Search results for: adaptive – PSO

Authors: Samhita Mummadi, Sree Divya Nagalli, Harshini Vemuri, Saketh Charan Nakka, Sumesh K. J.

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One of the most significant challenges faced by people in today’s digital era is an alarming increase in fraudulent activities on online platforms. The fascination with online shopping to avoid long queues in shopping malls, the availability of a variety of products, and home delivery of goods have paved the way for a rapid increase in vast online shopping platforms. This has had a major impact on increasing fraudulent activities as well. This loop of online shopping and transactions has paved the way for fraudulent users to commit fraud. For instance, consider a store that orders thousands of products all at once, but what’s fishy about this is the massive number of items purchased and their transactions turning out to be fraud, leading to a huge loss for the seller. Considering scenarios like these underscores the urgent need to introduce machine learning approaches to combat fraud in online shopping. By leveraging robust algorithms, namely KNN, Decision Trees, and Random Forest, which are highly effective in generating accurate results, this research endeavors to discern patterns indicative of fraudulent behavior within transactional data. Introducing a comprehensive solution to this problem in order to empower e-commerce administrators in timely fraud detection and prevention is the primary motive and the main focus. In addition to that, sentiment analysis is harnessed in the model so that the e-commerce admin can tailor to the customer’s and consumer’s concerns, feedback, and comments, allowing the admin to improve the user’s experience. The ultimate objective of this study is to ramp up online shopping platforms against fraud and ensure a safer shopping experience. This paper underscores a model accuracy of 84%. All the findings and observations that were noted during our work lay the groundwork for future advancements in the development of more resilient and adaptive fraud detection systems, which will become crucial as technologies continue to evolve.

Keywords: behavior analysis, feature selection, Fraudulent pattern recognition, imbalanced classification, transactional anomalies

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Authors: Kamila Irena Szpunar

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The central idea of the study is considered from two perspectives. The first perspective includes the interpersonal relationships formed by coach and athlete. Another perspective is connected with motivational environment which is created by the coach in team. This study will show the interplay between the perceived motivational climate created by the coach and the interpersonal dynamics between coaches and athletes. It is important because it will supply knowledge of the interpersonal conditions that can foster adaptive or maladaptive behavior in sport conditions. It also ensures implications for understanding how the perceived motivational atmosphere in a team is manifested at the level of coach – athlete relationship and interactions. The primary purpose of the study was to identify the association between coach-athlete relationship and athletes' perception of the motivational climate in team sports. The secondary purposes examined the differences between female and male athletes in perceiving of the motivational climate and the coach athlete-relationship. To check coach-athlete relationship Polish translation of The Coach-Athlete Relationship Questionnaire will be used. It measures athletes' perceptions of coach- athlete relationship defined by 3+1 Cs conceptual model of the coach-athlete relationship. From this model were used three constructs such as closeness (feelings of trust, respect etc.), commitment (thoughts about the future of the relationship), and complementarity (co-operative interactions during practice sessions). To check perceived motivational climate will be used Polish translation of The Perceived Motivational Climate in Sport Questionnaire-2 (PMCSQ-2). PMCSQ-2 was created to assess athletes' perceptions of the motivational climates in their teams. The questionnaire includes two general dimensions, the perceived task-involving climate and the perceived ego-involving climate; each contains three subscales. To check the associations between elements the motivational climate and coach-athlete relationship was used canonical correlation analysis. Student's t-test was used to check gender differences in athletes' perceptions of the motivational climate and the coach-athlete relationship. The findings suggest that in Polish athletes' perceptions of the coach-athlete relationship have motivational significance and that there are gender differences between female and male athletes in both variables – coach-athlete relationship and kind of motivational climate. According to the author's knowledge, such kind of study has not been conducted in Polish conditions before and is the first study on the subject of the motivational climate and the coach-athlete relationship in Poland. Information from this study can be useful for the development of interventions for enhancing the quality of coach- athlete relationship and its associated outcomes connected with motivational climate.

Keywords: coach-athlete relationship, ego-involving climate, motivational climate, task-involving climate

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Authors: V. Argyropoulos, M. Nikolaraizi, K. Tanou

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There is little available information concerning the cognitive and communicative abilities of the people who are deaf-blind. This mainly stems from the general inadequacy of existing assessment instruments employed with deafblind individuals. Although considerable variability exists with regard to cognitive capacities of the deaf-blind, careful examination of the literature reveals that the majority of these persons suffer from significant deficits in cognitive and adaptive functioning. The few reports available primarily are case studies, narrative program descriptions, or position papers by workers in the field. Without the objective verification afforded by controlled research, specialists in psychology, education, and other rehabilitation services must rely on personal speculations or biases to guide their decisions in the planning, implementation, and evaluation of services to deaf-blind children and adults. This paper highlights the framework and discusses the results of an action research network. The aim of this study was twofold: a) to describe and analyse the different ways in which a student with deafblindness approached a number of developmental issues such as novel tasks, exploration and manipulation of objects, reactions to social stimuli, motor coordination, and quality of play and b) to map the appropriate functional approach for the specific student that could be used to develop strategies for classroom participation and socialization. The persons involved in this collaborative action research scheme were general teachers, a school counsellor, academic staff and student teachers. Rating scales and checklists were used to gather information in natural activities and settings, and additional data were also obtained through interviews with the educators of the student. The findings of this case study indicated that there is a great need to focus on the development of effective intervention strategies. The results showed that the identification of positive reinforcers for this population might represent an important and challenging aspect of behaviour programmes. Finally, the findings suggest that additional empirical work is needed to increase attention to methodological and social validity issues.

Keywords: action research, cognitive and communicative abilities, deafblindness, effective strategies

Procedia PDF Downloads 185

Authors: Piotr Podlipniak

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Social consolidation has often been indicated as an adaptive function of music which led to the evolution of music faculty. According to many scholars this function is possible thanks to musical rhythm that enables sensorimotor synchronization to a musical beat. The ability to synchronize to music allows performing music collectively which enhances social cohesion. However, the collective performance of music consists also in spectral synchronization that depends on musical pitch structure. Similarly to rhythmic synchronization, spectral synchronization is a result of ‘brain states alignment’ between people who collectively listen to or perform music. In order to successfully synchronize pitches performers have to adequately expect the pitch structure. The most common form of music which predominates among all human societies is tonal music. In fact tonality understood in the broadest sense as such an organization of musical pitches in which some pitch is more important than others is the only kind of musical pitch structure that has been observed in all currently known musical cultures. The perception of such a musical pitch structure elicits specific emotional reactions which are often described as tensions and relaxations. These facts provoke some important questions. What is the evolutionary reason that people use pitch structure as a form of vocal communication? Why different pitch structures elicit different emotional states independent of extra-musical context? It is proposed in the current presentation that in the course of evolution pitch structure became a human specific tool of communication the function of which is to induce emotional states such as uncertainty and cohesion. By the means of eliciting these emotions during collective music performance people are able to unconsciously give cues concerning social acceptance. This is probably one of the reasons why in all cultures people collectively perform tonal music. It is also suggested that tonal pitch structure had been invented socially before it became an evolutionary innovation of Homo sapiens. It means that a predisposition to tonally organize pitches evolved by the means of ‘Baldwin effect’ – a process in which natural selection transforms the learned response of an organism into the instinctive response. The hypothetical evolutionary scenario of the emergence of tonal pitch structure will be proposed. In this scenario social forces such as a need for closer cooperation play the crucial role.

Keywords: emotion, evolution, tonality, social consolidation

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Authors: J. Oustric, L. Berti, J. Santini

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Nowadays, the objective of durable agriculture, and in particular organic agriculture, is to reduce the level of fertilizer inputs used in crops. Limiting the quantity of fertilizer inputs would optimize the economical result and minimizing the environmental impact. Nutrient deficiency, particularly of a major nutrient (N, P, and K), can seriously affect fruit production and quality. In citrus crops, rootstock/scion combinations. In citrus crop, scion/rootstock combinations are used frequently to improve tolerance to various abiotic stresses. New rootstocks are needed to respond to these constraints, and the use of new tetraploid rootstocks better adapted to lower nutrient intake could offer a promising way forward. The aim of this work was to determine whether a better tolerance to nutrient deficiency could be observed in a doubled diploid seedling and whether this tolerance could be observed in common clementine scion if used as rootstocks. We selected diploid (CM2x) and doubled diploid (CM4x) Citrumelo 4475 seedlings and common clementine (C) grafted onto Citrumelo 4475 diploid (C/CM2x) and doubled diploid (C/CM4x) rootstocks. Nutrient deficiency effects on the seedlings and scion/rootstock combinations were analyzed by studying anatomical, structural and ultrastructural determinants (chlorosis, stomata, ostiole and cells and their organelles), photosynthetic properties (leaf net photosynthetic rate (Pₙₑₜ), stomatal conductance (gₛ), chlorophyll a fluorescence (Fᵥ/Fₘ)) and oxidative marker (malondialdehyde). Nutrient deficiency affected differently foliar tissues, physiological parameters, and oxidative metabolism in leaves of seedlings depending on their ploidy level and of common clementine scion depending on their rootstocks ploidy level. Both CM4x and C/CM4x presented lower foliar damages (chlorosis, chloroplasts, mitochondria, and plastoglobuli), photosynthesis processes alteration (Pₙₑₜ, gₛ, and Fᵥ/Fₘ), and malondialdehyde accumulation than CM2x and C/CM2x after nutrient deficiency. Doubled diploid Citrumelo 4475 can improve nutrient deficiency tolerance, and its use as a rootstock allows to confer this tolerance to the common clementine scion.

Keywords: nutrient deficiency, oxidative stress, photosynthesis, polyploid rootstocks

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Authors: Hannah Rosenqvist, Fanny Guay

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Critical infrastructure protection has been an important topic for several years. Programmes such as the European Programme for Critical Infrastructure Protection (EPCIP), Critical Infrastructure Warning Information Network (CIWIN) and the European Reference Network for Critical Infrastructure Protection (ENR-CIP) have been the pillars to the work done since 2006. However, measuring critical infrastructure resilience has not been an easy task. This has to do with the fact that the concept of resilience has several definitions and is applied in different domains such as engineering and social sciences. Since June 2015, the EU project IMPROVER has been focusing on developing a methodology for implementing a combination of societal, organizational and technological resilience concepts, in the hope to increase critical infrastructure resilience. For this paper, we performed research on how to include societal resilience as a form of measurement of the context of critical infrastructure resilience. Because one of the main purposes of critical infrastructure (CI) is to deliver services to the society, we believe that societal resilience is an important factor that should be considered when assessing the overall CI resilience. We found that existing methods for CI resilience assessment focus mainly on technical aspects and therefore that is was necessary to develop a resilience model that take social factors into account. The model developed within the project IMPROVER aims to include the community’s expectations of infrastructure operators as well as information sharing with the public and planning processes. By considering such aspects, the IMPROVER framework not only helps operators to increase the resilience of their infrastructures on the technical or organizational side, but aims to strengthen community resilience as a whole. This will further be achieved by taking interdependencies between critical infrastructures into consideration. The knowledge gained during this project will enrich current European policies and practices for improved disaster risk management. The framework for societal resilience analysis is based on three dimensions for societal resilience; coping capacity, adaptive capacity and transformative capacity which are capacities that have been recognized throughout a widespread literature review in the field. A set of indicators have been defined that describe a community’s maturity within these resilience dimensions. Further, the indicators are categorized into six community assets that need to be accessible and utilized in such a way that they allow responding to changes and unforeseen circumstances. We conclude that the societal resilience model developed within the project IMPROVER can give a good indication of the level of societal resilience to critical infrastructure operators.

Keywords: community resilience, critical infrastructure protection, critical infrastructure resilience, societal resilience

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Authors: Michael Wagner, Philipp Steinbauer, Andrea Katharina Lietz, Alexander Hoffelner, Johannes Fessler

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Background: Cardiopulmonary resuscitations are stressful situations in which vital decisions must be made within seconds. Lack of routine due to the infrequency of pediatric emergencies can lead to serious medical and communication errors. Virtual reality can fundamentally change the way simulation training is conducted in the future. It appears to be a useful learning tool for technical and non-technical skills. It is important to investigate the use of VR in providing a strong sense of presence within simulations. Methods: In this randomized study, we will enroll doctors and medical students from the Medical University of Vienna, who will receive learning material regarding the resuscitation of a one-year-old child. The study will be conducted in three phases. In the first phase, 20 physicians and 20 medical students from the Medical University of Vienna will be included. They will perform simulation-based training with a standardized scenario of a critically ill child with a hypovolemic shock. The main goal of this phase is to establish a baseline for the following two phases to generate comparative values regarding cognitive load and stress. In phase 2 and 3, the same participants will perform the same scenario in a VR setting. In both settings, on three set points of progression, one of three predefined events is triggered. For each event, three different stress levels (easy, medium, difficult) will be defined. Stress and cognitive load will be analyzed using the NASA Task Load Index, eye-tracking parameters, and heart rate. Subsequently, these values will be compared between VR training and traditional simulation-based training. Hypothesis: We hypothesize that the VR training and the traditional training groups will not differ in physiological response (cognitive load, heart rate, and heart rate variability). We further assume that virtual reality training can be used as cost-efficient additional training. Objectives: The aim of this study is to measure cognitive load and stress level during a real-life simulation training and compare it with VR training in order to show that VR training evokes the same physiological response and cognitive load as real-life simulation training.

Keywords: virtual reality, cognitive load, simulation, adaptive virtual reality training

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Authors: Sabli, Eddy Rismunandar, Akhirudin, Nana Halim, Zulfikar, Nining Dwirosanti, Wila Ningsih, Pipih Siti Sofiah, Danik Dania Asadayanti, Dewi Eka Arini Algozi, Gita Mahardika Pamuji, Ajun, Mangasa Aritonang, Nanang Rukmana, Arief Rachman Wonodhipo, Victor Imanuel Nahumury, Lili Husada, Wawan Saepul Irwan, Al Mukhlas Fikri

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Covid-19 pandemic has widely impacted the lives. An adaptive strategy must be quickly formulated to maintain the quality of education, especially by vocational school which technical skill competencies are highly needed. This study aimed to evaluate the effectiveness of e-training on the attitude and skill competencies of vocational high school teachers in Indonesia. A total of 720 Indonesian vocational high school teachers with various programs, including hospitality, administration, online business and marketing, culinary arts, fashion, cashier, tourism, haircut, and accounting participated e-training for a month. The training used electronic learning management system to provide materials (modules, presentation slides, and tutorial videos), tasks, and evaluations. Tutorial class was carried out by video conference meeting. Attitude and skill competencies were evaluated before and after the training. Meanwhile, the teachers also gave satisfactory feedback on the quality of the organizer and tutors. Data analysis used paired sample t-test and Anova with Tukey’s post hoc test. The results showed that e-training significantly increased the score of attitude and skill competencies of the teachers (p <0,05). Moreover, the remarkable increase was found among hospitality (57,5%), cashier (50,1%), and online business and marketing (48,7%) teachers. However, the effect among fashion, tourism and haircut teachers was less obvious. In addition, the satisfactory score on the quality of the organizer and tutors were 88,9 (very good), and 93,5 (excellence), respectively. The study concludes that a well-organized e-training could increase the attitude and skill competencies of Indonesian vocational high school teachers during Covid-19 pandemic.

Keywords: E-training, skill, teacher, vocational high school

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Authors: Ahmet Karagoz, Irfan Karagoz

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Synthetic Aperture Radar (SAR) is a radar mechanism that can be integrated into manned and unmanned aerial vehicles to create high-resolution images in all weather conditions, regardless of day and night. In this study, SAR images of military vehicles with different azimuth and descent angles are pre-processed at the first stage. The main purpose here is to reduce the high speckle noise found in SAR images. For this, the Wiener adaptive filter, the mean filter, and the median filters are used to reduce the amount of speckle noise in the images without causing loss of data. During the image segmentation phase, pixel values are ordered so that the target vehicle region is separated from other regions containing unnecessary information. The target image is parsed with the brightest 20% pixel value of 255 and the other pixel values of 0. In addition, by using appropriate parameters of statistical region merging algorithm, segmentation comparison is performed. In the step of feature extraction, the feature vectors belonging to the vehicles are obtained by using Gabor filters with different orientation, frequency and angle values. A number of Gabor filters are created by changing the orientation, frequency and angle parameters of the Gabor filters to extract important features of the images that form the distinctive parts. Finally, images are classified by sparse representation method. In the study, l₁ norm analysis of sparse representation is used. A joint database of the feature vectors generated by the target images of military vehicle types is obtained side by side and this database is transformed into the matrix form. In order to classify the vehicles in a similar way, the test images of each vehicle is converted to the vector form and l₁ norm analysis of the sparse representation method is applied through the existing database matrix form. As a result, correct recognition has been performed by matching the target images of military vehicles with the test images by means of the sparse representation method. 97% classification success of SAR images of different military vehicle types is obtained.

Keywords: automatic target recognition, sparse representation, image classification, SAR images

Procedia PDF Downloads 365

Authors: E. Ormeno, C. Gutigny, J. Ruffault, J. Madrigal, M. Guijarro, C. Lecareux, C. Ballini

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Mediterranean plant species feature numerous metabolic and morpho-physiological responses crucial to survive under both, typical Mediterranean drought conditions and future aggravated drought expected by climate change. Whether these adaptive responses will, in turn, increase the ecosystem perturbation in terms of fire hazard, is an issue that needs to be addressed. The aim of this study was to test whether recurrent and aggravated drought in the Mediterranean area favors the accumulation of waxes in leaf litter, with an eventual increase of litter flammability. The study was conducted in 2017 in a garrigue in Southern France dominated by Quercus coccifera, where two drought treatments were used: a treatment with recurrent aggravated drought consisting of ten rain exclusion structures which withdraw part of the annual precipitation since January 2012, and a natural drought treatment where Q. coccifera stands are free of such structures and thus grow under natural precipitation. Waxes were extracted with organic solvent and analyzed by GC-MS and litter flammability was assessed through measurements of the ignition delay, flame residence time and flame intensity (flame height) using an epiradiator as well as the heat of combustion using an oxygen bomb calorimeter. Results show that after 5 years of rain restriction, wax content in the cuticle of leaf litter increases significantly compared to shrubs growing under natural precipitation, in accordance with the theoretical knowledge which expects increases of cuticle waxes in green leaves in order to limit water evapotranspiration. Wax concentrations were also linearly and positively correlated to litter flammability, a correlation that lies on the high flammability own to the long-chain alkanes (C25-C31) found in leaf litter waxes. This innovative investigation shows that climate change is likely to favor ecosystem fire hazard through accumulation of highly flammable waxes in litter. It also adds valuable information about the types of metabolites that are associated with increasing litter flammability, since so far, within the leaf metabolic profile, only terpene-like compounds had been related to plant flammability.

Keywords: cuticular waxes, drought, flammability, litter

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Authors: Fazıl Gökgöz, Fahrettin Filiz

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Load forecasting has become crucial in recent years and become popular in forecasting area. Many different power forecasting models have been tried out for this purpose. Electricity load forecasting is necessary for energy policies, healthy and reliable grid systems. Effective power forecasting of renewable energy load leads the decision makers to minimize the costs of electric utilities and power plants. Forecasting tools are required that can be used to predict how much renewable energy can be utilized. The purpose of this study is to explore the effectiveness of LSTM-based neural networks for estimating renewable energy loads. In this study, we present models for predicting renewable energy loads based on deep neural networks, especially the Long Term Memory (LSTM) algorithms. Deep learning allows multiple layers of models to learn representation of data. LSTM algorithms are able to store information for long periods of time. Deep learning models have recently been used to forecast the renewable energy sources such as predicting wind and solar energy power. Historical load and weather information represent the most important variables for the inputs within the power forecasting models. The dataset contained power consumption measurements are gathered between January 2016 and December 2017 with one-hour resolution. Models use publicly available data from the Turkish Renewable Energy Resources Support Mechanism. Forecasting studies have been carried out with these data via deep neural networks approach including LSTM technique for Turkish electricity markets. 432 different models are created by changing layers cell count and dropout. The adaptive moment estimation (ADAM) algorithm is used for training as a gradient-based optimizer instead of SGD (stochastic gradient). ADAM performed better than SGD in terms of faster convergence and lower error rates. Models performance is compared according to MAE (Mean Absolute Error) and MSE (Mean Squared Error). Best five MAE results out of 432 tested models are 0.66, 0.74, 0.85 and 1.09. The forecasting performance of the proposed LSTM models gives successful results compared to literature searches.

Keywords: deep learning, long short term memory, energy, renewable energy load forecasting

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Authors: Inda Annisa Fauzani, Rahayu Setyawati Arifin

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The development of Special Economic Zones in Indonesia cannot be separated from the development of the communities in them. In accordance with the SEZ's objectives as a driver of economic growth, the focus of SEZ development does not only prioritize investment receipts and infrastructure development. The community as one of the stakeholders must also be considered. This becomes a challenge when the development of an SEZ has the potential to have an impact on the community in it. These impacts occur due to changes in the development of the area in the form of changes in the main regional industries and changes in the main livelihoods of the community. As a result, people can feel threats and disturbances. The community as the object of development is required to be able to have resilience in order to achieve a synergy between regional development and community development. A lack of resilience in the community can eliminate the ability to recover from disturbances and difficulty to adapt to changes that occur in their area. Social resilience is the ability of the community to be able to recover from disturbances and changes that occur. The achievement of social resilience occurs when the community gradually has the capacity in the form of coping capacity, adaptive capacity, and transformative capacity. It is hoped that when social resilience is achieved, the community will be able to develop linearly with regional development so that the benefits of this development can have a positive impact on these communities. This study aims to identify and analyze social factors that influence the achievement of social resilience in the community in Special Economic Zones in Indonesia and develop a program framework for achieving social resilience capacity in the community so that it can be used as a strategy to support the successful development of Special Economic Zones in Indonesia that provide benefits to the local community. This study uses a quantitative research method approach. Questionnaires are used as research instruments which are distributed to predetermined respondents. Respondents in this study were determined by using purposive sampling of the people living in areas that were developed into Special Economic Zones. Respondents were given a questionnaire containing questions about the influence of social factors on the achievement of social resilience. As x variables, 42 social factors are provided, while social resilience is used as y variables. The data collected from the respondents is analyzed in SPSS using Spearman Correlation to determine the relation between x and y variables. The correlated factors are then used as the basis for the preparation of programs to increase social resilience capacity in the community.

Keywords: community development, program management, social factor, social resilience

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Authors: Masoud Sheidaei, Mohammad-Reza Kordasti, Fahimeh Koohdar

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Calotropis procera (Aiton) W.T.Aiton, (Apocynaceae), is an economically and medicinally important plant species which is an evergreen, perennial shrub growing in arid and semi-arid climates, and can tolerate very low annual rainfall (150 mm) and a dry season. The plant can also tolerate temperature ran off 20 to30°C and is not frost tolerant. This plant species prefers free-draining sandy soils but can grow also in alkaline and saline soils.It is found at a range of altitudes from exposed coastal sites to medium elevations up to 1300 m. Due to morpho-physiological adaptations of C. procera and its ability to tolerate various abiotic stresses. This taxa can compete with desirable pasture species and forms dense thickets that interfere with stock management, particularly mustering activities. Caloteropis procera grows only in southern part of Iran where in comprises a limited number of geographical populations. We used different population genetics and r landscape analysis to produce data on geographical populations of C. procera based on molecular genetic study using SCoT molecular markers. First, we used spatial principal components (sPCA), as it can analyze data in a reduced space and can be used for co-dominant markers as well as presence / absence data as is the case in SCoT molecular markers. This method also carries out Moran I and Mantel tests to reveal spatial autocorrelation and test for the occurrence of Isolation by distance (IBD). We also performed Random Forest analysis to identify the importance of spatial and geographical variables on genetic diversity. Moreover, we used both RDA (Redundency analysis), and LFMM (Latent factor mixed model), to identify the genetic loci significantly associated with geographical variables. A niche modellng analysis was carried our to predict present potential area for distribution of these plants and also the area present by the year 2050. The results obtained will be discussed in this paper.

Keywords: population genetics, landscape genetic, Calotreropis procera, niche modeling, SCoT markers

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Authors: Philippe Judlin, Olivier Morel

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Background: In France, the resident curriculum (RC) in Obstetrics and Gynecology (OBGYN) takes five years. In the course of the last 15 years, this RC has undergone major changes, characterized mainly by successive reductions of work hours. The program used to comprise long and frequent shifts, huge workload, poor supervision and erratic theoretical teaching. A decade ago, the French Ministry of Heath recommended a limitation of shift duration up to 24 hours and a minimum of 11 hours off duty between shifts. Last year, in order to comply with European Union directives, new recommendations have further limited residents’ work hours to 48 hours per week. Methods: Assessment of the residency program adjustments recently made to accommodate the recommendations while improving the training quality in resorting to new methods. Results: The challenge facing program directors was to provide an all-encompassing curriculum to OBGYN residents despite fewer work hours. Program has been dramatically redesigned, and several measures have been put in place: -The resident rotation system has been redesigned. Residents used to make 6-month rotations between 10-12 Departments of OBGYN or Surgery. Fewer Departments, those providing the best teaching, have been kept in the new RC. -Extensive inhouse supervision has been implemented for all kinds of clinical activities. Effectual supervision of residents has proved to be an effective tool to improve the quality of training. -The tutorship system, with academic members individually overseeing residents during their curriculum, has been perfected. It allows a better follow-up of residents’ progresses during the 5-year program. -The set up of an extensive program of lectures encompassing all maters in Obstetrics & Gynecology. These mandatory lectures are available online in a dedicated website. Therefore, face-to-face lectures have been limited in order to fit in the 48-hour limit. -The use of simulation has been significantly increased in obstetrics, materno-fetal medicine and surgery (stressing especially laparoscopic training). -Residents’ feedback has been taken into account in the setup of the new RC. Conclusion: This extensive overhaul of the Obstetrics and Gynecology RC has been in place since last year only. Nevertheless, the new program seems to adequately take into account the new recommendations while providing a better and more consistent teaching to the OBGYN residents.

Keywords: education, laparoscopy, residency, simulation

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Authors: Salamatu Shaibu, Jan Hernning Sommer

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Integrating biodiversity conservation practices in mining landscapes ensures the continual provision of various ecosystem services to the dependent communities whilst serving as ecological insurance for corporate mining when purchasing reclamation security bonds. Climate hazards such as long dry seasons, erratic rainfall patterns, and extreme weather events contribute to biodiversity loss in addition to the impact due to mining. Both corporate mining and mine-fringe communities perceive the effect of climate on biodiversity from the context of the benefits they accrue, which motivate their conservation practices. In this study, pragmatic approaches including semi-structured interviews, field visual observation, and review were used to collect data on corporate mining employees and households of fringing communities in the southwestern mining hub. The perceived changes in the local climatic conditions and the consequences on environmental management practices that promote biodiversity conservation were examined. Using a thematic content analysis tool, the result shows that best practices such as concurrent land rehabilitation, reclamation ponds, artificial wetlands, land clearance, and topsoil management are directly affected by prolonging long dry seasons and erratic rainfall patterns. Excessive dust and noise generation directly affect both floral and faunal diversity coupled with excessive fire outbreaks in rehabilitated lands and nearby forest reserves. Proposed adaptive measures include engaging national conservation authorities to promote reforestation projects around forest reserves. National government to desist from using permit for mining concessions in forest reserves, engaging local communities through educational campaigns to control forest encroachment and burning, promoting community-based resource management to promote community ownership, and provision of stricter environmental legislation to compel corporate, artisanal, and small scale mining companies to promote biodiversity conservation.

Keywords: biodiversity conservation, climate hazards, corporate mining, mining landscapes

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Authors: Margarida Porfírio Tomás, Paula Pereira, José Palma Oliveira

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Robotic grasping is advancing rapidly, but transferring techniques from rigid to deformable objects remains a challenge. Deformable and flexible items, such as food containers, demand nuanced handling due to their changing shapes. Bridging this gap is crucial for applications in food processing, surgical robotics, and household assistance. AGILEHAND, a Horizon project, focuses on developing advanced technologies for sorting, handling, and packaging soft and deformable products autonomously. These technologies serve as strategic tools to enhance flexibility, agility, and reconfigurability within the production and logistics systems of European manufacturing companies. Key components include intelligent detection, self-adaptive handling, efficient sorting, and agile, rapid reconfiguration. The overarching goal is to optimize work environments and equipment, ensuring both efficiency and safety. As new technologies emerge in the food industry, there will be some implications, such as labour force, safety problems and acceptance of the new technologies. To overcome these implications, AGILEHAND emphasizes the integration of social sciences and humanities, for example, the application of the Technology Acceptance Model (TAM). The project aims to create a change management manual, that will outline strategies for developing digital skills and managing health and safety transitions. It will also provide best practices and models for organizational change. Additionally, AGILEHAND will design effective training programs to enhance employee skills and knowledge. This information will be obtained through a combination of case studies, structured interviews, questionnaires, and a comprehensive literature review. The project will explore how organizations adapt during periods of change and identify factors influencing employee motivation and job satisfaction. This project received funding from European Union’s Horizon 2020/Horizon Europe research and innovation program under grant agreement No101092043 (AGILEHAND).

Keywords: change management, technology acceptance model, organizational change, health and safety

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Authors: Luciana Salomon

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The Andes hold one of the highest plant species diversity in the world. How such diversity originated is one of the most intriguing questions in studies addressing the pattern of plant diversity worldwide. Recently, the explosive adaptive radiations found in high Andean groups have been pointed as major triggers of this spectacular diversity. The Andes are one of the most species-rich area for the largest genus from the Asteraceae family, Senecio. There, the genus presents an incredible variation in growth form and ecological niche space. If this diversity of Andean Senecio can be explained by a monophyletic origin and subsequent radiation has not been tested up to now. Previous studies trying to disentangle the evolutionary history of some Andean Senecio struggled with the relatively low resolution and support of the phylogenies, which is indicative of recently radiated groups. Using Hyb-Seq, a powerful approach is available to address phylogenetic questions in groups whose evolutionary histories are recent and rapid. This approach was used for Senecio to build a phylogenetic backbone on which to study the mechanisms shaping its hyper-diversity in the Andes, focusing on Senecio ser. Culcitium, an exclusively Andean and well circumscribed group presenting large morphological variation and which is widely distributed across the Andes. Hyb-Seq data for about 130 accessions of Seneciowas generated. Using standard data analysis work flows and a newly developed tool to utilize paralogs for phylogenetic reconstruction, robustness of the species treewas investigated. Fully resolved and moderately supported species trees were obtained, showing Senecio ser. Culcitium as monophyletic. Within this group, some species formed well-supported clades congruent with morphology, while some species would not have exclusive ancestry, in concordance with previous studies showing a geographic differentiation. Additionally, paralogs were detected for a high number of loci, indicating duplication events and hybridization, known to be common in Senecio ser. Culcitium might have lead to hybrid speciation. The rapid diversification of the group seems to have followed a south-north distribution throughout the Andes, having accelerated in the conquest of new habitats more recently available: i.e., Montane forest, Paramo, and Superparamo.

Keywords: evolutionary radiations, andes, paralogy, hybridization, senecio

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Authors: Anne Mastamet-Mason

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Crimes against women is a global concern, and South Africa, in particular, is in a dilemma of dealing with constant criminal acts that face the country. Debates on violence against women in South Africa cannot be overemphasised any longer as crimes continue to rise year by year. The recent death of a university student at the University of Cape Town, as well as many other cases, continues to strengthen the need to find solutions from all the spheres of South African society. The advanced textiles market contains a high number and variety of technologies, many of which have protected status and constitute a relatively small portion of the textiles used for the consumer market. Examples of advanced textiles include nanomaterials, such as silver, titanium dioxide and zinc oxide, designed to create an anti-microbial and self-cleaning layer on top of the fibers, thereby reducing body smell and soiling. Smart textiles propose materials and fabrics versatile and adaptive to different situations and functions. Integrating textiles and computing technologies offer an opportunity to come up with differentiated characteristics and functionality. This paper presents a proposal to design a smart camisole/Yoga sports brazier and a smart Yoga sports pant garment to be worn by women while alone and while in purported danger zones. The smart garments are to be worn under normal clothing and cannot be detected or seen, or suspected by perpetrators. The garments are imbued with devices to sense any physical aggression and any abnormal or accelerated heartbeat that may be exhibited by the victim of violence. The signals created during the attack can be transmitted to the police and family members who own a mobile application system that accepts signals emitted. The signals direct the receiver to the exact location of the offence, and the victim can be rescued before major violations are committed. The design of the Yoga sports garments will be done by Professor Mason, who is a fashion designer by profession, while the mobile phone application system will be developed by Mr. Amos Yegon, who is an independent software developer.

Keywords: smart clothing, wearable technology, south africa, 4th industrial revolution

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Authors: Vaidehi Murarka, Sneha Mehta, Dishant Upadhyay

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Our project topic is “Alphabet Recognition using pixel probability distribution”. The project uses techniques of Image Processing and Machine Learning in Computer Vision. Alphabet recognition is the mechanical or electronic translation of scanned images of handwritten, typewritten or printed text into machine-encoded text. It is widely used to convert books and documents into electronic files etc. Alphabet Recognition based OCR application is sometimes used in signature recognition which is used in bank and other high security buildings. One of the popular mobile applications includes reading a visiting card and directly storing it to the contacts. OCR's are known to be used in radar systems for reading speeders license plates and lots of other things. The implementation of our project has been done using Visual Studio and Open CV (Open Source Computer Vision). Our algorithm is based on Neural Networks (machine learning). The project was implemented in three modules: (1) Training: This module aims “Database Generation”. Database was generated using two methods: (a) Run-time generation included database generation at compilation time using inbuilt fonts of OpenCV library. Human intervention is not necessary for generating this database. (b) Contour–detection: ‘jpeg’ template containing different fonts of an alphabet is converted to the weighted matrix using specialized functions (contour detection and blob detection) of OpenCV. The main advantage of this type of database generation is that the algorithm becomes self-learning and the final database requires little memory to be stored (119kb precisely). (2) Preprocessing: Input image is pre-processed using image processing concepts such as adaptive thresholding, binarizing, dilating etc. and is made ready for segmentation. “Segmentation” includes extraction of lines, words, and letters from the processed text image. (3) Testing and prediction: The extracted letters are classified and predicted using the neural networks algorithm. The algorithm recognizes an alphabet based on certain mathematical parameters calculated using the database and weight matrix of the segmented image.

Keywords: contour-detection, neural networks, pre-processing, recognition coefficient, runtime-template generation, segmentation, weight matrix

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Authors: Bianca Maria Rulli, Lenny Valentino Schiaretti

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The considerable recent urbanization has increasingly sharpened environmental and social problems all over the world. During the recent years, many answers to the alarming attitudes in modern cities have emerged: a drastic reduction in the rate of growth is becoming essential for future generations and small scale economies are considered more adaptive and sustainable. According to the concept of degrowth, cities should consider surpassing the centralization of urban living by redefining the relationship between rural and urban knowledge; growing food in cities fundamentally contributes to the increase of social and ecological resilience. Through an innovative approach, this research combines the benefits of urban agriculture (increase of biological diversity, shorter and thus more efficient supply chains, food security) and temporary land use. They stimulate collaborative practices to satisfy the changing needs of communities and stakeholders. The concept proposes a coherent strategy to create a sustainable development of urban spaces, introducing a productive green-network to link specific areas in the city. By shifting the current relationship between architecture and landscape, the former process of ground consumption is deeply revised. Temporary modules can be used as concrete tools to create temporal areas of innovation, transforming vacant or marginal spaces into potential laboratories for the development of the city. The only permanent ground traces, such as foundations, are minimized in order to allow future land re-use. The aim is to describe a new mindset regarding the quality of space in the metropolis which allows, in a completely flexible way, to bring back the green and the urban farming into the cities. The wide possibilities of the research are analyzed in two different case-studies. The first is a regeneration/connection project designated for social housing, the second concerns the use of temporary modules to answer to the potential needs of social structures. The intention of the productive green-network is to link the different vacant spaces to each other as well as to the entire urban fabric. This also generates a potential improvement of the current situation of underprivileged and disadvantaged persons.

Keywords: degrowth, green network, land use, temporary building, urban farming

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Authors: Kumari Rekha, Mathur K Dhananjay, Maheshwari Deepanshu, Nautiyal Nidhi, Shubham Smriti, Laal Deepika, Sinha Swati, Kumar Anupam, Biswas Subhrajit, Shiv Kumar Sarin

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Background: Mesenchymal stem cells are multipotent stem cells derived from mesoderm and are used for therapeutic purposes because of their self-renewal, homing capacity, Immunomodulatory capability, low immunogenicity and mitochondrial transfer signaling. MSCs have the ability to regulate the mechanism of both innate as well as adaptive immune responses through the modulation of cellular response and the secretion of inflammatory mediators. Different sources of MSC are UC MSC, BM MSC, Dental Pulp, and Adipose MSC. The most frequent source used is umbilical cord tissue due to its being easily available and free of limitations of collection procedures from respective hospitals. The immunosuppressive role of MSCs is particularly interesting for clinical use since it confers resistance to rejection by the host immune response. Methodology: In this study, T helper cells (TH4), Cytotoxic T cells (CD-8), immunoregulatory cells (CD25 +FOXP3+) are compared from isolated MSC from three different methods, UC Dissociation Kit (Miltenyi), Explant Culture and Collagenase Type-IV. To check the immunomodulatory property, these MSCs were seeded with PBMC(Coculture) in CD3 coated 24 well plates. Cd28 antibody was added in coculture for six days. The coculture was analyzed in FACS Verse flow cytometry. Results: From flow cytometry analysis of coculture, it found that All over T helper cells (CD4+) number p<0.0264 increases in (All Enzymes) MSC rather than explant MSC(p>0.0895) as compared to Collagenase(p>0.7889) in a coculture of Activated T cell and Mesenchymal Stem Cell. Similar T reg cells (CD25+, FOXP3+) expression p<0.0234increases in All Enzymes), decreases in Explant and Collagenase. Experiments have shown that MSCs can also directly prevent the cytotoxic activity of CD8 lymphocytes mainly by blocking their proliferation rather than by inhibiting the cytotoxic effect. And promoting the t-reg cells, which helps in the mediation of immune response in various diseases. Conclusion: MSC suppress Cytotoxic CD8 T cell and Enhance immunoregulatory T reg (CD4+, CD25+, FOXP3+) Cell expression. Thus, MSC maintains a proper balance(ratio) between CD4 T cells and Cytotoxic CD8 T cells.

Keywords: MSC, disease, T cell, T regulatory

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Authors: Rebecca K. Blais, Lindsey Monteith, Hallie Tannahill

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Military sexual trauma (MST) includes sexual harassment or assault that occurred during military service. Studies conducted to date on the association of MST with mental health and suicide outcomes are generally circumscribed to either active duty or veteran samples, precluding a thorough analysis of developmental trajectories of distress following MST within the context of ongoing (vs. discharged from) military service. The Military Social Science Laboratory has collected data on mixed service samples of men and women service members, addressing this important literature gap. The purpose of this study was to examine the association of MST, suicide risk, PTSD, depression, alcohol use, and posttraumatic cognitions using two separate samples, which collectively allow for a comprehensive examination of the development of distress following MST. The first sample consisted of 1389 men and women service members and veterans with varying levels of MST severity, including no MST, harassment-only MST, and assault MST. The second sample consisted of 400 men and women service members, all reporting the highest severity of MST, assault MST. In both samples, roughly half reported being discharged from service. Participants completed self-report measures of MST exposure severity, suicide ideation, suicide risk, PTSD, depression, alcohol misuse, and posttraumatic cognitions, as well as perceptions of how the military responded to their MST. Relative to those still serving in the US military, veterans were more likely to endorse suicidal ideation, higher PTSD symptoms, and higher depression symptoms if they felt the military mishandled their experience of MST (referred to as perceived institutional betrayal). However, among those reporting the most severe MST, veterans reported lower alcohol misuse and more adaptive posttraumatic cognitions. These findings suggest that those separated from the military experience different posttraumatic aftermath following MST relative to those who are currently serving in the military. Such findings suggest critical differences in the developmental trajectory of distress, necessitating different interventions to successfully reduce distress and dysfunction. Additional analyses will explore the impact of gender on these associations and explore full mechanistic models of distress grouped by discharged status.

Keywords: military sexual trauma, PTSD, suicide, developmental trajectories, depression

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Authors: Besma Khalfoun

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In many current Human Activity Recognition (HAR) applications, users' data is frequently shared and centrally stored by third parties, posing a significant privacy risk. This practice makes these entities attractive targets for extracting sensitive information about users, including their identity, health status, and location, thereby directly violating users' privacy. To tackle the issue of centralized data storage, a relatively recent paradigm known as federated learning has emerged. In this approach, users' raw data remains on their smartphones, where they train the HAR model locally. However, users still share updates of their local models originating from raw data. These updates are vulnerable to several attacks designed to extract sensitive information, such as determining whether a data sample is used in the training process, recovering the training data with inversion attacks, or inferring a specific attribute or property from the training data. In this paper, we first introduce PUR-Attack, a parameter-based user re-identification attack developed for HAR applications within a federated learning setting. It involves associating anonymous model updates (i.e., local models' weights or parameters) with the originating user's identity using background knowledge. PUR-Attack relies on a simple yet effective machine learning classifier and produces promising results. Specifically, we have found that by considering the weights of a given layer in a HAR model, we can uniquely re-identify users with an attack success rate of almost 100%. This result holds when considering a small attack training set and various data splitting strategies in the HAR model training. Thus, it is crucial to investigate protection methods to mitigate this privacy threat. Along this path, we propose SAFER, a privacy-preserving mechanism based on adaptive local differential privacy. Before sharing the model updates with the FL server, SAFER adds the optimal noise based on the re-identification risk assessment. Our approach can achieve a promising tradeoff between privacy, in terms of reducing re-identification risk, and utility, in terms of maintaining acceptable accuracy for the HAR model.

Keywords: federated learning, privacy risk assessment, re-identification risk, privacy preserving mechanisms, local differential privacy, human activity recognition

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Authors: John McDowall, Lucy Lightfoot

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Stigma constitutes a significant barrier to the recovery and social integration of individuals affected by mental illness. Although there is some debate in the literature regarding the definition and utility of stigma as a concept, it is widely accepted that it comprises three components: stereotypical beliefs, prejudicial reactions, and discrimination. Stereotypical beliefs describe the cognitive knowledge-based component of stigma, referring to beliefs (often negative) about members of a group that is based on cultural and societal norms (e.g. ‘People with anxiety are just weak’). Prejudice refers to the affective/evaluative component of stigma and describes the endorsement of negative stereotypes and the resulting negative emotional reactions (e.g. ‘People with anxiety are just weak, and they frustrate me’). Discrimination refers to the behavioural component of stigma, which is arguably the most problematic, as it exerts a direct effect on the stigmatized person and may lead people to behave in a hostile or avoidant way towards them (i.e. refusal to hire them). Research exploring anti-stigma initiatives focus primarily on an educational approach, with the view that accurate information will replace misconceptions and decrease stigma. Many approaches take a biogenetic stance, emphasising brain and biochemical deficits - the idea being that ‘mental illness is an illness like any other.' While this approach tends to effectively reduce blame, it has also demonstrated negative effects such as increasing prognostic pessimism, the desire for social distance and perceptions of stereotypes. In the present study 144 participants were split into three groups and read one of three vignettes presenting causal explanations for Generalised Anxiety Disorder (GAD): One explanation emphasized biogenetic factors as being important in the etiology of GAD, another emphasised psychosocial factors (e.g. aversive life events, poverty, etc.), and a third stressed the adaptive features of the disorder from an evolutionary viewpoint. A variety of measures tapping the various components of stigma were administered following the vignettes. No difference in stigma measures as a function of causal explanation was found. People who had contact with mental illness in the past were significantly less stigmatising across a wide range of measures, but this did not interact with the type of causal explanation.

Keywords: generalised anxiety disorder, discrimination, prejudice, stigma

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Authors: Rong Li, Brian D. Wirth, Bing Liu

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Graphite is the matrix, and structural material in the high temperature gas-cooled reactor exhibits an irradiation response. It is of significant importance to analyze the defect production and evaluate the role of graphite under irradiation. A vast experimental literature exists for graphite on the dimensional change, mechanical properties, and thermal behavior. However, simulations have not been applied to the atomistic perspective. Remarkably few molecular dynamics simulations have been performed to study the irradiation response in graphite. In this paper, irradiation-induced damage cascades in graphite were investigated with molecular dynamics simulation. Statistical results of the graphite defects were obtained by sampling a wide energy range (1–30 KeV) and 10 different runs for every cascade simulation with different random number generator seeds to the velocity scaling thermostat function. The chemical bonding in carbon was described using the adaptive intermolecular reactive empirical bond-order potential (AIREBO) potential coupled with the standard Ziegler–Biersack–Littmack (ZBL) potential to describe close-range pair interactions. This study focused on analyzing the number of defects, the final cascade morphology and the distribution of defect clusters in space, the length-scale cascade properties such as the cascade length and the range of primary knock-on atom (PKA), and graphite mechanical properties’ variation. It can be concluded that the number of surviving Frenkel pairs increased remarkably with the increasing initial PKA energy but did not exhibit a thermal spike at slightly lower energies in this paper. The PKA range and cascade length approximately linearly with energy which indicated that increasing the PKA initial energy will come at expensive computation cost such as 30KeV in this study. The cascade morphology and the distribution of defect clusters in space mainly related to the PKA energy meanwhile the temperature effect was relatively negligible. The simulations are in agreement with known experimental results and the Kinchin-Pease model, which can help to understand the graphite damage cascades and lifetime span under irradiation and provide a direction to the designs of these kinds of structural materials in the future reactors.

Keywords: graphite damage cascade, molecular dynamics, cascade morphology, cascade distribution

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Authors: Shunyi Yang, Jingjing Yan, Siyu Dong, Xiangguo Cui

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Current architectural façade design practices incorporate various daylighting and solar radiation analysis methods. These emphasize the impact of geometry on façade design. There is scope to extend this knowledge into methods that address material translucency, porosity, and form. Such approaches can also achieve these conditions through adaptive robotic manufacturing approaches that exploit material dynamics within the design, and alleviate fabrication waste from molds, ultimately accelerating the autonomous manufacturing system. Besides analyzing the environmental solar radiant in building facade design, there is also a vacancy research area of how lighting effects can be precisely controlled by engaging the instant real-time data-driven robot control and manipulating the material properties. Ceramics carries a wide range of transmittance and deformation potentials for robotics control with the research of its material property. This paper presents one semi-autonomous system that engages with real-time data-driven robotics control, hardware kit design, environmental building studies, human interaction, and exploratory research and experiments. Our objectives are to investigate the relationship between different clay bodies or ceramics’ physio-material properties and their transmittance; to explore the feedback system of instant lighting data in robotic fabrication to achieve precise lighting effect; to design the sufficient end effector and robot behaviors for different stages of deformation. We experiment with architectural clay, as the material of the façade that is potentially translucent at a certain stage can respond to light. Studying the relationship between form, material properties, and porosity can help create different interior and exterior light effects and provide façade solutions for specific architectural functions. The key idea is to maximize the utilization of in-progress robotics fabrication and ceramics materiality to create a highly integrated autonomous system for lighting facade design and manufacture.

Keywords: light transmittance, data-driven fabrication, computational design, computer vision, gamification for manufacturing

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Authors: Mamochana, A. Ramatea, Fumane, P. Khanare

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Enabling the learning environment is a significant and adaptive technique necessary to navigate learners’ educational challenges. However, research has indicated that quality provision of education in the environments that are enabling, especially to learners with visual impairments (LVIs, hereafter) in rural schools, remain an ongoing challenge globally. Hence, LVIs often have a lower level of academic performance as compared to their peers. To balance this gap and fulfill learners'fundamentalhuman rights¬ of receiving an equal quality education, appropriate measures and structures that make enabling learning environment a better place to learn must be better understood. This paper, therefore, intends to find possible means that rural schools of Lesotho can employ to make the learning environment for LVIs enabling. The present study aims to determine suitable assets that can be drawn to make the learning environment for LVIs enabling. The study is also informed by the transformative paradigm and situated within a qualitative research approach. Data were generated through focus group discussions with twelve teachers who were purposefully selected from two rural primary schools in Lesotho. The generated data were then analyzed thematically using Braun and Clarke's six-phase framework. The findings of the study indicated that participating teachers do have an understanding that rural schools boast of assets (existing and hidden) that have a positive influence in responding to the special educational needs of LVIs. However, the participants also admitted that although their schools boast of assets, they still experience limited knowledge about the use of the existing assets and thus, realized a need for improved collaboration, involvement of the existing assets, and enhancement of academic resources to make LVIs’ learning environment enabling. The findings of this study highlight the significance of the effective use of assets. Additionally, coincides with literature that shows recognizing and tapping into the existing assets enable learning for LVIs. In conclusion, the participants in the current study indicated that for LVIs’ learning environment to be enabling, there has to be sufficient use of the existing assets. The researchers, therefore, recommend that the appropriate use of assets is good, but may not be sufficient if the existing assets are not adequately managed. Hence,VILs experience a vicious cycle of vulnerability. It was thus, recommended that adequate use of assets and teachers' engagement as active assets should always be considered to make the learning environment a better place for LVIs to learan in the future

Keywords: assets, enabling learning environment, rural schools, learners with visual impairments

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Authors: Habtamu Ayenew Asegie

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Wealth, as opposed to income or consumption, implies a more stable and permanent status. Due to natural and human-made difficulties, households' economies will be diminished, and their well-being will fall into trouble. Hence, governments and humanitarian agencies offer considerable resources for poverty and malnutrition reduction efforts. One key factor in the effectiveness of such efforts is the accuracy with which low-income or poor populations can be identified. As a result, this study aims to predict a household’s wealth status using ensemble Machine learning (ML) algorithms. In this study, design science research methodology (DSRM) is employed, and four ML algorithms, Random Forest (RF), Adaptive Boosting (AdaBoost), Light Gradient Boosted Machine (LightGBM), and Extreme Gradient Boosting (XGBoost), have been used to train models. The Ethiopian Demographic and Health Survey (EDHS) dataset is accessed for this purpose from the Central Statistical Agency (CSA)'s database. Various data pre-processing techniques were employed, and the model training has been conducted using the scikit learn Python library functions. Model evaluation is executed using various metrics like Accuracy, Precision, Recall, F1-score, area under curve-the receiver operating characteristics (AUC-ROC), and subjective evaluations of domain experts. An optimal subset of hyper-parameters for the algorithms was selected through the grid search function for the best prediction. The RF model has performed better than the rest of the algorithms by achieving an accuracy of 96.06% and is better suited as a solution model for our purpose. Following RF, LightGBM, XGBoost, and AdaBoost algorithms have an accuracy of 91.53%, 88.44%, and 58.55%, respectively. The findings suggest that some of the features like ‘Age of household head’, ‘Total children ever born’ in a family, ‘Main roof material’ of their house, ‘Region’ they lived in, whether a household uses ‘Electricity’ or not, and ‘Type of toilet facility’ of a household are determinant factors to be a focal point for economic policymakers. The determinant risk factors, extracted rules, and designed artifact achieved 82.28% of the domain expert’s evaluation. Overall, the study shows ML techniques are effective in predicting the wealth status of households.

Keywords: ensemble machine learning, households wealth status, predictive model, wealth status prediction

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Authors: Ander Pomposo

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Purpose: The aim of this study was to investigate the impact that dialogue has on the relationship between shared leadership and innovative behavior and the importance of dialogue in innovation. This study wants to contribute to the literature by providing theorists and researchers a better understanding of how to move forward in the studies of moderator variables in the relationship between shared leadership and team outcomes such as innovation. Methodology: A systematic review of the literature, originally adopted from the medical sciences but also used in management and leadership studies, was conducted to synthesize research in a systematic, transparent and reproducible manner. A final sample of 48 empirical studies was scientifically synthesized. Findings: Shared leadership gives a better solution to team management challenges and goes beyond the classical, hierarchical, or vertical leadership models based on the individual leader approach. One of the outcomes that emerge from shared leadership is team innovative behavior. To intensify the relationship between shared leadership and team innovative behavior, and understand when is more effective, the moderating effects of other variables in this relationship should be examined. This synthesis of the empirical studies revealed that dialogue is a moderator variable that has an impact on the relationship between shared leadership and team innovative behavior when leadership is understood as a relational process. Dialogue is an activity between at least two speech partners trying to fulfill a collective goal and is a way of living open to people and ideas through interaction. Dialogue is productive when team members engage relationally with one another. When this happens, participants are more likely to take responsibility for the tasks they are involved and for the relationships they have with others. In this relational engagement, participants are likely to establish high-quality connections with a high degree of generativity. This study suggests that organizations should facilitate the dialogue of team members in shared leadership which has a positive impact on innovation and offers a more adaptive framework for the leadership that is needed in teams working in complex work tasks. These results uncover the necessity of more research on the role that dialogue plays in contributing to important organizational outcomes such as innovation. Case studies describing both best practices and obstacles of dialogue in team innovative behavior are necessary to gain a more detailed insight into the field. It will be interesting to see how all these fields of research evolve and are implemented in dialogue practices in the organizations that use team-based structures to deal with uncertainty, fast-changing environments, globalization and increasingly complex work.

Keywords: dialogue, innovation, leadership, shared leadership, team innovative behavior

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Authors: Matt Stichter

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Moral development requires learning from one’s failures, but that turnsout to be especially challenging when dealing with moral failures. The distress prompted by moral failure can cause responses ofdefensiveness or disengagement rather than attempts to make amends and work on self-change. The most potentially distressing response to moral failure is a shame. However, there appears to be two different senses of “shame” that are conflated in the literature, depending on whether the failure is appraised as the result of a global and unalterable self-defect, or a local and alterable self-defect. One of these forms of shame does prompt self-improvement in response to moral failure. This occurs if one views the failure as indicating only a specific (local) defect in one’s identity, where that’s something repairable, rather than asanoverall(orglobal)defectinyouridentity that can’t be fixed. So, if the whole of one’s identity as a morally good person isn’t being called into question, but only a part, then that is something one could work on to improve. Shame, in this sense, provides motivation for self-improvement to fix this part oftheselfinthe long run, and this would be important for moral development. One factor that looks to affect these different self-attributions in the wake of moral failure can be found in mindset theory, as reactions to moral failure in these two forms of shame are similar to how those with a fixed or growth mindset of their own abilities, such as intelligence, react to failure. People fall along a continuum with respect to how they view abilities – it is more of a fixed entity that you cannot do much to change, or it is malleable such that you can train to improve it. These two mindsets, ‘fixed’ versus ‘growth’, have different consequences for how we react to failure – a fixed mindset leads to maladaptive responses because of feelings of helplessness to do better; whereas a growth mindset leads to adaptive responses where a person puts forth effort to learn how to act better the next time. Here we can see the parallels between a fixed mindset of one’s own (im)morality, as the way people respond to shame when viewed as indicating a global and unalterable self-defect parallels the reactions people have to failure when they have a fixed mindset. In addition, it looks like there may be a similar structure to pride. Pride is, like shame, a self-conscious emotion that arises from internal attributions about the self as being the cause of some event. There are also paradoxical results from research on pride, where pride was found to motivate pro-social behavior in some cases but aggression in other cases. Research suggests that there may be two forms of pride, authentic and hubristic, that are also connected to different self-attributions, depending on whether one is feeling proud about a particular (local) aspect of the self versus feeling proud about the whole of oneself (global).

Keywords: emotion, mindset, moral development, moral psychology, pride, shame, self-regulation

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