Search results for: Alison Power

Authors: Sebastian Kehne, Alexander Epple, Werner Herfs

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A new method for optimal selection of components for multi-axes forward-feed drive systems is proposed in which the choice of motors, gear boxes and ball screw drives is optimized. Essential is here the synchronization of electrical and mechanical frequency behavior of all axes because even advanced controls (like H∞-controls) can only control a small part of the mechanical modes – namely only those of observable and controllable states whose value can be derived from the positions of extern linear length measurement systems and/or rotary encoders on the motor or gear box shafts. Further problems are the unknown processing forces like cutting forces in machine tools during normal operation which make the estimation and control via an observer even more difficult. To start with, the open source Modelica Feed Drive Library which was developed at the Laboratory for Machine Tools, and Production Engineering (WZL) is extended from one axis design to the multi axes design. It is capable to simulate the mechanical, electrical and thermal behavior of permanent magnet synchronous machines with inverters, different gear boxes and ball screw drives in a mechanical system. To keep the calculation time down analytical equations are used for field and torque producing equivalent circuit, heat dissipation and mechanical torque at the shaft. As a first step, a small machine tool with a working area of 635 x 315 x 420 mm is taken apart, and the mechanical transfer behavior is measured with an impulse hammer and acceleration sensors. With the frequency transfer functions, a mechanical finite element model is built up which is reduced with substructure coupling to a mass-damper system which models the most important modes of the axes. The model is modelled with Modelica Feed Drive Library and validated by further relative measurements between machine table and spindle holder with a piezo actor and acceleration sensors. In a next step, the choice of possible components in motor catalogues is limited by derived analytical formulas which are based on well-known metrics to gain effective power and torque of the components. The simulation in Modelica is run with different permanent magnet synchronous motors, gear boxes and ball screw drives from different suppliers. To speed up the optimization different black-box optimization methods (Surrogate-based, gradient-based and evolutionary) are tested on the case. The objective that was chosen is to minimize the integral of the deviations if a step is given on the position controls of the different axes. Small values are good measures for a high dynamic axes. In each iteration (evaluation of one set of components) the control variables are adjusted automatically to have an overshoot less than 1%. It is obtained that the order of the components in optimization problem has a deep impact on the speed of the black-box optimization. An approach to do efficient black-box optimization for multi-axes design is presented in the last part. The authors would like to thank the German Research Foundation DFG for financial support of the project “Optimierung des mechatronischen Entwurfs von mehrachsigen Antriebssystemen (HE 5386/14-1 | 6954/4-1)” (English: Optimization of the Mechatronic Design of Multi-Axes Drive Systems).

Keywords: ball screw drive design, discrete optimization, forward feed drives, gear box design, linear drives, machine tools, motor design, multi-axes design

Procedia PDF Downloads 286

Authors: Heejin Song

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Employing a critical action research approach that rejects essentialist onto-epistemological orientations to research in English language teaching (ELT) and interrogates the hegemonic relations in the knowledge construction and reconstruction processes, this study illuminates how an action research-informed pedagogical practice can transform the English for academic purposes (EAP) teaching to be more culturally and linguistically inclusive and critically oriented for English language learners’ advancement in academic literacies skills. More specifically, this paper aims to showcase the action research-informed pedagogical innovations that emphasize multilingual learners’ multiliteracies engagement and experiential education-oriented learning to facilitate the development of learners’ academic literacies, intercultural communicative competence, and inclusive global citizenship in the context of Canadian university EAP classrooms. The pedagogical innovations through action research embarked in response to growing discussions surrounding pedagogical possibilities of plurilingualism in ELT and synchronous online teaching. The paper is based on two iterations of action research over the pandemic years between 2020 and 2022. The data includes student work samples, focus group interviews, anonymous surveys, teacher feedback and comments on student work and teaching reflections. The first iteration of the action research focused on the affordances of multimodal expressions in individual learners’ academic endeavors for their literacy skills development through individual online activities such as ‘my language autobiography,’ ‘multimodal expression corner’ and public speeches. While these activities help English language learners enhance their knowledge and skills of English-spoken discourses, these tasks did not necessarily require learners’ team-based collaborative endeavors to complete the assigned tasks. Identifying this area for improvement in the instructional design, the second action research cycle/iteration emphasized collaborative performativity through newly added performance/action-based innovative learning tasks, including ‘situational role-playing’, ‘my cooking show & interview’, and group debates in order to provide learners increased opportunities to communicate with peers who joined the class virtually from different parts of the world and enhance learners’ intercultural competence through various strategic and pragmatic communicative skills to collaboratively achieve their shared goals (i.e., successful completion of the given group tasks). The paper exemplifies instances wherein learners’ unique and diverse linguistic and cultural strengths were amplified, and critical literacies were further developed through learners’ performance-oriented multiliteracies engagement. The study suggests that the action research-informed teaching practice that advocates for collaborative multiliteracies engagement serves to facilitate learners’ activation of their existing linguistic and cultural knowledge and contributes to the development of learners’ academic literacy skills. Importantly, the study illuminates that such action research-informed pedagogical initiatives create an inclusive space for learners to build a strong sense of connectedness as global citizens with increased intercultural awareness in their community of language and cultural practices, and further allow learners to actively participate in the construction of ‘collaborative relations of power’ with their peers.

Keywords: action research, EAP, higher education, multiliteracies

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Authors: Hoora Beheshti Haradasht, Abooali Golzary

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Environmental education plays a pivotal role in shaping the future stewards of our planet. Leveraging the power of artificial intelligence (AI) in this endeavor presents an innovative approach to captivate and educate elementary school children about environmental sustainability. This paper explores the application of AI technologies in designing interactive and personalized learning experiences that foster curiosity, critical thinking, and a deep connection to nature. By harnessing AI-driven tools, virtual simulations, and personalized content delivery, educators can create engaging platforms that empower children to comprehend complex environmental concepts while nurturing a lifelong commitment to protecting the Earth. With the pressing challenges of climate change and biodiversity loss, cultivating an environmentally conscious generation is imperative. Integrating AI in environmental education revolutionizes traditional teaching methods by tailoring content, adapting to individual learning styles, and immersing students in interactive scenarios. This paper delves into the potential of AI technologies to enhance engagement, comprehension, and pro-environmental behaviors among elementary school children. Modern AI technologies, including natural language processing, machine learning, and virtual reality, offer unique tools to craft immersive learning experiences. Adaptive platforms can analyze individual learning patterns and preferences, enabling real-time adjustments in content delivery. Virtual simulations, powered by AI, transport students into dynamic ecosystems, fostering experiential learning that goes beyond textbooks. AI-driven educational platforms provide tailored content, ensuring that environmental lessons resonate with each child's interests and cognitive level. By recognizing patterns in students' interactions, AI algorithms curate customized learning pathways, enhancing comprehension and knowledge retention. Utilizing AI, educators can develop virtual field trips and interactive nature explorations. Children can navigate virtual ecosystems, analyze real-time data, and make informed decisions, cultivating an understanding of the delicate balance between human actions and the environment. While AI offers promising educational opportunities, ethical concerns must be addressed. Safeguarding children's data privacy, ensuring content accuracy, and avoiding biases in AI algorithms are paramount to building a trustworthy learning environment. By merging AI with environmental education, educators can empower children not only with knowledge but also with the tools to become advocates for sustainable practices. As children engage in AI-enhanced learning, they develop a sense of agency and responsibility to address environmental challenges. The application of artificial intelligence in elementary environmental education presents a groundbreaking avenue to cultivate environmentally conscious citizens. By embracing AI-driven tools, educators can create transformative learning experiences that empower children to grasp intricate ecological concepts, forge an intimate connection with nature, and develop a strong commitment to safeguarding our planet for generations to come.

Keywords: artificial intelligence, environmental education, elementary children, personalized learning, sustainability

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Authors: Stefan K. Behfar

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The rapid growth of the Ethereum network has brought forth the urgent need for scalable analysis methods to handle the increasing volume of blockchain data. In this research, we propose efficient methodologies for making Ethereum network analysis scalable. Our approach leverages a combination of graph-based data representation, probabilistic sampling, and parallel processing techniques to achieve unprecedented scalability while preserving critical network insights. Data Representation: We develop a graph-based data representation that captures the underlying structure of the Ethereum network. Each block transaction is represented as a node in the graph, while the edges signify temporal relationships. This representation ensures efficient querying and traversal of the blockchain data. Probabilistic Sampling: To cope with the vastness of the Ethereum blockchain, we introduce a probabilistic sampling technique. This method strategically selects a representative subset of transactions and blocks, allowing for concise yet statistically significant analysis. The sampling approach maintains the integrity of the network properties while significantly reducing the computational burden. Graph Convolutional Networks (GCNs): We incorporate GCNs to process the graph-based data representation efficiently. The GCN architecture enables the extraction of complex spatial and temporal patterns from the sampled data. This combination of graph representation and GCNs facilitates parallel processing and scalable analysis. Distributed Computing: To further enhance scalability, we adopt distributed computing frameworks such as Apache Hadoop and Apache Spark. By distributing computation across multiple nodes, we achieve a significant reduction in processing time and enhanced memory utilization. Our methodology harnesses the power of parallelism, making it well-suited for large-scale Ethereum network analysis. Evaluation and Results: We extensively evaluate our methodology on real-world Ethereum datasets covering diverse time periods and transaction volumes. The results demonstrate its superior scalability, outperforming traditional analysis methods. Our approach successfully handles the ever-growing Ethereum data, empowering researchers and developers with actionable insights from the blockchain. Case Studies: We apply our methodology to real-world Ethereum use cases, including detecting transaction patterns, analyzing smart contract interactions, and predicting network congestion. The results showcase the accuracy and efficiency of our approach, emphasizing its practical applicability in real-world scenarios. Security and Robustness: To ensure the reliability of our methodology, we conduct thorough security and robustness evaluations. Our approach demonstrates high resilience against adversarial attacks and perturbations, reaffirming its suitability for security-critical blockchain applications. Conclusion: By integrating graph-based data representation, GCNs, probabilistic sampling, and distributed computing, we achieve network scalability without compromising analytical precision. This approach addresses the pressing challenges posed by the expanding Ethereum network, opening new avenues for research and enabling real-time insights into decentralized ecosystems. Our work contributes to the development of scalable blockchain analytics, laying the foundation for sustainable growth and advancement in the domain of blockchain research and application.

Keywords: Ethereum, scalable network, GCN, probabilistic sampling, distributed computing

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Authors: Chandu Rathnayake, Isuri Anuradha

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Early detection and accurate diagnosis of lung diseases play a crucial role in improving patient prognosis. However, conventional diagnostic methods heavily rely on subjective symptom assessments and medical imaging, often causing delays in diagnosis and treatment. To overcome this challenge, we propose a novel lung disease prediction system that integrates patient symptoms and X-ray images to provide a comprehensive and reliable diagnosis.In this project, develop a mobile application specifically designed for detecting lung diseases. Our application leverages both patient symptoms and X-ray images to facilitate diagnosis. By combining these two sources of information, our application delivers a more accurate and comprehensive assessment of the patient's condition, minimizing the risk of misdiagnosis. Our primary aim is to create a user-friendly and accessible tool, particularly important given the current circumstances where many patients face limitations in visiting healthcare facilities. To achieve this, we employ several state-of-the-art algorithms. Firstly, the Decision Tree algorithm is utilized for efficient symptom-based classification. It analyzes patient symptoms and creates a tree-like model to predict the presence of specific lung diseases. Secondly, we employ the Random Forest algorithm, which enhances predictive power by aggregating multiple decision trees. This ensemble technique improves the accuracy and robustness of the diagnosis. Furthermore, we incorporate a deep learning model using Convolutional Neural Network (CNN) with the RestNet50 pre-trained model. CNNs are well-suited for image analysis and feature extraction. By training CNN on a large dataset of X-ray images, it learns to identify patterns and features indicative of lung diseases. The RestNet50 architecture, known for its excellent performance in image recognition tasks, enhances the efficiency and accuracy of our deep learning model. By combining the outputs of the decision tree-based algorithms and the deep learning model, our mobile application generates a comprehensive lung disease prediction. The application provides users with an intuitive interface to input their symptoms and upload X-ray images for analysis. The prediction generated by the system offers valuable insights into the likelihood of various lung diseases, enabling individuals to take appropriate actions and seek timely medical attention. Our proposed mobile application has significant potential to address the rising prevalence of lung diseases, particularly among young individuals with smoking addictions. By providing a quick and user-friendly approach to assessing lung health, our application empowers individuals to monitor their well-being conveniently. This solution also offers immense value in the context of limited access to healthcare facilities, enabling timely detection and intervention. In conclusion, our research presents a comprehensive lung disease prediction system that combines patient symptoms and X-ray images using advanced algorithms. By developing a mobile application, we provide an accessible tool for individuals to assess their lung health conveniently. This solution has the potential to make a significant impact on the early detection and management of lung diseases, benefiting both patients and healthcare providers.

Keywords: CNN, random forest, decision tree, machine learning, deep learning

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Authors: Damith Tennakoon, Mojgan Jadidi, Seyedreza Razavialavi

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With recent advancements of automation in robotics, from self-driving cars to autonomous 4-legged quadrupeds, one industry that has been stagnant is the construction industry. The methodologies used in a modern-day construction site consist of arduous physical labor and the use of heavy machinery, which has not changed over the past few decades. The dangers of a modern-day construction site affect the health and safety of the workers due to performing tasks such as lifting and moving heavy objects and having to maintain unhealthy posture to complete repetitive tasks such as painting, installing drywall, and laying bricks. Further, training for heavy machinery is costly and requires a lot of time due to their complex control inputs. The main focus of this research is using immersive wearable technology and robotic arms to perform the complex and intricate skills of modern-day construction workers while alleviating the physical labor requirements to perform their day-to-day tasks. The methodology consists of mounting a stereo vision camera, the ZED Mini by Stereolabs, onto the end effector of an industrial grade robotic arm, streaming the video feed into the Virtual Reality (VR) Meta Quest 2 (Quest 2) head-mounted display (HMD). Due to the nature of stereo vision, and the similar field-of-views between the stereo camera and the Quest 2, human-vision can be replicated on the HMD. The main advantage this type of camera provides over a traditional monocular camera is it gives the user wearing the HMD a sense of the depth of the camera scene, specifically, a first-person view of the robotic arm’s end effector. Utilizing the built-in cameras of the Quest 2 HMD, open-source hand-tracking libraries from OpenXR can be implemented to track the user’s hands in real-time. A mixed-reality (XR) Unity application can be developed to localize the operator's physical hand motions with the end-effector of the robotic arm. Implementing gesture controls will enable the user to move the robotic arm and control its end-effector by moving the operator’s arm and providing gesture inputs from a distant location. Given that the end effector of the robotic arm is a gripper tool, gripping and opening the operator’s hand will translate to the gripper of the robot arm grabbing or releasing an object. This human-robot interaction approach provides many benefits within the construction industry. First, the operator’s safety will be increased substantially as they can be away from the site-location while still being able perform complex tasks such as moving heavy objects from place to place or performing repetitive tasks such as painting walls and laying bricks. The immersive interface enables precision robotic arm control and requires minimal training and knowledge of robotic arm manipulation, which lowers the cost for operator training. This human-robot interface can be extended to many applications, such as handling nuclear accident/waste cleanup, underwater repairs, deep space missions, and manufacturing and fabrication within factories. Further, the robotic arm can be mounted onto existing mobile robots to provide access to hazardous environments, including power plants, burning buildings, and high-altitude repair sites.

Keywords: construction automation, human-robot interaction, hand-tracking, mixed reality

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Authors: Emily Simone Doffing, Danielle Kohfeldt

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Disabled students are underrepresented in graduate-level degree enrollment and completion. There is limited research on disabled students' progression during the pandemic. Disabled graduate students (DGS) face unique interpersonal and institutional barriers, yet, limited research explores these barriers, buffering facilitators, and aids to academic persistence. This study adopts an asset-based, embodied disability approach using the critical pedagogy theoretical framework instead of the deficit research approach. The Participatory Action Research (PAR) paradigm, the critical pedagogy theoretical framework, and emancipatory disability research share the same purpose -creating a socially just world through reciprocal learning. This study is one of few, if not the first, to center solely on DGS’ lived understanding using a Participatory Action Research (PAR) epistemology. With a PAR paradigm, participants and investigators work as a research team democratically at every stage of the research process. PAR has individual and systemic outcomes. PAR lessens the researcher-participant power gap and elevates a marginalized community’s knowledge as expertise for local change. PAR and critical pedagogy work toward enriching everyone involved with empowerment, civic engagement, knowledge proliferation, socio-cultural reflection, skills development, and active meaning-making. The PAR process unveils the tensions between disability and graduate school in policy and practice during the pandemic. Likewise, institutional and ideological tensions influence the PAR process. This project is recruiting 10 DGS until September through purposive and snowball sampling. DGS will collectively practice praxis during four monthly focus groups in the fall 2023 semester. Participant researchers can attend a focus group or an interview, both with field notes. September will be our orientation and first monthly meeting. It will include access needs check-ins, ice breakers, consent form review, a group agreement, PAR introduction, research ethics discussion, research goals, and potential research topics. October and November will be available for meetings for dialogues about lived experiences during our collaborative data collection. Our sessions can be semi-structured with “framing questions,” which would be revised together. Field notes include observations that cannot be captured through audio. December will focus on local social action planning and dissemination. Finally, in January, there will be a post-study focus group for students' reflections on their experiences of PAR. Iterative analysis methods include transcribed audio, reflexivity, memos, thematic coding, analytic triangulation, and member checking. This research follows qualitative rigor and quality criteria: credibility, transferability, confirmability, and psychopolitical validity. Results include potential tension points, social action, individual outcomes, and recommendations for conducting PAR. Tension points have three components: dubious practices, contestable knowledge, and conflict. The dissemination of PAR recommendations will aid and encourage researchers to conduct future PAR projects with the disabled community. Identified stakeholders will be informed of DGS’ insider knowledge to drive social sustainability.

Keywords: participatory action research, graduate school, disability, higher education

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Authors: O. Lopez, F. Pedro, A. Tadeu, J. Antonio, A. Coelho

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The future of the railway industry lies in the innovation of lighter, more efficient and more sustainable trains. Weight optimizations in railway vehicles allow reducing power consumption and CO₂ emissions, increasing the efficiency of the engines and the maximum speed reached. Additionally, they reduce wear of wheels and rails, increase the space available for passengers, etc. Among the various systems that integrate railway interiors, the flooring system is one which has greater impact both on passenger safety and comfort, as well as on the weight of the interior systems. Due to the high weight saving potential, relative high mechanical resistance, good acoustic and thermal performance, ease of modular design, cost-effectiveness and long life, the use of new sustainable composite materials and panels provide the latest innovations for competitive solutions in the development of flooring systems. However, one of the main drawbacks of the flooring systems is their relatively poor resistance to point loads. Point loads in railway interiors can be caused by passengers or by components fixed to the flooring system, such as seats and restraint systems, handrails, etc. In this way, they can originate higher fatigue solicitations under service loads or zones with high stress concentrations under exceptional loads (higher longitudinal, transverse and vertical accelerations), thus reducing its useful life. Therefore, to verify all the mechanical and functional requirements of the flooring systems, many physical prototypes would be created during the design phase, with all of the high costs associated with it. Nowadays, the use of virtual prototyping methods by computer-aided design (CAD) and computer-aided engineering (CAE) softwares allow validating a product before committing to making physical test prototypes. The scope of this work was to current computer tools and integrate the processes of innovation, development, and manufacturing to reduce the time from design to finished product and optimise the development of the product for higher levels of performance and reliability. In this case, the mechanical response of several sandwich panels with different cores, polystyrene foams, and composite corks, were assessed, to optimise the weight and the mechanical performance of a flooring solution for railways. Sandwich panels with aluminum face sheets were tested to characterise its mechanical performance and determine the polystyrene foam and cork properties when used as inner cores. Then, a railway flooring solution was fully modelled (including the elastomer pads to provide the required vibration isolation from the car body) and perform structural simulations using FEM analysis to comply all the technical product specifications for the supply of a flooring system. Zones with high stress concentrations are studied and tested. The influence of vibration modes on the comfort level and stability is discussed. The information obtained with the computer tools was then completed with several mechanical tests performed on some solutions, and on specific components. The results of the numerical simulations and experimental campaign carried out are presented in this paper. This research work was performed as part of the POCI-01-0247-FEDER-003474 (coMMUTe) Project funded by Portugal 2020 through COMPETE 2020.

Keywords: cork agglomerate core, mechanical performance, numerical simulation, railway flooring system

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Authors: Merav Alush Levron, Sivan Rajuan Shtang

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From as early as their emergence in Europe and the US, postmodern and post-colonial paradigm have formed the backbone of the visual culture field of study. The self-representation project of political minorities is studied, described and explained within the premises and perspectives drawn from these paradigms, addressing the key issues they had raised: modernism’s crisis of representation. The struggle for self-representation, agency and multicultural visibility sought to challenge the liberal pretense of universality and equality, hitting at its different blind spots, on issues such as class, gender, race, sex, and nationality. This struggle yielded subversive identity and hybrid performances, including reclaiming, mimicry and masquerading. These performances sought to defy the uniform, universal self, which forms the basis for the liberal, rational, enlightened subject. The argument of this research runs that this politics of representation itself is confined within liberal thought. Alongside post-colonialism and multiculturalism’s contribution in undermining oppressive structures of power, generating diversity in cultural visibility, and exposing the failure of liberal colorblindness, this subversion is constituted in the visual field by way of confrontation, flying in the face of the universal law and relying on its ongoing comparison and attribution to this law. Relying on Deleuze and Guattari, this research set out to draw theoretic and empiric attention to an alternative, post-liberal occurrence which has been taking place in the visual field in parallel to the contra-hegemonic phase and as a product of political reality in the aftermath of the crisis of representation. It is no longer a counter-representation; rather, it is a motion of organic minor desire, progressing in the form of flows and generating what Deleuze and Guattari termed deterritorialization of social structures. This discussion shall have its focus on current post-liberal performances of ‘Mizrahim’ (Jewish Israelis of Arab and Muslim extraction) in the visual field in Israel. In television, video art and photography, these performances challenge the issue of representation and generate concrete peripheral Mizrahiness, realized in the visual organization of the photographic frame. Mizrahiness then transforms from ‘confrontational’ representation into a 'presence', flooding the visual sphere in our plain sight, in a process of 'becoming'. The Mizrahi desire is exerted on the plains of sound, spoken language, the body and the space where they appear. It removes from these plains the coding and stratification engendered by European dominance and rational, liberal enlightenment. This stratification, adhering to the hegemonic surface, is flooded not by way of resisting false consciousness or employing hybridity, but by way of the Mizrahi identity’s own productive, material immanent yearning. The Mizrahi desire reverberates with Mizrahi peripheral 'worlds of meaning', where post-colonial interpretation almost invariably identifies a product of internalized oppression, and a recurrence thereof, rather than a source in itself - an ‘offshoot, never a wellspring’, as Nissim Mizrachi clarifies in his recent pioneering work. The peripheral Mizrahi performance ‘unhook itself’, in Deleuze and Guattari words, from the point of subjectification and interpretation and does not correspond with the partialness, absence, and split that mark post-colonial identities.

Keywords: desire, minority, Mizrahi Jews, post-colonialism, post-liberalism, visibility, Deleuze and Guattari

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Authors: Moshreka Aditi Huq

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This study shows how a progressive portion of civil intellectuals in Bangladesh contributed as the solidarity activist entities in a movement of tea workers that became the symbol of their unique moral struggle. Their passive yet sharp way of resistance, with the integration of mass tea workers of a tea estate, got demonstrated against certain private companies and government officials who approached to establish a special economic zone inside the tea garden without offering any compensation and rehabilitation for poor tea workers. Due to massive protests and rebellion, the authorized entrepreneurs had to step back and called off the project immediately. The extraordinary features of this movement generated itself from the deep core social need of indigenous tea workers who are still imprisoned in the colonial cage. Following an anthropological and ethnographic perspective, this study adopted the main three techniques of intensive interview, focus group discussion, and laborious observation, to extract empirical data. The intensive interviews were undertaken informally using a mostly conversational approach. Focus group discussions were piloted among various representative groups where observations prevailed as part of the regular documentation process. These were conducted among civil intellectual entities, tea workers, tea estate authorities, civil service authorities, and business officials to obtain a holistic view of the situation. The fieldwork was executed in capital Dhaka city, along with northern areas like Chandpur-Begumkhan Tea Estate of Chunarughat Upazilla and Habiganj city of Habiganj District of Bangladesh. Correspondingly, secondary data were accessed through books, scholarly papers, archives, newspapers, reports, leaflets, posters, writing blog, and electronic pages of social media. The study results find that: (1) civil intellectuals opposed state-sponsored business impositions by producing counter-discourse and struggled against state hegemony through the phases of the movement; (2) instead of having the active physical resistance, civil intellectuals’ strength was preferably in passive form which was portrayed through their intellectual labor; (3) the combined movement of tea workers and civil intellectuals reflected on social security of ethnic worker communities that contrasts state’s pseudo-development motives which ultimately supports offensive and oppressive neoliberal growths of economy; (4) civil intellectuals are revealed as having certain functional limitations in the process of movement organization as well as resource mobilization; (5) in specific contexts, the genuine need of protest by indigenous subaltern can overshadow intellectual elitism and helps to raise the voices of ‘subjugated knowledge’. This study is quite likely to represent two sets of apparent protagonist entities in the discussion of social injustice and oppressive development intervention. On the one, hand it may help us to find the basic functional characteristics of civil intellectuals in Bangladesh when they are in a passive mode of resistance in social movement issues. On the other hand, it represents the community ownership and inherent protest tendencies of indigenous workers when they feel threatened and insecure. The study seems to have the potential to understand the conditions of ‘subjugated knowledge’ of subalterns. Furthermore, being the memory and narratives, these ‘activism mechanisms’ of social entities broadens the path to understand ‘power’ and ‘resistance’ in more fascinating ways.

Keywords: civil intellectuals, resistance, subjugated knowledge, indigenous

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Authors: Camille Aouinaït, Danilo Christen, Christoph Carlen

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Introduction: Small and Medium-sized Enterprises (SMEs) are facing different challenges such as pressures on environmental resources, the rise of downstream power, and trade liberalization. Remaining competitive by implementing innovations and engaging in collaborations could be a strategic solution. In Switzerland, the Federal Institute for Research in Agriculture (Agroscope), the Federal schools of technology (EPFL and ETHZ), Cantonal universities and Universities of Applied Sciences (UAS) can provide substantial inputs. UAS were developed with specific missions to match the labor markets and society needs. Research projects produce patents, publications and improved networks of scientific expertise. The study’s goal is to measure the contribution of UAS and research organization to innovation and the impact of collaborations with partners in the non-academic environment in Swiss traditional fruit production. Materials and methods: The European projects Traditional Food Network to improve the transfer of knowledge for innovation (TRAFOON) and Social Impact Assessment of Productive Interactions between science and society (SIAMPI) frame the present study. The former aims to fill the gap between the needs of traditional food producing SMEs and innovations implemented following European projects. The latter developed a method to assess the impacts of scientific research. On one side, interviews with market players have been performed to make an inventory of needs of Swiss SMEs producing apricots and berries. The participative method allowed matching the current needs and the existing innovations coming from past European projects. Swiss stakeholders (e.g. producers, retailers, an inter-branch organization of fruits and vegetables) directly rated the needs on a five-Likert scale. To transfer the knowledge to SMEs, training workshops have been organized for apricot and berries actors separately, on specific topics. On the other hand, a mapping of a social network is drawn to characterize the links between actors, with a focus on the Swiss canton of Valais and UAS Valais Wallis. Type and frequency of interactions among actors have identified thanks to interviews. Preliminary results: A list of 369 SMEs needs grouped in 22 categories was produced with 37 fulfilled questionnaires. Swiss stakeholders rated 31 needs very important. Training workshops on apricot are focusing on varietal innovations, storage, disease (bacterial blight), pest (Drosophila suzukii), sorting and rootstocks. Entrepreneurship was targeted through trademark discussions in berry production. The UAS Valais Wallis collaborated on a few projects with Agroscope along with industries, at European and national levels. Political and public bodies interfere with the central area of agricultural vulgarization that induces close relationships between the research and the practical side. Conclusions: The needs identified by Swiss stakeholders are becoming part of training workshops to incentivize innovations. The UAS Valais Wallis takes part in collaboration projects with the research environment and market players that bring innovations helping SMEs in their contextual environment. Then, a Strategic Research and Innovation Agenda will be created in order to pursue research and answer the issues facing by SMEs.

Keywords: agriculture, innovation, knowledge transfer, university and research collaboration

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Authors: Dhekra Khazri, Hakim Gabtni

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Because of Sidi Bouzid water table overexploitation, this study aims at integrating geophysical methods to determinate aquifers geometry assessing their geological situation and geophysical characteristics. However in highly tectonic zones controlled by Atlassic structural features with NE-SW major directions (central Tunisia), Bouguer gravimetric responses of some areas can be as much dominated by the regional structural tendency, as being non-identified or either defectively interpreted such as the case of Sidi Bouzid basin. This issue required a residual gravity anomaly elaboration isolating the Sidi Bouzid basin gravity response ranging between -8 and -14 mGal and crucial for its aquifers geometry characterization. Several gravity techniques helped constructing the Sidi Bouzid basin's residual gravity anomaly, such as Upwards continuation compared to polynomial regression trends and power spectrum analysis detecting deep basement sources at (3km), intermediate (2km) and shallow sources (1km). A 3D Euler Deconvolution was also performed detecting deepest accidents trending NE-SW, N-S and E-W with depth values reaching 5500 m and delineating the main outcropping structures of the study area. Further gravity treatments highlighted the subsurface geometry and structural features of Sidi Bouzid basin over Horizontal and vertical gradient, and also filters based on them such as Tilt angle and Source Edge detector locating rooted edges or peaks from potential field data detecting a new E-W lineament compartmentalizing the Sidi Bouzid gutter into two unequally residual anomaly and subsiding domains. This subsurface morphology is also detected by the used 2D seismic reflection sections defining the Sidi Bouzid basin as a deep gutter within a tectonic set of negative flower structures, and collapsed and tilted blocks. Furthermore, these structural features were confirmed by forward gravity modeling process over several modeled residual gravity profiles crossing the main area. Sidi Bouzid basin (central Tunisia) is also of a big interest cause of the unknown total thickness and the undefined substratum of its siliciclastic Tertiary package, and its aquifers unbounded structural subsurface features and deep accidents. The Combination of geological, hydrogeological and geophysical methods is then of an ultimate need. Therefore, a geophysical methods integration based on gravity survey supporting available seismic data through forward gravity modeling, enhanced lateral and vertical extent definition of the basin's complex sedimentary fill via 3D gravity models, improved depth estimation by a depth to basement modeling approach, and provided 3D isochronous seismic mapping visualization of the basin's Tertiary complex refining its geostructural schema. A subsurface basin geomorphology mapping, over an ultimate matching between the basin's residual gravity map and the calculated theoretical signature map, was also displayed over the modeled residual gravity profiles. An ultimate multidisciplinary geophysical study of the Sidi Bouzid basin aquifers can be accomplished via an aeromagnetic survey and a 4D Microgravity reservoir monitoring offering temporal tracking of the target aquifer's subsurface fluid dynamics enhancing and rationalizing future groundwater exploitation in this arid area of central Tunisia.

Keywords: aquifer geometry, geophysics, 3D gravity modeling, improved depths, source edge detector

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Authors: Andreas Rudisch, Ralf Lampert, Andreas Kolbitsch

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It is a well-known fact among the engineering community that earthquakes with comparatively low magnitudes can cause serious damage to nonstructural components (NSCs) of buildings, even when the supporting structure performs relatively well. Past research works focused mainly on NSCs of nuclear power plants and industrial plants. Particular attention should also be given to architectural façade elements of old masonry buildings (e.g. ornamental figures, balustrades, vases), which are very vulnerable under seismic excitation. Large numbers of these historical nonstructural components (HiNSCs) can be found in highly frequented historical city centers and in the event of failure, they pose a significant danger to persons. In order to estimate the vulnerability of acceleration sensitive HiNSCs, the peak horizontal floor acceleration (PHFA) is used. The PHFA depends on the dynamic characteristics of the building, the ground excitation, and induced nonlinearities. Consequently, the PHFA can not be generalized as a simple function of height. In the present research work, an extensive case study was conducted to investigate the influence of induced nonlinearity on the PHFA for old masonry buildings. Probabilistic nonlinear FE time-history analyses considering three different hazard levels were performed. A set of eighteen synthetically generated ground motions was used as input to the structure models. An elastoplastic macro-model (multiPlas) for nonlinear homogenized continuum FE-calculation was calibrated to multiple scales and applied, taking specific failure mechanisms of masonry into account. The macro-model was calibrated according to the results of specific laboratory and cyclic in situ shear tests. The nonlinear macro-model is based on the concept of multi-surface rate-independent plasticity. Material damage or crack formation are detected by reducing the initial strength after failure due to shear or tensile stress. As a result, shear forces can only be transmitted to a limited extent by friction when the cracking begins. The tensile strength is reduced to zero. The first goal of the calibration was the consistency of the load-displacement curves between experiment and simulation. The calibrated macro-model matches well with regard to the initial stiffness and the maximum horizontal load. Another goal was the correct reproduction of the observed crack image and the plastic strain activities. Again the macro-model proved to work well in this case and shows very good correlation. The results of the case study show that there is significant scatter in the absolute distribution of the PHFA between the applied ground excitations. An absolute distribution along the normalized building height was determined in the framework of probability theory. It can be observed that the extent of nonlinear behavior varies for the three hazard levels. Due to the detailed scope of the present research work, a robust comparison with code-recommendations and simplified PHFA distributions are possible. The chosen methodology offers a chance to determine the distribution of PHFA along the building height of old masonry structures. This permits a proper hazard assessment of HiNSCs under seismic loads.

Keywords: nonlinear macro-model, nonstructural components, time-history analysis, unreinforced masonry

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Authors: Adaku Thelma Olatise

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Mental health disparities among women from diverse ethnic, cultural, and religious backgrounds remain a pressing concern, particularly as current psychotherapeutic models often fail to address the unique challenges these groups face. This is of particular concern since epidemiological studies across various countries and cultures consistently demonstrate higher prevalence rates of common mental disorders amongst these groups of women because of a lack of access to culturally oriented psychotherapeutic services. This literature review aims to examine how CCAs in psychotherapy can address the specific ethnic, cultural, and religious challenges women encounter in accessing mental health care. A search of relevant articles was conducted through PsycARTICLES and PubMed databases, using terms such as ‘mental health’, ‘women’, ‘culture’, and ‘ethnic minorities’. Supplementary searches on Google Scholar were also performed to capture literature not covered by traditional databases. While the importance of cross-cultural approaches in psychotherapy has become more apparent because people from diverse ethnic backgrounds inevitably perceive the world through different lenses, influencing their interpretations of human behavior and norms, there is a notable gap in the literature in understanding the influences of using of CCAs in psychotherapy amongst women of an ethnic minority. This gap not only reflects a poor understanding of the complex stressors faced by these women—such as familial, communal, and societal expectations—but also highlights the lack of support and culturally adapted interventions available to them. Even though scholars have posited that aligning treatment approaches with patients' cultural backgrounds is important to enhance therapeutic effectiveness, and the acknowledgment of culture is crucial in psychotherapy theory and practice. As well as the increasing global focus on psychotherapy applications that integrate non-Western practices, such as spiritual healing and community-based interventions, the adaptation of these approaches in mainstream mental health care has remained limited. This review found that the expectations and experiences of ethnic minority women were heavily influenced by family and community pressures. However, there were limited evidence-based, culturally oriented psychotherapeutic interventions tailored to ethnic minority women. This gap extends to inadequate representation of minority groups in clinical research, as well as a lack of culturally validated mental health outcome measures. Furthermore, studies have shown that psychotherapeutic models have largely been Western-oriented and Euro-centric because of socially constructed hierarchies. The origin of psychology from the Western world has predominantly reflected Western cultural traditions, shaped by historical, linguistic, and sociopolitical influences. These factors have led to a lack of recognition of therapeutic approaches from minority ethnic groups and the biases that emanate from hegemonic cultural beliefs and power dynamics influence the decisions about which psychotherapeutic modalities to integrate and practice. Therefore, this plethora of factors adds to the challenges women from ethnically and culturally diverse backgrounds face in accessing mental health services at the individual, familial, community, and societal levels. In conclusion, a cross-cultural approach is urgently needed within psychotherapy to address these challenges, ensuring that treatment frameworks are both culturally sensitive and gender responsive. Only by considering the lived experiences of minority women, particularly in relation to their cultural and religious contexts, can mental health services provide the appropriate care necessary to support their well-being.

Keywords: mental health, women, culture, ethnicity

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Authors: Eduardo Rodrigues, Gisela Mendes, José M. Torres, José E. Sousa

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In the sequence of the liberalisation of the electricity sector a progressive engagement of consumers has been considered and targeted by sector regulatory policies. With the objective of promoting market competition while protecting consumers interests, by transferring some of the upstream benefits to the end users while reaching a fair distribution of system costs, different market models to value consumers’ demand flexibility at the energy community level are envisioned. Local Energy and Flexibility Markets (LEFM) involve stakeholders interested in providing or procure local flexibility for community, services and markets’ value. Under the scope of DOMINOES, a European research project supported by Horizon 2020, the local market concept developed is expected to: • Enable consumers/prosumers empowerment, by allowing them to value their demand flexibility and Distributed Energy Resources (DER); • Value local liquid flexibility to support innovative distribution grid management, e.g., local balancing and congestion management, voltage control and grid restoration; • Ease the wholesale market uptake of DER, namely small-scale flexible loads aggregation as Virtual Power Plants (VPPs), facilitating Demand Response (DR) service provision; • Optimise the management and local sharing of Renewable Energy Sources (RES) in Medium Voltage (MV) and Low Voltage (LV) grids, trough energy transactions within an energy community; • Enhance the development of energy markets through innovative business models, compatible with ongoing policy developments, that promote the easy access of retailers and other service providers to the local markets, allowing them to take advantage of communities’ flexibility to optimise their portfolio and subsequently their participation in external markets. The general concept proposed foresees a flow of market actions, technical validations, subsequent deliveries of energy and/or flexibility and balance settlements. Since the market operation should be dynamic and capable of addressing different requests, either prioritising balancing and prosumer services or system’s operation, direct procurement of flexibility within the local market must also be considered. This paper aims to highlight the research on the definition of suitable DR models to be used by the Distribution System Operator (DSO), in case of technical needs, and by the retailer, mainly for portfolio optimisation and solve unbalances. The models to be proposed and implemented within relevant smart distribution grid and microgrid validation environments, are focused on day-ahead and intraday operation scenarios, for predictive management and near-real-time control respectively under the DSO’s perspective. At local level, the DSO will be able to procure flexibility in advance to tackle different grid constrains (e.g., demand peaks, forecasted voltage and current problems and maintenance works), or during the operating day-to-day, to answer unpredictable constraints (e.g., outages, frequency deviations and voltage problems). Due to the inherent risks of their active market participation retailers may resort to DR models to manage their portfolio, by optimising their market actions and solve unbalances. The interaction among the market actors involved in the DR activation and in flexibility exchange is explained by a set of sequence diagrams for the DR modes of use from the DSO and the energy provider perspectives. • DR for DSO’s predictive management – before the operating day; • DR for DSO’s real-time control – during the operating day; • DR for retailer’s day-ahead operation; • DR for retailer’s intraday operation.

Keywords: demand response, energy communities, flexible demand, local energy and flexibility markets

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Authors: Monique M. Keller, Roline Barnes, Corlia Brandt

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Introduction Scientific evidence on the hand forces and the types of grasps measurement during daily tasks are lacking, leaving a gap in the field of hand rehabilitation and robotics. Measuring the grasp forces and types produced by the individual fingers during daily functional tasks is valuable to inform and grade rehabilitation practices for second to fifth metacarpal fractures with robust scientific evidence. Feix et al, 2016 identified the most extensive and complete grasp study that resulted in the GRASP taxonomy. Covid-19 virus changed data collection across the globe and safety precautions in research are essential to ensure the health of participants and researchers. Methodology A cross-sectional study investigated six healthy adults aged 20 to 59 years, pilot participants’ hand forces during 105 tasks. The tasks were categorized into five sections namely, personal care, transport and moving around, home environment and inside, gardening and outside, and office. The predominant grasp of each task was identified guided by the GRASP Taxonomy. Grasp forces were measured with 13mm force-sensing resistors glued onto a glove attached to each of the dominant and non-dominant hand’s individual fingers. Testing equipment included Flexiforce 13millimetres FSR .5" circle, calibrated prior to testing, 10k 1/4w resistors, Arduino pro mini 5.0v – compatible, Esp-01-kit, Arduino uno r3 – compatible board, USB ab cable - 1m, Ftdi ft232 mini USB to serial, Sil 40 inline connectors, ribbon cable combo male header pins, female to female, male to female, two gloves, glue to attach the FSR to glove, Arduino software programme downloaded on a laptop. Grip strength measurements with Jamar dynamometer prior to testing and after every 25 daily tasks were taken to will avoid fatigue and ensure reliability in testing. Covid-19 precautions included wearing face masks at all times, screening questionnaires, temperatures taken, wearing surgical gloves before putting on the testing gloves 1.5 metres long wires attaching the FSR to the Arduino to maintain social distance. Findings Predominant grasps observed during 105 tasks included, adducted thumb (17), lateral tripod (10), prismatic three fingers (12), small diameter (9), prismatic two fingers (9), medium wrap (7), fixed hook (5), sphere four fingers (4), palmar (4), parallel extension (4), index finger extension (3), distal (3), power sphere (2), tripod (2), quadpod (2), prismatic four fingers (2), lateral (2), large-diameter (2), ventral (2), precision sphere (1), palmar pinch (1), light tool (1), inferior pincher (1), and writing tripod (1). Range of forces applied per category, personal care (1-25N), transport and moving around (1-9 N), home environment and inside (1-41N), gardening and outside (1-26.5N), and office (1-20N). Conclusion Scientifically measurements of finger forces with careful consideration to types of grasps used in daily tasks should guide rehabilitation practices and robotic design to ensure a return to the full participation of the individual into the community.

Keywords: activities of daily living (ADL), Covid-19, force-sensing resistors, grasps, hand forces

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Authors: Manuel I. Capel, Antonio Tomeu, Alberto Salguero

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Tumor growth from a transformed cancer-cell up to a clinically apparent mass spans through a range of spatial and temporal magnitudes. Through computer simulations, Cellular Automata (CA) can accurately describe the complexity of the development of tumors. Tumor development prognosis can now be made -without making patients undergo through annoying medical examinations or painful invasive procedures- if we develop appropriate CA-based software tools. In silico testing mainly refers to Computational Biology research studies of application to clinical actions in Medicine. To establish sound computer-based models of cellular behavior, certainly reduces costs and saves precious time with respect to carrying out experiments in vitro at labs or in vivo with living cells and organisms. These aim to produce scientifically relevant results compared to traditional in vitro testing, which is slow, expensive, and does not generally have acceptable reproducibility under the same conditions. For speeding up computer simulations of cellular models, specific literature shows recent proposals based on the CA approach that include advanced techniques, such the clever use of supporting efficient data structures when modeling with deterministic stochastic cellular automata. Multiparadigm and multiscale simulation of tumor dynamics is just beginning to be developed by the concerned research community. The use of stochastic cellular automata (SCA), whose parallel programming implementations are open to yield a high computational performance, are of much interest to be explored up to their computational limits. There have been some approaches based on optimizations to advance in multiparadigm models of tumor growth, which mainly pursuit to improve performance of these models through efficient memory accesses guarantee, or considering the dynamic evolution of the memory space (grids, trees,…) that holds crucial data in simulations. In our opinion, the different optimizations mentioned above are not decisive enough to achieve the high performance computing power that cell-behavior simulation programs actually need. The possibility of using multicore and GPU parallelism as a promising multiplatform and framework to develop new programming techniques to speed-up the computation time of simulations is just starting to be explored in the few last years. This paper presents a model that incorporates parallel processing, identifying the synchronization necessary for speeding up tumor growth simulations implemented in Java and C++ programming environments. The speed up improvement that specific parallel syntactic constructs, such as executors (thread pools) in Java, are studied. The new tumor growth parallel model is proved using implementations with Java and C++ languages on two different platforms: chipset Intel core i-X and a HPC cluster of processors at our university. The parallelization of Polesczuk and Enderling model (normally used by researchers in mathematical oncology) proposed here is analyzed with respect to performance gain. We intend to apply the model and overall parallelization technique presented here to solid tumors of specific affiliation such as prostate, breast, or colon. Our final objective is to set up a multiparadigm model capable of modelling angiogenesis, or the growth inhibition induced by chemotaxis, as well as the effect of therapies based on the presence of cytotoxic/cytostatic drugs.

Keywords: cellular automaton, tumor growth model, simulation, multicore and manycore programming, parallel programming, high performance computing, speed up

Procedia PDF Downloads 244

Authors: Glauco M. M. M. Lustosa, João Paulo C. Costa, Sonia M. Zanetti, Mario Cilense, Leinig Antônio Perazolli, Maria Aparecida Zaghete

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The contamination of the environment has been one of the biggest problems of our time, mostly due to developments of many industries. SnO2 is an n-type semiconductor with band gap about 3.5 eV and has its electrical conductivity dependent of type and amount of modifiers agents added into matrix ceramic during synthesis process, allowing applications as sensing of gaseous pollutants on ambient. The chemical synthesis by polymeric precursor method consists in a complexation reaction between tin ion and citric acid at 90 °C/2 hours and subsequently addition of ethyleneglycol for polymerization at 130 °C/2 hours. It also prepared polymeric resin of zinc, cobalt and niobium ions. Stoichiometric amounts of the solutions were mixed to obtain the systems (Zn, Nb)-SnO2 and (Co, Nb) SnO2 . The metal immobilization reduces its segregation during the calcination resulting in a crystalline oxide with high chemical homogeneity. The resin was pre-calcined at 300 °C/1 hour, milled in Atritor Mill at 500 rpm/1 hour, and then calcined at 600 °C/2 hours. X-Ray Diffraction (XDR) indicated formation of SnO2 -rutile phase (JCPDS card nº 41-1445). The characterization by Scanning Electron Microscope of High Resolution showed spherical ceramic powder nanostructured with 10-20 nm of diameter. 20 mg of SnO2 -based powder was kept in 20 ml of isopropyl alcohol and then taken to an electrophoretic deposition (EPD) system. The EPD method allows control the thickness films through the voltage or current applied in the electrophoretic cell and by the time used for deposition of ceramics particles. This procedure obtains films in a short time with low costs, bringing prospects for a new generation of smaller size devices with easy integration technology. In this research, films were obtained in an alumina substrate with interdigital electrodes after applying 2 kV during 5 and 10 minutes in cells containing alcoholic suspension of (Zn, Nb)-SnO2 and (Co, Nb) SnO2 of powders, forming a sensing layer. The substrate has designed integrated micro hotplates that provide an instantaneous and precise temperature control capability when a voltage is applied. The films were sintered at 900 and 1000 °C in a microwave oven of 770 W, adapted by the research group itself with a temperature controller. This sintering is a fast process with homogeneous heating rate which promotes controlled growth of grain size and also the diffusion of modifiers agents, inducing the creation of intrinsic defects which will change the electrical characteristics of SnO2 -based powders. This study has successfully demonstrated a microfabricated system with an integrated micro-hotplate for detection of CO and NO2 gas at different concentrations and temperature, with self-heating SnO2 - based nanoparticles films, being suitable for both industrial process monitoring and detection of low concentrations in buildings/residences in order to safeguard human health. The results indicate the possibility for development of gas sensors devices with low power consumption for integration in portable electronic equipment with fast analysis. Acknowledgments The authors thanks to the LMA-IQ for providing the FEG-SEM images, and the financial support of this project by the Brazilian research funding agencies CNPq, FAPESP 2014/11314-9 and CEPID/CDMF- FAPESP 2013/07296-2.

Keywords: chemical synthesis, electrophoretic deposition, self-heating, gas sensor

Procedia PDF Downloads 275

Authors: Men An Pan, Ho Hsiung Huang, Jui Chuan Lin, Tsui Hsun Wu, Hsing Yuan Yen

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Pingtung County, located in the southernmost region of Taiwan, has the largest number of pig farms in the country. In the past, livestock operators in Dongpian Village discharged their wastewater into the nearby water bodies, causing water pollution in the local rivers and polluting the air with the stench of the pig excrement. These resulted in many complaints from the local residents. In response to a long time fighting back of the community against the livestock farms due to the confrict, the County Government's Environmental Protection Bureau (PTEPB) examined potential wayouts in addition to heavy fines to the perpetrators. Through helping the livestock farms to upgrade their pollution prevention equipment, promoting the reuse of biogas residue and slurry from the pig excrement, and environmental education, the confrict was successfully resolved. The properly treated wastewater from the livestock farms has been freely provided to the neighboring farmlands via pipelines and tankers. Thus, extensive cultivation of bananas, papaya, red dragon fruit, Inca nut, and cocoa has resulted in 34% resource utilization of biogas residue as a fertilizer. This has encouraged farmers to reduce chemical fertilizers and use microbial materials like photosynthetic bacteria after banning herbicides while lowering the cost of wastewater treatment in livestock farms and alleviating environmental pollution simultaneously. That is, the livestock farms fully demonstrate the determination to fulfill their corporate social responsibility (CSR). Due to the success, Eight farms jointly established a social enterprise - "Dongpian Gemstone Village Co., Ltd." to promote organic farming through a "shared farm." The company appropriates 5% of its total revenue back to the community through caregiving services for the elderly and a fund for young local farmers. The community adopted the Satoyama Initiative in accordance with the Conference of the CBD COP10. Through the positive impact of environmental education, the community seeks to realize the coexistence between society and nature while maintaining and developing socio-economic activities (including agriculture) with respect for nature and building a harmonic relationship between humans and nature. By way of sustainable management of resources and ensuring biodiversity, the community is transforming into a socio-ecological production landscape. Apart from nature conservation and watercourse ecology, preserving local culture is also a key focus of the environmental education. To mitigate the impact of global warming and climate change, the community and the government have worked together to develop a disaster prevention and relief system, strive to establish a low-carbon emitting homeland, and become a model for resilient communities. By the power of environmental education, this community has turned its residents’ hearts and minds into concrete action, fulfilled social responsibility, and moved towards realizing the UN SDGs. Even though it is not the only community to integrate government agencies, research institutions, and NGOs for environmental education, it is a prime example of a low-carbon sustainable community that achieves more than 9 SDGs, including responsible consumption and production, climate change action, and diverse partnerships. The community is also leveraging environmental education to become a net-zero carbon community targeted by COP26.

Keywords: environmental education, biogas residue, biogas slurry, CSR, SDGs, climate change, net-zero carbon emissions

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Authors: Diogo José Morgado Rebelo, Francisco António Carneiro Pacheco de Andrade, Paulo Jorge Freitas de Oliveira Novais

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Not everything in AI-power consumer credit scoring turns out to be a wonder. When using AI in Creditworthiness Assessment (CWA), opacity and unfairness ‘sins’ must be considered to the task be deemed Responsible. AI software is not always 100% accurate, which can lead to misclassification. Discrimination of some groups can be exponentiated. A hetero personalized identity can be imposed on the individual(s) affected. Also, autonomous CWA sometimes lacks transparency when using black box models. However, for this intended purpose, human analysts ‘on-the-loop’ might not be the best remedy consumers are looking for in credit. This study seeks to explore the legality of implementing a Multi-Agent System (MAS) framework in consumer CWA to ensure compliance with the regulation outlined in Article 14(4) of the Proposal for an Artificial Intelligence Act (AIA), dated 21 April 2021 (as per the last corrigendum by the European Parliament on 19 April 2024), Especially with the adoption of Art. 18(8)(9) of the EU Directive 2023/2225, of 18 October, which will go into effect on 20 November 2026, there should be more emphasis on the need for hybrid oversight in AI-driven scoring to ensure fairness and transparency. In fact, the range of EU regulations on AI-based consumer credit will soon impact the AI lending industry locally and globally, as shown by the broad territorial scope of AIA’s Art. 2. Consequently, engineering the law of consumer’s CWA is imperative. Generally, the proposed MAS framework consists of several layers arranged in a specific sequence, as follows: firstly, the Data Layer gathers legitimate predictor sets from traditional sources; then, the Decision Support System Layer, whose Neural Network model is trained using k-fold Cross Validation, provides recommendations based on the feeder data; the eXplainability (XAI) multi-structure comprises Three-Step-Agents; and, lastly, the Oversight Layer has a 'Bottom Stop' for analysts to intervene in a timely manner. From the analysis, one can assure a vital component of this software is the XAY layer. It appears as a transparent curtain covering the AI’s decision-making process, enabling comprehension, reflection, and further feasible oversight. Local Interpretable Model-agnostic Explanations (LIME) might act as a pillar by offering counterfactual insights. SHapley Additive exPlanation (SHAP), another agent in the XAI layer, could address potential discrimination issues, identifying the contribution of each feature to the prediction. Alternatively, for thin or no file consumers, the Suggestion Agent can promote financial inclusion. It uses lawful alternative sources such as the share of wallet, among others, to search for more advantageous solutions to incomplete evaluation appraisals based on genetic programming. Overall, this research aspires to bring the concept of Machine-Centered Anthropocentrism to the table of EU policymaking. It acknowledges that, when put into service, credit analysts no longer exert full control over the data-driven entities programmers have given ‘birth’ to. With similar explanatory agents under supervision, AI itself can become self-accountable, prioritizing human concerns and values. AI decisions should not be vilified inherently. The issue lies in how they are integrated into decision-making and whether they align with non-discrimination principles and transparency rules.

Keywords: creditworthiness assessment, hybrid oversight, machine-centered anthropocentrism, EU policymaking

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Authors: Alexandra Papagianni, George Filis, Panagiotis Papadopoulos

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The liberalization of the energy market and the increasing penetration of fluctuating renewables (e.g., wind and solar power) have heightened the importance of the spot market for ensuring efficient electricity supply. This is further emphasized by the EU’s goal of achieving net-zero emissions by 2050. The day-ahead market (DAM) plays a key role in European energy trading, accounting for 80-90% of spot transactions and providing critical insights for next-day pricing. Therefore, short-term electricity price forecasting (EPF) within the DAM is crucial for market participants to make informed decisions and improve their market positioning. Existing literature highlights out-of-sample performance as a key factor in assessing EPF accuracy, with influencing factors such as predictors, forecast horizon, model selection, and strategy. Several studies indicate that electricity demand is a primary price determinant, while renewable energy sources (RES) like wind and solar significantly impact price dynamics, often lowering prices. Additionally, incorporating data from neighboring countries, due to market coupling, further improves forecast accuracy. Most studies predict up to 24 steps ahead using hourly data, while some extend forecasts using higher-frequency data (e.g., half-hourly or quarter-hourly). Short-term EPF methods fall into two main categories: statistical and computational intelligence (CI) methods, with hybrid models combining both. While many studies use advanced statistical methods, particularly through different versions of traditional AR-type models, others apply computational techniques such as artificial neural networks (ANNs) and support vector machines (SVMs). Recent research combines multiple methods to enhance forecasting performance. Despite extensive research on EPF accuracy, a gap remains in understanding how forecasting strategy affects prediction outcomes. While iterated strategies are commonly used, they are often chosen without justification. This paper contributes by examining whether the choice of forecasting strategy impacts the quality of day-ahead price predictions, especially for multi-step forecasts. We evaluate both iterated and direct methods, exploring alternative ways of conducting iterated forecasts on benchmark and state-of-the-art forecasting frameworks. The goal is to assess whether these factors should be considered by end-users to improve forecast quality. We focus on the Greek DAM using data from July 1, 2021, to March 31, 2022. This period is chosen due to significant price volatility in Greece, driven by its dependence on natural gas and limited interconnection capacity with larger European grids. The analysis covers two phases: pre-conflict (January 1, 2022, to February 23, 2022) and post-conflict (February 24, 2022, to March 31, 2022), following the Russian-Ukraine conflict that initiated an energy crisis. We use the mean absolute percentage error (MAPE) and symmetric mean absolute percentage error (sMAPE) for evaluation, as well as the Direction of Change (DoC) measure to assess the accuracy of price movement predictions. Our findings suggest that forecasters need to apply all strategies across different horizons and models. Different strategies may be required for different horizons to optimize both accuracy and directional predictions, ensuring more reliable forecasts.

Keywords: short-term electricity price forecast, forecast strategies, forecast horizons, recursive strategy, direct strategy

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Authors: Samuel Escandón, María J. Peñaherrera-Vélez, Signe Vargas-Rosvik, Carlos Jerves Córdova, Ximena Vélez-Calvo, Angélica Ochoa-Avilés

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Overweight and obesity are considered risk factors in childhood for developing nutrition-related non-communicable diseases (NCDs), such as diabetes, cardiovascular diseases, and cancer. In Ecuador, 35.4% of 5- to 11-year-olds and 29.6% of 12- to 19-year-olds are overweight or obese. Globally, unhealthy food environments characterized by high consumption of processed/ultra-processed food and rapid urbanization are highly related to the increasing nutrition-related non-communicable diseases. The evidence shows that in low- and middle-income countries (LMICs), fiscal policies and regulatory measures significantly reduce unhealthy food environments, achieving substantial advances in health. However, in some LMICs, little is known about the impact of governments' action to implement healthy food-environment policies. This study aimed to generate evidence on the state of implementation of public policy focused on food environments for the prevention of overweight and obesity in children and adolescents in Ecuador compared to global best practices and to target key recommendations for reinforcing the current strategies. After adapting the INFORMAS' Healthy Food Environment Policy Index (Food‐EPI) to the Ecuadorian context, the Policy and Infrastructure support components were assessed. Individual online interviews were performed using fifty-one indicators to analyze the level of implementation of policies directly or indirectly related to preventing overweight and obesity in children and adolescents compared to international best practices. Additionally, a participatory workshop was conducted to identify the critical indicators and generate recommendations to reinforce or improve the political action around them. In total, 17 government and non-government experts were consulted. From 51 assessed indicators, only the one corresponding to the nutritional information and ingredients labelling registered an implementation level higher than 60% (67%) compared to the best international practices. Among the 17 indicators determined as priorities by the participants, those corresponding to the provision of local products in school meals and the limitation of unhealthy-products promotion in traditional and digital media had the lowest level of implementation (34% and 11%, respectively) compared to global best practices. The participants identified more barriers (e.g., lack of continuity of effective policies across government administrations) than facilitators (e.g., growing interest from the Ministry of Environment because of the eating-behavior environmental impact) for Ecuador to move closer to the best international practices. Finally, within the participants' recommendations, we highlight the need for policy-evaluation systems, information transparency on the impact of the policies, transformation of successful strategies into laws or regulations to make them mandatory, and regulation of power and influence from the food industry (conflicts of interest). Actions focused on promoting a more active role of society in the stages of policy formation and achieving more articulated actions between the different government levels/institutions for implementing the policy are necessary to generate a noteworthy impact on preventing overweight and obesity in children and adolescents. Including systems for internal evaluation of existing strategies to strengthen successful actions, create policies to fill existing gaps and reform policies that do not generate significant impact should be a priority for the Ecuadorian government to improve the country's food environments.

Keywords: children and adolescents, food-EPI, food policies, healthy food environment

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Authors: Wiseman Emmanuel Nkhomah, Chiyembekezo Kachimanga, Moses Banda Aron, Julia Higgins, Manuel Mulwafu, Kondwani Mpinga, Mwayi Chunga, Grace Momba, Enock Ndarama, Dickson Sumphi, Atupere Phiri, Fabien Munyaneza

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Background: Data is key to supporting health service delivery as stakeholders, including NGOs rely on it for effective service delivery, decision-making, and system strengthening. Several studies generated debate on data quality from national health management information systems (HMIS) in sub-Saharan Africa. This limits the utilization of data in resource-limited settings, which already struggle to meet standards set by the World Health Organization (WHO). We aimed to evaluate data quality improvement of Neno district HMIS over a 4-year period (2018 – 2021) following quarterly data reviews introduced in January 2020 by the district health management team and Partners In Health. Methods: Exploratory Mixed Research was used to examine report rates, followed by in-depth interviews using Key Informant Interviews (KIIs) and Focus Group Discussions (FGDs). We used the WHO module desk review to assess the quality of HMIS data in the Neno district captured from 2018 to 2021. The metrics assessed included the completeness and timeliness of 34 reports. Completeness was measured as a percentage of non-missing reports. Timeliness was measured as the span between data inputs and expected outputs meeting needs. We computed T-Test and recorded P-values, summaries, and percentage changes using R and Excel 2016. We analyzed demographics for key informant interviews in Power BI. We developed themes from 7 FGDs and 11 KIIs using Dedoose software, from which we picked perceptions of healthcare workers, interventions implemented, and improvement suggestions. The study was reviewed and approved by Malawi National Health Science Research Committee (IRB: 22/02/2866). Results: Overall, the average reporting completeness rate was 83.4% (before) and 98.1% (after), while timeliness was 68.1% and 76.4 respectively. Completeness of reports increased over time: 2018, 78.8%; 2019, 88%; 2020, 96.3% and 2021, 99.9% (p< 0.004). The trend for timeliness has been declining except in 2021, where it improved: 2018, 68.4%; 2019, 68.3%; 2020, 67.1% and 2021, 81% (p< 0.279). Comparing 2021 reporting rates to the mean of three preceding years, both completeness increased from 88% to 99% (in 2021), while timeliness increased from 68% to 81%. Sixty-five percent of reports have maintained meeting a national standard of 90%+ in completeness while only 24% in timeliness. Thirty-two percent of reports met the national standard. Only 9% improved on both completeness and timeliness, and these are; cervical cancer, nutrition care support and treatment, and youth-friendly health services reports. 50% of reports did not improve to standard in timeliness, and only one did not in completeness. On the other hand, factors associated with improvement included improved communications and reminders using internal communication, data quality assessments, checks, and reviews. Decentralizing data entry at the facility level was suggested to improve timeliness. Conclusion: Findings suggest that data quality in HMIS for the district has improved following collaborative efforts. We recommend maintaining such initiatives to identify remaining quality gaps and that results be shared publicly to support increased use of data. These results can inform Ministry of Health and its partners on some interventions and advise initiatives for improving its quality.

Keywords: data quality, data utilization, HMIS, collaboration, completeness, timeliness, decision-making

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Authors: Farhana Alam Bhuiyan, Saad Khan, Tanveer Hassan, Jhalok Ranjon Talukder, Syeda Farjana Ahmed, Rahil Roodsaz, Els Rommes, Sabina Faiz Rashid

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Breaking the shame’ is a 3 year (2015-2018) qualitative implementation research project which investigates several aspects of sexual and reproductive health and rights (SRHR) issues for adolescents living in Bangladesh. Scope of learning SRHR issues for adolescents is limited here due to cultural and religious taboos. This study adds to the ongoing discussions around adolescent’s SRHR needs and aims to, 1) understand the overall SRHR needs of urban and rural unmarried female and male adolescents and the challenges they face, 2) explore existing gaps in the content of SRHR curriculum and 3) finally, addresses some critical knowledge gaps by developing and implementing innovative SRHR educational materials. 18 in-depth interviews (IDIs) and 10 focus-group discussions (FGDs) with boys and 21 IDIs and 14 FGDs with girls of ages 13-19, from both urban and rural setting took place. Curriculum materials from two leading organizations, Unite for Body Rights (UBR) Alliance Bangladesh and BRAC Adolescent Development Program (ADP) were also reviewed, with discussions with 12 key program staff. This paper critically analyses the relevance of some of the SRHR topics that are covered, the challenges with existing pedagogic approaches and key sexuality issues that are not covered in the content, but are important for adolescents. Adolescents asked for content and guidance on a number of topics which remain missing from the core curriculum, such as emotional coping mechanisms particularly in relationships, bullying, impact of exposure to porn, and sexual performance anxiety. Other core areas of concern were effects of masturbation, condom use, sexual desire and orientation, which are mentioned in the content, but never discussed properly, resulting in confusion. Due to lack of open discussion around sexuality, porn becomes a source of information for the adolescents. For these reasons, several myths and misconceptions regarding SRHR issues like body, sexuality, agency, and gender roles still persist. The pedagogical approach is very didactic, and teachers felt uncomfortable to have discussions on certain SRHR topics due to cultural taboos or shame and stigma. Certain topics are favored- such as family planning, menstruation- and presented with an emphasis on biology and risk. Rigid formal teaching style, hierarchical power relations between students and most teachers discourage questions and frank conversations. Pedagogy approaches within classrooms play a critical role in the sharing of knowledge. The paper also describes the pilot approaches to implementing new content in SRHR curriculum. After a review of findings, three areas were selected as critically important, 1) myths and misconceptions 2) emotional management challenges, and 3) how to use condom, that have come up from adolescents. Technology centric educational materials such as web page based information platform and you tube videos are opted for which allow adolescents to bypass gatekeepers and learn facts and information from a legitimate educational site. In the era of social media, when information is always a click away, adolescents need sources that are reliable and not overwhelming. The research aims to ensure that adolescents learn and apply knowledge effectively, through creating the new materials and making it accessible to adolescents.

Keywords: adolescents, Bangladesh, media, sexuality education, unmet needs

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Authors: Jana Chakrabarti, Madhushrita Das, Ankhi Haldar, Roshni Chatterjee, Tanmoy Dey, Pubali Dhar

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High incidences of Protein Energy Malnutrition as a consequence of low protein intake are quite prevalent among the children in developing countries. Thus prevention of under-nutrition has emerged as a critical challenge to India’s developmental Planners in recent times. Increase in population over the last decade has led to greater pressure on the existing animal protein sources. But these resources are currently declining due to persistent drought, diseases, natural disasters, high-cost of feed, and low productivity of local breeds and this decline in productivity is most evident in some developing countries. So the need of the hour is to search for efficient utilization of unconventional low-cost animal protein resources. Molluscs, as a group is regarded as under-exploited source of health-benefit molecules. Bivalve is the second largest class of phylum Mollusca. Annual harvests of bivalves for human consumption represent about 5% by weight of the total world harvest of aquatic resources. The freshwater mussel Lamellidens marginalis is widely distributed in ponds and large bodies of perennial waters in the Indian sub-continent and well accepted as food all over India. Moreover, ethno-medicinal uses of the flesh of Lamellidens among the rural people to treat hypertension have been documented. Present investigation thus attempts to evaluate the potential of Lamellidens marginalis as functional food. Mussels were collected from freshwater ponds and brought to the laboratory two days before experimentation for acclimatization in laboratory conditions. Shells were removed and fleshes were preserved at- 20oC until analysis. Tissue homogenate was prepared for proximate studies. Fatty acids and amino acids composition were analyzed. Vitamins, Minerals and Heavy metal contents were also studied. Mussel Protein hydrolysate was prepared using Alcalase 2.4 L and degree of hydrolysis was evaluated to analyze its Functional properties. Ferric Reducing Antioxidant Power (FRAP) and DPPH Antioxidant assays were performed. Anti-hypertensive property was evaluated by measuring Angiotensin Converting Enzyme (ACE) inhibition assay. Proximate analysis indicates that mussel meat contains moderate amount of protein (8.30±0.67%), carbohydrate (8.01±0.38%) and reducing sugar (4.75±0.07%), but less amount of fat (1.02±0.20%). Moisture content is quite high but ash content is very low. Phospholipid content is significantly high (19.43 %). Lipid constitutes, substantial amount of eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) which have proven prophylactic values. Trace elements are found present in substantial amount. Comparative study of proximate nutrients between Labeo rohita, Lamellidens and cow’s milk indicates that mussel meat can be used as complementary food source. Functionality analyses of protein hydrolysate show increase in Fat absorption, Emulsification, Foaming capacity and Protein solubility. Progressive anti-oxidant and anti-hypertensive properties have also been documented. Lamellidens marginalis can thus be regarded as a functional food source as this may combine effectively with other food components for providing essential elements to the body. Moreover, mussel protein hydrolysate provides opportunities for utilizing it in various food formulations and pharmaceuticals. The observations presented herein should be viewed as a prelude to what future holds.

Keywords: functional food, functional properties, Lamellidens marginalis, protein hydrolysate

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Authors: Sergey Kozlov, Juliya Kozlova

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Introduction: The increased attention of researchers to an explosive trauma around the world is associated with a constant renewal of military weapons and a significant increase in terrorist activities using explosive devices. Explosive wave is a well known damaging factor of explosion. The most sensitive to the action of explosive wave in the human body are the head brain, lungs, intestines, urine bladder. The severity of damage to these organs depends on the distance from the explosion epicenter to the object, the power of the explosion, presence of barriers, parameters of the body position, and the presence of protective clothing. One of the places where a shock wave acts, in human tissues and organs, is the vascular endothelial barrier, which suffers the greatest damage in the head brain and lungs. The objective of the study was to determine the pathomorphological changes of the head brain followed the action of explosive wave. Materials and methods of research: To achieve the purpose of the study, there have been studied 6 male corpses delivered to the morgue of Municipal Institution "Dnipropetrovsk regional forensic bureau" during 2014-2016 years. The cause of death of those killed was a military explosive injury. After a visual external assessment of the head brain, for histological study there was conducted the 1 x 1 x 1 cm/piece sampling from different parts of the head brain, i.e. the frontal, parietal, temporal, occipital sites, and also from the cerebellum, pons, medulla oblongata, thalamus, walls of the lateral ventricles, the bottom of the 4th ventricle. Pieces of the head brain were immersed in 10% formalin solution for 24 hours. After fixing, the paraffin blocks were made from the material using the standard method. Then, using a microtome, there were made sections of 4-6 micron thickness from paraffin blocks which then were stained with hematoxylin and eosin. Microscopic analysis was performed using a light microscope with x4, x10, x40 lenses. Results of the study: According to the results of our study, injuries of the head brain were divided into macroscopic and microscopic. Macroscopic injuries were marked according to the results of visual assessment of haemorrhages under the membranes and into the substance, their nature, and localisation, areas of softening. In the microscopic study, our attention was drawn to both vascular changes and those of neurons and glial cells. Microscopic qualitative analysis of histological sections of different parts of the head brain revealed a number of structural changes both at the cellular and tissue levels. Typical changes in most of the studied areas of the head brain included damages of the vascular system. The most characteristic microscopic sign was the separation of vascular walls from neuroglia with the formation of perivascular space. Along with this sign, wall fragmentation of these vessels, haemolysis of erythrocytes, formation of haemorrhages in the newly formed perivascular spaces were found. In addition to damages of the cerebrovascular system, destruction of the neurons, presence of oedema of the brain tissue were observed in the histological sections of the brain. On some sections, the head brain had a heterogeneous step-like or wave-like nature. Conclusions: The pathomorphological microscopic changes in the brain, identified in the study on the died of explosive traumas, can be used for diagnostic purposes in conjunction with other characteristic signs of explosive trauma in forensic and pathological studies. The complex of microscopic signs in the head brain, i.e. separation of blood vessel walls from neuroglia with the perivascular space formation, fragmentation of walls of these blood vessels, erythrocyte haemolysis, formation of haemorrhages in the newly formed perivascular spaces is the direct indication of explosive wave action.

Keywords: blast wave, neurotrauma, human, brain

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Authors: Faranak Felfeliyan, Parvaneh Shokrani, Maryam Atarod

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Introduction Using electron beam is widespread in radiotherapy. The main criteria in radiation therapy is to irradiate the tumor volume with maximum prescribed dose and minimum dose to vital organs around it. Using abutting fields is common in radiotherapy. The main problem in using abutting fields is dose inhomogeneity in the junction region. Electron beam divergence and lateral scattering may lead to hot and cold spots in the junction region. One solution for this problem is using of a spoiler to broaden the penumbra and uniform dose in the junction region. The goal of this research was to compare titanium and aluminum effects as a spoiler for dose uniformity achievement in the junction region of oblique electron fields with Monte Carlo simulation. Dose uniformity in the junction region depends on density, scattering power, thickness of the spoiler and the angle between two fields. Materials and Methods In this study, Monte Carlo model of Siemens Primus linear accelerator was simulated for a 5 MeV nominal energy electron beam using manufacture provided specifications. BEAMnrc and EGSnrc user code were used to simulate the treatment head in electron mode (simulation of beam model). The resulting phase space file was used as a source for dose calculations for 10×10 cm2 field size at SSD=100 cm in a 30×30×45 cm3 water phantom using DOSXYZnrc user code (dose calculations). An automatic MP3-M water phantom tank, MEPHYSTO mc2 software platform and a Semi-Flex Chamber-31010 with sensitive vol­ume of 0.125 cm3 (PTW, Freiburg, Germany) were used for dose distribution measurements. Moreover, the electron field size was 10×10 cm2 and SSD=100 cm. Validation of devel­oped beam model was done by comparing the measured and calculated depth and lateral dose distributions (verification of electron beam model). Simulation of spoilers (using SLAB compo­nent module) placed at the end of the electron applicator, was done using previously vali­dated phase space file for a 5 MeV nominal energy and 10×10 cm2 field size (simulation of spoiler). An in-house routine was developed in order to calculate the combined isodose curves re­sulting from the two simulated abutting fields (calculation of dose distribution in abutting electron fields). Results Verification of the developed 5.9 MeV elec­tron beam model was done by comparing the calculated and measured dose distributions. The maximum percentage difference between calculated and measured PDD was 1%, except for the build-up region in which the difference was 2%. The difference between calculated and measured profile was 2% at the edges of the field and less than 1% in other regions. The effect of PMMA, aluminum, titanium and chromium in dose uniformity achievement in abutting normal electron fields with equivalent thicknesses to 5mm PMMA was evaluated. Comparing R90 and uniformity index of different materials, aluminum was chosen as the optimum spoiler. Titanium has the maximum surface dose. Thus, aluminum and titanium had been chosen to use for dose uniformity achievement in oblique electron fields. Using the optimum beam spoiler, junction dose decreased from 160% to 110% for 15 degrees, from 180% to 120% for 30 degrees, from 160% to 120% for 45 degrees and from 180% to 100% for 60 degrees oblique abutting fields. Using Titanium spoiler, junction dose decreased from 160% to 120% for 15 degrees, 180% to 120% for 30 degrees, 160% to 120% for 45 degrees and 180% to 110% for 60 degrees. In addition, penumbra width for 15 degrees, without spoiler in the surface was 10 mm and was increased to 15.5 mm with titanium spoiler. For 30 degrees, from 9 mm to 15 mm, for 45 degrees from 4 mm to 6 mm and for 60 degrees, from 5 mm to 8 mm. Conclusion Using spoilers, penumbra width at the surface increased, size and depth of hot spots was decreased and dose homogeneity improved at the junc­tion of abutting electron fields. Dose at the junction region of abutting oblique fields was improved significantly by using spoiler. Maximum dose at the junction region for 15⁰, 30⁰, 45⁰ and 60⁰ was decreased about 40%, 60%, 40% and 70% respectively for Titanium and about 50%, 60%, 40% and 80% for Aluminum. Considering significantly decrease in maximum dose using titanium spoiler, unfortunately, dose distribution in the junction region was not decreased less than 110%.

Keywords: abutting fields, electron beam, radiation therapy, spoilers

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Authors: Ling Ai, Ziyu Zhao, Zeyu Zhou, Xiaochen Yang, Heng Zhai, Stuart Holmes

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Optimizing the catalyst layer structure is crucial for enhancing the performance of proton exchange membrane fuel cells (PEMFCs) with low Platinum (Pt) loading. Current works focused on the utilization, durability, and site activity of Pt particles on support, and performance enhancement has been achieved by loading Pt onto porous support with different morphology, such as graphene, carbon fiber, and carbon black. Some schemes have also incorporated cost considerations to achieve lower Pt loading. However, the design of the catalyst layer (CL) structure in the membrane electrode assembly (MEA) must consider the interactions between the layers. Addressing the crucial aspects of water management, low contact resistance, and the establishment of effective three-phase boundary for MEA, multi-walled carbon nanotubes (MWCNTs) are promising CL support due to their intrinsically high hydrophobicity, high axial electrical conductivity, and potential for ordered alignment. However, the drawbacks of MWCNTs, such as strong agglomeration, wall surface chemical inertness, and unopened ends, are unfavorable for Pt nanoparticle loading, which is detrimental to MEA processing and leads to inhomogeneous CL surfaces. This further deteriorates the utilization of Pt and increases the contact resistance. Robust chemical oxidation or nitrogen doping can introduce polar functional groups onto the surface of MWCNTs, facilitating the creation of open tube ends and inducing defects in tube walls. This improves dispersibility and load capacity but reduces length and conductivity. Consequently, a trade-off exists between maintaining the intrinsic properties and the degree of functionalization of MWCNTs. In this work, MWCNTs were modified based on the operational requirements of the MEA from the viewpoint of interlayer interactions, including the search for the optimal degree of oxidation, N-doping, and micro-arrangement. MWCNT were functionalized by oxidizing, N-doping, as well as micro-alignment to achieve lower contact resistance between CL and proton exchange membrane (PEM), better hydrophobicity, and enhanced performance. Furthermore, this work expects to construct a more continuously distributed three-phase boundary by aligning MWCNT to form a locally ordered structure, which is essential for the efficient utilization of Pt active sites. Different from other chemical oxidation schemes that used HNO3:H2SO4 (1:3) mixed acid to strongly oxidize MWCNT, this scheme adopted pure HNO3 to partially oxidize MWCNT at a lower reflux temperature (80 ℃) and a shorter treatment time (0 to 10 h) to preserve the morphology and intrinsic conductivity of MWCNT. The maximum power density of 979.81 mw cm-2 was achieved by Pt loading on 6h MWCNT oxidation time (Pt-MWCNT6h). This represented a 59.53% improvement over the commercial Pt/C catalyst of 614.17 (mw cm-2). In addition, due to the stronger electrical conductivity, the charge transfer resistance of Pt-MWCNT6h in the electrochemical impedance spectroscopy (EIS) test was 0.09 Ohm cm-2, which was 48.86% lower than that of Pt/C. This study will discuss the developed catalysts and their efficacy in a working fuel cell system. This research will validate the impact of low-functionalization modification of MWCNTs on the performance of PEMFC, which simplifies the preparation challenges of CL and contributing for the widespread commercial application of PEMFCs on a larger scale.

Keywords: carbon nanotubes, electrocatalyst, membrane electrode assembly, proton exchange membrane fuel cell

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Authors: Maari Sugawara

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This ethnographic research interrogates female masochism within contemporary Japan, focusing on fifteen female BDSM (Bondage, Discipline, Dominance, Submission, Sadism, and Masochism) practitioners who identify as masochists, bottoms, and/or submissives. The study employs semi-structured interviews with these practitioners, representing diverse backgrounds and ages, to explore the intersection of sexuality and individual and/or collective trauma. The study focuses on a specific group of sadomasochists who, as survivors of gender and sexual violence, reenact their trauma through BDSM practices. This exploration draws on feminist performance studies, postcolonial studies, psychoanalysis, and affect analysis to highlight the complexities of female masochism. In a cultural milieu that often reduces female masochism to mere compliance with heteropatriarchy, this study argues that specific masochistic practices transcend submission, serving as vital strategies for confronting trauma and dismantling entrenched cultural narratives. Engaging with Lacan’s concept of feminine jouissance and the notion of "creative masochism" in the context of Japan's proximity to the imperial US, the study facilitates a nuanced exploration of female masochistic enjoyment. The study shows that these practices can act as both a means of survival and a mode of resilience, challenging dominant narratives that portray masochism solely as a form of subjugation, drawing on feminist performance studies, postcolonial studies, psychoanalysis, and affect analysis. It interprets masochism as a complex terrain of affective engagement, where shared suffering and consensual pain foster transformative possibilities. By analyzing BDSM as a cultural site, this research reframes masochism not only as a personal negotiation of pain but also as a broader allegory for Japan’s ongoing geopolitical self-positioning. Central to this analysis is the concept of "creative masochism," which positions masochism as both a metaphor and a practice through which Japan addresses its historical subordination to the United States. This framework allows for a deeper understanding of how participants' lived desires intersect with national narratives, illuminating the relationship between personal experiences and larger socio-political dynamics. It incorporates sadomasochistic metaphors into Japan-U.S. interactions, reflecting underlying patterns of submission, resistance, and cultural negotiation. Additionally, this research examines the effects, affects, and limitations of masochism within the post-WWII Japanese context, providing insights into how masochism can reshape one's relationship with their surroundings. This study challenges the notion that female masochism is entirely subsumed by hegemonic structures, revealing instead that subjects can assert their autonomy within their experiences of pleasure and pain. The consensual enactment of violence within these encounters emerges as a complex and ambivalent process, wherein pain transforms into a generative force for reimagining alternative forms of sociality and belonging. Additionally, the research identifies contradictions and connections between the personal and political, examining how kink practices shape participants' daily lives and identities, and vice versa, highlighting the profound impact of these practices on their sense of self and community. Ultimately, it reaffirms agency in the face of pervasive heteronormative power dynamics, suggesting that masochism can serve as a site of both resistance and redefinition.

Keywords: female masochism, BDSM, Japan, masochism, trauma, sexual violence

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Authors: Nayer Mofidtabatabaei

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Advancements in artificial intelligence (AI) have transformed various fields, including psychology and behavioral sciences. This paper explores the diverse ways in which AI is applied to enhance research, diagnosis, therapy, and understanding of human behavior and mental health. We discuss the potential benefits and challenges associated with AI in these fields, emphasizing the ethical considerations and the need for collaboration between AI researchers and psychological and behavioral science experts. Artificial Intelligence (AI) has gained prominence in recent years, revolutionizing multiple industries, including healthcare, finance, and entertainment. One area where AI holds significant promise is the field of psychology and behavioral sciences. AI applications in this domain range from improving the accuracy of diagnosis and treatment to understanding complex human behavior patterns. This paper aims to provide an overview of the various AI applications in psychological and behavioral sciences, highlighting their potential impact, challenges, and ethical considerations. Mental Health Diagnosis AI-driven tools, such as natural language processing and sentiment analysis, can analyze large datasets of text and speech to detect signs of mental health issues. For example, chatbots and virtual therapists can provide initial assessments and support to individuals suffering from anxiety or depression. Autism Spectrum Disorder (ASD) Diagnosis AI algorithms can assist in early ASD diagnosis by analyzing video and audio recordings of children's behavior. These tools help identify subtle behavioral markers, enabling earlier intervention and treatment. Personalized Therapy AI-based therapy platforms use personalized algorithms to adapt therapeutic interventions based on an individual's progress and needs. These platforms can provide continuous support and resources for patients, making therapy more accessible and effective. Virtual Reality Therapy Virtual reality (VR) combined with AI can create immersive therapeutic environments for treating phobias, PTSD, and social anxiety. AI algorithms can adapt VR scenarios in real-time to suit the patient's progress and comfort level. Data Analysis AI aids researchers in processing vast amounts of data, including survey responses, brain imaging, and genetic information. Privacy Concerns Collecting and analyzing personal data for AI applications in psychology and behavioral sciences raise significant privacy concerns. Researchers must ensure the ethical use and protection of sensitive information. Bias and Fairness AI algorithms can inherit biases present in training data, potentially leading to biased assessments or recommendations. Efforts to mitigate bias and ensure fairness in AI applications are crucial. Transparency and Accountability AI-driven decisions in psychology and behavioral sciences should be transparent and subject to accountability. Patients and practitioners should understand how AI algorithms operate and make decisions. AI applications in psychological and behavioral sciences have the potential to transform the field by enhancing diagnosis, therapy, and research. However, these advancements come with ethical challenges that require careful consideration. Collaboration between AI researchers and psychological and behavioral science experts is essential to harness AI's full potential while upholding ethical standards and privacy protections. The future of AI in psychology and behavioral sciences holds great promise, but it must be navigated with caution and responsibility.

Keywords: artificial intelligence, psychological sciences, behavioral sciences, diagnosis and therapy, ethical considerations

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