Search results for: neural perception.

Authors: José Antonio Donaire Benito, Konstantina Zerva

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Historically, cities have been places where people from many nations and cultures have met and settled together, while population flows and density have had a significant impact on urban dynamics. Cities' high density of social, cultural, business offerings, everyday services, and other amenities not intended for tourists draw not only tourists but a wide range of city users as well. With the coordination of city rhythms and the porosity of the community, city users order and frame their urban experience. From one side, recent literature focuses on the shift in urban tourist experience from 'having' a holiday through 'doing' activities to 'becoming' a local by experiencing a part of daily life. On the other hand, there is a debate on the 'touristification of everyday life', where middle and upper class urban dwellers display attitudes and behaviors that are virtually undistinguishable from those of visitors. With the advent of globalization and technological advances, modern society has undergone a radical transformation that has altered mobility patterns within it, blurring the boundaries between tourism and everyday life, work and leisure, and "hosts" and "guests". Additionally, the presence of other 'temporary city' users, such as commuters, digital nomads, second home owners, and migrants, contributes to a more complex transformation of tourist cities. Moving away from this traditional clear distinction between 'hosts' and 'guests', which represents a more static view of tourism, and moving towards a more liquid narrative of mobility, academics on tourism development are embracing the New Mobilities Paradigm. The latter moves beyond the static structures of the modern world and focuses on the ways in which social entities are made up of people, machines, information, and images in a moving system. In light of this fluid interdependence between tourists and guests, a question arises as to whether overtourism, which is considered as the underlying cause of citizens' perception of a lower urban quality of life, is a fair representation of perceived mobility excessiveness, place consumption disruptiveness, and residents displacement. As a representative example of an overtourism narrative, Barcelona was chosen as a study area for this purpose, focusing on the incoming city users to reflect in depth the variety of people who contribute to mobility flows beyond those residents already have. Several statistical data have been analyzed to determine the number of national and international visitors to Barcelona at some point during the day in 2019. Specifically, tracking data gathered from mobile phone users within the city are combined with tourist surveys, urban mobility data, zenithal data capture, and information about the city's attractions. The paper shows that tourists are only a small part of the different incoming city users that daily enter Barcelona; excursionists, commuters, and metropolitans also contribute to a high mobility flow. Based on the diversity of incoming city users and their place consumption, it seems that the city's urban experience is more likely to be impacted by over-mobility tan over-tourism.

Keywords: city users, density, new mobilities paradigm, over-tourism.

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Authors: Marina Karaseva

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The beginning of our century became a new digital epoch in the educational situation. Last decade the newest stage of this process had been initialized by the touch-screen mobile devices with program applications for them. The touch possibilities for learning fundamentals of music are of especially importance for music majors. The phenomenon of touching, firstly, makes it realistic to play on the screen as on music instrument, secondly, helps students to learn music theory while listening in its sound elements by music ear. Nowadays we can detect several levels of such mobile applications: from the basic ones devoting to the elementary music training such as intervals and chords recognition, to the more advanced applications which deal with music perception of non-major and minor modes, ethnic timbres, and complicated rhythms. The main purpose of the proposed paper is to disclose the main tendencies in this process and to demonstrate the most innovative features of music theory applications on the base of iOS and Android systems as the most common used. Methodological recommendations how to use these digital material musicologically will be done for the professional music education of different levels. These recommendations are based on more than ten year ‘iTheory’ teaching experience of the author. In this paper, we try to logically classify all types of ‘iTheory’mobile applications into several groups, according to their methodological goals. General concepts given below will be demonstrated in concrete examples. The most numerous group of programs is formed with simulators for studying notes with audio-visual links. There are link-pair types as follows: sound — musical notation which may be used as flashcards for studying words and letters, sound — key, sound — string (basically, guitar’s). The second large group of programs is programs-tests containing a game component. As a rule, their basis is made with exercises on ear identification and reconstruction by voice: sounds and intervals on their sounding — harmonical and melodical, music modes, rhythmic patterns, chords, selected instrumental timbres. Some programs are aimed at an establishment of acoustical communications between concepts of the musical theory and their musical embodiments. There are also programs focused on progress of operative musical memory (with repeating of sounding phrases and their transposing in a new pitch), as well as on perfect pitch training In addition a number of programs improvisation skills have been developed. An absolute pitch-system of solmisation is a common base for mobile programs. However, it is possible to find also the programs focused on the relative pitch system of solfegе. In App Store and Google Play Market online store there are also many free programs-simulators of musical instruments — piano, guitars, celesta, violin, organ. These programs may be effective for individual and group exercises in ear training or composition classes. Great variety and good sound quality of these programs give now a unique opportunity to musicians to master their music abilities in a shorter time. That is why such teaching material may be a way to effective study of music theory.

Keywords: ear training, innovation in music education, music theory, mobile devices

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Authors: D. Norton

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This qualitative study focuses on the lived experience and displacement of young white-collar masculinities in Japan. In recent years, the salaryman lifestyle has undergone significant disruption - increased competition for regular employment, rise in non-regular structurings of labour across public/private sectors, and shifting role expectations within the home. Despite this, related scholarship hints at a continued reinforcement of the traditional male gender role - that the salaryman remains a key benchmark of Japanese masculine identity. For those in structural proximity to these more ‘normative’ performativities, interest lies their engagement with such narratives - how they make sense of their masculinity in response to stated changes. In light of the historical emphasis on labour and breadwinning logics, notions of respective security or precarity generated as a result remain unclear. Similarly, concern extends to developments within the private sphere - by what means young white-collar men construct ideas of singlehood and companionship according to traditional gender ideologies or more contemporary, flexible readings. The influence of these still-emergent status distinctions on the logics of the social group in question is yet to be explored in depth by gender scholars. This project, therefore, focuses on a salaryman archetype as hegemonic - its transformation amidst these changes and socialising mechanisms that continue to legitimate unequal gender hierarchies. For data collection, a series of ethnographic interviews were held over a period of 12 months with university-educated, white-collar male employees from both Osaka and the Greater Tokyo Area. Findings suggest a modern salaryman ideal reflecting both continuities and shifts within white-collar employment. Whilst receptive to more contemporary workplace practices, the narratives of those interviewed remain imbued with logics supporting patterns of internal hegemony. Regular/non-regular distinction emerged as the foremost variable for both material and discursive patterns of white-collar stratification, with variants of displacement for each social group. Despite the heightened valorisation of stable employment, regular workers articulated various concerns over a model of corporate masculinity seen to be incompatible with recent socioeconomic developments. Likewise, non-regular employees face detachment owing to a still-inflexible perception of their working masculinity as marginalized amidst economic precarity. In seeking to negotiate respective challenges, those interviewed demonstrated an engagement with various concurrent social changes that would often either accommodate, reinforce, or expand upon traditional role behaviours. Few of these narratives offered any notable transgression of said ideal, however, suggesting that within the spectre of white-collar employment in Japan for the near future, any substantive transformation of corporate masculinity remains dependant upon economic developments, less so the agency of those involved.

Keywords: gender ideologies, hegemonic masculinity, Japan, white-collar employment

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Authors: Akeel A. Shah, Tong Zhang

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Computational approaches to learning the properties of materials are commonplace, motivated by the need to screen or design materials for a given application, e.g., semiconductors and energy storage. Experimental approaches can be both time consuming and costly. Unfortunately, computational approaches such as ab-initio electronic structure calculations and classical or ab-initio molecular dynamics are themselves can be too slow for the rapid evaluation of materials, often involving thousands to hundreds of thousands of candidates. Machine learning assisted approaches have been developed to overcome the time limitations of purely physics-based approaches. These approaches, on the other hand, require large volumes of data for training (hundreds of thousands on many standard data sets such as QM7b). This means that they are limited by how quickly such a large data set of physics-based simulations can be established. At high fidelity, such as configuration interaction, composite methods such as G4, and coupled cluster theory, gathering such a large data set can become infeasible, which can compromise the accuracy of the predictions - many applications require high accuracy, for example band structures and energy levels in semiconductor materials and the energetics of charge transfer in energy storage materials. In order to circumvent this problem, multi-fidelity approaches can be adopted, for example the Δ-ML method, which learns a high-fidelity output from a low-fidelity result such as Hartree-Fock or density functional theory (DFT). The general strategy is to learn a map between the low and high fidelity outputs, so that the high-fidelity output is obtained a simple sum of the physics-based low-fidelity and correction, Although this requires a low-fidelity calculation, it typically requires far fewer high-fidelity results to learn the correction map, and furthermore, the low-fidelity result, such as Hartree-Fock or semi-empirical ZINDO, is typically quick to obtain, For high-fidelity outputs the result can be an order of magnitude or more in speed up. In this work, a new multi-fidelity approach is developed, based on a graph convolutional network (GCN) combined with semi-supervised learning. The GCN allows for the material or molecule to be represented as a graph, which is known to improve accuracy, for example SchNet and MEGNET. The graph incorporates information regarding the numbers of, types and properties of atoms; the types of bonds; and bond angles. They key to the accuracy in multi-fidelity methods, however, is the incorporation of low-fidelity output to learn the high-fidelity equivalent, in this case by learning their difference. Semi-supervised learning is employed to allow for different numbers of low and high-fidelity training points, by using an additional GCN-based low-fidelity map to predict high fidelity outputs. It is shown on 4 different data sets that a significant (at least one order of magnitude) increase in accuracy is obtained, using one to two orders of magnitude fewer low and high fidelity training points. One of the data sets is developed in this work, pertaining to 1000 simulations of quinone molecules (up to 24 atoms) at 5 different levels of fidelity, furnishing the energy, dipole moment and HOMO/LUMO.

Keywords: .materials screening, computational materials, machine learning, multi-fidelity, graph convolutional network, semi-supervised learning

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Authors: Anna Marie Fisker, Daniele Sepe, Mette Bøgh Jensen, Daniela Rimei

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In the space of just a few years, the European policy framework on cultural heritage has been completely overhauled, moving towards a people-centred and holistic approach, and eliminating the divisions between the tangible, intangible and digital dimensions. The European Union regards cultural heritage as a potential shared resource, highlighting that all stakeholders share responsibility for its transmission to future generations. This new framework will potentially change the way in which cultural institutions manage, protect and provide access to their heritage. It will change the way in which citizens and communities engage with their cultural heritage and naturally influence the way that professionals deal with it. Participating in the creation of cultural heritage awareness can lead to an increased perception of its value, be it economic, social, environmental or cultural. It can also strengthen our personal identity, sense of belonging and community citizenship. Open Atelier, a Creative Europe project, is based on this foundation, with the goal through co-creation to develop the use, understanding and engagement with our cultural heritage. The project aim to transform selected parts of the heritage into an “experience lab” – an interactive, co-creative, dynamic and participatory space, where cultural heritage is the point of departure for new interactions and experiences between the audience and the museum and its professionals. Through a workshop-based approach built on interdisciplinary collaboration and co-creative processes, Open Atelier has started to design, develop, test, and evaluate a set of Experiences. The first collaborative initiative was set out in the discourse and knowledge of a highly creative period in Denmark where a specific group of Scandinavian artists, the Skagen Painters, gathered in the village of Skagen, the northernmost part of Denmark from the late 1870s until the turn of the century. The Art Museums of Skagen have a large collection of photos from the period, that has never been the subject of more thorough research. The photos display a variation of many different subjects: community, family photos, reproductions of art works, costume parties, family gatherings etc., and carry with them the energies of those peoples’ work and life and evoke instances of communication with the past. This paper is about how we in Open Atelier connect these special stories, this legacy, with another place, in another time, in another context and with another audience. The first Open Atelier Experience – the performance “Around the Lighthouse” – was an initiative resulted from the collaboration between AMAT, an Italian creative organisation, and the Art Museums of Skagen. A group of Italian artists developed a co-creative investigation and reinterpretation of a selection of these historical photos. A poetic journey through videos and voices, aimed at exploring new perspectives on the museum and its heritage. An experiment on how to create new ways to actively engage audiences in the way cultural heritage is explored, interpreted, mediated, presented, and used to examine contemporary issues. This article is about this experiment and its findings, and how different views and methodologies can be adopted to discuss the cultural heritage in museums around Europe and their connection to the community.

Keywords: cultural heritage, community, innovation, museums

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Authors: Gyu-Dong Kim, Wuk-Jae Yoo, Sang-Youl Lee

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Composite structures offer numerous advantages over conventional structural systems in the form of higher specific stiffness and strength, lower life-cycle costs, and benefits such as easy installation and improved safety. Recently, there has been a considerable increase in the use of composites in engineering applications and as wraps for seismic upgrading and repairs. However, these composites deteriorate with time because of outdated materials, excessive use, repetitive loading, climatic conditions, manufacturing errors, and deficiencies in inspection methods. In particular, damaged fibers in a composite result in significant degradation of structural performance. In order to reduce the failure probability of composites in service, techniques to assess the condition of the composites to prevent continual growth of fiber damage are required. Condition assessment technology and nondestructive evaluation (NDE) techniques have provided various solutions for the safety of structures by means of detecting damage or defects from static or dynamic responses induced by external loading. A variety of techniques based on detecting the changes in static or dynamic behavior of isotropic structures has been developed in the last two decades. These methods, based on analytical approaches, are limited in their capabilities in dealing with complex systems, primarily because of their limitations in handling different loading and boundary conditions. Recently, investigators have introduced direct search methods based on metaheuristics techniques and artificial intelligence, such as genetic algorithms (GA), simulated annealing (SA) methods, and neural networks (NN), and have promisingly applied these methods to the field of structural identification. Among them, GAs attract our attention because they do not require a considerable amount of data in advance in dealing with complex problems and can make a global solution search possible as opposed to classical gradient-based optimization techniques. In this study, we propose an alternative damage-detection technique that can determine the degraded stiffness distribution of vibrating laminated composites made of Glass Fiber-reinforced Polymer (GFRP). The proposed method uses a modified form of the bivariate Gaussian distribution function to detect degraded stiffness characteristics. In addition, this study presents a method to detect the fiber property variation of laminated composite plates from the micromechanical point of view. The finite element model is used to study free vibrations of laminated composite plates for fiber stiffness degradation. In order to solve the inverse problem using the combined method, this study uses only first mode shapes in a structure for the measured frequency data. In particular, this study focuses on the effect of the interaction among various parameters, such as fiber angles, layup sequences, and damage distributions, on fiber-stiffness damage detection.

Keywords: stiffness detection, fiber damage, genetic algorithm, layup sequences

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Authors: Teresa Naves, Katy Pallas, Carme Florit, Cristina Anton, Joan Collado, Diana Millan

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Although gender-fair language is relatively novel in Spain, in Catalonia, the Department of Education, as well as LGBT Associations, have been promoting several innovative programmes aimed at implementing gender-inclusive schools. These Rainbow School communities are ideal for looking at how these programmes affect the use of gender-fair language and the balanced representation of gender. The students' and teachers' perceptions and attitudes have been compared to those analysed in schools that have never implemented such programmes in primary or secondary education. Spanish and Catalan, unlike English, are gendered languages in which masculine forms have traditionally been used as the unmarked gender and have been claimed to be inclusive of all genders. While the Royal Spanish Academy (RAE) rejects the use of inclusive language and thus deems all variables of inclusion of double gender as unnecessary, the vast majority of universities are promoting not only inclusive language but also gender-inclusive curricula. Adopting gender-fair language policies and including gender perspective in the curricula is an innovative trend at university level and in primary and secondary school education. Inclusion in education is a basic human right and the foundation for a more just and equal society. Educators can facilitate the process of welcoming by ensuring handbooks, forms, and other communications are inclusive of all family structures and gender identities. Using gendered language such as 'girls and boys' can be alienating for gender non-conforming and gender diverse students; on the other hand, non-gendered words like 'students' are regarded as inclusive of all identities. The paper discusses the results of mixed method research (survey, interviews, and experiment) conducted in Rainbow and non-Rainbow schools in Alacant and Barcelona (Spain). The experiment aimed at checking the role of gender-fair language in learners' perception of gender balance. It was conducted in Spanish, Catalan, and English. Students aged 10 to 16 (N > 600) were asked to draw pictures of people using specific prompts. The prompts in Spanish and Catalan were written using the generic masculine, 'los presidentes' 'els presidents' (presidents); using double gendered language such as 'ninos y ninas', 'nens i nenes' (boys and girls); and using non-gendered words like 'alumnado' 'alumnat' (students). The prompts were subdivided into people in school contexts participants could identify with, such as students and teachers; occupations mostly associated with men, such as pilots and firefighters; and occupations associated with women, such as ballet dancers and nurses. As could be expected, the participants only drew approximately the same percentage of female and male characters when double-gendered language or non-gendered words such as 'students' or 'teachers' were used, regardless of the language used in the experiment. When they were asked to draw people using the so-called generic masculine in Spanish or Catalan, 'los estudiantes' 'els estudiants' (students), less than 35% of the drawings contained female characters. The differences between the results for Rainbow and Non-Rainbow schools will be discussed in the light of the innovative coeducation programmes and learners' perceptions on gender-fair language gathered in the surveys and interviews.

Keywords: gender-fair language, gender-inclusive schools, learners’ and teachers’ perceptions and attitudes, rainbow coeducation programmes

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Authors: Hannah Edwards, Femke T. A. Buisman-Pijlman, Adrian Esterman, Craig Phillips, Sandra Orgeig, Andrea Gordon

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Mother-infant bonding is a term which refers to the early emotional connectedness between a mother and her infant. Strong mother-infant bonding promotes higher quality mother and infant interactions including prolonged breastfeeding, secure attachment and increased sensitive parenting and maternal responsiveness. Strengthening of all such interactions leads to improved social behavior, and emotional and cognitive development throughout childhood, adolescence and adulthood. The positive outcomes observed following strong mother-infant bonding emphasize the need to screen new mothers for disrupted mother-infant bonding, and in turn the need for a robust, valid tool to assess mother-infant bonding. A recent scoping review conducted by the research team identified four tools to assess mother-infant bonding, all of which employed self-rating scales. Thus, whilst these tools demonstrated both adequate validity and reliability, they rely on self-reported information from the mother. As such this may reflect a mother’s perception of bonding with their infant, rather than their actual behavior. Therefore, a new tool to assess mother-infant bonding has been developed. The Recorded Interaction Task (RIT) addresses shortcomings of previous tools by employing observational methods to assess bonding. The RIT focusses on the common interaction between mother and infant of changing a nappy, at the target age of 2-6 months, which is visually recorded and then later assessed. Thirteen maternal and seven infant behaviors are scored on the RIT Observation Scoring Sheet, and a final combined score of mother-infant bonding is determined. The aim of the current study was to assess the content validity and inter-rater reliability of the RIT. A panel of six experts with specialized expertise in bonding and infant behavior were consulted. Experts were provided with the RIT Observation Scoring Sheet, a visual recording of a nappy change interaction, and a feedback form. Experts scored the mother and infant interaction on the RIT Observation Scoring Sheet and completed the feedback form which collected their opinions on the validity of each item on the RIT Observation Scoring Sheet and the RIT as a whole. Twelve of the 20 items on the RIT Observation Scoring Sheet were scored ‘Valid’ by all (n=6) or most (n=5) experts. Two items received a ‘Not valid’ score from one expert. The remainder of the items received a mixture of ‘Valid’ and ‘Potentially Valid’ scores. Few changes were made to the RIT Observation Scoring Sheet following expert feedback, including rewording of items for clarity and the exclusion of an item focusing on behavior deemed not relevant for the target infant age. The overall ICC for single rater absolute agreement was 0.48 (95% CI 0.28 – 0.71). Experts (n=6) ratings were less consistent for infant behavior (ICC 0.27 (-0.01 – 0.82)) compared to mother behavior (ICC 0.55 (0.28 – 0.80)). Whilst previous tools employ self-report methods to assess mother-infant bonding, the RIT utilizes observational methods. The current study highlights adequate content validity and moderate inter-rater reliability of the RIT, supporting its use in future research. A convergent validity study comparing the RIT against an existing tool is currently being undertaken to confirm these results.

Keywords: content validity, inter-rater reliability, mother-infant bonding, observational tool, recorded interaction task

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Authors: Zhao Gao, Eran Edirisinghe

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The production of an accurate sketch of a suspect based on a verbal description obtained from a witness is an essential task for most criminal investigations. The criminal investigation system employs specifically trained professional artists to manually draw a facial image of the suspect according to the descriptions of an eyewitness for subsequent identification. Within the advancement of Deep Learning, Recurrent Neural Networks (RNN) have shown great promise in Natural Language Processing (NLP) tasks. Additionally, Generative Adversarial Networks (GAN) have also proven to be very effective in image generation. In this study, a trained GAN conditioned on textual features such as keywords automatically encoded from a verbal description of a human face using an RNN is used to generate photo-realistic facial images for criminal investigations. The intention of the proposed system is to map corresponding features into text generated from verbal descriptions. With this, it becomes possible to generate many reasonably accurate alternatives to which the witness can use to hopefully identify a suspect from. This reduces subjectivity in decision making both by the eyewitness and the artist while giving an opportunity for the witness to evaluate and reconsider decisions. Furthermore, the proposed approach benefits law enforcement agencies by reducing the time taken to physically draw each potential sketch, thus increasing response times and mitigating potentially malicious human intervention. With publically available 'CelebFaces Attributes Dataset' (CelebA) and additionally providing verbal description as training data, the proposed architecture is able to effectively produce facial structures from given text. Word Embeddings are learnt by applying the RNN architecture in order to perform semantic parsing, the output of which is fed into the GAN for synthesizing photo-realistic images. Rather than the grid search method, a metaheuristic search based on genetic algorithms is applied to evolve the network with the intent of achieving optimal hyperparameters in a fraction the time of a typical brute force approach. With the exception of the ‘CelebA’ training database, further novel test cases are supplied to the network for evaluation. Witness reports detailing criminals from Interpol or other law enforcement agencies are sampled on the network. Using the descriptions provided, samples are generated and compared with the ground truth images of a criminal in order to calculate the similarities. Two factors are used for performance evaluation: The Structural Similarity Index (SSIM) and the Peak Signal-to-Noise Ratio (PSNR). A high percentile output from this performance matrix should attribute to demonstrating the accuracy, in hope of proving that the proposed approach can be an effective tool for law enforcement agencies. The proposed approach to criminal facial image generation has potential to increase the ratio of criminal cases that can be ultimately resolved using eyewitness information gathering.

Keywords: RNN, GAN, NLP, facial composition, criminal investigation

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Authors: Jane Oliver, Angeline Ferdinand, Jessica Kaufman, Peta Edler, Nicole Allard, Margie Danchin, Katherine B. Gibney

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Background: The cohealth Health Concierge program operated in Melbourne, Australia, from July 2020 to 30 June 2022. The program was designed to provide place-based peer-to-peer COVID-19 education and support to culturally and linguistically diverse residents of high-rise public housing estates. During this time, the COVID-19 public health response changed frequently. We conducted a mixed-methods evaluation to determine the program’s impact on residents’ trust, engagement and communication with health services and public health activities. Methods: The RE-AIM model was used to assess program reach, effectiveness, adoption, implementation and maintenance and the evaluation was informed by a Project Reference Group including end-users. Data were collected between March and May 2022 in four estates where the program operated. We surveyed 301 residents, conducted qualitative interviews with 32 stakeholders and analyzed data from 20,901 forms reporting interactions between Health Concierges and residents collected from August 2021 to May 2022. These forms outlined the support provided by Health Concierges during each interaction. Results: Overall, the program was effective in guiding residents to testing and vaccination services and facilitating COVID-19 safe practices. Nearly two-thirds (191; 63.5%) of the 301 surveyed participants reported speaking with a Health Concierge in the previous six months, and some described having meaningful conversations with them. Despite this, many of the interactions residents described having with Health Concierges were superficial. When considering surveyed participants’ responses to the adapted Public Health Disaster Trust Scale, the mean score across all estates was 2.3 (or slightly more than ‘somewhat confident’) in public health authorities’ ability to respond to a localized infectious disease outbreak. While the program was valued during the rapidly changing public health response, many felt it had failed to evolve in the ‘living with COVID’ phase. Some residents expressed frustration with Health Concierges’ having perceived inactive, passive roles - although other residents felt Health Concierges were helpful and appreciated them. A perception that the true impact of Health Concierges’ work was underrecognized was widely voiced by health staff. All 20,901 Interaction Forms identified COVID-19-related supports provided to residents; almost all included provision of facemasks and/or hand sanitiser and 78% identified additional supports that were also provided, most frequently provision of other health information. Conclusions: The program disseminated up-to-date information to a diverse population within a rapidly changing public health setting. Health Concierges were able promote COVID-19-safe behaviours, including vaccine uptake, and link residents with support services. We recommend the program be revised and continued. New programs that draw on the Health Concierge model may be valuable in supporting future pandemic responses and should be considered in preparedness planning.

Keywords: community health, COVID-19 pandemic, infectious diseases, public health, community health workers

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Authors: Ola Hall, Ibrahim Wahab, Thorsteinn Rognvaldsson, Mattias Ohlsson

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The subfield of poverty and welfare estimation that applies machine learning tools and methods on satellite imagery is a nascent but rapidly growing one. This is in part driven by the sustainable development goal, whose overarching principle is that no region is left behind. Among other things, this requires that welfare levels can be accurately and rapidly estimated at different spatial scales and resolutions. Conventional tools of household surveys and interviews do not suffice in this regard. While they are useful for gaining a longitudinal understanding of the welfare levels of populations, they do not offer adequate spatial coverage for the accuracy that is needed, nor are their implementation sufficiently swift to gain an accurate insight into people and places. It is this void that satellite imagery fills. Previously, this was near-impossible to implement due to the sheer volume of data that needed processing. Recent advances in machine learning, especially the deep learning subtype, such as deep neural networks, have made this a rapidly growing area of scholarship. Despite their unprecedented levels of performance, such models lack transparency and explainability and thus have seen limited downstream applications as humans generally are apprehensive of techniques that are not inherently interpretable and trustworthy. While several studies have demonstrated the superhuman performance of AI models, none has directly compared the performance of such models and human readers in the domain of poverty studies. In the present study, we directly compare the performance of human readers and a DL model using different resolutions of satellite imagery to estimate the welfare levels of demographic and health survey clusters in Tanzania, using the wealth quintile ratings from the same survey as the ground truth data. The cluster-level imagery covers all 608 cluster locations, of which 428 were classified as rural. The imagery for the human readers was sourced from the Google Maps Platform at an ultra-high resolution of 0.6m per pixel at zoom level 18, while that of the machine learning model was sourced from the comparatively lower resolution Sentinel-2 10m per pixel data for the same cluster locations. Rank correlation coefficients of between 0.31 and 0.32 achieved by the human readers were much lower when compared to those attained by the machine learning model – 0.69-0.79. This superhuman performance by the model is even more significant given that it was trained on the relatively lower 10-meter resolution satellite data while the human readers estimated welfare levels from the higher 0.6m spatial resolution data from which key markers of poverty and slums – roofing and road quality – are discernible. It is important to note, however, that the human readers did not receive any training before ratings, and had this been done, their performance might have improved. The stellar performance of the model also comes with the inevitable shortfall relating to limited transparency and explainability. The findings have significant implications for attaining the objective of the current frontier of deep learning models in this domain of scholarship – eXplainable Artificial Intelligence through a collaborative rather than a comparative framework.

Keywords: poverty prediction, satellite imagery, human readers, machine learning, Tanzania

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Authors: G. Cunningham, E. Cantor, X. Wu, F. Shen, G. Jiang, S. Philips, C. Bales, Y. Xiao, T. R. Cummins, J. C. Fehrenbacher, B. P. Schneider

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Background: Taxane-induced peripheral neuropathy (TIPN) is the most devastating survivorship issue for patients receiving therapy. Dose reductions due to TIPN in the curative setting lead to inferior outcomes for African American patients, as prior research has shown that this group is more susceptible to developing severe neuropathy. The mechanistic underpinnings of TIPN, however, have not been entirely elucidated. While it would be appealing to use primary tissue to study the development of TIPN, procuring nerves from patients is not realistically feasible, as nerve biopsies are painful and may result in permanent damage. Therefore, our laboratory has investigated paclitaxel-induced neuronal morphological and molecular changes using an ex vivo model of human-induced pluripotent stem cell (iPSC)-derived neurons. Methods: iPSCs are undifferentiated and endlessly dividing cells that can be generated from a patient’s somatic cells, such as peripheral blood mononuclear cells (PBMCs). We successfully reprogrammed PBMCs into iPSCs using the Erythroid Progenitor Reprograming Kit (STEMCell Technologiesᵀᴹ); pluripotency was verified by flow cytometry analysis. iPSCs were then induced into neurons using a differentiation protocol that bypasses the neural progenitor stage and uses selected small-molecule modulators of key signaling pathways (SMAD, Notch, FGFR1 inhibition, and Wnt activation). Results: Flow cytometry analysis revealed expression of core pluripotency transcription factors Nanog, Oct3/4 and Sox2 in iPSCs overlaps with commercially purchased pluripotent cell line UCSD064i-20-2. Trilineage differentiation of iPSCs was confirmed with immunofluorescent imaging with germ-layer-specific markers; Sox17 and ExoA2 for ectoderm, Nestin, and Pax6 for mesoderm, and Ncam and Brachyury for endoderm. Sensory neuron markers, β-III tubulin, and Peripherin were applied to stain the cells for the maturity of iPSC-derived neurons. Patch-clamp electrophysiology and calcitonin gene-related peptide (CGRP) release data supported the functionality of the induced neurons and provided insight into the timing for which downstream assays could be performed (week 4 post-induction). We have also performed a cell viability assay and fluorescence-activated cell sorting (FACS) using four cell-surface markers (CD184, CD44, CD15, and CD24) to select a neuronal population. At least 70% of the cells were viable in the isolated neuron population. Conclusion: We have found that these iPSC-derived neurons recapitulate mature neuronal phenotypes and demonstrate functionality. Thus, this represents a patient-derived ex vivo neuronal model to investigate the molecular mechanisms of clinical TIPN.

Keywords: chemotherapy, iPSC-derived neurons, peripheral neuropathy, taxane, paclitaxel

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Authors: Kenneth A. Rostowsky, Alexander S. Maher, Nahian F. Chowdhury, Andrei Irimia

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The clinical significance of cerebral microbleeds (CMBs) due to mild traumatic brain injury (mTBI) remains unclear. Here we use magnetic resonance imaging (MRI), diffusion tensor imaging (DTI) and connectomic analysis to investigate the statistical association between mTBI-related CMBs, post-TBI changes to the human connectome and neurological/cognitive deficits. This study was undertaken in agreement with US federal law (45 CFR 46) and was approved by the Institutional Review Board (IRB) of the University of Southern California (USC). Two groups, one consisting of 26 (13 females) mTBI victims and another comprising 26 (13 females) healthy control (HC) volunteers were recruited through IRB-approved procedures. The acute Glasgow Coma Scale (GCS) score was available for each mTBI victim (mean µ = 13.2; standard deviation σ = 0.4). Each HC volunteer was assigned a GCS of 15 to indicate the absence of head trauma at the time of enrollment in our study. Volunteers in the HC and mTBI groups were matched according to their sex and age (HC: µ = 67.2 years, σ = 5.62 years; mTBI: µ = 66.8 years, σ = 5.93 years). MRI [including T1- and T2-weighted volumes, gradient recalled echo (GRE)/susceptibility weighted imaging (SWI)] and gradient echo (GE) DWI volumes were acquired using the same MRI scanner type (Trio TIM, Siemens Corp.). Skull-stripping and eddy current correction were implemented. DWI volumes were processed in TrackVis (http://trackvis.org) and 3D Slicer (http://www.slicer.org). Tensors were fit to DWI data to perform DTI, and tractography streamlines were then reconstructed using deterministic tractography. A voxel classifier was used to identify image features as CMB candidates using Microbleed Anatomic Rating Scale (MARS) guidelines. For each peri-lesional DTI streamline bundle, the null hypothesis was formulated as the statement that there was no neurological or cognitive deficit associated with between-scan differences in the mean FA of DTI streamlines within each bundle. The statistical significance of each hypothesis test was calculated at the α = 0.05 level, subject to the family-wise error rate (FWER) correction for multiple comparisons. Results: In HC volunteers, the along-track analysis failed to identify statistically significant differences in the mean FA of DTI streamline bundles. In the mTBI group, significant differences in the mean FA of peri-lesional streamline bundles were found in 21 out of 26 volunteers. In those volunteers where significant differences had been found, these differences were associated with an average of ~47% of all identified CMBs (σ = 21%). In 12 out of the 21 volunteers exhibiting significant FA changes, cognitive functions (memory acquisition and retrieval, top-down control of attention, planning, judgment, cognitive aspects of decision-making) were found to have deteriorated over the six months following injury (r = -0.32, p < 0.001). Our preliminary results suggest that acute post-TBI CMBs may be associated with cognitive decline in some mTBI patients. Future research should attempt to identify mTBI patients at high risk for cognitive sequelae.

Keywords: traumatic brain injury, magnetic resonance imaging, diffusion tensor imaging, connectomics

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Authors: Iliana Georganta, Clare Deehan, Marysia Thomson, Miriam McDonald, Kerrie McNulty, Anna Strachan, Elizabeth Anderson, Alyaa Mostafa

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Context: A meta-analysis of randomized controlled trials (RCTs) comparing hysterectomy versus endometrial ablation and resection in the management of heavy menstrual bleeding. Objective: To evaluate the clinical efficacy, satisfaction rates and adverse events of hysterectomy compared to more minimally invasive techniques in the treatment of HMB. Evidence Acquisition: A literature search was performed for all RCTs and quasi-RCTs comparing hysterectomy with either endometrial ablation endometrial resection of both. The search had no language restrictions and was last updated in June 2020 using MEDLINE, EMBASE, Cochrane Central Register of Clinical Trials, PubMed, Google Scholar, PsycINFO, Clinicaltrials.gov and Clinical trials. EU. In addition, a manual search of the abstract databases of the European Haemophilia Conference on women's health was performed and further studies were identified from references of acquired papers. The primary outcomes were patient-reported and objective reduction in heavy menstrual bleeding up to 2 years and after 2 years. Secondary outcomes included satisfaction rates, pain, adverse events short and long term, quality of life and sexual function, further surgery, duration of surgery and hospital stay and time to return to work and normal activities. Data were analysed using RevMan software. Evidence synthesis: 12 studies and a total of 2028 women were included (hysterectomy: n = 977 women vs endometrial ablation or resection: n = 1051 women). Hysterectomy was compared with endometrial ablation only in five studies (Lin, Dickersin, Sesti, Jain, Cooper) and endometrial resection only in five studies (Gannon, Schulpher, O’Connor, Crosignani, Zupi) and a mixture of the Ablation and Resection in two studies (Elmantwe, Pinion). Of the 1² studies, 10 reported women’s perception of bleeding symptoms as improved. Meta-analysis showed that women in the hysterectomy group were more likely to show improvement in bleeding symptoms when compared with endometrial ablation or resection up to 2-year follow-up (RR 0.75, 95% CI 0.71 to 0.79, I² = 95%). Objective outcomes of improvement in bleeding also favored hysterectomy. Patient satisfaction was higher after hysterectomy within the 2 years follow-up (RR: 0.90, 95%CI: 0.86 to 0.94, I²:58%), however, there was no significant difference between the two groups at more than 2 years follow up. Sepsis (RR: 0.03, 95% CI 0.002 to 0.56; 1 study), wound infection (RR: 0.05, 95% CI: 0.01 to 0.28, I²: 0%, 3 studies) and Urinary tract infection (UTI) (RR: 0.20, 95% CI: 0.10 to 0.42, I²: 0%, 4 studies) all favoured hysteroscopic techniques. Fluid overload (RR: 7.80, 95% CI: 2.16 to 28.16, I² :0%, 4 studies) and perforation (RR: 5.42, 95% CI: 1.25 to 23.45, I²: 0%, 4 studies) however favoured hysterectomy in the short term. Conclusions: This meta-analysis has demonstrated that endometrial ablation and endometrial resection are both viable options when compared with hysterectomy for the treatment of heavy menstrual bleeding. Hysteroscopic procedures had better outcomes in the short term with fewer adverse events including wound infection, UTI and sepsis. The hysterectomy performed better when measuring more long-term impacts such as recurrence of symptoms, overall satisfaction at two years and the need for further treatment or surgery.

Keywords: menorrhagia, hysterectomy, ablation, resection

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Authors: E. Loffi Borghese

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In this comprehensive study, we delve into the intricate dynamics of the big tech oligopoly, focusing particularly on Apple as a case study. The core objective is to scrutinize the evolving relationship between a firm's commitment to positive social impact as its primary purpose and its resilience in the face of disruptive innovations within the big tech market. Our exploration begins with a theoretical framework, emphasizing the significance of distinguishing between corporate social responsibility and social impact as a primary purpose. Drawing on insights from Drumwright and Bartkus and Glassman, we underscore the transformative potential when a firm aligns its core business with a social mission, transcending mere side activities. Examining successful firms, such as Apple, we adopt Sinek's perspective on inspirational leadership and the "golden circle." This framework sheds light on why some organizations, like Apple, succeed in making positive social impact their primary purpose. Apple's early-stage life cycle is dissected, revealing a profound commitment to challenging the status quo and promoting simpler alternatives that resonate with its users' lives. The study then navigates through industry life cycles, drawing on Klepper's stages and Christensen's disruptive innovations. Apple's dominance in the big tech oligopoly is contrasted with companies like Harley Davidson and Polaroid, illustrating the consequences of failing to adapt to disruptive innovations. The data and methods employed encompass a qualitative approach, leveraging sources like ECB, Forbes, World in Data, and scientific articles. A secondary data analysis probes Apple's market evolution within the big tech oligopoly, emphasizing the shifts in market context and innovation trends that demand strategic adaptations. The subsequent sections scrutinize Apple's present innovation strategies, highlighting its diversified product portfolio and intensified focus on big data. We examine the implications of these shifts on Apple's capacity to maintain positive social impact as its primary purpose, pondering potential consequences on its brand perception. The study culminates in a reflection on the broader implications of the big tech oligopoly's dominance. It contemplates the diminishing competitiveness in the market and the potential sidelining of positive social impact as a competitive advantage. The expansion of tech firms into diverse sectors raises concerns about negative societal impacts, prompting a call for increased regulatory attention and awareness. In conclusion, this research serves as a catalyst for heightened awareness and discussion on the intricate interplay between firms' social impact goals, disruptive innovations, and the broader societal implications within the evolving landscape of the big tech oligopoly. Despite limitations, this study aims to stimulate further research, urging a conscious and responsible approach to shaping the future economic system.

Keywords: innovation trends, market dynamics, social impact, tech oligopoly

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Authors: Hatem Abou-Senna

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Interstate 4 (I-4) is a primary east-west transportation corridor between Tampa and Daytona cities, serving commuters, commercial and recreational traffic. I-4 is known to have severe recurring congestion during peak hours. The congestion spans about 11 miles in the evening peak period in the central corridor area as it is considered the only non-tolled limited access facility connecting the Orlando Central Business District (CBD) and the tourist attractions area (Walt Disney World). Florida officials had been skeptical of tolling I-4 prior to the recent legislation, and the public through the media had been complaining about the excessive toll facilities in Central Florida. So, in search for plausible mitigation to the congestion on the I-4 corridor, this research is implemented to evaluate the effectiveness of different toll pricing alternatives that might divert traffic from I-4 to the toll facilities during the peak period. The network is composed of two main diverging limited access highways, freeway (I-4) and toll road (SR 417) in addition to two east-west parallel toll roads SR 408 and SR 528, intersecting the above-mentioned highways from both ends. I-4 and toll road SR 408 are the most frequently used route by commuters. SR-417 is a relatively uncongested toll road with 15 miles longer than I-4 and $5 tolls compared to no monetary cost on 1-4 for the same trip. The results of the calibrated Orlando PARAMICS network showed that percentages of route diversion vary from one route to another and depends primarily on the travel cost between specific origin-destination (O-D) pairs. Most drivers going from Disney (O1) or Lake Buena Vista (O2) to Lake Mary (D1) were found to have a high propensity towards using I-4, even when eliminating tolls and/or providing real-time information. However, a diversion from I-4 to SR 417 for these OD pairs occurred only in the cases of the incident and lane closure on I-4, due to the increase in delay and travel costs, and when information is provided to travelers. Furthermore, drivers that diverted from I-4 to SR 417 and SR 528 did not gain significant travel-time savings. This was attributed to the limited extra capacity of the alternative routes in the peak period and the longer traveling distance. When the remaining origin-destination pairs were analyzed, average travel time savings on I-4 ranged between 10 and 16% amounting to 10 minutes at the most with a 10% increase in the network average speed. High propensity of diversion on the network increased significantly when eliminating tolls on SR 417 and SR 528 while doubling the tolls on SR 408 along with the incident and lane closure scenarios on I-4 and with real-time information provided. The toll roads were found to be a viable alternative to I-4 for these specific OD pairs depending on the user perception of the toll cost which was reflected in their specific travel times. However, on the macroscopic level, it was concluded that route diversion through toll reduction or elimination on surrounding toll roads would only have a minimum impact on reducing I-4 congestion during the peak period.

Keywords: congestion pricing, dynamic feedback assignment, microsimulation, paramics, route diversion

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Authors: Amarendar Reddy Addula

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Definition of Artificial Intelligence: Artificial intelligence is the simulation of mortal intelligence processes by machines, especially computer systems. Explicit operations of AI comprise expert systems, natural language processing, and speech recognition, and machine vision. Artificial Intelligence (AI) is an original medium for digital business, according to a new report by Gartner. The last 10 times represent an advance period in AI’s development, prodded by the confluence of factors, including the rise of big data, advancements in cipher structure, new machine literacy ways, the materialization of pall computing, and the vibrant open- source ecosystem. Influence of AI to a broader set of use cases and druggies and its gaining fashionability because it improves AI’s versatility, effectiveness, and rigidity. Edge AI will enable digital moments by employing AI for real- time analytics closer to data sources. Gartner predicts that by 2025, further than 50 of all data analysis by deep neural networks will do at the edge, over from lower than 10 in 2021. Responsible AI is a marquee term for making suitable business and ethical choices when espousing AI. It requires considering business and societal value, threat, trust, translucency, fairness, bias mitigation, explainability, responsibility, safety, sequestration, and nonsupervisory compliance. Responsible AI is ever more significant amidst growing nonsupervisory oversight, consumer prospects, and rising sustainability pretensions. Generative AI is the use of AI to induce new vestiges and produce innovative products. To date, generative AI sweats have concentrated on creating media content similar as photorealistic images of people and effects, but it can also be used for law generation, creating synthetic irregular data, and designing medicinals and accoutrements with specific parcels. AI is the subject of a wide- ranging debate in which there's a growing concern about its ethical and legal aspects. Constantly, the two are varied and nonplussed despite being different issues and areas of knowledge. The ethical debate raises two main problems the first, abstract, relates to the idea and content of ethics; the alternate, functional, and concerns its relationship with the law. Both set up models of social geste, but they're different in compass and nature. The juridical analysis is grounded on anon-formalistic scientific methodology. This means that it's essential to consider the nature and characteristics of the AI as a primary step to the description of its legal paradigm. In this regard, there are two main issues the relationship between artificial and mortal intelligence and the question of the unitary or different nature of the AI. From that theoretical and practical base, the study of the legal system is carried out by examining its foundations, the governance model, and the nonsupervisory bases. According to this analysis, throughout the work and in the conclusions, International Law is linked as the top legal frame for the regulation of AI.

Keywords: artificial intelligence, ethics & human rights issues, laws, international laws

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Authors: Ayse Collins

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The Agenda 2030 puts Higher Education Institutions (HEIs) in the situation where they should emphasize ways to promote sustainability accordingly. However, it is still unclear: a) how sustainability is understood, and b) which actions have been taken in both discourse and practice by HEIs regarding the three pillars of sustainability, society, environment, and economy. There are models of sustainable universities developed by different authors from different countries; For Example, The Global Reporting Initiative (GRI) methodology which offers a variety of indicators to diagnose performance. However, these models have never been developed for universities in particular. Any model, in this sense, cannot be completed adequately without defining the appropriate tools to measure, analyze and control the performance of initiatives. There is a need to conduct researches in different universities from different countries to understand where we stand in terms of sustainable higher education. Therefore, this study aims at exploring the actions taken by a university in Ankara, Turkey, since Agenda 2030 should consider localizing its objectives and targets according to a certain geography. This university just announced 2021-2022 as “Sustainability Year.” Therefore, this research is a multi-methodology longitudinal study and uses the theoretical framework of the organization and transition management (TM). It is designed to examine the activities as being strategic, tactical, operational, and reflexive in nature and covers the six main aspects: academic community, administrative staff, operations and services, teaching, research, and extension. The preliminary research will answer the role of the top university governance, perception of the stakeholders (students, instructors, administrative and support staff) regarding sustainability, and the level of achievement at the mid-evaluation and final, end of year evaluation. TM Theory is a multi-scale, multi-actor, process-oriented approach with the analytical framework to explore and promote change in social systems. Therefore, the stages and respective methodology for collecting data in this research is: Pre-development Stage: a) semi-structured interviews with university governance, c) open-ended survey with faculty, students, and administrative staff d) Semi-structured interviews with support staff, and e) analysis of current secondary data for sustainability. Take-off Stage: a) semi-structured interviews with university governance, faculty, students, administrative and support staff, b) analysis of secondary data. Breakthrough stabilization a) survey with all stakeholders at the university, b) secondary data analysis by using selected indicators for the first sustainability report for universities The findings from the predevelopment stage highlight how stakeholders, coming from different faculties, different disciplines with different identities and characteristics, face the sustainability challenge differently. Though similar sustainable development goals ((social, environmental, and economic) are set in the institution, there are differences across disciplines and among different stakeholders, which need to be considered to reach the optimum goal. It is believed that the results will help changes in HEIs organizational culture to embed sustainability values in their strategic planning, academic and managerial work by putting enough time and resources to be successful in coping with sustainability.

Keywords: higher education, sustainability, sustainability auditing, transition management

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Authors: Nitza Davidovitch, Yael Yossel-Eisenbach

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The purpose of the study was to inquire whether there was a change in the shaping of undergraduate students’ digitally-oriented study pattern in the pre-Covid (2016-2017) versus post-Covid period (2022-2023), as affected by three factors: social background characteristics, high school, and academic background characteristics. These two-time points were cauterized by dramatic changes in teaching and learning at institutions of higher education. The data were collected via cross-sectional surveys at two-time points, in the 2016-2017 academic school year (N=443) and in the 2022-2023 school year (N=326). The questionnaire was distributed on social media and it includes questions on demographic background characteristics, previous studies in high school and present academic studies, and questions on learning and reading habits. Method of analysis: A. Statistical descriptive analysis, B. Mean comparison tests were conducted to analyze the variations in the mean score for the digitally-oriented learning pattern variable at two-time points (pre- and post-Covid) in relation to each of the independent variables. C. Analysis of variance was performed to test the main effects and the interactions. D. Applying linear regression, the research aimed to examine the combined effect of the independent variables on shaping students' digitally-oriented learning habits. The analysis includes four models. In all four models, the dependent variable is students’ perception of digitally oriented learning. The first model included social background variables; the second model included scholastic background as well. In the third model, the academic background variables were added, and the fourth model includes all the independent variables together with the variable of period (pre- and post-COVID). E. Factor analysis confirms using the principal component method with varimax rotation; the variables were constructed by a weighted mean of all the relevant statements merged to form a single variable denoting a shared content world. The research findings indicate a significant rise in students’ perceptions of digitally-oriented learning in the post-COVID period. From a gender perspective, the impact of COVID on shaping a digital learning pattern was much more significant for female students. The socioeconomic status perspective is eliminated when controlling for the period, and the student’s job is affected - more than all other variables. It may be assumed that the student’s work pattern mediates effects related to the convenience offered by digital learning regarding distance and time. The significant effect of scholastic background on shaping students’ digital learning patterns remained stable, even when controlling for all explanatory variables. The advantage that universities had over colleges in shaping a digital learning pattern in the pre-COVID period dissipated. Therefore, it can be said that after COVID, there was a change in how colleges shape students’ digital learning patterns in such a way that no institutional differences are evident with regard to shaping the digital learning pattern. The study shows that period has a significant independent effect on shaping students’ digital learning patterns when controlling for the explanatory variables.

Keywords: learning pattern, COVID, socioeconomic status, digital learning

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Authors: Javad Jozaei, Rob G. Bell, Paula Blackett, Scott A. Stephens

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In the last few decades, Social Vulnerability Assessment (SVA) has been a favoured means in evaluating the susceptibility of social systems to drivers of change, including climate change and natural disasters. However, the application of SVA to inform responsive and practical strategies to deal with uncertain climate change impacts has always been challenging, and typically agencies resort back to conventional risk/vulnerability assessment. These challenges include complex nature of social vulnerability concepts which influence its applicability, complications in identifying and measuring social vulnerability determinants, the transitory social dynamics in a changing environment, and unpredictability of the scenarios of change that impacts the regime of vulnerability (including contention of when these impacts might emerge). Research suggests that the conventional quantitative approaches in SVA could not appropriately address these problems; hence, the outcomes could potentially be misleading and not fit for addressing the ongoing uncertain rise in risk. The second phase of New Zealand’s Resilience to Nature’s Challenges (RNC2) is developing a forward-looking vulnerability assessment framework and methodology that informs the decision-making and policy development in dealing with the changing coastal systems and accounts for complex dynamics of New Zealand’s coastal systems (including socio-economic, environmental and cultural). Also, RNC2 requires the new methodology to consider plausible drivers of incremental and unknowable changes, create mechanisms to enhance social and community resilience; and fits the New Zealand’s multi-layer governance system. This paper aims to analyse the conventional approaches and methodologies in SVA and offer recommendations for more responsive approaches that inform adaptive decision-making and policy development in practice. The research adopts a qualitative research design to examine different aspects of the conventional SVA processes, and the methods to achieve the research objectives include a systematic review of the literature and case study methods. We found that the conventional quantitative, reductionist and deterministic mindset in the SVA processes -with a focus the impacts of rapid stressors (i.e. tsunamis, floods)- show some deficiencies to account for complex dynamics of social-ecological systems (SES), and the uncertain, long-term impacts of incremental drivers. The paper will focus on addressing the links between resilience and vulnerability; and suggests how resilience theory and its underpinning notions such as the adaptive cycle, panarchy, and system transformability could address these issues, therefore, influence the perception of vulnerability regime and its assessment processes. In this regard, it will be argued that how a shift of paradigm from ‘specific resilience’, which focuses on adaptive capacity associated with the notion of ‘bouncing back’, to ‘general resilience’, which accounts for system transformability, regime shift, ‘bouncing forward’, can deliver more effective strategies in an era characterised by ongoing change and deep uncertainty.

Keywords: complexity, social vulnerability, resilience, transformation, uncertain risks

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Authors: Mohanad Elemary, Imose Itua, Rajeswari B. Matam

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Virologists and public health experts have been predicting potential pandemics from coronaviruses for decades. The viruses which caused the SARS and MERS pandemics and the Nipah virus led to many lost lives, but still, the COVID-19 pandemic caused by the SARS-CoV2 virus surprised many scientific communities, experts, and governments with its ease of transmission and its pathogenicity. Governments of various countries reacted by locking down entire populations to their homes to combat the devastation caused by the virus, which led to a loss of livelihood and economic hardship to many individuals and organizations. To revive national economies and support their citizens in resuming their lives, governments focused on the development and use of contact tracing apps as a digital way to track and trace exposure. Google and Apple introduced the Exposure Notification Systems (ENS) framework. Independent organizations and countries also developed different frameworks for contact tracing apps. The efficiency, popularity, and adoption rate of these various apps have been different across countries. In this paper, we present a critical analysis of the different contact tracing apps with respect to their efficiency, adoption rate and general perception, and the governmental strategies and policies, which led to the development of the applications. When it comes to the European countries, each of them followed an individualistic approach to the same problem resulting in different realizations of a similarly functioning application with differing results of use and acceptance. The study conducted an extensive review of existing literature, policies, and reports across multiple disciplines, from which a framework was developed and then validated through interviews with six key stakeholders in the field, including founders and executives in digital health startups and corporates as well as experts from international organizations like The World Health Organization. A framework of best practices and tactics is the result of this research. The framework looks at three main questions regarding the contact tracing apps; how to develop them, how to deploy them, and how to regulate them. The findings are based on the best practices applied by governments across multiple countries, the mistakes they made, and the best practices applied in similar situations in the business world. The findings include multiple strategies when it comes to the development milestone regarding establishing frameworks for cooperation with the private sector and how to design the features and user experience of the app for a transparent, effective, and rapidly adaptable app. For the deployment section, several tactics were discussed regarding communication messages, marketing campaigns, persuasive psychology, and the initial deployment scale strategies. The paper also discusses the data privacy dilemma and how to build for a more sustainable system of health-related data processing and utilization. This is done through principles-based regulations specific for health data to allow for its avail for the public good. This framework offers insights into strategies and tactics that could be implemented as protocols for future public health crises and emergencies whether global or regional.

Keywords: contact tracing apps, COVID-19, digital health applications, exposure notification system

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Authors: S. B. R. Slagmulder

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Monitoring inspiratory effort and dynamic lung stress in patients on pressure support ventilation in the ICU is important for protecting against self inflicted lung injury (P-SILI) and diaphragm dysfunction. Strategies to address the detrimental effects of respiratory drive and effort can lead to improved patient outcomes. Two non-invasive estimation methods, occlusion pressure (Pocc) and P0.1, have been proposed for achieving lung and diaphragm protective ventilation. However, their relationship and interpretation in neuro ICU patients is not well understood. P0.1 is the airway pressure measured during a 100-millisecond occlusion of the inspiratory port. It reflects the neural drive from the respiratory centers to the diaphragm and respiratory muscles, indicating the patient's respiratory drive during the initiation of each breath. Occlusion pressure, measured during a brief inspiratory pause against a closed airway, provides information about the inspiratory muscles' strength and the system's total resistance and compliance. Research Objective: Understanding the relationship between Pocc and P0.1 in brain-injured patients can provide insights into the interpretation of these values in pressure support ventilation. This knowledge can contribute to determining extubation readiness and optimizing ventilation strategies to improve patient outcomes. The central goal is to asses a study protocol for determining the relationship between Pocc and P0.1 in brain-injured patients on pressure support ventilation and their ability to predict successful extubation. Additionally, comparing these values between brain-damaged and non-brain-damaged patients may provide valuable insights. Key Areas of Inquiry: 1. How do Pocc and P0.1 values correlate within brain injury patients undergoing pressure support ventilation? 2. To what extent can Pocc and P0.1 values serve as predictive indicators for successful extubation in patients with brain injuries? 3. What differentiates the Pocc and P0.1 values between patients with brain injuries and those without? Methodology: P0.1 and occlusion pressures are standard measurements for pressure support ventilation patients, taken by attending doctors as per protocol. We utilize electronic patient records for existing data. Unpaired T-test will be conducted to compare P0.1 and Pocc values between both study groups. Associations between P0.1 and Pocc and other study variables, such as extubation, will be explored with simple regression and correlation analysis. Depending on how the data evolve, subgroup analysis will be performed for patients with and without extubation failure. Results: While it is anticipated that neuro patients may exhibit high respiratory drive, the linkage between such elevation, quantified by P0.1, and successful extubation remains unknown The analysis will focus on determining the ability of these values to predict successful extubation and their potential impact on ventilation strategies. Conclusion: Further research is pending to fully understand the potential of these indices and their impact on mechanical ventilation in different patient populations and clinical scenarios. Understanding these relationships can aid in determining extubation readiness and tailoring ventilation strategies to improve patient outcomes in this specific patient population. Additionally, it is vital to account for the influence of sedatives, neurological scores, and BMI on respiratory drive and occlusion pressures to ensure a comprehensive analysis.

Keywords: brain damage, diaphragm dysfunction, occlusion pressure, p0.1, respiratory drive

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Authors: Margherita Tufarelli, Leonardo Giliberti, Elena Pucci

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The fashion industry's interest in virtuality is linked, on the one hand, to the emotional and immersive possibilities of digital resources and the resulting languages and, on the other, to the greater efficiency that can be achieved throughout the value chain. The interaction between digital innovation and deep-rooted manufacturing traditions today translates into a paradigm shift for the entire fashion industry where, for example, the traditional values of industrial secrecy and know-how give way to experimentation in an open as well as participatory way, and the complete emancipation of virtual reality from actual 'reality'. The contribution aims to investigate the theme of digitisation in the Italian fashion industry, analysing its opportunities and the criticalities that have hindered its diffusion. There are two reasons why the most common approach in the fashion sector is still analogue: (i) the fashion product lives in close contact with the human body, so the sensory perception of materials plays a central role in both the use and the design of the product, but current technology is not able to restore the sense of touch; (ii) volumes are obtained by stitching flat surfaces that once assembled, given the flexibility of the material, can assume almost infinite configurations. Managing the fit and styling of virtual garments involves a wide range of factors, including mechanical simulation, collision detection, and user interface techniques for garment creation. After briefly reviewing some of the salient historical milestones in the resolution of problems related to the digital simulation of deformable materials and the user interface for the procedures for the realisation of the clothing system, the paper will describe the operation and possibilities offered today by the latest generation of specialised software. Parametric avatars and digital sartorial approach; drawing tools optimised for pattern making; materials both from the point of view of simulated physical behaviour and of aesthetic performance, tools for checking wearability, renderings, but also tools and procedures useful to companies both for dialogue with prototyping software and machinery and for managing the archive and the variants to be made. The article demonstrates how developments in technology and digital procedures now make it possible to intervene in different stages of design in the fashion industry. An integrated and additive process in which the constructed 3D models are usable both in the prototyping and communication of physical products and in the possible exclusively digital uses of 3D models in the new generation of virtual spaces. Mastering such tools requires the acquisition of specific digital skills and, at the same time, traditional skills for the design of the clothing system, but the benefits are manifold and applicable to different business dimensions. We are only at the beginning of the global digital transformation: the emergence of new professional figures and design dynamics leaves room for imagination, but in addition to applying digital tools to traditional procedures, traditional fashion know-how needs to be transferred into emerging digital practices to ensure the continuity of the technical-cultural heritage beyond the transformation.

Keywords: digital fashion, digital technology and couture, digital fashion communication, 3D garment simulation

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Authors: Niklas Ravn-Boess, Nainita Bhowmick, Takamitsu Hattori, Shohei Koide, Christopher Park, Dimitris Placantonakis

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Background: Glioblastoma (GBM) is the most common and deadly primary brain malignancy in adults. Tumor propagation, brain invasion, and resistance to therapy critically depend on GBM stem-like cells (GSCs); however, the mechanisms that regulate GSC self-renewal are incompletely understood. Given the aggressiveness and poor prognosis of GBM, it is imperative to find biomarkers that could also translate into novel drug targets. Along these lines, we have identified a cell surface antigen, CD97 (ADGRE5), an adhesion G protein-coupled receptor (GPCR), that is expressed on GBM cells but is absent from non-neoplastic brain tissue. CD97 has been shown to promote invasiveness, angiogenesis, and migration in several human cancers, but its frequency of expression and functional role in regulating GBM growth and survival, and its potential as a therapeutic target has not been investigated. Design: We assessed CD97 mRNA and protein expression in patient derived GBM samples and cell lines using publicly available RNA-sequencing datasets and flow cytometry, respectively. To assess CD97 function, we generated shRNA lentiviral constructs that target a sequence in the CD97 extracellular domain (ECD). A scrambled shRNA (scr) with no predicted targets in the genome was used as a control. We evaluated CD97 shRNA lentivirally transduced GBM cells for Ki67, Annexin V, and DAPI. We also tested CD97 KD cells for their ability to self-renew using clonogenic tumorsphere formation assays. Further, we utilized synthetic Abs (sAbs) generated against the ECD of CD97 to test for potential antitumor effects using patient-derived GBM cell lines. Results: CD97 mRNA expression was expressed at high levels in all GBM samples available in the TCGA cohort. We found high levels of surface CD97 protein expression in 6/6 patient-derived GBM cell cultures, but not human neural stem cells. Flow cytometry confirmed downregulation of CD97 in CD97 shRNA lentivirally transduced cells. CD97 KD induced a significant reduction in cell growth in 3 independent GBM cell lines representing mesenchymal and proneural subtypes, which was accompanied by reduced (~20%) Ki67 staining and increased (~30%) apoptosis. Incubation of GBM cells with sAbs (20 ug/ ml) against the ECD of CD97 for 3 days induced GSC differentiation, as determined by the expression of GFAP and Tubulin. Using three unique GBM patient derived cultures, we found that CD97 KD attenuated the ability of GBM cells to initiate sphere formation by over 300 fold, consistent with an impairment in GSC self-renewal. Conclusion: Loss of CD97 expression in patient-derived GBM cells markedly decreases proliferation, induces cell death, and reduces tumorsphere formation. sAbs against the ECD of CD97 reduce tumorsphere formation, recapitulating the phenotype of CD97 KD, suggesting that sAbs that inhibit CD97 function exhibit anti-tumor activity. Collectively, these findings indicate that CD97 is necessary for the proliferation and survival of human GBM cells and identify CD97 as a promising therapeutically targetable vulnerability in GBM.

Keywords: adhesion GPCR, CD97, GBM stem cell, glioblastoma

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Authors: Ganesh V., Asit Kumar Khanra

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An in-situ powder metallurgy technique was employed to create Ni-Al3Ni/Al3Ni2 core-shell-shaped aluminum-based intermetallic reinforced composites. The impact of Ni addition on the phase composition, microstructure, and mechanical characteristics of the Al-4Cu-xNi (x = 0, 2, 4, 6, 8, 10 wt.%) in relation to various sintering temperatures was investigated. Microstructure evolution was extensively examined using X-ray diffraction (XRD), scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDX), and transmission electron microscopy (TEM) techniques. Initially, under sintering conditions, the formation of "Single Core-Shell" structures was observed, consisting of Ni as the core with Al3Ni2 intermetallic, whereas samples sintered at 620°C exhibited both "Single Core-Shell" and "Double Core-Shell" structures containing Al3Ni2 and Al3Ni intermetallics formed between the Al matrix and Ni reinforcements. The composite achieved a high compressive yield strength of 198.13 MPa and ultimate strength of 410.68 MPa, with 24% total elongation for the sample containing 10 wt.% Ni. Additionally, there was a substantial increase in hardness, reaching 124.21 HV, which is 2.4 times higher than that of the base aluminum. Nanoindentation studies showed hardness values of 1.54, 4.65, 21.01, 13.16, 5.52, 6.27, and 8.39GPa corresponding to α-Al matrix, Ni, Al3Ni2, Ni and Al3Ni2 interface, Al3Ni, and their respective interfaces. Even at 200°C, it retained 54% of its room temperature strength (90.51 MPa). To investigate the deformation behavior of the composite material, experiments were conducted at deformation temperatures ranging from 300°C to 500°C, with strain rates varying from 0.0001s-1 to 0.1s-1. A sine-hyperbolic constitutive equation was developed to characterize the flow stress of the composite, which exhibited a significantly higher hot deformation activation energy of 231.44 kJ/mol compared to the self-diffusion of pure aluminum. The formation of Al2Cu intermetallics at grain boundaries and Al3Ni2/Al3Ni within the matrix hindered dislocation movement, leading to an increase in activation energy, which might have an adverse effect on high-temperature applications. Two models, the Strain-compensated Arrhenius model and the Artificial Neural Network (ANN) model, were developed to predict the composite's flow behavior. The ANN model outperformed the Strain-compensated Arrhenius model with a lower average absolute relative error of 2.266%, a smaller root means square error of 1.2488 MPa, and a higher correlation coefficient of 0.9997. Processing maps revealed that the optimal hot working conditions for the composite were in the temperature range of 420-500°C and strain rates between 0.0001s-1 and 0.001s-1. The changes in the composite microstructure were successfully correlated with the theory of processing maps, considering temperature and strain rate conditions. The uneven distribution in the shape and size of Core-shell/Al3Ni intermetallic compounds influenced the flow stress curves, leading to Dynamic Recrystallization (DRX), followed by partial Dynamic Recovery (DRV), and ultimately strain hardening. This composite material shows promise for applications in the automobile and aerospace industries.

Keywords: core-shell structure, hot deformation, intermetallic compounds, powder metallurgy

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Authors: Tracy L. F. Worley

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This presentation explores the environment that has limited leadership opportunities for Black women in cinema and advocates for autonomy among Black women filmmakers that is facilitated by strong internal and external networks and cooperative opportunities. Early images of African Americans in motion pictures were often conceptualized from the viewpoint of a White male director and depicted by White actors. The black film evolved in opposition to this context, leading to a Black film aesthetic. The oppositional context created in response to racist, misogynistic, and sexist representations in motion pictures sets the tone for female filmmakers of every hue – but especially for African American women. For them, the context of a male gaze, and for all intents and purposes, a White male gaze, forces them to create their own aesthetic. Theoretically, men and women, filmmakers and spectators have different perspectives across race, ethnicity, and gender. Two feminist theorists, bell hooks and Mary Ann Doane, suggest that female filmmakers are perceived as disparate from male filmmakers and that women, in general, are defined by what men see. Mary Ann Doane, a White feminist film theorist, has focused extensively on female spectatorship and women (White) in general as the object of the male gaze. Her discussion of the female body, male perception of it, and feminism in the motion picture industry support the suggestion that comprehending the organization and composition of Hollywood is critical to understanding women’s roles in the industry. Although much of her research addresses the silent film era and women’s roles then, Doane suggests that across cinematic periods, the theory assigned to “cinematic apparatus” is formulated within a context of sexuality. Men and women are viewed and treated differently in cinema (in front of and behind the camera), with women’s attractiveness and allure photographed specifically for the benefit of the “spectatorial desire” of the male gaze. Bell Hooks, an African American feminist writer and theorist with more than 30 published books and articles on race, gender, class, and culture in feminism and education, suggests that women can overcome the male gaze by using their “oppositional gaze” to transform reality and establish their own truth. She addresses gender within the context of race by acknowledging the realities faced by African American women and the fact that the feminist movement was never intended to include Black women. A grounded theory study led to the development of a leadership theory that explains why African American women are disproportionately represented in a mainstream motion picture leadership. The study helped to reveal the barriers to entry and illuminated potential strategies that African American female motion picture directors might pursue to reduce this inequity. Using semi-structured interviews as the primary means for data collection, the lived experiences of African American female directors and organizational leadership’s perceived role in the perpetuation of negative female imagery in major motion pictures led to the identification of support strategies for African American female motion picture directors that counter social stereotyping and validate the need for social networking in the mainstream.

Keywords: African American, cinema, directors, filmmaking, leadership, women

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Authors: Nancy A. Delich, Stephen D. Roberts

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This case study explores using self-efficacy theory in counseling deaf and hard of hearing students in one California school district. Self-efficacy is described as the confidence a student has for performing a set of skills required to succeed at a specific task. When students need to learn a skill, self-efficacy can be a major factor in influencing behavioral change. Self-efficacy is domain specific, meaning that students can have high confidence in their abilities to accomplish a task in one domain, while at the same time having low confidence in their abilities to accomplish another task in a different domain. The communication isolation experienced by deaf and hard of hearing children and adolescents can negatively impact their belief about their ability to navigate life challenges. There is a need to address issues that impact deaf and hard of hearing students’ social-emotional development. Failure to address these needs may result in depression, suicidal ideation, and anxiety among other mental health concerns. Self-efficacy training can be used to address these socio-emotional developmental issues with this population. Four sources of experiences are applied during an intervention: (a) enactive mastery experience, (b) vicarious experience, (c) verbal persuasion, and (d) physiological and affective states. This case study describes the use of self-efficacy training with a coed group of 12 deaf and hard of hearing high school students who experienced bullying at school. Beginning with enactive mastery experience, the counselor introduced the topic of bullying to the group. The counselor educated the students about the different types of bullying while teaching them the terminology, signs and their meanings. The most effective way to increase self-efficacy is through extensive practice. To better understand these concepts, the students practiced through role-playing with the goal of developing self-advocacy skills. Vicarious experience is the perception that students have about their capabilities. Viewing other students advocating for themselves, cognitively rehearsing what actions they will and will not take, and teaching each other how to stand up against bullying can strengthen their belief in successfully overcoming bullying. The third source of self-efficacy beliefs is verbal persuasion. It occurs when others express belief in the capabilities of the student. Didactic training and pedagogic materials on bullying were employed as part of the group counseling sessions. The fourth source of self-efficacy appraisals is physiological and affective states. Students expect positive emotions to be associated with successful skilled performance. When students practice new skills, the counselor can apply several strategies to enhance self-efficacy while reducing and controlling emotional and physical states. The intervention plan incorporated all four sources of self-efficacy training during several interactive group sessions regarding bullying. There was an increased understanding around the issues of bullying, resulting in the students’ belief of their ability to perform protective behaviors and deter future occurrences. The outcome of the intervention plan resulted in a reduction of reported bullying incidents. In conclusion, self-efficacy training can be an effective counseling and teaching strategy in addressing and enhancing the social-emotional functioning with deaf and hard of hearing adolescents.

Keywords: counseling, self-efficacy, bullying, social-emotional development, mental health, deaf and hard of hearing students

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Authors: Sofia Dokuka, Liz Lockhart, Alex Furman

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Organizational hierarchy, traditionally composed of individual contributors, middle management, and executives, is enhanced by the understanding of informal social roles. These roles, identified with organizational network analysis (ONA), might have an important effect on organizational functioning. In this paper, we identify three social roles – influencers, bridges, and soloists, and provide empirical analysis based on real-world organizational networks. Influencers are employees with broad networks and whose contacts also have rich networks. Influence is calculated using PageRank, initially proposed for measuring website importance, but now applied in various network settings, including social networks. Influencers, having high PageRank, become key players in shaping opinions and behaviors within an organization. Bridges serve as links between loosely connected groups within the organization. Bridges are identified using betweenness and Burt’s constraint. Betweenness quantifies a node's control over information flows by evaluating its role in the control over the shortest paths within the network. Burt's constraint measures the extent of interconnection among an individual's contacts. A high constraint value suggests fewer structural holes and lesser control over information flows, whereas a low value suggests the contrary. Soloists are individuals with fewer than 5 stable social contacts, potentially facing challenges due to reduced social interaction and hypothetical lack of feedback and communication. We considered social roles in the analysis of real-world organizations (N=1,060). Based on data from digital traces (Slack, corporate email and calendar) we reconstructed an organizational communication network and identified influencers, bridges and soloists. We also collected employee engagement data through an online survey. Among the top-5% of influencers, 10% are members of the Executive Team. 56% of the Executive Team members are part of the top influencers group. The same proportion of top influencers (10%) is individual contributors, accounting for just 0.6% of all individual contributors in the company. The majority of influencers (80%) are at the middle management level. Out of all middle managers, 19% hold the role of influencers. However, individual contributors represent a small proportion of influencers, and having information about these individuals who hold influential roles can be crucial for management in identifying high-potential talents. Among the bridges, 4% are members of the Executive Team, 16% are individual contributors, and 80% are middle management. Predominantly middle management acts as a bridge. Bridge positions of some members of the executive team might indicate potential micromanagement on the leader's part. Recognizing the individuals serving as bridges in an organization uncovers potential communication problems. The majority of soloists are individual contributors (96%), and 4% of soloists are from middle management. These managers might face communication difficulties. We found an association between being an influencer and attitude toward a company's direction. There is a statistically significant 20% higher perception that the company is headed in the right direction among influencers compared to non-influencers (p < 0.05, Mann-Whitney test). Taken together, we demonstrate that considering social roles in the company might indicate both positive and negative aspects of organizational functioning that should be considered in data-driven decision-making.

Keywords: organizational network analysis, social roles, influencer, bridge, soloist

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Authors: Irina Deputat, Anatoly Gribanov, Yuliya Dzhos, Alexandra Nekhoroshkova, Tatyana Yemelianova, Irina Bolshevidtseva, Irina Deryabina, Yana Kereush, Larisa Startseva, Tatyana Bagretsova, Irina Ikonnikova

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In the modern world the number of elderly people increases. Preservation of functionality of an organism in the elderly becomes very important now. During aging the higher cortical functions such as feelings, perception, attention, memory, and ideation are gradual decrease. It is expressed in the rate of information processing reduction, volume of random access memory loss, ability to training and storing of new information decrease. Perspective directions in studying of aging neurophysiological parameters are brain imaging: computer electroencephalography, neuroenergy mapping of a brain, and also methods of studying of a neurodynamic brain processes. Research aim – to study features of a brain aging in elderly people by electroencephalogram (EEG) and the DC-potential level. We examined 130 people aged 55 - 74 years that did not have psychiatric disorders and chronic states in a decompensation stage. EEG was recorded with a 128-channel GES-300 system (USA). EEG recordings are collected while the participant sits at rest with their eyes closed for 3 minutes. For a quantitative assessment of EEG we used the spectral analysis. The range was analyzed on delta (0,5–3,5 Hz), a theta - (3,5–7,0 Hz), an alpha 1-(7,0–11,0 Hz) an alpha 2-(11–13,0 Hz), beta1-(13–16,5 Hz) and beta2-(16,5–20 Hz) ranges. In each frequency range spectral power was estimated. The 12-channel hardware-software diagnostic ‘Neuroenergometr-KM’ complex was applied for registration, processing and the analysis of a brain constant potentials level. The DC-potential level registered in monopolar leads. It is revealed that the EEG of elderly people differ in higher rates of spectral power in the range delta (р < 0,01) and a theta - (р < 0,05) rhythms, especially in frontal areas in aging. By results of the comparative analysis it is noted that elderly people 60-64 aged differ in higher values of spectral power alfa-2 range in the left frontal and central areas (р < 0,05) and also higher values beta-1 range in frontal and parieto-occipital areas (р < 0,05). Study of a brain constant potential level distribution revealed increase of total energy consumption on the main areas of a brain. In frontal leads we registered the lowest values of constant potential level. Perhaps it indicates decrease in an energy metabolism in this area and difficulties of executive functions. The comparative analysis of a potential difference on the main assignments testifies to unevenness of a lateralization of a brain functions at elderly people. The results of a potential difference between right and left hemispheres testify to prevalence of the left hemisphere activity. Thus, higher rates of functional activity of a cerebral cortex are peculiar to people of early advanced age (60-64 years) that points to higher reserve opportunities of central nervous system. By 70 years there are age changes of a cerebral power exchange and level of electrogenesis of a brain which reflect deterioration of a condition of homeostatic mechanisms of self-control and the program of processing of the perceptual data current flow.

Keywords: brain, DC-potential level, EEG, elderly people

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Authors: Mayank Gupta, Siba Prasad Samal, Vasu Kakkirala

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The internet world and its priorities have changed considerably in the last decade. Browsing on smart phones has increased manifold and is set to explode much more. Users spent considerable time browsing different websites, that gives a great deal of insight into user’s preferences. Instead of plain information classifying different aspects of browsing like Bookmarks, History, and Download Manager into useful categories would improve and enhance the user’s experience. Most of the classification solutions are server side that involves maintaining server and other heavy resources. It has security constraints and maybe misses on contextual data during classification. On device, classification solves many such problems, but the challenge is to achieve accuracy on classification with resource constraints. This on device classification can be much more useful in personalization, reducing dependency on cloud connectivity and better privacy/security. This approach provides more relevant results as compared to current standalone solutions because it uses content rendered by browser which is customized by the content provider based on user’s profile. This paper proposes a Naive Bayes based lightweight classification engine targeted for a resource constraint devices. Our solution integrates with Web Browser that in turn triggers classification algorithm. Whenever a user browses a webpage, this solution extracts DOM Tree data from the browser’s rendering engine. This DOM data is a dynamic, contextual and secure data that can’t be replicated. This proposal extracts different features of the webpage that runs on an algorithm to classify into multiple categories. Naive Bayes based engine is chosen in this solution for its inherent advantages in using limited resources compared to other classification algorithms like Support Vector Machine, Neural Networks, etc. Naive Bayes classification requires small memory footprint and less computation suitable for smartphone environment. This solution has a feature to partition the model into multiple chunks that in turn will facilitate less usage of memory instead of loading a complete model. Classification of the webpages done through integrated engine is faster, more relevant and energy efficient than other standalone on device solution. This classification engine has been tested on Samsung Z3 Tizen hardware. The Engine is integrated into Tizen Browser that uses Chromium Rendering Engine. For this solution, extensive dataset is sourced from dmoztools.net and cleaned. This cleaned dataset has 227.5K webpages which are divided into 8 generic categories ('education', 'games', 'health', 'entertainment', 'news', 'shopping', 'sports', 'travel'). Our browser integrated solution has resulted in 15% less memory usage (due to partition method) and 24% less power consumption in comparison with standalone solution. This solution considered 70% of the dataset for training the data model and the rest 30% dataset for testing. An average accuracy of ~96.3% is achieved across the above mentioned 8 categories. This engine can be further extended for suggesting Dynamic tags and using the classification for differential uses cases to enhance browsing experience.

Keywords: chromium, lightweight engine, mobile computing, Naive Bayes, Tizen, web browser, webpage classification

Procedia PDF Downloads 163