Search results for: resource estimation

Authors: Damiano Omari, Topirian Kerempe, Dibo Sama, Walter Wafula, Sharon Chepkoech, Chrispine Juma, Gilbert Kirui, Simon Mburu, Susan Keino

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The One Health concept was officially adopted by the international organizations and scholarly bodies in 1984. It aims at combining human, animal and environmental components to address global health challenges. Using collaborative efforts optimal health to people, animals, and the environment can be achieved. One health approach plays a significant approach role in prevention and control of zoonosis diseases. It has also been noted that 75% of new emerging human infectious diseases are zoonotic. In Kenya, one health has been embraced and strongly advocated for by One Health East and Central Africa (OHCEA). It was inaugurated on 17th of October 2010 at a historic meeting facilitated by USAID with participants from 7 public health schools, seven faculties of veterinary medicine in Eastern Africa and 2 American universities (Tufts and University of Minnesota) in addition to respond project staff. The study was conducted in Loitoktok Sub County, specifically in the Amboseli Ecosystem. The Amboseli ecosystem covers an area of 5,700 square kilometers and stretches between Mt. Kilimanjaro, Chyulu Hills, Tsavo West National park and the Kenya/Tanzania border. The area is arid to semi-arid and is more suitable for pastoralism with a high potential for conservation of wildlife and tourism enterprises. The ecosystem consists of the Amboseli National Park, which is surrounded by six group ranches which include Kimana, Olgulului, Selengei, Mbirikani, Kuku and Rombo in Loitoktok District. The Manyatta of study was Osiram Cultural Manyatta in Mbirikani group ranch. Apart from visiting the Manyatta, we also visited the sub-county hospital, slaughter slab, forest service, Kimana market, and the Amboseli National Park. The aim of the study was to identify the one health issues facing the community. This was done by a conducting a community needs assessment and prioritization. Different methods were used in data collection for the qualitative and numerical data. They include among others; key informant interviews and focus group discussions. We also guided the community members in drawing their Resource Map this helped identify the major resources in their land and also help them identify some of the issues they were facing. Matrix piling, root cause analysis, and force field analysis tools were used to establish the one health related priority issues facing community members. Skits were also used to present to the community interventions to the major one health issues. Some of the prioritized needs among the community were water scarcity and inadequate markets for their beadwork. The group intervened on the various needs of the Manyatta. For water scarcity, we educated the community on water harvesting methods using gutters as well as proper storage by the use of tanks and earth dams. The community was also encouraged to recycle and conserve water. To improve markets; we educated the community to upload their products online, a page was opened for them and uploading the photos was demonstrated to them. They were also encouraged to be innovative to attract more clients.

Keywords: Amboseli ecosystem, community interventions, community needs assessment and prioritization, one health issues

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Authors: Sanaz Alizadeh, Yves Comeau, Arshath Abdul Rahim, Sunhasis Ghoshal

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The application of silver nanoparticles (AgNPs) in personal care products, various household and industrial products has resulted in an inevitable environmental exposure of such engineered nanoparticles (ENPs). Ag ENPs, released via household and industrial wastes, reach water resource recovery facilities (WRRFs), yet the fate and transport of ENPs in WRRFs and their potential risk in the biological wastewater processes are poorly understood. Accordingly, our main objective was to elucidate the impact of long-term continuous exposure to AgNPs on biological activity of aerobic wastewater biofilm. The fate, transport and toxicity of 10 μg.L-1and 100 μg.L-1 PVP-stabilized AgNPs (50 nm) were evaluated in an attached growth biological treatment process, using lab-scale moving bed bioreactors (MBBRs). Two MBBR systems for organic matter removal were fed with a synthetic influent and operated at a hydraulic retention time (HRT) of 180 min and 60% volumetric filling ratio of Anox-K5 carriers with specific surface area of 800 m2/m3. Both reactors were operated for 85 days after reaching steady state conditions to develop a mature biofilm. The impact of AgNPs on the biological performance of the MBBRs was characterized over a period of 64 days in terms of the filtered biodegradable COD (SCOD) removal efficiency, the biofilm viability and key enzymatic activities (α-glucosidase and protease). The AgNPs were quantitatively characterized using single-particle inductively coupled plasma mass spectroscopy (spICP-MS), determining simultaneously the particle size distribution, particle concentration and dissolved silver content in influent, bioreactor and effluent samples. The generation of reactive oxygen species and the oxidative stress were assessed as the proposed toxicity mechanism of AgNPs. Results indicated that a low concentration of AgNPs (10 μg.L-1) did not significantly affect the SCOD removal efficiency whereas a significant reduction in treatment efficiency (37%) was observed at 100 μg.L-1AgNPs. Neither the viability nor the enzymatic activities of biofilm were affected at 10 μg.L-1AgNPs but a higher concentration of AgNPs induced cell membrane integrity damage resulting in 31% loss of viability and reduced α-glucosidase and protease enzymatic activities by 31% and 29%, respectively, over the 64-day exposure period. The elevated intercellular ROS in biofilm at a higher AgNPs concentration over time was consistent with a reduced biological biofilm performance, confirming the occurrence of a nanoparticle-induced oxidative stress in the heterotrophic biofilm. The spICP-MS analysis demonstrated a decrease in the nanoparticles concentration over the first 25 days, indicating a significant partitioning of AgNPs into the biofilm matrix in both reactors. The concentration of nanoparticles increased in effluent of both reactors after 25 days, however, indicating a decreased retention capacity of AgNPs in biofilm. The observed significant detachment of biofilm also contributed to a higher release of nanoparticles due to cell-wall destabilizing properties of AgNPs as an antimicrobial agent. The removal efficiency of PVP-AgNPs and the biofilm biological responses were a function of nanoparticle concentration and exposure time. This study contributes to a better understanding of the fate and behavior of AgNPs in biological wastewater processes, providing key information that can be used to predict the environmental risks of ENPs in aquatic ecosystems.

Keywords: biofilm, silver nanoparticle, single particle ICP-MS, toxicity, wastewater

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Authors: Jun Byung Joon, Seo Seok Hyun, Lee Seo Young

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As carbon dioxide emissions increase due to rapid industrialization and reckless development, abnormal climates such as floods and droughts are occurring. In order to respond to such climate change, the use of existing fossil fuels is reduced, and the proportion of eco-friendly renewable energy is gradually increasing. Korea is an energy resource-poor country that depends on imports for 93% of its total energy. As the global energy supply chain instability experienced due to the Russia-Ukraine crisis increases, countries around the world are resetting energy policies to minimize energy dependence and strengthen security. Seawater thermal energy is a renewable energy that replaces the existing air heat energy. It uses the characteristic of having a higher specific heat than air to cool and heat main spaces of buildings to increase heat transfer efficiency and minimize power consumption to generate electricity using fossil fuels, and Carbon dioxide emissions can be minimized. In addition, the effect on the marine environment is very small by using only the temperature characteristics of seawater in a limited way. K-water carried out a demonstration project of supplying cooling and heating energy to spaces such as the central control room and presentation room in the management building by acquiring the heat source of seawater circulated through the power plant's waterway by using the characteristics of the tidal power plant. Compared to the East Sea and the South Sea, the main system was designed in consideration of the large tidal difference, small temperature difference, and low-temperature characteristics, and its performance was verified through operation during the demonstration period. In addition, facility improvements were made for major deficiencies to strengthen monitoring functions, provide user convenience, and improve facility soundness. To spread these achievements, the basic concept was to expand the seawater heating and cooling system with a scale of 200 USRT at the Tidal Culture Center. With the operational experience of the demonstration system, it will be possible to establish an optimal seawater heat cooling and heating system suitable for the characteristics of the west coast ocean. Through this, it is possible to reduce operating costs by KRW 33,31 million per year compared to air heat, and through industry-university-research joint research, it is possible to localize major equipment and materials and develop key element technologies to revitalize the seawater heat business and to advance into overseas markets. The government's efforts are needed to expand the seawater heating and cooling system. Seawater thermal energy utilizes only the thermal energy of infinite seawater. Seawater thermal energy has less impact on the environment than river water thermal energy, except for environmental pollution factors such as bottom dredging, excavation, and sand or stone extraction. Therefore, it is necessary to increase the sense of speed in project promotion by innovatively simplifying unnecessary licensing/permission procedures. In addition, support should be provided to secure business feasibility by dramatically exempting the usage fee of public waters to actively encourage development in the private sector.

Keywords: seawater thermal energy, marine energy, tidal power plant, energy consumption

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Authors: Philipp Sommer, Amgad Agoub

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The construction sector significantly impacts global CO₂ emissions, particularly through the energy usage of residential buildings. To address this, various governments, including Germany's, are focusing on reducing emissions via sustainable refurbishment initiatives. This study examines the application of machine learning (ML) to estimate energy demands dynamically in residential buildings and enhance the potential for large-scale sustainable refurbishment. A major challenge in Germany is the lack of extensive publicly labeled datasets for energy performance, as energy performance certificates, which provide critical data on building-specific energy requirements and consumption, are not available for all buildings or require on-site inspections. Conversely, England and other countries in the European Union (EU) have rich public datasets, providing a viable alternative for analysis. This research adapts insights from these English datasets to the German context by developing a comprehensive data schema and calibration dataset capable of predicting building energy demand effectively. The study proposes a minimal feature set, determined through feature importance analysis, to optimize the ML model. Findings indicate that ML significantly improves the scalability and accuracy of energy demand forecasts, supporting more effective emissions reduction strategies in the construction industry. Integrating energy performance certificates into municipal heat planning in Germany highlights the transformative impact of data-driven approaches on environmental sustainability. The goal is to identify and utilize key features from open data sources that significantly influence energy demand, creating an efficient forecasting model. Using Extreme Gradient Boosting (XGB) and data from energy performance certificates, effective features such as building type, year of construction, living space, insulation level, and building materials were incorporated. These were supplemented by data derived from descriptions of roofs, walls, windows, and floors, integrated into three datasets. The emphasis was on features accessible via remote sensing, which, along with other correlated characteristics, greatly improved the model's accuracy. The model was further validated using SHapley Additive exPlanations (SHAP) values and aggregated feature importance, which quantified the effects of individual features on the predictions. The refined model using remote sensing data showed a coefficient of determination (R²) of 0.64 and a mean absolute error (MAE) of 4.12, indicating predictions based on efficiency class 1-100 (G-A) may deviate by 4.12 points. This R² increased to 0.84 with the inclusion of more samples, with wall type emerging as the most predictive feature. After optimizing and incorporating related features like estimated primary energy consumption, the R² score for the training and test set reached 0.94, demonstrating good generalization. The study concludes that ML models significantly improve prediction accuracy over traditional methods, illustrating the potential of ML in enhancing energy efficiency analysis and planning. This supports better decision-making for energy optimization and highlights the benefits of developing and refining data schemas using open data to bolster sustainability in the building sector. The study underscores the importance of supporting open data initiatives to collect similar features and support the creation of comparable models in Germany, enhancing the outlook for environmental sustainability.

Keywords: machine learning, remote sensing, residential building, energy performance certificates, data-driven, heat planning

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Authors: Marilena Fatigante

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Contemporary psychoanalysis is increasingly acknowledging the existential demands of clients in psychotherapy. A significant aspect of the personal crises that patients face today is often rooted in the difficulty to find meaning in their own existence, even after working through or resolving traumatic memories and experiences. Tracing back to the correspondence between Freud and Romain Rolland (1927), psychoanalysis could not ignore that investigation of the psyche also encompasses the encounter with deep, psycho-sensory experiences, which involve a sense of "being one with the external world as a whole", the well-known “oceanic feeling”, as Rolland posed it. Despite the recognition of Non-ordinary States of Consciousness (NSC) as catalysts for transformation in clinical practice, highlighted by neuroscience and results from psychedelic-assisted therapies, there is few research on how psychoanalytic knowledge can integrate with other treatment traditions. These traditions, commonly rooted in non -Western, unconventional, and non-formal psychological knowledge, emphasize the individual’s innate tendency toward existential integrity and transcendence of self-boundaries. Inspired by an autobiographical account, this paper examines narratives of 12 individuals, who engaged in psychoanalytic therapy and also underwent treatment involving a non-formal helping relationship with an expert guide in consciousness, which included experience of this nature. The guide relies on 35 yrs of experience in Psychological, multidisciplinary studies in Human Sciences and Art, and demonstrates knowledge of many wisdom traditions, ranging from Eastern to Western philosophy, including Psychoanalysis and its development in cultural perspective (e.g, Ethnopsychiatry). Analyses focused primarily on two dimensions that research has identified as central in assessing the degree of treatment “success” in the patients’ narrative accounts of their therapies: agency and coherence, defined respectively as the increase, expressed in language, of the client’s perceived ability to manage his/her own challenges and the capacity, inherent in “narrative” itself as a resource for meaning making (Bruner, 1990), to provide the subject with a sense of unity, endowing his /her life experience with temporal and logical sequentiality. The present study reports that, in all narratives from the participants, agency and coherence are described differently than in “common” psychotherapy narratives. Although the participants consistently identified themselves as responsible agentic subject, the sense of agency derived from the non-conventional guidance pathway is never reduced to a personal, individual accomplishment. Rather, the more a new, fuller sense of “Life” (more than “Self”) develops out of the guidance pathway they engage with the expert guide, the more they “surrender” their own sense of autonomy and self-containment. Something, which Safran (2016) identified as well talking about the sense of surrender and “grace” in psychoanalytic sessions. Secondly, narratives of individuals engaging with the expert guide describe coherence not as repairing or enforcing continuity but as enhancing their ability to navigate dramatic discontinuities, falls, abrupt leaps and passages marked by feelings of loss and bereavement. The paper ultimately explores whether valid criteria can be established to analyze experiences of non-conventional paths of self-evolution. These paths are not opposed or alternative to conventional ones, and should not be simplistically dismissed as exotic or magical.

Keywords: oceanic feeling, non conventional guidance, consciousness, narratives, treatment outcomes

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Authors: F. Pedro, S. Dias, A. Tadeu, J. António, Ó. López, A. Coelho

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Railway transportation is considered the most economical and sustainable way to travel. However, future mobility brings important challenges to railway operators. The main target is to develop solutions that stimulate sustainable mobility. The research and innovation goals for this domain are efficient solutions, ensuring an increased level of safety and reliability, improved resource efficiency, high availability of the means (train), and satisfied passengers with the travel comfort level. These requirements are in line with the European Strategic Agenda for the 2020 rail sector, promoted by the European Rail Research Advisory Council (ERRAC). All these aspects involve redesigning current equipment and, in particular, the interior of the carriages. Recent studies have shown that two of the most important requirements for passengers are reasonable ticket prices and comfortable interiors. Passengers tend to use their travel time to rest or to work, so train interiors and their systems need to incorporate features that meet these requirements. Among the various systems that integrate train interiors, the flooring system is one of the systems with the greatest impact on passenger safety and comfort. It is also one of the systems that takes more time to install on the train, and which contributes seriously to the weight (mass) of all interior systems. Additionally, it presents a strong impact on manufacturing costs. The design of railway floor, in the development phase, is usually made relying on a design software that allows to draw and calculate several solutions in a short period of time. After obtaining the best solution, considering the goals previously defined, experimental data is always necessary and required. This experimental phase has such great significance, that its outcome can provoke the revision of the designed solution. This paper presents the methodology and some of the results of an experimental characterisation of composite panels for railway application. The mechanical tests were made for unaged specimens and for specimens that suffered some type of aging, i.e. heat, cold and humidity cycles or freezing/thawing cycles. These conditionings aim to simulate not only the time effect, but also the impact of severe environmental conditions. Both full solutions and separated components/materials were tested. For the full solution, (panel) these were: four-point bending tests, tensile shear strength, tensile strength perpendicular to the plane, determination of the spreading of water, and impact tests. For individual characterisation of the components, more specifically for the covering, the following tests were made: determination of the tensile stress-strain properties, determination of flexibility, determination of tear strength, peel test, tensile shear strength test, adhesion resistance test and dimensional stability. The main conclusions were that experimental characterisation brings a huge contribution to understand the behaviour of the materials both individually and assembled. This knowledge contributes to the increase the quality and improvements of premium solutions. This research work was framed within the POCI-01-0247-FEDER-003474 (coMMUTe) Project funded by Portugal 2020 through the COMPETE 2020.

Keywords: durability, experimental characterization, mechanical tests, railway flooring system

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Authors: Vanita Singh

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In developing countries, there are conflicting political agendas; policy makers have to prioritize issues from a list of issues competing for the limited resources. Thus, it is imperative to understand how some issues gain attention, and others lose in the policy circles. Multiple-Streams Theory of Kingdon (1984) is among the influential theories that help to understand the public policy process and is utilitarian for health policy makers to understand how certain health issues emerge on the policy agendas. The issue of maternal mortality was long standing in India and was linked with high birth rate thus the focus of maternal health policy was on family planning since India’s independence. However, a paradigm shift was noted in the maternal health policy in the year 1992 with the launch of Safe Motherhood Programme and then in the year 2005, when the agenda of maternal health policy became universalizing institutional deliveries and phasing-out of Traditional Birth Attendants (TBAs) from the health system. There were many solutions proposed by policy communities other than universalizing of institutional deliveries, including training of TBAs and improving socio-economic conditions of pregnant women. However, Government of India favored medical community, which was advocating for the policy of universalizing institutional delivery, and neglected the solutions proposed by other policy communities. It took almost 15 years for the advocates of institutional delivery to transform their proposed solution into a program - the Janani Suraksha Yojana (JSY), a safe-motherhood program promoting institutional delivery through cash incentives to pregnant women. Thus, the case of safe motherhood policy in India is worth studying to understand how certain issues/problems gain political attention and how advocacy work in policy circles. This paper attempts to understand the factors that favored the agenda of safe-motherhood in the policy circle in India, using John Kingdon’s Multiple-Stream model of agenda-setting. Through document analysis and literature review, the paper traces the evolution of safe motherhood program and maternal health policy. The study has used open source documents available on the website of Ministry of Health and Family Welfare, media reports (Times of India Archive) and related research papers. The documents analyzed include National health policy-1983, National Health Policy-2002, written reports of Ministry of Health and Family Welfare Department, National Rural Health Mission (NRHM) document, documents related to Janani Suraksha Yojana and research articles related to maternal health programme in India. The study finds that focusing events and credible indicators coupled with media attention has the potential to recognize a problem. The political elites favor clearly defined and well-accepted solutions. The trans-national organizations affect the agenda-setting process in a country through conditional resource provision. The closely-knit policy communities and political entrepreneurship are required for advocating solutions high on agendas. The study has implications for health policy makers in identifying factors that have the potential to affect the agenda-setting process for a desired policy agenda and identify the challenges in generating political priorities.

Keywords: agenda-setting, focusing events, Kingdon’s model, safe motherhood program India

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Authors: Gospel Iyioku, Jana Mazancova, Jiri Hejkrlik

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The “Agricultural Promotion Policy (2016–2020)” represents a strategic initiative by the Nigerian government to address domestic food shortages and the challenges in exporting products at the required quality standards. Hindered by an inefficient system for setting and enforcing food quality standards, coupled with a lack of market knowledge, the Federal Ministry of Agriculture and Rural Development (FMARD) aims to enhance support for the production and activities of key crops like cashew. By collaborating with farmers, processors, investors, and stakeholders in the cashew sector, the policy seeks to define and uphold high-quality standards across the cashew value chain. Given the challenges and opportunities faced by Nigerian cashew farmers, active participation in cashew marketing groups becomes imperative. These groups serve as essential platforms for farmers to collectively navigate market intricacies, access resources, share knowledge, improve output quality, and bolster their overall bargaining power. Through engagement in these cooperative initiatives, farmers not only boost their economic prospects but can also contribute significantly to the sustainable growth of the cashew industry, fostering resilience and community development. This study explores the perceptions and intentions of farmers regarding their involvement in cashew marketing cooperatives, utilizing an expanded version of the Theory of Planned Behaviour. Drawing insights from a diverse sample of 321 cashew farmers in Southwest Nigeria, the research sheds light on the factors influencing decision-making in cooperative participation. The demographic analysis reveals a diverse landscape, with a substantial presence of middle-aged individuals contributing significantly to the agricultural sector and cashew-related activities emerging as a primary income source for a substantial proportion (23.99%). Employing Structural Equation Modelling (SEM) with Maximum Likelihood Robust (MLR) estimation in R, the research elucidates the associations among latent variables. Despite the model’s complexity, the goodness-of-fit indices attest to the validity of the structural model, explaining approximately 40% of the variance in the intention to join cooperatives. Moral norms emerge as a pivotal construct, highlighting the profound influence of ethical considerations in decision-making processes, while perceived behavioural control presents potential challenges in active participation. Attitudes toward joining cooperatives reveal nuanced perspectives, with strong beliefs in enhanced connections with other farmers but varying perceptions on improved access to essential information. The SEM analysis establishes positive and significant effects of moral norms, perceived behavioural control, subjective norms, and attitudes on farmers’ intention to join cooperatives. The knowledge construct positively affects key factors influencing intention, emphasizing the importance of informed decision-making. A supplementary analysis using partial least squares (PLS) SEM corroborates the robustness of our findings, aligning with covariance-based SEM results. This research unveils the determinants of cooperative participation and provides valuable insights for policymakers and practitioners aiming to empower and support this vital demographic in the cashew industry.

Keywords: marketing cooperatives, theory of planned behaviour, structural equation modelling, cashew farmers

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Authors: Nirajan Shrestha

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Karnali is one of the most vulnerable provinces in Nepal, facing challenges from climate change, poverty, and natural calamities across different regions. In recent years, the province has been severely impacted by climate change stress such as temperature rises in glacier lake of mountainous region and spring source water shortages, particularly in hilly areas where settlements are located, and water sources have depleted from their original ground levels. As a result, Karnali could face a future without enough water for all. Deep causes of sustainable safe water supply have always been neglected in rural areas of Nepal, and communities are unfairly burdened with a challenge of keeping water facilities functioning in areas affected by frequent natural disasters where there is a substantial, well-documented funding gap between the revenues from user payments and the full cost of sustained services. The key importance of a permanent system to support communities in service delivery has been always underrated so far. The complexity of water service sustainability as a topic should be simplified to one clear indicator: the functionality rate, which can be expressed as uptime or the percentage of time that the service is delivered over the total time. For example, a functionality rate of 80% means that the water service is operational 80% of the time, while 20% of the time the system is not functioning. This represents 0.2 multiplied by 365, which equals 73 days every year, or roughly two and a half months without water. This percentage should be widely understood and used in Karnali. All local governments should report their targets and performance in improving it, and there should be a broader discussion about what target is acceptable and what can be realistically achieved. In response to these challenges, the Sustainable WASH for All (SUSWA) project has introduced innovative models and policy formulation strategies in various working local government. SUSWA’s approach, which delegates rural water supply and sanitation responsibilities to local governments, has been instrumental in addressing these issues. To keep pace with the growing demand, the province has adopted a service support center model, linking local governments with federal authorities to ensure effective service delivery to the communities By enhancing WASH governance through local governments engagement, capacity building and inclusive WASH policy frameworks, there is potential to address WASH gaps while fostering a circular economy. This strategy emphasizes resource recovery, waste minimization and the creation of local employment generation opportunities. The research highlights key governance mechanisms, innovative practices and policy interventions that can be scaled up across other regions. It also provides recommendations on how to leverage Karnali’s unique socio-economic and environmental context nature-based solutions to inspire innovation and drive sustainable WASH solutions. Key findings suggest that with strong ownership and leadership of local governments, community engagement and appropriate technology, Karnali Province can become a model for integrating WASH governance with circular economy concept, providing broader lessons for other regions in Nepal.

Keywords: vulnerable provinces, natural calamities, climate change stres, spring source depletion, resources recovery, governance mechanisms, appropriate technology, community engagement, innovation

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Authors: Simon Komesker, Achim Wagner, Martin Ruskowski

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In times of volatile markets with fluctuating demand and the uncertainty of global supply chains, flexible production systems are the key to an efficient implementation of a desired production program. In this publication, the authors present a holistic information concept taking into account various influencing factors for operating towards the global optimum. Therefore, a strategy for the implementation of multi-level planning for a flexible, reconfigurable production system with an alternative production concept in the automotive industry is developed. The main contribution of this work is a system structure mixing central and decentral planning and control evaluated in a simulation framework. The information system structure in current production systems in the automotive industry is rigidly hierarchically organized in monolithic systems. The production program is created rule-based with the premise of achieving uniform cycle time. This program then provides the information basis for execution in subsystems at the station and process execution level. In today's era of mixed-(car-)model factories, complex conditions and conflicts arise in achieving logistics, quality, and production goals. There is no provision for feedback loops of results from the process execution level (resources) and process supporting (quality and logistics) systems and reconsideration in the planning systems. To enable a robust production flow, the complexity of production system control is artificially reduced by the line structure and results, for example in material-intensive processes (buffers and safety stocks - two container principle also for different variants). The limited degrees of freedom of line production have produced the principle of progress figure control, which results in one-time sequencing, sequential order release, and relatively inflexible capacity control. As a result, modularly structured production systems such as modular production according to known approaches with more degrees of freedom are currently difficult to represent in terms of information technology. The remedy is an information concept that supports cross-system and cross-level information processing for centralized and decentralized decision-making. Through an architecture of hierarchically organized but decoupled subsystems, the paradigm of hybrid control is used, and a holonic manufacturing system is offered, which enables flexible information provisioning and processing support. In this way, the influences from quality, logistics, and production processes can be linked holistically with the advantages of mixed centralized and decentralized planning and control. Modular production systems also require modularly networked information systems with semi-autonomous optimization for a robust production flow. Dynamic prioritization of different key figures between subsystems should lead the production system to an overall optimum. The tasks and goals of quality, logistics, process, resource, and product areas in a cyber-physical production system are designed as an interconnected multi-agent-system. The result is an alternative system structure that executes centralized process planning and decentralized processing. An agent-based manufacturing control is used to enable different flexibility and reconfigurability states and manufacturing strategies in order to find optimal partial solutions of subsystems, that lead to a near global optimum for hybrid planning. This allows a robust near to plan execution with integrated quality control and intralogistics.

Keywords: holonic manufacturing system, modular production system, planning, and control, system structure

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Authors: Ronahlee Asuncion

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The nature of their work and employment relationship make domestic workers easy prey to abuse, maltreatment, and exploitation. Considering their plight, this research was conceptualized and examined the: a) level of awareness of Filipino domestic workers on occupational safety and health (OSH); b) their issues/problems/concerns on OSH; c) their intervention strategies at work to address OSH related issues/problems/concerns; d) issues/problems/concerns of government, employers, and non-government organizations with regard to implementation of OSH to Filipino domestic workers; e) the role of government, employers and non-government organizations to help Filipino domestic workers address OSH related issues/problems/concerns; and f) the necessary policy amendments/initiatives/programs to address OSH related issues/problems/concerns of Filipino domestic workers. The study conducted a survey using non-probability sampling, two focus group discussions, two group interviews, and fourteen face-to-face interviews. These were further supplemented with an email correspondence to a key informant based in another country. Books, journals, magazines, and relevant websites further substantiated and enriched data of the research. Findings of the study point to the fact that domestic workers have low level of awareness on OSH because of poor information drive, fragmented implementation of the Domestic Workers Act, inactive campaign at the barangay level, weakened advocacy for domestic workers, absence of law on OSH for domestic workers, and generally low safety culture in the country among others. Filipino domestic workers suffer from insufficient rest, long hours of work, heavy workload, occupational stress, poor accommodation, insufficient hours of sleep, deprivation of day off, accidents and injuries such as cuts, burns, slipping, stumbling, electrical grounding, and fire, verbal, physical and sexual abuses, lack of medical assistance, none provision of personal protective equipment (PPE), absence of knowledge on the proper way of lifting, working at heights, and insufficient food provision. They also suffer from psychological problems because of separation from one’s family, limited mobility in the household where they work, injuries and accidents from using advanced home appliances and taking care of pets, low self-esteem, ergonomic problems, the need to adjust to all household members who have various needs and demands, inability to voice their complaints, drudgery of work, and emotional stress. With regard to illness or health problems, they commonly experience leg pains, back pains, and headaches. In the absence of intervention programs like those offered in the formal employment set up, domestic workers resort to praying, turn to family, relatives and friends for social and emotional support, connect with them through social media like Facebook which also serve as a means of entertainment to them, talk to their employer, and just try to be optimistic about their situation. Promoting OSH for domestic workers is very challenging and complicated because of interrelated factors such as cultural, knowledge, attitudinal, relational, social, resource, economic, political, institutional and legal problems. This complexity necessitates using a holistic and integrated approach as this is not a problem requiring simple solutions. With this recognition comes the full understanding that its success involves the action and cooperation of all duty bearers in attaining decent work for domestic workers.

Keywords: decent work, Filipino domestic workers, occupational safety and health, working conditions

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Authors: Kriti Jain, Sucha Singh Gill

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Subsidies have been a major part of agricultural policies around the world, and more extensively since the green revolution in developing countries, for the sake of attaining higher agricultural productivity and achieving food security. But entrenched subsidies lead to distorted incentives and promote inefficiencies in the agricultural sector, threatening the viability of these very subsidies and sustainability of the agricultural production systems, posing a threat to the livelihood of farmers and laborers dependent on it. This paper analyzes the economic and ecological sustainability implications of prolonged input and output subsidies in agriculture by studying the case of Indian Punjab, an agriculturally developed state responsible for ensuring food security in the country when it was facing a major food crisis. The paper focuses specifically on the environmentally unsustainable cropping pattern changes as a result of Minimum Support Price (MSP) and assured procurement and on the resource use efficiency and cost implications of power subsidy for irrigation in Punjab. The study is based on an analysis of both secondary and primary data sources. Using secondary data, a time series analysis was done to capture the changes in Punjab’s cropping pattern, water table depth, fertilizer consumption, and electrification of agriculture. This has been done to examine the role of price and output support adopted to encourage the adoption of green revolution technology in changing the cropping structure of the state, resulting in increased input use intensities (especially groundwater and fertilizers), which harms the ecological balance and decreases factor productivity. Evaluation of electrification of Punjab agriculture helped evaluate the trend in electricity productivity of agriculture and how free power imposed further pressure on the extant agricultural ecosystem. Using data collected from a primary survey of 320 farmers in Punjab, the extent of wasteful application of groundwater irrigation, water productivity of output, electricity usage, and cost of irrigation driven electricity subsidy to the exchequer were estimated for the dominant cropping pattern amongst farmers. The main findings of the study revealed how because of a subsidy has driven agricultural framework, Punjab has lost area under agro climatically suitable and staple crops and moved towards a paddy-wheat cropping system, that is gnawing away the state’s natural resources like water table has been declining at a significant rate of 25 cms per year since 1975-76, and excessive and imbalanced fertilizer usage has led to declining soil fertility in the state. With electricity-driven tubewells as the major source of irrigation within a regime of free electricity and water-intensive crop cultivation, there is both wasteful application of irrigation water and electricity in the cultivation of paddy crops, burning an unproductive hole in the exchequer’s pocket. There is limited access to both agricultural extension services and water-conserving technology, along with policy imbalance, keeping farmers in an intensive and unsustainable production system. Punjab agriculture is witnessing diminishing returns to factor, which under the business-as-usual scenario, will soon enter the phase of negative returns to factor.

Keywords: cropping pattern, electrification, subsidy, sustainability

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Authors: Atefeh Salehipoor

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Textiles play a vital role in human life, particularly in the form of clothing. However, the alarming rate at which textiles end up in landfills presents a significant environmental risk. With approximately one garbage truck per second being filled with discarded textiles, urgent measures are required to mitigate this trend. Governments and responsible organizations are calling upon various stakeholders to shift from a linear economy to a circular economy model in the textile industry. This article highlights several key approaches that can be undertaken to address this pressing issue. These approaches include the creation of renewable raw material sources, rethinking production processes, maximizing the use and reuse of textile products, implementing reproduction and recycling strategies, exploring redistribution to new markets, and finding innovative means to extend the lifespan of textiles. However, the rapid accumulation of textiles in landfills poses a significant threat to the environment. This article explores the urgent need for the textile industry to transition from a linear economy model to a circular economy model. The linear model, characterized by the creation, use, and disposal of textiles, is unsustainable in the long term. By adopting a circular economy approach, the industry can minimize waste, reduce environmental impact, and promote sustainable practices. This article outlines key approaches that can be undertaken to drive this transition. Approaches to Address Environmental Challenges: 1. Creation of Renewable Raw Materials Sources: Exploring and promoting the use of renewable and sustainable raw materials, such as organic cotton, hemp, and recycled fibers, can significantly reduce the environmental footprint of textile production. 2. Rethinking Production Processes: Implementing cleaner production techniques, optimizing resource utilization, and minimizing waste generation are crucial steps in reducing the environmental impact of textile manufacturing. 3. Maximizing Use and Reuse of Textile Products: Encouraging consumers to prolong the lifespan of textile products through proper care, maintenance, and repair services can reduce the frequency of disposal and promote a culture of sustainability. 4. Reproduction and Recycling Strategies: Investing in innovative technologies and infrastructure to enable efficient reproduction and recycling of textiles can close the loop and minimize waste generation. 5. Redistribution of Textiles to New Markets: Exploring opportunities to redistribute textiles to new and parallel markets, such as resale platforms, can extend their lifecycle and prevent premature disposal. 6. Improvising Means to Extend Textile Lifespan: Encouraging design practices that prioritize durability, versatility, and timeless aesthetics can contribute to prolonging the lifespan of textiles. Conclusion The textile industry must urgently transition from a linear economy to a circular economy model to mitigate the adverse environmental impact caused by textile waste. By implementing the outlined approaches, such as sourcing renewable raw materials, rethinking production processes, promoting reuse and recycling, exploring new markets, and extending the lifespan of textiles, stakeholders can work together to create a more sustainable and environmentally friendly textile industry. These measures require collective action and collaboration between governments, organizations, manufacturers, and consumers to drive positive change and safeguard the planet for future generations.

Keywords: textiles, circular economy, environmental challenges, renewable raw materials, production processes, reuse, recycling, redistribution, textile lifespan extension

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Authors: Albert W. K. Tan

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This research consolidates a comprehensive array of publications from peer-reviewed journals, case studies, and seminar reports focused on reverse logistics and network design. By synthesizing this secondary knowledge, our objective is to identify and articulate key decision factors crucial to reverse logistics network design for e-commerce. Through this exploration, we aim to present a refined mathematical model that offers valuable insights for companies seeking to optimize their reverse logistics operations. The primary goal of this research endeavor is to develop a comprehensive framework tailored to advising organizations and companies on crafting effective networks for their reverse logistics operations, thereby facilitating the achievement of their organizational goals. This involves a thorough examination of various network configurations, weighing their advantages and disadvantages to ensure alignment with specific business objectives. The key objectives of this research include: (i) Identifying pivotal factors pertinent to network design decisions within the realm of reverse logistics across diverse supply chains. (ii) Formulating a structured framework designed to offer informed recommendations for sound network design decisions applicable to relevant industries and scenarios. (iii) Propose a mathematical model to optimize its reverse logistics network. A conceptual framework for designing a reverse logistics network has been developed through a combination of insights from the literature review and information gathered from company websites. This framework encompasses four key stages in the selection of reverse logistics operations modes: (1) Collection, (2) Sorting and testing, (3) Processing, and (4) Storage. Key factors to consider in reverse logistics network design: I) Centralized vs. decentralized processing: Centralized processing, a long-standing practice in reverse logistics, has recently gained greater attention from manufacturing companies. In this system, all products within the reverse logistics pipeline are brought to a central facility for sorting, processing, and subsequent shipment to their next destinations. Centralization offers the advantage of efficiently managing the reverse logistics flow, potentially leading to increased revenues from returned items. Moreover, it aids in determining the most appropriate reverse channel for handling returns. On the contrary, a decentralized system is more suitable when products are returned directly from consumers to retailers. In this scenario, individual sales outlets serve as gatekeepers for processing returns. Considerations encompass the product lifecycle, product value and cost, return volume, and the geographic distribution of returns. II) In-house vs. third-party logistics providers: The decision between insourcing and outsourcing in reverse logistics network design is pivotal. In insourcing, a company handles the entire reverse logistics process, including material reuse. In contrast, outsourcing involves third-party providers taking on various aspects of reverse logistics. Companies may choose outsourcing due to resource constraints or lack of expertise, with the extent of outsourcing varying based on factors such as personnel skills and cost considerations. Based on the conceptual framework, the authors have constructed a mathematical model that optimizes reverse logistics network design decisions. The model will consider key factors identified in the framework, such as transportation costs, facility capacities, and lead times. The authors have employed mixed LP to find the optimal solutions that minimize costs while meeting organizational objectives.

Keywords: reverse logistics, supply chain management, optimization, e-commerce

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Authors: Ayesha Selwyn, Annapoorni Chandrashekar, Kumar Ashwarya, Nishant Baghel

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Project-based learning (PBL) activities are typically implemented in technology-enabled schools by highly trained teachers. In rural India, students have limited access to technology and quality education. Implementing typical PBL activities is challenging. This study details how Pratham Education Foundation’s Hybrid Learning model was used to implement two PBL activities related to music in 900 remote Indian villages with 46,000 students aged 10-14. The activities were completed by 69% of groups that submitted a total of 15,000 videos (completed projects). Pratham’s H-Learning model reaches 100,000 students aged 3-14 in 900 Indian villages. The community-driven model engages students in 20,000 self-organized groups outside of school. The students are guided by 6,000 youth volunteers and 100 facilitators. The students partake in learning activities across subjects with the support of community stakeholders and offline digital content on shared Android tablets. A training and implementation toolkit for PBL activities is designed by subject experts. This toolkit is essential in ensuring efficient implementation of activities as facilitators aren’t highly skilled and have limited access to training resources. The toolkit details the activity at three levels of student engagement - enrollment, participation, and completion. The subject experts train project leaders and facilitators who train youth volunteers. Volunteers need to be trained on how to execute the activity and guide students. The training is focused on building the volunteers’ capacity to enable students to solve problems, rather than developing the volunteers’ subject-related knowledge. This structure ensures that continuous intervention of subject matter experts isn’t required, and the onus of judging creativity skills is put on community members. 46,000 students in the H-Learning program were engaged in two PBL activities related to Music from April-June 2019. For one activity, students had to conduct a “musical survey” in their village by designing a survey and shooting and editing a video. This activity aimed to develop students’ information retrieval, data gathering, teamwork, communication, project management, and creativity skills. It also aimed to identify talent and document local folk music. The second activity, “Pratham Idol”, was a singing competition. Students participated in performing, producing, and editing videos. This activity aimed to develop students’ teamwork and creative skills and give students a creative outlet. Students showcased their completed projects at village fairs wherein a panel of community members evaluated the videos. The shortlisted videos from all villages were further evaluated by experts who identified students and adults to participate in advanced music workshops. The H-Learning framework enables students in low resource settings to engage in PBL and develop relevant skills by leveraging community support and using video creation as a tool. In rural India, students do not have access to high-quality education or infrastructure. Therefore designing activities that can be implemented by community members after limited training is essential. The subject experts have minimal intervention once the activity is initiated, which significantly reduces the cost of implementation and allows the activity to be implemented at a massive scale.

Keywords: community supported learning, project-based learning, self-organized learning, education technology

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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: Simone Dell'Agnello

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There are laser retroreflectors on the Moon and no laser retroreflectors on Mars. Here we describe the design, construction, qualification and imminent deployment of next-generation, optimized laser retroreflectors on the Moon and on Mars (where they will be the first ones). These instruments are positioned by time-of-flight measurements of short laser pulses, the so-called 'laser ranging' technique. Data analysis is carried out with PEP, the Planetary Ephemeris Program of CfA (Center for Astrophysics). Since 1969 Lunar Laser Ranging (LLR) to Apollo/Lunokhod laser retro-reflector (CCR) arrays supplied accurate tests of General Relativity (GR) and new gravitational physics: possible changes of the gravitational constant Gdot/G, weak and strong equivalence principle, gravitational self-energy (Parametrized Post Newtonian parameter beta), geodetic precession, inverse-square force-law; it can also constraint gravitomagnetism. Some of these measurements also allowed for testing extensions of GR, including spacetime torsion, non-minimally coupled gravity. LLR has also provides significant information on the composition of the deep interior of the Moon. In fact, LLR first provided evidence of the existence of a fluid component of the deep lunar interior. In 1969 CCR arrays contributed a negligible fraction of the LLR error budget. Since laser station range accuracy improved by more than a factor 100, now, because of lunar librations, current array dominate the error due to their multi-CCR geometry. We developed a next-generation, single, large CCR, MoonLIGHT (Moon Laser Instrumentation for General relativity high-accuracy test) unaffected by librations that supports an improvement of the space segment of the LLR accuracy up to a factor 100. INFN also developed INRRI (INstrument for landing-Roving laser Retro-reflector Investigations), a microreflector to be laser-ranged by orbiters. Their performance is characterized at the SCF_Lab (Satellite/lunar laser ranging Characterization Facilities Lab, INFN-LNF, Frascati, Italy) for their deployment on the lunar surface or the cislunar space. They will be used to accurately position landers, rovers, hoppers, orbiters of Google Lunar X Prize and space agency missions, thanks to LLR observations from station of the International Laser Ranging Service in the USA, in France and in Italy. INRRI was launched in 2016 with the ESA mission ExoMars (Exobiology on Mars) EDM (Entry, descent and landing Demonstration Module), deployed on the Schiaparelli lander and is proposed for the ExoMars 2020 Rover. Based on an agreement between NASA and ASI (Agenzia Spaziale Italiana), another microreflector, LaRRI (Laser Retro-Reflector for InSight), was delivered to JPL (Jet Propulsion Laboratory) and integrated on NASA’s InSight Mars Lander in August 2017 (launch scheduled in May 2018). Another microreflector, LaRA (Laser Retro-reflector Array) will be delivered to JPL for deployment on the NASA Mars 2020 Rover. The first lunar landing opportunities will be from early 2018 (with TeamIndus) to late 2018 with commercial missions, followed by opportunities with space agency missions, including the proposed deployment of MoonLIGHT and INRRI on NASA’s Resource Prospectors and its evolutions. In conclusion, we will extend significantly the CCR Lunar Geophysical Network and populate the Mars Geophysical Network. These networks will enable very significantly improved tests of GR.

Keywords: general relativity, laser retroreflectors, lunar laser ranging, Mars geodesy

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Authors: Teodora Vukovic, Christoph Hottiger, Noah Bubenhofer

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The development of VIAN-DH aims at bridging two linguistic approaches: conversation analysis/interactional linguistics (IL), so far a dominantly qualitative field, and computational/corpus linguistics and its quantitative and automated methods. Contemporary IL investigates the systematic organization of conversations and interactions composed of speech, gaze, gestures, and body positioning, among others. These highly integrated multimodal behaviour is analysed based on video data aimed at uncovering so called “multimodal gestalts”, patterns of linguistic and embodied conduct that reoccur in specific sequential positions employed for specific purposes. Multimodal analyses (and other disciplines using videos) are so far dependent on time and resource intensive processes of manual transcription of each component from video materials. Automating these tasks requires advanced programming skills, which is often not in the scope of IL. Moreover, the use of different tools makes the integration and analysis of different formats challenging. Consequently, IL research often deals with relatively small samples of annotated data which are suitable for qualitative analysis but not enough for making generalized empirical claims derived quantitatively. VIAN-DH aims to create a workspace where many annotation layers required for the multimodal analysis of videos can be created, processed, and correlated in one platform. VIAN-DH will provide a graphical interface that operates state-of-the-art tools for automating parts of the data processing. The integration of tools that already exist in computational linguistics and computer vision, facilitates data processing for researchers lacking programming skills, speeds up the overall research process, and enables the processing of large amounts of data. The main features to be introduced are automatic speech recognition for the transcription of language, automatic image recognition for extraction of gestures and other visual cues, as well as grammatical annotation for adding morphological and syntactic information to the verbal content. In the ongoing instance of VIAN-DH, we focus on gesture extraction (pointing gestures, in particular), making use of existing models created for sign language and adapting them for this specific purpose. In order to view and search the data, VIAN-DH will provide a unified format and enable the import of the main existing formats of annotated video data and the export to other formats used in the field, while integrating different data source formats in a way that they can be combined in research. VIAN-DH will adapt querying methods from corpus linguistics to enable parallel search of many annotation levels, combining token-level and chronological search for various types of data. VIAN-DH strives to bring crucial and potentially revolutionary innovation to the field of IL, (that can also extend to other fields using video materials). It will allow the processing of large amounts of data automatically and, the implementation of quantitative analyses, combining it with the qualitative approach. It will facilitate the investigation of correlations between linguistic patterns (lexical or grammatical) with conversational aspects (turn-taking or gestures). Users will be able to automatically transcribe and annotate visual, spoken and grammatical information from videos, and to correlate those different levels and perform queries and analyses.

Keywords: multimodal analysis, corpus linguistics, computational linguistics, image recognition, speech recognition

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Authors: Ana Fonseca, Ana Gouveia, Edgar Ramalho, Rita Henriques, Filipa Figueiredo, João Nunes

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Due to persistent climate pressures, there is a need to find a resilient economic system that is regenerative in nature. Bioeconomy offers the possibility of replacing non-renewable and non-biodegradable materials derived from fossil fuels with ones that are renewable and biodegradable, while a Circular Economy aims at sustainable and resource-efficient operations. The term "Circular Bioeconomy", which can be summarized as all activities that transform biomass for its use in various product streams, expresses the interaction between these two ideas. Portugal has a very favourable context to promote a Circular Bioeconomy due to its variety of climates and ecosystems, availability of biologically based resources, location, and geomorphology. Recently, there have been political and legislative efforts to develop the Portuguese Circular Bioeconomy. The Action Plan for a Sustainable Bioeconomy, approved in 2021, is composed of five axes of intervention, ranging from sustainable production and the use of regionally based biological resources to the development of a circular and sustainable bioindustry through research and innovation. However, as some statistics show, Portugal is still far from achieving circularity. According to Eurostat, Portugal has circularity rates of 2.8%, which is the second lowest among the member states of the European Union. Some challenges contribute to this scenario, including sectorial heterogeneity and fragmentation, prevalence of small producers, lack of attractiveness for younger generations, and absence of implementation of collaborative solutions amongst producers and along value chains.Regarding the Portuguese industrial sector, there is a tendency towards complex bureaucratic processes, which leads to economic and financial obstacles and an unclear national strategy. Together with the limited number of incentives the country has to offer to those that pretend to abandon the linear economic model, many entrepreneurs are hesitant to invest the capital needed to make their companies more circular. Absence of disaggregated, georeferenced, and reliable information regarding the actual availability of biological resources is also a major issue. Low literacy on bioeconomy among many of the sectoral agents and in society in general directly impacts the decisions of production and final consumption. The WinBio project seeks to outline a strategic approach for the management of weaknesses/opportunities in the technology transfer process, given the reality of the territory, through road mapping and national and international benchmarking. The developed work included the identification and analysis of agents in the interior region of Portugal, natural endogenous resources, products, and processes associated with potential development. Specific flow of biological wastes, possible value chains, and the potential for replacing critical raw materials with bio-based products was accessed, taking into consideration other countries with a matured bioeconomy. The study found food industry, agriculture, forestry, and fisheries generate huge amounts of waste streams, which in turn provide an opportunity for the establishment of local bio-industries powered by this biomass. The project identified biological resources with potential for replication and applicability in the Portuguese context. The richness of natural resources and potentials known in the interior region of Portugal is a major key to developing the Circular Economy and sustainability of the country.

Keywords: circular bioeconomy, interior region of portugal, regional development., public policy

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Authors: Sebastião Milton Pinheiro da Silva, Michele Barbosa da Rocha, Ana Lúcia Fernandes Campos, Miquéias Rildo de Souza Silva

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Water is an essential natural resource for life on Earth. Rivers, lakes, lagoons and dams are the main sources of water storage for human consumption. The costs of extracting and using these water sources are lower than those of exploiting groundwater on transition zones to semi-arid terrains. However, the volume of surface water has decreased over time, with the depletion of first-order drainage and the disappearance of springs, phenomena which are easily observed in the field. Climate change worsens water scarcity, compromising supply and hydric security for rural populations. To minimize the expected impacts, producing and storing water through watershed management planning requires detailed cartographic information on the relief and topography, and updated data on the stage and intensity of catchment basin environmental degradation problems. The cartography available of the Brazilian northeastern territory dates to the 70s, with topographic maps, printed, at a scale of 1:100,000 which does not meet the requirements to execute this project. Exceptionally, there are topographic maps at scales of 1:50,000 and 1:25,000 of some coastal regions in northeastern Brazil. Still, due to scale limitations and outdatedness, they are products of little utility for mapping low-order watersheds drainage and springs. Remote sensing data and geographic information systems can contribute to guiding the process of mapping and environmental recovery by integrating detailed relief and topographic data besides social and other environmental information in the Guajiru River Basin, located on the east coast of Rio Grande do Norte, on the Northeast region of Brazil. This study aimed to recognize and map catchment basin, springs and low-order drainage features along estimating morphometric parameters. Alos PALSAR and Copernicus DEM digital elevation models were evaluated and provided regional drainage features and the watersheds limits extracted with Terraview/Terrahidro 5.0 software. CBERS 4A satellite images with 2 m spatial resolution, processed with ESA SNAP Toolbox, allowed generating land use land cover map of Guajiru River. A Mappir Survey 3 multiespectral camera onboard of a DJI Phantom 4, a Mavic 2 Pro PPK Drone and an X91 GNSS receiver to collect the precised position of selected points were employed to detail mapping. Satellite images enabled a first knowledge approach of watershed areas on a more regional scale, yet very current, and drone images were essential in mapping details of catchment basins. The drone multispectral image mosaics, the digital elevation model, the contour lines and geomorphometric parameters were generated using OpenDroneMap/ODM and QGis softwares. The drone images generated facilitated the location, understanding and mapping of watersheds, recharge areas and first-order ephemeral watercourses on an adequate scale and will be used in the following project’s phases: watershed management planning, recovery and environmental protection of Rio's springs Guajiru. Environmental degradation is being analyzed from the perspective of the availability and quality of surface water supply.

Keywords: imaging, relief, UAV, water

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Authors: Ali R. Alshawawreh, Francisco Liébana-Cabanillas, Francisco J. Blanco-Encomienda

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Collaboration between marketing and business intelligence (BI) is crucial in today's ever-evolving business landscape. These two domains play pivotal roles in molding customers' experiential knowledge. Marketing insights offer valuable information regarding customer needs, preferences, and behaviors. Conversely, BI facilitates data-driven decision-making, leading to heightened operational efficiency, product quality, and customer satisfaction. Customer experiential knowledge (CEK) encompasses customers' implicit comprehension of consumption experiences influenced by diverse factors, including social and cultural influences. This study primarily focuses on telecommunications companies in Jordan, scrutinizing how experiential customer knowledge mediates the relationship between marketing intelligence and business intelligence. Drawing on theoretical frameworks such as the resource-based view (RBV) and service-dominant logic (SDL), the research aims to comprehend how organizations utilize their resources, particularly knowledge, to foster Evolution. Employing a quantitative research approach, the study collected and analyzed primary data to explore hypotheses. Structural equation modeling (SEM) facilitated by Smart PLS software evaluated the relationships between the constructs, followed by mediation analysis to assess the indirect associations in the model. The study findings offer insights into the intricate dynamics of organizational Creation, uncovering the interconnected relationships between business intelligence, customer experiential knowledge-based innovation (CEK-DI), marketing intelligence (MI), and product and service innovation (PSI), underscoring the pivotal role of advanced intelligence capabilities in developing innovative practices rooted in a profound understanding of customer experiences. Furthermore, the positive impact of BI on PSI reaffirms the significance of data-driven decision-making in shaping the innovation landscape. The significant impact of CEK-DI on PSI highlights the critical role of customer experiences in driving an organization. Companies that actively integrate customer insights into their opportunity creation processes are more likely to create offerings that match customer expectations, which drives higher levels of product and service sophistication. Additionally, the positive and significant impact of MI on CEK-DI underscores the critical role of market insights in shaping evolutionary strategies. While the relationship between MI and PSI is positive, the slightly weaker significance level indicates a subtle association, suggesting that while MI contributes to the development of ideas, In conclusion, the study emphasizes the fundamental role of intelligence capabilities, especially artificial intelligence, emphasizing the need for organizations to leverage market and customer intelligence to achieve effective and competitive innovation practices. Collaborative efforts between marketing and business intelligence serve as pivotal drivers of development, influencing customer experiential knowledge and shaping organizational strategies and practices. Future research could adopt longitudinal designs and gather data from various sectors to offer broader insights. Additionally, the study focuses on the effects of marketing intelligence, business intelligence, customer experiential knowledge, and innovation, but other unexamined variables may also influence innovation processes. Future studies could investigate additional factors, mediators, or moderators, including the role of emerging technologies like AI and machine learning in driving innovation.

Keywords: marketing intelligence, business intelligence, product, customer experiential knowledge-driven innovation

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Authors: Pradipta Chandra, Titas Bhattacharjee, Bhaskar Bhowmick

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The foundation of economy in India is primarily based on agriculture while this is the most neglected in the rural setting. More significantly, household women take part in agriculture with higher involvement. However, because of lower education of women they have limited access towards financial decisions, land ownership and technology but they have vital role towards the individual family level. There are limited studies on the institution-wise training barriers with the focus of gender disparity. The main purpose of this paper is to find out the factors of institution-wise training (non-formal education) barriers in technology transfer with the focus of participation of rural women in agriculture. For this study primary and secondary data were collected in the line of qualitative and quantitative approach. Qualitative data were collected by several field visits in the adjacent areas of Seva-Bharati, Seva Bharati Krishi Vigyan Kendra through semi-structured questionnaires. In the next level detailed field surveys were conducted with close-ended questionnaires scored on the seven-point Likert scale. Sample size was considered as 162. During the data collection the focus was to include women although some biasness from the end of respondents and interviewer might exist due to dissimilarity in observation, views etc. In addition to that the heterogeneity of sample is not very high although female participation is more than fifty percent. Data were analyzed using Exploratory Factor Analysis (EFA) technique with the outcome of three significant factors of training barriers in technology adoption by farmers: (a) Failure of technology transfer training (TTT) comprehension interprets that the technology takers, i.e., farmers can’t understand the technology either language barrier or way of demonstration exhibited by the experts/ trainers. (b) Failure of TTT customization, articulates that the training for individual farmer, gender crop or season-wise is not tailored. (c) Failure of TTT generalization conveys that absence of common training methods for individual trainers for specific crops is more prominent at the community level. The central finding is that the technology transfer training method can’t fulfill the need of the farmers under an economically challenged area. The impact of such study is very high in the area of dry lateritic and resource crunch area of Jangalmahal under Paschim Medinipur district, West Bengal and areas with similar socio-economy. Towards the policy level decision this research may help in framing digital agriculture for implementation of the appropriate information technology for the farming community, effective and timely investment by the government with the selection of beneficiary, formation of farmers club/ farm science club etc. The most important research implication of this study lies upon the contribution towards the knowledge diffusion mechanism of the agricultural sector in India. Farmers may overcome the barriers to achieve higher productivity through adoption of modern farm practices. Corporates will be interested in agro-sector through investment under corporate social responsibility (CSR). The research will help in framing public or industry policy and land use pattern. Consequently, a huge mass of rural farm-women will be empowered and farmer community will be benefitted.

Keywords: dry lateritic zone, institutional barriers, technology transfer in India, farm-women participation

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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: Hsing-Hua Stella Chang, Mong-Ching Lin, Cher-Min Fong

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There has recently been a notable rise in the number of emerging-market industrial small and medium-sized enterprises (SMEs) that have managed to upgrade their operations. Evolving from original equipment manufacturing (OEM) into value-added original or own brand manufacturing (OBM) in such firms represents a specific process of internationalization. The OEM-OBM upgrade requires development of a firm’s own brand. In this respect, the extant literature points out that emerging-market industrial marketers (latecomers) have developed some marketing capabilities, of which branding has been identified as one of the most important. In specific, an industrial non-brand marketer (OEM) marks the division of labor between manufacturing and branding (as part of marketing). In light of this discussion, this research argues that branding capability plays a critical role in supporting the evolution of manufacture upgrade. This is because a smooth transformation from OEM to OBM entails the establishment of strong brands through which branding capability is developed. Accordingly, branding capability can be exemplified as a series of processes and practices in relation to mobilizing branding resources and orchestrating branding activities, which will result in the establishment of business relationships, greater acceptance of business partners (channels, suppliers), and increased industrial brand equity in the firm as key resource advantages). For the study purpose, Taiwan was chosen as the research context, representing a typical case that exemplifies the industrial development path of more-established emerging markets, namely, transformation from OEM to OBM. This research adopted a two-phase research design comprising exploratory (a qualitative study) and confirmatory approaches (a survey study) The findings show that: Country-specific advantage is positively related to branding capability for internationalizing SMEs. Firm-specific advantage is positively related to branding capability for internationalizing SMEs. Hsing-Hua Stella Chang is Assistant Professor with National Taichung University of Education, International Master of Business Administration, (Yingcai Campus) No.227, Minsheng Rd., West Dist., Taichung City 40359, Taiwan, R.O.C. (phone: 886-22183612; e-mail: [email protected]). Mong-Ching Lin is PhD candidate with National Sun Yat-Sen University, Department of Business Management, 70 Lien-hai Rd., Kaohsiung 804, Taiwan, R.O.C. (e-mail: [email protected]). Cher-Min Fong is Full Professor with National Sun Yat-Sen University, Department of Business Management, 70 Lien-hai Rd., Kaohsiung 804, Taiwan, R.O.C. (e-mail: [email protected]). Branding capability is positively related to international performance for internationalizing SMEs. This study presents a pioneering effort to distinguish industrial brand marketers from non-brand marketers in exploring the role of branding capability in the internationalizing small and medium-sized industrial brand marketers from emerging markets. Specifically, when industrial non-brand marketers (OEMs) enter into a more advanced stage of internationalization (i.e., OBM), they must overcome disadvantages (liabilities of smallness, foreignness, outsidership) that do not apply in the case of incumbent developed-country MNEs with leading brands. Such critical differences mark the urgency and significance of distinguishing industrial brand marketers from non-brand marketers on issues relating to their value-adding branding and marketing practices in international markets. This research thus makes important contributions to the international marketing, industrial branding, and SME internationalization literature.

Keywords: brand marketers, branding capability, emerging markets, SME internationalization

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Authors: Daniele Lerede, Gianvito Colucci, Matteo Nicoli, Laura Savoldi

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The European Green Deal is the first internationally agreed set of measures to contrast climate change and environmental degradation. Besides the main target of reducing emissions by at least 55% by 2030, it sets the target of accompanying European countries through an energy transition to make the European Union into a modern, resource-efficient, and competitive net-zero emissions economy by 2050, decoupling growth from the use of resources and ensuring a fair adaptation of all social categories to the transformation process. While the general purpose to allow the realization of the purposes of the Green Deal already dates back to 2019, strategies and policies keep being developed coping with recent circumstances and achievements. However, general long-term measures like the Circular Economy Action Plan, the proposals to shift from fossil natural gas to renewable and low-carbon gases, in particular biomethane and hydrogen, and to end the sale of gasoline and diesel cars by 2035, will all have significant effects on energy supply and demand evolution across the next decades. The interactions between energy supply and demand over long-term time frames are usually assessed via energy system models to derive useful insights for policymaking and to address technological choices and research and development. TEMOA-Europe is a newly developed energy system optimization model instance based on the minimization of the total cost of the system under analysis, adopting a technologically integrated, detailed, and explicit formulation and considering the evolution of the system in partial equilibrium in competitive markets with perfect foresight. TEMOA-Europe is developed on the TEMOA platform, an open-source modeling framework totally implemented in Python, therefore ensuring third-party verification even on large and complex models. TEMOA-Europe is based on a single-region representation of the European Union and EFTA countries on a time scale between 2005 and 2100, relying on a set of assumptions for socio-economic developments based on projections by the International Energy Outlook and a large technological dataset including 7 sectors: the upstream and power sectors for the production of all energy commodities and the end-use sectors, including industry, transport, residential, commercial and agriculture. TEMOA-Europe also includes an updated hydrogen module considering its production, storage, transportation, and utilization. Besides, it can rely on a wide set of innovative technologies, ranging from nuclear fusion and electricity plants equipped with CCS in the power sector to electrolysis-based steel production processes and steel in the industrial sector – with a techno-economic characterization based on public literature – to produce insightful energy scenarios and especially to cope with the very long analyzed time scale. The aim of this work is to examine in detail the scheme of measures and policies for the realization of the purposes of the Green Deal and to transform them into a set of constraints and new socio-economic development pathways. Based on them, TEMOA-Europe will be used to produce and comparatively analyze scenarios to assess the consequences of Green Deal-related measures on the future evolution of the energy mix over the whole energy system in an economic optimization environment.

Keywords: European Green Deal, energy system optimization modeling, scenario analysis, TEMOA-Europe

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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: Christina Kirsch, Adam Hatzigiannis

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Rail operators and maintainers worldwide are increasingly replacing walking patrols in the rail corridor with mechanized track patrols -essentially data capture on trains- and on-screen reviews of track infrastructure in centralized review facilities. The benefit is that infrastructure workers are less exposed to the dangers of the rail corridor. The impact is a significant change in work design from walking track sections and direct observation in the real world to sedentary jobs in the review facility reviewing captured data on screens. Defects in rail infrastructure can have catastrophic consequences. Reviewer performance regarding accuracy and efficiency of reviews within the available time frame is essential to ensure safety and operational performance. Rail operators must optimize workload and resource loading to transition to on-screen reviews successfully. Therefore, they need to know what workload assessment methodologies will provide reliable and valid data to optimize resourcing for on-screen reviews. This paper compares objective workload measures, including track difficulty ratings and review distance covered per hour, and subjective workload assessments (NASA TLX) and analyses the link between workload and reviewer performance, including sensitivity, precision, and overall accuracy. An experimental study was completed with eight on-screen reviewers, including infrastructure workers and engineers, reviewing track sections with different levels of track difficulty over nine days. Each day the reviewers completed four 90-minute sessions of on-screen inspection of the track infrastructure. Data regarding the speed of review (km/ hour), detected defects, false negatives, and false positives were collected. Additionally, all reviewers completed a subjective workload assessment (NASA TLX) after each 90-minute session and a short employee engagement survey at the end of the study period that captured impacts on job satisfaction and motivation. The results showed that objective measures for tracking difficulty align with subjective mental demand, temporal demand, effort, and frustration in the NASA TLX. Interestingly, review speed correlated with subjective assessments of physical and temporal demand, but to mental demand. Subjective performance ratings correlated with all accuracy measures and review speed. The results showed that subjective NASA TLX workload assessments accurately reflect objective workload. The analysis of the impact of workload on performance showed that subjective mental demand correlated with high precision -accurately detected defects, not false positives. Conversely, high temporal demand was negatively correlated with sensitivity and the percentage of detected existing defects. Review speed was significantly correlated with false negatives. With an increase in review speed, accuracy declined. On the other hand, review speed correlated with subjective performance assessments. Reviewers thought their performance was higher when they reviewed the track sections faster, despite the decline in accuracy. The study results were used to optimize resourcing and ensure that reviewers had enough time to review the allocated track sections to improve defect detection rates in accordance with the efficiency-thoroughness trade-off. Overall, the study showed the importance of a multi-method approach to workload assessment and optimization, combining subjective workload assessments with objective workload and performance measures to ensure that recommendations for work system optimization are evidence-based and reliable.

Keywords: automation, efficiency-thoroughness trade-off, human factors, job design, NASA TLX, performance optimization, subjective workload assessment, workload analysis

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Authors: Faruk Ozdemir, Roy Kalawsky, Peter Hubbard

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Accurate estimation of RUL provides a basis for effective predictive maintenance, reducing unexpected downtime for industrial equipment. However, while models such as the Random Forest have effective predictive capabilities, they are the so-called ‘black box’ models, where interpretability is at a threshold to make critical diagnostic decisions involved in industries related to aviation. The purpose of this work is to present a prognostic framework that embeds Explainable Artificial Intelligence (XAI) techniques in order to provide essential transparency in Machine Learning methods' decision-making mechanisms based on sensor data, with the objective of procuring actionable insights for the aviation industry. Sensor readings have been gathered from critical equipment such as turbofan jet engine and landing gear, and the prediction of the RUL is done by a Random Forest model. It involves steps such as data gathering, feature engineering, model training, and evaluation. These critical components’ datasets are independently trained and evaluated by the models. While suitable predictions are served, their performance metrics are reasonably good; such complex models, however obscure reasoning for the predictions made by them and may even undermine the confidence of the decision-maker or the maintenance teams. This is followed by global explanations using SHAP and local explanations using LIME in the second phase to bridge the gap in reliability within industrial contexts. These tools analyze model decisions, highlighting feature importance and explaining how each input variable affects the output. This dual approach offers a general comprehension of the overall model behavior and detailed insight into specific predictions. The proposed framework, in its third component, incorporates the techniques of causal analysis in the form of Granger causality tests in order to move beyond correlation toward causation. This will not only allow the model to predict failures but also present reasons, from the key sensor features linked to possible failure mechanisms to relevant personnel. The causality between sensor behaviors and equipment failures creates much value for maintenance teams due to better root cause identification and effective preventive measures. This step contributes to the system being more explainable. Surrogate Several simple models, including Decision Trees and Linear Models, can be used in yet another stage to approximately represent the complex Random Forest model. These simpler models act as backups, replicating important jobs of the original model's behavior. If the feature explanations obtained from the surrogate model are cross-validated with the primary model, the insights derived would be more reliable and provide an intuitive sense of how the input variables affect the predictions. We then create an iterative explainable feedback loop, where the knowledge learned from the explainability methods feeds back into the training of the models. This feeds into a cycle of continuous improvement both in model accuracy and interpretability over time. By systematically integrating new findings, the model is expected to adapt to changed conditions and further develop its prognosis capability. These components are then presented to the decision-makers through the development of a fully transparent condition monitoring and alert system. The system provides a holistic tool for maintenance operations by leveraging RUL predictions, feature importance scores, persistent sensor threshold values, and autonomous alert mechanisms. Since the system will provide explanations for the predictions given, along with active alerts, the maintenance personnel can make informed decisions on their end regarding correct interventions to extend the life of the critical machinery.

Keywords: predictive maintenance, explainable artificial intelligence, prognostic, RUL, machine learning, turbofan engines, C-MAPSS dataset

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Authors: Mohamed Gazzeh, Bradley Null, Fethi Tlili, Hichem Besbes

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The burgeoning global ownership of personal vehicles has posed a significant strain on urban infrastructure, notably parking facilities, leading to traffic congestion and environmental concerns. Effective parking management systems (PMS) are indispensable for optimizing urban traffic flow and reducing emissions. The most commonly deployed systems nowadays rely on computer vision technology. This paper explores the integration of radar sensors and simulation in the context of smart parking management. We concentrate on radar sensors due to their versatility and utility in automotive applications, which extends to PMS. Additionally, radar sensors play a crucial role in driver assistance systems and autonomous vehicle development. However, the resource-intensive nature of radar data collection for algorithm development and testing necessitates innovative solutions. Simulation, particularly the monoDrive simulator, an internal development tool used by NI the Test and Measurement division of Emerson, offers a practical means to overcome this challenge. The primary objectives of this study encompass simulating radar sensors to generate a substantial dataset for algorithm development, testing, and, critically, assessing the transferability of models between simulated and real radar data. We focus on occupancy detection in parking as a practical use case, categorizing each parking space as vacant or occupied. The simulation approach using monoDrive enables algorithm validation and reliability assessment for virtual radar sensors. It meticulously designed various parking scenarios, involving manual measurements of parking spot coordinates, orientations, and the utilization of TI AWR1843 radar. To create a diverse dataset, we generated 4950 scenarios, comprising a total of 455,400 parking spots. This extensive dataset encompasses radar configuration details, ground truth occupancy information, radar detections, and associated object attributes such as range, azimuth, elevation, radar cross-section, and velocity data. The paper also addresses the intricacies and challenges of real-world radar data collection, highlighting the advantages of simulation in producing radar data for parking lot applications. We developed classification models based on Support Vector Machines (SVM) and Density-Based Spatial Clustering of Applications with Noise (DBSCAN), exclusively trained and evaluated on simulated data. Subsequently, we applied these models to real-world data, comparing their performance against the monoDrive dataset. The study demonstrates the feasibility of transferring models from a simulated environment to real-world applications, achieving an impressive accuracy score of 92% using only one radar sensor. This finding underscores the potential of radar sensors and simulation in the development of smart parking management systems, offering significant benefits for improving urban mobility and reducing environmental impact. The integration of radar sensors and simulation represents a promising avenue for enhancing smart parking management systems, addressing the challenges posed by the exponential growth in personal vehicle ownership. This research contributes valuable insights into the practicality of using simulated radar data in real-world applications and underscores the role of radar technology in advancing urban sustainability.

Keywords: autonomous vehicle simulator, FMCW radar sensors, occupancy detection, smart parking management, transferability of models

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Authors: Mozhdeh Khalili Kordabadi

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Textiles play a vital role in human life, particularly in the form of clothing. However, the alarming rate at which textiles end up in landfills presents a significant environmental risk. With approximately one garbage truck per second being filled with discarded textiles, urgent measures are required to mitigate this trend. Governments and responsible organizations are calling upon various stakeholders to shift from a linear economy to a circular economy model in the textile industry. This article highlights several key approaches that can be undertaken to address this pressing issue. These approaches include the creation of renewable raw material sources, rethinking production processes, maximizing the use and reuse of textile products, implementing reproduction and recycling strategies, exploring redistribution to new markets, and finding innovative means to extend the lifespan of textiles. By adopting these strategies, the textile industry can contribute to a more sustainable and environmentally friendly future. Introduction: Textiles, particularly clothing, are essential to human existence. However, the rapid accumulation of textiles in landfills poses a significant threat to the environment. This article explores the urgent need for the textile industry to transition from a linear economy model to a circular economy model. The linear model, characterized by the creation, use, and disposal of textiles, is unsustainable in the long term. By adopting a circular economy approach, the industry can minimize waste, reduce environmental impact, and promote sustainable practices. This article outlines key approaches that can be undertaken to drive this transition. Approaches to Address Environmental Challenges: Creation of Renewable Raw Materials Sources: Exploring and promoting the use of renewable and sustainable raw materials, such as organic cotton, hemp, and recycled fibers, can significantly reduce the environmental footprint of textile production. Rethinking Production Processes: Implementing cleaner production techniques, optimizing resource utilization, and minimizing waste generation are crucial steps in reducing the environmental impact of textile manufacturing. Maximizing Use and Reuse of Textile Products: Encouraging consumers to prolong the lifespan of textile products through proper care, maintenance, and repair services can reduce the frequency of disposal and promote a culture of sustainability. Reproduction and Recycling Strategies: Investing in innovative technologies and infrastructure to enable efficient reproduction and recycling of textiles can close the loop and minimize waste generation. Redistribution of Textiles to New Markets: Exploring opportunities to redistribute textiles to new and parallel markets, such as resale platforms, can extend their lifecycle and prevent premature disposal. Improvising Means to Extend Textile Lifespan: Encouraging design practices that prioritize durability, versatility, and timeless aesthetics can contribute to prolonging the lifespan of textiles. Conclusion: The textile industry must urgently transition from a linear economy to a circular economy model to mitigate the adverse environmental impact caused by textile waste. By implementing the outlined approaches, such as sourcing renewable raw materials, rethinking production processes, promoting reuse and recycling, exploring new markets, and extending the lifespan of textiles, stakeholders can work together to create a more sustainable and environmentally friendly textile industry. These measures require collective action and collaboration between governments, organizations, manufacturers, and consumers to drive positive change and safeguard the planet for future generations.

Keywords: textiles, circular economy, environmental challenges, renewable raw materials, production processes, reuse, recycling, redistribution, textile lifespan extension.

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