Search results for: public transportation network

Authors: Hari K. Adhikari, Keshab Sharma, K. C. Apil

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The Gorkha Nepal earthquake of moment magnitude (Mw) 7.8 hit the central region of Nepal on April 25, 2015; with the epicenter about 77 km northwest of Kathmandu Valley. This paper aims to explore challenges of reconstruction in the rural earthquake-stricken areas of Nepal. The Gorkha earthquake on April 25, 2015, has significantly affected the livelihood of people and overall economy in Nepal, causing severe damage and destruction in central Nepal including nation’s capital. A larger part of the earthquake affected area is difficult to access with rugged terrain and scattered settlements, which posed unique challenges and efforts on a massive scale reconstruction and rehabilitation. 800 thousand buildings were affected leaving 8 million people homeless. Challenge of reconstruction of optimum 800 thousand houses is arduous for Nepal in the background of its turmoil political scenario and weak governance. With significant actors involved in the reconstruction process, no appreciable relief has reached to the ground, which is reflected over the frustration of affected people. The 2015 Gorkha earthquake is one of most devastating disasters in the modern history of Nepal. Best of our knowledge, there is no comprehensive study on reconstruction after disasters in modern Nepal, which integrates the necessary information to deal with challenges and opportunities of reconstructions. The study was conducted using qualitative content analysis method. Thirty engineers and ten social mobilizes working for reconstruction and more than hundreds local social workers, local party leaders, and earthquake victims were selected arbitrarily. Information was collected through semi-structured interviews and open-ended questions, focus group discussions, and field notes, with no previous assumption. Author also reviewed literature and document reviews covering academic and practitioner studies on challenges of reconstruction after earthquake in developing countries such as 2001 Gujarat earthquake, 2005 Kashmir earthquake, 2003 Bam earthquake and 2010 Haiti earthquake; which have very similar building typologies, economic, political, geographical, and geological conditions with Nepal. Secondary data was collected from reports, action plans, and reflection papers of governmental entities, non-governmental organizations, private sector businesses, and the online news. This study concludes that inaccessibility, absence of local government, weak governance, weak infrastructures, lack of preparedness, knowledge gap and manpower shortage, etc. are the key challenges of the reconstruction after 2015 earthquake in Nepal. After scrutinizing different challenges and issues, study counsels that good governance, integrated information, addressing technical issues, public participation along with short term and long term strategies to tackle with technical issues are some crucial factors for timely and quality reconstruction in context of Nepal. Sample collected for this study is relatively small sample size and may not be fully representative of the stakeholders involved in reconstruction. However, the key findings of this study are ones that need to be recognized by academics, governments, and implementation agencies, and considered in the implementation of post-disaster reconstruction program in developing countries.

Keywords: Gorkha earthquake, reconstruction, challenges, policy

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Authors: Reyard Mutamiswa, Frank Chidawanyika, Casper Nyamukondiwa

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Under stressful thermal environments, insects adjust their behaviour and physiology to maintain key life-history activities and improve survival. For interacting species, mutual or antagonistic, thermal stress may affect the participants in differing ways, which may then affect the outcome of the ecological relationship. In agroecosystems, this may be the fate of relationships between insect pests and their antagonistic parasitoids under acute and chronic thermal variability. Against this background, we therefore investigated the thermal tolerance of different developmental stages of Chilo partellus Swinhoe (Lepidoptera: Crambidae) and its larval parasitoid Cotesia sesamiae Cameron (Hymenoptera: Braconidae) using both dynamic and static protocols. In laboratory experiments, we determined lethal temperature assays (upper and lower lethal temperatures) using direct plunge protocols in programmable water baths (Systronix, Scientific, South Africa), effects of ramping rate on critical thermal limits following standardized protocols using insulated double-jacketed chambers (‘organ pipes’) connected to a programmable water bath (Lauda Eco Gold, Lauda DR.R. Wobser GMBH and Co. KG, Germany), supercooling points (SCPs) following dynamic protocols using a Pico logger connected to a programmable water bath, heat knock-down time (HKDT) and chill-coma recovery (CCRT) time following static protocols in climate chambers (HPP 260, Memmert GmbH + Co.KG, Germany) connected to a camera (HD Covert Network Camera, DS-2CD6412FWD-20, Hikvision Digital Technology Co., Ltd, China). When exposed for two hours to a static temperature, lower lethal temperatures ranged -9 to 6; -14 to -2 and -1 to 4ºC while upper lethal temperatures ranged from 37 to 48; 41 to 49 and 36 to 39ºC for C. partellus eggs, larvae and C. sesamiae adults respectively. Faster heating rates improved critical thermal maxima (CTmax) in C. partellus larvae and adult C. partellus and C. sesamiae. Lower cooling rates improved critical thermal minima (CTmin) in C. partellus and C. sesamiae adults while compromising CTmin in C. partellus larvae. The mean SCPs for C. partellus larvae, pupae and adults were -11.82±1.78, -10.43±1.73 and -15.75±2.47 respectively with adults having the lowest SCPs. Heat knock-down time and chill-coma recovery time varied significantly between C. partellus larvae and adults. Larvae had higher HKDT than adults, while the later recovered significantly faster following chill-coma. Current results suggest developmental stage differences in C. partellus thermal tolerance (with respect to lethal temperatures and critical thermal limits) and a compromised temperature tolerance of parasitoid C. sesamiae relative to its host, suggesting potential asynchrony between host-parasitoid population phenology and consequently biocontrol efficacy under global change. These results have broad implications to biological pest management insect-natural enemy interactions under rapidly changing thermal environments.

Keywords: chill-coma recovery time, climate change, heat knock-down time, lethal temperatures, supercooling point

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Authors: Adam J. Bowen

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Abstract— Should robots have rights or legal protections. Often debates concerning whether robots and AI should be afforded rights focus on conditions of personhood and the possibility of future advanced forms of AI satisfying particular intrinsic cognitive and moral attributes of rights-holding persons. Such discussions raise compelling questions about machine consciousness, autonomy, and value alignment with human interests. Although these are important theoretical concerns, especially from a future design perspective, they provide limited guidance for addressing the moral and legal standing of current and near-term AI that operate well below the cognitive and moral agency of human persons. Robots and AI are already being pressed into service in a wide range of roles, especially in healthcare and biomedical contexts. The design and large-scale implementation of robots in the context of core societal institutions like healthcare systems continues to rapidly develop. For example, we bring them into our homes, hospitals, and other care facilities to assist in care for the sick, disabled, elderly, children, or otherwise vulnerable persons. We enlist surgical robotic systems in precision tasks, albeit still human-in-the-loop technology controlled by surgeons. We also entrust them with social roles involving companionship and even assisting in intimate caregiving tasks (e.g., bathing, feeding, turning, medicine administration, monitoring, transporting). There have been advances to enable severely disabled persons to use robots to feed themselves or pilot robot avatars to work in service industries. As the applications for near-term AI increase and the roles of robots in restructuring our biomedical practices expand, we face pressing questions about the normative implications of human-robot interactions and collaborations in our collective worldmaking, as well as the moral and legal status of robots. This paper argues that robots operating in public and private spaces be afforded some protections as either moral patients or legal agents to establish prohibitions on robot abuse, misuse, and mistreatment. We already implement robots and embed them in our practices and institutions, which generates a host of human-to-machine and machine-to-machine relationships. As we interact with machines, whether in service contexts, medical assistance, or home health companions, these robots are first encountered in relationship to us and our respective roles in the encounter (e.g., surgeon, physical or occupational therapist, recipient of care, patient’s family, healthcare professional, stakeholder). This proposal aims to outline a framework for establishing limiting factors and determining the extent of moral or legal protections for robots. In doing so, it advocates for a relational approach that emphasizes the priority of mapping the complex contextually sensitive roles played and the relations in which humans and robots stand to guide policy determinations by relevant institutions and authorities. The relational approach must also be technically informed by the intended uses of the biomedical technologies in question, Design History Files, extensive risk assessments and hazard analyses, as well as use case social impact assessments.

Keywords: biomedical robots, robot ethics, robot laws, human-robot interaction

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

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

Keywords: sustainability, electric island, IOT, smart building

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Authors: Jose A. Alvarez Aldegunde, Adrian Fernandez Sanchez, Matthew D. Menden, Bernardo Vila Rodriguez

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Up to five statistical pre-processings have been carried out considering the pollutant records of the stations present in Cartagena de Indias, Colombia, also taking into account the childhood asthma incidence surveys conducted in hospitals in the city by the Health Ministry of Colombia for this study. These pre-processings have consisted of different techniques such as the determination of the quality of data collection, determination of the quality of the registration network, identification and debugging of errors in data collection, completion of missing data and purified data, as well as the improvement of the time scale of records. The characterization of the quality of the data has been conducted by means of density analysis of the pollutant registration stations using ArcGis Software and through mass balance techniques, making it possible to determine inconsistencies in the records relating the registration data between stations following the linear regression. The results obtained in this process have highlighted the positive quality in the pollutant registration process. Consequently, debugging of errors has allowed us to identify certain data as statistically non-significant in the incidence and series of contamination. This data, together with certain missing records in the series recorded by the measuring stations, have been completed by statistical imputation equations. Following the application of these prior processes, the basic series of incidence data for respiratory disease and pollutant records have allowed the characterization of the influence of pollutants on respiratory diseases such as, for example, childhood asthma. This characterization has been carried out using statistical correlation methods, including visual correlation, simple linear regression correlation and spectral analysis with PAST Software which identifies maximum periodicity cycles and minimums under the formula of the Lomb periodgram. In relation to part of the results obtained, up to eleven maximums and minimums considered contemporary between the incidence records and the particles have been identified taking into account the visual comparison. The spectral analyses that have been performed on the incidence and the PM2.5 have returned a series of similar maximum periods in both registers, which are at a maximum during a period of one year and another every 25 days (0.9 and 0.07 years). The bivariate analysis has managed to characterize the variable "Daily Vehicular Flow" in the ninth position of importance of a total of 55 variables. However, the statistical correlation has not obtained a favorable result, having obtained a low value of the R2 coefficient. The series of analyses conducted has demonstrated the importance of the influence of pollutants such as PM2.5 in the development of childhood asthma in Cartagena. The quantification of the influence of the variables has been able to determine that there is a 56% probability of dependence between PM2.5 and childhood respiratory asthma in Cartagena. Considering this justification, the study could be completed through the application of the BenMap Software, throwing a series of spatial results of interpolated values of the pollutant contamination records that exceeded the established legal limits (represented by homogeneous units up to the neighborhood level) and results of the impact on the exacerbation of pediatric asthma. As a final result, an economic estimate (in Colombian Pesos) of the monthly and individual savings derived from the percentage reduction of the influence of pollutants in relation to visits to the Hospital Emergency Room due to asthma exacerbation in pediatric patients has been granted.

Keywords: Asthma Incidence, BenMap, PM2.5, Statistical Analysis

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Authors: Gabrielle Robertson, Matthew Downs, Joseph Dagher

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Iron deposition in the brain has been linked with a host of neurological disorders such as Alzheimer’s, Parkinson’s, and Multiple Sclerosis. While some treatment options exist, there are no objective measurement tools that allow for the monitoring of iron levels in the brain in vivo. An emerging Magnetic Resonance Imaging (MRI) method has been recently proposed to deduce iron concentration through quantitative measurement of magnetic susceptibility. This is a multi-step process that involves repeated modeling of physical processes via approximate numerical solutions. For example, the last two steps of this Quantitative Susceptibility Mapping (QSM) method involve I) mapping magnetic field into magnetic susceptibility and II) mapping magnetic susceptibility into iron concentration. Process I involves solving an ill-posed inverse problem by using regularization via injection of prior belief. The end result from Process II highly depends on the model used to describe the molecular content of each voxel (type of iron, water fraction, etc.) Due to these factors, the accuracy and repeatability of QSM have been an active area of research in the MRI and medical imaging community. This work aims to estimate iron concentration in the brain via a single step. A synthetic numerical model of the human head was created by automatically and manually segmenting the human head on a high-resolution grid (640x640x640, 0.4mm³) yielding detailed structures such as microvasculature and subcortical regions as well as bone, soft tissue, Cerebral Spinal Fluid, sinuses, arteries, and eyes. Each segmented region was then assigned tissue properties such as relaxation rates, proton density, electromagnetic tissue properties and iron concentration. These tissue property values were randomly selected from a Probability Distribution Function derived from a thorough literature review. In addition to having unique tissue property values, different synthetic head realizations also possess unique structural geometry created by morphing the boundary regions of different areas within normal physical constraints. This model of the human brain is then used to create synthetic MRI measurements. This is repeated thousands of times, for different head shapes, volume, tissue properties and noise realizations. Collectively, this constitutes a training-set that is similar to in vivo data, but larger than datasets available from clinical measurements. This 3D convolutional U-Net neural network architecture was used to train data-driven Deep Learning models to solve for iron concentrations from raw MRI measurements. The performance was then tested on both synthetic data not used in training as well as real in vivo data. Results showed that the model trained on synthetic MRI measurements is able to directly learn iron concentrations in areas of interest more effectively than other existing QSM reconstruction methods. For comparison, models trained on random geometric shapes (as proposed in the Deep QSM method) are less effective than models trained on realistic synthetic head models. Such an accurate method for the quantitative measurement of iron deposits in the brain would be of important value in clinical studies aiming to understand the role of iron in neurological disease.

Keywords: magnetic resonance imaging, MRI, iron deposition, machine learning, quantitative susceptibility mapping

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Authors: Eleonora Carloni, Michela Arnaboldi

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In academia, the investigation of the relationship between cultural heritage and corporations is ubiquitous in several fields of studies. In practice corporations are more and more integrating arts and cultural heritage in their strategies for disparate benefits, such as: to foster customer’s purchase intention with authentic and aesthetic experiences, to improve their reputation towards local communities, and to motivate employees with creative thinking. There are diverse forms under which corporations set these artistic interventions, from sponsorships to arts-based training centers for employees, but scholars agree that the maximum expression of this cultural trend are corporate museums, growing in number and relevance. Corporate museums are museum-like settings, hosting artworks of corporations’ history and interests. In academia they have been ascribed as strategic asset and they have been associated with diverse uses for corporations’ benefits, from place for preservation of cultural heritage, to tools for public relations and cultural flagship stores. Previous studies have thus extensively but fragmentally studied the diverse benefits of corporate museum opening to corporations, with a lack of comprehensive approach and a digression on how to evaluate and report corporate museum’s performances. Stepping forward, the present study aims to investigate: 1) what are the key performance measures corporate museums need to report to the associated corporations; 2) how are the key performance measures reported to the concerned corporations. This direction of study is not only suggested as future direction in academia but it has solid basis in practice, aiming to answer to the need of corporate museums’ directors to account for corporate museum’s activities to the concerned corporation. Coherently, at an empirical level the study relies on action research method, whose distinctive feature is to develop practical knowledge through a participatory process. This paper indeed relies on the experience of a collaborative project between the researchers and a set of corporate museums in Italy, aimed at co-developing a performance measurement system. The project involved two steps: a first step, in which researchers derived the potential performance measures from literature along with exploratory interviews; a second step, in which researchers supported the pool of corporate museums’ directors in co-developing a set of key performance indicators for reporting. Preliminary empirical findings show that while scholars insist on corporate museums’ capability to develop networking relations, directors insist on the role of museums as internal supplier of knowledge for innovation goals. Moreover, directors stress museums’ cultural mission and outcomes as potential benefits for corporation, by remarking to include both cultural and business measures in the final tool. In addition, they give relevant attention to the wording used in humanistic terms while struggling to express all measures in economic terms. The paper aims to contribute to corporate museums’ and more broadly to arts-based initiatives’ literature in two directions. Firstly, it elaborates key performance measures with related indicators to report on cultural initiatives for corporations. Secondly, it provides evidence of challenges and practices to handle reporting on these initiatives, because of tensions arising from the co-existence of diverse perspectives, namely arts and business worlds.

Keywords: arts-based initiative, corporate museum, hybrid organization, performance measurement

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Authors: Jonathan Nii Laryea Ashong, Samuel Opare

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Current sustainable cities debate focuses on the formidable problems for the Ghana’s largest urban and rural agglomerations, the majority of all urban dwellers continue to reside in far smaller urban settlements. It is estimated that by year 2030, almost all the Ghana’s population growth will likely be intense in urban areas including Nkawkaw in the Kwahu West Municipality of Ghana. Nkawkaw is situated on the road and former railway between Accra and Kumasi, and lies about halfway between these cities. It is also connected by road to Koforidua and Konongo. According to the 2013 census, Nkawkaw has a settlement population of 61,785. Many international agencies, government and private architectures’ are been asked to adequately recognize the naming of streets and property addressing system among the 170 districts across Ghana. The naming of streets and numbering of properties is to assist Metropolitan, Municipal and District Assemblies to manage the processes for establishing coherent address system nationally. Street addressing in the Nkawkaw in the Kwahu West Municipality which makes it possible to identify the location of a parcel of land, public places or dwellings on the ground based on system of names and numbers, yet agreement on how to progress towards it remains elusive. Therefore, reliable and effective development control for proper street naming and property addressing systems are required. The Intelligent Addressing (IA) technology from the UK is being used to name streets and properties in Ghana. The intelligent addressing employs the technique of unique property Reference Number and the unique street reference number which would transform national security and other service providers’ ability to respond rapidly to distress calls. Where name change is warranted following the review of existing streets names, the Physical Planning Department (PPDs) shall, in consultation with the relevant traditional authorities and community leadership (or relevant major stakeholders), select a street name in accordance with the provisions of the policy and the processes outlined for street name change for new development. In the case of existing streets with no names, the respective PPDs shall, in consultation with the relevant traditional authorities and community leadership (or relevant major stakeholders), select a street name in accordance with the requirements set out in municipality. Naming of access ways proposed for new developments shall be done at the time of developing sector layouts (subdivision maps) for the designated areas. In the case of private gated developments, the developer shall submit the names of the access ways as part of the plan and other documentation forwarded to the Municipal District Assembly for approval. The names shall be reviewed first by the PPD to avoid duplication and to ensure conformity to the required standards before submission to the Assembly’s Statutory Planning Committee for approval. The Kwahu West Municipality is supposed to be self-sustaining, providing basic services to inhabitants as a result of proper planning layouts, street naming and property addressing system that prevail in the area. The implications of these future projections are discussed.

Keywords: Nkawkaw, Kwahu west municipality, street naming, property, addressing system

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Authors: Roland F. Karthaus, Rachel S. O'Brien

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Over the past decade, the authors have undertaken applied research aimed at enabling transformation within the prison service to improve conditions and outcomes for those living, working and visiting in prisons in the UK and the communities they serve. The research has taken place against a context of reducing resources and public discontent at increasing levels of violence, deteriorating conditions and persistently high levels of re-offending. Top-down governmental policies have mainly been ineffectual and in some cases counter-productive. The prison service is characterised by hierarchical organisation, and the research has applied design thinking at multiple levels to challenge and precipitate change: top-down, middle-out and bottom-up. The research employs three distinct but related approaches, system design (top-down): working at the national policy level to analyse the changing policy context, identifying opportunities and challenges; engaging with the Ministry of Justice commissioners and sector organisations to facilitate debate, introducing new evidence and provoking creative thinking, place-based design (middle-out): working with individual prison establishments as pilots to illustrate and test the potential for local empowerment, creative change, and improved architecture within place-specific contexts and organisational hierarchies, everyday design (bottom-up): working with individuals in the system to explore the potential for localised, significant, demonstrator changes; including collaborative design, capacity building and empowerment in skills, employment, communication, training, and other activities. The research spans a series of projects, through which the methodological approach has developed responsively. The projects include a place-based model for the re-purposing of Ministry of Justice land assets for the purposes of rehabilitation; an evidence-based guide to improve prison design for health and well-being; capacity-based employment, skills and self-build project as a template for future open prisons. The overarching research has enabled knowledge to be developed and disseminated through policy and academic networks. Whilst the research remains live and continuing; key findings are emerging as a basis for a new methodological approach to effecting change in the UK prison service. An interdisciplinary approach is necessary to overcome the barriers between distinct areas of the prison service. Sometimes referred to as total environments, prisons encompass entire social and physical environments which themselves are orchestrated by institutional arms of government, resulting in complex systems that cannot be meaningfully engaged through narrow disciplinary lenses. A scalar approach is necessary to connect strategic policies with individual experiences and potential, through the medium of individual prison establishments, operating as discrete entities within the system. A reflexive process is necessary to connect research with action in a responsive mode, learning to adapt as the system itself is changing. The role of individuals in the system, their latent knowledge and experience and their ability to engage and become agents of change are essential. Whilst the specific characteristics of the UK prison system are unique, the approach is internationally applicable.

Keywords: architecture, design, policy, prison, system, transformation

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Authors: K. C. Apil, Keshab Sharma, Bigul Pokharel

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Kathmandu Valley, capital city of Nepal houses numerous historical monuments as well as religious structures which are as old as from the 4th century A.D. The city alone is home to seven UNESCO’s world heritage sites including various public squares and religious sanctums which are often regarded as living heritages by various historians and archeological explorers. Recently on April 25, 2015, the capital city including other nearby locations was struck with Gorkha earthquake of moment magnitude (Mw) 7.8, followed by the strongest aftershock of moment magnitude (Mw) 7.3 on May 12. This study reports structural failures and collapse of heritage structures in Kathmandu Valley during the earthquake and presents preliminary findings as to the causes of failures and collapses. Field reconnaissance was carried immediately after the main shock and the aftershock, in major heritage sites: UNESCO world heritage sites, a number of temples and historic buildings in Kathmandu Durbar Square, Patan Durbar Square, and Bhaktapur Durbar Square. Despite such catastrophe, a significant number of heritage structures stood high, performing very well during the earthquake. Preliminary reports from archeological department suggest that 721 of such structures were severely affected, whereas numbers within the valley only were 444 including 76 structures which were completely collapsed. This study presents recorded accelerograms and geology of Kathmandu Valley. Structural typology and architecture of the heritage structures in Kathmandu Valley are briefly described. Case histories of damaged heritage structures, the patterns, and the failure mechanisms are also discussed in this paper. It was observed that performance of heritage structures was influenced by the multiple factors such as structural and architecture typology, configuration, and structural deficiency, local ground site effects and ground motion characteristics, age and maintenance level, material quality etc. Most of such heritage structures are of masonry type using bricks and earth-mortar as a bonding agent. The walls' resistance is mainly compressive, thus capable of withstanding vertical static gravitational load but not horizontal dynamic seismic load. There was no definitive pattern of damage to heritage structures as most of them behaved as a composite structure. Some structures were extensively damaged in some locations, while structures with similar configuration at nearby location had little or no damage. Out of major heritage structures, Dome, Pagoda (2, 3 or 5 tiered temples) and Shikhara structures were studied with similar variables. Studying varying degrees of damages in such structures, it was found that Shikhara structures were most vulnerable one where Dome structures were found to be the most stable one, followed by Pagoda structures. The seismic performance of the masonry-timber and stone masonry structures were slightly better than that of the masonry structures. Regular maintenance and periodic seismic retrofitting seems to have played pivotal role in strengthening seismic performance of the structure. The study also recommends some key functions to strengthen the seismic performance of such structures through study based on structural analysis, building material behavior and retrofitting details. The result also recognises the importance of documentation of traditional knowledge and its revised transformation in modern technology.

Keywords: Gorkha earthquake, field observation, heritage structure, seismic performance, masonry building

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Authors: Sonja Giese, Tess N. Peacock

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South African based Innovation Edge is experimenting with technology to drive positive behavior change, enable data-driven decision making, and scale quality early years services. This paper uses five case studies to illustrate how technology can be used in resource-constrained environments to first, encourage parenting practices that build early language development (using a stage-based mobile messaging pilot, ChildConnect), secondly, to improve the quality of ECD programs (using a mobile application, CareUp), thirdly, how to affordably scale services for the early detection of visual and hearing impairments (using a mobile tool, HearX), fourthly, how to build a transparent and accountable system for the registration and funding of ECD (using a blockchain enabled platform, Amply), and finally enable rapid data collection and feedback to facilitate quality enhancement of programs at scale (the Early Learning Outcomes Measure). ChildConnect and CareUp were both developed using a design based iterative research approach. The usage and uptake of ChildConnect and CareUp was evaluated with qualitative and quantitative methods. Actual child outcomes were not measured in the initial pilots. Although parents who used and engaged on either platform felt more supported and informed, parent engagement and usage remains a challenge. This is contrast to ECD practitioners whose usage and knowledge with CareUp showed both sustained engagement and knowledge improvement. HearX is an easy-to-use tool to identify hearing loss and visual impairment. The tool was tested with 10000 children in an informal settlement. The feasibility of cost-effectively decentralising screening services was demonstrated. Practical and financial barriers remain with respect to parental consent and for successful referrals. Amply uses mobile and blockchain technology to increase impact and accountability of public services. In the pilot project, Amply is being used to replace an existing paper-based system to register children for a government-funded pre-school subsidy in South Africa. Early Learning Outcomes Measure defines what it means for a child to be developmentally ‘on track’ at aged 50-69 months. ELOM administration is enabled via a tablet which allows for easy and accurate data collection, transfer, analysis, and feedback. ELOM is being used extensively to drive quality enhancement of ECD programs across multiple modalities. The nature of ECD services in South Africa is that they are in large part provided by disconnected private individuals or Non-Governmental Organizations (in contrast to basic education which is publicly provided by the government). It is a disparate sector which means that scaling successful interventions is that much harder. All five interventions show the potential of technology to support and enhance a range of ECD services, but pathways to scale are still being tested.

Keywords: assessment, behavior change, communication, data, disabilities, mobile, scale, technology, quality

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Authors: Francisco J. Ortega, Claudia Roman, Moisés García-Morales, Francisco J. Navarro

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Asphaltic bitumen has been largely used in both industrial and civil engineering, mostly in pavement construction and roofing membrane manufacture. However, bitumen as such is greatly susceptible to temperature variations, and dramatically changes its in-service behavior from a viscoelastic liquid, at medium-high temperatures, to a brittle solid at low temperatures. Bitumen modification prevents these problems and imparts improved performance. Isocyanates like polymeric MDI (mixture of 4,4′-diphenylmethane di-isocyanate, 2,4’ and 2,2’ isomers, and higher homologues) have shown to remarkably enhance bitumen properties at the highest in-service temperatures expected. This comes from the reaction between the –NCO pendant groups of the oligomer and the most polar groups of asphaltenes and resins in bitumen. In addition, oxygen diffusion and/or UV radiation may provoke bitumen hardening and ageing. With the purpose of minimizing these effects, nano-layered-silicates (nanoclays) are increasingly being added to bitumen formulations. Montmorillonites, a type of naturally occurring mineral, may produce a nanometer scale dispersion which improves bitumen thermal, mechanical and barrier properties. In order to increase their lipophilicity, these nanoclays are normally treated so that organic cations substitute the inorganic cations located in their intergallery spacing. In the present work, the combined effect of polymeric MDI and the commercial montmorillonite Cloisite® 20A was evaluated. A selected bitumen with penetration within the range 160/220 was modified with 10 wt.% Cloisite® 20A and 2 wt.% polymeric MDI, and the resulting ternary composites were characterized by linear rheology, X-ray diffraction (XRD) and Atomic Force Microscopy (AFM). The rheological tests evidenced a notable solid-like behavior at the highest temperatures studied when bitumen was just loaded with 10 wt.% Cloisite® 20A and high-shear blended for 20 minutes. However, if polymeric MDI was involved, the sequence of addition exerted a decisive control on the linear rheology of the final ternary composites. Hence, in bitumen/Cloisite® 20A/polymeric MDI formulations, the previous solid-like behavior disappeared. By contrast, an inversion in the order of addition (bitumen/polymeric MDI/ Cloisite® 20A) enhanced further the solid-like behavior imparted by the nanoclay. In order to gain a better understanding of the factors that govern the linear rheology of these ternary composites, a morphological and microstructural characterization based on XRD and AFM was conducted. XRD demonstrated the existence of clay stacks intercalated by bitumen molecules to some degree. However, the XRD technique cannot provide detailed information on the extent of nanoclay delamination, unless the entire fraction has effectively been fully delaminated (situation in which no peak is observed). Furthermore, XRD was unable to provide precise knowledge neither about the spatial distribution of the intercalated/exfoliated platelets nor about the presence of other structures at larger length scales. In contrast, AFM proved its power at providing conclusive information on the morphology of the composites at the nanometer scale and at revealing the structural modification that yielded the rheological properties observed. It was concluded that high-shear blending brought about a nanoclay-reinforced network. As for the bitumen/Cloisite® 20A/polymeric MDI formulations, the solid-like behavior was destroyed as a result of the agglomeration of the nanoclay platelets promoted by chemical reactions.

Keywords: Atomic Force Microscopy, bitumen, composite, isocyanate, montmorillonite.

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Authors: Andrew D. Henshaw, James M. Austin

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Introduction: Human trafficking is an increasingly serious transnational criminal enterprise and social security issue. Despite ongoing efforts to mitigate the phenomenon and a significant expansion of security scrutiny over past decades, it is not receding. This is true for many nations in Southeast Asia, widely recognized as the global hub for trafficked persons, including men, women, and children. Clearly, human trafficking is difficult to address because there are numerous drivers, causes, and motivators for it to persist, such as non-military and non-traditional security challenges, i.e., climate change, global warming displacement, and natural disasters. These make displaced persons and refugees particularly vulnerable. The issue is so large conservative estimates put a dollar value at around $150 billion-plus per year (Niethammer, 2020) spanning sexual slavery and exploitation, forced labor, construction, mining and in conflict roles, and forced marriages of girls and women. Coupled with corruption throughout military, police, and civil authorities around the world, and the active hands of powerful transnational criminal organizations, it is likely that such figures are grossly underestimated as human trafficking is misreported, under-detected, and deliberately obfuscated to protect those profiting from it. For example, the 2022 UN report on human trafficking shows a 56% reduction in convictions in that year alone (UNODC, 2022). Our Approach: To better understand this, our research utilizes a bespoke methodology. Applying a JAM (Juxtaposition Assessment Matrix), which we previously developed to detect flows of dark money around the globe (Henshaw, A & Austin, J, 2021), we now focus on the human trafficking paradigm. Indeed, utilizing a JAM methodology has identified key indicators of human trafficking not previously explored in depth. Being a set of structured analytical techniques that provide panoramic interpretations of the subject matter, this iteration of the JAM further incorporates behavioral and driver indicators, including the employment of Open-Source Artificial Intelligence (OS-AI) across multiple collection points. The extracted behavioral data was then applied to identify non-traditional indicators as they contribute to human trafficking. Furthermore, as the JAM OS-AI analyses data from the inverted position, i.e., the viewpoint of the traffickers, it examines the behavioral and physical traits required to succeed. This transposed examination of the requirements of success delivers potential leverage points for exploitation in the fight against human trafficking in a new and novel way. Findings: Our approach identified new innovative datasets that have previously been overlooked or, at best, undervalued. For example, the JAM OS-AI approach identified critical 'dark agent' lynchpins within human trafficking that are difficult to detect and harder to connect to actors and agents within a network. Our preliminary data suggests this is in part due to the fact that ‘dark agents’ in extant research have been difficult to detect and potentially much harder to directly connect to the actors and organizations in human trafficking networks. Our research demonstrates that using new investigative techniques such as OS-AI-aided JAM introduces a powerful toolset to increase understanding of human trafficking and transnational crime and illuminate networks that, to date, avoid global law enforcement scrutiny.

Keywords: human trafficking, open-source intelligence, transnational crime, human security, international human rights, intelligence analysis, JAM OS-AI, Dark Money

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Authors: F. Uriel, M. M. Fernandez Liporace

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In the last decade, academic achievement in higher education has become a topic of agenda in Argentina, regarding the high figures of adjustment problems, academic failure and dropout, and the low graduation rates in the context of massive classes and traditional teaching methods. Psychological variables, such as perceived social support, academic motivation and learning styles and strategies have much to offer since their measurement by tests allows a proper diagnose of their influence on academic achievement. Framed in a major research, several studies analysed multiple samples, totalizing 5135 students attending Argentinean public universities. The first goal was aimed at the identification of statistically significant differences in psychological variables -perceived social support, learning styles, learning strategies, and academic motivation- by age, gender, and degree of academic advance (freshmen versus sophomores). Thus, an inferential group differences study for each psychological dependent variable was developed by means of student’s T tests, given the features of data distribution. The second goal, aimed at examining associations between the four psychological variables on the one hand, and academic achievement on the other, was responded by correlational studies, calculating Pearson’s coefficients, employing grades as the quantitative indicator of academic achievement. The positive and significant results that were obtained led to the formulation of different predictive models of academic achievement which had to be tested in terms of adjustment and predictive power. These models took the four psychological variables above mentioned as predictors, using regression equations, examining predictors individually, in groups of two, and together, analysing indirect effects as well, and adding the degree of academic advance and gender, which had shown their importance within the first goal’s findings. The most relevant results were: first, gender showed no influence on any dependent variable. Second, only good achievers perceived high social support from teachers, and male students were prone to perceive less social support. Third, freshmen exhibited a pragmatic learning style, preferring unstructured environments, the use of examples and simultaneous-visual processing in learning, whereas sophomores manifest an assimilative learning style, choosing sequential and analytic processing modes. Despite these features, freshmen have to deal with abstract contents and sophomores, with practical learning situations due to study programs in force. Fifth, no differences in academic motivation were found between freshmen and sophomores. However, the latter employ a higher number of more efficient learning strategies. Sixth, freshmen low achievers lack intrinsic motivation. Seventh, models testing showed that social support, learning styles and academic motivation influence learning strategies, which affect academic achievement in freshmen, particularly males; only learning styles influence achievement in sophomores of both genders with direct effects. These findings led to conclude that educational psychologists, education specialists, teachers, and universities must plan urgent and major changes. These must be applied in renewed and better study programs, syllabi and classes, as well as tutoring and training systems. Such developments should be targeted to the support and empowerment of students in their academic pathways, and therefore to the upgrade of learning quality, especially in the case of freshmen, male freshmen, and low achievers.

Keywords: academic achievement, academic motivation, coping, learning strategies, learning styles, perceived social support

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Authors: Jing Jin

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The incorporation of artificial intelligence (AI) and machine learning (ML) in aircraft manufacturing and aerospace supply chains leads to the generation of a substantial amount of data among various tiers of suppliers and OEMs. Identifying the high-quality information challenges decision-makers. The application of AI/ML models necessitates access to 'high-quality' information to yield desired outputs. However, the process of information sharing introduces complexities, including distortion through various communication channels and biases introduced by both human and AI entities. This phenomenon significantly influences the quality of information, impacting decision-makers engaged in configuring supply chain systems. Traditionally, distorted information is categorized as 'low-quality'; however, this study challenges this perception, positing that distorted information, contributing to stakeholder goals, can be deemed high-quality within supply chains. The main aim of this study is to identify and evaluate the dimensions of information quality crucial to the UK aerospace supply chain. Guided by a central research question, "What information quality dimensions are considered when defining information quality in the UK aerospace supply chain?" the study delves into the intricate dynamics of information quality in the aerospace industry. Additionally, the research explores the nuanced impact of information distortion on stakeholders' decision-making processes, addressing the question, "How does the information distortion phenomenon influence stakeholders’ decisions regarding information quality in the UK aerospace supply chain system?" This study employs deductive methodologies rooted in positivism, utilizing a cross-sectional approach and a mono-quantitative method -a questionnaire survey. Data is systematically collected from diverse tiers of supply chain stakeholders, encompassing end-customers, OEMs, Tier 0.5, Tier 1, and Tier 2 suppliers. Employing robust statistical data analysis methods, including mean values, mode values, standard deviation, one-way analysis of variance (ANOVA), and Pearson’s correlation analysis, the study interprets and extracts meaningful insights from the gathered data. Initial analyses challenge conventional notions, revealing that information distortion positively influences the definition of information quality, disrupting the established perception of distorted information as inherently low-quality. Further exploration through correlation analysis unveils the varied perspectives of different stakeholder tiers on the impact of information distortion on specific information quality dimensions. For instance, Tier 2 suppliers demonstrate strong positive correlations between information distortion and dimensions like access security, accuracy, interpretability, and timeliness. Conversely, Tier 1 suppliers emphasise strong negative influences on the security of accessing information and negligible impact on information timeliness. Tier 0.5 suppliers showcase very strong positive correlations with dimensions like conciseness and completeness, while OEMs exhibit limited interest in considering information distortion within the supply chain. Introducing social network analysis (SNA) provides a structural understanding of the relationships between information distortion and quality dimensions. The moderately high density of ‘information distortion-by-information quality’ underscores the interconnected nature of these factors. In conclusion, this study offers a nuanced exploration of information quality dimensions in the UK aerospace supply chain, highlighting the significance of individual perspectives across different tiers. The positive influence of information distortion challenges prevailing assumptions, fostering a more nuanced understanding of information's role in the Industry 4.0 landscape.

Keywords: information distortion, information quality, supply chain configuration, UK aerospace industry

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Authors: Deepika Joshi

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Operations in automotive industry rely greatly on information shared between Supply Chain (SC) partners. This leads to efficient and effective management of SC activity. Automotive sector in India is growing at 14.2 percent per annum and has huge economic importance. We find that no study has been carried out on the role of information sharing in SC management of Indian automotive manufacturers. Considering this research gap, the present study is planned to establish the significance of information sharing in Indian auto-component supply chain activity. An empirical research was conducted for large scale auto component manufacturers from India. Twenty four Supply Chain Performance Indicators (SCPIs) were collected from existing literature. These elements belong to eight diverse but internally related areas of SC management viz., demand management, cost, technology, delivery, quality, flexibility, buyer-supplier relationship, and operational factors. A pair-wise comparison and an open ended questionnaire were designed using these twenty four SCPIs. The questionnaire was then administered among managerial level employees of twenty-five auto-component manufacturing firms. Analytic Network Process (ANP) technique was used to analyze the response of pair-wise questionnaire. Finally, twenty-five priority indexes are developed, one for each respondent. These were averaged to generate an industry specific priority index. The open-ended questions depicted strategies related to information sharing between buyers and suppliers and their influence on supply chain performance. Results show that the impact of information sharing on certain performance indicators is relatively greater than their corresponding variables. For example, flexibility, delivery, demand and cost related elements have massive impact on information sharing. Technology is relatively less influenced by information sharing but it immensely influence the quality of information shared. Responses obtained from managers reveal that timely and accurate information sharing lowers the cost, increases flexibility and on-time delivery of auto parts, therefore, enhancing the competitiveness of Indian automotive industry. Any flaw in dissemination of information can disturb the cycle time of both the parties and thus increases the opportunity cost. Due to supplier’s involvement in decisions related to design of auto parts, quality conformance is found to improve, leading to reduction in rejection rate. Similarly, mutual commitment to share right information at right time between all levels of SC enhances trust level. SC partners share information to perform comprehensive quality planning to ingrain total quality management. This study contributes to operations management literature which faces scarcity of empirical examination on this subject. It views information sharing as a building block which firms can promote and evolve to leverage the operational capability of all SC members. It will provide insights for Indian managers and researchers as every market is unique and suppliers and buyers are driven by local laws, industry status and future vision. While major emphasis in this paper is given to SC operations happening between domestic partners, placing more focus on international SC can bring in distinguished results.

Keywords: Indian auto component industry, information sharing, operations management, supply chain performance indicators

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Authors: Manjula Kola, K. Chandralekha

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Anaemia is one of the world’s most widespread health problems. Prevalence of anemia in south Asia is among the highest in the world. Iron deficiency anemia accounts for almost 85 percent of all types of anemia in India and affects more than half of the total population. Women of childbearing age particularly pregnant women, infants, preschool children and adolescents are at greatest risk of developing iron deficiency anemia. In India, 74 percent children between 6-35 months of age are anemic. Children between 1-6 years in major cities are found with a high prevalence rate of 64.8 percent. Iron deficiency anemia is not only a public health problem, but also a development problem. Its prevention and reduction must be viewed as investment in human capital that will enhance development and reduce poverty. Ending this hidden hunger in the form of iron deficiency is the most important achievable international health goal. Eliminating the underlying problem is essential to the sustained elimination of the iron deficiency anemia. The intervention programmes toward the sustained elimination need to be broadly based so that interventions become accepted community practices. Hence, intervention strategies need to go well beyond traditional health and nutrition systems and based upon empowering people and communities so that they will be capable of arranging for and sustaining an adequate intake of foods with respect to iron, independent of external support. Such strategies must necessarily be multisectoral and integrate interventions with social communications, evaluation and surveillance. The main objective of the study was to design a community based Nutrition intervention using theoretical framework of social marketing to sustain improvement of iron nutriture among preschool children. In order to carryout the study eight rural communities In Chittoor district of Andhra Pradesh, India were selected. A formative research was carryout for situational analysis and baseline data was generated with regard to demographic and socioeconomic status, dietary intakes, Knowledge, Attitude and Practices of the mothers of preschool children, clinical and hemoglobin status of the target group. Based on the formative research results, the research area was divides into four groups as experimental area I,II,III and control area. A community based, integrated and comprehensive social marketing intervention was designed based on various theories and models of nutrition education/ communication. In Experimental area I, Nutrition intervention using social marketing and a weekly iron folic acid supplementation was given to improve iron nutriture of preschool children. In experimental area II, Social marketing alone was implemented and in experimental area III Iron supplementation alone was given. No intervention was given in control area. The Impact evaluation revealed that among different interventions tested, the integrated social marketing intervention resulted best outcomes. The overall observations of the study state that social marketing, an integrated and functional strategy for nutrition communication to prevent and control iron deficiency. Various theoretical frame works / models for nutrition communication facilitate to design culturally appropriate interventions thus achieved improvements in the knowledge, attitude and practices there by resulting successful impact on nutritional status of the target groups.

Keywords: anemia, iron deficiency, social marketing, theoretical framework

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Authors: Tolulope Aremu

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The key process steps to produce liquid detergent products will introduce potential defects, such as formulation, mixing, filling, and packaging, which might compromise product quality, consumer safety, and operational efficiency. Real-time identification and characterization of such defects are of prime importance for maintaining high standards and reducing waste and costs. Usually, defect detection is performed by human inspection or rule-based systems, which is very time-consuming, inconsistent, and error-prone. The present study overcomes these limitations in dealing with optimization in defect characterization within the process for making liquid detergents using Machine Learning algorithms. Performance testing of various machine learning models was carried out: Support Vector Machine, Decision Trees, Random Forest, and Convolutional Neural Network on defect detection and classification of those defects like wrong viscosity, color deviations, improper filling of a bottle, packaging anomalies. These algorithms have significantly benefited from a variety of optimization techniques, including hyperparameter tuning and ensemble learning, in order to greatly improve detection accuracy while minimizing false positives. Equipped with a rich dataset of defect types and production parameters consisting of more than 100,000 samples, our study further includes information from real-time sensor data, imaging technologies, and historic production records. The results are that optimized machine learning models significantly improve defect detection compared to traditional methods. Take, for instance, the CNNs, which run at 98% and 96% accuracy in detecting packaging anomaly detection and bottle filling inconsistency, respectively, by fine-tuning the model with real-time imaging data, through which there was a reduction in false positives of about 30%. The optimized SVM model on detecting formulation defects gave 94% in viscosity variation detection and color variation. These values of performance metrics correspond to a giant leap in defect detection accuracy compared to the usual 80% level achieved up to now by rule-based systems. Moreover, this optimization with models can hasten defect characterization, allowing for detection time to be below 15 seconds from an average of 3 minutes using manual inspections with real-time processing of data. With this, the reduction in time will be combined with a 25% reduction in production downtime because of proactive defect identification, which can save millions annually in recall and rework costs. Integrating real-time machine learning-driven monitoring drives predictive maintenance and corrective measures for a 20% improvement in overall production efficiency. Therefore, the optimization of machine learning algorithms in defect characterization optimum scalability and efficiency for liquid detergent companies gives improved operational performance to higher levels of product quality. In general, this method could be conducted in several industries within the Fast moving consumer Goods industry, which would lead to an improved quality control process.

Keywords: liquid detergent manufacturing, defect detection, machine learning, support vector machines, convolutional neural networks, defect characterization, predictive maintenance, quality control, fast-moving consumer goods

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Authors: Elisabetta Cianfanelli, Maria Claudia Coppola, Margherita Tufarelli

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Design practices throughout history return a critical understanding of society since they always conveyed values and meanings aimed at (re)framing reality by acting in everyday life: here, design gains cultural and normative character, since its artifacts, services, and environments hold the power to intercept, influence and inspire thoughts, behaviors, and relationships. In this sense, design can be persuasive, engaging in the production of worlds and, as such, acting in the space between poietics and politics so that chasing preferable futures and their aesthetic strategies becomes a matter full of political responsibility. This resonates with contemporary landscapes of radical interdependencies challenging designers to focus on complex socio-technical systems and to better support values such as equality and justice for both humans and nonhumans. In fact, it is in times of crisis and structural uncertainty that designers turn into visionaries at the service of society, envisioning scenarios and dwelling in the territories of imagination to conceive new fictions and frictions to be added to the thickness of the real. Here, design’s main tasks are to develop options, to increase the variety of choices, to cultivate its role as scout, jester, agent provocateur for the public, so that design for transformation emerges, making an explicit commitment to society, furthering structural change in a proactive and synergic manner. However, the exploration of possible futures is both a trap and a trampoline because, although it embodies a radical research tool, it raises various challenges when the design process goes further in the translation of such vision into an artefact - whether tangible or intangible -, through which it should deliver that bit of future into everyday experience. Today designers are making up new tools and practices to tackle current wicked challenges, combining their approaches with other disciplinary domains: futuring through design, thus, rises from research strands like speculative design, design fiction, and critical design, where the blending of design approaches and futures thinking brings an action-oriented and product-based approach to strategic insights. The contribution positions at the intersection of those approaches, aiming at discussing design’s tools of inquiry through which it is possible to grasp the agency of imagined futures into present time. Since futures are not remote, they actively participate in creating path-dependent decisions, crystallized into designed artifacts par excellence, prototypes, and their conceptual other, provotypes: with both being unfinished and multifaceted, the first ones are effective in reiterating solutions to problems already framed, while the second ones prove to be useful when the goal is to explore and break boundaries, bringing closer preferable futures. By focusing on some provotypes throughout history which challenged markets and, above all, social and cultural structures, the contribution’s final aim is understanding the knowledge produced by provotypes, understood as design spaces where designs’s humanistic side might help developing a deeper sensibility about uncertainty and, most of all, the unfinished feature of societal artifacts, whose experimentation would leave marks and traces to build up f(r)ictions as vital sparks of plurality and collective life.

Keywords: speculative design, provotypes, design knowledge, political theory

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Authors: Claudia Trillo

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Regional innovation eco-ecosystems are composed of a variety of interconnected urban innovation eco-systems, mutually reinforcing each other and making the whole territorial system successful. Combining principles drawn from the new economic growth theory and from the socio-constructivist approach to the economic growth, with the new geography of innovation emerging from the networked nature of innovation districts, this paper explores the spatial configuration of urban innovation districts, with the aim of unveiling replicable spatial patterns and transferable portfolios of urban policies. While some authors suggest that cities should be considered ideal natural clusters, supporting cross-fertilization and innovation thanks to the physical setting they provide to the construction of collective knowledge, still a considerable distance persists between regional development strategies and urban policies. Moreover, while public and private policies supporting entrepreneurship normally consider innovation as the cornerstone of any action aimed at uplifting the competitiveness and economic success of a certain area, a growing body of literature suggests that innovation is non-neutral, hence, it should be constantly assessed against equity and social inclusion. This paper draws from a robust qualitative empirical dataset gathered through 4-years research conducted in Boston to provide readers with an evidence-based set of recommendations drawn from the lessons learned through the investigation of the chosen innovation districts in the Boston area. The evaluative framework used for assessing the overall performance of the chosen case studies stems from the Habitat III Sustainable Development Goals rationale. The concept of inclusive growth has been considered essential to assess the social innovation domain in each of the chosen cases. The key success factors for the development of the Boston innovation ecosystem can be generalized as follows: 1) a quadruple helix model embedded in the physical structure of the two cities (Boston and Cambridge), in which anchor Higher Education (HE) institutions continuously nurture the Entrepreneurial Environment. 2) an entrepreneurial approach emerging from the local governments, eliciting risk-taking and bottom-up civic participation in tackling key issues in the city. 3) a networking structure of some intermediary actors supporting entrepreneurial collaboration, cross-fertilization and co-creation, which collaborate at multiple-scales thus enabling positive spillovers from the stronger to the weaker contexts. 4) awareness of the socio-economic value of the built environment as enabler of cognitive networks allowing activation of the collective intelligence. 5) creation of civic-led spaces enabling grassroot collaboration and cooperation. Evidence shows that there is not a single magic recipe for the successful implementation of place-based and social innovation-driven strategies. On the contrary, the variety of place-grounded combinations of micro and macro initiatives, embedded in the social and spatial fine grain of places and encompassing a diversity of actors, can create the conditions enabling places to thrive and local economic activities to grow in a sustainable way.

Keywords: innovation-driven sustainable Eco-systems , place-based sustainable urban development, sustainable innovation districts, social innovation, urban policie

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Authors: L. R. Valencia Pérez, J. M. Peña Aguilar, A. Lamadrid Álvarez, A. Pastrana Palma, H. F. Valencia Pérez, M. Vivanco Vargas

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This work proposes a Cooperation-Competitive (Coopetitive) approach that allows coordinated work among the Secretary of Public Education (SEP), the Autonomous University of Querétaro (UAQ) and government funds from National Council for Science and Technology (CONACYT) or some other international organizations. To work on an overall knowledge transfer strategy with e-learning over the Cloud, where experts in junior high and high school education, working in multidisciplinary teams, perform analysis, evaluation, design, production, validation and knowledge transfer at large scale using a Cloud Computing platform. Allowing teachers and students to have all the information required to ensure a homologated nationally knowledge of topics such as mathematics, statistics, chemistry, history, ethics, civism, etc. This work will start with a pilot test in Spanish and initially in two regional dialects Otomí and Náhuatl. Otomí has more than 285,000 speaking indigenes in Queretaro and Mexico´s central region. Náhuatl is number one indigenous dialect spoken in Mexico with more than 1,550,000 indigenes. The phase one of the project takes into account negotiations with indigenous tribes from different regions, and the Information and Communication technologies to deliver the knowledge to the indigenous schools in their native dialect. The methodology includes the following main milestones: Identification of the indigenous areas where Otomí and Náhuatl are the spoken dialects, research with the SEP the location of actual indigenous schools, analysis and inventory or current schools conditions, negotiation with tribe chiefs, analysis of the technological communication requirements to reach the indigenous communities, identification and inventory of local teachers technology knowledge, selection of a pilot topic, analysis of actual student competence with traditional education system, identification of local translators, design of the e-learning platform, design of the multimedia resources and storage strategy for “Cloud Computing”, translation of the topic to both dialects, Indigenous teachers training, pilot test, course release, project follow up, analysis of student requirements for the new technological platform, definition of a new and improved proposal with greater reach in topics and regions. Importance of phase one of the project is multiple, it includes the proposal of a working technological scheme, focusing in the cultural impact in Mexico so that indigenous tribes can improve their knowledge about new forms of crop improvement, home storage technologies, proven home remedies for common diseases, ways of preparing foods containing major nutrients, disclose strengths and weaknesses of each region, communicating through cloud computing platforms offering regional products and opening communication spaces for inter-indigenous cultural exchange.

Keywords: Mexicans indigenous tribes, education, knowledge transfer, cloud computing, otomi, Náhuatl, language

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Authors: Abdul Wohab

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Context: The role of religion in the transformation of Bangladesh society has been significant since 1975. There has been a rise in religious presence, particularly Islam, in both private and public spheres supported by the state apparatuses. In 2009, a 'secular' political party came into power for the second time since independence and initiated the modernization of religious education systems. This research focuses on the transformation observed among the educated middle class who now prefer their children to attend modern, English medium madrasas that offer both religion-based and secular education. Research Aim: This research aims to investigate two main questions: a) what motivates the educated middle class to send their children to madrasa education? b) To what extent can it be argued that Bangladeshi society is transforming from its secular nature to being more religious?Methodology: The research applies a combination of primary and secondary methods. Case studies serve as the primary method, allowing for an in-depth exploration of the motivations of the educated middle class. The secondary method involves analyzing published news articles, op-eds, and websites related to madrasa education, as well as studying the reading syllabus of Aliya and Qwami madrasas in Bangladesh. Findings: Preliminary findings indicate that the educated middle class chooses madrasa education for reasons such as remembering and praying for their departed relatives, keeping their children away from substance abuse, fostering moral and ethical values, and instilling respect for seniors and relatives. The research also reveals that religious education is believed to help children remain morally correct according to the Quran and Hadith. Additionally, the establishment of madrasas in Bangladesh is attributed to economic factors, with demand and supply mechanisms playing a significant role. Furthermore, the findings suggest that government-run primary education institutions in rural areas face more challenges in enrollment compared to religious educational institutions like madrasas. Theoretical Importance: This research contributes to the understanding of societal transformation and the role of religion in this process. By examining the case of Bangladesh, it provides insights into how religion influences education choices and societal values. Data Collection and Analysis Procedures: Data for this research is collected through case studies, including interviews and observations of educated middle-class families who send their children to madrasas. In addition, analysis is conducted on relevant published materials such as news articles, op-eds, and websites. The reading syllabus of Aliya and Qwami madrasas is also analyzed to gain a comprehensive understanding of the education system. Questions Addressed: The research addresses two questions: a) what motivates the educated middle class to choose madrasa education for their children? b) To what extent can it be argued that Bangladeshi society is transforming from its secular nature to being more religious?Conclusion: The preliminary findings of this research highlight the motivations of the educated middle class in opting for madrasa education, including the desire to maintain religious traditions, promote moral values, and provide a strong foundation for their children. It also suggests that Bangladeshi society is experiencing a transformation towards a more religious orientation. This research contributes to the understanding of societal changes and the role of religion within Bangladesh, shedding light on the complex dynamics between religion and education.

Keywords: madrasa education, transformation, Bangladesh, religion and society, education

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Authors: Glykeria A. Visvini, George Ν. Mathioudakis, Amaia Soto Beobide, George A. Voyiatzis

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Polymer nanocomposites are materials in which a polymer matrix is reinforced with nanoscale inclusions, such as nanoparticles, nanoplates, or nanofibers. These nanoscale inclusions can significantly enhance the mechanical, thermal, electrical, and other properties of the polymer matrix, making them attractive for a wide range of industrial applications. These properties can be tailored by adjusting the type and the concentration of the nanoinclusions, which provides a high degree of flexibility in their design and development. An important property that polymeric membranes can exhibit is water vapor permeability (WVP). This can be accomplished by various methods, including the incorporation of micro/nano-fillers into the polymer matrix. In this way, a micro/nano-pore network can be formed, allowing water vapor to permeate through the membrane. At the same time, the membrane can be stretched uni- or bi-axially, creating aligned or cross-linked micropores in the composite, respectively, which can also increase the WVP. Nowadays, in industry, stretched films reinforced with CaCO3 develop micro-porosity sufficient to give them breathability characteristics. Carbon-based nanomaterials, such as graphene oxide (GO), are tentatively expected to be able to effectively improve the WVP of corresponding composite polymer films. The presence in the GO structure of various functional oxidizing groups enhances its ability to attract and channel water molecules, exploiting the unique large surface area of graphene that allows the rapid transport of water molecules. Polypropylene (PP) is widely used in various industrial applications due to its desirable properties, including good chemical resistance, excellent thermal stability, low cost, and easy processability. The specific properties of PP are highly influenced by its crystalline behavior, which is determined by its processing conditions. The development of the β-crystalline phase in PP, in combination with stretching, is anticipating improving the microporosity of the polymer matrix, thereby enhancing its WVP. The aim of present study is to create breathable PP composite membranes using carbon-based nanomaterials, such as graphene oxide (GO), reduced graphene oxide (rGO), and graphene nanoplatelets (GNPs). Unlike traditional methods that rely on the drawing process to enhance the WVP of PP, this study intents to develop a low-cost approach using melt mixing with β-nucleating agents and carbon fillers to create highly breathable PP composite membranes. The study aims to investigate how the concentration of these additives affects the water vapor transport properties of the resulting PP films/membranes. The presence of β-nucleating agents and carbon fillers is expected to enhance β-phase growth in PP, while an alternation between β- and α-phase is expected to lead to improved microporosity and WVP. Our ambition is to develop highly breathable PP composite films with superior performance and at a lower cost compared to the benchmark. Acknowledgment: This research has been co‐financed by the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation, under the call «Special Actions "AQUACULTURE"-"INDUSTRIAL MATERIALS"-"OPEN INNOVATION IN CULTURE"» (project code: Τ6YBP-00337)

Keywords: carbon based nanomaterials, nanocomposites, nucleating agent, polypropylene, water vapor permeability

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Authors: Artem Kim, Clara Savary, Christele Dubourg, Wilfrid Carre, Houda Hamdi-Roze, Valerie Dupé, Sylvie Odent, Marie De Tayrac, Veronique David

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Holoprosencephaly (HPE) is a rare congenital brain malformation resulting from the incomplete separation of the two cerebral hemispheres. It is characterized by a wide phenotypic spectrum and a high degree of locus heterogeneity. Genetic defects in 16 genes have already been implicated in HPE, but account for only 30% of cases, suggesting that a large part of genetic factors remains to be discovered. HPE has been recently redefined as a complex multigenic disorder, requiring the joint effect of multiple mutational events in genes belonging to one or several developmental pathways. The onset of HPE may result from accumulation of the effects of multiple rare variants in functionally-related genes, each conferring a moderate increase in the risk of HPE onset. In order to decipher the genetic basis of HPE, unconventional patterns of inheritance involving multiple genetic factors need to be considered. The primary objective of this study was to uncover possible disease causing combinations of multiple rare variants underlying HPE by performing trio-based Whole Exome Sequencing (WES) of familial cases where no molecular diagnosis could be established. 39 families were selected with no fully-penetrant causal mutation in known HPE gene, no chromosomic aberrations/copy number variants and without any implication of environmental factors. As the main challenge was to identify disease-related variants among a large number of nonpathogenic polymorphisms detected by WES classical scheme, a novel variant prioritization approach was established. It combined WES filtering with complementary gene-level approaches: transcriptome-driven (RNA-Seq data) and clinically-driven (public clinical data) strategies. Briefly, a filtering approach was performed to select variants compatible with disease segregation, population frequency and pathogenicity prediction to identify an exhaustive list of rare deleterious variants. The exome search space was then reduced by restricting the analysis to candidate genes identified by either transcriptome-driven strategy (genes sharing highly similar expression patterns with known HPE genes during cerebral development) or clinically-driven strategy (genes associated to phenotypes of interest overlapping with HPE). Deeper analyses of candidate variants were then performed on a family-by-family basis. These included the exploration of clinical information, expression studies, variant characteristics, recurrence of mutated genes and available biological knowledge. A novel bioinformatics pipeline was designed. Applied to the 39 families, this final integrated workflow identified an average of 11 candidate variants per family. Most of candidate variants were inherited from asymptomatic parents suggesting a multigenic inheritance pattern requiring the association of multiple mutational events. The manual analysis highlighted 5 new strong HPE candidate genes showing recurrences in distinct families. Functional validations of these genes are foreseen.

Keywords: complex genetic disorder, holoprosencephaly, multiple rare variants, whole exome sequencing

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Authors: Chris Fersterer, Col Fay, Tobias Danielmeier, Kat Achterberg, Scott Willis

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New Zealand, an island nation, has an extensive coastline peppered with small communities of iconic buildings known as Bachs. Post WWII, these modest buildings were constructed by their owners as retreats and generally were small, low cost, often using recycled material and often they fell below current acceptable building standards. In the latter part of the 20^th century, real estate prices in many of these communities remained low and these areas became permanent residences for people attracted to this affordable lifestyle choice. The Blueskin Resilient Communities Trust (BRCT) is an organisation that recognises the vulnerability of communities in low lying settlements as now being prone to increased flood threat brought about by climate change and sea level rise. Some of the inhabitants of Blueskin Bay, Otago, NZ have already found their properties to be un-insurable because of increased frequency of flood events and property values have slumped accordingly. Territorial authorities also acknowledge this increased risk and have created additional compliance measures for new buildings that are less than 2 m above tidal peaks. Community resilience becomes an additional concern where inhabitants are attracted to a lifestyle associated with a specific location and its people when this lifestyle is unable to be met in a suburban or city context. Traditional models of social housing fail to provide the sense of community connectedness and identity enjoyed by the current residents of Blueskin Bay. BRCT have partnered with the Otago Polytechnic Design School to design a new form of community housing that can react to this environmental change. It is a longitudinal project incorporating participatory approaches as a means of getting people ‘on board’, to understand complex systems and co-develop solutions. In the first period, they are seeking industry support and funding to develop a transportable and fully self-contained housing model that exploits current technologies. BRCT also hope that the building will become an educational tool to highlight climate change issues facing us today. This paper uses the Climate Safe House (CSH) as a case study for education in architectural sustainability through experiential learning offered as part of the Otago Polytechnics Bachelor of Design. Students engage with the project with research methodologies, including site surveys, resident interviews, data sourced from government agencies and physical modelling. The process involves collaboration across design disciplines including product and interior design but also includes connections with industry, both within the education institution and stakeholder industries introduced through BRCT. This project offers a rich learning environment where students become engaged through project based learning within a community of practice, including architecture, construction, energy and other related fields. The design outcomes are expressed in a series of public exhibitions and forums where community input is sought in a truly participatory process.

Keywords: community resilience, problem based learning, project based learning, case study

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

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

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

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Authors: Miguel García-Ferrús, Yolanda Domínguez, M Angeles Castillo, M Antonia Ferrús, Ana Jiménez-Belenguer

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Antibiotic resistance is a growing public health concern worldwide, and it is now regarded as a critical issue within the "One Health" approach that affects human and animal health, agriculture, and environmental waste management. This concept focuses on the interconnected nature of human, animal and environmental health, and WHO highlights zoonotic diseases, food safety, and antimicrobial resistance as three particularly relevant areas for this framework. Fresh vegetables are garnering attention in the food chain due to the presence of pathogens and because they can act as a reservoir for Antibiotic Resistance Bacteria (ARB) and Antibiotic Resistance Genes (ARG). These fresh products are frequently consumed raw, thereby contributing to the spread and transmission of antibiotic resistance. Therefore, the aim of this research was to study the microbiological quality, the prevalence of ARB, and their role in the dissemination of ARG in fresh vegetables intended for human consumption. For this purpose, 102 samples of fresh vegetables (30 lettuce, 30 cabbage, 18 strawberries and 24 spinach) from different retail establishments in Valencia (Spain) have been analyzed to determine their microbiological quality and their role in spreading ARB and ARG. The samples were collected and examined according to standardized methods for total viable bacteria, coliforms, Shiga toxin-producing Escherichia coli (STEC), Listeria monocytogenes and Salmonella spp. Isolation was made in culture media supplemented with antibiotics (cefotaxime and meropenem). A total of 239 strains resistant to beta-lactam antibiotics (Third-Generation Cephalosporins and Carbapenems) were isolated. Thirty Gram-negative isolates were selected and biochemically identified or partial sequencing of 16S rDNA. Their sensitivity to 12 antibiotic discs was determined using the Kirby-Bauer disc diffusion technique to different therapeutic groups. To determine the presence of ARG, PCR assays for the direct sample and selected isolate DNA were performed for main expanded spectrum beta-lactamase (ESBL)-, carbapenemase-encoding genes and plasmid-mediated quinolone resistance genes. From the total samples, 68% (24/24 spinach, 28/30 lettuce and 17/30 cabbage) showed total viable bacteria levels over the accepted standard 10(2)-10(5) cfu/g range; and 48% (24/24 spinach, 19/30 lettuce and 6/30) showed coliforms levels over the accepted standard 10(2)-10(4) cfu/g range. In 9 samples (3/24 spinach, 3/30 lettuce, 3/30 cabbage; 9/102 (9%)) E. coli levels were higher than the standard 10(3) cfu/g limit. Listeria monocytogenes, Salmonella and STEC have not been detected. Six different bacteria species were isolated from samples. Stenotrophomonas maltophilia (64%) was the prevalent species, followed by Acinetobacter pitii (14%) and Burkholderia cepacia (7%). All the isolates were resistant to at least one tested antibiotic, including meropenem (85%) and ceftazidime (46%). Of the total isolates, 86% were multidrug-resistant and 68% were ESBL productors. Results of PCR showed the presence of resistance genes to beta-lactams blaTEM (4%) and blaCMY-2 (4%), to carbapenemes blaOXA-48 (25%), blaVIM (7%), blaIMP (21%) and blaKPC (32%), and to quinolones QnrA (7%), QnrB (11%) and QnrS (18%). Thus, fresh vegetables harboring ARB and ARG constitute a potential risk to consumers. Further studies must be done to detect ARG and how they propagate in non-medical environments.

Keywords: ESBL, β-lactams, resistances, fresh vegetables.

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Authors: Chandu Rathnayake, Isuri Anuradha

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Early detection and accurate diagnosis of lung diseases play a crucial role in improving patient prognosis. However, conventional diagnostic methods heavily rely on subjective symptom assessments and medical imaging, often causing delays in diagnosis and treatment. To overcome this challenge, we propose a novel lung disease prediction system that integrates patient symptoms and X-ray images to provide a comprehensive and reliable diagnosis.In this project, develop a mobile application specifically designed for detecting lung diseases. Our application leverages both patient symptoms and X-ray images to facilitate diagnosis. By combining these two sources of information, our application delivers a more accurate and comprehensive assessment of the patient's condition, minimizing the risk of misdiagnosis. Our primary aim is to create a user-friendly and accessible tool, particularly important given the current circumstances where many patients face limitations in visiting healthcare facilities. To achieve this, we employ several state-of-the-art algorithms. Firstly, the Decision Tree algorithm is utilized for efficient symptom-based classification. It analyzes patient symptoms and creates a tree-like model to predict the presence of specific lung diseases. Secondly, we employ the Random Forest algorithm, which enhances predictive power by aggregating multiple decision trees. This ensemble technique improves the accuracy and robustness of the diagnosis. Furthermore, we incorporate a deep learning model using Convolutional Neural Network (CNN) with the RestNet50 pre-trained model. CNNs are well-suited for image analysis and feature extraction. By training CNN on a large dataset of X-ray images, it learns to identify patterns and features indicative of lung diseases. The RestNet50 architecture, known for its excellent performance in image recognition tasks, enhances the efficiency and accuracy of our deep learning model. By combining the outputs of the decision tree-based algorithms and the deep learning model, our mobile application generates a comprehensive lung disease prediction. The application provides users with an intuitive interface to input their symptoms and upload X-ray images for analysis. The prediction generated by the system offers valuable insights into the likelihood of various lung diseases, enabling individuals to take appropriate actions and seek timely medical attention. Our proposed mobile application has significant potential to address the rising prevalence of lung diseases, particularly among young individuals with smoking addictions. By providing a quick and user-friendly approach to assessing lung health, our application empowers individuals to monitor their well-being conveniently. This solution also offers immense value in the context of limited access to healthcare facilities, enabling timely detection and intervention. In conclusion, our research presents a comprehensive lung disease prediction system that combines patient symptoms and X-ray images using advanced algorithms. By developing a mobile application, we provide an accessible tool for individuals to assess their lung health conveniently. This solution has the potential to make a significant impact on the early detection and management of lung diseases, benefiting both patients and healthcare providers.

Keywords: CNN, random forest, decision tree, machine learning, deep learning

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Authors: Iryna P. Dzieciuch, Michael D. Putman

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Humidity is known to degrade Navy ship electronic equipment, especially in hot moist environments. If left untreated, it can cause significant and permanent damage. Even rigorous inspection and frequent clean-up would not prevent further equipment contamination and degradation because of the constant presence of favorable growth conditions for many microorganisms. Generally, relative humidity levels of less than 60% will inhibit corrosion in electronic equipment, but because NAVY electronics often operate in hot and humid environments, prevention via dehumidification is not always possible. Currently, there is no defined research that fully describes key mechanisms which cause electronics and its coating degradation. The corrosive action of most bacteria is mainly developed through (i) mycelium adherence to the metal plates, (ii) facilitation the formation of pitting areas, (iii) production of organic acids such as citric, iso-citric, cis-aconitic, alpha-ketoglutaric, which are corrosive to electronic equipment and its components. Our approach studies corrosive action in electronic equipment: circuit-board, wires and connections that are exposed in the humid environment that gets worse during condensation. In our new approach the technical task is built on work with the bacterial communities in public areas, bacterial genetics, bioinformatics, biostatistics and Scanning Electron Microscopy (SEM) of corroded circuit boards. Based on these methods, we collect and examine environmental samples from biofilms of the corroded and non-corroded sites, where bacterial contamination of electronic equipment, such as machine racks and shore boats, is an ongoing concern. Sample collection and sample analysis is focused on addressing the key questions identified above through the following tasks: laboratory sample processing and evaluation under scanning electron microscopy, initial sequencing and data evaluation; bioinformatics and data analysis. Preliminary results from scanning electron microscopy (SEM) have revealed that metal particulates and alloys in corroded samples consists mostly of Tin ( < 40%), Silicon ( < 4%), Sulfur ( < 1%), Aluminum ( < 2%), Magnesium ( < 2%), Copper ( < 1%), Bromine ( < 2%), Barium ( <1%) and Iron ( < 2%) elements. We have also performed X 12000 magnification of the same sites and that proved existence of undisrupted biofilm organelles and crystal structures. Non-corrosion sites have revealed high presence of copper ( < 47%); other metals remain at the comparable level as on the samples with corrosion. We have performed X 1000 magnification on the non-corroded at the sites and have documented formation of copper crystals. The next step of this study, is to perform metagenomics sequencing at all sites and to compare bacterial composition present in the environment. While copper is nontoxic to the living organisms, the process of bacterial adhesion creates acidic environment by releasing citric, iso-citric, cis-aconitic, alpha-ketoglutaric acidics, which in turn release copper ions Cu++, which that are highly toxic to the bacteria and higher order living organisms. This phenomenon, might explain natural “antibiotic” properties that are lacking in elements such as tin. To prove or deny this hypothesis we will use next - generation sequencing (NGS) methods to investigate types and growth cycles of bacteria that from bacterial biofilm the on corrosive and non-corrosive samples.

Keywords: bacteria, biofilm, circuit board, copper, corrosion, electronic equipment, organic acids, tin

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Authors: Lakshmi Rao Kandukuri, Mamata Deenadayal, Suma Prasad, Bipin Sethi, Srinadh Buragadda, Lalji Singh

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Worldwide; at least 7.6 million children are born annually with severe genetic or congenital malformations and among them 90% of these are born in mid and low-income countries. Precise prevalence data are difficult to collect, especially in developing countries, owing to the great diversity of conditions and also because many cases remain undiagnosed. The genetic and congenital disorder is the second most common cause of infant and childhood mortality and occurs with a prevalence of 25-60 per 1000 births. The higher prevalence of genetic diseases in a particular community may, however, be due to some social or cultural factors. Such factors include the tradition of consanguineous marriage, which results in a higher rate of autosomal recessive conditions including congenital malformations, stillbirths, or mental retardation. Genetic diseases can vary in severity, from being fatal before birth to requiring continuous management; their onset covers all life stages from infancy to old age. Those presenting at birth are particularly burdensome and may cause early death or life-long chronic morbidity. Genetic testing for several genetic diseases identifies changes in chromosomes, genes, or proteins. The results of a genetic test can confirm or rule out a suspected genetic condition or help determine a person's chance of developing or passing on a genetic disorder. Several hundred genetic tests are currently in use and more are being developed. Chromosomal abnormalities are the major cause of human suffering, which are implicated in mental retardation, congenital malformations, dysmorphic features, primary and secondary amenorrhea, reproductive wastage, infertility neoplastic diseases. Cytogenetic evaluation of patients is helpful in the counselling and management of affected individuals and families. We present here especially chromosomal abnormalities which form a major part of genetic disease burden in India. Different programmes on chromosome research and human reproductive genetics primarily relate to infertility since this is a major public health problem in our country, affecting 10-15 percent of couples. Prenatal diagnosis of chromosomal abnormalities in high-risk pregnancies helps in detecting chromosomally abnormal foetuses. Such couples are counselled regarding the continuation of pregnancy. In addition to the basic research, the team is providing chromosome diagnostic services that include conventional and advanced techniques for identifying various genetic defects. Other than routine chromosome diagnosis for infertility, also include patients with short stature, hypogonadism, undescended testis, microcephaly, delayed developmental milestones, familial, and isolated mental retardation, and cerebral palsy. Thus, chromosome diagnostics has found its applicability not only in disease prevention and management but also in guiding the clinicians in certain aspects of treatment. It would be appropriate to affirm that chromosomes are the images of life and they unequivocally mirror the states of human health. The importance of genetic counseling is increasing with the advancement in the field of genetics. The genetic counseling can help families to cope with emotional, psychological, and medical consequences of genetic diseases.

Keywords: India, chromosome abnormalities, genetic disorders, cytogenetic study

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