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Recent work on scale, chronotope and scale-making offers exciting ways for rethinking what we often refer to as "context". In this paper, we review these ideas pointing to how we might reconcile some of the overlaps in the concepts of scale and chronotope, while examining how we might look at chronotopic connection across quite different empirical divides drawn from a number of separate research projects in Indonesia. We propose that scale can be thought of as chains of chronotopes and that the semiotic forms that connect them as scale-makers, thus helping relate these two concepts to that of scale-making. • Explores how overlaps in the literature on scale, chronotope and scale-making might be reconciled. • Examines chronotopic connections across quite different empirical divides. • Explores how imitations connect chronotopes. [ABSTRACT FROM AUTHOR]

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]

Highlights: [•] A dynamic model for longitudinal vibration assisted guillotining of paper is developed. [•] Empirical model of a stack of thin paper material is identified. [•] Novel measurement procedure for determining dynamic behavior for ultrasonic assisted cutting is developed. [•] Simulated cutting forces are in agreement with the experimentally recorded cutting forces. [Copyright &y& Elsevier]

Abstract: There has been much debate on the topic of whether stricter environmental regulations can promote environmental performance and economic performance at the same time. Different researchers have used different indicators to measure environmental performance and economic performance in their empirical studies. However, it is a surprise that few studies have checked the relationship between environmental regulation and eco-efficiency, as the latter is widely regarded as a quite powerful tool of considering ecology and economy together. In this study the background is the implementation in 2003 of the Stricter Discharge Standard (SDS) in Shandong Province’s Pulp and Paper Industry (SPPI), compared to the national standards of China. The stricter regulations were intended to promote corporate change from passive management to active control and from end-of-pipe treatment to cleaner production. This study investigated the eco-efficiency trends of SPPI from 2001 to 2008 in three fields: water efficiency, energy efficiency and environment efficiency. A “de-linking” and “re-linking” tool was used to attain a further evaluation. The study showed that with the implementation of stricter regulation most of the efficiency indicators (except CO2 emission and energy consumption) had achieved significant improvements, and the overall environmental performance trends of SPPI showed it to be more sustainable. However, the study also found that it was not enough to address a single indicator in the environmental regulation of the pulp and paper industry. More holistic eco-efficiency indicators need to be further considered and introduced to the industry as the next step to create true sustainable development. [ABSTRACT FROM AUTHOR]

This is the last in a short series of papers on measurement theory and practice with particular relevance to intervention research in nursing, midwifery, and healthcare. Understanding how it is that people respond to the questions posed by researchers is fundamental to progress in the social and health sciences. For decades methodologists in psychology, marketing, education, and survey research have studied this issue. In this paper I review this diverse empirical literature to synthesize basic principles for creating rating scales which can reduce measurement error and increase the quality of resulting data. After introducing a theoretical framework known as the cognitive aspects of survey methods (CASM), I review the fundamentals of psychological scaling theory and discuss how it has been used to study the meanings of verbal response options and provide an illustration of how the quality of measurements may be influenced by our choice of the verbal phrases we present as response options. Next, I review the research on the optimal number of response options to use in various measurement situations and how verbal and numeric anchors can combine to influence data quality. Finally, I summarize the issues covered and present recommendations for best practice when creating and using rating scales in research. [ABSTRACT FROM AUTHOR]

Abstract: The rheological nature of paper or board is usually treated either as elasto-plastic or as viscoelastic depending on the studied paper making process or behavior in converting and end use. In this paper we study several stress–strain curve models and the determination of material parameters from an elasto-plastic point of view. Finally, a suitable approach for all stress–strain curves measured from 180 strips is constructed using a linear function for an elastic region and a nonlinear function for a strain hardening region. This model determines a proportional limit (elastic limit) and gives fairly elegant dependencies between material/fitting parameters and two important factors of mechanical properties of paper: dry solids content and anisotropy. In this paper the dependency of a plastic strain on dry solids content and anisotropy is estimated using the introduced stress–strain curve model. Correspondingly, the model can be used to estimate many other mechanical behaviors, for example, the tension differences arising from non-uniform moisture content of the paper web profile. However, the main target of this study is to produce competent parameters based on modeled stress–strain curves for further construction of a material model. This elasto-plastic material model will be utilized in out-of-plane deformation and fracture models. [Copyright &y& Elsevier]

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]

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]

Abstract This paper identifies some of the tasks and roles that academic libraries have to fulfil in order to react to the appearance of Research 2.0 that materialises in data intensive research and requires supporting activities. Reacting to the appearance of Research 2.0 by becoming service providers for scholars working on data-intensive tasks will become an imperative for libraries worldwide, even though due to the differences between countries and institutions, the tasks described in this paper may not seem urgent today. On the other hand, the issues, we identified are already part of everyday best practices in several institutions. Some of them are fairly recent or have taken new characteristics. A few roles identified in this paper are on their way to become standard occupation, while there are still ones that require innovative approaches. Our argument is based on a non-exhaustive review of the recent literature, reporting both on theoretical and practical issues and presenting the results of empirical research in the field. [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]

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]

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]

Given the substantial challenges in the teaching profession, prioritizing teacher resilience is essential. This paper reviews 54 studies on teacher resilience using the Job Demands and Resources (JD-R) model based on the PRISMA. The paper examines method quality, conceptualization of teacher resilience, and its antecedents. The study acknowledges the methodological limitations of the review and categorizes the conceptualization of teacher resilience while suggesting potential avenues for advancing the field of teacher resilience. Moreover, the findings highlight a greater emphasis on resource factors over demand factors and underline the need for further investigation into differentiating hindrance demands from challenge demands. • This paper organized the definitions and antecedents of teacher resilience from its inception in 2006–2023. • This paper utilized the JD-R model to analyse the antecedents of teacher resilience. • The paper encompassed personal hindrance and challenge demands into the JD-Rmodel. • This paper assessed the method quality of the empirical studies. [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]

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]

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]

Media ethics is an area of inquiry that has been of great concern among journalists and public relations professionals as well as scholars across the world. Empirical research on media ethics of comparative nature has increased, providing a descriptive account on the current situations across different countries. Yet, theoretical efforts to explain global media ethics are so far inexistent. The scope of this paper is to provide a conceptual model for explaining media ethics decision-making processes that takes into account personal, professional and environment values as main influencing forces. The proposed model suggests that besides considering personal factors, such as education, background, experience, gender, etc., and country specific factors, such as political, economic, socio-cultural conditions, one should first and foremost understand the degree to which personal, professional, and environment values influence one’s judgment. This model is the first of its kind in providing an explanation of differences in global media ethics by considering the interconnectedness of different values at micro, meso, and macro levels. [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]

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]

Abstract: Recently we received a commentary by Passian et al. [1] on our previously published paper [2] in the Ultramicroscopy. Although the commentators, who are also our co-authors in an earlier papers in similar line (see [3,5]), claimed to discuss and better explain the concept of “virtual resonance” in [3], they went on to conclude that the experimental results and findings in [3] have been misrepresented in [2]. We have theoretically considered a general semi-empirical nonlinear interaction force consisting of different terms with which the dynamic response of the system could be very dependent. Here, we highlight these types of dependencies on the amplitude at the difference frequency. Due to the nature of this communication, we would like to limit our response to matters of fact to the authors of the commentary. [Copyright &y& Elsevier]

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]

• Carry out wax deposit dissolution experiments under different conditions. • Propose five stages of wax deposit dissolution process. • Construct an empirical relationship calculating wax deposit dissolution rate. During the sequential transportation of waxy crude oil and light oil, the previous formed wax deposits on the pipe wall will dissolve by light oil, which brings risks to the flow safety of the pipeline. This paper adopted a Couette wax deposit dissolution experimental device to systematically study the effects of dissolution duration, oil temperature, rotation speed and wax deposit properties on the dissolution characteristics of wax deposits. It is found that the dissolution of wax deposits is a process that starts quickly and then slows down. Moreover, the wax content of wax deposit also decreased during the dissolution process. The wax deposit dissolution process is mainly divided into five stages such as diffusion of wax molecules from wax deposit to the light oil and from bottom layer deposit to the wax deposit-oil interface, dissolution of wax crystal particles, weakening of wax deposit structural strength, and shear stripping of wax deposits. Finally, an empirical model of wax deposit dissolution was established and the undetermined parameters were fitted based on experimental data. The prediction results have good prediction accuracy with the experimental values. [ABSTRACT FROM AUTHOR]

This article aims to explore a way of thinking based on chiastic structure (X-shaped structure), chiastic thinking. Characterized by its juxtaposition of opposite structure, chiastic thinking has an intriguing connection to Janusian thinking. This is because Janusian thinking is deemed a creative process wherein two opposite concepts or images are conceived simultaneously. At the beginning of the article, conceptual combination and Janusian thinking are presented, along with empirical research data to support the effectiveness of Janusian thinking. The paper then shifts to a discussion of chiastic thinking, which occupies a unique place in human culture and civilization but does not receive due attention. In the last part of this article, the examples of chiastic thinking in literature, science, and art are provided. Across diverse disciplines, the combination of opposites manifests in various ways, often adopting different technical terms that give rise to different theories. These terms and theories may share fundamental commonalities but differ in certain aspects. The main purpose of this review article is to examine the close relation between Chiastic and Janusian thinking. Hopefully, this review article can rekindle the academic interest in these two thinking processes and give them new meaning. • Chiastic thinking is a special type of thinking based on chiastic structure (X-shaped structure). • Given that chiastic thinking involves the juxtaposition of opposing forms, it is reasonable to consider chiastic thinking overlapping with Janusian thinking. • The traces of chiastic thinking can be found in diverse fields of human endeavor. • Chiastic thinking has a great potential to foster creativity. [ABSTRACT FROM AUTHOR]

In the past, under the GDP-centered promotion tournament, the growth coalition theory was often used to explain commercial and residential district regeneration in China, which was property-led and profit-driven. However, currently, due to the new domestic and international environment, China is undergoing an unprecedented and profound transformation and entering the inventory land era, leading to significant changes in the assessment system for local officials. Specifically, the new assessment system incorporates a diverse array of indicators beyond mere economic growth, signifying a transition from a GDP-centered to a multi-objective promotion tournament. Consequently, in this new context, the traditional growth coalition is no longer sufficient to theorize current urban regeneration. Additionally, industrial district regeneration, the mechanism of which may differ from commercial and residential district regeneration, was often neglected before and requires further investigation. Through the case study of Chengdu Hi-tech West District, this study explores the transformation of Chinese urban regeneration in this new era. It argues that China's governmental assessment system has adjusted by dismantling the previous promotion tournament model based on economic growth in the new era. Under the multi-objective promotion tournament, local officials now consider other aspects in addition to economic growth. For them, IDR has been treated as an effective approach to protecting cropland, undertaking new enterprises with limited space, and becoming the flagship in promoting economical and intensive land use, all of which are of great concern to the central government. Therefore, local officials are keen on industrial district regeneration now, even though it does not yield direct and immediate economic benefits. In this process, they mobilize other actors and leverage key resources to achieve and balance their multiple goals. Accordingly, the traditional growth coalition is declining, while a new kind of coalition based on high-quality development is emerging. • China is transitioning from an "incremental land era" to an "inventory land era.". • China's political and economic contexts have undergone significant changes, altering the rationale behind urban regeneration. • The paper presents a case study of China's Chengdu Hi-Tech Industrial Development District. • Due to adjustments in the assessment system, local officials are giving greater attention to industrial district regeneration than before. • A new coalition based on high-quality development is emerging, while the traditional growth coalition is waning. [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]

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]

Video clip retrieval and captioning tasks play an essential role in multimodal research and are the fundamental research problem for multimodal understanding and generation. The CLIP (Contrastive Language-Image Pre-training) model has demonstrated the power of visual concepts learning from web collected image-text datasets. In this paper, we propose a CLIP4Clip model to transfer the knowledge of the image-text pretrained CLIP model to video-text tasks in an end-to-end manner. Furthermore, we conduct several empirical studies including 1) Whether image feature is enough for video-text retrieval and captioning? 2) How a post-pretraining on a large-scale video-text dataset based on the CLIP affect the performance? 3) What is the practical mechanism to model temporal dependency between video frames? And 4) The Hyper-parameters sensitivity of the model. Extensive experimental results present that the CLIP4Clip model transferred from the CLIP can achieve SOTA results on various video-text datasets, including MSR-VTT, MSVD, LSMDC, and DiDeMo for multimodal understanding and generation tasks. [ABSTRACT FROM AUTHOR]

Accurate short-term prediction of bioenergy power generation structure can optimize the bioenergy structure and help achieve carbon neutrality. However, there are currently few related studies, and most of them present long-term predictions on the development potential of bioenergy, which cannot meet the modeling requirements of predicting structure. Hence, the Fractional-order-accumulation grey Compositional data Model with Particle swarm is proposed in this paper (PFCM (1,1)) for forecasting bioenergy power generation structure. The proposed model satisfies the modeling requirements by introducing the fractional accumulation operator to ensure the prediction accuracy, and constructing the spherical mapping space to reduce the data dimension. The empirical studies prove that the newly developed model performs better than other models, which is successfully employed to predict bioenergy power generation structure of China for 2020–2024. The results show that the share of renewable municipal waste in bioenergy power generation will exceed that of solid biofuels by 2023 and the share of biogas power generation has not changed much. Furthermore, although the total amount of bioenergy power generation in China is growing rapidly, unbalanced development and small share of power are two important challenges. [Display omitted] [ABSTRACT FROM AUTHOR]

The process of a virus spread is inherently spatial. Even though Latin America became the epicenter of the COVID-19 pandemic in May 2020, there is still little evidence of the relationship between urban mobility and virus propagation in the region. This paper combines network analysis of mobility patterns in public transportation with a spatial error correction model for Santiago de Chile. Results indicate that a 10% higher number of daily public transportation trips received by an administrative unit in the city was associated with a 1.3% higher number of confirmed COVID-19 cases per 100,000 inhabitants. Following these findings, we propose an empirical method to identify and classify neighborhoods according to the level and type of risk for COVID-19-like disease propagation, helping policymakers manage mobility during the initial stages of an epidemic outbreak. [ABSTRACT FROM AUTHOR]

In continual learning over deep neural networks (DNNs), the rehearsal strategy , in which the previous exemplars are jointly trained with new samples, is commonly employed for the purpose of addressing catastrophic forgetting. Unfortunately, due to the memory limit, rehearsal-based techniques inevitably cause the class imbalance issue leading to a DNN biased toward new tasks having more samples. Existing works mostly focus on correcting such a bias in the fully connected layer or classifier. In this paper, we newly discover that class imbalance tends to make old classes even more highly correlated with their similar new classes in the feature space, which turns out to be the major reason behind catastrophic forgetting, called inter-task forgetting. To alleviate inter-task forgetting, we propose a novel class incremental learning method, called attractive & repulsive training (ART) , which effectively captures the previous feature space into a set of class-wise flags , and thereby makes old and new similar classes less correlated in the new feature space. In our empirical study, our ART method is observed to be quite effective to improve the performance of the state-of-the-art methods by substantially mitigating inter-task forgetting. Our implementation is available at: https://github.com/bigdata-inha/ART/. [ABSTRACT FROM AUTHOR]

Active inference is a state-of-the-art framework for modelling the brain that explains a wide range of mechanisms such as habit formation, dopaminergic discharge and curiosity. However, recent implementations suffer from an exponential (space and time) complexity class when computing the prior over all the possible policies up to the time horizon. Fountas et al. (2020) used Monte Carlo tree search to address this problem, leading to very good results in two different tasks. Additionally, Champion et al. (2021a) proposed a tree search approach based on (temporal) structure learning. This was enabled by the development of a variational message passing approach to active inference (Champion, Bowman, Grześ, 2021), which enables compositional construction of Bayesian networks for active inference. However, this message passing tree search approach, which we call branching-time active inference (BTAI), has never been tested empirically. In this paper, we present an experimental study of the approach (Champion, Grześ, Bowman, 2021) in the context of a maze solving agent. In this context, we show that both improved prior preferences and deeper search help mitigate the vulnerability to local minima. Then, we compare BTAI to standard active inference (AcI) on a graph navigation task. We show that for small graphs, both BTAI and AcI successfully solve the task. For larger graphs, AcI exhibits an exponential (space) complexity class, making the approach intractable. However, BTAI explores the space of policies more efficiently, successfully scaling to larger graphs. Then, BTAI was compared to the POMCP algorithm (Silver and Veness, 2010) on the frozen lake environment. The experiments suggest that BTAI and the POMCP algorithm accumulate a similar amount of reward. Also, we describe when BTAI receives more rewards than the POMCP agent, and when the opposite is true. Finally, we compared BTAI to the approach of Fountas et al. (2020) on the dSprites dataset, and we discussed the pros and cons of each approach. [ABSTRACT FROM AUTHOR]

Relative to the easier removal of accumulated dust on the outside of solar devices, it's very difficult to clean up the internal dust particles. So, from the aspect of ensuring the long-term high-performance operation of transpired solar air collector, the paper investigates the tilt angle effects on the dust accumulation amount of glazing cover inner surface and associated reduction in collector performance. In process, various forces causing the dust particles move to the inner surface and collide with them and then deposit, are thoroughly analyzed. To estimate the heat collected loss induced by dust, an empirical relationship predicting the light transmittance reduction has been explored, valid for relatively small dust accumulation amount. The results indicate that mainly under the force of gravity, the dust deposition density on the inner surface increases with the tilt angle. However, in view of the difference of solar irradiance in five tilt angles at the same time, it is not that the higher the dust deposition density, the lower the temperature rise from collector inlet to outlet. Hence, the tilt angle should be determined based on the comprehensive evaluation of the resulting changes of solar irradiance and dust accumulation amount, combined with local meteorological conditions. [ABSTRACT FROM AUTHOR]

Empirical research writing is one of the primary means of disseminating knowledge in academia. It is through this particular form of knowledge dissemination that a rich body of scientific knowledge about a given phenomenon is accumulated. This paper explores patterns of variation in the language of this specific sub-register of academic writing, as reflected in the use of words in different sections of empirical research articles from across ten disciplinary fields. An inductive approach was adopted through which patterns of specificity in vocabulary use were systematically identified, triangulated and verified using different methods of data analysis. The results presented in this study show that the lexical choices academics make in the process of composing their research papers are differentially affected by the standards and conventions of scholarly activities in their field. It was found that such conventions have the potential to govern the delineation of authors' linguistic decisions at the most basic levels, such as the lexis. • The language of empirical research articles is characterized by highly specialized discourses that are far from being homogeneous. • The majority of the high-frequency vocabulary used in research writing is not widely shared among academic disciplines. • Research writing in the sciences demands the knowledge of a type of vocabulary that has a very narrow range of use and applicability. [ABSTRACT FROM AUTHOR]

• High ambient temperature can add to the high risk in construction industry. • This study assessed the effects of high ambient temperature on workers performance. • A sample of 120 construction workers participated, 60 in Summer and 60 in Winter. • Task battery performance was significantly lower in Summer than in Winter. • Accident data showed an increasing trend in Summer months. • Fatigue due to high ambient temperature in Summer is thought to be the cause. Introduction: The construction industry is known to be of high-risk when compared to other industries. Ambient temperature can also exacerbate this risk, where hot weather conditions can lead to increased physical and mental fatigue, reduced performance, slower reactions and more human errors. Yet this issue is rarely researched objectively. This paper describes a longitudinal empirical study that aimed to assess how high ambient temperatures affect construction workers performance. Method: A sample of 120 randomly selected workers (age range 22–35 years) from a large construction company in Dubai participated in this study. Since construction workers performance cannot be directly measured due to the nature of work involved, performance of 60 participants was measured on a task battery involving single reaction time and choice reaction time in summer months before starting work and 5.5 h after starting work. Then the same procedure was repeated on 60 workers in winter months. Accident reports for one full year within the same company were also collected and analyzed. Results: Results show that performance on both tasks before starting work was significantly lower in summer than in winter months possibly due to accumulated fatigue resulting from the high ambient temperature in summer. Results also show that performance on both tasks significantly deteriorated during the first 5.5 h of work to a greater extent in summer months than in winter months. Results also indicate that accidents showed an increasing trend in summer months. Conclusions: Accumulated fatigue due to high ambient temperature in Summer is thought to cause this drop in performance and increase in accidents. Practical implications: Based on the findings, recommendations to enhance construction workers performance and reduce accidents are given. [ABSTRACT FROM AUTHOR]

In the field of data mining, outlier detection is an important and challenging task. This paper focuses on studying the impacts of outliers on the performance of models learned from large-scale datasets while it is unknown whether a data point is outlier or not. In the proposed approach, a fuzzy c-means clustering algorithm is applied and outliers are defined as those that have greater membership values in the cluster and are located further away from the cluster centroid. Ideally, the sample with a higher membership value should be located closer to the cluster centroid. In this context, we calculate the weight of each sample using the AdaBoost algorithm, where a weight determines the representativeness of each sample within the data distribution. Additionally, in this study, the impact of weighted loss functions in different situations are discussed in detail. At last, our method is evaluated on 12 UCI datasets and the accuracy of our method is greater than 95% on some datasets, such as banknote 99.99%, biodeg 99.01%, optdigits 99.19%, and letters 97.37%. The experimental results show the efficiency and effectiveness of the proposed approach. • Outlier impact is investigated in a classification context. • Outliers are identified as having higher membership and found outside cluster center. • Different weighted loss functions are also discussed in detail in various situations. • The efficiency and effectiveness of the proposed method are verified experimentally. [ABSTRACT FROM AUTHOR]