Search results for: tools for students

Authors: Anshu Gupta, Charu Gupta

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Background: Adolescence is the transitional period between puberty and adulthood. It is marked by immense turmoil in emotional and behavioral spheres. Adolescents are at risk of an array of behavioral and emotional problems, resulting in social, academic and vocational function impairments. Conflicts in the family and inability of the parents to cope with the changing demands of an adolescent have a negative impact on the overall development of the child. This augers ill for the individual’s future, resulting in depression, delinquency and suicides among other problems. Aim: The aim of the study was to compare the prevalence of behavioral and emotional problems in school going adolescents aged 13 to 15 years residing in Ludhiana city. Method: A total of 1380 school children in the age group of 13 to 15 years were assessed by the adolescent health screening questionnaire (FAPS) and Youth Self-Report (2001) questionnaire. Statistical significance was ascertained by t-test, chi-square test (x²) and ANOVA, as appropriate. Results: A considerably high prevalence of behavioral and emotional problems was found in school going adolescents (26.5%), more in girls (31.7%) than in boys (24.4%). In case of boys, the maximum problem was in the 13 year age group, i.e., 28.2%, followed by a significant decline by the age of 14 years, i.e., 24.2% and 15 years, i.e., 19.6%. In case of girls also, the maximum problem was in the 13 year age group, i.e., 32.4% followed by a marginal decline in the 14 years i.e., 31.8% and 15 year age group, i.e., 30.2%. Demographic factors were non contributory. Internalizing syndrome (22.4%) was the most common problem followed by the neither internalizing nor externalizing (17.6%) group. In internalizing group, most (26.5%) of the students were observed to be anxious/ depressed. Social problem was observed to be the most frequent (10.6%) among neither internalizing nor externalizing group. Aggressive behavior was the commonest (8.4%) among externalizing group. Internalizing problems, mainly anxiety and depression, were commoner in females (30.6%) than males (24.6%). More boys (16%) than girls (13.4%) were reported to suffer from externalizing disorders. A critical review of the data showed that most of the adolescents had poor knowledge about reproductive health. Almost 36% reported that the source of their information on sexual and reproductive health being friends and the electronic media. There was a high percentage of adolescents who reported being worried about sexual abuse (20.2%) with majority of them being girls (93.6%) reflecting poorly on the social setup in the country. About 41% of adolescents reported being concerned about body weight and most of them being girls (92.4%). Up to 14.5% reported having thoughts of using alcohol or drugs perhaps due to the easy availability of substances of abuse in this part of the country. 12.8% (mostly girls) reported suicidal thoughts. Summary/conclusion: There is a high prevalence of emotional and behavioral problems among school-going adolescents. Resolution of these problems during adolescence is essential for attaining a healthy adulthood. The need of the hour is to spread awareness among caregivers and formulation of effective management strategies including school mental health programme.

Keywords: adolescence, behavioral, emotional, internalizing problem

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Authors: Diana F. Lopes, Jorge Simoes, José Martins, Eduardo Castro

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Health professionals are the keystone of any health system, by delivering health services to the population. Given the time and cost involved in training new health professionals, the planning process of the health workforce is particularly important as it ensures a proper balance between the supply and demand of these professionals and it plays a central role on the Health 2020 policy. In the past 40 years, the planning of the health workforce in Portugal has been conducted in a reactive way lacking a prospective vision based on an integrated, comprehensive and valid analysis. This situation may compromise not only the productivity and the overall socio-economic development but the quality of the healthcare services delivered to patients. This is even more critical given the expected shortage of the health workforce in the future. Furthermore, Portugal is facing an aging context of some professional classes (physicians and nurses). In 2015, 54% of physicians in Portugal were over 50 years old, and 30% of all members were over 60 years old. This phenomenon associated to an increasing emigration of young health professionals and a change in the citizens’ illness profiles and expectations must be considered when planning resources in healthcare. The perspective of sudden retirement of large groups of professionals in a short time is also a major problem to address. Another challenge to embrace is the health workforce imbalances, in which Portugal has one of the lowest nurse to physician ratio, 1.5, below the European Region and the OECD averages (2.2 and 2.8, respectively). Within the scope of the HEALTH 2040 project – which aims to estimate the ‘Future needs of human health resources in Portugal till 2040’ – the present study intends to get a comprehensive dynamic approach of the problem, by (i) estimating the needs of physicians and nurses in Portugal, by specialties and by quinquenium till 2040; (ii) identifying the training needs of physicians and nurses, in medium and long term, till 2040, and (iii) estimating the number of students that must be admitted into medicine and nursing training systems, each year, considering the different categories of specialties. The development of such approach is significantly more critical in the context of limited budget resources and changing health care needs. In this context, this study presents the drivers of the healthcare needs’ evolution (such as the demographic and technological evolution, the future expectations of the users of the health systems) and it proposes a Bayesian methodology, combining the best available data with experts opinion, to model such evolution. Preliminary results considering different plausible scenarios are presented. The proposed methodology will be integrated in a user-friendly decision support system so it can be used by politicians, with the potential to measure the impact of health policies, both at the regional and the national level.

Keywords: bayesian estimation, health economics, health workforce planning, human health resources planning

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Authors: Brianne Nichols, John A. Parkinson

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Positive Psychology has provided a rich understanding of the beneficial effects of positive emotions in relation to optimal functioning, and research has been devoted to promote states of positive feeling and thinking. While this is a worthwhile pursuit, positive emotions are not useful in all contexts - some situations may require the individual to make use of their negative emotions to reach a desired end state. To account for the potential value of a wider range of emotional experiences that are common to the human condition, Positive Psychology needs to expand its horizons and investigate how individuals achieve positive outcomes using varied means. The current research seeks to understand the positive psychology of fear of failure (FF), which is a commonly experienced negative emotion relevant to most life domains. On the one hand, this emotion has been linked with avoidance motivation and self-handicap behaviours, on the other; FF has been shown to act as a drive to move the individual forward. To fully capture the depth of this highly subjective emotional experience and understand the circumstances under which FF may be adaptive, this study adopted a mixed methods design using SenseMaker; a web-based tool that combines the richness of narratives with the objectivity of numerical data. Two hundred participants consisting mostly of undergraduate university students shared a story of a time in the recent past when they feared failure of achieving a valued goal. To avoid researcher bias in the interpretation of narratives, participants self-signified their stories in a tagging system that was based on researchers’ aim to explore the role of past failures, the cognitive, emotional and behavioural profile of individuals high and low in FF, and the relationship between these factors. In addition, the role of perceived personal control and self-esteem were investigated in relation to FF using self-report questionnaires. Results from quantitative analyses indicated that individuals with high levels of FF, compared to low, were strongly influenced by past failures and preoccupied with their thoughts and emotions relating to the fear. This group also reported an unwillingness to accept their internal experiences, which in turn was associated with withdrawal from goal pursuit. Furthermore, self-esteem was found to mediate the relationship between perceived control and FF, suggesting that self-esteem, with or without control beliefs, may have the potential to buffer against high FF. It is hoped that the insights provided by the current study will inspire future research to explore the ways in which ‘acceptance’ may help individuals keep moving towards a goal despite the presence of FF, and whether cultivating a non-contingent self-esteem is the key to resilience in the face of failures.

Keywords: fear of failure, goal-pursuit, negative emotions, optimal functioning, resilience

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Authors: M. Trousselard, D. Steiler, C. Drogou, P. van-Beers, G. Lamour, S. N. Crosnier, O. Bouilland, P. Dubost, M. Chennaoui, D. Léger

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According to published data, undersea navigation for long periods (nuclear-powered ballistic missile submarine, SSBN) constitutes an extreme environment in which crews are subjected to multiple stresses, including the absence of natural light, illuminance below 1,000 lux, and watch schedules that do not respect natural chronobiological rhythms, for a period of 60-80 days. These stresses seem clearly detrimental to the submariners’ sleep, with consequences for their affective (seasonal affective disorder-like) and cognitive functioning. In the long term, there are abundant publications regarding the consequences of sleep disruption for the occurrence of organic cardiovascular, metabolic, immunological or malignant diseases. It seems essential to propose countermeasures for the duration of the patrol in order to reduce the negative physiological effects on the sleep and mood of submariners. Light therapy, the preferred treatment for dysfunctions of the internal biological clock and the resulting seasonal depression, cannot be used without data to assist knowledge of submariners’ chronobiology (melatonin secretion curve) during patrols, given the unusual characteristics of their working environment. These data are not available in the literature. The aim of this project was to assess, in the course of two studies, the benefits of two environmental techniques for managing chronobiological stress: techniques for optimizing potential (TOP; study 1)3, an existing programme to help in the psychophysiological regulation of stress and sleep in the armed forces, and dawn and dusk simulators (DDS, study 2). For each experiment, psychological, physiological (sleep) or biological (melatonin secretion) data were collected on D20 and D50 of patrol. In the first experiment, we studied sleep and depressive distress in 19 submariners in an operational setting on board an SSBM during a first patrol, and assessed the impact of TOP on the quality of sleep and depressive distress in these same submariners over the course of a second patrol. The submariners were trained in TOP between the two patrols for a 2-month period, at a rate of 1 h of training per week, and assigned daily informal exercises. Results show moderate disruptions in sleep pattern and duration associated with the intensity of depressive distress. The use of TOP during the following patrol improved sleep and depressive mood only in submariners who regularly practiced the techniques. In light of these limited benefits, we assessed, in a second experiment, the benefits of DDS on chronobiology (daily secretion of melatonin) and depressive distress. Ninety submariners were randomly allocated to two groups, group 1 using DDS daily, and group 2 constituting the control group. Although the placebo effect was not controlled, results showed a beneficial effect on chronobiology and depressive mood for submariners with a morning chronotype. Conclusions: These findings demonstrate the difficulty of practicing the tools of psychophysiological management in real life. They raise the question of the subjects’ autonomy with respect to using aids that involve regular practice. It seems important to study autonomy in future studies, as a cognitive resource resulting from the interaction between internal positive resources and “coping” resources, to gain a better understanding of compliance problems.

Keywords: chronobiology, light therapy, seasonal affective disorder, sleep, stress, stress management, submarine

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Authors: Olayeye Olubunmi Shola

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Amidst increasing global environmental concerns, sustainable urban planning has emerged as a vital strategy in counteracting the negative impacts of urbanization on the environment. However, the emphasis on sustainability often disregards crucial elements of fairness and equal participation within urban settings. This abstract presents a comprehensive overview of the challenges, objectives, significance, and methodologies for addressing social inequalities in the development of eco-cities, with a specific focus on Abuja, Nigeria. Sustainable urban planning, particularly in the context of developing eco-cities, aims to construct cities prioritizing environmental sustainability and resilience. Nonetheless, a significant gap exists in addressing the enduring social disparities within these initiatives. Equitable distribution of resources, access to services, and social inclusivity are essential components that must be integrated into urban planning frameworks for cities that are genuinely sustainable and habitable. Abuja, the capital city of Nigeria, provides a distinctive case for examining the intersection of sustainability and social justice in urban planning. Despite the urban development, Abuja grapples with challenges such as socio-economic disparities, unequal access to essential services, and inadequate housing among its residents. Recognizing and redressing these disparities within the framework of eco-city development is critical for nurturing an inclusive and sustainable urban environment. The primary aim of this study is to scrutinize and pinpoint the social discrepancies within Abuja's initiatives for eco-city development. Specific objectives include: Evaluating the current socio-economic landscape of Abuja to identify disparities in resource, service, and infrastructure access. Comprehending the existing sustainable urban planning initiatives and their influence on social fairness. Suggesting strategies and recommendations to improve fairness and inclusivity within Abuja's plans for eco-city development. This research holds substantial importance for urban planning practices and policy formulation, not only in Abuja but also on a global scale. By highlighting the crucial role of social equity and inclusivity in the development of eco-cities, this study aims to provide insights that can steer more comprehensive, people-centered urban planning practices. Addressing social disparities within sustainability initiatives is crucial for achieving genuinely sustainable and fair urban spaces. The study will employ qualitative and quantitative methodologies. Data collection will involve surveys, interviews, and observations to capture the diverse experiences and perspectives of various social groups within Abuja. Furthermore, quantitative data on infrastructure, service access, and socio-economic indicators will be collated from government reports, academic sources, and non-governmental organizations. Analytical tools such as Geographic Information Systems (GIS) will be utilized to map and visualize spatial disparities in resource allocation and service access. Comparative analyses and case studies of successful interventions in other cities will be conducted to derive applicable strategies for Abuja's context. In conclusion, this study aims to contribute to the discourse on sustainable urban planning by advocating for equity and inclusivity in the development of eco-cities. By centering on Abuja as a case study, it aims to provide practical insights and solutions for the creation of more fair and sustainable urban environments.

Keywords: fairness, sustainability, geographical information system, equity

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Authors: Antonella Falanga, Armando Cartenì

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"Big data" refers to extremely vast and complex sets of data, encompassing extraordinarily large and intricate datasets that require specific tools for meaningful analysis and processing. These datasets can stem from diverse origins like sensors, mobile devices, online transactions, social media platforms, and more. The utilization of big data is pivotal, offering the chance to leverage vast information for substantial advantages across diverse fields, thereby enhancing comprehension, decision-making, efficiency, and fostering innovation in various domains. Big data, distinguished by its remarkable attributes of enormous volume, high velocity, diverse variety, and significant value, represent a transformative force reshaping the industry worldwide. Their pervasive impact continues to unlock new possibilities, driving innovation and advancements in technology, decision-making processes, and societal progress in an increasingly data-centric world. The use of these technologies is becoming more widespread, facilitating and accelerating operations that were once much more complicated. In particular, big data impacts across multiple sectors such as business and commerce, healthcare and science, finance, education, geography, agriculture, media and entertainment and also mobility and logistics. Within the transportation sector, which is the focus of this study, big data applications encompass a wide variety, spanning across optimization in vehicle routing, real-time traffic management and monitoring, logistics efficiency, reduction of travel times and congestion, enhancement of the overall transportation systems, but also mitigation of pollutant emissions contributing to environmental sustainability. Meanwhile, in public administration and the development of smart cities, big data aids in improving public services, urban planning, and decision-making processes, leading to more efficient and sustainable urban environments. Access to vast data reservoirs enables deeper insights, revealing hidden patterns and facilitating more precise and timely decision-making. Additionally, advancements in cloud computing and artificial intelligence (AI) have further amplified the potential of big data, enabling more sophisticated and comprehensive analyses. Certainly, utilizing big data presents various advantages but also entails several challenges regarding data privacy and security, ensuring data quality, managing and storing large volumes of data effectively, integrating data from diverse sources, the need for specialized skills to interpret analysis results, ethical considerations in data use, and evaluating costs against benefits. Addressing these difficulties requires well-structured strategies and policies to balance the benefits of big data with privacy, security, and efficient data management concerns. Building upon these premises, the current research investigates the efficacy and influence of big data by conducting an overview of the primary and recent implementations of big data in transportation systems. Overall, this research allows us to conclude that big data better provide to enhance rational decision-making for mobility choices and is imperative for adeptly planning and allocating investments in transportation infrastructures and services.

Keywords: big data, public transport, sustainable mobility, transport demand, transportation planning

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Authors: Krzysztof Skiba, Zbigniew Czyz, Ksenia Siadkowska, Piotr Borowiec

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The article presents selected concepts of technologies that use intelligent materials in aircraft in order to improve their performance. Most of the research focuses on solutions that improve the performance of fixed wing aircraft due to related to their previously dominant market share. Recently, the development of the rotorcraft has been intensive, so there are not only helicopters but also gyroplanes and unmanned aerial vehicles using rotors and vertical take-off and landing. There are many different technologies to change a shape of the aircraft or its elements. Piezoelectric, deformable actuator systems can be applied in the system of an active control of vibration dampening in the aircraft tail structure. Wires made of shape memory alloys (SMA) could be used instead of hydraulic cylinders in the rear part of the aircraft flap. The aircraft made of intelligent materials (piezoelectrics and SMA) is one of the NASA projects which provide the possibility of changing a wing shape coefficient by 200%, a wing surface by 50%, and wing deflections by 20 degrees. Active surfaces made of shape memory alloys could be used to control swirls in the flowing stream. An intelligent control system for helicopter blades is a method for the active adaptation of blades to flight conditions and the reduction of vibrations caused by the rotor. Shape memory alloys are capable of recovering their pre-programmed shapes. They are divided into three groups: nickel-titanium-based, copper-based, and ferromagnetic. Due to the strongest shape memory effect and the best vibration damping ability, a Ni-Ti alloy is the most commercially important. The subject of this work was to prepare a conceptual design of a rotor blade with SMA actuators. The scope of work included 3D design of the supporting rotor blade, 3D design of beams enabling to change the geometry by changing the angle of rotation and FEM (Finite Element Method) analysis. The FEM analysis was performed using NX 12 software in the Pre/Post module, which includes extended finite element modeling tools and visualizations of the obtained results. Calculations are presented for two versions of the blade girders. For FEM analysis, three types of materials were used for comparison purposes (ABS, aluminium alloy 7057, steel C45). The analysis of internal stresses and extreme displacements of crossbars edges was carried out. The internal stresses in all materials were close to the yield point in the solution of girder no. 1. For girder no. 2 solution, the value of stresses decreased by about 45%. As a result of the displacement analysis, it was found that the best solution was the ABS girder no. 1. The displacement of about 0.5 mm was obtained, which resulted in turning the crossbars (upper and lower) by an angle equal to 3.59 degrees. This is the largest deviation of all the tests. The smallest deviation was obtained for beam no. 2 made of steel. The displacement value of the second girder solution was approximately 30% lower than the first solution. Acknowledgement: This work has been financed by the Polish National Centre for Research and Development under the LIDER program, Grant Agreement No. LIDER/45/0177/L-9/17/NCBR/2018.

Keywords: aircraft, helicopters, shape memory alloy, SMA, smart material, unmanned aerial vehicle, UAV

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Authors: Kiran Datta, Daniella Holland-Hart, Anthony Byrne

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Introduction: Oesophago-gastric (OG) cancers are the fifth commonest in the UK, accounting for over 12,000 deaths each year. Most patients will present at later stages of the disease, with only 21% of patients with stage 4 disease surviving longer than a year. As a result, many patients are unsuitable for curative surgery and instead receive palliative treatment to improve prognosis and symptom burden. However, palliative chemotherapy can result in significant toxicity: almost half of the patients are unable to complete their chemotherapy regimen, with this proportion rising significantly in older and frailer patients. In addition, clinical trials often exclude older and frailer patients due to strict inclusion criteria, meaning there is limited evidence to guide which patients are most likely to benefit from palliative chemotherapy. Inappropriate chemotherapy administration is at odds with the goals of palliative treatment and care, which are to improve quality of life, and this also represents a significant resource expenditure. This literature review aimed to examine and appraise evidence regarding treatment resilience in order to guide clinicians in identifying the most suitable candidates for palliative chemotherapy. Factors influencing treatment resilience were assessed, as measured by completion rates, dose reductions, and toxicities. Methods: This literature review was conducted using rapid review methodology, utilising modified systematic methods. A literature search was performed across the MEDLINE, EMBASE, and Cochrane Library databases, with results limited to papers within the last 15 years and available in English. Key inclusion criteria included: 1) participants with either oesophageal, gastro-oesophageal junction, or gastric cancers; 2) patients treated with palliative chemotherapy; 3) available data evaluating the association between baseline participant characteristics and treatment resilience. Results: Of the 2326 papers returned, 11 reports of 10 studies were included in this review after excluding duplicates and irrelevant papers. Treatment resilience factors that were assessed included: age, performance status, frailty, inflammatory markers, and sarcopenia. Age was generally a poor predictor for how well patients would tolerate chemotherapy, while poor performance status was a better indicator of the need for dose reduction and treatment non-completion. Frailty was assessed across one cohort using multiple screening tools and was an effective marker of the risk of toxicity and the requirement for dose reduction. Inflammatory markers included lymphopenia and the Glasgow Prognostic Score, which assessed inflammation and hypoalbuminaemia. Although quick to obtain and interpret, these findings appeared less reliable due to the inclusion of patients treated with palliative radiotherapy. Sarcopenia and body composition were often associated with chemotherapy toxicity but not the rate of regimen completion. Conclusion: This review demonstrates that there are numerous measures that can estimate the ability of patients with oesophago-gastric cancer to tolerate palliative chemotherapy, and these should be incorporated into clinical assessments to promote personalised decision-making around treatment. Age should not be a barrier to receiving chemotherapy and older and frailer patients should be included in future clinical trials to better represent typical patients with oesophago-gastric cancers. Decisions regarding palliative treatment should be guided by these factors identified as well as patient preference.

Keywords: frailty, oesophago-gastric cancer, palliative chemotherapy, treatment resilience

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Authors: Vilma Zydziunaite, Gitana Balezentiene, Vilma Zydziunaite

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Teaching is one of most responsible profession, and it is not only a job of an artisan. This profes-sion needs a developed ability to identify oneself with the chosen teaching profession. Research questions: How teachers characterize their authentic individual professional identity? What factors teachers exclude, which support and limit the professional identity? Aim was to develop the grounded theory (GT) about teacher’s professional identity (TPI). Research methodology is based on Charmaz GT version. Data were collected via semi-structured interviews with the he sample of 12 teachers. Findings. 15 extracted categories revealed that the core of TPI is teacher’s professional calling. Premises of TPI are family support, motives for choos-ing teacher’s profession, teacher’s didactic competence. Context of TPI consists of teacher compli-ance with the profession, purposeful preparation for pedagogical studies, professional growth. The strategy of TPI is based on teacher relationship with school community strengthening. The profes-sional frustration limits the TPI. TPI outcome includes teacher recognition, authority; professional mastership, professionalism, professional satisfaction. Dimensions of TPI GT the past (reaching teacher’s profession), present (teacher’s commitment to professional activity) and future (teacher’s profession reconsideration). Conclusions. The substantive GT describes professional identity as complex, changing and life-long process, which develops together with teacher’s personal identity and is connected to professional activity. The professional decision "to be a teacher" is determined by the interaction of internal (professional vocation, personal characteristics, values, self-image, talents, abilities) and external (family, friends, school community, labor market, working condi-tions) factors. The dimensions of the TPI development includes: the past (the pursuit of the teaching profession), the present (the teacher's commitment to professional activity) and the future (the revi-sion of the teaching profession). A significant connection emerged - as the teacher's professional commitment strengthens (creating a self-image, growing the teacher's professional experience, recognition, professionalism, mastery, satisfaction with pedagogical activity), the dimension of re-thinking the teacher's profession weakens. This proves that professional identity occupies an im-portant place in a teacher's life and it affects his professional success and job satisfaction. Teachers singled out the main factors supporting a teacher's professional identity: their own self-image per-ception, professional vocation, positive personal qualities, internal motivation, teacher recognition, confidence in choosing a teaching profession, job satisfaction, professional knowledge, professional growth, good relations with the school community, pleasant experiences, quality education process, excellent student achievements.

Keywords: grounded theory, teacher professional identity, semi-structured interview, school, students, school community, family

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Authors: Adedayo B. Adegbaju, Carel B. Schoeman, Ilse M. Schoeman

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The unique urban contexts that emanated from the apartheid history of South Africa informed the transport landscape of the City of Johannesburg. Apartheid‘s divisive spatial planning and land use management policies promoted sprawling and separated workers from job opportunities. This was further exacerbated by poor funding of public transport and road designs that encouraged the use of private cars. However, the democratization of the country in 1994 and the hosting of the 2010 FIFA World Cup provided a new impetus to the city’s public transport-oriented urban planning inputs. At the same time, the state’s new approach to policy formulations that entails the provision of public transport as one of the tools to end years of marginalization and inequalities soon began to largely reflect in planning decisions of other spheres of government. The Rea Vaya BRT and the Gautrain were respectively implemented by the municipal and provincial governments to demonstrate strong political will and commitment to the new policy direction. While the Gautrain was implemented to facilitate elite movement within Gauteng and to crowd investments and economic growths around station nodes, the BRT was provided for previously marginalized public transport users to provide a sustainable alternative to the dominant minibus taxi. The aim of this research is to evaluate the spatial impacts of the Gautrain and Rea Vaya BRT on the City of Johannesburg and to inform future outcomes by determining the existing potentials. By using the case study approach with a focus on the BRT and fast rail in a metropolitan context, the triangulation research method, which combines various data collection methods, was used to determine the research outcomes. The use of interviews, questionnaires, field observation, and databases such as REX, Quantec, StatsSA, GCRO observatory, national and provincial household travel surveys, and the quality of life surveys provided the basis for data collection. The research concludes that the Gautrain has demonstrated that viable alternatives to the private car can be provided, with its satisfactory feedbacks from users; while some of its station nodes (Sandton, Rosebank) have shown promises of transit-oriented development, one of the project‘s key objectives. The other stations have been unable to stimulate growth due to reasons like non-implementation of their urban design frameworks and lack of public sector investment required to attract private investors. The Rea Vaya BRT continues to be expanded in spite of both its inability to induce modal change and its low ridership figures. The research identifies factors like the low peak to base ratio, pricing, and the city‘s disjointed urban fabric as some of the reasons for its below-average performance. By drawing from the highlights and limitations, the study recommends that public transport provision should be institutionally integrated across and within spheres of government. Similarly, harmonization of the funding structure, better understanding of users’ needs, and travel patterns, underlined with continuity of policy direction and objectives, will equally promote optimal outcomes.

Keywords: bus rapid transit, Gautrain, Rea Vaya, sustainable transport, spatial and transport planning, transit oriented development

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Authors: Yohannes Haile, Dipo Onipede, Jr., Omar Ashour

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The main thrust of our research is to determine Industry 4.0 readiness of small and mid-size manufacturing companies in our region and assist them to implement Cyber Physical Production System (CPPS) capabilities. Adopting CPPS capabilities will help organizations realize improved quality, order delivery, throughput, new value creation, and reduced idle time of machines and work centers of their manufacturing operations. The key metrics for the assessment include the level of intelligence, internal and external connections, responsiveness to internal and external environmental changes, capabilities for customization of products with reference to cost, level of additive manufacturing, automation, and robotics integration, and capabilities to manufacture hybrid products in the near term, where near term is defined as 0 to 18 months. In our initial evaluation of several manufacturing firms which are profitable and successful in what they do, we found low level of Physical-Digital-Physical (PDP) loop in their manufacturing operations, whereas 100% of the firms included in this research have specialized manufacturing core competencies that have differentiated them from their competitors. The level of automation and robotics integration is low to medium range, where low is defined as less than 30%, and medium is defined as 30 to 70% of manufacturing operation to include automation and robotics. However, there is a significant drive to include these capabilities at the present time. As it pertains to intelligence and connection of manufacturing systems, it is observed to be low with significant variance in tying manufacturing operations management to Enterprise Resource Planning (ERP). Furthermore, it is observed that the integration of additive manufacturing in general, 3D printing, in particular, to be low, but with significant upside of integrating it in their manufacturing operations in the near future. To hasten the readiness of the local and regional manufacturing companies to Industry 4.0 and transitions towards CPPS capabilities, our working group (ADMAR Working Group) in partnership with our university have been engaged with the local and regional manufacturing companies. The goal is to increase awareness, share know-how and capabilities, initiate joint projects, and investigate the possibility of establishing the Center for Cyber Physical Production Systems Innovation (C2P2SI). The center is intended to support the local and regional university-industry research of implementing intelligent factories, enhance new value creation through disruptive innovations, the development of hybrid and data enhanced products, and the creation of digital manufacturing enterprises. All these efforts will enhance local and regional economic development and educate students that have well developed knowledge and applications of cyber physical manufacturing systems and Industry 4.0.

Keywords: automation, cyber-physical production system, digital manufacturing enterprises, disruptive innovation, new value creation, physical-digital-physical loop

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Authors: Tamar Lin, Nufar Buchshtab, Yifat Elharar, Julian Nicenboim, Rotem Edgar, Iddo Weiner, Lior Zelcbuch, Ariel Cohen, Sharon Kredo-Russo, Inbar Gahali-Sass, Naomi Zak, Sailaja Puttagunta, Merav Bassan

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Background: Atopic dermatitis (AD) is a chronic, relapsing inflammatory skin disorder that is characterized by dry skin and flares of eczematous lesions and intense pruritus. Multiple lines of evidence suggest that AD is associated with increased colonization by Staphylococcus aureus, which contributes to disease pathogenesis through the release of virulence factors that affect both keratinocytes and immune cells, leading to disruption of the skin barrier and immune cell dysfunction. The aim of the current study is to develop a bacteriophage-based product that specifically targets S. aureus. Methods: For the discovery of phage, environmental samples were screened on 118 S. aureus strains isolated from skin samples, followed by multiple enrichment steps. Natural phages were isolated, subjected to Next-generation Sequencing (NGS), and analyzed using proprietary bioinformatics tools for undesirable genes (toxins, antibiotic resistance genes, lysogeny potential), taxonomic classification, and purity. Phage host range was determined by an efficiency of plating (EOP) value above 0.1 and the ability of the cocktail to completely lyse liquid bacterial culture under different growth conditions (e.g., temperature, bacterial stage). Results: Sequencing analysis demonstrated that the 118 S. aureus clinical strains were distributed across the phylogenetic tree of all available Refseq S. aureus (~10,750 strains). Screening environmental samples on the S. aureus isolates resulted in the isolation of 50 lytic phages from different genera, including Silviavirus, Kayvirus, Podoviridae, and a novel unidentified phage. NGS sequencing confirmed the absence of toxic elements in the phages’ genomes. The host range of the individual phages, as measured by the efficiency of plating (EOP), ranged between 41% (48/118) to 79% (93/118). Host range studies in liquid culture revealed that a subset of the phages can infect a broad range of S. aureus strains in different metabolic states, including stationary state. Combining the single-phage EOP results of selected phages resulted in a broad host range cocktail which infected 92% (109/118) of the strains. When tested in vitro in a liquid infection assay, clearance was achieved in 87% (103/118) of the strains, with no evidence of phage resistance throughout the study (24 hours). A S. aureus host was identified that can be used for the production of all the phages in the cocktail at high titers suitable for large-scale manufacturing. This host was validated for the absence of contaminating prophages using advanced NGS methods combined with multiple production cycles. The phages are produced under optimized scale-up conditions and are being used for the development of a topical formulation (BX005) that may be administered to subjects with atopic dermatitis. Conclusions: A cocktail of natural phages targeting S. aureus was effective in reducing bacterial burden across multiple assays. Phage products may offer safe and effective steroid-sparing options for atopic dermatitis.

Keywords: atopic dermatitis, bacteriophage cocktail, host range, Staphylococcus aureus

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Authors: Berna Çalışkan

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The integrated water management is a colloborative approach to planning that brings together institutions that influence all elements of the water cycle, waterways, watershed characteristics, wetlands, ponds, lakes, floodplain areas, stream channel structure. It encourages collaboration where it will be beneficial and links between water planning and other planning processes that contribute to improving sustainable urban development and liveability. Hydraulic considerations can influence the selection of a highway corridor and the alternate routes within the corridor. widening a roadway, replacing a culvert, or repairing a bridge. Because of this, the type and amount of data needed for planning studies can vary widely depending on such elements as environmental considerations, class of the proposed highway, state of land use development, and individual site conditions. The extraction of drainage networks provide helpful preliminary drainage data from the digital elevation model (DEM). A case study was carried out using the Arc Hydro extension within ArcGIS in the study area. It provides the means for processing and presenting spatially-referenced Stream Model. Study area’s flow routing, stream levels, segmentation, drainage point processing can be obtained using DEM as the 'Input surface raster'. These processes integrate the fields of hydrologic, engineering research, and environmental modeling in a multi-disciplinary program designed to provide decision makers with a science-based understanding, and innovative tools for, the development of interdisciplinary and multi-level approach. This research helps to manage transport project planning and construction phases to analyze the surficial water flow, high-level streams, wetland sites for development of transportation infrastructure planning, implementing, maintenance, monitoring and long-term evaluations to better face the challenges and solutions associated with effective management and enhancement to deal with Low, Medium, High levels of impact. Transport projects are frequently perceived as critical to the ‘success’ of major urban, metropolitan, regional and/or national development because of their potential to affect significant socio-economic and territorial change. In this context, sustaining and development of economic and social activities depend on having sufficient Water Resources Management. The results of our research provides a workflow to build a stream network how can classify suitability map according to stream levels. Transportation projects establish, develop, incorporate and deliver effectively by selecting best location for reducing construction maintenance costs, cost-effective solutions for drainage, landslide, flood control. According to model findings, field study should be done for filling gaps and checking for errors. In future researches, this study can be extended for determining and preventing possible damage of Sensitive Areas and Vulnerable Zones supported with field investigations.

Keywords: water resources management, hydro tool, water protection, transportation

Procedia PDF Downloads 58

Authors: Safa Ladhari, Alireza Saidi, Phuong Nguyen-Tri

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During health crises, such as COVID-19, using disposable protective equipment (PEs) (masks, gowns, etc.) causes long-term problems, increasing the volume of hazardous waste that must be handled safely and expensively. Therefore, producing textiles for antimicrobial and reusable materials is highly desirable to decrease the use of disposable PEs that should be treated as hazardous waste. In addition, if these items are used regularly in the workplace or for daily activities by the public, they will most likely end up in household waste. Furthermore, they may pose a high risk of contagion to waste collection workers if contaminated. Therefore, to protect the whole population in times of sanitary crisis, it is necessary to equip these materials with tools that make them resilient to the challenges of carrying out daily activities without compromising public health and the environment and without depending on them external technologies and producers. In addition, the materials frequently used for EPs are plastics of petrochemical origin. The subject of the present work is replacing petroplastics with bioplastic since it offers better biodegradability. The chosen polymer is polyhydroxybutyrate (PHB), a family of polyhydroxyalkanoates synthesized by different bacteria. It has similar properties to conventional plastics. However, it is renewable, biocompatible, and has attractive barrier properties compared to other polyesters. These characteristics make it ideal for EP protection applications. The current research topic focuses on the preparation and rapid evaluation of the biological activity of nanotechnology-based antimicrobial agents to treat textile surfaces used for PE. This work will be carried out to provide antibacterial solutions that can be transferred to a workplace application in the fight against short-term biological risks. Three main objectives are proposed during this research topic: 1) the development of suitable methods for the deposition of antibacterial agents on the surface of textiles; 2) the development of a method for measuring the antibacterial activity of the prepared textiles and 3) the study of the biodegradability of the prepared textiles. The studied textile is a non-woven fabric based on a biodegradable polymer manufactured by the electrospinning method. Indeed, nanofibers are increasingly studied due to their unique characteristics, such as high surface-to-volume ratio, improved thermal, mechanical, and electrical properties, and confinement effects. The electrospun film will be surface modified by plasma treatment and then loaded with hybrid antibacterial silver and titanium dioxide nanoparticles by the dip-coating method. This work uses simple methods with emerging technologies to fabricate nanofibers with suitable size and morphology to be used as components for protective equipment. The antibacterial agents generally used are based on silver, zinc, copper, etc. However, to our knowledge, few researchers have used hybrid nanoparticles to ensure antibacterial activity with biodegradable polymers. Also, we will exploit visible light to improve the antibacterial effectiveness of the fabric, which differs from the traditional contact mode of killing bacteria and presents an innovation of active protective equipment. Finally, this work will allow for the innovation of new antibacterial textile materials through a simple and ecological method.

Keywords: protective equipment, antibacterial textile materials, biodegradable polymer, electrospinning, hybrid antibacterial nanoparticles

Procedia PDF Downloads 82

Authors: Jan C. Droste, Justine Burns, Nithin Narayan

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Introduction: Life-threatening detrimental effects of inappropriate adrenaline (epinephrine) administration, e.g., by giving the wrong dose, in the context of anaphylaxis management is well documented in the medical literature. Half of the fatal anaphylactic reactions in the UK are iatrogenic, and the median time to a cardio-respiratory arrest can be as short as 5 minutes. It is therefore imperative that hospital doctors of all grades have active and accurate knowledge of the correct route, site, and dosage of administration of adrenaline. Given this time constraint and the potential fatal outcome with inappropriate management of anaphylaxis, it is alarming that surveys over the last 15 years have repeatedly shown only a minority of doctors to have accurate knowledge of adrenaline administration as recommended by the UK Resuscitation Council guidelines (2008 updated 2012). This comparison of survey results of the medical workforce over several years in a small NHS District General Hospital was conducted in order to establish the effect of the employment of multiple educational methods regarding adrenaline administration in anaphylaxis in adults. Methods: Between 2010 and 2017, several education methods and tools were used to repeatedly inform the medical workforce (doctors and advanced clinical practitioners) in a single district general hospital regarding the treatment of anaphylaxis in adults. Whilst the senior staff remained largely the same cohort, junior staff had changed fully in every survey. Examples included: (i) Formal teaching -in Grand Rounds; during the junior doctors’ induction process; advanced life support courses (ii) In-situ simulation training performed by the clinical skills simulation team –several ad hoc sessions and one 3-day event in 2017 visiting 16 separate clinical areas performing an acute anaphylaxis scenario using actors- around 100 individuals from multi-disciplinary teams were involved (iii) Hospital-wide distribution of the simulation event via the Trust’s Simulation Newsletter (iv) Laminated algorithms were attached to the 'crash trolleys' (v) A short email 'alert' was sent to all medical staff 3 weeks prior to the survey detailing the emergency treatment of anaphylaxis (vi) In addition, the performance of the surveys themselves represented a teaching opportunity when gaps in knowledge could be addressed. Face to face surveys were carried out in 2010 ('pre-intervention), 2015, and 2017, in the latter two occasions including advanced clinical practitioners (ACP). All surveys consisted of convenience samples. If verbal consent to conduct the survey was obtained, the medical practitioners' answers were recorded immediately on a data collection sheet. Results: There was a sustained improvement in the knowledge of the medical workforce from 2010 to 2017: Answers improved regarding correct drug by 11% (84%, 95%, and 95%); the correct route by 20% (76%, 90%, and 96%); correct site by 40% (43%, 83%, and 83%) and the correct dose by 45% (27%, 54%, and 72%). Overall, knowledge of all components -correct drug, route, site, and dose-improved from 13% in 2010 to 62% in 2017. Conclusion: This survey comparison shows knowledge of the medical workforce regarding adrenaline administration for treatment of anaphylaxis in adults can be considerably improved by employing a variety of educational methods.

Keywords: adrenaline, anaphylaxis, epinephrine, medical education, patient safety

Procedia PDF Downloads 129

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

Procedia PDF Downloads 351

Authors: Medan Isaeva, Anna Degtyareva

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Context: Biliary atresia is a common reason for liver transplants in children, and the Kasai procedure can potentially be successful in avoiding the need for transplantation. However, it is important to identify factors that influence surgical outcomes in order to optimize treatment and improve patient outcomes. Research aim: The aim of this study was to develop prognostic models to assess the outcomes of the Kasai procedure in children with biliary atresia. Methodology: This retrospective study analyzed data from 166 children with biliary atresia who underwent the Kasai procedure between 2002 and 2021. The effectiveness of the operation was assessed based on specific criteria, including post-operative stool color, jaundice reduction, and bilirubin levels. The study involved a comparative analysis of various parameters, such as gestational age, birth weight, age at operation, physical development, liver and spleen sizes, and laboratory values including bilirubin, ALT, AST, and others, measured pre- and post-operation. Ultrasonographic evaluations were also conducted pre-operation, assessing the hepatobiliary system and related quantitative parameters. The study was carried out by two experienced specialists in pediatric hepatology. Comparative analysis and multifactorial logistic regression were used as the primary statistical methods. Findings: The study identified several statistically significant predictors of a successful Kasai procedure, including the presence of the gallbladder and levels of cholesterol and direct bilirubin post-operation. A detectable gallbladder was associated with a higher probability of surgical success, while elevated post-operative cholesterol and direct bilirubin levels were indicative of a reduced chance of positive outcomes. Theoretical importance: The findings of this study contribute to the optimization of treatment strategies for children with biliary atresia undergoing the Kasai procedure. By identifying early predictive signs of success, clinicians can modify treatment plans and manage patient care more effectively and proactively. Data collection and analysis procedures: Data for this analysis were obtained from the health records of patients who received the Kasai procedure. Comparative analysis and multifactorial logistic regression were employed to analyze the data and identify significant predictors. Question addressed: The study addressed the question of identifying predictive factors for the success of the Kasai procedure in children with biliary atresia. Conclusion: The developed prognostic models serve as valuable tools for early detection of patients who are less likely to benefit from the Kasai procedure. This enables clinicians to modify treatment plans and manage patient care more effectively and proactively. Potential limitations of the study: The study has several limitations. Its retrospective nature may introduce biases and inconsistencies in data collection. Being single centered, the results might not be generalizable to wider populations due to variations in surgical and postoperative practices. Also, other potential influencing factors beyond the clinical, laboratory, and ultrasonographic parameters considered in this study were not explored, which could affect the outcomes of the Kasai operation. Future studies could benefit from including a broader range of factors.

Keywords: biliary atresia, kasai operation, prognostic model, native liver survival

Procedia PDF Downloads 56

Authors: Zakia Hbellaq

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The Mediterranean region is considered a hotbed for climate change. Morocco is a semi-arid Mediterranean country facing water shortages and poor water quality. Its limited water resources limit the activities of various economic sectors. Most of Morocco's territory is in arid and desert areas. The potential water resources are estimated at 22 billion m3, which is equivalent to about 700 m3/inhabitant/year, and Morocco is in a state of structural water stress. Strictly speaking, the Kingdom of Morocco is one of the “very riskiest” countries, according to the World Resources Institute (WRI), which oversees the calculation of water stress risk in 167 countries. The surprising results of the Institute (WRI) rank Morocco as one of the riskiest countries in terms of water scarcity, ranking 3.89 out of 5, thus occupying the 23rd place out of a total of 167 countries, which indicates that the demand for water exceeds the available resources. Agriculture with a score of 3.89 is most affected by water stress from irrigation and places a heavy burden on the water table. Irrigation is an unavoidable technical need and has undeniable economic and social benefits given the available resources and climatic conditions. Irrigation, and therefore the agricultural sector, currently uses 86% of its water resources, while industry uses 5.5%. Although its development has undeniable economic and social benefits, it also contributes to the overfishing of most groundwater resources and the surprising decline in levels and deterioration of water quality in some aquifers. In this context, REUSE is one of the proposed solutions to reduce the water footprint of the agricultural sector and alleviate the shortage of water resources. Indeed, wastewater reuse, also known as REUSE (reuse of treated wastewater), is a step forward not only for the circular economy but also for the future, especially in the context of climate change. In particular, water reuse provides an alternative to existing water supplies and can be used to improve water security, sustainability, and resilience. However, given the introduction of organic trace pollutants or, organic micro-pollutants, the absorption of emerging contaminants, and decreasing salinity, it is possible to tackle innovative capabilities to overcome these problems and ensure food and health safety. To this end, attention will be paid to the adoption of an integrated and attractive approach, based on the reinforcement and optimization of the treatments proposed for the elimination of the organic load with particular attention to the elimination of emerging pollutants, to achieve this goal. , membrane bioreactors (MBR) as stand-alone technologies are not able to meet the requirements of WHO guidelines. They will be combined with heterogeneous Fenton processes using persulfate or hydrogen peroxide oxidants. Similarly, adsorption and filtration are applied as tertiary treatment In addition, the evaluation of crop performance in terms of yield, productivity, quality, and safety, through the optimization of Trichoderma sp strains that will be used to increase crop resistance to abiotic stresses, as well as the use of modern omics tools such as transcriptomic analysis using RNA sequencing and methylation to identify adaptive traits and associated genetic diversity that is tolerant/resistant/resilient to biotic and abiotic stresses. Hence, ensuring this approach will undoubtedly alleviate water scarcity and, likewise, increase the negative and harmful impact of wastewater irrigation on the condition of crops and the health of their consumers.

Keywords: water scarcity, food security, irrigation, agricultural water footprint, reuse, emerging contaminants

Procedia PDF Downloads 163

Authors: William Kerua

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The PNG University of Technology (Unitech) has mandatory access to teaching, research and extension education. Given such function, the Agriculture Department has established the ‘South Pacific Institute of Sustainable Agriculture and Rural Development (SPISARD)’ in 2004. SPISARD is established as a vehicle to improve farming systems practiced in selected villages by undertaking pluralistic extension method through ‘Educational Institutional Approach’. Unlike other models, SPISARD’s educational institutional approach stresses on improving the whole farming systems practiced in a holistic manner and has a two-fold focus. The first is to understand the farming communities and improve the productivity of the farming systems in a sustainable way to increase income, improve nutrition and food security as well as livelihood enhancement trainings. The second is to enrich the Department’s curriculum through teaching, research, extension and getting inputs from farming community. SPISARD has established number of model villages in various provinces in Papua New Guinea (PNG) and with many positive outcome and success stories. Adaption of ‘educational institutional approach’ thus binds research, extension and training into one package with the use of students and academic staff through model village establishment in delivering development and extension to communities. This centre (SPISARD) coordinates the activities of the model village programs and linkages. The key to the development of the farming systems is establishing and coordinating linkages, collaboration, and developing partnerships both within and external institutions, organizations and agencies. SPISARD has a six-point step strategy for the development of sustainable agriculture and rural development. These steps are (i) establish contact and identify model villages, (ii) development of model village resource centres for research and trainings, (iii) conduct baseline surveys to identify problems/needs of model villages, (iv) development of solution strategies, (v) implementation and (vi) evaluation of impact of solution programs. SPISARD envisages that the farming systems practiced being improved if the villages can be made the centre of SPISARD activities. Therefore, SPISARD has developed a model village approach to channel rural development. The model village when established become the conduit points where teaching, training, research, and technology transfer takes place. This approach is again different and unique to the existing ones, in that, the development process take place in the farmers’ environment with immediate ‘real time’ feedback mechanisms based on the farmers’ perspective and satisfaction. So far, we have developed 14 model villages and have conducted 75 trainings in 21 different areas/topics in 8 provinces to a total of 2,832 participants of both sex. The aim of these trainings is to directly participate with farmers in the pursuit to improving their farming systems to increase productivity, income and to secure food security and nutrition, thus to improve their livelihood.

Keywords: development, educational institutional approach, livelihood improvement, sustainable agriculture

Procedia PDF Downloads 155

Authors: Parth Gupta, Ujjawal Singh, Shashank Kumar, Mansi Chandra, Arnab Sarkar

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Microfluidic devices have emerged as indispensable tools across various scientific disciplines, offering precise control and manipulation of fluids at the microscale. Their efficacy in flow-based research, spanning engineering, chemistry, and biology, relies heavily on the geometric design of microfluidic channels. This work introduces a novel approach to optimise these channels through Response Surface Methodology (RSM), departing from the conventional practice of addressing one parameter at a time. Traditionally, optimising microfluidic channels involved isolated adjustments to individual parameters, limiting the comprehensive understanding of their combined effects. In contrast, our approach considers the simultaneous impact of multiple parameters, employing RSM to efficiently explore the complex design space. The outcome is an innovative microfluidic channel that consumes an optimal sample volume and minimises flow time, enhancing overall efficiency. The relevance of geometric parameter optimization in microfluidic channels extends significantly in biomedical engineering. The flow characteristics of porous materials within these channels depend on many factors, including fluid viscosity, environmental conditions (such as temperature and humidity), and specific design parameters like sample volume, channel width, channel length, and substrate porosity. This intricate interplay directly influences the performance and efficacy of microfluidic devices, which, if not optimized, can lead to increased costs and errors in disease testing and analysis. In the context of biomedical applications, the proposed approach addresses the critical need for precision in fluid flow. it mitigate manufacturing costs associated with trial-and-error methodologies by optimising multiple geometric parameters concurrently. The resulting microfluidic channels offer enhanced performance and contribute to a streamlined, cost-effective process for testing and analyzing diseases. A key highlight of our methodology is its consideration of the interconnected nature of geometric parameters. For instance, the volume of the sample, when optimized alongside channel width, length, and substrate porosity, creates a synergistic effect that minimizes errors and maximizes efficiency. This holistic optimization approach ensures that microfluidic devices operate at their peak performance, delivering reliable results in disease testing. A key highlight of our methodology is its consideration of the interconnected nature of geometric parameters. For instance, the volume of the sample, when optimized alongside channel width, length, and substrate porosity, creates a synergistic effect that minimizes errors and maximizes efficiency. This holistic optimization approach ensures that microfluidic devices operate at their peak performance, delivering reliable results in disease testing. A key highlight of our methodology is its consideration of the interconnected nature of geometric parameters. For instance, the volume of the sample, when optimized alongside channel width, length, and substrate porosity, creates a synergistic effect that minimizes errors and maximizes efficiency. This holistic optimization approach ensures that microfluidic devices operate at their peak performance, delivering reliable results in disease testing.

Keywords: microfluidic device, minitab, statistical optimization, response surface methodology

Procedia PDF Downloads 70

Authors: Haleema Sadia

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The study is aimed at exploring the identity construction of female British born Pakistani postgraduate student who shifted to Pakistan at the age of 12, stayed there for 8 years and re-shifted to UK for Higher Education. Research questions are: 1. What is the academic and socio-cultural background of the participant prior to joining the UoM as a postgrad student? 2. How the participant talk, see herself and act in relation to cultural and social norms and practices? Participant’ identity is explored through positioning theory of Holland et al. (1998), referring to the ways people understand and enact their social positions in the figured world. The research is a case study based on narrative interview of Shabana, a British-born Pakistani female postgraduate student, who has recently joined the university of Manchester. Shabana received her primary education in UK during the first twelve years of her life. She is the youngest among the three sisters, with only one brother younger to her. Her father, although not well educated is a successful entrepreneur, maintaining offices in UK and Pakistan. Her mother is a housewife with no formal education. Shabana’s elder sister got involved in a relationship with a Pakistani boy against cultural norms of arranged marriage. Resultantly the three sisters were shifted to Pakistan to be equated with socio-religious norms. Shabana termed her first year in Pakistan as disgusting and she hated her father for the decision. However after a year’s time and shifting from an orthodox city to the provincial capital Lahore, she developed liking for the Pakistani culture. She gradually developed a new socio-religious identity during her stay, which she expressed as a turning point in her life. After completing O level Shabana returned back to UK and joined the University of Hull as undergraduate Student. At Hull she remained isolated, missed the religious environment and relished the memories of Lahore. She would visit Pakistan almost three times a year. After obtaining her BSc degree from Hull she went back to Pakistan. Soon after she decided to improve her academic qualification. She came to UK to join her parents and got admission in the MSc chemistry program at UoM. Presently Shabana talks about the dominant role of male members in the family culture in decision-making. She strongly feels to struggle hard and attain equal status with males in education, employment, earning, authority and freedom. She sees herself in a position to share the authority with her (would be) husband in important family and other matters. Shabana has developed a new identity of a mix of both Pakistani and UK culture. She is appreciative of the socio-cultural values of UK while still regarding the cultural and religious values of Pakistan in high esteem.

Keywords: postgraduate students, identity construction, cultural shifts, female british pakistani student

Procedia PDF Downloads 627

Authors: Zachary Blanks, Solomon Sonya

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Poaching presents a serious threat to endangered animal species, environment conservations, and human life. Additionally, some poaching activity has even been linked to supplying funds to support terrorist networks elsewhere around the world. Consequently, agencies dedicated to protecting wildlife habitats have a near intractable task of adequately patrolling an entire area (spanning several thousand kilometers) given limited resources, funds, and personnel at their disposal. Thus, agencies need predictive tools that are both high-performing and easily implementable by the user to help in learning how the significant features (e.g. animal population densities, topography, behavior patterns of the criminals within the area, etc) interact with each other in hopes of abating poaching. This research develops a classification model using machine learning algorithms to aid in forecasting future attacks that is both easy to train and performs well when compared to other models. In this research, we demonstrate how data imputation methods (specifically predictive mean matching, gradient boosting, and random forest multiple imputation) can be applied to analyze data and create significant predictions across a varied data set. Specifically, we apply these methods to improve the accuracy of adopted prediction models (Logistic Regression, Support Vector Machine, etc). Finally, we assess the performance of the model and the accuracy of our data imputation methods by learning on a real-world data set constituting four years of imputed data and testing on one year of non-imputed data. This paper provides three main contributions. First, we extend work done by the Teamcore and CREATE (Center for Risk and Economic Analysis of Terrorism Events) research group at the University of Southern California (USC) working in conjunction with the Department of Homeland Security to apply game theory and machine learning algorithms to develop more efficient ways of reducing poaching. This research introduces ensemble methods (Random Forests and Stochastic Gradient Boosting) and applies it to real-world poaching data gathered from the Ugandan rain forest park rangers. Next, we consider the effect of data imputation on both the performance of various algorithms and the general accuracy of the method itself when applied to a dependent variable where a large number of observations are missing. Third, we provide an alternate approach to predict the probability of observing poaching both by season and by month. The results from this research are very promising. We conclude that by using Stochastic Gradient Boosting to predict observations for non-commercial poaching by season, we are able to produce statistically equivalent results while being orders of magnitude faster in computation time and complexity. Additionally, when predicting potential poaching incidents by individual month vice entire seasons, boosting techniques produce a mean area under the curve increase of approximately 3% relative to previous prediction schedules by entire seasons.

Keywords: ensemble methods, imputation, machine learning, random forests, statistical analysis, stochastic gradient boosting, wildlife protection

Procedia PDF Downloads 294

Authors: Sarah Nauwelaerts, Koen De Cremer, Alfred Bernard, Meredith Verlooy, Kristel Heremans, Natalia Bustos Sierra, Katrien Tersago, Tim Nawrot, Jordy Vercauteren, Christophe Stroobants, Sigrid C. J. De Keersmaecker, Nancy Roosens

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Projected climate changes could lead to exacerbation of respiratory disorders associated with reduced air quality. Air pollution and climate changes influence each other through complex interactions. The poor air quality in urban and rural areas includes high levels of particulate matter (PM), ozone (O3) and nitrogen oxides (NOx), representing a major threat to public health and especially for the most vulnerable population strata, and especially young children. In this study, we aim to develop generic standardized policy supporting tools and methods that allow evaluating in future follow-up larger scale epidemiological studies the risks of the combined short-term effects of O3 and PM on the cardiorespiratory system of children. We will use non-invasive indicators of airway damage/inflammation and of genetic or epigenetic variations by using urine or saliva as alternative to blood samples. Therefore, a multi-phase field study will be organized in order to assess the sensitivity and applicability of these tests in large cohorts of children during episodes of air pollution. A first test phase was planned in March 2018, not yet taking into account ‘critical’ pollution periods. Working with non-invasive samples, choosing the right set-up for the field work and the volunteer selection were parameters to consider, as they significantly influence the feasibility of this type of study. During this test phase, the selection of the volunteers was done in collaboration with medical doctors from the Centre for Student Assistance (CLB), by choosing a class of pre-pubertal children of 9-11 years old in a primary school in Flemish Brabant, Belgium. A questionnaire, collecting information on the health and background of children and an informed consent document were drawn up for the parents as well as a simplified cartoon-version of this document for the children. A detailed study protocol was established, giving clear information on the study objectives, the recruitment, the sample types, the medical examinations to be performed, the strategy to ensure anonymity, and finally on the sample processing. Furthermore, the protocol describes how this field study will be conducted in relation with the prevision and monitoring of air pollutants for the future phases. Potential protein, genetic and epigenetic biomarkers reflecting the respiratory function and the levels of air pollution will be measured in the collected samples using unconventional technologies. The test phase results will be used to address the most important bottlenecks before proceeding to the following phases of the study where the combined effect of O3 and PM during pollution peaks will be examined. This feasibility study will allow identifying possible bottlenecks and providing missing scientific knowledge, necessary for the preparation, implementation and evaluation of federal policies/strategies, based on the most appropriate epidemiological studies on the health effects of air pollution. The research leading to these results has been funded by the Belgian Science Policy Office through contract No.: BR/165/PI/PMOLLUGENIX-V2.

Keywords: air pollution, biomarkers, children, field study, feasibility study, non-invasive

Procedia PDF Downloads 179

Authors: W. Linthicum-Blackhorse, P. Martens

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This present study seeks to discover attitudinal commonalities and differences within a musician population relative to the communication of emotion via music. We hypothesized that instrument type, as well as age and gender, would bear significantly on musicians’ opinions. A survey was administered to 178 participants; 152 were current music majors (mean age 20.3 years, 62 female) and 26 were adult participants in a community choir (mean age 54.0 years, 12 female). The adult participants were all vocalists, while student participants represented the full range of orchestral instruments. The students were grouped by degree program, (performance, music education, or other) and instrument type (voice, brass, woodwinds, strings, percussion). The survey asked 'How important are each of the following areas to you for portraying emotion in music?' Participants were asked to rate each of 15 items on a scale of 1 (not at all important) to 10 (very important). Participants were also instructed to leave blank any item that they did not understand. The 15 items were: dynamic contrast, overall volume, phrasing, facial expression, staging (placement), pitch accuracy, tempo changes, bodily movement, your mood, your attitude, vibrato, rubato, stage/room lighting, clothing type, and clothing color. Contrary to our hypothesis, there was no overall effect of gender or age, and neither did any single response item show a significant difference due to these subject parameters. Among the student participants, however, one-way ANOVA revealed a significant effect of degree program on the rated importance of four items: dynamic contrast, tempo changes, vibrato, and rubato. Significant effects of instrument type were found in the responses to eight items: facial expression, staging, body movement, vibrato, rubato, lighting, clothing type, and clothing color. Post hoc comparisons (Tukey) show that some variation follows from obvious differences between instrument types (e.g. string players are more concerned with vibrato than everyone but woodwind players; vocalists are significantly more concerned with facial expression than everyone but string players), but other differences could point to communal mindsets toward vicarious cues within instrument type. These mindsets could be global (e.g. brass players deeming body movement significantly less important than string players, being less often featured as soloists and appearing less often at the front of the stage) or local (e.g. string players being significantly more concerned than all other groups about both clothing color and type, perhaps due to the strongly-expressed opinions of specific teachers). Future work will attempt to identify the source of these self-appraisals, whether enculturated via explicit pedagogy, or whether absorbed from individuals' observations and performance experience.

Keywords: performance, vicarious cues, communication, emotion

Procedia PDF Downloads 111

Authors: Esmael Makarian, Ayub Elyasi, Fatemeh Saberi, Olusegun Stanley Tomomewo

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Rock mechanical investigation is one of the most crucial activities in underground operations, especially in surveys related to hydrocarbon exploration and production, geothermal reservoirs, energy storage, mining, and geotechnics. There is a wide range of traditional methods for driving, collecting, and analyzing rock mechanics data. However, these approaches may not be suitable or work perfectly in some situations, such as fractured zones. Cutting-edge technologies have been provided to solve and optimize the mentioned issues. Internet of Things (IoT), Edge, and Cloud Computing technologies (ECt & CCt, respectively) are among the most widely used and new artificial intelligence methods employed for geomechanical studies. IoT devices act as sensors and cameras for real-time monitoring and mechanical-geological data collection of rocks, such as temperature, movement, pressure, or stress levels. Structural integrity, especially for cap rocks within hydrocarbon systems, and rock mass behavior assessment, to further activities such as enhanced oil recovery (EOR) and underground gas storage (UGS), or to improve safety risk management (SRM) and potential hazards identification (P.H.I), are other benefits from IoT technologies. EC techniques can process, aggregate, and analyze data immediately collected by IoT on a real-time scale, providing detailed insights into the behavior of rocks in various situations (e.g., stress, temperature, and pressure), establishing patterns quickly, and detecting trends. Therefore, this state-of-the-art and useful technology can adopt autonomous systems in rock mechanical surveys, such as drilling and production (in hydrocarbon wells) or excavation (in mining and geotechnics industries). Besides, ECt allows all rock-related operations to be controlled remotely and enables operators to apply changes or make adjustments. It must be mentioned that this feature is very important in environmental goals. More often than not, rock mechanical studies consist of different data, such as laboratory tests, field operations, and indirect information like seismic or well-logging data. CCt provides a useful platform for storing and managing a great deal of volume and different information, which can be very useful in fractured zones. Additionally, CCt supplies powerful tools for predicting, modeling, and simulating rock mechanical information, especially in fractured zones within vast areas. Also, it is a suitable source for sharing extensive information on rock mechanics, such as the direction and size of fractures in a large oil field or mine. The comprehensive review findings demonstrate that digital transformation through integrated IoT, Edge, and Cloud solutions is revolutionizing traditional rock mechanical investigation. These advanced technologies have empowered real-time monitoring, predictive analysis, and data-driven decision-making, culminating in noteworthy enhancements in safety, efficiency, and sustainability. Therefore, by employing IoT, CCt, and ECt, underground operations have experienced a significant boost, allowing for timely and informed actions using real-time data insights. The successful implementation of IoT, CCt, and ECt has led to optimized and safer operations, optimized processes, and environmentally conscious approaches in underground geological endeavors.

Keywords: rock mechanical studies, internet of things, edge computing, cloud computing, underground surveys, geological operations

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Authors: S. J. Yune, S. Y. Lee, S. J. Im, B. S. Kam, S. Y. Baek

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This study aimed to determine the reliability of clinical performance assessments, having been emphasized by ability-based education, and professors overall assessment methods. We addressed the following problems: First, we try to find out whether there is a difference in what we consider to be the main variables affecting the clinical performance test according to the evaluator’s working period and the number of evaluation experience. Second, we examined the relationship among the global rating score (G), analytic global rating score (Gc), and the sum of the analytical checklists (C). What are the main factors affecting clinical performance assessments in relation to the numbers of times the evaluator had administered evaluations and the length of their working period service? What is the relationship between overall assessment score and analytic checklist score? How does analytic global rating with 6 components in OSCE and 4 components in sub-domains (Gc) CPX: aseptic practice, precision, systemic approach, proficiency, successfulness, and attitude overall assessment score and task-specific analytic checklist score sum (C) affect the professor’s overall global rating assessment score (G)? We studied 75 professors who attended a 2016 Bugyeoung Consortium clinical skills performances test evaluating third and fourth year medical students at the Pusan National University Medical school in South Korea (39 prof. in OSCE, 36 prof. in CPX; all consented to participate in our study). Each evaluator used 3 forms; a task-specific analytic checklist, subsequent analytic global rating scale with sub-6 domains, and overall global scale. After the evaluation, the professors responded to the questionnaire on the important factors of clinical performance assessment. The data were analyzed by frequency analysis, correlation analysis, and hierarchical regression analysis using SPSS 21.0. Their understanding of overall assessment was analyzed by dividing the subjects into groups based on experiences. As a result, they considered ‘precision’ most important in overall OSCE assessment, and ‘precise accuracy physical examination’, ‘systemic approaches to taking patient history’, and ‘diagnostic skill capability’ in overall CPX assessment. For OSCE, there was no clear difference of opinion about the main factors, but there was for CPX. Analytic global rating scale score, overall rating scale score, and analytic checklist score had meaningful mutual correlations. According to the regression analysis results, task-specific checklist score sum had the greatest effect on overall global rating. professors regarded task-specific analytic checklist total score sum as best reflecting overall OSCE test score, followed by aseptic practice, precision, systemic approach, proficiency, successfulness, and attitude on a subsequent analytic global rating scale. For CPX, subsequent analytic global rating scale score, overall global rating scale score, and task-specific checklist score had meaningful mutual correlations. These findings support explanations for validity of professors’ global rating in clinical performance assessment.

Keywords: global rating, clinical performance assessment, medical education, analytic checklist

Procedia PDF Downloads 235

Authors: Ye Xue, Zhenhua Deng

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Objectives: Facial soft tissue thickness (FSTT) data could be obtained from CT scans by measuring the face-to-skull distances at sparsely distributed anatomical landmarks by manually located on face and skull. However, automated measurement using 3D facial and skull models by dense points using open-source software has become a viable option due to the development of computed assisted imaging technologies. By utilizing dense FSTT information, it becomes feasible to generate plausible automated facial approximations. Therefore, establishing a comprehensive and detailed, densely calculated FSTT database is crucial in enhancing the accuracy of facial approximation. Materials and methods: This study utilized head CT scans from 250 Chinese adults of Han ethnicity, with 170 participants originally born and residing in northern China and 80 participants in southern China. The age of the participants ranged from 14 to 82 years, and all samples were divided into five non-overlapping age groups. Additionally, samples were also divided into three categories based on BMI information. The 3D Slicer software was utilized to segment bone and soft tissue based on different Hounsfield Unit (HU) thresholds, and surface models of the face and skull were reconstructed for all samples from CT data. Following procedures were performed unsing MeshLab, including converting the face models into hollowed cropped surface models amd automatically measuring the Hausdorff Distance (referred to as FSTT) between the skull and face models. Hausdorff point clouds were colorized based on depth value and exported as PLY files. A histogram of the depth distributions could be view and subdivided into smaller increments. All PLY files were visualized of Hausdorff distance value of each vertex. Basic descriptive statistics (i.e., mean, maximum, minimum and standard deviation etc.) and distribution of FSTT were analysis considering the sex, age, BMI and birthplace. Statistical methods employed included Multiple Regression Analysis, ANOVA, principal component analysis (PCA). Results: The distribution of FSTT is mainly influenced by BMI and sex, as further supported by the results of the PCA analysis. Additionally, FSTT values exceeding 30mm were found to be more sensitive to sex. Birthplace-related differences were observed in regions such as the forehead, orbital, mandibular, and zygoma. Specifically, there are distribution variances in the depth range of 20-30mm, particularly in the mandibular region. Northern males exhibit thinner FSTT in the frontal region of the forehead compared to southern males, while females shows fewer distribution differences between the northern and southern, except for the zygoma region. The observed distribution variance in the orbital region could be attributed to differences in orbital size and shape. Discussion: This study provides a database of Chinese individuals distribution of FSTT and suggested opening source tool shows fine function for FSTT measurement. By incorporating birthplace as an influential factor in the distribution of FSTT, a greater level of detail can be achieved in facial approximation.

Keywords: forensic anthropology, forensic imaging, cranial facial reconstruction, facial soft tissue thickness, CT, open-source tool

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Authors: Rahy Farooq, Maria Ahmad Khan, Ayesha Isani Majeed

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Objective: The main aim of this research is to assess the knowledge, attitude and practices of female nursing staff and nursing students regarding breast cancer, to provide a baseline for monitoring trends of breast cancer awareness in them. Background: Healthcare professionals are a direct source of information for the patients and the general public as a whole. It is, therefore, essential that the information they convey be accurate and helps in building additional awareness. However, clinical experience does not influence the knowledge, attitude and practices regarding breast cancer. Nurses, being the prime part of the healthcare professionals, play a significant role and hence, their awareness regarding this pressing issue is pertinent. Lack of awareness regarding common presenting symptoms or breast cancer risk factors translates to poor breast cancer screening practices and late diagnosis. Methodology: A cross-sectional study of 280 female nurses was conducted at a tertiary care hospital in Islamabad, Pakistan. A pre-tested structured questionnaire with additional variables like cultural barriers to seeking medical help was used. The scores for outcome variables including knowledge, attitude and practices were pre-defined. Data was analyzed using SPSSv23. Results: Of the 280 participants with a mean age of 28.99±9.98 years, 142 (50.7%) were married, and 138 (49.3%) were unmarried. Mean scores were computed to be 6.14±2.93 (out of 12), 0.30±0.7 (out of 3) and 9.53±1.92 (out of 16) for knowledge, attitude and practice respectively. Using independent sample T-test, a statistically significant correlation was found when means for the score of Attitude was compared with age. With a p-value of 0.018, 117 nurses of age more than 30 years, faced more practical, financial, emotional and service barriers as compared to 163 women younger than 30 years of age. Knowledge of age-related lifetime risks was also significantly poor more in single women; with a p-value of 0.006 for identification of correct age as a risk factor and a p-value of 0.005 for correct identification of risk for development of breast cancer in the lifetime of women. By application of Chi-square test, there was a significant correlation between marital status and cultural barriers to seeking medical help, showing that single women (58.7%) shy away from talking about breast cancer considering it a taboo (p-value 0.028) whereas, more married nurses (59.2%) were apprehensive that they might be considered at fault by the society, as compared to 40.8% of single nurses. (p-value 0.038). Conclusion: Owing to the scarcity of awareness among nurses, this study recognizes the need for delivering effective information to the female nurses regarding breast cancer. Educating patients is likely to be effective if the female nurses play their part and have correct attitudes towards breast cancer practices. A better understanding of the knowledge and practices regarding breast cancer among the nursing population will enable high-risk patients to be recognized early. Therefore, we recommend arrangement of special courses and seminars for all healthcare professionals including the nursing staff.

Keywords: breast cancer, cultural barriers, kap, nurses

Procedia PDF Downloads 239

Authors: Rubaiat S. Ahmed, Jemer Garrido, Sergey M. Motov

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Clinical informatics (CI) enables the transformation of data into a systematic organization that improves the quality of care and the generation of positive health outcomes.Innovative technology through informatics that compiles accurate data on analgesic utilization in the emergency department can enhance pain management in this important clinical setting. We aim to establish a simplified reporting system through CI to examine and assess the analgesic prescribing practices in the EDthrough executing a U.S. federal grant project on opioid reduction initiatives. Queried data points of interest from a level-one trauma ED’s electronic medical records were used to create data sets and develop informational/visual reporting dashboards (on Microsoft Excel and Google Sheets) concerning analgesic usage across several pre-defined parameters and performance metrics using CI. The data was then qualitatively analyzed to evaluate ED analgesic prescribing trends by departmental clinicians and leadership. During a 12-month reporting period (Dec. 1, 2020 – Nov. 30, 2021) for the ongoing project, about 41% of all ED patient visits (N = 91,747) were for pain conditions, of which 81.6% received analgesics in the ED and at discharge (D/C). Of those treated with analgesics, 24.3% received opioids compared to 75.7% receiving opioid alternatives in the ED and at D/C, including non-pharmacological modalities. Demographics showed among patients receiving analgesics, 56.7% were aged between 18-64, 51.8% were male, 51.7% were white, and 66.2% had government funded health insurance. Ninety-one percent of all opioids prescribed were in the ED, with intravenous (IV) morphine, IV fentanyl, and morphine sulfate immediate release (MSIR) tablets accounting for 88.0% of ED dispensed opioids. With 9.3% of all opioids prescribed at D/C, MSIR was dispensed 72.1% of the time. Hydrocodone, oxycodone, and tramadol usage to only 10-15% of the time, and hydromorphone at 0%. Of opioid alternatives, non-steroidal anti-inflammatory drugs were utilized 60.3% of the time, 23.5% with local anesthetics and ultrasound-guided nerve blocks, and 7.9% with acetaminophen as the primary non-opioid drug categories prescribed by ED providers. Non-pharmacological analgesia included virtual reality and other modalities. An average of 18.5 ED opioid orders and 1.9 opioid D/C prescriptions per 102.4 daily ED patient visits was observed for the period. Compared to other specialties within our institution, 2.0% of opioid D/C prescriptions are given by ED providers, compared to the national average of 4.8%. Opioid alternatives accounted for 69.7% and 30.3% usage, versus 90.7% and 9.3% for opioids in the ED and D/C, respectively.There is a pressing need for concise, relevant, and reliable clinical data on analgesic utilization for ED providers and leadership to evaluate prescribing practices and make data-driven decisions. Basic computer software can be used to create effective visual reporting dashboards with indicators that convey relevant and timely information in an easy-to-digest manner. We accurately examined our ED's analgesic prescribing practices using CI through dashboard reporting. Such reporting tools can quickly identify key performance indicators and prioritize data to enhance pain management and promote safe prescribing practices in the emergency setting.

Keywords: clinical informatics, dashboards, emergency department, health informatics, healthcare informatics, medical informatics, opioids, pain management, technology

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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

Procedia PDF Downloads 241