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To improve the prediction accuracy of traffic flow under the influence of nearby time traffic flow disturbance, a dynamic spatiotemporal graph attention network traffic flow prediction model based on the attention mechanism was proposed. Considering the macroscopic periodic characteristics of traffic flow, the spatiotemporal features are extracted by constructing spatiotemporal blocks with an adjacent period, daily period, and weekly period respectively. The spatiotemporal block is mainly composed of a two-layer graph attention network and a gated recurrent unit to capture the hidden features of space and time. In space, based on considering adjacent road segments, the Pearson correlation coefficient is used to capture the hidden correlation characteristics between non-adjacent road segments according to a certain time step. In terms of time, due to the random disturbance of traffic flow at the micro level, the attention mechanism is introduced to use the adjacent time as the query matrix to weight the output characteristics of daily cycle and weekly cycle, and the three are connected in series to output the prediction results through the linear layer. Finally, the experimental results on the public data sets show that the proposed model is superior to the six baseline models.

Two-dimensional organic-inorganic hybrid halide perovskites possess diverse structural polymorphs with versatile physical properties, which can be controlled by order-disorder transition of the spacer cation, making them attractive for constructing semiconductor homojunctions. Here, we demonstrate a space-cation-dopant-induced phase stabilization approach to creating a lateral homojunction composed of ordered and disordered phases within a two-dimensional perovskite. By doping a small quantity of pentylammonium into (butylammonium) 2 PbI 4 or vice versa, we effectively suppress the ordering transition of the spacer cation and the associated out-of-plane octahedral tilting in the inorganic framework, resulting in phase pining of the disordered phase when decreasing temperature or increasing pressure. This enables epitaxial growth of a two-dimensional perovskite homojunction with tunable optical properties under temperature and pressure stimuli, as well as directional exciton diffusion across the interface. Our results demonstrate a previously unexplored strategy for constructing two-dimensional perovskite heterostructures by thermodynamic tuning and spacer cation doping. Hong et al. report 2D perovskite lateral homojunction consists of ordered and disordered phases, achieved by organic cation doping induced phase pinning, built upon which they develop tuneable optical properties under external stimuli and directional exciton diffusion in the homojunctions.

This study investigated the effects of dietary guanidinoacetic acid (GAA) supplementation on growth performance, carcass traits, meat quality, intestinal morphology, and cecal microbiota composition in yellow-feathered broilers. A total of 360 one-day-old chicks were randomly assigned to five groups with diets containing 0 (control), 300 mg/kg, 600 mg/kg, 900 mg/kg, and 1200 mg/kg GAA. In the initial growth phase, GAA supplementation increased average daily gain (ADG) by 13.01%, 8.97%, and 12.95% for the 300, 600, and 900 mg/kg groups, respectively, and reduced the feed conversion ratio (FCR), though these changes were not statistically significant (p > 0.05). Higher GAA dosages (900 and 1200 mg/kg) improved post-slaughter pH levels in breast muscle, indicating better meat quality, and significantly enhanced intestinal barrier function by increasing villus height and the villus-to-crypt ratio. However, 1200 mg/kg GAA led to a significant increase in serum ALT levels, raising concerns about potential liver stress. Overall, 900 mg/kg GAA supplementation demonstrated the most beneficial effects across various parameters, suggesting it as an optimal dosage to enhance production performance and meat quality in yellow-feathered broilers. Future studies are encouraged to investigate its long-term safety and underlying mechanisms.

Social media, particularly microblogging platforms, have been more and more essential for rapid information sharing and public discussion. However, they are also ideal platforms for spreading rumors, often leading to serious consequences (e.g., social panic and chaos). Since the rumors spread extremely rapidly on social media, automatically debunking the rumors in the early stage is of great importance to keep social media a healthy environment. Existing studies for early rumor detection mainly learn clues from the contents of rumor candidates and user profiles, however, difficult to use the rumor propagation patterns adequately, which has been proven crucial for rumor detection, as the propagation structure containing the abnormal pattern has not yet been formed in the early stage. To fill this gap, we propose a P ropagation P re diction based E arly R umor D etection (PreERD) model, which first predicts the propagation structure of a post and then combines it with the content and user profile features to identify rumors. Specifically, inspired by the idea of link prediction in complex networks, we construct the user propagation network, and apply a GAN-based model to predict the propagation link of posts, and then a GNN-based detection model with a hierarchical attention mechanism is designed to identify rumors, which aggregates the information of neighbours in predicted propagation network of the target post. Extensive experiments on 3 real-world datasets show that our PreERD model can achieve effective early rumour detection and significantly outperform multiple competitive rumour detection models.

Against the backdrop of increasingly interconnected environmental, social, and governance (ESG) challenges, enterprises must formulate sustainable strategies to achieve synergistic development among economic performance, social responsibility, and ecological conservation. As a core organizational resource, human resources serves as a critical enabler for fulfilling corporate social responsibility (CSR) and driving sustainable development. Whether enterprises can enhance the contribution of human resources to the fulfillment of corporate social responsibility and sustainable development is an important issue that currently needs to be studied in the field of human resource management. Therefore, this research follows the grounded theory method, integrates CSR and sustainable development theories, and uses systematic thinking to deeply explore the concept and structure of sustainable human resource management systems, and it develops relevant scales and combines exploratory and confirmatory factor analysis methods to revise and validate the scales. The research results show that the sustainable human resource management system is a multidimensional concept, including the following: employee rights protection, employee training and development, employee occupational health, employee relations management, and sustainable development management; its measurement scale contains five factors, with a total of 20 items. The results of factor analysis indicate that the reliability and validity tests of the developed scale have reached an ideal level. The research results enrich the concept and connotation of sustainable human resource management systems, and the development of the sustainable human resource management systems scale aims to promote the extension of the field of sustainable human resource management systems from theoretical exploration to empirical analysis research, providing a theoretical basis for Chinese enterprises to achieve sustainable development goals.

Background Cervical extension and flexion are presumably harmful to patients with degenerative cervical myelopathy (DCM) because they worsen medullary compression visible on dynamic magnetic resonance imaging (MRI). Dynamic somatosensory evoked potentials (SSEPs) are an objective tool to measure the electrophysiological function of the spinal cord at different neck positions. In contrast to previous hypotheses, a considerable proportion of patients with DCM present improved SSEPs upon extension and flexion compared to a neutral position. Methods Patients with DCM who underwent preoperative dynamic SSEP examinations and subsequent decompression surgeries between 2015 and 2019 were retrospectively evaluated. We compared extension and flexion SSEPs with neutral SSEPs in each patient and classified them into extension-improved (EI) or extension-nonimproved (EN) and flexion-improved (FI) or flexion-nonimproved (FN) groups. Preoperative clinical evaluations, decompression surgical methods and one-year follow-up clinical data were recorded. Cervical spondylolisthesis and cervical alignment types were evaluated on plain cervical lateral radiographs. The number of stenotic segments, Mühle stenosis grade and disc degeneration stage of the most severe segment, and presence of ligamentum flavum hypertrophy and intramedullary T2 weighted imaging (T2WI) hyperintensity were evaluated on lateral and axial MRI. Data were compared between the EN and EN groups or FI and FN groups with T-tests, chi-square tests or Kruskal-Wallis tests. Prediction criteria were determined with logistic regression analyses. Results Forty-nine patients were included, and 9 (18.4%) and 11 (22.4%) showed improved extension and flexion SSEPs compared to their own neutral SSEPs, respectively. Interestingly, EI or FI patients had significantly better one-year postoperative mJOA recoveries than EN or FN patients (T-test, P  < 0.001). Moreover, the disease duration (T-test, P  = 0.024), involved segment number (Kruskal-Wallis test, P < 0.001), and cervical alignment type (chi-square test, P  = 0.005) varied significantly between the EI and EN groups. The FI group presented a significantly higher Mühle stenosis grade than the FN group (Kruskal-Wallis test, P  = 0.038). Furthermore, ≤ 2 involved segments and straight or sigmoid cervical alignment were significant criteria predicting improved extension SSEPs (probability: 85.7%), while Mühle stenosis Grade 3 and disease duration ≤6 months were significant criteria predicting improved flexion SSEPs (probability: 85.7%). Conclusions Our findings provide evidence for neurophysiological improvement in patients with DCM at extension and flexion and its significance in predicting prognoses. Moreover, certain clinical and radiographic criteria may help predict neurophysiological improvement upon extension or flexion. Trial registration “ [2020]151 ”. Retrospectively registered on April 30, 2020.

Recently, wireless power transfer (WPT) technology has attracted much attention and shown rapid development. However, a fundamental challenge emerges in practical applications: how to achieve robust power transfer against the variation of operating conditions, such as the fluctuation of transfer distance, as well as the relative orientation of resonant coils. In this article, we theoretically propose and experimentally demonstrate that the robustness of a parity-time (PT) asymmetric system with unbalanced gain-loss working in a weak coupling region can be improved significantly, compared with that of a PT-symmetric system with balanced gain-loss working in a strong coupling region under the premise that the system works at a fixed optimal frequency. A pure real mode known as bound state in the continuum (BIC) in the weak coupling region of the PT-asymmetric system is adopted to ensure the high efficiency and stability of the WPT and break the limitations of balanced gain-loss of the PT-symmetric system. The better robustness performance originates from the orthogonal state with a pure real eigenmode embedded in the weak coupling region. Further experiments also verify that the PT-asymmetric system can achieve higher efficiency than that of the PT-symmetric system. In addition, we discuss the performance of the WPT system based on the theories of coupled mode theory (CMT) and circuit theory (CT); the BIC in the framework of CMT and a perfect impedance matching condition in the framework of CT for efficient power transfer are consistent. We also conducted power experimental verification of 30 watts, and found the efficiency between the coils can reach over 90% in dynamic scenarios, which meets expectations. The presented framework extends the field of non-Hermitian physics, bridges the gap between the non-ideal PT-symmetric system and a practical engineering application, and introduces a novel WPT mechanism for flexible application scenarios. Our results could provide instructive significance for practical applications of the WPT system in the long term.

Background In recent years, ophthalmology has emerged as a new frontier in medical artificial intelligence (AI) with multi-modal AI in ophthalmology garnering significant attention across interdisciplinary research. This integration of various types and data models holds paramount importance as it enables the provision of detailed and precise information for diagnosing eye and vision diseases. By leveraging multi-modal ophthalmology AI techniques, clinicians can enhance the accuracy and efficiency of diagnoses, and thus reduce the risks associated with misdiagnosis and oversight while also enabling more precise management of eye and vision health. However, the widespread adoption of multi-modal ophthalmology poses significant challenges. Main text In this review, we first summarize comprehensively the concept of modalities in the field of ophthalmology, the forms of fusion between modalities, and the progress of multi-modal ophthalmic AI technology. Finally, we discuss the challenges of current multi-modal AI technology applications in ophthalmology and future feasible research directions. Conclusion In the field of ophthalmic AI, evidence suggests that when utilizing multi-modal data, deep learning-based multi-modal AI technology exhibits excellent diagnostic efficacy in assisting the diagnosis of various ophthalmic diseases. Particularly, in the current era marked by the proliferation of large-scale models, multi-modal techniques represent the most promising and advantageous solution for addressing the diagnosis of various ophthalmic diseases from a comprehensive perspective. However, it must be acknowledged that there are still numerous challenges associated with the application of multi-modal techniques in ophthalmic AI before they can be effectively employed in the clinical setting.

Background Dynamic somatosensory evoked potentials (DSSEP) can be used to disclose abnormalities of ascending sensory pathways at dynamic positions and diagnose cervical spondylotic myelopathy (CSM). However, radiographic tests including magnetic resonance imaging (MRI) and dynamic X-ray are used much more widely in the management of CSM. Our study aims to clarify the correlations between several radiographic parameters and the DSSEP results, and further determine their reliability with clinical data. Methods We retrospectively enrolled 38 CSM patients with surgical intervention. DSSEP tests were performed before surgery. Amplitude ratios of DSSEP N13 and N20 waves at extension and flexion were calculated and recorded as N13_E, N20_E, N13_F, N20_F, respectively. Baseline severity was evaluated with the modified Japanese Orthopedic Association (mJOA) score and the Nurick grades. Prognosis was evaluated based on the 2-year recovery rate. Sagittal diameter and transverse areas of the cord and canal were measured and the the compressive ratios at the compressed site (Compression_Ratio), central (Central_Ratio), and 1/4-lateral points (1/4-Lateral_Compression_Ratio), and spinal cord/Canal Area Ratio were calculated. The intramedullary T2 hyperintensity patterns (Ax-CCM types) were also collected from MRI axial images. Dynamic X-rays were used to test for segmental instability of the cervical spine. The correlations between radiologic findings, DSSEP data, and clinical assessments were investigated. Results We found that DSSEP N13_E and N13_F correlated with the Compression_Ratio, Central_Ratio, 1/4-Lateral_Compression_Ratio (Pearson, p  < 0.05) and Ax-CCM types (ANOVA, p < 0.05) in MRI axial images and cervical segmental instability in dynamic X-ray (t-test, p  < 0.05). Apart from the 1/4-Lateral_Compression_Ratio, these radiographic parameters above also correlated with the baseline clinical assessments (Spearman or ANOVA or t-test, p  < 0.05) and postoperative recovery rate (Pearson or ANOVA or t-test, p < 0.05). Conclusions We found that the preoperative Compression_Ratio, Central_Ratio and 1/4-Lateral_Compression_Ratio in MRI and cervical segmental instability in dynamic X-ray could reflect the dynamic neural dysfunction of the spinal cord. Different Ax-CCM types corresponded to different DSSEP results at extension and flexion, suggesting divergent pathophysiology. These radiographic parameters could help evaluate disease severity and predict postoperative prognosis.

Due to its wide distribution, the long‐distance oil and gas pipeline will inevitably pass through the landslide risk area. This study aims to investigate the impact of landslide geological disasters on oil and gas pipelines, particularly focusing on the deformation characteristics of pipelines under various landslide dip angles. To achieve this, a large physical simulation platform was designed and established as part of the methods used to replicate the effects of landslide geological disasters on oil and gas pipelines. Experiments were conducted at different dip angles, monitoring and analyzing changes in stress and strain within the pipeline, as well as soil displacement. Based on the experimental results, we draw the following conclusions: (1) the bending process of the pipeline can be divided into slow‐bending stage, constant‐speed bending stage, and accelerated‐bending stage. (2) The tensile strain is produced back to the impact direction of landslide; the compressive strain is produced facing the direction of landslide. At the point with the largest impact force of the landslide, when the dip angle of the landslide is 38°, the rate of slow increase is the greatest in the four stages, which is about 77 times that at a slope of 10° (3) At the same point, with the increase of the dip angle, stress is also gradually increasing. When the slope reaches the angle posing a landslide hazard, the maximum rate of change of stress is about 26.9 × 10−6 kPa/s. (4) At the centre of the pipeline, the strain difference between the back and facing the direction of the landslide increases continuously. These experimental results have obtained the pipeline deformation law in the whole process of pipeline landslide disaster, which can provide great help for the monitoring and early warning of pipeline landslide disasters on site. This study investigates the impact of landslide geological disasters on oil and gas pipelines, focusing on pipeline deformation under varying landslide dip angles. A large physical simulation platform was used to replicate landslide effects, with experiments conducted at different dip angles to monitor stress, strain, and soil displacement. The results reveal distinct bending stages of the pipeline, significant variations in strain and stress with increasing dip angles.