Previous studies revealed structural differences in cerebellar regions between monolinguals and bilinguals. However, the effect of bilingual experiences on cerebellar functional neuroplasticity remains unclear. Using resting-state functional magnetic resonance imaging (fMRI) data, we compared cerebellar functional connectivity (FC) between monolinguals and bilinguals, and then examined how age of second language acquisition (AoA-L2), immersion of L2 (Immersion-L2), proficiency level of L2 (PL-L2) and usage of L2 (Usage-L2) influence cerebellar FC in bilinguals. We found monolinguals exhibited increased FC between lobules VI, VIIIa and superior temporal gyrus. Increased AoA-L2 was related to decreased cerebello-cortical FC involving lobules VI, CrusI and precentral gyrus. Increased Immersion-L2 was associated with decreased cerebello-orbitofrontal FC. Higher PL-L2 corresponded to stronger cerebellar FC with posterior cingulate gyrus. Bilinguals who used L2 more frequently at home exhibited decreased cerebellar FC, while increased social Usage-L2 was associated with increased FC. These findings highlight bilingualism’s impact on cerebellar functional neuroplasticity, shaped by different bilingual experiences.

This paper introduces the Chinese Learner English Corpus (CLEC), comprising argumentative texts written by Chinese lower and upper secondary school students. CLEC expands learner corpus research by including texts from intermediate-level learners and rich metadata on their backgrounds, including engagement with self-initiated, so-called Extramural English (EE) activities outside the classroom. To illustrate potential uses, two case studies are presented. The first uses a keyword analysis to reveal thematic and stylistic differences between CLEC and its Swedish counterpart, SLEC, highlighting linguistic priorities related to distinct learning contexts. The second investigates lexical bundles associated with gaming, demonstrating how EE engagement might influence learners’ use of multiword units. Freely available online, CLEC facilitates contrastive interlanguage analysis and supports further research into L2 learning and use, particularly regarding the role of language exposure. The corpus is also a valuable resource for teacher trainees aiming to deepen their understanding of SLA processes.

This article explores innovation in the chamber music that the internationally acclaimed composer Tan Dun (b. 1957) composed during the early 1980s, particularly his integration of traditional Chinese music elements with modern Western composition techniques. A detailed analysis of a representative selection of these early chamber music works focuses on Tan Dun’s pursuit of cultural symbols within a contemporary musical landscape. The findings highlight Tan Dun’s use of musical features such as microtones, aleatoric elements and special playing techniques to evoke traditional Chinese cultural traces in his compositions. The article also discusses his approach to polyphonic construction, which not only continues the horizontal melodic axis of Chinese music, but also creates rich vertical textures.

We document that firms prefer counties with higher ethnic diversity in locating their interstate investments, especially for those pursuing innovation, seeking to establish service centers, or managing a diverse workforce. We also find some evidence that interstate investment in high ethnic diversity locations results in increased patent applications, sales growth, positive media coverage, and overall operating performance. Taken together, we show that firms prefer to invest in ethnically diverse locations as they recognize the potential benefits of leveraging a diverse labor supply, such as enhancing problem-solving, innovation, and performance.

Natural enemies serve a crucial role in crop protection through the regulation of pest population dynamics. Cyrtorhinus lividipennis is an important natural enemy of rice planthoppers. Fatty acid synthase (FAS), a multifunctional enzyme crucial for fatty acid biosynthesis, serves as a vital energy source for insect reproduction. However, the function of FAS in the reproductive processes of C. lividipennis remains incompletely understood. In this study, the ClFAS gene was successfully cloned from C. lividipennis. The open reading frame of ClFAS was 7224 bp, encoding a putative protein of 2407 amino acids. The expression levels of ClFAS were notably elevated in the fifth-instar nymphs, adults, as well as in the fat body and ovaries of female individuals. Silencing of ClFAS resulted in a reduction of 58.4%, 34.6%, and 49.0% in the expression levels of ClVg at 1-, 2-, and 3-days post-dsRNA injection, respectively. Furthermore, RNA interference (RNAi)-mediated depletion of ClFAS not only suppressed the Vg protein expression but also significantly impaired oocyte maturation and ovarian development. The fecundity of dsFAS-treated C. lividipennis females was markedly reduced by 49.5%, accompanied by significant decreases of 32.7% in oviposition duration and 26.3% in female adult lifespan. Our findings showed that ClFAS positively regulates the reproduction of C. lividipennis by promoting vitellogenesis and ovarian development, which provides valuable insights into how lipid metabolism governs fecundity in predatory insects.

Extant studies on cross-border venture capital (VC) investment predominantly focus on how country-level formal institutions impact the flow of VCs across borders, but the potential role of country-level sentiments in this process has received less attention. Drawing upon the trust literature, we explore how home country political sentiment affects cross-border VC investment. Using data on Chinese VCs’ cross-border investments from 2000 to 2021, we find that home country political sentiment positively affects the amount of cross-border VC investment. Government VC (GVC) and connected VC (through sentiment transmission) positively, while investor managerial team education and investor host country experience (through sentiment suppression) negatively, moderate the influence of home country political sentiment.

Femoral neck bone mineral density (FNBMD) is a high risk factor for femoral head fractures, and coffee intake affects bone mineral density, but the effect on FNBMD remains to be explored. First, we conducted an observational study in the National Health and Nutrition Examination Survey and collected data on coffee intake, FNBMD, and sixteen covariates. Weight linear regression was used to explore the association of coffee intake with FNBMD. Then, Mendelian randomisation (MR) was used to explore the causal relationship between coffee intake and FNBMD, the exposure factor was coffee intake, and the outcome factor was FNBMD. The inverse variance weighting (IVW) method was used for the analysis, while heterogeneity tests, sensitivity, and pleiotropy analysis were performed. A total of 5 915 people were included in the cross-sectional study, including 3 178 men and 2 737 women. In the completely adjusted model, no coffee was used as a reference. The ORs for the overall population at ‘< 1’, ‘1–<2’, ‘2–<4’, and ‘4+’ (95% CI) were 0.02 (–0.01, 0.04), 0.00 (–0.01, 0.02), –0.01 (–0.02, 0.00), and 0.00 (–0.01, 0.02), respectively. The male and female population showed no statistically significant differences in both univariate and multivariate linear regressions. In the MR study, the IVW results showed an OR (95% CI) of 1.06 (0.88–1.27), a P-value of 0.55, and an overall F-value of 80.31. The heterogeneity, sensitivity analyses, and pleiotropy had no statistical significance. Our study used cross-sectional studies and MR to demonstrate that there is no correlation or causal relationship between coffee intake and FNBMD.

Ultra-thin liquid sheets generated by impinging two liquid jets are crucial high-repetition-rate targets for laser ion acceleration and ultra-fast physics, and serve widely as barrier-free samples for structural biochemistry. The impact of liquid viscosity on sheet thickness should be comprehended fully to exploit its potential. Here, we demonstrate experimentally that viscosity significantly influences thickness distribution, while surface tension primarily governs shape. We propose a thickness model based on momentum exchange and mass transport within the radial flow, which agrees well with the experiments. These results provide deeper insights into the behaviour of liquid sheets and enable accurate thickness control for various applications, including atomization nozzles and laser-driven particle sources.

Using the syntactic priming paradigm, this study investigated abstract syntactic knowledge of Chinese transitive structures (i.e., subject-verb-object [SVO], BA, and BEI) in deaf children with cochlear implants (CIs). Specifically, we focused on the differences in the development of various syntactic structures (within CI children and compared with their typically hearing children) and the possible individual differences during this process. Results showed that both CI and hearing children exhibited structural priming for all syntactic structures (i.e., SVO, SbaOV structure [agent-patient ordering], and ObeiSV structure [patient-agent ordering]) after comprehending and repeating the prime sentence regardless of verb repetition. However, verb repetition induced an intense abstract priming effect in CI children but not hearing children, with the lexical boost effect more significant for SVO and BA structures. In addition, CI children’s working memory capability modulated the production of the BA structure but not SVO and BEI structures.

The multi-colour complete light curves and low-resolution spectra of two short period eclipsing Am binaries V404 Aur and GW Gem are presented. The stellar atmospheric parameters of the primary stars were derived through the spectra fitting. The observed and TESS-based light curves of them were analysed by using the Wilson-Devinney code. The photometric solutions suggest that both V404 Aur and GW Gem are semi-detached systems with the secondary component filling its critical Roche Lobe, while the former should be a marginal contact binary. The $O-C$ analysis found that the period of V404 Aur is decreasing at a rate of $dP/dt=-1.06(\pm0.01)\times 10^{-7}\,\mathrm{d}\,\mathrm{ yr}^{-1}$, while the period of GW Gem is increasing at $dP/dt=+2.41(\pm0.01)\times 10^{-8} \mathrm{d}\,\mathrm{yr}^{-1}$. The period decrease of V404 Aur may mainly be caused by the combined effects of the angular momentum loss (AML) via an enhanced stellar wind of the more evolved secondary star and mass transfer between two components. The period increase of GW Gem supports the mass transfer from the secondary to the primary. Both targets may be in the broken contact stage predicted by the thermal relaxation oscillations theory and will eventually evolve to the contact stage. We have collected about 54 well-known eclipsing Am binaries with absolute parameters from the literature. The relations of these parameters are summarised. There are some components that have a higher degree of evolution. The majority of their hydrogen shell may have been stripped away and the stellar internal layer exposed. The accretion processes from such evolved components may be very important for the formation of Am peculiarity in binaries.

Computer-based interactive items have become prevalent in recent educational assessments. In such items, detailed human–computer interactive process, known as response process, is recorded in a log file. The recorded response processes provide great opportunities to understand individuals’ problem solving processes. However, difficulties exist in analyzing these data as they are high-dimensional sequences in a nonstandard format. This paper aims at extracting useful information from response processes. In particular, we consider an exploratory analysis that extracts latent variables from process data through a multidimensional scaling framework. A dissimilarity measure is described to quantify the discrepancy between two response processes. The proposed method is applied to both simulated data and real process data from 14 PSTRE items in PIAAC 2012. A prediction procedure is used to examine the information contained in the extracted latent variables. We find that the extracted latent variables preserve a substantial amount of information in the process and have reasonable interpretability. We also empirically prove that process data contains more information than classic binary item responses in terms of out-of-sample prediction of many variables.

The inverse probability of treatment weighted (IPTW) estimator can be used to make causal inferences under two assumptions: (1) no unobserved confounders (ignorability) and (2) positive probability of treatment and of control at every level of the confounders (positivity), but is vulnerable to bias if by chance, the proportion of the sample assigned to treatment, or proportion of control, is zero at certain levels of the confounders. We propose to deal with this sampling zero problem, also known as practical violation of the positivity assumption, in a setting where the observed confounder is cluster identity, i.e., treatment assignment is ignorable within clusters. Specifically, based on a random coefficient model assumed for the potential outcome, we augment the IPTW estimating function with the estimated potential outcomes of treatment (or of control) for clusters that have no observation of treatment (or control). If the cluster-specific potential outcomes are estimated correctly, the augmented estimating function can be shown to converge in expectation to zero and therefore yield consistent causal estimates. The proposed method can be implemented in the existing software, and it performs well in simulated data as well as with real-world data from a teacher preparation evaluation study.

Accurate assessment of a student’s ability is the key task of a test. Assessments based on final responses are the standard. As the infrastructure advances, substantially more information is observed. One of such instances is the process data that is collected by computer-based interactive items and contain a student’s detailed interactive processes. In this paper, we show both theoretically and with simulated and empirical data that appropriately including such information in the assessment will substantially improve relevant assessment precision.

Process data refer to data recorded in log files of computer-based items. These data, represented as timestamped action sequences, keep track of respondents’ response problem-solving behaviors. Process data analysis aims at enhancing educational assessment accuracy and serving other assessment purposes by utilizing the rich information contained in response processes. The R package ProcData presented in this article is designed to provide tools for inspecting, processing, and analyzing process data. We define an S3 class ‘proc’ for organizing process data and extend generic methods summary and print for ‘proc’. Feature extraction methods for process data are implemented in the package for compressing information in the irregular response processes into regular numeric vectors. ProcData also provides functions for making predictions from neural-network-based sequence models. In addition, a real dataset of response processes from the climate control item in the 2012 Programme for International Student Assessment is included in the package.