Search results for: demographic indicators

Authors: Denise De Fátima Fernandes Barbosa, Tyane Mayara Ferreira Oliveira, Diego Jorge Maia Lima, Paula Renata Amorim Lessa, Ana Karina Bezerra Pinheiro, Cintia Gondim Pereira Calou, Glauberto Da Silva Quirino, Hellen Lívia Oliveira Catunda, Tatiana Gomes Guedes, Nicolau Da Costa

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The aim of this study is to evaluate the use of Digital Cervicography (DC) in the diagnosis of precancerous lesions related to Human Papillomavirus (HPV). Cross-sectional study with a quantitative approach, of evaluative type, held in a health unit linked to the Pro Dean of Extension of the Federal University of Ceará, in the period of July to August 2015 with a sample of 33 women. Data collecting was conducted through interviews with enforcement tool. Franco (2005) standardized the technique used for DC. Polymerase Chain Reaction (PCR) was performed to identify high-risk HPV genotypes. DC were evaluated and classified by 3 judges. The results of DC and PCR were classified as positive, negative or inconclusive. The data of the collecting instruments were compiled and analyzed by the software Statistical Package for Social Sciences (SPSS) with descriptive statistics and cross-references. Sociodemographic, sexual and reproductive variables were analyzed through absolute frequencies (N) and their respective percentage (%). Kappa coefficient (κ) was applied to determine the existence of agreement between the DC of reports among evaluators with PCR and also among the judges about the DC results. The Pearson's chi-square test was used for analysis of sociodemographic, sexual and reproductive variables with the PCR reports. It was considered statistically significant (p<0.05). Ethical aspects of research involving human beings were respected, according to 466/2012 Resolution. Regarding the socio-demographic profile, the most prevalent ages and equally were those belonging to the groups 21-30 and 41-50 years old (24.2%). The brown color was reported in excess (84.8%) and 96.9% out of them had completed primary and secondary school or studying. 51.5% were married, 72.7% Catholic, 54.5% employed and 48.5% with income between one and two minimum wages. As for the sexual and reproductive characteristics, prevailed heterosexual (93.9%) who did not use condoms during sexual intercourse (72.7%). 51.5% had a previous history of Sexually Transmitted Infection (STI), and HPV the most prevalent STI (76.5%). 57.6% did not use contraception, 78.8% underwent examination Cancer Prevention Uterus (PCCU) with shorter time interval or equal to one year, 72.7% had no cases of Cervical Cancer in the family, 63.6% were multiparous and 97% were not vaccinated against HPV. DC identified good level of agreement between raters (κ=0.542), had a specificity of 77.8% and sensitivity of 25% when compared their results with PCR. Only the variable race showed a statistically significant association with CRP (p=0.042). DC had 100% acceptance amongst women in the sample, revealing the possibility of other experiments in using this method so that it proves as a viable technique. The DC positivity criteria were developed by nurses and these professionals also perform PCCU in Brazil, which means that DC can be an important complementary diagnostic method for the appreciation of these professional’s quality of examinations.

Keywords: gynecological examination, human papillomavirus, nursing, papillomavirus infections, uterine lasmsneop

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Authors: Huseyin Sinan Gunesli

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Process Safety Management is a disciplined framework for managing the integrity of systems and processes that handle hazardous substances. It relies on good design principles, well-implemented automation systems, and operating and maintenance practices. Alarm Management Systems play a critically important role in the safe and efficient operation of modern industrial plants. In that respect, Alarm Management is one of the critical factors feeding the safe operations of the plants in the manner of applying effective process safety principles. Trans Anatolian Natural Gas Pipeline (TANAP) is part of the Southern Gas Corridor, which extends from the Caspian Sea to Italy. TANAP transports Natural Gas from the Shah Deniz gas field of Azerbaijan, and possibly from other neighboring countries, to Turkey and through Trans Adriatic Pipeline (TAP) Pipeline to Europe. TANAP plays a crucial role in maintaining Energy Security for the region and Europe. In that respect, the application of Process Safety principles is vital to deliver safe, reliable and efficient Natural Gas delivery to Shippers both in the region and Europe. Effective Alarm Management is one of those Process Safety principles which feeds safe operations of the TANAP pipeline. Alarm Philosophy was designed and implemented in TANAP Pipeline according to the relevant standards. However, it is essential to manage the alarms received in the control room effectively to maintain safe operations. In that respect, TANAP has commenced Alarm Management & Rationalization program as of February 2022 after transferring to Plateau Regime, reaching the design parameters. While Alarm Rationalization started, there were more than circa 2300 alarms received per hour from one of the compressor stations. After applying alarm management principles such as reviewing and removal of bad actors, standing, stale, chattering, fleeting alarms, comprehensive review and revision of alarm set points through a change management principle, conducting alarm audits/design verification and etc., it has been achieved to reduce down to circa 40 alarms per hour. After the successful implementation of alarm management principles as specified above, the number of alarms has been reduced to industry standards. That significantly improved operator vigilance to focus on mainly important and critical alarms to avoid any excursion beyond safe operating limits leading to any potential process safety events. Following the ‟What Gets Measured, Gets Managed” principle, TANAP has identified key Performance Indicators (KPIs) to manage Process Safety principles effectively, where Alarm Management has formed one of the key parameters of those KPIs. However, review and analysis of the alarms were performed manually. Without utilizing Alarm Management Software, achieving full compliance with international standards is almost infeasible. In that respect, TANAP has started using one of the industry-wide known Alarm Management Applications to maintain full review and analysis of alarms and define actions as required. That actually significantly empowered TANAP’s process safety principles in terms of Alarm Management.

Keywords: process safety principles, energy security, natural gas pipeline operations, alarm rationalization, alarm management, alarm management application

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Authors: S. B. R. Slagmulder

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

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

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Authors: Miriam I. Jimenez-Perez, Mariana C. Orellana-Haro, Carolina Guzman-Brambila

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As part of microbiology and dietetics courses, students of medicine and nutrition analyze the main pathogenic microorganisms and perform dietary analyzes. The course of microbiology describes in a general way the main pathogens including bacteria, viruses, fungi, and parasites, as well as their interaction with the human species. We hypothesize that lack of practical application of the course causes the students not to find the value and the clinical application of it when in reality it is a matter of great importance for healthcare in our country. The courses of the medical microbiology and dietetics are mostly theoretical and only a few hours of laboratory practices. Therefore, it is necessary the incorporation of new innovative techniques that involve more practices and community fieldwork, real cases analysis and real-life situations. The purpose of this intervention was to incorporate real-world learning experiences in the instruction of medical microbiology and dietetics courses, in order to improve the learning process, understanding and the application in the field. During a period of 6 months, medicine and nutrition students worked in a community of urban poverty. We worked with 90 children between 4 and 6 years of age from low-income families with no access to medical services, to give an infectious diagnosis related to nutritional status in these children. We expect that this intervention would give a different kind of context to medical microbiology and dietetics students improving their learning process, applying their knowledge and laboratory practices to help a needed community. First, students learned basic skills in microbiology diagnosis test during laboratory sessions. Once, students acquired abilities to make biochemical probes and handle biological samples, they went to the community and took stool samples from children (with the corresponding informed consent). Students processed the samples in the laboratory, searching for enteropathogenic microorganism with RapID™ ONE system (Thermo Scientific™) and parasites using Willis and Malloy modified technique. Finally, they compared the results with the nutritional status of the children, previously measured by anthropometric indicators. The anthropometric results were interpreted by the OMS Anthro software (WHO, 2011). The microbiological result was interpreted by ERIC® Electronic RapID™ Code Compendium software and validated by a physician. The results were analyses of infectious outcomes and nutritional status. Related to fieldwork community learning experiences, our students improved their knowledge in microbiology and were capable of applying this knowledge in a real-life situation. They found this kind of learning useful when they translate theory to a real-life situation. For most of our students, this is their first contact as health caregivers with real population, and this contact is very important to help them understand the reality of many people in Mexico. In conclusion, real-world or fieldwork learning experiences empower our students to have a real and better understanding of how they can apply their knowledge in microbiology and dietetics and help a much- needed population, this is the kind of reality that many people live in our country.

Keywords: real-world learning experiences, medical microbiology, dietetics, nutritional status, infectious status.

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Authors: Carolina Busco, Daniela Osses

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The development of digital literacy has become a fundamental element that allows for citizen inclusion, access to quality jobs, and a labor market capable of responding to the digital economy. There are no methodological instruments available in Chile to measure the workforce’s digital literacy and improve national policies on this matter. Thus, the objective of this research is to develop a survey to measure digital literacy in a sample of 200 Chilean workers. Dimensions considered in the instrument are sociodemographics, access to infrastructure, digital education, digital skills, and the ability to use e-government services. To achieve the research objective of developing a digital literacy model of indicators and a research instrument for this purpose, along with an exploratory analysis of data using factor analysis, we used an empirical, quantitative-qualitative, exploratory, non-probabilistic, and cross-sectional research design. The research instrument is a survey created to measure variables that make up the conceptual map prepared from the bibliographic review. Before applying the survey, a pilot test was implemented, resulting in several adjustments to the phrasing of some items. A validation test was also applied using six experts, including their observations on the final instrument. The survey contained 49 items that were further divided into three sets of questions: sociodemographic data; a Likert scale of four values ranked according to the level of agreement; iii) multiple choice questions complementing the dimensions. Data collection occurred between January and March 2022. For the factor analysis, we used the answers to 12 items with the Likert scale. KMO showed a value of 0.626, indicating a medium level of correlation, whereas Bartlett’s test yielded a significance value of less than 0.05 and a Cronbach’s Alpha of 0.618. Taking all factor selection criteria into account, we decided to include and analyze four factors that together explain 53.48% of the accumulated variance. We identified the following factors: i) access to infrastructure and opportunities to develop digital skills at the workplace or educational establishment (15.57%), ii) ability to solve everyday problems using digital tools (14.89%), iii) online tools used to stay connected with others (11.94%), and iv) residential Internet access and speed (11%). Quantitative results were discussed within six focus groups using heterogenic selection criteria related to the most relevant variables identified in the statistical analysis: upper-class school students; middle-class university students; Ph.D. professors; low-income working women, elderly individuals, and a group of rural workers. The digital divide and its social and economic correlations are evident in the results of this research. In Chile, the items that explain the acquisition of digital tools focus on access to infrastructure, which ultimately puts the first filter on the development of digital skills. Therefore, as expressed in the literature review, the advance of these skills is radically different when sociodemographic variables are considered. This increases socioeconomic distances and exclusion criteria, putting those who do not have these skills at a disadvantage and forcing them to seek the assistance of others.

Keywords: digital literacy, digital society, workforce digitalization, digital skills

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Authors: Soheila Sadeghi

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Infrastructure projects often encounter contract variations that can significantly deviate from the original tender estimates, leading to cost overruns, schedule delays, and financial implications. This research aims to quantitatively assess the impact of changes in contract variations on project performance by conducting an in-depth analysis of a comprehensive dataset from the Regional Airport Car Park project. The dataset includes tender budget, contract quantities, rates, claims, and revenue data, providing a unique opportunity to investigate the effects of variations on project outcomes. The study focuses on 21 specific variations identified in the dataset, which represent changes or additions to the project scope. The research methodology involves establishing a baseline for the project's planned cost and scope by examining the tender budget and contract quantities. Each variation is then analyzed in detail, comparing the actual quantities and rates against the tender estimates to determine their impact on project cost and schedule. The claims data is utilized to track the progress of work and identify deviations from the planned schedule. The study employs statistical analysis using R to examine the dataset, including tender budget, contract quantities, rates, claims, and revenue data. Time series analysis is applied to the claims data to track progress and detect variations from the planned schedule. Regression analysis is utilized to investigate the relationship between variations and project performance indicators, such as cost overruns and schedule delays. The research findings highlight the significance of effective variation management in construction projects. The analysis reveals that variations can have a substantial impact on project cost, schedule, and financial outcomes. The study identifies specific variations that had the most significant influence on the Regional Airport Car Park project's performance, such as PV03 (additional fill, road base gravel, spray seal, and asphalt), PV06 (extension to the commercial car park), and PV07 (additional box out and general fill). These variations contributed to increased costs, schedule delays, and changes in the project's revenue profile. The study also examines the effectiveness of project management practices in managing variations and mitigating their impact. The research suggests that proactive risk management, thorough scope definition, and effective communication among project stakeholders can help minimize the negative consequences of variations. The findings emphasize the importance of establishing clear procedures for identifying, assessing, and managing variations throughout the project lifecycle. The outcomes of this research contribute to the body of knowledge in construction project management by demonstrating the value of analyzing tender, contract, claims, and revenue data in variation impact assessment. However, the research acknowledges the limitations imposed by the dataset, particularly the absence of detailed contract and tender documents. This constraint restricts the depth of analysis possible in investigating the root causes and full extent of variations' impact on the project. Future research could build upon this study by incorporating more comprehensive data sources to further explore the dynamics of variations in construction projects.

Keywords: contract variation impact, quantitative analysis, project performance, claims analysis

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Authors: André Python

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To this day, terrorism persists as a worldwide threat, exemplified by the recent deadly attacks in January 2015 in Paris and the ongoing massacres perpetrated by ISIS in Iraq and Syria. In response to this threat, states deploy various counterterrorism measures, the cost of which could be reduced through effective preventive measures. In order to increase the efficiency of preventive measures, policy-makers may benefit from accurate predictive models that are able to capture the complex spatial dynamics of terrorism occurring at a local scale. Despite empirical research carried out at country-level that has confirmed theories explaining the diffusion processes of terrorism across space and time, scholars have failed to assess diffusion’s theories on a local scale. Moreover, since scholars have not made the most of recent statistical modelling approaches, they have been unable to build up predictive models accurate in both space and time. In an effort to address these shortcomings, this research suggests a novel approach to systematically assess the theories of terrorism’s diffusion on a local scale and provide a predictive model of the local spatial dynamics of terrorism worldwide. With a focus on the lethal terrorist events that occurred after 9/11, this paper addresses the following question: why and how does lethal terrorism diffuse in space and time? Based on geolocalised data on worldwide terrorist attacks and covariates gathered from 2002 to 2013, a binomial spatio-temporal point process is used to model the probability of terrorist attacks on a sphere (the world), the surface of which is discretised in the form of Delaunay triangles and refined in areas of specific interest. Within a Bayesian framework, the model is fitted through an integrated nested Laplace approximation - a recent fitting approach that computes fast and accurate estimates of posterior marginals. Hence, for each location in the world, the model provides a probability of encountering a lethal terrorist attack and measures of volatility, which inform on the model’s predictability. Diffusion processes are visualised through interactive maps that highlight space-time variations in the probability and volatility of encountering a lethal attack from 2002 to 2013. Based on the previous twelve years of observation, the location and lethality of terrorist events in 2014 are statistically accurately predicted. Throughout the global scope of this research, local diffusion processes such as escalation and relocation are systematically examined: the former process describes an expansion from high concentration areas of lethal terrorist events (hotspots) to neighbouring areas, while the latter is characterised by changes in the location of hotspots. By controlling for the effect of geographical, economical and demographic variables, the results of the model suggest that the diffusion processes of lethal terrorism are jointly driven by contagious and non-contagious factors that operate on a local scale – as predicted by theories of diffusion. Moreover, by providing a quantitative measure of predictability, the model prevents policy-makers from making decisions based on highly uncertain predictions. Ultimately, this research may provide important complementary tools to enhance the efficiency of policies that aim to prevent and combat terrorism.

Keywords: diffusion process, terrorism, spatial dynamics, spatio-temporal modeling

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Authors: Marielle Leijten, Catherine Meulemans, Sven De Maeyer, Luuk Van Waes

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For the diagnosis of Alzheimer's disease (AD), a large variety of neuropsychological tests are available. In some of these tests, linguistic processing - both oral and written - is an important factor. Language disturbances might serve as a strong indicator for an underlying neurodegenerative disorder like AD. However, the current diagnostic instruments for language assessment mainly focus on product measures, such as text length or number of errors, ignoring the importance of the process that leads to written or spoken language production. In this study, it is our aim to describe and test differences between cognitive and impaired elderly on the basis of a selection of writing process variables (inter- and intrapersonal characteristics). These process variables are mainly related to pause times, because the number, length, and location of pauses have proven to be an important indicator of the cognitive complexity of a process. Method: Participants that were enrolled in our research were chosen on the basis of a number of basic criteria necessary to collect reliable writing process data. Furthermore, we opted to match the thirteen cognitively impaired patients (8 MCI and 5 AD) with thirteen cognitively healthy elderly. At the start of the experiment, participants were each given a number of tests, such as the Mini-Mental State Examination test (MMSE), the Geriatric Depression Scale (GDS), the forward and backward digit span and the Edinburgh Handedness Inventory (EHI). Also, a questionnaire was used to collect socio-demographic information (age, gender, eduction) of the subjects as well as more details on their level of computer literacy. The tests and questionnaire were followed by two typing tasks and two picture description tasks. For the typing tasks participants had to copy (type) characters, words and sentences from a screen, whereas the picture description tasks each consisted of an image they had to describe in a few sentences. Both the typing and the picture description tasks were logged with Inputlog, a keystroke logging tool that allows us to log and time stamp keystroke activity to reconstruct and describe text production processes. The main rationale behind keystroke logging is that writing fluency and flow reveal traces of the underlying cognitive processes. This explains the analytical focus on pause (length, number, distribution, location, etc.) and revision (number, type, operation, embeddedness, location, etc.) characteristics. As in speech, pause times are seen as indexical of cognitive effort. Results. Preliminary analysis already showed some promising results concerning pause times before, within and after words. For all variables, mixed effects models were used that included participants as a random effect and MMSE scores, GDS scores and word categories (such as determiners and nouns) as a fixed effect. For pause times before and after words cognitively impaired patients paused longer than healthy elderly. These variables did not show an interaction effect between the group participants (cognitively impaired or healthy elderly) belonged to and word categories. However, pause times within words did show an interaction effect, which indicates pause times within certain word categories differ significantly between patients and healthy elderly.

Keywords: Alzheimer's disease, keystroke logging, matching, writing process

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Authors: Ruth Leitch, Joanne Hughes

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

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

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Authors: Lillian M. Seo, Curtis L. Petersen, Ryan J. Halter, David Kotz, John A. Batsis

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Background: Resistance-based exercises effectively enhance muscle strength, which is especially important in older populations as it reduces the risk of disability. Our group developed a Bluetooth-enabled handle for resistance exercise bands that wirelessly transmits relative force data through low-energy Bluetooth to a local smartphone or similar device. The system has the potential to measure home-based exercise interventions, allowing health professionals to monitor compliance. Its feasibility has already been demonstrated in both clinical and field-based settings, but it remained unclear whether the system’s usability persisted upon repeated use. The current study sought to assess the usability of this system and its users’ satisfaction with repeated use by deploying the device among younger adults to gather formative information that can ultimately improve the device’s design for older adults. Methods: A usability study was conducted in which 32 participants used the above system. Participants executed 10 repetitions of four commonly performed exercises: bicep flexion, shoulder abduction, elbow extension, and triceps extension. Each completed three exercise sessions, separated by at least 24 hours to minimize muscle fatigue. At its conclusion, subjects completed an adapted version of the usefulness, satisfaction, and ease (USE) questionnaire – assessing the system across four domains: usability, satisfaction, ease of use, and ease of learning. The 20-item questionnaire examined how strongly a participant agrees with positive statements about the device on a seven-point Likert scale, with one representing ‘strongly disagree’ and seven representing ‘strongly agree.’ Participants’ data were aggregated to calculate mean response values for each question and domain, effectively assessing the device’s performance across different facets of the user experience. Summary force data were visualized using a custom web application. Finally, an optional prompt at the end of the questionnaire allowed for written comments and feedback from participants to elicit qualitative indicators of usability. Results: Of the n=32 participants, 13 (41%) were female; their mean age was 32.4 ± 11.8 years, and no participants had a physical impairment. No usability questions received a mean score < 5 of seven. The four domains’ mean scores were: usefulness 5.66 ± 0.35; satisfaction 6.23 ± 0.06; ease of use 6.25 ± 0.43; and ease of learning 6.50 ± 0.19. Representative quotes of the open-ended feedback include: ‘A non-rigid strap-style handle might be useful for some exercises,’ and, ‘Would need different bands for each exercise as they use different muscle groups with different strength levels.’ General impressions were favorable, supporting the expectation that the device would be a useful tool in exercise interventions. Conclusions: A simple usability assessment of a Bluetooth-enabled resistance exercise band supports a consistent and positive user experience among young adults. This study provides adequate formative data, assuring the next steps can be taken to continue testing and development for the target population of older adults.

Keywords: Bluetooth, exercise, mobile health, mHealth, usability

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Authors: Sheikh Mohammed Rafiul Huque

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Bangladesh since its inception has been an economy that is fuelled by agriculture and agriculture has significant contribution to the GDP of Bangladesh. The agriculture of Bangladesh predominantly and historically dependent on organic sources of raw material though the place has taken in decades by inorganic sources of raw materials due to the high demand of food for rapidly growing of population. Meanwhile, a new market segment, which is niche market, has been evolving in the urban area in favor of organic products, though 71.1% population living in rural areas is dependent mainly on conventional products. The new market segment is search of healthy and safer source of food and they could believe that organic products are the solution of that. In Bangladesh, food adulteration is very common practices among the shop-keepers to extend the shelf life of raw vegetables and fruits. The niche group of city dwellers is aware about the fact and gradually shifting their buying behavior to organic products. A recent survey on organic farming revealed that 16,200 hectares under organic farming in recent time, which was only 2,500 hectares in 2008. This study is focused on consumer awareness of organic products and tried to explore the factors affecting organic food consumption among high income group of people. The hypothesis is developed to explore the effect of gender (GENDER), ability to purchase (ABILITY) and health awareness (HEALTH) on purchase intention (INTENTION). A snowball sampling was administered among the high income group of people in Dhaka city among 150 respondents. In this sampling process the study could identify only those samples who has consume organic products. A Partial Least Square (PLS) method was used to analyze data using path analysis. It was revealed from the analysis that coefficient determination R2 is 0.829 for INTENTION endogenous latent variable. This means that three latent variables (GENDER, ABILITY, and HEALTH) significantly explain 82.9% of the variance in INTENTION of purchasing organic products. Moreover, GENDER solely explains 6.3% and 8.6% variability of ABILITY and HEALTH respectively. The inner model suggests that HEALTH has strongest negative effect on INTENTION (-0.647) followed by ABILITY (0.344) and GENDER (0.246). The hypothesized path relationship between ABILITY->INTENTION, HEALTH->INTENTION and GENDER->INTENTION are statistically significant. Furthermore, the hypothesized path relationship between GENDER->ABILITY (0.262) and GENDER->HEALTH (-0.292) also statistically significant. The purpose of the study is to demonstrate how an organic product producer can improve his participatory guarantee system (PGS) while marketing the products. The study focuses on understanding gender (GENDER), ability (ABILITY) and health (HEALTH) factors while positioning the products (INTENTION) in the mind of the consumer. In this study, the respondents are found to care about high price and ability to purchase variables with loading -0.920 and 0.898. They are good indicators of ability to purchase (ABILITY). The marketers should consider about price of organic comparing to conventional products while marketing, otherwise, that will create negative intention to buy with a loading of -0.939. Meanwhile, it is also revealed that believability of chemical free component in organic products and health awareness affects health (HEALTH) components with high loading -0.941 and 0.682. The study analyzes that low believability of chemical free component and high price of organic products affects intension to buy. The marketers should not overlook this point while targeting the consumers in Bangladesh.

Keywords: health awareness, organic products, purchase ability, purchase intention

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Authors: V. Rekha, Rama Pal

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The study examines the degree and magnitude of wealth-based inequalities in child health and its determinants in India. Despite making strides in economic growth, India has failed to secure a better nutritional status for all the children. The country currently faces the double burden of malnutrition as well as the problems of overweight and obesity. Child malnutrition, obesity, unsafe water, sanitation among others are identified as the risk factors for Non-Communicable Diseases (NCDs). Eliminating malnutrition in all its forms will catalyse improved health and economic outcomes. The assessment of the distributive dimension of child health across various segments of the population is essential for effective policy intervention. The study utilises the fourth round of District Level Health Survey for 2012-13 to analyse the inequalities among children in the age group 0-14 years in Maharashtra, a state in the western region of India with a population of 11.24 crores which constitutes 9.3 percent of the total population of India. The study considers the extent of health inequality by state, districts, sector, age-groups, and gender. The z-scores of four child health outcome variables are computed to assess the nutritional status of pre-school and school children using WHO reference. The descriptive statistics, concentration curves, concentration indices, correlation matrix, logistic regression have been used to analyse the data. The results indicate that magnitude of inequality is higher in Maharashtra and child health inequalities manifest primarily among the weaker sections of society. The concentration curves show that there exists a pro-poor inequality in child malnutrition measured by stunting, wasting, underweight, anaemia and a pro-rich overweight inequality. The inequalities in anaemia are observably lower due to the widespread prevalence. Rural areas exhibit a higher incidence of malnutrition, but greater inequality is observed in the urban areas. Overall, the wealth-based inequalities do not vary significantly between age groups. It appears that there is no gender discrimination at the state level. Further, rural-urban differentials in gender show that boys from the rural area and girls living in the urban region experience higher disparities in health. The relative distribution of undernutrition across districts in Maharashtra reveals that malnutrition is rampant and considerable heterogeneity also exists. A negative correlation is established between malnutrition prevalence and human development indicators. The findings of logistic regression analysis reveal that lower economic status of the household is associated with a higher probability of being malnourished. The study recognises household wealth, education of the parent, child gender, and household size as factors significantly related to malnutrition. The results suggest that among the supply-side variables, child-oriented government programmes might be beneficial in tackling nutrition deficit. In order to bridge the health inequality gap, the government needs to target the schemes better and should expand the coverage of services.

Keywords: child health, inequality, malnutrition, obesity

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Authors: Mona Isazad Mashinchi, Davood Roshan Sangachin, Francis J. Sullivan, Dietrich Rebholz-Schuhmann

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Background: Decision-making processes are nowadays driven by data, data analytics and Business Intelligence (BI). BI as a software platform can provide a wide variety of capabilities such as organization memory, information integration, insight creation and presentation capabilities. Visualizing data through dashboards is one of the BI solutions (for a variety of areas) which helps managers in the decision making processes to expose the most informative information at a glance. In the healthcare domain to date, dashboard presentations are more frequently used to track performance related metrics and less frequently used to monitor those quality parameters which relate directly to patient outcomes. Providing effective and timely care for patients and improving the health outcome are highly dependent on presenting and visualizing data and information. Objective: In this research, the focus is on the presentation capabilities of BI to design a dashboard for prostate cancer (PC) data that allows better decision making for the patients, the hospital and the healthcare system related to a cancer dataset. The aim of this research is to customize a retrospective PC dataset in a dashboard interface to give a better understanding of data in the categories (risk factors, treatment approaches, disease control and side effects) which matter most to patients as well as other stakeholders. By presenting the outcome in the dashboard we address one of the major targets of a value-based health care (VBHC) delivery model which is measuring the value and presenting the outcome to different actors in HC industry (such as patients and doctors) for a better decision making. Method: For visualizing the stored data to users, three interactive dashboards based on the PC dataset have been developed (using the Tableau Software) to provide better views to the risk factors, treatment approaches, and side effects. Results: Many benefits derived from interactive graphs and tables in dashboards which helped to easily visualize and see the patients at risk, better understanding the relationship between patient's status after treatment and their initial status before treatment, or to choose better decision about treatments with fewer side effects regarding patient status and etc. Conclusions: Building a well-designed and informative dashboard is related to three important factors including; the users, goals and the data types. Dashboard's hierarchies, drilling, and graphical features can guide doctors to better navigate through information. The features of the interactive PC dashboard not only let doctors ask specific questions and filter the results based on the key performance indicators (KPI) such as: Gleason Grade, Patient's Age and Status, but may also help patients to better understand different treatment outcomes, such as side effects during the time, and have an active role in their treatment decisions. Currently, we are extending the results to the real-time interactive dashboard that users (either patients and doctors) can easily explore the data by choosing preferred attribute and data to make better near real-time decisions.

Keywords: business intelligence, dashboard, decision making, healthcare, prostate cancer, value-based healthcare

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Authors: Samantha Ramachandra, Avanthi Rupasinghe

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Demographic transition from lower to higher percentage of elderly population eventually coupled with epidemiological transition from communicable to non-communicable diseases (NCD). Higher percentage of NCD overload the health system as NCD survivors claims continuous health care. The demands are challenging to a resource constrained setting but reorganizing the system may find solutions. The study focused on the facilities available and their utilization at outpatient department (OPD) setting of the public hospitals of Sri Lanka for continuous medical care. This will help in identifying steps of reorganizing the system to provide better care with the maximum utilization of available facilities. The study was conducted as a situation analysis with secondary data at hospital planning units. Variable were identified according to the world health organization (WHO) recommendation on continuous health care for elders in “age-friendly primary health care toolkit”. Data were collected from secondary and tertiary care hospitals of Sri Lanka where most of the continuous care services are available. Out of 58 secondary and tertiary care hospitals, 16 were included in the study to represent each hospital categories. Average number of patient attending for episodic treatment at OPD and Clinical follow-up of chronic conditions shows vast disparity according to the category of the hospital ranging from 3750 – 800 per day at OPD and 1250 – 200 per clinic session. Average time spent per person at OPD session is low, range from 1.54 - 2.28 minutes, the time was increasing as the hospital category goes down. 93.7% hospitals had special arrangements for providing acute care on chronic conditions such as catheter, feeding tube and wound care. 25% hospitals had special clinics for elders, 81.2% hospitals had healthy lifestyle clinics (HLC), 75% hospitals had physical rehabilitation facilities and 68.8% hospitals had facilities for counselling. Elderly clinics and HLC were mostly available at lower grade hospitals where as rehabilitation and counselling facilities were mostly available at bigger hospitals. HLC are providing health education for both patients and their family members, refer patients for screening of complication but not provide medical examinations, investigations or treatments even though they operate in the hospital setting. Physical rehabilitation is basically offered for patients with rheumatological conditions but utilization of centers for injury rehabilitation and rehabilitation of survivors following major illness such as myocardial infarctions, stroke, cancer is not satisfactory (12.5%). Human Resource distribution within hospital shows vast disparity and there are 103 physiotherapists in the biggest hospital where only 36 physiotherapists available at the next level hospital. Counselling facilities also provided mainly for the patient with psychological conditions (100%) but they were not providing counselling for newly diagnosed patients with major illnesses (0%). According to results, most of the public-sector hospitals in Sri Lanka have basic facilities required in providing continuous care but the utilization of services need more focus. Hospital administration or the government need to have initial steps in proper utilization of them in improving continuous health care incorporating team approach of rehabilitation. The author wishes to acknowledge that this paper was made possible by the support and guidance given by the “Australia Awards Fellowships Program for Sri Lanka – 2017,” which was funded by the Department of Foreign Affairs and Trade, Australia, and co-hosted by Monash University, Australia and the Sri Lanka Institute of Development Administration.

Keywords: continuous care, outpatient department, non communicable diseases, rehabilitation

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Authors: V. Saccà, A. Sarica, F. Novellino, S. Barone, T. Tallarico, E. Filippelli, A. Granata, P. Valentino, A. Quattrone

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The work aim was to evaluate how well Random Forest (RF) and Support Vector Machine (SVM) algorithms could support the early diagnosis of Multiple Sclerosis (MS) from resting-state functional connectivity data. In particular, we wanted to explore the ability in distinguishing between controls and patients of mean signals extracted from ICA components corresponding to 15 well-known networks. Eighteen patients with early-MS (mean-age 37.42±8.11, 9 females) were recruited according to McDonald and Polman, and matched for demographic variables with 19 healthy controls (mean-age 37.55±14.76, 10 females). MRI was acquired by a 3T scanner with 8-channel head coil: (a)whole-brain T1-weighted; (b)conventional T2-weighted; (c)resting-state functional MRI (rsFMRI), 200 volumes. Estimated total lesion load (ml) and number of lesions were calculated using LST-toolbox from the corrected T1 and FLAIR. All rsFMRIs were pre-processed using tools from the FMRIB's Software Library as follows: (1) discarding of the first 5 volumes to remove T1 equilibrium effects, (2) skull-stripping of images, (3) motion and slice-time correction, (4) denoising with high-pass temporal filter (128s), (5) spatial smoothing with a Gaussian kernel of FWHM 8mm. No statistical significant differences (t-test, p < 0.05) were found between the two groups in the mean Euclidian distance and the mean Euler angle. WM and CSF signal together with 6 motion parameters were regressed out from the time series. We applied an independent component analysis (ICA) with the GIFT-toolbox using the Infomax approach with number of components=21. Fifteen mean components were visually identified by two experts. The resulting z-score maps were thresholded and binarized to extract the mean signal of the 15 networks for each subject. Statistical and machine learning analysis were then conducted on this dataset composed of 37 rows (subjects) and 15 features (mean signal in the network) with R language. The dataset was randomly splitted into training (75%) and test sets and two different classifiers were trained: RF and RBF-SVM. We used the intrinsic feature selection of RF, based on the Gini index, and recursive feature elimination (rfe) for the SVM, to obtain a rank of the most predictive variables. Thus, we built two new classifiers only on the most important features and we evaluated the accuracies (with and without feature selection) on test-set. The classifiers, trained on all the features, showed very poor accuracies on training (RF:58.62%, SVM:65.52%) and test sets (RF:62.5%, SVM:50%). Interestingly, when feature selection by RF and rfe-SVM were performed, the most important variable was the sensori-motor network I in both cases. Indeed, with only this network, RF and SVM classifiers reached an accuracy of 87.5% on test-set. More interestingly, the only misclassified patient resulted to have the lowest value of lesion volume. We showed that, with two different classification algorithms and feature selection approaches, the best discriminant network between controls and early MS, was the sensori-motor I. Similar importance values were obtained for the sensori-motor II, cerebellum and working memory networks. These findings, in according to the early manifestation of motor/sensorial deficits in MS, could represent an encouraging step toward the translation to the clinical diagnosis and prognosis.

Keywords: feature selection, machine learning, multiple sclerosis, random forest, support vector machine

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Authors: Irene T. Ho

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Students with Autism Spectrum Disorder (ASD) studying in mainstream schools often face difficulties adjusting to school life and teachers often find it challenging to meet the needs of these students. The Hong Kong Jockey Club Autism Support Network (JC A-Connect) is an initiative launched in 2015 to enhance support for students with ASD as well as their families and schools. The School Support Programme of the Project aims at building the capacity of schools to provide quality education for these students. The present report provides a summary of the main features of the support model and the related evaluation results. The school support model was conceptualized in response to four observed needs: (1) inadequate teacher expertise in dealing with the related challenges, (2) the need to promote evidence-based practices in schools, (3) less than satisfactory home-school collaboration and whole-school participation, and (4) lack of concerted effort by different parties involved in providing support to schools. The resulting model had partnership and capacity building as two guiding tenets for the School Support Programme. There were two levels of partnership promoted in the project. At the programme support level, a platform that enables effective collaboration among major stakeholders was established, including the funding body that provides the necessary resources, the Education Bureau that helps to engage schools, university experts who provide professional leadership and research support, as well as non-governmental organization (NGO) professionals who provide services to the schools. At the programme implementation level, tripartite collaboration among teachers, parents and professionals was emphasized. This notion of partnership permeated efforts at capacity building targeting students with ASD, school personnel, parents and peers. During 2015 to 2018, school-based programmes were implemented in over 400 primary and secondary schools with the following features: (1) spiral Tier 2 (group) training for students with ASD to enhance their adaptive skills, led by professionals but with strong teacher involvement to promote transfer of knowledge and skills; (2) supplementary programmes for teachers, parents and peers to enhance their capability to support students with ASD; and (3) efforts at promoting continuing or transfer of learning, on the part of both students and teachers, to Tier 1 (classroom practice) and Tier 3 (individual training) contexts. Over 5,000 students participated in the Programme, representing about 50% of students diagnosed with ASD in mainstream public sector schools in Hong Kong. Results showed that the Programme was effective in helping students improve to various extents at three levels: achievement of specific training goals, improvement in adaptive skills in school, and change in ASD symptoms. The sense of competence of teachers and parents in dealing with ASD-related issues, measured by self-report rating scales, was also significantly enhanced. Moreover, effects on enhancing the school system to provide support for students with ASD, assessed according to indicators of inclusive education, were seen. The process and results of this Programme illustrate how obstacles to inclusive education for students with ASD could be overcome by strengthening the necessary partnerships and building the required capabilities of all parties concerned.

Keywords: autism, school support, skills training, teacher development, three-tier model

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Authors: Jhovana Silvia Escobar Ortega, Ines Eugenia Garcia De Salamone

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Cover crops are an agri-technological alternative to improve all properties of soils. Cover crops such as oats and rye could be used to reduce erosion and favor system sustainability when they are grown in the same agricultural cycle of the soybean crop. This crop is very profitable but its low contribution of easily decomposable residues, due to its low C/N ratio, leaves the soil exposed to erosive action and raises the need to reduce its monoculture. Furthermore, inoculation with the plant growth promoting rhizobacteria contributes to the implementation, development and production of several cereal crops. However, there is little information on its effects on forage crops which are often used as cover crops to improve soil quality. In order to evaluate the effect of combined inoculation with Azospirillum brasilense and Pseudomonas fluorescens on rhizosphere microbial communities, field experiments were conducted in the west of Buenos Aires province, Argentina, with a split-split plot randomized complete block factorial design with three replicates. The factors were: type of cover crop, inoculation and fertilization. In the main plot two levels of fertilization 0 and 7 40-0-5 (NPKS) were established at sowing. Rye (Secale cereale cultivar Quehué) and oats (Avena sativa var Aurora.) were sown in the subplots. In the sub-subplots two inoculation treatments are applied without and with application of a combined inoculant with A. brasilense and P. fluorescens. Due to the growth of cover crops has to be stopped usually with the herbicide glyphosate, rhizosphere soil of 0-20 and 20-40 cm layers was sampled at three sampling times which were: before glyphosate application (BG), a month after glyphosate application (AG) and at soybean harvest (SH). Community level of physiological profiles (CLPP) and Shannon index of microbial diversity (H) were obtained by multivariate analysis of Principal Components. Also, the most probable number (MPN) of nitrifiers and cellulolytics were determined using selective liquid media for each functional group. The CLPP of rhizosphere microbial communities showed significant differences between sampling times. There was not interaction between sampling times and both, types of cover crops and inoculation. Rhizosphere microbial communities of samples obtained BG had different CLPP with respect to the samples obtained in the sampling times AG and SH. Fertilizer and depth of sampling also caused changes in the CLPP. The H diversity index of rhizosphere microbial communities of rye in the sampling time BG were higher than those associated with oats. The MPN of both microbial functional types was lower in the deeper layer since these microorganisms are mostly aerobic. The MPN of nitrifiers decreased in rhizosphere of both cover crops only AG. At the sampling time BG, the NMP of both microbial types were larger than those obtained for AG and SH. This may mean that the glyphosate application could cause fairly permanent changes in these microbial communities which can be considered bio-indicators of soil quality. Inoculation and fertilizer inputs could be included to improve management of these cover crops because they can have a significant positive effect on the sustainability of the agro-ecosystem.

Keywords: community level of physiological profiles, microbial diversity, plant growth promoting rhizobacteria, rhizosphere microbial communities, soil quality, system sustainability

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Authors: Afolabi K. Esther, Kuye Tolulope, Babafemi, L. Olayemi, Omikunle Yemisi

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Background: Cervical cancer is a potentially preventable disease of public significance. All sexually active women are at risk of cervical cancer; however, the uptake and coverage are low in low-middle resource countries. Hence, the programme explored the feasibility of demonstrating an innovative and low-cost system approach to cervical cancer screening service delivery among reproductive-aged women in low–resource settings in Southwestern Nigeria. This was to promote the uptake and quality improvement of cervical cancer screening services. Methods: This study was an intervention project in three senatorial districts in Osun State that have primary, secondary and tertiary health facilities. The project was in three phases; Pre-intervention, Intervention, and Post-intervention. The study utilised the existing infrastructure, facilities and staff in project settings. The study population was nurse-midwives, community health workers and reproductive-aged women (30-49 years). The intervention phase entailed using innovative, culturally appropriate strategies to create awareness of cervical cancer and preventive health-seeking behaviour among women in the reproductive-aged group (30-49) years. Also, the service providers (community health workers, Nurses, and Midwives) were trained on screening methods and treatment of pre-cancerous lesions, and there was the provision of essential equipment and supplies for cervical cancer screening services at health facilities. Besides, advocacy and engagement were made with relevant stakeholders to integrate the cervical cancer screening services into related reproductive health services and greater allocation of resources. The expected results compared the pre and post-intervention using the baseline and process indicators and the effect of the intervention phase on screening coverage using a plausibility assessment design. The project lasted 12 months; visual Inspection with Acetic acid (VIA) screening for the women for six months and follow-up in 6 months for women receiving treatment. Results: The pre-intervention phase assessed baseline service delivery statistics in the previous 12 months drawn from the retrospective data collected as part of the routine monitoring and reporting systems. The uptake of cervical cancer screening services was low as the number of women screened in the previous 12 months was 156. Service personnel's competency level was fair (54%), and limited availability of essential equipment and supplies for cervical cancer screening services. At the post-intervention phase, the level of uptake had increased as the number of women screened was 1586 within six months in the study settings. This showed about a 100-%increase in the uptake of cervical cancer screening services compared with the baseline assessment. Also, the post-intervention level of competency of service delivery personnel had increased to 86.3%, which indicates quality improvement of the cervical cancer screening service delivery. Conclusion: the findings from the study have shown an effective approach to strengthening and improving cervical cancer screening service delivery in Southwestern Nigeria. Hence, the intervention promoted a positive attitude and health-seeking behaviour among the target population, significantly influencing the uptake of cervical cancer screening services.

Keywords: cervical cancer, screening, nigeria, health system strengthening

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Authors: Saraswati Kerketta

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Tea industry is one of the oldest organised sector of India. It employs roughly 1.5 million people directly. Since the last decade Indian tea industry, especially in the northern region is experiencing worst crisis in the post-independence period. Due to many reason the prices of tea show steady decline. The workers are paid one of the lowest wage in tea industry in the world (1.5$ a day) below the UN's $2 a day for extreme poverty. The workers rely on addition benefits from plantation which includes food, housing and medical facilities. These have been effective means of enslavement of generations of labourers by the owners. There is hardly any change in the tea estates where the owners determine the fate of workers. When the tea garden is abandoned or is closed all the facilities disappear immediately. The workers are the descendants of tribes from central India also known as 'tea tribes'. Alienated from their native place, the geographical and social isolation compounded their vulnerability of these people. The economy of the region being totally dependent on tea has resulted in absolute unemployment for the workers of these tea gardens. With no other livelihood and no land to grow food, thousands of workers faced hunger and starvation. The Plantation Labour Act which ensures the decent working and living condition is violated continuously. The labours are forced to migrate and are also exposed to the risk of human trafficking. Those who are left behind suffers from starvation, malnutrition and disease. The condition in the sick tea plantation is no better. Wage are not paid regularly, subsidised food, fuel are also not supplied properly. Health care facilities are in very bad shape. Objectives: • To study the socio-cultural and demographic characteristics of the tea garden labourers in the study area. • To examine the social situation of workers in sick estates in dooars region. • To assess the magnitude of deprivation the impact of economic crisis on abandoned and closed tea estates in the region. Data Base: The study is based on data collected from field survey. Methods: Quantative: Cross-Tabulation, Regression analysis. Qualitative: Household Survey, Focussed Group Discussion, In-depth interview of key informants. Findings: Purchasing power parity has declined since in last three decades. There has been many fold increase in migration. Males migrates long distance towards central and west and south India. Females and children migrates both long and short distance. No one has reported to migrate back to the place of origin of their ancestors. Migrant males work mostly as construction labourers and as factory workers whereas females and children work as domestic help and construction labourers. In about 37 cases either they haven't contacted their families in last six months or are not traceable. The families with single earning members are more likely to migrate. Burden of disease and the duration of sickness, abandonment and closure of plantation are closely related. Death tolls are likely to rise 1.5 times in sick tea gardens and three times in closed tea estates. Sixty percent of the people are malnourished in the sick tea gardens and more than eighty five per cent in abandoned and sick tea gardens.

Keywords: migration, trafficking, starvation death, tea garden workers

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Authors: Yusuf Berkay Metinal, Gulden Gumusburun Ayalp

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Architectural education is characterized by its distinctive amalgamation of studio-based pedagogy and theoretical instruction. It offers students a comprehensive learning experience that blends practical skill development with critical inquiry and conceptual exploration. Design studios are central to this educational paradigm, which serve as dynamic hubs of creativity and innovation, providing students with immersive environments for experimentation and collaborative engagement. The physical presence and interactive dynamics inherent in studio-based learning underscore the indispensability of face-to-face instruction and interpersonal interaction in nurturing the next generation of architects. However, architectural education underwent a seismic transformation in response to the global COVID-19 pandemic, precipitating an abrupt transition from traditional, in-person instruction to online education modalities. While this shift introduced newfound flexibility in terms of temporal and spatial constraints, it also brought many challenges to the fore. Chief among these challenges was maintaining effective communication and fostering meaningful collaboration among students in virtual learning environments. Besides these challenges, lack of peer learning emerged as a vital issue of the educational experience, particularly crucial for novice students navigating the intricacies of architectural practice. Nevertheless, the pivot to online education also laid bare a discernible decline in educational efficacy, prompting inquiries regarding the enduring viability of online education in architectural pedagogy. Moreover, as educational institutions grappled with the exigencies of remote instruction, discernible disparities between different institutional contexts emerged. While state universities often contended with fiscal constraints that shaped their operational capacities, private institutions encountered challenges from a lack of institutional fortification and entrenched educational traditions. Acknowledging the multifaceted nature of these challenges, this study endeavored to undertake a comprehensive inquiry into the dynamics of online education within architectural pedagogy by interrogating variables such as class level and type of university; the research aimed to elucidate demographic critical success factors that underpin the effectiveness of online education initiatives. To this end, a meticulously constructed questionnaire was administered to architecture students from diverse academic institutions across Turkey, informed by an exhaustive review of extant literature and scholarly discourse. The resulting dataset, comprising responses from 232 participants, underwent rigorous statistical analysis, including independent samples t-test and one-way ANOVA, to discern patterns and correlations indicative of overarching trends and salient insights. In sum, the findings of this study serve as a scholarly compass for educators, policymakers, and stakeholders navigating the evolving landscapes of architectural education. By elucidating the intricate interplay of demographical factors that shape the efficacy of online education in architectural pedagogy, this research offers a scholarly foundation upon which to anchor informed decisions and strategic interventions to elevate the educational experience for future cohorts of aspiring architects.

Keywords: architectural education, COVID-19, distance education, online education

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Authors: Melanie Schinnerl, Dorothea Greiling

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In the context of the 2020 strategy, poverty and its fight returned to the center of national political efforts. This served as motivation for an Austrian research grant-funded project to focus on the under-researched local government level with the aim to identify municipal best-practice cases and to derive policy implications for Austria. Designing effective poverty reduction strategies is a complex challenge which calls for an integrated multi-actor in approach. Cities are increasingly confronted to combat poverty, even in rich EU-member states. By doing so cities face substantial demographic, cultural, economic and social challenges as well as changing welfare state regimes. Furthermore, there is a low willingness of (right-wing) governments to support the poor. Against this background, the research questions are: 1. How do local governments define poverty? 2. Who are the main risk groups and what are the most pressing problems when fighting urban poverty? 3. What is regarded as successful anti-poverty initiatives? 4. What is the underlying welfare state concept? To address the research questions a multi-method approach was chosen, consisting of a systematic literature analysis, a comprehensive document analysis, and expert interviews. For interpreting the data the project follows the qualitative-interpretive paradigm. Municipal approaches for reducing poverty are compared based on deductive, as well as inductive identified criteria. In addition to an intensive literature analysis, interviews (40) were conducted in Austria since the project started in March 2018. From the other countries, 14 responses have been collected, providing a first insight. Regarding the definition of poverty the EU SILC-definition as well as counting the persons who receive need-based minimum social benefits, the Austrian form of social welfare, are the predominant approaches in Austria. In addition to homeless people, single-parent families, un-skilled persons, long-term unemployed persons, migrants (first and second generation), refugees and families with at least 3 children were frequently mentioned. The most pressing challenges for Austrian cities are: expected reductions of social budgets, a great insecurity of the central government's social policy reform plans, the growing number of homeless people and a lack of affordable housing. Together with affordable housing, old-age poverty will gain more importance in the future. The Austrian best practice examples, suggested by interviewees, focused primarily on homeless, children and young people (till 25). Central government’s policy changes have already negative effects on programs for refugees and elderly unemployed. Social Housing in Vienna was frequently mentioned as an international best practice case, other growing cities can learn from. The results from Austria indicate a change towards the social investment state, which primarily focuses on children and labour market integration. The first insights from the other countries indicate that affordable housing and labor market integration are cross-cutting issues. Inherited poverty and old-age poverty seems to be more pressing outside Austria.

Keywords: anti-poverty policies, European cities, empirical study, social investment

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Authors: Carlos M. Parra, Matthew Sutherland, Ranjita Poudel

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Reduced mental-bandwidth related to low socioeconomic status (low-SES) might lead to impulsivity and risk-taking behavior, which poses as a major hurdle towards asset building (savings) behavior. Understanding the relationship between risk-related personality metrics as well as laboratory risk behavior and real-life savings behavior can help facilitate the development of effective asset building programs, which are vital for mitigating financial vulnerability and income inequality. As such, this study explored the relationship between personality metrics, laboratory behavior in a risky decision-making task and real-life asset building (savings) behaviors among individuals with low-SES from Miami, Florida (FL). Study participants (12 male, 15 female) included racially and ethnically diverse adults (mean age 41.22 ± 12.65 years), with incomplete higher education (18% had High School Diploma, 30% Associates, and 52% Some College), and low annual income (mean $13,872 ± $8020.43). Participants completed eight self-report surveys and played a widely used risky decision-making paradigm called the Balloon Analogue Risk Task (BART). Specifically, participants played three runs of BART (20 trials in each run; total 60 trials). In addition, asset building behavior data was collected for 24 participants who opened and used savings accounts and completed a 6-month savings program that involved monthly matches, and a final reward for completing the savings program without any interim withdrawals. Each participant’s total savings at the end of this program was the main asset building indicator considered. In addition, a new effective use of average pump bet (EUAPB) indicator was developed to characterize each participant’s ability to place winning bets. This indicator takes the ratio of each participant’s total BART earnings to average pump bet (APB) in all 60 trials. Our findings indicated that EUAPB explained more than a third of the variation in total savings among participants. Moreover, participants who managed to obtain BART earnings of at least 30 cents out of their APB, also tended to exhibit better asset building (savings) behavior. In particular, using this criterion to separate participants into high and low EUAPB groups, the nine participants with high EUAPB (mean BART earnings of 35.64 cents per APB) ended up with higher mean total savings ($255.11), while the 15 participants with low EUAPB (mean BART earnings of 22.50 cents per APB) obtained lower mean total savings ($40.01). All mean differences are statistically significant (2-tailed p  .0001) indicating that the relation between higher EUAPB and higher total savings is robust. Overall, these findings can help refine asset building interventions implemented by policy makers and practitioners interested in reducing financial vulnerability among low-SES population. Specifically, by helping identify individuals who are likely to readily take advantage of savings opportunities (such as matched savings programs) and avoiding the stipulation of unnecessary and expensive financial coaching programs to these individuals. This study was funded by J.P. Morgan Chase (JPMC) and carried out by scientists from Florida International University (FIU) in partnership with Catalyst Miami.

Keywords: balloon analogue risk task (BART), matched savings programs, asset building capability, low-SES participants

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Authors: Kaaryn Cater

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People vary in how they perceive, process, and react to internal, external, social, and emotional environmental factors; some are more sensitive than others. Compassionate people have a highly reactive nervous system and are more impacted by positive and negative environmental conditions (Differential Susceptibility). Further, some sensitive individuals are disproportionately able to benefit from positive and supportive environments without necessarily suffering negative impacts in less supportive environments (Vantage Sensitivity). Environmental sensitivity is underpinned by physiological, genetic, and personality/temperamental factors, and the phenotypic expression of high sensitivity is Sensory Processing Sensitivity. The hallmarks of Sensory Processing Sensitivity are deep cognitive processing, emotional reactivity, high levels of empathy, noticing environmental subtleties, a tendency to observe new and novel situations, and a propensity to become overwhelmed when over-stimulated. Several educational advantages associated with high sensitivity include creativity, enhanced memory, divergent thinking, giftedness, and metacognitive monitoring. High sensitivity can also lead to some educational challenges, particularly managing multiple conflicting demands and negotiating low sensory thresholds. A mixed methods study was undertaken. In the first quantitative study, participants completed the Perceived Success in Study Survey (PSISS) and the Highly Sensitive Person Scale (HSPS-12). Inclusion criteria were current or previous postsecondary education experience. The survey was presented on social media, and snowball recruitment was employed (n=365). The Excel spreadsheets were uploaded to the statistical package for the social sciences (SPSS)26, and descriptive statistics found normal distribution. T-tests and analysis of variance (ANOVA) calculations found no difference in the responses of demographic groups, and Principal Components Analysis and the posthoc Tukey calculations identified positive associations between high sensitivity and three of the five PSISS factors. Further ANOVA calculations found positive associations between the PSISS and two of the three sensitivity subscales. This study included a response field to register interest in further research. Respondents who scored in the 70th percentile on the HSPS-12 were invited to participate in a semi-structured interview. Thirteen interviews were conducted remotely (12 female). Reflexive inductive thematic analysis was employed to analyse data, and a descriptive approach was employed to present data reflective of participant experience. The results of this study found that compassionate students prioritize work-life balance; employ a range of practical metacognitive study and self-care strategies; value independent learning; connect with learning that is meaningful; and are bothered by aspects of the physical learning environment, including lighting, noise, and indoor environmental pollutants. There is a dearth of research investigating sensitivity in the educational context, and these studies highlight the need to promote widespread education sector awareness of environmental sensitivity, and the need to include sensitivity in sector and institutional diversity and inclusion initiatives.

Keywords: differential susceptibility, highly sensitive person, learning, neurosensitivity, sensory processing sensitivity, vantage sensitivity

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Authors: Aishwarya Venkat, Anastasia Marshak, Ryan B. Simpson, Elena N. Naumova

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Livestock ownership is simultaneously linked to improved nutritional status through increased availability of animal-source protein, and increased risk of enteric infections through higher exposure to contaminated water sources. Agrarian and agro-pastoral households, especially those with cattle, goats, and sheep, are highly dependent on seasonally various environmental conditions, which directly impact nutrition and health. This study explores global spatiotemporally explicit evidence regarding the relationship between livestock ownership, enteric infections, and malnutrition. Seasonal and cyclical fluctuations, as well as mediating effects, are further examined to elucidate health and nutrition outcomes of individual and communal livestock ownership. The US Agency for International Development’s Demographic and Health Surveys (DHS) and the United Nations International Children's Emergency Fund’s Multi-Indicator Cluster Surveys (MICS) provide valuable sources of household-level information on anthropometry, asset ownership, and disease outcomes. These data are especially important in data-sparse regions, where surveys may only be conducted in the aftermath of emergencies. Child-level disease history, anthropometry, and household-level asset ownership information have been collected since DHS-V (2003-present) and MICS-III (2005-present). This analysis combines over 15 years of survey data from DHS and MICS to study 2,466,257 children under age five from 82 countries. Subnational (administrative level 1) measures of diarrhea prevalence, mean livestock ownership by type, mean and median anthropometric measures (height for age, weight for age, and weight for height) were investigated. Effects of several environmental, market, community, and household-level determinants were studied. Such covariates included precipitation, temperature, vegetation, the market price of staple cereals and animal source proteins, conflict events, livelihood zones, wealth indices and access to water, sanitation, hygiene, and public health services. Children aged 0 – 6 months, 6 months – 2 years, and 2 – 5 years of age were compared separately. All observations were standardized to interview day of year, and administrative units were harmonized for consistent comparisons over time. Geographically weighted regressions were constructed for each outcome and subnational unit. Preliminary results demonstrate the importance of accounting for seasonality in concurrent assessments of malnutrition and enteric infections. Household assets, including livestock, often determine the intensity of these outcomes. In many regions, livestock ownership affects seasonal fluxes in malnutrition and enteric infections, which are also directly affected by environmental and local factors. Regression analysis demonstrates the spatiotemporal variability in nutrition outcomes due to a variety of causal factors. This analysis presents a synthesis of evidence from global survey data on the interrelationship between enteric infections, malnutrition, and livestock. These results provide a starting point for locally appropriate interventions designed to address this nexus in a timely manner and simultaneously improve health, nutrition, and livelihoods.

Keywords: diarrhea, enteric infections, households, livestock, malnutrition, seasonality

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Authors: Alexander K. Edwards

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Introduction: The moral dimension of teacher education globally has assumed a new paradigm of thinking based on the public gain (return-on-investments), value-creation (quality), professionalism (practice), and business strategies (innovations). Abundant literature reveals an interesting revolutionary trend in complimenting the raising of teachers and academic performances. Because of the global competition in the knowledge-creation and service areas, the C21st teacher at all levels is expected to be resourceful, strategic thinker, socially intelligent, relationship aptitude, and entrepreneur astute. This study is a significant contribution to practice and innovations to raise exemplary or primal teachers. In this study, the qualities needed were considered as ‘Quadrant Intelligence (Q-i)’ model for a primal teacher leadership beyond the classroom. The researcher started by examining the issue of the majority of teachers in Ghana Education Services (GES) in need of this Q-i to be effective and efficient. The conceptual framing became determinants of such Q-i. This is significant for global employability and versatility in teacher education to create premium and primal teacher leadership, which are again gaining high attention in scholarship due to failing schools. The moral aspect of teachers failing learners is a highly important discussion. In GES, some schools score zero percent at the basic education certificate examination (BECE). The question is what will make any professional teacher highly productive, marketable, and an entrepreneur? What will give teachers the moral consciousness of doing the best to succeed? Method: This study set out to develop a model for primal teachers in GES as an innovative way to highlight a premium development for the C21st business-education acumen through desk reviews. The study is conceptually framed by examining certain skill sets such as strategic thinking, social intelligence, relational and emotional intelligence and entrepreneurship to answer three main burning questions and other hypotheses. Then the study applied the causal comparative methodology with a purposive sampling technique (N=500) from CoE, GES, NTVI, and other teachers associations. Participants responded to a 30-items, researcher-developed questionnaire. Data is analyzed on the quadrant constructs and reported as ex post facto analyses of multi-variances and regressions. Multiple associations were established for statistical significance (p=0.05). Causes and effects are postulated for scientific discussions. Findings: It was found out that these quadrants are very significant in teacher development. There were significant variations in the demographic groups. However, most teachers lack considerable skills in entrepreneurship, leadership in teaching and learning, and business thinking strategies. These have significant effect on practices and outcomes. Conclusion and Recommendations: It is quite conclusive therefore that in GES teachers may need further instructions in innovations and creativity to transform knowledge-creation into business venture. In service training (INSET) has to be comprehensive. Teacher education curricula at Colleges may have to be re-visited. Teachers have the potential to raise their social capital, to be entrepreneur, and to exhibit professionalism beyond their community services. Their primal leadership focus will benefit many clienteles including students and social circles. Recommendations examined the policy implications for curriculum design, practice, innovations and educational leadership.

Keywords: emotional intelligence, entrepreneurship, leadership, quadrant intelligence (q-i), primal teacher leadership, strategic thinking, social intelligence

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Authors: Zahirah Dhurmeea, Iker Zudaire, Heidi Pethybridge, Emmanuel Chassot, Maria Cedras, Natacha Nikolic, Jerome Bourjea, Wendy West, Chandani Appadoo, Nathalie Bodin

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Scientific advice on the status of fish stocks relies on indicators that are based on strong assumptions on biological parameters such as condition, maturity and fecundity. Currently, information on the biology of albacore tuna, Thunnus alalunga, in the Indian Ocean is scarce. Consequently, many parameters used in stock assessment models for Indian Ocean albacore originate largely from other studied stocks or species of tuna. Inclusion of incorrect biological data in stock assessment models would lead to inappropriate estimates of stock status used by fisheries manager’s to establish future catch allowances. The reproductive biology of albacore tuna in the western Indian Ocean was examined through analysis of the sex ratio, spawning season, length-at-maturity (L50), spawning frequency, fecundity and fish condition. In addition, the total lipid content (TL) and lipid class composition in the gonads, liver and muscle tissues of female albacore during the reproductive cycle was investigated. A total of 923 female and 867 male albacore were sampled from 2013 to 2015. A bias in sex-ratio was found in favour of females with fork length (LF) <100 cm. Using histological analyses and gonadosomatic index, spawning was found to occur between 10°S and 30°S, mainly to the east of Madagascar from October to January. Large females contributed more to reproduction through their longer spawning period compared to small individuals. The L50 (mean ± standard error) of female albacore was estimated at 85.3 ± 0.7 cm LF at the vitellogenic 3 oocyte stage maturity threshold. Albacore spawn on average every 2.2 days within the spawning region and spawning months from November to January. Batch fecundity varied between 0.26 and 2.09 million eggs and the relative batch fecundity (mean  standard deviation) was estimated at 53.4 ± 23.2 oocytes g-1 of somatic-gutted weight. Depending on the maturity stage, TL in ovaries ranged from 7.5 to 577.8 mg g-1 of wet weight (ww) with different proportions of phospholipids (PL), wax esters (WE), triacylglycerol (TAG) and sterol (ST). The highest TL were observed in immature (mostly TAG and PL) and spawning capable ovaries (mostly PL, WE and TAG). Liver TL varied from 21.1 to 294.8 mg g-1 (ww) and acted as an energy (mainly TAG and PL) storage prior to reproduction when the lowest TL was observed. Muscle TL varied from 2.0 to 71.7 g-1 (ww) in mature females without a clear pattern between maturity stages, although higher values of up to 117.3 g-1 (ww) was found in immature females. TL results suggest that albacore could be viewed predominantly as a capital breeder relying mostly on lipids stored before the onset of reproduction and with little additional energy derived from feeding. This study is the first one to provide new information on the reproductive development and classification of albacore in the western Indian Ocean. The reproductive parameters will reduce uncertainty in current stock assessment models which will eventually promote sustainability of the fishery.

Keywords: condition, size-at-maturity, spawning behaviour, temperate tuna, total lipid content

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Authors: Amine Ganibardi, Cherif Arab Ali

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This paper addresses the data cleaning issue as a part of web usage data preprocessing within the scope of Web Usage Mining. Weblog data recorded by web servers within log files reflect usage activity, i.e., End-users’ clicks and underlying user-agents’ hits. As Web Usage Mining is interested in End-users’ behavior, user-agents’ hits are referred to as noise to be cleaned-off before mining. Filtering hits from clicks is not trivial for two reasons, i.e., a server records requests interlaced in sequential order regardless of their source or type, website resources may be set up as requestable interchangeably by end-users and user-agents. The current methods are content-centric based on filtering heuristics of relevant/irrelevant items in terms of some cleaning attributes, i.e., website’s resources filetype extensions, website’s resources pointed by hyperlinks/URIs, http methods, user-agents, etc. These methods need exhaustive extra-weblog data and prior knowledge on the relevant and/or irrelevant items to be assumed as clicks or hits within the filtering heuristics. Such methods are not appropriate for dynamic/responsive Web for three reasons, i.e., resources may be set up to as clickable by end-users regardless of their type, website’s resources are indexed by frame names without filetype extensions, web contents are generated and cancelled differently from an end-user to another. In order to overcome these constraints, a clustering-based cleaning method centered on the logging structure is proposed. This method focuses on the statistical properties of the logging structure at the requested and referring resources attributes levels. It is insensitive to logging content and does not need extra-weblog data. The used statistical property takes on the structure of the generated logging feature by webpage requests in terms of clicks and hits. Since a webpage consists of its single URI and several components, these feature results in a single click to multiple hits ratio in terms of the requested and referring resources. Thus, the clustering-based method is meant to identify two clusters based on the application of the appropriate distance to the frequency matrix of the requested and referring resources levels. As the ratio clicks to hits is single to multiple, the clicks’ cluster is the smallest one in requests number. Hierarchical Agglomerative Clustering based on a pairwise distance (Gower) and average linkage has been applied to four logfiles of dynamic/responsive websites whose click to hits ratio range from 1/2 to 1/15. The optimal clustering set on the basis of average linkage and maximum inter-cluster inertia results always in two clusters. The evaluation of the smallest cluster referred to as clicks cluster under the terms of confusion matrix indicators results in 97% of true positive rate. The content-centric cleaning methods, i.e., conventional and advanced cleaning, resulted in a lower rate 91%. Thus, the proposed clustering-based cleaning outperforms the content-centric methods within dynamic and responsive web design without the need of any extra-weblog. Such an improvement in cleaning quality is likely to refine dependent analysis.

Keywords: clustering approach, data cleaning, data preprocessing, weblog data, web usage data

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Authors: Аndrey Marchenko, Oleg Linkov, Alexander Osetrov, Sergiy Kravchenko

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The low-calorie of gases include biogas, coal gas, coke oven gas, associated petroleum gas, gases sewage, etc. These gases are usually released into the atmosphere or burned on flares, causing substantial damage to the environment. However, with the right approach, low-calorie gas fuel can become a valuable source of energy. Specified determines the relevance of areas related to the development of low-calorific gas utilization technologies. As an example, in the work considered one of way of utilization of coalmine gas, because Ukraine ranks fourth in the world in terms of coal mine gas emission (4.7% of total global emissions, or 1.2 billion m³ per year). Experts estimate that coal mine gas is actively released in the 70-80 percent of existing mines in Ukraine. The main component of coal mine gas is methane (25-60%) Methane in 21 times has a greater impact on the greenhouse effect than carbon dioxide disposal problem has become increasingly important in the context of the increasing need to address the problems of climate, ecology and environmental protection. So marked causes negative effect of both local and global nature. The efforts of the United Nations and the World Bank led to the adoption of the program 'Zero Routine Flaring by 2030' dedicated to the cessation of these gases burn in flares and disposing them with the ability to generate heat and electricity. This study proposes to use coal gas as a fuel for gas engines to generate heat and electricity. Analyzed the physical-chemical properties of low-calorie gas fuels were allowed to choose a suitable engine, as well as estimate the influence of the composition of the fuel at its techno-economic indicators. Most suitable for low-calorie gas is engine with pre-combustion chamber jet ignition. In Ukraine is accumulated extensive experience in exploitation and production of gas engines with capacity of 1100 kW type GD100 (10GDN 207/2 * 254) fueled by natural gas. By using system pre- combustion chamber jet ignition and quality control in the engines type GD100 introduces the concept of burning depleted burn fuel mixtures, which in turn leads to decrease in the concentration of harmful substances of exhaust gases. The main problems of coal mine gas as a fuel for ICE is low calorific value, the presence of components that adversely affect combustion processes and terms of operation of the ICE, the instability of the composition, weak ignition. In some cases, these problems can be solved by adaptation engine design using coal mine gas as fuel (changing compression ratio, fuel injection quantity increases, change ignition time, increase energy plugs, etc.). It is shown that the use of coal mine gas engines with prechamber has not led to significant changes in the indicator parameters (ηi = 0.43 - 0.45). However, this significantly increases the volumetric fuel consumption, which requires increased fuel injection quantity to ensure constant nominal engine power. Thus, the utilization of low-calorie gas fuels in stationary gas engine type-based GD100 will significantly reduce emissions of harmful substances into the atmosphere when the generate cheap electricity and heat.

Keywords: gas engine, low-calorie gas, methane, pre-combustion chamber, utilization

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Authors: Brooklyn Rushton, Michelle Rutty, Natalie Knowles, Daniel Scott

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As people are increasingly on the search for extraordinary experiences and connections with nature, adventure tourism is experiencing significant growth and providing tourists with life-changing experiences. Unlike built attraction-based tourism, adventure tourism relies entirely on natural heritage, which leaves communities dependent on adventure tourism extremely vulnerable to environmental and climatic changes. A growing body of evidence suggests that global climate change will influence the future of adventure tourism and mountain outdoor recreation opportunities on a global scale. Across Canada, more specifically, climate change is broadly anticipated to present risks for winter-snow sports, while opportunities are anticipated to arise for green season activities. These broad seasonal shifts do not account for the indirect impacts of climate change on adventure tourism, such as the cost of adaptation or the increase of natural hazards and the associated likelihood of accidents. While some research has examined the impact of climate change on natural environments that adventure tourism relies on, a very small body of research has specifically focused on guides’ perspectives or included hard adventure tourism activities. The guiding industry is unique, as guides are trained through an elegant blend of art and science to make decisions based on experience, observation, and intuition. While quantitative research can monitor change in natural environments, guides local knowledge can provide eye-witness accounts and outline what environmental changes mean for the future sustainability of adventure tourism. This research will capture the extensive knowledge of mountain guides to better understand the implications of climate change for mountain adventure and potential adaptive responses for the adventure tourism industry. This study uses a structured online survey with open and close-ended questions that will be administered using Qualtrics (an online survey platform). This survey is disseminated to current members of the Association of Canadian Mountain Guides (ACMG). Participation in this study will be exclusive to members of the ACMG operating in the outdoor guiding streams. The 25 survey questions are organized into four sections: demographic and professional operation (9 questions), physical change (4 questions), climate change perception (6 questions), and climate change adaptation (6 questions). How mountain guides perceive and respond to climate change is important knowledge for the future of the expanding adventure tourism industry. Results from this study are expected to provide important information to mountain destinations on climate change vulnerability and adaptive capacity. Expected results of this study include guides insight into: (1) experience-safety relevant observed physical changes in guided regions (i.e. glacial coverage, permafrost coverage, precipitation, temperature, and slope instability) (2) changes in hazards within the guiding environment (i.e. avalanches, rockfall, icefall, forest fires, flooding, and extreme weather events), (3) existing and potential adaptation strategies, and (4) key information and other barriers for adaptation. By gaining insight from the knowledge of mountain guides, this research can help the tourism industry at large understand climate risk and create adaptation strategies to ensure the resiliency of the adventure tourism industry.

Keywords: adventure tourism, climate change, environmental change, mountain hazards

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Authors: Linna Li

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The capability to move around places is doubtless very important for individuals to maintain good health and social functions. People’s activities in space and time have long been a research topic in behavioral and socio-economic studies, particularly focusing on the highly dynamic urban environment. By analyzing groups of people who share similar activity patterns, many socio-economic and socio-demographic problems and their relationships with individual behavior preferences can be revealed. Los Angeles, known for its large population, ethnic diversity, cultural mixing, and entertainment industry, faces great transportation challenges such as traffic congestion, parking difficulties, and long commuting. Understanding people’s travel behavior and movement patterns in this metropolis sheds light on potential solutions to complex problems regarding urban mobility. This project visualizes people’s trajectories in Greater Los Angeles (L.A.) Area over a period of two months using Twitter data. A Python script was used to collect georeferenced tweets within the Greater L.A. Area including Ventura, San Bernardino, Riverside, Los Angeles, and Orange counties. Information associated with tweets includes text, time, location, and user ID. Information associated with users includes name, the number of followers, etc. Both aggregated and individual activity patterns are demonstrated using various geovisualization techniques. Locations of individual Twitter users were aggregated to create a surface of activity hot spots at different time instants using kernel density estimation, which shows the dynamic flow of people’s movement throughout the metropolis in a twenty-four-hour cycle. In the 3D geovisualization interface, the z-axis indicates time that covers 24 hours, and the x-y plane shows the geographic space of the city. Any two points on the z axis can be selected for displaying activity density surface within a particular time period. In addition, daily trajectories of Twitter users were created using space-time paths that show the continuous movement of individuals throughout the day. When a personal trajectory is overlaid on top of ancillary layers including land use and road networks in 3D visualization, the vivid representation of a realistic view of the urban environment boosts situational awareness of the map reader. A comparison of the same individual’s paths on different days shows some regular patterns on weekdays for some Twitter users, but for some other users, their daily trajectories are more irregular and sporadic. This research makes contributions in two major areas: geovisualization of spatial footprints to understand travel behavior using the big data approach and dynamic representation of activity space in the Greater Los Angeles Area. Unlike traditional travel surveys, social media (e.g., Twitter) provides an inexpensive way of data collection on spatio-temporal footprints. The visualization techniques used in this project are also valuable for analyzing other spatio-temporal data in the exploratory stage, thus leading to informed decisions about generating and testing hypotheses for further investigation. The next step of this research is to separate users into different groups based on gender/ethnic origin and compare their daily trajectory patterns.

Keywords: geovisualization, human mobility pattern, Los Angeles, social media

Procedia PDF Downloads 113