Search results for: trade integration

Authors: Syed Irfan Raza Naqvi, Zheng Jiangbin, Ahmad Moshin, Pervez Akhter

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Currently, the IoT system depends on a centralized client-servant architecture that causes various scalability and privacy vulnerabilities. Distributed ledger technology (DLT) introduces a set of opportunities for the IoT, which leads to practical ideas for existing components at all levels of existing architectures. Blockchain Technology (BCT) appears to be one approach to solving several IoT problems, like Bitcoin (BTC) and Ethereum, which offer multiple possibilities. Besides, IoTs are resource-constrained devices with insufficient capacity and computational overhead to process blockchain consensus mechanisms; the traditional BCT existing challenge for IoTs is poor scalability, energy efficiency, and transaction fees. IOTA is a distributed ledger based on Direct Acyclic Graph (DAG) that ensures M2M micro-transactions are free of charge. IOTA has the potential to address existing IoT-related difficulties such as infrastructure scalability, privacy and access control mechanisms. We proposed an architecture, SLDBI: A Scalable, lightweight DAG-based Blockchain Design for Intelligent IoT Systems, which adapts the DAG base Tangle and implements a lightweight message data model to address the IoT limitations. It enables the smooth integration of new IoT devices into a variety of apps. SLDBI enables comprehensive access control, energy efficiency, and scalability in IoT ecosystems by utilizing the Masked Authentication Message (MAM) protocol and the IOTA Smart Contract Protocol (ISCP). Furthermore, we suggest proof-of-work (PoW) computation on the full node in an energy-efficient way. Experiments have been carried out to show the capability of a tangle to achieve better scalability while maintaining energy efficiency. The findings show user access control management at granularity levels and ensure scale up to massive networks with thousands of IoT nodes, such as Smart Connected Buildings (SCBDs).

Keywords: blockchain, IOT, direct acyclic graphy, scalability, access control, architecture, smart contract, smart connected buildings

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Authors: Roberto Rosenhaim, Marcos Antonio Crus Moreira, Robson da Cunha, Gerson Gomes Cunha

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This work provides details on the wind speed behavior within cities of Arraial do Cabo and São Pedro da Aldeia located in the Lakes Region of the State of Rio de Janeiro, Brazil. This region has one of the best potentials for wind power generation. In interurban layer, wind conditions are very complex and depend on physical geography, size and orientation of buildings and constructions around, population density, and land use. In the same context, the fundamental surface parameter that governs the production of flow turbulence in urban canyons is the surface roughness. Such factors can influence the potential for power generation from the wind within the cities. Moreover, the use of wind on a small scale is not fully utilized due to complexity of wind flow measurement inside the cities. It is difficult to accurately predict this type of resource. This study demonstrates how fuzzy logic can facilitate the assessment of the complexity of the wind potential inside the cities. It presents a decision support tool and its ability to deal with inaccurate information using linguistic variables created by the heuristic method. It relies on the already published studies about the variables that influence the wind speed in the urban environment. These variables were turned into the verbal expressions that are used in computer system, which facilitated the establishment of rules for fuzzy inference and integration with an application for smartphones used in the research. In the first part of the study, challenges of the sustainable development which are described are followed by incentive policies to the use of renewable energy in Brazil. The next chapter follows the study area characteristics and the concepts of fuzzy logic. Data were collected in field experiment by using qualitative and quantitative methods for assessment. As a result, a map of the various points is presented within the cities studied with its wind viability evaluated by a system of decision support using the method multivariate classification based on fuzzy logic.

Keywords: behavior of winds, wind power, fuzzy logic, sustainable development

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Authors: Lucas L. L. Fortes, Sandro T. M. Gonçalves

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In this work, it is analyzed the wideband performance with the mesh discretization impoverishment of the Conformal Finite Difference Time-Domain (C-FDTD) approaches developed by Raj Mittra, Supriyo Dey and Wenhua Yu for the Finite Difference Time-Domain (FDTD) method. These approaches are a simple and efficient way to optimize the scattering simulation of curved surfaces for Dielectric and Perfect Electric Conducting (PEC) structures in the FDTD method, since curved surfaces require dense meshes to reduce the error introduced due to the surface staircasing. Defined, on this work, as D-FDTD-Diel and D-FDTD-PEC, these approaches are well-known in the literature, but the improvement upon their application is not quantified broadly regarding wide frequency bands and poorly discretized meshes. Both approaches bring improvement of the accuracy of the simulation without requiring dense meshes, also making it possible to explore poorly discretized meshes which bring a reduction in simulation time and the computational expense while retaining a desired accuracy. However, their applications present limitations regarding the mesh impoverishment and the frequency range desired. Therefore, the goal of this work is to explore the approaches regarding both the wideband and mesh impoverishment performance to bring a wider insight over these aspects in FDTD applications. The D-FDTD-Diel approach consists in modifying the electric field update in the cells intersected by the dielectric surface, taking into account the amount of dielectric material within the mesh cells edges. By taking into account the intersections, the D-FDTD-Diel provides accuracy improvement at the cost of computational preprocessing, which is a fair trade-off, since the update modification is quite simple. Likewise, the D-FDTD-PEC approach consists in modifying the magnetic field update, taking into account the PEC curved surface intersections within the mesh cells and, considering a PEC structure in vacuum, the air portion that fills the intersected cells when updating the magnetic fields values. Also likewise to D-FDTD-Diel, the D-FDTD-PEC provides a better accuracy at the cost of computational preprocessing, although with a drawback of having to meet stability criterion requirements. The algorithms are formulated and applied to a PEC and a dielectric spherical scattering surface with meshes presenting different levels of discretization, with Polytetrafluoroethylene (PTFE) as the dielectric, being a very common material in coaxial cables and connectors for radiofrequency (RF) and wideband application. The accuracy of the algorithms is quantified, showing the approaches wideband performance drop along with the mesh impoverishment. The benefits in computational efficiency, simulation time and accuracy are also shown and discussed, according to the frequency range desired, showing that poorly discretized mesh FDTD simulations can be exploited more efficiently, retaining the desired accuracy. The results obtained provided a broader insight over the limitations in the application of the C-FDTD approaches in poorly discretized and wide frequency band simulations for Dielectric and PEC curved surfaces, which are not clearly defined or detailed in the literature and are, therefore, a novelty. These approaches are also expected to be applied in the modeling of curved RF components for wideband and high-speed communication devices in future works.

Keywords: accuracy, computational efficiency, finite difference time-domain, mesh impoverishment

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Authors: Desplanches Maxime

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Accurate estimation of the remaining useful life of lithium-ion batteries for electronic devices is crucial. Data-driven methodologies encounter challenges related to data volume and acquisition protocols, particularly in capturing a comprehensive range of aging indicators. To address these limitations, we propose a hybrid approach that integrates an electrochemical model with state-of-the-art data analysis techniques, yielding a comprehensive database. Our methodology involves infusing an aging phenomenon into a Newman model, leading to the creation of an extensive database capturing various aging states based on non-destructive parameters. This database serves as a robust foundation for subsequent analysis. Leveraging advanced data analysis techniques, notably principal component analysis and t-Distributed Stochastic Neighbor Embedding, we extract pivotal information from the data. This information is harnessed to construct a regression function using either random forest or support vector machine algorithms. The resulting predictor demonstrates a 5% error margin in estimating remaining battery life, providing actionable insights for optimizing usage. Furthermore, the database was built from the Newman model calibrated for aging and performance using data from a European project called Teesmat. The model was then initialized numerous times with different aging values, for instance, with varying thicknesses of SEI (Solid Electrolyte Interphase). This comprehensive approach ensures a thorough exploration of battery aging dynamics, enhancing the accuracy and reliability of our predictive model. Of particular importance is our reliance on the database generated through the integration of the electrochemical model. This database serves as a crucial asset in advancing our understanding of aging states. Beyond its capability for precise remaining life predictions, this database-driven approach offers valuable insights for optimizing battery usage and adapting the predictor to various scenarios. This underscores the practical significance of our method in facilitating better decision-making regarding lithium-ion battery management.

Keywords: Li-ion battery, aging, diagnostics, data analysis, prediction, machine learning, electrochemical model, regression

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Authors: Dejenie Birile Gemeda, Wilhelm Stork

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The power system is one of the most important systems in modern society. The existing power system is approaching the critical operating limits as views of several power system operators. With the increase of load demand, high capacity and long transmission networks are widely used to meet the requirement. With the integration of renewable energies such as wind and solar, the uncertainty, intermittence bring bigger challenges to the operation of power systems. These dynamic uncertainties in the power system lead to power disturbances. The disturbances in a heavily stressed power system cause distance relays to mal-operation or false alarms during post fault power oscillations. This unintended operation of these relays may propagate and trigger cascaded trappings leading to total power system blackout. This is due to relays inability to take an appropriate tripping decision based on ensuing power swing. According to the N-1 criterion, electric power systems are generally designed to withstand a single failure without causing the violation of any operating limit. As a result, some overloaded components such as overhead transmission lines can still work for several hours under overload conditions. However, when a large power swing happens in the power system, the settings of the distance relay of zone 3 may trip the transmission line with a short time delay, and they will be acting so quickly that the system operator has no time to respond and stop the cascading. Misfiring of relays in absence of fault due to power swing may have a significant loss in economic performance, thus a loss in revenue for power companies. This research paper proposes a method to distinguish stable power swing from unstable using dynamic line rating (DLR) in response to power swing or disturbances. As opposed to static line rating (SLR), dynamic line rating support effective mitigation actions against propagating cascading outages in a power grid. Effective utilization of existing transmission lines capacity using machine learning DLR predictions will improve the operating point of distance relay protection, thus reducing unintended power outages due to power swing.

Keywords: blackout, cascading outages, dynamic line rating, power swing, overhead transmission lines

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Authors: Gabrielle Peck, Ryan Hayes

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This research presents the design and creation of a drone gas analyser, aimed at addressing the need for independent data collection and analysis of gas emissions during large-scale fires, particularly wasteland fires. The analyser drone, comprising a lightweight gas analysis system attached to a remote-controlled drone, enables the real-time assessment of smoke toxicity and the monitoring of gases released into the atmosphere during such incidents. The key components of the analyser unit included two gas line inlets connected to glass wool filters, a pump with regulated flow controlled by a mass flow controller, and electrochemical cells for detecting nitrogen oxides, hydrogen cyanide, and oxygen levels. Additionally, a non-dispersive infrared (NDIR) analyser is employed to monitor carbon monoxide (CO), carbon dioxide (CO₂), and hydrocarbon concentrations. Thermocouples can be attached to the analyser to monitor temperature, as well as McCaffrey probes combined with pressure transducers to monitor air velocity and wind direction. These additions allow for monitoring of the large fire and can be used for predictions of fire spread. The innovative system not only provides crucial data for assessing smoke toxicity but also contributes to fire prediction and management. The remote-controlled drone's mobility allows for safe and efficient data collection in proximity to the fire source, reducing the need for human exposure to hazardous conditions. The data obtained from the gas analyser unit facilitates informed decision-making by emergency responders, aiding in the protection of both human health and the environment. This abstract highlights the successful development of a drone gas analyser, illustrating its potential for enhancing smoke toxicity analysis and fire prediction capabilities. The integration of this technology into fire management strategies offers a promising solution for addressing the challenges associated with wildfires and other large-scale fire incidents. The project's methodology and results contribute to the growing body of knowledge in the field of environmental monitoring and safety, emphasizing the practical utility of drones for critical applications.

Keywords: fire prediction, drone, smoke toxicity, analyser, fire management

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Authors: Vijaya Dixit Aasheesh Dixit

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Shipbuilding industry operates in Engineer Procure Construct (EPC) context. Product mix of a shipyard comprises of various types of ships like bulk carriers, tankers, barges, coast guard vessels, sub-marines etc. Each order is unique based on the type of ship and customized requirements, which are engineered into the product right from design stage. Thus, to execute every new project, a shipyard needs to upgrade its production expertise. As a result, over the long run, holistic learning occurs across different types of projects which contributes to the knowledge base of the shipyard. Simultaneously, in the short term, during execution of a project comprising of multiple sister ships, repetition of similar tasks leads to learning at activity level. This research aims to capture above learnings of a shipyard and incorporate learning curve effect in project scheduling and materials procurement to improve project performance. Extant literature provides support for the existence of such learnings in an organization. In shipbuilding, there are sequences of similar activities which are expected to exhibit learning curve behavior. For example, the nearly identical structural sub-blocks which are successively fabricated, erected, and outfitted with piping and electrical systems. Learning curve representation can model not only a decrease in mean completion time of an activity, but also a decrease in uncertainty of activity duration. Sister ships have similar material requirements. The same supplier base supplies materials for all the sister ships within a project. On one hand, this provides an opportunity to reduce transportation cost by batching the order quantities of multiple ships. On the other hand, it increases the inventory holding cost at shipyard and the risk of obsolescence. Further, due to learning curve effect the production scheduled of each consequent ship gets compressed. Thus, the material requirement schedule of every next ship differs from its previous ship. As more and more ships get constructed, compressed production schedules increase the possibility of batching the orders of sister ships. This work aims at integrating materials management with project scheduling of long duration projects for manufacturing of multiple sister ships. It incorporates the learning curve effect on progressively compressing material requirement schedules and addresses the above trade-off of transportation cost and inventory holding and shortage costs while satisfying budget constraints of various stages of the project. The activity durations and lead time of items are not crisp and are available in the form of probabilistic distribution. A Stochastic Mixed Integer Programming (SMIP) model is formulated which is solved using evolutionary algorithm. Its output provides ordering dates of items and degree of order batching for all types of items. Sensitivity analysis determines the threshold number of sister ships required in a project to leverage the advantage of learning curve effect in materials management decisions. This analysis will help materials managers to gain insights about the scenarios: when and to what degree is it beneficial to treat a multiple ship project as an integrated one by batching the order quantities and when and to what degree to practice distinctive procurement for individual ship.

Keywords: learning curve, materials management, shipbuilding, sister ships

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Authors: Deddi Nordiawan

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Effective public policy creation required a strong budget system, both in terms of design and implementation. Performance-based Budget is an evolutionary approach with two substantial characteristics; first, the strong integration between budgeting and planning, and second, its existence as guidance so that all activities and expenditures refer to measurable performance targets. There are four processes in the government that should be followed in order to make the budget become performance-based. These four processes consist of the preparation of a vision according to the bold aspiration, the formulation of outcome, the determination of output based on the analysis of organizational resources, and the formulation of Value Creation Map that contains a series of programs and activities. This is consistent with the concept of logic model which revealed that the budget performance should be placed within a relational framework of resources, activities, outputs, outcomes and impacts. Through the issuance of Law 17/2003 regarding State Finance, local governments in Indonesia have to implement performance-based budget. Central Government then issued Government Regulation 58/2005 which contains the detail guidelines how to prepare local governments budget. After a decade, implementation of performance budgeting in local government is still not fully meet expectations, though the guidance is completed, socialization routinely performed, and trainings have also been carried out at all levels. Accordingly, this study views the practice of performance-based budget at local governments as a problematic situation. This condition must be approached with a system approach that allows the solutions from many point of views. Based on the fact that the infrastructure of budgeting has already settled, the study then considering the situation as complexity. Therefore, the intervention needs to be done in the area of human activity system. Using Soft Systems Methodology, this research will reconstruct the process of performance-based budget at local governments is area of human activity system. Through conceptual models, this study will invite all actors (central government, local government, and the parliament) for dialogue and formulate interventions in human activity systems that systematically desirable and culturally feasible. The result will direct central government in revise the guidance to local government budgeting process as well as a reference to build the capacity building strategy.

Keywords: soft systems methodology, performance-based budgeting, Indonesia, public policy

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Authors: Yasser Sanad, Thu Trang Dao

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Introduction: Implementing the One Health (OH) approach requires an integrated, interdisciplinary, and cross-sectoral methodology. OH is a key tool for developing and implementing programs and projects and includes developing ambitious policies that consider the common needs and benefits of human, animal, plant, and ecosystem health. OH helps humanity readjust its path to environmentally friendly and impartial sustainability. As co-leader of the Global Health Security Agenda’s Zoonotic Disease Action Package, Vietnam pioneered a strong OH approach to effectively address early waves of the COVID-19 outbreak in-country. Context and Aim: The repeated surges in COVID-19 in Vietnam challenged the capabilities of the national system and disclosed the gaps in multi-sectoral coordination and resilience. To address this, FHI 360 advocated for the standardization of the OH platform by government actors to increase the resiliency of the system during and post COVID-19. Methods: FHI 360 coordinated technical resources to develop and implement evidence-based OH policies, promoting high-level policy dialogue between the Ministries of Health, Agriculture, and the Environment, and policy research to inform developed policies and frameworks. Through discussions, an OH-building Partnership (OHP) was formed, linking climate change, the environment, and human and animal health. Findings: The OHP Framework created a favorable policy environment within and between sectors, as well as between governments and international health security partners. It also promoted strategic dialogue, resource mobilization, policy advocacy, and integration of international systems with National Steering Committees to ensure accountability and emphasize national ownership. Innovative contribution to policy, practice and/or research: OHP was an effective evidence-based research-to-policy platform linking to the National One Health Strategic Plan (2021-2025). Collectively they serve as a national framework for the implementation and monitoring of OH activities. Through the adoption of policies and plans, the risk of zoonotic pathogens, environmental agent spillover, and antimicrobial resistance can be minimized through strengthening multi-sectoral OH collaboration for health security.

Keywords: one health, national policies, health security, COVID-19, Vietnam

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Authors: Zhou Congling

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The integration of private tutoring has emerged as an indispensable facet in the acquisition of language proficiency beyond formal educational settings. Notably, there has been a discernible surge in the demand for private English tutoring, specifically geared towards the preparation for internationally recognized gatekeeping examinations, such as IELTS, TOEFL, GMAT, and GRE. This trajectory has engendered an escalating need for English Language Teaching Assistants (ELTAs) operating within the realm of Private Tutoring Schools (PTSs). The objective of this study is to unravel the intricate process by which these ELTAs formulate their professional identities in the nascent stages of their careers as English educators, as well as to delineate their perceptions regarding their professional trajectories. The construct of language teacher identity is inherently multifaceted, shaped by an amalgamation of individual, societal, and cultural determinants, exerting a profound influence on how language educators navigate their professional responsibilities. This investigation seeks to scrutinize the experiential and influential factors that mold the identities of ELTAs in PTSs, particularly post the culmination of their language-oriented academic programs. Employing a qualitative narrative inquiry approach, this study aims to delve into the nuanced understanding of how ELTAs conceptualize their professional identities and envision their future roles. The research methodology involves purposeful sampling and the conduct of in-depth, semi-structured interviews with ten participants. Data analysis will be conducted utilizing Barkhuizen’s Short Story Analysis, a method designed to explore a three-dimensional narrative space, elucidating the intricate interplay of personal experiences and societal contexts in shaping the identities of ELTAs. The anticipated outcomes of this study are poised to contribute substantively to a holistic comprehension of ELTA identity formation, holding practical implications for diverse stakeholders within the private tutoring sector. This research endeavors to furnish insights into strategies for the retention of ELTAs and the enhancement of overall service quality within PTSs.

Keywords: China, English language teacher, narrative inquiry, private tutoring school, teacher identity

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Authors: Raluca Cosmina Budian

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The homeless population in Spain, particularly among immigrants, has been a persistent and multifaceted issue. The government has implemented various housing public policies over the years to address homelessness, ranging from shelter programs to initiatives promoting permanent housing solutions. However, understanding the effectiveness of these policies requires insight from the very individuals and professionals directly impacted by or involved in their execution. This research sheds light on national strategies (The 2015-2020 Comprehensive National Strategy for the Homeless and National Strategy to Combat Homelessness in Spain 2023-2030) aimed at tackling homelessness in Spain, with a focus on the evolving landscape of housing public policies and their relationship with the homeless population. We investigate how these strategies have transformed over time and their impact on the inclusion of this vulnerable group. Furthermore, we explore the perspectives of homeless immigrants, distinguishing between those with an extended residency in Spain and those who have more recently arrived (less than 2 years); and distinguishing between women and men. Additionally, we incorporate insights from 13 interviews with professionals dedicated to serving the homeless population. These insights offer a deeper understanding of the intricacies of current homelessness service provision. Our findings reveal the complex dynamics of providing services to homeless individuals, and the importance of aligning these efforts with the broader national strategies for tackling homelessness. Drawing on a comprehensive dataset, we offer a nuanced view of the challenges and successes in implementing inclusive housing policies in the Spanish context. Our research highlights the importance of collaboration between policy makers, service providers and advocates to create a cohesive and effective approach. By fostering such collaboration, we aim to create a more inclusive and comprehensive strategy to address homelessness in Spain and possible affordable housing proposals for this vulnerable group. It´s only underscores the importance of tailored approaches but also contributes to the broader discourse on housing public policies' ability to address homelessness and foster integration. We suggest that a more comprehensive approach, considering the unique needs of immigrants and working in collaboration with professionals in the field, is essential for the development of effective strategies to combat homelessness and ensure the right to adequate housing for all.

Keywords: housing, homeless, public policy, Spain

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Authors: John K. Avor, Choong-Koo Chang

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The transfer of electrical loads at power generation stations from Standby Auxiliary Transformer (SAT) to Unit Auxiliary Transformer (UAT) and vice versa is through a fast bus transfer scheme. Fast bus transfer is a time-critical application where the transfer process depends on various parameters, thus transfer schemes apply advance algorithms to ensure power supply reliability and continuity. In a nuclear power generation station, supply continuity is essential, especially for critical class 1E electrical loads. Bus transfers must, therefore, be executed accurately within 4 to 10 cycles in order to achieve safety system requirements. However, the main problem is that there are instances where transfer schemes scrambled due to inaccurate interpretation of key parameters; and consequently, have failed to transfer several critical loads from UAT to the SAT during main generator trip event. Although several techniques have been adopted to develop robust transfer schemes, a combination of Artificial Neural Network and Fuzzy Systems (Neuro-Fuzzy) has not been extensively used. In this paper, we apply the concept of Neuro-Fuzzy to determine plant operating mode and dynamic prediction of the appropriate bus transfer algorithm to be selected based on the first cycle of voltage information. The performance of Sequential Fast Transfer and Residual Bus Transfer schemes was evaluated through simulation and integration of the Neuro-Fuzzy system. The objective for adopting Neuro-Fuzzy approach in the bus transfer scheme is to utilize the signal validation capabilities of artificial neural network, specifically the back-propagation algorithm which is very accurate in learning completely new systems. This research presents a combined effect of artificial neural network and fuzzy systems to accurately interpret key bus transfer parameters such as magnitude of the residual voltage, decay time, and the associated phase angle of the residual voltage in order to determine the possibility of high speed bus transfer for a particular bus and the corresponding transfer algorithm. This demonstrates potential for general applicability to improve reliability of the auxiliary power distribution system. The performance of the scheme is implemented on APR1400 nuclear power plant auxiliary system.

Keywords: auxiliary power system, bus transfer scheme, fuzzy logic, neural networks, reliability

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Authors: Ousmane Sarr

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The Senegalese coasts have high productivity of fishery resources due to the frequency of intense up-welling system that occurs along its coast, caused by the maritime trade winds making its waters nutrients rich. Fishing plays a primordial role in Senegal's socioeconomic plans and food security. However, a global diagnosis of the Senegalese maritime fishing sector has highlighted the challenges this sector encounters. Among these concerns, some significant stocks, a priority target for artisanal fishing, need further assessment. If no efforts are made in this direction, most stock will be overexploited or even in decline. It is in this context that this research was initiated. This investigation aimed to apply a multi-modal approach (LBB, Catch-only-based CMSY model and its most recent version (CMSY++); JABBA, and JABBA-Select) to assess the stock of Atlantic bonito, Sarda sarda (Bloch, 1793) in the Senegalese Exclusive Economic Zone (SEEZ). Available catch, effort, and size data from Atlantic bonito over 15 years (2004-2018) were used to calculate the nominal and standardized CPUE, size-frequency distribution, and length at retentions (50 % and 95 % selectivity) of the species. These relevant results were employed as input parameters for stock assessment models mentioned above to define the stock status of this species in this region of the Atlantic Ocean. The LBB model indicated an Atlantic bonito healthy stock status with B/BMSY values ranging from 1.3 to 1.6 and B/B0 values varying from 0.47 to 0.61 of the main scenarios performed (BON_AFG_CL, BON_GN_Length, and BON_PS_Length). The results estimated by LBB are consistent with those obtained by CMSY. The CMSY model results demonstrate that the SEEZ Atlantic bonito stock is in a sound condition in the final year of the main scenarios analyzed (BON, BON-bt, BON-GN-bt, and BON-PS-bt) with sustainable relative stock biomass (B2018/BMSY = 1.13 to 1.3) and fishing pressure levels (F2018/FMSY= 0.52 to 1.43). The B/BMSY and F/FMSY results for the JABBA model ranged between 2.01 to 2.14 and 0.47 to 0.33, respectively. In contrast, The estimated B/BMSY and F/FMSY for JABBA-Select ranged from 1.91 to 1.92 and 0.52 to 0.54. The Kobe plots results of the base case scenarios ranged from 75% to 89% probability in the green area, indicating sustainable fishing pressure and an Atlantic bonito healthy stock size capable of producing high yields close to the MSY. Based on the stock assessment results, this study highlighted scientific advice for temporary management measures. This study suggests an improvement of the selectivity parameters of longlines and purse seines and a temporary prohibition of the use of sleeping nets in the fishery for the Atlantic bonito stock in the SEEZ based on the results of the length-base models. Although these actions are temporary, they can be essential to reduce or avoid intense pressure on the Atlantic bonito stock in the SEEZ. However, it is necessary to establish harvest control rules to provide coherent and solid scientific information that leads to appropriate decision-making for rational and sustainable exploitation of Atlantic bonito in the SEEZ and the Eastern Atlantic Ocean.

Keywords: multi-model approach, stock assessment, atlantic bonito, SEEZ

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Authors: John McDowall, Lucy Lightfoot

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Stigma constitutes a significant barrier to the recovery and social integration of individuals affected by mental illness. Although there is some debate in the literature regarding the definition and utility of stigma as a concept, it is widely accepted that it comprises three components: stereotypical beliefs, prejudicial reactions, and discrimination. Stereotypical beliefs describe the cognitive knowledge-based component of stigma, referring to beliefs (often negative) about members of a group that is based on cultural and societal norms (e.g. ‘People with anxiety are just weak’). Prejudice refers to the affective/evaluative component of stigma and describes the endorsement of negative stereotypes and the resulting negative emotional reactions (e.g. ‘People with anxiety are just weak, and they frustrate me’). Discrimination refers to the behavioural component of stigma, which is arguably the most problematic, as it exerts a direct effect on the stigmatized person and may lead people to behave in a hostile or avoidant way towards them (i.e. refusal to hire them). Research exploring anti-stigma initiatives focus primarily on an educational approach, with the view that accurate information will replace misconceptions and decrease stigma. Many approaches take a biogenetic stance, emphasising brain and biochemical deficits - the idea being that ‘mental illness is an illness like any other.' While this approach tends to effectively reduce blame, it has also demonstrated negative effects such as increasing prognostic pessimism, the desire for social distance and perceptions of stereotypes. In the present study 144 participants were split into three groups and read one of three vignettes presenting causal explanations for Generalised Anxiety Disorder (GAD): One explanation emphasized biogenetic factors as being important in the etiology of GAD, another emphasised psychosocial factors (e.g. aversive life events, poverty, etc.), and a third stressed the adaptive features of the disorder from an evolutionary viewpoint. A variety of measures tapping the various components of stigma were administered following the vignettes. No difference in stigma measures as a function of causal explanation was found. People who had contact with mental illness in the past were significantly less stigmatising across a wide range of measures, but this did not interact with the type of causal explanation.

Keywords: generalised anxiety disorder, discrimination, prejudice, stigma

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Authors: Khushboo Shah

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Categorical bans on the death penalty and life-without-parole sentences for juvenile offenders in a growing number of countries have established a new era in juvenile jurisprudence. This has been brought about by integration of the growing knowledge in cognitive neuroscience and appreciation of the inherent differences between adults and adolescents over the last ten years. This evolving understanding of being a child in the criminal system can be aptly reflected through policies that incorporate the mitigating traits of youth. First, the presentation will delineate the structures in cognitive neuroscience and in particular, focus on the prefrontal cortex, the amygdala, and the basal ganglia. These key anatomical structures in the brain are linked to three mitigating adolescent traits—an underdeveloped sense of responsibility, an increased vulnerability to negative influences, and transitory personality traits—that establish why juveniles have a lessened culpability. The discussion will delve into the details depicting how an underdeveloped prefrontal cortex results in the heightened emotional angst, high-energy and risky behavior characteristic of the adolescent time period or how the amygdala, the emotional center of the brain, governs different emotional expression resulting in why teens are susceptible to negative influences. Based on this greater understanding, it is incumbent that policies adequately reflect the adolescent physiology and psychology in the criminal system. However, it is important to ensure that these views are appropriately weighted while considering the jurisprudence for the treatment of children in the law. To ensure this balance is appropriately stricken, policies must incorporate the distinctive traits of youth in sentencing and legal considerations and yet refrain from the potential fallacies of absolving a juvenile offender of guilt and culpability. Accordingly, three policies will demonstrate how these results can be achieved: (1) eliminate housing of juvenile offenders in the adult prison system, (2) mandate fitness hearings for all transfers of juveniles to adult criminal court, and (3) use the post-disposition review as a type of rehabilitation method for juvenile offenders. Ultimately, this interdisciplinary approach of science and law allows for a better understanding of adolescent psychological and social functioning and can effectuate better legal outcomes for juveniles tried as adults.

Keywords: criminal law, Juvenile Justice, interdisciplinary, neuroscience

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Authors: Jiri Nepereny, Vladimir Vrzal

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Staphylococcus intermedius/pseudintermedius bacteria are commonly found on the skin of healthy dogs and can cause pruritic skin diseases under certain circumstances (trauma, allergy, immunodeficiency, ectoparasitosis, endocrinological diseases, glucocorticoid therapy, etc.). These can develop into complicated superficial or deep pyoderma, which represent a large group of problematic skin diseases in dogs. These are predominantly inflammations of a secondary nature, associated with the occurrence of coagulase-positive Staphylococcus spp. A major problem is increased itching, which greatly complicates the healing process. The aim of this work is to verify the efficacy of the developed preparation Bacteriophage SI (Staphylococcus intermedius). The tested preparation contains a lysate of bacterial cells of S. intermedius host culture including culture medium and live virions of specific phage. Sodium Merthiolate is added as a preservative in a safe concentration. Validation of the efficacy of the product was demonstrated by monitoring the therapeutic effect after application to indicated cases from clinical practice. The indication for inclusion of the patient into the trial was an adequate history and clinical examination accompanied by sample collection for bacteriological examination and isolation of the specific causative agent. Isolate identification was performed by API BioMérieux identification system (API ID 32 STAPH) and rep-PCR typing. The suitability of therapy for a specific case was confirmed by in vitro testing of the lytic ability of the bacteriophage to lyse the specific isolate = formation of specific plaques on the culture isolate on the surface of the solid culture medium. So far, a total of 32 dogs of different sexes, ages and breed affiliations with different symptoms of staphylococcal dermatitis have been included in the testing. Their previous therapy consisted of more or less successful systemic or local application of broad-spectrum antibiotics. The presence of S. intermedius/pseudintermedius has been demonstrated in 26 cases. The isolates were identified as a S. pseudintermedius, in all cases. Contaminant bacterial microflora was always present in the examined samples. The test product was applied subcutaneously in gradually increasing doses over a period of 1 month. After improvement in health status, maintenance therapy was followed by application of the product once a week for 3 months. Adverse effects associated with the administration of the product (swelling at the site of application) occurred in only 2 cases. In all cases, there was a significant reduction in clinical signs (healing of skin lesions and reduction of inflammation) after therapy and an improvement in the well-being of the treated animals. A major problem in the treatment of pyoderma is the frequent resistance of the causative agents to antibiotics, especially the increasing frequency of multidrug-resistant and methicillin-resistant S. pseudintermedius (MRSP) strains. Specific phagolysate using for the therapy of these diseases could solve this problem and to some extent replace or reduce the use of antibiotics, whose frequent and widespread application often leads to the emergence of resistance. The advantage of the therapeutic use of bacteriophages is their bactericidal effect, high specificity and safety. This work was supported by Project FV40213 from Ministry of Industry and Trade, Czech Republic.

Keywords: bacteriophage, pyoderma, staphylococcus spp, therapy

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

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Geothermal reservoirs (GTRs) have garnered global recognition as a sustainable energy source. The Thermo-Hydro-Mechanical-Chemical (THMC) integration coupling proves to be a practical and effective method for optimizing production in GTRs. The study outcomes demonstrate that THMC coupling serves as a versatile and valuable tool, offering in-depth insights into GTRs and enhancing their operational efficiency. This is achieved through temperature analysis and pressure changes and their impacts on mechanical properties, structural integrity, fracture aperture, permeability, and heat extraction efficiency. Moreover, THMC coupling facilitates potential benefits assessment and risks associated with different geothermal technologies, considering the complex thermal, hydraulic, mechanical, and chemical interactions within the reservoirs. However, THMC-coupling utilization in GTRs presents a multitude of challenges. These challenges include accurately modeling and predicting behavior due to the interconnected nature of processes, limited data availability leading to uncertainties, induced seismic events risks to nearby communities, scaling and mineral deposition reducing operational efficiency, and reservoirs' long-term sustainability. In addition, material degradation, environmental impacts, technical challenges in monitoring and control, accurate assessment of resource potential, and regulatory and social acceptance further complicate geothermal projects. Addressing these multifaceted challenges is crucial for successful geothermal energy resources sustainable utilization. This paper aims to illuminate the challenges and opportunities associated with THMC coupling in enhanced geothermal systems. Practical solutions and strategies for mitigating these challenges are discussed, emphasizing the need for interdisciplinary approaches, improved data collection and modeling techniques, and advanced monitoring and control systems. Overcoming these challenges is imperative for unlocking the full potential of geothermal energy making a substantial contribution to the global energy transition and sustainable development.

Keywords: geothermal reservoirs, THMC coupling, interdisciplinary approaches, challenges and opportunities, sustainable utilization

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Authors: Chiao-Yi Chen, Dung-Ying Lin

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With the growing awareness of environmental protection and the implementation of government carbon reduction policies, the number of electric vehicles (EVs) has rapidly increased, leading to a surge in charging demand and imposing significant challenges on the existing power grid’s capacity. Traditional urban power grid planning has not adequately accounted for the additional load generated by EV charging, which often strains the infrastructure. This study aims to optimize grid operation and load management by dynamically adjusting EV charging prices based on real-time electricity supply and demand, leveraging consumer demand elasticity to enhance system efficiency. This study uniquely addresses the intricate interplay between urban traffic patterns and power grid dynamics in the context of electric vehicle (EV) adoption. By integrating Hsinchu City's road network with the IEEE 33-bus system, the research creates a comprehensive model that captures both the spatial and temporal aspects of EV charging demand. This approach allows for a nuanced analysis of how traffic flow directly influences the load distribution across the power grid. The strategic placement of charging stations at key nodes within the IEEE 33-bus system, informed by actual road traffic data, enables a realistic simulation of the dynamic relationship between vehicle movement and energy consumption. This integration of transportation and energy systems provides a holistic view of the challenges and opportunities in urban EV infrastructure planning, highlighting the critical need for solutions that can adapt to the ever-changing interplay between traffic patterns and grid capacity. The proposed dynamic pricing strategy effectively reduces peak charging loads, enhances the operational efficiency of charging stations, and maximizes operator profits, all while ensuring grid stability. These findings provide practical insights and a valuable framework for optimizing EV charging infrastructure and policies in future smart cities, contributing to more resilient and sustainable urban energy systems.

Keywords: dynamic pricing, demand elasticity, EV charging, grid load balancing, optimization

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Authors: A. Vahanyan

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The paper touches upon the problem of revision and modernization of the current curriculum on translation studies at the Armenian Higher Education Institutions (HEIs). In the contemporary world where quality and speed of services provided are mostly valued, certain higher education centers in Armenia though do not demonstrate enough flexibility in terms of the revision and amendment of courses taught. This issue is present for various curricula at the university level and Translation Studies related curriculum, in particular. Technological innovations that are of great help for translators have been long ago smoothly implemented into the global Translation Industry. According to the European Master's in Translation (EMT) framework, translation service provision comprises linguistic, intercultural, information mining, thematic, and technological competencies. Therefore, to form the competencies mentioned above, the curriculum should be seriously restructured to meet the modern education and job market requirements, relevant courses should be proposed. New courses, in particular, should focus on the formation of technological competences. These suggestions have been made upon the author’s research of the problem across various HEIs in Armenia. The updated curricula should include courses aimed at familiarization with various computer-assisted translation (CAT) tools (MemoQ, Trados, OmegaT, Wordfast, etc.) in the translation process, creation of glossaries and termbases compatible with different platforms), which will ensure consistency in translation of similar texts and speeding up the translation process itself. Another aspect that may be strengthened via curriculum modification is the introduction of interdisciplinary and Project-Based Learning courses, which will enable info mining and thematic competences, which are of great importance as well. Of course, the amendment of the existing curriculum with the mentioned courses will require corresponding faculty development via training, workshops, and seminars. Finally, the provision of extensive internship with translation agencies is strongly recommended as it will ensure the synthesis of theoretical background and practical skills highly required for the specific area. Summing up, restructuring and modernization of the existing curricula on Translation Studies should focus on three major aspects, i.e., introduction of new courses that meet the global quality standards of education, professional development for faculty, and integration of extensive internship supervised by experts in the field.

Keywords: competencies, curriculum, modernization, technical literacy, translation studies

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Authors: Chan Yan Nok

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The present study is a qualitative study based on the coping experiences of six Hong Kong Chinese mothers who had childhood trauma from their first-person perspective. Expanding the perspective beyond the dominant discourse of “inter-generation transmission of trauma”, this study explores the experiences and meanings of child trauma embedded in their narratives through the process of thematic analysis and narrative analysis. The interviewees painted a nuanced picture of their process of coping and trauma resolution. First, acknowledgement; second, feel safe and start to tell the story of trauma; third, feel the feelings and expression of emotions; fourth, clarifying and coping with the impacts of trauma; fifth, integration and transformation; and sixth, using their new understanding of experience to have a better life. It was seen that there was no “end” within the process of trauma resolution. Instead, this is an ongoing process with positive healing trajectory. Analysis of the stories of the mothers revealed recurrent themes around continuous self-reflective awareness in the process of trauma coping. Rather than being necessarily negative and detrimental, childhood trauma could highlight the meanings of being a mother and reveal opportunities for continuous personal growth and self-enhancement. Utilizing the sense of inadequacy as a core driver in the trauma recovery process while developing a heightened awareness of the unfinished business embedded in their “automatic pattern” of behaviors, emotions, and thoughts can help these mothers become more flexible to formulate new methods in facing future predicaments. Future social work and parent education practices should help mothers deal with unresolved trauma, make sense of their impacts of childhood trauma and discover the growth embedded in the past traumatic experience. They should be facilitated in “acknowledging the reality of the trauma”, including understanding their complicated emotions arising from the traumatic experiences and voicing their struggles. In addition, helping these mothers to be aware of short-term and long-term trauma impacts (i.e., secondary responses to the trauma) and explore their effective coping strategies in “overcoming secondary responses to the trauma” are crucial for their future positive adjustment and transformation. Through affirming their coping abilities and lessons learnt from past experiences, mothers can reduce feelings of shame and powerlessness and enhance their parental capacity.

Keywords: childhood trauma, coping, mothers, self-awareness, self-reflection, trauma resolution

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Authors: Mihaela Munteanu (Pila), Silvius Stanciu

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This paper presents the aspects of the official control of fishery in the Republic of Moldova. Currently, the regulations and the activity of national institutions with responsibilities in the field of food quality are in a process of harmonization with the European rules, aiming at European integration, quality improvement and providing a higher level of food safety. The National Agency for Food Safety is the main national body with responsibilities in the field of food safety. In the field of fishery products, the Agency carries out an intensive activity of informing the citizen and controlling the products marketed. The paper presents the dangers related to the consumption of fish and fishery products traded on the national market, the sanitary-veterinary inspections conducted by the profile institution and the improper situations identified. The national market of fishery products depends largely on imports, mainly focused on ocean fish. The research carried out has shown that during the period 2011-2018, following the inspections carried out on fishery products traded on the national market, a number of inconsistencies have been identified. Thus, indigenous products were frequently detected with sensory characteristics unfit for consumption, and being commercialized in inappropriate locations or contaminated with chemical pollutants. On import products controlled, the most frequent inconsistent situations have been represented by inconsistent sensory aspects and by parasite contamination. Taking into account the specific aspects of aquatic products, including the high level of alterability, special conditions of growth, marketing, culinary preparation and consumption are necessary in order to decrease the risk of disease over the population. Certificates, attestations and other documents certifying the quality of batches, completed by additional laboratory examinations, are necessary in order to increase the level of confidence on the quality of products marketed in the Republic. The implementation of various control procedures and mechanisms at national level, correlated with the focused activity of the specialized institutions, can decrease the risk of contamination and avoid cases of disease on the population due to the consumption of fishery products.

Keywords: fishery products, food safety, quality control, Republic of Moldova

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Authors: Sidong Zhao, Xingping Wang

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Recently, the government of China has provided strong support the developments of overseas industrial parks. The global distribution of China overseas industrial parks has gradually moved from the 'sparks of fire' to the 'prairie fires.' The support and distribution have promoted developing overseas industrial parks to a strategy of constructing a China's new open economic system and a typical representative of the 'Chinese wisdom' and the 'China's plans' that China has contributed to the globalization of the new era under the initiative of the Belt and Road. As the industrial parks are the basis of 'work/employment', a basic function of a city (Athens Constitution), planning for developments of industrial parks has become a long-term focus of urban planning. Based on the research of the planning and the analysis of the present developments of some typical China overseas industrial parks, we found some interesting rules: First, large numbers of the China overseas industrial parks are located in less developed countries. These industrial parks have become significant drives of the developments of the host cities and even the regions in those countries, especially in investment, employment and paid tax fee for the local, etc. so, the planning and development of overseas industrial parks have received extensive attention. Second, there are some problems in the small part of the overseas Park, such as the planning of the park not following the planning of the host city and lack of implementation of the park planning, etc. These problems have led to the difficulties of the implementation of the planning and the sustainable developments of the parks. Third, a unique pattern of space development has been formed. in the dimension of the patterns of regional spatial distribution, there are five characteristics - along with the coast, along the river, along with the main traffic lines and hubs, along with the central urban area and along the connections of regions economic. In the dimension of the spatial relationships between the industrial park and the city, there is a growing and evolving trend as 'separation – integration - union'. In the dimension of spatial mode of the industrial parks, there are different patterns of development, such as a specialized industrial park, complex industrial park, characteristic town and new urban area of industry, etc. From the perspective of the trends of the developments and spatial modes, in the future, the planning of China overseas industrial parks should emphasize the idea of 'building a city based on the industrial park'. In other words, it's making the developments of China overseas industrial parks move from 'driven by policy' to 'driven by the functions of the city', accelerating forming the system of China overseas industrial parks and integrating the industrial parks and the cities.

Keywords: overseas industrial park, spatial mode, planning, China

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Authors: Dohun Kim

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Technological innovations have stimulated flipped learning in many disciplines, including language teaching. It is a specific type of blended learning, which combines onsite (i.e. face-to-face) with online experiences to produce effective, efficient and flexible learning. Flipped learning literally ‘flips’ conventional teaching and learning activities upside down: it leverages technologies to deliver a lecture and direct instruction—other asynchronous activities as well—outside the classroom to reserve onsite time for interaction and activities in the upper cognitive realms: applying, analysing, evaluating and creating. Unlike the conventional flipped approaches, which focused on video lecture, followed by face-to-face or on-site session, new innovative methods incorporate various means and structures to serve the needs of different academic disciplines and classrooms. In the light of such innovations, this study adopted ‘student-engaged’ approaches to interpreter training and contrasts them with traditional classrooms. To this end, students were also encouraged to engage in asynchronous activities online, and innovative technologies, such as Telepresence, were employed. Based on the class implementation, a thorough examination was conducted to examine how we can structure and implement flipped classrooms for language and interpreting training while actively engaging learners. This study adopted a quantitative research method, while complementing it with a qualitative one. The key findings suggest that the significance of the instructor’s role does not dwindle, but his/her role changes to a moderator and a facilitator. Second, we can apply flipped learning to both theory- and practice-oriented modules. Third, students’ integration into the community of inquiry is of significant importance to foster active and higher-order learning. Fourth, cognitive presence and competence can be enhanced through strengthened and integrated teaching and social presences. Well-orchestrated teaching presence stimulates students to find out the problems and voices the convergences and divergences, while fluid social presence facilitates the exchanges of knowledge and the adjustment of solutions, which eventually contributes to consolidating cognitive presence—a key ingredient that enables the application and testing of the solutions and reflection thereon.

Keywords: blended learning, Community of Inquiry, flipped learning, interpreter training, student-centred learning

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Authors: Oluwatosin Adewale

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The sustainability of built heritage has become a relevant issue in recent years due to the social and economic values associated with these buildings. Heritage buildings provide a means for human perception of culture and represent a legacy of long-existing history; they define the local character of the social world and provide a vital connection to the past with their associated aesthetical and communal benefits. The identified values of heritage buildings have increased the importance of conservation and the lifecycle management of these buildings. The recent developments of digital design technology in engineering and the built environment have led to the adoption of Building Information Modelling (BIM) by the Architecture, Engineering, Construction, and Operations (AECO) industry. BIM provides a platform for the lifecycle management of a construction project through effective collaboration among stakeholders and the analysis of a digital information model. This growth in digital design technology has also made its way into the field of architectural heritage management in the form of Historic Building Information Modelling (HBIM). A reverse engineering process for digital documentation of heritage assets that draws upon similar information management processes as the BIM process. However, despite the several scientific and technical contributions made to the development of the HBIM process, it doesn't remain easy to integrate at the most practical level of heritage asset management. The main objective identified under the scope of the study is to review the limitations and challenges faced by heritage management professionals in adopting an HBIM-based asset management procedure for historic building projects. This paper uses an exploratory study in the form of semi-structured interviews to investigate the research problem. A purposive sample of heritage industry experts and professionals were selected to take part in a semi-structured interview to appraise some of the limitations and challenges they have faced with the integration of HBIM into their project workflows. The findings from this study will present the challenges and limitations faced in applying and integrating the HBIM concept for the management of historic buildings.

Keywords: building information modelling, built heritage, heritage asset management, historic building information modelling, lifecycle management

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Authors: Pranav Gunhal., Krish Jhurani

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This study tackles the significant computational challenge of predicting excited state dynamics in organic photovoltaic (OPV) materials—a pivotal factor in the performance of solar energy solutions. Time-dependent density functional theory (TDDFT), though effective, is computationally prohibitive for larger and more complex molecules. As a solution, the research explores the application of transformer neural networks, a type of artificial intelligence (AI) model known for its superior performance in natural language processing, to predict excited state dynamics in OPV materials. The methodology involves a two-fold process. First, the transformer model is trained on an extensive dataset comprising over 10,000 TDDFT calculations of excited state dynamics from a diverse set of OPV materials. Each training example includes a molecular structure and the corresponding TDDFT-calculated excited state lifetimes and key electronic transitions. Second, the trained model is tested on a separate set of molecules, and its predictions are rigorously compared to independent TDDFT calculations. The results indicate a remarkable degree of predictive accuracy. Specifically, for a test set of 1,000 OPV materials, the transformer model predicted excited state lifetimes with a mean absolute error of 0.15 picoseconds, a negligible deviation from TDDFT-calculated values. The model also correctly identified key electronic transitions contributing to the excited state dynamics in 92% of the test cases, signifying a substantial concordance with the results obtained via conventional quantum chemistry calculations. The practical integration of the transformer model with existing quantum chemistry software was also realized, demonstrating its potential as a powerful tool in the arsenal of materials scientists and chemists. The implementation of this AI model is estimated to reduce the computational cost of predicting excited state dynamics by two orders of magnitude compared to conventional TDDFT calculations. The successful utilization of transformer neural networks to accurately predict excited state dynamics provides an efficient computational pathway for the accelerated discovery and design of new OPV materials, potentially catalyzing advancements in the realm of sustainable energy solutions.

Keywords: transformer neural networks, organic photovoltaic materials, excited state dynamics, time-dependent density functional theory, predictive modeling

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Authors: Linyao Qiu, Zhiqiang Du

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As the rapid development of urbanization, economic developments, and steady population growth in China, the widespread devastation, economic damages, and loss of human lives caused by numerous forms of natural disasters are becoming increasingly serious every year. Disaster management requires available and effective cooperation of different roles and organizations in whole process including mitigation, preparedness, response and recovery. Due to the imbalance of regional development in China, the disaster management capabilities of national and provincial disaster reduction centers are uneven. When an undeveloped area suffers from disaster, neither local reduction department could get first-hand information like high-resolution remote sensing images from satellites and aircrafts independently, nor sharing mechanism is provided for the department to access to data resources deployed in other place directly. Most existing disaster management systems operate in a typical passive data-centric mode and work for single department, where resources cannot be fully shared. The impediment blocks local department and group from quick emergency response and decision-making. In this paper, we introduce a collaborative platform for distributed disaster reduction. To address the issues of imbalance of sharing data sources and technology in the process of disaster reduction, we propose a multi-role oriented collaboration business mechanism, which is capable of scheduling and allocating for optimum utilization of multiple resources, to link various roles for collaborative reduction business in different place. The platform fully considers the difference of equipment conditions in different provinces and provide several service modes to satisfy technology need in disaster reduction. An integrated collaboration system based on focusing services mechanism is designed and implemented for resource scheduling, functional integration, data processing, task management, collaborative mapping, and visualization. Actual applications illustrate that the platform can well support data sharing and business collaboration between national and provincial department. It could significantly improve the capability of disaster reduction in China.

Keywords: business collaboration, data sharing, distributed disaster reduction, focusing service

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Authors: Jingwen Ou

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Writing for academic purposes in a second or foreign language poses a significant challenge for non-native speakers, particularly at the tertiary level, where English academic writing for L2 students is often hindered by difficulties in academic discourse, including vocabulary, academic register, and organization. The past two decades have witnessed a rising popularity in the application of the data-driven learning (DDL) approach in EAP writing instruction. In light of such a trend, this study aims to enhance the integration of DDL into English for academic purposes (EAP) writing classrooms by investigating the perception of Chinese college students regarding the use of corpus tools for improving EAP writing. Additionally, the research explores their corpus consultation behaviors during training to provide insights into corpus-assisted EAP instruction for DDL practitioners. Given the uprising popularity of DDL, this research aims to investigate Chinese university students’ use of corpus tools with three main foci: 1) the influence of corpus tools on learning behaviours, 2) the influence of corpus tools on students’ academic writing performance outcomes, and 3) students’ perceptions and potential perceptional changes towards the use of such tools. Three corpus tools, CQPWeb, Sketch Engine, and LancsBox X, are selected for investigation due to the scarcity of empirical research on patterns of learners’ engagement with a combination of multiple corpora. The research adopts a pre-test / post-test design for the evaluation of students’ academic writing performance before and after the intervention. Twenty participants will be divided into two groups: an intervention and a non-intervention group. Three corpus training workshops will be delivered at the beginning, middle, and end of a semester. An online survey and three separate focus group interviews are designed to investigate students’ perceptions of the use of corpus tools for improving academic writing skills, particularly the rhetorical functions in different essay sections. Insights from students’ consultation sessions indicated difficulties with DDL practice, including insufficiency of time to complete all tasks, struggle with technical set-up, unfamiliarity with the DDL approach and difficulty with some advanced corpus functions. Findings from the main study aim to provide pedagogical insights and training resources for EAP practitioners and learners.

Keywords: corpus linguistics, data-driven learning, English for academic purposes, tertiary education in China

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Authors: Sophie Lemoussu, Jean-Charles Chaudemar, Robertus A. Vingerhoeds

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Many innovative projects exist in the field of aeronautics, each addressing specific areas so to reduce weight, increase autonomy, reduction of CO2, etc. In many cases, such innovative developments are being carried out by very small enterprises (VSE’s) or small and medium sized-enterprises (SME’s). A good example concerns airships that are being studied as a real alternative to passenger and cargo transportation. Today, no international regulations propose a precise and sufficiently detailed framework for the development and certification of airships. The absence of such a regulatory framework requires a very close contact with regulatory instances. However, VSE’s/SME’s do not always have sufficient resources and internal knowledge to handle this complexity and to discuss these issues. This poses an additional challenge for those VSE’s/SME’s, in particular those that have system integration responsibilities and that must provide all the necessary evidence to demonstrate their ability to design, produce, and operate airships with the expected level of safety and reliability. The main objective of this research is to provide a methodological framework enabling VSE’s/SME’s with limited resources to organize the development of airships while taking into account the constraints of safety, cost, time and performance. This paper proposes to provide a contribution to this problematic by proposing a Model-Based Systems Engineering approach. Through a comprehensive process modeling approach applied to the development processes, the regulatory constraints, existing best practices, etc., a good image can be obtained as to the process landscape that may influence the development of airships. To this effect, not only the necessary regulatory information is taken on board, also other international standards and norms on systems engineering and project management are being modeled and taken into account. In a next step, the model can be used for analysis of the specific situation for given developments, derive critical paths for the development, identify eventual conflicting aspects between the norms, standards, and regulatory expectations, or also identify those areas where not enough information is available. Once critical paths are known, optimization approaches can be used and decision support techniques can be applied so to better support VSE’s/SME’s in their innovative developments. This paper reports on the adopted modeling approach, the retained modeling languages, and how they all fit together.

Keywords: aeronautics, certification, process modeling, project management, regulation, SME, systems engineering, VSE

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Authors: Marzouk Benali, Jawad Jeaidi, Behrang Mansoornejad, Olumoye Ajao, Banafsheh Gilani, Nima Ghavidel Mehr

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Canadian forest industry is seeking to identify and implement transformational strategies for enhanced financial performance through the emerging bioeconomy or more specifically through the concept of the biorefinery. For example, processing forest residues or surplus of biomass available on the mill sites for the production of biofuels, biochemicals and/or biomaterials is one of the attractive strategies along with traditional wood and paper products and cogenerated energy. There are many possible process-product biorefinery pathways, each associated with specific product portfolios with different levels of risk. Thus, it is not obvious which unique strategy forest industry should select and implement. Therefore, there is a need for analytical and design tools that enable evaluating biorefinery strategies based on a set of criteria considering a perspective of sustainability over the short and long terms, while selecting the existing core products as well as selecting the new product portfolio. In addition, it is critical to assess the manufacturing flexibility to internalize the risk from market price volatility of each targeted bio-based product in the product portfolio, prior to invest heavily in any biorefinery strategy. The proposed paper will focus on introducing a systematic methodology for designing integrated biorefineries using process systems engineering tools as well as a multi-criteria decision making framework to put forward the most effective biorefinery strategies that fulfill the needs of the forest industry. Topics to be covered will include market analysis, techno-economic assessment, cost accounting, energy integration analysis, life cycle assessment and supply chain analysis. This will be followed by describing the vision as well as the key features and functionalities of the I-BIOREF software platform, developed by CanmetENERGY of Natural Resources Canada. Two industrial case studies will be presented to support the robustness and flexibility of I-BIOREF software platform: i) An integrated Canadian Kraft pulp mill with lignin recovery process (namely, LignoBoost™); ii) A standalone biorefinery based on ethanol-organosolv process.

Keywords: biorefinery strategies, bioproducts, co-production, multi-criteria decision making, tool

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Authors: Xukai Fu

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The concept of circular economy is interdisciplinary, intersecting environmental engineering, information technology, business, and social science domains. Over the course of its 15-year tenure in the sanitation industry, Jinkai has concentrated its efforts in the past five years on integrating artificial intelligence (AI) technology with street sanitation apparatus and systems. This endeavor has led to the development of various innovations, including the Intelligent Identification Sweeper Truck (Intelligent Waste Recognition and Energy-saving Control System), the Intelligent Identification Water Truck (Intelligent Flushing Control System), the intelligent food waste treatment machine, and the Intelligent City Road Sanitation Surveillance Platform. This study will commence with an examination of prevalent global challenges, elucidating how Jinkai effectively addresses each within the framework of circular economy principles. Utilizing a review and analysis of pertinent environmental management data, we will elucidate Jinkai's strategic approach. Following this, we will investigate how Jinkai utilizes the advantages of circular economy principles to guide the design of street sanitation machinery, with a focus on digitalization integration. Moreover, we will scrutinize Jinkai's sustainable practices throughout the invention and operation phases of street sanitation machinery, aligning with the triple bottom line theory. Finally, we will delve into the significance and enduring impact of corporate social responsibility (CSR) and environmental, social, and governance (ESG) initiatives. Special emphasis will be placed on Jinkai's contributions to community stakeholders, with a particular emphasis on human rights. Despite the widespread adoption of circular economy principles across various industries, achieving a harmonious equilibrium between environmental justice and social justice remains a formidable task. Jinkai acknowledges that the mere development of energy-saving technologies is insufficient for authentic circular economy implementation; rather, they serve as instrumental tools. To earnestly promote and embody circular economy principles, companies must consistently prioritize the UN Sustainable Development Goals and adapt their technologies to address the evolving exigencies of our world.

Keywords: circular economy, core principles, benefits, the tripple bottom line, CSR, ESG, social justice, human rights, Jinkai

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