Miracle-dz/UniFAR-FTUs huggingface dataset:
The Impact of Place of Origin on International and Domestic Graduates’ Mobility in China

This article addresses the cumulative effect of graduate migration and opportunities for career development. Using data from an online survey of 756 master’s-level graduates educated in China and the UK, it examines their geographical mobility patterns and reveals significant differences between Chinese students who graduated from domestic universities and those who were educated abroad. Spatial autocorrelation analysis shows that international returnees, who usually had more privileged family backgrounds, clustered in China’s highly developed core cities of the Bohai Economic Rim and Yangtze River Delta regions, such as Beijing and Shanghai, while domestic graduates tended to work and live in less affluent medium-sized cities around these regions. Women international graduates were more mobile than their men counterparts. Our results provide new evidence that draws attention to migration’s role in graduate career development opportunities and highlights inherent economic discrimination within China, which is perpetuated by the national residency permit system — Hukou. The case of Chinese graduates shows that the mobility patterns of international and domestic graduates are influenced by and contribute to growing regional inequalities for career development in China.
Characterization and Evolution of Organized Shallow Convection in the Downstream North Atlantic Trades

The organization of deep convection has long been recognized to influence the global distribution of moisture and, as a consequence, the climate. Shallow convection, as is common in the trades, is usually not thought of as being organized. Rather, in the mind's eye of many researchers, trade-wind clouds are randomly distributed, have little vertical development and have generally been assumed to play little role in the climate system. Over the past twenty years however, the out-sized role of maritime shallow clouds on Earth's radiation budget — and discrepancies in how models predict their changes with warming (Bony & Dufresne, 2005) — have made a determination of processes controlling their coverage a central focus of climate science. During this period, observational studies such as RICO (Rauber et al., 2007) and the emergence of satellite imagery with spatial resolution on the hectometer scale began emphasizing how shallow clouds in the trades adopt different forms of organization, often in association with precipitation development and the formation of cold pools (Seifert & Heus, 2013; Seifert et al., 2015; Zuidema et al., 2012). More recently, several approaches to characterize these forms of organizations have been developed (Denby, 2020; Janssens et al., 2021; Stevens et al., 2020). Stevens et al. (2020) identified that most of the largescale patterns of shallow convection can be categorized into four categories, which they called Sugar, Gravel, Flowers, and Fish. Although based solely on the subjective visual inspection of visible satellite imagery in the vicinity of the Barbados Cloud Observatory (BCO), these patterns have varied net cloud radiative effects and thus may influence Earth's climate sensitivity (Bony et al., 2020).
Police self-legitimacy and democratic orientations: Assessing shared values

Using a sample of frontline police officers from several mid-sized municipal police departments in the United States, this study explores the relationships between frontline police officers’ self-legitimacy, organizational fit, moral alignment with policed communities, and attitudes toward democratic policing principles. Using partial least squares structural equation modeling, the analysis frames democratic policing using a formative latent construct to test several hypotheses. The results support a direct positive relationship between self-legitimacy and attitudes toward democratic policing, and suggest the relationship is partially mediated by officers' perceptions of moral alignment with their policed communities. The results further demonstrate that self-legitimacy is significantly related to organizational fit, but organizational fit does not appear to mediate the relationship between self-legitimacy and attitudes toward democratic policing.
Flexible Ti3C2Tx@Al electrodes with Ultrahigh Areal Capacitance: In Situ Regulation of Interlayer Conductivity and Spacing

Although Ti3C2 MXene has shown great potential in energy storage field, poor conductivity and restacking between MXene flakes seriously hinders the maximization of its capacitance. Herein, a new strategy to solve the problems is developed. Gallery Al atoms in Ti3AlC2 are partially removed by simple hydrothermal etching to get Ti3C2Tx reserving appropriate Al interlayers (Ti3C2Tx@Al). Ti3C2Tx@Al keeps stable layered structure rather than isolated Ti3C2Tx flakes, which avoids flake restacking. The removal of partial Al frees up space for easy electrolyte infiltration while the reserved Al as “electron bridges” ensures high interlayer conductivity. As a result, the areal capacitance reaches up to 1087 mF cm−2 at 1 mA cm−2 and over 95% capacitance is maintained after 6000 cycles. The all‐solid‐state supercapacitor (ASSS) based on Ti3C2Tx@Al delivers a high capacitance of 242.3 mF cm−2 at 1 mV s−1 and exhibits stable performance at different bending states. Two ASSSs in tandem can light up a light‐emitting diode under the planar or wrapping around an arm. The established strategy provides a new avenue to improve capacitance performances of MXenes.
More is not always better: determinants of choice overload and satisfaction with customization in fast casual restaurants

ABSTRACT Mass customization in fast casual restaurants has been a growing trend to meet customers’ increasingly tailored demands. To receive customization services, however, customers are required to make several choices with limited time. Therefore, this study examines the effects of a perceived number of choices and time pressure on choice overload and the subsequent effects of choice overload on satisfaction with customization in fast casual restaurants. Path analyses with the data of 371 highly valid respondents from a nationwide consumer sample demonstrated that perceived number of choices and time pressure increased participants’ choice overload. In addition, once customers were overwhelmed by choices, they were less likely to be satisfied with the customization process. Notably, when customers had high hedonic or utilitarian restaurant values, there was no negative effect of choice overload on satisfaction. This study provides better insights into the current restaurant trend of mass customization for both scholars and practitioners.
An Advanced Decision Making Framework via Joint Utilization of Context-Dependent Data Envelopment Analysis and Sentimental Messages

Compared to widely examined topics in the related literature, such as financial crises/difficulties in accurate prediction, studies on corporate performance forecasting are quite scarce. To fill the research gap, this study introduces an advanced decision making framework that incorporates context-dependent data envelopment analysis (CD-DEA), fuzzy robust principal component analysis (FRPCA), latent Dirichlet allocation (LDA), and stochastic gradient twin support vector machine (SGTSVM) for corporate performance forecasting. Ratio analysis with the merits of easy-to-use and intuitiveness plays an essential role in performance analysis, but it typically has one input variable and one output variable, which is unable to appropriately depict the inherent status of a corporate’s operations. To combat this, we consider CD-DEA as it can handle multiple input and multiple output variables simultaneously and yields an attainable target to analyze decision making units (DMUs) when the data present great variations. To strengthen the discriminant ability of CD-DEA, we also conduct FRPCA, and because numerical messages based on historical principles normally cannot transmit future corporate messages, we execute LDA to decompose the accounting narratives into many topics and preserve those topics that are relevant to corporate operations. Sequentially, the process matches the preserved topics with a sentimental dictionary to exploit the hidden sentiments in each topic. The analyzed data are then fed into SGTSVM to construct the forecasting model. The result herein reveals that the introduced decision making framework is a promising alternative for performance forecasting.
From “Oh, you’re Chinese . . . ” to “No bats, thx!”: Racialized Experiences of Australian-Based Chinese Queer Women in the Mobile Dating Context

This article explores racial exclusion, bias, and prejudice in the context of same-sex mobile dating, focusing on the experiences of a group of Australian-based Chinese queer women. Semi-structured in-depth interviews and participant observation were used to examine participants’ racialized experiences. The findings indicate that Western dating apps, such as Tinder, Bumble, and HER, served as crucial channels of these women’s interracial and intercultural encounters while living in Australia. However, they largely perceived these apps, and HER in particular, as White-dominated and ill-suited to their dating practices, thus reinforcing their sense of exclusion and ostracism. Although the participants frequently encountered subtle prejudice on dating apps, they experienced more blatant and aggressive forms of racism triggered by the COVID-19 outbreak. Multiple factors, including their language capability, the COVID-19 pandemic, and their racial, ethnic, and diasporic identities, played an intersectional role in these women’s racialized experiences. Correspondingly, the participants developed diverse interpretations of and responses to their racialized experiences. This study reveals how the anti-Asian racism in the global West permeates the realm of queer women in the context of mobile dating. It contributes to understanding the digital dating practices and racialized experiences of queer women and the broader Chinese diaspora.
Interpreting testing and assessment: A state-of-the-art review

Over the past decade, testing and assessing spoken-language interpreting has garnered an increasing amount of attention from stakeholders in interpreter education, professional certification, and interpreting research. This is because in these fields assessment results provide a critical evidential basis for high-stakes decisions, such as the selection of prospective students, the certification of interpreters, and the confirmation/refutation of research hypotheses. However, few reviews exist providing a comprehensive mapping of relevant practice and research. The present article therefore aims to offer a state-of-the-art review, summarizing the existing literature and discovering potential lacunae. In particular, the article first provides an overview of interpreting ability/competence and relevant research, followed by main testing and assessment practice (e.g., assessment tasks, assessment criteria, scoring methods, specificities of scoring operationalization), with a focus on operational diversity and psychometric properties. Second, the review describes a limited yet steadily growing body of empirical research that examines rater-mediated interpreting assessment, and casts light on automatic assessment as an emerging research topic. Third, the review discusses epistemological, psychometric, and practical challenges facing interpreting testers. Finally, it identifies future directions that could address the challenges arising from fast-changing pedagogical, educational, and professional landscapes.
Impact of Ballast Fouling on the Mechanical Properties of Railway Ballast: Insights from Discrete Element Analysis

Ballast fouling is a major factor that contributes to the reduction of shear strength of railway ballast, which can further affect the stability of railway supporting structure. The major sources of ballast fouling include infiltration of foreign fines into the ballast material and ballast degradation induced by train movement on the supported tracks. In this paper, a discrete element model is developed and used to simulate the shear stress–strain response of fouled ballast assembly subjected to direct shear loading. A simplified computational approach is then proposed to model the induced ballast fouling and capture the mechanical response of the ballast at various levels of contamination. The approach is based on the assumption that fine particles comprising the fouling material will not only change the interparticle friction angle, but also the contact stiffness between the ballast particles. Therefore, both the interparticle friction coefficient and effective modulus are adjusted based on a fouled ballast model that is validated using experimental results. The effect of ballast degradation is also investigated by gradually changing the particle size distribution of the ballast assembly in the discrete element model to account for the increased range of particle sizes. Using the developed model, the effect of ballast degradation on the shear strength is then evaluated. Conclusions are made to highlight the suitability of these approximate approaches in efficiently modeling ballast assemblies under shear loading conditions.
What do we have faith in? – a comparative study on trust and performance appraisal practices in French and German MNE-subsidiaries

Abstract We explore how subsidiaries in a high-trust (Germany) and low-trust (France) country adopt the performance appraisal (PA) system from their US-headquarter. In-depth interviews with 30 informants illustrate trickle-down effects of trust from the national level to the organizational and individual levels shaping processes, outputs, and interactions of PA. While German informants expressed trust in the overall PA practice of the US-headquarter, French informants reacted with mistrust to PA manifested in different processes, rater and ratee attitudes, outcomes of PA, as well as the role of HR. We add to the comparative HRM literature by untangling, within an MNE context, the interaction of societal, organizational, and individual trust with the overall PA to provide a more holistic explanation for cross-national variations in PA beyond the mere assignment to separate cultural categories.
Competitiveness in the visitor economy: A systematic literature review

Competitiveness is a well-discussed research topic in various disciplines and fields, amongst which competitiveness in the visitor economy is a prominent research stream. With rapid transformations in the visitor economy, destinations, regions, sectors and businesses have had to adapt – with varying degrees of success – to internal and external changes, significantly affecting their competitiveness. Existing studies are dominantly based on a few pioneering models and indicators and relatively few empirically challenge the assumed causality of competitiveness factors at different scales. This article, therefore, conducts a systematic literature review of competitiveness in the visitor economy post-2005 and examines the intellectual and conceptual structures of the extant literature as a platform to identify knowledge gaps and emerging trends and perspectives for future research.
Efficient Design of Energy Disaggregation Model with BERT-NILM Trained by AdaX Optimization Method for Smart Grid

One of the basic conditions for the successful implementation of energy demand-side management (EDM) in smart grids is the monitoring of different loads with an electrical load monitoring system. Energy and sustainability concerns present a multitude of issues that can be addressed using approaches of data mining and machine learning. However, resolving such problems due to the lack of publicly available datasets is cumbersome. In this study, we first designed an efficient energy disaggregation (ED) model and evaluated it on the basis of publicly available benchmark data from the Residential Energy Disaggregation Dataset (REDD), and then we aimed to advance ED research in smart grids using the Turkey Electrical Appliances Dataset (TEAD) containing household electricity usage data. In addition, the TEAD was evaluated using the proposed ED model tested with benchmark REDD data. The Internet of things (IoT) architecture with sensors and Node-Red software installations were established to collect data in the research. In the context of smart metering, a nonintrusive load monitoring (NILM) model was designed to classify household appliances according to TEAD data. A highly accurate supervised ED is introduced, which was designed to raise awareness to customers and generate feedback by demand without the need for smart sensors. It is also cost-effective, maintainable, and easy to install, it does not require much space, and it can be trained to monitor multiple devices. We propose an efficient BERT-NILM tuned by new adaptive gradient descent with exponential long-term memory (Adax), using a deep learning (DL) architecture based on bidirectional encoder representations from transformers (BERT). In this paper, an improved training function was designed specifically for tuning of NILM neural networks. We adapted the Adax optimization technique to the ED field and learned the sequence-to-sequence patterns. With the updated training function, BERT-NILM outperformed state-of-the-art adaptive moment estimation (Adam) optimization across various metrics on REDD datasets; lastly, we evaluated the TEAD dataset using BERT-NILM training.
LARS: A Latency-Aware and Real-Time Scheduling Framework for Edge-Enabled Internet of Vehicles

With the development of Internet of Things and mobile computing, the explosive proliferation of latency-sensitive applications raises high computation demands for mobile devices. To this end, offloading computation of applications to edge-enabled Internet of Vehicles (IoV) has emerged as an effective solution. However, most of the existing studies on this issue assume that IoV can be easily formed in the practical environment, and neglect the dependency relationship between tasks of the offloading application. In this article, we first give several observations based on the analysis results of the real traffic dataset to verify the feasibility of aggregating vehicular resources in the real world. Then, we design a Latency-aware Real-time Scheduling Framework for the edge-enabled IoV, named LARS, in which mobile users can offload applications to LARS, and the offloading tasks can be scheduled to the appropriate vehicular resources in real-time. First, we propose a clustering-based algorithm to generate Herds, which treats connected vehicles as edge computation resources to provide cooperative computing services. Second, considering the dependency relationship between tasks in the job, we present a greedy-based task scheduling algorithm for offloading jobs, the objective of which is to minimize the total latency of the job as well as maximize the resource utilization of Herds. The simulation experiment based on the real traffic dataset shows that Herds generated by the proposed clustering-based algorithm can maintain a stable period to provide computing service, and the experiments on testbed include two case studies demonstrate that the superiority of the proposed scheme compared to baselines, in terms of latency and resource utilization.
An Evaluation of the Possible Uses of CNT in Flow Conditions for Removing Humic Substances from Water

This study concerns an evaluation of humic substance removal during an adsorption process on three sorbents: two consisting of carbon nanotubes embedded on a polymer (polypropylene and polyethylene) and granulated active carbon as a reference. The results that were obtained show a significantly lower organic substance removal effectiveness in the case of sorbents containing carbon nanotubes, with an insignificantly lower unit effectiveness (mg/g) of the nanosorbents during first two hours of adsorption. Unfortunately, nanosorbents only allow removing substances with a low molecular weight and high aromaticity, which significantly reduces the possibility of its use in technical conditions for naturally occurring water and the sorption capacity nanotubes were significantly lower in comparison to the GAC.
DETERMINAN PRAKTIK TRANSFER PRICING DENGAN FIRM SIZE SEBAGAI PEMODERASI PADA PERUSAHAAN PERTAMBANGAN YANG TERDAFTAR DI BURSA EFEK INDONESIA

The purpose of this study is to analyze the effect of debt covenant, tax minimization, and audit quality on transfer pricing practice with firm size as the moderating variable. Employing purposive sampling, as much as 21 mining companies listed on the IDX in 2017-2019 were available for the test of hypothesis . Moderated regression analysis was used for the test of hypothesis. The results showed that debt covenants have no significant effect on transfer pricing. Tax minimization and audit quality have negative effect on transfer pricing and audit quality. In addition, firm size does not significantly moderate the relationship between debt covenant and transfer pricing, but firm size can significantly moderate the relationship between tax minimization and transfer pricing and can also significantly moderate the relationship between audit quality and transfer pricing.
Perceived stressors of undergraduate dental students at an Australasian dental school

The purpose of this study was to identify the perceived stressors of Bachelor of Dental Surgery (BDS) students at a prominent Australasian dental school using the Dental Environment Stress (DES) questionnaire. All BDS students were emailed a modified version of the DES questionnaire. The questionnaire consisted of forty questions: seven collecting demographic information, one free text question and thirty-two items related to various sources of stress, grouped into four subscales: 1) Academic 2) Clinical and patient related 3) Environmental and 4) Personal. Students were asked to rate the items on a five-point Likert-type scale ranging from not at all stressful (1) to extremely stressful (5). Of the 314 students emailed, 165 responded to the survey (52.5% response rate). The academic subscale had the highest self-reported mean stress score (3.09 ± 0.68 (SD)); compared with the clinical (2.71 ± 0.77), environmental (2.40 ± 0.77) and personal (2.37 ± 0.68) subscales. There was a statistically significant difference (p<0.05) in self-perceived clinic related stress levels between male and female students, with female students reporting more stress. There was also a statistically significant difference in self-perceived environmental stress between second- and third-year students (p=0.037), and in perceived personal stress between students based on their English language status (p=0.034). These findings can enable identification of students who might be at higher risk of stress to ensure support is provided for them; specifically, female students and students in their third year. Results also indicate the need to develop interventions to help all students with academic stressors.
It’s also about timing! When do pedestrians want to receive navigation instructions

ABSTRACT Despite the increased research interest in wayfinding assistance systems, research on the appropriate point in time or space to automatically present a route instruction remains a desideratum. We address this research gap by reporting on the results of an outdoor, within-subject design wayfinding study ( ). Participants walked two different routes for which they requested spoken, landmark-based turn-by-turn route instructions. By means of a survival analysis, we model the points in space at which participants issue such requests, considering personal, environmental, route- and trial-related variables. We reveal different landcover classes (e.g., densely built-up areas) and personal variables (e.g., egocentric orientation and age) to be important, discuss potential reasons for their impact and derive open research questions.