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Combined with the prime paradigm, the present study aimed to explore the influence of emotion (anger, fear, happiness, and neutral) on performing multiplication estimation. Participants were asked to complete a two-digit multiplication estimation task using the down-up strategy (e.g., doing 20 × 80 = 1600 for 24 × 79). Behavioral results showed that the reaction time for completing multiplication estimation tasks under happy conditions was shorter than for those under anger and fear, and it was shorter under neutral than under fearful conditions. The ERP results showed that about 100 ms after multiplication estimation task onset, multiplication estimation execution in the context of happiness (vs. neutral) elicited smaller P1 amplitudes; about 170 ms after multiplication estimation task onset, the N170 amplitudes elicited by multiplication estimation strategy execution under different emotional priming conditions showed no significant differences. The above results showed that the impact of emotion priming demonstrates the occurrence of a dynamic process when participants use a specified strategy to complete the multiplication estimation task. The present study revealed that emotional valence modulated arithmetic strategy execution, suggesting the role of different emotions should be fully considered in similar study.

High-resolution X-ray spectroscopy in the sub-nanosecond to femtosecond time range requires ultrashort X-ray pulses and a spectral X-ray flux considerably larger than that presently available. X-ray free-electron laser (XFEL) radiation from hard X-ray self-seeding (HXRSS) setups has been demonstrated in the past and offers the necessary peak flux properties. So far, these systems could not provide high repetition rates enabling a high average flux. We report the results for a cascaded HXRSS system installed at the European XFEL, currently the only operating high-repetition-rate hard X-ray XFEL facility worldwide. A high repetition rate, combined with HXRSS, allows the generation of millijoule-level pulses in the photon energy range of 6–14 keV with a bandwidth of around 1 eV (corresponding to about 1 mJ eV–1 peak spectral density) at the rate of ten trains per second, each train including hundreds of pulses arriving at a megahertz repetition rate. At 2.25 MHz repetition rate and photon energies in the 6–7 keV range, we observed and characterized the heat-load effects on the HXRSS crystals, substantially altering the spectra of subsequent X-ray pulses. We demonstrated that our cascaded self-seeding scheme reduces this detrimental effect to below the detection level. This opens up exciting new possibilities in a wide range of scientific fields employing ultrafast X-ray spectroscopy, scattering and imaging techniques.A cascaded hard X-ray self-seeding system is demonstrated at the European X-ray free-electron laser. The setup enables millijoule-level pulses in the photon energy range of 6–14 keV at the rate of ten trains per second, with each train including hundreds of pulses arriving at a megahertz repetition rate.

A self-seeded X-ray free-electron laser (XFEL) is a promising approach to realize bright, fully coherent free-electron laser (FEL) sources in the hard X-ray domain that have been a long-standing issue with longitudinal coherence remaining challenging. At the Pohang Accelerator Laboratory XFEL, we have demonstrated a hard X-ray self-seeded XFEL with a peak brightness of 3.2 × 1035 photons s–1 mm–2 mrad–2 0.1% bandwidth (BW)–1 at 9.7 keV. The bandwidth (0.19 eV) is about 1/70 times as wide (close to the Fourier transform limit) and the peak spectral brightness is 40 times higher than in self-amplified spontaneous emission (SASE), with substantial improvements in the stability of self-seeding and noticeably suppressed pedestal effects. We could reach an excellent self-seeding performance at a photon energy of 3.5 keV (lowest) and 14.6 keV (highest) with the same stability as the 9.7 keV self-seeding. The bandwidth of the 14.6 keV seeded FEL was 0.32 eV, and the peak brightness was 1.3 × 1035 photons s–1 mm–2 mrad–2 0.1%BW–1. We show that the use of seeded FEL pulses with higher reproducibility and a cleaner spectrum results in serial femtosecond crystallography data of superior quality compared with data collected using SASE mode.A hard X-ray self-seeded X-ray free-electron laser at the Pohang Accelerator Laboratory provides X-ray pulses with peak brightness of 3.2 × 1035 photons s–1 mm–2 mrad–2 0.1%BW–1 at 9.7 keV and a very small shot-to-shot electron energy jitter of 0.012%.

To enhance the development of massive open online course (MOOC) teaching and learning, prevalent methods and characteristics employed by college students in MOOC learning strategies must be investigated. This study employed the grounded theory approach to systematically encode and construct a learning strategy model for the use of MOOCs among college students in China. This study used data obtained from 57 college students and applied qualitative research coding procedures and NVivo software (version 12.0). The results revealed that the core learning strategies used by college students in MOOC learning could be categorized into cognitive, resource management, and metacognitive types. Five specific learning strategies were most frequently used: elaboration, interactive and cooperation, help-seeking, effort management, and information selection strategies. However, association and questioning strategies are infrequently employed by college students in their learning. Therefore, educators must actively guide students to expand their innovative thinking abilities by implementing these strategies.

Zhang, et al. (2017) established the ecological microexpression recognition test (EMERT), but it only used white models’ expressions as microexpressions and backgrounds, and there was no research detecting its relevant brain activity. The current study used white, black and yellow models’ expressions as microexpressions and backgrounds to improve the materials ecological validity of EMERT, and it used eyes-closed and eyes-open resting-state fMRI to detect relevant brain activity of EMERT for the first time. The results showed: (1) Two new recapitulative indexes of EMERT were adopted, such as microexpression M and microexpression SD . The participants could effectively identify almost all the microexpressions, and each microexpression type had a significantly background effect. The EMERT had good retest reliability and calibration validity. (2) ALFFs (Amplitude of Low-Frequency Fluctuations) in both eyes-closed and eyes-open resting-states and ALFFs-difference could predict microexpression M . The relevant brain areas of microexpression M were some frontal lobes, insula, cingulate cortex, hippocampus, parietal lobe, caudate nucleus, thalamus, amygdala, occipital lobe, fusiform, temporal lobe, cerebellum and vermis. (3) ALFFs in both eyes-closed and eyes-open resting-states and ALFFs-difference could predict microexpression SD , and the ALFFs-difference was more predictive. The relevant brain areas of microexpression SD were some frontal lobes, insula, cingulate cortex, cuneus, amygdala, fusiform, occipital lobe, parietal lobe, precuneus, caudate lobe, putamen lobe, thalamus, temporal lobe, cerebellum and vermis. (4) There were many similarities and some differences in the relevant brain areas between microexpression M and SD . All these brain areas can be trained to enhance ecological microexpression recognition ability.

The PREMERT by Zhang, Yin, Shu, & Liu (2020) could test the individual’s microexpression recognition ability with six microexpression Ms and six microexpression SDs, but it and other studies did not explore the general microexpression recognition ability (the GMERA), or could not test the GMERA effectively. Therefore, the current study put forward and established the GMERA with the behavioral data of Zhang, Yin, Shu, & Liu (2020) and explored the relevant resting state brain activity of the GMERA indicators to prove that the GMERA is an individual cognitive characteristic from brain mechanisms with the neuroimaging data of Zhang, Yin, Shu, & Liu (2020). The results showed: (1) There was a three-layer hierarchical structure in human microexpression recognition ability: the GMERA (the highest layer); recognition of a type of microexpression under different expression backgrounds (the second layer); recognition of a certain microexpression under a certain expression background (the third layer). A common factor GMERA was extracted from the six microexpression types recognition in PREMERT. Four indicators of the GMERA were calculated from six microexpression Ms and six microexpression SDs, such as GMERAL (level of GMERA), GMERAF (fluctuation of GMERA), GMERAB (background effect of GMERA) and GMERABF (fluctuation of GMERAB), which had good parallel-forms reliability, calibration validity and ecological validity. The GMERA provided a concise and comprehensive overview of the individual’s microexpression recognition ability. The PREMERT was proved a good test to measure the GMERA. (2) ALFFs in both eyes-closed and eyes-opened resting-states and ALFFs-difference could predict the four indicators of the GMERA. The relevant resting state brain areas were some areas of the expression recognition network, the microexpression consciousness and attention network, and the motor network for the change from expression backgrounds to microexpression. (3) The relevant brain areas of the GMERA and of different types of microexpression recognition belonged to the three cognitive processes, but the relevant brain areas of the GMERA were the “higher-order” areas to be more concise and critical than those of different types of microexpression recognition.

The EMERT(ecological microexpression recognition test) by Zhang, et.al.(2017) used block design for backgrounds, therefore participants could not get comparable scores. The current study used random design for backgrounds to improve EMERT to REMERT (random EMERT), and used eyes-closed and eyes-open resting-state fMRI to detect relevant brain activity of REMERT for the first time. The results showed: (1)Two new recapitulative indexes of REMERT/EMERT were adopted, such as microexpression M and microexpression SD. Using random design, the participants could effectively identify almost all the microexpressions, and each microexpression type had significantly background effect. Using two EMERT as duplicates and calibrations, the REMERT had good duplicate reliability and calibration validity. Therefore the REMERT can be used as an individual test, and each participant can get comparable and recapitulative scores. (2)ALFFs in both eyes-closed and eyes-open resting-states and ALFFs-difference could predict microexpression M, and the ALFFs-difference was less predictive. The relevant brain areas of microexpression M were some frontal lobes, insula, cingulate cortex, hippocampus, amygdala, fusiform gyrus, parietal lobe, caudate nucleus, precuneus, thalamus, putamen, temporal lobe and cerebellum. (3)ALFFs in both eyes-closed and eyes-open resting-states and ALFFs-difference could predict microexpression SD, and the ALFFs-difference was more predictive. The relevant brain areas of microexpression SD were some frontal lobes, central anterior gyrus, supplementary motor area, insula, hippocampus, amygdala, cuneus, occipital lobe, fusiform gyrus, parietal lobe, caudate nucleus, pallidum, putamen, thalamus, temporal lobe and cerebellum. (4)There were many similarities and some differences of the relevant brain areas between microexpression M and SD. The ALFFs-difference was more sensitive to REMERT fluctuations. All these brain areas can be trained to enhance ecological microexpression recognition ability.

A cavity‐based X‐ray free‐electron laser (CBXFEL) is a possible future direction in the development of fully coherent X‐ray sources. CBXFELs consist of a low‐emittance electron source, a magnet system with several undulators and chicanes, and an X‐ray cavity. The X‐ray cavity stores and circulates X‐ray pulses for repeated FEL interactions with electron pulses until the FEL reaches saturation. CBXFEL cavities require low‐loss wavefront‐preserving optical components: near‐100%‐reflectivity X‐ray diamond Bragg‐reflecting crystals, outcoupling devices such as thin diamond membranes or X‐ray gratings, and aberration‐free focusing elements. In the framework of the collaborative CBXFEL research and development project of Argonne National Laboratory, SLAC National Accelerator Laboratory and SPring‐8, we report here the design, manufacturing and characterization of X‐ray optical components for the CBXFEL cavity, which include high‐reflectivity diamond crystal mirrors, a diamond drumhead crystal with thin membranes, beryllium refractive lenses and channel‐cut Si monochromators. All the designed optical components have been fully characterized at the Advanced Photon Source to demonstrate their suitability for the CBXFEL cavity application. The design, manufacturing and characterization of X‐ray optics for a cavity‐based X‐ray free‐electron laser are presented.

Both tai chi and walking can improve the physical health of the elderly, but the effect on the emotional cognitive function of the elderly is unclear. To investigate the effect of long-term walking and tai chi exercise on the emotional cognitive function of the elderly, 63 subjects were recruited in this study according to age and exercise habits, including 16 in the youth control group, 15 in the elderly non-exercise control group, 17 in the elderly walking group, and 18 in the elderly tai chi group. The “learning–test paradigm” of emotional faces was used to measure the subjects’ ability to recognize and remember emotional (negative and neutral) faces. Behavioral and EEG data were recorded during the learning and testing phases. The results showed that there is aging in emotional cognition in older adults compared with younger adults. Long-term walking and tai chi exercise can delay the deterioration of emotional cognitive function in older adults to some extent. Both walking and tai chi exercise can delay the decline in aging-related emotional face recognition function to some extent. Walking exercise can delay the decline in aging-related emotional face memory function to some extent.