the materials will provide an optimal scenario for the application on PCM in tropical areas. Future works will focus on the development of bio-based PCMs with the selected properties followed by experimental and numerical validation of the materials. 1Materiaux ´ a Changement de Phase, une innovation pour le B ` ati Tropical

Keywords: energyplus, multi-layer of PCM, phase changing materials, tropical area

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335 Contrastive Analysis of Parameters Registered in Training Rowers and the Impact on the Olympic Performance

Authors: Gheorghe Braniste

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The management of the training process in sports is closely related to the awareness of the close connection between performance and the morphological, functional and psychological characteristics of the athlete's body. Achieving high results in Olympic sports is influenced, on the one hand, by the genetically determined characteristics of the body and, on the other hand, by the morphological, functional and motor abilities of the athlete. Taking into account the importance of properly understanding the evolutionary specificity of athletes to assess their competitive potential, this study provides a comparative analysis of the parameters that characterize the growth and development of the level of adaptation of sweeping rowers, considering the growth interval between 12 and 20 years. The study established that, in the multi-annual training process, the bodies of the targeted athletes register significant adaptive changes while analyzing parameters of the morphological, functional, psychomotor and sports-technical spheres. As a result of the influence of physical efforts, both specific and non-specific, there is an increase in the adaptability of the body, its transfer to a much higher level of functionality within the parameters, useful and economical adaptive reactions influenced by environmental factors, be they internal or external. The research was carried out for 7 years, on a group of 28 athletes, following their evolution and recording the specific parameters of each age stage. In order to determine the level of physical, morpho-functional, psychomotor development and technical training of rowers, the screening data were applied at the State University of Physical Education and Sports in the Republic of Moldova. During the research, measurements were made on the waist, in the standing and sitting position, arm span, weight, circumference and chest perimeter, vital capacity of the lungs, with the subsequent determination of the vital index (tolerance level to oxygen deficiency in venous blood in Stange and Genchi breath-taking tests that characterize the level of oxygen saturation, absolute and relative strength of the hand and back, calculation of body mass and morphological maturity indices (Kettle index), body surface area (body gait), psychomotor tests (Romberg test), test-tepping 10 s., reaction to a moving object, visual and auditory-motor reaction, recording of technical parameters of rowing on a competitive distance of 200 m. At the end of the study it was found that highly performance is sports is to be associated on the one hand with the genetically determined characteristics of the body and, on the other hand, with favorable adaptive reactions and energy saving, as well as morphofunctional changes influenced by internal and external environmental factors. The importance of the results obtained at the end of the study was positively reflected in obtaining the maximum level of training of athletes in order to demonstrate performance in large-scale competitions and mostly in the Olympic Games.

Keywords: olympics, parameters, performance, peak

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334 Shocks and Flows - Employing a Difference-In-Difference Setup to Assess How Conflicts and Other Grievances Affect the Gender and Age Composition of Refugee Flows towards Europe

Authors: Christian Bruss, Simona Gamba, Davide Azzolini, Federico Podestà

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In this paper, the authors assess the impact of different political and environmental shocks on the size and on the age and gender composition of asylum-related migration flows to Europe. With this paper, the authors contribute to the literature by looking at the impact of different political and environmental shocks on the gender and age composition of migration flows in addition to the size of these flows. Conflicting theories predict different outcomes concerning the relationship between political and environmental shocks and the migration flows composition. Analyzing the relationship between the causes of migration and the composition of migration flows could yield more insights into the mechanisms behind migration decisions. In addition, this research may contribute to better informing national authorities in charge of receiving these migrant, as women and children/the elderly require different assistance than young men. To be prepared to offer the correct services, the relevant institutions have to be aware of changes in composition based on the shock in question. The authors analyze the effect of different types of shocks on the number, the gender and age composition of first time asylum seekers originating from 154 sending countries. Among the political shocks, the authors consider: violence between combatants, violence against civilians, infringement of political rights and civil liberties, and state terror. Concerning environmental shocks, natural disasters (such as droughts, floods, epidemics, etc.) have been included. The data on asylum seekers applying to any of the 32 Schengen Area countries between 2008 and 2015 is on a monthly basis. Data on asylum applications come from Eurostat, data on shocks are retrieved from various sources: georeferenced conflict data come from the Uppsala Conflict Data Program (UCDP), data on natural disasters from the Centre for Research on the Epidemiology of Disasters (CRED), data on civil liberties and political rights from Freedom House, data on state terror from the Political Terror Scale (PTS), GDP and population data from the World Bank, and georeferenced population data from the Socioeconomic Data and Applications Center (SEDAC). The authors adopt a Difference-in-Differences identification strategy, exploiting the different timing of several kinds of shocks across countries. The highly skewed distribution of the dependent variable is taken into account by using count data models. In particular, a Zero Inflated Negative Binomial model is adopted. Preliminary results show that different shocks - such as armed conflict and epidemics - exert weak immediate effects on asylum-related migration flows and almost non-existent effects on the gender and age composition. However, this result is certainly affected by the fact that no time lags have been introduced so far. Finding the correct time lags depends on a great many variables not limited to distance alone. Therefore, finding the appropriate time lags is still a work in progress. Considering the ongoing refugee crisis, this topic is more important than ever. The authors hope that this research contributes to a less emotionally led debate.

Keywords: age, asylum, Europe, forced migration, gender

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333 Psychodiagnostic Tool Development for Measurement of Social Responsibility in Ukrainian Organizations

Authors: Olena Kovalchuk

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How to define the understanding of social responsibility issues by Ukrainian companies is a contravention question. Thus, one of the practical uses of social responsibility is a diagnostic tool development for educational, business or scientific purposes. So the purpose of this research is to develop a tool for measurement of social responsibility in organization. Methodology: A 21-item questionnaire “Organization Social Responsibility Scale” was developed. This tool was adapted for the Ukrainian sample and based on the questionnaire “Perceived Role of Ethics and Social Responsibility” which connects ethical and socially responsible behavior to different aspects of the organizational effectiveness. After surveying the respondents, the factor analysis was made by the method of main compounds with orthogonal rotation VARIMAX. On the basis of the obtained results the 21-item questionnaire was developed (Cronbach’s alpha – 0,768; Inter-Item Correlations – 0,34). Participants: 121 managers at all levels of Ukrainian organizations (57 males; 65 females) took part in the research. Results: Factor analysis showed five ethical dilemmas concerning the social responsibility and profit compatibility in Ukrainian organizations. Below we made an attempt to interpret them: — Social responsibility vs profit. Corporate social responsibility can be a way to reduce operational costs. A firm’s first priority is employees’ morale. Being ethical and socially responsible is the priority of the organization. The most loaded question is "Corporate social responsibility can reduce operational costs". Significant effect of this factor is 0.768. — Profit vs social responsibility. Efficiency is much more important to a firm than ethics or social responsibility. Making the profit is the most important concern for a firm. The dominant question is "Efficiency is much more important to a firm than whether or not the firm is seen as ethical or socially responsible". Significant effect of this factor is 0.793. — A balanced combination of social responsibility and profit. Organization with social responsibility policy is more attractive for its stakeholders. The most loaded question is "Social responsibility and profitability can be compatible". Significant effect of this factor is 0.802. — Role of Social Responsibility in the successful organizational performance. Understanding the value of social responsibility and business ethics. Well-being and welfare of the society. The dominant question is "Good ethics is often good business". Significant effect of this factor is 0.727. — Global vision of social responsibility. Issues related to global social responsibility and sustainability. Innovative approaches to poverty reduction. Awareness of climate change problems. Global vision for successful business. The dominant question is "The overall effectiveness of a business can be determined to a great extent by the degree to which it is ethical and socially responsible". Significant effect of this factor is 0.842. The theoretical contribution. The perspective of the study is to develop a tool for measurement social responsibility in organizations and to test questionnaire’s adequacy for social and cultural context. Practical implications. The research results can be applied for designing a training programme for business school students to form their global vision for successful business as well as the ability to solve ethical dilemmas in managerial practice. Researchers interested in social responsibility issues are welcome to join the project.

Keywords: corporate social responsibility, Cronbach’s alpha, ethical behaviour, psychodiagnostic tool

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332 Effects of a Cluster Grouping of Gifted and Twice Exceptional Students on Academic Motivation, Socio-emotional Adjustment, and Life Satisfaction

Authors: Line Massé, Claire Baudry, Claudia Verret, Marie-France Nadeau, Anne Brault-Labbé

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Little research has been conducted on educational services adapted for twice exceptional students. Within an action research, a cluster grouping was set up in an elementary school in Quebec, bringing together gifted or doubly exceptional (2E) students (n = 11) and students not identified as gifted (n = 8) within a multilevel class (3ᵣ𝒹 and 4ₜₕ years). 2E students had either attention deficit hyperactivity disorder (n = 8, including 3 with specific learning disability) or autism spectrum disorder (n = 2). Differentiated instructions strategies were implemented, including the possibility of progressing at their own pace of learning, independent study or research projects, flexible accommodation, tutoring with older students and the development of socio-emotional learning. A specialized educator also supported the teacher in the class for behavioural and socio-affective aspects. Objectives: The study aimed to assess the impacts of the grouping on all students, their academic motivation, and their socio-emotional adaptation. Method: A mixed method was used, combining a qualitative approach with a quantitative approach. Semi-directed interviews were conducted with students (N = 18, 4 girls and 14 boys aged 8 to 9) and one of their parents (N = 18) at the end of the school year. Parents and students completed two questionnaires at the beginning and end of the school year: the Behavior Assessment System for Children-3, children or parents versions (BASC-3, Reynolds and Kampus, 2015) and the Academic Motivation in Education (Vallerand et al., 1993). Parents also completed the Multidimensional Student Life Satisfaction Scale (Huebner, 1994, adapted by Fenouillet et al., 2014) comprising three domains (school, friendships, and motivation). Mixed thematic analyzes were carried out on the data from the interviews using the N'Vivo software. Related-samples Wilcoxon rank-sums tests were conducted for the data from the questionnaires. Results: Different themes emerge from the students' comments, including a positive impact on school motivation or attitude toward school, improved school results, reduction of their behavioural difficulties and improvement of their social relations. These remarks were more frequent among 2E students. Most 2E students also noted an improvement in their academic performance. Most parents reported improvements in attitudes toward school and reductions in disruptive behaviours in the classroom. Some parents also observed changes in behaviours at home or in the socio-emotional well-being of their children, here again, particularly parents of 2E children. Analysis of questionnaires revealed significant differences at the end of the school year, more specifically pertaining to extrinsic motivation identified, problems of conduct, attention, emotional self-control, executive functioning, negative emotions, functional deficiencies, and satisfaction regarding friendships. These results indicate that this approach could benefit not only gifted and doubly exceptional students but also students not identified as gifted.

Keywords: Cluster grouping, elementary school, giftedness, mixed methods, twice exceptional students

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331 Carbon Footprint Assessment and Application in Urban Planning and Geography

Authors: Hyunjoo Park, Taehyun Kim, Taehyun Kim

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Human life, activity, and culture depend on the wider environment. Cities offer economic opportunities for goods and services, but cannot exist in environments without food, energy, and water supply. Technological innovation in energy supply and transport speeds up the expansion of urban areas and the physical separation from agricultural land. As a result, division of urban agricultural areas causes more energy demand for food and goods transport between the regions. As the energy resources are leaking all over the world, the impact on the environment crossing the boundaries of cities is also growing. While advances in energy and other technologies can reduce the environmental impact of consumption, there is still a gap between energy supply and demand by current technology, even in technically advanced countries. Therefore, reducing energy demand is more realistic than relying solely on the development of technology for sustainable development. The purpose of this study is to introduce the application of carbon footprint assessment in fields of urban planning and geography. In urban studies, carbon footprint has been assessed at different geographical scales, such as nation, city, region, household, and individual. Carbon footprint assessment for a nation and a city is available by using national or city level statistics of energy consumption categories. By means of carbon footprint calculation, it is possible to compare the ecological capacity and deficit among nations and cities. Carbon footprint also offers great insight on the geographical distribution of carbon intensity at a regional level in the agricultural field. The study shows the background of carbon footprint applications in urban planning and geography by case studies such as figuring out sustainable land-use measures in urban planning and geography. For micro level, footprint quiz or survey can be adapted to measure household and individual carbon footprint. For example, first case study collected carbon footprint data from the survey measuring home energy use and travel behavior of 2,064 households in eight cities in Gyeonggi-do, Korea. Second case study analyzed the effects of the net and gross population densities on carbon footprint of residents at an intra-urban scale in the capital city of Seoul, Korea. In this study, the individual carbon footprint of residents was calculated by converting the carbon intensities of home and travel fossil fuel use of respondents to the unit of metric ton of carbon dioxide (tCO₂) by multiplying the conversion factors equivalent to the carbon intensities of each energy source, such as electricity, natural gas, and gasoline. Carbon footprint is an important concept not only for reducing climate change but also for sustainable development. As seen in case studies carbon footprint may be measured and applied in various spatial units, including but not limited to countries and regions. These examples may provide new perspectives on carbon footprint application in planning and geography. In addition, additional concerns for consumption of food, goods, and services can be included in carbon footprint calculation in the area of urban planning and geography.

Keywords: carbon footprint, case study, geography, urban planning

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330 Analytical Model of Locomotion of a Thin-Film Piezoelectric 2D Soft Robot Including Gravity Effects

Authors: Zhiwu Zheng, Prakhar Kumar, Sigurd Wagner, Naveen Verma, James C. Sturm

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Soft robots have drawn great interest recently due to a rich range of possible shapes and motions they can take on to address new applications, compared to traditional rigid robots. Large-area electronics (LAE) provides a unique platform for creating soft robots by leveraging thin-film technology to enable the integration of a large number of actuators, sensors, and control circuits on flexible sheets. However, the rich shapes and motions possible, especially when interacting with complex environments, pose significant challenges to forming well-generalized and robust models necessary for robot design and control. In this work, we describe an analytical model for predicting the shape and locomotion of a flexible (steel-foil-based) piezoelectric-actuated 2D robot based on Euler-Bernoulli beam theory. It is nominally (unpowered) lying flat on the ground, and when powered, its shape is controlled by an array of piezoelectric thin-film actuators. Key features of the models are its ability to incorporate the significant effects of gravity on the shape and to precisely predict the spatial distribution of friction against the contacting surfaces, necessary for determining inchworm-type motion. We verified the model by developing a distributed discrete element representation of a continuous piezoelectric actuator and by comparing its analytical predictions to discrete-element robot simulations using PyBullet. Without gravity, predicting the shape of a sheet with a linear array of piezoelectric actuators at arbitrary voltages is straightforward. However, gravity significantly distorts the shape of the sheet, causing some segments to flatten against the ground. Our work includes the following contributions: (i) A self-consistent approach was developed to exactly determine which parts of the soft robot are lifted off the ground, and the exact shape of these sections, for an arbitrary array of piezoelectric voltages and configurations. (ii) Inchworm-type motion relies on controlling the relative friction with the ground surface in different sections of the robot. By adding torque-balance to our model and analyzing shear forces, the model can then determine the exact spatial distribution of the vertical force that the ground is exerting on the soft robot. Through this, the spatial distribution of friction forces between ground and robot can be determined. (iii) By combining this spatial friction distribution with the shape of the soft robot, in the function of time as piezoelectric actuator voltages are changed, the inchworm-type locomotion of the robot can be determined. As a practical example, we calculated the performance of a 5-actuator system on a 50-µm thick steel foil. Piezoelectric properties of commercially available thin-film piezoelectric actuators were assumed. The model predicted inchworm motion of up to 200 µm per step. For independent verification, we also modelled the system using PyBullet, a discrete-element robot simulator. To model a continuous thin-film piezoelectric actuator, we broke each actuator into multiple segments, each of which consisted of two rigid arms with appropriate mass connected with a 'motor' whose torque was set by the applied actuator voltage. Excellent agreement between our analytical model and the discrete-element simulator was shown for both for the full deformation shape and motion of the robot.

Keywords: analytical modeling, piezoelectric actuators, soft robot locomotion, thin-film technology

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329 Deep Learning Framework for Predicting Bus Travel Times with Multiple Bus Routes: A Single-Step Multi-Station Forecasting Approach

Authors: Muhammad Ahnaf Zahin, Yaw Adu-Gyamfi

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Bus transit is a crucial component of transportation networks, especially in urban areas. Any intelligent transportation system must have accurate real-time information on bus travel times since it minimizes waiting times for passengers at different stations along a route, improves service reliability, and significantly optimizes travel patterns. Bus agencies must enhance the quality of their information service to serve their passengers better and draw in more travelers since people waiting at bus stops are frequently anxious about when the bus will arrive at their starting point and when it will reach their destination. For solving this issue, different models have been developed for predicting bus travel times recently, but most of them are focused on smaller road networks due to their relatively subpar performance in high-density urban areas on a vast network. This paper develops a deep learning-based architecture using a single-step multi-station forecasting approach to predict average bus travel times for numerous routes, stops, and trips on a large-scale network using heterogeneous bus transit data collected from the GTFS database. Over one week, data was gathered from multiple bus routes in Saint Louis, Missouri. In this study, Gated Recurrent Unit (GRU) neural network was followed to predict the mean vehicle travel times for different hours of the day for multiple stations along multiple routes. Historical time steps and prediction horizon were set up to 5 and 1, respectively, which means that five hours of historical average travel time data were used to predict average travel time for the following hour. The spatial and temporal information and the historical average travel times were captured from the dataset for model input parameters. As adjacency matrices for the spatial input parameters, the station distances and sequence numbers were used, and the time of day (hour) was considered for the temporal inputs. Other inputs, including volatility information such as standard deviation and variance of journey durations, were also included in the model to make it more robust. The model's performance was evaluated based on a metric called mean absolute percentage error (MAPE). The observed prediction errors for various routes, trips, and stations remained consistent throughout the day. The results showed that the developed model could predict travel times more accurately during peak traffic hours, having a MAPE of around 14%, and performed less accurately during the latter part of the day. In the context of a complicated transportation network in high-density urban areas, the model showed its applicability for real-time travel time prediction of public transportation and ensured the high quality of the predictions generated by the model.

Keywords: gated recurrent unit, mean absolute percentage error, single-step forecasting, travel time prediction.

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328 The Strategic Role of Accommodation Providers in Encouraging Travelers to Adopt Environmentally-Friendly Modes of Transportation: An Experiment from France

Authors: Luc Beal

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Introduction. Among the stakeholders involved in the tourist decision-making process, the accommodation provider has the potential to play a crucial role in raising awareness, disseminating information, and thus influencing the tourists’ choice of transportation. Since the early days of tourism, the accommodation provider has consistently served as the primary point of contact with the destination, and consequently, as the primary source of information for visitors. By offering accommodation and hospitality, the accommodation provider has evolved into a trusted third party, functioning as an 'ambassador' capable of recommending the finest attractions and activities available at the destination. In contemporary times, when tourists plan their trips, they make a series of consecutive decisions, with the most important decision being to lock-in the accommodation reservation for the earliest days, so as to secure a safe arrival. Consequently, tourists place their trust in the accommodation provider not only for lodging but also for recommendations regarding restaurants, activities, and more. Thus, the latter has the opportunity to inform and influence tourists well in advance of their arrival, particularly during the booking phase, namely when it comes to selecting their mode of transportation. The pressing need to reduce greenhouse gas emissions within the tourism sector presents an opportunity to underscore the influence that accommodation providers have historically exerted on tourist decision-making . Methodology A participatory research, currently ongoing in south-western France, in collaboration with a nationwide hotel group and several destination management organizations, aims at examining the factors that determine the ability of accommodation providers to influence tourist transportation choices. Additionally, the research seeks to identify the conditions that motivate accommodation providers to assume a proactive role, such as fostering customer loyalty, reduced distribution costs, and financial compensation mechanisms. A panel of hotels participated in a series of focus group sessions with tourists, with the objective of modeling the decision-making process of tourists regarding their choice of transportation mode and to identify and quantify the types and levels of incentives liable to encourage environmentally responsible choices. Individual interviews were also conducted with hotel staff, including receptionists and guest relations officers, to develop a framework for interactions with tourists during crucial decision-making moments related to transportation choices. The primary finding of this research indicates that financial incentives significantly outweigh symbolic incentives in motivating tourists to opt for eco-friendly modes of transportation. Another noteworthy result underscores the crucial impact of organizational conditions governing interactions with tourists both before and during their stay. These conditions greatly influence the ability to raise awareness at key decision-making moments and the possibility of gathering data about the chosen transportation mode during the stay. In conclusion, this research has led to the formulation of practical recommendations for accommodation providers and Destination Marketing Organizations (DMOs). These recommendations pertain to communication protocols with tourists, the collection of evidences confirming chosen transportation modes, and the implementation of necessary incentives. Through these measures, accommodation provider can assume a central role in guiding tourists towards making responsible choices in terms of transportation.

Keywords: accommodation provider, trusted third party, environmentally-friendly transportation, green house gas, tourist decision-making process

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327 Barbie in India: A Study of Effects of Barbie in Psychological and Social Health

Authors: Suhrita Saha

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Barbie is a fashion doll manufactured by the American toy company Mattel Inc and it made debut at the American International Toy Fair in New York in 9 March 1959. From being a fashion doll to a symbol of fetishistic commodification, Barbie has come a long way. A Barbie doll is sold every three seconds across the world, which makes the billion dollar brand the world’s most popular doll for the girls. The 11.5 inch moulded plastic doll has a height of 5 feet 9 inches at 1/6 scale. Her vital statistics have been estimated at 36 inches (chest), 18 inches (waist) and 33 inches (hips). Her weight is permanently set at 110 pounds which would be 35 pounds underweight. Ruth Handler, the creator of Barbie wanted a doll that represented adulthood and allowed children to imagine themselves as teenagers or adults. While Barbie might have been intended to be independent, imaginative and innovative, the physical uniqueness does not confine the doll to the status of a play thing. It is a cultural icon but with far reaching critical implications. The doll is a commodity bearing more social value than practical use value. The way Barbie is produced represents industrialization and commodification of the process of symbolic production. And this symbolic production and consumption is a standardized planned one that produce stereotypical ‘pseudo-individuality’ and suppresses cultural alternatives. Children are being subject to and also arise as subjects in this consumer context. A very gendered, physiologically dissected sexually charged symbolism is imposed upon children (both male and female), childhood, their social worlds, identity, and relationship formation. Barbie is also very popular among Indian children. While the doll is essentially an imaginative representation of the West, it is internalized by the Indian sensibilities. Through observation and questionnaire-based interview within a sample population of adolescent children (primarily female, a few male) and parents (primarily mothers) in Kolkata, an Indian metropolis, the paper puts forth findings of sociological relevance. 1. Barbie creates, recreates, and accentuates already existing divides between the binaries like male- female, fat- thin, sexy- nonsexy, beauty- brain and more. 2. The Indian girl child in her associative process with Barbie wants to be like her and commodifies her own self. The male child also readily accepts this standardized commodification. Definition of beauty is thus based on prejudice and stereotype. 3. Not being able to become Barbie creates health issues both psychological and physiological varying from anorexia to obesity as well as personality disorder. 4. From being a plaything Barbie becomes the game maker. Barbie along with many other forms of simulation further creates a consumer culture and market for all kind of fitness related hyper enchantment and subsequent disillusionment. The construct becomes the reality and the real gets lost in the play world. The paper would thus argue that Barbie from being an innocuous doll transports itself into becoming social construct with long term and irreversible adverse impact.

Keywords: barbie, commodification, personality disorder, sterotype

Procedia PDF Downloads 319
326 Planning Railway Assets Renewal with a Multiobjective Approach

Authors: João Coutinho-Rodrigues, Nuno Sousa, Luís Alçada-Almeida

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Transportation infrastructure systems are fundamental in modern society and economy. However, they need modernizing, maintaining, and reinforcing interventions which require large investments. In many countries, accumulated intervention delays arise from aging and intense use, being magnified by financial constraints of the past. The decision problem of managing the renewal of large backlogs is common to several types of important transportation infrastructures (e.g., railways, roads). This problem requires considering financial aspects as well as operational constraints under a multidimensional framework. The present research introduces a linear programming multiobjective model for managing railway infrastructure asset renewal. The model aims at minimizing three objectives: (i) yearly investment peak, by evenly spreading investment throughout multiple years; (ii) total cost, which includes extra maintenance costs incurred from renewal backlogs; (iii) priority delays related to work start postponements on the higher priority railway sections. Operational constraints ensure that passenger and freight services are not excessively delayed from having railway line sections under intervention. Achieving a balanced annual investment plan, without compromising the total financial effort or excessively postponing the execution of the priority works, was the motivation for pursuing the research which is now presented. The methodology, inspired by a real case study and tested with real data, reflects aspects of the practice of an infrastructure management company and is generalizable to different types of infrastructure (e.g., railways, highways). It was conceived for treating renewal interventions in infrastructure assets, which is a railway network may be rails, ballasts, sleepers, etc.; while a section is under intervention, trains must run at reduced speed, causing delays in services. The model cannot, therefore, allow for an accumulation of works on the same line, which may cause excessively large delays. Similarly, the lines do not all have the same socio-economic importance or service intensity, making it is necessary to prioritize the sections to be renewed. The model takes these issues into account, and its output is an optimized works schedule for the renewal project translatable in Gantt charts The infrastructure management company provided all the data for the first test case study and validated the parameterization. This case consists of several sections to be renewed, over 5 years and belonging to 17 lines. A large instance was also generated, reflecting a problem of a size similar to the USA railway network (considered the largest one in the world), so it is not expected that considerably larger problems appear in real life; an average of 25 years backlog and ten years of project horizon was considered. Despite the very large increase in the number of decision variables (200 times as large), the computational time cost did not increase very significantly. It is thus expectable that just about any real-life problem can be treated in a modern computer, regardless of size. The trade-off analysis shows that if the decision maker allows some increase in max yearly investment (i.e., degradation of objective ii), solutions improve considerably in the remaining two objectives.

Keywords: transport infrastructure, asset renewal, railway maintenance, multiobjective modeling

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325 Strategic Planning Practice in a Global Perspective:the Case of Guangzhou, China

Authors: Shuyi Xie

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As the vital city in south China since the ancient time, Guangzhou has been losing its leading role among the rising neighboring cities, especially, Hong Kong and Shenzhen, since the late 1980s, with the overloaded infrastructure and deteriorating urban environment in its old inner city. Fortunately, with the new expansion of its administrative area in 2000, the local municipality considered it as a great opportunity to solve a series of alarming urban problems. Thus, for the first time, strategic planning was introduced to China for providing more convincing and scientific basis towards better urban future. Differed from traditional Chinese planning practices, which rigidly and dogmatically focused on future blueprints, the strategic planning of Guangzhou proceeded from analyzing practical challenges and opportunities towards establishing reasonable developing objectives and proposing corresponding strategies. Moreover, it was pioneering that the municipality invited five planning institutions for proposals, among which, the paper focuses on the one proposed by China Academy of Urban Planning & Design from its theoretical basis to problems’ defining and analyzing the process, as well as planning results. Since it was closer to the following municipal decisions and had a more far-reaching influence for other Chinese cities' following practices. In particular, it demonstrated an innovative exploration on the role played by urban developing rate on deciding urban growth patterns (‘Spillover-reverberation’ or ‘Leapfrog’). That ultimately established an unprecedented paradigm on deciding an appropriate urban spatial structure in future, including its specific location, function and scale. Besides the proposal itself, this article highlights the role of interactions, among actors, as well as proposals, subsequent discussions, summaries and municipal decisions, especially the establishment of the rolling dynamic evaluation system for periodical reviews on implementation situations, as the first attempt in China. Undoubtedly, strategic planning of Guangzhou has brought out considerable benefits, especially opening the strategic mind for plentiful Chinese cities in the following years through establishing a flexible and dynamic planning mechanism highlighted the interactions among multiple actors with innovative and effective tools, methodologies and perspectives on regional, objective-approach and comparative analysis. However, compared with some developed countries, the strategic planning in China just started and has been greatly relied on empirical studies rather than scientific analysis. Moreover, it still faced a bit of controversy, for instance, the certain gap among institutional proposals, final municipal decisions and implemented results, due to the lacking legal constraint. Also, how to improve the public involvement in China with an absolute up-down administrative system is another urgent task. In future, despite of irresistible and irretrievable weakness, some experiences and lessons from previous international practices, with the combination of specific Chinese situations and domestic practices, would enable to promote the further advance on strategic planning in China.

Keywords: evaluation system, global perspective, Guangzhou, interactions, strategic planning, urban growth patterns

Procedia PDF Downloads 361
324 Job Satisfaction among Brigadista in Nicaragua: A Lesson to Be Considered for Task-Shifting

Authors: Rashed Shah, Jeanne Koepsell, Dixmer Rivera, Eric Swedberg, David Marsh

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Success of primary health care goals of health promotion and disease prevention may well be determined by community based health workers’ overall job satisfaction. It is also important to understand the ways community health workers perceive their jobs and the importance they give to the various factors influencing their job satisfaction, which is critical before making a decision for task-shifting and for expanding their scope of work. Although brigadistas are unpaid volunteers, they are formally recognized and receive support and supervision from the Ministry of Health in Nicaragua. Brigadistas are responsible for classifying and diagnosing illnesses, administering treatment, counseling mothers and care givers within the community, encouraging referral in case of serious illness and making follow-up visits at home. Some brigadistas provide more technically advanced services, including treatment for pneumonia, diarrhea, malaria and tuberculosis and/or distribution of contraceptives. Expanding brigadistas’ duties could threaten their heretofore ‘job satisfaction’. This study primarily aims to report on job satisfaction of brigadistas in Nicaragua before expanding the scope of their work by adding more responsibilities. The study was guided by the following research questions: 1) What aspects of their job made the brigadistas satisfied or dissatisfied? 2) What is the job satisfaction level of brigadistas in Nicaragua? This cross-sectional study was conducted during March – July 2014, to assess brigadistas’ job satisfaction, prior to deciding on inclusion of care for sick newborns and young infants (<2 months of age) to brigadistas’ existing service package of community case management for children of 2-59 months of age. Following stratified random sampling strategy, 15 brigadistas were randomly selected from each of the following four strata: [(1) females under 25 years of age, (2) females over 30 years of age, (3) males under 25 years of age, and (4) males over 30 years of age. Out of 45 completed in-person interview with eligible and available brigadistas, 20 (44.4%) were with female and 25 (55.6%) were with male respondents; the mean age (±sd) was found as 32.0 (±3.2) years. About 53% (24/45) brigadista mentioned “Training” as the most helpful for performing their job. Another 31% (14/45) mentioned that “feeling of doing good, supporting community, women and children” was helpful to perform their job well. When asked about difficulty, about 35.5% (16/45) brigadistas mentioned about “Lack of time” due to their responsibilities in family, farm, other work places, study and such time constraint made their job performance difficult. Measured on a 0-5 scale, estimated average job satisfaction was 4.2. Current trends in task-shifting and integrated program delivery require community health workers (like the brigadistas) to deliver several essential services, including maternal, newborn and child health, and family planning, and thereby increasing their responsibilities. Given the reported level of job satisfaction among brigadistas (4.2 out of 5), and the mentioned difficulty in performing their current job (as ‘Lack of Time’) in this study results, the policy makers and program managers in MOH should be cautious enough before making a decision to expand current scope of work for brigadistas in Nicaragua.

Keywords: Brigadisata, job satisfaction, Nicaragua, task-shifting

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323 Fighting the Crisis with 4.0 Competences: Higher Education Projects in the Times of Pandemic

Authors: Jadwiga Fila, Mateusz Jezowski, Pawel Poszytek

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The outbreak of the global COVID-19 pandemic started the times of crisis full of uncertainty, especially in the field of transnational cooperation projects based on the international mobility of their participants. This is notably the case of Erasmus+ Program for higher education, which is the flagship European initiative boosting cooperation between educational institutions, businesses, and other actors, enabling students and staff mobility, as well as strategic partnerships between different parties. The aim of this abstract is to study whether competences 4.0 are able to empower Erasmus+ project leaders in sustaining their international cooperation in times of global crisis, widespread online learning, and common project disruption or cancellation. The concept of competences 4.0 emerged from the notion of the industry 4.0, and it relates to skills that are fundamental for the current labor market. For the aim of the study presented in this abstract, four main 4.0 competences were distinguished: digital, managerial, social, and cognitive competence. The hypothesis for the study stipulated that the above-mentioned highly-developed competences may act as a protective shield against the pandemic challenges in terms of projects’ sustainability and continuation. The objective of the research was to assess to what extent individual competences are useful in managing projects in times of crisis. For this purpose, the study was conducted, involving, among others, 141 Polish higher education project leaders who were running their cooperation projects during the peak of the COVID-19 pandemic (Mar-Nov 2020). The research explored the self-perception of the above-mentioned competences among Erasmus+ project leaders and the contextual data regarding the sustainability of the projects. The quantitative character of data permitted validation of scales (Cronbach’s Alfa measure), and the use of factor analysis made it possible to create a distinctive variable for each competence and its dimensions. Finally, logistic regression was used to examine the association of competences and other factors on project status. The study shows that the project leaders’ competence profile attributed the highest score to digital competence (4.36 on the 1-5 scale). Slightly lower values were obtained for cognitive competence (3.96) and managerial competence (3.82). The lowest score was accorded to one specific dimension of social competence: adaptability and ability to manage stress (1.74), which proves that the pandemic was a real challenge which had to be faced by project coordinators. For higher education projects, 10% were suspended or prolonged because of the COVID-19 pandemic, whereas 90% were undisrupted (continued or already successfully finished). The quantitative analysis showed a positive relationship between the leaders’ levels of competences and the projects status. In the case of all competences, the scores were higher for project leaders who finished projects successfully than for leaders who suspended or prolonged their projects. The research demonstrated that, in the demanding times of the COVID-19 pandemic, competences 4.0, to a certain extent, do play a significant role in the successful management of Erasmus+ projects. The implementation and sustainability of international educational projects, despite mobility and sanitary obstacles, depended, among other factors, on the level of leaders’ competences.

Keywords: Competences 4.0, COVID-19 pandemic, Erasmus+ Program, international education, project sustainability

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322 Developing an Innovative General Foundation Programme (GFP) and an IELTS Centre in a New Military College

Authors: Jessica Peart, Sarim Al Zubaidy

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This paper examines the main dialogic and reformative aspects that have constituted the developing implementation of an English language module in a common pre-sessional program in Oman, the General Foundation Program (GFP), at the new Military Technological College (MTC), in Oman’s capital, muscat. The MTC is the first of its kind in the country to merge military with academic training and has been running programs since September 2013 over five trimesters to date, receiving external validation and accreditation from the University of Portsmouth (UoP), UK. From this starting point, We will provide context on the parameters that necessitated delivery of this common but specially tailored pre-sessional program at the MTC and outline in detail how the English module with integrated key study skills and personal tutoring support was initially conceived before operations commenced and cooperation between all stakeholders took practical shape. This enquiry traces how stakeholders from students to faculty, college boards and collaborative university partners have considered and redefined the in part static and dynamic boundaries of their larger and smaller scale stakes. With regard to the widely held recognition that pre-sessional students require training in transferable study skills in order to succeed at university, we will chart the subsequent and ongoing adjustments made to the generic, pastoral and integrated elements of that program. Driving this concerted effort has been at base the need for a GFP concerned with three criteria for incoming MTC students cadets, namely to develop candidate’s rounded capacity for intellectual, technical and physical skill as both students and cadets, to generate linguistic proficiency and discerning use of appropriate language registers and to allow personal and collective time for adjustment to a multilayered, brand new environment, while also working within a regulated timeline for academic progression to the MTC diploma or degree levels. The English Department teaching staff’s facilitation of the initial program’s methodologies and timeframe for the GFP English module has garnered a keen and diverse sense of the holistic student cadet experience, which a range of alterations to the program demonstrate. These include alterations to the class types and overall program duration as well as greater multiplicity of exposure within learning environments. In surveying the impact of these composite maneuvers and challenges within a proactive and evolving context of teaching and learning, it is finally demonstrated how student cadet levels of productivity and self-reliance on the one hand and retention issues on the other are being gainfully steered towards progression within a framework for inclusive reciprocal dialogue, gathering thereby civilian and military backgrounds toward uniquely united ends.

Keywords: English module transferable skills, faculty dialogue, governance structure, overarching regulatory agencies

Procedia PDF Downloads 259
321 Clinical Validation of an Automated Natural Language Processing Algorithm for Finding COVID-19 Symptoms and Complications in Patient Notes

Authors: Karolina Wieczorek, Sophie Wiliams

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Introduction: Patient data is often collected in Electronic Health Record Systems (EHR) for purposes such as providing care as well as reporting data. This information can be re-used to validate data models in clinical trials or in epidemiological studies. Manual validation of automated tools is vital to pick up errors in processing and to provide confidence in the output. Mentioning a disease in a discharge letter does not necessarily mean that a patient suffers from this disease. Many of them discuss a diagnostic process, different tests, or discuss whether a patient has a certain disease. The COVID-19 dataset in this study used natural language processing (NLP), an automated algorithm which extracts information related to COVID-19 symptoms, complications, and medications prescribed within the hospital. Free-text patient clinical patient notes are rich sources of information which contain patient data not captured in a structured form, hence the use of named entity recognition (NER) to capture additional information. Methods: Patient data (discharge summary letters) were exported and screened by an algorithm to pick up relevant terms related to COVID-19. Manual validation of automated tools is vital to pick up errors in processing and to provide confidence in the output. A list of 124 Systematized Nomenclature of Medicine (SNOMED) Clinical Terms has been provided in Excel with corresponding IDs. Two independent medical student researchers were provided with a dictionary of SNOMED list of terms to refer to when screening the notes. They worked on two separate datasets called "A” and "B”, respectively. Notes were screened to check if the correct term had been picked-up by the algorithm to ensure that negated terms were not picked up. Results: Its implementation in the hospital began on March 31, 2020, and the first EHR-derived extract was generated for use in an audit study on June 04, 2020. The dataset has contributed to large, priority clinical trials (including International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) by bulk upload to REDcap research databases) and local research and audit studies. Successful sharing of EHR-extracted datasets requires communicating the provenance and quality, including completeness and accuracy of this data. The results of the validation of the algorithm were the following: precision (0.907), recall (0.416), and F-score test (0.570). Percentage enhancement with NLP extracted terms compared to regular data extraction alone was low (0.3%) for relatively well-documented data such as previous medical history but higher (16.6%, 29.53%, 30.3%, 45.1%) for complications, presenting illness, chronic procedures, acute procedures respectively. Conclusions: This automated NLP algorithm is shown to be useful in facilitating patient data analysis and has the potential to be used in more large-scale clinical trials to assess potential study exclusion criteria for participants in the development of vaccines.

Keywords: automated, algorithm, NLP, COVID-19

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320 The Influence of Mechanical and Physicochemical Characteristics of Perfume Microcapsules on Their Rupture Behaviour and How This Relates to Performance in Consumer Products

Authors: Andrew Gray, Zhibing Zhang

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The ability for consumer products to deliver a sustained perfume response can be a key driver for a variety of applications. Many compounds in perfume oils are highly volatile, meaning they readily evaporate once the product is applied, and the longevity of the scent is poor. Perfume capsules have been introduced as a means of abating this evaporation once the product has been delivered. The impermeable capsules are aimed to be stable within the formulation, and remain intact during delivery to the desired substrate, only rupturing to release the core perfume oil through application of mechanical force applied by the consumer. This opens up the possibility of obtaining an olfactive response hours, weeks or even months after delivery, depending on the nature of the desired application. Tailoring the properties of the polymeric capsules to better address the needs of the application is not a trivial challenge and currently design of capsules is largely done by trial and error. The aim of this work is to have more predictive methods for capsule design depending on the consumer application. This means refining formulations such that they rupture at the right time for the specific consumer application, not too early, not too late. Finding the right balance between these extremes is essential if a benefit is sought with respect to neat addition of perfume to formulations. It is important to understand the forces that influence capsule rupture, first, by quantifying the magnitude of these different forces, and then by assessing bulk rupture in real-world applications to understand how capsules actually respond. Samples were provided by an industrial partner and the mechanical properties of individual capsules within the samples were characterized via a micromanipulation technique, developed by Professor Zhang at the University of Birmingham. The capsules were synthesized such as to change one particular physicochemical property at a time, such as core: wall material ratio, and the average size of capsules. Analysis of shell thickness via Transmission Electron Microscopy, size distribution via the use of a Mastersizer, as well as a variety of other techniques confirmed that only one particular physicochemical property was altered for each sample. The mechanical analysis was subsequently undertaken, showing the effect that changing certain capsule properties had on the response under compression. It was, however, important to link this fundamental mechanical response to capsule performance in real-world applications. As such, the capsule samples were introduced to a formulation and exposed to full scale stresses. GC-MS headspace analysis of the perfume oil released from broken capsules enabled quantification of what the relative strengths of capsules truly means for product performance. Correlations have been found between the mechanical strength of capsule samples and performance in terms of perfume release in consumer applications. Having a better understanding of the key parameters that drive performance benefits the design of future formulations by offering better guidelines on the parameters that can be adjusted without worrying about the performance effects, and singles out those parameters that are essential in finding the sweet spot for capsule performance.

Keywords: consumer products, mechanical and physicochemical properties, perfume capsules, rupture behaviour

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319 Role of Baseline Measurements in Assessing Air Quality Impact of Shale Gas Operations

Authors: Paula Costa, Ana Picado, Filomena Pinto, Justina Catarino

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Environmental impact associated with large scale shale gas development is of major concern to the public, policy makers and other stakeholders. To assess this impact on the atmosphere, it is important to monitoring ambient air quality prior to and during all shale gas operation stages. Baseline observations can provide a standard of the pre-shale gas development state of the environment. The lack of baseline concentrations was identified as an important knowledge gap to assess the impact of emissions to the air due to shale gas operations. In fact baseline monitoring of air quality are missing in several regions, where there is a strong possibility of future shale gas exploration. This makes it difficult to properly identify, quantify and characterize environmental impacts that may be associated with shale gas development. The implementation of a baseline air monitoring program is imperative to be able to assess the total emissions related with shale gas operations. In fact, any monitoring programme should be designed to provide indicative information on background levels. A baseline air monitoring program should identify and characterize targeted air pollutants, most frequently described from monitoring and emission measurements, as well as those expected from hydraulic fracturing activities, and establish ambient air conditions prior to start-up of potential emission sources from shale gas operations. This program has to be planned for at least one year accounting for ambient variations. In the literature, in addition to GHG emissions of CH4, CO2 and nitrogen oxides (NOx), fugitive emissions from shale gas production can release volatile organic compounds (VOCs), aldehydes (formaldehyde, acetaldehyde) and hazardous air pollutants (HAPs). The VOCs include a.o., benzene, toluene, ethyl benzene, xylenes, hexanes, 2,2,4-trimethylpentane, styrene. The concentrations of six air pollutants (ozone, particulate matter (PM), carbon monoxide (CO), nitrogen oxides (NOx), sulphur oxides (SOx), and lead) whose regional ambient air levels are regulated by the Environmental Protection Agency (EPA), are often discussed. However, the main concern in the emissions to air associated to shale gas operations, seems to be the leakage of methane. Methane is identified as a compound of major concern due to its strong global warming potential. The identification of methane leakage from shale gas activities is complex due to the existence of several other CH4 sources (e.g. landfill, agricultural activity or gas pipeline/compressor station). An integrated monitoring study of methane emissions may be a suitable mean of distinguishing the contribution of different sources of methane to ambient levels. All data analysis needs to be carefully interpreted taking, also, into account the meteorological conditions of the site. This may require the implementation of a more intensive monitoring programme. So, it is essential the development of a low-cost sampling strategy, suitable for establishing pre-operations baseline data as well as an integrated monitoring program to assess the emissions from shale gas operation sites. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 640715.

Keywords: air emissions, baseline, green house gases, shale gas

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318 Fuzzy Multi-Objective Approach for Emergency Location Transportation Problem

Authors: Bidzina Matsaberidze, Anna Sikharulidze, Gia Sirbiladze, Bezhan Ghvaberidze

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In the modern world emergency management decision support systems are actively used by state organizations, which are interested in extreme and abnormal processes and provide optimal and safe management of supply needed for the civil and military facilities in geographical areas, affected by disasters, earthquakes, fires and other accidents, weapons of mass destruction, terrorist attacks, etc. Obviously, these kinds of extreme events cause significant losses and damages to the infrastructure. In such cases, usage of intelligent support technologies is very important for quick and optimal location-transportation of emergency service in order to avoid new losses caused by these events. Timely servicing from emergency service centers to the affected disaster regions (response phase) is a key task of the emergency management system. Scientific research of this field takes the important place in decision-making problems. Our goal was to create an expert knowledge-based intelligent support system, which will serve as an assistant tool to provide optimal solutions for the above-mentioned problem. The inputs to the mathematical model of the system are objective data, as well as expert evaluations. The outputs of the system are solutions for Fuzzy Multi-Objective Emergency Location-Transportation Problem (FMOELTP) for disasters’ regions. The development and testing of the Intelligent Support System were done on the example of an experimental disaster region (for some geographical zone of Georgia) which was generated using a simulation modeling. Four objectives are considered in our model. The first objective is to minimize an expectation of total transportation duration of needed products. The second objective is to minimize the total selection unreliability index of opened humanitarian aid distribution centers (HADCs). The third objective minimizes the number of agents needed to operate the opened HADCs. The fourth objective minimizes the non-covered demand for all demand points. Possibility chance constraints and objective constraints were constructed based on objective-subjective data. The FMOELTP was constructed in a static and fuzzy environment since the decisions to be made are taken immediately after the disaster (during few hours) with the information available at that moment. It is assumed that the requests for products are estimated by homeland security organizations, or their experts, based upon their experience and their evaluation of the disaster’s seriousness. Estimated transportation times are considered to take into account routing access difficulty of the region and the infrastructure conditions. We propose an epsilon-constraint method for finding the exact solutions for the problem. It is proved that this approach generates the exact Pareto front of the multi-objective location-transportation problem addressed. Sometimes for large dimensions of the problem, the exact method requires long computing times. Thus, we propose an approximate method that imposes a number of stopping criteria on the exact method. For large dimensions of the FMOELTP the Estimation of Distribution Algorithm’s (EDA) approach is developed.

Keywords: epsilon-constraint method, estimation of distribution algorithm, fuzzy multi-objective combinatorial programming problem, fuzzy multi-objective emergency location/transportation problem

Procedia PDF Downloads 294
317 Mapping Iron Content in the Brain with Magnetic Resonance Imaging and Machine Learning

Authors: Gabrielle Robertson, Matthew Downs, Joseph Dagher

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Iron deposition in the brain has been linked with a host of neurological disorders such as Alzheimer’s, Parkinson’s, and Multiple Sclerosis. While some treatment options exist, there are no objective measurement tools that allow for the monitoring of iron levels in the brain in vivo. An emerging Magnetic Resonance Imaging (MRI) method has been recently proposed to deduce iron concentration through quantitative measurement of magnetic susceptibility. This is a multi-step process that involves repeated modeling of physical processes via approximate numerical solutions. For example, the last two steps of this Quantitative Susceptibility Mapping (QSM) method involve I) mapping magnetic field into magnetic susceptibility and II) mapping magnetic susceptibility into iron concentration. Process I involves solving an ill-posed inverse problem by using regularization via injection of prior belief. The end result from Process II highly depends on the model used to describe the molecular content of each voxel (type of iron, water fraction, etc.) Due to these factors, the accuracy and repeatability of QSM have been an active area of research in the MRI and medical imaging community. This work aims to estimate iron concentration in the brain via a single step. A synthetic numerical model of the human head was created by automatically and manually segmenting the human head on a high-resolution grid (640x640x640, 0.4mm³) yielding detailed structures such as microvasculature and subcortical regions as well as bone, soft tissue, Cerebral Spinal Fluid, sinuses, arteries, and eyes. Each segmented region was then assigned tissue properties such as relaxation rates, proton density, electromagnetic tissue properties and iron concentration. These tissue property values were randomly selected from a Probability Distribution Function derived from a thorough literature review. In addition to having unique tissue property values, different synthetic head realizations also possess unique structural geometry created by morphing the boundary regions of different areas within normal physical constraints. This model of the human brain is then used to create synthetic MRI measurements. This is repeated thousands of times, for different head shapes, volume, tissue properties and noise realizations. Collectively, this constitutes a training-set that is similar to in vivo data, but larger than datasets available from clinical measurements. This 3D convolutional U-Net neural network architecture was used to train data-driven Deep Learning models to solve for iron concentrations from raw MRI measurements. The performance was then tested on both synthetic data not used in training as well as real in vivo data. Results showed that the model trained on synthetic MRI measurements is able to directly learn iron concentrations in areas of interest more effectively than other existing QSM reconstruction methods. For comparison, models trained on random geometric shapes (as proposed in the Deep QSM method) are less effective than models trained on realistic synthetic head models. Such an accurate method for the quantitative measurement of iron deposits in the brain would be of important value in clinical studies aiming to understand the role of iron in neurological disease.

Keywords: magnetic resonance imaging, MRI, iron deposition, machine learning, quantitative susceptibility mapping

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316 Trends of Conservation and Development in Mexican Biosphere Reserves: Spatial Analysis and Linear Mixed Model

Authors: Cecilia Sosa, Fernanda Figueroa, Leonardo Calzada

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Biosphere reserves (BR) are considered as the main strategy for biodiversity and ecosystems conservation. Mexican BR are mainly inhabited by rural communities who strongly depend on forests and their resources. Even though the dual objective of conservation and development has been sought in BR, land cover change is a common process in these areas, while most rural communities are highly marginalized, partly as a result of restrictions imposed by conservation to the access and use of resources. Achieving ecosystems conservation and social development face serious challenges. Factors such as financial support for development projects (public/private), environmental conditions, infrastructure and regional economic conditions might influence both land use change and wellbeing. Examining the temporal trends of conservation and development in BR is central for the evaluation of outcomes for these conservation strategies. In this study, we analyzed changes in primary vegetation cover (as a proxy for conservation) and the index of marginalization (as a proxy for development) in Mexican BR (2000-2015); we also explore the influence of various factors affecting these trends, such as conservation-development projects financial support (public or private), geographical distribution in ecoregions (as a proxy for shared environmental conditions) and in economic zones (as a proxy for regional economic conditions). We developed a spatial analysis at the municipal scale (2,458 municipalities nationwide) in ArcGIS, to obtain road densities, geographical distribution in ecoregions and economic zones, the financial support received, and the percent of municipality area under protection by protected areas and, particularly, by BR. Those municipalities with less than 25% of area under protection were regarded as part of the protected area. We obtained marginalization indexes for all municipalities and, using MODIS in Google Earth Engine, the number of pixels covered by primary vegetation. We used a linear mixed model in RStudio for the analysis. We found a positive correlation between the marginalization index and the percent of primary vegetation cover per year (r=0.49-0.5); i.e., municipalities with higher marginalization also show higher percent of primary vegetation cover. Also, those municipalities with higher area under protection have more development projects (r=0.46) and some environmental conditions were relevant for percent of vegetation cover. Time, economic zones and marginalization index were all important. Time was particularly, in 2005, when both marginalization and deforestation decreased. Road densities and financial support for conservation-development projects were irrelevant as factors in the general correlation. Marginalization is still being affected by the conservation strategies applied in BR, even though that this management category considers both conservation and development of local communities as its objectives. Our results suggest that roads densities and support for conservation-development projects have not been a factor of poverty alleviation. As better conservation is being attained in the most impoverished areas, we face the dilemma of how to improve wellbeing in rural communities under conservation, since current strategies have not been able to leave behind the conservation-development contraposition.

Keywords: deforestation, local development, marginalization, protected areas

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315 Housing Recovery in Heavily Damaged Communities in New Jersey after Hurricane Sandy

Authors: Chenyi Ma

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Background: The second costliest hurricane in U.S. history, Sandy landed in southern New Jersey on October 29, 2012, and struck the entire state with high winds and torrential rains. The disaster killed more than 100 people, left more than 8.5 million households without power, and damaged or destroyed more than 200,000 homes across the state. Immediately after the disaster, public policy support was provided in nine coastal counties that constituted 98% of the major and severely damaged housing units in NJ overall. The programs include Individuals and Households Assistance Program, Small Business Loan Program, National Flood Insurance Program, and the Federal Emergency Management Administration (FEMA) Public Assistance Grant Program. In the most severely affected counties, additional funding was provided through Community Development Block Grant: Reconstruction, Rehabilitation, Elevation, and Mitigation Program, and Homeowner Resettlement Program. How these policies individually and as a whole impacted housing recovery across communities with different socioeconomic and demographic profiles has not yet been studied, particularly in relation to damage levels. The concept of community social vulnerability has been widely used to explain many aspects of natural disasters. Nevertheless, how communities are vulnerable has been less fully examined. Community resilience has been conceptualized as a protective factor against negative impacts from disasters, however, how community resilience buffers the effects of vulnerability is not yet known. Because housing recovery is a dynamic social and economic process that varies according to context, this study examined the path from community vulnerability and resilience to housing recovery looking at both community characteristics and policy interventions. Sample/Methods: This retrospective longitudinal case study compared a literature-identified set of pre-disaster community characteristics, the effects of multiple public policy programs, and a set of time-variant community resilience indicators to changes in housing stock (operationally defined by percent of building permits to total occupied housing units/households) between 2010 and 2014, two years before and after Hurricane Sandy. The sample consisted of 51 municipalities in the nine counties in which between 4% and 58% of housing units suffered either major or severe damage. Structural equation modeling (SEM) was used to determine the path from vulnerability to the housing recovery, via multiple public programs, separately and as a whole, and via the community resilience indicators. The spatial analytical tool ArcGIS 10.2 was used to show the spatial relations between housing recovery patterns and community vulnerability and resilience. Findings: Holding damage levels constant, communities with higher proportions of Hispanic households had significantly lower levels of housing recovery while communities with households with an adult >age 65 had significantly higher levels of the housing recovery. The contrast was partly due to the different levels of total public support the two types of the community received. Further, while the public policy programs individually mediated the negative associations between African American and female-headed households and housing recovery, communities with larger proportions of African American, female-headed and Hispanic households were “vulnerable” to lower levels of housing recovery because they lacked sufficient public program support. Even so, higher employment rates and incomes buffered vulnerability to lower housing recovery. Because housing is the "wobbly pillar" of the welfare state, the housing needs of these particular groups should be more fully addressed by disaster policy.

Keywords: community social vulnerability, community resilience, hurricane, public policy

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314 The Influence of Leadership Styles on Organizational Performance and Innovation: Empirical Study in Information Technology Sector in Spain

Authors: Richard Mababu Mukiur

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Leadership is an important drive that plays a key role in the success and development of organizations, particularly in the current context of digital transformation, highly competitivity and globalization. Leaders are persons that hold a dominant and privileged position within an organization, field, or sector of activities and are able to manage, motivate and exercise a high degree of influence over other in order to achieve the institutional goals. They achieve commitment and engagement of others to embrace change, and to make good decisions. Leadership studies in higher education institutions have examined how effective leaders hold their organizations, and also to find approaches which fit best in the organizations context for its better management, transformation and improvement. Moreover, recent studies have highlighted the impact of leadership styles on organizational performance and innovation capacities, since some styles give better results than others. Effective leadership is part of learning process that take place through day-to-day tasks, responsibilities, and experiences that influence the organizational performance, innovation and engagement of employees. The adoption of appropriate leadership styles can improve organization results and encourage learning process, team skills and performance, and employees' motivation and engagement. In the case of case of Information Technology sector, leadership styles are particularly crucial since this sector is leading relevant changes and transformations in the knowledge society. In this context, the main objective of this study is to analyze managers leadership styles with their relation to organizational performance and innovation that may be mediated by learning organization process and demographic variables. Therefore, it was hypothesized that the transformational and transactional leadership will be the main style adopted in Information Technology sector and will influence organizational performance and innovation capacity. A sample of 540 participants from Information technology sector has been determined in order to achieve the objective of this study. The Multifactor Leadership Questionnaire was administered as the principal instrument, Scale of innovation and Learning Organization Questionnaire. Correlations and multiple regression analysis have been used as the main techniques of data analysis. The findings indicate that leadership styles have a relevant impact on organizational performance and innovation capacity. The transformational and transactional leadership are predominant styles in Information technology sector. The effective leadership style tend to be characterized by the capacity of generating and sharing knowledge that improve organization performance and innovation capacity. Managers are adopting and adapting their leadership styles that respond to the new organizational, social and cultural challenges and realities of contemporary society. Managers who encourage innovation, foster learning process, share experience are useful to the organization since they contribute to its development and transformation. Learning process capacity and demographic variables (age, gender, and job tenure) mediate the relationship between leadership styles, innovation capacity and organizational performance. The transformational and transactional leadership tend to enhance the organizational performance due to their significant impact on team-building, employees' engagement and satisfaction. Some practical implications and future lines of research have been proposed.

Keywords: leadership styles, tranformational leadership, organisational performance, organisational innovation

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313 Enhancing Financial Security: Real-Time Anomaly Detection in Financial Transactions Using Machine Learning

Authors: Ali Kazemi

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The digital evolution of financial services, while offering unprecedented convenience and accessibility, has also escalated the vulnerabilities to fraudulent activities. In this study, we introduce a distinct approach to real-time anomaly detection in financial transactions, aiming to fortify the defenses of banking and financial institutions against such threats. Utilizing unsupervised machine learning algorithms, specifically autoencoders and isolation forests, our research focuses on identifying irregular patterns indicative of fraud within transactional data, thus enabling immediate action to prevent financial loss. The data we used in this study included the monetary value of each transaction. This is a crucial feature as fraudulent transactions may have distributions of different amounts than legitimate ones, such as timestamps indicating when transactions occurred. Analyzing transactions' temporal patterns can reveal anomalies (e.g., unusual activity in the middle of the night). Also, the sector or category of the merchant where the transaction occurred, such as retail, groceries, online services, etc. Specific categories may be more prone to fraud. Moreover, the type of payment used (e.g., credit, debit, online payment systems). Different payment methods have varying risk levels associated with fraud. This dataset, anonymized to ensure privacy, reflects a wide array of transactions typical of a global banking institution, ranging from small-scale retail purchases to large wire transfers, embodying the diverse nature of potentially fraudulent activities. By engineering features that capture the essence of transactions, including normalized amounts and encoded categorical variables, we tailor our data to enhance model sensitivity to anomalies. The autoencoder model leverages its reconstruction error mechanism to flag transactions that deviate significantly from the learned normal pattern, while the isolation forest identifies anomalies based on their susceptibility to isolation from the dataset's majority. Our experimental results, validated through techniques such as k-fold cross-validation, are evaluated using precision, recall, and the F1 score alongside the area under the receiver operating characteristic (ROC) curve. Our models achieved an F1 score of 0.85 and a ROC AUC of 0.93, indicating high accuracy in detecting fraudulent transactions without excessive false positives. This study contributes to the academic discourse on financial fraud detection and provides a practical framework for banking institutions seeking to implement real-time anomaly detection systems. By demonstrating the effectiveness of unsupervised learning techniques in a real-world context, our research offers a pathway to significantly reduce the incidence of financial fraud, thereby enhancing the security and trustworthiness of digital financial services.

Keywords: anomaly detection, financial fraud, machine learning, autoencoders, isolation forest, transactional data analysis

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312 Association between Physical Inactivity and Sedentary Behaviours with Risk of Hypertension among Sedentary Occupation Workers: A Cross-Sectional Study

Authors: Hanan Badr, Fahad Manee, Rao Shashidhar, Omar Bayoumy

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Introduction: Hypertension is the major risk factor for cardiovascular diseases and stroke and a universe leading cause of disability-adjusted life years and mortality. Adopting an unhealthy lifestyle is thought to be associated with developing hypertension regardless of predisposing genetic factors. This study aimed to examine the association between recreational physical activity (RPA), and sedentary behaviors with a risk of hypertension among ministry employees, where there is no role for occupational physical activity (PA), and to scrutinize participants’ time spent in RPA and sedentary behaviors on the working and weekend days. Methods: A cross-sectional study was conducted among randomly selected 2562 employees working at ten randomly selected ministries in Kuwait. To have a representative sample, the proportional allocation technique was used to define the number of participants in each ministry. A self-administered questionnaire was used to collect data about participants' socio-demographic characteristics, health status, and their 24 hours’ time use during a regular working day and a weekend day. The time use covered a list of 20 different activities practiced by a person daily. The New Zealand Physical Activity Questionnaire-Short Form (NZPAQ-SF) was used to assess the level of RPA. The scale generates three categories according to the number of hours spent in RPA/week: relatively inactive, relatively active, and highly active. Gender-matched trained nurses performed anthropometric measurements (weight and height) and measuring blood pressure (two readings) using an automatic blood pressure monitor (95% accuracy level compared to a calibrated mercury sphygmomanometer). Results: Participants’ mean age was 35.3±8.4 years, with almost equal gender distribution. About 13% of the participants were smokers, and 75% were overweight. Almost 10% reported doctor-diagnosed hypertension. Among those who did not, the mean systolic blood pressure was 119.9±14.2 and the mean diastolic blood pressure was 80.9±7.3. Moreover, 73.9% of participants were relatively physically inactive and 18% were highly active. Mean systolic and diastolic blood pressure showed a significant inverse association with the level of RPA (means of blood pressure measures were: 123.3/82.8 among relatively inactive, 119.7/80.4 among relatively active, and 116.6/79.6 among highly active). Furthermore, RPA occupied 1.6% and 1.8% of working and weekend days, respectively, while sedentary behaviors (watching TV, using electronics for social media or entertaining, etc.) occupied 11.2% and 13.1%, respectively. Sedentary behaviors were significantly associated with high levels of systolic and diastolic blood pressure. Binary logistic regression revealed that physical inactivity (OR=3.13, 95% CI: 2.25-4.35) and sedentary behaviors (OR=2.25, CI: 1.45-3.17) were independent risk factors for high systolic and diastolic blood pressure after adjustment for other covariates. Conclusions: Physical inactivity and sedentary lifestyle were associated with a high risk of hypertension. Further research to examine the independent role of RPA in improving blood pressure levels and cultural and occupational barriers for practicing RPA are recommended. Policies should be enacted in promoting PA in the workplace that might help in decreasing the risk of hypertension among sedentary occupation workers.

Keywords: physical activity, sedentary behaviors, hypertension, workplace

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311 Measurement and Modelling of HIV Epidemic among High Risk Groups and Migrants in Two Districts of Maharashtra, India: An Application of Forecasting Software-Spectrum

Authors: Sukhvinder Kaur, Ashok Agarwal

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Background: For the first time in 2009, India was able to generate estimates of HIV incidence (the number of new HIV infections per year). Analysis of epidemic projections helped in revealing that the number of new annual HIV infections in India had declined by more than 50% during the last decade (GOI Ministry of Health and Family Welfare, 2010). Then, National AIDS Control Organisation (NACO) planned to scale up its efforts in generating projections through epidemiological analysis and modelling by taking recent available sources of evidence such as HIV Sentinel Surveillance (HSS), India Census data and other critical data sets. Recently, NACO generated current round of HIV estimates-2012 through globally recommended tool “Spectrum Software” and came out with the estimates for adult HIV prevalence, annual new infections, number of people living with HIV, AIDS-related deaths and treatment needs. State level prevalence and incidence projections produced were used to project consequences of the epidemic in spectrum. In presence of HIV estimates generated at state level in India by NACO, USIAD funded PIPPSE project under the leadership of NACO undertook the estimations and projections to district level using same Spectrum software. In 2011, adult HIV prevalence in one of the high prevalent States, Maharashtra was 0.42% ahead of the national average of 0.27%. Considering the heterogeneity of HIV epidemic between districts, two districts of Maharashtra – Thane and Mumbai were selected to estimate and project the number of People-Living-with-HIV/AIDS (PLHIV), HIV-prevalence among adults and annual new HIV infections till 2017. Methodology: Inputs in spectrum included demographic data from Census of India since 1980 and sample registration system, programmatic data on ‘Alive and on ART (adult and children)’,‘Mother-Baby pairs under PPTCT’ and ‘High Risk Group (HRG)-size mapping estimates’, surveillance data from various rounds of HSS, National Family Health Survey–III, Integrated Biological and Behavioural Assessment and Behavioural Sentinel Surveillance. Major Findings: Assuming current programmatic interventions in these districts, an estimated decrease of 12% points in Thane and 31% points in Mumbai among new infections in HRGs and migrants is observed from 2011 by 2017. Conclusions: Project also validated decrease in HIV new infection among one of the high risk groups-FSWs using program cohort data since 2012 to 2016. Though there is a decrease in HIV prevalence and new infections in Thane and Mumbai, further decrease is possible if appropriate programme response, strategies and interventions are envisaged for specific target groups based on this evidence. Moreover, evidence need to be validated by other estimation/modelling techniques; and evidence can be generated for other districts of the state, where HIV prevalence is high and reliable data sources are available, to understand the epidemic within the local context.

Keywords: HIV sentinel surveillance, high risk groups, projections, new infections

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