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Traffic flow prediction is a key issue in intelligent transportation systems. The growing trend in data disclosure has created more potential sources for the input for predictive models, posing new challenges to the prediction of traffic flow in the era of big data. In this study, the prediction of urban traffic flow was regarded as a spatiotemporal prediction problem, focusing on the traffic speed. A Graph LSTM (Long Short-Term Memory) Spatiotemporal Neural Network (GLSNN) model was constructed to perform a multi-scale spatiotemporal fusion prediction based on the multi-source input data. The GLSNN model consists of three parts: MS-LSTM, LZ-GCN, and LSTM-GRU. We used the MS-LSTM module to scale the traffic timing data, and then used the LZ-GCN network and the LSTM-GRU network to capture both the time and space dependencies. The model was tested on a real traffic dataset, and the experiment results verified the superior performance of the GLSNN model on both a high-precision and multi-scale prediction of urban traffic flow.

The origin–destination (OD) matrix describes traffic flow information between regions. It is a critical input for intelligent transportation systems (ITS). However, obtaining the OD matrix remains challenging due to high costs and privacy concerns. Synthetic data, which have the same statistical distribution of real data, help address privacy issues and data scarcity. Based on Generative Adversarial Networks (GAN), OD matrix generation models, which can effectively generate a synthetic OD matrix, help to address the challenge of obtaining OD matrix data in ITS research. However, existing OD matrix generation methods can only handle with tens of nodes. To address this challenge, this study proposes the Origin–Destination Progressive Growing Generative Adversarial Networks (OD-PGGAN) for large-scale OD matrix generation task which adapt the PGGAN architecture. OD-PGGAN adopts a progressive learning strategy to gradually learn the structure of the OD matrix from a coarse to fine scale. OD-PGGAN utilizes multi-scale generators and discriminators to perform generation and discrimination tasks at different spatial resolutions. OD-PGGAN introduces a geography-based upsampling and downsampling algorithm to maintain the geographical significance of the OD matrix during spatial resolution transformations. The results demonstrate that the proposed OD-PGGAN can generate a large-scale synthetic OD matrix with 1024 nodes that have the same distribution as the real sample and outperforms two classical methods. The OD-PGGAN can effectively provide reliable synthetic data for transportation applications.

Autonomous localization without local wireless facilities is proven as an efficient way for realizing location-based services in complex urban environments. The precision of the current map-matching algorithms is subject to the poor ability of integrated sensor-based trajectory estimation and the efficient combination of pedestrian motion information and the pedestrian indoor network. This paper proposes an autonomous multi-floor localization framework based on smartphone-integrated sensors and pedestrian network matching (ML-ISNM). A robust data and model dual-driven pedestrian trajectory estimator is proposed for accurate integrated sensor-based positioning under different handheld modes and disturbed environments. A bi-directional long short-term memory (Bi-LSTM) network is further applied for floor identification using extracted environmental features and pedestrian motion features, and further combined with the indoor network matching algorithm for acquiring accurate location and floor observations. In the multi-source fusion procedure, an error ellipse-enhanced unscented Kalman filter is developed for the intelligent combination of a trajectory estimator, human motion constraints, and the extracted pedestrian network. Comprehensive experiments indicate that the presented ML-ISNM achieves autonomous and accurate multi-floor positioning performance in complex and large-scale urban buildings. The final evaluated average localization error was lower than 1.13 m without the assistance of wireless facilities or a navigation database.

Previous real-time map matching algorithms for in-vehicle navigation systems had some efficiencies and defects on time lagging and low accuracy. As a response, this paper proposes a new algorithm that integrates STP (spatio-temporal proximity) and IWC (improved weighted circle), in which the new algorithm proposes STP to dynamically refine candidate matching roads, and IWC to adaptively identify the optimal matching road. Specifically, three spatio-temporal proximity indicators are defined in STP to build a three-dimensional stereoscopic cone, and then the two-dimensional projection of the cone are adopted to dynamically select the candidate matching roads. Further, by adaptively setting the weight, the IWC algorithm is developed to integrate three new parameters to adaptively determine the optimal matching road. The test results show that the matching accuracy of the algorithm is over 95%, much higher than that of the existing algorithm, which demonstrates the feasibility and efficiency of the new algorithm.

Adding CDK4/6 inhibitor dalpiciclib to fulvestrant significantly prolonged progression-free survival in patients with hormone receptor-positive, HER2-negative advanced breast cancer progressing after endocrine therapy. We aimed to assess the efficacy and safety of dalpiciclib plus letrozole or anastrozole in patients with hormone receptor-positive, HER2-negative advanced breast cancer who had no previous systemic therapy in the advanced setting. DAWNA-2 is a randomised, double-blind, placebo-controlled, phase 3 trial done at 42 hospitals in China. Eligible patients were aged 18–75 years, of any menopausal status, had an ECOG performance status of 0–1, and had pathologically confirmed hormone receptor-positive, HER2-negative untreated advanced breast cancer. Patients were randomly assigned (2:1) to receive oral dalpiciclib (150 mg per day for 3 weeks, followed by 1 week off) or matching placebo. Both groups also received endocrine therapy: either 2·5 mg letrozole or 1 mg anastrozole orally once daily continuously. Randomisation was using an interactive web response system (block size of six) and stratified according to visceral metastasis, previous endocrine therapy in the adjuvant or neoadjuvant setting, and endocrine therapy partner. All investigators, patients, and the funders of the study were masked to group allocation. We present the results of the preplanned interim analyses for the primary endpoint of investigator-assessed progression-free survival, which was assessed in all randomly assigned patients who met the eligibility criteria by intention-to treat. Safety was analysed in all randomly assigned patients who received at least one dose of study treatment. The superiority boundary was calculated as a one-sided p value of 0·0076 or less. This trial is registered with ClinicalTrials.gov, NCT03966898, and is ongoing but closed to recruitment. Between July 19, 2019, and Dec 25, 2020, 580 patients were screened and 456 were eligible and randomly assigned to the dalpiciclib group (n=303) or placebo group (n=153). At data cutoff (June 1, 2022), median follow-up was 21·6 months (IQR 18·3–25·9), and 103 (34%) of 303 patients in the dalpiciclib group and 83 (54%) of 153 patients in the placebo group had disease progression or died. Median progression-free survival was significantly longer in the dalpiciclib group than in the placebo group (30·6 months [95% CI 30·6–not reached] vs 18·2 months [16·5–22·5]; stratified hazard ratio 0·51 [95% CI 0·38–0·69]; one-sided log-rank p<0·0001). Adverse events of grade 3 or 4 were reported in 271 (90%) of 302 patients in the dalpiciclib group and 18 (12%) of 153 patients in the placebo group. The most common adverse events of grade 3 or 4 were neutropenia (259 [86%] in the dalpiciclib group vs none in the placebo group) and leukopenia (201 [67%] vs none). Serious adverse events were reported for 36 (12%) patients in the dalpiciclib group and ten (7%) patients in the placebo group. Two treatment-related deaths occurred, both in the dalpiciclib group (deaths from unknown causes). Our findings suggest that dalpiciclib plus letrozole or anastrozole could be a novel standard first-line treatment for patients with hormone receptor-positive, HER2-negative advanced breast cancer, and is an alternative option to the current treatment landscape. Jiangsu Hengrui Pharmaceuticals and Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences. For the Chinese translation of the abstract see Supplementary Materials section.

Addressing the significant pressure for carbon emission reduction in the cement industry, the development of novel cement materials capable of achieving “in situ carbon sequestration” has become an important research focus. This study introduces nesquehonite (MgCO3·3H2O, NQ) as a functional admixture into the Portland cement system, systematically investigating its effects on the cement hydration process, the evolution of hydration products, and its carbon sequestration efficiency. Through designed penetration resistance tests and hydration tests with a high water-to-solid ratio, this research utilized X-ray diffraction analysis to determine the phase composition and content of hydration products at different ages. This was combined with scanning electron microscopy to observe microstructural evolution and Nano Measure software 1.2.5 for ettringite crystal size measurement, analyzing the impact of NQ on the early hydration process of P.I cement. The results indicate that the incorporation of NQ significantly alters the early hydration of P.I cement. The Mg2+ and CO32− ions released upon its dissolution interact with Ca2+ and OH− in the pore solution, effectively promoting the early precipitation of carbon sequestration products such as calcium carbonate and minor magnesium-containing carbonates. The addition of 10% NQ hindered the crystallization of Ca(OH)2 before 6 h but promoted its formation after 24 h. Mechanical property tests revealed that a sample with an optimal 3% NQ dosage not only increased the paste’s penetration resistance but also enhanced the compressive strength of the 1-day hardened sample by 8.37% compared to the plain sample, without a decrease and even a slight increase at 28 days. This enhancement is closely related to the microstructural strengthening effect induced by the carbonation products. This study confirms the feasibility of using NQ to steer the cement hydration pathway towards a low-carbon direction, revealing its dual functionality in regulating hydration and sequestering carbon within cement-based materials. The findings provide a new theoretical basis and technical pathway for developing high-performance, low-carbon cement.

Background Collagens are the most abundant proteins in extra cellular matrix and important components of tumor microenvironment. Recent studies have showed that aberrant expression of collagens can influence tumor cell behaviors. However, their roles in hepatocellular carcinoma (HCC) are poorly understood. Methods In this study, we screened all 44 collagen members in HCC using whole transcriptome sequencing data from the public datasets, and collagen type IV alpha1 chain (COL4A1) was identified as most significantly differential expressed gene. Expression of COL4A1 was detected in HCC samples by quantitative real-time polymerase chain reaction (qRT-PCR), western blot and immunohistochemistry (IHC). Finally, functions and potential mechanisms of COL4A1 were explored in HCC progression. Results COL4A1 is the most significantly overexpressed collagen gene in HCC. Upregulation of COL4A1 facilitates the proliferation, migration and invasion of HCC cells through FAK-Src signaling. Expression of COL4A1 is upregulated by RUNX1 in HCC. HCC cells with high COL4A1 expression are sensitive to the treatment with FAK or Src inhibitor. Conclusion COL4A1 facilitates growth and metastasis in HCC via activation of FAK-Src signaling. High level of COL4A1 may be a potential biomarker for diagnosis and treatment with FAK or Src inhibitor for HCC.

Acetamiprid (ACE) and thiacloprid (THIA) are the dominant cyano-substituted neonicotinoids detected in fruit juices and bottled water, which raises food-safety concerns and regulatory scrutiny. Conventional purification with activated carbon or advanced oxidation shows limited selectivity and has a high energy demand. Covalent organic frameworks (COFs) offer tunable chemistry for targeted adsorption, yet no strategy exists to engineer COF sites that preferentially recognize the cyano group of ACE/THIA. Here, we synthesized a magnetic core-shell adsorbent, Fe3O4@COF(TBTD-BD)-Au, by growing cyano-affinitive Au nanoparticles on a Cl-decorated COF shell surrounding a Fe3O4 core. Under optimized conditions (pH 6.0, 25 °C), the Fe3O4@COF(TBTD-BD)-Au achieved maximum adsorption capacities of 157 mg g−1 (ACE) and 156 mg g−1 (THIA). Uptake followed pseudo-second-order kinetics and the Freundlich isotherm; thermodynamic analysis confirmed an endothermic, spontaneous process. Competitive tests showed >80% removal of ACE and THIA in the presence of four co-occurring neonicotinoids, and the adsorbent retained 91.5% of its initial capacity after six adsorption–desorption cycles. Synergistic Au-cyano coordination, Cl-mediated hydrogen bonding, and π–π stacking confinement confer high selectivity and capacity. This ligand-guided, post-functionalized COF provides promising potential in the field of food sample treatment for contaminant removal.

Electrical tree degradation is one of the main causes of insulation failure in high‐frequency transformers. Electrical tree degradation is studied on pure epoxy resin (EP) and MgO/EP composites at frequencies ranging from 50 Hz to 130 kHz. The results show that the tree initiation voltage of EP decreases, while the growth rate and the expansion coefficient increase with frequency. Moreover, the bubble phenomenon at high frequencies in EP composites is discussed. Combined with trap distribution characteristics within the material, the intrinsic mechanism of epoxy composites to inhibit the growth of the electrical tree at different frequencies is discussed. It can be concluded that more deep traps and blocking effect are introduced by doping nano‐MgO into EP bulks, which can improve the electrical tree resistance performance of EP composites in a wide frequency range.

Intracerebral hemorrhage (ICH) is a severe subtype of stroke lacking effective pharmacological targets. Long noncoding RNA (lncRNA) has been confirmed to participate in the pathophysiological progress of various neurological disorders. However, how lncRNA affects ICH outcomes in the acute phase is not completely clear. In this study, we aimed to reveal the relationship of lncRNA-miRNA-mRNA following ICH. We conducted the autologous blood injection ICH model and extracted total RNAs on day 7. Microarray scanning was used to obtain mRNA and lncRNA profiles, which were validated by RT-qPCR. GO/KEGG analysis of differentially expressed mRNAs was performed using the Metascape platform. We calculated the Pearson correlation coefficients (PCCs) of lncRNA-mRNA for co-expression network construction. A competitive endogenous (Ce-RNA) network was established based on DIANALncBase and miRDB database. Finally, the Ce-RNA network was visualized and analyzed by Cytoscape. In total, 570 differentially expressed mRNAs and 313 differentially expressed lncRNAs were identified (FC ≥ 2 and value of <0.05). The function of differentially expressed mRNAs was mainly enriched in immune response, inflammation, apoptosis, ferroptosis, and other typical pathways. The lncRNA-mRNA co-expression network contained 57 nodes (21 lncRNAs and 36 mRNAs) and 38 lncRNA-mRNA pairs. The ce-RNA network was generated with 303 nodes (29 lncRNAs, 163 mRNAs, and 111 miRNAs) and 906 edges. Three hub clusters were selected to indicate the most significant lncRNA-miRNA-mRNA interactions. Our study suggests that the top differentially expressed RNA molecules may be the biomarker of acute ICH. Furthermore, the hub lncRNA-mRNA pairs and lncRNA-miRNA-mRNA correlations may provide new clues for ICH treatment.