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For the large number of news reports generated every day, in order to obtain effective information from these unstructured news text data more efficiently. In this paper, we study the real-time crawling of news data from news websites through crawling techniques and propose a BERT model-based approach to extract events from news long text. In this study, NetEase news website is selected as an example for real-time extraction to crawl the news data of this website. BERT model as a pre-trained model based on two-way encoded representation of transformer performs well on natural language understanding and natural language generation tasks. In this study, we will fine-tune the training based on BERT model on news corpus related dataset and perform sequence annotation through CRF layer to finally complete the event extraction task. In this paper, the DUEE dataset is chosen to train the model, and the experiments show that the overall performance of the BERT model is better than other network models. Finally, the model of this paper is further optimised, using the ALBERT and RoBERTa models improved on the basis of the BERT model, experiments were conducted, the results show that both models are improved compared to the BERT model, the ALBERT model algorithm performs the best, the model algorithm's F1 value is 1% higher than that of BERT. The results show that the performance is optimised.

The effect of adverse pressure gradient (APG) on near-wall turbulence is studied, with a particular attention to the turbulence production mechanism. A plane turbulent Couette flow is considered for several values of constant APG in the lower wall region. A direct numerical simulation (DNS) in a large computational domain shows that turbulence near the lower wall continues to exist even at sufficiently large APGs. On increasing the APG, the cross-streamwise turbulence intensities increase, and the near-wall streaks gradually disappear. A linear analysis using the optimal transient growth indicates that the APG inhibits the generation of near-wall streaks due to the significant reduction of the mean shear in the region near the lower wall. The turbulent fluctuation dynamics beyond the linear regime is studied with a DNS in a minimal flow unit. The near-wall self-sustaining process involving streaks is significantly weakened or destroyed as APG increases, while the turbulent fluctuations become more isotropic and localised. Using a conditional averaging analysis, a new mechanism of near-wall turbulence production under strong APG is uncovered. This mechanism is initiated by the wall-normal nonlinear transport of an outer wall-normal velocity fluctuation to the near-wall region. The transported wall-normal velocity fluctuation is subsequently amplified via the Orr mechanism, resulting in the non-zero turbulence production involving spatially localised vortical structures. This mechanism is also confirmed by DNS of the flow in a large computational domain, where strong correlation between the wall-normal nonlinear transport and turbulence production is observed.

Piezoelectric polymer nanofibers are promising for wearable electronics due to their mechanical compliance and electromechanical responsiveness. Poly(vinylidene fluoride)‐trifluoroethylene (PVDF‐TrFE) is widely used for its ferroelectric β ‐phase and favorable piezoelectric properties, yet its limited elasticity hinders applications in soft bioelectronics. Electrospun PVDF‐TrFE mats can stretch through fiber rearrangement but lack true elastic recovery unless molecular interactions and junctions are modified. Achieving nanofiber networks that are both stretchable and piezoelectrically stable under cyclic strain remains a challenge. Here, we report a strategy combining PVDF‐TrFE with a small fraction of poly(ethylene glycol) bis(amine) (PEG‐diamine) and thermal annealing to form fused nanofibrous mats with enhanced elasticity and stable piezoelectric output. The blended mats doubled the strain‐to‐failure (~30%) compared to pure PVDF‐TrFE (~14%) and showed Mullins‐like elastic recovery up to approximately 9% with reduced hysteresis. Piezoelectric response improved by approximately 25% in peak voltage (~150 mV), with greater signal stability. Structural analyses (Fourier‐transform infrared [FTIR], differential scanning calorimetry [DSC], and X‐ray diffraction [XRD]) confirmed increased β ‐phase content and selective cross‐linking in amorphous domains without compromising ferroelectric order. This work demonstrates a scalable material‐based approach to improve elasticity and durability in electrospun piezoelectric fibers, enabling stretchable and skin‐conformable sensors for smart fabrics, wearable health monitors, and energy harvesting.

Activating cGAS‐STING pathway has great potential to achieve effective antitumor immunotherapy. However, mutant p53 (mutp53), a commonly observed genetic alteration in over 50% of human cancer, will impede the therapeutic performance of the cGAS‐STING pathway. Herein, multifunctional ZIF‐8@MnO2 nanoparticles are constructed to degrade mutp53 and facilitate the cGAS‐STING pathway. The synthesized ZIF‐8@MnO2 can release Zn2+ and Mn2+ in cancer cells to induce oxidative stress and cytoplasmic leakage of fragmented mitochondrial double‐stranded DNAs (dsDNAs). Importantly, the released Zn2+ induces variable degradation of multifarious p53 mutants through proteasome ubiquitination, which can alleviate the inhibitory effects of mutp53 on the cGAS‐STING pathway. In addition, the released Mn2+ further increases the sensitivity of cGAS to dsDNAs as immunostimulatory signals. Both in vitro and in vivo results demonstrate that ZIF‐8@MnO2 effectively promotes the cGAS‐STING pathway and synergizes with PD‐L1 checkpoint blockades, leading to remarkable regression of local tumors as well as distant metastases of breast cancer. This study proposes an inorganic metal ion‐based nanoplatform to enhance the cGAS‐STING‐mediated antitumor immunotherapy, especially to those tumors with mutp53 expression. A nanotechnology‐based Mn–Zn dual‐ion delivery platform is constructed. It can enhance the cGAS‐STING‐mediated anti‐tumor immunotherapy via. multiple aspects, including GSH responsive, cGAS enzymatic activity‐modulated, and mutp53‐targeted manifold pathways. This study lays a foundation for designing therapeutic strategies targeting the cGAS‐STING pathway and offers new immunotherapeutic options for patients with overexpressed mutant p53.

Biochar has been paid great attentions during the last two decades, because of its resources potentials and environmental benefits. A bibliometric analysis was applied to assess the publications regarding the keyword biochar from the Web of Science database during the period of 1999 to 2018. A total of 8629 publications were obtained with a rapid increase of annual citations and number of papers. The research topics were diversified, which were mainly divided into “Environmental Sciences and Ecology,” “Agriculture,” and “Engineering.” Bioresource Technology was the journal which published most of the relevant papers. China ranked first in the number of published papers, followed by the USA, Australia, UK, and Germany. Especially, China established close collaboration with the USA in joint publication. Analysis of the keywords indicated that biochar production, comparative sorption, soil-applied black carbon, and soil management were the main research hotspots of biochar. The burst detection reflected that the innovation of biochar production and the new application field of biochar was the future research trends. These results can provide insight into the research progress regarding biochar.

This paper explores the influence of micro textures on cutting performance of polycrystalline cubic boron nitride (PCBN) tools from two aspects, that is, tool wear and machined surface roughness. By designing micro-hole textures with different forms and scales on the rake face of tools when PCBN tools turn hardened steel GCr15, and combining finite element analysis (FEA) technology and cutting experiments, the cutting performance of micro-textured tools is simulated and analyzed. This paper analyses the influence of micro textures on tool wear and machined surface roughness by analyzing cutting force, Mises stress and maximum shear stress of tool surface. Results of finite element analysis (FEA) and cutting experiments show that the reasonable micro-hole textures can significantly alleviate tool wear and improve machined surface quality when compared with the non-textured tools. Besides, the size of micro-hole textures on the rake face play an important role in reducing the cutting force and tool wear. This is mainly because micro-hole textures can reduce cutting force and improve tool surface stress. Finally, by designing reasonable micro-hole textures on the rake face, the problems of bad roughness of machined workpiece and severe tool wear of PCBN tools in cutting GCr15 material are solved. Consequently, the paper shows that micro-hole textures have a positive effect on improving the cutting performance of tool.

Continuous glucose monitoring (CGM) is rapidly becoming a vital tool in the management of type 1 diabetes. Its use has been shown to improve glycaemic management and reduce the risk of hypoglycaemic events. The cost of CGM remains a barrier to its widespread application. We aimed to identify and synthesize evidence about the cost‐effectiveness of utilizing CGM in patients with type 1 diabetes. Studies were identified from MEDLINE, Embase and Cochrane Library from January 2010 to February 2022. Those that assessed the cost‐effectiveness of CGM compared to self‐monitored blood glucose (SMBG) in patients with type 1 diabetes and reported lifetime incremental cost‐effectiveness ratio (ICER) were included. Studies on critically ill or pregnant patients were excluded. Nineteen studies were identified. Most studies compared continuous subcutaneous insulin infusion and SMBG to a sensor‐augmented pump (SAP). The estimated ICER range was [ $18,734–$ 99,941] and the quality‐adjusted life year (QALY) gain range was [0.76–2.99]. Use in patients with suboptimal management or greater hypoglycaemic risk revealed more homogenous results and lower ICERs. Limited studies assessed CGM in the context of multiple daily injections (MDI) (n = 4), MDI and SMBG versus SAP (n = 2) and three studies included hybrid closed‐loop systems. Most studies (n = 17) concluded that CGM is a cost‐effective tool. This systematic review suggests that CGM appears to be a cost‐effective tool for individuals with type 1 diabetes. Cost‐effectiveness is driven by reducing short‐ and long‐term complications. Use in patients with suboptimal management or at risk of severe hypoglycaemia is most cost‐effective. Continuous glucose monitoring has advanced significantly in the last few years. Multiple studies and meta‐analysis have reported the benefit of continuous glucose monitoring in improving diabetes management and hypoglycemic risk. Cost has however remained a barrier to its widespread use. This review summarises available studies assessing the cost‐effectiveness of CGM.

Task allocation is a critical issue of spatial crowdsourcing. Although the batching strategy performs better than the real-time matching mode, it still has the following two drawbacks: (1) Because the granularity of the batch size set obtained by batching is too coarse, it will result in poor matching accuracy. However, roughly designing the batch size for all possible delays will result in a large computational overhead. (2) Ignoring non-stationary factors will lead to a change in optimal batch size that cannot be found as soon as possible. Therefore, this paper proposes a fine-grained, batching-based task allocation algorithm (FGBTA), considering non-stationary setting. In the batch method, the algorithm first uses variable step size to allow for fine-grained exploration within the predicted value given by the multi-armed bandit (MAB) algorithm and uses the results of pseudo-matching to calculate the batch utility. Then, the batch size with higher utility is selected, and the exact maximum weight matching algorithm is used to obtain the allocation result within the batch. In order to cope with the non-stationary changes, we use the sliding window (SW) method to retain the latest batch utility and discard the historical information that is too far away, so as to finally achieve refined batching and adapt to temporal changes. In addition, we also take into account the benefits of requesters, workers, and the platform. Experiments on real data and synthetic data show that this method can accomplish the task assignment of spatial crowdsourcing effectively and can adapt to the non-stationary setting as soon as possible. This paper mainly focuses on the spatial crowdsourcing task of ride-hailing.

This study aimed to examine the association between different obesity-related metabolic phenotypes, transitions in metabolic status over time, and cognitive function improvement among middle-aged and older adults in China. Data were derived from the China Health and Retirement Longitudinal Study, a nationally representative longitudinal cohort involving urban and rural residents aged 45 years and older. Baseline data were collected in 2011, with follow-up assessments extending to 2020. Participants were classified into four body mass index (BMI)-metabolic phenotypes: Metabolically Healthy Normal Weight (MHNW), Metabolically Unhealthy Normal Weight (MUNW), Metabolically Healthy Overweight/Obesity (MHOO), and Metabolically Unhealthy Overweight/Obesity (MUOO). Cognitive function was evaluated through assessments of episodic memory, mental status, and overall cognitive performance. Statistical analyses were performed using R Studio 4.3.1. Cox regression analysis models were employed to estimate associations between metabolic phenotypes, their longitudinal transitions, and changes in cognitive function. In both the 2011 and 2015 surveys, MHOO demonstrated significantly higher scores in episodic memory, mental status, and overall cognitive function compared to other groups, while MUNW demonstrated significantly lower scores across all domains. In addition, cognitive outcomes varied by BMI-metabolic phenotypes: MHOO was positively associated with cognitive improvement, MUNW was usually associated with poorer cognitive outcomes, and MUOO had no significant association with cognitive changes. Moreover, individuals with stable MUNW status exhibited a lower likelihood of cognitive improvement relative to those with stable MHNW status. In contrast, individuals with stable MHOO status demonstrated a significantly greater likelihood of cognitive improvement. Furthermore, transitioning from MHNW to MUNW was associated with decreased likelihood of favorable cognitive outcomes. Regardless of weight classification, metabolic health was associated with superior baseline cognitive function and a slower rate of cognitive decline. These findings underscore the significance of metabolic health in predicting cognitive aging trajectories among middle-aged and older individuals.

This paper applies micro textures to the rake face of PCBN (Polycrystalline Cubic Boron Nitride) tools, including three types of micro textures that are microgroove textures vertical to the cutting edge, microgroove textures parallel to the cutting edge, and microhole textures. In this paper, the effects of different cutting speeds on the surface quality of hardened bearing steel GCr15 by dry turning with non-texture PCBN tools and micro-texture PCBN tools are studied, and the surface roughness values obtained by different micro textures were compared and analyzed. The results showed that, compared to that of non-texture tools, the influence degree of the micro-texture tools on the machined surface roughness was different. The microhole texture and vertical microgroove texture were able to effectively reduce the surface roughness of the workpiece, and microhole texture had the best effective influence on surface roughness, but the parallel microgroove texture increased surface roughness. The influence of cutting speeds on surface roughness was different due to different types of micro textures. The influence of micro textures on surface roughness has huge potential for tool applications.