To assess the therapeutic effects of probiotic oral therapy in pediatric patients with anorexia nervosa and to investigate its impact on intestinal flora composition, brain-gut peptide levels, and overall clinical outcomes. A retrospective study was conducted involving 100 children diagnosed with anorexia nervosa at Xingtang County People’s Hospital between January 2023 and June 2024. Patients were divided into two groups: a control group (n=50) receiving zinc gluconate oral solution alone and an observation group (n=50) receiving zinc gluconate plus probiotics. Outcome measures included intestinal flora analysis, brain-gut peptide levels (SS, NO), clinical efficacy, serum trace element levels (calcium, zinc, iron), and prognosis, including recurrence rates six months post-treatment. Baseline characteristics were similar between the two groups (P>0.05). After treatment, the observation group showed significantly higher levels of Bifidobacterium and Lactobacillus and lower levels of Enterobacter compared to the control group (P<0.05). Additionally, the observation group had lower levels of SS and NO (P<0.05), indicating improved brain-gut communication. Clinical efficacy was significantly higher in the observation group (P<0.05), with improved serum trace element levels (P<0.05 for calcium, zinc, and iron). Furthermore, the recurrence rate six months post-treatment was significantly lower in the observation group compared to the control group (P<0.05). Probiotic supplementation in children with anorexia nervosa effectively modulates intestinal flora, improves brain-gut peptide levels, and enhances clinical outcomes.

This study examines how the managerial interpretation of incentive arrangement affects corporate engagement in social areas, as reflected in corporate social performance, from two interrelated perspectives: the political influence view and the normative agency view. Building the theoretical framework on state-owned enterprise (SOE) executives' dual-career tracks perspective, we contend that economic factors (performance decline and relative pay gap) and political factors (socialist imprints and political career horizon) could divergently reshape the interpretation of incentive arrangement on corporate social performance. Using ‘Pay Ceiling Order’ as a quasi-natural experiment context, a secondary analysis, and a controlled experiment reveal that compensation restriction on top executives causes a decrease in corporate social performance. This relationship is weakened when there are stronger socialist imprints inherited by a focal firm and when the executives have a longer political prospect. In contrast, the relationship is strengthened when firms face severe performance declines and when the executives' compensation is relatively lower than peers. The findings show that compensation is an indispensable incentive joining with political and economic factors, enabling SOEs to engage in social areas. We discuss the implications of understanding top executive incentives with incentive arrangements and how the government purpose influences top executive responses to compensation incentive in ways that matter for long-term social value.

Aiming to address the issue of low accuracy in model predictions obtained from fitting frequency domain response curves for small unmanned helicopters during the process of modeling their flight dynamics, this study proposes a system identification algorithm based on the combination of weighted least squares and improved grey wolf optimisation algorithm. The algorithm utilises the weighted least squares method to obtain the initial model structure, optimises the initial model parameters using the improved grey wolf optimisation algorithm, and enhances the local search and global optimisation ability of the grey wolf optimisation algorithm by introducing an improved grey wolf subgrouping rule, nonlinear convergence factor and dynamic cooperative rule. Ultimately, this approach establishes a dynamic model for small, unmanned helicopters. The identified model is validated using flight test data, with findings demonstrating that this method achieves higher accuracy in model identification and better fits to frequency domain response curves, thus providing a more accurate reflection of the flight dynamics of small unmanned helicopters.

In rural China, male offspring are traditionally regarded as the primary heirs of household assets, particularly land. This study examines the impact of offspring gender composition on long-term agricultural investment behavior, using commercial organic fertilizer application as an example of a strategic long-term investment in farmland. Based on cross-sectional data from 4090 rice farming households across 10 cities (counties) in Hubei province, collected between 2021 and 2023, this analysis identifies three key findings. First, the absence of male offspring significantly reduces long-term agricultural investments, a result that remains robust even when addressing potential endogeneity biases using instrumental variable techniques. Second, households without male heirs exhibit stronger present-oriented preferences and diminished social capital, which further hinder long-term agricultural investments. Third, the negative impact of not having male offspring is more pronounced when the current agricultural decision-maker is male and when land marketization is underdeveloped. These findings underscore the complex interplay between gender norms and agricultural behavior, revealing significant socioeconomic implications of inheritance practices. The study provides insights into addressing these challenges by emphasizing the importance of promoting gender equality and advancing land marketization to enhance equitable land use and support long-term agricultural investment.

This paper revisits the role of skill distribution in shaping regional comparative advantage. Theoretically, we show that it is the relative skill dispersion between exporters and importers, rather than the absolute skill dispersion of exporters, that matters for the pattern of international trade. Using industry-level data on Chinese provincial export flows, we demonstrate that regions with a more dispersed skill distribution relative to their trading partners export more goods produced by sectors with lower skill complementarity. Exploring the potential mechanisms, we further find that the trade-promoting effect from relative skill dispersion probably operates through improving product quality and diversity.

The dynamic behaviour of helicopter during water impact, considering variations in initial downward velocity and pitching angle, have been investigated numerically and theoretically in the present study. The air-water two-phase flows are simulated by solving unsteady Reynolds-averaged Navier-Stokes equations enclosed by standard $k - \omega $ turbulence model. A treatment for computational domain in combination with a global dynamic mesh technique is applied to deal with the relative motion between the helicopter and water. Results indicate that the initial downward velocity of helicopter exhibits behaviour similar to that of a V-shaped body impacting on water, as does the initial pitching angle. To extend the theoretical approach for predicting the kinematic parameters during helicopter ditching, a shape factor capturing the combined effect of various attributes and an average deadrise angle for asymmetric wedges are also introduced.

Prehistoric humans seem to have preferred inhabiting small river basins, which were closer in distance to most settlements compared to larger rivers. The Holocene landscape evolution is considered to have played a pivotal role in shaping the spatiotemporal patterns of these settlements. In this study, we conducted comprehensive research on the relationship between landscape evolution and settlement distribution within the Huangshui River basin, which is a representative small river in Central China with numerous early settlements, including a prehistoric city known as the Wangjinglou site (WJL). Using geoarchaeological investigations, optically stimulated luminescence dating, pollen analysis, and grain-size analysis, we analyzed the characteristics of the Holocene environment. The results indicate the presence of two distinct geomorphic systems, namely the red clay hills and the river valley. The red clay hills, formed in the Neogene, represent remnants of the Songshan piedmont alluvial fan that was eroded by rivers. There are three grades of terraces within the river valley. T3 is a strath terrace and formed around 8.0 ka. Both T2 and T1 are fill terraces, which were developed around 4.0 ka and during the historical period, respectively. The sedimentary features and pollen analysis indicate the existence of an ancient lake-swamp on the platform during 11.0–9.0 ka. This waterbody gradually shrank during 9.0–8.0 ka, and ultimately disappeared after 8.0 ka. Since then, the development of large-scale areas of water ceased on the higher geomorphic units. River floods also cannot reach the top of these high geomorphic units, where numerous prehistoric settlements are located, including the Xia–Shang cities of the WJL site. Our research demonstrates that landscape stability supported the long-term and sustainable development of ancient cultures and facilitated the establishment of the WJL ancient cities in the region.

Embodiment theories postulate that language processing inherently engages the sensorimotor system. This study explores the embodiment of action verbs in the second language (L2) and the effects of various L2 experiences (L2 age of acquisition, exposure, dominance, and proficiency) on L2 embodiment. Sixty-one Chinese–English bilinguals participated in two experiments judging semantic relatedness: Experiment 1 involved verb–picture pairs, while Experiment 2 focused on verb–verb pairs. Both experiments were conducted in the participants’ first language (Chinese) and second language (English), with the stimuli depicting actions performed by specific effectors (e.g., mouth, hand, and foot). Results showed that participants took longer to reject mismatched verb–picture pairs and semantic-unrelated verb–verb pairs when the actions shared the same effector (e.g., walk–run) than those involving different effectors (e.g., eat–touch). Moreover, L2 age of acquisition, exposure, and dominance correlated with the L2 embodiment effect, with L2 age of acquisition and exposure modulating this effect. This study enhances our understanding of L2 embodied semantics and illuminates the impact of multidimensional L2 experiences on embodiment.

The Eastern population of the Lesser White-fronted Goose (EPLWFG) Anser erythropus is shared between Russia and China. The summer range of the EPLWFG has been recognised as a continuous area extending from the Olenyok River in the west to the Anadyr River in the east and northwards from 64°N. The aim of this study was to provide information on breeding behaviour; nest-sites, nesting habitats, and time of nesting; nesting success; timing of summer movements including moult migration; moult timing, duration, and moulting habitats; site fidelity; and the effect of human presence. To accomplish this, we combined the results from field surveys with GPS/GSM tracking. A total of 30 summer tracks from 19 individual EPLWFG were analysed. We estimated breeding propensity in 93.8% of adult LWFG, and this factor did not seem to depend on breeding success in the previous season. Reproductive success was 13.3% in all nesting attempts. Non-breeders arrived three-week later and departed a week earlier. The EPLWFG are highly mobile during the summer. The core moulting site for the entire EPLWFG was discovered by this study and is located along the lower reaches of the San-Yuryakh and Kyuanekhtyakh rivers flowing towards the Omulyakhskaya Bay of the East Siberian Sea. The EPLWFG flightless period was 24.8 ± 2.8 days. A part of failured EPLWFG (43.7 %) migrated back to its early summer breeding/staging site after having completed moult. The strong site fidelity (100%) of adult birds to both nesting and moulting sites promotes the formation of local breeding populations, which could be considered conservation units if genetic studies support this differentiation. The EPLWFG selects the remotest and least human-accessible area for their remigial moult, and the main site was discovered with the help of tracking.

This study aims to explore the dynamics of leadership reconfiguration within emergent state-owned enterprises (SOEs), i.e., privately owned enterprises (POEs) that have been acquired by SOEs. From an institutional logic perspective, we argue that the emergence of these SOEs reflects a process in which POEs, previously dominated by market logic, incorporate state logic and transition to a hybrid form. However, this process presents a paradox for emergent SOEs: while a greater extent of reconfiguration of leadership helps them gain greater legitimacy in front of state-related institutional referents, it also results in greater conflicts between members adhering to different logics. To address this paradox, we theorize on the differences in the reconfigurations of the board and top management team (TMT) by respectively connecting their functions to institutional control and agency, two typical forms of institutional power. Our analysis reveals that emergent SOEs tend to experience reconfiguration more in the board while less in TMT. Furthermore, we find that these main effects are moderated by the industrial state-ownership density and acquirees' preacquisition political connections. Our study contributes to the SOE and M&A literature by highlighting the uniqueness of emergent SOEs arising from POE-to-SOE acquisitions. Additionally, we propose a strategy to reconcile legitimation and internal stabilizations during logic hybridizations, thereby contributing to the institutional logic literature.

The rapid development of generative artificial intelligence (AI) systems, particularly those fuelled by increasingly advanced large language models, has raised concerns of their potential risks among policymakers globally. In July 2023, Chinese regulators enacted the Interim Measures for the Management of Generative AI Services (“the Measures”). The Measures aim to mitigate various risks associated with public-facing generative AI services, particularly those concerning information content safety and security. China’s approach to regulating AI to date has sought to address the risks associated with rapidly advancing AI technologies while fostering innovation and development. Tensions between these policy objectives are reflected in the provisions of the Measures. As Beijing moves towards establishing a comprehensive legal framework for AI governance, there will be growing interest in how China’s approach may influence AI governance and regulation at a global level.

We consider a test which allows students to attempt a multiple-choice question multiple times (i.e., multiple attempts). The most extreme form of multiple attempts is the answer-until-correct (AUC) procedure. Previous research has demonstrated that multiple-attempt procedures such as AUC could potentially enhance learning and increase reliability. However, for multiple-choice items, guessing is still non-ignorable. Traditional models of sequential item response theory (SIRT) could model multiple-attempt procedures but fail to take guessing into account. The purpose of this study is to propose SIRT models for multiple-choice, multiple-attempt items (SIRT-MM). First, we defined a family of SIRT-MM models to account for the idiosyncrasies of items, answer options, and examinee behavior. We also explained how these models could improve person parameter estimates by taking into account partial (mis)information of examinees. Second, we conducted model comparisons between the SIRT-MM models, the graded response model, and the nominal response model. Third, we discussed how the item and person parameters can be estimated, and evaluated item and person parameter recovery of SIRT-MM models under different conditions through a simulation study. Finally, we applied the SIRT-MM models to a real dataset and demonstrated their utility through model selection, person parameter recovery, and information functions.

In this paper, we propose a novel and highly effective variational Bayesian expectation maximization-maximization (VBEM-M) inference method for log-linear cognitive diagnostic model (CDM). In the implementation of the variational Bayesian approach for the saturated log-linear CDM, the conditional variational posteriors of the parameters that need to be derived are in the same distributional family as the priors, the VBEM-M algorithm overcomes this problem. Our algorithm can directly estimate the item parameters and the latent attribute-mastery pattern simultaneously. In contrast, Yamaguchi and Okada’s (2020a) variational Bayesian algorithm requires a transformation step to obtain the item parameters for the log-linear cognitive diagnostic model (LCDM). We conducted multiple simulation studies to assess the performance of the VBEM-M algorithm in terms of parameter recovery, execution time, and convergence rate. Furthermore, we conducted a series of comparative studies on the accuracy of parameter estimation for the DINA model and the saturated LCDM, focusing on the VBEM-M, VB, expectation-maximization, and Markov chain Monte Carlo algorithms. The results indicated that our method can obtain more stable and accurate estimates, especially for the small sample sizes. Finally, we demonstrated the utility of the proposed algorithm using two real datasets.

For the pulse shaping system of the SG-II-up facility, we propose a U-shaped convolutional neural network that integrates multi-scale feature extraction capabilities, an attention mechanism and long short-term memory units, which effectively facilitates real-time denoising of diverse shaping pulses. We train the model using simulated datasets and evaluate it on both the simulated and experimental temporal waveforms. During the evaluation of simulated waveforms, we achieve high-precision denoising, resulting in great performance for temporal waveforms with frequency modulation-to-amplitude modulation conversion (FM-to-AM) exceeding 50%, exceedingly high contrast of over 300:1 and multi-step structures. The errors are less than 1% for both root mean square error and contrast, and there is a remarkable improvement in the signal-to-noise ratio by over 50%. During the evaluation of experimental waveforms, the model can obtain different denoised waveforms with contrast greater than 200:1. The stability of the model is verified using temporal waveforms with identical pulse widths and contrast, ensuring that while achieving smooth temporal profiles, the intricate details of the signals are preserved. The results demonstrate that the denoising model, trained utilizing the simulation dataset, is capable of efficiently processing complex temporal waveforms in real-time for experiments and mitigating the influence of electronic noise and FM-to-AM on the time–power curve.

In this paper, we propose a joint modeling approach to analyze dependency in parallel response data. We define two types of dependency: higher-level dependency and within-item conditional dependency. While higher-level dependency can be estimated with common latent variable modeling approaches, within-item conditional dependency is a unique kind of information that is often not captured with extant methods, despite its potential to shed new insights into the relationship between the two types of response data. We differentiate three ways of modeling within-item conditional dependency by conditioning on raw values, expected values, or residual values of the response data, which have different implications in terms of response processes. The proposed approach is illustrated with the example of analyzing parallel data on response accuracy and brain activations from a Theory of Mind assessment. The consequence of ignoring within-item conditional dependency is investigated with empirical and simulation studies in comparison to conventional dependency analysis that focuses exclusively on relationships between latent variables.

Mediation analysis constitutes an important part of treatment study to identify the mechanisms by which an intervention achieves its effect. Structural equation model (SEM) is a popular framework for modeling such causal relationship. However, current methods impose various restrictions on the study designs and data distributions, limiting the utility of the information they provide in real study applications. In particular, in longitudinal studies missing data is commonly addressed under the assumption of missing at random (MAR), where current methods are unable to handle such missing data if parametric assumptions are violated.

In this paper, we propose a new, robust approach to address the limitations of current SEM within the context of longitudinal mediation analysis by utilizing a class of functional response models (FRM). Being distribution-free, the FRM-based approach does not impose any parametric assumption on data distributions. In addition, by extending the inverse probability weighted (IPW) estimates to the current context, the FRM-based SEM provides valid inference for longitudinal mediation analysis under the two most popular missing data mechanisms; missing completely at random (MCAR) and missing at random (MAR). We illustrate the approach with both real and simulated data.