Search results for: emergency department

Authors: Abdullah Al Mohiuddin

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Bangladesh is one of the poorest countries in the world, and ranks low on almost all measures of economic development, thus leaving the population extremely vulnerable to natural disasters and climate events. 20% of GDP come from agriculture but more than 60% of the population relies on agriculture as their main source of income making the entire economy vulnerable to climate change and natural disasters. High population density exacerbates the exposure to and effect of climate events, and increases the levels of vulnerability, as does the poor institutional development of the country. The most vulnerable sectors to climate change impacts in Bangladesh are agriculture, coastal zones, water resources, forestry, fishery, health, biomass, and energy. High temperatures, heavy rainfall, high humidity and fairly marked seasonal variations characterize the climate in Bangladesh: Mild winter, hot humid summer and humid, warm rainy monsoon. Much of the country is flooded during the summer monsoon. The Department of Environment (DOE) under the Ministry of Environment and Forestry (MoEF) is the focal point for the United Nations Framework Convention on Climate Change (UNFCCC) and coordinates climate related activities in the country. Recently, a Climate Change Cell (CCC) has been established to address several issues including adaptation to climate change. The climate change focus started with The National Environmental Management Action Plan (NEMAP) which was prepared in 1995 in order to initiate the process to address environmental and climate change issues as long-term environmental problems for Bangladesh. Bangladesh was one of the first countries to finalise a NAPA (Preparation of a National Adaptation Plan of Action) which addresses climate change issues. The NAPA was completed in 2005, and is the first official initiative for mainstreaming adaptation to national policies and actions to cope with climate change and vulnerability. The NAPA suggests a number of adaptation strategies, for example: - Providing drinking water to coastal communities to fight the enhanced salinity caused by sea level rise, - Integrating climate change in planning and design of infrastructure, - Including climate change issues in education, - Supporting adaptation of agricultural systems to new weather extremes, - Mainstreaming CCA into policies and programmes in different sectors, e.g. disaster management, water and health, - Dissemination of CCA information and awareness raising on enhanced climate disasters, especially in vulnerable communities. Bangladesh has geared up its environment conservation steps to save the world’s poorest countries from the adverse effects of global warming. Now it is turning towards green economy policies to save the degrading ecosystem. Bangladesh is a developing country and always fights against Natural Disaster. At the same time we also fight for establishing ecological environment through promoting Green Economy/Energy by Youth Networking. ANTAR is coordinating a big Youth Network in the southern part of Bangladesh where 30 Youth group involved. It can be explained as the economic development based on sustainable development which generates growth and improvement in human’s lives while significantly reducing environmental risks and ecological scarcities. Green economy in Bangladesh promotes three bottom lines – sustaining economic, environment and social well-being.

Keywords: resilience, networking, mobilizing, resource

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Authors: Kevin F. Hsu, Alvin Chua, Sarah X. Lin

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As a multilingual society, Singaporean names for different parts of the city have changed over time. Residents included Indigenous Malays, dialect-speakers from China, European settler-colonists, and Tamil-speakers from South India. Each group would name locations in their own languages. Today, as ancestral tongues are increasingly supplanted by English, contemporary Singaporeans’ understanding of once-common place names is disappearing. After demolition or redevelopment, some urban places will only exist in archival records or in human memory. United Nations conferences on the standardization of geographic names have called attention to how place names relate to identity, well-being, and a sense of belonging. The Singapore Place-Naming Project responds to these imperatives by capturing past and present place names through digitizing historical maps, mining archival records, and applying selective crowd-sourcing to trace the evolution of place names throughout the city. The project ensures that both formal and vernacular geographical names remain accessible to historians, city planners, and the public. The project is compiling a gazetteer, a geospatial archive of placenames, with streets, buildings, landmarks, and other points of interest (POI) appearing in the historic maps and planning documents of Singapore, currently held by the National Archives of Singapore, the National Library Board, university departments, and the Urban Redevelopment Authority. To create a spatial layer of information, the project links each place name to either a geo-referenced point, line segment, or polygon, along with the original source material in which the name appears. This record is supplemented by crowd-sourced contributions from civil service officers and heritage specialists, drawing from their collective memory to (1) define geospatial boundaries of historic places that appear in past documents, but maybe unfamiliar to users today, and (2) identify and record vernacular place names not captured in formal planning documents. An intuitive interface allows participants to demarcate feature classes, vernacular phrasings, time periods, and other knowledge related to historical or forgotten spaces. Participants are stratified into age bands and ethnicity to improve representativeness. Future iterations could allow additional public contributions. Names reveal meanings that communities assign to each place. While existing historical maps of Singapore allow users to toggle between present-day and historical raster files, this project goes a step further by adding layers of social understanding and planning documents. Tracking place names illuminates linguistic, cultural, commercial, and demographic shifts in Singapore, in the context of transformations of the urban environment. The project also demonstrates how a moderated, selectively crowd-sourced effort can solicit useful geospatial data at scale, sourced from different generations, and at higher granularity than traditional surveys, while mitigating negative impacts of unmoderated crowd-sourcing. Stakeholder agencies believe the project will achieve several objectives, including Supporting heritage conservation and public education; Safeguarding intangible cultural heritage; Providing historical context for street, place or development-renaming requests; Enhancing place-making with deeper historical knowledge; Facilitating emergency and social services by tagging legal addresses to vernacular place names; Encouraging public engagement with heritage by eliciting multi-stakeholder input.

Keywords: collective memory, crowd-sourced, digital heritage, geospatial, geographical names, linguistic heritage, place-naming, Singapore, Southeast Asia

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Authors: Bailey Houghtaling, Sarah Misyak

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Food access; the availability, affordability, convenience, and desirability of food and beverage products within communities, is influential on consumers’ purchasing and consumption decisions. These variables may contribute to lower dietary quality scores and a higher obesity prevalence documented among rural and disadvantaged populations in the United States (U.S.). Current research assessing linkages between food access and obesity outcomes has primarily focused on distance to a traditional grocery/supermarket store as a measure of optimality. However, low-income consumers especially, including U.S. Department of Agriculture’s Supplemental Nutrition Assistance Program (SNAP) participants, seem to utilize non-traditional food store formats with greater frequency for household dietary needs. Non-traditional formats have been associated with less nutritious food and beverage options and consumer purchases that are high in saturated fats, added sugars, and sodium. Authors’ formative research indicated differences by U.S. region and rurality in the distribution of traditional and non-traditional SNAP-authorized food store formats. Therefore, using Virginia as a case study, the purpose of this research was to determine if a relationship between store format, rurality, and obesity exists. This research applied SNAP-authorized food store data (food access points for SNAP as well as non-SNAP consumers) and obesity prevalence data by Virginia county using publicly available databases: (1) SNAP Retailer Locator, and; (2) U.S. County Health Rankings. The alpha level was set a priori at 0.05. All Virginia SNAP-authorized stores (n=6,461) were coded by format – grocery, drug, mass merchandiser, club, convenience, dollar, supercenter, specialty, farmers market, independent grocer, and non-food store. Simple linear regression was applied primarily to assess the relationship between store format and obesity. Thereafter, multiple variables were added to the regression to account for potential moderating relationships (e.g., county income, rurality). Convenience, dollar, non-food or restaurant, mass merchandiser, farmers market, and independent grocer formats were significantly, positively related to obesity prevalence. Upon controlling for urban-rural status and income, results indicated the following formats to be significantly related to county obesity prevalence with a small, positive effect: convenience (p=0.010), accounting for 0.3% of the variance in obesity prevalence; dollar (p=0.005; 0.5% of the variance), and; non-food (p=0.030; 1.3% of the variance) formats. These results align with current literature on consumer behavior at non-traditional formats. For example, consumers’ food and beverage purchases at convenience and dollar stores are documented to be high in saturated fats, added sugars, and sodium. Further, non-food stores (i.e., quick-serve restaurants) often contribute to a large portion of U.S. consumers’ dietary intake and thus poor dietary quality scores. Current food access research investigates grocery/supermarket access and obesity outcomes. These results suggest more research is needed that focuses on non-traditional food store formats. Nutrition interventions within convenience, dollar, and non-food stores, for example, that aim to enhance not only healthy food access but the affordability, convenience, and desirability of nutritious food and beverage options may impact obesity rates in Virginia. More research is warranted utilizing the presented investigative framework in other U.S. and global regions to explore the role and the potential of non-traditional food store formats to prevent and reduce obesity.

Keywords: food access, food store format, non-traditional food stores, obesity prevalence

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Authors: Hamda Ajmal, Karen Young, Ruth Melia, John Bogue, Mary O'Sullivan, Jim Duggan, Hannah Wood

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The Covid-19 pandemic led to a range of public health mitigation strategies in order to suppress the SARS-CoV-2 virus. The drastic changes in everyday life due to lockdowns had the potential for a significant negative impact on public mental health, and a key public health goal is to now assess the evidence from available Irish datasets to provide useful insights on this issue. Text-50808 is an online text-based mental health support service, established in Ireland in 2020, and can provide a measure of revealed distress and mental health concerns across the population. The aim of this study is to explore statistical associations between public mental health in Ireland and the Covid-19 pandemic. Uniquely, this study combines two measures of emotional wellbeing in Ireland: (1) weekly text volume at Text-50808, and (2) emotional wellbeing indicators reported by respondents of the Amárach public opinion survey, carried out on behalf of the Department of Health, Ireland. For this analysis, a multivariate graphical exploratory data analysis (EDA) was performed on the Text-50808 dataset dated from 15th June 2020 to 30th June 2021. This was followed by time-series analysis of key mental health indicators including: (1) the percentage of daily/weekly texts at Text-50808 that mention Covid-19 related issues; (2) the weekly percentage of people experiencing anxiety, boredom, enjoyment, happiness, worry, fear and stress in Amárach survey; and Covid-19 related factors: (3) daily new Covid-19 case numbers; (4) daily stringency index capturing the effect of government non-pharmaceutical interventions (NPIs) in Ireland. The cross-correlation function was applied to measure the relationship between the different time series. EDA of the Text-50808 dataset reveals significant peaks in the volume of texts on days prior to level 3 lockdown and level 5 lockdown in October 2020, and full level 5 lockdown in December 2020. A significantly high positive correlation was observed between the percentage of texts at Text-50808 that reported Covid-19 related issues and the percentage of respondents experiencing anxiety, worry and boredom (at a lag of 1 week) in Amárach survey data. There is a significant negative correlation between percentage of texts with Covid-19 related issues and percentage of respondents experiencing happiness in Amárach survey. Daily percentage of texts at Text-50808 that reported Covid-19 related issues to have a weak positive correlation with daily new Covid-19 cases in Ireland at a lag of 10 days and with daily stringency index of NPIs in Ireland at a lag of 2 days. The sudden peaks in text volume at Text-50808 immediately prior to new restrictions in Ireland indicate an association between a rise in mental health concerns following the announcement of new restrictions. There is also a high correlation between emotional wellbeing variables in the Amárach dataset and the number of weekly texts at Text-50808, and this confirms that Text-50808 reflects overall public sentiment. This analysis confirms the benefits of the texting service as a community surveillance tool for mental health in the population. This initial EDA will be extended to use multivariate modeling to predict the effect of additional Covid-19 related factors on public mental health in Ireland.

Keywords: COVID-19 pandemic, data analysis, digital health, mental health, public health, digital health

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Authors: Aparajita Bhattacharya, Mousumi Dutta, Zakir Husain, Dionne Sequeira, Asima Mukhopadhyay

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Background: Tata Medical Centre (TMC), Kolkata is a major cancer referral centre in Eastern India and neighbouring countries providing state of the art facilities; however, it is a non-profit organisation with patients requiring to pay at subsidised rates. Although a system for social assessment and applying for governmental/ non-governmental (NGO) funds is in place, access is challenging. Amongst gynaecological cancers (GC), ovarian cancer (OC) is associated with the highest treatment cost; majority of which is required at the beginning when complex surgery is performed and funding arrangements cannot be made in time. We therefore appointed a dedicated Medical Social Worker (MSW) in 2016, supported by NGO for GC patients in order to assist patients/family members to access/avail these funds more readily and assist in economic evaluation for both direct and opportunity costs. Objectives: To reflect on our experience and challenges in collecting data on economic evaluation of cancer patients and compare success rates in achieving fund mobilization after introduction of MSW. Methods: A Retrospective survey. Patients with OC and their relatives were seen by the MSW during the initial outpatients department visit and followed though till discharge from the hospital and during follow-up visits. Assistance was provided in preparing the essential documents/paperwork/contacts for the funding agencies including both governmental (Chief-Minister/Prime-Minister/President) and NGO sources. In addition, a detailed questionnaire was filled up for economic assessment of direct/opportunity costs during the entire treatment and 12 months follow up period which forms a part of the study called HEPTROC (Health economic evaluation of primary treatment for ovarian cancer) developed in collaboration with economics departments of Universities. Results: In 2015, 102 patients were operated for OC; only 16 patients (15.68 %) had availed funding of a total sum of INR 1640000 through the hospital system for social assessment. Following challenges were faced by majority of the relatives: 1. Gathering important documents/proper contact details for governmental funding bodies and difficulty in following up the current status 3. Late arrival of funds. In contrast in 2016, 104 OC patients underwent surgery; the direct cost of treatment was significantly higher (median, INR 300000- 400000) compared to other GCs (n=274). 98/104 (94.23%) OC patients could be helped to apply for funds and 90/104(86.56%) patients received funding amounting to a total of INR 10897000. There has been a tenfold increase in funds mobilized in 2016 after the introduction of dedicated MSW in GC. So far, in 2017 (till June), 46/54(85.18%) OC patients applied for funds and 37/54(68.51%) patients have received funding. In a qualitative survey, all patients appreciated the role of the MSW who subsequently became the key worker for patient follow up and the chief portal for patient reported outcome monitoring. Data collection quality for the HEPTROC study was improved when questionnaires were administered by the MSW compared to researchers. Conclusion: Introduction of cancer specific MSW can expedite the availability of funds required for cancer patients and it can positively impact on patient satisfaction and outcome reporting. The economic assessment will influence fund allocation and decision for policymaking in ovarian cancer. Acknowledgement: Jivdaya Foundation Dallas, Texas.

Keywords: economic evaluation, funding, medical social worker, ovarian cancer

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Authors: Bailey Houghtaling, Elena Serrano, Vivica Kraak, Samantha Harden, George Davis, Sarah Misyak

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United States (U.S.) Department of Agriculture Supplemental Nutrition Assistance Program (SNAP) participants are low-income Americans receiving federal dollars for supplemental food and beverage purchases. Participants use a variety of (traditional/non-traditional) SNAP-authorized stores for household dietary purchases - also representing food access points for all Americans. Importantly consumers' food and beverage purchases from non-traditional store formats tend to be higher in saturated fats, added sugars, and sodium when compared to purchases from traditional (e.g., grocery/supermarket) formats. Overconsumption of energy-dense and low-nutrient food and beverage products contribute to high obesity rates and adverse health outcomes that differ in severity among urban/rural U.S. locations and high/low-income populations. Little is known about the SNAP-authorized food store format landscape nationally, regionally, or by urban-rural status, as traditional formats are currently used as the gold standard in food access research. This research utilized publicly available U.S. databases to fill this large literature gap and to provide insight into modes of food access for vulnerable U.S. populations: (1) SNAP Retailer Locator which provides a list of all authorized food stores in the U.S., and; (2) Rural-Urban Continuum Codes (RUCC) that categorize U.S. counties as urban (RUCC 1-3) or rural (RUCC 4-9). Frequencies were determined for the highest occurring food store formats nationally and within two regionally diverse U.S. states – Virginia in the east and California in the west. Store format codes were assigned (e.g., grocery, drug, convenience, mass merchandiser, supercenter, dollar, club, or other). RUCC was applied to investigate state-level differences in urbanity-rurality regarding prevalent food store formats and Chi Square test of independence was used to determine if food store format distributions significantly (p < 0.05) differed by region or rurality. The resulting research sample that represented highly prevalent SNAP-authorized food stores nationally included 41.25% of all SNAP stores in the U.S. (N=257,839), comprised primarily of convenience formats (31.94%) followed by dollar (25.58%), drug (19.24%), traditional (10.87%), supercenter (6.85%), mass merchandiser (1.62%), non-food store or restaurant (1.81%), and club formats (1.09%). Results also indicated that the distribution of prevalent SNAP-authorized formats significantly differed by state. California had a lower proportion of traditional (9.96%) and a higher proportion of drug (28.92%) formats than Virginia- 11.55% and 19.97%, respectively (p < 0.001). Virginia also had a higher proportion of dollar formats (26.11%) when compared to California (10.64%) (p < 0.001). Significant differences were also observed for rurality variables (p < 0.001). Prominently, rural Virginia had a significantly higher proportion of dollar formats (41.71%) when compared to urban Virginia (21.78%) and rural California (21.21%). Non-traditional SNAP-authorized formats are highly prevalent and significantly differ in distribution by U.S. region and rurality. The largest proportional difference was observed for dollar formats where the least nutritious consumer purchases are documented in the literature. Researchers/practitioners should investigate non-traditional food stores at the local level using these research findings and similar applied methodologies to determine how access to various store formats impact obesity prevalence. For example, dollar stores may be prime targets for interventions to enhance nutritious consumer purchases in rural Virginia while targeting drug formats in California may be more appropriate.

Keywords: food access, food store format, nutrition interventions, SNAP consumers

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Authors: Benjamin J. Kuo, Silvia D. Vaca, Joao Ricardo Nickenig Vissoci, Catherine A. Staton, Linda Xu, Michael Muhumuza, Hussein Ssenyonjo, John Mukasa, Joel Kiryabwire, Lydia Nanjula, Christine Muhumuza, Henry E. Rice, Gerald A. Grant, Michael M. Haglund

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Background: Traumatic Brain Injury (TBI) is disproportionally concentrated in low- and middle-income countries (LMICs), with the odds of dying from TBI in Uganda more than 4 times higher than in high income countries (HICs). The disparities in the injury incidence and outcome between LMICs and resource-rich settings have led to increased health outcomes research for TBIs and their associated risk factors in LMICs. While there have been increasing TBI studies in LMICs over the last decade, there is still a need for more robust prospective registries. In Uganda, a trauma registry implemented in 2004 at the Mulago National Referral Hospital (MNRH) showed that RTI is the major contributor (60%) of overall mortality in the casualty department. While the prior registry provides information on injury incidence and burden, it’s limited in scope and doesn’t follow patients longitudinally throughout their hospital stay nor does it focus specifically on TBIs. And although these retrospective analyses are helpful for benchmarking TBI outcomes, they make it hard to identify specific quality improvement initiatives. The relationship among epidemiology, patient risk factors, clinical care, and TBI outcomes are still relatively unknown at MNRH. Objective: The objectives of this study are to describe the processes of care and determine risk factors predictive of poor outcomes for TBI patients presenting to a single tertiary hospital in Uganda. Methods: Prospective data were collected for 563 TBI patients presenting to a tertiary hospital in Kampala from 1 June – 30 November 2016. Research Electronic Data Capture (REDCap) was used to systematically collect variables spanning 8 categories. Univariate and multivariate analysis were conducted to determine significant predictors of mortality. Results: 563 TBI patients were enrolled from 1 June – 30 November 2016. 102 patients (18%) received surgery, 29 patients (5.1%) intended for surgery failed to receive it, and 251 patients (45%) received non-operative management. Overall mortality was 9.6%, which ranged from 4.7% for mild and moderate TBI to 55% for severe TBI patients with GCS 3-5. Within each TBI severity category, mortality differed by management pathway. Variables predictive of mortality were TBI severity, more than one intracranial bleed, failure to receive surgery, high dependency unit admission, ventilator support outside of surgery, and hospital arrival delayed by more than 4 hours. Conclusions: The overall mortality rate of 9.6% in Uganda for TBI is high, and likely underestimates the true TBI mortality. Furthermore, the wide-ranging mortality (3-82%), high ICU fatality, and negative impact of care delays suggest shortcomings with the current triaging practices. Lack of surgical intervention when needed was highly predictive of mortality in TBI patients. Further research into the determinants of surgical interventions, quality of step-up care, and prolonged care delays are needed to better understand the complex interplay of variables that affect patient outcome. These insights guide the development of future interventions and resource allocation to improve patient outcomes.

Keywords: care continuum, global neurosurgery, Kampala Uganda, LMIC, Mulago, prospective registry, traumatic brain injury

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Authors: Oleg Shovkovyy

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This research conducted in response to one of the most pressing questions on the agenda of many public administration offices around the world: “What could be done for better integration and assimilation of immigrants into hosting communities?” In author’s view, the answer could be suggested by immigrants themselves. They, often ‘bogged down in the past,’ snared by own idols and demons, perceive things differently, which, in turn, may result in their inability to integrate smoothly into hosting communities. Brief literature review suggests that perceptions of immigrants are completely neglected or something unsought in the current research on migrants, which, often, based on opinion polls by members of hosting communities themselves or superficial research data by various research organizations. Even those specimens that include voices of immigrants, unlikely to shed any additional light onto the problem simply because certain things are not made to speak out loud, especially to those in whose hands immigrants’ fate is (authorities). In this regard, this qualitative study, conducted by an insider to a few Russian-speaking communities, represents a unique opportunity for all stakeholders to look at the question of integration through the eyes of immigrants, from a different perspective and thus, makes research findings especially valuable for better understanding of the problem. Case study research employed ethnographic methods of gathering data where, approximately 200 Russian-speaking immigrants of first and second generations were closely observed by the Russian-speaking researcher in their usual setting, for eight months, and at different venues. The number of informal interviews with 27 key informants, with whom the researcher managed to establish a good rapport and who were keen enough to share their experiences voluntarily, were conducted. The field notes were taken at 14 locations (study sites) within the Brisbane region of Queensland, Australia. Moreover, all this time, researcher lived in dwelling of one of the immigrants and was an active participant in the social life (worship, picnics, dinners, weekend schools, concerts, cultural events, social gathering, etc.) of observed communities, whose members, to a large extent, belong to various religious lines of the Russian and Protestant Church. It was found that the majority of immigrants had experienced some discrimination in matters of hiring, employment, recognition of educational qualifications from home countries, and simply felt a sort of dislike from society in various everyday situations. Many noted complete absences or very limited state assistance in terms of employment, training, education, and housing. For instance, the Australian Government Department of Human Services not only does not stimulate job search but, on the contrary, encourages to refuse short-term works and employment. On the other hand, offered free courses on adaptation, and the English language proved to be ineffective and unpopular amongst immigrants. Many interviewees have reported overstated requirements for English proficiency and local work experience, whereas it was not critical for the given task or job. Based on the result of long-term monitoring, the researcher also had the courage to assert the negative and decelerating roles of immigrants’ communities, particularly religious communities, on processes of integration and assimilation. The findings suggest that governments should either change current immigration policies in the direction of their toughening or to take more proactive and responsible role in dealing with immigrant-related issues; for instance, increasing assistance and support to all immigrants and probably, paying more attention to and taking stake in managing and organizing lives of immigrants’ communities rather, simply leaving it all to chance.

Keywords: Australia, immigration, integration, perceptions

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Authors: Manavjit Singh Dhindsa, Ursula Das, Kshirasagar Naik, Marzia Zaman, Richard Purcell, Srinivas Sampalli, Abdul Mutakabbir, Chung-Horng Lung, Thambirajah Ravichandran

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These days, wildland fires, also known as forest fires, are more prevalent than ever. Wildfires have major repercussions that affect ecosystems, communities, and the environment in several ways. Wildfires lead to habitat destruction and biodiversity loss, affecting ecosystems and causing soil erosion. They also contribute to poor air quality by releasing smoke and pollutants that pose health risks, especially for individuals with respiratory conditions. Wildfires can damage infrastructure, disrupt communities, and cause economic losses. The economic impact of firefighting efforts, combined with their direct effects on forestry and agriculture, causes significant financial difficulties for the areas impacted. This research explores different forest fire spread models and presents a comprehensive review of various techniques and methodologies used in the field. A forest fire spread model is a computational or mathematical representation that is used to simulate and predict the behavior of a forest fire. By applying scientific concepts and data from empirical studies, these models attempt to capture the intricate dynamics of how a fire spreads, taking into consideration a variety of factors like weather patterns, topography, fuel types, and environmental conditions. These models assist authorities in understanding and forecasting the potential trajectory and intensity of a wildfire. Emphasizing the need for a comprehensive understanding of wildfire dynamics, this research explores the approaches, assumptions, and findings derived from various models. By using a comparison approach, a critical analysis is provided by identifying patterns, strengths, and weaknesses among these models. The purpose of the survey is to further wildfire research and management techniques. Decision-makers, researchers, and practitioners can benefit from the useful insights that are provided by synthesizing established information. Fire spread models provide insights into potential fire behavior, facilitating authorities to make informed decisions about evacuation activities, allocating resources for fire-fighting efforts, and planning for preventive actions. Wildfire spread models are also useful in post-wildfire mitigation strategies as they help in assessing the fire's severity, determining high-risk regions for post-fire dangers, and forecasting soil erosion trends. The analysis highlights the importance of customized modeling approaches for various circumstances and promotes our understanding of the way forest fires spread. Some of the known models in this field are Rothermel’s wildland fuel model, FARSITE, WRF-SFIRE, FIRETEC, FlamMap, FSPro, cellular automata model, and others. The key characteristics that these models consider include weather (includes factors such as wind speed and direction), topography (includes factors like landscape elevation), and fuel availability (includes factors like types of vegetation) among other factors. The models discussed are physics-based, data-driven, or hybrid models, also utilizing ML techniques like attention-based neural networks to enhance the performance of the model. In order to lessen the destructive effects of forest fires, this initiative aims to promote the development of more precise prediction tools and effective management techniques. The survey expands its scope to address the practical needs of numerous stakeholders. Access to enhanced early warning systems enables decision-makers to take prompt action. Emergency responders benefit from improved resource allocation strategies, strengthening the efficacy of firefighting efforts.

Keywords: artificial intelligence, deep learning, forest fire management, fire risk assessment, fire simulation, machine learning, remote sensing, wildfire modeling

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Authors: Justin Woulfe

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Siloed logistics and supply chain management systems throughout the Department of Defense (DOD) has led to disparate approaches to modeling and simulation (M&S), a lack of understanding of how one system impacts the whole, and issues with “optimal” solutions that are good for one organization but have dramatic negative impacts on another. Many different systems have evolved to try to understand and account for uncertainty and try to reduce the consequences of the unknown. As the DoD undertakes expansive digital transformation initiatives, there is an opportunity to fuse and leverage traditionally disparate data into a centrally hosted source of truth. With a streamlined process incorporating machine learning (ML) and artificial intelligence (AI), advanced M&S will enable informed decisions guiding program success via optimized operational readiness and improved mission success. One of the current challenges is to leverage the terabytes of data generated by monitored systems to provide actionable information for all levels of users. The implementation of a cloud-based application analyzing data transactions, learning and predicting future states from current and past states in real-time, and communicating those anticipated states is an appropriate solution for the purposes of reduced latency and improved confidence in decisions. Decisions made from an ML and AI application combined with advanced optimization algorithms will improve the mission success and performance of systems, which will improve the overall cost and effectiveness of any program. The Systecon team constructs and employs model-based simulations, cutting across traditional silos of data, aggregating maintenance, and supply data, incorporating sensor information, and applying optimization and simulation methods to an as-maintained digital twin with the ability to aggregate results across a system’s lifecycle and across logical and operational groupings of systems. This coupling of data throughout the enterprise enables tactical, operational, and strategic decision support, detachable and deployable logistics services, and configuration-based automated distribution of digital technical and product data to enhance supply and logistics operations. As a complete solution, this approach significantly reduces program risk by allowing flexible configuration of data, data relationships, business process workflows, and early test and evaluation, especially budget trade-off analyses. A true capability to tie resources (dollars) to weapon system readiness in alignment with the real-world scenarios a warfighter may experience has been an objective yet to be realized to date. By developing and solidifying an organic capability to directly relate dollars to readiness and to inform the digital twin, the decision-maker is now empowered through valuable insight and traceability. This type of educated decision-making provides an advantage over the adversaries who struggle with maintaining system readiness at an affordable cost. The M&S capability developed allows program managers to independently evaluate system design and support decisions by quantifying their impact on operational availability and operations and support cost resulting in the ability to simultaneously optimize readiness and cost. This will allow the stakeholders to make data-driven decisions when trading cost and readiness throughout the life of the program. Finally, sponsors are available to validate product deliverables with efficiency and much higher accuracy than in previous years.

Keywords: artificial intelligence, digital transformation, machine learning, predictive analytics

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Authors: Michael Radwan Omary

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Context: This scientific innovation demonstrate organic catalysis engineered media effective desalination of surface and groundwater. The author has developed a technology called “Storm-Water Ions Filtration Treatment” (SWIFTTM) cold reactor modules designed to retrofit typical urban street storm drains or catch basins. SWIFT triggers biochemical redox reactions with water stream-embedded toxic total dissolved solids (TDS) and electrical conductivity (EC). SWIFTTM Catalysts media unlock the sub-molecular bond energy, break down toxic chemical bonds, and neutralize toxic molecules, bacteria and pathogens. Research Aim: This research aims to develop and design lower O&M cost, zero-brine discharge, energy input-free, chemical-free water desalination and disinfection systems. The objective is to provide an effective resilient and sustainable solution to urban storm-water and groundwater decontamination and disinfection. Methodology: We focused on the development of organic, non-chemical, no-plugs, no pumping, non-polymer and non-allergenic approaches for water and waste water desalination and disinfection. SWIFT modules operate by directing the water stream to flow freely through the electrically charged media cold reactor, generating weak interactions with a water-dissolved electrically conductive molecule, resulting in the neutralization of toxic molecules. The system is powered by harvesting sub-molecular bonds embedded in energy. Findings: The SWIFTTM Technology case studies at CSU-CI and CSU-Fresno Water Institute, demonstrated consistently high reduction of all 40 detected waste-water pollutants including pathogens to levels below a state of California Department of Water Resources “Drinking Water Maximum Contaminants Levels”. The technology has proved effective in reducing pollutants such as arsenic, beryllium, mercury, selenium, glyphosate, benzene, and E. coli bacteria. The technology has also been successfully applied to the decontamination of dissolved chemicals, water pathogens, organic compounds and radiological agents. Theoretical Importance: SWIFT technology development, design, engineering, and manufacturing, offer cutting-edge advancement in achieving clean-energy source bio-catalysis media solution, an energy input free water and waste water desalination and disinfection. A significant contribution to institutions and municipalities achieving sustainable, lower cost, zero-brine and zero CO2 discharges clean energy water desalination. Data Collection and Analysis Procedures: The researchers collected data on the performance of the SWIFTTM technology in reducing the levels of various pollutants in water. The data was analyzed by comparing the reduction achieved by the SWIFTTM technology to the Drinking Water Maximum Contaminants Levels set by the state of California. The researchers also conducted live oral presentations to showcase the applications of SWIFTTM technology in storm water capture and decontamination as well as providing clean drinking water during emergencies. Conclusion: The SWIFTTM Technology has demonstrated its capability to effectively reduce pollutants in water and waste water to levels below regulatory standards. The Technology offers a sustainable solution to groundwater and storm-water treatments. Further development and implementation of the SWIFTTM Technology have the potential to treat storm water to be reused as a new source of drinking water and an ambient source of clean and healthy local water for recharge of ground water.

Keywords: catalysis, bio electro interactions, water desalination, weak-interactions

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Authors: Sofia Horjales, Florencia Palma

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Our society is currently experiencing a profound transformation, demanding a proactive response from governmental bodies and higher education institutions to empower the next generation as catalysts for change. Environmental sustainability is rooted in the critical need to maintain the equilibrium and integrity of natural ecosystems, ensuring the preservation of precious natural resources and biodiversity for the benefit of both present and future generations. It is an essential cornerstone of sustainable development, complementing social and economic sustainability. In this evolving landscape, active methodologies take a central role, aligning perfectly with the principles of the 2030 Agenda for Sustainable Development and emerging as a pivotal element of teacher education. The emphasis on active learning methods has been driven by the urgent need to nurture sustainability and instill social responsibility in our future leaders. The Universidad Tecnológica of Uruguay (UTEC) is a public, technologically-oriented institution established in 2012. UTEC is dedicated to decentralization, expanding access to higher education throughout Uruguay, and promoting inclusive social development. Operating through Regional Technological Institutes (ITRs) and associated centers spread across the country, UTEC faces the challenge of remote student populations. To address this, UTEC utilizes e-learning for equal opportunities, self-regulated learning, and digital skills development, enhancing communication among students, teachers, and peers through virtual classrooms. The Interdisciplinary Continuing Education Program is part of the Innovation and Entrepreneurship Department of UTEC. The main goal is to strengthen innovation skills through a transversal and multidisciplinary approach. Within this Program, we have developed a Case of Study and Project-Based Learning Virtual Course designed for university students and open to the broader UTEC community. The primary aim of this course is to establish a strong foundation for comprehending and addressing environmental sustainability issues from an interdisciplinary perspective. Upon completing the course, we expect students not only to understand the intricate interactions between social and ecosystem environments but also to utilize their knowledge and innovation skills to develop projects that offer enhancements or solutions to real-world challenges. Our course design centers on innovative learning experiences, rooted in active methodologies. We explore the intersection of these methods with sustainability and social responsibility in the education of university students. A paramount focus lies in gathering student feedback, empowering them to autonomously generate ideas with guidance from instructors, and even defining their own project topics. This approach underscores that when students are genuinely engaged in subjects of their choice, they not only acquire the necessary knowledge and skills but also develop essential attributes like effective communication, critical thinking, and problem-solving abilities. These qualities will benefit them throughout their lifelong learning journey. We are convinced that education serves as the conduit to merge knowledge and cultivate interdisciplinary collaboration, igniting awareness and instigating action for environmental sustainability. While systemic changes are undoubtedly essential for society and the economy, we are making significant progress by shaping perspectives and sparking small, everyday actions within the UTEC community. This approach empowers our students to become engaged global citizens, actively contributing to the creation of a more sustainable future.

Keywords: active learning, environmental education, project-based learning, soft skills development

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Authors: Rajwanlop Kumpoopong, Sukit Yindeesuk, Pornchai Silarom

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On May 5, 2014, an earthquake of magnitude 6.3 Richter hit the Northern part of Thailand. The epicenter was in Phan District, Chiang Rai Province. This earthquake or the so-called 2014-Chiang Rai Earthquake is the strongest ground shaking that Thailand has ever been experienced in her modern history. The 2014-Chiang Rai Earthquake confirms the geological evidence, which has previously been ignored by most engineers, that earthquakes of considerable magnitudes 6 to 7 Richter can occurr within the country. This promptly stimulates authorized agencies to pay more attention at the safety of their assets and promotes the comprehensive review of seismic resistance design of their building structures. The focus of this paper is to summarize the damages of highway bridges as a result of the 2014-Chiang Rai ground shaking, the remedy actions, and the research needs. The 2014-Chiang Rai Earthquake caused considerable damages to nearby structures such as houses, schools, and temples. The ground shaking, however, caused damage to only one highway bridge, Mae Laos Bridge, located several kilometers away from the epicenter. The damage of Mae Laos Bridge was in the form of concrete spalling caused by pounding of cap beam on the deck structure. The damage occurred only at the end or abutment span. The damage caused by pounding is not a surprise, but the pounding by only one bridge requires further investigation and discussion. Mae Laos Bridge is a river crossing bridge with relatively large approach structure. In as much, the approach structure is confined by strong retaining walls. This results in a rigid-like approach structure which vibrates at the acceleration approximately equal to the ground acceleration during the earthquake and exerts a huge force to the abutment causing the pounding of cap beam on the deck structure. Other bridges nearby have relatively small approach structures, and therefore have no capability to generate pounding. The effect of mass of the approach structure on pounding of cap beam on the deck structure is also evident by the damage of one pedestrian bridge in front of Thanthong Wittaya School located 50 meters from Mae Laos Bridge. The width of the approach stair of this bridge is wider than the typical one to accommodate the stream of students during pre- and post-school times. This results in a relatively large mass of the approach stair which in turn exerts a huge force to the pier causing pounding of cap beam on the deck structure during ground shaking. No sign of pounding was observed for a typical pedestrian bridge located at another end of Mae Laos Bridge. Although pounding of cap beam on the deck structure of the above mentioned bridges does not cause serious damage to bridge structure, this incident promotes the comprehensive review of seismic resistance design of highway bridges in Thailand. Given a proper mass and confinement of the approach structure, the pounding of cap beam on the deck structure can be easily excited even at the low to moderate ground shaking. In as much, if the ground shaking becomes stronger, the pounding is certainly more powerful. This may cause the deck structure to be unseated and fall off in the case of unrestrained bridge. For the bridge with restrainer between cap beam and the deck structure, the restrainer may prevent the deck structure from falling off. However, preventing free movement of the pier by the restrainer may damage the pier itself. Most highway bridges in Thailand have dowel bars embedded connecting cap beam and the deck structure. The purpose of the existence of dowel bars is, however, not intended for any seismic resistance. Their ability to prevent the deck structure from unseating and their effect on the potential damage of the pier should be evaluated. In response to this expected situation, Thailand Department of Highways (DOH) has set up a team to revise the standard practices for the seismic resistance design of highway bridges in Thailand. In addition, DOH has also funded the research project 'Seismic Resistance Evaluation of Pre- and Post-Design Modifications of DOH’s Bridges' with the scope of full-scale tests of single span bridges under reversed cyclic static loadings for both longitudinal and transverse directions and computer simulations to evaluate the seismic performance of the existing bridges and the design modification bridges. The research is expected to start in October, 2015.

Keywords: earthquake, highway bridge, Thailand, damage, pounding, seismic resistance

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Authors: G. Senoga, D. Nakimuli, B. Ndagire, B. Lukwago, D. Kyamagwa

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Background: The COVID-19 epidemic affected the education sector, with some private schools closing while other children missed schooling for fear contracting COVID-19. Post COVID-19, PSIU in collaborated with Kampala City Council Authority Directorate of Education and Social Science, Water and Sanitation department, and Directorate of Public Health and Environment to improve sanitation and hygiene among pupils and staff in 50 public and private school system in Kampala city. The “Be Clean, Stay Healthy Campaign” used a behavioral change approach in educating, reinforcing and engaging learners on proper hand washing behaviors, proper toilet usage and garbage disposal. In April 2022, 40 Washa lots were constructed, to reduce the pupil - hand wash station ratio; distributed KCCA approved printed materials; oriented 50 teachers, WASH committees to execute and implement hygiene promotion. To ensure sustainability, WASH messages were memorized and practiced through hand washing songs, Pledge, prayer, Poems, Skits, Music, dance and drama, coupled with participatory, practical demonstrations using peer to peer approach, guest speakers at assemblies and in classes. This improved hygiene and sanitation practices. Premised on this, PSI conducted an end line assessment to explore the impact of a hand washing campaign in regards to improvements in hand washing practices and hand hygiene among pupils, accessibility, functionality and usage of the constructed hygiene and sanitation facilities. Method: A cross-sectional post intervention assessment using a mixed methods approach, targeting headteachers, wash committee members and pupils less <17 years was used. Quantitative approaches with a mix of open-ended questions were used in purposively selected respondents in 50 schools. Primary three to primary seven pupils were randomly selected, data was analyzed using the Statistical Package for Social Scientists (SPSS) Outcomes and Findings: 46,989 pupils (51% female), 1,127 and 524 teaching and non-teaching staff were reached by the intervention, respectively. 96% of schools trained on sanitation, sustainable water usage and hygiene constituted 17-man school WASH committees with teacher, parents and pupils representatives. (31%) of the WASH committees developed workplans, (78%) held WASH meetings monthly. This resulted into improved sanitation, water usage, waste management, proper use of toilets, and improved pupils’ health with reduced occurrences of stomach upsets, diarrhoea initially attributed to improper use of latrines and general waste management. Teachers reported reduced number of school absenteeism due to improved hygiene and general waste management at school, especially proper management of sanitary pads. School administrations response rate in purchase of hygiene equipment’s and detergents like soap improved. Regular WASH meetings in classes, teachers and community supervision ensured WASH facilities are used appropriately. Conclusion and Recommendations: Practical behaviour change innovations improves pupil’s knowledge and understanding of hygiene messages and usage. Over 70% of pupils had clear recall of key WASH Messages. There is need for continuous water flow in the Washa lots, harvesting rain water would reduce water bills while complementing National water supply coupled with increasing on Washa lots in densely populated schools.

Keywords: handwashing, hygyiene, sanitation, behaviour change

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Authors: Jai Bakliya, Palak Dhamecha

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Today customer satisfaction is given utmost priority be it any industry. But when it comes to hospitality industry this applies even more as they come in direct contact with customers while providing them services. Employee engagement is new concept adopted by Human Resource Department which impacts customer satisfactions. To satisfy your customers, it is necessary to see that the employees in the organisation are satisfied and engaged enough in their work that they meet the company’s expectations and contribute in the process of achieving company’s goals and objectives. After all employees is human capital of the organisation. Employee engagement has become a top business priority for every organisation. In this fast moving economy, business leaders know that having a potential and high-performing human resource is important for growth and survival. They recognize that a highly engaged manpower can increase innovation, productivity, and performance, while reducing costs related to retention and hiring in highly competitive talent markets. But while most executives see a clear need to improve employee engagement, many have yet to develop tangible ways to measure and tackle this goal. Employee Engagement is an approach which is applied to establish an emotional connection between an employee and the organisation which ensures the employee’s commitment towards his work which affects the productivity and overall performance of the organisation. The study was conducted in hospitality industry. A popular branded hotel was chosen as a sample unit. Data were collected, both qualitative and quantitative from respondents. It is found that employee engagement level of the organisation (Hotel) is quite low. This means that employees are not emotionally connected with the organisation which may in turn, affect performance of the employees it is important to note that in hospitality industry individual employee’s performance specifically in terms of emotional engagement is critical and, therefore, a low engagement level may contribute to low organisation performance. An attempt to this study was made to identify employee engagement level. Another objective to take this study was to explore the factors impeding employee engagement and to explore employee engagement facilitation. While in the hospitality industry where people tend to work for as long as 16 to 18 hours concepts like employee engagement is essential. Because employees get tired of their routine job and in case where job rotation cannot be done employee engagement acts as a solution. The study was conducted at Trident Hotel, Udaipur. It was conducted on the sample size of 30 in-house employees from 6 different departments. The various departments were: Accounts and General, Front Office, Food & Beverage Service, Housekeeping, Food & Beverage Production and Engineering. It was conducted with the help of research instrument. The research instrument was Questionnaire. Data collection source was primary source. Trident Udaipur is one of the busiest hotels in Udaipur. The occupancy rate of the guest over there is nearly 80%. Due the high occupancy rate employees or staff of the hotel used to remain very busy and occupied all the time in their work. They worked for their remuneration only. As a result, they do not have any encouragement for their work nor they are interested in going an extra mile for the organisation. The study result shows working environment factors including recognition and appreciation, opinions of the employee, counselling, feedback from superiors, treatment of managers and respect from the organisation are capable of increasing employee engagement level in the hotel. The above study result encouraged us to explore the factors contributed to low employee engagement. It is being found that factors such as recognition and appreciation, feedback from supervisors, opinion of the employee, counselling, feedback from supervisors, treatment from managers has contributed negatively to employee engagement level. Probable reasons for the low contribution are number of employees gave the negative feedback in accordance to the factors stated above of the organisation. It seems that the structure of organisation itself is responsible for the low contribution of employee engagement. The scope of this study is limited to trident hotel situated in the Udaipur. The limitation of the study was that that the results or findings were only based on the responses of respondents of Trident, Udaipur. And so the recommendations were also applicable in Trident, Udaipur and not to all the like organisations across the country. Through the data collected was further analysed, interpreted and concluded. On the basis of the findings, suggestions were provided to the hotel for improvisation.

Keywords: human resource, employee engagement, research, study

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Authors: Mohamed Sameer Mughal, Andrew D. Ross, Damian J. Fearon

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Background: The fast-paced changing landscape of UK Higher Education Institution (HEIs) is poised by changes and challenges affecting Middle Managers (MM) in their job roles. MM contribute to the success of HEIs by balancing the equilibrium and pass organization strategies from senior staff towards operationalization directives to junior staff. However, this study showcased from the data analyzed during the semi structured interviews; MM job role is becoming more complex due to changes and challenges creating colossal pressures and workloads in day-to-day working. Current development programmes provisions by Human Resources (HR) departments in such HEIs are not feasible, applicable, and matching the true essence and requirements of MM who suggest that programmes offered by HR are too generic to suit their precise needs and require tailor made espousal to work effectively in their pertinent job roles. Methodologies: This study aims to capture demands of MM Development Needs (DN) by means of a conceptual model as conclusive part of the research that is divided into 2 phases. Phase 1 initiated by carrying out 2 pilot interviews with a retired Emeritus status professor and HR programmes development coordinator. Key themes from the pilot and literature review subsidized into formulation of 22 set of questions (Kvale and Brinkmann) in form of interviewing questionnaire during qualitative data collection. Data strategy and collection consisted of purposeful sampling of 12 semi structured interviews (n=12) lasting approximately an hour for all participants. The MM interviewed were at faculty and departmental levels which included; deans (n=2), head of departments (n=4), subject leaders (n=2), and lastly programme leaders (n=4). Participants recruitment was carried out via emails and snowballing technique. The interviews data was transcribed (verbatim) and managed using Computer Assisted Qualitative Data Analysis using Nvivo ver.11 software. Data was meticulously analyzed using Miles and Huberman inductive approach of positivistic style grounded theory, whereby key themes and categories emerged from the rich data collected. The data was precisely coded and classified into case studies (Robert Yin); with a main case study, sub cases (4 classes of MM) and embedded cases (12 individual MMs). Major Findings: An interim conceptual model emerged from analyzing the data with main concepts that included; key performance indicators (KPI’s), HEI effectiveness and outlook, practices, processes and procedures, support mechanisms, student events, rules, regulations and policies, career progression, reporting/accountability, changes and challenges, and lastly skills and attributes. Conclusion: Dynamic elements affecting MM includes; increase in government pressures, student numbers, irrelevant development programmes, bureaucratic structures, transparency and accountability, organization policies, skills sets… can only be confronted by employing structured development programmes originated by HR that are not provided generically. Future Work: Stage 2 (Quantitative method) of the study plans to validate the interim conceptual model externally through fully completed online survey questionnaire (Bram Oppenheim) from external HEIs (n=150). The total sample targeted is 1500 MM. Author contribution focuses on enhancing management theory and narrow the gap between by HR and MM development programme provision.

Keywords: development needs (DN), higher education institutions (HEIs), human resources (HR), middle managers (MM)

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Authors: Gertraud Koch, Teresa Stumpf, Alejandra Tijerina García

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Discourse analysis research approaches belong to the central research strategies applied throughout the humanities; they focus on the countless forms and ways digital texts and images shape present-day notions of the world. Despite the constantly growing number of relevant digital, multimodal discourse resources, digital humanities (DH) methods are thus far not systematically developed and accessible for discourse analysis approaches. Specifically, the significance of multimodality and meaning plurality modelling are yet to be sufficiently addressed. In order to address this research gap, the D-WISE project aims to develop a prototypical working environment as digital support for the sociology of knowledge approach to discourse analysis and new IT-analysis approaches for the use of context-oriented embedding representations. Playing an essential role throughout our research endeavor is the constant optimization of hermeneutical methodology in the use of (semi)automated processes and their corresponding epistemological reflection. Among the discourse analyses, the sociology of knowledge approach to discourse analysis is characterised by the reconstructive and accompanying research into the formation of knowledge systems in social negotiation processes. The approach analyses how dominant understandings of a phenomenon develop, i.e., the way they are expressed and consolidated by various actors in specific arenas of discourse until a specific understanding of the phenomenon and its socially accepted structure are established. This article presents insights and initial findings from D-WISE, a joint research project running since 2021 between the Institute of Anthropological Studies in Culture and History and the Language Technology Group of the Department of Informatics at the University of Hamburg. As an interdisciplinary team, we develop central innovations with regard to the availability of relevant DH applications by building up a uniform working environment, which supports the procedure of the sociology of knowledge approach to discourse analysis within open corpora and heterogeneous, multimodal data sources for researchers in the humanities. We are hereby expanding the existing range of DH methods by developing contextualized embeddings for improved modelling of the plurality of meaning and the integrated processing of multimodal data. The alignment of this methodological and technical innovation is based on the epistemological working methods according to grounded theory as a hermeneutic methodology. In order to systematically relate, compare, and reflect the approaches of structural-IT and hermeneutic-interpretative analysis, the discourse analysis is carried out both manually and digitally. Using the example of current discourses on digitization in the healthcare sector and the associated issues regarding data protection, we have manually built an initial data corpus of which the relevant actors and discourse positions are analysed in conventional qualitative discourse analysis. At the same time, we are building an extensive digital corpus on the same topic based on the use and further development of entity-centered research tools such as topic crawlers and automated newsreaders. In addition to the text material, this consists of multimodal sources such as images, video sequences, and apps. In a blended reading process, the data material is filtered, annotated, and finally coded with the help of NLP tools such as dependency parsing, named entity recognition, co-reference resolution, entity linking, sentiment analysis, and other project-specific tools that are being adapted and developed. The coding process is carried out (semi-)automated by programs that propose coding paradigms based on the calculated entities and their relationships. Simultaneously, these can be specifically trained by manual coding in a closed reading process and specified according to the content issues. Overall, this approach enables purely qualitative, fully automated, and semi-automated analyses to be compared and reflected upon.

Keywords: entanglement of structural IT and hermeneutic-interpretative analysis, multimodality, plurality of meaning, sociology of knowledge approach to discourse analysis

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Authors: Lauren B. Birney

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The envisioned long-term outcome of this three-year research, and implementation plan is for 1) teachers and students to design and build their own computational models of real-world environmental-human health phenomena occurring within the context of the “Human Harbor” and 2) project researchers to evaluate the degree to which these integrated Computer Science (CS) education experiences in New York City (NYC) public school classrooms (PreK-12) impact students’ computational-technical skill development, job readiness, career motivations, and measurable abilities to understand, articulate, and solve the underlying phenomena at the center of their models. This effort builds on the partnership’s successes over the past eight years in developing a benchmark Model of restoration-based Science, Technology, Engineering, and Math (STEM) education for urban public schools and achieving relatively broad-based implementation in the nation’s largest public school system. The Billion Oyster Project Curriculum and Community Enterprise for Restoration Science (BOP-CCERS STEM + Computing) curriculum, teacher professional developments, and community engagement programs have reached more than 200 educators and 11,000 students at 124 schools, with 84 waterfront locations and Out of School of Time (OST) programs. The BOP-CCERS Partnership is poised to develop a more refined focus on integrating computer science across the STEM domains; teaching industry-aligned computational methods and tools; and explicitly preparing students from the city’s most under-resourced and underrepresented communities for upwardly mobile careers in NYC’s ever-expanding “digital economy,” in which jobs require computational thinking and an increasing percentage require discreet computer science technical skills. Project Objectives include the following: 1. Computational Thinking (CT) Integration: Integrate computational thinking core practices across existing middle/high school BOP-CCERS STEM curriculum as a means of scaffolding toward long term computer science and computational modeling outcomes. 2. Data Science and Data Analytics: Enabling Researchers to perform interviews with Teachers, students, community members, partners, stakeholders, and Science, Technology, Engineering, and Mathematics (STEM) industry Professionals. Collaborative analysis and data collection were also performed. As a centerpiece, the BOP-CCERS partnership will expand to include a dedicated computer science education partner. New York City Department of Education (NYCDOE), Computer Science for All (CS4ALL) NYC will serve as the dedicated Computer Science (CS) lead, advising the consortium on integration and curriculum development, working in tandem. The BOP-CCERS Model™ also validates that with appropriate application of technical infrastructure, intensive teacher professional developments, and curricular scaffolding, socially connected science learning can be mainstreamed in the nation’s largest urban public school system. This is evidenced and substantiated in the initial phases of BOP-CCERS™. The BOP-CCERS™ student curriculum and teacher professional development have been implemented in approximately 24% of NYC public middle schools, reaching more than 250 educators and 11,000 students directly. BOP-CCERS™ is a fully scalable and transferable educational model, adaptable to all American school districts. In all settings of the proposed Phase IV initiative, the primary beneficiary group will be underrepresented NYC public school students who live in high-poverty neighborhoods and are traditionally underrepresented in the STEM fields, including African Americans, Latinos, English language learners, and children from economically disadvantaged households. In particular, BOP-CCERS Phase IV will explicitly prepare underrepresented students for skilled positions within New York City’s expanding digital economy, computer science, computational information systems, and innovative technology sectors.

Keywords: computer science, data science, equity, diversity and inclusion, STEM education

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Authors: David J. Foran, Nhan Do, Samuel Ajjarapu, Wenjin Chen, Tahsin Kurc, Joel H. Saltz

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The large-scale data and computational requirements of investigators throughout the clinical and research communities demand an informatics infrastructure that supports both existing and new investigative and translational projects in a robust, secure environment. In some subspecialties of medicine and research, the capacity to generate data has outpaced the methods and technology used to aggregate, organize, access, and reliably retrieve this information. Leading health care centers now recognize the utility of establishing an enterprise-wide, clinical data warehouse. The primary benefits that can be realized through such efforts include cost savings, efficient tracking of outcomes, advanced clinical decision support, improved prognostic accuracy, and more reliable clinical trials matching. The overarching objective of the work presented here is the development and implementation of a flexible Intelligent Retrieval and Interrogation System (IRIS) that exploits the combined use of computational imaging, genomics, and data-mining capabilities to facilitate clinical assessments and translational research in oncology. The proposed System includes a multi-modal, Clinical & Research Data Warehouse (CRDW) that is tightly integrated with a suite of computational and machine-learning tools to provide insight into the underlying tumor characteristics that are not be apparent by human inspection alone. A key distinguishing feature of the System is a configurable Extract, Transform and Load (ETL) interface that enables it to adapt to different clinical and research data environments. This project is motivated by the growing emphasis on establishing Learning Health Systems in which cyclical hypothesis generation and evidence evaluation become integral to improving the quality of patient care. To facilitate iterative prototyping and optimization of the algorithms and workflows for the System, the team has already implemented a fully functional Warehouse that can reliably aggregate information originating from multiple data sources including EHR’s, Clinical Trial Management Systems, Tumor Registries, Biospecimen Repositories, Radiology PAC systems, Digital Pathology archives, Unstructured Clinical Documents, and Next Generation Sequencing services. The System enables physicians to systematically mine and review the molecular, genomic, image-based, and correlated clinical information about patient tumors individually or as part of large cohorts to identify patterns that may influence treatment decisions and outcomes. The CRDW core system has facilitated peer-reviewed publications and funded projects, including an NIH-sponsored collaboration to enhance the cancer registries in Georgia, Kentucky, New Jersey, and New York, with machine-learning based classifications and quantitative pathomics, feature sets. The CRDW has also resulted in a collaboration with the Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC) at the U.S. Department of Veterans Affairs to develop algorithms and workflows to automate the analysis of lung adenocarcinoma. Those studies showed that combining computational nuclear signatures with traditional WHO criteria through the use of deep convolutional neural networks (CNNs) led to improved discrimination among tumor growth patterns. The team has also leveraged the Warehouse to support studies to investigate the potential of utilizing a combination of genomic and computational imaging signatures to characterize prostate cancer. The results of those studies show that integrating image biomarkers with genomic pathway scores is more strongly correlated with disease recurrence than using standard clinical markers.

Keywords: clinical data warehouse, decision support, data-mining, intelligent databases, machine-learning.

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Authors: Krishna Raj Regmi

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A “Climate change adaptation and disaster risk management for sustainable agriculture” project was implemented in Nepal, a Himalayan country during 2008 to 2013 sponsored jointly by Food and Agriculture Organization (FAO) and United Nations Development Programme (UNDP), Nepal. The paper is based on the results and findings of this joint pilot project. The climate change events such as increased intensity of erratic rains in short spells, trend of prolonged drought, gradual rise in temperature in the higher elevations and occurrence of cold and hot waves in Terai (lower plains) has led to flash floods, massive erosion in the hills particularly in Churia range and drying of water sources. These recurring natural and climate-induced disasters are causing heavy damages through sedimentation and inundation of agricultural lands, crops, livestock, infrastructures and rural settlements in the downstream plains and thus reducing agriculture productivity and food security in the country. About 65% of the cultivated land in Nepal is rainfed with drought-prone characteristics and stabilization of agricultural production and productivity in these tracts will be possible through adoption of rainfed and drought-tolerant technologies as well as efficient soil-water management by the local communities. The adaptation and mitigation technologies and options identified by the project for soil erosion, flash floods and landslide control are on-farm watershed management, sloping land agriculture technologies (SALT), agro-forestry practices, agri-silvi-pastoral management, hedge-row contour planting, bio-engineering along slopes and river banks, plantation of multi-purpose trees and management of degraded waste land including sandy river-bed flood plains. The stress tolerant technologies with respect to drought, floods and temperature stress for efficient utilization of nutrient, soil, water and other resources for increased productivity are adoption of stress tolerant crop varieties and breeds of animals, indigenous proven technologies, mixed and inter-cropping systems, system of rice/wheat intensification (SRI), direct rice seeding, double transplanting of rice, off-season vegetable production and regular management of nurseries, orchards and animal sheds. The alternate energy use options and resource conservation practices for use by local communities are installation of bio-gas plants and clean stoves (Chulla range) for mitigation of green house gas (GHG) emissions, use of organic manures and bio-pesticides, jatropha cultivation, green manuring in rice fields and minimum/zero tillage practices for marshy lands. The efficient water management practices for increasing productivity of crops and livestock are use of micro-irrigation practices, construction of water conservation and water harvesting ponds, use of overhead water tanks and Thai jars for rain water harvesting and rehabilitation of on-farm irrigation systems. Initiation of some works on community-based early warning system, strengthening of met stations and disaster database management has made genuine efforts in providing disaster-tailored early warning, meteorological and insurance services to the local communities. Contingent planning is recommended to develop coping strategies and capacities of local communities to adopt necessary changes in the cropping patterns and practices in relation to adverse climatic and disaster risk conditions. At the end, adoption of awareness raising and capacity development activities (technical and institutional) and networking on climate-induced disaster and risks through training, visits and knowledge sharing workshops, dissemination of technical know-how and technologies, conduct of farmers' field schools, development of extension materials and their displays are being promoted. However, there is still need of strong coordination and linkage between agriculture, environment, forestry, meteorology, irrigation, climate-induced pro-active disaster preparedness and research at the ministry, department and district level for up-scaling, implementation and institutionalization of climate change and disaster risk management activities and adaptation mitigation options in agriculture for sustainable livelihoods of the communities.

Keywords: climate change adaptation, disaster risk management, soil-water management practices, sustainable agriculture

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