Search

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]

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]

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]

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]

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]

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]

• 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]

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]

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]

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]

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]

• 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]

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]

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]

• 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]

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]

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 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]

• 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 this paper, the stage-discharge relationship of a labyrinth sluice gate is theoretically deduced by the Π-Theorem of dimensional analysis and the self-similarity condition. This approach was then compared with the classical approach using the discharge coefficient C d proposed by Hashem et al. (2024). The classical stage-discharge equation (Eq. 4), with the discharge coefficient estimated by the empirical relationship (Eq. (1)) proposed by Hashem et al. (2024), resulted in errors E that are less than or equal to ±5 % for 74.3 % of the investigated cases and a mean square error MSE of 0.0078. The new stage-discharge relationship, deduced by dimensional analysis and self-similarity theory, was calibrated using the dataset by Hashem et al. (2024). The obtained stage-discharge equation (Eq. 20) is characterized by errors in the discharge estimate E that are less than or equal to ±5 % for 82.2 % of the investigated cases and a mean square error MSE of 0.0051. In conclusion, the stage-discharge relationship deduced by dimensional analysis allows for the best performance in the discharge estimate, which can be obtained without knowledge of the empirical discharge coefficient. • Stage-discharge relation of labyrinth sluice gates is deduced by dimensional analysis. • The tested approach is compared with the classical one using discharge coefficient. • The tested approach allows for the best performance in the discharge estimate. [ABSTRACT FROM AUTHOR]

This paper investigates how the notion of degrowth directs our focus as researchers, which leads us to deliberate on the consequences of empirically placing degrowth 'in the world.' We propose to rethink methodological questions about how phenomena are put into relation with notions of degrowth (or not) – and our own role as researchers in this process. Mobilizing the concept of diffraction, we argue that careful attention must be paid to what notions of 'degrowth' do in/to our research practices, including their role in researchers' selecting, thinking and talking about social phenomena – as well as the material and discursive practices encountered in fieldwork. This is illustrated through engagement with two studies, which undertook research on a housing community in Manchester (United Kingdom) and eco-social entrepreneurs in Stuttgart (Germany). Analyzing these cases with a diffractive lens, we show how an attunement to difference allows for attention to be paid to the 'translation' and 'operationalization' of degrowth in (research) practice. This orientation, we suggest, can help scholars with the inevitable negotiations intrinsic to the choice of how and whether to engage with and understand degrowth in empirical research. [ABSTRACT FROM AUTHOR]

The uncertainty associated with option price predictions has largely been overlooked in the literature. This paper aims to fill this gap by quantifying such uncertainty using conformal prediction. Conformal prediction is a model-agnostic procedure that constructs prediction intervals, ensuring valid coverage in finite samples without relying on distributional assumptions. Through the simulation of synthetic option prices, we find that conformal prediction generates prediction intervals for gradient boosting machines with an empirical coverage close to the nominal level. Conversely, non-conformal prediction intervals exhibit empirical coverage levels that fall short of the nominal target. In other words, they fail to contain the actual option price more frequently than expected for a given coverage level. As anticipated, we also observe a decrease in the width of prediction intervals as the size of the training data increases. However, we uncover significant variations in the width of these intervals across different options. Specifically, out-of-the-money options and those with a short time-to-maturity exhibit relatively wider prediction intervals. Then, we perform an empirical study using American call and put options on individual stocks. We find that the empirical results replicate those obtained in the simulation experiment. • Conformal prediction quantifies well the uncertainty of option price predictions. • Conformal prediction intervals have empirical coverage near the nominal level. • Non-conformal prediction intervals have empirical coverage below the nominal level. • Large variations in prediction intervals are found for American call and put options. • Larger intervals are found for out-of-the-money and short time-to-maturity options. [ABSTRACT FROM AUTHOR]

Geotechnical parameters required for estimating the maximum allowable annular pressure (P max) in horizontal directional drilling (HDD) are often empirically determined based on the results from the standard penetration test (SPT). Despite the benefits of SPT, its use in practice could be challenging as the geotechnical parameters determined based on SPT results vary largely depending on the choice made for SPT correlations. Such variability within the geotechnical parameters could result in a high degree of uncertainty within the estimates of P max in HDD. In this paper, an SPT-based algorithm is developed to study the variation in estimates of geotechnical parameters and P max due to the choice made for SPT correlation. Sensitivity analysis conducted using the SPT-based algorithm presents significant variations in both estimates of geotechnical parameters (relative ranges vary from 11% to 1516%) and P max (relative ranges vary from 10% to 1313%) for cases where the understanding of soil behavior and characteristics is insufficient. Error analysis conducted based on the errors in the geotechnical parameters determined using SPT correlations and the corresponding estimates of P max presents that the two types of errors are found closely related for most cases; however, exceptions also exist for the cases with the SPT correlations related to modulus of elasticity. Based on the results of the error analysis, suggestions for the use of SPT correlations are made for determining the input geotechnical parameters required for estimating the P max in HDD, and they are applied to a case study related to the hydraulic fracture experiments to demonstrate their usefulness in a real-world example. The case study presents high precision (R2 > 0.81) in the estimates of P max obtained by following the suggestions for the use of SPT correlations. In remark, the estimates of P max made based on some SPT correlations are found nearly equal to the measurements of annular pressure at hydraulic fracture, confirming that the SPT-based algorithm and the suggestions for the use of SPT correlations provided herein are reasonably reliable for estimating the P max in HDD. These results highlight the challenges with using empirically determined geotechnical parameters in the design of HDD and provide practitioners with valuable information for evaluating the stability of the HDD borehole. • Challenges with using empirical method for estimating P max in HDD is studied. • Sensitivity of P max estimate to the choice made for SPT correlation is analyzed. • An SPT-based algorithm for calculating P max is developed for the sensitivity analysis. • Errors in the SPT correlations and the corresponding estimates of P max are analyzed. • Based on the quantified results, suggestions for the use of SPT correlations are made. [ABSTRACT FROM AUTHOR]

The central environmental protection inspection is an institutional innovation in China that aims to supervise enterprises by monitoring government environmental enforcement. This paper examines the effectiveness of central environmental protection inspection in improving enterprise environmental performance by using a quasi-natural experiment of the first round of central environmental protection inspection. The study reveals that the central environmental protection inspection improves enterprise environmental performance by strengthening local government environmental enforcement and environmental attention. This is evidenced by the increase in enterprise environmental capital expenditure and the decrease in pollution discharge fees. The impact of central environmental protection inspection on enterprise environmental performance is strengthened by local governments' environmental regulation and environmental fiscal expenditure, as well as by public participation. Under the pressure of central environmental protection inspection, heavily polluting enterprises engage in production process improvement and R&D investment, which can improve their economic performance. This can ultimately lead to a competitive advantage for enterprises, promoting a win-win situation for both environmental and economic performance. [ABSTRACT FROM AUTHOR]

The maritime industry is constantly facing new challenges and technological advancements, making the adaptation of innovative solutions like digital twins a bridge enhancing safety and efficiency between theoretical models and real-world maritime applications. Digital twin simulators for complex dynamic operation systems such as shipboard cranes, allow the operators to practice demanding operations in a risk-free immersive environment with various scenarios. This paper presents the process of developing a digital twin-based simulation tool designed for shipboard crane operations. It is based on co-simulation using the Functional Mock-up Interface (FMI) standard. This allows for the integration of the operation scenarios with different physical domain models, including such as the ship, environmental forces, hydraulic power systems, and controllers. In addition, the digital twin has opened up new opportunities for the optimization of maritime systems. It can be used to identify the optimal operating conditions, predict potential risks, and provide onboard support to the operator. A demo crane digital twin is implemented for the Palfinger crane on the Gunnerus research vessel with system validation via a series of marine operations being real-time monitored by the Remote Control Center (RCC). • Co-simulation technology based on the FMI standard integrating the operation scenarios with different physical domain models. • Real-time ship-crane operations monitored by Remote Control Center lying in the collection, transmission, and storage of sensor data for IoT solutions. • System validation using sensor data and offshore pre-operation varying the environmental parameters in demanding operations. [ABSTRACT FROM AUTHOR]

Over recent decades, China's economy has continued to develop steadily and rapidly, contributing to a large environmental cost. Therefore, many researchers propose various methods to evaluate environmental efficiency to deal with these serious issues accurately. This paper is the first to evaluate environmental efficiency using a model featuring not only a parallel structure with three component processes (primary, secondary, and tertiary industries) in the first stage but also a sewage treatment process in the second stage. Simultaneously, we propose radial but also nonradial versions of the Environmental Multiple Variable Return to Scale (EMVRS) model. These two models both consider shared inputs as well as shared outputs, and the proportion of the shared inputs and shared outputs utilized in each component process is assumed to be unknown. Additionally, we further analyze the factors influencing environmental efficiency by utilizing the Tobit model. The results when EMVRS is applied to Chinese provinces can be divided into 3 parts: (1) Most provinces do not purify wastewater appropriately contributing to the bad environmental efficiency. (2) The efficiency values of the three industry types are similar or identical to each other in most provinces. (3) The population of people employed negatively impacts environmental efficiency. [ABSTRACT FROM AUTHOR]

• Short-term distribution planning (S-DSP): Focus on the load transfer ability project. • MILP-based modeling: Incorporating diverse optimization techniques for S-DSP. • Pareto-front estimation: Enhancing S-DSP decision-making. • Empirical study in Korea: Practical application and insights. This paper presents an optimal Short-term Distribution System Planning (S-DSP) problem, with a particular focus on the load transfer ability project. Section 2 formulates the problem as a Mixed-Integer Linear Programming (MILP) optimization, considering the objective function of minimizing investment costs and non-switchable capacity, along with constraints like distribution system power flow, line capacity, and bus voltage. Section 3 extends the optimization problem into a multi-objective function-based approach using the Epsilon constraint method. In Section 4, we introduce a method for estimating the Pareto-front set and outline the decision-making process for selecting the optimal alternative. The proposed method's effectiveness is demonstrated through in-depth case studies, first with a 36-bus test system and then with a practical application to Korea's distribution system, which features 2056 buses and 2082 lines (Section 5 and Section 6). This research based on the empirical study underscores the practical applicability of the proposed S-DSP approach to the advance distribution management system (ADMS) in Korea. [ABSTRACT FROM AUTHOR]

Most prior work on online reviews assumes that the value of reviews for consumers lies only in providing information about the product or the consumer's experience with the product. Yet, consumers also post and interact with pseudo-reviews, defined as reviews that describe exaggerated product experiences while trying to be entertaining. To address the nature and consequences of pseudo-reviews, this study develops a framework for understanding their value and how they affect consumer decision-making. First, we define how pseudo-reviews differ from other types of reviews. Then, we empirically examine how pseudo-reviews moderate the relationship between online review valence (how positive or negative the review is) and purchase intention. Finally, using a dual-processing theoretical lens, we examine how pseudo-reviews affect consumer decision-making through systematic and affective processing. We test our model through two experiments. The first study finds that pseudo-reviews reduce the impact of review valence on purchase intention when compared to genuine reviews. The second study shows that pseudo-reviews affect uncertainty and amusement, and these, in turn, affect purchase intention. We discuss the implications of pseudo-reviews for theory and practice. • Previous studies on online reviews often ignore the amusement value of online reviews. • The paper focuses on pseudo-reviews and develops a framework to understand their influence on consumer decisions. • For positive reviews, pseudo-reviews decrease the positive effect of review valence on purchase intention. • Pseudo-reviews affect consumer decisions by increasing both uncertainty and amusement. [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]

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]

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]

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]

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]

• 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]

Due to its effectivity and efficiency, deep hashing approaches are widely used for large-scale visual search. However, it is still challenging to produce compact and discriminative hash codes for images associated with multiple semantics for two main reasons, 1) similarity constraints designed in most of the existing methods are based upon an oversimplified similarity assignment(i.e., 0 for instance pairs sharing no label, 1 for instance pairs sharing at least 1 label), 2) the exploration in multi-semantic relevance are insufficient or even neglected in many of the existing methods. These problems significantly limit the discrimination of generated hash codes. In this paper, we propose a novel Deep Hashing with Self-Supervised Asymmetric Semantic Excavation and Margin-Scalable Constraint(SADH) approach to cope with these problems. SADH implements a self-supervised network to sufficiently preserve semantic information in a semantic feature dictionary and a semantic code dictionary for the semantics of the given dataset, which efficiently and precisely guides a feature learning network to preserve multi-label semantic information using an asymmetric learning strategy. By further exploiting semantic dictionaries, a new margin-scalable constraint is employed for both precise similarity searching and robust hash code generation. Extensive empirical research on four popular benchmarks validates the proposed method and shows it outperforms several state-of-the-art approaches. The source codes URL of our SADH is: http://github.com/SWU-CS-MediaLab/SADH. [ABSTRACT FROM AUTHOR]

National strategies have a large influence on the development of ports, especially gateway ports. The Bohai Rim is facing a new round of China's national strategies. It could be predicted that the statuses of the regional gateway ports in the international liner shipping network would change. In this paper, AIS data are adopted to identify the gateway ports in the Bohai Rim. With consideration of the choice behaviour of shippers and the uncertainty of the effects of national strategies, a liner network optimization model is constructed to estimate the service frequency of liners at four gateway ports (Qingdao, Tianjin, Dalian, Busan). On this basis, the roles of these ports in the global liner shipping network and the competitiveness regarding typical shipping routes (U.S., European and Southeast Asian routes) are investigated. The results reveal the following: (i) The transport demand growth brought by the revitalization strategy of the Old Industrial Base would significantly promote the status of Dalian Port. The calling frequencies of Qingdao Port would be improved, narrowing the gap in route density between it and Busan Port. However, more than expected, this growth might weaken the competitiveness of Tianjin Port, especially regarding U.S. and Southeast Asian routes. (ii) The pilot free trade zone (FTZ) policy could significantly promote the service frequencies of trunk routes at the Qingdao, Tianjin and Dalian Ports. When trade facilitation reaches the same level as that of Busan Port, the calling frequencies of Qingdao Port might surpass those of Busan Port. • AIS data are adopted to identify the gateway ports in the Bohai Rim. • Liner network optimization model to estimate the service frequency of liners. • Impacts of transport demand and pilot FTZ policy on Gateway Ports in Bohai Rim. [ABSTRACT FROM AUTHOR]

Dynamic quality of service (QoS) data contain rich temporal patterns of user-service interactions, which are vital for better understanding user behaviors and service conditions. Canonical polyadic (CP)-based latent factorization model has proven to be capable of capturing such patterns. However, it models the relations among latent features of user, service and time in a rigid and unnatural way, causing its failures in capturing the complex patterns when the target QoS data become massive. To address that issue, this paper proposes a B iased N on-negative Tuc ker F actorization of 3D tensors (BNTucF) model with the four-fold ideas: (1) utilizing a core tensor for modeling the complex interactions among latent features; (2) incorporating linear biases into the model for accurate descriptions on QoS fluctuation; (3) constraining the model to be non-negative for describing QoS non-negativity; (4) deducing a single latent factor-dependent, multiplicative updating scheme for training the model in an efficient density-oriented way. Empirical studies demonstrate that the proposed BNTucF can learn complex dynamic user-service interaction patterns more accurately, hence achieving accurate predictions on missing QoS data. • A model utilizes a tucker decomposition paradigm for accurate QoS prediction. • Incorporation of Tucker decomposition (TD) helps to extract the feature accurately. • Decoupled ranks allow accuracy boosting with optimal ranks for a specific dataset. • Bias incorporation and ADM-STL scheme are vital for achieving high model accuracy. [ABSTRACT FROM AUTHOR]

Prior research lacks understanding about how collaborative arrangements and network structures influence innovation outcomes in platform-based ecosystems. This paper addresses this gap by using an NK simulation model to investigate the impacts of different collaboration patterns and network structures on innovation performance. The NK simulation approach overcomes the shortcomings of empirical methods and enables examining the dynamic impacts. The results reveal that the "special platform + generic complementor" pattern leads to the highest innovation output. The impact of component correlations on the innovation performance follows an inverted U-shape. The small world network structure promotes innovation versus regular or random networks. The results provide novel theoretical insights into strategically configuring platform partnerships and network connections to optimize innovation. The findings offer practical guidance for firms to choose beneficial collaboration pattern and design proper network structure. [ABSTRACT FROM AUTHOR]