Search results for: analytical modeling

Authors: Nikeshala Weerasekara, Roshan Ajward

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Contemporary business environment, given the circumstance of stringent scrutiny toward corporate behavior, organizations are under pressure to develop and implement solid overarching Corporate Social Responsibility (CSR) strategies. In that milieu, in order to differentiate themselves from competitors and maintain stakeholder confidence banks spend millions of dollars on CSR programmes. However, knowledge on how non-western bank employees perceive such activities is inconclusive. At the same time recently only researchers have shifted their focus on positive effects of compassion at work or the organizational conditions under which it arises. Nevertheless, mediation mechanisms between CSR and compassion at work have not been adequately examined leaving a vacuum to be explored. Despite finding a purpose in work that is greater than extrinsic outcomes of the work is important to employees, meaningful work has not been examined adequately. Thus, in addition to examining the direct relationship between CSR and compassion at work, this study examined the mediating capability of meaningful work between these variables. Specifically, the researcher explored how CSR enables employees to sense work as meaningful which in turn would enhance their level of compassion at work. Hypotheses were developed to examine the direct relationship between CSR and compassion at work and the mediating effect of meaningful work on the relationship between CSR and compassion at work. Both Social Identity Theory (SIT) and Social Exchange Theory (SET) were used to theoretically support the relationships. The sample comprised of 450 respondents covering different levels of the bank. A convenience sampling strategy was used to secure responses from 13 local licensed commercial banks in Sri Lanka. Data was collected using a structured questionnaire which was developed based on a comprehensive review of literature and refined using both expert opinions and a pilot survey. Structural equation modeling using Smart Partial Least Square (PLS) was utilized for data analysis. Findings indicate a positive and significant (p < .05) relationship between CSR and compassion at work. Also, it was found that meaningful work partially mediates the relationship between CSR and compassion at work. As per the findings it is concluded that bank employees’ perception of CSR engagement not only directly influence compassion at work but also impact such through meaningful work as well. This implies that employees consider working for a socially responsible bank since it creates greater meaningfulness of work to retain with the organization, which in turn trigger higher level of compassion at work. By utilizing both SIT and SET in explaining relationships between CSR and compassion at work it amounts to theoretical significance of the study. Enhance existing literature on CSR and compassion at work. Also, adds insights on mediating capability of psychologically related variables such as meaningful work. This study is expected to have significant policy implications in terms of increasing compassion at work where managers must understand the importance of including CSR activities into their strategy in order to thrive. Finally, it provides evidence of suitability of using Smart PLS to test models with mediating relationships involving non normal data.

Keywords: compassion at work, corporate social responsibility, employee commitment, meaningful work, positive affect

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Authors: Ha Phuong Tran, Feng Wang, Jo Dewulf, Hai Trung Huynh, Thomas Schaubroeck

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The fast increase and complex components have made waste of electrical and electronic equipment (or e-waste) one of the most problematic waste streams worldwide. Precise information on its size on national, regional and global level has therefore been highlighted as prerequisite to obtain a proper management system. However, this is a very challenging task, especially in developing countries where both formal e-waste management system and necessary statistical data for e-waste estimation, i.e. data on the production, sale and trade of electrical and electronic equipment (EEE), are often lacking. Moreover, there is an inflow of non-registered electronic and electric equipment, which ‘invisibly’ enters the EEE domestic market and then is used for domestic consumption. The non-registration/invisibility and (in most of the case) illicit nature of this flow make it difficult or even impossible to be captured in any statistical system. The e-waste generated from it is thus often uncounted in current e-waste estimation based on statistical market data. Therefore, this study focuses on enhancing e-waste estimation in developing countries and proposing a calculation pathway to quantify the magnitude of the non-registered EEE inflow. An advanced Input-Out Analysis model (i.e. the Sale–Stock–Lifespan model) has been integrated in the calculation procedure. In general, Sale-Stock-Lifespan model assists to improve the quality of input data for modeling (i.e. perform data consolidation to create more accurate lifespan profile, model dynamic lifespan to take into account its changes over time), via which the quality of e-waste estimation can be improved. To demonstrate the above objectives, a case study on televisions (TVs) in Vietnam has been employed. The results show that the amount of waste TVs in Vietnam has increased four times since 2000 till now. This upward trend is expected to continue in the future. In 2035, a total of 9.51 million TVs are predicted to be discarded. Moreover, estimation of non-registered TV inflow shows that it might on average contribute about 15% to the total TVs sold on the Vietnamese market during the whole period of 2002 to 2013. To tackle potential uncertainties associated with estimation models and input data, sensitivity analysis has been applied. The results show that both estimations of waste and non-registered inflow depend on two parameters i.e. number of TVs used in household and the lifespan. Particularly, with a 1% increase in the TV in-use rate, the average market share of non-register inflow in the period 2002-2013 increases 0.95%. However, it decreases from 27% to 15% when the constant unadjusted lifespan is replaced by the dynamic adjusted lifespan. The effect of these two parameters on the amount of waste TV generation for each year is more complex and non-linear over time. To conclude, despite of remaining uncertainty, this study is the first attempt to apply the Sale-Stock-Lifespan model to improve the e-waste estimation in developing countries and to quantify the non-registered EEE inflow to domestic consumption. It therefore can be further improved in future with more knowledge and data.

Keywords: e-waste, non-registered electrical and electronic equipment, TVs, Vietnam

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Authors: Haruka Ando

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Undernutrition of children is a critical issue, especially for people in the remote areas of the Republic of Djibouti, since household food insecurity, inadequate child caring and feeding, unhealthy environment and lack of clean water, as well as insufficient maternal and child healthcare, are underlying causes which affect. Nomadic pastoralists living in the Dikhil region (Dikhil) are socio-economically and geographically more vulnerable due to displacement, which in turn worsens the situation of child stunting. A high prevalence of inappropriate complementary feeding among pastoral mothers might be a significant barrier to child growth. This study aims to identify health promotion intervention strategies that would support an increase in optimal complementary feeding among pastoral mothers of children aged 6-23 months in Dikhil. There are four objectives; to explore and to understand the existing practice of complementary feeding among pastoral mothers in Dikhil; to identify the barriers in appropriate complementary feeding among the mothers; to critically explore and analyse the strategies for an increase in complementary feeding among the mothers; to make pragmatic recommendations to address the barriers in Djibouti. This is an in-depth study utilizing a conceptual framework, the behaviour change wheel, to analyse the determinants of complementary feeding and categorize health promotion interventions for increasing optimal complementary feeding among pastoral mothers living in Dikhil. The analytical tool was utilized to appraise the strategies to mitigate the selected barriers against optimal complementary feeding. The data sources were secondary literature from both published and unpublished sources. The literature was systematically collected. The findings of the determinants including the barriers of optimal complementary feeding were identified: heavy household workload, caring for multiple children under five, lack of education, cultural norms and traditional eating habits, lack of husbands' support, poverty and food insecurity, lack of clean water, low media coverage, insufficient health services on complementary feeding, fear, poor personal hygiene, and mothers' low decision-making ability and lack of motivation for food choice. To mitigate selected barriers of optimal complementary feeding, four intervention strategies based on interpersonal communication at the community-level were chosen: scaling up mothers' support groups, nutrition education, grandmother-inclusive approach, and training for complementary feeding counseling. The strategies were appraised through the criteria of effectiveness and feasibility. Scaling up mothers' support groups could be the best approach. Mid-term and long-term recommendations are suggested based on the situation analysis and appraisal of intervention strategies. Mid-term recommendations include complementary feeding promotion interventions are integrated into the healthcare service providing system in Dikhil, and donor agencies advocate and lobby the Ministry of Health Djibouti (MoHD) to increase budgetary allocation on complementary feeding promotion to implement interventions at a community level. Moreover, the recommendations include a community health management team in Dikhil training healthcare workers and mother support groups by using complementary feeding communication guidelines and monitors behaviour change of pastoral mothers and health outcome of their children. Long-term recommendations are the MoHD develops complementary feeding guidelines to cover sector-wide collaboration for multi-sectoral related barriers.

Keywords: Afar, child food, child nutrition, complementary feeding, complementary food, developing countries, Djibouti, East Africa, hard-to-reach areas, Horn of Africa, nomad, pastoral, rural area, Somali, Sub-Saharan Africa

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Authors: Magdalena Idzikowska, Katarzyna Pająk, Kamil Kowalczyk

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Seafloor topography is a fundamental issue in geological, geophysical, and oceanographic studies. Single-beam or multibeam sonars attached to the hulls of ships are used to emit a hydroacoustic signal from transducers and reproduce the topography of the seabed. This solution provides relevant accuracy and spatial resolution. Bathymetric data from ships surveys provides National Centers for Environmental Information – National Oceanic and Atmospheric Administration. Unfortunately, most of the seabed is still unidentified, as there are still many gaps to be explored between ship survey tracks. Moreover, such measurements are very expensive and time-consuming. The solution is raster bathymetric models shared by The General Bathymetric Chart of the Oceans. The offered products are a compilation of different sets of data - raw or processed. Indirect data for the development of bathymetric models are also measurements of gravity anomalies. Some forms of seafloor relief (e.g. seamounts) increase the force of the Earth's pull, leading to changes in the sea surface. Based on satellite altimetry data, Sea Surface Height and marine gravity anomalies can be estimated, and based on the anomalies, it’s possible to infer the structure of the seabed. The main goal of the work is to create regional bathymetric models and models of the sea surface in the area of the east coast of North America – a region of seamounts and undulating seafloor. The research includes an analysis of the methods and techniques used, an evaluation of the interpolation algorithms used, model thickening, and the creation of grid models. Obtained data are raster bathymetric models in NetCDF format, survey data from multibeam soundings in MB-System format, and satellite altimetry data from Copernicus Marine Environment Monitoring Service. The methodology includes data extraction, processing, mapping, and spatial analysis. Visualization of the obtained results was carried out with Geographic Information System tools. The result is an extension of the state of the knowledge of the quality and usefulness of the data used for seabed and sea surface modeling and knowledge of the accuracy of the generated models. Sea level is averaged over time and space (excluding waves, tides, etc.). Its changes, along with knowledge of the topography of the ocean floor - inform us indirectly about the volume of the entire water ocean. The true shape of the ocean surface is further varied by such phenomena as tides, differences in atmospheric pressure, wind systems, thermal expansion of water, or phases of ocean circulation. Depending on the location of the point, the higher the depth, the lower the trend of sea level change. Studies show that combining data sets, from different sources, with different accuracies can affect the quality of sea surface and seafloor topography models.

Keywords: seafloor, sea surface height, bathymetry, satellite altimetry

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Authors: S. Fares, K. Mellakh, A. Hmouri

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The StorMer project aims to set up a network of researchers to study traditional hydraulic rainwater harvesting systems in the Mediterranean basin, a region suffering from the major impacts of climate change and limited natural water resources. The arid and semi-arid Mediterranean basin has a long history of pioneering water management practices. The region has developed various ancient traditional water management systems, such as cisterns and qanats, to sustainably manage water resources under historical conditions of scarcity. Therefore, the StorMer project brings together Spain, France, Italy, Greece, Jordan and Morocco to explore traditional rainwater harvesting practices and systems in the Mediterranean region and to develop accurate modeling to simulate the performance and sustainability of these technologies under present-day climatic conditions. The ultimate goal of this project was to resuscitate and valorize these practices in the context of contemporary challenges. This project was intended to establish a Mediterranean network to serve as a basis for a more ambitious project. The ultimate objective was to analyze traditional hydraulic systems and create a prototype hydraulic ecosystem using a coupled environmental approach and traditional and ancient know-how, with the aim of reinterpreting them in the light of current techniques. The combination of ‘traditional’ and ‘modern knowledge/techniques’ is expected to lead to proposals for innovative hydraulic systems. The pandemic initially slowed our progress, but in the end it forced us to carry out the fieldwork in Morocco and Saudi Arabia, and so restart the project. With the participation of colleagues from chronologically distant fields (archaeology, sociology), we are now prepared to share our observations and propose the next steps. This interdisciplinary approach should give us a global vision of the project's objectives and challenges. A diachronic approach is needed to tackle the question of the long-term adaptation of societies in a Mediterranean context that has experienced several periods of water stress. The next stage of the StorMer project is the implementation of pilots in non-urbanized regions. These pilots will test the implementation of traditional systems and will be maintained and evaluated in terms of effectiveness, cost and acceptance. Based on these experiences, larger projects will be proposed and could provide information for regional water management policies. One of the most important lessons learned from this project is the highly social nature of managing traditional rainwater harvesting systems. Unlike modern, centralized water infrastructures, these systems often require the involvement of communities, which assume ownership and responsibility for them. This kind of community engagement leads to greater maintenance and, therefore, sustainability of the systems. Knowledge of the socio-cultural characteristics of these communities means that the systems can be adapted to the needs of each location, ensuring greater acceptance and efficiency.

Keywords: oasis, rainfall harvesting, arid regions, Mediterranean

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Authors: Ian O'Loughlin

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Memory networks aim to integrate some of the recent successes in machine learning with a dynamic memory base that can be updated and deployed in artificial reasoning tasks. These models involve training networks to identify, update, and operate over stored elements in a large memory array in order, for example, to ably perform question and answer tasks parsing real-world and simulated discourses. This family of approaches still faces numerous challenges: the performance of these network models in simulated domains remains considerably better than in open, real-world domains, wide-context cues remain elusive in parsing words and sentences, and even moderately complex sentence structures remain problematic. This innovation, employing an array of stored and updatable ‘memory’ elements over which the system operates as it parses text input and develops responses to questions, is a compelling one for at least two reasons: first, it addresses one of the difficulties that standard machine learning techniques face, by providing a way to store a large bank of facts, offering a way forward for the kinds of long-term reasoning that, for example, recurrent neural networks trained on a corpus have difficulty performing. Second, the addition of a stored long-term memory component in artificial reasoning seems psychologically plausible; human reasoning appears replete with invocations of long-term memory, and the stored but dynamic elements in the arrays of memory networks are deeply reminiscent of the way that human memory is readily and often characterized. However, this apparent psychological plausibility is belied by a recent turn in the study of human memory in cognitive science. In recent years, the very notion that there is a stored element which enables remembering, however dynamic or reconstructive it may be, has come under deep suspicion. In the wake of constructive memory studies, amnesia and impairment studies, and studies of implicit memory—as well as following considerations from the cognitive neuroscience of memory and conceptual analyses from the philosophy of mind and cognitive science—researchers are now rejecting storage and retrieval, even in principle, and instead seeking and developing models of human memory wherein plasticity and dynamics are the rule rather than the exception. In these models, storage is entirely avoided by modeling memory using a recurrent neural network designed to fit a preconceived energy function that attains zero values only for desired memory patterns, so that these patterns are the sole stable equilibrium points in the attractor network. So although the array of long-term memory elements in memory networks seem psychologically appropriate for reasoning systems, they may actually be incurring difficulties that are theoretically analogous to those that older, storage-based models of human memory have demonstrated. The kind of emergent stability found in the attractor network models more closely fits our best understanding of human long-term memory than do the memory network arrays, despite appearances to the contrary.

Keywords: artificial reasoning, human memory, machine learning, neural networks

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Authors: I. Hosni, L. Bennaceur Farah, N. Saber, R Bennaceur

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Soil moisture content is a key variable in many environmental sciences. Even though it represents a small proportion of the liquid freshwater on Earth, it modulates interactions between the land surface and the atmosphere, thereby influencing climate and weather. Accurate modeling of the above processes depends on the ability to provide a proper spatial characterization of soil moisture. The measurement of soil moisture content allows assessment of soil water resources in the field of hydrology and agronomy. The second parameter in interaction with the radar signal is the geometric structure of the soil. Most traditional electromagnetic models consider natural surfaces as single scale zero mean stationary Gaussian random processes. Roughness behavior is characterized by statistical parameters like the Root Mean Square (RMS) height and the correlation length. Then, the main problem is that the agreement between experimental measurements and theoretical values is usually poor due to the large variability of the correlation function, and as a consequence, backscattering models have often failed to predict correctly backscattering. In this study, surfaces are considered as band-limited fractal random processes corresponding to a superposition of a finite number of one-dimensional Gaussian process each one having a spatial scale. Multiscale roughness is characterized by two parameters, the first one is proportional to the RMS height, and the other one is related to the fractal dimension. Soil moisture is related to the complex dielectric constant. This multiscale description has been adapted to two-dimensional profiles using the bi-dimensional wavelet transform and the Mallat algorithm to describe more correctly natural surfaces. We characterize the soil surfaces and sub-surfaces by a three layers geo-electrical model. The upper layer is described by its dielectric constant, thickness, a multiscale bi-dimensional surface roughness model by using the wavelet transform and the Mallat algorithm, and volume scattering parameters. The lower layer is divided into three fictive layers separated by an assumed plane interface. These three layers were modeled by an effective medium characterized by an apparent effective dielectric constant taking into account the presence of air pockets in the soil. We have adopted the 2D multiscale three layers small perturbations model including, firstly air pockets in the soil sub-structure, and then a vegetable canopy in the soil surface structure, that is to simulate the radar backscattering. A sensitivity analysis of backscattering coefficient dependence on multiscale roughness and new soil moisture has been performed. Later, we proposed to change the dielectric constant of the multilayer medium because it takes into account the different moisture values of each layer in the soil. A sensitivity analysis of the backscattering coefficient, including the air pockets in the volume structure with respect to the multiscale roughness parameters and the apparent dielectric constant, was carried out. Finally, we proposed to study the behavior of the backscattering coefficient of the radar on a soil having a vegetable layer in its surface structure.

Keywords: multiscale, bidimensional, wavelets, backscattering, multilayer, SPM, air pockets

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Authors: Hatem Abou-Senna, Essam Radwan

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With increasing traffic and limited resources, accommodating left-turning traffic has been a challenge for traffic engineers as they seek balance between intersection capacity and safety; these are two conflicting goals in the operation of a signalized intersection that are mitigated through signal phasing techniques. Hence, to increase the left-turn capacity and reduce the delay at the intersections, the Florida Department of Transportation (FDOT) moves forward with a vision of optimizing intersection control using innovative intersection designs through the Transportation Systems Management & Operations (TSM&O) program. These alternative designs successfully eliminate the left-turn phase, which otherwise reduces the conventional intersection’s (CI) efficiency considerably, and divide the intersection into smaller networks that would operate in a one-way fashion. This study focused on the Crossover Displaced Left-turn intersections (XDL), also known as Continuous Flow Intersections (CFI). The XDL concept is best suited for intersections with moderate to high overall traffic volumes, especially those with very high or unbalanced left turn volumes. There is little guidance on determining whether partial XDL intersections are adequate to mitigate the overall intersection condition or full XDL is always required. The primary objective of this paper was to evaluate the overall intersection performance in the case of different partial XDL designs compared to a full XDL. The XDL alternative was investigated for 4 different scenarios; partial XDL on the east-west approaches, partial XDL on the north-south approaches, partial XDL on the north and east approaches and full XDL on all 4 approaches. Also, the impact of increasing volume on the intersection performance was considered by modeling the unbalanced volumes with 10% increment resulting in 5 different traffic scenarios. The study intersection, located in Orlando Florida, is experiencing recurring congestion in the PM peak hour and is operating near capacity with volume to a capacity ratio closer to 1.00 due to the presence of two heavy conflicting movements; southbound and westbound. The results showed that a partial EN XDL alternative proved to be effective and compared favorably to a full XDL alternative followed by the partial EW XDL alternative. The analysis also showed that Full, EW and EN XDL alternatives outperformed the NS XDL and the CI alternatives with respect to the throughput, delay and queue lengths. Significant throughput improvements were remarkable at the higher volume level with percent increase in capacity of 25%. The percent reduction in delay for the critical movements in the XDL scenarios compared to the CI scenario ranged from 30-45%. Similarly, queue lengths showed percent reduction in the XDL scenarios ranging from 25-40%. The analysis revealed how partial XDL design can improve the overall intersection performance at various demands, reduce the costs associated with full XDL and proved to outperform the conventional intersection. However, partial XDL serving low volumes or only one of the critical movements while other critical movements are operating near or above capacity do not provide significant benefits when compared to the conventional intersection.

Keywords: continuous flow intersections, crossover displaced left-turn, microscopic traffic simulation, transportation system management and operations, VISSIM simulation model

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Authors: María-Luisa Pinto-Salamanca, Wilson-Javier Pérez-Holguín

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Reconstruction of contact forces is a fundamental technique for analyzing the properties of a touched object and is essential for regulating the grip force in slip control loops. This is based on the processing of the distribution, intensity, and direction of the forces during the capture of the sensors. Currently, efficient hardware alternatives have been used more frequently in different fields of application, allowing the implementation of computationally complex algorithms, as is the case with tactile signal processing. The use of hardware for smart tactile sensing systems is a research area that promises to improve the processing time and portability requirements of applications such as artificial skin and robotics, among others. The literature review shows that hardware implementations are present today in almost all stages of smart tactile detection systems except in the force reconstruction process, a stage in which they have been less applied. This work presents a hardware implementation of a model-driven reported in the literature for the contact force reconstruction of flat and rigid tactile sensor arrays from normal stress data. From the analysis of a software implementation of such a model, this implementation proposes the parallelization of tasks that facilitate the execution of matrix operations and a two-dimensional optimization function to obtain a vector force by each taxel in the array. This work seeks to take advantage of the parallel hardware characteristics of Field Programmable Gate Arrays, FPGAs, and the possibility of applying appropriate techniques for algorithms parallelization using as a guide the rules of generalization, efficiency, and scalability in the tactile decoding process and considering the low latency, low power consumption, and real-time execution as the main parameters of design. The results show a maximum estimation error of 32% in the tangential forces and 22% in the normal forces with respect to the simulation by the Finite Element Modeling (FEM) technique of Hertzian and non-Hertzian contact events, over sensor arrays of 10×10 taxels of different sizes. The hardware implementation was carried out on an MPSoC XCZU9EG-2FFVB1156 platform of Xilinx® that allows the reconstruction of force vectors following a scalable approach, from the information captured by means of tactile sensor arrays composed of up to 48 × 48 taxels that use various transduction technologies. The proposed implementation demonstrates a reduction in estimation time of x / 180 compared to software implementations. Despite the relatively high values of the estimation errors, the information provided by this implementation on the tangential and normal tractions and the triaxial reconstruction of forces allows to adequately reconstruct the tactile properties of the touched object, which are similar to those obtained in the software implementation and in the two FEM simulations taken as reference. Although errors could be reduced, the proposed implementation is useful for decoding contact forces for portable tactile sensing systems, thus helping to expand electronic skin applications in robotic and biomedical contexts.

Keywords: contact forces reconstruction, forces estimation, tactile sensor array, hardware implementation

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Authors: Hadi S. Hosseini, Larry A. Taber

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In the embryo, heart is initially a simple tubular structure that undergoes complex morphological changes as it transforms into a four-chambered pump. This work focuses on mechanisms that create heart tube (HT). The early embryo is composed of three relatively flat primary germ layers called endoderm, mesoderm, and ectoderm. Precardiac cells located within bilateral regions of the mesoderm called heart fields (HFs) fold and fuse along the embryonic midline to create the HT. The right and left halves of this plate fold symmetrically to bring their upper edges into contact along the midline, where they fuse. In a region near the fusion line, these layers then separate to generate the primitive HT and foregut, which then extend vertically. The anterior intestinal portal (AIP) is the opening at the caudal end of the foregut, which descends as the HT lengthens. The biomechanical mechanisms that drive this folding are poorly understood. Our central hypothesis is that folding is caused by differences in growth between the endoderm and mesoderm while subsequent extension is driven by contraction along the AIP. The feasibility of this hypothesis is examined using experiments with chick embryos and finite-element modeling (FEM). Fertilized white Leghorn chicken eggs were incubated for approximately 22-33 hours until appropriate Hamburger and Hamilton stage (HH5 to HH9) was reached. To inhibit contraction, embryos were cultured in media containing blebbistatin (myosin II inhibitor) for 18h. Three-dimensional models were created using ABAQUS (D. S. Simulia). The initial geometry consists of a flat plate including two layers representing the mesoderm and endoderm. Tissue was considered as a nonlinear elastic material with growth and contraction (negative growth) simulated using a theory, in which the total deformation gradient is given by F=F^*.G, where G is growth tensor and F* is the elastic deformation gradient tensor. In embryos exposed to blebbistatin, initial folding and AIP descension occurred normally. However, after HFs partially fused to create the upper part of the HT, fusion, and AIP descension stopped, and the HT failed to grow longer. These results suggest that cytoskeletal contraction is required only for the later stages of HT formation. In the model, a larger biaxial growth rate in the mesoderm compared to the endoderm causes the bilayered plate to bend ventrally, as the upper edge moves toward the midline, where it 'fuses' with the other half . This folding creates the upper section of the HT, as well as the foregut pocket bordered by the AIP. After this phase completes by stage HH7, contraction along the arch-shaped AIP pulls the lower edge of the plate downward, stretching the two layers. Results given by model are in reasonable agreement with experimental data for the shape of HT, as well as patterns of stress and strain. In conclusion, results of our study support our hypothesis for the creation of the heart tube.

Keywords: heart tube formation, FEM, chick embryo, biomechanics

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Authors: Zahide Tepeli Temiz, Itir Tari Comert

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Attachment patterns based on early emotional interactions between infant and primary caregiver continue to be influential in adult life, in terms of mental health and behaviors of individuals. Several studies reveal that infant-caregiver relationships have impressed the affect regulation, coping with stressful and negative situations, general satisfaction of life, and self image in adulthood, besides the attachment styles. The present study aims to examine the relationships between university students’ attachment style and their self-esteem, alexithymic features, satisfaction of life, and level of resilience. In line with this aim, the hypothesis of the prediction of attachment styles (anxious and avoidant) over life satisfaction, self-esteem, alexithymia, and psychological resilience was tested. Additionally, in this study Structural Equational Modeling was conducted to investigate the mediational role of self-esteem in the relationship between attachment styles and alexithymia, life satisfaction, and resilience. This model was examined with path analysis. The sample of the research consists of 425 university students who take education from several region of Turkey. The participants who sign the informed consent completed the Demographic Information Form, Experiences in Close Relationships-Revised, Rosenberg Self-Esteem Scale, The Satisfaction with Life Scale, Toronto Alexithymia Scale, and Resilience Scale for Adults. According to results, anxious, and avoidant dimensions of insecure attachment predicted the self-esteem score and alexithymia in positive direction. On the other hand, these dimensions of attachment predicted life satisfaction in negative direction. The results of linear regression analysis indicated that anxious and avoidant attachment styles didn’t predict the resilience. This result doesn’t support the theory and research indicating the relationship between attachment style and psychological resilience. The results of path analysis revealed the mediational role self esteem in the relation between anxious, and avoidant attachment styles and life satisfaction. In addition, SEM analysis indicated the indirect effect of attachment styles over alexithymia and resilience besides their direct effect. These findings support the hypothesis of this research relation to mediating role of self-esteem. Attachment theorists suggest that early attachment experiences, including supportive and responsive family interactions, have an effect on resilience to harmful situations in adult life, ability to identify, describe, and regulate emotions and also general satisfaction with life. Several studies examining the relationship between attachment styles and life satisfaction, alexithymia, and psychological resilience draw attention to mediational role of self-esteem. Results of this study support the theory of attachment patterns with the mediation of self-image influence the emotional, cognitive, and behavioral regulation of person throughout the adulthood. Therefore, it is thought that any intervention intended for recovery in attachment relationship will increase the self-esteem, life satisfaction, and resilience level, on the one side, decrease the alexithymic features, on the other side.

Keywords: alexithymia, anxious attachment, avoidant attachment, life satisfaction, path analysis, resilience, self-esteem, structural equation

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Authors: Tesfaldet Mekonnen Estifanos, Chen Hui, Afewerki Weldezgi

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Background: Intimate partner violence (hereafter IPV) is a major global public health challenge that tortures and disables women in the place where they are ought to be most secure within their own families. The fact that the family unit is commonly viewed as a private circle, violent acts towards women remains undermined. There are limited research and knowledge about the influencing factors linked to IPV in Sierra Leone. This study, therefore, estimates the prevalence rate and the predicting factors associated with IPV. Methods: Data were taken from Sierra-Leone Demographic and Health Survey (SDHS, 2013): the first in its form to incorporate information on domestic violence. Multistage cluster sampling research design was used, and information was gathered by a standard questionnaire. A total of 5185 respondents selected were interviewed, out of whom 870 were never been in union, thus excluded. To analyze the two dependent variables: experience of IPV, ‘ever’ and 'last 12 months prior to the survey', a total of 4315 (currently or formerly married) and 4029 women (currently in union) were included respectively. These dependent variables were constructed from the three forms of violence namely physical, emotional and sexual. Data analysis was applied using SPSS version 23, comprising three-step process. First, descriptive statistics were used to show the frequency distribution of both the outcome and explanatory variables. Second, bivariate analysis adopting chi-square test was applied to assess the individual relationship between the outcome and explanatory variables. Third, multivariate logistic regression analysis was undertaken using hierarchical modeling strategy to identify the influence of the explanatory variables on the outcome variables. Odds ratio (OR) and 95% confidence interval (CI) were utilized to examine the association of the variables considering p-values less than 0.05 statistically significant. Results: The prevalence of lifetime IPV among ever married women was 48.4%, while 39.8% of those currently married experienced IPV in the previous year preceding the survey. Women having 1 to 4 and more than 5 number of ever born babies were almost certain to encounter lifetime IPV. However, women who own a property, and those who referenced 3-5 reasons for which wife-beating is acceptable were less probably to experience lifetime IPV. Attesting parental violence, partner’s dominant marital behavior, and women afraid of their partner were the variables related to both experience of IPV ‘ever’ and ‘the previous year prior to the survey’. Respondents who concur that wife-beating is sensible in certain situations and occupations under the professional category had diminished chances of revealing IPV in the year prior to the data collection. Conclusion: This study indicated that factors significantly correlated with IPV in Sierra-Leone are mostly linked with husband related factors specifically, marital controlling behaviors. Addressing IPV in Sierra-Leone requires joint efforts that target men raise awareness to address controlling behavior and empower security in affiliations.

Keywords: husband behavior, married women, partner violence, Sierra Leone

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Authors: Abdelkhalek Bouchikhi, Elyes Benmokhtar, Sebastien Saletzki

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The aeronautical field is experiencing issues with RF spectrum congestion due to the constant increase in the number of flights, aircrafts and telecom systems on board. In addition, these systems are bulky in size, weight and energy consumption. The cognitive radio helps particularly solving the spectrum congestion issue by its capacity to detect idle frequency channels then, allowing an opportunistic exploitation of the RF spectrum. The present work aims to propose a new use case for aeronautical spectrum sharing and to study the performances of three different detection techniques: energy detector, matched filter and cyclostationary detector within the aeronautical use case. The spectrum in the proposed cognitive radio is allocated dynamically where each cognitive radio follows a cognitive cycle. The spectrum sensing is a crucial step. The goal of the sensing is gathering data about the surrounding environment. Cognitive radio can use different sensors: antennas, cameras, accelerometer, thermometer, etc. In IEEE 802.22 standard, for example, a primary user (PU) has always the priority to communicate. When a frequency channel witch used by the primary user is idle, the secondary user (SU) is allowed to transmit in this channel. The Distance Measuring Equipment (DME) is composed of a UHF transmitter/receiver (interrogator) in the aircraft and a UHF receiver/transmitter on the ground. While the future cognitive radio will be used jointly to alleviate the spectrum congestion issue in the aeronautical field. LDACS, for example, is a good candidate; it provides two isolated data-links: ground-to-air and air-to-ground data-links. The first contribution of the present work is a strategy allowing sharing the L-band. The adopted spectrum sharing strategy is as follow: the DME will play the role of PU which is the licensed user and the LDACS1 systems will be the SUs. The SUs could use the L-band channels opportunely as long as they do not causing harmful interference signals which affect the QoS of the DME system. Although the spectrum sensing is a key step, it helps detecting holes by determining whether the primary signal is present or not in a given frequency channel. A missing detection on primary user presence creates interference between PU and SU and will affect seriously the QoS of the legacy radio. In this study, first brief definitions, concepts and the state of the art of cognitive radio will be presented. Then, a study of three communication channel detection algorithms in a cognitive radio context is carried out. The study is made from the point of view of functions, material requirements and signal detection capability in the aeronautical field. Then, we presented a modeling of the detection problem by three different methods (energy, adapted filter, and cyclostationary) as well as an algorithmic description of these detectors is done. Then, we study and compare the performance of the algorithms. Simulations were carried out using MATLAB software. We analyzed the results based on ROCs curves for SNR between -10dB and 20dB. The three detectors have been tested with a synthetics and real world signals.

Keywords: aeronautic, communication, navigation, surveillance systems, cognitive radio, spectrum sensing, software defined radio

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Authors: Anastasia Tsakiridi

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Geographic information systems (GIS) have been utilized in numerous spatial problems, such as site research, land suitability, and demographic analysis. Besides, GIS has been applied in scientific fields like geography, health, and economics. In business studies, GIS has been used to provide insights and spatial perspectives in demographic trends, spending indicators, and network analysis. To date, the information regarding the available usages of GIS in supply chain management (SCM) and how these analyses can benefit businesses is limited. A systematic literature review (SLR) of the last 5-year peer-reviewed academic literature was conducted, aiming to explore the existing usages of GIS in SCM. The searches were performed in 3 databases (Web of Science, ProQuest, and Business Source Premier) and reported using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology. The analysis resulted in 79 papers. The results indicate that the existing GIS applications used in SCM were in the following domains: a) network/ transportation analysis (in 53 of the papers), b) location – allocation site search/ selection (multiple-criteria decision analysis) (in 45 papers), c) spatial analysis (demographic or physical) (in 34 papers), d) combination of GIS and supply chain/network optimization tools (in 32 papers), and e) visualization/ monitoring or building information modeling applications (in 8 papers). An additional categorization of the literature was conducted by examining the usage of GIS in the supply chain (SC) by the business sectors, as indicated by the volume of the papers. The results showed that GIS is mainly being applied in the SC of the biomass biofuel/wood industry (33 papers). Other industries that are currently utilizing GIS in their SC were the logistics industry (22 papers), the humanitarian/emergency/health care sector (10 papers), the food/agro-industry sector (5 papers), the petroleum/ coal/ shale gas sector (3 papers), the faecal sludge sector (2 papers), the recycle and product footprint industry (2 papers), and the construction sector (2 papers). The results were also presented by the geography of the included studies and the GIS software used to provide critical business insights and suggestions for future research. The results showed that research case studies of GIS in SCM were conducted in 26 countries (mainly in the USA) and that the most prominent GIS software provider was the Environmental Systems Research Institute’s ArcGIS (in 51 of the papers). This study is a systematic literature review of the usage of GIS in SCM. The results showed that the GIS capabilities could offer substantial benefits in SCM decision-making by providing key insights to cost minimization, supplier selection, facility location, SC network configuration, and asset management. However, as presented in the results, only eight industries/sectors are currently using GIS in their SCM activities. These findings may offer essential tools to SC managers who seek to optimize the SC activities and/or minimize logistic costs and to consultants and business owners that want to make strategic SC decisions. Furthermore, the findings may be of interest to researchers aiming to investigate unexplored research areas where GIS may improve SCM.

Keywords: supply chain management, logistics, systematic literature review, GIS

Procedia PDF Downloads 116

Authors: Lamiek Abraham, Xinli Du, Yohan Noh, Polin Hsu, Tingting Wu, Tom Logan, Ifan Yen

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In the field of minimally invasive, smart medical instruments such as catheters and guidewires are typically used at a remote distance to gain access to the diseased artery, often negotiating tortuous, complex, and diseased vessels in the process. Three optical fiber sensors with a diameter of 1.5mm each that are 120° apart from each other is proposed to be mounted into a catheter-based pump device with a diameter of 10mm. These sensors are configured to solve the challenges surgeons face during insertion through curvy major vessels such as the aortic arch. Moreover, these sensors deal with providing information on rubbing the walls and shape sensing. This study presents an experimental and mathematical models of the optical fiber sensors with 2 degrees of freedom. There are two eight gear-shaped tubes made up of 3D printed thermoplastic Polyurethane (TPU) material that are connected. The optical fiber sensors are mounted inside the first tube for protection from external light and used TPU material as a prototype for a catheter. The second tube is used as a flat reflection for the light intensity modulation-based optical fiber sensors. The first tube is attached to the linear guide for insertion and withdrawal purposes and can manually turn it 45° by manipulating the tube gear. A 3D hard material phantom was developed that mimics the aortic arch anatomy structure in which the test was carried out. During the insertion of the sensors into the 3D phantom, datasets are obtained in terms of voltage, distance, and position of the sensors. These datasets reflect the characteristics of light intensity modulation of the optical fiber sensors with a plane project of the aortic arch structure shape. Mathematical modeling of the light intensity was carried out based on the projection plane and experiment set-up. The performance of the system was evaluated in terms of its accuracy in navigating through the curvature and information on the position of the sensors by investigating 40 single insertions of the sensors into the 3D phantom. The experiment demonstrated that the sensors were effectively steered through the 3D phantom curvature and to desired target references in all 2 degrees of freedom. The performance of the sensors echoes the reflectance of light theory, where the smaller the radius of curvature, the more of the shining LED lights are reflected and received by the photodiode. A mathematical model results are in good agreement with the experiment result and the operation principle of the light intensity modulation of the optical fiber sensors. A prototype of a catheter using TPU material with three optical fiber sensors mounted inside has been developed that is capable of navigating through the different radius of curvature with 2 degrees of freedom. The proposed system supports operators with pre-scan data to make maneuverability and bendability through curvy major vessels easier, accurate, and safe. The mathematical modelling accurately fits the experiment result.

Keywords: Intensity modulated optical fiber sensor, mathematical model, plane projection, shape sensing.

Procedia PDF Downloads 220

Authors: N. Šarlija, S. Pfeifer, M. Jeger, A. Bilandžić

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Enterprise growth is generally considered as a key driver of competitiveness, employment, economic development and social inclusion. As such, it is perceived to be a highly desirable outcome of entrepreneurship for scholars and decision makers. The huge academic debate resulted in the multitude of theoretical frameworks focused on explaining growth stages, determinants and future prospects. It has been widely accepted that enterprise growth is most likely nonlinear, temporal and related to the variety of factors which reflect the individual, firm, organizational, industry or environmental determinants of growth. However, factors that affect growth are not easily captured, instruments to measure those factors are often arbitrary, causality between variables and growth is elusive, indicating that growth is not easily modeled. Furthermore, in line with heterogeneous nature of the growth phenomenon, there is a vast number of measurement constructs assessing growth which are used interchangeably. Differences among various growth measures, at conceptual as well as at operationalization level, can hinder theory development which emphasizes the need for more empirically robust studies. In line with these highlights, the main purpose of this paper is twofold. Firstly, to compare structure and performance of three growth prediction models based on the main growth measures: Revenues, employment and assets growth. Secondly, to explore the prospects of financial indicators, set as exact, visible, standardized and accessible variables, to serve as determinants of enterprise growth. Finally, to contribute to the understanding of the implications on research results and recommendations for growth caused by different growth measures. The models include a range of financial indicators as lag determinants of the enterprises’ performances during the 2008-2013, extracted from the national register of the financial statements of SMEs in Croatia. The design and testing stage of the modeling used the logistic regression procedures. Findings confirm that growth prediction models based on different measures of growth have different set of predictors. Moreover, the relationship between particular predictors and growth measure is inconsistent, namely the same predictor positively related to one growth measure may exert negative effect on a different growth measure. Overall, financial indicators alone can serve as good proxy of growth and yield adequate predictive power of the models. The paper sheds light on both methodology and conceptual framework of enterprise growth by using a range of variables which serve as a proxy for the multitude of internal and external determinants, but are unlike them, accessible, available, exact and free of perceptual nuances in building up the model. Selection of the growth measure seems to have significant impact on the implications and recommendations related to growth. Furthermore, the paper points out to potential pitfalls of measuring and predicting growth. Overall, the results and the implications of the study are relevant for advancing academic debates on growth-related methodology, and can contribute to evidence-based decisions of policy makers.

Keywords: growth measurement constructs, logistic regression, prediction of growth potential, small and medium-sized enterprises

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Authors: Linda Márcia Mendes Delazeri, Dênis Antônio Da Cunha

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Over the past few years, the evidence that human activities have altered the concentration of greenhouse gases in the atmosphere have become stronger, indicating that this accumulation is the most likely cause of climate change observed so far. The risks associated with climate change, although uncertain, have the potential to increase social vulnerability, exacerbating existing socioeconomic challenges. Developing countries are potentially the most affected by climate change, since they have less potential to adapt and are those most dependent on agricultural activities, one of the sectors in which the major negative impacts are expected. In Brazil, specifically, it is expected that the localities which form the semiarid region are among the most affected, due to existing irregularity in rainfall and high temperatures, in addition to economic and social factors endemic to the region. Given the strategic limitations to handle the environmental shocks caused by climate change, an alternative adopted in response to these shocks is migration. Understanding the specific features of migration flows, such as duration, destination and composition is essential to understand the impacts of migration on origin and destination locations and to develop appropriate policies. Thus, this study aims to examine whether climatic factors have contributed to rural-urban migration in semiarid municipalities in the recent past and how these migration flows will be affected by future scenarios of climate change. The study was based on microeconomic theory of utility maximization, in which, to decide to leave the countryside and move on to the urban area, the individual seeks to maximize its utility. Analytically, we estimated an econometric model using the modeling of Fixed Effects and the results confirmed the expectation that climate drivers are crucial for the occurrence of the rural-urban migration. Also, other drivers of the migration process, as economic, social and demographic factors were also important. Additionally, predictions about the rural-urban migration motivated by variations in temperature and precipitation in the climate change scenarios RCP 4.5 and 8.5 were made for the periods 2016-2035 and 2046-2065, defined by the Intergovernmental Panel on Climate Change (IPCC). The results indicate that there will be increased rural-urban migration in the semiarid region in both scenarios and in both periods. In general, the results of this study reinforce the need for formulations of public policies to avoid migration for climatic reasons, such as policies that give support to the productive activities generating income in rural areas. By providing greater incentives for family agriculture and expanding sources of credit for the farmer, it will have a better position to face climate adversities and to settle in rural areas. Ultimately, if migration becomes necessary, there must be the adoption of policies that seek an organized and planned development of urban areas, considering migration as an adaptation strategy to adverse climate effects. Thus, policies that act to absorb migrants in urban areas and ensure that they have access to basic services offered to the urban population would contribute to the social costs reduction of climate variability.

Keywords: climate change, migration, rural productivity, semiarid region

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Authors: Priyanka Botny Srinath, Alessandro Suglia, Mel McKendrick

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Background: Organizational cultural studies integrate sociology and anthropology, portraying man as a creator of symbols, languages, beliefs, and ideologies -essentially, a creator and manager of meaning. In our research, we leverage analytical measures to discern whether an organization embodies a singular culture or a myriad of subcultures. Fast-forward to 2023, our research thesis focuses on digitally measuring culture, coining it as the "Work Culture Quotient." This entails conceptually mapping common experiential patterns to provide executives insights into the digital organization journey, aiding in understanding their current position and identifying future steps. Objectives: Finding the new age skills that help in defining the culture; understand the implications of post-COVID effects; derive a digital framework for measuring skillsets. Method: We conducted two comprehensive Delphi studies to distill essential insights. Delphi 1: Through a thematic analysis of interviews with 20 high-level leaders representing companies across diverse regions -India, Japan, the US, Canada, Morocco, and Uganda- we identified 20 key skills critical for cultivating a robust organizational culture. The skills are -influence, self-confidence, optimism, empathy, leadership, collaboration and cooperation, developing others, commitment, innovativeness, leveraging diversity, change management, team capabilities, self-control, digital communication, emotional awareness, team bonding, communication, problem solving, adaptability, and trustworthiness. Delphi 2: Subject matter experts were asked to complete a questionnaire derived from the thematic analysis in stage 1 to formalise themes and draw consensus amongst experts on the most important workplace skills. Results: The thematic analysis resulted in 20 workplace employee skills being identified. These skills were all included in the Delphi round 2 questionnaire. From the outputs, we analysed the data using R Studio for arriving at agreement and consensus, we also used sum of squares method to compare various agreements to extract various themes with a threshold of 80% agreements. This yielded three themes at over 80% agreement (leadership, collaboration and cooperation, communication) and three further themes at over 60% agreement (commitment, empathy, trustworthiness). From this, we selected five questionnaires to be included in the primary data collection phase, and these will be paired with the digital footprints to provide a workplace culture quotient. Implications: The findings from these studies bear profound implications for decision-makers, revolutionizing their comprehension of organizational culture. Tackling the challenge of mapping the digital organization journey involves innovative methodologies that probe not only external landscapes but also internal cultural dynamics. This holistic approach furnishes decision-makers with a nuanced understanding of their organizational culture and visualizes pivotal skills for employee growth. This clarity enables informed choices resonating with the organization's unique cultural fabric. Anticipated outcomes transcend mere individual cultural measurements, aligning with organizational goals to unveil a comprehensive view of culture, exposing artifacts and depth. Armed with this profound understanding, decision-makers gain tangible evidence for informed decision-making, strategically leveraging cultural strengths to cultivate an environment conducive to growth, innovation, and enduring success, ultimately leading to measurable outcomes.

Keywords: leadership, cooperation, collaboration, teamwork, work culture

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Authors: Jasna Hrncic

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Poor family relations predict depression, but also to other mental health issues. Mediating effect of self-efficacy and differentiation of self and moderating effect of decreased accessibility and/or success of other adaptive and defensive mechanisms for overcoming social disadvantages could explain depression as a specific outcome of dysfunctional family relations. The present study analyzes the mediation effect of self-efficacy and differentiation of self from poor family functioning to depressive symptoms and the moderation effect of deprivation of liberty on the listed mediation effect. Deprivation of liberty has, as a general consequence, a decreased accessibility and/or success of many adaptive and defensive mechanisms. It is hypothesized that: 1) self-efficacy and differentiation of self will mediate between family functioning and depressiveness in the total sample, and 2) deprivation of liberty will moderate the stated relations. Cross-sectional study was conducted among 323 male juveniles in Serbia divided in three groups: 98 adolescents deprived of their liberty due to antisocial behavior (incarcerated antisocial group - IAG), 121 adolescents with antisocial behavior in their natural setting (antisocial control group - CAG) and 105 adolescents in general population (general control group - CGG). The CAG was included along with GCG to control the possible influence that comorbidity of antisocial behavior and depressiveness could have on results. Instruments for family relations assessment were: for a whole family of origin the emotional exchange scale and individuation scale from GRADIR by Knezevic, and for a relationship with mother PCS-YSR and CRPBI by barber, and intimacy, rejection, sacrifice, punishment, demands, control and internal control by Opacic and Kos. Differentiation of self (DOS) is measured by emotional self scale (Opacic), self-efficacy (SE) by general incompetence scale by Bezinovic, and depression by BDI (Back), CES-D (Radloff) and D6R (Momirovic). Two-path structural equation modeling based on most commonly reported fit indices, showed that the mediation model had unfavorable fit to our data for total sample [(χ2 (1, N = 324) = 13.73); RMSEA= .20 (90% CI= [.12, .30]); CFI= .98; NFI= .97; AIC=31.73]. Path model provided an adequate fit to the data only for AIG - and not to the data from ACG and GCG. SE and DOS mediated the relationship between PFF and depressiveness. Test of the indirect effects revealed that 23.85% of PFF influences on depressiveness is mediated by these two mediators (the quotient of mediated effect = .24). Test of specific indirect effects showed that SE mediates 22.17%, while DOS mediates 1.67% of PFF influence on depressiveness. Lack of expected mediation effect could be explained by missing other potential mediators (i.e., relationship with that father, social skills, self-esteem) and lower variability of both predictor and criterion variable due to their low levels on the whole sample and on control subsamples. Results suggested that inaccessibility and/or successfulness of other adaptive and defensive mechanisms for overcoming social disadvantages has a strong impact on the mediation effect of self/efficacy and differentiation of self from poor family functioning to depressive symptoms. Further researches could include other potential mediators and a sample of clinically depressed people.

Keywords: antisocial behavior, mediating effect, moderating effect, natural setting, incarceration

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Authors: Sinisa J. Vukicevic

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Edmonton is currently one of the youngest North American cities and has achieved significant growth over the past 40 years. Strong urban shift requires a new approach to how the city is envisioned, planned, and built. This approach is evidence-based scenario development, and an urban growth model was a key support tool in framing Edmonton development strategies, developing urban policies, and assessing policy implications. The urban growth model has been developed using the Metronamica software platform. The Metronamica land use model evaluated the dynamic of land use change under the influence of key development drivers (population and employment), zoning, land suitability, and land and activity accessibility. The model was designed following the Big City Moves ideas: become greener as we grow, develop a rebuildable city, ignite a community of communities, foster a healing city, and create a city of convergence. The Big City Moves were converted to three development scenarios: ‘Strong Central City’, ‘Node City’, and ‘Corridor City’. Each scenario has a narrative story that expressed scenario’s high level goal, scenario’s approach to residential and commercial activities, to transportation vision, and employment and environmental principles. Land use demand was calculated for each scenario according to specific density targets. Spatial policies were analyzed according to their level of importance within the policy set definition for the specific scenario, but also through the policy measures. The model was calibrated on the way to reproduce known historical land use pattern. For the calibration, we used 2006 and 2011 land use data. The validation is done independently, which means we used the data we did not use for the calibration. The model was validated with 2016 data. In general, the modeling process contain three main phases: ‘from qualitative storyline to quantitative modelling’, ‘model development and model run’, and ‘from quantitative modelling to qualitative storyline’. The model also incorporates five spatial indicators: distance from residential to work, distance from residential to recreation, distance to river valley, urban expansion and habitat fragmentation. The major finding of this research could be looked at from two perspectives: the planning perspective and technology perspective. The planning perspective evaluates the model as a tool for scenario development. Using the model, we explored the land use dynamic that is influenced by a different set of policies. The model enables a direct comparison between the three scenarios. We explored the similarities and differences of scenarios and their quantitative indicators: land use change, population change (and spatial allocation), job allocation, density (population, employment, and dwelling unit), habitat connectivity, proximity to objects of interest, etc. From the technology perspective, the model showed one very important characteristic: the model flexibility. The direction for policy testing changed many times during the consultation process and model flexibility in applying all these changes was highly appreciated. The model satisfied our needs as scenario development and evaluation tool, but also as a communication tool during the consultation process.

Keywords: urban growth model, scenario development, spatial indicators, Metronamica

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Authors: Mehwish Jawaad

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Purpose: The concept of GrSCM (Green Supply Chain Management) in the academic and research field is still thought to be in the development stage especially in Asian Emerging Economies. The purpose of this paper is to contribute significantly to the first wave of empirical investigation on GrSCM Practices and Firm Performance measures in Pakistan. The aim of this research is to develop a more holistic approach towards investigating the impact of Green Supply Chain Management Practices (Ecodesign, Internal Environmental Management systems, Green Distribution, Green Purchasing and Cooperation with Customers) on multiple dimensions of Firm Performance Measures (Economic Performance, Environmental Performance and Operational Performance) with a mediating role of Investment Recovery and Competitiveness. This paper also serves as an initiative to identify if the relationship between Investment Recovery and Firm Performance Measures is mediated by Competitiveness. Design/ Methodology/Approach: This study is based on survey Data collected from 272, ISO (14001) Certified Textile Firms Based in Lahore, Faisalabad, and Karachi which are involved in Spinning, Dyeing, Printing or Bleaching. A Theoretical model was developed incorporating the constructs representing Green Activities and Firm Performance Measures of a firm. The data was analyzed using Partial Least Square Structural Equation Modeling. Senior and Mid-level managers provided the data reflecting the degree to which their organizations deal with both internal and external stakeholders to improve the environmental sustainability of their supply chain. Findings: Of the 36 proposed Hypothesis, 20 are considered valid and significant. The statistics result reveal that GrSCM practices positively impact Environmental Performance followed by Economic and Operational Performance. Investment Recovery acts as a strong mediator between Intra organizational Green activities and performance outcomes. The relationship of Reverse Logistics influencing outcomes is significantly mediated by Competitiveness. The pressure originating from customers exert significant positive influence on the firm to adopt Green Practices consequently leading to higher outcomes. Research Contribution/Originality: Underpinning the Resource dependence theory and as a first wave of investigating the impact of Green Supply chain on performance outcomes in Pakistan, this study intends to make a prominent mark in the field of research. Investment and Competitiveness together are tested as a mediator for the first time in this arena. Managerial implications: Practitioner is provided with a framework for assessing the synergistic impact of GrSCM practices on performance. Upgradation of Accreditations and Audit Programs on regular basis are the need of the hour. Making the processes leaner with the sale of excess inventories and scrap helps the firm to work more efficiently and productively.

Keywords: economic performance, environmental performance, green supply chain management practices, operational performance, sustainability, a textile sector of Pakistan

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Authors: Marina Shakleina, Konstantin Shaklein, Stanislav Yakiro

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The digitalization of modern human life over the last decade has facilitated the acquisition, storage, and processing of data, which are used to detect changes in consumer preferences and to improve the internal efficiency of the production process. This emerging trend has attracted academic interest in the use of big data in research. The study focuses on modeling the social comfort of the Russian population for the period 2010-2021 using big data. Big data provides enormous opportunities for understanding human interactions at the scale of society with plenty of space and time dynamics. One of the most popular big data sources is Google Trends. The methodology for assessing social comfort using big data involves several steps: 1. 574 words were selected based on the Harvard IV-4 Dictionary adjusted to fit the reality of everyday Russian life. The set of keywords was further cleansed by excluding queries consisting of verbs and words with several lexical meanings. 2. Search queries were processed to ensure comparability of results: the transformation of data to a 10-point scale, elimination of popularity peaks, detrending, and deseasoning. The proposed methodology for keyword search and Google Trends processing was implemented in the form of a script in the Python programming language. 3. Block and summary integral indicators of social comfort were constructed using the first modified principal component resulting in weighting coefficients values of block components. According to the study, social comfort is described by 12 blocks: ‘health’, ‘education’, ‘social support’, ‘financial situation’, ‘employment’, ‘housing’, ‘ethical norms’, ‘security’, ‘political stability’, ‘leisure’, ‘environment’, ‘infrastructure’. According to the model, the summary integral indicator increased by 54% and was 4.631 points; the average annual rate was 3.6%, which is higher than the rate of economic growth by 2.7 p.p. The value of the indicator describing social comfort in Russia is determined by 26% by ‘social support’, 24% by ‘education’, 12% by ‘infrastructure’, 10% by ‘leisure’, and the remaining 28% by others. Among 25% of the most popular searches, 85% are of negative nature and are mainly related to the blocks ‘security’, ‘political stability’, ‘health’, for example, ‘crime rate’, ‘vulnerability’. Among the 25% most unpopular queries, 99% of the queries were positive and mostly related to the blocks ‘ethical norms’, ‘education’, ‘employment’, for example, ‘social package’, ‘recycling’. In conclusion, the introduction of the latent category ‘social comfort’ into the scientific vocabulary deepens the theory of the quality of life of the population in terms of the study of the involvement of an individual in the society and expanding the subjective aspect of the measurements of various indicators. Integral assessment of social comfort demonstrates the overall picture of the development of the phenomenon over time and space and quantitatively evaluates ongoing socio-economic policy. The application of big data in the assessment of latent categories gives stable results, which opens up possibilities for their practical implementation.

Keywords: big data, Google trends, integral indicator, social comfort

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Authors: Sumedha Weerasekara, Morgan Miles, Mark Morrison, Branka Krivokapic-Skoko

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This paper is aimed at exploring the interrelationships among entrepreneurial ecosystem factors and entrepreneurial cognition in regional and metropolitan ecosystems. Entrepreneurial ecosystem factors examined include: culture, infrastructure, access to finance, informal networks, support services, access to universities, and the depth and breadth of the talent pool. Using a multivariate approach we explore the impact of these ecosystem factors or elements on entrepreneurial cognition. In doing so, the existing body of knowledge from the literature on entrepreneurial ecosystem and cognition have been blended to explore the relationship between entrepreneurial ecosystem factors and cognition in a way not hitherto investigated. The concept of the entrepreneurial ecosystem has received increased attention as governments, universities and communities have started to recognize the potential of integrated policies, structures, programs and processes that foster entrepreneurship activities by supporting innovation, productivity and employment growth. The notion of entrepreneurial ecosystems has evolved and grown with the advancement of theoretical research and empirical studies. Importance of incorporating external factors like culture, political environment, and the economic environment within a single framework will enhance the capacity of examining the whole systems functionality to better understand the interaction of the entrepreneurial actors and factors within a single framework. The literature on clusters underplays the role of entrepreneurs and entrepreneurial management in creating and co-creating organizations, markets, and supporting ecosystems. Entrepreneurs are only one actor following a limited set of roles and dependent upon many other factors to thrive. As a consequence, entrepreneurs and relevant authorities should be aware of the other actors and factors with which they engage and rely, and make strategic choices to achieve both self and also collective objectives. The study uses stratified random sampling method to collect survey data from 12 different regions in regional and metropolitan regions of NSW, Australia. A questionnaire was administered online among 512 Small and medium enterprise owners operating their business in selected 12 regions in NSW, Australia. Data were analyzed using descriptive analyzing techniques and partial least squares - structural equation modeling. The findings show that even though there is a significant relationship between each and every entrepreneurial ecosystem factors, there is a weak relationship between most entrepreneurial ecosystem factors and entrepreneurial cognition. In the metropolitan context, the availability of finance and informal networks have the largest impact on entrepreneurial cognition while culture, infrastructure, and support services having the smallest impact and the talent pool and universities having a moderate impact on entrepreneurial cognition. Interestingly, in a regional context, culture, availability of finance, and the talent pool have the highest impact on entrepreneurial cognition, while informal networks having the smallest impact and the remaining factors – infrastructure, universities, and support services have a moderate impact on entrepreneurial cognition. These findings suggest the need for a location-specific strategy for supporting the development of entrepreneurial cognition.

Keywords: academic achievement, colour response card, feedback

Procedia PDF Downloads 117

Authors: Hanan Begali, Shahi Dost, Annett Ziegler, Markus Cornberg, Maria-Esther Vidal, Anke R. M. Kraft

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Chronic hepatitis B virus (HBV) infection can be treated with nucleot(s)ide analog (NA), for example, which inhibits HBV replication. However, they have hardly any influence on the functional cure of HBV, which is defined by hepatitis B surface antigen (HBsAg) loss. NA needs to be taken life-long, which is not available for all patients worldwide. Additionally, NA-treated patients are still at risk of developing cirrhosis, liver failure, or hepatocellular carcinoma (HCC). Although each patient has the same components of the immune system, immune responses vary between patients. Therefore, a deeper understanding of the immune response against HBV in different patients is necessary to understand the parameters leading to HBV cure and to use this knowledge to optimize HBV therapies. This requires seamless integration of an enormous amount of diverse and fine-grained data from viral markers, e.g., hepatitis B core-related antigen (HBcrAg) and hepatitis B surface antigen (HBsAg). The data integration system relies on the assumption that profiling human immune systems requires the analysis of various variables (e.g., demographic data, treatments, pre-existing conditions, immune cell response, or HLA-typing) rather than only one. However, the values of these variables are collected independently. They are presented in a myriad of formats, e.g., excel files, textual descriptions, lab book notes, and images of flow cytometry dot plots. Additionally, patients can be identified differently in these analyses. This heterogeneity complicates the integration of variables, as data management techniques are needed to create a unified view in which individual formats and identifiers are transparent when profiling the human immune systems. The proposed study (HBsRE) aims at integrating heterogeneous data sets of 87 chronically HBV-infected patients, e.g., clinical data, immune cell response, and HLA-typing, with knowledge encoded in biomedical ontologies and open-source databases into a knowledge-driven framework. This new technique enables us to harmonize and standardize heterogeneous datasets in the defined modeling of the data integration system, which will be evaluated in the knowledge graph (KG). KGs are data structures that represent the knowledge and data as factual statements using a graph data model. Finally, the analytic data model will be applied on top of KG in order to develop a deeper understanding of the immune profiles among various patients and to evaluate factors playing a role in a holistic profile of patients with HBsAg level loss. Additionally, our objective is to utilize this unified approach to stratify patients for new effective treatments. This study is developed in the context of the project “Transforming big data into knowledge: for deep immune profiling in vaccination, infectious diseases, and transplantation (ImProVIT)”, which is a multidisciplinary team composed of computer scientists, infection biologists, and immunologists.

Keywords: chronic hepatitis B infection, immune response, knowledge graphs, ontology

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Authors: Natalia V. Naryzhnaya, Alexandr V. Mukhomedzyanov, Ivan A. Derkachev, Boris K. Kurbatov, Leonid N. Maslov

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Background: Techniques of adaptation to hypoxia and remote postconditioning (RPost) have great prospects for use in the clinic. However, recent studies have shown low efficacy of remote postconditioning in patients with AMI. We hypothesize that the reasons for this inefficiency may be metabolic disorders, which are very common, especially in patients with cardiovascular disease, and age of patients. The purpose of the study was to reveal the effectiveness of adaptation to chronic hypoxia and RPost. To determine the possible relationship between the decrease in the effectiveness of projective impacts and disorders of carbohydrate and lipid metabolism. Design: The study was carried out on Wistar rats 60 day old. MetS was induced by high-carbohydrate, high-fat diet (HСHFD). Modeling MS led to the formation of obesity, hypertension, impaired lipid and carbohydrate metabolism, hyperleptinemia, and moderate stress. Groups with adaptation to chronic hypoxia were subjected to hypoxia for 21 days at 12% O2 and 0.3% CO2 after complete of HСHFD. All animals were subjected to 45 min coronary occlusion and 120 min reperfusion. Groups with RPost, immediately after the end of ischemia, tourniquets were applied to the hind limbs in the area of the hip joint (3 times in the mode of 5 min ischemia, 5 min reperfusion). Results: RPost led to a twofold reduction of infarct size in rats with intact metabolism (р < 0.0001), while in rats with MetS, a decrease in infarct size during RPost was 25 % (p = 0.00003). A direct correlation was found between of infarct size during RPost and the serum leptin level of rats with MetC (r = 0.85). The presented data suggested that a decrease in the efficiency of remote postconditioning in rats with diet-induced metabolic syndrome depends on serum leptin. Chronic hypoxia resulted in a 38% reduced in infarct size in metabolically intact rats. The decrease of cardioprotection was observed in rats with chronic hypoxia and MetS. Infarct size showed a direct correlation with impaired glucose tolerance (AUC, glucose tolerance test, r = 0.034) and serum triglyceride levels (r = 0.39). Our study showed the dependence of cardioprotection in rats with metabolic syndrome during chronic hypoxia and DPost on opioids in the blood serum and myocardium, protein kinase C and NO synthase activity. Conclusion: The results obtained showed that the infarct-limiting efficiency of adaptation to hypoxia and remote postconditioning is reduced or completely absent in animals with metabolic syndrome. The increase in the infarction, in this case, directly depends on the disturbances in carbohydrate. lipid metabolism and opioids signaling. Funding: Investigation of effectiveness of chronic hypoxia at the metabolic syndrome was carried out within the support of Russian Science Foundation Grant 22-15-00048. Studies of the mechanisms of arterial hypertension in induced metabolic syndrome were carried out within the framework of the state assignment (122020300042-4). The work was performed using the Center for Collective Use "Medical Genomics".

Keywords: chronic hypoxia, opioids, remote postconditioning, metabolic syndrome

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Authors: Mohkammad Nur Cahyadi, Imam Wahyu Farid, Ronny Mardianto, Agung Budi Cahyono, Eko Yuli Handoko, Daud Wahyu Imani, Arizal Bawazir, Luki Adi Triawan

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Unmanned aerial vehicle (UAV) technology has cost efficiency and data retrieval time advantages. Using technologies such as UAV, GNSS, and LiDAR will later be combined into one of the newest technologies to cover each other's deficiencies. This integration system aims to increase the accuracy of calculating the volume of the land stockpile of PT. Garam (Salt Company). The use of UAV applications to obtain geometric data and capture textures that characterize the structure of objects. This study uses the Taror 650 Iron Man drone with four propellers, which can fly for 15 minutes. LiDAR can classify based on the number of image acquisitions processed in the software, utilizing photogrammetry and structural science principles from Motion point cloud technology. LiDAR can perform data acquisition that enables the creation of point clouds, three-dimensional models, Digital Surface Models, Contours, and orthomosaics with high accuracy. LiDAR has a drawback in the form of coordinate data positions that have local references. Therefore, researchers use GNSS, LiDAR, and drone multi-sensor technology to map the stockpile of salt on open land and warehouses every year, carried out by PT. Garam twice, where the previous process used terrestrial methods and manual calculations with sacks. Research with LiDAR needs to be combined with UAV to overcome data acquisition limitations because it only passes through the right and left sides of the object, mainly when applied to a salt stockpile. The UAV is flown to assist data acquisition with a wide coverage with the help of integration of the 200-gram LiDAR system so that the flying angle taken can be optimal during the flight process. Using LiDAR for low-cost mapping surveys will make it easier for surveyors and academics to obtain pretty accurate data at a more economical price. As a survey tool, LiDAR is included in a tool with a low price, around 999 USD; this device can produce detailed data. Therefore, to minimize the operational costs of using LiDAR, surveyors can use Low-Cost LiDAR, GNSS, and UAV at a price of around 638 USD. The data generated by this sensor is in the form of a visualization of an object shape made in three dimensions. This study aims to combine Low-Cost GPS measurements with Low-Cost LiDAR, which are processed using free user software. GPS Low Cost generates data in the form of position-determining latitude and longitude coordinates. The data generates X, Y, and Z values to help georeferencing process the detected object. This research will also produce LiDAR, which can detect objects, including the height of the entire environment in that location. The results of the data obtained are calibrated with pitch, roll, and yaw to get the vertical height of the existing contours. This study conducted an experimental process on the roof of a building with a radius of approximately 30 meters.

Keywords: LiDAR, unmanned aerial vehicle, low-cost GNSS, contour

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Authors: A. Odoom, A. Salama, H. Ibrahim

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Hydrogen is a clean source of energy for power production and transportation. The main source of hydrogen in this research is biodiesel. Glycerol also called glycerine is a by-product of biodiesel production by transesterification of vegetable oils and methanol. This is a reliable and environmentally-friendly source of hydrogen production than fossil fuels. A typical composition of crude glycerol comprises of glycerol, water, organic and inorganic salts, soap, methanol and small amounts of glycerides. Crude glycerol has limited industrial application due to its low purity thus, the usage of crude glycerol can significantly enhance the sustainability and production of biodiesel. Reforming techniques is an approach for hydrogen production mainly Steam Reforming (SR), Autothermal Reforming (ATR) and Partial Oxidation Reforming (POR). SR produces high hydrogen conversions and yield but is highly endothermic whereas POR is exothermic. On the downside, PO yields lower hydrogen as well as large amount of side reactions. ATR which is a fusion of partial oxidation reforming and steam reforming is thermally neutral because net reactor heat duty is zero. It has relatively high hydrogen yield, selectivity as well as limits coke formation. The complex chemical processes that take place during the production phases makes it relatively difficult to construct a reliable and robust numerical model. Numerical model is a tool to mimic reality and provide insight into the influence of the parameters. In this work, we introduce a finite volume numerical study for an 'in-house' lab-scale experiment of ATR. Previous numerical studies on this process have considered either using Comsol or nodal finite difference analysis. Since Comsol is a commercial package which is not readily available everywhere and lab-scale experiment can be considered well mixed in the radial direction. One spatial dimension suffices to capture the essential feature of ATR, in this work, we consider developing our own numerical approach using MATLAB. A continuum fixed bed reactor is modelled using MATLAB with both pseudo homogeneous and heterogeneous models. The drawback of nodal finite difference formulation is that it is not locally conservative which means that materials and momenta can be generated inside the domain as an artifact of the discretization. Control volume, on the other hand, is locally conservative and suites very well problems where materials are generated and consumed inside the domain. In this work, species mass balance, Darcy’s equation and energy equations are solved using operator splitting technique. Therefore, diffusion-like terms are discretized implicitly while advection-like terms are discretized explicitly. An upwind scheme is adapted for the advection term to ensure accuracy and positivity. Comparisons with the experimental data show very good agreements which build confidence in our modeling approach. The models obtained were validated and optimized for better results.

Keywords: autothermal reforming, crude glycerol, hydrogen, numerical model

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Authors: Oibar Martinez, Clara Oliver, Jose Miguel Miranda

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

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

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Authors: Andrzej Szewczak

Abstract:

Study of the effect of high temperatures on polymer coatings represents an important field of research of their properties. Polymers, as materials with numerous features (chemical resistance, ease of processing and recycling, corrosion resistance, low density and weight) are currently the most widely used modern building materials, among others in the resin concrete, plastic parts, and hydrophobic coatings. Unfortunately, the polymers have also disadvantages, one of which decides about their usage - low resistance to high temperatures and brittleness. This applies in particular thin and flexible polymeric coatings applied to other materials, such a steel and concrete, which degrade under varying thermal conditions. Research about improvement of this state includes methods of modification of the polymer composition, structure, conditioning conditions, and the polymerization reaction. At present, ways are sought to reflect the actual environmental conditions, in which the coating will be operating after it has been applied to other material. These studies are difficult because of the need for adopting a proper model of the polymer operation and the determination of phenomena occurring at the time of temperature fluctuations. For this reason, alternative methods are being developed, taking into account the rapid modeling and the simulation of the actual operating conditions of polymeric coating’s materials in real conditions. The nature of a duration is typical for the temperature influence in the environment. Studies typically involve the measurement of variation one or more physical and mechanical properties of such coating in time. Based on these results it is possible to determine the effects of temperature loading and develop methods affecting in the improvement of coatings’ properties. This paper contains a description of the stability studies of silicone coatings deposited on the surface of a ceramic brick. The brick’s surface was hydrophobized by two types of inorganic polymers: nano-polymer preparation based on dialkyl siloxanes (Series 1 - 5) and an aqueous solution of the silicon (series 6 - 10). In order to enhance the stability of the film formed on the brick’s surface and immunize it to variable temperature and humidity loading, the nano silica was added to the polymer. The right combination of the polymer liquid phase and the solid phase of nano silica was obtained by disintegration of the mixture by the sonification. The changes of viscosity and surface tension of polymers were defined, which are the basic rheological parameters affecting the state and the durability of the polymer coating. The coatings created on the brick’s surfaces were then subjected to a temperature loading of 100° C and moisture by total immersion in water, in order to determine any water absorption changes caused by damages and the degradation of the polymer film. The effect of moisture and temperature was determined by measurement (at specified number of cycles) of changes in the surface hardness (using a Vickers’ method) and the absorption of individual samples. As a result, on the basis of the obtained results, the degradation process of polymer coatings related to their durability changes in time was determined.

Keywords: silicones, siloxanes, surface hardness, temperature, water absorption

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Authors: Davide Palma, Dimitra Papagiannaki, Marco Minella, Manuel Lai, Rita Binetti, Claire Richard

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Modern analytical technologies allow us to detect water contaminants at trace and ultra-trace concentrations highlighting how a large number of organic compounds is not efficiently abated by most wastewater treatment facilities relying on biological processes; we usually refer to these micropollutants as contaminants of emerging concern (CECs). The availability of reliable end effective technologies, able to guarantee the high standards of water quality demanded by legislators worldwide, has therefore become a primary need. In this context, water plasma stands out among developing technologies as it is extremely effective in the abatement of numerous classes of pollutants, cost-effective, and environmentally friendly. In this work, a custom-built non-thermal pulsed plasma discharge generator was used to abate the concentration of selected CECs in the water samples. Samples were treated in a 50 mL pyrex reactor using two different types of plasma discharge occurring at the surface of the treated solution or, underwater, working with positive polarity. The distance between the tips of the electrodes determined where the discharge was formed: underwater when the distance was < 2mm, at the water surface when the distance was > 2 mm. Peak voltage was in the 100-130kV range with typical current values of 20-40 A. The duration of the pulse was 500 ns, and the frequency of discharge could be manually set between 5 and 45 Hz. Treatment of 100 µM diclofenac solution in MilliQ water, with a pulse frequency of 17Hz, revealed that surface discharge was more efficient in the degradation of diclofenac that was no longer detectable after 6 minutes of treatment. Over 30 minutes were required to obtain the same results with underwater discharge. These results are justified by the higher rate of H₂O₂ formation (21.80 µmolL⁻¹min⁻¹ for surface discharge against 1.20 µmolL⁻¹min⁻¹ for underwater discharge), larger discharge volume and UV light emission, high rate of ozone and NOx production (up to 800 and 1400 ppb respectively) observed when working with surface discharge. Then, the surface discharge was used for the treatment of the three selected perfluoroalkyl compounds, namely, perfluorooctanoic acid (PFOA), perfluorohexanoic acid (PFHxA), and pefluorooctanesulfonic acid (PFOS) both individually and in mixture, in ultrapure and groundwater matrices with initial concentration of 1 ppb. In both matrices, PFOS exhibited the best degradation reaching complete removal after 30 min of treatment (degradation rate 0.107 min⁻¹ in ultrapure water and 0.0633 min⁻¹ in groundwater), while the degradation rate of PFOA and PFHxA was slower of around 65% and 80%, respectively. Total nitrogen (TN) measurements revealed levels up to 45 mgL⁻¹h⁻¹ in water samples treated with surface discharge, while, in analogous samples treated with underwater discharge, TN increase was 5 to 10 times lower. These results can be explained by the significant NOx concentrations (over 1400 ppb) measured above functioning reactor operating with superficial discharge; rapid NOx hydrolysis led to nitrates accumulation in the solution explaining the observed evolution of TN values. Ionic chromatography measures confirmed that the vast majority of TN was under the form of nitrates. In conclusion, non-thermal pulsed plasma discharge, obtained with a custom-built generator, was proven to effectively degrade diclofenac in water matrices confirming the potential interest of this technology for wastewater treatment. The surface discharge was proven to be more effective in CECs removal due to the high rate of formation of H₂O₂, ozone, reactive radical species, and strong UV light emission. Furthermore, nitrates enriched water obtained after treatment could be an interesting added-value product to be used as fertilizer in agriculture. Acknowledgment: This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 765860.

Keywords: CECs removal, nitrogen fixation, non-thermal plasma, water treatment

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