Search results for: e-T Guide

Authors: Ronald Orth, Johanna Haunschild, Sara Tsog

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The bioeconomy is an inter- and cross-disciplinary field covering a large number and wide scope of existing and emerging technologies. It has a great potential to contribute to the transformation process of industry landscape and ultimately drive the economy towards sustainability. However, bioeconomy per se is not necessarily sustainable and technology should be seen as an enabler rather than panacea to all our ecological, social and economic issues. Therefore, to draw and maximize benefits from bioeconomy in terms of sustainability, we propose that innovative activities should encompass not only novel technologies and bio-based new materials but also multifocal innovations. For multifocal innovation endeavors, innovation management plays a substantial role, as any innovation emerges in a complex iterative process where communication and knowledge exchange among relevant stake holders has a pivotal role. The knowledge generation and innovation are although at the core of transition towards a more sustainable bio-based economy, to date, there is a significant lack of concepts and models that approach bioeconomy from the innovation management approach. The aim of this paper is therefore two-fold. First, it inspects the role of transformative approach in the adaptation of bioeconomy that contributes to the environmental, ecological, social and economic sustainability. Second, it elaborates the importance of technology and innovation management as a tool for smooth, prompt and effective transition of firms to the bioeconomy. We conduct a qualitative literature study on the sustainability challenges that bioeconomy entails thus far using Science Citation Index and based on grey literature, as major economies e.g. EU, USA, China and Brazil have pledged to adopt bioeconomy and have released extensive publications on the topic. We will draw an example on the forest based business sector that is transforming towards the new green economy more rapidly as expected, although this sector has a long-established conventional business culture with consolidated and fully fledged industry. Based on our analysis we found that a successful transition to sustainable bioeconomy is conditioned on heterogenous and contested factors in terms of stakeholders , activities and modes of innovation. In addition, multifocal innovations occur when actors from interdisciplinary fields engage in intensive and continuous interaction where the focus of innovation is allocated to a field of mutually evolving socio-technical practices that correspond to the aims of the novel paradigm of transformative innovation policy. By adopting an integrated and systems approach as well as tapping into various innovation networks and joining global innovation clusters, firms have better chance of creating an entire new chain of value added products and services. This requires professionals that have certain capabilities and skills such as: foresight for future markets, ability to deal with complex issues, ability to guide responsible R&D, ability of strategic decision making, manage in-depth innovation systems analysis including value chain analysis. Policy makers, on the other hand, need to acknowledge the essential role of firms in the transformative innovation policy paradigm.

Keywords: bioeconomy, innovation and technology management, multifocal innovation, sustainability, transformative innovation policy

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Authors: Zofia Wlodarczyk

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I study the experiences of domestic violence survivors who flee their countries of origin in times of political conflict using insight and evidence from forty-five biographical interviews with female Chechen refugees and twelve refugee resettlement professionals in Poland. Both refugees and women are often described as having less agency—that is, they lack the power to decide to migrate – refugees less than economic migrants and women less than men. In this paper, I focus on how female refugees who have been victims of domestic violence make decisions about leaving their countries of origin during times of political conflict. I use several existing migration theories to trace how the migration experience of these women is shaped by dynamics at different levels of society: the macro level, the meso level and the micro level. At the macro level of analysis, I find that political conflict can be both a source of and an escape from domestic violence. Ongoing conflict can strengthen the patriarchal cultural norms, increase violence and constrain women’s choices when it comes to marriage. However, political conflict can also destabilize families and make pathways for women to escape. At the meso level I demonstrate that other political migrants and institutions that emerge due to politically triggered migration can guide those fleeing domestic violence. Finally, at the micro level, I show that family dynamics often force domestic abuse survivors to make their decision to escape alone or with the support of only the most trusted female relatives. Taken together, my analyses show that we cannot look solely at one level of society when describing decision-making processes of women fleeing domestic violence. Conflict-related micro, meso and macro forces interact with and influence each other: on the one hand, strengthening an abusive trap, and on the other hand, opening a door to escape. This study builds upon several theoretical and empirical debates. First, it expands theories of migration by incorporating both refugee and gender perspectives. Few social scientists have used the migration theory framework to discuss the unique circumstances of refugee flows. Those who have mainly focus on “political” migrants, a designation that frequently fails to account for gender, does not incorporate individuals fleeing gender-based violence, including domestic-violence victims. The study also enriches migration scholarship, typically focused on the US and Western-European context, with research from Eastern Europe and Caucasus. Moreover, it contributes to the literature on the changing roles of gender in the context of migration. I argue that understanding how gender roles and hierarchies influence the pre-migration stage of female refugees is crucial, as it may have implications for policy-making efforts in host countries that recognize the asylum claims of those fleeing domestic violence. This study also engages in debates about asylum and refugee law. Domestic violence is normatively and often legally considered an individual-level problem whereas political persecution is recognized as a structural or societal level issue. My study challenges these notions by showing how the migration triggered by domestic violence is closely intertwined with politically motivated refuge.

Keywords: AGENCY, DOMESTIC VIOLENCE, FEMALE REFUGEES, POLITICAL REFUGE, SOCIAL NETWORKS

Procedia PDF Downloads 169

Authors: Piyaorn Wajanatinapart, Diane R. Lauver

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The number of persons with dementia (PWD) has increased. Informal caregivers are the major providing care. They can have perceived gains and burdens. Caregivers who reported high in perceived gains may report low in burdens and better health. Gaps of caregiving literature were: no report psychometrics in a few studies and unclear definitions of gains; most studies with no theory-guided and conducting in Western countries; not fully described relationships among caregiving variables: motivations, satisfaction with psychological needs, social support, gains, burdens, and physical and psycho-emotional health. Those gaps were filled by assessing psychometric properties of selected measures, providing clearly definitions of gains, using self-determination theory (SDT) to guide the study, and developing the study in Thailand. The study purposes were to evaluate six measures for internal consistency reliability, content validity, and construct validity. This study also examined relationships of caregiving variables: motivations (controlled and autonomous motivations), satisfaction with psychological needs (autonomy, competency, and relatedness), perceived social support, perceived gains, perceived burdens, and physical and psycho-emotional health. This study was a cross-sectional and correlational descriptive design with two convenience samples. Sample 1 was five Thai experts to assess content validity of measures. Sample 2 was 146 Thai caregivers of PWD to assess construct validity, reliability, and relationships among caregiving variables. Experts rated questionnaires and sent them back via e-mail. Caregivers answered questionnaires at clinics of four Thai hospitals. Data analysis was used descriptive statistics and bivariate and multivariate analyses using the composite indicator structural equation model to control measurement errors. For study results, most caregivers were female (82%), middle age (M =51.1, SD =11.9), and daughters (57%). They provided care for 15 hours/day with 4.6 years. The content validity indices of items and scales were .80 or higher for clarity and relevance. Experts suggested item revisions. Cronbach’s alphas were .63 to .93 of ten subscales of four measures and .26 to .57 of three subscales. The gain scale was acceptable for construct validity. With controlling covariates, controlled motivations, the satisfaction with three subscales of psychological needs, and perceived social support had positive relationships with physical and psycho-emotional health. Both satisfaction with autonomy subscale and perceived social support had negative relationship with perceived burdens. The satisfaction with three subscales of psychological needs had positive relationships among them. Physical and psycho-emotional health subscales had positive relationships with each other. Furthermore, perceived burdens had negative relationships with physical and psycho-emotional health. This study was the first use SDT to describe relationships of caregiving variables in Thailand. Caregivers’ characteristics were consistent with literature. Four measures were valid and reliable except two measures. Breadth knowledge about relationships was provided. Interpretation of study results was cautious because of using same sample to evaluate psychometric properties of measures and relationships of caregiving variables. Researchers could use four measures for further caregiving studies. Using a theory would help describe concepts, propositions, and measures used. Researchers may examine the satisfaction with psychological needs as mediators. Future studies to collect data with caregivers in communities are needed.

Keywords: caregivers, caregiving, dementia, measures

Procedia PDF Downloads 308

Authors: Iman Farasat, Howard M. Salis

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Engineered genetic circuits reprogram cellular behavior to act as living computers with applications in detecting cancer, creating self-controlling artificial tissues, and dynamically regulating metabolic pathways. Phenemenological models are often used to simulate and design genetic circuit behavior towards a desired behavior. While such models assume that each circuit component’s function is modular and independent, even small changes in a circuit (e.g. a new promoter, a change in transcription factor expression level, or even a new media) can have significant effects on the circuit’s function. Here, we use statistical thermodynamics to account for the several factors that control transcriptional regulation in bacteria, and experimentally demonstrate the model’s accuracy across 825 measurements in several genetic contexts and hosts. We then employ our first principles model to design, experimentally construct, and characterize a family of signal amplifying genetic circuits (genetic OpAmps) that expand the dynamic range of cell sensors. To develop these models, we needed a new approach to measuring the in vivo binding free energies of transcription factors (TFs), a key ingredient of statistical thermodynamic models of gene regulation. We developed a new high-throughput assay to measure RNA polymerase and TF binding free energies, requiring the construction and characterization of only a few constructs and data analysis (Figure 1A). We experimentally verified the assay on 6 TetR-homolog repressors and a CRISPR/dCas9 guide RNA. We found that our binding free energy measurements quantitatively explains why changing TF expression levels alters circuit function. Altogether, by combining these measurements with our biophysical model of translation (the RBS Calculator) as well as other measurements (Figure 1B), our model can account for changes in TF binding sites, TF expression levels, circuit copy number, host genome size, and host growth rate (Figure 1C). Model predictions correctly accounted for how these 8 factors control a promoter’s transcription rate (Figure 1D). Using the model, we developed a design framework for engineering multi-promoter genetic circuits that greatly reduces the number of degrees of freedom (8 factors per promoter) to a single dimensionless unit. We propose the Ptashne (Pt) number to encapsulate the 8 co-dependent factors that control transcriptional regulation into a single number. Therefore, a single number controls a promoter’s output rather than these 8 co-dependent factors, and designing a genetic circuit with N promoters requires specification of only N Pt numbers. We demonstrate how to design genetic circuits in Pt number space by constructing and characterizing 15 2-repressor OpAmp circuits that act as signal amplifiers when within an optimal Pt region. We experimentally show that OpAmp circuits using different TFs and TF expression levels will only amplify the dynamic range of input signals when their corresponding Pt numbers are within the optimal region. Thus, the use of the Pt number greatly simplifies the genetic circuit design, particularly important as circuits employ more TFs to perform increasingly complex functions.

Keywords: transcription factor, synthetic biology, genetic circuit, biophysical model, binding energy measurement

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

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

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

Procedia PDF Downloads 140

Authors: Vera G. Dianova, Lori P. Montross, Charles M. Burke

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In the digital age, the widespread and frequently excessive use of mobile phones amongst university students is recognized as a significant distractor which interferes with their ability to enter a deep state of concentration during studies and diminishes their prospects of experiencing the enjoyable and instrumental state of flow, as defined and described by psychologist M. Csikszentmihalyi. This study has targeted 50 university students with the aim of teaching them to cultivate their ability to engage in deep work and to attain the state of flow, fostering more effective and enjoyable learning experiences. Prior to the start of the intervention, all participating students completed a comprehensive survey based on a variety of validated scales assessing their inclination toward lifelong learning, frequency of flow experiences during study, frustration tolerance, sense of agency, as well as their love of learning and daily time devoted to non-academic mobile phone activities. Several days after this initial assessment, students received a 90-minute lecture on the principles of flow and deep work, accompanied by a critical discourse on the detrimental effects of excessive mobile phone usage. They were encouraged to practice deep work and strive for frequent flow states throughout the semester. Subsequently, students submitted weekly surveys, including the 10-item CORE Dispositional Flow Scale, a 3-item agency scale and furthermore disclosed their average daily hours spent on non-academic mobile phone usage. As a final step, at the end of the semester students engaged in reflective report writing, sharing their experiences and evaluating the intervention's effectiveness. They considered alterations in their love of learning, reflected on the implications of their mobile phone usage, contemplated improvements in their tolerance for boredom and perseverance in complex tasks, and pondered the concept of lifelong learning. Additionally, students assessed whether they actively took steps towards managing their recreational phone usage and towards improving their commitment to becoming lifelong learners. Employing a mixed-methods approach our study offers insights into the dynamics of concentration, flow, mobile phone usage and attitudes towards learning among undergraduate and graduate university students. The findings of this study aim to promote profound contemplation, on the part of both students and instructors, on the rapidly evolving digital-age higher education environment. In an era defined by digital and AI advancements, the ability to concentrate, to experience the state of flow, and to love learning has never been more crucial. This study underscores the significance of addressing mobile phone distractions and providing strategies for cultivating deep concentration. The insights gained can guide educators in shaping effective learning strategies for the digital age. By nurturing a love for learning and encouraging lifelong learning, educational institutions can better prepare students for a rapidly changing labor market, where adaptability and continuous learning are paramount for success in a dynamic career landscape.

Keywords: deep work, flow, higher education, lifelong learning, love of learning

Procedia PDF Downloads 68

Authors: Eleftheria Atta, Yianna Vovides, Marios Katsioloudes

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In the fusion of neoliberalism and globalization, Higher Education (HE) is becoming increasingly complex. The changing patterns of the economy worldwide caused the development of high value-added economy HE has been viewed as a social investment, significant for the development of knowledge-based societies and economies. In order to contribute to economic competitiveness universities are required to produce local and employable workers in order to fit into the neoliberal economic environment. The emergence of neoliberal performativity, which measures outcomes, is a key aspect in a neoliberal era. It facilitates the redesign of institutions making organizations and individuals to think about themselves in relation to their performance. Performativity and performance management systems lead academics to become more effective, professionally advance, improve and become better than others and therefore act competitively. Besides the aforementioned complexities, universities also encounter the challenge of maintaining a set of values to guide an institution’s actions and which have always been highly respected in developing a HE institution. The formulation of a clear set of values also determines the institutional culture which will be maintained. It is evident that values create a significant framework for the workplace and may determine positive institutional results. Universities are required to engage in activities for capacity building which will improve their students’ competence as well as offer opportunities to administrative and academic staff to professionally develop in light of neoliberal performativity. Additionally, the University is now considered as an innovation ecosystem playing a significant role in providing education, research and innovation to help create solutions to meet social, environmental and economic challenges. Thus, Universities become central in orchestrating multi-actor innovation networks. This presentation will discuss the establishment of an institutional unit entitled ‘Human Development Unit’ (HDU) in a European start-up university. The activities of the HDU are envisioned as drivers for innovation that would enable the university as a whole to maintain its position in a fast-changing world and be ready to face adaptive challenges. In addition, the HDU provides its students, staff, and faculty with opportunities to advance their academic and professional development through engagement in programs that align with institutional values. It also serves as a connector with the broader community. The presentation will highlight the functions of three centers which the unit will coordinate namely, the Student Development Center (SDC), the Faculty & Staff Development Center (FSDC) and the Continuing Education Center (CEC). The presentation aligns with the aim of the conference as it welcomes presentations to discuss innovations and challenges encountered in HE. Particularly, this presentation seeks to discuss the establishment of an innovative unit at a start-up university which will contribute to creating an institutional culture shaped by the value of academic excellence for students as well as for staff, shaping and defining the functions and activities of the unit. The establishment of the proposed unit is crucial in a start-up university both to differentiate from other competitors but also to sustain its presence given the pressures in a neoliberal HE context.

Keywords: academic excellence, globalization, human development unit, neoliberalism

Procedia PDF Downloads 143

Authors: Jessica To

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Feedback is one of the powerful levers for enhancing students’ performance. However, some students are under-engaged with feedback because they lack responsibility for feedback uptake. To resolve this conundrum, recent literature proposes feedback partnerships in which students and teachers share the power and responsibilities to co-construct feedback. During feedback co-construction, students express feedback needs to teachers, and teachers respond to individuals’ needs in return. Though this approach can increase students’ feedback ownership, its application is lagging as the field lacks conceptual clarity and implementation guide. This presentation aims to discuss the conceptual framework of feedback partnerships and feedback co-construction strategies. It identifies the components of feedback partnerships and strategies which could facilitate feedback co-construction. A systematic literature review was conducted to answer the questions. The literature search was performed using ERIC, PsycINFO, and Google Scholar with the keywords “assessment partnership”, “student as partner,” and “feedback engagement”. No time limit was set for the search. The inclusion criteria encompassed (i) student-teacher partnerships in feedback, (ii) feedback engagement in higher education, (iii) peer-reviewed publications, and (iv) English as the language of publication. Those without addressing conceptual understanding and implementation strategies were excluded. Finally, 65 publications were identified and analysed using thematic analysis. For the procedure, the texts relating to the questions were first extracted. Then, codes were assigned to summarise the ideas of the texts. Upon subsuming similar codes into themes, four themes emerged: students’ responsibilities, teachers’ responsibilities, conditions for partnerships development, and strategies. Their interrelationships were examined iteratively for framework development. Establishing feedback partnerships required different responsibilities of students and teachers during feedback co-construction. Students needed to self-evaluate performance against task criteria, identify inadequacies and communicate their needs to teachers. During feedback exchanges, they interpreted teachers’ comments, generated self-feedback through reflection, and co-developed improvement plans with teachers. Teachers had to increase students’ understanding of criteria and evaluation skills and create opportunities for students’ expression of feedback needs. In feedback dialogue, teachers responded to students’ needs and advised on the improvement plans. Feedback partnerships would be best grounded in an environment with trust and psychological safety. Four strategies could facilitate feedback co-construction. First, students’ understanding of task criteria could be increased by rubrics explanation and exemplar analysis. Second, students could sharpen evaluation skills if they participated in peer review and received teacher feedback on the quality of peer feedback. Third, provision of self-evaluation checklists and prompts and teacher modeling of self-assessment process could aid students in articulating feedback needs. Fourth, the trust could be fostered when teachers explained the benefits of feedback co-construction, showed empathy, and provided personalised comments in dialogue. Some strategies were applied in interactive cover sheets in which students performed self-evaluation and made feedback requests on a cover sheet during assignment submission, followed by teachers’ response to individuals’ requests. The significance of this presentation lies in unpacking the conceptual framework of feedback partnerships and outlining feedback co-construction strategies. With a solid foundation in theory and practice, researchers and teachers could better enhance students’ engagement with feedback.

Keywords: conceptual framework, feedback co-construction, feedback partnerships, implementation strategies

Procedia PDF Downloads 90

Authors: Su Yen Chen

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ChatGPT has shown both strengths and limitations in clinical, educational, and research settings, raising important concerns about accuracy, transparency, and ethical use. Despite an improved understanding of user acceptance and satisfaction, there is still a gap in how general AI perceptions translate into practical applications within healthcare. This study focuses on examining the perceptions of ChatGPT's impact among 266 healthcare majors in Taiwan, exploring its implications for their career development, as well as its utility in clinical practice, medical education, and research. By employing a structured survey with precisely defined subscales, this research aims to probe the breadth of ChatGPT's applications within healthcare, assessing both the perceived benefits and the challenges it presents. Additionally, to further enhance the comprehensiveness of our methodology, we have incorporated qualitative data collection methods, which provide complementary insights to the quantitative findings. The findings from the survey reveal that perceptions and usage of ChatGPT among healthcare majors vary significantly, influenced by factors such as its perceived utility, risk, novelty, and trustworthiness. Graduate students and those who perceive ChatGPT as more beneficial and less risky are particularly inclined to use it more frequently. This increased usage is closely linked to significant impacts on personal career development. Furthermore, ChatGPT's perceived usefulness and novelty contribute to its broader impact within the healthcare domain, suggesting that both innovation and practical utility are key drivers of acceptance and perceived effectiveness in professional healthcare settings. Trust emerges as an important factor, especially in clinical settings where the stakes are high. The trust that healthcare professionals place in ChatGPT significantly affects its integration into clinical practice and influences outcomes in medical education and research. The reliability and practical value of ChatGPT are thus critical for its successful adoption in these areas. However, an interesting paradox arises with regard to the ease of use. While making ChatGPT more user-friendly is generally seen as beneficial, it also raises concerns among users who have lower levels of trust and perceive higher risks associated with its use. This complex interplay between ease of use and safety concerns necessitates a careful balance, highlighting the need for robust security measures and clear, transparent communication about how AI systems work and their limitations. The study suggests several strategic approaches to enhance the adoption and integration of AI in healthcare. These include targeted training programs for healthcare professionals to increase familiarity with AI technologies, reduce perceived risks, and build trust. Ensuring transparency and conducting rigorous testing are also vital to foster trust and reliability. Moreover, comprehensive policy frameworks are needed to guide the implementation of AI technologies, ensuring high standards of patient safety, privacy, and ethical use. These measures are crucial for fostering broader acceptance of AI in healthcare, as the study contributes to enriching the discourse on AI's role by detailing how various factors affect its adoption and impact.

Keywords: ChatGPT, healthcare, survey study, IT adoption, behaviour, applcation, concerns

Procedia PDF Downloads 28

Authors: Hassan Younis

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Purpose: The objective of this study is to review influential papers in the sustainability and supply chain studies domain, leveraging insights from this review to develop a structured framework for academics and researchers. This framework aims to assist scholars in identifying the most impactful publications for their scholarly pursuits. Subsequently, the study will apply and trial the developed framework on selected scholarly articles within the sustainability and supply chain studies domain to evaluate its efficacy, practicality, and reliability. Design/Methodology/Approach: Utilizing the "Publish or Perish" tool, a search was conducted to locate papers incorporating "sustainability" and "supply chain" in their titles. After rigorous filtering steps, a panel of university professors identified five crucial criteria for evaluating research robustness: average yearly citation counts (25%), scholarly contribution (25%), alignment of findings with objectives (15%), methodological rigor (20%), and journal impact factor (15%). These five evaluation criteria are abbreviated as “ACMAJ" framework. Each paper then received a tiered score (1-3) for each criterion, normalized within its category, and summed using weighted averages to calculate a Final Normalized Score (FNS). This systematic approach allows for objective comparison and ranking of the research based on its impact, novelty, rigor, and publication venue. Findings: The study's findings highlight the lack of structured frameworks for assessing influential sustainability research in supply chain management, which often results in a dependence on citation counts. A complete model that incorporates five essential criteria has been suggested as a response. By conducting a methodical trial on specific academic articles in the field of sustainability and supply chain studies, the model demonstrated its effectiveness as a tool for identifying and selecting influential research papers that warrant additional attention. This work aims to fill a significant deficiency in existing techniques by providing a more comprehensive approach to identifying and ranking influential papers in the field. Practical Implications: The developed framework helps scholars identify the most influential sustainability and supply chain publications. Its validation serves the academic community by offering a credible tool and helping researchers, students, and practitioners find and choose influential papers. This approach aids field literature reviews and study suggestions. Analysis of major trends and topics deepens our grasp of this critical study area's changing terrain. Originality/Value: The framework stands as a unique contribution to academia, offering scholars an important and new tool to identify and validate influential publications. Its distinctive capacity to efficiently guide scholars, learners, and professionals in selecting noteworthy publications, coupled with the examination of key patterns and themes, adds depth to our understanding of the evolving landscape in this critical field of study.

Keywords: supply chain management, sustainability, framework, model

Procedia PDF Downloads 52

Authors: Hazel James P. Agngarayngay, Arnold R. Elepaño

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Mango is the third most important export fruit in the Philippines. Despite the expanding mango trade in world market, problems on postharvest losses caused by pests and diseases are still prevalent. Many disease control and pest disinfestation methods have been studied and adopted. Heat treatment is necessary to eliminate pests and diseases to be able to pass the quarantine requirements of importing countries. During heat treatments, temperature and time are critical because fruits can easily be damaged by over-exposure to heat. Modeling the process enables researchers and engineers to study the behaviour of temperature distribution within the fruit over time. Understanding physical processes through modeling and simulation also saves time and resources because of reduced experimentation. This research aimed to simulate the heat transfer mechanism and predict the temperature distribution in ‘Carabao' mangoes during hot water treatment (HWT) and extended hot water treatment (EHWT). The simulation was performed in ANSYS CFD Software, using ANSYS CFX Solver. The simulation process involved model creation, mesh generation, defining the physics of the model, solving the problem, and visualizing the results. Boundary conditions consisted of the convective heat transfer coefficient and a constant free stream temperature. The three-dimensional energy equation for transient conditions was numerically solved to obtain heat flux and transient temperature values. The solver utilized finite volume method of discretization. To validate the simulation, actual data were obtained through experiment. The goodness of fit was evaluated using mean temperature difference (MTD). Also, t-test was used to detect significant differences between the data sets. Results showed that the simulations were able to estimate temperatures accurately with MTD of 0.50 and 0.69 °C for the HWT and EHWT, respectively. This indicates good agreement between the simulated and actual temperature values. The data included in the analysis were taken at different locations of probe punctures within the fruit. Moreover, t-tests showed no significant differences between the two data sets. Maximum heat fluxes obtained at the beginning of the treatments were 394.15 and 262.77 J.s-1 for HWT and EHWT, respectively. These values decreased abruptly at the first 10 seconds and gradual decrease was observed thereafter. Data on heat flux is necessary in the design of heaters. If underestimated, the heating component of a certain machine will not be able to provide enough heat required by certain operations. Otherwise, over-estimation will result in wasting of energy and resources. This study demonstrated that the simulation was able to estimate temperatures accurately. Thus, it can be used to evaluate the influence of various treatment conditions on the temperature-time history in mangoes. When combined with information on insect mortality and quality degradation kinetics, it could predict the efficacy of a particular treatment and guide appropriate selection of treatment conditions. The effect of various parameters on heat transfer rates, such as the boundary and initial conditions as well as the thermal properties of the material, can be systematically studied without performing experiments. Furthermore, the use of ANSYS software in modeling and simulation can be explored in modeling various systems and processes.

Keywords: heat transfer, heat treatment, mango, modeling and simulation

Procedia PDF Downloads 247

Authors: K. A.Veselova, N. V.Gromova, I. N.Antonova, I. N. Kalakutskii

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There are many diseases and incidents that may result facial defects and deformities: cancer, trauma, burns, congenital anomalies, and autoimmune diseases. In some cases, patient may acquire atypically extensive facial defect, including more than one anatomical region or, by contrast, atypically small defect (e.g. partial auricular defect). The anaplastology gives us opportunity to help patient with facial disfigurement in cases when plastic surgery is contraindicated. Using of implant retention for facial prosthesis is strongly recommended because improves both aesthetic and functional results and makes using of the prosthesis more comfortable. Prostheticly oriented fixture position is extremely important for aesthetic and functional long-term result; however, the optimal site for fixture placement is not clear in cases with atypical configuration of facial defect. The objective of this report is to demonstrate challenges in fixture position determination we have faced with and offer the solution. In this report, four cases of implant-supported facial prosthesis are described. Extra-oral implants with four millimeter length were used in all cases. The decision regarding the quantity of surgical stages was based on anamnesis of disease. Facial prostheses were manufactured according to conventional technique. Clinical and technological difficulties and mistakes are described, and prostheticly oriented approach for determination of fixture position is demonstrated. The case with atypically large combined orbital and nasal defect resulting after arteriovenous malformation is described: the correct positioning of artificial eye was impossible due to wrong position of the fixture (with suprastructure) located in medial aspect of supraorbital rim. The suprastructure was unfixed and this fixture wasn`t used for retention in order to achieve appropriate artificial eye placement and better aesthetic result. In other case with small partial auricular defect (only helix and antihelix were absent) caused by squamoized cell carcinoma T1N0M0 surgical template was used to avoid the difficulties. To achieve the prostheticly oriented fixture position in case of extremely small defect the template was made on preliminary cast using vacuum thermoforming method. Two radiopaque markers were incorporated into template in preferable for fixture placement positions taking into account future prosthesis configuration. The template was put on remaining ear and cone-beam CT was performed to insure, that the amount of bone is enough for implant insertion in preferable position. Before the surgery radiopaque markers were extracted and template was holed for guide drill. Fabrication of implant-retained facial prostheses gives us opportunity to improve aesthetics, retention and patients’ quality of life. But every inaccuracy in planning leads to challenges on surgery and prosthetic stages. Moreover, in cases with atypically small or extended facial defects prostheticly oriented approach for determination of fixture position is strongly required. The approach including surgical template fabrication is effective, easy and cheap way to avoid mistakes and unpredictable result.

Keywords: anaplastology, facial prosthesis, implant-retained facial prosthesis., maxillofacil prosthese

Procedia PDF Downloads 114

Authors: Oluwaseun Adeleke, Grace Amarachi Omenife, Jennifer Adebambo, Mopelola Raji, Anthony Nwala, Mogbonjubade Adesulure

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Introduction: The incorporation of digital technology in healthcare systems is instrumental in transforming the delivery, management, and overall experience of healthcare and holds the potential to scale up access through over 200 million active mobile phones used in Nigeria. Digital tools enable increased access to care, stronger client engagement, progress in research and data-driven insights, and more effective promotion of self-care and do-it-yourself practices. The Delivering Innovation in Self-Care (DISC) project 2021 has played a pivotal role in granting women greater autonomy over their sexual and reproductive health (SRH) through a variety of approaches, including information and training to self-inject contraception (DMPA-SC). To optimize its outcomes, the project also leverages digital technology platforms like social media: Facebook, Instagram, and Meet Tina (Chatbot) via WhatsApp, Customer Relationship Management (CRM) applications Freshworks, and Viamo. Methodology: The project has been successful at optimizing in-person digital cyberspace interaction to sensitize individuals effectively about self-injection and provide linkages to SI services. This platform employs the Freshworks CRM software application, along with specially trained personnel known as Cyber IPC Agents and DHIS calling centers. Integration of Freshworks CRM software with social media allows a direct connection with clients to address emerging issues, schedule follow-ups, send reminders to improve compliance with self-injection schedules, enhance the overall user experience for self-injection (SI) clients, and generate comprehensive reports and analytics on client interactions. Interaction covers a range of topics, including – How to use SI, learning more about SI, side-effects and its management, accessing services, fertility, ovulation, other family planning methods, inquiries related to Sexual Reproductive Health as well as uses an address log to connect them with nearby facilities or online pharmaceuticals. Results: Between the months of March to September, a total of 5,403 engagements were recorded. Among these, 4,685 were satisfactorily resolved. Since the program's inception, digital advertising has created 233,633,075 impressions, reached 12,715,582 persons, and resulted in 3,394,048 clicks. Conclusion: Leveraging digital technology has proven to be an invaluable tool in client management and improving client experience. The use of Cyber technology has enabled the successful development and maintenance of client relationships, which have been effective at providing support, facilitating delivery and compliance with DMPA-SC self-injection services, and ensuring overall client satisfaction. Concurrently, providing qualitative data, including user experience feedback, has enabled the derivation of crucial insights that inform the decision-making process and guide in normalizing self-care behavior.

Keywords: selfcare, DMPA-SC self-injection, digital technology, cyber technology, freshworks CRM software

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Authors: Meiling Yu, Nadia Rouatbi, Khuloud T. Al-Jamal

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Background: Treatment of neurological disorders with modern medical and surgical approaches remains difficult. Gene therapy, allowing the delivery of genetic materials that encodes potential therapeutic molecules, represents an attractive option. The treatment of brain diseases with gene therapy requires the gene-editing tool to be delivered efficiently to the central nervous system. In this study, we explored the efficiency of different delivery routes, namely intravenous (i.v.), intra-cranial (i.c.), and intra-nasal (i.n.), to deliver stable nucleic acid-lipid particles (SNALPs) containing gene-editing tools namely Cas9 mRNA and sgRNA encoding for GFP as a reporter protein. We hypothesise that SNALPs can reach the brain and perform gene-editing to different extents depending on the administration route. Intranasal administration (i.n.) offers an attractive and non-invasive way to access the brain circumventing the blood–brain barrier. Successful delivery of gene-editing tools to the brain offers a great opportunity for therapeutic target validation and nucleic acids therapeutics delivery to improve treatment options for a range of neurodegenerative diseases. In this study, we utilised Rosa26-Cas9 knock-in mice, expressing GFP, to study brain distribution and gene-editing efficiency of SNALPs after i.v.; i.c. and i.n. routes of administration. Methods: Single guide RNA (sgRNA) against GFP has been designed and validated by in vitro nuclease assay. SNALPs were formulated and characterised using dynamic light scattering. The encapsulation efficiency of nucleic acids (NA) was measured by RiboGreen™ assay. SNALPs were incubated in serum to assess their ability to protect NA from degradation. Rosa26-Cas9 knock-in mice were i.v., i.n., or i.c. administered with SNALPs to test in vivo gene-editing (GFP knockout) efficiency. SNALPs were given as three doses of 0.64 mg/kg sgGFP following i.v. and i.n. or a single dose of 0.25 mg/kg sgGFP following i.c.. knockout efficiency was assessed after seven days using Sanger Sequencing and Inference of CRISPR Edits (ICE) analysis. In vivo, the biodistribution of DiR labelled SNALPs (SNALPs-DiR) was assessed at 24h post-administration using IVIS Lumina Series III. Results: Serum-stable SNALPs produced were 130-140 nm in diameter with ~90% nucleic acid loading efficiency. SNALPs could reach and stay in the brain for up to 24h following i.v.; i.n. and i.c. administration. Decreasing GFP expression (around 50% after i.v. and i.c. and 20% following i.n.) was confirmed by optical imaging. Despite the small number of mice used, ICE analysis confirmed GFP knockout in mice brains. Additional studies are currently taking place to increase mice numbers. Conclusion: Results confirmed efficient gene knockout achieved by SNALPs in Rosa26-Cas9 knock-in mice expressing GFP following different routes of administrations in the following order i.v.= i.c.> i.n. Each of the administration routes has its pros and cons. The next stages of the project involve assessing gene-editing efficiency in wild-type mice and replacing GFP as a model target with therapeutic target genes implicated in Motor Neuron Disease pathology.

Keywords: CRISPR, nanoparticles, brain diseases, administration routes

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Authors: Rachel Buchanan, Rebecca LaRiviere

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Context: The ongoing effects of colonialism continue to be experienced through paternalistic policies and funding processes that cause disjuncture between and across Indigenous early childhood programming on-reserve and in urban and Northern settings in Canada. While various educational organizations and social service providers have risen to address these challenges in the short, medium and long term, there continues to be a lack in nation-wide cohesive, culturally grounded, and meaningful early learning programming for Indigenous children in Canada. Indigenous-centered early learning programs tend to face one of two scaling dilemmas: their program goals are too prescriptive to enable the program to be meaningfully replicated in different cultural/ community settings, or their program goals are too broad to be meaningfully adapted to the unique cultural and contextual needs and desires of Indigenous communities (the “franchise approach”). There are over 600 First Nations communities in Canada representing more than 50 Nations and languages. Consequently, Indigenous early learning programming cannot be applied with a universal or “one size fits all” approach. Sustainable and comprehensive programming must be responsive to each community context, building upon existing strengths and assets to avoid program duplication and irrelevance. Thesis: Community-driven and culturally adapted early childhood programming is critical but cannot be achieved on a large scale within traditional program models that are constrained by prescriptive overarching program goals. Principles, rather than goals, are an effective way to navigate and evaluate complex and dynamic systems. Principles guide an intervention to be adaptable, flexible and scalable. The Martin Family Initiative (MFI) ’s Early Years program engages a principles-based approach to programming. As will be discussed in this paper, this approach enables the program to catalyze existing community-based strengths and organizational assets toward bridging gaps across and disjuncture between Indigenous early learning programs, as well as to scale programming in sustainable, context-responsive and dynamic ways. This paper argues that using a principles-driven and adaptive scaling approach, the Early Years model establishes important learnings for culturally adapted Indigenous early learning programming in Canada. Methodology: The Early Years has leveraged this approach to develop an array of programming with partner organizations and communities across the country. The Early Years began as a singular pilot project in one First Nation. In just three years, it has expanded to five different regions and community organizations. In each context, the program supports the partner organization through different means and to different ends, the extent to which is determined in partnership with each community-based organization: in some cases, this means supporting the organization to build home visiting programming from the ground-up; in others, it means offering organization-specific culturally adapted early learning resources to support the programming that already exists in communities. Principles underpin but do not define the practices of the program in each of these relationships. This paper will explore numerous examples of principles-based adaptability with the context of the Early Years, concluding that the program model offers theadaptability and dynamism necessary to respond to unique and ever-evolving community contexts and needs of Indigenous children today.

Keywords: culturally adapted programming, indigenous early learning, principles-based approach, program scaling

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Authors: Kimberley Adamek

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According to the Council on Tall Buildings, there has been a rapid increase in the construction of tall or “megatall” buildings over the past two decades. Simultaneously, the New England Journal of Medicine has reported that there has been a steady increase in climate related natural disasters since the 1970s; the eastern expansion of the USA's infamous Tornado Alley being just one of many current issues. In the future, this could mean that tall buildings, which already guide high speed winds down to pedestrian levels would have to withstand stronger forces and protect pedestrians in more extreme ways. Although many projects are required to be verified within wind tunnels and a handful of cities such as San Francisco have included wind testing within building code standards, there are still many examples where wind is only considered for basic loading. This typically results in and an increase of structural expense and unwanted mitigation strategies that are proposed late within a project. When building cities, architects rarely consider how each building alters the invisible patterns of wind and how these alterations effect other areas in different ways later on. It is not until these forces move, overpower and even destroy cities that people take notice. For example, towers have caused winds to blow objects into people (Walkie-Talkie Tower, Leeds, England), cause building parts to vibrate and produce loud humming noises (Beetham Tower, Manchester), caused wind tunnels in streets as well as many other issues. Alternatively, there exist towers which have used their form to naturally draw in air and ventilate entire facilities in order to eliminate the needs for costly HVAC systems (The Met, Thailand) and used their form to increase wind speeds to generate electricity (Bahrain Tower, Dubai). Wind and weather exist and effect all parts of the world in ways such as: Science, health, war, infrastructure, catastrophes, tourism, shopping, media and materials. Working in partnership with a leading wind engineering company RWDI, a series of tests, images and animations documenting discovered interactions of different building forms with wind will be collected to emphasize the possibilities for wind use to architects. A site within San Francisco (due to its increasing tower development, consistently wind conditions and existing strict wind comfort criteria) will host a final design. Iterations of this design will be tested within the wind tunnel and computational fluid dynamic systems which will expose, utilize and manipulate wind flows to create new forms, technologies and experiences. Ultimately, this thesis aims to question the amount which the environment is allowed to permeate building enclosures, uncover new programmatic possibilities for wind in buildings, and push the boundaries of working with the wind to ensure the development and safety of future cities. This investigation will improve and expand upon the traditional understanding of wind in order to give architects, wind engineers as well as the general public the ability to broaden their scope in order to productively utilize this living phenomenon that everyone constantly feels but cannot see.

Keywords: wind engineering, climate, visualization, architectural aerodynamics

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Authors: Leonid Zhukov, Dmytro Petrenko

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Optical thermometry has no alternative in many cases of industrial most effective continuous temperature control. Classical optical thermometry technologies can be used on available for pyrometers controlled objects with stable radiation characteristics and transmissivity of the intermediate medium. Without using temperature corrections, it is possible in the case of a “black” body for energy pyrometry and the cases of “black” and “grey” bodies for spectral ratio pyrometry or with using corrections – for any colored bodies. Consequently, with increasing the number of operating waves, optical thermometry possibilities to reduce methodical errors significantly expand. That is why, in recent 25-30 years, research works have been reoriented on more perfect spectral (multicolor) thermometry technologies. There are two physical material substances, i.e., substance (controlled object) and electromagnetic field (thermal radiation), to be operated in optical thermometry. Heat is transferred by radiation; therefore, radiation has the energy, entropy, and temperature. Optical thermometry was originating simultaneously with the developing of thermal radiation theory when the concept and the term "radiation temperature" was not used, and therefore concepts and terms "conditional temperatures" or "pseudo temperature" of controlled objects were introduced. They do not correspond to the physical sense and definitions of temperature in thermodynamics, molecular-kinetic theory, and statistical physics. Launched by the scientific thermometric society, discussion about the possibilities of temperature measurements of objects, including colored bodies, using the temperatures of their radiation is not finished. Are the information about controlled objects transferred by their radiation enough for temperature measurements? The positive and negative answers on this fundamental question divided experts into two opposite camps. Recent achievements of spectral thermometry develop events in her favour and don’t leave any hope for skeptics. This article presents the results of investigations and developments in the field of spectral thermometry carried out by the authors in the Department of Thermometry and Physics-Chemical Investigations. The authors have many-year’s of experience in the field of modern optical thermometry technologies. Innovative technologies of optical continuous temperature control have been developed: symmetric-wave, two-color compensative, and based on obtained nonlinearity equation of spectral emissivity distribution linear, two-range, and parabolic. Тhe technologies are based on direct measurements of physically substantiated and proposed by Prof. L. Zhukov, radiation temperatures with the next calculation of the controlled object temperature using this radiation temperatures and corresponding mathematical models. Тhe technologies significantly increase metrological characteristics of continuous contactless and light-guide temperature control in energy, metallurgical, ceramic, glassy, and other productions. For example, under the same conditions, the methodical errors of proposed technologies are less than the errors of known spectral and classical technologies in 2 and 3-13 times, respectively. Innovative technologies provide quality products obtaining at the lowest possible resource-including energy costs. More than 600 publications have been published on the completed developments, including more than 100 domestic patents, as well as 34 patents in Australia, Bulgaria, Germany, France, Canada, the USA, Sweden, and Japan. The developments have been implemented in the enterprises of USA, as well as Western Europe and Asia, including Germany and Japan.

Keywords: emissivity, radiation temperature, object temperature, spectral thermometry

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Authors: David F. Nettleton, Elodie Bugnicourt, Christian Wasiak, Alejandro Rosales

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In this presentation, preliminary results are given for the modeling and calibration of two different industrial winding MIMO (Multiple Input Multiple Output) processes using machine learning techniques. In contrast to previous approaches which have typically used ‘black-box’ linear statistical methods together with a definition of the mechanical behavior of the process, we use non-linear machine learning algorithms together with a ‘white-box’ rule induction technique to create a supervised model of the fitting error between the expected and real force measures. The final objective is to build a precise model of the winding process in order to control de-tension of the material being wound in the first case, and the friction of the material passing through the die, in the second case. Case 1, Tension Control of a Winding Process. A plastic web is unwound from a first reel, goes over a traction reel and is rewound on a third reel. The objectives are: (i) to train a model to predict the web tension and (ii) calibration to find the input values which result in a given tension. Case 2, Friction Force Control of a Micro-Pullwinding Process. A core+resin passes through a first die, then two winding units wind an outer layer around the core, and a final pass through a second die. The objectives are: (i) to train a model to predict the friction on die2; (ii) calibration to find the input values which result in a given friction on die2. Different machine learning approaches are tested to build models, Kernel Ridge Regression, Support Vector Regression (with a Radial Basis Function Kernel) and MPART (Rule Induction with continuous value as output). As a previous step, the MPART rule induction algorithm was used to build an explicative model of the error (the difference between expected and real friction on die2). The modeling of the error behavior using explicative rules is used to help improve the overall process model. Once the models are built, the inputs are calibrated by generating Gaussian random numbers for each input (taking into account its mean and standard deviation) and comparing the output to a target (desired) output until a closest fit is found. The results of empirical testing show that a high precision is obtained for the trained models and for the calibration process. The learning step is the slowest part of the process (max. 5 minutes for this data), but this can be done offline just once. The calibration step is much faster and in under one minute obtained a precision error of less than 1x10-3 for both outputs. To summarize, in the present work two processes have been modeled and calibrated. A fast processing time and high precision has been achieved, which can be further improved by using heuristics to guide the Gaussian calibration. Error behavior has been modeled to help improve the overall process understanding. This has relevance for the quick optimal set up of many different industrial processes which use a pull-winding type process to manufacture fibre reinforced plastic parts. Acknowledgements to the Openmind project which is funded by Horizon 2020 European Union funding for Research & Innovation, Grant Agreement number 680820

Keywords: data model, machine learning, industrial winding, calibration

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Authors: Meenakshi Barsaul Chauhan, Aastha Chauhan, Shilpa Hurmade, Rajeev Sen, Jyotsna Sen, Monika Dalal

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Introduction: Ovarian masses are common forms of neoplasm in women and represent 2/3rd of gynaecological malignancies. A pre-operative suggestion of malignancy can guide the gynecologist to refer women with suspected pelvic mass to a gynecological oncologist for appropriate therapy and optimized treatment, which can improve survival. In the younger age group preoperative differentiation into benign or malignant pathology can decide for conservative or radical surgery. Imaging modalities have a definite role in establishing the diagnosis. By using International Ovarian Tumor Analysis (IOTA) classification with sonography, costly radiological methods like Magnetic Resonance Imaging (MRI) / computed tomography (CT) scan can be reduced, especially in developing countries like India. Thus, this study is being undertaken to evaluate the role of clinical methods and sonography for diagnosis of the nature of the ovarian tumor. Material And Methods: This prospective observational study was conducted on 40 patients presenting with ovarian masses, in the Department of Obstetrics and Gynaecology, at a tertiary care center in northern India. Functional cysts were excluded. Ultrasonography and color Doppler were performed on all the cases.IOTA rules were applied, which take into account locularity, size, presence of solid components, acoustic shadow, dopper flow etc . Magnetic Resonance Imaging (MRI) / computed tomography (CT) scans abdomen and pelvis were done in cases where sonography was inconclusive. In inoperable cases, Fine needle aspiration cytology (FNAC) was done. The histopathology report after surgery and cytology report after FNAC was correlated statistically with the pre-operative diagnosis made clinically and sonographically using IOTA rules. Statistical Analysis: Descriptive measures were analyzed by using mean and standard deviation and the Student t-test was applied and the proportion was analyzed by applying the chi-square test. Inferential measures were analyzed by sensitivity, specificity, negative predictive value, and positive predictive value. Results: Provisional diagnosis of the benign tumor was made in 16(42.5%) and of the malignant tumor was made in 24(57.5%) patients on the basis of clinical findings. With IOTA simple rules on sonography, 15(37.5%) were found to be benign, while 23 (57.5%) were found to be malignant and findings were inconclusive in 2 patients (5%). FNAC/Histopathology reported that benign ovarian tumors were 14 (35%) and 26(65%) were malignant, which was taken as the gold standard. The clinical finding alone was found to have a sensitivity of 66.6% and a specificity of 90.9%. USG alone had a sensitivity of 86% and a specificity of 80%. When clinical findings and IOTA simple rules of sonography were combined (excluding inconclusive masses), the sensitivity and specificity were 83.3% and 92.3%, respectively. While including inconclusive masses, sensitivity came out to be 91.6% and specificity was 89.2. Conclusion: IOTA's simple sonography rules are highly sensitive and specific in the prediction of ovarian malignancy and also easy to use and easily reproducible. Thus, combining clinical examination with USG will help in the better management of patients in terms of time, cost and better prognosis. This will also avoid the need for costlier modalities like CT, and MRI.

Keywords: benign, international ovarian tumor analysis classification, malignant, ovarian tumours, sonography

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Authors: Selin Guney, Andres Riquelme

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Among the main purposes of optimal and efficient forecasts of agricultural commodity prices is to guide the firms to advance the economic decision making process such as planning business operations and marketing decisions. Governments are also the beneficiaries and suppliers of agricultural price forecasts. They use this information to establish a proper agricultural policy, and hence, the forecasts affect social welfare and systematic errors in forecasts could lead to a misallocation of scarce resources. Various empirical approaches have been applied to forecast commodity prices that have used different methodologies. Most commonly-used approaches to forecast commodity sectors depend on classical time series models that assume values of the response variables are precise which is quite often not true in reality. Recently, this literature has mostly evolved to a consideration of fuzzy time series models that provide more flexibility in terms of the classical time series models assumptions such as stationarity, and large sample size requirement. Besides, fuzzy modeling approach allows decision making with estimated values under incomplete information or uncertainty. A number of fuzzy time series models have been developed and implemented over the last decades; however, most of them are not appropriate for forecasting repeated and nonconsecutive transitions in the data. The modeling scheme used in this paper eliminates this problem by introducing Markov modeling approach that takes into account both the repeated and nonconsecutive transitions. Also, the determination of length of interval is crucial in terms of the accuracy of forecasts. The problem of determining the length of interval arbitrarily is overcome and a methodology to determine the proper length of interval based on the distribution or mean of the first differences of series to improve forecast accuracy is proposed. The specific purpose of this paper is to propose and investigate the potential of a new forecasting model that integrates methodologies for determining the proper length of interval based on the distribution or mean of the first differences of series and Fuzzy Time Series- Markov Chain model. Moreover, the accuracy of the forecasting performance of proposed integrated model is compared to different univariate time series models and the superiority of proposed method over competing methods in respect of modelling and forecasting on the basis of forecast evaluation criteria is demonstrated. The application is to daily corn and soybean prices observed at three commercially important North Carolina markets; Candor, Cofield and Roaring River for corn and Fayetteville, Cofield and Greenville City for soybeans respectively. One main conclusion from this paper is that using fuzzy logic improves the forecast performance and accuracy; the effectiveness and potential benefits of the proposed model is confirmed with small selection criteria value such MAPE. The paper concludes with a discussion of the implications of integrating fuzzy logic and nonarbitrary determination of length of interval for the reliability and accuracy of price forecasts. The empirical results represent a significant contribution to our understanding of the applicability of fuzzy modeling in commodity price forecasts.

Keywords: commodity, forecast, fuzzy, Markov

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Authors: Dario Milani, Guido Morgenthal

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Fluid dynamic computation of wind caused forces on bluff bodies e.g light flexible civil structures or high incidence of ground approaching airplane wings, is one of the major criteria governing their design. For such structures a significant dynamic response may result, requiring the usage of small scale devices as guide-vanes in bridge design to control these effects. The focus of this paper is on the numerical simulation of the bluff body problem involving multiscale phenomena induced by small scale devices. One of the solution methods for the CFD simulation that is relatively successful in this class of applications is the Vortex Particle Method (VPM). The method is based on a grid free Lagrangian formulation of the Navier-Stokes equations, where the velocity field is modeled by particles representing local vorticity. These vortices are being convected due to the free stream velocity as well as diffused. This representation yields the main advantages of low numerical diffusion, compact discretization as the vorticity is strongly localized, implicitly accounting for the free-space boundary conditions typical for this class of FSI problems, and a natural representation of the vortex creation process inherent in bluff body flows. When the particle resolution reaches the Kolmogorov dissipation length, the method becomes a Direct Numerical Simulation (DNS). However, it is crucial to note that any solution method aims at balancing the computational cost against the accuracy achievable. In the classical VPM method, if the fluid domain is discretized by Np particles, the computational cost is O(Np2). For the coupled FSI problem of interest, for example large structures such as long-span bridges, the aerodynamic behavior may be influenced or even dominated by small structural details such as barriers, handrails or fairings. For such geometrically complex and dimensionally large structures, resolving the complete domain with the conventional VPM particle discretization might become prohibitively expensive to compute even for moderate numbers of particles. It is possible to reduce this cost either by reducing the number of particles or by controlling its local distribution. It is also possible to increase the accuracy of the solution without increasing substantially the global computational cost by computing a correction of the particle-particle interaction in some regions of interest. In this paper different strategies are presented in order to extend the conventional VPM method to reduce the computational cost whilst resolving the required details of the flow. The methods include temporal sub stepping to increase the accuracy of the particles convection in certain regions as well as dynamically re-discretizing the particle map to locally control the global and the local amount of particles. Finally, these methods will be applied on a test case and the improvements in the efficiency as well as the accuracy of the proposed extension to the method are presented. The important benefits in terms of accuracy and computational cost of the combination of these methods will be thus presented as long as their relevant applications.

Keywords: adaptation, fluid dynamic, remeshing, substepping, vortex particle method

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Authors: Swadha Singh

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International Solar Alliance is the foremost treaty-based global organization concerned with tapping the potential of sun-abundant nations between the Tropics of Cancer and Capricorn and enables co-operation among them. As a founding member of the International Solar Alliance, India exhibits its positioning as an upcoming leader in clean energy. India has set ambitious goals and targets to expand the share of solar in its energy mix and is playing a proactive role both at the regional and global levels. ISA aims to serve multiple goals- bring about scale commercialization of solar power, boost domestic manufacturing, and leverage solar diplomacy in African countries, amongst others. Against this backdrop, this paper attempts to examine the ways in which ISA as an intergovernmental organization under Indian leadership can leverage the cause of clean energy (solar) diplomacy and effectively shape partnerships and collaborations with other developing countries in terms of sharing solar technology, capacity building, risk mitigation, mobilizing financial investment and providing an aggregate market. A more specific focus of ISA is on the developing countries, which in the absence of a collective, are constrained by technology and capital scarcity, despite being naturally endowed with solar resources. Solar rich but finance-constrained economies face political risk, foreign exchange risk, and off-taker risk. Scholars argue that aligning India’s climate change discourse and growth prospects in its engagements, collaborations, and partnerships at the bilateral, multilateral and regional level can help promote trade, attract investments, and promote resilient energy transition both in India and in partner countries. For developing countries, coming together in an action-oriented way on issues of climate and clean energy is particularly important since it is developing and underdeveloped countries that face multiple and coalescing challenges such as the adverse impact of climate change, uneven and low access to reliable energy, and pressing employment needs. Investing in green recovery is agreed to be an assured way to create resilient value chains, create sustainable livelihoods, and help mitigate climate threats. If India is able to ‘green its growth’ process, it holds the potential to emerge as a climate leader internationally. It can use its experience in the renewable sector to guide other developing countries in balancing multiple similar objectives of development, energy security, and sustainability. The challenges underlying solar expansion in India have lessons to offer other developing countries, giving India an opportunity to assume a leadership role in solar diplomacy and expand its geopolitical influence through inter-governmental organizations such as ISA. It is noted that India has limited capacity to directly provide financial funds and support and is not a leading manufacturer of cheap solar equipment, as does China; however, India can nonetheless leverage its large domestic market to scale up the commercialization of solar power and offer insights and learnings to similarly placed abundant solar countries. The paper examines the potential of and limits placed on India’s solar diplomacy.

Keywords: climate diplomacy, energy security, solar diplomacy, renewable energy

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Authors: Nuno Biga

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Artificial Intelligence (AI) has the potential to transform management into several impactful ways. It allows machines to interpret information to find patterns in big data and learn from context analysis, optimize operations, make predictions sensitive to each specific situation and support data-driven decision making. The introduction of an 'artificial brain' in organization also enables learning through complex information and data provided by those who train it, namely its users. The "Assisted-BIGAMES" version of the Accident & Emergency (A&E) simulator introduces the concept of a "Virtual Assistant" (VA) sensitive to context, that provides users useful suggestions to pursue the following operations such as: a) to relocate workstations in order to shorten travelled distances and minimize the stress of those involved; b) to identify in real time existing bottleneck(s) in the operations system so that it is possible to quickly act upon them; c) to identify resources that should be polyvalent so that the system can be more efficient; d) to identify in which specific processes it may be advantageous to establish partnership with other teams; and e) to assess possible solutions based on the suggested KPIs allowing action monitoring to guide the (re)definition of future strategies. This paper is built on the BIGAMES© simulator and presents the conceptual AI model developed and demonstrated through a pilot project (BIG-AI). Each Virtual Assisted BIGAME is a management simulator developed by the author that guides operational and strategic decision making, providing users with useful information in the form of management recommendations that make it possible to predict the actual outcome of different alternative management strategic actions. The pilot project developed incorporates results from 12 editions of the BIGAME A&E that took place between 2017 and 2022 at AESE Business School, based on the compilation of data that allows establishing causal relationships between decisions taken and results obtained. The systemic analysis and interpretation of data is powered in the Assisted-BIGAMES through a computer application called "BIGAMES Virtual Assistant" (VA) that players can use during the Game. Each participant in the VA permanently asks himself about the decisions he should make during the game to win the competition. To this end, the role of the VA of each team consists in guiding the players to be more effective in their decision making, through presenting recommendations based on AI methods. It is important to note that the VA's suggestions for action can be accepted or rejected by the managers of each team, as they gain a better understanding of the issues along time, reflect on good practice and rely on their own experience, capability and knowledge to support their own decisions. Preliminary results show that the introduction of the VA provides a faster learning of the decision-making process. The facilitator designated as “Serious Game Controller” (SGC) is responsible for supporting the players with further analysis. The recommended actions by the SGC may differ or be similar to the ones previously provided by the VA, ensuring a higher degree of robustness in decision-making. Additionally, all the information should be jointly analyzed and assessed by each player, who are expected to add “Emotional Intelligence”, an essential component absent from the machine learning process.

Keywords: artificial intelligence, gamification, key performance indicators, machine learning, management simulators, serious games, virtual assistant

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Authors: Joanna Wielochowska, Aneta Wielochowska

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Whilst the relationship between scientific areas such as cognitive psychology, neurobiology and philosophy of mind has been emphasized in recent decades of scientific research, concepts and discoveries made in both fields overlap and complement each other in their quest for answers to similar questions. The object of the following case study is to describe, analyze and illustrate the nature and characteristics of a certain cognitive experience which appears to display features of synaesthesia, or rather high-level synaesthesia (ideasthesia). The following research has been conducted on the subject of two authors, monozygotic twins (both polysynaesthetes) experiencing involuntary associations of identical nature. Authors made attempts to identify which cognitive and conceptual dependencies may guide this experience. Operating on self-introduced nomenclature, the described phenomenon- multi-dimensional processing of textual and visual information- aims to define a relationship that involuntarily and immediately couples the content introduced by means of text or image a sensation of appearing in a certain place in the mind’s eye. More precisely: (I) defining a concept introduced by means of textual content during activity of reading or writing, or (II) defining a concept introduced by means of visual content during activity of looking at image(s) with simultaneous sensation of being allocated to a given place in the mind’s eye. A place can be then defined as a cognitive representation of a certain concept. During the activity of processing information, a person has an immediate and involuntary feel of appearing in a certain place themselves, just like a character of a story, ‘observing’ a venue or a scenery from one or more perspectives and angles. That forms a unique and unified experience, constituting a background mental landscape of text or image being looked at. We came to a conclusion that semantic allocations to a given place could be divided and classified into the categories and subcategories and are naturally linked with an individual’s semantic knowledge-base. A place can be defined as a representation one’s unique idea of a given concept that has been established in their semantic knowledge base. A multi-level structure of selectivity of places in the mind’s eye, as a reaction to a given information (one stimuli), draws comparisons to structures and patterns found in botany. Double-flowered varieties of flowers and a whorl system (arrangement) which is characteristic to components of some flower species were given as an illustrative example. A composition of petals that fan out from one single point and wrap around a stem inspired an idea that, just like in nature, in philosophy of mind there are patterns driven by the logic specific to a given phenomenon. The study intertwines terms perceived through the philosophical lens, such as definition of meaning, subjectivity of meaning, mental atmosphere of places, and others. Analysis of this rare experience aims to contribute to constantly developing theoretical framework of the philosophy of mind and influence the way human semantic knowledge base and processing given content in terms of distinguishing between information and meaning is researched.

Keywords: information and meaning, information processing, mental atmosphere of places, patterns in nature, philosophy of mind, selectivity, semantic knowledge base, senses, synaesthesia

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Authors: Margarida Soares, Zlatina Genisheva, Lucas Nascimento, André Ribeiro, Tiago Miranda, Eduardo Pereira, Joana Carvalho

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In the current global context, we face a significant challenge: the rapid population increase combined with the pressing need for sustainable management of agro-industrial waste. Beyond understanding how population growth impacts waste generation, it is essential to first identify the primary types of waste produced and the countries responsible to guide targeted actions. This study presents key statistical data on waste production from the agriculture, forestry, and fishing sectors across the European Union, alongside information on the agricultural areas dedicated to crop production in each European Union country. These insights will form the basis for future research into waste production by crop type and country to improve waste management practices and promote recovery methods that are vital for environmental sustainability. The agricultural sector must stay at the forefront of scientific and technological advancements to meet climate change challenges, protect the environment, and ensure food and health security. The study's findings indicate that population growth significantly increases pressure on natural resources, leading to a rise in agro-industrial waste production. EUROSTAT data shows that, in 2020, the agriculture, forestry, and fishing sectors produced over 21 million tons of waste. Spain emerged as the largest producer, contributing nearly 30% of the EU's total waste in these sectors. Furthermore, five countries—Spain, the Netherlands, France, Sweden, and Germany—were responsible for producing more than two-thirds of the waste from these sectors. Regarding agricultural land use, the data for 2020 revealed that around two-thirds of the total agricultural area was concentrated in six countries: France, Spain, Germany, Poland, Romania, and Italy. Regarding waste production per capita, the Netherlands had the highest figures in the EU for 2020. The data presented in this study highlights the urgent need for action in managing agricultural waste in the EU. As population growth continues to drive up demand for agricultural products, waste generation will inevitably rise unless significant changes are made in managing of agro-industrial waste. The countries must lead the way in adopting technological waste management strategies that focus on reducing, reusing, and recycling waste to benefit both the environment and society. Equally important is the need to promote collaborative efforts between governments, industries, and research institutions to develop and implement technologies that transform waste into valuable resources. The insights from this study are critical for informing future strategies to improve the management and valorization of waste from the agro-industrial sector. One of the most promising approaches is adopting circular economy principles to create closed-loop systems that minimize environmental impacts. By rethinking waste as a valuable resource rather than a by-product, agricultural industries can contribute to more sustainable practices that support both environmental health and economic growth.

Keywords: agricultural area, agricultural waste, circular economy, environmental challenges, population growth

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Authors: Juan Pablo Bertuzzi, Mauro Chiarella

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Employing a communication studies perspective and a socio-technological approach, this paper introduces a theoretical framework for understanding the concept of hybrid world; the avatarization phenomena; and the communicational archetype of co-hybridization. This analysis intends to make a contribution to future design of virtual reality experimental applications. Ultimately, this paper presents an ongoing research project that proposes the study of human-avatar interactions in digital educational environments, as well as an innovative reflection on inner digital communication. The aforementioned project presents the analysis of human-avatar interactions, through the development of an interactive experience in virtual reality. The goal is to generate an innovative communicational dimension that could reinforce the hypotheses presented throughout this paper. Being thought for its initial application in educational environments, the analysis and results of this research are dependent and have been prepared in regard of a meticulous planning of: the conception of a 3D digital platform; the interactive game objects; the AI or computer avatars; the human representation as hybrid avatars; and lastly, the potential of immersion, ergonomics and control diversity that can provide the virtual reality system and the game engine that were chosen. The project is divided in two main axes: The first part is the structural one, as it is mandatory for the construction of an original prototype. The 3D model is inspired by the physical space that belongs to an academic institution. The incorporation of smart objects, avatars, game mechanics, game objects, and a dialogue system will be part of the prototype. These elements have all the objective of gamifying the educational environment. To generate a continuous participation and a large amount of interactions, the digital world will be navigable both, in a conventional device and in a virtual reality system. This decision is made, practically, to facilitate the communication between students and teachers; and strategically, because it will help to a faster population of the digital environment. The second part is concentrated to content production and further data analysis. The challenge is to offer a scenario’s diversity that compels users to interact and to question their digital embodiment. The multipath narrative content that is being applied is focused on the subjects covered in this paper. Furthermore, the experience with virtual reality devices proposes users to experiment in a mixture of a seemingly infinite digital world and a small physical area of movement. This combination will lead the narrative content and it will be crucial in order to restrict user’s interactions. The main point is to stimulate and to grow in the user the need of his hybrid avatar’s help. By building an inner communication between user’s physicality and user’s digital extension, the interactions will serve as a self-guide through the gameworld. This is the first attempt to make explicit the avatarization phenomena and to further analyze the communicational archetype of co-hybridization. The challenge of the upcoming years will be to take advantage from these forms of generalized avatarization, in order to create awareness and establish innovative forms of hybridization.

Keywords: avatar, hybrid worlds, socio-technology, virtual reality

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Authors: Anzal Abbas Jaffari, Wajiha Javed, Naseem Salahuddin

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Rationale: Rabies, a vaccine preventable disease, continues to be a critical public health issue as it kills around 2000-5000 people annually in Pakistan. Along with the disease spread among animals, the dog population remains a victim of brutal culling practices by the local authorities, which adversely affects ecosystem (sinking of poison in the soil – affecting vegetation & contaminating water) and the disease spread. The dog population has been exponentially rising primarily because a lack of a consolidated nationwide Animal Birth Control program and awareness among the local communities in general and children in particular. This is reflected in Pakistan’s low SARE score - 1.5, which makes the country trails behind other developing countries like Bangladesh (2.5) and Philippines (3.5).According to an estimate, the province of Sindh alone is home to almost 2.5 million dogs. The clustering of dogs in Peri-Urban areas and inner cities localities leads to an increase of reported dog bite cases in these areas specifically. Objective: Rabies Free Pakistan (RFP), which is a joint venture of Getz Pharma Private Limited and Indus Hospital & Health Network (IHHN); it was established in 2018 to eliminate Rabies from Pakistan by 2030 using the One Health Approach. Methodology: The RFP team is actively working on advocacy and policy front with both the Federal & Provincial government to ensure that all stakeholders currently involved in dog culling in Pakistan have a paradigm shift towards humane methods of vaccination and ABC. Along with the federal government, RFP aims to declare Rabies as a notifiable disease. Whereas RFP closely works with the provincial government of Sindh to initiate a province wide Rabies Control Program.RFP program follows international standards and WHO approved protocols for this program in Pakistan.RFP team has achieved various milestones in the fight against Rabies after successfully scaling up project operations and has vaccinated more than 30,000 dogs and neutered around 7,000 dogs since 2018. Recommendations: Effective implementation of Rabies program (MDV and ABC) requires a concentrated effort to address a variety of structural and policy challenges. This essentially demands a massive shift in the attitude of individuals towards rabies. The two most significant challenges in implementing a standard policy at the structural level are lack of institutional capacity, shortage of vaccine, and absence of inter-departmental coordination among major stakeholders: federal government, provincial ministry of health, livestock, and local bodies (including local councils). The lack of capacity in health care workers to treat dog bite cases emerges as a critical challenge at the clinical level. Conclusion: Pakistan can learn from the successful international models of Sri Lanka and Mexico as they adopted the One Health Approach to eliminate rabies like RFP. The WHO advised One Health approach provides the policymakers with an interactive and cross-sectoral guide, which involves all the essential elements of the eco system (including animals, humans, and other components).

Keywords: animal birth control, dog population, mass dog vaccination, one health, rabies elimination

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Authors: Mingxin Li, Liya Ni

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Autonomous parking is a valuable feature applicable to many robotics applications such as tour guide robots, UV sanitizing robots, food delivery robots, and warehouse robots. With auto-parking, the robot will be able to park at the charging zone and charge itself without human intervention. As compared to self-driving vehicles, auto-parking is more challenging for a small-scale mobile robot only equipped with a front camera due to the camera view limited by the robot’s height and the narrow Field of View (FOV) of the inexpensive camera. In this research, auto-parking of a small-scale mobile robot with a front camera only was achieved in a four-step process: Firstly, transfer learning was performed on the AlexNet, a popular pre-trained convolutional neural network (CNN). It was trained with 150 pictures of empty parking slots and 150 pictures of occupied parking slots from the view angle of a small-scale robot. The dataset of images was divided into a group of 70% images for training and the remaining 30% images for validation. An average success rate of 95% was achieved. Secondly, the image of detected empty parking space was processed with edge detection followed by the computation of parametric representations of the boundary lines using the Hough Transform algorithm. Thirdly, the positions of the entrance point and center of available parking space were predicted based on the robot kinematic model as the robot was driving closer to the parking space because the boundary lines disappeared partially or completely from its camera view due to the height and FOV limitations. The robot used its wheel speeds to compute the positions of the parking space with respect to its changing local frame as it moved along, based on its kinematic model. Lastly, the predicted entrance point of the parking space was used as the reference for the motion control of the robot until it was replaced by the actual center when it became visible again by the robot. The linear and angular velocities of the robot chassis center were computed based on the error between the current chassis center and the reference point. Then the left and right wheel speeds were obtained using inverse kinematics and sent to the motor driver. The above-mentioned four subtasks were all successfully accomplished, with the transformed learning, image processing, and target prediction performed in MATLAB, while the motion control and image capture conducted on a self-built small scale differential drive mobile robot. The small-scale robot employs a Raspberry Pi board, a Pi camera, an L298N dual H-bridge motor driver, a USB power module, a power bank, four wheels, and a chassis. Future research includes three areas: the integration of all four subsystems into one hardware/software platform with the upgrade to an Nvidia Jetson Nano board that provides superior performance for deep learning and image processing; more testing and validation on the identification of available parking space and its boundary lines; improvement of performance after the hardware/software integration is completed.

Keywords: autonomous parking, convolutional neural network, image processing, kinematics-based prediction, transfer learning

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Authors: S. M. Ashikur Elahee, Md. Zahidur Rahman, Md. Shofiqur Rahman

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This study evaluated the impact of different water interventions under WASH program on access of household's to safe drinking water. Following survey method, the study was carried out in two Upazila of South-west coastal region of Bangladesh namely Koyra from Khulna and Shymnagar from Satkhira district. Being an explanatory study, a total of 200 household's selected applying random sampling technique were interviewed using a structured interview schedule. The predicted probability suggests that around 62 percent household's are out of year-round access to safe drinking water whereby, only 25 percent household's have access at SPHERE standard (913 Liters/per person/per year). Besides, majority (78 percent) of the household's have not accessed at both indicators simultaneously. The distance from household residence to the water source varies from 0 to 25 kilometer with an average distance of 2.03 kilometers. The study also reveals that the increase in monthly income around BDT 1,000 leads to additional 11 liters (coefficient 0.01 at p < 0.1) consumption of safe drinking water for a person/year. As expected, lining up time has significant negative relationship with dependent variables i.e., for higher lining up time, the probability of getting access for both SPHERE standard and year round access variables becomes lower. According to ordinary least square (OLS) regression results, water consumption decreases at 93 liters for per person/year of a household if one member is added to that household. Regarding water consumption intensity, ordered logistic regression (OLR) model shows that one-minute increase of lining up time for water collection tends to reduce water consumption intensity. On the other hand, as per OLS regression results, for one-minute increase of lining up time, the water consumption decreases by around 8 liters. Considering access to Deep Tube Well (DTW) as a reference dummy, in OLR, the household under Pond Sand Filter (PSF), Shallow Tube Well (STW), Reverse Osmosis (RO) and Rainwater Harvester System (RWHS) are respectively 37 percent, 29 percent, 61 percent and 27 percent less likely to ensure year round access of water consumption. In line of health impact, different type of water born diseases like diarrhea, cholera, and typhoid are common among the coastal community caused by microbial impurities i.e., Bacteria, Protozoa. High turbidity and TDS in pond water caused by reduction of water depth, presence of suspended particle and inorganic salt stimulate the growth of bacteria, protozoa, and algae causes affecting health hazard. Meanwhile, excessive growth of Algae in pond water caused by excessive nitrate in drinking water adversely effects on child health. In lieu of ensuring access at SPHERE standard, we need to increase the number of water interventions at reasonable distance, preferably a half kilometer away from the dwelling place, ensuring community peoples involved with its installation process where collectively owned water intervention is found more effective than privately owned. In addition, a demand-responsive approach to supply of piped water should be adopted to allow consumer demand to guide investment in domestic water supply in future.

Keywords: access, impact, safe drinking water, Sphere standard, water interventions

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Authors: Adam J. Bowen

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

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

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