Search results for: classified representation

Authors: Vladislav Grigorovitch, Marina Grigorovitch, David Pearlmutter, Erez Gal

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The concept of “electric island” is involved with achieving the balance between the self-power generation ability of each educational institution and energy consumption demand. Photo-Voltaic (PV) solar system installed on the roofs of educational buildings is a common way to absorb the available solar energy and generate electricity for self-consumption and even for returning to the grid. The main objective of this research is to develop and implement an “electric island” monitoring infrastructure for promoting energy efficiency in educational buildings. A microscale monitoring methodology will be developed to provide a platform to estimate energy consumption performance classified by rooms and subspaces rather than the more common macroscale monitoring of the whole building. The monitoring platform will be established on the experimental sites, enabling an estimation and further analysis of the variety of environmental and physical conditions. For each building, separate measurement configurations will be applied taking into account the specific requirements, restrictions, location and infrastructure issues. The direct results of the measurements will be analyzed to provide deeper understanding of the impact of environmental conditions and sustainability construction standards, not only on the energy demand of public building, but also on the energy consumption habits of the children that study in those schools and the educational and administrative staff that is responsible for providing the thermal comfort conditions and healthy studying atmosphere for the children. A monitoring methodology being developed in this research is providing online access to real-time data of Interferential Therapy (IFTs) from any mobile phone or computer by simply browsing the dedicated website, providing powerful tools for policy makers for better decision making while developing PV production infrastructure to achieve “electric islands” in educational buildings. A detailed measurement configuration was technically designed based on the specific conditions and restriction of each of the pilot buildings. A monitoring and analysis methodology includes a large variety of environmental parameters inside and outside the schools to investigate the impact of environmental conditions both on the energy performance of the school and educational abilities of the children. Indoor measurements are mandatory to acquire the energy consumption data, temperature, humidity, carbon dioxide and other air quality conditions in different parts of the building. In addition to that, we aim to study the awareness of the users to the energy consideration and thus the impact on their energy consumption habits. The monitoring of outdoor conditions is vital for proper design of the off-grid energy supply system and validation of its sufficient capacity. The suggested outcomes of this research include: 1. both experimental sites are designed to have PV production and storage capabilities; 2. Developing an online information feedback platform. The platform will provide consumer dedicated information to academic researchers, municipality officials and educational staff and students; 3. Designing an environmental work path for educational staff regarding optimal conditions and efficient hours for operating air conditioning, natural ventilation, closing of blinds, etc.

Keywords: sustainability, electric island, IOT, smart building

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Authors: Jorge Cortés, Alejandra Martínez, Carlos Pérez, Anaid Simón

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The presence of government, news media, and general citizenry in social media allows considering interactions between them as a form of political communication (i.e. the public exchange of contradictory discourses about politics). Twitter’s asymmetrical following model (users can follow, mention or reply to other users that do not follow them) could foster alternative democratic practices and have an impact on Mexican political culture, which has been marked by a lack of direct communication channels between these actors. The research aim is to assess Twitter’s role in political communication practices through the analysis of interaction dynamics between government, news media, and citizens by extracting and visualizing data from Twitter’s API to observe general behavior patterns. The hypothesis is that regardless the fact that Twitter’s features enable direct and horizontal interactions between actors, users repeat traditional dynamics of interaction, without taking full advantage of the possibilities of this medium. Through an interdisciplinary team including Communication Strategies, Information Design, and Interaction Systems, the activity on Twitter generated by the controversy over the presence of Uber in Mexico City was analysed; an issue of public interest, involving aspects such as public opinion, economic interests and a legal dimension. This research includes techniques from social network analysis (SNA), a methodological approach focused on the comprehension of the relationships between actors through the visual representation and measurement of network characteristics. The analysis of the Uber event comprised data extraction, data categorization, corpus construction, corpus visualization and analysis. On the recovery stage TAGS, a Google Sheet template, was used to extract tweets that included the hashtags #UberSeQueda and #UberSeVa, posts containing the string Uber and tweets directed to @uber_mx. Using scripts written in Python, the data was filtered, discarding tweets with no interaction (replies, retweets or mentions) and locations outside of México. Considerations regarding bots and the omission of anecdotal posts were also taken into account. The utility of graphs to observe interactions of political communication in general was confirmed by the analysis of visualizations generated with programs such as Gephi and NodeXL. However, some aspects require improvements to obtain more useful visual representations for this type of research. For example, link¬crossings complicates following the direction of an interaction forcing users to manipulate the graph to see it clearly. It was concluded that some practices prevalent in political communication in Mexico are replicated in Twitter. Media actors tend to group together instead of interact with others. The political system tends to tweet as an advertising strategy rather than to generate dialogue. However, some actors were identified as bridges establishing communication between the three spheres, generating a more democratic exercise and taking advantage of Twitter’s possibilities. Although interactions in Twitter could become an alternative to political communication, this potential depends on the intentions of the participants and to what extent they are aiming for collaborative and direct communications. Further research is needed to get a deeper understanding on the political behavior of Twitter users and the possibilities of SNA for its analysis.

Keywords: interaction, political communication, social network analysis, Twitter

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Authors: M. Isabel Santos, Ana Breda, Ana Margarida Almeida

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Research on academic abilities of individuals with autism spectrum disorder (ASD) underlines the importance of mathematics interventions. Yet the proposal of digital applications for children and youth with ASD continues to attract little attention, namely, regarding the development of mathematical reasoning, being the use of the digital technologies an area of great interest for individuals with this disorder and its use is certainly a facilitative strategy in the development of their mathematical abilities. The use of digital technologies can be an effective way to create innovative learning opportunities to these students and to develop creative, personalized and constructive environments, where they can develop differentiated abilities. The children with ASD often respond well to learning activities involving information presented visually. In this context, we present the digital Learning Environment on Mathematics for Autistic children (LEMA) that was a research project conducive to a PhD in Multimedia in Education and was developed by the Thematic Line Geometrix, located in the Department of Mathematics, in a collaboration effort with DigiMedia Research Center, of the Department of Communication and Art (University of Aveiro, Portugal). LEMA is a digital mathematical learning environment which activities are dynamically adapted to the user’s profile, towards the development of mathematical abilities of children aged 6–12 years diagnosed with ASD. LEMA has already been evaluated with end-users (both students and teacher’s experts) and based on the analysis of the collected data readjustments were made, enabling the continuous improvement of the prototype, namely considering the integration of universal design for learning (UDL) approaches, which are of most importance in ASD, due to its heterogeneity. The learning strategies incorporated in LEMA are: (i) provide options to custom choice of math activities, according to user’s profile; (ii) integrates simple interfaces with few elements, presenting only the features and content needed for the ongoing task; (iii) uses a simple visual and textual language; (iv) uses of different types of feedbacks (auditory, visual, positive/negative reinforcement, hints with helpful instructions including math concept definitions, solved math activities using split and easier tasks and, finally, the use of videos/animations that show a solution to the proposed activity); (v) provides information in multiple representation, such as text, video, audio and image for better content and vocabulary understanding in order to stimulate, motivate and engage users to mathematical learning, also helping users to focus on content; (vi) avoids using elements that distract or interfere with focus and attention; (vii) provides clear instructions and orientation about tasks to ease the user understanding of the content and the content language, in order to stimulate, motivate and engage the user; and (viii) uses buttons, familiarly icons and contrast between font and background. Since these children may experience little sensory tolerance and may have an impaired motor skill, besides the user to have the possibility to interact with LEMA through the mouse (point and click with a single button), the user has the possibility to interact with LEMA through Kinect device (using simple gesture moves).

Keywords: autism spectrum disorder, digital technologies, inclusion, mathematical abilities, mathematical learning activities

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Authors: Jim O'brien

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Contemporary global representation and consumption of La Liga across a plethora of media platform outlets has resulted in significant implications for the historical, political and cultural developments which shaped the development of Spanish club football. This has established and reinforced a hierarchy of a small number of teams belonging to or aspiring to belong to a cluster of global elite clubs seeking to imitate the blueprint of the English Premier League in respect of corporate branding and marketing in order to secure a global fan base through success and exposure in La Liga itself and through the Champions League. The synthesis between globalization, global sport and the status of high profile clubs has created radical change within the folkloric iconography of Spanish football. The main focus of this paper is to critically evaluate the consequences of globalization on the rich tapestry at the core of the game’s distinctive history in Spain. The seminal debate underpinning the study considers whether the divergent aspects of globalization have acted as a malevolent force, eroding tradition, causing financial meltdown and reducing much of the fabric of club football to the status of by standers, or have promoted a renaissance of these traditions, securing their legacies through new fans and audiences. The study draws on extensive sources on the history, politics and culture of Spanish football, in both English and Spanish. It also uses primary and archive material derived from interviews and fieldwork undertaken with scholars, media professionals and club representatives in Spain. The paper has four main themes. Firstly, it contextualizes the key historical, political and cultural forces which shaped the landscape of Spanish football from the late nineteenth century. The seminal notions of region, locality and cultural divergence are pivotal to this discourse. The study then considers the relationship between football, ethnicity and identity as a barometer of continuity and change, suggesting that tradition is being reinvented and re-framed to reflect the shifting demographic and societal patterns within the Spanish state. Following on from this, consideration is given to the paradoxical function of ‘El Clasico’ and the dominant duopoly of the FC Barcelona – Real Madrid axis in both eroding tradition in the global nexus of football’s commodification and in protecting historic political rivalries. To most global consumers of La Liga, the mega- spectacle and hyperbole of ‘El Clasico’ is the essence of Spanish football, with cultural misrepresentation and distortion catapulting the event to the global media audience. Finally, the paper examines La Liga as a sporting phenomenon in which elite clubs, cult managers and galacticos serve as commodities on the altar of mass consumption in football’s global entertainment matrix. These processes accentuate a homogenous mosaic of cultural conformity which obscures local, regional and national identities and paradoxically fuses the global with the local to maintain the distinctive hue of La Liga, as witnessed by the extraordinary successes of Athletico Madrid and FC Eibar in recent seasons.

Keywords: Spanish football, globalization, cultural identity, tradition, folklore

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Authors: Shivani Dhande, Sanjiv Choudhary, Adarshlata Singh

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Introduction: Chemical peeling is a popular, relatively inexpensive day procedure and generally safe method for treatment of pigmentary skin disorders and for skin rejuvenation. Chemical peels are classified by the depth of action into superficial, medium, and deep peels.Various facial pigmentary conditions have significant impact on quality of life causing psychological stress, necessitating its safe and effective treatment.Aim & Objectives:To compare the efficacy of Salicylic acid, Trichloroaceticacid & Glycolic Acid in facial melanosis(melasma,photomelanosis& post acne pigmentation).To study the side effects of above mentioned peeling agents. Method and Materials:It was a randomized parallel control single blind study consisting of total of 36 cases, 12 cases each of melasma, photo melanosis and post acne pigmentation within age group 20-50 years having fitzpatrick’s skin type4. Woods lamp examination was done to confirm the type of melasma.Patients with keloidal tendency, active herpes infection or past history of hypersensitivity to salicylic acid, trichloroaceticand glycolic acid as well aspatients on systemic isotretinoin were excluded.Clinical photographs at the beginning of therapy and then serially, were taken to assess the clinical response. Prior to application a written informed consent was obtained. A post auricular test peel was performed. Patients were divided into 3 groups, containing 12 patients each of melasma, photomelanosis and post acnepigmentation.All the three peels SA peel 20% (done once in 2 weeks), GA peel 50% (done once in 3 weeks) and TCA 15% (done once in 3 weeks) were used with total six settings for each patient. Before application of peel patients were counseled to wash the face with soap and water. Then face was dried and cleaned with spirit and acetone to remove all cutaneous oils. GA, TCA, SA were applied with cotton buds/gauze withmild strokes. After a contact period off 5-10mins neutralization was done with cold water. Post peel topical sunscreen application was mandatory. MASI was used pre and post treatment to assess melasma. Investigator’s global improvement scale- overall hyperpigmentation (4-significant, 3-moderate, 2-mild, 1-minimal, 0-no change ) and Patient’s satisfaction grading scale (>70%- excellent response, 50-70%- good response, <50%- average response) was used to assess improvement in all the three facial melanosis.Results:In our study of 12 patients of melasma, 4 (33.33%)patients showed excellent results;3 (25%) with GAand 1(8.33%) of TCA.Good response was seen in 4 (33.33%) patients;1(8.33%) each for GA & SA and 2(16.66%) for TCA.Poor response was seen in 4(33.33%) patients;1(8.33%) for TCA and 3 (25%) for SA.Of 12 patients of photomelanosis, excellent resultswas seen in 3(25%)patients of TCA. Good response was seen in 4 (33.33%) patients, 1(8.33%) each of TCA &SA and 2(16.66%) of GA.Poor responsewas seen in 5(41.66%) patients;3 (25%) for SA and 2(16.66%) of GA.Of 12 patients of post acne pigmentation, excellent responsein 3 (25%) patients;2(16.66%) of SA and 1(8.33%) of TCA.Good responsewas seen in 5(41.66%) patients;2(16.66%) of SA and GA and1(8.33%) of TCA.Poor response was seen in 4 (33.33%) patients; 2 (16.66%) for SA and TCA both. No major side effects in the form of scarring or persistant pigmentation was seen. Transient blackening of skin with burning sensation was seen in cases treated with TCA and SA. Post procedural itching and redness was noted with GA peel. Conclusion- In our study GA(50%),TCA(15%) & SA(20%) peels showed excellent response in melasma, photomelanosis and post-acne pigmentation respectively.All the 3 peeling agents were well tolerated without any significant side-effects in the above specified concentrations.

Keywords: facial melanosis, gycolic acid, salicylic acid, trichloroacetic acid

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Authors: Paul Licina, Emma M. Johnston, David Lisle, Mark Young, Chris Brady

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Background: Lumbar pars pathology is a common cause of pain in the growing spine. It can be seen in young athletes participating in at-risk sports and can affect sporting performance and long-term health due to its resistance to traditional management. There is a current lack of consensus of classification and treatment for pars injuries. Previous systems used CT to stage pars defects but could not assess early stress reactions. A modified classification is proposed that considers findings on MRI, significantly improving early treatment guidance. The treatment protocol is designed for patients aged 5 to 19 years. Method: Clinical screening identifies patients with a low, medium, or high index of suspicion for lumbar pars injury using patient age, sport participation and pain characteristics. MRI of the at-risk cohort enables augmentation of existing CT-based classification while avoiding ionising radiation. Patients are classified into five categories based on MRI findings. A type 0 lesion (stress reaction) is present when CT is normal and MRI shows high signal change (HSC) in the pars/pedicle on T2 images. A type 1 lesion represents the ‘early defect’ CT classification. The group previously referred to as a 'progressive stage' defect on CT can be split into 2A and 2B categories. 2As have HSC on MRI, whereas 2Bs do not. This distinction is important with regard to healing potential. Type 3 lesions are terminal stage defects on CT, characterised by pseudarthrosis. MRI shows no HSC. Results: Stress reactions (type 0) and acute fractures (1 and 2a) can heal and are treated in a custom-made hard brace for 12 weeks. It is initially worn 23 hours per day. At three weeks, patients commence basic core rehabilitation. At six weeks, in the absence of pain, the brace is removed for sleeping. Exercises are progressed to positions of daily living. Patients with continued pain remain braced 23 hours per day without exercise progression until becoming symptom-free. At nine weeks, patients commence supervised exercises out of the brace for 30 minutes each day. This allows them to re-learn muscular control without rigid support of the brace. At 12 weeks, bracing ceases and MRI is repeated. For patients with near or complete resolution of bony oedema and healing of any cortical defect, rehabilitation is focused on strength and conditioning and sport-specific exercise for the full return to activity. The length of this final stage is approximately nine weeks but depends on factors such as development and level of sports participation. If significant HSC remains on MRI, CT scan is considered to definitively assess cortical defect healing. For these patients, return to high-risk sports is delayed for up to three months. Chronic defects (2b and 3) cannot heal and are not braced, and rehabilitation follows traditional protocols. Conclusion: Appropriate clinical screening and imaging with MRI can identify pars pathology early. In those with potential for healing, we propose hard bracing and appropriate rehabilitation as part of a multidisciplinary management protocol. The validity of this protocol will be tested in future studies.

Keywords: adolescents, MRI classification, pars interticularis, treatment protocol

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Authors: Ruth Leitch, Joanne Hughes

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This paper presents the findings of a three-year government-funded study (ILiAD) that aimed to understand the reasons for differential educational achievement within and between socially and economically deprived areas in Northern Ireland. Previous international studies have concluded that there is a positive correlation between deprivation and underachievement. Our preliminary secondary data analysis suggested that the factors involved in educational achievement within multiple deprived areas may be more complex than this, with some areas of high multiple deprivation having high levels of student attainment, whereas other less deprived areas demonstrated much lower levels of student attainment, as measured by outcomes on high stakes national tests. The study proposed that no single explanation or disparate set of explanations could easily account for the linkage between levels of deprivation and patterns of educational achievement. Using a social capital perspective that centralizes the connections within and between individuals and social networks in a community as a valuable resource for educational achievement, the ILiAD study involved a multi-level case study analysis of seven community sites in Northern Ireland, selected on the basis of religious composition (housing areas are largely segregated by religious affiliation), measures of multiple deprivation and differentials in educational achievement. The case study approach involved three (interconnecting) levels of qualitative data collection and analysis - what we have termed Micro (or community/grassroots level) understandings, Meso (or school level) explanations and Macro (or policy/structural) factors. The analysis combines a statistical mapping of factors with qualitative, in-depth data interpretation which, together, allow for deeper understandings of the dynamics and contributory factors within and between the case study sites. Thematic analysis of the qualitative data reveals both cross-cutting factors (e.g. demographic shifts and loss of community, place of the school in the community, parental capacity) and analytic case studies of explanatory factors associated with each of the community sites also permit a comparative element. Issues arising from the qualitative analysis are classified either as drivers or inhibitors of educational achievement within and between communities. Key issues that are emerging as inhibitors/drivers to attainment include: the legacy of the community conflict in Northern Ireland, not least in terms of inter-generational stress, related with substance abuse and mental health issues; differing discourses on notions of ‘community’ and ‘achievement’ within/between community sites; inter-agency and intra-agency levels of collaboration and joined-up working; relationship between the home/school/community triad and; school leadership and school ethos. At this stage, the balance of these factors can be conceptualized in terms of bonding social capital (or lack of it) within families, within schools, within each community, within agencies and also bridging social capital between the home/school/community, between different communities and between key statutory and voluntary organisations. The presentation will outline the study rationale, its methodology, present some cross-cutting findings and use an illustrative case study of the findings from a community site to underscore the importance of attending to community differences when trying to engage in research to understand and improve educational attainment for all.

Keywords: educational achievement, multiple deprivation, community case studies, social capital

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Authors: Satish Kumar, Nisha Goyal

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In the stock market, individual investors exhibit different kinds of behaviour. Traditional finance is built on the notion of 'homo economics', which states that humans always make perfectly rational choices to maximize their wealth and minimize risk. That is, traditional finance has concern for how investors should behave rather than how actual investors are behaving. Behavioural finance provides the explanation for this phenomenon. Although finance has been studied for thousands of years, behavioural finance is an emerging field that combines the behavioural or psychological aspects with conventional economic and financial theories to provide explanations on how emotions and cognitive factors influence investors’ behaviours. These emotions and cognitive factors are known as behavioural biases. Because of these biases, investors make irrational investment decisions. Besides, the emotional and cognitive factors, the social influence of media as well as friends, relatives and colleagues also affect investment decisions. Psychological factors influence individual investors’ investment decision making, but few studies have used qualitative methods to understand these factors. The aim of this study is to explore the behavioural factors or biases that affect individuals’ investment decision making. For the purpose of this exploratory study, an in-depth interview method was used because it provides much more exhaustive information and a relaxed atmosphere in which people feel more comfortable to provide information. Twenty investment advisors having a minimum 5 years’ experience in securities firms were interviewed. In this study, thematic content analysis was used to analyse interview transcripts. Thematic content analysis process involves analysis of transcripts, coding and identification of themes from data. Based on the analysis we categorized the statements of advisors into various themes. Past market returns and volatility; preference for safe returns; tendency to believe they are better than others; tendency to divide their money into different accounts/assets; tendency to hold on to loss-making assets; preference to invest in familiar securities; tendency to believe that past events were predictable; tendency to rely on the reference point; tendency to rely on other sources of information; tendency to have regret for making past decisions; tendency to have more sensitivity towards losses than gains; tendency to rely on own skills; tendency to buy rising stocks with the expectation that this rise will continue etc. are some of the major concerns showed by experts about investors. The findings of the study revealed 13 biases such as overconfidence bias, disposition effect, familiarity bias, framing effect, anchoring bias, availability bias, self-attribution bias, representativeness, mental accounting, hindsight bias, regret aversion, loss aversion and herding bias/media biases present in Indian investors. These biases have a negative connotation because they produce a distortion in the calculation of an outcome. These biases are classified under three categories such as cognitive errors, emotional biases and social interaction. The findings of this study may assist both financial service providers and researchers to understand the various psychological biases of individual investors in investment decision making. Additionally, individual investors will also be aware of the behavioural biases that will aid them to make sensible and efficient investment decisions.

Keywords: financial advisors, individual investors, investment decisions, psychological biases, qualitative thematic content analysis

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Authors: Babak Forouraghi

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A genetic circuit is a collection of interacting genes and proteins that enable individual cells to implement and perform vital biological functions such as cell division, growth, death, and signaling. In cell engineering, synthetic gene circuits are engineered networks of genes specifically designed to implement functionalities that are not evolved by nature. These engineered networks enable scientists to tackle complex problems such as engineering cells to produce therapeutics within the patient's body, altering T cells to target cancer-related antigens for treatment, improving antibody production using engineered cells, tissue engineering, and production of genetically modified plants and livestock. Construction of computational models to realize genetic circuits is an especially challenging task since it requires the discovery of flow of genetic information in complex biological systems. Building synthetic biological models is also a time-consuming process with relatively low prediction accuracy for highly complex genetic circuits. The primary goal of this study was to investigate the utility of a pre-trained bidirectional encoder transformer that can accurately predict gene expressions in genetic circuit designs. The main reason behind using transformers is their innate ability (attention mechanism) to take account of the semantic context present in long DNA chains that are heavily dependent on spatial representation of their constituent genes. Previous approaches to gene circuit design, such as CNN and RNN architectures, are unable to capture semantic dependencies in long contexts as required in most real-world applications of synthetic biology. For instance, RNN models (LSTM, GRU), although able to learn long-term dependencies, greatly suffer from vanishing gradient and low-efficiency problem when they sequentially process past states and compresses contextual information into a bottleneck with long input sequences. In other words, these architectures are not equipped with the necessary attention mechanisms to follow a long chain of genes with thousands of tokens. To address the above-mentioned limitations of previous approaches, a transformer model was built in this work as a variation to the existing DNA Bidirectional Encoder Representations from Transformers (DNABERT) model. It is shown that the proposed transformer is capable of capturing contextual information from long input sequences with attention mechanism. In a previous work on genetic circuit design, the traditional approaches to classification and regression, such as Random Forrest, Support Vector Machine, and Artificial Neural Networks, were able to achieve reasonably high R2 accuracy levels of 0.95 to 0.97. However, the transformer model utilized in this work with its attention-based mechanism, was able to achieve a perfect accuracy level of 100%. Further, it is demonstrated that the efficiency of the transformer-based gene expression classifier is not dependent on presence of large amounts of training examples, which may be difficult to compile in many real-world gene circuit designs.

Keywords: transformers, generative ai, gene expression design, classification

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Authors: Rawan Hakawati, Beatrice Smyth, David Rooney, Geoffrey McCullough

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Targets have been set in the EU to increase the share of renewable energy consumption to 20% by 2020, but developments have not occurred evenly across the member states. Northern Ireland is almost 90% dependent on imported fossil fuels. With such high energy dependency, Northern Ireland is particularly susceptible to the security of supply issues. Linked to fossil fuels are greenhouse gas emissions, and the EU plans to reduce emissions by 20% by 2020. The use of indigenously produced biomass could reduce both greenhouse gas emissions and external energy dependence. With a wide range of both crop and waste feedstock potentially available in Northern Ireland, anaerobic digestion has been put forward as a possible solution for renewable energy production, waste management, and greenhouse gas reduction. Not all feedstock, however, is the same, and an understanding of feedstock suitability is important for both plant operators and policy makers. The aim of this paper is to investigate biomass suitability for anaerobic digestion in Northern Ireland. It is also important that decisions are based on solid scientific evidence. For this reason, the methodology used is multi-criteria decision matrix analysis which takes multiple criteria into account simultaneously and ranks alternatives accordingly. The model uses the weighted sum method (which follows the Entropy Method to measure uncertainty using probability theory) to decide on weights. The Topsis method is utilized to carry out the mathematical analysis to provide the final scores. Feedstock that is currently available in Northern Ireland was classified into two categories: wastes (manure, sewage sludge and food waste) and energy crops, specifically grass silage. To select the most suitable feedstock, methane yield, feedstock availability, feedstock production cost, biogas production, calorific value, produced kilowatt-hours, dry matter content, and carbon to nitrogen ratio were assessed. The highest weight (0.249) corresponded to production cost reflecting a variation of £41 gate fee to 22£/tonne cost. The weights calculated found that grass silage was the most suitable feedstock. A sensitivity analysis was then conducted to investigate the impact of weights. The analysis used the Pugh Matrix Method which relies upon The Analytical Hierarchy Process and pairwise comparisons to determine a weighting for each criterion. The results showed that the highest weight (0.193) corresponded to biogas production indicating that grass silage and manure are the most suitable feedstock. Introducing co-digestion of two or more substrates can boost the biogas yield due to a synergistic effect induced by the feedstock to favor positive biological interactions. A further benefit of co-digesting manure is that the anaerobic digestion process also acts as a waste management strategy. From the research, it was concluded that energy from agricultural biomass is highly advantageous in Northern Ireland because it would increase the country's production of renewable energy, manage waste production, and would limit the production of greenhouse gases (current contribution from agriculture sector is 26%). Decision-making methods based on scientific evidence aid policy makers in classifying multiple criteria in a logical mathematical manner in order to reach a resolution.

Keywords: anaerobic digestion, biomass as feedstock, decision matrix, renewable energy

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Authors: Madalena Corte-real, João Pedro Nunes, Bernardo Fernandes, Ana Jorge Correira

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This presentation looks, from a sociological perspective, at neighboring practices in the inner city of Lisbon. The capital of Portugal, with half a million inhabitants, inserted in a metropolitan area with almost 2,9 million people, has been in the international spotlight seen as an interesting city to live in and to invest in, especially in the real estate market. This promotion emerged in the context of the financial crisis, where local authorities aimed to make Lisbon a more competitive city, calling for visitors and financial and human capital. Especially in the last decade, Portugal’s capital has been experiencing a significant increase in terms of migration from creative and entrepreneurial exiles to economic and political expats. In this context, the territory under analysis, in particular, is a mixed-used area undergoing rapid transformations in recent years marked by the presence of newcomers and non-nationals as well as social and cultural heterogeneity. It is next to one of the main arteries, considered the most multicultural part of the city, and presented in the press as one of the coolest neighborhoods in Europe. In view of these aspects, this research aims to address key-topics in current urban research: anonymity often related to big cities, socio-spatial attachment to the neighborhood, and the effects of diversity in the everyday relations of residents and shopkeepers. This case-study intends to look at particularities in local regimes differently affected by growing mobility. Against a backdrop of unidimensional generalizations and a tendency to refer to central countries and global cities, it aims to discuss national and local specificities. In methodological terms, the project comprises essentially a qualitative approach that consists of direct observation techniques and ethnographic methods as well semi-structured interviews to residents and local stakeholders whose narratives are subject to content analysis. The paper starts with a characterization of the broader context of the city of Lisbon, followed by territorial specificities regarding socio-spatial development, namely the city’s and the inner-areas morphology as well as the population’s socioeconomic profile. Following the residents and stakeholders’ narratives and practices it will assess the perception and behaviors regarding the representation of the area, relationships and experiences, routines, and sociability. Results point to a significant presence of neighborhood relations and different forms of support, in particular, among the different groups – e.g., old long-time residents, middle-class families, global creative class, and communities of economic migrants. Fieldwork reveals low levels of place-attachment although some residents refer, presently, high levels of satisfaction. Engagement with living space, this case-study suggests, reveals the social construction and lived the experience of neighboring by different groups, but also the way different and contrasting visions and desires are articulated to the profound urban, cultural and political changes that permeate the area.

Keywords: diversity, lisbon, neighboring and neighborhood, place-attachment

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Authors: Michele Paleologo, Marta Acampora, Serena Barello, Guendalina Graffigna

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Introduction: In the face of increasing demands for higher agricultural productivity with minimal environmental impact, participatory research approaches emerge as promising means to promote innovation. However, the complexities and ambiguities surrounding these approaches in both theory and practice present challenges. This Scoping Review seeks to bridge these gaps by mapping participatory approaches in agricultural contexts, analyzing their characteristics, and identifying indicators of success. Methods: Following PRISMA guidelines, we conducted a systematic Scoping Review, searching Scopus and Web of Science databases. Our review encompassed 34 projects from diverse geographical regions and farming contexts. Thematic analysis was employed to explore the types of innovation promoted and the categories of participants involved. Results: The identified innovation types encompass technological advancements, sustainable farming practices, and market integration, forming 5 main themes: climate change, cultivar, irrigation, pest and herbicide, and technical improvement. These themes represent critical areas where participatory research drives innovation to address pressing agricultural challenges. Participants were categorized as citizens, experts, NGOs, private companies, and public bodies. Understanding their roles is vital for designing effective participatory initiatives that embrace diverse stakeholders. The review also highlighted 27 theoretical frameworks underpinning participatory projects. Clearer guidelines and reporting standards are crucial for facilitating the comparison and synthesis of findings across studies, thereby enhancing the robustness of future participatory endeavors. Furthermore, we identified three main categories of barriers and facilitators: pragmatic/behavioral, emotional/relational, and cognitive. These insights underscore the significance of participant engagement and collaborative decision-making for project success beyond theoretical considerations. Regarding participation, projects were classified as contributory (5 cases), where stakeholders contributed insights; collaborative (10 cases), with active co-designing of solutions; and co-created (19 cases), featuring deep stakeholder involvement from ideation to implementation, resulting in joint ownership of outcomes. Such diverse participation modes highlight the adaptability of participatory approaches to varying agricultural contexts. Discussion: In conclusion, this Scoping Review demonstrates the potential of participatory research in driving transformative changes in farmers' practices, fostering sustainability and innovation in agriculture. Understanding the diverse landscape of participatory approaches, theoretical frameworks, and participant engagement strategies is essential for designing effective and context-specific interventions. Collaborative efforts among researchers, practitioners, and stakeholders are pivotal in harnessing the full potential of participatory approaches and driving positive change in agricultural settings worldwide. The identified themes of innovation and participation modes provide valuable insights for future research and targeted interventions in agricultural innovation.

Keywords: participatory research, co-creation, agricultural innovation, stakeholders' engagement

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Authors: Diana Reckien

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Vulnerability assessments are increasingly used to support policy-making in complex environments, like urban areas. Usually, vulnerability studies include the construction of aggregate (sub-) indices and the subsequent mapping of indices across an area of interest. Vulnerability studies show a couple of advantages: they are great communication tools, can inform a wider general debate about environmental issues, and can help allocating and efficiently targeting scarce resources for adaptation policy and planning. However, they also have a number of challenges: Vulnerability assessments are constructed on the basis of a wide range of methodologies and there is no single framework or methodology that has proven to serve best in certain environments, indicators vary highly according to the spatial scale used, different variables and metrics produce different results, and aggregate or composite vulnerability indicators that are mapped easily distort or bias the picture of vulnerability as they hide the underlying causes of vulnerability and level out conflicting reasons of vulnerability in space. So, there is urgent need to further develop the methodology of vulnerability studies towards a common framework, which is one reason of the paper. We introduce a social vulnerability approach, which is compared with other approaches of bio-physical or sectoral vulnerability studies relatively developed in terms of a common methodology for index construction, guidelines for mapping, assessment of sensitivity, and verification of variables. Two approaches are commonly pursued in the literature. The first one is an additive approach, in which all potentially influential variables are weighted according to their importance for the vulnerability aspect, and then added to form a composite vulnerability index per unit area. The second approach includes variable reduction, mostly Principal Component Analysis (PCA) that reduces the number of variables that are interrelated into a smaller number of less correlating components, which are also added to form a composite index. We test these two approaches of constructing indices on the area of New York City as well as two different metrics of variables used as input and compare the outcome for the 5 boroughs of NY. Our analysis yields that the mapping exercise yields particularly different results in the outer regions and parts of the boroughs, such as Outer Queens and Staten Island. However, some of these parts, particularly the coastal areas receive the highest attention in the current adaptation policy. We imply from this that the current adaptation policy and practice in NY might need to be discussed, as these outer urban areas show relatively low social vulnerability as compared with the more central parts, i.e. the high dense areas of Manhattan, Central Brooklyn, Central Queens and the Southern Bronx. The inner urban parts receive lesser adaptation attention, but bear a higher risk of damage in case of hazards in those areas. This is conceivable, e.g., during large heatwaves, which would more affect more the inner and poorer parts of the city as compared with the outer urban areas. In light of the recent planning practice of NY one needs to question and discuss who in NY makes adaptation policy for whom, but the presented analyses points towards an under representation of the needs of the socially vulnerable population, such as the poor, the elderly, and ethnic minorities, in the current adaptation practice in New York City.

Keywords: vulnerability mapping, social vulnerability, additive approach, Principal Component Analysis (PCA), New York City, United States, adaptation, social sensitivity

Procedia PDF Downloads 371

Authors: Vijaya Dixit Aasheesh Dixit

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Shipbuilding industry operates in Engineer Procure Construct (EPC) context. Product mix of a shipyard comprises of various types of ships like bulk carriers, tankers, barges, coast guard vessels, sub-marines etc. Each order is unique based on the type of ship and customized requirements, which are engineered into the product right from design stage. Thus, to execute every new project, a shipyard needs to upgrade its production expertise. As a result, over the long run, holistic learning occurs across different types of projects which contributes to the knowledge base of the shipyard. Simultaneously, in the short term, during execution of a project comprising of multiple sister ships, repetition of similar tasks leads to learning at activity level. This research aims to capture above learnings of a shipyard and incorporate learning curve effect in project scheduling and materials procurement to improve project performance. Extant literature provides support for the existence of such learnings in an organization. In shipbuilding, there are sequences of similar activities which are expected to exhibit learning curve behavior. For example, the nearly identical structural sub-blocks which are successively fabricated, erected, and outfitted with piping and electrical systems. Learning curve representation can model not only a decrease in mean completion time of an activity, but also a decrease in uncertainty of activity duration. Sister ships have similar material requirements. The same supplier base supplies materials for all the sister ships within a project. On one hand, this provides an opportunity to reduce transportation cost by batching the order quantities of multiple ships. On the other hand, it increases the inventory holding cost at shipyard and the risk of obsolescence. Further, due to learning curve effect the production scheduled of each consequent ship gets compressed. Thus, the material requirement schedule of every next ship differs from its previous ship. As more and more ships get constructed, compressed production schedules increase the possibility of batching the orders of sister ships. This work aims at integrating materials management with project scheduling of long duration projects for manufacturing of multiple sister ships. It incorporates the learning curve effect on progressively compressing material requirement schedules and addresses the above trade-off of transportation cost and inventory holding and shortage costs while satisfying budget constraints of various stages of the project. The activity durations and lead time of items are not crisp and are available in the form of probabilistic distribution. A Stochastic Mixed Integer Programming (SMIP) model is formulated which is solved using evolutionary algorithm. Its output provides ordering dates of items and degree of order batching for all types of items. Sensitivity analysis determines the threshold number of sister ships required in a project to leverage the advantage of learning curve effect in materials management decisions. This analysis will help materials managers to gain insights about the scenarios: when and to what degree is it beneficial to treat a multiple ship project as an integrated one by batching the order quantities and when and to what degree to practice distinctive procurement for individual ship.

Keywords: learning curve, materials management, shipbuilding, sister ships

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Authors: Juan Pablo Bertuzzi, Mauro Chiarella

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Employing a communication studies perspective and a socio-technological approach, this paper introduces a theoretical framework for understanding the concept of hybrid world; the avatarization phenomena; and the communicational archetype of co-hybridization. This analysis intends to make a contribution to future design of virtual reality experimental applications. Ultimately, this paper presents an ongoing research project that proposes the study of human-avatar interactions in digital educational environments, as well as an innovative reflection on inner digital communication. The aforementioned project presents the analysis of human-avatar interactions, through the development of an interactive experience in virtual reality. The goal is to generate an innovative communicational dimension that could reinforce the hypotheses presented throughout this paper. Being thought for its initial application in educational environments, the analysis and results of this research are dependent and have been prepared in regard of a meticulous planning of: the conception of a 3D digital platform; the interactive game objects; the AI or computer avatars; the human representation as hybrid avatars; and lastly, the potential of immersion, ergonomics and control diversity that can provide the virtual reality system and the game engine that were chosen. The project is divided in two main axes: The first part is the structural one, as it is mandatory for the construction of an original prototype. The 3D model is inspired by the physical space that belongs to an academic institution. The incorporation of smart objects, avatars, game mechanics, game objects, and a dialogue system will be part of the prototype. These elements have all the objective of gamifying the educational environment. To generate a continuous participation and a large amount of interactions, the digital world will be navigable both, in a conventional device and in a virtual reality system. This decision is made, practically, to facilitate the communication between students and teachers; and strategically, because it will help to a faster population of the digital environment. The second part is concentrated to content production and further data analysis. The challenge is to offer a scenario’s diversity that compels users to interact and to question their digital embodiment. The multipath narrative content that is being applied is focused on the subjects covered in this paper. Furthermore, the experience with virtual reality devices proposes users to experiment in a mixture of a seemingly infinite digital world and a small physical area of movement. This combination will lead the narrative content and it will be crucial in order to restrict user’s interactions. The main point is to stimulate and to grow in the user the need of his hybrid avatar’s help. By building an inner communication between user’s physicality and user’s digital extension, the interactions will serve as a self-guide through the gameworld. This is the first attempt to make explicit the avatarization phenomena and to further analyze the communicational archetype of co-hybridization. The challenge of the upcoming years will be to take advantage from these forms of generalized avatarization, in order to create awareness and establish innovative forms of hybridization.

Keywords: avatar, hybrid worlds, socio-technology, virtual reality

Procedia PDF Downloads 115

Authors: A. C. Facin, M. C. Maronezi , M. P. Menezes, G. L. Montanhim, L. Pavan, M. A. R. Feliciano, R. P. Nociti, R. A. R. Uscategui, P. C. Moraes

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The incidence of brachycephalic syndrome (BS) in the clinical routine of small animals has increased significantly giving the higher proportion of brachycephalic pets in the last years and has been considered as an animal welfare problem. The treatment of BS is surgical and the clinical signs related can be considerably attenuated. Nevertheless, the systemic effects of the BS are still poorly reported and little is known about these when the surgical correction is not performed early. Affected dogs are more likely to develop cardiopulmonary, gastrointestinal and sleep disorders in which the chronic hypoxemia plays a major role. This syndrome is compared with the obstructive sleep apnea (OSA) in humans, both considered as causes of systemic and metabolic dysfunction. Among the several consequences of the BS little is known if the syndrome also affects the hepatic tissue of brachycephalic patients. Elastography is a promising ultrasound technique that evaluates tissue elasticity and has been recently used with the purpose of diagnosis of liver fibrosis. In medicine, it is a growing concern regarding the hepatic injury of patients affected by OSA. This prospective study hypothesizes if there is any consequence of BS in the hepatic parenchyma of brachycephalic dogs that don’t receive any surgical treatment. This study was conducted following the approval of the Animal Ethics and Welfare Committee of the Faculdade de Ciências Agrárias e Veterinárias, UNESP, Campus Jaboticabal, Brazil (protocol no 17944/2017) and funded by Sao Paulo Research Foundation (FAPESP, process no 2017/24809-4). The methodology was based in ARFI elastography using the ACUSON S2000/SIEMENS device, with convex multifrequential transducer and specific software as well as clinical evaluation of the syndrome, in order to determine if they can be used as a prognostic non-invasive tool. On quantitative elastography, it was collected three measures of shear wave velocity (meters per second) and depth in centimeters in the left lateral, left medial, right lateral, right medial and caudate lobe of the liver. The brachycephalic patients, 16 pugs and 30 french bulldogs, were classified using a previously established 4-point functional grading system based on clinical evaluation before and after a 3-minute exercise tolerance test already established and validated. The control group was based on the same features collected in 22 beagles. The software R version 3.3.0 was used for the analysis and the significance level was set at 0.05. The data were analysed for normality of residuals and homogeneity of variances by Shapiro-Wilks test. Comparisons of parametric continuous variables between breeds were performed by using ANOVA with a post hoc test for pair wise comparison. The preliminary results show significant statistic differences between the brachycephalic groups and the control group in all lobes analysed (p ≤ 0,05), with higher values of shear wave velocities in the hepatic tissue of brachycephalic dogs. In this context, the results obtained in this study contributes to the understanding of BS as well as its consequences in our patients, reflecting in evidence that one more systemic consequence of the syndrome may occur in brachycephalic patients, which was not related in the veterinary literature yet.

Keywords: airway obstruction, brachycephalic airway obstructive syndrome, hepatic injury, obstructive sleep apnea

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Authors: Ksenia Volkova, Artur Petrosyan, Ignatii Dubyshkin, Alexei Ossadtchi

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Brain-computer interfaces are a growing research field producing many implementations that find use in different fields and are used for research and practical purposes. Despite the popularity of the implementations using non-invasive neuroimaging methods, radical improvement of the state channel bandwidth and, thus, decoding accuracy is only possible by using invasive techniques. Electrocorticography (ECoG) is a minimally invasive neuroimaging method that provides highly informative brain activity signals, effective analysis of which requires the use of machine learning methods that are able to learn representations of complex patterns. Deep learning is a family of machine learning algorithms that allow learning representations of data with multiple levels of abstraction. This study explores the potential of deep learning approaches for ECoG processing, decoding movement intentions and the perception of proprioceptive information. To obtain synchronous recording of kinematic movement characteristics and corresponding electrical brain activity, a series of experiments were carried out, during which subjects performed finger movements at their own pace. Finger movements were recorded with a three-axis accelerometer, while ECoG was synchronously registered from the electrode strips that were implanted over the contralateral sensorimotor cortex. Then, multichannel ECoG signals were used to track finger movement trajectory characterized by accelerometer signal. This process was carried out both causally and non-causally, using different position of the ECoG data segment with respect to the accelerometer data stream. The recorded data was split into training and testing sets, containing continuous non-overlapping fragments of the multichannel ECoG. A deep convolutional neural network was implemented and trained, using 1-second segments of ECoG data from the training dataset as input. To assess the decoding accuracy, correlation coefficient r between the output of the model and the accelerometer readings was computed. After optimization of hyperparameters and training, the deep learning model allowed reasonably accurate causal decoding of finger movement with correlation coefficient r = 0.8. In contrast, the classical Wiener-filter like approach was able to achieve only 0.56 in the causal decoding mode. In the noncausal case, the traditional approach reached the accuracy of r = 0.69, which may be due to the presence of additional proprioceptive information. This result demonstrates that the deep neural network was able to effectively find a representation of the complex top-down information related to the actual movement rather than proprioception. The sensitivity analysis shows physiologically plausible pictures of the extent to which individual features (channel, wavelet subband) are utilized during the decoding procedure. In conclusion, the results of this study have demonstrated that a combination of a minimally invasive neuroimaging technique such as ECoG and advanced machine learning approaches allows decoding motion with high accuracy. Such setup provides means for control of devices with a large number of degrees of freedom as well as exploratory studies of the complex neural processes underlying movement execution.

Keywords: brain-computer interface, deep learning, ECoG, movement decoding, sensorimotor cortex

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Authors: Abhinav Singh

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Point Of Sale (POS) malwares have been stealing the limelight this year. They have been the elemental factor in some of the biggest breaches uncovered in past couple of years. Some of them include • Target: A Retail Giant reported close to 40 million credit card data being stolen • Home Depot : A home product Retailer reported breach of close to 50 million credit records • Kmart: A US retailer recently announced breach of 800 thousand credit card details. Alone in 2014, there have been reports of over 15 major breaches of payment systems around the globe. Memory scrapping malwares infecting the point of sale devices have been the lethal weapon used in these attacks. These malwares are capable of reading the payment information from the payment device memory before they are being encrypted. Later on these malwares send the stolen details to its parent server. These malwares are capable of recording all the critical payment information like the card number, security number, owner etc. All these information are delivered in raw format. This Talk will cover the aspects of what happens after these details have been sent to the malware authors. The entire ecosystem of credit card frauds can be broadly classified into these three steps: • Purchase of raw details and dumps • Converting them to plastic cash/cards • Shop! Shop! Shop! The focus of this talk will be on the above mentioned points and how they form an organized network of cyber-crime. The first step involves buying and selling of the stolen details. The key point to emphasize are : • How is this raw information been sold in the underground market • The buyer and seller anatomy • Building your shopping cart and preferences • The importance of reputation and vouches • Customer support and replace/refunds These are some of the key points that will be discussed. But the story doesn’t end here. As of now the buyer only has the raw card information. How will this raw information be converted to plastic cash? Now comes in picture the second part of this underground economy where-in these raw details are converted into actual cards. There are well organized services running underground that can help you in converting these details into plastic cards. We will discuss about this technique in detail. At last, the final step involves shopping with the stolen cards. The cards generated with the stolen details can be easily used to swipe-and-pay for purchased goods at different retail shops. Usually these purchases are of expensive items that have good resale value. Apart from using the cards at stores, there are underground services that lets you deliver online orders to their dummy addresses. Once the package is received it will be delivered to the original buyer. These services charge based on the value of item that is being delivered. The overall underground ecosystem of credit card fraud works in a bulletproof way and it involves people working in close groups and making heavy profits. This is a brief summary of what I plan to present at the talk. I have done an extensive research and have collected good deal of material to present as samples. Some of them include: • List of underground forums • Credit card dumps • IRC chats among these groups • Personal chat with big card sellers • Inside view of these forum owners. The talk will be concluded by throwing light on how these breaches are being tracked during investigation. How are credit card breaches tracked down and what steps can financial institutions can build an incidence response over it.

Keywords: POS mawalre, credit card frauds, enterprise security, underground ecosystem

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Authors: Dr Grace Scaplehorn, Mr Muhammad Adeel Akhtar, Dr Jane Gibson

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Background: Canoe Slalom entails the skilful navigation of a carbon composite canoe or kayak through a series of 18-25 hanging gates, strategically positioned along the course, either upstream or downstream, amidst currents of whitewater rapids in natural and man-made river settings. Athletes compete individually in timed trials, competing for the fastest course time, typically around 80 to 120 seconds. In the new discipline of Kayak Cross, descents of the course are initiated by groups of four athletes freefalling simultaneously from a starting platform situated 3m above the river. Kayak Cross athletes, in contrast to Canoe Slalom, can make physical contact with suspended gates without incurring time penalties and are required to perform a kayak roll half way down the course. The Canoe Slalom World Championships were held at Lee Valley Whitewater Centre, London, from 19th to 24th September 2023. The event comprised 299 international athletes competing for 10 World Championship titles in Canoe/Kayak Slalom events (Olympic Debut Munich 1972), and the new Kayak Cross discipline (Olympic Debut Paris 2024). The inaugural appearance of Kayak Cross at the World Championships occurred in 2017, in Pau, France. There is limited literature surrounding Kayak Cross and the incidence of athlete injuries compared to traditional Canoe Slalom, hence it was felt important to undertake this review to address the perception that the event is dangerous. Aim: The study aimed to quantify and collate data collected from athletes presenting to the event medical centre. Methods: Athletes’ details were collected at initial assessments from the start of the practice period (16th–18th September) and throughout the event. Demographics such as age, sex and nationality were recorded along with presenting complaints, treatment, medication administered and outcome. Specifically, injuries were then sub-classified into body regions. The data does not include athletes who sought medical attention from their own governing body’s medical team. Results: During the 8-day period, there were 11 individual presentations to the medical centre, 3.7% of the athlete population (n=299). The mean age was 23.9 years (n=7), 6 were male (n=10). The most common presentation was minor injury (n=9), with 6 being musculoskeletal and 3 comprising skin damage, followed by insect sting/allergy (n=1) and pain relief requests (n=1). Five presentations were event-related, all being musculoskeletal injuries; 2 shoulder/arm, 1 head/neck, 1 hand/wrist and 1 other (data was not recorded). Of these injuries, the only intervention was 2 cases of 400mg Ibuprofen, which was given to both shoulder/arm injuries. Four of the 11 presentations were pre-existing injuries, which had been exacerbated due to increased intensity of practice. Two patients were advised to return for review, with 100% compliance. There were no unplanned re-presentations, and no emergency transfers to secondary care. Both the Kayak Cross and Canoe Slalom competitions resulted in 1 new event-related athlete presentation each. Conclusion: The event resulted in a negligible incidence of presentations at the medical centre, for both Kayak Cross and Canoe Slalom. This data holds significance in informing risk assessments and medical protocols necessary for the organisation of canoe slalom events.

Keywords: canoe slalom, kayak cross, athlete injuries, event injuries

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Authors: Yana Snegireva

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Carbonate reservoirs are known for their heterogeneity, resulting from various geological processes such as diagenesis and fracturing. These complexities may cause great challenges in understanding fluid flow behavior and predicting the production performance of naturally fractured reservoirs. The investigation of carbonate reservoirs is crucial, as many petroleum reservoirs are naturally fractured, which can be difficult due to the complexity of their fracture networks. This can lead to geological uncertainties, which are important for global petroleum reserves. The problem outlines the key challenges in carbonate reservoir modeling, including the accurate representation of fractures and their connectivity, as well as capturing the impact of fractures on fluid flow and production. Traditional reservoir modeling techniques often oversimplify fracture networks, leading to inaccurate predictions. Therefore, there is a need for a modern approach that can capture the complexities of carbonate reservoirs and provide reliable predictions for effective reservoir management and production optimization. The modern approach to carbonate reservoir modeling involves the utilization of the hybrid fracture modeling approach, including the discrete fracture network (DFN) method and implicit fracture network, which offer enhanced accuracy and reliability in characterizing complex fracture systems within these reservoirs. This study focuses on the application of the hybrid method in the Nepsko-Botuobinskaya anticline of the Eastern Siberia field, aiming to prove the appropriateness of this method in these geological conditions. The DFN method is adopted to model the fracture network within the carbonate reservoir. This method considers fractures as discrete entities, capturing their geometry, orientation, and connectivity. But the method has significant disadvantages since the number of fractures in the field can be very high. Due to limitations in the amount of main memory, it is very difficult to represent these fractures explicitly. By integrating data from image logs (formation micro imager), core data, and fracture density logs, a discrete fracture network (DFN) model can be constructed to represent fracture characteristics for hydraulically relevant fractures. The results obtained from the DFN modeling approaches provide valuable insights into the East Siberia field's carbonate reservoir behavior. The DFN model accurately captures the fracture system, allowing for a better understanding of fluid flow pathways, connectivity, and potential production zones. The analysis of simulation results enables the identification of zones of increased fracturing and optimization opportunities for reservoir development with the potential application of enhanced oil recovery techniques, which were considered in further simulations on the dual porosity and dual permeability models. This approach considers fractures as separate, interconnected flow paths within the reservoir matrix, allowing for the characterization of dual-porosity media. The case study of the East Siberia field demonstrates the effectiveness of the hybrid model method in accurately representing fracture systems and predicting reservoir behavior. The findings from this study contribute to improved reservoir management and production optimization in carbonate reservoirs with the use of enhanced and improved oil recovery methods.

Keywords: carbonate reservoir, discrete fracture network, fracture modeling, dual porosity, enhanced oil recovery, implicit fracture model, hybrid fracture model

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Authors: Omer Zvi Shaked, Amir Tirosh

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Type 1 Diabetes (T1DM) is an incurable chronic illness with no known preventive measures. Excess to insulin therapy can lead to hypoglycemia with neuro-glycogenic symptoms such as shakiness, nausea, sweating, irritability, fatigue, excessive thirst or hunger, weakness, seizure, and coma. Severe Hypoglycemia (SH) is also considered a most aversive event since it may put patients at risk for injury and death, which matches the criteria of a traumatic event. SH has a ranging prevalence of 20%, which makes it a primary medical Issue. One of the results of SH is an intense emotional fear reaction resembling the form of post-traumatic stress symptoms (PTS), causing many patients to avoid insulin therapy and social activities in order to avoid the possibility of hypoglycemia. As a result, they are at risk for irreversible health deterioration and medical complications. Fear of Hypoglycemia (FOH) is, therefore, a major disturbance for T1DM patients. FOH differs from prevalent post-traumatic stress reactions to other forms of traumatic events since the threat to life continuously exists in the patient's body. That is, it is highly probable that orthodox interventions may not be sufficient for helping patients after SH to regain healthy social function and proper medical treatment. Accordingly, the current presentation will demonstrate the results of a study conducted among T1DM patients after SH. The study was designed in two stages. First, a preliminary qualitative phenomenological study among ten patients after SH was conducted. Analysis revealed that after SH, patients confuse between stress symptoms and Hypoglycemia symptoms, divide life before and after the event, report a constant sense of fear, a loss of freedom, a significant decrease in social functioning, a catastrophic thinking pattern, a dichotomous split between the self and the body, and internalization of illness identity, a loss of internal locus of control, a damaged self-representation, and severe loneliness for never being understood by others. The second stage was a two steps study of intervention among five patients after SH. The first part of the intervention included three months of therapeutic 3rd wave CBT therapy. The contents of the therapeutic process were: acceptance of fear and tolerance to stress; cognitive de-fusion combined with emotional self-regulation; the adoption of an active position relying on personal values; and self-compassion. Then, the intervention included a one-week practical real-time 24/7 support by trained medical personnel, alongside a gradual exposure to increased insulin therapy in a protected environment. The results of the intervention are a decrease in stress symptoms, increased social functioning, increased well-being, and decreased avoidance of medical treatment. The presentation will discuss the unique emotional state of T1DM patients after SH. Then, the presentation will discuss the effectiveness of the intervention for patients with chronic conditions after a traumatic event. The presentation will make evident the unique situation of illness-related PTSD. The presentation will also demonstrate the requirement for multi-professional collaboration between social work and medical care for populations with chronic medical conditions. Limitations of the study and recommendations for further research will be discussed.

Keywords: type 1 diabetes, chronic illness, post-traumatic stress, illness-related PTSD

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Authors: Manana Lobzhanidze

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The COVID-19 pandemic has made significant changes in migration processes, notably changes in the study migration process. The constraints caused by the COVID-19 pandemic led to changes in the studying process, which negatively affected its efficiency. The educational process has partially or completely shifted to distance learning; Both labor and study migration have increased significantly in the world. The employment and education market has become global and consequently, a number of challenges have arisen for employers, researchers, and businesses. The role of preparing qualified personnel in achieving high productivity is justified, the benefits for employers and employees are assessed on the one hand, and the role of study migration for the country’s development is examined on the other hand. Research methods. The research is based on methods of analysis and synthesis, quantitative and qualitative, groupings, relative and mean quantities, graphical representation, comparison, analysis and etc. In-depth interviews were conducted with experts to determine quantitative and qualitative indicators. Research findings. Factors affecting study migration are analysed in the paper and the environment that stimulates migration is explored. One of the driving forces of migration is considered to be the desire for receiving higher pay. Levels and indicators of study migration are studied by country. Comparative analysis has found that study migration rates are high in countries where the price of skilled labor is high. The productivity of individuals with low skills is low, which negatively affects the economic development of countries. It has been revealed that students leave the country to improve their skills during study migration. The process mentioned in the article is evaluated as a positive event for a developing country, as individuals are given the opportunity to share the technology of developed countries, gain knowledge, and then introduce it in their own country. The downside of study migration is the return of a small proportion of graduates from developed economies to their home countries. The article concludes that countries with emerging economies devote less resources to research and development, while this is a priority in developed countries, allowing highly skilled individuals to use their skills efficiently. The paper studies the national education system examines the level of competition in the education market and the indicators of educational migration. The level of competition in the education market and the indicators of educational migration are studied. The role of qualified personnel in achieving high productivity is substantiated, the benefits of employers and employees are assessed on the one hand, and the role of study migration in the development of the country is revealed on the other hand. The paper also analyzes the level of competition in the education and labor markets and identifies indicators of study migration. During the pandemic period, there was a great demand for the digital technologies. Open access to a variety of comprehensive platforms will significantly reduce study migration to other countries. As a forecast, it can be said that the intensity of the use of e-learning platforms will be increased significantly in the post-pandemic period. The paper analyzes the positive and negative effects of study migration on economic development, examines the challenges of study migration in light of the COVID-19 pandemic, suggests ways to avoid negative consequences, and develops recommendations for improving the study migration process in the post-pandemic period.

Keywords: study migration, COVID-19 pandemic, factors affecting migration, economic development, post-pandemic migration

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Authors: Emilio Galdeano-Gómez, Juan C. Pérez-Mesa, Laura Piedra-Muñoz, María C. García-Barranco, Jesús Hernández-Rubio

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The situation in which firms engage in simultaneous cooperation and competition with each other is a phenomenon known as co-opetition. This scenario has received increasing attention in business economics and management analyses. In the domain of supply chain networks and for small and medium-sized enterprises, SMEs, these strategies are of greater relevance given the complex environment of globalization and competition in open markets. These firms face greater challenges regarding technology and access to specific resources due to their limited capabilities and limited market presence. Consequently, alliances and collaborations with both buyers and suppliers prove to be key elements in overcoming these constraints. However, rivalry and competition are also regarded as major factors in successful internationalization processes, as they are drivers for firms to attain a greater degree of specialization and to improve efficiency, for example enabling them to allocate scarce resources optimally and providing incentives for innovation and entrepreneurship. The present work aims to contribute to the literature on SMEs’ internationalization strategies. The sample is constituted by a panel data of marketing firms from the Andalusian food sector and a multivariate regression analysis is developed, measuring variables of co-opetition and international activity. The hierarchical regression equations method has been followed, thus resulting in three estimated models: the first one excluding the variables indicative of channel type, while the latter two include the international retailer chain and wholesaler variable. The findings show that the combination of several factors leads to a complex scenario of inter-organizational relationships of cooperation and competition. In supply chain management analyses, these relationships tend to be classified as either buyer-supplier (vertical level) or supplier-supplier relationships (horizontal level). Several buyers and suppliers tend to participate in supply chain networks, and in which the form of governance (hierarchical and non-hierarchical) influences cooperation and competition strategies. For instance, due to their market power and/or their closeness to the end consumer, some buyers (e.g. large retailers in food markets) can exert an influence on the selection and interaction of several of their intermediate suppliers, thus endowing certain networks in the supply chain with greater stability. This hierarchical influence may in turn allow these suppliers to develop their capabilities (e.g. specialization) to a greater extent. On the other hand, for those suppliers that are outside these networks, this environment of hierarchy, characterized by a “hub firm” or “channel master”, may provide an incentive for developing their co-opetition relationships. These results prove that the analyzed firms have experienced considerable growth in sales to new foreign markets, mainly in Europe, dealing with large retail chains and wholesalers as main buyers. This supply industry is predominantly made up of numerous SMEs, which has implied a certain disadvantage when dealing with the buyers, as negotiations have traditionally been held on an individual basis and in the face of high competition among suppliers. Over recent years, however, cooperation among these marketing firms has become more common, for example regarding R&D, promotion, scheduling of production and sales.

Keywords: co-petition networks, international supply chain, maketing agrifood firms, SMEs strategies

Procedia PDF Downloads 54

Authors: Esha Thakkar, Ina Liu, Kalynn Hosea, Shana Katz, Katie Marks, Sarah Hall, Cat Liu, Suzanne Harris

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Purpose: Inequities in mental healthcare accessibility are cited as an international public health concern by the World Health Organization (WHO) and National Alliance on Mental Illness (NAMI). These disparities are further exacerbated in racial and ethnic minority groups and are especially concerning in health professional training settings such as Doctor of Pharmacy (PharmD) programs and postgraduate residency training where mental illness rates are high. The purpose of the study was to determine baseline access to culturally sensitive mental healthcare and how to improve such access and communication for racially and ethnically minoritized pharmacy students and residents at one school of pharmacy and a partnering academic medical center in the United States. Methods: This IRB-exempt study included 60-minute focus groups conducted in person or online from November 2021 to February 2022. Eligible participants included PharmD students in their first (P1), second (P2), third (P3), or fourth year (P4) or pharmacy residents completing a postgraduate year 1 (PGY1) or PGY2 who identify as Black, Indigenous, or Person of Color (BIPOC). There were four core theme questions asked during the focus groups to lead the discussion, specifically on the core themes of personal barriers, identities, areas that are working well, and areas for improvement. Participant responses were transcribed and analyzed using an open coding system with two individual reviews, followed by collaborative and intentional discussion and, as needed, an external audit of the coding by a third research team member to reach a consensus on themes. Results: This study enrolled 26 participants, with eight P1, five P2, seven P3, two P4, and four resident participants. Within the four core themes of barriers, identities, areas working well, and areas for improvement, emerging subthemes included: lack of time, access to resources, and stigma under barriers; lack of representation, cultural and family stigma, and gender identities for identity barriers; supportive faculty, sense of community and culture supporting paid time off for areas going well; and wellness days, reduced workload and diversity of the workforce in areas of improvement. Subthemes sometimes varied within a core theme depending on the participant year. Conclusions: There is a gap in the literature in addressing barriers and disparities in mental health access for pharmacy trainees who identify as BIPOC. We identified key findings in regards to barriers, identities, areas going well and areas for improvement that can inform the School and the Residency Program in two priority initiatives of well-being and diversity equity and inclusion in creating actionable recommendations for trainees, program directors, and employers of our institutions, and also has the potential to provide insight for other organizations about the structures influencing access to culturally sensitive care in BIPOC trainees. These findings can inform organizations on how to continue building on communication with those who identify as BIPOC and improve access to care.

Keywords: mental health, disparities, minorities, wellbeing, identity, communication, barriers

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Authors: Babak Forouraghi

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A genetic circuit is a collection of interacting genes and proteins that enable individual cells to implement and perform vital biological functions such as cell division, growth, death, and signaling. In cell engineering, synthetic gene circuits are engineered networks of genes specifically designed to implement functionalities that are not evolved by nature. These engineered networks enable scientists to tackle complex problems such as engineering cells to produce therapeutics within the patient's body, altering T cells to target cancer-related antigens for treatment, improving antibody production using engineered cells, tissue engineering, and production of genetically modified plants and livestock. Construction of computational models to realize genetic circuits is an especially challenging task since it requires the discovery of the flow of genetic information in complex biological systems. Building synthetic biological models is also a time-consuming process with relatively low prediction accuracy for highly complex genetic circuits. The primary goal of this study was to investigate the utility of a pre-trained bidirectional encoder transformer that can accurately predict gene expressions in genetic circuit designs. The main reason behind using transformers is their innate ability (attention mechanism) to take account of the semantic context present in long DNA chains that are heavily dependent on the spatial representation of their constituent genes. Previous approaches to gene circuit design, such as CNN and RNN architectures, are unable to capture semantic dependencies in long contexts, as required in most real-world applications of synthetic biology. For instance, RNN models (LSTM, GRU), although able to learn long-term dependencies, greatly suffer from vanishing gradient and low-efficiency problem when they sequentially process past states and compresses contextual information into a bottleneck with long input sequences. In other words, these architectures are not equipped with the necessary attention mechanisms to follow a long chain of genes with thousands of tokens. To address the above-mentioned limitations, a transformer model was built in this work as a variation to the existing DNA Bidirectional Encoder Representations from Transformers (DNABERT) model. It is shown that the proposed transformer is capable of capturing contextual information from long input sequences with an attention mechanism. In previous works on genetic circuit design, the traditional approaches to classification and regression, such as Random Forrest, Support Vector Machine, and Artificial Neural Networks, were able to achieve reasonably high R2 accuracy levels of 0.95 to 0.97. However, the transformer model utilized in this work, with its attention-based mechanism, was able to achieve a perfect accuracy level of 100%. Further, it is demonstrated that the efficiency of the transformer-based gene expression classifier is not dependent on the presence of large amounts of training examples, which may be difficult to compile in many real-world gene circuit designs.

Keywords: machine learning, classification and regression, gene circuit design, bidirectional transformers

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Authors: Yaser Ghasemi Aryan, Firoozeh Moghiminejad, Mohammadreza Shahraki

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Background: The cooperative institution is considered the first and most essential pillar of strengthening social capital, whose sustainability is the main guarantee of survival and continued participation of local communities in natural resource management projects. The Village Development Group and the Microcredit Fund are two important social and economic institutions in the implementation of the International Project for the Restoration of Degraded Forest Lands (RFLDL) in Sarayan City, South Khorasan Province, which has learned positive lessons from the participation of the beneficiaries in the implementation. They have brought more effective projects to deal with desertification. However, the low activity or liquidation of some of these institutions has become one of the important challenges and concerns of project executive experts. The current research was carried out with the aim of explaining the main components of the instability of these institutions. Materials and Methods: This research is descriptive-analytical in terms of method, practical in terms of purpose, and the method of collecting information is two documentary and survey methods. The statistical population of the research included all the members of the village development groups and microcredit funds in the target villages of the RFLDL project of Sarayan city, based on the Kochran formula and matching with the Karjesi and Morgan table. Net people were selected as a statistical sample. After confirming the validity of the expert's opinions, the reliability of the questionnaire was 0.83, which shows the appropriate reliability of the researcher-made questionnaire. Data analysis was done using SPSS software. Results: The results related to the extraction of obstacles to the stability of social and economic networks were classified and prioritized in the form of 5 groups of social-cultural, economic, administrative, educational-promotional and policy-management factors. Based on this, in the socio-cultural factors, the items ‘not paying attention to the structural characteristics and composition of groups’, ‘lack of commitment and moral responsibility in some members of the group,’ and ‘lack of a clear pattern for the preservation and survival of groups’, in the disciplinary factors, The items ‘Irregularity in holding group meetings’ and ‘Irregularity of members to participate in meetings’, in the economic factors of the items "small financial capital of the fund’, ‘the low amount of loans of the fund’ and ‘the fund's inability to conclude contracts and attract capital from other sources’, in the educational-promotional factors of the items ‘non-simultaneity of job training with the granting of loans to create jobs’ and ‘insufficient training for the effective use of loans and job creation’ and in the policy-management factors of the item ‘failure to provide government facilities for support From the funds, they had the highest priority. Conclusion: In general, the results of this research show that policy-management factors and social factors, especially the structure and composition of social and economic institutions, are the most important obstacles to their sustainability. Therefore, it is suggested to form cooperative institutions based on network analysis studies in order to achieve the appropriate composition of members.

Keywords: cooperative institution, social capital, network analysis, participation, Sarayan.

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Authors: Sundaram Arulmozhiraja, Kanade Shimizu, Yuta Yamamoto, Satoshi Ichikawa, Maenaka Katsumi, Hiroaki Tokiwa

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Drug discovery is shifting from small molecule based drugs targeting local active site to middle molecules (MM) targeting large, flat, and groove-shaped binding sites, for example, protein-protein interface because at least half of all targets assumed to be involved in human disease have been classified as “difficult to drug” with traditional small molecules. Hence, MMs such as peptides, natural products, glycans, nucleic acids with various high potent bioactivities become important targets for drug discovery programs in the recent years as they could be used for ‘undruggable” intracellular targets. Cell membrane permeability is one of the key properties of pharmacodynamically active MM drug compounds and so evaluating this property for the potential MMs is crucial. Computational prediction for cell membrane permeability of molecules is very challenging; however, recent advancement in the molecular dynamics simulations help to solve this issue partially. It is expected that MMs with high membrane permeability will enable drug discovery research to expand its borders towards intracellular targets. Further to understand the chemistry behind the permeability of MMs, it is necessary to investigate their conformational changes during the permeation through membrane and for that their interactions with the membrane field should be studied reliably because these interactions involve various non-bonding interactions such as hydrogen bonding, -stacking, charge-transfer, polarization dispersion, and non-classical weak hydrogen bonding. Therefore, parameters-based classical mechanics calculations are hardly sufficient to investigate these interactions rather, quantum mechanical (QM) calculations are essential. Fragment molecular orbital (FMO) method could be used for such purpose as it performs ab initio QM calculations by dividing the system into fragments. The present work is aimed to study the cell permeability of middle molecules using molecular dynamics simulations and FMO-QM calculations. For this purpose, a natural compound syringolin and its analogues were considered in this study. Molecular simulations were performed using NAMD and Gromacs programs with CHARMM force field. FMO calculations were performed using the PAICS program at the correlated Resolution-of-Identity second-order Moller Plesset (RI-MP2) level with the cc-pVDZ basis set. The simulations clearly show that while syringolin could not permeate the membrane, its selected analogues go through the medium in nano second scale. These correlates well with the existing experimental evidences that these syringolin analogues are membrane-permeable compounds. Further analyses indicate that intramolecular -stacking interactions in the syringolin analogues influenced their permeability positively. These intramolecular interactions reduce the polarity of these analogues so that they could permeate the lipophilic cell membrane. Conclusively, the cell membrane permeability of various middle molecules with potent bioactivities is efficiently studied using molecular dynamics simulations. Insight of this behavior is thoroughly investigated using FMO-QM calculations. Results obtained in the present study indicate that non-bonding intramolecular interactions such as hydrogen-bonding and -stacking along with the conformational flexibility of MMs are essential for amicable membrane permeation. These results are interesting and are nice example for this theoretical calculation approach that could be used to study the permeability of other middle molecules. This work was supported by Japan Agency for Medical Research and Development (AMED) under Grant Number 18ae0101047.

Keywords: fragment molecular orbital theory, membrane permeability, middle molecules, molecular dynamics simulation

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Authors: Rupesh S. Gundewar, Kanchan C. Khare

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Runoff contribution from urban areas is generally from manmade structures and few natural contributors. The manmade structures are buildings; roads and other paved areas whereas natural contributors are groundwater and overland flows etc. Runoff alleviation is done by manmade as well as natural storages. Manmade storages are storage tanks or other storage structures such as soakways or soak pits which are more common in western and European countries. Natural storages are catchment slope, infiltration, catchment length, channel rerouting, drainage density, depression storage etc. A literature survey on the manmade and natural storages/inflow has presented percentage contribution of each individually. Sanders et.al. in their research have reported that a vegetation canopy reduces runoff by 7% to 12%. Nassif et el in their research have reported that catchment slope has an impact of 16% on bare standard soil and 24% on grassed soil on rainfall runoff. Infiltration being a pervious/impervious ratio dependent parameter is catchment specific. But a literature survey has presented a range of 15% to 30% loss of rainfall runoff in various catchment study areas. Catchment length and channel rerouting too play a considerable role in reduction of rainfall runoff. Ground infiltration inflow adds to the runoff where the groundwater table is very shallow and soil saturates even in a lower intensity storm. An approximate percent contribution through this inflow and surface inflow contributes to about 2% of total runoff volume. Considering the various contributing factors in runoff it has been observed during a literature survey that integrated modelling approach needs to be considered. The traditional storm water network models are able to predict to a fair/acceptable degree of accuracy provided no interaction with receiving water (river, sea, canal etc), ground infiltration, treatment works etc. are assumed. When such interactions are significant then it becomes difficult to reproduce the actual flood extent using the traditional discrete modelling approach. As a result the correct flooding situation is very rarely addressed accurately. Since the development of spatially distributed hydrologic model the predictions have become more accurate at the cost of requiring more accurate spatial information.The integrated approach provides a greater understanding of performance of the entire catchment. It enables to identify the source of flow in the system, understand how it is conveyed and also its impact on the receiving body. It also confirms important pain points, hydraulic controls and the source of flooding which could not be easily understood with discrete modelling approach. This also enables the decision makers to identify solutions which can be spread throughout the catchment rather than being concentrated at single point where the problem exists. Thus it can be concluded from the literature survey that the representation of urban details can be a key differentiator to the successful understanding of flooding issue. The intent of this study is to accurately predict the runoff from impermeable areas from urban area in India. A representative area has been selected for which data was available and predictions have been made which are corroborated with the actual measured data.

Keywords: runoff, urbanization, impermeable response, flooding

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Authors: Bangun F., Crevits B., Bellet T., Banet A., Boy G. A., Katili I.

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This paper seeks the incoherencies in cognitive process during an accident of Powered Two Wheelers (PTW) by understanding the factual sequences of events and causal relations for each case of accident. The principle of this approach is undertaking in-depth investigations on case per case of PTW accidents based on elaborate data acquisitions on accident sites that officially stamped in Police Crash Report (PCRs) 2012 of Medan with criteria, involved at least one PTW and resulted in serious injury and fatalities. The analysis takes into account four modules: accident chronologies, perpetrator, and victims, injury surveillance, vehicles and road infrastructures, comprising of traffic facilities, road geometry, road alignments and weather. The proposal for improvement could have provided a favorable influence on the chain of functional processes and events leading to collision. Decision Aiding Processes (DAP) assists in structuring different entities at different decisional levels, as each of these entities has its own objectives and constraints. The entities (A) are classified into 6 groups of accidents: solo PTW accidents; PTW vs. PTW; PTW vs. pedestrian; PTW vs. motor-trishaw; and PTW vs. other vehicles and consecutive crashes. The entities are also distinguished into 4 decisional levels: level of road users and street systems; operational level (crash-attended police officers or CAPO and road engineers), tactical level (Regional Traffic Police, Department of Transportation, and Department of Public Work), and strategic level (Traffic Police Headquarters (TCPHI)), parliament, Ministry of Transportation and Ministry of Public Work). These classifications will lead to conceptualization of Problem Situations (P) and Problem Formulations (I) in DAP context. The DAP concerns the sequences process of the incidents until the time the accident occurs, which can be modelled in terms of five activities of procedural rationality: identification on initial human features (IHF), investigation on proponents attributes (PrAT), on Injury Surveillance (IS), on the interaction between IHF and PrAt and IS (intercorrelation), then unravel the sequences of incidents; filtering and disclosure, which include: what needs to activate, modify or change or remove, what is new and what is priority. These can relate to the activation or modification or new establishment of law. The PrAt encompasses the problems of environmental, road infrastructure, road and traffic facilities, and road geometry. The evaluation model (MP) is generated to bridge P and I since MP is produced by the intercorrelations among IHF, PrAT and IS extracted from the PCRs 2012 of Medan. There are 7 findings of incoherences: lack of knowledge and awareness on the traffic regulations and the risks of accidents, especially when riding between 0 < x < 10 km from house, riding between 22 p.m.–05.30 a.m.; lack of engagements on procurement of IHF Data by CAPO; lack of competency of CAPO on data procurement in accident-sites; no intercorrelation among IHF and PrAt and IS in the database systems of PCRs; lack of maintenance and supervision on the availabilities and the capacities of traffic facilities and road infrastructure; instrumental bias with wash-back impacts towards the TCPHI; technical robustness with wash-back impacts towards the CAPO and TCPHI.

Keywords: decision aiding processes, evaluation model, PTW accidents, police crash reports

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Authors: Tugba Altin

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In an era where the impacts of climate change resonate more pronouncedly than ever, communities globally grapple with events bearing both tangible and intangible ramifications. Situating this within the evolving landscapes of Psychological and Behavioral Sciences, this research probes the profound psychological and behavioral responses evoked by such events. The Lytton Creek Fire of 2021 epitomizes these challenges. While tangible destruction is immediate and evident, the intangible repercussions—emotional distress, disintegration of cultural landscapes, and disruptions in place attachment (PA)—require meticulous exploration. PA, emblematic of the emotional and cognitive affiliations individuals nurture with their environments, emerges as a cornerstone for comprehending how environmental cataclysms influence cultural identity and bonds to land. This study, harmonizing the core tenets of an interpretive phenomenological approach with a hermeneutic framework, underscores the pivotal nature of this attachment. It delves deep into the realm of individuals' experiences post the Lytton Creek Fire, unraveling the intricate dynamics of PA amidst such calamity. The study's methodology deviates from conventional paradigms. Instead of traditional interview techniques, it employs walking audio sessions and photo elicitation methods, granting participants the agency to immerse, re-experience, and vocalize their sentiments in real-time. Such techniques shed light on spatial narratives post-trauma and capture the otherwise elusive emotional nuances, offering a visually rich representation of place-based experiences. Central to this research is the voice of the affected populace, whose lived experiences and testimonies form the nucleus of the inquiry. As they renegotiate their bonds with transformed environments, their narratives reveal the indispensable role of cultural landscapes in forging place-based identities. Such revelations accentuate the necessity of integrating both tangible and intangible trauma facets into community recovery strategies, ensuring they resonate more profoundly with affected individuals. Bridging the domains of environmental psychology and behavioral sciences, this research accentuates the intertwined nature of tangible restoration with the imperative of emotional and cultural recuperation post-environmental disasters. It advocates for adaptation initiatives that are rooted in the lived realities of the affected, emphasizing a holistic approach that recognizes the profundity of human connections to landscapes. This research advocates the interdisciplinary exchange of ideas and strategies in addressing post-disaster community recovery strategies. It not only enriches the climate change discourse by emphasizing the human facets of disasters but also reiterates the significance of an interdisciplinary approach, encompassing psychological and behavioral nuances, for fostering a comprehensive understanding of climate-induced traumas. Such a perspective is indispensable for shaping more informed, empathetic, and effective adaptation strategies.

Keywords: place attachment, community recovery, disaster response, restorative landscapes, sensory response, visual methodologies

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