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The accumulation of high amounts of plastic waste in the environment has raised ecological and health concerns, particularly in croplands, and biological degradation presents a promising approach for the sustainable treatment of this issue. In this study, a polyvinyl chloride (PVC)-degrading bacterium was isolated from farmland soil samples attached to waste plastic, utilizing PVC as the sole carbon source. The circular chromosome of the strain Cbmb3, with a length of 5,768,926 bp, was subsequently sequenced. The average GC content was determined to be 35.45%, and a total of 5835 open reading frames were identified. The strain Cbmb3 was designated as Bacillus toyonensis based on phylogenomic analyses and genomic characteristics. The bioinformatic analysis of the Cbmb3 genome revealed putative genes encoding essential enzymes involved in PVC degradation. Additionally, the potential genomic characteristics associated with phytoprobiotic effects, such as the synthesis of indole acetic acid and secondary metabolite synthesis, were also revealed. Overall, the present study provides the first complete genome of Bacillus toyonensis with PVC-degrading properties, suggesting that Cbmb3 is a potential strain for PVC bioremediation and application.

Abstract The evaluation of Physical Education Teaching Methods in Colleges and Universities faces two main challenges: an excess of evaluating elements and a lack of assessment framework. Hence, the research proposes the multi-feature fuzzy evaluation model based on artificial intelligence to streamline the evaluation process and provide an efficient framework for accessing teaching methods. The framework integrates natural/human language using fuzzy instructions considering three evaluation perspectives, including the management stage, instructors, and students and employs the enhanced cuckoo search optimization algorithm. After the teaching expert has determined each parameter's ratings, they are fed into the improved cuckoo search algorithm and solved using an unbiased function to assess the assessment's final result. It incorporates the students' mobility mechanism and movement vector deconstruction designed based on functional criteria. A system for evaluating the quality of instruction has been developed utilizing the proposed model with enhanced cuckoo search optimization. The results indicate that the proposed algorithm has achieved the highest scores across multiple assessment categories, average skill performances of 97.01%, learning progress of 87.36%, physical fitness of 93.49%, participation rate of 95.04%, student satisfaction of 95.49%, and physical education of 96.8% teaching efficiency. The usefulness of the proposed framework in enhancing physical education teaching methods has been demonstrated by comparing the results with traditional methods. It contributes to advancing pedagogical practices in the field.

Abstract Glaucoma is a prevalent cause of blindness globally, characterized by the progressive degeneration of retinal ganglion cells (RGCs). Among various factors, glutamate excitotoxicity stands out as a significant contributor of RGCs loss in glaucoma. Our study focused on Ripa-56 and its protective effect against NMDA-induced retinal damage in mice, aiming to delve into the potential underlying mechanism. The R28 cells were categorized into four groups: glutamate (Glu), Glu + Ripa-56, Ripa-56 and Control group. After 24 h of treatment, cell death was assessed by PI / Hoechst staining. Mitochondrial membrane potential changes, apoptosis and reactive oxygen species (ROS) production were analyzed using flow cytometry. The alterations in the expression of RIP-1, p-MLKL, Bcl-2, BAX, Caspase-3, Gpx4 and SLC7A11 were examined using western blot analysis. C57BL/6j mice were randomly divided into NMDA, NMDA + Ripa-56, Ripa-56 and control groups. Histological changes in the retina were evaluated using hematoxylin and eosin (H&E) staining. RGCs survival and the protein expression changes of RIP-1, Caspase-3, Bcl-2, Gpx4 and SLC7A11 were observed using immunofluorescence. Ripa-56 exhibited a significant reduction in the levels of RIP-1, p-MLKL, Caspase-3, and BAX induced by glutamate, while promoting the expression of Bcl-2, Gpx-4, and SLC7A1 in the Ripa-56-treated group. In our study, using an NMDA-induced normal tension glaucoma mice model, we employed immunofluorescence and H&E staining to observe that Ripa-56 treatment effectively ameliorated retinal ganglion cell loss, mitigating the decrease in retinal ganglion cell layer and bipolar cell layer thickness caused by NMDA. In this study, we have observed that Ripa-56 possesses remarkable anti- necroptotic, anti-apoptotic and anti-ferroptosis properties. It demonstrates the ability to combat not only glutamate-induced excitotoxicity in R28 cells, but also NMDA-induced retinal excitotoxicity in mice. Therefore, Ripa-56 could be used as a potential retinal protective agent.

Abstract Background Obesity is the most important driver of non-alcoholic fatty liver disease (NAFLD); nevertheless, the relationship of weight-adjusted waist index (WWI), a new obesity index, with NAFLD is unclear. Methods This retrospective study used data from the NAGALA project from 1994 to 2016. WWI values were calculated using waist circumference (WC) and weight measurements of the participants. Three stepwise adjusted logistic regression models were developed to assess the relationship of WWI with NAFLD in the whole population and in both sexes. Additionally, we also conducted a series of exploratory analysis to test the potential impact of body mass index (BMI), age, smoking status and exercise habits on the association of WWI with NAFLD. Receiver operating characteristic (ROC) curves were used to estimate cut-off points for identifying NAFLD in the entire population and in both sexes. Results The current study included a population of 11,805 individuals who participated in health screenings, including 6,451 men and 5,354 women. After adjusting for all non-collinear variables in the multivariable logistic regression model, we found a significant positive correlation of WWI with NAFLD. For each unit increase in WWI, the risk of NAFLD increased by 72% in the entire population, by 84% in men, and by 63% in women. Furthermore, subgroup analyses revealed no significant discrepancies in the correlation of WWI with NAFLD across individuals with varying ages, exercise habits, and smoking status (all P-interaction > 0.05), except for different BMI groups (P-interaction

Abstract Efficient oxygen evolution reaction electrocatalysts are essential for sustainable clean energy conversion. However, catalytic materials followed the conventional adsorbate evolution mechanism (AEM) with the inherent scaling relationship between key oxygen intermediates *OOH and *OH, or the lattice-oxygen-mediated mechanism (LOM) with the possible lattice oxygen migration and structural reconstruction, which are not favorable to the balance between high activity and stability. Herein, we propose an unconventional Co-Fe dual-site segmentally synergistic mechanism (DSSM) for single-domain ferromagnetic catalyst CoFeS x nanoclusters on carbon nanotubes (CNT) (CFS-ACs/CNT), which can effectively break the scaling relationship without sacrificing stability. Co3+ (L.S, t 2g 6 e g 0) supplies the strongest OH* adsorption energy, while Fe3+ (M.S, t 2g 4 e g 1) exposes strong O* adsorption. These dual-sites synergistically produce of Co-O-O-Fe intermediates, thereby accelerating the release of triplet-state oxygen ( ↑ O = O ↑ ). As predicted, the prepared CFS-ACs/CNT catalyst exhibits less overpotential than that of commercial IrO2, as well as approximately 633 h of stability without significant potential loss.

Highlights Digital holography can realize the in situ observation of electrode/electrolyte interface and provide dynamic evolution information of the liquid phase of electrode, which is both efficient and effective in investing the interficial electrochemical mechanism and screening electrolyte additives. Thioacetamide electrolyte additive effectively enhances the electrochemical performance of Zn anode by regulating the interficial ion flux to induce dendrite-free Zn deposition and constructing adsorption molecule layers to inhibit side reactions.

Abstract Objective Metagenomic next-generation sequencing (mNGS), as an emerging technique for pathogen detection, has been widely used in clinic. However, reports on the application of mNGS in cancer patients with severe pneumonia remain limited. This study aims to evaluate the diagnostic performance of bronchoalveolar lavage fluid (BALF) mNGS in cancer patients complicated with severe pneumonia. Methods A total of 62 cancer patients with severe pneumonia simultaneously received culture and mNGS of BALF were enrolled in this study. We systematically analyzed the diagnostic significance of BALF mNGS. Subsequently, optimization of anti-infective therapy based on the distribution of pathogens obtained from BALF mNGS was also assessed. Results For bacteria and fungi, the positive detection rate of mNGS was significantly higher than culture method (91.94% versus 51.61%, P

Abstract Ovarian cancer (OV) is the most lethal gynecological malignancy worldwide, with high recurrence rates. Anoikis, a newly-acknowledged form of programmed cell death, plays an essential role in cancer progression, though studies focused on prognostic patterns of anoikis in OV are still lacking. We filtered 32 potential anoikis-related genes (ARGs) among the 6406 differentially expressed genes (DEGs) between the 180 normal controls and 376 TCGA-OV samples. Through the LASSO-Cox analysis, a 2-gene prognostic signature, namely AKT2, and DAPK1, was finally distinguished. We then demonstrated the promising prognostic value of the signature through the K-M survival analysis and time-dependent ROC curves (p-value

Image segmentation plays a crucial role in the roadwork operations of autonomous line-painting machines. However, the limited resources of mobile platforms in intelligent line-painting applications pose a dual challenge of ensuring both accuracy and real-time performance in road segmentation. To address this issue, this study introduces a lightweight yet efficient image segmentation model, termed the SLTM Network. Central to this network is the lightweight SLTM module, which significantly reduces the model’s parameter count and lowers the computational overhead of the decoder. To enhance the interplay of information at different spatial resolutions, the network incorporates an SE attention-enhanced upsampling module (SAUM) and employs a Spatial Attention Sequence (SAS) unit to improve global environment perception at a low computational cost. Comprehensive experimental evaluations on the Cityscapes dataset demonstrate that the SLTM Network excels in balancing speed and accuracy, achieving an mIoU of 70.5% with only 4.07M parameters and an impressive inference speed of 267.1 FPS. On the embedded device Jetson Xavier NX, it achieves an inference speed of 34.2 FPS. Compared to existing lightweight image segmentation models, the SLTM Network exhibits significant advantages in both processing speed and accuracy, making it particularly suitable for real-time autonomous line-painting machine applications.

Multi-agent deep reinforcement learning inherits one of the shortcomings of reinforcement learning, which is that a very large number of experimental episodes need to be performed to train an agent model to learn the optimal policy. Transfer learning is a typical method to accelerate the training process in machine learning field. In cooperative multi-agent deep reinforcement learning, we can reasonably design transfer learning methods to accelerate the learning of homogeneous agents. Transfer learning in the field of multi-agent systems is different from that in single agent environment, as in the systems there are multiple agents learning at the same time, online policy transfer methods can be used among these agents. In this paper, we propose an online policy transfer algorithm based on attention mechanism and time abstraction for multi-agent deep reinforcement learning (ATA-MAOPT). The algorithm employs the option-critic framework, which is a typical temporal abstraction mechanism and utilizes the option mechanism to select the source policy for policy transfer, and at the same time, the algorithm introduces the attention mechanism into the algorithm to make these options focus more on important features in observation spaces, making the source policy more accurate and improving the efficiency of policy transfer. The experimental results demonstrate that the algorithm can effectively speed up the learning process of the agents and reduce the computational costs.

Though improving the efficiency of urban land use, high-rise buildings greatly increase the difficulty in search and rescue during fires. Therefore, effective search and rescue in high-rise building fires has always been a hot and difficult issue in emergency management. Starting from the characteristics of high-rise building fires and the difficulties in addressing them, this paper introduced unmanned aerial vehicle (UAV) technology into search and rescue operations in fires. Based on the influences of dynamic factors on wireless signal (WS) states in a static environment, it investigated the techniques for extracting and sensing wireless channel state features when indoor personnel waves for help and proposed a method for indoor personnel detection based on channel state information (CSI) sensing. In the article, a single source wireless device (common Wi-Fi router) is used as the detection terminal to collect the wireless channel state, and the signal sampling, support vector machine (SVM), and other technologies are combined to realize the wireless channel state sensing and classification. The outcomes of the experiment revealed that the suggested approach can effectively succeed in through-wall detection and sensing for indoor personnel calling for help in the event of a fire, with an accuracy of 94.6%. Incorporating the non-invasive, robust, universal, and low-cost characteristics, the method promises broad application values in improving the search and rescue efficiency of firefighters.

The delay jitter in the visible light communication (VLC) network is analyzed in this work. First, the delay jitter under single-user and multi-user scenarios is investigated and a closed-form expression is obtained, whose accuracy is verified by simulation. Second, through analyzing the delay jitter under two typical indoor light emitting diode (LED) layouts, we find that the mean user delay jitter under cellular layout is a little lower than that of square layout. Then, we study the delay jitter for mobile users, and the relationship among user movement speed, arrival rate and delay jitter in different scenarios. The delay jitter performance is evaluated assuming perfect coordinated multiple points (CoMP) transmission strategy in VLC network. Simulation results show that in the context of VLC, static users can experience an average delay jitter of up to $10^{-6}$ s, while mobile users can experience an average delay jitter of up to $10^{-5}$ s. Therefore, VLC network can provide users with good delay jitter performance and customized services to meet the higher service quality requirements of future users.

Abstract Sensitive and stable perovskite X-ray detectors are attractive in low-dosage medical examinations. The high sensitivity, tunable chemical compositions, electronic dimensions, and low-cost raw materials make perovskites promising next-generation semiconductors. However, their ionic nature brings serious concerns about their chemical and water stability, limiting their applications in well-established technologies like crystal polishing, micro-processing, photolithography, etc. Herein we report a one-dimensional tryptamine lead iodide perovskite, which is stable in water for several months as the strong cation-π interactions between organic cations. The one-dimensional and two-dimensional tryptamine lead iodide perovskite tablets are switchable through thermal-annealing or water-soaking treatments to relax microstrains. The water-stable and microstrain-free one-dimensional perovskite tablets yield a large sensitivity of 2.5 × 106 μC Gyair −1 cm−2 with the lowest detectable dose rate of 5 nGyair s−1. Microelectrode arrays are realized by surface photolithography to construct high-performance X-ray flat mini-panels with good X-ray imaging capability, and a record spatial resolution of 17.2 lp mm−1 is demonstrated.

Abstract Time-resolved X-ray photoelectron spectroscopy (TXPS) is a well-established technique to probe coherent nuclear wavepacket dynamics using both table-top and free-electron-based ultrafast X-ray lasers. Energy resolution, however, becomes compromised for a very short pulse duration in the sub-femtosecond range. By resonantly tuning the X-ray pulse to core-excited states undergoing Auger decay, this drawback of TXPS can be mitigated. While resonant Auger-electron spectroscopy (RAS) can recover the vibrational structures not hidden by broadband excitation, the full reconstruction of the wavepacket is a standing challenge. Here, we theoretically demonstrate how the complete information of a nuclear wavepacket, i.e., the populations and relative phases of the vibrational states constituting the wavepacket, can be retrieved from time-resolved RAS (TRAS) measurements. Thus, TRAS offers key insights into coupled nuclear and electronic dynamics in complex systems on ultrashort timescales, providing an alternative to leverage femtosecond and attosecond X-ray probe pulses.

Abstract Background Pre-injury frailty is associated with adverse in-hospital outcomes in older trauma patients, but the association with longer term survival and recovery is unclear. We aimed to investigate post discharge survival and health-related quality of life (HRQoL) in older frail patients at six months after Major Trauma Centre (MTC) admission. Methods This was a multi-centre study of patients aged ≥ 65 years admitted to five MTCs. Data were collected via questionnaire at hospital discharge and six months later. The primary outcome was patient-reported HRQoL at follow up using Euroqol EQ5D-5 L visual analogue scale (VAS). Secondary outcomes included health status according to EQ5D dimensions and care requirements at follow up. Multivariable linear regression analysis was conducted to evaluate the association between predictor variables and EQ-5D-5 L VAS at follow up. Results Fifty-four patients died in the follow up period, of which two-third (64%) had been categorised as frail pre-injury, compared to 21 (16%) of the 133 survivors. There was no difference in self-reported HRQoL between frail and not-frail patients at discharge (Mean EQ-VAS: Frail 55.8 vs. Not-frail 64.1, p = 0.137) however at follow-up HRQoL had improved for the not-frail group but deteriorated for frail patients (Mean EQ-VAS: Frail: 50.0 vs. Not-frail: 65.8, p = 0.009). There was a two-fold increase in poor quality of life at six months (VAS ≤ 50) for frail patients (Frail: 65% vs. Not-frail: 30% p < 0.009). Frailty (β-13.741 [95% CI -25.377, 2.105], p = 0.02), increased age (β -1.064 [95% CI [-1.705, -0.423] p = 0.00) and non-home discharge (β -12.017 [95% CI [118.403, 207.203], p = 0.04) were associated with worse HRQoL at follow up. Requirements for professional carers increased five-fold in frail patients at follow-up (Frail: 25% vs. Not-frail: 4%, p = 0.01). Conclusions Frailty is associated with increased mortality post trauma discharge and frail older trauma survivors had worse HRQoL and increased care needs at six months post-discharge. Pre-injury frailty is a predictor of poor longer-term HRQoL after trauma and recognition should enable early specialist pathways and discharge planning.

The identification of optimal landing sites is a critical first step for successful missions to the Moon and other extraterrestrial bodies, necessitating the integration of various environmental factors over large spatial scales. At the lunar south pole, site selection must balance engineering safety with areas of high scientific interest, requiring extensive analysis of potential locations. Although intelligent algorithms have been increasingly investigated for this purpose, the application of deep learning techniques in landing site selection remains unexplored. In this study, we employ one-dimensional convolutional neural networks (1D-CNNs) to quantitatively assess potential landing sites for exploration and lunar base construction, considering both scientific and engineering criteria. We also evaluate the influence of various factors on site selection using Shapley additive explanations (SHAP) values. The 1D-CNN model demonstrates robust performance across training, validation, and testing phases. Potential landing sites identified comprise less than 1% of the total study area, with factors such as visibility, volatile distribution, topography, and geological characteristics playing crucial roles. By applying operational constraints, we delineate sites suitable for direct landings and further refine this subset for base construction based on stringent requirements for resource utilization and energy sustainability. The combined use of CNN and SHAP enables more effective potential site screening and a deeper understanding of the factors influencing selection. Our findings offer a valuable framework for future lunar south pole expeditions, potentially minimizing manual survey efforts and enhancing the precision of landing site selection.

In this study, the extraction of sea ice drift from imagery captured by the 1-meter C-SAR 01 satellite (C-SAR/01) was facilitated utilizing the oriented fast and rotated brief algorithm within the feature tracking procedure, thus addressing the previously unexplored area of sea ice drift extraction using C-SAR/01 imagery. The retained keypoints and nearest neighbor distance ratio test for sea ice drift extracted from C-SAR/01 imagery were compared, indicating high reliability with 300 000 and 0.75, respectively. In addition, the local outlier factor algorithm is proposed in this article, which can effectively remove erroneous sea ice drift vectors. The sea ice drift extracted from C-SAR/01 was validated against manually extracted sea ice drift, revealing an uncertainty of 0.271 cm/s in speed and 8.331° in direction. Furthermore, the sea ice drift obtained from the algorithm in this study, when compared with sea ice drift from IABP buoys, exhibits high accuracy, reflecting the robustness of the algorithm.

This paper considers an agent identity privacy problem in Markov decision process. There are two types of agents with different instantaneous control reward functions, e.g., two types of energy consumption activities in smart grid. An eavesdropper is assumed to intercept the observations of agent and make a statistic inference on the agent identity, which is privacy-sensitive and can be utilized by the eavesdropper to further make corresponding malicious attacks. With regard to the agent identity privacy problem, a privacy-preserving Markov decision process is formulated and a novel adversarial reinforcement learning algorithm is further proposed by exploiting the ideas of deep reinforcement learning and variational method to design the agent policies with the aim to optimally tradeoff improving cumulative control reward and preventing agent identity privacy leakage. Experiments in a modified OpenAI Gym environment show different training process patterns and justify the effectiveness of the proposed algorithm.

In this paper, we present a novel reliability analysis of massive Internet of Things (IoT) connectivity in cellular networks. In massive IoT networks, IoT devices sporadically and unpredictably send short data packets to nearby base stations (BSs), potentially interfering with other IoT devices with whom they share the uplink channel. Assuming slotted ALOHA random access policy, we investigate the probability that an IoT device transmitting a short data packet is not decoded at the nearest BS under Nakagami fading. We derive error probability expressions combining the tools of finite block-length (FBL) information theory and stochastic geometry. Derived FBL-based results are confirmed by Monte Carlo simulations and further compared with the asymptotic expressions available in the previous studies that are obtained under assumption that a device transmits asymptotically long data packets. Numerical results confirm the accuracy of the obtained expressions and their applicability to the massive IoT system design and performance evaluation under a wide range of system parameters. For example, the matching between the values obtained by numerical integration and approximation results of the FBL error probability is in the range between 97.6-99.4 % for different choices of the parameters.

Glutamate excitotoxicity has been shown to play an important role in glaucoma, and glutamate can induce ferroptosis. The p38 mitogen-activated protein kinase (MAPK) pathway inhibitor SB202190 has a potential ability to suppress ferroptosis, and its downstream targets, such as p53, have been shown to be associated with ferroptosis. However, whether ferroptosis also occurs in retinal ganglion cells in response to glutamate excitotoxicity and whether inhibition of ferroptosis reduces the loss of retinal ganglion cells induced by glutamate excitotoxicity remain unclear. This study investigated ferroptosis in a glutamate-induced glaucoma rat model and explored the effects and molecular mechanisms of SB202190 on retinal ganglion cells. A glutamate-induced excitotoxicity model in R28 cells and an N-methyl-D-aspartate-induced glaucoma model in rats were used. In vitro experiments showed that glutamate induced the accumulation of iron and lipid peroxide and morphological changes of mitochondria in R28 cells, and SB202190 inhibited these changes. Glutamate induced the levels of p-p38 MAPK/p38 MAPK and SAT1 and decreased the expression levels of ferritin light chain, SLC7A11, and GPX4. SB202190 inhibited the expression of iron death-related proteins induced by glutamate. In vivo experiments showed that SB202190 attenuated N-methyl-D-aspartate-induced damage to rat retinal ganglion cells and improved visual function. These results suggest that SB202190 can inhibit ferroptosis and protect retinal ganglion cells by regulating ferritin light chain, SAT1, and SLC7A11/Gpx4 pathways and may represent a potential retina protectant.

Abstract Background Clinical trials have demonstrated the efficacy of edaravone dexborneol in the treatment of acute ischemic stroke. This study aims to determine the cost-effectiveness of edaravone dexborneol compared with human urinary kallidinogenase from China’s healthcare system perspective. Methods A combination of the decision tree and Markov model was constructed to evaluate the cost-effectiveness of edaravone dexborneol versus human urinary kallidinogenase in the treatment of acute ischemic stroke over a lifetime horizon. Efficacy data were derived from pivotal clinical trials of edaravone dexborneol and human urinary kallidinogenase (TASTE trial and RESK trial, respectively) and adjusted using matching-adjusted indirect comparison. Cost and health utility inputs were extracted from published literature and open databases. One-way deterministic sensitivity and probabilistic sensitivity analyses were performed to examine the robustness of the results. Results Compared with human urinary kallidinogenase, edaravone dexborneol generated 0.153 incremental quality-adjusted life years (QALYs) with an incremental cost of ¥856, yielding an incremental cost-effectiveness ratio of ¥5,608 per QALY gained under the willingness-to-pay threshold (one-time gross domestic product per capita). Both one-way deterministic sensitivity analysis and probabilistic sensitivity analysis demonstrated the robustness of the base case results. Conclusions Edaravone dexborneol is a cost-effective treatment choice for acute ischemic stroke patients compared with human urinary kallidinogenase in China.

Perception plays a vital role in autonomous driving as it serves as a prerequisite for downstream planning and decision tasks. Existing research has mainly focused on developing vehicle-side perception models using a single type of sensors. However, relying solely on one type of on-board sensors to perceive the surrounding environment leads to perceptual deficiencies owing to inherent characteristics and sensor sparsity. To address this bottleneck, we propose ViT-FuseNet, a novel vehicle-infrastructure cooperative perception framework that utilizes a Vision Transformer to fuse feature maps extracted from LiDAR and camera data. The key component is a multimodal fusion module designed based on a cross-attention mechanism. ViT-FuseNet has two distinct advantages: i) it incorporates roadside LiDAR point clouds as additional inputs to enhance the 3D object detection capability of the vehicle; and ii) for the effective fusion of data from two different modal sensors, we employ a cross-attention mechanism for feature fusion, rather than directly merging camera features with point clouds at the raw data level. Extensive experiments are conducted using the DAIR-V2X Dataset to demonstrate the effectiveness of the proposed method. Compared with advanced cooperative perception methods, our method achieves a 6.17% improvement in 3D-mAP (IoU=0.5) and an 8.72% improvement in 3D-mAP (IoU=0.7). Moreover, the framework achieves the highest 3D-mAP (IoU=0.5) in all three object categories of benchmarks for single-vehicle perception.

Zero-shot remote sensing scene classification refers to making the model to have the ability to identify the unseen class scenes based on seen class scenes, and has become a research hotspot in the field of remote sensing. Contemporary approaches in zero-shot remote sensing scene classification primarily focus on extracting global information from scenes, neglecting nuanced local landscape features. This oversight diminishes the discriminative capabilities of recognition models. Furthermore, these methods overlook the semantic relevance between seen and unseen class scenes in training, leading to reduced emphasis on learning from varied scenes and subsequent declines in classification performance. To address these challenges, this article proposes the “Zero-Shot Remote Sensing Scene Classification Method Based on Local-Global Feature Fusion and Weight Mapping Loss (LGFFWM).” The design incorporates a local-global feature fusion (LGFF) module enabling adaptive labeling and feature modeling of internal local landscapes, effectively merging them with global features for a more discriminative representation of remote sensing scenes. Furthermore, a weight mapping loss (WM Loss) function is introduced, leveraging a semantic correlation matrix to compel the model to prioritize learning seen class scenes that exhibit strong correlations with unseen class scenes by assigning higher training weights. Extensive experiments have been conducted on classical remote sensing scene datasets, including UCM, AID, and NWPU, demonstrate the superiority of the proposed LGFFWM method over ten advanced comparative methods, yielding overall accuracy improvements of over 2.25%, 3.47%, and 0.44%, respectively. Additional experiments on the SIRI-WHU and RSSCN7 datasets underscore the transferability of LGFFWM, achieving overall accuracies of 53.50% and 47.37%, respectively.

Currently, a lane imbalance design scheme without auxiliary lanes for two-lane exits is increasing. To study the rationality of this exit scheme, the relationship between lane balance and traffic efficiency in the diverging area is investigated using a drone and image recognition software. The Kalman filter is used to optimize the original data and simplify the process of extracting the traffic volume, density and speed by Frenet coordinate transformation. Under the three states of free flow, saturated flow and supersaturated flow, lane balanced exit and lane imbalanced exit simulation models were constructed by using VISSIM. Based on the traffic flow theory, the curve of the relationship between traffic volume and density was fitted. The traffic volume corresponding to the difference between two schemes at the same density not exceeding 5% or 10% is calculated, and this traffic volume is defined as the scheme selection limit value. The results show that the traffic efficiency of lane imbalance scheme is consistently lower than that of lane balance scheme under all traffic conditions at the freeway exits. However, the difference in traffic efficiency between the two schemes is not fixed but increases as the upstream input traffic volume increases. When the exit forecast service traffic volume is lower than the “scheme selection limit value” (SSLV), the difference in traffic efficiency between the two schemes will not exceed 5% or 10%. In conclusion, the lane imbalance scheme can be used in the diverging area under certain traffic volume conditions, thus reducing the land, engineering volume and cost requirements. It also provides ideas for the study of three-lane exit ramp design schemes.

Abstract Cell immobilization plays an important role in biocatalysis for high-value products. It is necessary to maintain the viability of immobilized cells for bioconversion using viable cells as biocatalysts. In this study, a novel polyester nonwoven chemostat was designed for cell immobilization to investigate biofilm formation and the dynamic balance between adsorption and desorption of cells on polyester nonwoven. The polyester nonwoven was suitable for cell immobilization, and the cell numbers on the polyester nonwoven can reach 6.5 ± 0.38 log CFU/mL. After adding the polyester nonwoven to the chemostat, the fluctuation phenomenon of free bacterial cells occurred. The reason for this phenomenon was the balance between adsorption and desorption of bacterial cells on the polyester nonwoven. Bacterial cells could adhere to the surface of polyester nonwoven via secreting extracellular polymeric substances (EPS) to form biofilms. As the maturation of biofilms, some dead cells inside the biofilms can cause the detachment of biofilms. This process of continuous adsorption and desorption of cells can ensure that the polyester nonwoven chemostat has lasting biological activity. Graphical Abstract

With the development of e-commerce logistics in China, online shopping has become increasingly popular among consumers, and the fresh e-commerce industry has shifted to a pre-positioning warehouse distribution model closer to consumers. This study starts from consumer demands and considers the spatial distribution characteristics of consumers. Through cluster analysis, demand points with high consumer density are identified, and potential locations are determined through two rounds of clustering. Drawing insights from the warehousing and distribution models of Freshippo and MissFresh in Wuhan and Nanjing, four classification algorithms are compared to determine the optimal pre-positioning warehouse distribution model for the enterprise in this study. A multi-objective optimization model is established, aiming to minimize enterprise costs and maximize customer satisfaction, and the optimal site selection plan is obtained. By determining the number and locations of pre-positioning warehouses through the optimal solution, the enterprise can achieve maximum investment returns in the spatial layout of these warehouses.

Abstract Background Adenosquamous carcinoma is a rare sub-type of colorectal cancer with a poor prognosis. Little is known about its clinicopathological and molecular characteristics in Asian populations. This study aimed to investigate these features in a cohort of patients with adenosquamous carcinoma in the colorectum. Methods Tumor cases pathologically diagnosed with colorectal adenosquamous carcinoma were retrieved from the Sixth Affiliated Hospital, Sun Yat-sen University tissue archive between December 2012 and June 2020. Clinicopathological features, molecular characteristics, and oncology outcomes were analyzed. Results Among 18,139 cases of colorectal cancer, 11 were diagnosed with adenosquamous carcinoma, providing an incidence rate of 0.061%. The median overall survival (OS) was 14 months, and the expected 3-year OS rate was 29.6%. As of October 14, 2022, four cases had local recurrence and five had distant metastasis. KRAS gene mutations were found in four of seven patients (57.1%), and three out of eleven (27.3%) patients had mismatch repair-deficient (dMMR) tumors. Conclusions Adenosquamous carcinoma is associated with a poor prognosis. Compared to other sub-types of colorectal cancer, a higher proportion of patients with dMMR and KRAS mutations were observed. These findings suggested that more patients with adenosquamous carcinoma could benefit from targeted therapies, such as immunotherapy.

Thermoelectrics has played a fascinating role in the developments of direct energy conversion technologies. Over the past decade, sulfur-based thermoelectric materials have been significantly advanced in optimizing electrical and thermal transport due to their similarities in chemical and structural properties with tellurides and selenides. This review provides research progress on metal sulfides, particularly focuses on materials exhibiting high thermoelectric figure of merit (ZT > 1.0). It highlights the potential compounds, e.g. CuS, SnS, PbS based, and polysulfides. Great strategies of superionic conducting, band configuration tuning, high-entropy alloying, and anomalous harmonic scattering are try to demonstrate the performance-improved mechanisms for thermoelectric sulfides. In addition, some common synthesis recipes are briefly introduced, and thereby making potential candidates as excellent alternatives for producing thermoelectric power generators in the mid temperature. Key outcomes along with how to further improve the thermoelectric performance and promote its scale-up applications are also outlined at the end.

Abstract Atherosclerosis is one of the leading causes of death worldwide. miR-26 is a potential biomarker of atherosclerosis. Standardized diagnostic tests for miR-26 (MIR26-DX) have been developed, but the fastest progress has been in predicting the efficacy of IFN-α therapy for hepatocellular carcinoma (HCC, phase 3). MiR-26 slows atherosclerosis development by suppressing ACC1/2, ACLY, ACSL3/4, ALDH3A2, ALPL, BMP2, CD36, COL1A1, CPT1A, CTGF, DGAT2, EHHADH, FAS, FBP1, GATA4, GSK3β, G6PC, Gys2, HMGA1, HMGB1, LDLR, LIPC, IL-1β, IL-6, JAG2, KCNJ2, MALT1, β-MHC, NF-κB, PCK1, PLCβ1, PYGL, RUNX2, SCD1, SMAD1/4/5/7, SREBF1, TAB3, TAK1, TCF7L2, and TNF-α expression. Many agents targeting these genes, such as the ACC1/2 inhibitors GS-0976, PF-05221304, and MK-4074; the DGAT2 inhibitors IONIS-DGAT2Rx, PF-06427878, PF-0685571, and PF-07202954; the COL1A1 inhibitor HT-100; the stimulants 68Ga-CBP8 and RCT-01; the CPT1A inhibitors etomoxir, perhexiline, and teglicar; the FBP1 inhibitors CS-917 and MB07803; and the SMAD7 inhibitor mongersen, have been investigated in clinical trials. Interestingly, miR-26 better reduced intima-media thickness (IMT) than PCSK9 or CT-1 knockout. Many PCSK9 inhibitors, including alirocumab, evolocumab, inclisiran, AZD8233, Civi-007, MK-0616, and LIB003, have been investigated in clinical trials. Recombinant CT-1 was also investigated in clinical trials. Therefore, miR-26 is a promising target for agent development. miR-26 promotes foam cell formation by reducing ABCA1 and ARL4C expression. Multiple materials can be used to deliver miR-26, but it is unclear which material is most suitable for mass production and clinical applications. This review focuses on the potential use of miR-26 in treating atherosclerosis to support the development of agents targeting it.

Abstract Background The aim of this study is to conduct a comparative evaluation of different designs of clear aligners and examine the disparities between clear aligners and fixed appliances. Methods 3D digital models were created, consisting of a maxillary dentition without first premolars, maxilla, periodontal ligaments, attachments, micro-implant, 3D printed lingual retractor, brackets, archwire and clear aligner. The study involved the creation of five design models for clear aligner maxillary anterior internal retraction and one design model for fixed appliance maxillary anterior internal retraction, which were subsequently subjected to finite element analysis. These design models included: (1) Model C0 Control, (2) Model C1 Posterior Micro-implant, (3) Model C2 Anterior Micro-implant, (4) Model C3 Palatal Plate, (5) Model C4 Lingual Retractor, and (6) Model F0 Fixed Appliance. Results In the clear aligner models, a consistent pattern of tooth movement was observed. Notably, among all tested models, the modified clear aligner Model C3 exhibited the smallest differences in sagittal displacement of the crown-root of the central incisor, vertical displacement of the central incisor, sagittal displacement of the second premolar and second molar, as well as vertical displacement of posterior teeth. However, distinct variations in tooth movement trends were observed between the clear aligner models and the fixed appliance model. Furthermore, compared to the fixed appliance model, significant increases in tooth displacement were achieved with the use of clear aligner models. Conclusions In the clear aligner models, the movement trend of the teeth remained consistent, but there were variations in the amount of tooth displacement. Overall, the Model C3 exhibited better torque control and provided greater protection for posterior anchorage teeth compared to the other four clear aligner models. On the other hand, the fixed appliance model provides superior anterior torque control and better protection of the posterior anchorage teeth compared to clear aligner models. The clear aligner approach and the fixed appliance approach still exhibit a disparity; nevertheless, this study offers a developmental direction and establishes a theoretical foundation for future non-invasive, aesthetically pleasing, comfortable, and efficient modalities of clear aligner treatment.

The optimal selections of supplier portfolios and supplier substitutes are important research contents of the supplier selection problem. However, most of the existing supplier selection methods are based on the efficiency of indicator capability of supplier, the complementary capability (i.e., weak similarity) between suppliers for the supplier portfolio, and the substitution capabilities (i.e., strong similarity) of supplier substitutes for the best supplier may not be considered. Therefore, two new supplier selection models, namely TOPSIS-NS considering the negative influence of similarity for supplier portfolio selection and TOPSIS-PS considering the positive influence of similarity for supplier substitute selection, are proposed based on TOPSIS and intuitionistic fuzzy set (IFS). Firstly, the efficiency of indicator capability of supplier is expressed by the membership degree of IFS obtained by TOPSIS, while the similarity among suppliers is expressed by the nonmembership degree of IFS obtained by the concordance correlation coefficient. Then, the process of TOPSIS-NS for supplier portfolio selection is constructed based on the score function of IFS, and the supplier portfolio selected by TOPSIS-NS can have higher complementary capabilities. Furthermore, the process of TOPSIS-PS for supplier substitute selection is constructed based on the accuracy function of IFS, and the supplier substitute selected by TOPSIS-PS can have higher substitution capabilities. Finally, two illustrative examples for optimal selections of supplier portfolio and supplier substitute are given respectively, and the results show the superiority of TOPSIS-NS in supplier portfolio selection and TOPSIS-PS in supplier substitute selection.

Background: The utilization of decellularized extracellular matrix has gained considerable attention across numerous areas in regenerative research. Of particular interest is the human articular cartilage-derived extracellular matrix (hACECM), which presents as a promising facilitator for cartilage regeneration. Concurrently, the microfracture (MF) ​technique, a well-established marrow stimulation method, has proven efficacious in the repair of cartilage defects. However, as of the current literature review, no investigations have explored the potential of a combined application of hACECM and the microfracture technique in the repair of cartilage defects within a sheep model. Hypothesis: The combination of hACECM scaffold and microfracture will result in improved repair of full-thickness femoral condyle articular cartilage defects compared to the use of either technique alone. Study design: Controlled laboratory study. Methods: Full-thickness femoral condyle articular cartilage defect (diameter, 7.0 ​mm; debrided down to the subchondral bone plate) were created in the weight-bearing area of the femoral medial and lateral condyles (n ​= ​24). All of defected sheep were randomly divided into four groups: control, microfracture, hACECM scaffold, and hACECM scaffold ​+ ​microfracture. After 3, 6 and 12 months, the chondral repair was assessed for standardized (semi-) quantitative macroscopic, imaging, histological, immunohistochemical, mechanics, and biochemical analyses in each group. Result: At 3, 6 and 12 months after implantation, the gross view and pathological staining of regenerative tissues were better in the hACECM scaffold and hACECM scaffold ​+ ​microfracture groups than in the microfracture and control groups; Micro-CT result showed that the parameters about the calcified layer of cartilage and subchondral bone were better in the hACECM scaffold and hACECM scaffold ​+ ​microfracture groups than the others, and excessive subchondral bone proliferation in the microfracture group. The results demonstrate that human cartilage extracellular matrix scaffold alone is an efficient, safe and simple way to repair cartilage defects. Conclusion: hACECM scaffolds combined with/without microfracture facilitate chondral defect repair. The translational potential of this article: Preclinical large animal models represent an important adjunct and surrogate for studies on articular cartilage repair, while the sheep stifle joint reflects many key features of the human knee and are therefore optimal experimental model for future clinical application in human. In this study, we developed a human articular cartilage-derived extracellular matrix scaffold and to verify the viability of its use in sheep animal models. Clinical studies are warranted to further quantify the effects of hACECM scaffolds in similar settings.

Background: The neurogenesis hypothesis is a promising candidate etiologic hypothesis for depression, and it is associated with electroconvulsive therapy (ECT). However, human in vivo molecular-level evidence is lacking. Objective: We used neuron-derived extracellular vesicles (NDEVs) as a “window to the neurons” to explore the in vivo neurogenesis status associated with ECT in patients with treatment-resistant depression (TRD). Methods: In this study, we enrolled 40 patients with TRD and 35 healthy controls (HCs). We isolated NDEVs from the plasma of each participant to test the levels of doublecortin (DCX), a marker of neurogenesis, and cluster of differentiation (CD) 81, a marker of EVs. We also assessed the plasma levels of brain-derived neurotrophic factor (BDNF), a protein that is known to be associated with ECT and neuroplastic processes. Results: Our findings indicated that both the levels of DCX in NDEVs and BDNF in plasma were significantly lower in TRD patients compared to HCs at baseline, but increased following ECTs. Conversely, levels of CD81 in NDEVs were found higher in TRD patients at baseline, but did not change after the ECT treatments. Exploratory analyses revealed that lower levels of BDNF in plasma and DCX in NDEVs, along with higher CD81 levels in NDEVs, were associated with more severe depressive symptoms and reduced cognitive function at baseline. Furthermore, higher baseline CD81 concentrations in NDEVs were correlated with greater decreases in depression symptoms. Conclusions: We first present human in vivo evidence of early neurogenesis using DCX through NDEVs: decreased in TRD patients, increased after ECTs.

As a vital and integral component of transportation infrastructure, pavement has a direct and tangible impact on socio-economic sustainability. In recent years, an influx of groundbreaking and state-of-the-art materials, structures, equipment, and detection technologies related to road engineering have continually and progressively emerged, reshaping the landscape of pavement systems. There is a pressing and growing need for a timely summarization of the current research status and a clear identification of future research directions in these advanced and evolving technologies. Therefore, Journal of Road Engineering has undertaken the significant initiative of introducing a comprehensive review paper with the overarching theme of “advanced road materials, structures, equipment, and detection technologies”. This extensive and insightful review meticulously gathers and synthesizes research findings from 39 distinguished scholars, all of whom are affiliated with 19 renowned universities or research institutions specializing in the diverse and multidimensional field of highway engineering. It covers the current state and anticipates future development directions in the four major and interconnected domains of road engineering: advanced road materials, advanced road structures and performance evaluation, advanced road construction equipment and technology, and advanced road detection and assessment technologies.

Abstract Tourism eco-efficiency is an important indicator to measure the sustainable development of tourism with the core objective of "minimum resource input and environmental damage, maximum economic and social output". This paper explores the spatial and temporal evolution characteristics of tourism eco-efficiency and its influencing factors in Fujian Province from 2011 to 2020 by combining the unexpected output Super-SBM model, gravity center model, standard deviation ellipse, and optimal parameters-based geographical detector model. The results are as follows. Tourism eco-efficiency in Fujian Province showed an overall fluctuating growth trend with an increase of 160.065% during the study period. The coefficient of variation of tourism eco-efficiency tends to fluctuate and decrease, and regional differences narrow. The spatial differentiation is remarkable, and it presents the spatial distribution characteristics of "Xiamen > Nanping > Quanzhou > Fuzhou > Longyan > Ningde > Sanming > Zhangzhou > Putian". The spatial pattern of tourism eco-efficiency is obvious in the direction of "northeast-southwest", and the trajectory of the center of gravity is "southwest-northeast-northwest", with spatial characteristics tending towards agglomeration. Tourism industry structure has the greatest impact on tourism eco-efficiency, followed by education level, urbanization level, technology innovation level, infrastructure investment, and economic development level. This study provides reference suggestions for improving tourism eco-efficiency which helps to promote adequate, balanced, and sustainable development of the regional tourism industry.

Abstract The incentive mechanism of federated learning has been a hot topic, but little research has been done on the compensation of privacy loss. To this end, this study uses the Local SGD federal learning framework and gives a theoretical analysis under the use of differential privacy protection. Based on the analysis, a multi‐attribute reverse auction model is proposed to be used for user selection as well as payment calculation for participation in federal learning. The model uses a mixture of economic and non‐economic attributes in making choices for users and is transformed into an optimisation equation to solve the user choice problem. In addition, a post‐auction negotiation model that uses the Rubinstein bargaining model as well as optimisation equations to describe the negotiation process and theoretically demonstrate the improvement of social welfare is proposed. In the experimental part, the authors find that their algorithm improves both the model accuracy and the F1‐score values relative to the comparison algorithms to varying degrees.

Abstract Background Type 1 gastric neuroendocrine tumors (NETs) are relatively rare to the extent that some physicians have little experience in diagnosing and treating them. The purpose of this study was to increase the understanding of the disease by analyzing and summarizing the management and prognoses of patients with type 1 gastric NETs at our center. Methods The data of 229 patients (59.4% female) with type 1 gastric NETs who were treated at our center during 2011–2022 were retrospectively analyzed. Results The average patient age was 50.5 ± 10.8 years. Multiple tumors affected 72.5% of the patients; 66.4% of the tumors were

Abstract The present work was an endeavor to shed light on how mild photothermia possibly synergizes with immune checkpoint inhibition for tumor therapy. We established mild photothermal heating protocols to generate temperatures of 43 °C and 45 °C in both in vitro and in vivo mouse 4T1 triple-negative breast cancer (TNBC) models using polyglycerol-coated carbon nanohorns (CNH-PG) and 808 nm laser irradiation. Next, we found that 1) CNH-PG-mediated mild photothermia (CNH-PG-mPT) significantly increased expression of the immune checkpoint PD-L1 and type-1 macrophage (M1) markers in the TNBC tumors; 2) CNH-PG-mPT had a lower level of anti-tumor efficacy which was markedly potentiated by BMS-1, a PD-L1 blocker. These observations prompted us to explore the synergetic mechanisms of CNH-PG-mPT and BMS-1 in the context of tumor cell-macrophage interactions mediated by PD-L1 since tumor-associated macrophages (TAMs) are a major source of PD-L1 expression in tumors. In vitro, the study then identified two dimensions where BMS-1 potentiated CNH-PG-mPT. First, CNH-PG-mPT induced PD-L1 upregulation in the tumor cells and showed a low level of cytotoxicity which was potentiated by BMS-1. Second, CNH-PG-mPT skewed TAMs towards an M1-like anti-tumor phenotype with upregulated PD-L1, and BMS-1 bolstered the M1-like phenotype. The synergistic effects of BMS-1 and CNH-PG-mPT both on the tumor cells and TAMs were more pronounced when the two cell populations were in co-culture. Further in vivo study confirmed PD-L1 upregulation both in tumor cells and TAMs in the TNBC tumors following treatment of CNH-PG-mPT. Significantly, TAMs depletion largely abolished the anti-TNBC efficacy of CNH-PG-mPT alone and in synergy with BMS-1. Collectively, our findings reveal PD-L1 upregulation to be a key response of TNBC to mild photothermal stress, which plays a pro-survival role in the tumor cells while also acting as a brake on the M1-like activation of the TAMs. Blockade of mPT‑induced PD‑L1 achieves synergistic anti-TNBC efficacy by taking the intrinsic survival edge off the tumor cells on one hand and taking the brakes off the M1-like TAMs on the other. Our findings reveal a novel way (i.e. mild thermia plus PD-L1 blockade) to modulate the TAMs-tumor cell interaction to instigate a mutiny of the TAMs against their host tumor cells. Graphical Abstract

The gas-phase hydrogenation of furfural to furfuralcohol over Cr-free Cu-based catalysts has attracted increasing attention due to its environmentally friendly nature and mild operating conditions. Although reduced pure nano-sized CuO exhibits complete furfural hydrogenation and nearly 100% furfuralcohol selectivity, it suffers from rapid deactivation caused by sintering. In this study, we conducted comparative investigations on the catalytic performance and stability of two Cu-based catalysts: 90%CuO-10%SiO2 and 90%CuO-5%CaO-5%SiO2, in the gas-phase furfural hydrogenation. The reaction is carried out under various conditions, including temperatures ranging from 120 to 170 ℃, LHSVs of 1 to 2.2 h−1, and H2 to furfural molar ratios of 3.5 to 12.5. The results indicate that under optimal conditions, the Ca-modified catalyst achieves nearly complete furfural conversion and almost 100% furfuralcohol selectivity for a test duration of 31 h. In contrast, the unmodified catalyst exhibits stable performance for only seven hours despite the similar initial performance. XRD analysis confirms that the gradual deactivation of both catalysts is attributed to the oxidation of reduced metallic Cu sites to Cu oxides. Further characterizations of the two spent catalysts using HRTEM and XPS analyses, along with DFT calculations, suggest that the presence of Ca in Cu lattices prevents the loss of electrons from low-valence Cu sites or the reduced metallic Cu sites, thus inhibiting their oxidation to high-valence Cu oxides. This phenomenon contributes to suppressing the deactivation of Cu-catalysts in the gas-phase furfural hydrogenation process.

Fuzzy-ball fluid is a two-phase fluid composed of fuzzy-ball and base fluid. It can enhance oil recovery by approximately 30% after water flooding and polymer flooding, which has been demonstrated in laboratory experiments and field applications. However, the EOR mechanism of fuzzy-ball fluid still needs further research. In this study, the microstructure of fuzzy-ball was observed using optical and cryo-scanning electron microscopy. The EOR mechanism of fuzzy-ball fluid was investigated by the microscopic glass etching model experiment and inter-molecular force calculation. EOR contribution ratio of three parts of fuzzy-ball was evaluated by the single core flooding experiment. Results showed that fuzzy-ball was further subdivided into fuzzy-ball structure and floss structure. Correspondingly, the EOR effects of fuzzy-ball fluid were mainly divided into three parts: (a) base fluid. Emulsification was the main way for base fluid to enhance oil recovery; (b) fuzzy-ball structure. According to the distribution characteristics of residual oil, the EOR mechanisms of fuzzy-ball structure were mainly as follows: wedging displacement for membranous oil, squeezing-carrying mechanism for columnar oil, and extruding-squeezing mechanism for blind-end oil; (c) floss structure. Floss structure enhanced oil recovery mainly through entanglement and carrying mechanism. Moreover, the EOR contribution ratio of base fluid, fuzzy-ball structure, and floss structure are 18.35%, 50.94%, and 30.71%, respectively. This study elucidates the EOR mechanism of fuzzy-ball fluid and provides guidance for its subsequent field application and performance improvement.

To accommodate the integration of renewable energy, coal-fired power plants must take on the task of peak regulation, making the low-load operation of boilers increasingly routine. Under low-load conditions, the phase transition point (PTP) of the working fluid fluctuates, leading to potential flow instability, which can compromise boiler safety. In this paper, a one-dimensional coupled dynamic model of the combustion and hydrodynamics of a supercritical boiler is developed on the Modelica/Dymola 2022 platform. The spatial distribution of key thermal parameters in the furnace and the PTP position in the water-cooled wall (WCW) are analyzed in a 660 MW supercritical boiler when parameters on the combustion side change under full-load and low-load conditions. The dynamic response characteristics of the temperature, mass flow rate, and the PTP position are investigated. The results show that the over-fire air (OFA) ratio significantly influences the flue gas temperature distribution. A lower OFA ratio increases the flue gas temperature in the burner zone but reduces it at the furnace exit. The lower OFA ratio leads to a higher fluid temperature and shortens the length of the evaporation section. The temperature difference in the WCW outlet fluid between the 20% and 60% OFA ratios is 11.7 °C under BMCR conditions and 7.4 °C under 50% THA conditions. Under the BMCR and 50% THA conditions, a 5% increase in the coal caloric value raises the flue gas outlet temperature by 32.7 °C and 35.4 °C and the fluid outlet temperature by 6.5 °C and 9.9 °C, respectively. An increase in the coal calorific value reduces the length of the evaporation section. The changes in the length of the evaporation section are −2.95 m, 2.95 m, −2.62 m, and 0.54 m when the coal feeding rate, feedwater flow rate, feedwater temperature, and air supply rate are increased by 5%, respectively.

This study reviews the applications of big data (BD) and blockchain technology in modern food testing and explores their impact on educational reform. The first part highlights the critical role of BD in ensuring food safety across the supply chain, discussing various data collection methods, such as national and international food safety databases, while addressing the challenges related to data storage and real-time information retrieval. Additionally, blockchain technology has been explored for its ability to enhance transparency, traceability, and security in the food-testing process by creating immutable records of testing data, ensuring data integrity, and reducing the risk of tampering or fraud. The second part focuses on the influence of BD and blockchain on educational reform, particularly within food science curricula. BD enables data-driven curriculum design, supporting personalized learning and more effective educational outcomes, while blockchain ensures transparency in course management and credentials. This study advocates integrating these technologies into curriculum reform to enhance both the efficiency and quality of education.

With the background of global climate change and rapid economic growth, there are increasing problems threatening regional sustainable development [...]

During petroleum drilling, the reciprocating motion in the seal device leads to piston and sleeve wear, which may cause leakage of the sealing medium. Selecting appropriate materials for the piston and sleeve, along with surface modifications, can effectively prolong the seal service life of the seal. The friction and wear properties of piston and sleeve pairs of different materials in a metal sealing device were simulated by the laboratory “pin-on-block” reciprocating friction test. Pins made of 45# steel, 35CrMo, and 20Cr13 were used to simulate piston bulges, while 35CrMo samples were used to simulate sleeves. Additionally, the influence of DLC (diamond-like carbon) coating and QPQ (Quench–Polish–Quench) nitriding on the wear resistance of the materials was studied. Based on this, the friction and wear properties, along with the wear mechanism of different material pairs, were analyzed. The results show that the friction coefficient curves of the three piston base materials and the 35CrMo sleeve are similar, and the friction coefficient of 45# steel is lower than that of 35CrMo and 20Cr13 at the initial stage. The DLC surface coating exhibited the best anti-wear performance, with the lowest friction coefficient, minimal wear, and the most stable friction coefficient. Surface QPQ nitriding treatment can also improve the wear resistance of the base material. However, due to the oxide formed during nitriding being prone to flaking, the friction coefficient fluctuates significantly at the initial stage of testing, and its anti-wear performance was inferior to that of the DLC coating. This study on material pairing and surface modification provides theoretical support for material selection and surface modification design of pistons and sleeves in oil drilling sealing devices.

Background: HPV vaccination is the key measure to prevent cervical cancer, but uptake in China lags behind global targets. Understanding Chinese guardians’ preferences is key to improving vaccine acceptance and coverage. Methods: A nationwide online discrete choice experiment survey was conducted among 4933 Chinese guardians across seven provinces in 2022 to quantify preferences and willingness to pay. Attributes included effectiveness, safety, duration, valency, location, and out-of-pocket cost. Results: Out of the 4933 guardians who participated in the study, 4179 (84.72%) were mothers. More than 60% of the guardians belonged to the age group of 35–44 years. Additionally, over half of the respondents (53.15%) had daughters between the ages of 9 and 14 years. Respondents were open to accepting the HPV vaccine with 95% efficacy and exceptional safety. Guardians expressed a preference for longer protection duration (specifically 15 years (βa = 0.340, 95% CI: 0.31, 0.37)) and higher vaccine valency. As for willingness to pay, the respondents placed the highest value on vaccine efficacy, being willing to shell out more than USD 1100 for 95% protection as compared to 50%. Furthermore, very good safety commanded a premium of over USD 800 when compared to average safety. When it comes to willingness to uptake, a vaccine with 95% efficacy led to a more than 35% increase in acceptance as compared to one with 50% efficacy. Similarly, exceptional safety resulted in an increased willingness to uptake of over 25% when compared to average safety. Conclusions: The DCE highlighted effectiveness, safety, and durability as critical drivers of HPV vaccine acceptance, but substantial barriers persist regarding adolescent female coverage in China.

Ephedra sinica (E. sinica) holds significant economic and medicinal importance and is predominantly found in arid areas. Due to the limitations of environmental variables, growth habits, and human activities, the production and suitability areas of E. sinica have significantly decreased, especially in the five northwestern provinces of China. In this study, 212 distribution points of E. sinica and 40 environmental variables were obtained to project the habitat suitability of E. sinica under different emission scenarios in the future. It identified precipitation in the wettest month, monthly mean of the diurnal temperature difference, and solar radiation intensity in April and July as the primary environmental factors affecting the suitability of E. sinica in the region. The areas of high, medium, and low suitability in the region cover 103,000 km2, 376,500 km2, and 486,800 km2. Under future scenarios, the suitability areas from 2021 to 2100 will decrease by 20%, with high suitability areas decreasing by 65% to 85% particularly. With comprehensive environmental variables, the suitability areas of E. sinica from 2021 to 2100 are projected, filling the gap in the projection of E. sinica suitability areas in the five northwestern provinces of China over long time period. The suitability areas show a significant decreasing trend. This research provides valuable insights into the suitability areas and crucial environmental factors, offering theoretical support for future protection and management efforts for E. sinica.

The primary objective of this research paper is to explore strategies for enhancing the electrical performance of dual active layer thin film transistors (TFTs) utilizing LZTO/ZTO as the bilayer architecture. By systematically adjusting the thickness of the active layers, we achieved significant improvements in the performance of the LZTO/ZTO TFTs. An XPS analysis was performed to elucidate the impact of the varying O2 element distribution ratio within the LZTO/ZTO bilayer thin film on the TFTs performance, which was directly influenced by the modification in the active layer thickness. Furthermore, we utilized atomic force microscopy to analyze the effect of altering the active layer thickness on the surface roughness of the LZTO/ZTO bilayer film and the impact of this roughness on the TFTs electrical performance. Through the optimization of the ZTO active layer thickness, the LZTO/ZTO TFT exhibited an mobility of 10.26 cm2 V−1 s−1 and a switching current ratio of 5.7 × 107, thus highlighting the effectiveness of our approach in enhancing the electrical characteristics of the TFT device.

As the share of renewable energy in a grid increases, the grid’s frequency support capability weakens, and the spatial distribution of grid frequency becomes more pronounced. As a result, control strategies based on system frequency consistency and traditional frequency regulation dominated by synchronous machines are becoming increasingly inadequate for meeting the frequency regulation requirements of new-type power systems. To enhance the system’s frequency support capability, it is imperative to fully utilize the frequency regulation resources within the power system. To address this issue, this paper first introduces a system frequency security posture assessment method that accounts for the spatial distribution characteristics of the grid. Subsequently, a parameter optimization method for diverse frequency regulation resources is proposed in conjunction with the proposed comprehensive evaluation method for frequency regulation. Next, using a renewable energy feeder regional grid as an example, an integrated frequency regulation method based on the system frequency security posture is presented. Finally, the frequency regulation performance and economic costs of different frequency regulation methods are analyzed under various operating scenarios and disturbances using a model based on actual data from the renewable energy feeder regional grid. The simulation and index calculation results demonstrate that the method proposed in this paper effectively enhances the system’s frequency support capability, reduces the frequency disparity between different nodes within the grid, and maintains high economic performance.