Search results for: library program assessment

Authors: Rajkumar Ghosh

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Water scarcity is a pressing issue in urban areas, even in smart cities where efficient resource management is a priority. This scarcity is mainly caused by factors such as lifestyle changes, excessive groundwater extraction, over-usage of water, rapid urbanization, and uncontrolled population growth. In the specific case of Gomti Nagar, Lucknow, Uttar Pradesh, India, the depletion of groundwater resources is particularly severe, leading to a water imbalance and posing a significant challenge for the region's sustainable development. The aim of this study is to address the water shortage in the Gomti Nagar region by focusing on the implementation of artificial groundwater recharge methods. Specifically, the research aims to investigate the effectiveness of rainwater collection through rooftop rainwater harvesting systems (RTRWHs) as a sustainable approach to reduce aquifer depletion and bridge the gap between groundwater recharge and extraction. The research methodology for this study involves the utilization of RTRWHs as the main method for collecting rainwater. This approach is considered effective in managing and conserving water resources in a sustainable manner. The focus is on implementing RTRWHs in residential and commercial buildings to maximize the collection of rainwater and its subsequent utilization for various purposes in the Gomti Nagar region. The study reveals that the installation of RTRWHs in the Gomti Nagar region has a positive impact on addressing the water scarcity issue. Currently, RTRWHs cover only a small percentage (0.04%) of the total rainfall collected in the region. However, when RTRWHs are installed in all buildings, their influence on increasing water availability and reducing aquifer depletion will be significantly greater. The study also highlights the significant water imbalance of 24519 ML/yr in the region, emphasizing the urgent need for sustainable water management practices. This research contributes to the theoretical understanding of sustainable water management systems in smart cities. By highlighting the effectiveness of RTRWHs in reducing aquifer depletion, it emphasizes the importance of implementing such systems in urban areas. The findings of this study can serve as a basis for policymakers, urban planners, and developers to prioritize and incentivize the installation of RTRWHs as a potential solution to the water shortage crisis. The data for this study were collected through various sources such as government reports, surveys, and existing groundwater abstraction patterns. The collected data were then analysed to assess the current water situation, groundwater depletion rate, and the potential impact of implementing RTRWHs. Statistical analysis and modelling techniques were employed to quantify the water imbalance and evaluate the effectiveness of RTRWHs. The findings of this study demonstrate that the implementation of RTRWHs can effectively mitigate the water scarcity crisis in Gomti Nagar. By reducing aquifer depletion and bridging the gap between groundwater recharge and extraction, RTRWHs offer a sustainable solution to the region's water scarcity challenges. The study highlights the need for widespread adoption of RTRWHs in all buildings and emphasizes the importance of integrating such systems into the urban planning and development process. By doing so, smart cities like Gomti Nagar can achieve efficient water management, ensuring a better future with improved water availability for its residents.

Keywords: rooftop rainwater harvesting, rainwater, water management, aquifer

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Authors: Lyndsee Baumann-Birkbeck, Sohil A. Khan, Shailendra Anoopkumar-Dukie, Gary D. Grant

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Technology-enhanced education tools are being rapidly integrated into health programs globally. These tools provide an interactive platform for students and can be used to deliver topics in various modes including games and simulations. Simulations are of particular interest to healthcare education, where they are employed to enhance clinical knowledge and help to bridge the gap between theory and practice. Simulations will often assess competencies for practical tasks, yet limited research examines the effects of simulation on student perceptions of their learning. The aim of this study was to determine the effects of an interactive virtual patient simulation for pharmacology education and clinical practice on student knowledge, skills and confidence. Ethics approval for the study was obtained from Griffith University Research Ethics Committee (PHM/11/14/HREC). The simulation was intended to replicate the pharmacy environment and patient interaction. The content was designed to enhance knowledge of proton-pump inhibitor pharmacology, role in therapeutics and safe supply to patients. The tool was deployed into a third-year clinical pharmacology and therapeutics course. A number of core practice areas were examined including the competency domains of questioning, counselling, referral and product provision. Baseline measures of student self-reported knowledge, skills and confidence were taken prior to the simulation using a specifically designed questionnaire. A more extensive questionnaire was deployed following the virtual patient simulation, which also included measures of student engagement with the activity. A quiz assessing student factual and conceptual knowledge of proton-pump inhibitor pharmacology and related counselling information was also included in both questionnaires. Sixty-one students (response rate >95%) from two cohorts (2014 and 2015) participated in the study. Chi-square analyses were performed and data analysed using Fishers exact test. Results demonstrate that student knowledge, skills and confidence within the competency domains of questioning, counselling, referral and product provision, show improvement following the implementation of the virtual patient simulation. Statistically significant (p<0.05) improvement occurred in ten of the possible twelve self-reported measurement areas. Greatest magnitude of improvement occurred in the area of counselling (student confidence p<0.0001). Student confidence in all domains (questioning, counselling, referral and product provision) showed a marked increase. Student performance in the quiz also improved, demonstrating a 10% improvement overall for pharmacology knowledge and clinical practice following the simulation. Overall, 85% of students reported the simulation to be engaging and 93% of students felt the virtual patient simulation enhanced learning. The data suggests that the interactive virtual patient simulation developed for clinical pharmacology and therapeutics education enhanced students knowledge, skill and confidence, with respect to the competency domains of questioning, counselling, referral and product provision. These self-reported measures appear to translate to learning outcomes, as demonstrated by the improved student performance in the quiz assessment item. Future research of education using virtual simulation should seek to incorporate modern quantitative measures of student learning and engagement, such as eye tracking.

Keywords: clinical simulation, education, pharmacology, simulation, virtual learning

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Authors: Dana Zelicha

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A 6-week mindfulness programme was launched to improve the well being and performance of 20 managers (including the supervisor) of an international corporation in London. A unique assessment methodology was customised to the organisation’s needs, measuring four parameters: prioritising skills, listening skills, mindfulness levels and happiness levels. All parameters showed significant improvements (p < 0.01) post intervention, with a remarkable increase in listening skills and mindfulness levels. Although corporate mindfulness programmes have proven to be effective, the challenge remains the low engagement levels at home and the implementation of these tools beyond the scope of the intervention. This study has offered an innovative approach to enforce home engagement levels, which yielded promising results. The programme launched with a 2-day introduction intervention, which was followed by a 6-week training course (1 day a week; 2 hours each). Participants learned all basic principles of mindfulness such as mindfulness meditations, Mindfulness Based Stress Reduction (MBSR) techniques and Mindfulness Based Cognitive Therapy (MBCT) practices to incorporate into their professional and personal lives. The programme contained experiential mindfulness meditations and innovative mindfulness tools (OWBA-MT) created by OWBA - The Well Being Agency. Exercises included Mindful Meetings, Unitasking and Mindful Feedback. All sessions concluded with guided discussions and group reflections. One fundamental element of this programme was engagement level outside of the workshop. In the office, participants connected with a mindfulness buddy - a team member in the group with whom they could find support throughout the programme. At home, participants completed online daily mindfulness forms that varied according to weekly themes. These customised forms gave participants the opportunity to reflect on whether they made time for daily mindfulness practice, and to facilitate a sense of continuity and responsibility. At the end of the programme, the most engaged team member was crowned the ‘mindful maven’ and received a special gift. The four parameters were measured using online self-reported questionnaires, including the Listening Skills Inventory (LSI), Mindfulness Attention Awareness Scale (MAAS), Time Management Behaviour Scale (TMBS) and a modified version of the Oxford Happiness Questionnaire (OHQ). Pre-intervention questionnaires were collected at the start of the programme, and post-intervention data was collected 4-weeks following completion. Quantitative analysis using paired T-tests of means showed significant improvements, with a 23% increase in listening skills, a 22% improvement in mindfulness levels, a 12% increase in prioritising skills, and an 11% improvement in happiness levels. Participant testimonials exhibited high levels of satisfaction and the overall results indicate that the mindfulness programme substantially impacted the team. These results suggest that 6-week mindfulness programmes can improve employees’ capacities to listen and work well with others, to effectively manage time and to experience enhanced satisfaction both at work and in life. Limitations noteworthy to consider include the afterglow effect and lack of generalisability, as this study was conducted on a small and fairly homogenous sample.

Keywords: corporate mindfulness, listening skills, organisational well being, prioritising skills, mindful leadership

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Authors: Ann P. Daunic, Nancy Corbett

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Background and Significance: Researchers emphasize the role that motivation, self-esteem, and self-regulation play in children’s early adjustment to the school culture, including skills such as identifying their own feelings and understanding the feelings of others. As social-emotional growth, academic learning, and successful integration within culture and society are inextricably connected, the Social-Emotional Learning Foundations (SELF) curriculum was designed to integrate social-emotional learning (SEL) instruction within early literacy instruction (specifically, reading) for Kindergarten and first-grade students at risk for emotional and behavioral difficulties. Storybook reading is a typically occurring activity in the primary grades; thus SELF provides an intervention that is both theoretically and practically sound. Methodology: The researchers will report on findings from the first two years of a three-year study funded by the US Department of Education’s Institute of Education Sciences to evaluate the effects of the SELF curriculum versus “business as usual” (BAU). SELF promotes the development of self-regulation by incorporating instructional strategies that support children’s use of SEL related vocabulary, self-talk, and critical thinking. The curriculum consists of a carefully coordinated set of materials and pedagogy designed specifically for primary grade children at early risk for emotional and behavioral difficulties. SELF lessons (approximately 50 at each grade level) are organized around 17 SEL topics within five critical competencies. SELF combines whole-group (the first in each topic) and small-group lessons (the 2nd and 3rd in each topic) to maximize opportunities for teacher modeling and language interactions. The researchers hypothesize that SELF offers a feasible and substantial opportunity within the classroom setting to provide a small-group social-emotional learning intervention integrated with K-1 literacy-related instruction. Participating target students (N = 876) were identified by their teachers as potentially at risk for emotional or behavioral issues. These students were selected from 122 Kindergarten and 100 first grade classrooms across diverse school districts in a southern state in the US. To measure the effectiveness of the SELF intervention, the researchers asked teachers to complete assessments related to social-emotional learning and adjustment to the school culture. A social-emotional learning related vocabulary assessment was administered directly to target students receiving small-group instruction. Data were analyzed using a 3-level MANOVA model with full information maximum likelihood to estimate coefficients and test hypotheses. Major Findings: SELF had significant positive effects on vocabulary, knowledge, and skills associated with social-emotional competencies, as evidenced by results from the measures administered. Effect sizes ranged from 0.41 for group (SELF vs. BAU) differences in vocabulary development to 0.68 for group differences in SEL related knowledge. Conclusion: Findings from two years of data collection indicate that SELF improved outcomes related to social-emotional learning and adjustment to the school culture. This study thus supports the integration of SEL with literacy instruction as a feasible and effective strategy to improve outcomes for K-1 students at risk for emotional and behavioral difficulties.

Keywords: Socio-cultural context for learning, social-emotional learning, social skills, vocabulary development

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Authors: Mazlum Çelik, Burcu Gürkan Ercan, Ahmet Ayaz, Hilal Yakut İpekoğlu, Furkan Baltacı, Mustafa Kurtoğlu, Bilge Kalkavan, Sinem Küçükyılmaz, Hikmet Çağrı Yardımcı, Şeyma Sevgican, Cemile Gökçe Elkovan, Bilal Çayır, Mehmet Emin Düzcan

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The earthquake research literature generally examines emotional, cognitive, and behavioral responses after an earthquake. Studies concerning the behavioral responses to earthquakes reveal that after the earthquake, people either flee in a panic or do not act according to the stereotype that they act irrationally and anti-socially and sometimes give rational and adaptive reactions. However, the rareness of research dealing with human behavior experiencing the earthquake moment makes it necessary to pay particular attention to these behavior patterns. In this direction, this study aims to examine human behavior indoors in case of rising earthquake intensity. In Turkey, located on geography in the earthquake zone, devastating earthquakes took place, such as in "Istanbul" with a magnitude of 7.4 in 1999 and in "Elazığ" with a magnitude of 6.8 in 2020. Occurred recently, the "Kahramanmaraş" earthquake affected 11 provinces, with a magnitude of 7.7 and 7.6 in 2023. In addition, there is expected to be a devastating earthquake in Istanbul, experts warn. For this reason, it is essential to understand human behavior for disaster risk. Management and pre-disaster preparedness to be effective and efficient and to take realistic measures to protect human life. Mazlum Çelik, Burcu Gürkan Ercan, Ahmet Ayaz, Hilal Yakut İpekoğlu, Furkan Baltacı, Mustafa Kurtoğlu, Bilge Kalkavan, Sinem Küçükyılmaz, Hikmet Çağrı Yardımcı, Şeyma Sevgican, Cemile Gökçe Elkovan, Bilal Çayır, Mehmet Emin Düzcan. In this study, which is currently part of a project supported by The Scientific and Technological Council of Turkey (TUBITAK), the indoor recordings during the earthquakes in Elazig on January 24, 2020, and in İzmir on October 30, 2020, are examined, and the people's behavior during the earthquake is analyzed. In this direction, video recordings taken from the YouTube archives of İzmir and Elazığ Disaster and Emergency Management Presidency (AFAD) Directorates and metropolitan municipalities are examined. The researchers have created an observation form in line with the information in the relevant literature to classify people's behavior during an earthquake. It is intended to determine the behavioral patterns by classifying according to the form and video analysis of the people heading toward the door, remaining stable, taking protective measures, turning to people, and engaging in "other" behaviors outside of these behaviors during the earthquake. A total of 60 video analyzes are carried out from Elazığ and İzmir. The descriptive statistic has been used with the SPSS 23.0 package program in the data analysis. It is found that in the event of an increase in the severity of the earthquake, unlike Elazığ, in İzmir, protective action is preferred to the act of remaining stable. In addition, it is observed that with the increase in the earthquake's intensity, women attempt to take more protective action while men head toward the door. In contrast, a rise is observed in the behavior of young people heading toward the door and taking protective actions, while there is a decrease in their behavior directing to people. These findings, unlike the literature, reveal that human behavior during earthquakes cannot be reduced to a single behavior pattern, such as drop-cover-hold-on. The results show that it is necessary to understand the behaviors of individuals during the earthquake and to develop practical policy proposals for combating earthquakes by considering sociocultural, geographical, and demographic variables.

Keywords: descriptive analysis, earthquake, human behaviour, disaster policy.

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Authors: Ghidey Ghebreyohanes, Eltahir Awad Gasim Khalil, Zemenfes Tsighe, Faiza Ali

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Background: reproductive health (RH) is a state of physical, mental and social well-being in all matters relating to the reproductive system at all stages of life. In East Africa including Eritrea, adolescents comprise more than a quarter of the population. The region holds the highest rates of sexually transmitted diseases, HIV, unwanted pregnancy and unsafe abortion with its complications. Young girls carry the highest burden of reproductive health problems due to their risk taking behavior, lack of knowledge, peer pressure, physiologic immaturity and low socioeconomic status. Design: this was a Community-based, randomized, case-controlled and pre-test-post-test intervention study. Setting: Zoba Debub was randomly selected out of the six zobas in Eritrea. The four high schools out of the 26 in Zoba Debub were randomly selected as study target schools. Over three quarter of the people live on farming. The target population was female students attending grade nine with majority of these girls live in the distant villages and walk to school. The study participants were randomly selected (n=165) from each school. Furthermore, the 1 intervention and 3 controls for the study arms were assigned randomly. Objectives: this study aimed to assess the effectiveness of peer reproductive health education in improving knowledge, attitude, and health service use of high school adolescent girls in Eritrea Methods: the protocol was reviewed and approved by the Scientific and Ethics Committees of Faculty of Nursing Sciences, University of Khartoum. Data was collected using pre-designed and pretested questionnaire emphasizing on reproductive health knowledge, attitude and practice. Sample size was calculated using proportion formula (α 0.01; power of 95%). Measures used were scores and proportions. Descriptive and inferential statistics, t-test and chi square at (α .01), 99% confidence interval were used to compare changes of pre and post-intervention scores using SPSS soft ware. Seventeen students were selected for peer educators by the school principals and other teachers based on inclusion criteria that include: good academic performance and acceptable behavior. One peer educator educated one group composed of 8-10 students for two months. One faculty member was selected to supervise peer educators. The principal investigator conducted the training of trainers and provided supervision and discussion to peer educators every two weeks until the end of intervention. Results: following informed consent, 627 students [164 in intervention and 463 in the control group] with a ratio of 1 to 3, were enrolled in the study. The mean age for the total study population was 15.4±1.0 years. The intervention group mean age was 15.3±1.0 year; while the control group had a mean age of 15.4±1.0. The mean ages for the study arms were similar (p= 0.4). The majority (96 %) of the study participants are from Tigrigna ethnic group. Reproductive knowledge scores which was calculated out of a total 61 grade points: intervention group (pretest 6.7 %, post-test 33.6 %; p= 0.0001); control group (pretest 7.3 %, posttest 7.3 %, p= 0.92). Proportion difference in attitude calculated out of 100%: intervention group (pretest 42.3 % post test 54.7% p= 0.001); controls group (pretest 45%, post test 44.8 p= 0.7). Proportion difference in Practice calculated out of 100 %: intervention group (pretest 15.4%, post test 80.4 % p= 0.0001); control group (pretest 16.8%, posttest 16.9 % p= 0.8). Mothers were quoted as major (> 90 %) source of reproductive health information. All focus group discussants and most of survey participants agreed on the urgent need of reproductive health information and services for adolescent girls. Conclusion: reproductive health knowledge and use of facilities is poor among adolescent girls in sub-urban Eretria. School-based peer reproductive health education is effective and is the best strategy to improve reproductive health knowledge and attitudes.

Keywords: reproductive health, adolescent girls, eretria, health education

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Authors: Anas Hallak, Latifa Seblini, Juergen Wilde

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In mechatronics or sensor technology, plastic housings are used to protect sensitive components from harmful environmental influences, such as moisture, media, or reactive substances. Connections, preferably in the form of metallic lead-frame structures, through the housing wall are required for their electrical supply or control. In this system, an insufficient connection between the plastic component, e.g., Polyamide66, and the metal surface, e.g., copper, due to the incompatibility is dominating. As a result, leakage paths can occur along with the plastic-metal interface. Since adhesive bonding has been established as one of the most important joining processes and its use has expanded significantly, driven by the development of improved high-performance adhesives and bonding techniques, this technology has been involved in metal-plastic hybrid structures. In this study, an epoxy bonding agent from DELO (DUALBOND LT2266) has been used to improve the mechanical and chemical binding between the metal and the polymer. It is an adhesion promoter with two reaction stages. In these, the first stage provides fixation to the lead frame directly after the coating step, which can be done by UV-Exposure for a few seconds. In the second stage, the material will be thermally hardened during injection molding. To analyze the two reaction stages of the primer, dynamic DSC experiments were carried out and correlated with Fourier-transform infrared spectroscopy measurements. Furthermore, the number of crosslinking bonds formed in the system in each reaction stage has also been estimated by a rheological characterization. Those investigations have been performed with different times of UV exposure: 12, 96 s and in an industrial preferred temperature range from -20 to 175°C. The shear viscosity values of primer have been measured as a function of temperature and exposure times. For further interpretation, the storage modulus values have been calculated, and the so-called Booij–Palmen plot has been sketched. The next approach in this study is the self-healing mechanisms in the hydride system in which the primer should flow into micro-damage such as interface, cracks, inhibit them from growing, and close them. The ability of the primer to flow in and penetrate defined capillaries made in Ultramid was investigated. Holes with a diameter of 0.3 mm were produced in injection-molded A3EG7 plates with 4 mm thickness. A copper substrate coated with the DUALBOND was placed on the A3EG7 plate and pressed with a certain force. Metallographic analyses were carried out to verify the filling grade, which showed an almost 95% filling ratio of the capillaries. Finally, to estimate the self-healing mechanism in metal-plastic hybrid systems, characterizations have been done on a simple geometry with a metal inlay developed by the Institute of Polymer Technology in Friedrich-Alexander-University. The specimens have been modified with tungsten wire which was to be pulled out after the injection molding to create a micro-hole in the specimen at the interface between the primer and the polymer. The capability of the primer to heal those micro-cracks upon heating, pressing, and thermal aging has been characterized through metallographic analyses.

Keywords: hybrid structures, self-healing, thermoplastic housing, adhesive

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Authors: Sini George

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Active learning pedagogies are valued for their success in increasing 21st-century learners’ engagement, developing transferable skills like critical thinking or quantitative reasoning, and creating deeper and more lasting educational gains. 'Blended learning' is an active learning pedagogical approach in which direct instruction moves from the group learning space to the individual learning space, and the resulting group space is transformed into a dynamic, interactive learning environment where the educator guides students as they apply concepts and engage creatively in the subject matter. This project aimed to develop a blended learning instructional approach to teaching concepts around pharmaceutical calculations to year 1 pharmacy students. The wrong dose, strength or frequency of a medication accounts for almost a third of medication errors in the NHS therefore, progression to year 2 requires a 70% pass in this calculation test, in addition to the standard progression requirements. Many students were struggling to achieve this requirement in the past. It was also challenging to teach these concepts to students of a large class (> 130) with mixed mathematical abilities, especially within a traditional didactic lecture format. Therefore, short screencasts with voice-over of the lecturer were provided in advance of a total of four teaching sessions (two hours/session), incorporating core content of each session and talking through how they approached the calculations to model metacognition. Links to the screencasts were posted on the learning management. Viewership counts were used to determine that the students were indeed accessing and watching the screencasts on schedule. In the classroom, students had to apply the knowledge learned beforehand to a series of increasingly difficult set of questions. Students were then asked to create a question in group settings (two students/group) and to discuss the questions created by their peers in their groups to promote deep conceptual learning. Students were also given time for question-and-answer period to seek clarifications on the concepts covered. Student response to this instructional approach and their test grades were collected. After collecting and organizing the data, statistical analysis was carried out to calculate binomial statistics for the two data sets: the test grade for students who received blended learning instruction and the test grades for students who received instruction in a standard lecture format in class, to compare the effectiveness of each type of instruction. Student response and their performance data on the assessment indicate that the learning of content in the blended learning instructional approach led to higher levels of student engagement, satisfaction, and more substantial learning gains. The blended learning approach enabled each student to learn how to do calculations at their own pace freeing class time for interactive application of this knowledge. Although time-consuming for an instructor to implement, the findings of this research demonstrate that the blended learning instructional approach improves student academic outcomes and represents a valuable method to incorporate active learning methodologies while still maintaining broad content coverage. Satisfaction with this approach was high, and we are currently developing more pharmacy content for delivery in this format.

Keywords: active learning, blended learning, deep conceptual learning, instructional approach, metacognition, pharmaceutical calculations

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Authors: Mei Chen, Yingping Hou, Michelle Hao, Soheil Aghamohammadzadeh, Esteban Terzo, Roger Clark, Vijay Modur

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Background: Recessive Dystrophic Epidermolysis Bullosa (RDEB) is a genetic skin condition characterized by skin tearing and unremitting blistering upon minimal trauma. Repeated blistering, fibrosis, and scarring lead to aggressive squamous cell carcinoma later in life. RDEB is caused by mutations in the COL7A1 gene encoding collagen type VII (C7), the major component of anchoring fibrils mediating epidermis-dermis adherence. Nonsense mutations in the COL7A1 gene of a subset of RDEB patients leads to premature termination codons (PTC). Similarly, most Junctional Epidermolysis Bullosa (JEB) cases are caused by nonsense mutations in the LAMB3 gene encoding the β3 subunit of laminin 332. Currently, there is an unmet need for the treatment of RDEB and JEB. Zikani Therapeutics has discovered an array of macrocyclic compounds with ring structures similar to macrolide antibiotics that can facilitate readthrough activity of nonsense mutations in the COL7A1 and LAMB3 genes by acting as Ribosome Modulating Agents (RMAs). The medicinal chemistry synthetic advancements of these macrocyclic compounds have allowed targeting the human ribosome while preserving the structural elements responsible for the safety and pharmacokinetic profile of clinically used macrolide antibiotics. Methods: C7 expression was used as a measure of readthrough activity by immunoblot assays in two primary human fibroblasts from RDEB patients (R578X/R578X and R163X/R1683X-COL7A1). Similarly, immunoblot assays in C325X/c.629-12T > A-LAMB3 keratinocytes were used to measure readthrough activity for JEB. The relative readthrough activity of each compound was measured relative to Gentamicin. An imaging-based fibroblast migration assay was used as an assessment of C7 functionality in RDEB-fibroblasts over 16-20 hrs. The incubation period for the above experiments was 48 hrs for RDEB fibroblasts and 72 hours for JEB keratinocytes. Results: 9 RMAs demonstrated increased protein expression in both patient RDEB fibroblasts. The highest readthrough activity at tested concentrations without cytotoxicities increased protein expression up to 179% of Gentamicin (400 µg/ml), with favored readthrough activity in R163X/R1683X-COL7A1 fibroblasts. Concurrent with protein expression, fibroblast hypermotility phenotype observed in RDEB was rescued by reducing motility by ~35% to WT levels (the same level as 690 µM Gentamicin treated cells). Laminin β3 expression was also shown to be increased by 6 RMAs in keratinocytes to 33-83% of (400 µg/ml) Gentamicin. Conclusions: To date, 9 RMAs have been identified that enhance the expression of functional C7 in a mutation-dependent manner in two different RDEB patient fibroblast backgrounds (R578X/R578X and R163X/R1683X-COL7A1). A further 6 RMAs have been identified that enhance the readthrough of C325X-LAMB3 in JEB patient keratinocytes. Based on the clinical trial conducted by us with topical gentamycin in 2017, Zikani’s RMAs achieve clinically significant levels of read-through for the treatment of recessive dystrophic and Junctional Epidermolysis Bullosa.

Keywords: epidermolysis bullosa, nonsense mutation, readthrough, ribosome modulation

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Authors: Yogesh Kumar Singh, T. S. Murugesh Prabhu, Upasana Dutta, Girishchandra Yendargaye, Rahul Yadav, Rohini Gopinath Kale, Binay Kumar, Manoj Khare

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The Indian subcontinent is severely affected by floods that cause intense irreversible devastation to crops and livelihoods. With increased incidences of floods and their related catastrophes, an Early Warning System for Flood Prediction and an efficient Flood Management System for the river basins of India is a must. Accurately modeled hydrological conditions and a web-based early warning system may significantly reduce economic losses incurred due to floods and enable end users to issue advisories with better lead time. This study describes the design and development of an EWS-FP using advanced computational tools/methods, viz. High-Performance Computing (HPC), Remote Sensing, GIS technologies, and open-source tools for the Mahanadi River Basin of India. The flood prediction is based on a robust 2D hydrodynamic model, which solves shallow water equations using the finite volume method. Considering the complexity of the hydrological modeling and the size of the basins in India, it is always a tug of war between better forecast lead time and optimal resolution at which the simulations are to be run. High-performance computing technology provides a good computational means to overcome this issue for the construction of national-level or basin-level flash flood warning systems having a high resolution at local-level warning analysis with a better lead time. High-performance computers with capacities at the order of teraflops and petaflops prove useful while running simulations on such big areas at optimum resolutions. In this study, a free and open-source, HPC-based 2-D hydrodynamic model, with the capability to simulate rainfall run-off, river routing, and tidal forcing, is used. The model was tested for a part of the Mahanadi River Basin (Mahanadi Delta) with actual and predicted discharge, rainfall, and tide data. The simulation time was reduced from 8 hrs to 3 hrs by increasing CPU nodes from 45 to 135, which shows good scalability and performance enhancement. The simulated flood inundation spread and stage were compared with SAR data and CWC Observed Gauge data, respectively. The system shows good accuracy and better lead time suitable for flood forecasting in near-real-time. To disseminate warning to the end user, a network-enabled solution is developed using open-source software. The system has query-based flood damage assessment modules with outputs in the form of spatial maps and statistical databases. System effectively facilitates the management of post-disaster activities caused due to floods, like displaying spatial maps of the area affected, inundated roads, etc., and maintains a steady flow of information at all levels with different access rights depending upon the criticality of the information. It is designed to facilitate users in managing information related to flooding during critical flood seasons and analyzing the extent of the damage.

Keywords: flood, modeling, HPC, FOSS

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Authors: Xu Fei (Philip) WU

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As waste recycling concept been accepted more and more in modern societies, the organic portion of the municipal waste become a sires issue in today’s life. Depend on location and season, the organic waste can bee anywhere between 40-65% of total municipal solid waste. Also composting and anaerobic digestion technologies been applied in this field for years, however both process have difficulties been selected by economical and environmental factors. Beside environmental pollution and risk of virus spread, the compost is not a product been welcomed by people even the waste management has to give up them at no cost. The anaerobic digester has to have 70% of water and keep at 35 degree C or above; base on above conditions, the retention time only can be up to two weeks and remain solid has to be dewater and composting again. The enhancive waste water treatment has to be added after. Because these reasons, the voice of suggesting cancelling recycling program and turning all waste to mass burn incinerations have been raised-A process has already been proved has least energy efficiency and most air pollution problem associated process. A newly developed WXF Bio-energy process employs recently developed and patented pre-designed separation, multi-layer and multi-cavity successive bioreactor landfill technology. It features an improved leachate recycling technology, technologies to maximize the biogas generation rate and a reduced overall turnaround period on the land. A single properly designed and operated site can be used indefinitely. In this process, all collected biogas will be processed to eliminate H2S and other hazardous gases. The methane, carbon dioxide and hydrogen will be utilized in a proprietary process to manufacture methanol which can be sold to mitigate operating costs of the landfill. This integration of new processes offers a more advanced alternative to current sanitary landfill, incineration and compost technology. Xu Fei (Philip) Wu Xu Fei Wu is founder and Chief Scientist of W&Y Environmental International Inc. (W & Y), a Canadian environmental and sustainable energy technology company with patented landfill processes and proprietary waste to energy technologies. He has worked in environmental and sustainable energy fields over the last 25 years. Before W&Y, he worked for Conestoga-Rovers & Associates Limited, Microbe Environmental Science and Technology Inc. of Canada and The Ministry of Nuclear Industry and Ministry of Space Flight Industry of China. Xu Fei Wu holds a Master of Engineering Science degree from The University of Western Ontario. I wish present this paper as an oral presentation only Selected Conference Presentations: • “Removal of Phenolic Compounds with Algae” Presented at 25th Canadian Symposium on Water Pollution Research (CAWPRC Conference), Burlington, Ontario Canada. February, 1990 • “Removal of Phenolic Compounds with Algae” Presented at Annual Conference of Pollution Control Association of Ontario, London, Ontario, Canada. April, 1990 • “Removal of Organochlorine Compounds in a Flocculated Algae Photo-Bioreactor” Presented at International Symposium on Low Cost and Energy Saving Wastewater Treatment Technologies (IAWPRC Conference), Kiyoto, Japan, August, 1990 • “Maximizing Production and Utilization of Landfill Gas” 2009 Wuhan International Conference on Environment(CAWPRC Conference, sponsored by US EPA) Wuhan, China. October, 2009. • “WXF Bio-Energy-A Green, Sustainable Waste to Energy Process” Presented at 9Th International Conference Cooperation for Waste Issues, Kharkiv, Ukraine March, 2012 • “A Lannfill Site Can Be Recycled Indefinitely” Presented at 28th International Conference on solid Waste Technology and Management, Philadelphia, Pennsylvania, USA. March, 2013. Hosted by The Journal of Solid Waste Technology and Management.

Keywords: green fuel, waste management, bio-energy, sustainable development, methanol

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Authors: Marie-Helena Docherty, Sion Edryd Williams

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The prevalence of diabetes mellitus is increasing worldwide. In Sub-Saharan Africa, type 2 diabetes represents over 90% of all types of diabetes with the number of diabetic patients expected to rise. This represents a huge economic burden in an area already contending with high rates of other significant diseases, including the highest worldwide prevalence of HIV. Diabetic complications considerably impact on morbidity and mortality. The epidemiological data for the region quotes high rates of retinopathy (7-63%), neuropathy (27-66%) and microalbuminuria (10-83%). It is therefore imperative that diabetic screening programmes are established. It is recognised that in many parts of the developing world the implementation and management of such programmes is limited by a lack of available resources. The International Diabetes Federation produced guidelines in 2012 taking these limitations into account suggesting that all diabetic patients should have access to basic screening. These guidelines are consistent with the national diabetic guidelines produced by the Lesotho Medical Council. However, diabetic care in Lesotho is delivered at the local level, with variable levels of quality. A cross sectional study was performed in the outpatient department of Maluti Hospital in Mapoteng, Lesotho, a busy rural hospital in the Berea district. Demographic data on gender, age and modality of treatment were collected over a six-week time period. Information regarding 3 basic screening parameters was obtained. These parameters included eye screening (defined as a documented ophthalmology review within the last 12 months), foot screening (defined as a documented foot health assessment by any health care professional within the last 12 months) and secondary prevention (defined as a documented blood pressure and lipid profile reading within the last 12 months). These parameters were selected on the basis of the absolute minimum level of resources in Maluti Hospital. Renal screening was excluded, as the hospital does not have access to reliable renal profile checks or urinalysis. There is however a fully functioning on-site ophthalmology department run by a senior ophthalmologist with the ability to provide retinal photography, retinal surgery and photocoagulation therapy. Data was collected on 183 type 2 diabetics. 112 patients were male and 71 were female. The average age was 43 years. 4 patients were diet controlled, 140 patients were on oral hypoglycaemic agents (metformin and/or glibenclamide), and 39 patients were on a combination of insulin and oral hypoglycaemics. In the preceding 12 months, 5 patients had undergone eye screening (3%), 24 patients had undergone foot screening (13%), and 31 patients had lipid profile testing (17%). All patients had a documented blood pressure reading (100%). Our results show that screening is poorly performed in the basic indicators suggested by the IDF and the Lesotho Medical Council. On the basis of these results, a screening programme was developed using the mnemonic SaFE; secondary prevention, foot and eye care. This is simple, memorable and transferable between healthcare professionals. In the future, the expectation would be to expand upon this current programme to include renal screening, and to further develop screening pertaining to secondary prevention.

Keywords: Africa, complications, rural, screening

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Authors: Mukondi Esther Nethavhakone

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In 2020 World Health Organization announced the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), also known as Coronavirus disease 2019 (COVID-19) pandemic. To curb or contain the spread of the novel coronavirus (COVID 19), global governments implemented social distancing and lockdown regulations. Subsequently, it was no longer business as per usual, life as we knew it had changed, and so many aspects of people's lives were negatively affected, including financial and employment stability. Mainly, because companies/businesses had to put their operations on hold, some had to shut down completely, resulting in the loss of income for many people globally. Finances and employment insecurities are some of the issues that exacerbated many social issues that the world was already faced with, such as school drop-outs, teenage pregnancies, sexual assaults, gender-based violence, crime, child abuse, elderly abuse, to name a few. Expectedly the majority of the population's mental health state was threatened. This resulted in an increased number of people seeking mental healthcare services. The increasing need for mental healthcare services in Low and Middle-income countries proves to be a challenge because it is a well-known fact due to financial constraints and not well-established healthcare systems, mental healthcare provision is not as prioritised as the primary healthcare in these countries. It is against this backdrop that the researcher seeks to find viable, cost-effective, and accessible mental health solutions for low and middle-income countries amid the pressures of any pandemic. The researcher will undertake a systematic review of the technology-based mental health solutions that have been implemented/adopted by developed countries during COVID 19 lockdown and social distancing periods. This systematic review study aims to determine if low and middle-income countries can adopt the cost-effective version of digital mental health solutions for the healthcare system to adequately provide mental healthcare services during critical times such as pandemics (when there's an overwhelming diminish in mental health globally). The researcher will undertake a systematic review study through mixed methods. It will adhere to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The mixed-methods uses findings from both qualitative and quantitative studies in one review study. It will be beneficial to conduct this kind of study using mixed methods because it is a public health topic that involves social interventions and it is not purely based on medical interventions. Therefore, the meta-ethnographic (qualitative data) analysis will be crucial in understanding why and which digital methods work and for whom does it work, rather than only the meta-analysis (quantitative data) providing what digital mental health methods works. The data collection process will be extensive, involving the development of a database, table of summary of evidence/findings, and quality assessment process lastly, The researcher will ensure that ethical procedures are followed and adhered to, ensuring that sensitive data is protected and the study doesn't pose any harm to the participants.

Keywords: digital, mental health, covid, low and middle-income countries

Procedia PDF Downloads 76

Authors: Diana Reckien

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Vulnerability assessments are increasingly used to support policy-making in complex environments, like urban areas. Usually, vulnerability studies include the construction of aggregate (sub-) indices and the subsequent mapping of indices across an area of interest. Vulnerability studies show a couple of advantages: they are great communication tools, can inform a wider general debate about environmental issues, and can help allocating and efficiently targeting scarce resources for adaptation policy and planning. However, they also have a number of challenges: Vulnerability assessments are constructed on the basis of a wide range of methodologies and there is no single framework or methodology that has proven to serve best in certain environments, indicators vary highly according to the spatial scale used, different variables and metrics produce different results, and aggregate or composite vulnerability indicators that are mapped easily distort or bias the picture of vulnerability as they hide the underlying causes of vulnerability and level out conflicting reasons of vulnerability in space. So, there is urgent need to further develop the methodology of vulnerability studies towards a common framework, which is one reason of the paper. We introduce a social vulnerability approach, which is compared with other approaches of bio-physical or sectoral vulnerability studies relatively developed in terms of a common methodology for index construction, guidelines for mapping, assessment of sensitivity, and verification of variables. Two approaches are commonly pursued in the literature. The first one is an additive approach, in which all potentially influential variables are weighted according to their importance for the vulnerability aspect, and then added to form a composite vulnerability index per unit area. The second approach includes variable reduction, mostly Principal Component Analysis (PCA) that reduces the number of variables that are interrelated into a smaller number of less correlating components, which are also added to form a composite index. We test these two approaches of constructing indices on the area of New York City as well as two different metrics of variables used as input and compare the outcome for the 5 boroughs of NY. Our analysis yields that the mapping exercise yields particularly different results in the outer regions and parts of the boroughs, such as Outer Queens and Staten Island. However, some of these parts, particularly the coastal areas receive the highest attention in the current adaptation policy. We imply from this that the current adaptation policy and practice in NY might need to be discussed, as these outer urban areas show relatively low social vulnerability as compared with the more central parts, i.e. the high dense areas of Manhattan, Central Brooklyn, Central Queens and the Southern Bronx. The inner urban parts receive lesser adaptation attention, but bear a higher risk of damage in case of hazards in those areas. This is conceivable, e.g., during large heatwaves, which would more affect more the inner and poorer parts of the city as compared with the outer urban areas. In light of the recent planning practice of NY one needs to question and discuss who in NY makes adaptation policy for whom, but the presented analyses points towards an under representation of the needs of the socially vulnerable population, such as the poor, the elderly, and ethnic minorities, in the current adaptation practice in New York City.

Keywords: vulnerability mapping, social vulnerability, additive approach, Principal Component Analysis (PCA), New York City, United States, adaptation, social sensitivity

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Authors: Monica Arnaudo, Monika Topel, Bjorn Laumert

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Within the Swedish context, the current trend of relatively low electricity prices promotes the electrification of the energy infrastructure. The residential heating sector takes part in this transition by proposing a switch from a centralized district heating system towards a distributed heat pumps-based setting. When it comes to urban environments, two issues arise. The first, seen from an electricity-sector perspective, is related to the fact that existing networks are limited with regards to their installed capacities. Additional electric loads, such as heat pumps, can cause severe overloads on crucial network elements. The second, seen from a heating-sector perspective, has to do with the fact that the indoor comfort conditions can become difficult to handle when the operation of the heat pumps is limited by a risk of overloading on the distribution grid. Furthermore, the uncertainty of the electricity market prices in the future introduces an additional variable. This study aims at assessing the extent to which distributed heat pumps can penetrate an existing heat energy network while respecting the technical limitations of the electricity grid and the thermal comfort levels in the buildings. In order to account for the multi-disciplinary nature of this research question, a cosimulation modeling approach was adopted. In this way, each energy technology is modeled in its customized simulation environment. As part of the cosimulation methodology: a steady-state power flow analysis in pandapower was used for modeling the electrical distribution grid, a thermal balance model of a reference building was implemented in EnergyPlus to account for space heating and a fluid-cycle model of a heat pump was implemented in JModelica to account for the actual heating technology. With the models set in place, different scenarios based on forecasted electricity market prices were developed both for present and future conditions of Hammarby Sjöstad, a neighborhood located in the south-east of Stockholm (Sweden). For each scenario, the technical and the comfort conditions were assessed. Additionally, the average cost of heat generation was estimated in terms of levelized cost of heat. This indicator enables a techno-economic comparison study among the different scenarios. In order to evaluate the levelized cost of heat, a yearly performance simulation of the energy infrastructure was implemented. The scenarios related to the current electricity prices show that distributed heat pumps can replace the district heating system by covering up to 30% of the heating demand. By lowering of 2°C, the minimum accepted indoor temperature of the apartments, this level of penetration can increase up to 40%. Within the future scenarios, if the electricity prices will increase, as most likely expected within the next decade, the penetration of distributed heat pumps can be limited to 15%. In terms of levelized cost of heat, a residential heat pump technology becomes competitive only within a scenario of decreasing electricity prices. In this case, a district heating system is characterized by an average cost of heat generation 7% higher compared to a distributed heat pumps option.

Keywords: cosimulation, distributed heat pumps, district heating, electrical distribution grid, integrated energy systems

Procedia PDF Downloads 132

Authors: Bianca Peterson, Tomasz J. Sańko, Carlos C. Bezuidenhout, Johnnie Van Den Berg

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Busseola fusca (Fuller) (Lepidoptera: Noctuidae), the maize stem borer, is a major pest in sub-Saharan Africa. It causes economic damage to maize and sorghum crops and has evolved non-recessive resistance to genetically modified (GM) maize expressing the Cry1Ab insecticidal toxin. Since B. fusca is a non-model organism, very little genomic information is publicly available, and is limited to some cytochrome c oxidase I, cytochrome b, and microsatellite data. The biology of B. fusca is well-described, but still poorly understood. This, in combination with its larval-specific behavior, may pose problems for limiting the spread of current resistant B. fusca populations or preventing resistance evolution in other susceptible populations. As part of on-going research into resistance evolution, B. fusca larvae were collected from Bt and non-Bt maize in South Africa, followed by RNA isolation (15 specimens) and sequencing on the Illumina HiSeq 2500 platform. Quality of reads was assessed with FastQC, after which Trimmomatic was used to trim adapters and remove low quality, short reads. Trinity was used for the de novo assembly, whereas TransRate was used for assembly quality assessment. Transcript identification employed BLAST (BLASTn, BLASTp, and tBLASTx comparisons), for which two libraries (nucleotide and protein) were created from 3.27 million lepidopteran sequences. Several transcripts that have previously been implicated in Cry toxin resistance was identified for B. fusca. These included aminopeptidase N, cadherin, alkaline phosphatase, ATP-binding cassette transporter proteins, and mitogen-activated protein kinase. MEGA7 was used to align these transcripts to reference sequences from Lepidoptera to detect mutations that might potentially be contributing to Cry toxin resistance in this pest. RSEM and Bioconductor were used to perform differential gene expression analysis on groups of B. fusca larvae challenged and unchallenged with the Cry1Ab toxin. Pairwise expression comparisons of transcripts that were at least 16-fold expressed at a false-discovery corrected statistical significance (p) ≤ 0.001 were extracted and visualized in a hierarchically clustered heatmap using R. A total of 329,194 transcripts with an N50 of 1,019 bp were generated from the over 167.5 million high-quality paired-end reads. Furthermore, 110 transcripts were over 10 kbp long, of which the largest one was 29,395 bp. BLAST comparisons resulted in identification of 157,099 (47.72%) transcripts, among which only 3,718 (2.37%) were identified as Cry toxin receptors from lepidopteran insects. According to transcript expression profiles, transcripts were grouped into three subclusters according to the similarity of their expression patterns. Several immune-related transcripts (pathogen recognition receptors, antimicrobial peptides, and inhibitors) were up-regulated in the larvae feeding on Bt maize, indicating an enhanced immune status in response to toxin exposure. Above all, extremely up-regulated arylphorin genes suggest that enhanced epithelial healing is one of the resistance mechanisms employed by B. fusca larvae against the Cry1Ab toxin. This study is the first to provide a resource base and some insights into a potential mechanism of Cry1Ab toxin resistance in B. fusca. Transcriptomic data generated in this study allows identification of genes that can be targeted by biotechnological improvements of GM crops.

Keywords: epithelial healing, Lepidoptera, resistance, transcriptome

Procedia PDF Downloads 173

Authors: Sakshi Gupta, Kavita Sardana

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Management of a forest catchment involves diverse dimensions, multiple stakeholders, and conflicting interests, primarily due to the wide variety of valuable ecosystem services offered by it. Often, the coordination among different levels of formal institutions governing the catchment, local communities, as well as societal norms, taboos, customs and practices, happens to be amiss, leading to conflicting policy interventions which prove detrimental for such resources. In the case of Ala Catchment, which is a protected forest located at a distance of 9 km North-East of the town of Dalhousie, within district Chamba of Himachal Pradesh, India, and serves as one of the primary sources of public water supply for the downstream town of Dalhousie and nearby areas, several policy measures have been adopted for the restoration of the forest catchment, as well as for the improvement of public water supply. These catchment forest restoration measures include; the installation of a fence along the perimeter of the catchment, plantation of trees in the empty patches of the forest, construction of check dams, contour trenches, contour bunds, issuance of grazing permits, and installation of check posts to keep track of trespassers. While the measures adopted to address the acute shortage of public water supply in the Dalhousie region include; building and maintenance of large capacity water storage tanks, laying of pipelines, expanding public water distribution infrastructure to include water sources other than Ala Catchment Forest and introducing of five new water supply schemes for drinking water as well as irrigation. However, despite these policy measures, the degradation of the Ala catchment and acute shortage of water supply continue to distress the region. This study attempts to conduct an institutional analysis to assess the impact of policy measures for the restoration of the Ala Catchment in the Chamba district of Himachal Pradesh in India. For this purpose, the theoretical framework of Ostrom’s Institutional Assessment and Development (IAD) Framework was used. Snowball sampling was used to conduct private interviews and focused group discussions. A semi-structured questionnaire was administered to interview a total of 184 respondents across stakeholders from both formal and informal institutions. The central hypothesis of the study is that the interplay of formal and informal institutions facilitates the implementation of policy measures for ameliorating Ala Catchment, in turn improving the livelihood of people depending on this forest catchment for direct and indirect benefits. The findings of the study suggest that leakages in the successful implementation of policy measures occur at several nodes of decision-making, which adversely impact the catchment and the ecosystem services provided by it. Some of the key reasons diagnosed by the immediate analysis include; ad-hoc assignment of property rights, rise in tourist inflow increasing the pressures on water demand, illegal trespassing by local and nomadic pastoral communities for grazing and unlawful extraction of forest products, and rent-seeking by a few influential formal institutions. Consequently, it is indicated that the interplay of formal and informal institutions may be obscuring the consequentiality of the policy measures on the restoration of the catchment.

Keywords: catchment forest restoration, institutional analysis and development framework, institutional interplay, protected forest, water supply management

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Authors: Kelly S. Parkinson, Katherine Y. Teh-White

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Futureye has a bespoke social licence to operate methodology which has successfully secured community approval and commercial return for fisheries which have faced regulatory and financial risk. This unique approach to fisheries management focuses on delivering improved social and environmental outcomes to support the fishing industry make steps towards achieving the United Nations SDGs. An SLO is the community’s implicit consent for a business or project to exist. An SLO must be earned and maintained alongside regulatory licences. In current and new operations, it helps you to anticipate and measure community concerns around your operations – leading to more predictable and sensible policy outcomes that will not jeopardise your commercial returns. Rising societal expectations and increasing activist sophistication mean the international fishing industry needs to resolve community concerns at each stage their supply chain. Futureye applied our tested social licence to operate (SLO) methodology to help Austral Fisheries who was being attacked by activists concerned about the sustainability of Patagonian Toothfish. Austral was Marine Stewardship Council certified, but pirates were making the overall catch unsustainable. Austral wanted to be carbon neutral. SLO provides a lens on the risk that helps industries and companies act before regulatory and political risk escalates. To do this assessment, we have a methodology that assesses the risk that we can then translate into a process to create a strategy. 1) Audience: we understand the drivers of change and the transmission of those drivers across all audience segments. 2) Expectation: we understand the level of social norming of changing expectations. 3) Outrage: we understand the technical and perceptual aspects of risk and the opportunities to mitigate these. 4) Inter-relationships: we understand the political, regulatory, and reputation system so that we can understand the levers of change. 5) Strategy: we understand whether the strategy will achieve a social licence through bringing the internal and external stakeholders on the journey. Futureye’s SLO methodologies helped Austral to understand risks and opportunities to enhance its resilience. Futureye reviewed the issues, assessed outrage and materiality and mapped SLO threats to the company. Austral was introduced to a new way that it could manage activism, climate action, and responsible consumption. As a result of Futureye’s work, Austral worked closely with Sea Shepherd who was campaigning against pirates illegally fishing Patagonian Toothfish as well as international governments. In 2016 Austral launched the world’s first carbon neutral fish which won Austral a thirteen percent premium for tender on the open market. In 2017, Austral received the prestigious Banksia Foundation Sustainability Leadership Award for seafood that is sustainable, healthy and carbon neutral. Austral’s position as a leader in sustainable development has opened doors for retailers all over the world. Futureye’s SLO methodology can identify the societal, political and regulatory risks facing fisheries and position them to proactively address the issues and become an industry leader in sustainability.

Keywords: carbon neutral, fisheries management, risk communication, social licence to operate, sustainable development

Procedia PDF Downloads 103

Authors: Jennifer Buz, Alvin Spivey

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The most common greenhouse gas emitted through human activities, carbon dioxide (CO2), is naturally consumed by plants during photosynthesis. This process is actively being monetized by companies wishing to offset their carbon dioxide emissions. For example, companies are now able to purchase protections for vegetated land due-to-be clear cut or purchase barren land for reforestation. Therefore, by actively preventing the destruction/decay of plant matter or by introducing more plant matter (reforestation), a company can theoretically offset some of their emissions. One of the biggest issues in the carbon credit market is validating and verifying carbon offsets. There is a need for a system that can accurately and frequently ensure that the areas sold for carbon credits have the vegetation mass (and therefore for carbon offset capability) they claim. Traditional techniques for measuring vegetation mass and determining health are costly and require many person-hours. Orbital Sidekick offers an alternative approach that accurately quantifies carbon mass and assesses vegetation health through satellite hyperspectral imagery, a technique which enables us to remotely identify material composition (including plant species) and condition (e.g., health and growth stage). How much carbon a plant is capable of storing ultimately is tied to many factors, including material density (primarily species-dependent), plant size, and health (trees that are actively decaying are not effectively storing carbon). All of these factors are capable of being observed through satellite hyperspectral imagery. This abstract focuses on speciation. To build a species classification model, we matched pixels in our remote sensing imagery to plants on the ground for which we know the species. To accomplish this, we collaborated with the researchers at the Teakettle Experimental Forest. Our remote sensing data comes from our airborne “Kato” sensor, which flew over the study area and acquired hyperspectral imagery (400-2500 nm, 472 bands) at ~0.5 m/pixel resolution. Coverage of the entire teakettle experimental forest required capturing dozens of individual hyperspectral images. In order to combine these images into a mosaic, we accounted for potential variations of atmospheric conditions throughout the data collection. To do this, we ran an open source atmospheric correction routine called ISOFIT1 (Imaging Spectrometer Optiman FITting), which converted all of our remote sensing data from radiance to reflectance. A database of reflectance spectra for each of the tree species within the study area was acquired using the Teakettle stem map and the geo-referenced hyperspectral images. We found that a wide variety of machine learning classifiers were able to identify the species within our images with high (>95%) accuracy. For the most robust quantification of carbon mass and the best assessment of the health of a vegetated area, speciation is critical. Through the use of high resolution hyperspectral data, ground-truth databases, and complex analytical techniques, we are able to determine the species present within a pixel to a high degree of accuracy. These species identifications will feed directly into our carbon mass model.

Keywords: hyperspectral, satellite, carbon, imagery, python, machine learning, speciation

Procedia PDF Downloads 98

Authors: Sagar Saroha, Sawan S. Sinha, Sunil Lakshmipathy

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Reynolds averaged Navier-Stokes (RANS) model is the popular computational tool for prediction of turbulent flows. Being computationally less expensive as compared to direct numerical simulation (DNS), RANS has received wide acceptance in industry and research community as well. However, for high Reynolds number flows, the traditional RANS approach based on the Boussinesq hypothesis is incapacitated to capture all the essential flow characteristics, and thus, its performance is restricted in high Reynolds number flows of practical interest. RANS performance turns out to be inadequate in regimes like flow over curved surfaces, flows with rapid changes in the mean strain rate, duct flows involving secondary streamlines and three-dimensional separated flows. In the recent decade, partially averaged Navier-Stokes (PANS) methodology has gained acceptability among seamless bridging methods of turbulence- placed between DNS and RANS. PANS methodology, being a scale resolving bridging method, is inherently more suitable than RANS for simulating turbulent flows. The superior ability of PANS method has been demonstrated for some cases like swirling flows, high-speed mixing environment, and high Reynolds number turbulent flows. In our work, we intend to evaluate PANS in case of separated turbulent flows past bluff bodies -which is of broad aerodynamic research and industrial application. PANS equations, being derived from base RANS, continue to inherit the inadequacies from the parent RANS model based on linear eddy-viscosity model (LEVM) closure. To enhance PANS’ capabilities for simulating separated flows, the shortcomings of the LEVM closure need to be addressed. Inabilities of the LEVMs have inspired the development of non-linear eddy viscosity models (NLEVM). To explore the potential improvement in PANS performance, in our study we evaluate the PANS behavior in conjugation with NLEVM. Our work can be categorized into three significant steps: (i) Extraction of PANS version of NLEVM from RANS model, (ii) testing the model in the homogeneous turbulence environment and (iii) application and evaluation of the model in the canonical case of separated non-homogeneous flow field (flow past prismatic bodies and bodies of revolution at high Reynolds number). PANS version of NLEVM shall be derived and implemented in OpenFOAM -an open source solver. Homogeneous flows evaluation will comprise the study of the influence of the PANS’ filter-width control parameter on the turbulent stresses; the homogeneous analysis performed over typical velocity fields and asymptotic analysis of Reynolds stress tensor. Non-homogeneous flow case will include the study of mean integrated quantities and various instantaneous flow field features including wake structures. Performance of PANS + NLEVM shall be compared against the LEVM based PANS and LEVM based RANS. This assessment will contribute to significant improvement of the predictive ability of the computational fluid dynamics (CFD) tools in massively separated turbulent flows past bluff bodies.

Keywords: bridging methods of turbulence, high Re-CFD, non-linear PANS, separated turbulent flows

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Authors: Alexandra Steed

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Alexandra Steed URBAN was commissioned to undertake the South Essex Green and Blue Infrastructure Study (SEGBI) on behalf of the Association of South Essex Local Authorities (ASELA): a partnership of seven neighboring councils within the Thames Estuary. Located on London’s doorstep, the 70,000-hectare region is under extraordinary pressure for regeneration, further development, and economic expansion, yet faces extreme challenges: sea-level rise and inadequate flood defenses, stormwater flooding and threatened infrastructure, loss of internationally important habitats, significant existing community deprivation, and lack of connectivity and access to green space. The brief was to embrace these challenges in the creation of a document that would form a key part of ASELA’s Joint Strategic Framework and feed into local plans and master plans. Thus, helping to tackle climate change, ecological collapse, and social inequity at a regional scale whilst creating a relationship and awareness between urban communities and the surrounding landscapes and nature. The SEGBI project applied a ‘land-based’ methodology, combined with a co-design approach involving numerous stakeholders, to explore how living infrastructure can address these significant issues, reshape future planning and development, and create thriving places for the whole community of life. It comprised three key stages, including Baseline Review; Green and Blue Infrastructure Assessment; and the final Green and Blue Infrastructure Report. The resulting proposals frame an ambitious vision for the delivery of a new regional South Essex Estuary (SEE) Park – 24,000 hectares of protected and connected landscapes. This unified parkland system will drive effective place-shaping and “leveling up” for the most deprived communities while providing large-scale nature recovery and biodiversity net gain. Comprehensive analysis and policy recommendations ensure best practices will be embedded within planning documents and decisions guiding future development. Furthermore, a Natural Capital Account was undertaken as part of the strategy showing the tremendous economic value of the natural assets. This strategy sets a pioneering precedent that demonstrates how the prioritisation of living infrastructure has the capacity to address climate change and ecological collapse, while also supporting sustainable housing, healthier communities, and resilient infrastructures. It was only achievable through a collaborative and cross-boundary approach to strategic planning and growth, with a shared vision of place, and a strong commitment to delivery. With joined-up thinking and a joined-up region, a more impactful plan for South Essex was developed that will lead to numerous environmental, social, and economic benefits across the region, and enhancing the landscape and natural environs on the periphery of one of the largest cities in the world.

Keywords: climate change, green and blue infrastructure, landscape architecture, master planning, regional planning, social equity

Procedia PDF Downloads 73

Authors: Juan Manuel Macia

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The Montreal Port Authority (MPA) wanted to build a new road link via Souligny Avenue to increase the fluidity of goods transported by truck in the Viau Street area of Montreal and to mitigate the current traffic problems on Notre-Dame Street. With the purpose of having a better integration and acceptance of this project with the neighboring residential surroundings, this project needed to include an architectural integration, bringing some artistic components to the bridge design along with some landscaping components. The MPA is required primarily to provide direct truck access to Port of Montreal with a direct connection to the future Assomption Boulevard planned by the City of Montreal and, thus, direct access to Souligny Avenue. The MPA also required other key aspects to be considered for the proposal and development of the project, such as the layout of road and rail configurations, the reconstruction of underground structures, the relocation of power lines, the installation of lighting systems, the traffic signage and communication systems improvement, the construction of new access ramps, the pavement reconstruction and a summary assessment of the structural capacity of an existing service tunnel. The identification of the various possible scenarios began by identifying all the constraints related to the numerous infrastructures located in the area of the future link between the port and the future extension of Souligny Avenue, involving interaction with several disciplines and technical specialties. Several viaduct- and tunnel-type geometries were studied to link the port road to the right-of-way north of Notre-Dame Street and to improve traffic flow at the railway corridor. The proposed design took into account the existing access points to Port of Montreal, the built environment of the MPA site, the provincial and municipal rights-of-way, and the future Notre-Dame Street layout planned by the City of Montreal. These considerations required the installation of an engineering structure with a span of over 60 m to free up a corridor for the future urban fabric of Notre-Dame Street. The best option for crossing this span length was identified by the design and construction of a curved bridge over Notre-Dame Street, which is essentially a structure with a deck formed by a reinforced concrete slab on steel box girders with a single span of 63.5m. The foundation units were defined as pier-cap type abutments on drilled shafts to bedrock with rock sockets, with MSE-type walls at the approaches. The configuration of a single-span curved structure posed significant design and construction challenges, considering the major constraints of the project site, a design for durability approach, and the need to guarantee optimum performance over a 75-year service life in accordance with the client's needs and the recommendations and requirements defined by the standards used for the project. These aspects and the need to include architectural and artistic components in this project made it possible to design, build, and integrate a signature infrastructure project with a sustainable approach, from which the MPA, the commuters, and the city of Montreal and its residents will benefit.

Keywords: curved bridge, steel box girder, medium span, simply supported, industrial and urban environment, architectural integration, design for durability

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Authors: Dorothy Kagazi

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The African elephant (Loxodonta africana) remains one of the most crop-damaging species around Kibale National Park, western Uganda. Elephant crop raiding deprives communities of food and incomes, consequently impacting livelihoods, attitude, and support for conservation. It also attracts an aggressive reaction from local communities including the retaliatory killing of a species that is already endangered and listed under Appendix I of the Convention on Endangered Species of Flora and Fauna (CITES). In order to mitigate against elephant crop raiding and minimize conflict, a number of interventions were devised by the government of Uganda such as physical guarding, scare-shooting, excavation of trenches, growing of unpalatable crops and fire lighting all of which have over the years been implemented around the park. These generated varying degrees of effectiveness but largely never solved the problem of elephants crossing into communities to destroy food and shelter which had a negative effect onto sustainable tourism of the communities who often resorted to killing these animals and hence contributing the falling numbers of these animals. It was until government discovered that there are far more effective ways of deterring these animals from crossing to communities that it commissioned a study to deploy the African honeybee (Apis mellifera scutellata) as a deterrent against elephant crop raiding and income enhancement for local people around the park. These efforts led to a number of projects around Kibale National Park where communities were facilitated to keep bees for human-elephant conflict mitigation and rural income enhancement through the sale of honey. These projects have registered tremendous success in reducing crop damage, enhance rural incomes, influence positive attitude change and ultimately secure community support for elephant and park conservation which is a clear manifestation of sustainable tourism development in the area. To address the issue of sustainability, the project was aligned with four major objectives that contributed to the overall goal of maintaining the areas around the parks and the national park itself in such a manner that it remains viable over an infinite period. Among these included determining deterrence effects of bees against elephant crop raiding, assessing the contribution of beekeeping towards rural income enhancement, determining the impact of community involvement of park conservation and management among others. The project deployed 500 improved hives by placing them at specific and previously identified and mapped out elephant crossing points along the park boundary. A control site was established without any intervention to facilitate comparison of findings and data was collected on elephant raiding frequency, patterns, honey harvested, and community attitude towards the park. A socio-economic assessment was also undertaken to ascertain the contribution of beekeeping to incomes and attitude change. In conclusion, human-wildlife conflicts have disturbed conservation and sustainable tourism development efforts. Such success stories like the beekeeping strategy should hence be extensively discussed and widely shared as a conservation technique for sustainable tourism.

Keywords: bees, communities, conservation, elephants

Procedia PDF Downloads 184

Authors: Ho-Won Jung, Donghun Lee, Hyung-Jin Kim

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Predictive analytics (data analysis) uses a subset of measurements (the features, predictor, or independent variable) to predict another measurement (the outcome, target, or dependent variable) on a single person or unit. It applies empirical methods in statistics, operations research, and machine learning to predict the future, or otherwise unknown events or outcome on a single or person or unit, based on patterns in data. Most analyses of metabolic syndrome are not predictive analytics but statistical explanatory studies that build a proposed model (theory building) and then validate metabolic syndrome predictors hypothesized (theory testing). A proposed theoretical model forms with causal hypotheses that specify how and why certain empirical phenomena occur. Predictive analytics and explanatory modeling have their own territories in analysis. However, predictive analytics can perform vital roles in explanatory studies, i.e., scientific activities such as theory building, theory testing, and relevance assessment. In the context, this study is to demonstrate how to use our predictive analytics to support theory building (i.e., hypothesis generation). For the purpose, this study utilized a big data predictive analytics platform TM based on a co-occurrence graph. The co-occurrence graph is depicted with nodes (e.g., items in a basket) and arcs (direct connections between two nodes), where items in a basket are fully connected. A cluster is a collection of fully connected items, where the specific group of items has co-occurred in several rows in a data set. Clusters can be ranked using importance metrics, such as node size (number of items), frequency, surprise (observed frequency vs. expected), among others. The size of a graph can be represented by the numbers of nodes and arcs. Since the size of a co-occurrence graph does not depend directly on the number of observations (transactions), huge amounts of transactions can be represented and processed efficiently. For a demonstration, a total of 13,254 metabolic syndrome training data is plugged into the analytics platform to generate rules (potential hypotheses). Each observation includes 31 predictors, for example, associated with sociodemographic, habits, and activities. Some are intentionally included to get predictive analytics insights on variable selection such as cancer examination, house type, and vaccination. The platform automatically generates plausible hypotheses (rules) without statistical modeling. Then the rules are validated with an external testing dataset including 4,090 observations. Results as a kind of inductive reasoning show potential hypotheses extracted as a set of association rules. Most statistical models generate just one estimated equation. On the other hand, a set of rules (many estimated equations from a statistical perspective) in this study may imply heterogeneity in a population (i.e., different subpopulations with unique features are aggregated). Next step of theory development, i.e., theory testing, statistically tests whether a proposed theoretical model is a plausible explanation of a phenomenon interested in. If hypotheses generated are tested statistically with several thousand observations, most of the variables will become significant as the p-values approach zero. Thus, theory validation needs statistical methods utilizing a part of observations such as bootstrap resampling with an appropriate sample size.

Keywords: explanatory modeling, metabolic syndrome, predictive analytics, theory building

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Authors: May Bazzi, Shafik Tokmaj, Younes Saberi, Mats Geijer, Tony Jurkiewicz, Patrik Sund, Anna Bjällmark

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Mobile radiography, employing portable X-ray equipment, has become a routine procedure within hospital settings, with chest X-rays in intensive care units standing out as the most prevalent mobile X-ray examinations. This approach is not limited to hospitals alone, as it extends its benefits to imaging patients in various settings, particularly those too frail to be transported, such as elderly care residents in nursing homes. Moreover, the utility of mobile X-ray isn't confined solely to traditional healthcare recipients; it has proven to be a valuable resource for vulnerable populations, including the homeless, drug users, asylum seekers, and patients with multiple co-morbidities. Mobile X-rays reduce patient stress, minimize costly hospitalizations, and offer cost-effective imaging. While studies confirm its reliability, further research is needed, especially regarding image quality. Recent advancements in lightweight equipment with enhanced battery and detector technology provide the potential for nearly handheld radiography. The main aim of this study was to evaluate a new lightweight mobile X-ray system with two different detectors and compare the image quality with a modern stationary system. Methods: A total of 74 images of the chest (chest anterior-posterior (AP) views and chest lateral views) and pelvic/hip region (AP pelvis views, hip AP views, and hip cross-table lateral views) were acquired on a whole-body phantom (Kyotokagaku, Japan), utilizing varying image parameters. These images were obtained using a stationary system - 18 images (Mediel, Sweden), a mobile X-ray system with a second-generation detector - 28 images (FDR D-EVO II; Fujifilm, Japan) and a mobile X-ray system with a third-generation detector - 28 images (FDR D-EVO III; Fujifilm, Japan). Image quality was assessed by visual grading analysis (VGA), which is a method to measure image quality by assessing the visibility and accurate reproduction of anatomical structures within the images. A total of 33 image criteria were used in the analysis. A panel of two experienced radiologists, two experienced radiographers, and two final-term radiographer students evaluated the image quality on a 5-grade ordinal scale using the software Viewdex 3.0 (Viewer for Digital Evaluation of X-ray images, Sweden). Data were analyzed using visual grading characteristics analysis. The dose was measured by the dose-area product (DAP) reported by the respective systems. Results: The mobile X-ray equipment (both detectors) showed significantly better image quality than the stationary equipment for the pelvis, hip AP and hip cross-table lateral images with AUCVGA-values ranging from 0.64-0.92, while chest images showed mixed results. The number of images rated as having sufficient quality for diagnostic use was significantly higher for mobile X-ray generation 2 and 3 compared with the stationary X-ray system. The DAP values were higher for the stationary compared to the mobile system. Conclusions: The new lightweight radiographic equipment had an image quality at least as good as a fixed system at a lower radiation dose. Future studies should focus on clinical images and consider radiographers' viewpoints for a comprehensive assessment.

Keywords: mobile x-ray, visual grading analysis, radiographer, radiation dose

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Authors: Antonella Falanga, Armando Cartenì

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Today, an unprecedented amount of data coming from several sources, including mobile devices, sensors, tracking systems, and online platforms, characterizes our lives. The term “big data” not only refers to the quantity of data but also to the variety and speed of data generation. These data hold valuable insights that, when extracted and analyzed, facilitate informed decision-making. The 4Vs of big data - velocity, volume, variety, and value - highlight essential aspects, showcasing the rapid generation, vast quantities, diverse sources, and potential value addition of these kinds of data. This surge of information has revolutionized many sectors, such as business for improving decision-making processes, healthcare for clinical record analysis and medical research, education for enhancing teaching methodologies, agriculture for optimizing crop management, finance for risk assessment and fraud detection, media and entertainment for personalized content recommendations, emergency for a real-time response during crisis/events, and also mobility for the urban planning and for the design/management of public and private transport services. Big data's pervasive impact enhances societal aspects, elevating the quality of life, service efficiency, and problem-solving capacities. However, during this transformative era, new challenges arise, including data quality, privacy, data security, cybersecurity, interoperability, the need for advanced infrastructures, and staff training. Within the transportation sector (the one investigated in this research), applications span planning, designing, and managing systems and mobility services. Among the most common big data applications within the transport sector are, for example, real-time traffic monitoring, bus/freight vehicle route optimization, vehicle maintenance, road safety and all the autonomous and connected vehicles applications. Benefits include a reduction in travel times, road accidents and pollutant emissions. Within these issues, the proper transport demand estimation is crucial for sustainable transportation planning. Evaluating the impact of sustainable mobility policies starts with a quantitative analysis of travel demand. Achieving transportation decarbonization goals hinges on precise estimations of demand for individual transport modes. Emerging technologies, offering substantial big data at lower costs than traditional methods, play a pivotal role in this context. Starting from these considerations, this study explores the usefulness impact of big data within transport demand estimation. This research focuses on leveraging (big) data collected during the COVID-19 pandemic to estimate the evolution of the mobility demand in Italy. Estimation results reveal in the post-COVID-19 era, more than 96 million national daily trips, about 2.6 trips per capita, with a mobile population of more than 37.6 million Italian travelers per day. Overall, this research allows us to conclude that big data better enhances rational decision-making for mobility demand estimation, which is imperative for adeptly planning and allocating investments in transportation infrastructures and services.

Keywords: big data, cloud computing, decision-making, mobility demand, transportation

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Authors: Soheila Sadeghi

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Accurate cost prediction is essential for effective project management and decision-making in the construction industry. This study aims to develop a cost prediction model for construction projects using Machine Learning techniques and Particle Swarm Optimization (PSO). The research utilizes a comprehensive dataset containing project cost estimates, actual costs, resource details, and project performance metrics from a road reconstruction project. The methodology involves data preprocessing, feature selection, and the development of an Artificial Neural Network (ANN) model optimized using PSO. The study investigates the impact of various input features, including cost estimates, resource allocation, and project progress, on the accuracy of cost predictions. The performance of the optimized ANN model is evaluated using metrics such as Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and R-squared. The results demonstrate the effectiveness of the proposed approach in predicting project costs, outperforming traditional benchmark models. The feature selection process identifies the most influential variables contributing to cost variations, providing valuable insights for project managers. However, this study has several limitations. Firstly, the model's performance may be influenced by the quality and quantity of the dataset used. A larger and more diverse dataset covering different types of construction projects would enhance the model's generalizability. Secondly, the study focuses on a specific optimization technique (PSO) and a single Machine Learning algorithm (ANN). Exploring other optimization methods and comparing the performance of various ML algorithms could provide a more comprehensive understanding of the cost prediction problem. Future research should focus on several key areas. Firstly, expanding the dataset to include a wider range of construction projects, such as residential buildings, commercial complexes, and infrastructure projects, would improve the model's applicability. Secondly, investigating the integration of additional data sources, such as economic indicators, weather data, and supplier information, could enhance the predictive power of the model. Thirdly, exploring the potential of ensemble learning techniques, which combine multiple ML algorithms, may further improve cost prediction accuracy. Additionally, developing user-friendly interfaces and tools to facilitate the adoption of the proposed cost prediction model in real-world construction projects would be a valuable contribution to the industry. The findings of this study have significant implications for construction project management, enabling proactive cost estimation, resource allocation, budget planning, and risk assessment, ultimately leading to improved project performance and cost control. This research contributes to the advancement of cost prediction techniques in the construction industry and highlights the potential of Machine Learning and PSO in addressing this critical challenge. However, further research is needed to address the limitations and explore the identified future research directions to fully realize the potential of ML-based cost prediction models in the construction domain.

Keywords: cost prediction, construction projects, machine learning, artificial neural networks, particle swarm optimization, project management, feature selection, road reconstruction

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Authors: Devin Doos, Ashley Hughes, Trang Pham, Paul Barach, Rami Ahmed

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Over 115,000 Health Care Workers (HCWs) have died from COVID-19, and millions have been infected while caring for patients. HCWs have filed thousands of safety complaints surrounding safety concerns due to Personal Protective Equipment (PPE) shortages, which included concerns around inadequate and PPE reuse. Protocols for donning and doffing PPE remain ambiguous, lacking an evidence-base, and often result in wide deviations in practice. PPE donning and doffing protocol deviations commonly result in self-contamination but have not been thoroughly addressed. No evidence-driven protocols provide guidance on protecting HCW during periods of PPE reuse. Objective: The aim of this study was to examine safety-related threats and risks to Health Care Workers (HCWs) due to the reuse of PPE among Emergency Department personnel. Method: We conducted a prospective observational study to examine the risks of reusing PPE. First, ED personnel were asked to don and doff PPE in a simulation lab. Each participant was asked to don and doff PPE five times, according to the maximum reuse recommendation set by the Centers for Disease Control and Prevention (CDC). Each participant was videorecorded; video recordings were reviewed and coded independently by at least 2 of the 3trained coders for safety behaviors and riskiness of actions. A third coder was brought in when the agreement between the 2 coders could not be reached. Agreement between coders was high (81.9%), and all disagreements (100%) were resolved via consensus. A bowtie risk assessment chart was constructed analyzing the factors that contribute to increased risks HCW are faced with due to PPE use and reuse. Agreement amongst content experts in the field of Emergency Medicine, Human Factors, and Anesthesiology was used to select aspects of health care that both contribute and mitigate risks associated with PPE reuse. Findings: Twenty-eight clinician participants completed five rounds of donning/doffing PPE, yielding 140 PPE donning/doffing sequences. Two emerging threats were associated with behaviors in donning, doffing, and re-using PPE: (i) direct exposure to contaminant, and (ii) transmission/spread of contaminant. Protective behaviors included: hand hygiene, not touching the patient-facing surface of PPE, and ensuring a proper fit and closure of all PPE materials. 100% of participants (n= 28) deviated from the CDC recommended order, and most participants (92.85%, n=26) self-contaminated at least once during reuse. Other frequent errors included failure to tie all ties on the PPE (92.85%, n=26) and failure to wash hands after a contamination event occurred (39.28%, n=11). Conclusions: There is wide variation and regular errors in how HCW don and doffPPE while including in reusing PPE that led to self-contamination. Some errors were deemed “recoverable”, such as hand washing after touching a patient-facing surface to remove the contaminant. Other errors, such as using a contaminated mask and accidentally spreading to the neck and face, can lead to compound risks that are unique to repeated PPE use. A more comprehensive understanding of the contributing threats to HCW safety and complete approach to mitigating underlying risks, including visualizing with risk management toolsmay, aid future PPE designand workflow and space solutions.

Keywords: bowtie analysis, health care, PPE reuse, risk management

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Authors: Domenico Palladino, Nicolandrea Calabrese, Francesca Caffari, Giulia Centi, Francesca Margiotta, Giovanni Murano, Laura Ronchetti, Paolo Signoretti, Lisa Volpe, Silvia Di Turi

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The aim to achieve a fully decarbonized building stock by 2050 stands as one of the most challenging issues within the spectrum of energy and climate objectives. Numerous strategies are imperative, particularly emphasizing the reduction and optimization of energy demand. Ensuring the high energy performance of buildings emerges as a top priority, with measures aimed at cutting energy consumptions. Concurrently, it is imperative to decrease greenhouse gas emissions by using renewable energy sources for the on-site energy production, thereby striving for an energy balance leading towards zero-emission buildings. Italy's predominant building stock comprises ancient buildings, many of which hold historical significance and are subject to stringent preservation and conservation regulations. Attaining high levels of energy efficiency and reducing CO2 emissions in such buildings poses a considerable challenge, given their unique characteristics and the imperative to adhere to principles of conservation and restoration. Additionally, conducting a meticulous analysis of these buildings' current state is crucial for accurately quantifying their energy performance and predicting the potential impacts of proposed renovation strategies on energy consumption reduction. Within this framework, the paper presents a pilot case in Rome, outlining a methodological approach for the renovation of historic buildings towards achieving Zero Emission Building (ZEB) objective. The building has a mixed function with offices, a conference hall, and an exposition area. The building envelope is made of historical and precious materials used as cladding which must be preserved. A thorough understanding of the building's current condition serves as a prerequisite for analyzing its energy performance. This involves conducting comprehensive archival research, undertaking on-site diagnostic examinations to characterize the building envelope and its systems, and evaluating actual energy usage data derived from energy bills. Energy simulations and audit are the first step in the analysis with the assessment of the energy performance of the actual current state. Subsequently, different renovation scenarios are proposed, encompassing advanced building techniques, to pinpoint the key actions necessary for improving mechanical systems, automation and control systems, and the integration of renewable energy production. These scenarios entail different levels of renovation, ranging from meeting minimum energy performance goals to achieving the highest possible energy efficiency level. The proposed interventions are meticulously analyzed and compared to ascertain the feasibility of attaining the Zero Emission Building objective. In conclusion, the paper provides valuable insights that can be extrapolated to inform a broader approach towards energy-efficient refurbishment of historical buildings that may have limited potential for renovation in their building envelopes. By adopting a methodical and nuanced approach, it is possible to reconcile the imperative of preserving cultural heritage with the pressing need to transition towards a sustainable, low-carbon future.

Keywords: energy conservation and transition, energy efficiency in historical buildings, buildings energy performance, energy retrofitting, zero emission buildings, energy simulation

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Authors: Stephanie Ann Houghton

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SDG-driven intercultural citizenship education through performing arts and history research, combined with dance-fitness development inspired by performing arts, can provide a third space in which performing arts, local history, and contemporary society drive educational and social development, supporting the performing arts in student-generated ways, reflecting their sense, priorities, and goals. Within a string of rugged volcanic peninsulas along the north-western coastline of the Ariake Sea, Kyushu, southern Japan, are found a range of traditional performing arts endangered in Japan’s ageing society, including Menburyu mask dance. From 2017, Menburyu culture and history were explored with Menburyu veterans and students within Houghton’s FURYU Educational Program (FEP) at Saga University. Through collaboration with professional fitness instructor Kazuki Miyata, basic Menburyu movements and concepts were blended into aerobics routines to generate Menburyu-Inspired Dance-Fitness (MIDF). Drawing on history, legends, and myths, three important storylines for understanding Menburyu, captured in students’ bilingual (English/Japanese) exhibition panels, emerged: harvest, demons and gods, and the Battle of Tadenawate 1530. Houghton and Miyata performed the first MIDF routine at the 22nd Traditional Performing Arts Festival at Yutoku Inari Shrine, Kashima, in September 2019. FEP exhibitions, dance-fitness events, and MIDF performance have been reported in the media locally and nationally. In an action research case study, a classroom research project was conducted with four female Japanese students over fifteen three-hour online lessons (April-July 2020). Part 1 of each lesson focused on Menburyu history. This included a guest lecture by Kensuke Ryuzoji. The three Menburyu storylines served as keys for exploring Menburyu history from international standpoints.Part 2 focused on the development of MIDF basic steps and an online MIDF event with outside guests. Through post-lesson reflective diaries and reports/videos documenting their experience, students engaged in heritage management, intercultural dialogue, health/fitness, technology and art generation activities within the FEP, centring on UN Sustainable Development Goals (SDGs) including health and wellness (SDG3), and quality education (SDG4), taking a glocal approach. In this presentation, qualitative analysis of student-generated reflective diary and reports will be presented to reveal educational processes, learning outcomes,and apparent areas of (potential) social impact of this classroom research project. Data will be presented in two main parts: (1) The mutually beneficial relationship between local traditional performing arts research and local history researchwill be addressed. One has the power both inform and illuminate the other given their deep connections. This can drive the development of students’ intercultural history competence related to and through the performing arts. (2) The development of dance-fitness inspired by traditional performing arts provides a third space in which performing arts, local history and contemporary society can be connected through SDG-driven education inside the classroom in ways that can also drive social innovation outside the classroom, potentially supporting the performing arts itself in student-generated ways, reflecting their own sense, priorities and social goals. Links will be drawn with intercultural citizenship, strengths and weaknesses of this teaching approach will be highlighted, and avenues for future research in this exciting new area will be suggested.

Keywords: cultural traditions, dance-fitness performance and participation, intercultural communication approach, mask dance origins

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