Search results for: combine threshing

Authors: Fikret Yalcinkaya, Hamza Unsal

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To understand how neurons work, it is required to combine experimental studies on neural science with numerical simulations of neuron models in a computer environment. In this regard, the simplicity and applicability of spiking neuron modeling functions have been of great interest in computational neuron science and numerical neuroscience in recent years. Spiking neuron models can be classified by exhibiting various neuronal behaviors, such as spiking and bursting. These classifications are important for researchers working on theoretical neuroscience. In this paper, three different spiking neuron models; Izhikevich, Adaptive Exponential Integrate Fire (AEIF) and Hindmarsh Rose (HR), which are based on first order differential equations, are discussed and compared. First, the physical meanings, derivatives, and differential equations of each model are provided and simulated in the Matlab environment. Then, by selecting appropriate parameters, the models were visually examined in the Matlab environment and it was aimed to demonstrate which model can simulate well-known biological neuron behaviours such as Tonic Spiking, Tonic Bursting, Mixed Mode Firing, Spike Frequency Adaptation, Resonator and Integrator. As a result, the Izhikevich model has been shown to perform Regular Spiking, Continuous Explosion, Intrinsically Bursting, Thalmo Cortical, Low-Threshold Spiking and Resonator. The Adaptive Exponential Integrate Fire model has been able to produce firing patterns such as Regular Ignition, Adaptive Ignition, Initially Explosive Ignition, Regular Explosive Ignition, Delayed Ignition, Delayed Regular Explosive Ignition, Temporary Ignition and Irregular Ignition. The Hindmarsh Rose model showed three different dynamic neuron behaviours; Spike, Burst and Chaotic. From these results, the Izhikevich cell model may be preferred due to its ability to reflect the true behavior of the nerve cell, the ability to produce different types of spikes, and the suitability for use in larger scale brain models. The most important reason for choosing the Adaptive Exponential Integrate Fire model is that it can create rich ignition patterns with fewer parameters. The chaotic behaviours of the Hindmarsh Rose neuron model, like some chaotic systems, is thought to be used in many scientific and engineering applications such as physics, secure communication and signal processing.

Keywords: Izhikevich, adaptive exponential integrate fire, Hindmarsh Rose, biological neuron behaviours, spiking neuron models

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Authors: Glenn Auld Knierim

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Automated robotic winding of high-temperature superconductors (HTS) addresses precision, efficiency, and reliability critical to the commercialization of products. Today’s HTS materials are mature and commercially promising but require manufacturing attention. In particular to the exaggerated rectangular cross-section (very thin by very wide), winding precision is critical to address the stress that can crack the fragile ceramic superconductor (SC) layer and destroy the SC properties. Damage potential is highest during peak operations, where winding stress magnifies operational stress. Another challenge is operational parameters such as magnetic field alignment affecting design performance. Winding process performance, including precision, capability for geometric complexity, and efficient repeatability, are required for commercial production of current HTS. Due to winding limitations, current HTS magnets focus on simple pancake configurations. HTS motors, generators, MRI/NMR, fusion, and other projects are awaiting robotic wound solenoid, planar, and spherical magnet configurations. As with conventional power cables, full transposition winding is required for long length alternating current (AC) and pulsed power cables. Robotic production is required for transposition, periodic swapping of cable conductors, and placing into precise positions, which allows power utility required minimized reactance. A full transposition SC cable, in theory, has no transmission length limits for AC and variable transient operation due to no resistance (a problem with conventional cables), negligible reactance (a problem for helical wound HTS cables), and no long length manufacturing issues (a problem with both stamped and twisted stacked HTS cables). The Infinity Physics team is solving manufacturing problems by developing automated manufacturing to produce the first-ever reliable and utility-grade commercial SC cables and magnets. Robotic winding machines combine mechanical and process design, specialized sense and observer, and state-of-the-art optimization and control sequencing to carefully manipulate individual fragile SCs, especially HTS, to shape previously unattainable, complex geometries with electrical geometry equivalent to commercially available conventional conductor devices.

Keywords: automated winding manufacturing, high temperature superconductor, magnet, power cable

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Authors: Vito Telesca, Giuseppina A. Giorgio, M. Ragosta

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The effects of extreme heat events are increasing in recent years. Humans are forced to adjust themselves to adverse climatic conditions. The impact of weather on human health has become public health significance, especially in light of climate change and rising frequency of devasting weather events (e.g., heat waves and floods). The interest of scientific community is widely known. In particular, the associations between temperature and mortality are well studied. Weather conditions are natural factors that affect the human organism. Recent works show that the temperature threshold at which an impact is seen varies by geographic area and season. These results suggest heat warning criteria should consider local thresholds to account for acclimation to local climatology as well as the seasonal timing of a forecasted heat wave. Therefore, it is very important the problem called ‘local warming’. This is preventable with adequate warning tools and effective emergency planning. Since climate change has the potential to increase the frequency of these types of events, improved heat warning systems are urgently needed. This would require a better knowledge of the full impact of extreme heat on morbidity and mortality. The majority of researchers who analyze the associations between human health and weather variables, investigate the effect of air temperature and bioclimatic indices. These indices combine air temperature, relative humidity, and wind speed and are very important to determine the human thermal comfort. Health impact studies of weather events showed that the prevention is an essential element to dramatically reduce the impact of heat waves. The summer Italian of 2012 was characterized with high average temperatures (con un +2.3°C in reference to the period 1971-2000), enough to be considered as the second hottest summer since 1800. Italy was the first among countries in Europe which adopted tools for to predict these phenomena with 72 hours in advance (Heat Health Watch Warning System - HHWWS). Furthermore, in Italy heat alert criteria relies on the different Indexes, for example Apparent temperature, Scharlau index, Thermohygrometric Index, etc. This study examines the importance of developing public health policies that protect the most vulnerable people (such as the elderly) to extreme temperatures, highlighting the factors that confer susceptibility.

Keywords: heat waves, Italy, local warming, temperature

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Authors: Karen Eastman

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More youths and young adults with autism spectrum disorder (ASD) have been entering the workforce in recent years. Historically, students with ASD struggle after leaving high school and experience lower rates of employment, with social skills continuing to be the most problematic area of concern. Special education teachers may find it challenging to identify effective combinations of evidence-based practices (EBPs) and supports to best guide these students. One EBP, Peer Mediated Instruction and Intervention (PMII) has been well documented in the literature as being effective for younger students with autism but not researched as much with older students and adults, particularly in work settings. A need to combine PMII with other EBPs has been identified as a way to achieve a greater positive impact rather than any practice alone. A multiple baseline across skills design was used in this research project with two participants in different settings. PMII was combined with Visual Supports, with typical peers being trained in both practices. PMII is an evidence-based practice used to address social concerns by training peers without disabilities as to how they can provide feedback to and support, the student with ASD with social interactions in structured settings. The peers without disabilities were the instructors, while the adults facilitated the social situations and provided support to both the peers and students with ASD when needed. Because many individuals with ASD learn best with visual input, rather than using only the spoken word (verbal directions and feedback), Visual Supports were used in conjunction with PMII. Visual Supports can include written words, pictures, symbols, videos, or objects. In this project, the Visual Supports used were written social scripts, videos, Stop and Think signs, written reminder cards, a school map, and a pictorial task analysis of work tasks. Variables that may affect intervention outcomes in this project included attendance at school and school-based work settings for both the students with ASD and the peers without disabilities and behaviors and responses from others in the settings. Qualitative data was also collected from observations and surveys with peers about the process and their role. Data indicated that the students with ASD responded more positively to redirection and support from their peers than to teachers and staff and showed an increase in positive interactions with others. Those surveyed indicated a positive attitude toward and response to the use of peer interventions with visual supports.

Keywords: autism, social skills, vocational training, peer interventions

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Authors: Maria Cherepanova, Svetlana Maximova

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Background And Aims: Suicide is among ten most common causes of death of the working-age population in the world. According to the WHO forecasts, by 2025 suicide will be the third leading cause of death, after cardiovascular diseases and cancer. In 2019, the global suicide rate in the world was 10,5 per 100,000 people. In Russia, the average figure was 11.6. However, in some depressed regions of Russia, such as Buryatia and Altai, it reaches 35.3. The aim of this study was to develop models based on the regional factors of social well-being deprivation that provoke the suicidal risk of various age groups of Russian population. We also investigated suicidal risk prevention in modern Russia, analyzed its efficacy, and developed recommendations for suicidal risk prevention improvement. Methods: In this study, we analyzed the data from sociological surveys from six regions of Russia. Totally we interviewed 4200 people, the age of the respondents was from 16 to 70 years. The results were subjected to factorial and regression analyzes. Results: The results of our study indicate that young people are especially socially vulnerable, which result in ineffective patterns of self-preservation behavior and increase the risk of suicide. That is due to lack of anti-suicidal barriers formation; low importance of vital values; the difficulty or impossibility to achieve basic needs; low satisfaction with family and professional life; and decrease in personal unconditional significance. The suicidal risk of the middle-aged population is due to a decrease in social well-being in the main aspects of life, which determines low satisfaction, decrease in ontological security, and the prevalence of auto-aggressive deviations. The suicidal risk of the elderly population is due to increased factors of social exclusion which result in narrowing the social space and limiting the richness of life. Conclusions: The existing system for lowering suicide risk in modern Russia is predominantly oriented to a medical treatment, which provides only intervention to people who already committed suicide, that significantly limits its preventive effectiveness and social control of this deviation. The national strategy for suicide risk reduction in modern Russian society should combine medical and social activities, designed to minimize possible situations resulting to suicide. The strategy for elimination of suicidal risk should include a systematic and significant improvement of the social well-being of the population and aim at overcoming the basic aspects of social disadvantages such as poverty, unemployment as well as implementing innovative mental health improvement, developing life-saving behavior that will help to counter suicides in Russia.

Keywords: social factors, suicide, prevention, Russia

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Authors: Kayode A. Olaniyi, Olabanji F. Omotoye, Adeola A. Ogunleye

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Computer system components such as the CPU, the Controllers, and the operating system, work together as a team, and storage or memory is the essential parts of this team apart from the processor. The memory and storage system including processor caches, main memory, and storage, form basic storage component of a computer system. The characteristics of the different types of storage are inherent in the design and the technology employed in the manufacturing. These memory characteristics define the speed, compatibility, cost, volatility, and density of the various storage types. Most computers rely on a hierarchy of storage devices for performance. The effective and efficient use of the memory hierarchy of the computer system therefore is the single most important aspect of computer system design and use. The memory hierarchy is becoming a fundamental performance and energy bottleneck, due to the widening gap between the increasing demands of modern computer applications and the limited performance and energy efficiency provided by traditional memory technologies. With the dramatic development in the computers systems, computer storage has had a difficult time keeping up with the processor speed. Computer architects are therefore facing constant challenges in developing high-speed computer storage with high-performance which is energy-efficient, cost-effective and reliable, to intercept processor requests. It is very clear that substantial advancements in redesigning the existing memory physical and logical structures to meet up with the latest processor potential is crucial. This research work investigates the importance of computer memory (storage) hierarchy in the design of computer systems. The constituent storage types of the hierarchy today were investigated looking at the design technologies and how the technologies affect memory characteristics: speed, density, stability and cost. The investigation considered how these characteristics could best be harnessed for overall efficiency of the computer system. The research revealed that the best single type of storage, which we refer to as ideal memory is that logical single physical memory which would combine the best attributes of each memory type that make up the memory hierarchy. It is a single memory with access speed as high as one found in CPU registers, combined with the highest storage capacity, offering excellent stability in the presence or absence of power as found in the magnetic and optical disks as against volatile DRAM, and yet offers a cost-effective attribute that is far away from the expensive SRAM. The research work suggests that to overcome these barriers it may then mean that memory manufacturing will take a total deviation from the present technologies and adopt one that overcomes the associated challenges with the traditional memory technologies.

Keywords: cache, memory-hierarchy, memory, registers, storage

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Authors: Ahlem Dhahri, Waleed Omri, Audrey Becuwe, Abdelwahed Omri

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In industrial processes, decision-making ranges across different scales, from process control to supply chain management. The purchasing decision-making process in the supply chain is presently gaining more attention as a critical contributor to the company's strategic success. Given the scarcity of thorough summaries in the prior studies, this bibliometric analysis aims to adopt a meticulous approach to achieve quantitative knowledge on the constantly evolving subject of purchasing decision-making in supply chain management. Through bibliometric analysis, we examine a sample of 358 peer-reviewed articles from the Scopus database. VOSviewer and Gephi software were employed to analyze, combine, and visualize the data. Data analytic techniques, including citation network, page-rank analysis, co-citation, and publication trends, have been used to identify influential works and outline the discipline's intellectual structure. The outcomes of this descriptive analysis highlight the most prominent articles, authors, journals, and countries based on their citations and publications. The findings from the research illustrate an increase in the number of publications, exhibiting a slightly growing trend in this field. Co-citation analysis coupled with content analysis of the most cited articles identified five research themes mentioned as follows integrating sustainability into the supplier selection process, supplier selection under disruption risks assessment and mitigation strategies, Fuzzy MCDM approaches for supplier evaluation and selection, purchasing decision in vendor problems, decision-making techniques in supplier selection and order lot sizing problems. With the help of a graphic timeline, this exhaustive map of the field illustrates a visual representation of the evolution of publications that demonstrate a gradual shift from research interest in vendor selection problems to integrating sustainability in the supplier selection process. These clusters offer insights into a wide variety of purchasing methods and conceptual frameworks that have emerged; however, they have not been validated empirically. The findings suggest that future research would emerge with a greater depth of practical and empirical analysis to enrich the theories. These outcomes provide a powerful road map for further study in this area.

Keywords: bibliometric analysis, citation analysis, co-citation, Gephi, network analysis, purchasing, SCM, VOSviewer

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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: Tefera Kebede Leyu

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The purpose of this study was to estimate the impact of LIVES project participation on the level of technical efficiency of farm households in three regions of Ethiopia. We used household-level data gathered by IRLI between February and April 2014 for the year 2013(retroactive). Data on 1,905 (754 intervention and 1, 151 control groups) sample households were analyzed using STATA software package version 14. Efforts were made to combine stochastic frontier modeling with impact evaluation methodology using the Heckman (1979) two-stage model to deal with possible selectivity bias arising from unobservable characteristics in the stochastic frontier model. Results indicate that farmers in the two groups are not efficient and operate below their potential frontiers i.e., there is a potential to increase crop productivity through efficiency improvements in both groups. In addition, the empirical results revealed selection bias in both groups of farmers confirming the justification for the use of selection bias corrected stochastic frontier model. It was also found that intervention farmers achieved higher technical efficiency scores than the control group of farmers. Furthermore, the selectivity bias-corrected model showed a different technical efficiency score for the intervention farmers while it more or less remained the same for that of control group farmers. However, the control group of farmers shows a higher dispersion as measured by the coefficient of variation compared to the intervention counterparts. Among the explanatory variables, the study found that farmer’s age (proxy to farm experience), land certification, frequency of visit to improved seed center, farmer’s education and row planting are important contributing factors for participation decisions and hence technical efficiency of farmers in the study areas. We recommend that policies targeting the design of development intervention programs in the agricultural sector focus more on providing farmers with on-farm visits by extension workers, provision of credit services, establishment of farmers’ training centers and adoption of modern farm technologies. Finally, we recommend further research to deal with this kind of methodological framework using a panel data set to test whether technical efficiency starts to increase or decrease with the length of time that farmers participate in development programs.

Keywords: impact evaluation, efficiency analysis and selection bias, stochastic frontier model, Heckman-two step

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Authors: Inas Hussein

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Communication in the modern world is increasingly becoming multimodal due to globalization and the digital space we live in which have remarkably affected how people communicate. Accordingly, Multimodal Discourse Analysis (MDA) is an emerging paradigm in discourse studies with the underlying assumption that other semiotic resources such as images, colours, scientific symbolism, gestures, actions, music and sound, etc. combine with language in order to  communicate meaning. One of the effective multimodal media that combines both verbal and non-verbal elements to create meaning is political cartoons. Furthermore, since political and social issues are mirrored in political cartoons, these are regarded as potential objects of discourse analysis since they not only reflect the thoughts of the public but they also have the power to influence them. The aim of this paper is to analyze some selected cartoons on the recognition of Jerusalem as Israel's capital by the American President, Donald Trump, adopting a multimodal approach. More specifically, the present research examines how the various semiotic tools and resources utilized by the cartoonists function in projecting the intended meaning. Ten political cartoons, among a surge of editorial cartoons highlighted by the Anti-Defamation League (ADL) - an international Jewish non-governmental organization based in the United States - as publications in different Arabic-language newspapers in Egypt, Saudi Arabia, UAE, Oman, Iran and UK, were purposively selected for semiotic analysis. These editorial cartoons, all published during 6^th–18^th December 2017, invariably suggest one theme: Jewish and Israeli domination of the United States. The data were analyzed using the framework of Visual Social Semiotics. In accordance with this methodological framework, the selected visual compositions were analyzed in terms of three aspects of meaning: representational, interactive and compositional. In analyzing the selected cartoons, an interpretative approach is being adopted. This approach prioritizes depth to breadth and enables insightful analyses of the chosen cartoons. The findings of the study reveal that semiotic resources are key elements of political cartoons due to the inherent political communication they convey. It is proved that adequate interpretation of the three aspects of meaning is a prerequisite for understanding the intended meaning of political cartoons. It is recommended that further research should be conducted to provide more insightful analyses of political cartoons from a multimodal perspective.

Keywords: Multimodal Discourse Analysis (MDA), multimodal text, political cartoons, visual modality

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Authors: M. Ekiert, T. Uhl, A. Mlyniec

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Tendons are the biological soft tissue structures composed of collagen, proteoglycan, glycoproteins, water and cells of extracellular matrix (ECM). Tendons, which primary function is to transfer force generated by the muscles to the bones causing joints movement, are exposed to many micro and macro damages. In fact, tendons and ligaments trauma are one of the most numerous injuries of human musculoskeletal system, causing for many people (particularly for athletes and physically active people), recurring disorders, chronic pain or even inability of movement. The number of tendons reconstruction and transplantation procedures is increasing every year. Therefore, studies on soft tissues storage conditions (influencing i.e. tissue aging) seem to be an extremely important issue. In this study, an atomic-scale investigation on the kinetics of decomposition of two selected tendon components – collagen type I (which forms a 60-85% of a tendon dry mass) and elastin protein (which combine with ECM creates elastic fibers of connective tissues) is presented. A molecular model of collagen and elastin was developed based on crystal structure of triple-helical collagen-like 1QSU peptide and P15502 human elastin protein, respectively. Each model employed 4 linear strands collagen/elastin strands per unit cell, distributed in 2x2 matrix arrangement, placed in simulation box filled with water molecules. A decomposition phenomena was simulated with molecular dynamics (MD) method using ReaxFF force field and periodic boundary conditions. A set of NVT-MD runs was performed for 1000K temperature range in order to obtained temperature-depended rate of production of decomposition by-products. Based on calculated reaction rates activation energies and pre-exponential factors, required to formulate Arrhenius equations describing kinetics of decomposition of tested soft tissue components, were calculated. Moreover, by adjusting a model developed for collagen, system scalability and correct implementation of the periodic boundary conditions were evaluated. An obtained results provide a deeper insight into decomposition of selected tendon components. A developed methodology may also be easily transferred to other connective tissue elements and therefore might be used for further studies on soft tissues aging.

Keywords: decomposition, molecular dynamics, soft tissue, tendons

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Authors: Lucrezia Crescenzi-Lanna, Silvia Cataldi, Williams Contreras, Valerio Pieri

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According to the European Commission, gender-based violence (GBV) is a violation of human rights and a form of discrimination against women in five areas: physical violence, sexual violence, psychological violence, mistreatment of women, and economic violence (henceforth EV). The TESORO project "Treatment, ExpoSition, and ORigin of economic viOlence: An innovation and internationalization project between Italy and Spain" focuses on this last dimension of gender-based violence, the least studied and the one that has received least media coverage. In Spain, 12% (2,350,684) of women over fifteen years of age have suffered economic violence from their partner or ex-partner during their lives. In Italy, another country participating in the project, many women who are welcomed in refuges and who report cases of psychological violence (79%) and/or physical violence (61%) are also victims of economic violence (34%), according to the D.i.Re. Thermometer: "Donne in Rete contro la Violenza", the association that brings together more than eighty refuges against violence in Italy. At the social level, this form of violence is incorporated into practices of inequality that manifest themselves in both the daily management of couples and families and the workplace and institutional settings. As for the mechanisms related to EV, the literature argues that it is a complex and multidimensional phenomenon that has socioeconomic and cultural roots. EV manifests itself through various strategies, which represent forms of power and control aimed at preventing women's financial independence. To analyse the issue of EV we use a multidisciplinary approach and a mixed design that includes: 1) a questionnaire administered to a stratified sample of more than a thousand Italian and Spanish citizens to study the cultural and socio-relational mechanisms and the origin of EV in family and couple contexts; and 2) interviews with those running refuges as part of the struggle against gender violence, to understand how mechanisms and educational activities in the field of economic violence are manifested in the respective region and are supportive of women. The decision to use this strategy responds to the need to combine an exploratory perspective with an explanatory one in order to understand some of the relevant concepts related to the complex phenomena of EV and the interventions dedicated to its prevention. The data will be finalized in June 2022 and presented at the ICWS conference. Among TESORO’s contributions, its collection of qualitative and quantitative data on EV in Italy and Spain stands out, deepening its origin, prevention, and treatment beyond its incidence, which has already been studied in the Macro-Survey on Violence against Women.

Keywords: gender-based violence, economic violence, economic harm, gender inequality, workplace and family contexts

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Authors: Viviana Ventre, Giacomo Di Tollo, Roberta Martino

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The portfolio selection problem includes the evaluation of many criteria that are difficult to compare directly and is characterized by uncertain elements. The portfolio selection problem can be modeled as a group decision problem in which several experts are invited to present their assessment. In this context, it is important to study and analyze the process of reaching a consensus among group members. Indeed, due to the various diversities among experts, reaching consensus is not necessarily always simple and easily achievable. Moreover, the concept of consensus is accompanied by the concept of false consensus, which is particularly interesting in the dynamics of group decision-making processes. False consensus can alter the evaluation and selection phase of the alternative and is the consequence of the decision maker's inability to recognize that his preferences are conditioned by subjective structures. The present work aims to investigate the dynamics of consensus attainment in a group decision problem in which equivalent portfolios are proposed. In particular, the study aims to analyze the impact of the subjective structure of the decision-maker during the evaluation and selection phase of the alternatives. Therefore, the experimental framework is divided into three phases. In the first phase, experts are sent to evaluate the characteristics of all portfolios individually, without peer comparison, arriving independently at the selection of the preferred portfolio. The experts' evaluations are used to obtain individual Analytical Hierarchical Processes that define the weight that each expert gives to all criteria with respect to the proposed alternatives. This step provides insight into how the decision maker's decision process develops, step by step, from goal analysis to alternative selection. The second phase includes the description of the decision maker's state through Markov chains. In fact, the individual weights obtained in the first phase can be reviewed and described as transition weights from one state to another. Thus, with the construction of the individual transition matrices, the possible next state of the expert is determined from the individual weights at the end of the first phase. Finally, the experts meet, and the process of reaching consensus is analyzed by considering the single individual state obtained at the previous stage and the false consensus bias. The work contributes to the study of the impact of subjective structures, quantified through the Analytical Hierarchical Process, and how they combine with the false consensus bias in group decision-making dynamics and the consensus reaching process in problems involving the selection of equivalent portfolios.

Keywords: analytical hierarchical process, consensus building, false consensus effect, markov chains, portfolio selection problem

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Authors: Aleksandr Kavetskiy, Galina Yakubova, Nikolay Sargsyan, Stephen A. Prior, H. Allen Torbert

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Determining soil elemental content and distribution (mapping) within a field are key features of modern agricultural practice. While traditional chemical analysis is a time consuming and labor-intensive multi-step process (e.g., sample collections, transport to laboratory, physical preparations, and chemical analysis), neutron-gamma soil analysis can be performed in-situ. This analysis is based on the registration of gamma rays issued from nuclei upon interaction with neutrons. Soil elements such as Si, C, Fe, O, Al, K, and H (moisture) can be assessed with this method. Data received from analysis can be directly used for creating soil elemental distribution maps (based on ArcGIS software) suitable for agricultural purposes. The neutron-gamma analysis system developed for field application consisted of an MP320 Neutron Generator (Thermo Fisher Scientific, Inc.), 3 sodium iodide gamma detectors (SCIONIX, Inc.) with a total volume of 7 liters, 'split electronics' (XIA, LLC), a power system, and an operational computer. Paired with GPS, this system can be used in the scanning mode to acquire gamma spectra while traversing a field. Using acquired spectra, soil elemental content can be calculated. These data can be combined with geographical coordinates in a geographical information system (i.e., ArcGIS) to produce elemental distribution maps suitable for agricultural purposes. Special software has been developed that will acquire gamma spectra, process and sort data, calculate soil elemental content, and combine these data with measured geographic coordinates to create soil elemental distribution maps. For example, 5.5 hours was needed to acquire necessary data for creating a carbon distribution map of an 8.5 ha field. This paper will briefly describe the physics behind the neutron gamma analysis method, physical construction the measurement system, and main characteristics and modes of work when conducting field surveys. Soil elemental distribution maps resulting from field surveys will be presented. and discussed. Comparison of these maps with maps created on the bases of chemical analysis and soil moisture measurements determined by soil electrical conductivity was similar. The maps created by neutron-gamma analysis were reproducible, as well. Based on these facts, it can be asserted that neutron stimulated soil gamma spectroscopy paired with GPS system is fully applicable for soil elemental agricultural field mapping.

Keywords: ArcGIS mapping, neutron gamma analysis, soil elemental content, soil gamma spectroscopy

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Authors: Philippe Gugler

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The aim of this study is to investigate how home country patterns may influence the competitiveness of EMNEs in international markets and more specifically their ability to invest abroad. The study examines the dynamic relationship between home country specific advantage and firms’ competitiveness. Are EMNEs still driven by strong country specific advantages or are EMNEs increasingly relying on their own firm specific competitiveness? EMNEs are not commonly recognized as a ‘homogeneous group’. Therefore, the approaches to these questions need to be specific while still attempting to extract some common evidence. The aim of the study is to elaborate a framework to investigate this issue in a dynamic context of international business’s strategies. The study focuses on two major research questions. The first one relates to the role of the home-base context in the internationalization process of EMNEs and more specifically the home-base assets’ influence on EMNEs competitiveness. Another question is to investigate the interactions among home-base context, recipient country context and EMNEs competitiveness. The evolution of EMNEs’ competitiveness is shaped by the evolution of the home country’s business environment. The nature of the home-based components in EMNEs’ specific advantages has changed over time due to the increased integration of emerging countries in the world market and the inherent changes related to their institutional, structural and regulatory patterns. The home country offers not only inherited assets but also a productive business environment, allowing firms to innovate, be more productive, create unique value for customers and finally, to face international competition successfully. The more sophisticated the home business environment is, the more opportunities there are for firms to developed exclusive and unique competitive assets. The international expansion of EMNEs is a fascinating but challenging issue. Among the numerous questions raised by the involvement of EMNEs in international competition is the evolving role of the home market. The purpose of this study is to examine some of the theoretical ideas and empirical evidence to allow us to deepen our understanding of the role of emerging home countries in the internationalization process of their domestic firms and more specifically in their ability to compete successfully abroad. How much do home specific assets still influence EMNEs’ foreign investment? Which home country assets provide the main competitive drivers to invest and compete abroad? How do EMNEs combine home country assets and host country assets to strengthen their competitive advantages? These questions as well as various others deserve further examination by the scientific community.

Keywords: competitiveness, emerging countries' multinational enterprises, foreign direct investments, international business

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Authors: Kumar Divyendra

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Underwater Sensor Networks (UWSNs) have wide applications in areas such as water quality monitoring, marine wildlife management etc. A typical UWSN system consists of a set of sensors deployed randomly underwater which communicate with each other using acoustic links. RF communication doesn't work underwater, and GPS too isn't available underwater. Additionally Automated Underwater Vehicles (AUVs) are deployed to collect data from some special nodes called Cluster Heads (CHs). These CHs aggregate data from their neighboring nodes and forward them to the AUVs using optical links when an AUV is in range. This helps reduce the number of hops covered by data packets and helps conserve energy. We consider the three-dimensional model of the UWSN. Nodes are initially deployed randomly underwater. They attach themselves to the surface using a rod and can only move upwards or downwards using a pump and bladder mechanism. We use graph theory concepts to maximize the coverage volume while every node maintaining connectivity with at least one surface node. We treat the surface nodes as landmarks and each node finds out its hop distance from every surface node. We treat these hop-distances as coordinates and use them for AUV navigation. An AUV intending to move closer to a node with given coordinates moves hop by hop through nodes that are closest to it in terms of these coordinates. In absence of GPS, multiple different approaches like Inertial Navigation System (INS), Doppler Velocity Log (DVL), computer vision-based navigation, etc., have been proposed. These systems have their own drawbacks. INS accumulates error with time, vision techniques require prior information about the environment. We propose a method that makes use of the earth's magnetic field values for navigation and combines it with other methods that simultaneously increase the coverage volume under the UWSN. The AUVs are fitted with magnetometers that measure the magnetic intensity (I), horizontal inclination (H), and Declination (D). The International Geomagnetic Reference Field (IGRF) is a mathematical model of the earth's magnetic field, which provides the field values for the geographical coordinateson earth. Researchers have developed an inverse deep learning model that takes the magnetic field values and predicts the location coordinates. We make use of this model within our work. We combine this with with the hop-by-hop movement described earlier so that the AUVs move in such a sequence that the deep learning predictor gets trained as quickly and precisely as possible We run simulations in MATLAB to prove the effectiveness of our model with respect to other methods described in the literature.

Keywords: clustering, deep learning, network backbone, parallel computing

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Authors: Joao Ferreira Do Rosario, Nuno Gustavo, Ana Machado, Lurdes Calisto, Luisa Carvalho, Georgette Andraz

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Currently, tourism small and medium enterprises (TSMEs) face serious economic and financial problems, making recovery efforts difficult. How the pandemic will affect tourists' behavior is still to be known. Will tourists be even more cautious regarding their choices or, on the contrary, will they be more adventurers with an enormous desire to travel in search of the lost freedom? Tourists may become even more demanding when traveling, more austere, or less concerned and eager to socialize. Adjusting to this "new tourist" is an added challenge for tourism service providers. Generation Z made up of individuals born in 1995 and following years, currently tends to assume a particular role and meaning in the present and future economic and social context, considering that we are facing the youngest workforce as well as tomorrow's consumers. This generation is distinguished from others as it is the first generation to combine a high level of education and technological knowledge and to fully experience the digital world. These young people are framed by a new value system that can explain new behaviours and consumption, namely, in the context of tourism. All these considerations point to the importance of investigating this target group as it is essential to understand how these individuals perceive, understand, act, and can be involved in a new environment built around a society regulated by new priorities and challenges of a sustainable nature. This leads not only to a focus on short-term market choices but mainly to predict future choices from a longer-term perspective. Together with the social background of a person, values are considered a stable antecedent of behavior and might therefore predict not just immediate, but also future choices. Furthermore, the meaning attributed to travel has a general connotation and goes beyond a specific travel choice or experience. In other words, values and travel's meaning form a chain of influences on the present and future travel behavior. This study explores the social background and values of Generation Z travelers vs the meaning these tourists give to travel. The aim is to discover in their present behavior cues to predict travel choices so that the future of tourism can be secured. This study also provides data for predicting the tourism choices of youngsters in the more immediate future. Methodologically, a quantitative approach was adopted based on the collection of data through a survey. Since academic research on Generation Z of tourists is still scarce, it is expected to contribute to deepening scientific knowledge in this area. Furthermore, it is expected that this research will support tourism professionals in defining differentiated marketing strategies and adapted to the requirements of this target, in a new time.

Keywords: Generation Z, travel behavior, travel meaning, Generation Z Values

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Authors: Ana Teixeira, Joao Orvalho

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This paper describes experiments using Scratch games, to check the feasibility of employing cerebral palsy users gestures as an alternative of interaction with a computer carried out by students of Master Human Computer Interaction (HCI) of IPC Coimbra. The main focus of this work is to study the usability of a Web Camera as a motion tracking device to achieve a virtual human-computer interaction used by individuals with CP. An approach for Human-computer Interaction (HCI) is present, where individuals with cerebral palsy react and interact with a scratch game through the use of a webcam as an external interaction device. Motion tracking interaction is an emerging technology that is becoming more useful, effective and affordable. However, it raises new questions from the HCI viewpoint, for example, which environments are most suitable for interaction by users with disabilities. In our case, we put emphasis on the accessibility and usability aspects of such interaction devices to meet the special needs of people with disabilities, and specifically people with CP. Despite the fact that our work has just started, preliminary results show that, in general, computer vision interaction systems are very useful; in some cases, these systems are the only way by which some people can interact with a computer. The purpose of the experiments was to verify two hypothesis: 1) people with cerebral palsy can interact with a computer using their natural gestures, 2) scratch games can be a research tool in experiments with disabled young people. A game in Scratch with three levels is created to be played through the use of a webcam. This device permits the detection of certain key points of the user’s body, which allows to assume the head, arms and specially the hands as the most important aspects of recognition. Tests with 5 individuals of different age and gender were made throughout 3 days through periods of 30 minutes with each participant. For a more extensive and reliable statistical analysis, the number of both participants and repetitions in further investigations should be increased. However, already at this stage of research, it is possible to draw some conclusions. First, and the most important, is that simple scratch games on the computer can be a research tool that allows investigating the interaction with computer performed by young persons with CP using intentional gestures. Measurements performed with the assistance of games are attractive for young disabled users. The second important conclusion is that they are able to play scratch games using their gestures. Therefore, the proposed interaction method is promising for them as a human-computer interface. In the future, we plan to include the development of multimodal interfaces that combine various computer vision devices with other input devices improvements in the existing systems to accommodate more the special needs of individuals, in addition, to perform experiments on a larger number of participants.

Keywords: motion tracking, cerebral palsy, rehabilitation, HCI

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Authors: Mujahid Muhammad, Paul Kearney, Adel Aneiba

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The ability for vehicles to communicate with other vehicles (V2V), the physical (V2I) and network (V2N) infrastructures, pedestrians (V2P), etc. – collectively known as V2X (Vehicle to Everything) – will enable a broad and growing set of applications and services within the intelligent transport domain for improving road safety, alleviate traffic congestion and support autonomous driving. The telecommunication research and industry communities and standardization bodies (notably 3GPP) has finally approved in Release 14, cellular communications connectivity to support V2X communication (known as LTE – V2X). LTE – V2X system will combine simultaneous connectivity across existing LTE network infrastructures via LTE-Uu interface and direct device-to-device (D2D) communications. In order for V2X services to function effectively, a robust security mechanism is needed to ensure legal and safe interaction among authenticated V2X entities in the LTE-based V2X architecture. The characteristics of vehicular networks, and the nature of most V2X applications, which involve human safety makes it significant to protect V2X messages from attacks that can result in catastrophically wrong decisions/actions include ones affecting road safety. Attack vectors include impersonation attacks, modification, masquerading, replay, MiM attacks, and Sybil attacks. In this paper, we focus our attention on LTE-based V2X security and access control mechanisms. The current LTE-A security framework provides its own access authentication scheme, the AKA protocol for mutual authentication and other essential cryptographic operations between UEs and the network. V2N systems can leverage this protocol to achieve mutual authentication between vehicles and the mobile core network. However, this protocol experiences technical challenges, such as high signaling overhead, lack of synchronization, handover delay and potential control plane signaling overloads, as well as privacy preservation issues, which cannot satisfy the adequate security requirements for majority of LTE-based V2X services. This paper examines these challenges and points to possible ways by which they can be addressed. One possible solution, is the implementation of the distributed peer-to-peer LTE security mechanism based on the Bitcoin/Namecoin framework, to allow for security operations with minimal overhead cost, which is desirable for V2X services. The proposed architecture can ensure fast, secure and robust V2X services under LTE network while meeting V2X security requirements.

Keywords: authentication, long term evolution, security, vehicle-to-everything

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Authors: Andrea Giacomelli, Luciano Massetti, Elena Maggi, Antonio Raschi

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The presentation will report the activities managed during the Summer of 2017 by a team composed by staff from a University Department, a National Research Council Institute, and an outreach NGO, collecting measurements of night sky brightness and other information on artificial lighting, in order to characterize light pollution issues on portions of the Tuscan coast, in Central Italy. These activities combine measurements collected by the principal scientists, citizen science observations led by students, and outreach events targeting a broad audience. This campaign aggregates the efforts of three actors: the BuioMetria Partecipativa project, which started collecting light pollution data on a national scale in 2008 with an environmental engineering and free/open source GIS core team; the Institute of Biometeorology from the National Research Council, with ongoing studies on light and urban vegetation and a consolidated track record in environmental education and citizen science; the Department of Biology from the University of Pisa, which started experiments to assess the impact of light pollution in coastal environments in 2015. While the core of the activities concerns in situ data, the campaign will account also for remote sensing data, thus considering heterogeneous data sources. The aim of the campaign is twofold: (1) To test actions of citizen and student engagement in monitoring sky brightness (2) To collect night sky brightness data and test a protocol for applications to studies on the ecological impact of light pollution, with a special focus on marine coastal ecosystems. The collaboration of an interdisciplinary team in the study of artificial lighting issues is not a common case in Italy, and the possibility of undertaking the campaign in Tuscany has the added value of operating in one of the territories where it is possible to observe both sites with extremely high lighting levels, and areas with extremely low light pollution, especially in the Southern part of the region. Combining environmental monitoring and communication actions in the context of the campaign, this effort will contribute to the promotion of night skies with a good quality as an important asset for the sustainability of coastal ecosystems, as well as to increase citizen awareness through star gazing, night photography and actively participating in field campaign measurements.

Keywords: citizen science, light pollution, marine coastal biodiversity, environmental education

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Authors: Xiangtuo Chen, Paul-Henry Cournéde

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Crop yield prediction is a paramount issue in agriculture. The main idea of this paper is to find out efficient way to predict the yield of corn based meteorological records. The prediction models used in this paper can be classified into model-driven approaches and data-driven approaches, according to the different modeling methodologies. The model-driven approaches are based on crop mechanistic modeling. They describe crop growth in interaction with their environment as dynamical systems. But the calibration process of the dynamic system comes up with much difficulty, because it turns out to be a multidimensional non-convex optimization problem. An original contribution of this paper is to propose a statistical methodology, Multi-Scenarios Parameters Estimation (MSPE), for the parametrization of potentially complex mechanistic models from a new type of datasets (climatic data, final yield in many situations). It is tested with CORNFLO, a crop model for maize growth. On the other hand, the data-driven approach for yield prediction is free of the complex biophysical process. But it has some strict requirements about the dataset. A second contribution of the paper is the comparison of these model-driven methods with classical data-driven methods. For this purpose, we consider two classes of regression methods, methods derived from linear regression (Ridge and Lasso Regression, Principal Components Regression or Partial Least Squares Regression) and machine learning methods (Random Forest, k-Nearest Neighbor, Artificial Neural Network and SVM regression). The dataset consists of 720 records of corn yield at county scale provided by the United States Department of Agriculture (USDA) and the associated climatic data. A 5-folds cross-validation process and two accuracy metrics: root mean square error of prediction(RMSEP), mean absolute error of prediction(MAEP) were used to evaluate the crop prediction capacity. The results show that among the data-driven approaches, Random Forest is the most robust and generally achieves the best prediction error (MAEP 4.27%). It also outperforms our model-driven approach (MAEP 6.11%). However, the method to calibrate the mechanistic model from dataset easy to access offers several side-perspectives. The mechanistic model can potentially help to underline the stresses suffered by the crop or to identify the biological parameters of interest for breeding purposes. For this reason, an interesting perspective is to combine these two types of approaches.

Keywords: crop yield prediction, crop model, sensitivity analysis, paramater estimation, particle swarm optimization, random forest

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Authors: Kobauri Sophio, Kantaria Tengiz, Tugushi David, Puiggali Jordi, Katsarava Ramaz

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Biodegradable biomaterials (BB) are of high interest for numerous applications in modern medicine as resorbable surgical materials and drug delivery systems. This kind of materials can be cleared from the body after the fulfillment of their function that excludes a surgical intervention for their removal. One of the most promising BBare amino acids based biodegradable poly(ester amide)s (PEAs) which are composed of naturally occurring (α-amino acids) and non-toxic building blocks such as fatty diols and dicarboxylic acids. Key bis-nucleophilic monomers for synthesizing the PEAs are diamine-diesters-di-p-toluenesulfonic acid salts of bis-(α-amino acid)-alkylenediesters (TAADs) which form the PEAs after step-growth polymerization (polycondensation) with bis-electrophilic counter-partners - activated diesters of dicarboxylic acids. The PEAs combine all advantages of the 'parent polymers' – polyesters (PEs) and polyamides (PAs): Ability of biodegradation (PEs), a high affinity with tissues and a wide range of desired mechanical properties (PAs). The scopes of applications of thePEAs can substantially be expanded by their functionalization, e.g. through the incorporation of hydrophobic fragments into the polymeric backbones. Hydrophobically modified PEAs can form non-covalent adducts with various compounds that make them attractive as drug carriers. For hydrophobic modification of the PEAs, we selected so-called 'Azlactone Method' based on the application of p-phenylene-bis-oxazolinons (bis-azlactones, BALs) as active bis-electrophilic monomers in step-growth polymerization with TAADs. Interaction of BALs with TAADs resulted in the PEAs with low MWs (Mw2,800-19,600 Da) and poor material properties. The high-molecular-weight PEAs (Mw up to 100,000) with desirable material properties were synthesized after replacement of a part of BALs with activated diester - di-p-nitrophenylsebacate, or a part of TAAD with alkylenediamine – 1,6-hexamethylenediamine. The new hydrophobically modified PEAs were characterized by FTIR, NMR, GPC, and DSC. It was shown that after the hydrophobic modification the PEAs retain the biodegradability (in vitro study catalyzed by α-chymptrypsin and lipase), and are of interest for constructing resorbable surgical and pharmaceutical devices including drug delivering containers such as microspheres. The new PEAs are insoluble in hydrophobic organic solvents such as chloroform or dichloromethane (swell only) that allowed elaborating a new technology of fabricating microspheres.

Keywords: amino acids, biodegradable polymers, bis-azlactones, microspheres

Procedia PDF Downloads 175

Authors: Deanne McArthur, Melinda Wall, Claire Hanlon, Dana Agnolin, Krista Davis, Melanie Dennis, Elizabeth Glidden, Anne Marie Smith, Claudette Thomson

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Background and significance: Patients with eating disorders have traditionally been an underserviced population within the publicly-funded Canadian healthcare system. This situation was worsened by the COVID-19 pandemic and accompanying public health measures, such as “lockdowns” which led to increased isolation, changes in routine, and other disruptions. Illness severity and prevalence rose significantly with corresponding increases in patient suffering and poor outcomes. In Ontario, Canada, the provincial government responded by increasing funding for the treatment of eating disorders, including the launch of a new day program at an intermediate, regional health centre that already housed an outpatient treatment service. The funding was received in March 2022. The care team sought to optimize this opportunity by designing a program that would fit well within the resource-constrained context in Ontario. Methods: This case study will detail how the team consulted the literature and sought patient and family input to design a program that optimizes patient outcomes and supports for patients and families while they await treatment. Early steps include a review of the literature, expert consultation and patient and family focus groups. Interprofessional consensus was sought at each step with the team adopting a shared leadership and patient-centered approach. Methods will include interviews, observations and document reviews to detail a rich description of the process undertaken to design the program, including evaluation measures adopted. Interim findings pertaining to the early stages of the program-building process will be detailed as well as early lessons and ongoing evolution of the program and design process. Program implementation and outcome evaluation will continue throughout 2022 and early 2023 with further publication and presentation of study results expected in the summer of 2023. The aim of this study is to contribute to the body of knowledge pertaining to the design and implementation of eating disorder treatment services that combine outpatient and day treatment services in a resource-constrained context.

Keywords: eating disorders, day program, interprofessional, outpatient, adolescents, transitional aged youth

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Authors: Beatriz Garcia-Juan, Ana B. Escrig-Tena, Vicente Roca-Puig

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The aim of this article is to conduct a theoretical and empirical study in order to examine how the goal orientation (GO) of public employees affects the relationship between the structural and psychological empowerment that they experience at their workplaces. In doing so, we follow structural empowerment (SE) and psychological empowerment (PE) conceptualizations, and relate them to the public administration framework. Moreover, we review arguments from GO theories, and previous related contributions. Empowerment has emerged as an important issue in the public sector organization setting in the wake of mainstream New Public Management (NPM), the new orientation in the public sector that aims to provide a better service for citizens. It is closely linked to the drive to improve organizational effectiveness through the wise use of human resources. Nevertheless, it is necessary to combine structural (managerial) and psychological (individual) approaches in an integrative study of empowerment. SE refers to a set of initiatives that aim the transference of power from managerial positions to the rest of employees. PE is defined as psychological state of competence, self-determination, impact, and meaning that an employee feels at work. Linking these two perspectives will lead to arrive at a broader understanding of the empowerment process. Specifically in the public sector, empirical contributions on this relationship are therefore important, particularly as empowerment is a very useful tool with which to face the challenges of the new public context. There is also a need to examine the moderating variables involved in this relationship, as well as to extend research on work motivation in public management. It is proposed the study of the effect of individual orientations, such as GO. GO concept refers to the individual disposition toward developing or confirming one’s capacity in achievement situations. Employees’ GO may be a key factor at work and in workforce selection processes, since it explains the differences in personal work interests, and in receptiveness to and interpretations of professional development activities. SE practices could affect PE feelings in different ways, depending on employees’ GO, since they perceive and respond differently to such practices, which is likely to yield distinct PE results. The model is tested on a sample of 521 Spanish local authority employees. Hierarchical regression analysis was conducted to test the research hypotheses using SPSS 22 computer software. The results do not confirm the direct link between SE and PE, but show that learning goal orientation has considerable moderating power in this relationship, and its interaction with SE affects employees’ PE levels. Therefore, the combination of SE practices and employees’ high levels of LGO are important factors for creating psychologically empowered staff in public organizations.

Keywords: goal orientation, moderating effect, psychological empowerment, structural empowerment

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Authors: Happy Kumar Das, Md. Shahriar Shafiq

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This paper portrays an assumed change in the primary teacher education program in Bangladesh. An initiative has been taken with a vision to ensure an integrated approach to developing trainee teachers’ knowledge and understanding about learning at a deeper level, and with that aim, the Diploma in Primary Education (DPEd) program replaces the Certificate-in-Education (C-in-Ed) program in Bangladeshi context for primary teachers. The stated professional values of the existing program such as ‘learner-centered’, ‘reflective’ approach to pedagogy tend to contradict the practice exemplified through the delivery mechanism. To address the challenges, through the main two components (i) Training Institute-based learning and (ii) School-based learning, the new program tends to cover knowledge and value that underpin the actual practice of teaching. These two components are given approximately equal weighting within the program in terms of both time, content and assessment as the integration seeks to combine theoretical knowledge with practical knowledge and vice versa. The curriculum emphasizes a balance between the taught modules and the components of the practicum. For example, the theories of formative and summative assessment techniques are elaborated through focused reflection on case studies as well as observation and teaching practice in the classroom. The key ideology that is reflected through this newly developed program is teacher’s belief in ‘holistic education’ that can lead to creating opportunities for skills development in all three (Cognitive, Social and Affective) domains simultaneously. The proposed teacher education program aims to address these areas of generic skill development alongside subject-specific learning outcomes. An exploratory study has been designed in this regard where 7 Primary Teachers’ Training Institutes (PTIs) in 7 divisions of Bangladesh was used for experimenting DPEd program. The analysis was done based on document analysis, periodical monitoring report and empirical data gathered from the experimental PTIs. The findings of the study revealed that the intervention brought positive change in teachers’ professional beliefs, attitude and skills along with improvement of school environment. Teachers in training schools work together for collective professional development where they support each other through lesson study, action research, reflective journals, group sharing and so on. Although the DPEd program addresses the above mentioned factors, one of the challenges of the proposed program is the issue of existing capacity and capabilities of the PTIs towards its effective implementation.

Keywords: Bangladesh, effective implementation, primary teacher education, reflective approach

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Authors: Mmbulaheni Ramulondi, Sandy Van Vuuren, Helene De Wet

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The use of plant combinations to treat various medical conditions is not a new concept, and it is known that traditional people do not only rely on a single plant extract for efficacy but often combine various plant species for treatment. The knowledge of plant combinations is transferred from one generation to the other in the belief that combination therapy may enhance efficacy, reduce toxicity, decreases adverse effects, increase bioavailability and result in lower dosages. However, combination therapy may also be harmful when the interaction is antagonistic, since it may result in increasing toxicity. Although a fair amount of research has been done on the toxicity of medicinal plants, there is very little done on the toxicity of medicinal plants in combination. The aim of the study was to assess the toxicity potential of 19 plant combinations which have been documented as treatments of hypertension in northern KwaZulu-Natal by lay people. The aqueous extracts were assessed using two assays; the Brine shrimp assay (Artemia franciscana) and the Ames test (Mutagenicity). Only one plant combination (Aloe marlothii with Hypoxis hemerocallidea) in the current study has been previously assessed for toxicity. With the Brine shrimp assay, the plant combinations were tested in two concentrations (2 and 4 mg/ml), while for mutagenicity tests, they were tested at 5 mg/ml. The results showed that in the Brine shrimp assay, six combinations were toxic at 4 mg/ml. The combinations were Albertisia delagoensis with Senecio serratuloides (57%), Aloe marlothii with Catharanthus roseus (98%), Catharanthus roseus with Hypoxis hemerocallidea (66%), Catharanthus roseus with Musa acuminata (89%), Catharanthus roseus with Momordica balsamina (99%) and Aloe marlothii with Trichilia emetica and Hyphaene coriacea (50%). However when the concentration was reduced to 2 mg/ml, only three combinations were toxic which were Aloe marlothii with Catharanthus roseus (76%), Catharanthus roseus with Musa acuminata (66%) and Catharanthus roseus with Momordica balsamina (73%). For the mutagenicity assay, only the combinations between Catharanthus roseus with Hypoxis hemerocallidea and Catharanthus roseus with Momordica balsamina were mutagenic towards the Salmonella typhimurium strains TA98 and TA100. Most of the combinations which were toxic involve C. roseus which was also toxic when tested singularly. It is worth noting that C. roseus was one of the most frequently used plant species both to treat hypertension singularly and in combination and some of the individuals have been using this for the last 20 years. The mortality percentage of the Brine shrimp showed a significant correlation between dosage and toxicity thus toxicity was dosage dependant. A combination which is worth noting is the combination between A. delagoensis and S. serratuloides. Singularly these plants were non-toxic towards Brine shrimp, however their combination resulted in antagonism with the mortality rate of 57% at the total concentration of 4 mg/ml. Low toxicity was mostly observed, giving some validity to combined use, however the few combinations showing increased toxicity demonstrate the importance of analysing plant combinations.

Keywords: dosage, hypertension, plant combinations, toxicity

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Authors: Chunhua Liao, Jinfei Wang, Bo Shan, Yang Song, Yongjun He, Taifeng Dong

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Winter wheat is one of the main crops in Canada. Forecasting of within-field variability of yield in winter wheat at the early stages is essential for precision farming. However, the crop yield modelling based on high spatial resolution satellite data is generally affected by the lack of continuous satellite observations, resulting in reducing the generalization ability of the models and increasing the difficulty of crop yield forecasting at the early stages. In this study, the correlations between Sentinel-2 data (vegetation indices and reflectance) and yield data collected by combine harvester were investigated and a generalized multivariate linear regression (MLR) model was built and tested with data acquired in different years. It was found that the four-band reflectance (blue, green, red, near-infrared) performed better than their vegetation indices (NDVI, EVI, WDRVI and OSAVI) in wheat yield prediction. The optimum phenological stage for wheat yield prediction with highest accuracy was at the growing stages from the end of the flowering to the beginning of the filling stage. The best MLR model was therefore built to predict wheat yield before harvest using Sentinel-2 data acquired at the end of the flowering stage. Further, to improve the ability of the yield prediction at the early stages, three simple unsupervised domain adaptation (DA) methods were adopted to transform the reflectance data at the early stages to the optimum phenological stage. The winter wheat yield prediction using multiple vegetation indices showed higher accuracy than using single vegetation index. The optimum stage for winter wheat yield forecasting varied with different fields when using vegetation indices, while it was consistent when using multispectral reflectance and the optimum stage for winter wheat yield prediction was at the end of flowering stage. The average testing RMSE of the MLR model at the end of the flowering stage was 604.48 kg/ha. Near the booting stage, the average testing RMSE of yield prediction using the best MLR was reduced to 799.18 kg/ha when applying the mean matching domain adaptation approach to transform the data to the target domain (at the end of the flowering) compared to that using the original data based on the models developed at the booting stage directly (“MLR at the early stage”) (RMSE =1140.64 kg/ha). This study demonstrated that the simple mean matching (MM) performed better than other DA methods and it was found that “DA then MLR at the optimum stage” performed better than “MLR directly at the early stages” for winter wheat yield forecasting at the early stages. The results indicated that the DA had a great potential in near real-time crop yield forecasting at the early stages. This study indicated that the simple domain adaptation methods had a great potential in crop yield prediction at the early stages using remote sensing data.

Keywords: wheat yield prediction, domain adaptation, Sentinel-2, within-field scale

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Authors: Elia Favarelli, Enrico Testi, Andrea Giorgetti

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Autonomous structural health monitoring (SHM) of many structures and bridges became a topic of paramount importance for maintenance purposes and safety reasons. This paper proposes a set of machine learning (ML) tools to perform automatic feature selection and detection of anomalies in a bridge from vibrational data and compare different feature extraction schemes to increase the accuracy and reduce the amount of data collected. As a case study, the Z-24 bridge is considered because of the extensive database of accelerometric data in both standard and damaged conditions. The proposed framework starts from the first four fundamental frequencies extracted through operational modal analysis (OMA) and clustering, followed by density-based time-domain filtering (tracking). The fundamental frequencies extracted are then fed to a dimensionality reduction block implemented through two different approaches: feature selection (intelligent multiplexer) that tries to estimate the most reliable frequencies based on the evaluation of some statistical features (i.e., mean value, variance, kurtosis), and feature extraction (auto-associative neural network (ANN)) that combine the fundamental frequencies to extract new damage sensitive features in a low dimensional feature space. Finally, one class classifier (OCC) algorithms perform anomaly detection, trained with standard condition points, and tested with normal and anomaly ones. In particular, a new anomaly detector strategy is proposed, namely one class classifier neural network two (OCCNN2), which exploit the classification capability of standard classifiers in an anomaly detection problem, finding the standard class (the boundary of the features space in normal operating conditions) through a two-step approach: coarse and fine boundary estimation. The coarse estimation uses classics OCC techniques, while the fine estimation is performed through a feedforward neural network (NN) trained that exploits the boundaries estimated in the coarse step. The detection algorithms vare then compared with known methods based on principal component analysis (PCA), kernel principal component analysis (KPCA), and auto-associative neural network (ANN). In many cases, the proposed solution increases the performance with respect to the standard OCC algorithms in terms of F1 score and accuracy. In particular, by evaluating the correct features, the anomaly can be detected with accuracy and an F1 score greater than 96% with the proposed method.

Keywords: anomaly detection, frequencies selection, modal analysis, neural network, sensor network, structural health monitoring, vibration measurement

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Authors: Tamar Grdzelishvili, Zaza Sinauridze

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Introduction: Preeclampsia is a complication of the second trimester of pregnancy, which is characterized by high morbidity and multiorgan damage. Many complex pathogenic mechanisms are now implicated to be responsible for this disease (1). Preeclampsia is one of the leading causes of maternal mortality worldwide. Statistics are enough to convince you of the seriousness of this pathology: about 100,000 women die of preeclampsia every year. It occurs in 3-14% (varies significantly depending on racial origin or ethnicity and geographical region) of pregnant women, in 75% of cases - in a mild form, and in 25% - in a severe form. During severe pre-eclampsia-eclampsia, perinatal mortality increases by 5 times and stillbirth by 9.6 times. Considering that the only way to treat the disease is to end the pregnancy, the main thing is timely diagnosis and prevention of the disease. Identification of high-risk pregnant women for PE and giving prophylaxis would reduce the incidence of preterm PE. First-trimester screening model developed by the Fetal Medicine Foundation (FMF), which uses the Bayes-theorem to combine maternal characteristics and medical history together with measurements of mean arterial pressure, uterine artery pulsatility index, and serum placental growth factor, has been proven to be effective and have superior screening performance to that of traditional risk factor-based approach for the prediction of PE (2) Methods: Retrospective single center screening study. The study population consisted of women from the Tbilisi maternity hospital “Pineo medical ecosystem” who met the following criteria: they spoke Georgian, English, or Russian and agreed to participate in the study after discussing informed consent and answering questions. Prior to the study, the informed consent forms approved by the Institutional Review Board were obtained from the study subjects. Early assessment of preeclampsia was performed between 11-13 weeks of pregnancy. The following were evaluated: anamnesis, dopplerography of the uterine artery, mean arterial blood pressure, and biochemical parameter: Pregnancy-associated plasma protein A (PAPP-A). Individual risk assessment was performed with performed by Fast Screen 3.0 software ThermoFisher scientific. Results: A total of 513 women were recruited and through the study, 51 women were diagnosed with preeclampsia (34.5% in the pregnant women with high risk, 6.5% in the pregnant women with low risk; P<0.000 1). Conclusions: First-trimester screening combining maternal factors with uterine artery Doppler, blood pressure, and pregnancy-associated plasma protein-A is useful to predict PE in a routine care setting. More patient studies are needed for final conclusions. The research is still ongoing.

Keywords: first-trimester, preeclampsia, screening, pregnancy-associated plasma protein

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Authors: Cristina Felipeto, Catherine Bore, Eduardo Calil

Abstract:

This work aims to analyze and compare the punctuation marks (PM) in school texts of Brazilian and French students and the comments on these PM made spontaneously by the students during the ongoing text. Assuming textual genetics as an investigative field within a dialogical and enunciative approach, we defined a common methodological design in two 1st year classrooms (7 years old) of the primary school, one classroom in Brazil (Maceio) and the other one in France (Paris). Through a multimodal capture system of writing processes in real time and space (Ramos System), we recorded the collaborative writing proposal in dyads in each of the classrooms. This system preserves the classroom’s ecological characteristics and provides a video recording synchronized with dialogues, gestures and facial expressions of the students, the stroke of the pen’s ink on the sheet of paper and the movement of the teacher and students in the classroom. The multimodal register of the writing process allowed access to the text in progress and the comments made by the students on what was being written. In each proposed text production, teachers organized their students in dyads and requested that they should talk, combine and write a fictional narrative. We selected a Dyad of Brazilian students (BD) and another Dyad of French students (FD) and we have filmed 6 proposals for each of the dyads. The proposals were collected during the 2nd Term of 2013 (Brazil) and 2014 (France). In 6 texts written by the BD there were identified 39 PMs and 825 written words (on average, a PM every 23 words): Of these 39 PMs, 27 were highlighted orally and commented by either student. In the texts written by the FD there were identified 48 PMs and 258 written words (on average, 1 PM every 5 words): Of these 48 PM, 39 were commented by the French students. Unlike what the studies on punctuation acquisition point out, the PM that occurred the most were hyphens (BD) and commas (FD). Despite the significant difference between the types and quantities of PM in the written texts, the recognition of the need for writing PM in the text in progress and the comments have some common characteristics: i) the writing of the PM was not anticipated in relation to the text in progress, then they were added after the end of a sentence or after the finished text itself; ii) the need to add punctuation marks in the text came after one of the students had ‘remembered’ that a particular sign was needed; iii) most of the PM inscribed were not related to their linguistic functions, but the graphic-visual feature of the text; iv) the comments justify or explain the PM, indicating metalinguistic reflections made by the students. Our results indicate how the comments of the BD and FD express the dialogic and subjective nature of knowledge acquisition. Our study suggests that the initial learning of PM depends more on its graphic features and interactional conditions than on its linguistic functions.

Keywords: collaborative writing, erasure, graphic marks, learning, metalinguistic awareness, textual genesis

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