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The primary objective of this research paper is to conduct a comprehensive investigation into the process of developing briefs for Public–Private Partnership (PPP) projects. The study aims to outline the fundamental stages, standard processes, and critical decision points involved in this process. This is achieved through a comparative analysis of briefing frameworks used in three countries that are among the top in the PPP Market Maturity chart: The United Kingdom, Australia, and Canada. The paper discusses the stages and decision points within these countries' briefing processes, highlighting their challenges, similarities, and differences. It emphasizes the fundamental role of effective communication and coordination in PPP projects, which involve multiple stakeholders. By examining these interconnected activities and analyzing the phases, stages, and key processes constituting the briefing process, the study provides valuable insights into the PPP briefing processes in these nations. The paper concludes by proposing a conceptual process framework for brief development in PPP projects, which will be further tailored for adaptation in the PPP market in the United Arab Emirates. [ABSTRACT FROM AUTHOR]

AI chatbots have emerged as powerful tools for providing text-based solutions to a wide range of everyday challenges. Selecting the appropriate chatbot is crucial for optimising outcomes. This paper presents a comprehensive comparative analysis of five leading chatbots: ChatGPT, Bard, Llama, Ernie, and Grok. The analysis is based on a systematic review of 28 scholarly articles. The review indicates that ChatGPT, developed by OpenAI, excels in educational, medical, humanities, and writing applications but struggles with real-time data accuracy and lacks open-source flexibility. Bard, powered by Google, leverages real-time internet data for problem solving and shows potential in competitive quiz environments, albeit with performance variability and inconsistencies in responses. Llama, an open-source model from Meta, demonstrates significant promise in medical contexts, natural language processing, and personalised educational tools, yet it requires substantial computational resources. Ernie, developed by Baidu, specialises in Chinese language tasks, thus providing localised advantages that may not extend globally due to restrictive policies. Grok, developed by Xai and still in its early stages, shows promise in providing engaging, real-time interactions, humour, and mathematical reasoning capabilities, but its full potential remains to be evaluated through further development and empirical testing. The findings underscore the context-dependent utility of each model and the absence of a singularly superior chatbot. Future research should expand to include a wider range of fields, explore practical applications, and address concerns related to data privacy, ethics, security, and the responsible deployment of these technologies. [ABSTRACT FROM AUTHOR]

This paper presents an experimental comparison of two types of Li-ion battery stacks for low-voltage energy storage in small urban Electric or Hybrid Electric Vehicles (EVs/HEVs). These systems are a combination of lithium battery cells, a battery management system (BMS), and a central control circuit—a lithium energy storage and management system (LESMS). Li-Ion cells are assembled with two different active cathode materials, nickel–cobalt–aluminum (NCA) and lithium iron phosphate (LFP), both with an integrated decentralized BMS. Based on experiments conducted on the two assembled LESMSs, this paper suggests that although LFP batteries have inferior characteristics in terms of energy and power density, they have great capacity for improvement. [ABSTRACT FROM AUTHOR]

Sustainable urban logistics require support of sustainable logistics center location planning. Nevertheless, urban public authorities generally experience difficulties in choosing a successful planning scheme, due to the lack of a rigorous analytical tool designed to help understand how logistics center location affects sustainability throughout the supply chain. A poor location can keep a firm or a supply chain from reaching its economic, environmental, and social sustainability goals. A good location can help meet these goals. To address the pressing cause of policy failure, this paper developed an analytical framework by integrating the multi-criteria decision-making method and the shortest path model with multiple objectives. The developed framework can be used to evaluate the effects of logistics center location schemes on travel time, transport costs, carbon emission, and road traffic, and further explore the conflict level among them. It is applied to Beijing in this paper. The analysis results reveal that: (1) travel time, transport costs, and carbon emissions all vary along with the distance from logistics center location to the city center; (2) encouraging cargo companies to plan their truck paths with the navigation objective of minimizing travel time is an excellent way to achieve sustainable urban logistics, because in this scenario, freight transport is the quickest, and transport costs and carbon emissions are all more moderate. Additionally, this paper confirmed the conflict level among sustainability goals of urban logistics based on actual contextual data. The proposed framework is a helpful guide tool for urban planners to develop sustainable logistics land-use planning and responsive policy interventions. [ABSTRACT FROM AUTHOR]

In the intricate landscape of the global food system, a nuanced understanding of dynamic evolution patterns and driving mechanisms of food trade network is essential for advancing insights into the African food trade and maintaining the food security of Africa. This paper constructs a framework for analyzing the food trade network from a comparative perspective by comparing and analyzing the evolution of food trade networks in China, the United States, Russia, the European Union, and African countries. The development trend of food trade between China, Russia, the United States, the European Union, and African countries is relatively good. China, the United States, Russia, and the European Union export far more food to African countries than they import, and bilateral food trade plays an important role in alleviating food supply shortages in Africa. The food trade networks between China, the United States, Russia, the European Union, and African countries exhibit a butterfly-shaped structure centered in Africa, and the overall intensity of bilateral trade linkages is gradually increasing. France has the greatest control over the food trade network between China, the United States, Russia, the European Union, and African countries, and the influence of the United States on the food trade network between China, the United States, Russia, the European Union, and African countries is increasing. China's independence in the food trade network between China, the United States, Russia, the European Union, and African countries is enhanced, but its control ability is limited. The impact of differences in total population, differences in food production, and geographical borders on the trade network between China, the United States, the European Union, and African countries tends to decrease, while the influence of differences in the proportion of agricultural employment, differences in the arable land available for food production, and institutional distance tends to increase. [ABSTRACT FROM AUTHOR]

Optimization methods, namely, gradient optimization methods, are a key part of neural network training. In this paper, we propose a new gradient optimization method using exponential decay and the adaptive learning rate using a discrete second-order derivative of gradients. The MAMGD optimizer uses an adaptive learning step, exponential smoothing and gradient accumulation, parameter correction, and some discrete analogies from classical mechanics. The experiments included minimization of multivariate real functions, function approximation using multilayer neural networks, and training neural networks on popular classification and regression datasets. The experimental results of the new optimization technology showed a high convergence speed, stability to fluctuations, and an accumulation of gradient accumulators. The research methodology is based on the quantitative performance analysis of the algorithm by conducting computational experiments on various optimization problems and comparing it with existing methods. [ABSTRACT FROM AUTHOR]

Background: This paper investigates the impact of Ecuador's Ley Orgánica de Educación Superior (LOES), enacted in 2010, which mandated comprehensive reforms in higher education. Objective: The objective of this study is to determine whether the implementation of the LOES has led to a significant increase in academic publications in Ecuador, thereby contributing to sustainable educational practices and aligning with the Sustainable Development Goals (SDGs). In this context, sustainability refers to the ongoing capacity of higher education institutions to generate research that contributes to the long-term development of knowledge, aligns with global sustainability goals, and ensures educational practices that are responsive to societal needs. Methods: Using a synthetic control method, this study evaluates the impact of the LOES on the number of academic publications recorded in Scopus. A synthetic control consisting of data from countries with similar educational and economic profiles serves as a counterfactual to Ecuador's situation. Results: Before the LOES, the average annual number of publications was stable at 253.4 per year. Post-2010, this number surged, reaching an average of 3645.84 publications per year, representing a 358.41% increase. By 2023, the actual number of publications in Ecuador rose to approximately 6584, significantly surpassing the synthetic control estimate of 1431 publications. Conclusions: The findings confirm that the LOES has been effective in increasing research output and advancing educational sustainability in Ecuador. This analysis not only contributes to the literature on the impact of educational policies but also demonstrates the utility of synthetic control methods in assessing policy effectiveness, underscoring the potential of targeted interventions to promote academic excellence and sustainability in education. [ABSTRACT FROM AUTHOR]

This paper presents the design and analysis of PRSEUS structures with no openings, small openings, and mid-sized openings. For the typical panel structure of the small-opening PRSEUS (Pultruded Rod Stitched Efficient Unitized Structure), five reinforcement schemes are developed using different types, such as mouth frames and convex platforms. Simulation analyses of tensile and compressive load are conducted. Compared to the non-opening PRSEUS panel, the small-opening PRSEUS panel's maximum von Mises stress increases by 4.57 times under uniaxial tensile load, and the maximum von Mises stress increases by 2.55 times under uniaxial compressive load. The reinforcement efficiency of the small-opening PRSEUS panel in all five schemes exceeded 30%, Scheme E exhibits the highest load-bearing efficiency under both tensile and compressive load conditions, at 673.63 MPa/kg and 503.38 MPa/kg, respectively. For the typical PRSEUS panel structure with a mid-sized opening, three reinforcement schemes are proposed based on different methods, such as grid and cross-shaped reinforcement. These address the impact of mid-sized openings on the bearing capacity of the PRSEUS pane by analyzing the bearing efficiency of the three schemes. Compared to the non-opening PRSEUS panel, the maximum von Mises stress increases by 15.22 times under a uniaxial tensile load and by 32.45 times under a uniaxial compressive load. The reinforcement efficiency of the mid-sized-opening PRSEUS panel in these three schemes is greater than 50%, with Scheme III providing the highest bearing efficiency under a tensile load at 20.74 MPa/kg and 50.66 MPa/kg under a compressive load. [ABSTRACT FROM AUTHOR]

The modernist architecture of the twentieth century, often referred to as the International Style, exhibited diverse forms and urban layouts shaped by local cultural, economic, and political factors. To comprehensively understand the architectural heritage of this era, it is essential to consider both universal and local principles. This paper explores the adaptation of modernism within a local context by analysing the urban layouts of housing estates in Izmir (Turkey) and Tychy (Poland), constructed during the latter half of the twentieth century. The aim is to enhance our understanding of the architectural heritage of this modernist period through a comparative analysis. The selection of these examples is based on their shared formal similarities, despite the vastly different contexts in which they were built. While the circumstances surrounding the two cases were starkly dissimilar, the scale of the buildings and the spatial arrangements exhibit similarities. This study employs a mixed-method approach, incorporating qualitative methods such as observation and case study alongside quantitative methods such as research and surveys. The comparative analysis presented in this paper illuminates the local idiosyncrasies of architecture while unveiling the complexity of the modernist architectural legacy and the intricate developmental processes that culminated in ostensibly similar spatial outcomes. This proposed comparative analysis aims to address existing gaps in the literature on modern housing and contribute to broader discussions within an international context. It intends to promote knowledge, raise awareness, and contribute to the sustainable discourse of modern architecture. [ABSTRACT FROM AUTHOR]

Interpretations of integrated water cycle management (IWCM) differ across jurisdictions. This paper discusses 10 interpretations of the IWCM concept globally, in Australia and in jurisdictions similar to Australia. Five interpretations of many IWCM versions in Australia are reviewed. This strategic concept aims to address the internal challenges of managing water demand and supply, achieving appropriate disposal and/or wastewater recycling for re-use and distribution networks and providing services at an affordable rate, per changing community needs. The IWCM concept is also recognised as a resource planning tool to address external challenges, such as the uncertainties of climate change, the circular economy and resilience. All 10 IWCM concepts reviewed in this paper acknowledge governance and stakeholders to be of primary importance: governance to drive the conceptual interpretation and stakeholders to develop, drive, implement and promote IWCM as adept at addressing local challenges. The two global interpretations place primary importance on governance, stakeholder engagement and natural resource management, whereas the local interpretations place equally high importance on water critical infrastructure and water economy. Technology, which is changing at an unprecedented pace, is considered, but not as an immediate or primary challenge. These differences are mainly attributed to the organisations' responsibilities and constraints, which drive IWCM concept design. [ABSTRACT FROM AUTHOR]

This paper introduces a rigorous and comprehensive approach to the assessment of marine shafting systems through the utilization of an advanced π-Theorem-based scaling methodology. Integrating journal-bearing similarity assessment and shaft-line scaling methodology with advanced dimensional analysis, the study aims to provide a methodology foundation for systematic replication and analysis of marine shafting systems through scaled models. The proposed scaling methodology ensures geometric and mechanical similarity in terms of shaft-line deflection, considering key scaling parameters such as shaft length, diameter, weight, loads, rotational speed, material properties, bearing locations, and offsets. The advanced dimensional analysis computes specific non-dimensional ratios to guarantee a close resemblance between a real-size system and a scaled lab model. The methodology is analytically derived and validated with numerical simulations for a case study, conducting comparative analysis, evaluating discrepancies, and utilizing the integrated framework for experimentation. [ABSTRACT FROM AUTHOR]

This paper presents an analysis of two methodologies that can be used to predict refueling behavior. Both models aim to provide insights into hydrogen-fuel vehicle users' refueling patterns and behaviors. The first model leverages probabilistic transitions between refueling states to simulate and predict the refueling behavior of hydrogen vehicle users. In contrast, the GP-1 model employs Gaussian processes to capture the underlying patterns and uncertainties in hydrogen-fuel vehicle refueling behavior, taking into consideration additional factors such as weather conditions and the time of the year. The model demonstrates statistical significance and accuracy in predicting trips while identifying the insignificance of precipitation and high ambient temperatures. The methodologies, findings, strengths, and limitations of the two models were tested and compared to identify their relevant contributions. By contrasting their methodologies and evaluating their predictive performance, using performance metrics such as accuracy, precision, and recall values, this study provides valuable insights into the strengths and limitations of each approach. Limitations include assuming a stationary refueling process and excluding external factors and limitations related to data availability, as well as the absence of a specific focus on hydrogen-fuel vehicles. By understanding the differences and similarities between these two models, this paper aims to provide a unique perspective on gaps and further requirements for accurate prediction and modeling of refueling behavior to guide policymakers, infrastructure planners, and stakeholders in making informed decisions regarding the design and optimization of hydrogen refueling infrastructure. [ABSTRACT FROM AUTHOR]

Mobility as a service (MaaS) is a promising lever to achieve a more sustainable, co-modal, and flexible urban system for daily mobility. MaaS is crucial to addressing the challenges imposed by hyper-urbanization, social changes, saturation of public soil with private motor vehicles, and local and global environmental issues. The aim of this paper is to analyse important characteristics of MaaS, namely public governance, regional scale, and high level of development. A total of 13 MaaS initiatives implemented in some European cities were compared using multi-criteria analysis. The results show that, although the MaaS implementation process is faster for private initiatives, public governance is shown to be the most appropriate entity to develop stable MaaS services, as it can enable the achievement of a higher level of integration, coupled with a high rate of service adoption, as well as reduce market entry barriers for service providers while also guaranteeing fair competition, and consequently fostering a higher level of service provided to users. The regional coverage of MaaS is crucial to ensure service provision to a wider population, living in both metropolitan and rural areas. These important features are included in the BIPforMaaS project run by the Italian region of Piedmont, described in detail in this paper. [ABSTRACT FROM AUTHOR]

Data processing in robotics is currently challenged by the effective building of multimodal and common representations. Tremendous volumes of raw data are available and their smart management is the core concept of multimodal learning in a new paradigm for data fusion. Although several techniques for building multimodal representations have been proven successful, they have not yet been analyzed and compared in a given production setting. This paper explored three of the most common techniques, (1) the late fusion, (2) the early fusion, and (3) the sketch, and compared them in classification tasks. Our paper explored different types of data (modalities) that could be gathered by sensors serving a wide range of sensor applications. Our experiments were conducted on Amazon Reviews, MovieLens25M, and Movie-Lens1M datasets. Their outcomes allowed us to confirm that the choice of fusion technique for building multimodal representation is crucial to obtain the highest possible model performance resulting from the proper modality combination. Consequently, we designed criteria for choosing this optimal data fusion technique. [ABSTRACT FROM AUTHOR]

The phenomenon of firms grouping together has been extensively researched and is commonly known as industrial clusters. There are various ways to categorize these clusters, and in this paper, we adopt Markusen's classification, which identifies four distinct types of industrial districts: the Marshallian/Italianate type, the hub-and-spoke type, the satellite industrial platforms, and the state-anchored clusters. Adding to Markusen's typology, we will also try to delineate these two clusters' "European Aspects". We will examine if they have developed any "inter-European" synergy/ies with other entities (clusters, companies, E.U. institutions, etc.) of the E.U. ecosystem. The creation of such synergies includes the creation of technology innovation and interpersonal networks to serve as conduits for the diffusion of knowledge and exchange of information, the development of innovation initiatives between the entities of the technological ecosystem of the E.U. defense industry, and the creation of tangible "knowledge links". The aim of this study is to investigate which of the four types of industrial clusters described by Markusen the French Aerospace Valley cluster of the Midi-Pyrénées and Acquitaine regions and the Andalucia Aerospace cluster belong to. [ABSTRACT FROM AUTHOR]

This paper aims to numerically validate the aerodynamic performance and benefits of variable camber rate morphing wings, by comparing them to conventional ones with plain flaps, when deflection angles vary, assessing their D reduction or L/D improvement. Many morphing-related research works mainly focus on the design of morphing mechanisms using smart materials, and innovative mechanism designs through materials and structure advancements. However, the foundational work that establishes the motivation of morphing technology development has been overlooked in most research works. All things considered, this paper starts with the verification of the numerical model used for the aerodynamic performance analysis and then conducts the aerodynamic performance analysis of (1) variable camber rate in morphing wings and (2) variable deflection angles in conventional wings. Finally, we find matching pairs for a direct comparison to validate the effectiveness of morphing wings. As a result, we validate that variable camber morphing wings, equivalent to conventional wings with varying flap deflection angles, are improved by at least 1.7% in their L/D ratio, and up to 18.7% in their angle of attack, with α = 8° at a 3% camber morphing rate. Overall, in the entire range of α, which conceptualizes aircrafts mission planning for operation, camber morphing wings are superior in D, L/D, and their improvement rate over conventional ones. By providing the improvement rates in L/D, this paper numerically evaluates and validates the efficiency of camber morphing aircraft, the most important aspect of aircraft operation, as well as the agility and manoeuvrability, compared to conventional wing aircraft. [ABSTRACT FROM AUTHOR]

Sustainable transportation goals include an improvement in the level of road safety worldwide. It is well known that traffic accidents are one of the major causes of death worldwide. Black spots are road locations with a higher than statistically expected number of accidents. Remedying black spots would decisively improve road safety. A literature review of black spot identification methods, i.e., accident numbers, accident rates related to exposure, severity of accidents, Poisson and quality control methods, is presented within the framework of this paper. The various approaches adopted by key European and other countries are also summarized and evaluated. An important parameter is the unit length of a road, where accidents are referred. The quality of accident records is also critical. It is concluded that the coupling of statistical and accident severity index methods can contribute to assessing road infrastructure in a more holistic way and, therefore, in providing more reliable results with regard to the road safety level. The design and implementation of effective road safety strategies, based on black spot analysis, can be of great value for the decision makers and decision takers who are involved in the development of a sustainable transportation system. [ABSTRACT FROM AUTHOR]

As a platform to improve the efficiency of matching supply and demand, parking applications once blossomed in many cities. However, some have achieved success while others quickly withered. By comparing the development of parking applications between Beijing and London, it is found that price controls are a key factor. Price controls include price limits and hourly limits. Flexible price or controlled duration facilitate platform sustainability, as these increase the supply side's digital investment and willingness to access the platform, and also increase demanders' willingness to use the platform. Meanwhile, flat and low pricing or no time limit will make the platform less attractive, since these reduce the supply and its mobility, and also discourage demanders from using the platform. This paper enriches the literature on the digital platform ecosystem and information systems (IS) and provides practical inspiration for urban parking management. [ABSTRACT FROM AUTHOR]

Featured Application: The research within this paper can provide a feasible, technical means for the design of new high-contact-ratio gears and can effectively promote the progress of gear transmission technology. The research results can be applied to the transmission systems of complex equipment such as tanks, armored vehicles, and ships, which is of great significance to improving their performance. Tooth root bending stress and surface contact stress are two major determinants of the load carrying capacity of gear drives. Generally, a high contact ratio has the potential to enhance the gear strength. In this paper, the basic procedures and methods for constructing a high-contact-ratio (HCR) internal spur gear pair with the arc path of the contact are presented. The effects of design and modification parameters such as deflection angle, modification angle, and addendum coefficient on gear drive are analyzed in detail based on 2D finite-element models (FEMs). A comparison of experimental and finite-element analyses (FEA) of the bending stress, contact stress, and contact ratio between HCR and involute internal spur gear drives was conducted to demonstrate the advantages of the HCR gear drive in terms of load capacity. The results show that appropriately increasing the deflection angle and addendum coefficient is beneficial for reducing bending and contact stresses. It was also observed that the bending and contact stresses of a HCR pinion are lower than those of an involute one. Moreover, the contact ratio increases with input torque. [ABSTRACT FROM AUTHOR]

The effectiveness of the hydraulic fracturing procedure is crucially dependent on the stage of fracture planning and design. Forecasting fracture behavior in rock formations characterized by non-uniform toughness is a serious challenge. In the present paper, a planar-3D model considering the rock's non-uniform fracture toughness has been developed for the uneven propagation of a hydraulic fracture. The series of numerical experiments were designed to study the effect of inhomogenous fracture toughness. The results show that the fracture toughness contract significantly controls the overall direction of fracture propagation, and a combination of toughness contrast and the proportion between the pay zone and barrier zone determine the fracture profile: from almost circular with or without a pair of narrow wedges when the proportion is small to almost rectangular otherwise. This paper also discusses the process of cleaning a fracture from hydraulic fracturing fluid by oil. Using numerical modeling on the basis of the constructed mathematical model, a relationship is established between the quality of hydraulic fracture cleaning and the geometrical parameters of the fracture and the region filled with the hydraulic fracturing fluid. The results of numerical experiments show that while fracturing fluid is more viscous than oil, the length of the fracture has a greater influence on the cleaning process than the viscosity of the fracturing fluid. [ABSTRACT FROM AUTHOR]

Probabilistic models of competence assessment join the benefits of automation with human judgment. We start this paper by replicating two preexisting probabilistic models of peer assessment ( P G 1 -bias and PAAS). Despite the use that both make of probability theory, the approach of these models is radically different. While P G 1 -bias is purely Bayesian, PAAS models the evaluation process in a classroom as a multiagent system, where each actor relies on the judgment of others as long as their opinions coincide. To reconcile the benefits of Bayesian inference with the concept of trust posed in PAAS, we propose a third peer evaluation model that considers the correlations between any pair of peers who have evaluated someone in common: P G -bivariate. The rest of the paper is devoted to a comparison with synthetic data from these three models. We show that P G 1 -bias produces predictions with lower root mean squared error (RMSE) than P G -bivariate. However, both models display similar behaviors when assessing how to choose the next assignment to be graded by a peer, with an " R M S E decreasing policy" reporting better results than a random policy. Fair comparisons among the three models show that P G 1 -bias makes the lowest error in situations of scarce ground truths. Nevertheless, once nearly 20 % of the teacher's assessments are introduced, PAAS sometimes exceeds the quality of P G 1 -bias' predictions by following an entropy minimization heuristic. P G -bivariate, our new proposal to reconcile PAAS' trust-based approach with P G 1 -bias' theoretical background, obtains a similar percentage of error values to those of the original models. Future work includes applying the models to real experimental data and exploring new heuristics to determine which teacher's grade should be obtained next to minimize the overall error. [ABSTRACT FROM AUTHOR]

The construction industry has great potential for carbon emission reduction, which strongly impacts the peak of carbon emissions and carbon neutrality. This paper compares foreign and Chinese articles on building carbon emissions from publication objects, journals, subject categories, authors, and institutions. It discusses the differences in research trends and hotspots from keywords, reference co-citation analysis, and historical citation analysis. The results show that the number of publications on building carbon emissions steadily increased. The research on building carbon emissions in foreign articles is earlier and more systematic than that in China, and the output and influence of foreign articles are generally more prominent than those of Chinese articles. However, the production and influence of articles by certain Chinese authors and institutions have been remarkable. The topics of 'CO2 emission', 'life-cycle assessment', 'environmental impact', 'greenhouse gas emission', and 'renewable energy' are essential subjects for foreign and Chinese articles in the research field of building carbon emissions and the development trend is similar. The thematic direction of Chinese articles is more divergent and lacks well-developed themes that greatly influence other research themes. Finally, based on the research results, this study puts forward the potential future research direction of building carbon emissions. The results of this study will provide a current and systematic overview of this field, which will be helpful for future researchers to promote the development of research on building carbon emissions. [ABSTRACT FROM AUTHOR]

This paper deals with problems of freight transport sustainability from the perspective of four key factors: greenhouse gas production, fossil fuel dependence, congestion, and accident rates. It is based on the results of the FreightVision project, in which the author participated as a researcher and member of the design team. The aim was to develop a set of 35 recommendations to serve as a tool for European Union decision-making in transport policy matters at the highest level. The developed measures were prioritized, and a list of individual recommendations was drawn up according to their potentials. Then, the set of measures was processed using multi-criteria analysis tools, and these results were compared with the original list using comparative analysis to identify differences between the two approaches. The contribution of this work is the development of a methodology for evaluating the traffic measures according to their priorities and, at the same time, the verification of the empirical results thus obtained with the results that were the output of the mathematical processing. This work fills a research gap in a similar problem area by working with specific measures systematically developed for the purposes of analysis; these results are used to formulate recommendations for the European Commission whose policy decisions should lead to an increased level of freight transport sustainability. [ABSTRACT FROM AUTHOR]

The emergence of immersive technologies, such as virtual reality (VR) headsets, has revolutionized the way we experience the physical world by creating a virtual, interactive environment. In the field of education, this technology has immense potential to provide students with a safe and controlled environment in which to experience real-world scenarios that may be otherwise unfeasible or unsafe. However, limited research exists on the effectiveness of integrating immersive technologies into technical education delivery. This research investigated the potential use of immersive virtual reality (IVR) in university-level construction management courses, with a focus on integrating IVR technology into traditional education for construction project planning and control. The experiment involved comparing the students' learning and understanding of the subject matter using a set of two-dimensional construction drawings and a critical path method (CPM)-based construction schedule, with and without the use of an immersive environment. The findings suggested that the use of immersive technology significantly improved the students' ability to understand technical concepts and identify any errors in the construction sequence when compared to traditional teaching methods. This paper presents the details of the experiment and a comparative analysis of both approaches in terms of students' learning and understanding of project planning, sequencing, and scheduling. [ABSTRACT FROM AUTHOR]

The aim of predictive maintenance, within the field of prognostics and health management (PHM), is to identify and anticipate potential issues in the equipment before these become serious. The main challenge to be addressed is to assess the amount of time a piece of equipment will function effectively before it fails, which is known as remaining useful life (RUL). Deep learning (DL) models, such as Deep Convolutional Neural Networks (DCNN) and Long Short-Term Memory (LSTM) networks, have been widely adopted to address the task, with great success. However, it is well known that these kinds of black box models are opaque decision systems, and it may be hard to explain their outputs to stakeholders (experts in the industrial equipment). Due to the large number of parameters that determine the behavior of these complex models, understanding the reasoning behind the predictions is challenging. This paper presents a critical and comparative revision on a number of explainable AI (XAI) methods applied on time series regression models for PM. The aim is to explore XAI methods within time series regression, which have been less studied than those for time series classification. This study addresses three distinct RUL problems using three different datasets, each with its own unique context: gearbox, fast-charging batteries, and turbofan engine. Five XAI methods were reviewed and compared based on a set of nine metrics that quantify desirable properties for any XAI method. One of the metrics introduced in this study is a novel metric. The results show that Grad-CAM is the most robust method, and that the best layer is not the bottom one, as is commonly seen within the context of image processing. [ABSTRACT FROM AUTHOR]

This research paper studies and highlights the features of the most popular finite control set model predictive control (FCS-MPC) strategies available in the state of the art, which are the optimal switching vector (OSV-MPC), modulated model predictive control (M2PC), and optimal switching sequence (OSS-MPC) methods. Thus, these strategies are studied experimentally by analyzing the transient and steady state performance using a grid tie conventional three-phase two-level voltage source inverter (VSI) with inductive output filter in a Typhoon HIL real-time simulator (RTS) with a Texas Instruments F28379D digital signal processor (DSP). Hence, quantitative indicators, such as the maximum tracking error, the mean absolute error, the settling time, the total harmonic distortion, the switching frequency spectrum, the switching pattern, and the computational burden are compared with the aim to deduce the best strategy for each criteria. [ABSTRACT FROM AUTHOR]

This paper investigates the determinants of mathematics performance by gender, exploiting a multilevel random forest approach. OECD PISA 2018 data from 28 European countries are employed to explore the performance of male and female students as a function of students' family characteristics, their attitudes towards education, and class and school environment. Results show that the gender gap in favour of boys persists in most European countries. However, teacher and school practices like fostering student reading and creating a cooperative environment allow mitigating the influence of family background in countries without gender gap. Policy implications to foster performance equality are provided. [ABSTRACT FROM AUTHOR]

Underground mining safety risk increases with the more complicated geological conditions in deep strata, so coal mines turn to the upper limit mining of shallow coal seams under the Cenozoic strata. Nevertheless, coal mines in the Northern China coalfield are mainly covered by thicker loose sandy layers with more abundant water. The analysis of overburdened strata deformation properties is essential for safe, efficient, and environmentally friendly production. This paper discusses the deformation and migration of overburdened strata through mechanical analysis, numerical and physical similar simulations, and in situ field measurement. A thorough understanding of overburdened strata deformation induced by mining has been obtained, and the results are as follows: The immediate roof first collapses to form the caved zone accompanied by the first weighting, and the fractured zone and bending deformation zone begin to develop in sequence; the separation layer is observed during the period of fracture development. However, the occurrence of the bending deformation subsidence results in the closure of the separation space; the ratio of fractured and mining height is quantified to 14.4:1.0 by the comparative analysis. The results may serve as technical evidence to support the mining safety of the study area and other coal mines with similar geological conditions. [ABSTRACT FROM AUTHOR]

This paper deals with problems of the comparative analysis of results provided by the processing of predicting trends in freight transport, especially concerning dependency on fossil fuels and GHG (greenhouse gas) production. This topic has been in compliance with current requests for sustainable transport and the environment both being strongly emphasized in recent EU directions. Based on publicly available statistical data covering the selected time period, two completely different predicting methods—neural networks and mathematical statistics—are used for forecasting both of the above-mentioned trends. Obtained results are further analyzed from viewpoints of value concordance and reliability. The concluding comparative analysis summarizes the pros and cons of both approaches. Given the fact that forecasting methods generate model values representing future events whose states are unverifiable, the presented procedure can be used as a tool for verifying of their verisimilitude by means of comparing results obtained by the above-mentioned methods. [ABSTRACT FROM AUTHOR]

The essence of sustainable urbanization is to take a holistic approach to the harmonious development of economic, social, cultural and environmental protection. This paper applies the urban sustainability assessment system to analyze the characteristics of indicators related to the quality of the built environment and environmental pressure of 91 cities in four major megalopolises in China from 2010 to 2018. It also combines statistical methods to summarize the general features of urban development through a comprehensive urban performance evaluation by comparative and classification analysis for the purpose of scientific guidance on sustainable urbanization. The comparative results showed that in terms of urban sustainability, the Yangtze River Delta performed best, followed by JingJinJi, Pearl River Delta and Shandong Peninsula. Of which, the quality of built environment in JingJinJi and the environment pressure in the Shandong Peninsula require particular attention to improve and decrease, respectively. Moreover, cities can be grouped into six development types through performance clustering including three positive and three negative types. The characteristics of all types are summarized, and the performance of the specific indicators are detailed compared to serve as a guiding basis for making generic recommendations of sustainable urbanization. [ABSTRACT FROM AUTHOR]

Compared with the conventional column caps, the reverse column caps that are used for slab-column joint of basement roof can improve the clearance of the basement while ensuring structural safety, and they are hidden in the covering soil without affecting the appearance and use of upper surface of flat slabs. In this paper, four finite element models, which are loaded by column-end displacement-control mechanism, are established. These models are used to investigate the mechanical performance of slab-column joint for flat slabs with reverse and conventional column caps. The obtained numerical results were thoroughly analysed, indicating that the load-carrying capacity performances of flat slabs with conventional column caps are much higher than their counterparts with reverse column caps, but flat slabs with conventional column caps possess lower mechanical ductility. Moreover, the reverse column caps were found to exhibit a severe damage at ultimate load; therefore, transverse stirrups were distributed into the reverse and conventional column caps for the purpose of comparison. The comparison results revealed that the ultimate load of the slab-column joints with reverse column cap can be increased by 2.4% by arranging transverse stirrups in column cap, but the ductility is decreased by 13.4%. For the slab-column joints with conventional column cap, the ultimate load is decreased by 10.0% and the ductility is decreased by 1.6% when transverse stirrups are arranged in column cap. Therefore, arrangement of transverse stirrups in column cap should be determined based on the actual situation in the flat slab system with reverse column cap, and it is not recommended to arrange transverse stirrups in column cap in the flat slab system with conventional column cap. [ABSTRACT FROM AUTHOR]

The popularization of electric vehicles (EVs) is beneficial to the sustainable development of energy and the environment. China's promotion and development strategy for EVs will serve as a model for other countries. EV ownership has a significant difference between first/second-tier (FST) cities and third/fourth-tier (TFT) cities and there is a huge growth potential for the EV market in those TFT cities. This paper aims to explore the factors influencing the adoption intentions for EVs in FST and TFT cities under a subsidy deduction and to make a comparative analysis of their regional heterogeneity. Based on the extended theory of planned behavior (TPB) model, the structural equation model is used to compare the factors affecting the adoption intention for EVs of 858 respondents in China. The results show that attitude, subjective norms, novelty seeking, non-financial incentive, product cognition, and environmental concerns are positively related to intention in FST and TFT cities; however, infrastructure development only has a positive significant impact in the TFT cities. Additionally, the subsidy deduction has a more negative impact on the adoption intentions in FST cities. Our findings provide vital insights for formulating government regulations and marketing strategies depending on the diverse sizes and attributes of Chinese cities. [ABSTRACT FROM AUTHOR]

Featured Application: The resulting collection of Russian poetic texts annotated in terms of rhetorical structure theory provide data for investigating the author's styles of poetic reasoning. Potentially the corpus can give additional data for machine learning, particularly in its application to poetic text's generation and simulating the author's styles. The paper considers the pragmatic textual level and focuses on peculiarities of reasoning realized in the lyric verses written by the representatives of Russian classic poetry. The investigated material of poetic texts includes the verses written by A.K. Tolstoy, K.K. Sluchevsky, and I.F. Annensky. The purposes of the study involve adapting the rhetorical structure theory (RST) to poetic texts, annotating these texts, searching for regularities of poetic reasoning specific to the considered authors. Applying RST to poetic texts was a novel task; the lack of experience made it necessary to adapt the method, that is, to elaborate the adequate set of rhetorical relations and to specify two sets of criteria: segmenting a text and identifying the relations. The resulting set of relations consists of 34 items. After annotating the texts in terms of the adopted RST, several lines of comparison were the objects of investigation. They include collating the frequency spectrums of relations and the semantical groups of relations for the three authors, as well as comparing two periods of creativity for A.K. Tolstoy and K.K. Sluchevsky. The results of the comparative investigation revealed certain regularities both in the distribution of isolated relations and the distribution of semantically grouped relations. [ABSTRACT FROM AUTHOR]

Nowadays, the high-dimensionality of data causes a variety of problems in machine learning. It is necessary to reduce the feature number by selecting only the most relevant of them. Different approaches called Feature Selection are used for this task. In this paper, we propose a Feature Selection method that uses Swarm Intelligence techniques. Swarm Intelligence algorithms perform optimization by searching for optimal points in the search space. We show the usability of these techniques for solving Feature Selection and compare the performance of five major swarm algorithms: Particle Swarm Optimization, Artificial Bee Colony, InvasiveWeed Optimization, Bat Algorithm, and Grey Wolf Optimizer. The accuracy of a decision tree classifier was used to evaluate the algorithms. It turned out that the dimension of the data can be reduced about two times without a loss in accuracy. Moreover, the accuracy increased when abandoning redundant features. Based on our experiments GWO turned out to be the best. It has the highest ranking on different datasets, and its average iteration number to find the best solution is 30.8. ABC obtained the lowest ranking on high-dimensional datasets. [ABSTRACT FROM AUTHOR]

This paper explores the connection between corporate social responsibility (CSR) and food safety and how best to promote CSR in Chinese food companies by comparing two groups of food companies, one which had food safety incidents in the previous three years and one which had no food safety incidents during the same period. Managers of 498 food companies in 17 regions of China were surveyed. It was found that companies where the senior management gave higher levels of support and commitment to CSR and companies that had higher levels of CSR engagement had lower food safety incident rates. Motives for CSR engagement by food companies are the expected benefits that might accrue to the company including helping to achieve strategic objectives, improving daily management, ensuring food safety, improving internal cooperation, enhancing food quality, improving employees' skills at work, increasing employee benefit and improving their morale, and maintaining business integrity. It was also found that the external factors for CSR engagement are consumer demand, as well as pressures from the government and from other companies in the supply chain. Finally, the paper makes a number of suggestions for improvements in policy. [ABSTRACT FROM AUTHOR]

Emerging countries in Southeast Asia are facing considerable challenges in addressing rising motorisation and its negative impact on air quality, traffic, energy security, liveability, and greenhouse gas emissions. This paper presents a comparative analysis of the approach and status of sustainable, low-carbon transport policy in ASEAN countries and identifies differences and similarities. The methodology is based on a taxonomy of policy components as developed by Howlett and Cashore. The data come from comprehensive country studies for Indonesia, the Philippines, Thailand and Vietnam and interviews with policymakers. We find that each country has a specific set of goals, objectives and targets that support sustainable transport, and, directly or indirectly, climate change mitigation. In terms of specific mechanisms and calibrations, which we analyse based on the Avoid-Shift-Improve approach, there are notable differences between the countries, for example in terms of fuel economy policy. Even though an initial response to climate change mitigation challenges is visible in these countries' transport policies, much more effort is required to enable a transition to a transport system compatible with long-term climate change and sustainable development targets. [ABSTRACT FROM AUTHOR]

The design of shallow foundations is performed in accordance with different building regulations depending on geotechnical and geological conditions. This paper involves the design calculations applying Kazakhstani and European approaches. The design of shallow foundations in Nur-Sultan city in Kazakhstan was implemented by the calculation of bearing capacity and elastic settlement in accordance with the design procedures provided in SP RK 5.01-102-2013: Foundations of buildings and structures, and Eurocode 7: Geotechnical design. The calculated results of bearing capacity and elastic settlement for two types of shallow foundations, such as pad foundation and strip foundation, adhering to Kazakhstani and European approaches are relatively comparable. However, the European approach provided higher values of bearing capacity and elastic settlement for the designed shallow foundation compared to the Kazakhstani approach. The difference in the results is explained by the application of different values of partial factors of safety for the determination of bearing capacity and different methods for the calculation of the elastic settlement of shallow foundations (i.e., elasticity theory and layer summation method). [ABSTRACT FROM AUTHOR]

The deep-sea mining lift pump is one of the pivotal components in deep-sea mineral transportation systems and its internal flow is very complex; consequently, unraveling its unsteady flow behavior pattern holds immense practical value. This study adopts numerical methods to analyze the time-averaged distribution characteristics of the internal flow field in mining lift pumps, as well as the flow field's pulsation intensity distribution characteristics, the vortex's spatiotemporal evolution process in both moving and static cascades, and the time- and frequency-domain pulsation characteristics of internal pressure in each flow passage component under four different flow conditions are also investigated. The hydraulic properties of mining lift pumps under these four different conditions are also evaluated, and the outcomes are benchmarked against those of numerical predictions. Our findings reveal that the interplay between impeller blades and guide vanes significantly influences the pump's flow characteristics, with the pump's unsteady flow influencing its hydraulic properties. Experimental validation of this system confirms that the pump under study is in line with design specifications in terms of hydraulic properties. The method validation test on the prototype pump shows that the SST k-ω model is capable of successfully forecasting instability in the flow features of deep-sea mining lift pumps. These results will serve as a theoretical reference for regulating the flow state inside deep-sea mining lift pumps. [ABSTRACT FROM AUTHOR]

The precise segmentation of different regions of the prostate is crucial in the diagnosis and treatment of prostate-related diseases. However, the scarcity of labeled prostate data poses a challenge for the accurate segmentation of its different regions. We perform the segmentation of different regions of the prostate using U-Net- and Vision Transformer (ViT)-based architectures. We use five semi-supervised learning methods, including entropy minimization, cross pseudo-supervision, mean teacher, uncertainty-aware mean teacher (UAMT), and interpolation consistency training (ICT) to compare the results with the state-of-the-art prostate semi-supervised segmentation network uncertainty-aware temporal self-learning (UATS). The UAMT method improves the prostate segmentation accuracy and provides stable prostate region segmentation results. ICT plays a more stable role in the prostate region segmentation results, which provides strong support for the medical image segmentation task, and demonstrates the robustness of U-Net for medical image segmentation. UATS is still more applicable to the U-Net backbone and has a very significant effect on a positive prediction rate. However, the performance of ViT in combination with semi-supervision still requires further optimization. This comparative analysis applies various semi-supervised learning methods to prostate zonal segmentation. It guides future prostate segmentation developments and offers insights into utilizing limited labeled data in medical imaging. [ABSTRACT FROM AUTHOR]

In this paper, the aggregate index of national economies' circularity (INEC) was proposed and empirically verified. For this purpose, the taxonomic linear ordering method was used, which is a multi-criteria decision-making procedure. This method replaces the analysis of the phenomenon described by a set of indicators with an analysis using one aggregate indicator: the so-called 'synthetic metric'. Based on 14 circular economy indicators that are available in the Eurostat database, the circularity indexes were constructed for 24 EU countries (including the United Kingdom). This allowed the author, on the one hand, to create a ranking of the countries, and on the other, to assign them to four groups, which were characterized by a similar level of circularity. This paper attempts to answer the following questions: how circular are the European economies? What are the main challenges in achieving circularity in Europe? Taking into account the INEC range [0,1], it should be noted that the level of circularity in the analysed European countries is low (an average of 0.3021). Therefore, the paper indicates the areas requiring improvement in this respect. [ABSTRACT FROM AUTHOR]

Energy communities (ECs), intended as collective action initiatives in the energy field involving citizens' participation, have been gaining relevance for the past decades as an alternative way to organize the energy chain to challenge the incumbent system. With Europe's recently adopted Clean Energy Package, ECs found a formal recognition by the European Union as potential actors of the transition of the energy system towards a wider and more decentralized use of renewable sources. Although the potential role of ECs in the transition is therefore hardly questionable, a thorough comprehension of the enabling factors that might foster their diffusion and scaling up is still lacking. Through a comparative analysis of the evolutionary trajectories in six EU countries regarding their energy systems, their regulatory frameworks and their historical evolution of ECs, namely through the example of cooperative models, this paper aims at providing some preliminary evidence about the factors and dynamics that seem to have played, and may play, a role in hampering or facilitating EC model diffusion. Attention is therefore specifically paid to three dimensions of analysis referring to: the energy mix and market structure; the institutional and policy landscape; the wider social attitudes towards environmental issues and cooperation among citizens. In addition to providing a wide comparison of different EU countries, the paper shows that the historical evolution pathways have to be carefully taken into account to understand what might trigger ECs exploitation in the EU. [ABSTRACT FROM AUTHOR]

The objective of this study is to perform a comparative analysis of the impact of incorporating alkaline earth metal carbonates (MCO3, where M–Mg, Ca, Sr, Ba) into low-calcium fly ash (FA) on the geopolymerization processes and the resultant properties of composite geopolymers. Mechanical activation was employed to enhance the reactivity of the mixtures. The reactivity of the mechanically activated (FA + alkaline earth carbonate) blends towards NaOH solution was experimentally studied using XRD analysis and FTIR spectroscopy. In agreement with thermodynamic calculations, MgCO3 demonstrated the most active interaction with the alkaline solution, whereas strontium and barium carbonates exhibited little to no chemical interaction, and calcite was situated in the transition region. As the calcite content in the mixture with FA increased, the compressive strength of the geopolymers continuously improved. The addition of Mg, Sr, and Ba carbonates to the FA did not enhance the strength of geopolymers. However, the strength of geopolymers based on these blends was comparable with that of geopolymers based on 100% FA. The strength of geopolymers synthesized from the 100% FA and from the (90% FA + 10% MCO3) blends, mechanically activated for 180 s, at the age of 180 days was 11.0 MPa (0% carbonate), 11.1 MPa (10% MgCO3), 36.5 MPa (10% CaCO3), 13.6 MPa (10% SrCO3), and 12.4 MPa (10% BaCO3) MPa, respectively. The influence of carbonate additives on the properties of the composite geopolymers was examined, highlighting filler, dilution, and chemical effects. The latter determined the unique position of calcite among the carbonates of alkaline earth metals. [ABSTRACT FROM AUTHOR]

As the educational landscape evolves, understanding and fostering student adaptability has become increasingly critical. This study presents a comparative analysis of XAI techniques to interpret machine learning models aimed at classifying student adaptability levels. Leveraging a robust dataset of 1205 instances, we employed several machine learning algorithms with a particular focus on Random Forest, which demonstrated highest accuracy at 91%. The models' precision, recall and F1-score were also evaluated, with Random Forest achieving a precision of 0.93, a recall of 0.94, and an F1-score of 0.94. Our study utilizes SHAP, LIME, Anchors, ALE, and Counterfactual explanations to reveal the specific contributions of various features impacting adaptability predictions. SHAP values highlighted 'Class Duration' significance (mean SHAP value: 0.175); LIME explained socio-economic and institutional factors' intricate influence. Anchors provided high-confidence rule-based explanations (confidence: 97.32%), emphasizing demographic characteristics. ALE analysis underscored the importance of 'Financial Condition' with a positive slope, while Counterfactual scenarios highlighted the impact of slight feature variations of 0.5 change in 'Class Duration'. Consistently, 'Class Duration' and 'Financial Condition' emerge as key factors, while the study also underscores the subtle effects of 'Institution Type' and 'Load-shedding'. This multi-faceted interpretability approach bridges the gap between machine learning performance and educational relevance, presenting a model that not only predicts but also explains the dynamic factors influencing student adaptability. The synthesized insights advocate for educational policies accommodating socioeconomic factors, instructional time, and infrastructure stability to enhance student adaptability. The implications extend to informed and personalized educational interventions, fostering an adaptable learning environment. This methodical research contributes to responsible AI application in education, promoting predictive and interpretable models for equitable and effective educational strategies. [ABSTRACT FROM AUTHOR]

Transitional streets serve as intermediary spaces between the Central Business Districts (CBDs) and surrounding residential areas, offering diverse functions and activities within urban interiors. However, a practical methodology for accurately classifying these streets has been lacking, due primarily to transitional areas' spatial constraints and functional complexities. This study leverages Point of Interest (PoI) data from 2023 to develop an innovative methodological framework that addresses these challenges. This framework analyses transitional streets' functional distribution and typology, employing PoI frequency density and functional type ratios to identify and classify functional zones. It generally delineates eight main types of transitional streets in the CBD of Chongqing, a prototypical hillside city. Utilising advanced data technology from internet maps, this research pioneers new approaches for identifying and analysing the functionality of transitional streets. The findings underscore the effectiveness of PoI data in precisely recognising the functional types of transitional streets, thereby providing a robust theoretical and practical foundation for the in-depth study of transitional streets. Moreover, the results enhance urban spatial planning in hillside cities of China, effectively demonstrating the advantages of PoI data in defining street typology compared to traditional methods. This approach provides a more detailed understanding of urban functional dynamics by allowing for a more nuanced data analysis of street functions. [ABSTRACT FROM AUTHOR]

As escalating environmental pollution results from economic development, the green supply chain is vital in enhancing ecological quality. In light of the rapid growth of online shopping, the dual-channel supply chain has gained significant popularity. Governments have implemented policies to achieve carbon peaks and neutrality worldwide. Considering green quality and channel preferences, this study constructs a Stackelberg model led by the manufacturer within a dual-channel supply chain to compare the effects under two government subsidy strategies. A Stackelberg game-theoretic approach is applied to analyze the model. The findings indicate the following: (1) Increases in the subsidy coefficient can increase product greenness and the overall profit in both subsidy strategies, which makes sense; (2) When direct sales channels become dominant, subsidizing the manufacturer proves superior to subsidizing the retailer in terms of promoting green quality and overall profit, which extends existing studies of government subsidy decisions. Furthermore, subsidizing the retailer may negatively affect the total supply chain profit; (3) Consistent with previous literature, intense competition between manufacturers and retailers is expected to enhance the overall profit of the supply chain; (4) Interestingly, customer preference for online channels does not influence product green quality under manufacturer subsidization strategies but exhibits a negative impact under retailer subsidization strategies. Finally, this research provides managerial implications for decision-makers and potential issues for future research. [ABSTRACT FROM AUTHOR]

This study aims to comprehensively analyze the operational status and international competitiveness of global container shipping enterprises in the era of sustainability and digitalization within the field of international container transportation. Utilizing the entropy method, this study quantitatively evaluates the direct operational strength of 14 leading container shipping enterprises while considering multiple factors including environmental protection, service quality, company scale, customer satisfaction, research and development level, and brand influence. The contributions of this study to the existing knowledge are primarily manifested in several aspects: firstly, by constructing a comprehensive evaluation framework, it offers a new perspective for assessing the international competitiveness of container shipping enterprises, facilitating a more comprehensive understanding of their strengths and weaknesses. Secondly, this study emphasizes the crucial roles of environmental protection and customer service in the competitiveness of shipping enterprises, providing new strategic directions for the industry's sustainable development and digital transformation. Lastly, through detailed analysis of the operational performance of different companies, this study provides specific improvement suggestions for shipping enterprises, aiding them in achieving more precise management and more efficient development. The research findings demonstrate that companies exhibit varied performance in different aspects, showcasing their respective strengths and challenges. Particularly, this study identifies leading enterprises that have made significant progress in environmental technology innovation and customer service, while also highlighting deficiencies in some companies regarding scale expansion and brand building. These findings not only offer valuable insights for the development of the shipping industry but also serve as a window for policymakers, investors, and consumers to gain a deeper understanding of the shipping market. Through the thorough analysis conducted in this study, we aim to contribute to the sustainable development and digital transformation of the global container shipping industry. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has underscored the critical need for the advancement of diagnostic and therapeutic platforms. These platforms rely on the rapid development of molecular binders that should facilitate surveillance and swift intervention against viral infections. In this study, we have evaluated by three independent research groups the binding characteristics of various published RNA and DNA aptamers targeting the spike protein of the SARS-CoV-2 virus. For this comparative analysis, we have employed different techniques such as biolayer interferometry (BLI), enzyme-linked oligonucleotide assay (ELONA), and flow cytometry. Our data show discrepancies in the reported specificity and affinity among several of the published aptamers and underline the importance of standardized methods, the impact of biophysical techniques, and the controls used for aptamer characterization. We expect our results to contribute to the selection and application of suitable aptamers for the detection of SARS-CoV-2. [ABSTRACT FROM AUTHOR]

To slow down climate warming and achieve sustainable development, the Paris Agreement attempts to establish cooperative approaches (Article 6.2 in the Paris Agreement) and a sustainable development mechanism (Article 6.4 in the Paris Agreement) for carbon trading. However, deficiencies in implementation exist due to a lack of systematic execution regulations and an integrated management system. To strengthen the effectiveness of the two carbon trading mechanisms for reducing carbon emission, this paper aims to propose an implementation framework of cooperative approaches and a sustainable development mechanism. Based on the international regime theory in global climate change and the nine elements of the market mechanism, the paper makes use of comparative analysis to discuss the type of mechanism, coverage of the system, operational framework, governance framework, and implementation framework of cooperative approaches and a sustainable development mechanism. The main results and conclusions are as follows: (1) Cooperative approaches are considered as project-based and quota-/credit-based carbon market mechanisms. Under cooperative approaches, trading units should be authorized at the international-regional and sub-regional levels. CO2, CH4, N2O, HFCs, PFCs, SF6, and NF3 are the seven types of greenhouse gases that could be traded through cooperative approaches, and they shall be accounted by the unit of CO2-eq. (2) The sustainable development mechanism is considered as an industry-based and credit-based carbon market framework. Under the sustainable development mechanism, trading units should be authorized at the international level. CO2, CH4, N2O, and PFCs can work in the sustainable development mechanism as subject matters. The unit of gases shall be CO2-eq as well. (3) The implementation framework of cooperative approaches ought to follow three stages: project preparation, project submission, and auditing, as well as internationally transferred mitigation outcomes transfer. The implementation framework of the sustainable development mechanism ought to contain three stages: project development and review, project implementation and monitoring, and project acceptance and unit transfer. The authors hope it can work as a guideline for the early implementation stage of the cooperative approaches and sustainable development mechanism to stimulate carbon reduction and further slow climate change. [ABSTRACT FROM AUTHOR]

The analytical model of a permanent magnet eddy current coupler (PMECC) is mainly used for evaluation of its characteristics and the initial optimization of design. Based on the equivalent magnetic circuit method, this paper carries out analytical modeling for four typical PMECCs composed of surface-mounted and interior permanent magnet, slotted and non-slotted conductor rotors, which provides a theoretical basis for the subsequent research in this paper. The basic electromagnetic characteristics of the PMECCs are investigated by the established analytical model. Simultaneously, the analytical results about permeance, flux density, torque and power are verified by FEA simulation. The analysis results show that the slotted CR will obtain a much higher power density, and the iron loss mainly exists in the CRs. In addition, the analytical and FEA results agree well, which proves the reliability of the proposed, nearly unified analytical model. [ABSTRACT FROM AUTHOR]

Multidimensional crisis phenomena (financial–economic, environmental and social), plaguing the international community, especially in the last 30 years, have intensified resentment towards traditional models of growth and socio-economic development. The European Commission has placed the idea of a green economy (GE) at the heart of the Europe 2020 strategy. This paper presents an assessment of the implementation of the green economy assumptions in EU countries in 2018, taking 2010 as the base year. Using taxonomic methods, a synthetic evaluation index (GEI—Green Economy Index) was constructed based on a multi-criterion set of 27 indicators. This paper attempts to answer the following questions: How green are the European economies? What are the main challenges in this context? The average value of the index for the EU countries decreased in the studied years from 0.3423 to 0.3294, which can be interpreted as a slowdown in the greening processes. The key recommendations for the upcoming years include the improvement of energy efficiency indicators, the further increase in the share of renewable energy sources in the energy balance. Moreover, a significant problem continues to be the high percentage of the population at risk of poverty or social exclusion, as well as low CO2 and resource productivity rates. [ABSTRACT FROM AUTHOR]