Continued self-regulation is recognized as a critical factor for students’ successful learning in an online learning environment. In the context of college students’ online self-regulated learning (SRL), a research approach based on self-determination theory (SDT) is developed to explain the relations of students’ basic psychological needs to their intrinsic and extrinsic motivation, as well as their continued intention to engage in online SRL. The results show that the three basic needs are associated with intrinsic motivation, while only two needs, namely perceived relatedness and competence, are related to extrinsic motivation. In addition, continued intention to engage in online SRL is related to intrinsic and extrinsic motivation. Our study provides empirical evidence for the appropriateness of the application of SDT in online SRL.

The novel coronavirus disease 2019 (COVID-19) rapidly escalated to a global pandemic. To control the rate of transmission, governments advocated that the public practice social distancing, which included staying at home. However, compliance with stay-at-home orders has varied between countries such as China and the United States, and little is known about the mechanisms underlying the national differences. Based on the health belief model, the theory of reasoned action, and the technology acceptance model, health beliefs and behavioral intention are suggested as possible explanations. A total of 498 Chinese and 292 American college students were recruited to complete an online survey. The structural equation modeling results showed that health beliefs (i.e., perceived susceptibility, severity, and barriers) and behavioral intention played multiple mediating roles in the association between nationality and actual stay-at-home behaviors. Notably, the effect via perceived barriers → behavioral intention was stronger than the effects via perceived susceptibility and severity → behavioral intention. That is, American participants perceived high levels of susceptibility whereas Chinese participants perceived high levels of severity, especially few barriers, which further led to increased behavioral intention and more frequent stay-at-home behaviors. These findings not only facilitate a comprehensive understanding of cross-country differences in compliance with stay-at-home orders during peaks in the COVID-19 pandemic but also lend support for mitigation of the current global crisis and future disease prevention and health promotion efforts.

Although the relationship between stressors and thriving at work has been established, the linkage between them is still in the early stages of theory development. This study proposed a two-path model, based on Lepine’s stressors-performance model, to analyze the effects of the stressors on the thriving at work. Two complementary mediating paths were proposed, i.e., affective strain (positive affect) and motivation (self-efficacy), which were explained using affective events theory and expectancy theory, respectively. Based on the empirical data from 233 employees, the results show that challenge stressors could enhance employees’ positive affect and self-efficacy, thus leading to thriving at work; on the contrary, hindrance stressors would result in negative influences. In addition, it is also found that the effect of affective path tend to be greater than that of motivation path, which could provide a practical guide for organizations to effectively apply stress management and to promote employees thriving at work.

The High Energy X-ray telescope (HE) on-board the Hard X-ray Modulation Telescope (Insight-HXMT) can serve as a wide Field of View (FOV) gamma-ray monitor with high time resolution (μs) and large effective area (up to thousands cm2). We developed a pipeline to search for Gamma-Ray Bursts (GRBs), using the traditional signal-to-noise ratio (SNR) method for blind search and the coherent search method for targeted search. By taking into account the location and spectrum of the burst and the detector response, the targeted coherent search is more powerful to unveil weak and sub-threshold bursts, especially those in temporal coincidence with Gravitational Wave (GW) events. Based on the original method in literature, we further improved the coherent search to filter out false triggers caused by spikes in light curves, which are commonly seen in gamma-ray instruments (e.g. Fermi/GBM, POLAR). We show that our improved targeted coherent search method could eliminate almost all false triggers caused by spikes. Based on the first two years of Insight-HXMT/HE data, our targeted search recovered 40 GRBs, which were detected by either Swift/BAT or Fermi/GBM but too weak to be found in our blind search. With this coherent search pipeline, the GRB detection sensitivity of Insight-HXMT/HE is increased to about 1.5E-08 erg cm−2 (200 keV–3 MeV). We also used this targeted coherent method to search Insight-HXMT/HE data for electromagnetic (EM) counterparts of LIGO-Virgo GW events (including O2 and O3a runs). However, we did not find any significant burst associated with GW events.

This study discusses the influence of transformational leadership on job satisfaction through assessing six alternative models related to the mediators of leadership trust and change commitment utilizing a data sample (N = 341; M age = 32.5 year, SD = 5.2) for service promotion personnel in Taiwan. The bootstrap sampling technique was used to select the better fitting model. The tool of hierarchical nested model analysis was applied, along with the approaches of bootstrapping mediation, PRODCLIN2, and structural equation modeling comparison. The results overall demonstrate that leadership is important and that leadership role identification (trust) and workgroup cohesiveness (commitment) form an ordered serial relationship.

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It is imperative to understand the interconnectedness of water use and hydrological impacts for water policy design underlying varying hydrological conditions across space and over time. However, such analysis remains difficult, constrained by the lack of appropriate modeling tools that fully integrate water policies, water use, and hydrological processes with high spatiotemporal resolutions. To address this challenge, this study proposes a distributed policy design scheme featuring spatially variable and temporally dynamic policies for conjunctive surface water‐groundwater management in large river basins. A fully integrated modeling framework is developed to tightly couple (a) an agent‐based model for farmers' water use under distributed water policies and (b) a physically based hydrological model for surface water‐groundwater processes. The modeling framework is applied to the Heihe River Basin to assess water use and hydrological impacts under distributed water policies. By using the distributed policy scheme to adjust a water policy (e.g., groundwater tax) across space and over time, we found that hydrological outcomes can be improved without adversely reducing agricultural water supply. For example, by shifting the implementation of a high groundwater tax from dry to wet years, a rise of the water table by 0.28 m (0.03–0.95 m across different irrigation districts) can be achieved while the total water supply is maintained at a similar level. Furthermore, hydrological externality effects among nearby districts can be explicitly identified and quantified based on assessments of spatially varying water policies. This study highlights the need for water policy design to consider spatiotemporal variations in the physical hydrological system.

The merger event of double neutron star (DNS) system (GW170817) was detected by the gravitational-wave (GW) detectors (Advanced LIGO and Advanced Virgo) in 2017 for the first time, so their mass distribution has become a significant topic with the new round GW hunting (O3) in 2019. A few models (e.g. Gaussian, two-Gaussian, or mixture-Gaussian) were adopted to draw the mass distribution of observed Galactic DNS systems, however, there is no a confirmed model now due to the small size of DNS samples (N < 20). Here we focus on determining the most probable distribution ranges of DNS masses without model selection by assuming the neutron star masses to be uniformly distributed between the lower and upper bounds. We apply a Bayesian analysis and Markov chain Monte Carlo simulation to 15 Galactic DNS systems, and obtain that the component masses of DNS systems should mainly fall in the range of 1.165–1.590 M⊙, and the predominant ranges for the total mass, mass ratio, and chirp mass lie in 2.535–2.867 M⊙, 0.741–0.995, and 1.115–1.237 M⊙, respectively. Our results are in agreement with the properties of DNS in GW170817, whose 90 per cent credible intervals for the component masses, total masses, mass ratio, and chirp masses are 1.16–1.60 M⊙, $2.73_{-0.01}^{+0.04}\, \mathrm{ M}_\odot$, 0.73–1.00, and $1.186_{-0.001}^{+0.001}\, \mathrm{ M}_\odot$, respectively. The above similarity is an important indicator that reveals the source of GW170817 to be a DNS system from the galaxy NGC 4993, and our results can be tested by the forthcoming GW hunting O3.