Search results for: loading factor performance

Authors: Ivana Scidà, Francesco Alotto, Anna Osello

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Due to the importance given today to innovation, the education sector is evolving thanks digital technologies. Virtual Reality (VR) can be a potential teaching tool offering many advantages in the field of training and education, as it allows to acquire theoretical knowledge and practical skills using an immersive experience in less time than the traditional educational process. These assumptions allow to lay the foundations for a new educational environment, involving and stimulating for students. Starting from the objective of strengthening the innovative teaching offer and the learning processes, the case study of the research concerns the digitalization of MastrLAB, High Quality Laboratory (HQL) belonging to the Department of Structural, Building and Geotechnical Engineering (DISEG) of the Polytechnic of Turin, a center specialized in experimental mechanical tests on traditional and innovative building materials and on the structures made with them. The MastrLAB-VR has been developed, a revolutionary innovative training tool designed with the aim of educating the class in total safety on the techniques of use of machinery, thus reducing the dangers arising from the performance of potentially dangerous activities. The virtual laboratory, dedicated to the students of the Building and Civil Engineering Courses of the Polytechnic of Turin, has been projected to simulate in an absolutely realistic way the experimental approach to the structural tests foreseen in their courses of study: from the tensile tests to the relaxation tests, from the steel qualification tests to the resilience tests on elements at environmental conditions or at characterizing temperatures. The research work proposes a methodology for the virtualization of technical laboratories through the application of Building Information Modelling (BIM), starting from the creation of a digital model. The process includes the creation of an independent application, which with Oculus Rift technology will allow the user to explore the environment and interact with objects through the use of joypads. The application has been tested in prototype way on volunteers, obtaining results related to the acquisition of the educational notions exposed in the experience through a virtual quiz with multiple answers, achieving an overall evaluation report. The results have shown that MastrLAB-VR is suitable for both beginners and experts and will be adopted experimentally for other laboratories of the University departments.

Keywords: building information modelling, digital learning, education, virtual laboratory, virtual reality

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Authors: Teresa Shuk-Ching Poon

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This paper sets out to examine the changing employment relations practices in Hong Kong’s retail banking sector over a period of more than 10 years. The major objective of the research is to examine whether and to what extent local institutional influences have overshadowed global market forces in shaping strategic management decisions and employment relations practices in Hong Kong, with a view to drawing implications to comparative employment relations studies. Examining the changing pattern of employment relations, this paper finds the industrial relations strategic choice model (Kochan, McKersie and Cappelli, 1984) appropriate to use as a framework for the study. Four broad aspects of employment relations are examined, including work organisation and job design; staffing and labour adjustment; performance appraisal, compensation and employee development; and labour unions and employment relations. Changes in the employment relations practices in two multinational retail banks operated in Hong Kong are examined in detail. The retail banking sector in Hong Kong is chosen as a case to examine as it is a highly competitive segment in the financial service industry very much susceptible to global market influences. This is well illustrated by the fact that Hong Kong was hit hard by both the Asian and the Global Financial Crises. This sector is also subject to increasing institutional influences, especially after the return of Hong Kong’s sovereignty to the People’s Republic of China (PRC) since 1997. The case study method is used as it is a suitable research design able to capture the complex institutional and environmental context which is the subject-matter to be examined in the paper. The paper concludes that operation of the retail banks in Hong Kong has been subject to both institutional and global market changes at different points in time. Information obtained from the two cases examined tends to support the conclusion that the relative significance of institutional as against global market factors in influencing retail banks’ operation and their employment relations practices is depended very much on the time in which these influences emerged and the scale and intensity of these influences. This case study highlights the importance of placing comparative employment relations studies within a context where employment relations practices in different countries or different regions/cities within the same country could be examined and compared over a longer period of time to make the comparison more meaningful.

Keywords: employment relations, institutional influences, global market forces, strategic management decisions, retail banks, Hong Kong

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Authors: Malihe Aliasgari, Yousef Nejatbakhsh

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The era of Big Data and the immensity of real-life datasets compels computation tasks to be performed in a distributed fashion, where the data is dispersed among many servers that operate in parallel. However, massive parallelization leads to computational bottlenecks due to faulty servers and stragglers. Stragglers refer to a few slow or delay-prone processors that can bottleneck the entire computation because one has to wait for all the parallel nodes to finish. The problem of straggling processors, has been well studied in the context of distributed computing. Recently, it has been pointed out that, for the important case of linear functions, it is possible to improve over repetition strategies in terms of the tradeoff between performance and latency by carrying out linear precoding of the data prior to processing. The key idea is that, by employing suitable linear codes operating over fractions of the original data, a function may be completed as soon as enough number of processors, depending on the minimum distance of the code, have completed their operations. The problem of matrix-matrix multiplication in the presence of practically big sized of data sets faced with computational and memory related difficulties, which makes such operations are carried out using distributed computing platforms. In this work, we study the problem of distributed matrix-matrix multiplication W = XY under storage constraints, i.e., when each server is allowed to store a fixed fraction of each of the matrices X and Y, which is a fundamental building of many science and engineering fields such as machine learning, image and signal processing, wireless communication, optimization. Non-secure and secure matrix multiplication are studied. We want to study the setup, in which the identity of the matrix of interest should be kept private from the workers and then obtain the recovery threshold of the colluding model, that is, the number of workers that need to complete their task before the master server can recover the product W. The problem of secure and private distributed matrix multiplication W = XY which the matrix X is confidential, while matrix Y is selected in a private manner from a library of public matrices. We present the best currently known trade-off between communication load and recovery threshold. On the other words, we design an achievable PSGPD scheme for any arbitrary privacy level by trivially concatenating a robust PIR scheme for arbitrary colluding workers and private databases and the proposed SGPD code that provides a smaller computational complexity at the workers.

Keywords: coded distributed computation, private information retrieval, secret sharing, stragglers

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Authors: Zoran Barac, Maja Martinovic

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Higher Education Institutions (HEIs) are a special kind of organization, with its unique purpose and combination of actors. From the societal point of view, they are central institutions in the society that are involved in the activities of education, research, and innovation. At the same time, their societal function derives complex relationships between involved actors, ranging from students, faculty and administration, business community and corporate partners, government agencies, to the general public. HEIs are also particularly interesting as objects of governance research because of their unique public purpose and combination of stakeholders. Furthermore, they are the special type of institutions from an organizational viewpoint. HEIs are often described as “loosely coupled systems” or “organized anarchies“ that implies the challenging nature of their governance models. Governance models of HEIs describe roles, constellations, and modes of interaction of the involved actors in the process of strategic direction and holistic control of institutions, taking into account each particular context. Many governance models of the HEIs are primarily based on the balance of power among the involved actors. Besides the actors’ power and influence, leadership style and environmental contingency could impact the governance model of an HEI. Analyzing them through the frameworks of institutional and contingency theories, HEI governance models originate as outcomes of their institutional and contingency adaptation. HEIs tend to fit to institutional context comprised of formal and informal institutional rules. By fitting to institutional context, HEIs are converging to each other in terms of their structures, policies, and practices. On the other hand, contingency framework implies that there is no governance model that is suitable for all situations. Consequently, the contingency approach begins with identifying contingency variables that might impact a particular governance model. In order to be effective, the governance model should fit to contingency variables. While the institutional context creates converging forces on HEI governance actors and approaches, contingency variables are the causes of divergence of actors’ behavior and governance models. Finally, an HEI governance model is a balanced adaptation of the HEIs to the institutional context and contingency variables. It also encompasses roles, constellations, and modes of interaction of involved actors influenced by institutional and contingency pressures. Actors’ adaptation to the institutional context brings benefits of legitimacy and resources. On the other hand, the adaptation of the actors’ to the contingency variables brings high performance and effectiveness. HEI governance models outlined and analyzed in this paper are collegial, bureaucratic, entrepreneurial, network, professional, political, anarchical, cybernetic, trustee, stakeholder, and amalgam models.

Keywords: governance, governance models, higher education institutions, institutional context, situational context

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Authors: Imed Feki, Faouzi Msahli

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Selection of relevant parameters from a high dimensional process operation setting space is a problem frequently encountered in industrial process modelling. This paper presents a method for selecting the most relevant fabric physical parameters for each sensory quality feature. The proposed relevancy criterion has been developed using two approaches. The first utilizes a fuzzy sensitivity criterion by exploiting from experimental data the relationship between physical parameters and all the sensory quality features for each evaluator. Next an OWA aggregation procedure is applied to aggregate the ranking lists provided by different evaluators. In the second approach, another panel of experts provides their ranking lists of physical features according to their professional knowledge. Also by applying OWA and a fuzzy aggregation model, the data sensitivity-based ranking list and the knowledge-based ranking list are combined using our proposed percolation technique, to determine the final ranking list. The key issue of the proposed percolation technique is to filter automatically and objectively the relevant features by creating a gap between scores of relevant and irrelevant parameters. It permits to automatically generate threshold that can effectively reduce human subjectivity and arbitrariness when manually choosing thresholds. For a specific sensory descriptor, the threshold is defined systematically by iteratively aggregating (n times) the ranking lists generated by OWA and fuzzy models, according to a specific algorithm. Having applied the percolation technique on a real example, of a well known finished textile product especially the stonewashed denims, usually considered as the most important quality criteria in jeans’ evaluation, we separate the relevant physical features from irrelevant ones for each sensory descriptor. The originality and performance of the proposed relevant feature selection method can be shown by the variability in the number of physical features in the set of selected relevant parameters. Instead of selecting identical numbers of features with a predefined threshold, the proposed method can be adapted to the specific natures of the complex relations between sensory descriptors and physical features, in order to propose lists of relevant features of different sizes for different descriptors. In order to obtain more reliable results for selection of relevant physical features, the percolation technique has been applied for combining the fuzzy global relevancy and OWA global relevancy criteria in order to clearly distinguish scores of the relevant physical features from those of irrelevant ones.

Keywords: data sensitivity, feature selection, fuzzy logic, OWA operators, percolation technique

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Authors: Ivan Maguire, Ciprian Briciu, Alan Barrett, Dara Kervick, Jens Ducrèe, Fiona Regan

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With the ever-increasing myriad of applications of which microfluidic devices are capable, reliable fluidic actuation development has remained fundamental to the success of these microfluidic platforms. There are a number of approaches which can be taken in order to integrate liquid actuation on microfluidic platforms, which can usually be split into two primary categories; active microvalves and passive microvalves. Active microvalves are microfluidic valves which require a physical parameter change by external, or separate interaction, for actuation to occur. Passive microvalves are microfluidic valves which don’t require external interaction for actuation due to the valve’s natural physical parameters, which can be overcome through sample interaction. The purpose of this paper is to illustrate how further improvements to past microvalve solutions can largely enhance systematic reliability and performance, with both novel active and passive microvalves demonstrated. Covered within this scope will be two alternative and novel microvalve solutions for centrifugal microfluidic platforms; a revamped pneumatic-dissolvable film active microvalve (PAM) strategy and a spray-on Sol-Gel based hydrophobic passive microvalve (HPM) approach. Both the PAM and the HPM mechanisms were demonstrated on a centrifugal microfluidic platform consisting of alternating layers of 1.5 mm poly(methyl methacrylate) (PMMA) (for reagent storage) sheets and ~150 μm pressure sensitive adhesive (PSA) (for microchannel fabrication) sheets. The PAM approach differs from previous SOLUBON™ dissolvable film methods by introducing a more reliable and predictable liquid delivery mechanism to microvalve site, thus significantly reducing premature activation. This approach has also shown excellent synchronicity when performed in a multiplexed form. The HPM method utilises a new spray-on and low curing temperature (70°C) sol-gel material. The resultant double layer coating comprises a PMMA adherent sol-gel as the bottom layer and an ultra hydrophobic silica nano-particles (SNPs) film as the top layer. The optimal coating was integrated to microfluidic channels with varying cross-sectional area for assessing microvalve burst frequencies consistency. It is hoped that these microvalving solutions, which can be easily added to centrifugal microfluidic platforms, will significantly improve automation reliability.

Keywords: centrifugal microfluidics, hydrophobic microvalves, lab-on-a-disc, pneumatic microvalves

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Authors: Ricardo Torcato, Helder Morais

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The manufacture of crystal glass parts is based on obtaining the rough geometry by blowing and/or injection, generally followed by a set of manual finishing operations using cutting and grinding tools. The forming techniques used do not allow the obtainment, with repeatability, of parts with complex shapes and the finishing operations use intensive specialized labor resulting in high cycle times and production costs. This work aims to explore the digital manufacture of crystal glass parts by investigating new subtractive techniques for the automated, flexible finishing of these parts. Finishing operations are essential to respond to customer demands in terms of crystal feel and shine. It is intended to investigate the applicability of different computerized finishing technologies, namely milling and grinding in a CNC machining center with or without ultrasonic assistance, to crystal processing. Research in the field of grinding hard and brittle materials, despite not being extensive, has increased in recent years, and scientific knowledge about the machinability of crystal glass is still very limited. However, it can be said that the unique properties of glass, such as high hardness and very low toughness, make any glass machining technology a very challenging process. This work will measure the performance improvement brought about by the use of ultrasound compared to conventional crystal grinding. This presentation is focused on the mechanical characterization and analysis of the cutting forces in CNC machining of superior crystal glass (Pb ≥ 30%). For the mechanical characterization, the Vickers hardness test provides an estimate of the material hardness (Hv) and the fracture toughness based on cracks that appear in the indentation. Mechanical impulse excitation test estimates the Young’s Modulus, shear modulus and Poisson ratio of the material. For the cutting forces, it a dynamometer was used to measure the forces in the face grinding process. The tests were made based on the Taguchi method to correlate the input parameters (feed rate, tool rotation speed and depth of cut) with the output parameters (surface roughness and cutting forces) to optimize the process (better roughness using the cutting forces that do not compromise the material structure and the tool life) using ANOVA. This study was conducted for conventional grinding and for the ultrasonic grinding process with the same cutting tools. It was possible to determine the optimum cutting parameters for minimum cutting forces and for minimum surface roughness in both grinding processes. Ultrasonic-assisted grinding provides a better surface roughness than conventional grinding.

Keywords: CNC machining, crystal glass, cutting forces, hardness

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Authors: Sylvie Sossou, Grégoire Gansou, Ildevert Egue

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Introduction: The mission of the family and the school is to educate and train citizens of the city. But the family’s values , parental roles, respect for life collapse in their traditional African form. Indeed laxity with regard to divorce, liberal ideas about child rearing influence the emotional life of the latter. Several causes may contribute to the decline in academic performance. In order to seek a psychological solution to the issue, a study was conducted in 6 schools at the 9th district in Cotonou, cosmopolitan city of Benin. Objective: To evaluate the impact of single parenthood on the psycho child development. Materials and Methods: Questionnaires and interviews were used to gather verbal information. The questionnaires were administered to parents and children (schoolchildren 4, 5 and six form) from 7 to 12 years in lone parenthood. The interview was done with teachers and school leaders. We identified 209 cases of children living with a "single-parent" and 68 single parents. Results: Of the 209 children surveyed the results showed that 116 children are cut relational triangle in early childhood (before 3 years). The psychological effects showed that the separation has caused sadness for 52 children, anger 22, shame 17, crying at 31 children, fear for 14, the silence at 58 children. In front of complete family’s children, these children experience feelings of aggression in 11.48%; sadness in 30.64%; 5.26% the shame, the 6.69% tears; jealousy in 2.39% and 2.87% of indifference. The option to get married in 44.15% of children is a challenge to want to give a happy childhood for their offspring; 22.01% feel rejected, there is uncertainty for 11.48% of cases and 25.36% didn’t give answer. 49, 76% of children want to see their family together; 7.65% are against to avoid disputes and in many cases to save the mother of the father's physical abuse. 27.75% of the ex-partners decline responsibility in the care of the child. Furthermore family difficulties affecting the intellectual capacities of children: 37.32% of children see school difficulties related to family problems despite all the pressure single-parent to see his child succeed. Single parenthood affects inter-family relations: pressure 33.97%; nervousness 24.88%; overprotection 29.18%; backbiting 11.96%, are the lives of these families. Conclusion: At the end of the investigation, results showed that there is a causal relationship between psychological disorders, academic difficulties of children and quality of parental relationships. Other cases may exist, but the lack of resources meant that we have only limited at 6 schools. Early psychological treatment for these children is needed.

Keywords: single-parent, psycho child, school, Cotonou

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Authors: Bi Xiao Fang, Tan Bao Zhen

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Soft skills, core competencies, and generic competencies are exchangeable terminologies often used to represent a similar concept. In the Singapore context, such skills are currently being referred to as Critical Core Skills (CCS). In 2019, SkillsFuture Singapore (SSG) reviewed the Generic Skills and Competencies (GSC) framework that was first introduced in 2016, culminating in the development of the Critical Core Skills (CCS) framework comprising 16 soft skills classified into three clusters. The CCS framework is part of the Skills Framework, and whose stated purpose is to create a common skills language for individuals, employers and training providers. It is also developed with the objectives of building deep skills for a lean workforce, enhance business competitiveness and support employment and employability. This further helps to facilitate skills recognition and support the design of training programs for skills and career development. According to SSG, every job role requires a set of technical skills and a set of Critical Core Skills to perform well at work, whereby technical skills refer to skills required to perform key tasks of the job. There has been an increasing emphasis on soft skills for the future of work. A recent study involving approximately 80 organizations across 28 sectors in Singapore revealed that more enterprises are beginning to recognize that soft skills support their employees’ performance and business competitiveness. Though CCS is of high importance for the development of the workforce’s employability, there is little attention paid to the CCS use and profiling across occupations. A better understanding of how CCS is distributed across the economy will thus significantly enhance SSG’s career guidance services as well as training providers’ services to graduates and workers and guide organizations in their hiring for soft skills. This CCS profiling study sought to understand how CCS is demanded in different occupations. To achieve its research objectives, this study adopted a quantitative method to measure CCS use across different occupations in the Singaporean workforce. Based on the CCS framework developed by SSG, the research team adopted a formative approach to developing the CCS profiling tool to measure the importance of and self-efficacy in the use of CCS among the Singaporean workforce. Drawing on the survey results from 2500 participants, this study managed to profile them into seven occupation groups based on the different patterns of importance and confidence levels of the use of CCS. Each occupation group is labeled according to the most salient and demanded CCS. In the meantime, the CCS in each occupation group, which may need some further strengthening, were also identified. The profiling of CCS use has significant implications for different stakeholders, e.g., employers could leverage the profiling results to hire the staff with the soft skills demanded by the job.

Keywords: employability, skills profiling, skills measurement, soft skills

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Authors: Katsue Edo, Yu Hiroi

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T Increasing attention has been paid to using pictures and photographs in research since the beginning of the 21th century in social sciences. Meanwhile we have been studying the usefulness of Picture mining, which is one of the new ways for a these picture using researches. Picture Mining is an explorative research analysis method that takes useful information from pictures, photographs and static or moving images. It is often compared with the methods of text mining. The Picture Mining concept includes observational research in the broad sense, because it also aims to analyze moving images (Ochihara and Edo 2013). In the recent literature, studies and reports using pictures are increasing due to the environmental changes. These are identified as technological and social changes (Edo et.al. 2013). Low price digital cameras and i-phones, high information transmission speed, low costs for information transferring and high performance and resolution of the cameras of mobile phones have changed the photographing behavior of people. Consequently, there is less resistance in taking and processing photographs for most of the people in the developing countries. In these studies, this method of collecting data from respondents is often called as ‘participant-generated photography’ or ‘respondent-generated visual imagery’, which focuses on the collection of data and its analysis (Pauwels 2011, Snyder 2012). But there are few systematical and conceptual studies that supports it significance of these methods. We have discussed in the recent years to conceptualize these picture using research methods and formalize theoretical findings (Edo et. al. 2014). We have identified the most efficient fields of Picture mining in the following areas inductively and in case studies; 1) Research in Consumer and Customer Lifestyles. 2) New Product Development. 3) Research in Fashion and Design. Though we have found that it will be useful in these fields and areas, we must verify these assumptions. In this study we will focus on the field of fashion and design, to determine whether picture mining methods are really reliable in this area. In order to do so we have conducted an empirical research of the respondents’ attitudes and behavior concerning pictures and photographs. We compared the attitudes and behavior of pictures toward fashion to meals, and found out that taking pictures of fashion is not as easy as taking meals and food. Respondents do not often take pictures of fashion and upload their pictures online, such as Facebook and Instagram, compared to meals and food because of the difficulty of taking them. We concluded that we should be more careful in analyzing pictures in the fashion area for there still might be some kind of bias existing even if the environment of pictures have drastically changed in these years.

Keywords: empirical research, fashion and design, Picture Mining, qualitative research

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Authors: Silvia Gastaldello, Maria Grillo, Luca Tassoni, Claudio Maran, Stefano Balbo

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Antioxidants are nowadays attractive not only for the countless benefits to the human and animal health, but also for the perspective of use as food preservative instead of synthetic chemical molecules. In this study, the radical scavenging activity of six protein extracts from pulse and oleaginous seeds was evaluated. The selected matrices are Pisum sativum (yellow pea from two different origins), Carthamus tinctorius (safflower), Helianthus annuus (sunflower), Lupinus luteus cv Mister (lupin) and Glycine max (soybean), since they are economically interesting for both human and animal nutrition. The seeds were grinded and proteins extracted from 20mg powder with a specific vegetal-extraction kit. Proteins have been quantified through Bradford protocol and scavenging activity was revealed using DPPH assay, based on radical DPPH (2,2-diphenyl-1-picrylhydrazyl) absorbance decrease in the presence of antioxidants molecules. Different concentrations of the protein extract (1, 5, 10, 50, 100, 500 µg/ml) were mixed with DPPH solution (DPPH 0,004% in ethanol 70% v/v). Ascorbic acid was used as a scavenging activity standard reference, at the same six concentrations of protein extracts, while DPPH solution was used as control. Samples and standard were prepared in triplicate and incubated for 30 minutes in dark at room temperature, the absorbance was read at 517nm (ABS30). Average and standard deviation of absorbance values were calculated for each concentration of samples and standard. Statistical analysis using t-students and p-value were performed to assess the statistical significance of the scavenging activity difference between the samples (or standard) and control (ABSctrl). The percentage of antioxidant activity has been calculated using the formula [(ABSctrl-ABS30)/ABSctrl]*100. The obtained results demonstrate that all matrices showed antioxidant activity. Ascorbic acid, used as standard, exhibits a 96% scavenging activity at the concentration of 500 µg/ml. At the same conditions, sunflower, safflower and yellow peas revealed the highest antioxidant performance among the matrices analyzed, with an activity of 74%, 68% and 70% respectively (p < 0.005). Although lupin and soybean exhibit a lower antioxidant activity compared to the other matrices, they showed a percentage of 46 and 36 respectively. All these data suggest the possibility to use undervalued edible matrices as antioxidants source. However, further studies are necessary to investigate a possible synergic effect of several matrices as well as the impact of industrial processes for a large-scale approach.

Keywords: antioxidants, DPPH assay, natural matrices, vegetal proteins

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Authors: Arindam Chaudhuri

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Classification of data has been actively used for most effective and efficient means of conveying knowledge and information to users. The prima face has always been upon techniques for extracting useful knowledge from data such that returns are maximized. With emergence of huge datasets the existing classification techniques often fail to produce desirable results. The challenge lies in analyzing and understanding characteristics of massive data sets by retrieving useful geometric and statistical patterns. We propose a supervised parallel fuzzy rough support vector machine (PFRSVM) for data classification in cloud environment. The classification is performed by PFRSVM using hyperbolic tangent kernel. The fuzzy rough set model takes care of sensitiveness of noisy samples and handles impreciseness in training samples bringing robustness to results. The membership function is function of center and radius of each class in feature space and is represented with kernel. It plays an important role towards sampling the decision surface. The success of PFRSVM is governed by choosing appropriate parameter values. The training samples are either linear or nonlinear separable. The different input points make unique contributions to decision surface. The algorithm is parallelized with a view to reduce training times. The system is built on support vector machine library using Hadoop implementation of MapReduce. The algorithm is tested on large data sets to check its feasibility and convergence. The performance of classifier is also assessed in terms of number of support vectors. The challenges encountered towards implementing big data classification in machine learning frameworks are also discussed. The experiments are done on the cloud environment available at University of Technology and Management, India. The results are illustrated for Gaussian RBF and Bayesian kernels. The effect of variability in prediction and generalization of PFRSVM is examined with respect to values of parameter C. It effectively resolves outliers’ effects, imbalance and overlapping class problems, normalizes to unseen data and relaxes dependency between features and labels. The average classification accuracy for PFRSVM is better than other classifiers for both Gaussian RBF and Bayesian kernels. The experimental results on both synthetic and real data sets clearly demonstrate the superiority of the proposed technique.

Keywords: FRSVM, Hadoop, MapReduce, PFRSVM

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Authors: Narendra Akhadkar, Silvestre Cano, Christophe Gourru

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Injection-molded parts are widely used in power system protection products. One of the biggest challenges in an injection molding process is shrinkage and warpage of the molded parts. All these geometrical variations may have an adverse effect on the quality of the product, functionality, cost, and time-to-market. The situation becomes more challenging in the case of intricate shapes and in mass production using multi-cavity tools. To control the effects of shrinkage and warpage, it is very important to correctly find out the input parameters that could affect the product performance. With the advances in the computer-aided engineering (CAE), different tools are available to simulate the injection molding process. For our case study, we used the MoldFlow insight tool. Our aim is to predict the spread of the functional dimensions and geometrical variations on the part due to variations in the input parameters such as material viscosity, packing pressure, mold temperature, melt temperature, and injection speed. The input parameters may vary during batch production or due to variations in the machine process settings. To perform the accurate product assembly variation simulation, the first step is to perform an individual part variation simulation to render realistic tolerance ranges. In this article, we present a method to simulate part variations coming from the input parameters variation during batch production. The method is based on computer simulations and experimental validation using the full factorial design of experiments (DoE). The robustness of the simulation model is verified through input parameter wise sensitivity analysis study performed using simulations and experiments; all the results show a very good correlation in the material flow direction. There exists a non-linear interaction between material and the input process variables. It is observed that the parameters such as packing pressure, material, and mold temperature play an important role in spread on functional dimensions and geometrical variations. This method will allow us in the future to develop accurate/realistic virtual prototypes based on trusted simulated process variation and, therefore, increase the product quality and potentially decrease the time to market.

Keywords: correlation, molding process, tolerance, sensitivity analysis, variation simulation

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Authors: Ole-Christian Galbo Engstrøm, Erik Schou Dreier, Birthe Møller Jespersen, Kim Steenstrup Pedersen

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Grain quality analysis is a multi-parameterized problem that includes a variety of qualitative and quantitative parameters such as grain type classification, damage type classification, and nutrient regression. Currently, these parameters require human inspection, a multitude of instruments employing a variety of sensor technologies, and predictive model types or destructive and slow chemical analysis. This paper investigates the feasibility of applying near-infrared hyperspectral imaging (NIR-HSI) to grain quality analysis. For this study two datasets of NIR hyperspectral images in the wavelength range of 900 nm - 1700 nm have been used. Both datasets contain images of sparsely and densely packed grain kernels. The first dataset contains ~87,000 image crops of bulk wheat samples from 63 harvests where protein value has been determined by the FOSS Infratec NOVA which is the golden industry standard for protein content estimation in bulk samples of cereal grain. The second dataset consists of ~28,000 image crops of bulk grain kernels from seven different wheat varieties and a single rye variety. In the first dataset, protein regression analysis is the problem to solve while variety classification analysis is the problem to solve in the second dataset. Deep convolutional neural networks (CNNs) have the potential to utilize spatio-spectral correlations within a hyperspectral image to simultaneously estimate the qualitative and quantitative parameters. CNNs can autonomously derive meaningful representations of the input data reducing the need for advanced preprocessing techniques required for classical chemometric model types such as artificial neural networks (ANNs) and partial least-squares regression (PLS-R). A comparison between different CNN architectures utilizing 2D and 3D convolution is conducted. These results are compared to the performance of ANNs and PLS-R. Additionally, a variety of preprocessing techniques from image analysis and chemometrics are tested. These include centering, scaling, standard normal variate (SNV), Savitzky-Golay (SG) filtering, and detrending. The results indicate that the combination of NIR-HSI and CNNs has the potential to be the foundation for an automatic system unifying qualitative and quantitative grain quality analysis within a single sensor technology and predictive model type.

Keywords: deep learning, grain analysis, hyperspectral imaging, preprocessing techniques

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Authors: Jiahao Tian, Michael D. Porter

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Law enforcement agencies are tasked with crime prevention and crime reduction under limited resources. Having an accurate temporal estimate of the crime rate would be valuable to achieve such a goal. However, estimation is usually complicated by the interval-censored nature of crime data. We cast the problem of intensity estimation as a Poisson regression using an EM algorithm to estimate the parameters. Two special penalties are added that provide smoothness over the time of day and day of the week. This approach presented here provides accurate intensity estimates and can also uncover day-of-week clusters that share the same intensity patterns. Anticipating where and when crimes might occur is a key element to successful policing strategies. However, this task is complicated by the presence of interval-censored data. The censored data refers to the type of data that the event time is only known to lie within an interval instead of being observed exactly. This type of data is prevailing in the field of criminology because of the absence of victims for certain types of crime. Despite its importance, the research in temporal analysis of crime has lagged behind the spatial component. Inspired by the success of solving crime-related problems with a statistical approach, we propose a statistical model for the temporal intensity estimation of crime with censored data. The model is built on Poisson regression and has special penalty terms added to the likelihood. An EM algorithm was derived to obtain maximum likelihood estimates, and the resulting model shows superior performance to the competing model. Our research is in line with the smart policing initiative (SPI) proposed by the Bureau Justice of Assistance (BJA) as an effort to support law enforcement agencies in building evidence-based, data-driven law enforcement tactics. The goal is to identify strategic approaches that are effective in crime prevention and reduction. In our case, we allow agencies to deploy their resources for a relatively short period of time to achieve the maximum level of crime reduction. By analyzing a particular area within cities where data are available, our proposed approach could not only provide an accurate estimate of intensities for the time unit considered but a time-variation crime incidence pattern. Both will be helpful in the allocation of limited resources by either improving the existing patrol plan with the understanding of the discovery of the day of week cluster or supporting extra resources available.

Keywords: cluster detection, EM algorithm, interval censoring, intensity estimation

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Authors: I. Irska, S. Paszkiewicz, D. Pawlikowska, E. Piesowicz, A. Linares, T. A. Ezquerra

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Due to the number of advantages such as high tensile strength, sensitivity to hydrolytic degradation, and biocompatibility poly(lactic acid) (PLA) is one of the most common polyesters for biomedical and pharmaceutical applications. However, PLA is a rigid, brittle polymer with low heat distortion temperature and slow crystallization rate. In order to broaden the range of PLA applications, it is necessary to improve these properties. In recent years a number of new strategies have been evolved to obtain PLA-based materials with improved characteristics, including manipulation of crystallinity, plasticization, blending, and incorporation into block copolymers. Among the other methods, synthesis of aliphatic-aromatic copolyesters has been attracting considerable attention as they may combine the mechanical performance of aromatic polyesters with biodegradability known from aliphatic ones. Given the need for highly flexible biodegradable polymers, in this contribution, a series of aromatic-aliphatic based on poly(butylene terephthalate) and poly(lactic acid) (PBT-b-PLA) copolyesters exhibiting superior mechanical properties were copolymerized with an additional poly(tetramethylene oxide) (PTMO) soft block. The structure and properties of both series were characterized by means of attenuated total reflectance – Fourier transform infrared spectroscopy (ATR-FTIR), nuclear magnetic resonance spectroscopy (¹H NMR), differential scanning calorimetry (DSC), wide-angle X-ray scattering (WAXS) and dynamic mechanical, thermal analysis (DMTA). Moreover, the related changes in tensile properties have been evaluated and discussed. Lastly, the viscoelastic properties of synthesized poly(ester-ether) copolymers were investigated in detail by step cycle tensile tests. The block lengths decreased with the advance of treatment, and the block-random diblock terpolymers of (PBT-ran-PLA)-b-PTMO were obtained. DSC and DMTA analysis confirmed unambiguously that synthesized poly(ester-ether) copolymers are microphase-separated systems. The introduction of polyether co-units resulted in a decrease in crystallinity degree and melting temperature. X-ray diffraction patterns revealed that only PBT blocks are able to crystallize. The mechanical properties of (PBT-ran-PLA)-b-PTMO copolymers are a result of a unique arrangement of immiscible hard and soft blocks, providing both strength and elasticity.

Keywords: aliphatic-aromatic copolymers, multiblock copolymers, phase behavior, thermoplastic elastomers

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Authors: Sibongile Masemola

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In 2018, South Africa decriminalised recreational cannabis use and private cultivation, since then, cannabis businesses have been established to meet the demand. However, marketing activities remain limited in this industry, and businesses are unable to disseminate promotional messages, however, as a solution, firms can promote their brands and positioning instead of the actual product (Bick, 2015). Branding is essential to create differences among cannabis firms and to attract and keep customers (Abrahamsson, 2014). Building cannabis firms into brands can better position them in the mind of the consumer so that they become and remain competitive. The aim of this study was to explore how South African cannabis retailers can build brand equity in a stigmatised market, despite significant restrictions on marketing efforts. Keller’s (2001) customer-based brand equity (CBBE) model was used as the as the theoretical framework and explored how cannabis firms build their businesses into brands through developing their brand identity, meaning, performance, and relationships, and ultimately creating brand equity. The study employed a qualitative research method, using semi-structured in-depth interviews among 17 participants to gain insights from cannabis owners and marketers in the recreational cannabis environment. Most findings were presented according to the blocks of CBBE model. Furthermore, a conceptual framework named the stigma-based brand equity (SBBE) model was adapted from Keller’s CBBE model to include an additional building block that accounts for industry-specific characteristics unique to stigmatised markets. Findings revealed the pervasiveness of education and its significance to brand building in a stigmatised industry. Results also demonstrated the overall effect stigma has on businesses and their consumers due to the longstanding negative evaluations of cannabis. Hence, through stigma-bonding, brands can develop deep identity-related psychological bonds with their consumers that will potentially lead to strong brand resonance. This study aims to contribute business-relevant knowledge for firms operating in core-stigmatised markets under controlled marketing regulations by exploring how cannabis firms can build brand equity. Practically, this study presents recommendations for retailers in stigmatised markets on how to destigmatise, build brand identity, create brand meaning, elicit desired brand responses, and develop brand relationships – ultimately building brand equity.

Keywords: branding, brand equity, cannabis, organisational stigma

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Authors: Priscila A. Bernardes, Marcos E. Buzanskas, Luciana C. A. Regitano, Ricardo V. Ventura, Danisio P. Munari

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The best linear unbiased predictor (BLUP) is a method commonly used in genetic evaluations of breeding programs. However, this approach can lead to higher inbreeding coefficients in the population due to the intensive use of few bulls with higher genetic potential, usually presenting some degree of relatedness. High levels of inbreeding are associated to low genetic viability, fertility, and performance for some economically important traits and therefore, should be constantly monitored. Unreliable pedigree data can also lead to misleading results. Genomic information (i.e., single nucleotide polymorphism – SNP) is a useful tool to estimate the inbreeding coefficient. Runs of homozygosity have been used to evaluate homozygous segments inherited due to direct or collateral inbreeding and allows inferring population selection history. This study aimed to evaluate runs of homozygosity (ROH) and inbreeding in a population of Nelore beef cattle. A total of 814 animals were genotyped with the Illumina BovineHD BeadChip and the quality control was carried out excluding SNPs located in non-autosomal regions, with unknown position, with a p-value in the Hardy-Weinberg equilibrium lower than 10⁻⁵, call rate lower than 0.98 and samples with the call rate lower than 0.90. After the quality control, 809 animals and 509,107 SNPs remained for analyses. For the ROH analysis, PLINK software was used considering segments with at least 50 SNPs with a minimum length of 1Mb in each animal. The inbreeding coefficient was calculated using the ratio between the sum of all ROH sizes and the size of the whole genome (2,548,724kb). A total of 25.711 ROH were observed, presenting mean, median, minimum, and maximum length of 3.34Mb, 2Mb, 1Mb, and 80.8Mb, respectively. The number of SNPs present in ROH segments varied from 50 to 14.954. The longest ROH length was observed in one animal, which presented a length of 634Mb (24.88% of the genome). Four bulls were among the 10 animals with the longest extension of ROH, presenting 11% of ROH with length higher than 10Mb. Segments longer than 10Mb indicate recent inbreeding. Therefore, the results indicate an intensive use of few sires in the studied data. The distribution of ROH along the chromosomes showed that chromosomes 5 and 6 presented a large number of segments when compared to other chromosomes. The mean, median, minimum, and maximum inbreeding coefficients were 5.84%, 5.40%, 0.00%, and 24.88%, respectively. Although the mean inbreeding was considered low, the ROH indicates a recent and intensive use of few sires, which should be avoided for the genetic progress of breed.

Keywords: autozygosity, Bos taurus indicus, genomic information, single nucleotide polymorphism

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Authors: Parker Murray, Marci Johnson, Tyson S. Burnham, Alina K. Fong, Mark D. Allen, Bruce McIff

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Purpose: Pathological dysregulation of Neurovascular Coupling (NVC) caused by mild traumatic brain injury (mTBI) is the predominant source of chronic post-concussion syndrome (PCS) symptomology. fNCI has the ability to localize dysregulation in NVC by measuring blood-oxygen-level-dependent (BOLD) signaling during the performance of fMRI-adapted neuropsychological evaluations. With fNCI, 57 brain areas consistently affected by concussion were identified as PCS neural markers, which were validated on large samples of concussion patients and healthy controls. These neuromarkers provide the basis for a computation of PCS severity which is referred to as the Severity Index Score (SIS). The SIS has proven valuable in making pre-treatment decisions, monitoring treatment efficiency, and assessing long-term stability of outcomes. Methods and Materials: After being scanned while performing various cognitive tasks, 476 concussed patients received an SIS score based on the neural dysregulation of the 57 previously identified brain regions. These scans provide an objective measurement of attentional, subcortical, visual processing, language processing, and executive functioning abilities, which were used as biomarkers for post-concussive neural dysregulation. Initial SIS scores were used to develop individualized therapy incorporating cognitive, occupational, and neuromuscular modalities. These scores were also used to establish pre-treatment benchmarks and measure post-treatment improvement. Results: Changes in SIS were calculated in percent change from pre- to post-treatment. Patients showed a mean improvement of 76.5 percent (σ= 23.3), and 75.7 percent of patients showed at least 60 percent improvement. Longitudinal reassessment of 24 of the patients, measured an average of 7.6 months post-treatment, shows that SIS improvement is maintained and improved, with an average of 90.6 percent improvement from their original scan. Conclusions: fNCI provides a reliable measurement of NVC allowing for identification of concussion pathology. Additionally, fNCI derived SIS scores direct tailored therapy to restore NVC, subsequently resolving chronic PCS resulting from mTBI.

Keywords: concussion, functional magnetic resonance imaging (fMRI), neurovascular coupling (NVC), post-concussion syndrome (PCS)

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Authors: Amir Shariffar, Haider Salman, Tanveer Siddique, Omar Manasreh

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According to the recent studies on metal-oxide memristors, researchers tend to improve the stability, endurance, and uniformity of resistive switching (RS) behavior in memristors. Specifically, the main challenge is to prevent abrupt ruptures in the memristor’s filament during the RS process. To address this problem, we are proposing a low-cost hybrid structure of metal oxide quantum dots (QDs) and thin films to control the formation of filaments in memristors. We aim to use metal oxide quantum dots because of their unique electronic properties and quantum confinement, which may improve the resistive switching behavior. QDs have discrete energy spectra due to electron confinement in three-dimensional space. Because of Coulomb repulsion between electrons, only a few free electrons are contained in a quantum dot. This fact might guide the growth direction for the conducting filaments in the metal oxide memristor. As a result, it is expected that QDs can improve the endurance and uniformity of RS behavior in memristors. Moreover, we use a hybrid structure of intrinsic n-type quantum dots and p-type thin films to introduce a potential barrier at the junction that can smooth the transition between high and low resistance states. A bottom-up approach is used for fabricating the proposed memristor using different types of metal-oxide QDs and thin films. We synthesize QDs including, zinc oxide, molybdenum trioxide, and nickel oxide combined with spin-coated thin films of titanium dioxide, copper oxide, and hafnium dioxide. We employ fluorine-doped tin oxide (FTO) coated glass as the substrate for deposition and bottom electrode. Then, the active layer composed of one type of quantum dots, and the opposite type of thin films is spin-coated onto the FTO. Lastly, circular gold electrodes are deposited with a shadow mask by using electron-beam (e-beam) evaporation at room temperature. The fabricated devices are characterized using a probe station with a semiconductor parameter analyzer. The current-voltage (I-V) characterization is analyzed for each device to determine the conduction mechanism. We evaluate the memristor’s performance in terms of stability, endurance, and retention time to identify the optimal memristive structure. Finally, we assess the proposed hypothesis before we proceed to the optimization process for fabricating the memristor.

Keywords: memristor, quantum dot, resistive switching, thin film

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Authors: Xining Wang

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After-school educational service has been proven that it could benefit children’s academic performance, socio-emotional skills, and physical health level. However, there is little research demonstrating parents’ perspectives on the choice of after-school educational service from a level of cross-cultural backgrounds. China and Ireland are typical representatives of collectivist countries (e.g., estimated individualism score is 20) and individualist countries (e.g., estimated individualism score is 70) according to Hofstede's cultural dimensions theory. Living in countries with distinguished cultural backgrounds, there is an evident discrepancy in parents’ attitudes towards domestic after-school education and parents’ motivations for choosing after-school educational services. Through conducting a semi-structured interview with 15 parents from China and 15 parents from Ireland, using thematic analysis software (ATLAS) to extract the key information, and applying a comparative approach to process data analysis; results present polarization of Chinese and Irish parents' perspectives and motivations on after-school educational service. For example, Chinese parents tend to view after-school education as a complement to school education. It is a service they purchased for their children to acquire extra knowledge and skills so that they could adapt to the highly competitive educational setting. Given the fact that children’s education is a priority for Chinese families, most parents believe that their children would succeed in the future through massive learning. This attitude reflects that Chinese parents are more likely to apply authoritarian parenting methods and having a strong expectations for their children. Conversely, Irish parents' choice of after-school educational service is a consideration that primarily based on their own situation, secondly, for their family. For instance, with the expansion of the labor market, there is a change in household structure. Irish mothers are more likely to seek working opportunities instead of looking after the family. Irish parents view that after-school educational service is an essential need for themselves and a beneficial component for their family due to the external pressure (e.g., the growing work intensity and extended working hours, increasing numbers of separated families, as well as parents’ pursuit of higher education and promotion). These factors are fundamental agents that encourage Irish parents to choose after-school educational services. To conclude, the findings could provide readers with a better understanding of parents’ disparate and contrasting perspectives on after-school educational services from a multi-culture level.

Keywords: after-school, China, family studies, Ireland, parents

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Authors: Aisha Giwa, Mohammed-Faosy Adeniran, Olufunke Femi-Ojo

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Four decades ago, the World Health Organization (WHO) launched the Expanded Programme on Immunization (EPI). The EPI blueprint laid out the technical and managerial functions necessary to routinely vaccinate children with a limited number of vaccines, providing protection against diphtheria, tetanus, whooping cough, measles, polio, and tuberculosis, and to prevent maternal and neonatal tetanus by vaccinating women of childbearing age with tetanus toxoid. Despite global efforts, the Routine Immunization (RI) coverage in two of the World Health Organization (WHO) regions; the African Region and the South-East Asia Region, still remains short of its targets. As a result, the WHO Regional Director for Africa declared 2012 as the year for intensifying RI in these regions and this also coincided with the declaration of polio as a programmatic emergency by the WHO Executive Board. In order to intensify routine immunization, the National Routine Immunization Strategic Plan (2013-2015) stated that its core priority is to ensure 100% adequacy and availability of vaccines for safe immunization. To achieve 100% availability, the “PUSH System” and then “Push-Plus” were adopted for vaccine distribution, which replaced the inefficient “PULL” method. The NPHCDA plays the key role in coordinating activities in area advocacy, capacity building, engagement of 3PL for the state as well as monitoring and evaluation of the vaccine delivery process. eHealth Africa (eHA) is a player as a 3PL service provider engaged by State Primary Health Care Boards (SPHCDB) to ensure vaccine availability through Vaccine Direct Delivery (VDD) project which is essential to successful routine immunization services. The VDD project ensures the availability and adequate supply of high-quality vaccines and immunization-related materials to last-mile facilities. eHA’s commitment to the VDD project saw the need for an assessment of the project vis-a-vis the overall project performance, evaluation of a process for necessary improvement suggestions as well as general impact across Kano State (Where eHA had transitioned to the state), Bauchi State (currently manage delivery to all LGAs except 3 LGAs currently being managed by the state), Sokoto State (eHA currently covers all LGAs) and Zamfara State (Currently, in-sourced and managed solely by the state).

Keywords: cold chain logistics, health supply chain system strengthening, logistics management information system, vaccine delivery traceability and accountability

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Authors: Gulcin Satir, Ahmet Yildirim

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Globally, including Turkey, health problems associated with malnutrition and nutrient deficiencies in childhood will remain major public health problems in future. Nutrition is a major environmental influence on physical and mental growth and development in early life. Many studies support the fact that nutritional knowledge makes contribution to wellbeing of children and their school performance. The purpose of this study was to examine nutritional knowledge and eating habits of primary school children and to investigate differences in these variables by socioeconomic status. A quasi-experimental one group pretest/posttest design study was conducted in five primary schools totaling 200 children aging 9-10 years in grade 4 to determine the effect of nutritional awareness programme on eating habits of primary school children. The schools were chosen according to parents’ social and demographic characteristics. The implemented nutritional awareness education programme focused on healthy lifestyle such as beneficial foods, eating habits, personal hygiene, physical activity and the programme consisted of eight lessons. The teaching approaches used included interactive teaching, role-playing, demonstration, small group discussions, questioning, and feedback. The lessons were given twice a week for four weeks totaling eight lessons. All lessons lasted 45-60 minutes and first 5 minutes of this was pre-assessment and last 5 minutes post assessment evaluation. The obtained data were analyzed for normality, and the distribution of the variables was tested by the Kolmogorov-Smirnov test. Paired t-test was used to evaluate the effectiveness of education programme and to compare the above-mentioned variables in each school separately before and after the lessons. The result of the paired t-test conducted separately for each school showed that on average after eight lessons, there was a 25-32% increase in nutritional knowledge of students regardless of the school they attend to and this rate was significant (P < 0.01). This shows that increase in nutritional awareness in these five schools having different socio-economic status was similar to each other. This study suggests that having children involved directly in lessons help to achieve nutritional awareness leading to healthy eating habits. It is concluded that nutritional awareness is a valuable tool to change eating habits. Study findings will provide information for developing nutrition education programmes for the healthy life and obesity prevention in children.

Keywords: children, nutritional awareness, obesity, socioeconomic status

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Authors: J. Knight, E. Barberà

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Language learning strategies have been defined as thoughts and actions, consciously chosen and operationalized by language learners, to help them in carrying out a multiplicity of tasks from the very outset of learning to the most advanced levels of target language performance. While research in the field of Second Language Acquisition has focused on ‘good’ language learners, the effectiveness of strategy-use and orchestration by effective learners in face-to-face classrooms much less research has attended to learner strategies in online contexts, particular strategies in relation to technological tool use which can be part of a task design. In addition, much research on learner strategies and strategy use has been explored focusing on cognitive, attitudinal and metacognitive behaviour with less research focusing on the social aspect of strategies. This study focuses on how learners mediate with a technological tool designed to support synchronous spoken interaction and how this shape their spoken interaction in the opening of their talk. A case study approach is used incorporating notions from communities of practice theory to analyse and understand learner strategies of dyads carrying out a role play task. The study employs analysis of transcripts of spoken interaction in the openings of the talk along with log files of tool use. The study draws on results of previous studies pertaining to the same tool as a form of triangulation. Findings show how learners gain pre-task planning time through technological tool control. The strategies involving learners’ choices to enter and exit the tool shape their spoken interaction qualitatively, with some cases demonstrating long silences whilst others appearing to start the pedagogical task immediately. Who/what learners orientate to in the openings of the talk: an audience (i.e. the teacher), each other and/or screen-based signifiers in the opening moments of the talk also becomes a focus. The study highlights how tool use as a social practice should be considered a learning strategy in online contexts whereby different usages may be understood in the light of the more usual asynchronous social practices of the online community. The teachers’ role in the community is also problematised as the evaluator of the practices of that community. Results are pertinent for task design for synchronous speaking tasks. The use of community of practice theory supports an understanding of strategy use that involves both metacognition alongside social context revealing how tool-use strategies may need to be orally (socially) negotiated by learners and may also differ from an online language community.

Keywords: learner strategy, tool use, community of practice, speaking task

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Authors: Pauline Bredy, Yves Schuurman, David Farrusseng

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To fulfill climate objectives, the production of synthetic e-fuels using CO₂ as a raw material appears as part of the solution. In particular, Power-to-Liquid (PtL) concept combines CO₂ with hydrogen supplied from water electrolysis, powered by renewable sources, which is currently gaining interest as it allows the production of sustainable fossil-free liquid fuels. The proposed process discussed here is an upgrading of the well-known Fischer-Tropsch synthesis. The concept deals with two cascade reactions in one pot, with first the conversion of CO₂ into CO via the reverse water gas shift (RWGS) reaction, which is then followed by the Fischer-Tropsch Synthesis (FTS). Instead of using a Fe-based catalyst, which can carry out both reactions, we have chosen the strategy to decouple the two functions (RWGS and FT) on two different catalysts within the same reactor. The FTS shall shift the equilibrium of the RWGS reaction (which alone would be limited to 15-20% of conversion at 250°C) by converting the CO into hydrocarbons. This strategy shall enable optimization of the catalyst pair and thus lower the temperature of the reaction thanks to the equilibrium shift to gain selectivity in the liquid fraction. The challenge lies in maximizing the activity of the RWGS catalyst but also in the ability of the FT catalyst to be highly selective. Methane production is the main concern as the energetic barrier of CH₄ formation is generally lower than that of the RWGS reaction, so the goal will be to minimize methane selectivity. Here we report the study of different combinations of copper-based RWGS catalysts with different cobalt-based FTS catalysts. We investigated their behaviors under mild process conditions by the use of high-throughput experimentation. Our results show that at 250°C and 20 bars, Cobalt catalysts mainly act as methanation catalysts. Indeed, CH₄ selectivity never drops under 80% despite the addition of various protomers (Nb, K, Pt, Cu) on the catalyst and its coupling with active RWGS catalysts. However, we show that the activity of the RWGS catalyst has an impact and can lead to longer hydrocarbons chains selectivities (C₂⁺) of about 10%. We studied the influence of the reduction temperature on the activity and selectivity of the tandem catalyst system. Similar selectivity and conversion were obtained at reduction temperatures between 250-400°C. This leads to the question of the active phase of the cobalt catalysts, which is currently investigated by magnetic measurements and DRIFTS. Thus, in coupling it with a more selective FT catalyst, better results are expected. This was achieved using a cobalt/iron FTS catalyst. The CH₄ selectivity dropped to 62% at 265°C, 20 bars, and a GHSV of 2500ml/h/gcat. We propose that the conditions used for the cobalt catalysts could have generated this methanation because these catalysts are known to have their best performance around 210°C in classical FTS, whereas the iron catalysts are more flexible but are also known to have an RWGS activity.

Keywords: cobalt-copper catalytic systems, CO₂-hydrogenation, Fischer-Tropsch synthesis, hydrocarbons, low-temperature process

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Authors: H. Pegram, R. Stevens, L. De Girolamo

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Aligned electrospun nanofibres act as effective neuronal and glial cell scaffolds that can be layered to contain multiple sheets harboring different cell populations. This allows personalised biofunctional prostheses to be manufactured with both acellular and cellularised layers for the treatment of spinal cord injury. Additionally, the manufacturing route may be configured to produce in-vitro 3D cell based model of spinal cord injury to aid drug development and enhance prosthesis performance. The goal of this investigation was to optimise the multi-layer scaffold design parameters for prosthesis manufacture, to enable the development of multi-layer patient specific implant therapies. The work has also focused on the fabricating aligned nanofibre scaffolds that promote in-vitro neuronal and glial cell population growth, cell-to-cell interaction and long-term survival following trauma to mimic an in-vivo spinal cord lesion. The approach has established reproducible lesions and has identified markers of trauma and regeneration marked by effective neuronal migration across the lesion with glial support. The investigation has advanced the development of an in-vitro model of traumatic spinal cord injury and has identified a route to manufacture prostheses which target the repair spinal cord injury. Evidence collated to investigate the multi-layer concept suggests that physical cues provided by nanofibres provide both a natural extra-cellular matrix (ECM) like environment and controls cell proliferation and migration. Specifically, aligned nanofibre layers act as a guidance system for migrating and elongating neurons. On a larger scale, material type in multi-layer systems also has an influence in inter-layer migration as cell types favour different material types. Results have shown that layering nanofibre membranes create a multi-level scaffold system which can enhance or prohibit cell migration between layers. It is hypothesised that modifying nanofibre layer material permits control over neuronal/glial cell migration. Using this concept, layering of neuronal and glial cells has become possible, in the context of tissue engineering and also modelling in-vitro induced lesions.

Keywords: electrospinning, layering, lesion, modeling, nanofibre

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Authors: Soumyadip Banerjee, Tanmoy Maity

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The recovery of power from waste air generated by mine ventilation fans presents a promising avenue for enhancing energy efficiency in mining operations. This abstract explores the feasibility and benefits of utilizing turbine generators to capture the kinetic energy present in waste air and convert it into electrical power. By integrating turbine generator systems into mine ventilation infrastructures, the potential to harness and utilize the previously untapped energy within the waste air stream is realized. This study examines the principles underlying turbine generator technology and its application within the context of mine ventilation systems. The process involves directing waste air from ventilation fans through specially designed turbines, where the kinetic energy of the moving air is converted into rotational motion. This mechanical energy is then transferred to connected generators, which convert it into electrical power. The recovered electricity can be employed for various on-site applications, including powering mining equipment, lighting, and control systems. The benefits of power recovery from waste air using turbine generators are manifold. Improved energy efficiency within the mining environment results in reduced dependence on external power sources and associated cost savings. Additionally, this approach contributes to environmental sustainability by utilizing a previously wasted resource for power generation. Resource conservation is further enhanced, aligning with modern principles of sustainable mining practices. However, successful implementation requires careful consideration of factors such as waste air characteristics, turbine design, generator efficiency, and integration into existing mine infrastructure. Maintenance and monitoring protocols are necessary to ensure consistent performance and longevity of the turbine generator systems. While there is an initial investment associated with equipment procurement, installation, and integration, the long-term benefits of reduced energy costs and environmental impact make this approach economically viable. In conclusion, the recovery of power from waste air from mine ventilation fans using turbine generators offers a tangible solution to enhance energy efficiency and sustainability within mining operations. By capturing and converting the kinetic energy of waste air into usable electrical power, mines can optimize resource utilization, reduce operational costs, and contribute to a greener future for the mining industry.

Keywords: waste to energy, wind power generation, exhaust air, power recovery

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Authors: Qier Wu, Issam Takla, Thomas Rougelot, Nicolas Burlion

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In the framework of French underground disposal of intermediate level radioactive wastes, concrete is widely used as a construction material for containers and tunnels. Drying shrinkage is one of the most disadvantageous phenomena of concrete structures. Cracks generated by differential shrinkage could impair the mechanical behavior, increase the permeability of concrete and act as a preferential path for aggressive species, hence leading to an overall decrease in durability and serviceability. It is of great interest to understand the drying shrinkage phenomenon in order to predict and even to control the strains of concrete. The question is whether the results obtained from laboratory samples are in accordance with the measurements on a real structure. Another question concerns the influence of reinforcement on drying shrinkage of concrete. As part of a global project with Andra (French National Radioactive Waste Management Agency), the present study aims to experimentally investigate the scale effect as well as the influence of reinforcement on the development of drying shrinkage of two high performance concretes (based on CEM I and CEM V cements, according to European standards). Various sizes of samples are chosen, from ordinary laboratory specimens up to real-scale specimens: prismatic specimens with different volume-to-surface (V/S) ratios, thin slices (thickness of 2 mm), cylinders with different sizes (37 and 160 mm in diameter), hollow cylinders, cylindrical columns (height of 1000 mm) and square columns (320×320×1000 mm). The square columns have been manufactured with different reinforcement rates and can be considered as mini-structures, to approximate the behavior of a real voussoir from the waste disposal facility. All the samples are kept, in a first stage, at 20°C and 50% of relative humidity (initial conditions in the tunnel) in a specific climatic chamber developed by the Laboratory of Mechanics of Lille. The mass evolution and the drying shrinkage are monitored regularly. The obtained results show that the specimen size has a great impact on water loss and drying shrinkage of concrete. The specimens with a smaller V/S ratio and a smaller size have a bigger drying shrinkage. The correlation between mass variation and drying shrinkage follows the same tendency for all specimens in spite of the size difference. However, the influence of reinforcement rate on drying shrinkage is not clear based on the present results. The second stage of conservation (50°C and 30% of relative humidity) could give additional results on these influences.

Keywords: concrete, drying shrinkage, mass evolution, reinforcement, scale effect

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Authors: Hanwei Gao, Louis Jezequel, Eric Cabrol, Bernard Vitry

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The chassis system is composed of complex elements that take up all the loads from the tire-ground contact area and thus it plays an important role in numerous specifications such as durability, comfort, crash, etc. During the development of new vehicle projects in Renault, durability validation is always the main focus while deployment of comfort comes later in the project. Therefore, sometimes design choices have to be reconsidered because of the natural incompatibility between these two specifications. Besides, robustness is also an important point of concern as it is related to manufacturing costs as well as the performance after the ageing of components like shock absorbers. In this paper an approach is proposed aiming to realize a multi-objective optimization between chassis endurance and comfort while taking the random factors into consideration. The adaptive-sparse polynomial chaos expansion method (PCE) with Chebyshev polynomial series has been applied to predict responses’ uncertainty intervals of a system according to its uncertain-but-bounded parameters. The approach can be divided into three steps. First an initial design of experiments is realized to build the response surfaces which represent statistically a black-box system. Secondly within several iterations an optimum set is proposed and validated which will form a Pareto front. At the same time the robustness of each response, served as additional objectives, is calculated from the pre-defined parameter intervals and the response surfaces obtained in the first step. Finally an inverse strategy is carried out to determine the parameters’ tolerance combination with a maximally acceptable degradation of the responses in terms of manufacturing costs. A quarter car model has been tested as an example by applying the road excitations from the actual road measurements for both endurance and comfort calculations. One indicator based on the Basquin’s law is defined to compare the global chassis durability of different parameter settings. Another indicator related to comfort is obtained from the vertical acceleration of the sprung mass. An optimum set with best robustness has been finally obtained and the reference tests prove a good robustness prediction of Chebyshev PCE method. This example demonstrates the effectiveness and reliability of the approach, in particular its ability to save computational costs for a complex system.

Keywords: chassis durability, Chebyshev polynomials, multi-objective optimization, polynomial chaos expansion, ride comfort, robust design

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Authors: A. M. Tarola, R. Preti, A. M. Girelli, P. Campana

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Safeguarding, studying and enhancing biodiversity play an important and indispensable role in re-launching agriculture. The ancient local varieties are therefore a precious resource for genetic and health improvement. In order to protect biodiversity through the recovery and valorization of autochthonous varieties, in this study we analyzed 12 samples of four ancient apple cultivars representative of Friuli Venezia Giulia, selected by local farmers who work on a project for the recovery of ancient apple cultivars. The aim of this study is to evaluate the polyphenolic profile and the antioxidant capacity that characterize the organoleptic and functional qualities of this fruit species, besides having beneficial properties for health. In particular, for each variety, the following compounds were analyzed, both in the skins and in the pulp: gallic acid, catechin, chlorogenic acid, epicatechin, caffeic acid, coumaric acid, ferulic acid, rutin, phlorizin, phloretin and quercetin to highlight any differences in the edible parts of the apple. The analysis of individual phenolic compounds was performed by High Performance Liquid Chromatography (HPLC) coupled with a diode array UV detector (DAD), the antioxidant capacity was estimated using an in vitro essay based on a Free Radical Scavenging Method and the total phenolic compounds was determined using the Folin-Ciocalteau method. From the results, it is evident that the catechins are the most present polyphenols, reaching a value of 140-200 μg/g in the pulp and of 400-500 μg/g in the skin, with the prevalence of epicatechin. Catechins and phlorizin, a dihydrohalcone typical of apples, are always contained in larger quantities in the peel. Total phenolic compounds content was positively correlated with antioxidant activity in apple pulp (r² = 0,850) and peel (r² = 0,820). Comparing the results, differences between the varieties analyzed and between the edible parts (pulp and peel) of the apple were highlighted. In particular, apple peel is richer in polyphenolic compounds than pulp and flavonols are exclusively present in the peel. In conclusion, polyphenols, being antioxidant substances, have confirmed the benefits of fruit in the diet, especially as a prevention and treatment for degenerative diseases. They demonstrated to be also a good marker for the characterization of different apple cultivars. The importance of protecting biodiversity in agriculture was also highlighted through the exploitation of native products and ancient varieties of apples now forgotten.

Keywords: apple, biodiversity, polyphenols, antioxidant activity, HPLC-DAD, characterization

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