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Predictivism is the thesis that evidence successfully predicted by a scientific theory counts more (or ought to count more) in the confirmation of that theory than already known evidence would. One rationale that has been proposed for predictivism is that predictive success guards against ad hoc hypotheses. Despite the intuitive attraction of predictivism, there is historical evidence that speaks against it. As valuable as the historical evidence may be, however, it is largely indirect evidence for the epistemic attitudes of individual – albeit prominent – scientists. This paper presents the results of an empirical study of scientists' attitudes toward predictivism and ad hoc-ness (n = 492), which will put the debate on a more robust empirical footing. The paper also draws attention to a tension between the ad hoc-ness avoidance rationale of predictivism and the ways philosophers have spelled out the notion of ad hoc-ness. [ABSTRACT FROM AUTHOR]

JSON Web Token (JWT) is a simple, compact way to share claims in a space-constrained environment. JWT is part of the interoperable JSON-based identity suite. Many libraries that provide JWT-based authentication and authorization exist. While the JWT standard is secure, some implementations still need to be made. This research paper delves into a comprehensive analysis of the prominent Python libraries utilized for JWT authentication. By meticulously examining these libraries, we aim to provide an in-depth understanding of their features and capabilities. Our investigation encompasses an enumeration of the distinct signing algorithms that are supported by each of these JWT Python libraries. To ensure the robustness and security of these libraries, we employ a multifaceted approach that utilizes various statistical application Security Testing (SAST) tools. These tools play a pivotal role in our assessment by not only evaluating the adherence of the codebase to the PEP8 standard but also by meticulously scanning for common security vulnerabilities and bugs that could potentially compromise the integrity of the authentication process. Our research goes beyond mere identification; we meticulously analyze each warning generated by the SAST tools, emphasizing those warnings that hold the most tremendous significance regarding potential security risks. Furthermore, our investigation extends to gauging the popularity and adoption of each library. To achieve this, we leverage GitHub statistics and harness the power of the Sourcegraph code search utility. By delving into these metrics, we gain a comprehensive view of the community's engagement, usage trends, and overall traction of each library. In summary, this paper thoroughly explores the landscape of JWT authentication in Python, encompassing library evaluation, security assessment, warning analysis, and popularity metrics. [ABSTRACT FROM AUTHOR]

In an ever-changing business environment, frequent new product development projects are inevitable. Ramp-up as a critical lifecycle phase plays a major role in successful product marketing. This paper provides an updated overview of ramp-up concepts, challenges, and strategies, and makes recommendations for managing ramp-up projects. To this end, theoretical insights from the literature provided valuable insights which were extended by the findings of an empirical study. The study consists of a survey conducted between November 2021 and January 2022 in 147 companies from the manufacturing sector. The paper culminates in a set of recommendations to support ramp-up projects, which are structured in three steps: preparation, conducting ramp-up, and transfer to production. The following principles have been identified as highly important in ramp-up projects, namely, agility principles, collaboration and integration, and system robustness and continuous improvement. The recommendations support agile ramp-up management and are designed to help practitioners to deal with frequent ramp-ups in a more effective and structured manner. [Display omitted] [ABSTRACT FROM AUTHOR]

This paper studies the behaviour of the local linear (LL) estimator for regression with nonparametrically generated regressors under weak dependence conditions, effectively extending the main result of Mammen et al. (2012) to the case with strongly mixing (or α -mixing) data. Specifically, we establish that the convergence rate in their Theorem 1 carries over to the case with geometrically α -mixing data. In contrast, this convergence rate does not necessarily remain the same for polynomially α -mixing data. We then apply the obtained uniform stochastic expansion of the second-step LL estimator to derive normal approximations for the LL estimator of a nonparametric censored autoregressive model and the three-step nonparametric estimator of the risk–return regression in finance. A rule for bandwidth selection in nonparametric regressions with estimated covariates to obtain valid inference is also suggested. We then provide a simulation study and a real data application to illustrate the practical relevance of the proposed approach. Lastly, technically speaking, to establish a uniform bound for the upper tail probability of a summation involving polynomially strong-mixing empirical processes, we propose a new exponential inequality, which plays a pivotal role in the proof of the main theorem and is of independent interest. • This paper studies the behaviour of the local linear (LL) estimator for regression with nonparametrically generated regressors under weak dependence conditions. • Derivation of normal approximations for the LL estimator of a nonparametric censored autoregressive model and the three-step nonparametric estimator of the risk–return regression in finance. • A rule for bandwidth selection in nonparametric regressions with estimated covariates to obtain valid inference is also suggested. • A simulation study and a real data application are provided to illustrate the practical relevance of the proposed approach. • A new exponential inequality is also proposed to establish a uniform bound for the upper tail probability of a summation involving polynomially strong-mixing empirical processes. [ABSTRACT FROM AUTHOR]

Research background: With the development of science and technology and the intelligence of the construction industry, the traditional extensive construction method can no longer meet the social demand for safety, which requires the construction enterprises and construction units to constantly change the safety management mode. With the advancement of urbanization, intelligent management and control has become the future development direction of the construction industry, and BIM software has also become an important synchronization platform, which will continuously improve the promotion of the overall project and the management of construction safety. Research methods: This paper mainly uses literature survey, quantitative and qualitative analysis, empirical analysis and other methods, which can study the construction safety management and intelligent management and control as a whole. Through literature survey, this paper has obtained a large amount of literature, which can enrich theoretical analysis and comprehensively understand the current construction safety management mode and intelligent management and control mode. Through relevant theories, this paper can fully demonstrate the follow-up research and empirical analysis. Through quantitative and qualitative analysis method, this paper can use statistical analysis method to analyze construction safety accident data, which will analyze the internal relationship through relevant software. Therefore, the quantitative and qualitative analysis method provides important data support for the subsequent research, which can provide statistical methods for the analysis of building safety hazard sources. Through the empirical simulation method, this paper can analyze specific projects with real cases, which will truly simulate the intelligent monitoring system. Through the empirical simulation method, this paper can verify the scientific nature of the algorithm, and can also demonstrate the management and control mode of the intelligent monitoring system. Research conclusion: Through BIM and RFID, this paper builds an intelligent monitoring system, which also builds the information collection, processing and application stages of the overall framework, and realizes the intelligent management and control of the future construction safety. [ABSTRACT FROM AUTHOR]

The industrial sector absorbs a significant amount of energy and solutions are still being sought, the use of which will allow energy consumption during production processes to be reduced, but which will not influence on the quality of the final product or an order's completion time. One solution is to change the technology in the production process, but such a drastic decision would require a detailed analysis of the profitability of an investment. This article analyses movement in production technology processes towards additive manufacturing (AM) technologies in terms of reducing energy consumption. This paper has used literature studies to describe AM methods, in terms of energy consumption in production companies and a questionnaire survey, which was conducted within 125 automotive manufacturing companies in western Poland and finally for further analysis data from the small and medium sized enterprises (SMEs) were selected in order to determine the impact of the use of AM technology on energy consumption. This sector in particular needs to conduct energy consumption reducing activities at a time when Europe is threatened with massive increases in energy prices. Additionally a statistical analysis was also conducted using correlation coefficients. The results show that the SMEs surveyed, which bore the highest costs of energy consumption in production, declared that they were not interested in implementing AM technology while other companies, incurring high energy consumption costs for illuminating their production halls, saw the benefits of implementing AM and were able to reduce production costs in the assembly stage, use material more effectively and have greater freedom in the design and customization of their products, according to specific customer requirements. It was also determined that managers of manufacturing companies, who are interested in implementing AM would also like to implement water or heat recovery systems. • This paper explores the energy consumption in the context of the implementation of AM. • Employs the empirical analysis Polish SMEs (automotive industry) • Provides the actions taken by manufacturing enterprises to reduce energy consumption • Determines benefits of implementing AM in the automotive industry in the context of energy consumption • The media consumption monitoring system implemented in production processes enhances awareness of energy consumption. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to present research related to the analysis and evaluation of the applicability of project maturity models in organizations conducting research projects, and to propose a project maturity model that could be used in such organizations. The subject of the mixed research undertaken was how to measure the project maturity of organizations conducting research projects (using university as an example). The following research steps were performed: a literature review, empirical research, and a synthesis of the obtained knowledge. [ABSTRACT FROM AUTHOR]

Distortions and resource misallocation cause large productivity losses, especially in developing countries. But removing (all) distortions is infeasible in practice. Policymakers face second-best policy options at best. However, empirical studies typically do not show the productivity gain from a partial removal of distortions. In this paper we analyze the productivity gain from (only) removing ownership distortions within the Hsieh and Klenow (2009) framework using the Vietnam Enterprise Census over the period 2000–2015. We show analytically how the productivity gains from a removal of ownership distortions depends on their covariances with other distortions. Empirically, state-owned enterprises and foreign firms experience significantly lower capital distortions than private firms in most manufacturing industries. However, the removal of ownership distortions has little impact because of complementary size-dependent distortions in Vietnam. This type of analysis can support policymakers in designing productivity enhancing policy interventions in the presence of complementarities. [ABSTRACT FROM AUTHOR]

Online ride-splitting has rapidly evolved worldwide, providing new means to enhance the efficiency of urban travel and reduce the number of vehicles and traffic congestion. While ride-splitting is currently believed to improve vehicle occupancy rates and decrease total travel distances, passengers may perceive it as resulting in additional travel due to ride sharing. To gain a more intuitive understanding of the current operations of ride-splitting, this study delves into carpooling behavior and analyzes its relative impact using GPS trajectory data from DiDi Chuxing in Chengdu, China. The investigation focuses on the behavior of ride-splitting and examines its relative impact based on disparities in total vehicle miles traveled (VMT) and travel duration between ride-splitting traveling (RST) and corresponding separated traveling (ST), aiming to estimate the effect of RST on urban mobility. Following are the three main findings of this study: (a) The existing operation of RST induces 7%–10% extra VMT and 20%–35% extra duration for RST users; (b) The RST achieves 30%–35% VMT and 10%–20% duration saving for drivers who are willing to provide RST service; (c) The RST saves up to 10% VMT and duration varying by time in a day. This paper offers some insights to quantify the current impact of RST and evaluate the orientation of mobility service quality improvement. • Introducing a novel approach to analyzing ride-splitting behaviors. • By leveraging rich GPS data, the research provides a comprehensive analysis of ride-splitting behaviors. • Identifying key limitations, including low ride-splitting rates, prompting future research directions to address this issue. • Providing valuable suggestions and emphasizing the integration of psychological perception benefits. [ABSTRACT FROM AUTHOR]

Shared electric vehicles (SEVs) are an emerging mode of transportation that offers advantages in environmental protection. It is unclear what role travel satisfaction plays in operations. User's feedback is an important factor to the future development of SEVs. How to accurately collect user's feedback and predictions is the focus of attention. In this paper, we innovatively used sentiment analysis to construct the travel satisfaction index based on text data from the largest social network platforms in China. In addition, we used a vector autoregression model to analyse and confirm that users' trip satisfaction is an important factor influencing subsequent use of SEVs. A large-scale data set of travel records combined with point of interest information of SEVs that covered 1.64 million records of 3,100 vehicles. The results showed that low rates of satisfaction of SEVs are attributed to the fault rate of vehicles and poor services. Arranging SEV services around restaurants and commercial areas will result in higher user's satisfaction. Moreover, an increase in user's satisfaction will increase the usage frequency of SEVs in future trips. An increase in satisfaction will reduce rental times of returning users in the short term, but it has no effect on travel distance. • Identified the aspects of travel satisfaction with the Attributional Theory of Motivation and Emotion. • Constructed the travel satisfaction of SEVs based on text mining and sentiment analysis. • The SEV related comments from Internet were taken to reflect the user's emotional expression. • The real-time monitoring driving data was combined with Internet comment data and point of interest information (POI) data. [ABSTRACT FROM AUTHOR]

Doubly censored data are very common in epidemiology studies. Ignoring censorship in the analysis may lead to biased parameter estimation. In this paper, we highlight that the publicly available COVID19 data may involve high percentage of double-censoring and point out the importance of dealing with such missing information in order to achieve better forecasting results. Existing statistical methods for doubly censored data may suffer from the convergence problems of the EM algorithms or may not be good enough for small sample sizes. This paper develops a new empirical likelihood method to analyze the recovery rate of COVID19 based on a doubly censored dataset. The efficient influence function of the parameter of interest is used to define the empirical likelihood (EL) ratio. We prove that − 2 log (EL-ratio) asymptotically follows a standard χ 2 distribution. This new method does not require any scale parameter adjustment for the log-likelihood ratio and thus does not suffer from the convergence problems involved in traditional EM-type algorithms. Finite sample simulation results show that this method provides much less biased estimate than existing methods, when censoring percentage is large. The application to COVID19 data will help researchers in other field to achieve better estimates and forecasting results. • A new empirical likelihood method to analyze doubly censored data. • To use efficient influence function of the parameter of interest to make the efficient empirical likelihood inference. • To apply the efficient empirical likelihood method to analyze the recovery rate of COVID19 based on doubly censored dataset. [ABSTRACT FROM AUTHOR]

"Carbon Peaking" and "Carbon Neutralization" is the strategic direction and key period in the current stage of ecologic civilization construction. Green finance refers to making the financial industry a guide and supervisor of other industries. Green finance will help other industries save energy and reduce emissions to achieve "Carbon Peaking" and "Carbon Neutralization" at an early date. This paper takes Zhejiang, Jiangxi, Guangdong, Guizhou and Xinjiang provinces, which were approved as green finance reform pilot zones in 2017, as examples, and uses synthetic control method to study the constraint effect of the local carbon emissions in pilot zones. The results show that Guizhou has the best emission constraint effect. Jiangxi Province has a certain degree of emission constraint effect. Zhejiang, Guangdong and Xinjiang have no emission constraint effect. The following placebo test results show that the experiment is stable and robust. By combining the actual pilot zones policy schemes and experimental results of the five provinces, this paper concludes that the main reason for the differences in emission constraint effects of the five pilot zones are the differences in the policy selection and the different characteristics of the provinces. Based on this result, relevant policy suggestions are put forward. [ABSTRACT FROM AUTHOR]

Recent commentaries have proposed 'all-world ageing' as a new perspective for social scientific ageing research. It is based on the theoretical observation that the ageing process involves all forms of entities co-ageing relationally with each other, and with their surrounds. Its disciplinary implications hence being that what we categorize as ageing in social scientific ageing research should not be limited to human bodies, and that ageing non-humans should be brought under its purview. To empirically illustrate these theoretical and disciplinary assertions, and explore their implications, the current paper reports a study of how people co-age with non-humans they interact with in their daily lives. Sixteen people aged 66–90 were interviewed, ten of them also being observed at those times. The findings show some intricate and diverse relations that involve their co-ageing with varied biological entities and nature surrounds (such as plants, domestic animals and green spaces) and varied non-biological entities and non-nature surrounds (such as materials, technologies, accommodations, organizations and infrastructures). Meanwhile, important crosscutting themes – including lifespan, function and aesthetics – emerge as objectives of care, valued and exercised in broad terms. This empirical reconnaissance shows the potential for an all-world ageing perspective to engage diverse societal challenges and inform diverse areas of practice as part of a wider ethics of care. From it, a number of important considerations and undertakings arise for future scholarship. • The paper empirically road tests an all-world ageing perspective. • The paper posits that ageing research should not be limited to ageing human bodies. • Older people are found to co-age with biological and nonbiological entities/surrounds. • Lifespan, function and aesthetics are care objectives, valued and exercised broadly. • Theoretical and empirical considerations are highlighted for future scholarship. [ABSTRACT FROM AUTHOR]

This paper analyzes how the increase in the proportion of automated machines to general capital inputs affects the wage gap of the labor force complementary to the two types of capital, the general equilibrium model and constant elasticity of substitution production function are introduced and the impact mechanism is explored using a task-based model. Data for listed Chinese manufacturing companies from 2012 to 2020 is used and a double fixed effects model is invoked for empirical testing. The findings show that (1) a rise in the proportion of automated machines to general capital inputs increases the wage gap of labor complementary to automated machine capital and general capital, and a rise in the proportion of demand for both types of labor complementary to automated machines and general capital is an influential mechanism; (2) the productivity-enhancing effect suppresses the widening of the wage gap between the two types of labor; and (3) the results of heterogeneity analysis show that an increase in automated machine inputs among non-state-owned manufacturing firms and technology-intensive firms widens the labor wage gap. This paper makes a contribution to both theoretical and empirical analysis and provides references for the alleviation of the labor wage gap. • Labor is divided into those complementary to automated machines and general capital. • Increased automated machine input raises the wage gap between labor complementary to automated machines and general capital. • Labor structure and productivity effects are impact mechanisms. • Emphasize human advantages like creativity and social cognitive abilities. [ABSTRACT FROM AUTHOR]

The application of model transformations is a critical component in Model-Driven Engineering (MDE). To ensure the correctness of the generated models, these model transformations need to be extensively tested. However, during the regression testing of these model transformations, it becomes too costly to frequently run a large number of test cases. Test case prioritization techniques are needed to rank the test cases and help the tester during the regression testing to be more efficient. The objective is to rank the fault revealing test cases higher so that a tester can only execute the top ranked test cases and still be able to detect as many faults as possible in the case of limited budget and resources. The aim of this paper is to present a test prioritization approach for the regression testing of model transformations. The approach is based on exploiting the rule coverage information of the test cases. The paper presents an empirical study which compares several techniques introduced by our approach for prioritizing test cases. The approach is complemented with a tool that implements the proposed techniques and can automatically generate test case orderings. [ABSTRACT FROM AUTHOR]

Recently, Social Media (SM)'s adoption as educational instruments in Higher Education (HE) has been gaining popularity among researchers and practitioners. Nonetheless it has been adopted to support various learning approaches such as Cooperative Learning (CL). Despite the growing research in this field, few studies have proposed a comprehensive SM integration framework as well as empirical studies to evaluate its effectiveness. This paper examines how SM is being used as a pedagogical tool in HE and identifies major factors that drives SM's inclusion in HE classrooms. In addition, the paper investigates the effectiveness of a previously proposed integration framework which was developed to promote CL using a popular SM platform, LinkedIn. A survey was administered to collect data from students in different subjects at a university in Australia. Structural Equation Modelling (SEM) was adopted for data analysis using IBM's SPSS26 and AMOS26. One of the notable results of this study is the significant positive relation found between the use of the adopted integration framework and CL, SM challenges' mitigation, students' intention to use SM and their learning process. The findings of this study have important implications for practice and pave the way for future empirical studies. [ABSTRACT FROM AUTHOR]

Whenever the policy challenges to address ask for a strong scientific background, decision makers depend on the underlying research activities. One of the fields in which research is able to affect the design and implementation of policies is given by the Circular Economy (CE). Our purpose in this paper is to understand how scholars carry out their research in the CE to realize whether a common pattern emerge and identify implications for policy. We provide a systematic investigation of the world's ten largest national research communities (NRCs) to highlight differences and similarities and understand the underlying patterns of research. We refer to eight key dimensions, which are mostly original ones and, therefore, represent elements of novelty of the paper: internationality, interdisciplinarity, specialization, relevance of local issues, policy implications, provision of case studies, research focus and research method. A dataset with 3027 CE-related research publications that range from 2001 to 2018 has been used for the elaborations. Results show some similarities and differences: everywhere, the empirical method prevails over the theoretical, and research is mostly focused on the micro-level of analysis (e.g., consumers and firms), while national research communities differ with respect to the openness to international collaborations, the degree with which some specific disciplines contribute to research in the field of CE, and the consideration of local issues provide. • A cross-country comparison of national research communities (NRCs) studying CE is offered. • NRCs are compared along eight key-dimensions using eleven indicators. • Empirical methods prevail over theory and research focus is on micro-level analyses. • Differences emerge with respect to interdisciplinarity and attention to local issues. • China, US, and European countries are moving along diverse research trajectories. [ABSTRACT FROM AUTHOR]

• Childcare policy responses towards Covid-19 differed in European welfare states. • Policy responses cause informalization of childcare to different degrees. • Informalization of childcare is mainly connected with social risks for women. • Cultural and institutional differences help to understand varying policy responses. The closure of extra-familial childcare facilities by European governments in 2020 was an important part of interventions against the spread of the COVID-19 pandemic. One consequence was that childcare was provided by parents at home, mainly by women. As a result, women mainly experienced financial and employment risks related to this "informalization" of childcare. The childcare policies of European welfare states differ in the extent to which they include measures to reduce the social risks related to informalization. Against this backdrop, this paper asks: How should one understand cross-national differences in childcare policies during the pandemic? We are also particularly interested in the effects of childcare policies on the social risks connected with the informalization of childcare and what these mean for the gendered division of paid work and care. Differences in childcare policies during the pandemic are commonly explained in terms of the path dependence of such policies. Using the theoretical approach of "care arrangement," this article introduces a broader theoretical framework that considers the role of cultural and institutional factors for understanding the cross-national differences in childcare policies during the pandemic. We introduce the findings of a comparative empirical study of childcare policies in three European welfare states—Denmark, Germany and England—that represent different types of care arrangements. This paper uses policy and media documents, quantitative data on childcare and women's employment, cultural ideas and secondary analysis of empirical studies. We find that governments did not per se respond to the pandemic based on institutional path dependence regarding childcare policies, while the integration of culture into the theoretical framework allows for a more comprehensive understanding. [ABSTRACT FROM AUTHOR]

Electroencephalography (EEG) is commonly used for measuring brain activity information due to its high temporal resolution. However, it severely suffers from noises produced by non-brain sources, called EEG artifacts. Ocular, muscle, and power line artifacts are the most common ones. In this paper, a novel two-stage automatic artifact removal method is proposed to handle different artifacts under miscellaneous EEG applications. Empirical wavelet transform (EWT), canonical correlation analysis (CCA), and an outlier detection algorithm, isolation forest constitute the pipeline. In the first stage, EEG data are decomposed by CCA and preliminary purified by isolation forest. In the second stage, a further decomposition of the EEG data is conducted using EWT and CCA, followed by removal of irrelevant components using isolation forest. We thoroughly evaluate the qualitative and quantitative performance of the proposed method on multiple datasets. Experiment results show that the proposed method can effectively remove artifacts under complex conditions and different signal-to-noise ratios. Ablation studies and comparison results demonstrate the significance of the two-stage combination, which outperforms single-stage methods and state-of-the-art methods. This paper explores the potential for a fully data-driven and adaptive way for robust artifact removal in various EEG applications. • We combined empirical wavelet transform (EWT) with canonical correlation analysis and isolation forest. • We designed a two-stage removal process which focused on different artifacts at different stages. • We tested our method on multiple datasets, in a variety of ways. [ABSTRACT FROM AUTHOR]

• Multi-source data and econometric models are used to study charging demands of operating EVs. • Charging demands are spatiotemporal uneven, with peak hours and areas. • Irregular spatial division can mirror spatial features of charging demands. • Low SOCs, parking lots, population and road network density have positive effects on demands. • Charging demands of adjacent units are dependent, especially in peak areas. In order to address the mismatch between the current charging demand of electric vehicles and the layout of charging stations, this paper collects multi-source heterogeneous data that may affect charging demand, and explores their spatiotemporal distributions in depth. Then, this paper proposes a Voronoi polygon spatial partitioning method based on charging demand clustering and two spatial econometric models, spatial lag model (SLM) and spatial error model (SEM), to quantitatively analyze the influences of various elements on charging demands. Empirical research in Chongqing, China reveals that the spatiotemporal distribution of charging demand is uneven, with peak areas and periods for charging, and the division of Voronoi polygon can better reflect the spatial heterogeneity of charging demands than regular grid division. The positive factors include the low SOC, parking lot density, population density, and road network density, especially the low SOC and parking lot density, and the negative items contain consumption related Point Of Interest (POI), tourism related POI, and transportation hub related POI. Among them, population density and road network density, as static data, have similar influences on charging demands at different intervals, while the impact of other factors on charging demand varies with periods, with obvious peak-valley characteristics. There is spatial dependence and lag effect between charging demands within polygons, causing SLM outperforms SEM. The research results are beneficial for the rational siting and optimization of charging stations. [ABSTRACT FROM AUTHOR]

Conventional empirical methods for rock mass characterisation can only offer limited understanding and qualitative statements of rock mass condition based on past experience in similar geological conditions. Quantifiable measures; such as possible block size, block shape, fracture trace length, etc; are not directly obtained. When possible, determination of these parameters often involves a convoluted process. It should be acknowledged that these factors influence the behaviour of a rock mass during excavation and sole reliance on empirical methods potentially constrains our understanding of rock mass behaviour during excavation. This can lead to less than optimum designs or in more severe cases rock mass failure, if the governing failure mechanism is not properly understood. The study in this paper attempts to evaluate the applicability of a DFN approach as a forward modelling tool in estimating rock mass condition using data from a completed underground project to verify the proposed methodology. This paper demonstrates the DFN models ability in estimating ranges of potential fracture intensities and fracture trace lengths to be encountered on site during excavation. The DFN predictions have been compared to the actual data mapping data to assess the effectiveness of the method. The DFN models exhibit 'resemblance', albeit not an exact match, to the actual tunnel face conditions encountered. The results and comparisons described in this paper also demonstrate that adopting DFN approach can allow more objective, realistic, detailed, and site-specific rock mass characterisation and risk assessment work to be completed when undertaking the design, by reducing the influence of personal bias, experience and engineering judgement. Lastly, the study results also indicate that the DFN approach, utilising more realistic rock mass models, also offers opportunities in optimising underground support design compared to traditional approaches. Despite the benefits, the inherent limitations of DFN models highlighted at the end of the paper, still need to be taken into consideration when preparing a design. [ABSTRACT FROM AUTHOR]

Unconditional basic income (UBI) is one of the most discussed policy options for a degrowth transition. Advocates highlight UBI's theoretical potential to reduce unnecessary material consumption, alleviate poverty and redistribute social wealth, achieve wellbeing within ecological limits, shift activity from wage-labour to meaningful work, and facilitate increased social participation. However, UBI's radical potential remains under-examined within the empirical research, which focuses more on the policy's potential to increase the supply of wage-labour and stimulate economic growth. This paper aims to push back against this limiting trend. It begins by outlining some of the characteristics of more sustainable and just societies, based on post-growth perspectives, and outlines the arguments put forward to support UBI's compatibility with a degrowth transition. It then demonstrates that, despite support from UBI and many post-growth scholars, such arguments are not mainstreamed in the contemporary empirical UBI research. The paper argues that this increases the risk of UBI being captured by capitalist interests. To avoid this outcome, the paper proposes an alternative research agenda to help assess and advance UBI's radical potential in line with post-growth visions. • How do the characteristics of modern societies compare to those that align with post-growth perspectives? • UBI is advocated for having a role to play in the transition to more sustainable and just societies. • However, much of the empirical UBI research neglects to address many of the questions raised in the post-growth literature. • Understanding UBI's potential contribution to a degrowth transition therefore requires a new research agenda. [ABSTRACT FROM AUTHOR]

Based on the panel data of various daily air pollution indicators of 288 prefecture-level cities in China from January 1, 2015 to December 31,2018, this paper takes the first round of central environmental protection inspection (CEPI) as a quasi-natural experiment, and empirically analyzes its impact on urban air pollution by using multi-period difference-in-difference (DID) method. The results show that: (1) the first round of five batches of environmental inspection and two batches of "looking back" have significantly reduced the concentration of seven pollutants; (2) The first five batches of environmental inspection have a stronger impact on reducing air pollution than "looking back"; Moreover, in the short tel·in after the inspection, it still has a significant reduction effect on air pollution; (3) The impact of central environmental protection inspection on air pollution shows strong heterogeneity in different batches of inspections, urban scale and economic development level, as well as the air quality level of cities before the inspection. The research results of this paper provide corresponding policy recommendations and decision-making basis for the Chinese central government to further deepen the reform of environmental protection supervision mechanism and promote the emissions of multiple pollutants mitigation. [ABSTRACT FROM AUTHOR]

Despite the advent of enormous computing power and the switch to the web as the primary means of reporting empirical research results, papers available online present data on a screen exactly as if it was a printed page. It is now straightforward to program analyses to create interactive figures that allow readers to hover the cursor over a graph and see numerical estimates and tables that allow presentation of data according to user-defined inputs. We recommend that interactive apps for statistical results be routinely included in the HTML versions of medical research papers or as supplementary material. [ABSTRACT FROM AUTHOR]

In sample surveys, when we need information regarding rare sensitive issues which people often do not prefer to share with others. In such situations this is also awkward for interviewers to ask the direct questions related to confidential and private matters of interviewees. An approach towards the open queries about sensitive issues generally results in the high non-response rates or misleading answers. The aim of this paper is to develop an effective randomized response model to overcome with these types of challenges arising due to sensitive nature of characteristic under study. In this paper we have proposed three-stage randomized response model for estimating mean number of individuals who possessed rare sensitive attribute which makes use of Poisson distribution. The properties of the proposed estimation procedures have been deeply examined when the parameter of a rare unrelated attribute is known as well as unknown. Privacy protection of respondents is also an equally important matter of concern. So measure of privacy protection for the proposed randomized response model has also been examined. Empirical studies are performed to support the theoretical results, which show the dominance of the proposed estimators over well-known contemporary estimators. From the findings of this study we may conclude that proposed randomized response model is rewarding in terms of percent relative efficiencies and privacy protection and may be recommended to survey practitioners for real life applications. [ABSTRACT FROM AUTHOR]

• An empirical study of the performance of the 6th generation ports (6GP) model is conducted for six container ports in mainland China. • A novel hybrid methodology is developed, comprising of CFPR, TOPSIS, and VIKOR. • Insights and implications for port managers, shipping companies, freight forwarders, and policy-makers, are suggested in the post-pandemic era. • This paper contributes to expanding the port devolution theory. Since the UNCTAD proposed the initial port model, called the first generation port model (1GP) in 1994, its adaptation and transformation have evolved, reflecting not only the evolution of port operations and technological advancements, but also the resilience of ports to natural disasters and supply disruptions. Recently, the trio of COVID-19, digitalization, and decarbonization (CDD) has emerged as core challenges whilst providing numerous opportunities for building adaption and resilience for the port industry. In light of this, the sixth generation ports (6GP) model has emerged. This paper addresses crucial research gaps by empirically testing the 6GP model, emphasizing the impact of emerging factors of the CDD, including 1) the lack of empirical testing for the 6GP model and the emphasis on the CDD; 2) the exploration of factors contributing to the significant development of Chinese container ports; 3) the investigation into how the CDD lead to the reversal of the port devolution continuum path. In doing so, an empirical study has been conducted, focusing on six major container ports in mainland China, all of which are among the world's top 10 container ports in terms of container throughput. It evaluates the importance of the criteria of the 6GP model with the performance of the six ports. The findings of this research are discussed for managerial and policy implications, enriching the existing literature on port devolution, and providing the port industry with a holistic view of port development and strategy in the post-pandemic period. [ABSTRACT FROM AUTHOR]

Advanced organizational processes today require many process-relevant artifacts to be formally represented in process models. As these processes become more complex, process designers face the challenge of maintaining high comprehensibility while adequately visualizing process-relevant information. Modularization has been introduced to address the increasing complexity and information overload of process models, tackling this issue. While research acknowledges the importance of process model comprehensibility in order to benefit from the merits of such models, there still needs to be more clarity about the benefits of process model modularization. Recent research has focused on the human visual system and investigated visual behavior in the context of process model literacy. Continuing this branch of research, this paper analyses gaze behavior when comprehending modularized process models. A follow-up eye-tracking study was conducted to comprehend differently modularized BPMN 2.0 process models (i.e., vertical, horizontal, orthogonal). The results indicated that process model readers comprehend modularization approaches differently. Vertical modularization was perceived as the best comprehensible approach, whereas horizontal received the least acceptance. Considered eye movement performance measures confirm prior observation that attention is deployed more effectively in vertical modularization. Based upon the findings, the paper proposes a revised theoretical model from prior work that relates visual tasks to the execution of visual routines, explaining comprehension and information processing in modularized process models. The theoretical model elaborates how the visual system process and comprehends information obtained from modularized process models. Furthermore, the paper derived implications for modeling and practical applications, pointing out solid representational points and shortcomings of each modularization approach regarding how modularized process models are read and comprehended. [ABSTRACT FROM AUTHOR]

The purpose of this study is to analyze how cultural difference plays a different role in overseas tourists of different age groups. It examines how perceived cultural differences affect the perceived value of tourists from different age groups, in their travel abroad and, consequently, their satisfaction. The paper is based on self-determination theory (SDT) and develops a structural equation model (SEM) between tourists' cultural needs, perceived cultural differences, perceived value and satisfaction. Through textual analysis, questionnaires and interviews, this paper conducts three studies to empirically analyze the relationship between cultural difference variables related to overseas tourism and tries to explore the influence mechanisms of the cultural differences. The effects of cultural SDT needs of autonomy, competence, and relatedness have different effects upon different age groups. Cultural factors play a significant role in influencing the experience of young tourists, but not in older tourists. The possible reasons why cultural differences play different roles in different groups of people are also explored. • The perceived cultural differences have no direct effect on perceived value in the context of overseas tourism. While the moderating effects of perceived cultural differences are confirmed. • Satisfaction of self-determination theory needs has no effects on the elderly groups. Conversely, among the younger group, the effects are significant. [ABSTRACT FROM AUTHOR]

This paper makes the first attempt to look at the response of the energy market to the shock from the AI industry and the role of AI in the energy market risk spillover network. The innovation of the paper lies in adopting a quantile-based and time-varying framework in the empirical analysis. This enables us to reveal the cross-quantile and lead-lag correlations between AI and the energy market. We find that an extreme negative shock from AI tends to correspond to an extreme downward movement in crude oil, gasoline, gas oil, and clean energy markets and the shock response dissipates after 66 days. Meanwhile, the cross-quantile correlations are subject to structural changes once the extreme events arrive. As for the total spillover effect of the energy market, it increases by 5.34 % after AI is considered as a source of uncertainty in the risk spillover network dominated by the crude oil market. Thus, the shock from AI challenges the stability of the energy market. A close relationship between the AI industry and the clean energy market is also identified. We contribute to studying the relationship between the AI industry and the energy market from the perspective of the risk connectedness between the two fields. [Display omitted] • The extreme negative shock from AI corresponds to the extreme downward performance in the energy market. • The cross-quantile correlations are subject to structural changes once the extreme events arrive. • The total spillover index of the energy market increases by 5.34 % after AI is considered. • A close relationship between the AI industry and the clean energy market is identified. [ABSTRACT FROM AUTHOR]

The article is theoretical and empirical in nature. The primary research objective was to assess the feasibility of implementing flexicurity to IT companies, with a special focus put on its benefits and barriers. The achievement of the above objective was determined by the use of specific research methods. In the research process, critical analysis of the literature, content analysis, comparative methods, analytical-descriptive methods, and logical analysis were used. In addition, the above objective also conditioned the structure of the article. In the first part, relying on the literature, the definitions of the concept of flexicurity were analyzed, which made it possible to present in the second part of the paper, the selected results of the empirical study on the awareness, benefits and barriers resulting from the implementation of flexicurity to IT enterprises. The study covered 156 IT companies. [ABSTRACT FROM AUTHOR]

This paper is concerned with unloading of containers at ports, which are key to international trade. Work on the gantry cranes takes place 50 m above ground level in an operation room with a glass footwell, which causes to arise a psychological bias. We conducted a line-of-sight measurement of gantry crane operators working in such an environment. Based on this data, cognitive bias was defined by our own, and certain characteristics could be found by visualizing the relationship with years of experience. We discuss how this can be used for skill transfer [ABSTRACT FROM AUTHOR]

The China–Singapore International Land–Sea Trade Corridor (C-S-ILSTC) was officially proposed in 2018, under the government-to-government framework of the China–Singapore (Chongqing) Demonstration Initiative on Strategic Connectivity. C-S-ILSTC is expected to play an important role in the international trade and connectivity between Western China and Southeast Asia, where Chongqing serves as the logistics hub in Western China, and Singapore is a transshipment hub for Association of Southeast Asian Nations (ASEAN) region. This paper aims to analyse the newly formed intermodal freight container transport network in the context of C-S-ILSTC and China–Singapore/ASEAN region quantitatively from both supply and demand sides, and investigate C-S-ILSTC's advantages and disadvantages. For the demand side analysis, the results show that the trade volume between China and ASEAN countries is forecasted to consistently increase in recent years, and the most commonly traded cargo types between China and ASEAN have also been identified. For the supply side analysis, we examine the infrastructure and development status of the essential nodes along C-S-ILSTC. In addition, we also compare C-S-ILSTC with the conventional intermodal container transport routes connecting Western China and Southeast Asia, and discuss the development prospect of C-S-ILSTC. The results of this study could provide policy implications for the development of C-S-ILSTC and the cooperation between China and ASEAN region. • Research on the newly formed intermodal freight container transport network • Quantitative analysis from both supply and demand sides • Investigate the advantages and disadvantages of C-S-ILSTC • Discuss the development prospect of C-S-ILSTC • Provide policy implications for C-S-ILSTC development and regional cooperation [ABSTRACT FROM AUTHOR]

Like other organizations, academic libraries strive to reshape and rethink their services and skills to preserve their relevance and contribution; innovation is becoming a survival strategy. Besides, knowledge sharing (KS) is believed to be an important factor in creating innovative capabilities and improving innovation. Yet, only scanty empirical research has investigated the possible effect of KS on service innovation (SEI), and empirical evidence on the possible effects of other innovations on SEI is lacking. This study adopted a theoretical framework to analyze the effect of KS on SEI as well as the mediating effects of information technology innovation (ITI) and management innovation (MIN) on the relationship between KS and SEI. The results are derived using a data set from two large academic libraries in Egypt. Although KS has a significant total effect on SEI, its role in augmenting SEI is only secondary since it depends mainly on the mediating role of ITI and MIN. The implications and limitations of these results are further discussed in the paper. • knowledge sharing (KS) is an important factor in creating innovative capabilities and improving innovation in academic libraries. • Yet, only scanty empirical research has investigated the possible effect of KS on service innovation (SEI), and empirical evidence on the possible effects of other innovations on SEI is lacking. • A research model was adopted to analyze the effect of KS on SEI as well as the mediating effects of information technology innovation (ITI) and management innovation (MIN) on the relationship between KS and SEI, using a data set from two Egyptian academic libraries. • Although KS has a significant total effect on SEI, its role in augmenting SEI is only secondary since it depends mainly on the mediating role of ITI and MIN. [ABSTRACT FROM AUTHOR]

In the past 40 years, a large number of children have been abandoned or abducted in China. We argue that the implementation of the one-child policy can help to explain changes in the patterns of both child abandonment and child abduction. We also contend that the cultural preference for sons in China has shaped unique gender-based patterns, as attested to by the fact that the majority of the children who are abandoned are girls and the majority of the children who are abducted are boys. We provide empirical evidence for the following findings: (1) Stricter implementation of the one-child policy leads to more child abandonment locally and more child abduction in neighboring regions; (2) A stronger son-preference bias intensifies both the local effects and spatial spillover effects of the region's one-child policy on child abandonment and abduction; and, (3) With the gradual relaxation of the one-child policy after 2002, the frequency of both child abandonment and child abduction has decreased significantly. This paper is the first to provide empirical evidence regarding the unintended consequences of the one-child policy in relation to missing children in China. [ABSTRACT FROM AUTHOR]

While the pursuitworthiness of philosophical ideas has changed over time, philosophical practice and methodology have not kept pace. The worthiness of a philosophical pursuit includes not only the ideas and objectives one pursues but also the methods with which one pursues them. In this paper, we articulate how empirical approaches benefit philosophy of science, particularly advocating for the use of qualitative methods for understanding the social and normative aspects of scientific inquiry. After situating qualitative methods within empirical philosophy of science, we discuss how to adapt these traditionally sociological methods to empirically inform philosophical questions. Our aim is to normalize and legitimize qualitative methods for philosophical purposes and discuss how they can elucidate descriptive and normative components of scientific practice in a more generalizable non-idealized manner. We contend that qualitative methods are particularly well suited to philosophical interest in the social norms of science, their achievability, and their mutability. Furthermore, unlike more historical case studies in philosophy, qualitative methods enable more confidence in generalizability, albeit limited, from a concrete sample to a larger class. We conclude by addressing anxieties about the distinctness of empirical philosophy of science from social epistemology and from sociology of science. • Argues for more inclusive boundary-work & a more diverse philosophical methodology. • Motivates disciplinary openness regarding adapting methods to inform philosophical questions empirically. • Discusses the data, explanations, and ideas afforded by qualitative methods. • Incorporates descriptive and normative components to study scientific reasoning and inquiry in practice. • Considers the scope of generalizability for qualitative studies in philosophy. [ABSTRACT FROM AUTHOR]

Deep learning based methods have significantly boosted the study of automatic building extraction from remote sensing images. However, delineating vectorized and regular building contours like a human does remains very challenging, due to the difficulty of the methodology, the diversity of building structures, and the imperfect imaging conditions. In this paper, we propose the first end-to-end learnable building contour extraction framework, named BuildMapper, which can directly and efficiently delineate building polygons just as a human does. BuildMapper consists of two main components: 1) a contour initialization module that generates initial building contours; and 2) a contour evolution module that performs both contour vertex deformation and reduction, which removes the need for complex empirical post-processing used in existing methods. In both components, we provide new ideas, including a learnable contour initialization method to replace the empirical methods, dynamic predicted and ground truth vertex pairing for the static vertex correspondence problem, and a lightweight encoder for vertex information extraction and aggregation, which benefit a general contour-based method; and a well-designed vertex classification head for building corner vertices detection, which casts light on direct structured building contour extraction. We also built a suitable large-scale building dataset, the WHU-Mix (vector) building dataset, to benefit the study of contour-based building extraction methods. The extensive experiments conducted on the WHU-Mix (vector) dataset, the WHU dataset, and the CrowdAI dataset verified that BuildMapper can achieve a state-of-the-art performance, with a higher mask average precision (AP) and boundary AP than both segmentation-based and contour-based methods. We also confirmed that more than 60.0/50.8% of the building polygons predicted by BuildMapper in the WHU-Mix (vector) test sets I/II, 84.2% in the WHU building test set, and 68.3% in the CrowdAI test set are on par with the manual delineation level. [ABSTRACT FROM AUTHOR]

The paper deals with the subject of R&D project management in the early phases of project life cycle. A multiple holistic case study was conducted, where the selected research subjects were representatives of research and development institutes, industrial companies and universities. Interviews with them concerned the ways in which R&D projects are managed. On the basis of conversations with respondents and literature review, recommendations and good practices were established in terms of R&D project management in the early stages of the life cycle, i.e. initiating and planning. [ABSTRACT FROM AUTHOR]

This paper investigates the effectiveness of four different airfoil collars (b c 1 , b c 2 , b c 3 , and b c 4 ) in reducing scour around the bridge pier. A total of 69 experiments are conducted under two threshold velocities with two pier diameters of 0.05 and 0.06 m and four airfoil collars placed at four locations from the uniform sediment bed. This study investigates the scour hole profiles and their depth, effect of flow intensity, collar diameter, and location on scour depth, and computes the protection efficiencies. The results show that the collar effectively reduces the scour depth. When the collar is located at bed level (i.e., y = 0, where y is water depth from the bed), y /4, y /2, and 3 y /4 above the bed level, the protection efficacies are found to be ranging between the percentages 65–100%, 40–53%, 23–38%, and 8–29% for b c 1 , b c 2 , b c 3 , and b c 4 , respectively. An empirical relationship is proposed for variation of scour depth with respect to time. Statistical sensitivity analyses are performed and found that the most and least sensitive parameters are h / y and T c , where h and T c are the collar's location from the water surface and dimensionless time, respectively. • This paper investigates the effectiveness of four different airfoil collars (b c 1 , b c 2 , b c 3 , and b c 4 ) in reducing scour around the bridge pier. • This study investigates the scour hole profiles and their depth, effect of flow intensity, collar diameter, and location on scour depth, and computes the protection efficiencies. The results show that the collar effectively reduces the scour depth. • When the collar is located at bed level (i.e., y = 0, where y is water depth from the bed), y /4, y /2, and 3 y /4 above the bed level, the protection efficacies are found to be ranging between the percentages 65–100%, 40–53%, 23–38%, and 8–29% for b c 1 , b c 2 , b c 3 , and b c 4 , respectively. • Empirical relationships are proposed for maximum scour depth and variation in scour depth with time. • Statistical sensitivity analyses are performed and found that the most and least sensitive parameters are h / y and T c , where h and T c are the collar's location from the water surface and dimensionless time, respectively. [ABSTRACT FROM AUTHOR]

• Discretion is affected by individual, relational and organisational factors. • In an experimental design, we study what affects discretion. • The use of interpreters is dependent on relation to the child. • Interpreter services are less likely to be used in acute situations. • The use of interpreter services is less dependent on the children's language skills. This paper focuses on child welfare workers' discretionary decision making. They can rely on routines, procedures and manuals as part of their work, but in the end, they still have to make a choice, based on the available information at the time. Discretionary decision making is a way of reasoning when facing uncertainty in professional work and when laws, rules and systematic knowledge must be applied in specific cases. A larger body of research on discretion and discretionary decision making in social work has developed, but there remains much ground to cover in terms of empirical analyses of how discretionary processes play out in real-life contexts. The two main research questions ask how the characteristics of each child and context and of social workers and their work situation affect the latter's decision to use interpreter services in their work with unaccompanied minors and children from minority backgrounds. The decision to use or not to use interpreter services in different situations, as an act of discretionary decision making by child welfare workers, is analysed in this paper. To study discretionary decision making among child welfare workers, a combination of a traditional survey and a vignette experiment has been used, bringing together organisational features, individual traits and situational characteristics. The findings indicate that interpreter services are less likely to be used in acute situations and more likely to be used with the children whom the child welfare staff members know better, irrespective of the children's language skills. The analyses also show varying effects of the staff's training and educational backgrounds, and surprisingly, the negative effects of institutional guidelines. One possible interpretation of this is that the guidelines are perceived as rigid constraints, instead of positive recommendations for actions. [ABSTRACT FROM AUTHOR]

Accelerating the sustainability transition demands managers to more intensively and more frequently envisage in supererogatory acts. Supererogatory action is not legally or morally required but consist of praiseworthy acts beyond duty that have the capacity to build a better future. This perspective paper argues that strategic decision-making during sustainability transitions should be more supererogatory, and research should pay more explicit attention to the supererogatory acts of managers and business organizations. Supererogation is especially important in any transition, where the business environment is changing rapidly and fundamentally, where stakeholder preferences conflict and first-mover advantages are significant. Our argument is that perceived rightness and confidence are prerequisites for managers to envisage desirable futures and act in ways that transcend duty. We also critically reflect on the threats implied by supererogatory management. Our arguments are illustrated by interview data collected from Finnish managers with first-hand experience with supererogatory acts in the current sustainability transitions of the food packaging industry. We call for empirical research explaining the role of supererogatory management in driving sustainability transitions in different settings and hope that this perspective paper can spur the awareness of managers and policy makers regarding the power of supererogatory acts in management. • Managers must consider supererogatory actions to accelerate sustainability transitions. • Supererogatory acts are ethically praiseworthy beyond duty. • Supererogatory management requires perceived rightness and confidence of managers. • Managers can be role models if firms provide psychological safety and accept risk. • Supererogatory management is a complement to traditional management. [ABSTRACT FROM AUTHOR]

In this paper, we consider function-indexed normalized weighted integrated periodograms for equidistantly sampled multivariate continuous-time state space models which are multivariate continuous-time ARMA processes. Thereby, the sampling distance is fixed and the driving Lévy process has at least a finite fourth moment. Under different assumptions on the function space and the moments of the driving Lévy process we derive a central limit theorem for the function-indexed normalized weighted integrated periodogram. Either the assumption on the function space or the assumption on the existence of moments of the Lévy process is weaker. Furthermore, we show the weak convergence in both the space of continuous functions and in the dual space to a Gaussian process and give an explicit representation of the covariance function. The results can be used to derive the asymptotic behavior of the Whittle estimator and to construct goodness-of-fit test statistics as the Grenander–Rosenblatt statistic and the Cramér–von Mises statistic. We present the exact limit distributions of both statistics and show their performance through a simulation study. [ABSTRACT FROM AUTHOR]

• This paper empirically analyses the effect of natural resources rents on the size of informal economy in sub-Saharan Africa (SSA). • The estimation procedure include Pooled OLS and GMM System. • The results reveal that natural resources rents increase the size of informal economy in SSA. • These results are robust to several sensitivity analyses. • The positive relationship between natural resource rents and the size of the informal economy becomes negative when good and strong institutions are in place. Despite the extensive literature on the resource curse, little is known about the empirical relationship between natural resource abundance and the size of the informal economy. Theoretical predictions suggest that natural resource abundance contributes to the growth of the informal economy because the investments and expenditures associated with natural resource revenues limit opportunities in the formal sector, thereby channeling more labor and firms into the informal sector. This theory is empirically tested using data from 44 sub-Saharan Africa countries over the period 1991-2015. The main results reveal a positive and significant relationship that natural resource abundance favors the growth of the informal sector in SSA. These results are robust to several tests. Furthermore, the positive relationship between natural resource abundance and the size of the informal economy becomes negative when good and strong institutions are in place. [ABSTRACT FROM AUTHOR]

The increasing number of private vehicles has caused severe traffic congestion and air pollution. As an innovative transportation mode, mobility services such as ridesharing have been considered as an alternative. However, it has been evidenced that most private vehicle owners would not switch from driving to using ridesharing because such options only attract those who never intend to own a car. Therefore, it is more meaningful for private vehicle owners to provide ridesharing services, also known as Hitch, which can improve urban traffic efficiency on the service supply side. This study outlines an empirical study which is conducted to assess drivers as a group, to examine the factors which influence their intention of ridesharing. A sample of 597 private vehicle owners in Tianjin, China, completed a questionnaire. Structural equation modeling (SEM) is implemented to analyze the proposed model, specially explore the mediating role of trust and habit. The results indicate that habit is the most important factor, which is mainly influenced by extrinsic motivation (i.e., instrumental motive). Furthermore, habit can increase trust in ridesharing, another important factor, which is mainly affected by intrinsic motivation (i.e., affective motive and responsibility). Therefore, this shows the relationship between intrinsic motivation and extrinsic motivation. The findings in this paper have strong implications for both governments and platform developers, to promote the transition from solo driving to ridesharing to improve traffic condition and environmental pollution. • We test the factors leading private vehicle owners to share a ride, on the service supply side. • This study analyzes trust and habit as mediators bridging motivations. • Motivation theory and material possession theory (MPT) are used. [ABSTRACT FROM AUTHOR]

We consider nonparametric invariant density and drift estimation for a class of multidimensional degenerate resp. hypoelliptic diffusion processes, so-called stochastic damping Hamiltonian systems or kinetic diffusions, under anisotropic smoothness assumptions on the unknown functions. The analysis is based on continuous observations of the process, and the estimators' performance is measured in terms of the sup -norm loss. Regarding invariant density estimation, we obtain highly nonclassical results for the rate of convergence, which reflect the inhomogeneous variance structure of the process. Concerning estimation of the drift vector, we suggest both non-adaptive and fully data-driven procedures. All of the aforementioned results strongly rely on tight uniform moment bounds for empirical processes associated to deterministic and stochastic integrals of the investigated process, which are also proven in this paper. [ABSTRACT FROM AUTHOR]

A growing number of studies in forensic voice comparison have explored how elements of phonetic analysis and automatic speaker recognition systems may be integrated for optimal speaker discrimination performance. However, few studies have investigated the evidential value of long-term speech features using forensically-relevant speech data. This paper reports an empirical validation study that assesses the evidential strength of the following long-term features: fundamental frequency (F0), formant distributions, laryngeal voice quality, mel-frequency cepstral coefficients (MFCCs), and combinations thereof. Non-contemporaneous recordings with speech style mismatch from 75 male Australian English speakers were analyzed. Results show that 1) MFCCs outperform long-term acoustic phonetic features; 2) source and filter features do not provide considerably complementary speaker-specific information; and 3) the addition of long-term phonetic features to an MFCCs-based system does not lead to meaningful improvement in system performance. Implications for the complementarity of phonetic analysis and automatic speaker recognition systems are discussed. • The evidential strength of long-term acoustic phonetic features, MFCCs, and combinations thereof was evaluated. • Non-contemporaneous recordings with speech style mismatch from 75 male Australian English speakers were analyzed. • MFCCs consistently outperform long-term acoustic phonetic features. • Source and filter features do not provide considerably complementary speaker-specific information. • The addition of long-term phonetic features to an MFCCs-based system does not lead to meaningful improvement in system performance. [ABSTRACT FROM AUTHOR]

Neural network based models have emerged as a powerful tool in multiscale modeling of materials. One promising approach is to use a neural network based model, trained using data generated from repeated solution of an expensive small scale model, as a surrogate for the small scale model in application scale simulations. Such approaches have been shown to have the potential accuracy of concurrent multiscale methods like FE 2 , but at the cost comparable to empirical methods like classical constitutive models or parameter passing. A key question is to understand how much and what kind of data is necessary to obtain an accurate surrogate. This paper examines this question for history dependent elastic–plastic behavior of an architected metamaterial modeled as a truss. We introduce an iterative approach where we use the rich arbitrary class of trajectories to train an initial model, but then iteratively update the class of trajectories with those that arise in large scale simulation and use transfer learning to update the model. We show that such an approach converges to a highly accurate surrogate, and one that is transferable. • Proposes Recurrent Neural Operator as a surrogate for multiscale modeling • Addresses history dependent elastic–plastic behavior of an architected metamaterial • Introduces an iterative approach to training neural approximations [ABSTRACT FROM AUTHOR]

The gains of sustainability-oriented interventions are threatened by the existence of so-called rebound effects (RE), i.e., higher-order effects of interventions arising due to systemic responses which partially or completely offset potential sustainability gains. While the number of theoretical and empirical studies exploring RE has proliferated, the literature remains highly fragmented and disordered. This paper aims to consolidate and systematize the body of empirical RE studies in its entirety to connect the disjointed literature and shed light on existing research gaps for the identification of future research avenues. Through a systematic literature review, six critical points are identified: (1) an under-exploration of certain RE (i.e., RE outside of direct and economy-wide RE initiated by (energy) efficiency at the household- and macroeconomic production-level); (2) uneven distribution of explored RE mechanisms (i.e., a narrow focus on monetary re-spending effects); (3) a lack of studies exploring the interrelatedness and interdependence of RE mechanisms; (4) a strong emphasis on generalized mechanisms and an underemphasis on context-dependent RE; (5) comparability problems associated with unharmonized RE magnitude estimation techniques and heterogeneity of RE cases; and (6) ambiguity surrounding RE definitions impeding interdisciplinary research. Finally, three research avenues for future research are proposed. [ABSTRACT FROM AUTHOR]

Since its onset in 2020, the COVID-19 pandemic has globally disrupted school operations, leading to a shift to some form of homeschooling arrangements. After two years, in March 2022, the government of Malaysia officially reopened all schools, ending its homeschooling program. In this paper, we exploit a purposefully designed, nationwide, cross-sectional survey of government-owned primary and secondary schools in Malaysia to document student learning experiences during the early months of the home-to-school transition. Our empirical analysis and choice of indicators is guided by a conceptual framework that distinguishes between two competing hypotheses related to school reopening experiences: resumption vs transitional disruption. We find that 59 % of secondary and 72 % of primary level students report that they are happy to be back in school. School reopening also coincides with a significant reduction in educational-related worries (e.g., concerns over dropout, learning loss, and loss of interest in study) and indices of negative emotions (i.e., feelings of being tense, depressed, and restless), particularly among secondary school students. More importantly, those satisfied upon return to school report a statistically significant reduction in worries related to learning loss. These correlations support the resumption hypothesis. Yet our data highlights an important puzzle: Even after school reopening, one-third of students report that they do not learn more, at least one-fifth report a struggle to catch up on studies, and up to 40 % are concerned about learning loss. The majority of learners additionally report not receiving more support from teachers and parents. Recipients of public aid as well as private (i.e., parental) support report being happy about school reopening and are less likely to report "not learning more." We conclude by discussing these somewhat paradoxical findings and the need for remedial measures beyond financial support for struggling learners to minimize post school reopening, transitional disruptions. • We develop a conceptual framework for the home-to-school transition, differentiating between resumption and disruption hypotheses. • Data from Malaysia's "Trust Schools Programme" is collected to analyze student experiences during the initial transition months. • Student responses show support for the resumption hypothesis, with reduced education-related worries and negative emotions upon school reopening. • Students satisfied with home schooling (PdPR) also reported positive experiences with school reopening, including less absenteeism, more study time, and increased happiness. • Significant disruptions were also reported, such as limited learning progress, struggles to catch up, learning loss concerns, and lack of support from teachers and parents. [ABSTRACT FROM AUTHOR]

Soil thermal conductivity (k) is an important parameter for geotechnical engineering temperature field analysis and energy pile design. It is affected by various factors such as degree of saturation, dry density, and mineral composition. Due to the nonlinear correlation between k and these influencing factors, accurate prediction of k is of great significance to guide practical engineering. In this paper 337 soil thermal conductivity data were collected and the intrinsic correlations between k and the influencing factors were systematically analyzed. Based on the Johansen model, a new predictive model was developed by the multivariate probability distribution (MPD) method. The proposed model was also verified by making a comparative analysis with the empirical ones. The results show that the Johansen model has a superior performance in predicting k after the improvement of MPD analysis, in which the correlation coefficient R2 increases from 0.641 to 0.961. The prediction accuracy of the improved model is significantly better than the traditional empirical relationship models. It is recommended to use the K e - { n , γ d , S r , C q , C c , C si , C sa } model to predict the k when the soil parameters are clear. [ABSTRACT FROM AUTHOR]