Miracle-dz/UniFAR-FTUs huggingface dataset:
The Effect and its Internal Mechanism of Inward FDI on Outward FDI– Empirical Test Based on Data of Fujian Province from 2004 to 2019

Inward foreign direct investment (IFDI) and outward foreign direct investment (OFDI) are two important parts of Fujian's opening-up strategy. With the deepening of economic globalization, Fujian Province has achieved rapid growth both in attracting foreign investment and in outward investment. So, what is the relationship between IFDI and OFDI? Does the spillover effect of attracting foreign investment in Fujian Province promote outward investment? On the basis of combing the influence mechanism of IFDI on OFDI, combined with the theory of Investment Development Path, this paper empirically tests the influence of IFDI on OFDI by using the provincial data of Fujian Province from 2004 to 2019. The results show that: attracting foreign investment in Fujian Province significantly promotes the increase of non-financial outward investment, and the strength of this effect is related to the absorption capacity of IFDI spillover effect. The empirical test also shows that: the sounder the infrastructure system and the higher the level of financial development, the better the absorption of the spillover effect. Contrary to our expectation, the cross regression coefficient of human capital and IFDI is negative, which may be related to the mismatch of human capital in foreign-invested enterprises in Fujian Province, but the important role of human capital in absorptive capacity cannot be underestimated.
How Social Influence and Image Impact on the Intention to Use a Technology: A Study from the Battery Electric Vehicle Domain

Technology research offers several theories and models to explain how individuals accept and use technology innovations. While these often focus on the technical aspects of the innovation, they tend to downplay the affective component of technology. Recognizing that the adoption of technology is also determined by what it means and represents to the users, this paper aims to fill the gap in the literature by studying the effects of social influence and image on the behavioral intention to adopt a technology. We used structural equation modeling (SmartPLS) to analyze data collected from 238 self-administrated surveys regarding the behavioral intention of Macau residents to use battery electric vehicles. The result showed significant relationships among the variables in the model and depicted the construct of image as a strong factor in the adoption decision. Our findings suggest that social influence may not exhibit substantial impact in the case of innovations in their initial phase and, more importantly, the construct of image could be included as a key predictor of behavioral intention in technology acceptance models, particularly in contexts where the choices that consumers make are public, and therefore subject to judgments from the members of the community.
Coal not diamonds: how memory pressure falters mobile video QoE

The popularity of video streaming on smartphones has led to rising demands for high-quality mobile video streaming. Consequently, we are observing growing support for higher resolution videos (e.g., HD, FHD, QHD) and higher video frame rates (e.g., 48 FPS, 60 FPS). However, supporting high-quality video streaming on smartphones introduces new challenges---besides the available network capacity, the smartphone itself can become a bottleneck due to resource constraints, such as low available memory. In this paper, we conduct an in-depth investigation of memory usage on smartphones and its impacts on mobile video streaming. Our investigation - driven by a combination of a user study, user survey, and experiments on real smartphones - reveals that (i) most smartphones observe memory pressure (i.e., low available memory scenarios), (ii) memory pressure can have a significant impact on mobile video QoE when streaming high-quality videos, e.g., resulting in the mean frame drop rate of 9--100% across smartphones and significantly lower user ratings, and (iii) the drop in mobile video QoE happens primarily due to the way in which video processes interact with kernel-level memory management mechanism, with opportunities for improving mobile video QoE through better adaptation by video clients.
Stochastic Event-Based Control and Estimation

Digital controllers are traditionally implemented using periodic sampling, computation, and actuation events. As more control systems are implemented to share limited network and CPU bandwidth with other tasks, it is becoming increasingly attractive to use some form of event-based control instead, where precious events are used only when needed. Forms of event-based control have been used in practice for a very long time, but mostly in an ad-hoc way. Though optimal solutions to most event-based control problems are unknown, it should still be viable to compare performance between suggested approaches in a reasonable manner. This thesis investigates an event-based variation on the stochastic linear-quadratic (LQ) control problem, with a fixed cost per control event. The sporadic constraint of an enforced minimum inter-event time is introduced, yielding a mixed continuous-/discrete-time formulation. The quantitative trade-off between event rate and control performance is compared between periodic and sporadic control. Example problems for first-order plants are investigated, for a single control loop and for multiple loops closed over a shared medium. Path constraints are introduced to model and analyze higher-order event-based control systems. This component-based approach to stochastic hybrid systems allows to express continuous- and discrete-time dynamics, state and switching constraints, control laws, and stochastic disturbances in the same model. Sum-of-squares techniques are then used to find bounds on control objectives using convex semidefinite programming. The thesis also considers state estimation for discrete time linear stochastic systems from measurements with convex set uncertainty. The Bayesian observer is considered given log-concave process disturbances and measurement likelihoods. Strong log-concavity is introduced, and it is shown that the observer preserves log-concavity, and propagates strong log-concavity like inverse covariance in a Kalman filter. A recursive state estimator is developed for systems with both stochastic and set-bounded process and measurement noise terms. A time-varying linear filter gain is optimized using convex semidefinite programming and ellipsoidal over-approximation, given a relative weight on the two kinds of error. (Less)
How Chinese Proverbs Influence Risk Attitude and Intertemporal Decision- Making in Chinese People

This paper focuses on whether Chinese proverbs have an impact on people's risk choice and time preference, which is a relatively new and interesting topic. The main research method used was a questionnaire survey, based on which some mathematical methods were used along with the literature to analyse and investigate. According to the overall results, it is clear that proverbs have an influence on people in both areas, implying that these factors may be relevant in future analyses of behavioural economics and that new perspectives in this field may be identified through this analysis, which may provide new ideas and approaches for solving related problems in the future.
The Continuity of Locomotion

Natural interaction between multiple users within a shared virtual environment (VE) relies on each other's awareness of the current position of the interaction partners. This, however, cannot be warranted when users employ noncontinuous locomotion techniques, such as teleportation, which may cause confusion among bystanders. In this paper, we pursue two approaches to create a pleasant experience for both the moving user and the bystanders observing that movement. First, we will introduce a Smart Avatar system that delivers continuous full-body human representations for noncontinuous locomotion in shared virtual reality (VR) spaces. Smart Avatars imitate their assigned user's real-world movements when close-by and autonomously navigate to their user when the distance between them exceeds a certain threshold, i.e., after the user teleports. As part of the Smart Avatar system, we implemented four avatar transition techniques and compared them to conventional avatar locomotion in a user study, revealing significant positive effects on the observers' spatial awareness, as well as pragmatic and hedonic quality scores. Second, we introduce the concept of Stuttered Locomotion, which can be applied to any continuous locomotion method. By converting a continuous movement into short-interval teleport steps, we provide the merits of non-continuous locomotion for the moving user while observers can easily keep track of their path. Thus, while the experience for observers is similarly positive as with continuous motion, a user study confirmed that Stuttered Locomotion can significantly reduce the occurrence of cybersickness symptoms for the moving user, making it an attractive choice for shared VEs. We will discuss the potential of Smart Avatars and Stuttered Locomotion for shared VR experiences, both when applied individually and in combination.
Neural Brushstroke Engine

We propose Neural Brushstroke Engine, the first method to apply deep generative models to learn a distribution of interactive drawing tools. Our conditional GAN model learns the latent space of drawing styles from a small set (about 200) of unlabeled images in different media. Once trained, a single model can texturize stroke patches drawn by the artist, emulating a diverse collection of brush styles in the latent space. In order to enable interactive painting on a canvas of arbitrary size, we design a painting engine able to support real-time seamless patch-based generation, while allowing artists direct control of stroke shape, color and thickness. We show that the latent space learned by our model generalizes to unseen drawing and more experimental styles (e.g. beads) by embedding real styles into the latent space. We explore other applications of the continuous latent space, such as optimizing brushes to enable painting in the style of an existing artwork, automatic line drawing stylization, brush interpolation, and even natural language search over a continuous space of drawing tools. Our prototype received positive feedback from a small group of digital artists.
Infrared Power-Law Galaxies in the Chandra Deep Field-South: Active Galactic Nuclei and Ultraluminous Infrared Galaxies

We investigate the nature of a sample of 92 Spitzer MIPS 24 μm-selected galaxies in the CDF-S, showing power-law-like emission in the Spitzer IRAC 3.6-8 μm bands. The main goal is to determine whether the galaxies not detected in X-rays (47% of the sample) are part of the hypothetical population of obscured AGNs not detected even in deep X-ray surveys. The majority of the IR power-law galaxies are ULIRGs at z > 1, and those with LIRG-like IR luminosities are usually detected in X-rays. The optical-to-IR SEDs of the X-ray-detected galaxies are almost equally divided between a BLAGN SED class (similar to an optically selected QSO) and an NLAGN SED (similar to the BLAGN SED but with an obscured UV/optical continuum). A small fraction of SEDs resemble warm ULIRGs (e.g., Mrk 231). Most galaxies not detected in X-rays have SEDs in the NLAGN+ULIRG class as they tend to be optically fainter and possibly more obscured. Moreover, the IR power-law galaxies have SEDs significantly different from those of high-z (zsp > 1) IR (24 μm) selected and optically bright (VVDS IAB ≤ 24) star-forming galaxies whose SEDs show a very prominent stellar bump at 1.6 μm. The galaxies detected in X-rays have 2-8 keV rest-frame luminosities typical of AGNs. The galaxies not detected in X-rays have global X-ray-to-mid-IR SED properties that make them good candidates to contain IR-bright X-ray-absorbed AGNs. If all these sources are actually obscured AGNs, we would observe a ratio of obscured to unobscured 24 μm-detected AGNs of 2 : 1, whereas models predict a ratio of up to 3 : 1. Additional studies using Spitzer to detect X-ray-quiet AGNs are likely to find more such obscured sources.
The Effect of Workplace Bullying on Sleep Quality: A Mediated Moderation Model

Workplace bullying is one of the focuses of organizational behavior research in recent years. Previous studies have shown that it is not only an important factor affecting employees' career performance, but also affects employees' life happiness, physical and mental health, and even their sleep quality. However, it is a pity that the mechanism of workplace bullying on sleep quality is still unclear in China's workplace environment. Therefore, in order to further explore the mediating mechanism and possible regulating mechanism of the impact of workplace bullying on employees' sleep quality, we conducted an online survey study on 436 employees. SPSS 24.0 and PROCESS were used to analyze the data results, and the Bootstrap method was used to analyze the mediation effect. The results found that: 1) workplace bullying was negatively related to sleep quality; 2) affective rumination mediated the relationship between workplace bullying and sleep quality and 3) this indirect effect was moderated by psychological detachment, specifically when workplace bullying is low, individuals with high psychological detachment are better able to cope with it than those with low psychological detachment. High psychological disengaged individuals always had lower levels of affective rumination than low psychological disengaged individuals. Research significance: The results of this study can help reduce the damage of workplace bullying to the sleep quality of employees, thus improving the happiness of life of employees, helping to improve the management ability of enterprises, and contributing to the development of a well-off society.
High-Order Directional Fields

We introduce a framework for representing face-based directional fields of an arbitrary piecewise-polynomial order. Our framework is based on a primal-dual decomposition of fields, where the exact component of a field is the gradient of piecewise-polynomial conforming function, and the coexact component is defined as the adjoint of a dimensionally-consistent discrete curl operator. Our novel formulation sidesteps the difficult problem of constructing high-order non-conforming function spaces, and makes it simple to harness the flexibility of higher-order finite elements for directional-field processing. Our representation is structure-preserving, and draws on principles from finite-element exterior calculus. We demonstrate its benefits for applications such as Helmholtz-Hodge decomposition, smooth PolyVector fields, the vector heat method, and seamless parameterization.
Mixed-Cultural Speech for Intelligent Virtual Agents - the Impact of Different Non-Native Accents Using Natural or Synthetic Speech in the English Language

This paper presents an exploratory study investigating the impact of non-native accented speech on the perception of Intelligent Virtual Agents (IVAs). In an online study, native English speakers watched a video of an IVA holding a monologue whilst speaking English with either a Spanish, Hindi or Mandarin accent that was either recorded by native speakers of that respective language (natural speech) or synthetically generated (synthetic speech). The results showed a significant impact of naturalness of speech on the IVAs perceived warmth and a significant interaction of accent and naturalness of speech on its perceived competence. The naturalness of speech impacted the participants’ perception of the IVA as a non-native speaker of English, and the correctness of the attributed mother tongue in the Spanish and the Mandarin accent condition. These results are a valuable contribution to research on mixed-cultural IVAs in general and non-native speech as a cultural cue more specifically.
The Application of Beneish M-Score Method in Detecting Fraudulent Manipulation on Financial Statements (Case Study of Indonesian Government-State Owned Enterprise (SOE) Registered on Indonesian Stock Exchange 2016-2020

This research aims to identify and examine the detection of financial fraud using Beneish M-Score analysis. The analysis consists of eight-fold independent variables: Days Sales in Receivable Index (DSRI), Gross Margin Index (GMI), Asset Quality Index (AQI), Sales Growth Index (SGI), Depreciation Index (DEPI), Selling, General and Administrative Index (SGAI), Leverage Index (LVGI), and Total Accruals to Total Assets (TATA). Secondary data is utilized throughout the data collection process whilst the research sample involves 11 government- state owned enterprise (SOE) that are registered on the Indonesian Stock Exchange (BEI) over the year of 2016-2020. The aforementioned sample is elected by purposive sampling technique. The researchers adopt SPSS 25 to conduct the data processing and multiple linear regression for testing the corresponding hypotheses. The results of this research indicate that Beneish M-Score is not only proven for its effectiveness in fraud detection, but also for its comprehensive assistance in expecting potential fraud inside BUMNs, particularly in regard to financial statements.
Investigation on citizen trust towards e-government services in GBA – A study on WeChat and Alipay government service mini-programs

Citizens' trust in eGovernment is crucial for the successful implementation of new electronic services. This relationship in the Greater Bay Area (GBA) plays an essential role since the Government services rely on mobile mini-programs This study investigates the trust towards government service mini-programs in WeChat and Alipay. A user feedback questionnaire was designed, and a total of 609 valid samples were collected from Shenzhen, Guangzhou, Hong Kong, and Macau. The findings imply that competence, integrity, and benevolence are the key components of trust in e-government (TIEG). TIEG positively influences perceived value (PV), which positively affects citizens' Intention to adopt service mini-programs. PV significantly mediates the relationship between TIEG and Intention. Although TIEG does not effectively reduce perceived risk (PR), risk issues cannot be ignored in the adoption process. Finally, this article proposes relevant implications and suggestions for the GBA government agents and policy makers.
Learning Virtual Chimeras by Dynamic Motion Reassembly

The Chimera is a mythological hybrid creature composed of different animal parts. The chimera's movements are highly dependent on the spatial and temporal alignments of its composing parts. In this paper, we present a novel algorithm that creates and animates chimeras by dynamically reassembling source characters and their movements. Our algorithm exploits a two-network architecture: part assembler and dynamic controller. The part assembler is a supervised learning layer that searches for the spatial alignment among body parts, assuming that the temporal alignment is provided. The dynamic controller is a reinforcement learning layer that learns robust control policy for a wide variety of potential temporal alignments. These two layers are tightly intertwined and learned simultaneously. The chimera animation generated by our algorithm is energy efficient and expressive in terms of describing weight shifting, balancing, and full-body coordination. We demonstrate the versatility of our algorithm by generating the motor skills of a large variety of chimeras from limited source characters.
THE DQ HERCULIS STARS

We review the properties of the DQ Herculis stars: cataclysmic variables containting an accreting, magnetic, rapidly rotating white dwarf. These stars are characterized by strong X-ray emission, high-excitation spectra, and very stable optical and X-ray pulsations in their light curves. There is considerable resemblance to their more famous cousins, the AM Herculis stars, but hte latter class is additionally characterized by spin-orbit synchronism and the presence of strong circular polarization. We list eighteen stars passing muster as certain or very likely DQ Her stars. The rotational periods range from 33 seconds to 2.0 hours. Additional periods can result when the rotating searchlight illuminates other structures in the binary. A single hypothesis explains most of the observed properties: magnetically channeled accretion within a truncated disk. Some accretion flow still seems to proceed directly to the mangetosphere, however. The white dwarfs' magnetic moments are in the range 1032 - 1034 G cm3, slighly weaker than in AM Her stars but with some probable overlap. The more important reason why DQ Hers have broken synchronism is probably their greater accretion rate and orbital separation. The observed Lx/Lv values are surprisingly low for a rapidly accreting white dwarf, suggesting that most of the accretion energy is not radiated in a strong shock above the magnetic pole. The fluxes can be more satisfactorily explained if most of the radial infall energy manages to bypass the shock and deposit itself directly in the white dwarf photosphere, where it should emerge as EUV radiation. This also provides an adequate source of ionizing photons to power the high-excitation optical and UV emission lines. This is probablythe DQ Her analogue to the famous "soft X-ray excess" in AM Her stars. However, unlike the AM Her case, this radiation has not been directly observed, so the analogy must not (yet) be embraced too firmly. There is some conventional wisdom today which segregates the short-period from the long-period DQ Her stars. But the observational grounds for this distinction are slim, except in one respect: X-ray emission from short-period systems appears to be weaker and softer. This must be due to the shallower depth of the potential well, and/or the greater difficulty the fast rotators have in enforcing radial accretion flow.
How gullible are web measurement tools?: a case study analysing and strengthening OpenWPM's reliability

Automated browsers are widely used to study the web at scale. Their premise is that they measure what regular browsers would encounter on the web. In practice, deviations due to detection of automation have been found. To what extent automated browsers can be improved to reduce such deviations has so far not been investigated in detail. In this paper, we investigate this for a specific web automation framework: OpenWPM, a popular research framework specifically designed to study web privacy. We analyse (1) detectability of OpenWPM, (2) resilience of OpenWPM's data recording, and (3) prevalence of OpenWPM detection. Our analysis (1) reveals OpenWPM is easily detectable. Our investigation of OpenWPM's data recording integrity (2) identifies novel evasion techniques and previously unknown attacks against OpenWPM's instrumentation. We investigate and develop mitigations to address the identified issues. Finally, in a scan of 100,000 sites (3), we observe that OpenWPM is commonly detected (~14% of front pages). Moreover, we discover integrated routines in scripts specifically to detect OpenWPM clients. In conclusion, our case study shows that even the most popular web measurement framework, OpenWPM, is more gullible than expected, and this gullibility is rarely accounted for in studies.