Search Results (1,277)

Research on extracting building from airborne point clouds is abundant, yet discussions regarding scenarios where vegetation and building structures are closely intertwined with similar height in rural areas remain relatively scarce. This thesis adopts a region representative of typical rural building features in China as an experimental site to conduct research on building classification procedures from airborne point clouds. Firstly, the multi-level grid size is dynamically determined through slope analysis to creatively segment and recognize terrain type, then differentiated filtering parameters are applied to various terrains to fully extract ground points, providing a ground reference for building classification. Secondly, the selection of building Region of Interest is conducted by multiple geometric feature differences between building and other objects based on watershed segmentation results, which eliminates interference from non-building points, significantly reducing redundant and unnecessary mathematical computation. Finally, refined building classification is achieved based on multiple morphological differences between buildings and other objects. The experimental results show that the precision, recall, and F1 of both datasets exceeded 93.37%, 97.05%, and 95.17%, respectively. The average precision, recall, and F1 reached 94.02%, 97.20%, and 95.58%, respectively. This method demonstrates successful building classification in rural areas, showing strong adaptability and practicality for the extraction of various building data. Full article

Condition-based maintenance strategies using AI-driven health monitoring have emerged as valuable tools for industrial reliability, yet their implementation remains challenging in industries with limited operational data. Class I induction motors (≤15 kW), which power critical equipment in industries such as grain handling facilities, represent a significant portion of industrial assets but lack established healthy vibration baselines for effective monitoring. A fundamental challenge exists in deploying AI-based health monitoring systems when no historical performance data is available, creating a ’cold-start’ problem that prevents industries from adopting predictive maintenance strategies without costly pilot programs or prolonged data collection periods. This study developed a data-driven health monitoring framework for Class I induction motors that eliminates the dependency on long-term historical trends. Through extensive experimental testing of 98 configurations on new motors, a correlation between vibration amplitude at rotational frequency and motor power rating was established, enabling the creation of a synthetic signal generation algorithm. A robust Health Index (HI) model with integrated diagnostic capabilities was developed using the JPCCED-HI framework, trained on both experimental and synthetically generated healthy vibration data to detect degradation and diagnose common failure modes. The regression analysis revealed a statistically significant relationship between motor power rating and healthy vibration signatures, enabling synthetic generation of baseline data for any Class I motor within the rated range. When implemented at an operational grain silo facility, the HI model successfully detected faulty behavior and accurately diagnosed probable failure modes in equipment with no prior monitoring history, demonstrating that maintenance decisions could be made based on condition data rather than reactive responses to failures. This framework enables immediate deployment of AI-based condition monitoring in industries lacking historical data, eliminating a major barrier to adopting predictive maintenance strategies. The synthetic data generation approach provides a cost-effective solution to the data scarcity problem identified as a critical challenge in industrial AI applications, while the successful industrial implementation validates the feasibility of this approach for small-to-medium industrial facilities. Full article

Recovery of the stratospheric ozone layer following the ban on ozone-depleting substances represents one of the most successful examples of international environmental policy. However, the long-term fate of ozone under continuing climate change remains uncertain. We present the first multi-century projections of ozone evolution to 2200 using emission-driven CMIP7 scenarios in the SOCOL-MPIOM chemistry-climate model. Our results show that despite the elimination of halogenated compounds, total column ozone exhibits non-monotonic evolution, with an initial increase of 8–12% by 2080–2100, followed by a decline to 2200, remaining 4.5–7% above the 2020 baseline. Stratospheric ozone at 50 hPa shows a monotonic decline of 2–11% by 2200 across all scenarios, with no recovery despite ongoing Montreal Protocol implementation. Critically, even in the high-overshoot scenario where CO₂ concentrations decline from 830 to 350 ppm between 2100 and 2200, stratospheric ozone continues to decrease. Intensification of the Brewer-Dobson circulation in warmer climates reduces ozone residence time in the tropical stratosphere, decreasing photochemical production efficiency. This dynamic effect outweighs the reduction in ozone-depleting substances, leading to persistent stratospheric ozone depletion despite total column ozone enhancements in polar regions. Spatial analysis reveals pronounced regional differentiation: Antarctic regions show sustained total column enhancement of +18–26% by 2190–2200, while tropical regions decline to levels below baseline (−4 to −5%). Our results reveal fundamental asymmetry between climate forcing and ozone response, with characteristic adjustment timescales of 100–200 years, and have critical implications for long-term atmospheric protection policy. Full article

Chimeric antigen receptor (CAR)-T cell therapy has emerged as a transformative form of immunotherapy, enabling the precise engineering of T cells to recognize and eliminate pathogenic cells. In hematologic malignancies, CAR-T cells targeting CD19 or B cell maturation antigens have achieved remarkable remission rates and durable responses in patients with otherwise refractory disease. Despite these successes, extending CAR-T cell therapy to solid tumors remains challenging due to antigen heterogeneity, poor T cell infiltration, and the immunosuppressive tumor microenvironment (TME). Beyond oncology, CAR-T cell therapy has also shown promise in autoimmune diseases, where early clinical studies suggest that B cell-directed CAR-T cells can induce sustained remission in conditions such as systemic lupus erythematosus. This review highlights advances in CAR-T cell engineering, including DNA- and mRNA-based platforms for ex vivo and in vivo programming, and discusses emerging strategies to enhance CAR-T cell trafficking, persistence, and resistance to TME. Full article

Most aircraft skin components are typical sheet metal components, and stretch forming serves as the primary forming process. The die face is the core foundation for both the finite element simulation and mold trial. Due to the intricate geometric characteristics of aircraft skin components and iterative revisions caused by stretch forming process adjustments and product design changes, the die face design of aircraft skin components is inherently time-intensive, highly complex, and prone to instability. To address these issues, a Hierarchical and Hybrid Association Method (HHAM) based on a robust updating mechanism and hybrid associations is proposed for the intelligent design system. HHAM can significantly enhance the stability and efficiency of die face design. Specifically, the hierarchical and automatic updating process of HHAM, incorporating robust error handling mechanisms, is the core methodology that guarantees the stability of complex and iterative die face design for aircraft skin. Moreover, the inter-module hybrid association, which integrates parametric modeling and automatic connection techniques, eliminates the instability in die face design updating caused by feature and topology variations. Additionally, robust geometric algorithms for wireframe modeling effectively improve the surface quality and generation success rate of the die face. The intelligent design system developed based on the CATIA platform has been successfully applied in two professional aircraft skin component manufacturing enterprises. Case studies and industrial application practices verify the effectiveness of the proposed system, achieving a 72.7% improvement in design efficiency and a 70.27% reduction in the risk of die face update errors. Full article

Background/Objectives: Precise implant positioning is critical for successful prosthetic rehabilitation, particularly in completely edentulous patients where anatomical landmarks are lost. The aim of this study was to assess the accuracy of implant placement in the edentulous maxilla and mandible using computer-assisted planning and a bone-supported stackable surgical guide protocol. Methods: This retrospective clinical study included 15 completely edentulous patients who received a total of 60 implants. A dual-scan protocol was utilized for planning. The surgical protocol involved a base guide fixed to the bone with pins, serving as a rigid foundation for stackable components used for osteotomy and implant insertion. Postoperative CBCT scans were superimposed onto the preoperative plan to calculate angular deviations, 3D linear deviations at the implant neck and apex, and depth deviations. Results: The analysis demonstrated high accuracy with a mean angular deviation of 1.25° ± 0.80°. The mean 3D linear deviation was 0.96 ± 0.57 mm at the implant neck and 1.07 ± 0.56 mm at the apex. Depth deviation showed a mean discrepancy of 0.37 ± 0.58 mm. All measured parameters were statistically significantly lower (p < 0.05) than the pre-established clinical safety thresholds. Conclusions: Within the limitations of this study, the bone-supported stackable surgical guide protocol proved to be a highly accurate method for full-arch rehabilitation. By eliminating mucosal resilience and ensuring rigid fixation, this approach enables predictable implant placement and facilitates the passive fit of screw-retained bar-supported prostheses, representing a reliable alternative to dynamic navigation in daily clinical practice. Full article

With the wide application of lithium-ion batteries (LIBs), many spent LIBs will face the problem of recycling and treatment in the future. The recycling of valuable substances from battery materials is particularly important. In this paper, the spent LiNi_0.5Co_0.2Mn_0.3O₂ (S-NCM523) cathode material from used LIBs was regenerated by using the eutectic lithium salt of Li₂CO₃/LiOH. The lithium element lost by S-NCM523 was supplemented through solid–liquid contact with the molten lithium salt, restoring the layered structure at high temperatures. The successful repair of the regenerated material was verified by various characterization methods, including the elimination of the rock salt phase and the lower Li⁺/Ni²⁺ disorder. This research shows that the regenerated cathode material still has a high specific discharge capacity of 146.8 mAh/g after 100 cycles, with a capacity retention rate of 96.0%. The excellent electrochemical performance of the regenerated material demonstrates the feasibility of directly regenerating spent NCM using the molten salt method. Full article

In view of the technical bottleneck of microbial dynamic monitoring during the solid-state fermentation of traditional Baijiu, this study introduced green fluorescent protein (GFP) labeling technology into the dominant Saccharomyces cerevisiae of Jiang-flavored Baijiu to construct the chromosomal integration engineering strain named FSC01. By designing an integrated recombinant plasmid containing the GFP gene and the geneticmycin resistance gene, an engineered strain that stably expresses fluorescent proteins was obtained by electroconversion. Flow cytometry verification showed that FSC01 showed excellent linear responses in the pure microbial system (R² = 0.998) and the complex matrix of Baijiu jiupei (R² = 0.981), with a detection limit of 10² cells/mL, and the detection cycle was shortened to 10 min. Solid-state fermentation simulation experiments show that the inoculation volume of FSC01 of 10⁵ cells/kg can not only ensure the effective identification of fluorescence signals, but also does not significantly interfere with the growth and growth patterns of the original yeast (p > 0.05), which is highly consistent with the results of the traditional plate counting method. Dynamic monitoring shows that Saccharomyces cerevisiae during fermentation presents a typical succession pattern of “increase first and then decrease”, reaching a peak on the 7th day (1.2 × 10⁷ cells/g), which is positively correlated with the base alcohol yield rate (26.7%). Compared with metagenomic (72 h) and PMA-qPCR (4 h) methods, this technology breaks through the limitations of specificity and timeliness of live bacteria detection, and provides a single-cell-level dynamic analysis tool for the digitization of traditional brewing processes. In the future, it will be expanded to monitor key functional microorganisms such as lactic acid bacteria through a multi-color fluorescent labeling system, and optimized pretreatment to eliminate starch granule interference, and promote the in-depth application of synthetic biology technology in the traditional fermentation industry. Full article

Impedance diagnostics is commonly employed in the study of transport phenomena in conducting media of different sizes. A common reason for choosing the more complex method of exciting the conductive medium at finite frequencies ($ac$ mode) instead of the relatively simple method of excitation at zero frequency ($dc$ mode) is to eliminate the influence of contact phenomena on the current–volt charateristic (IVC) during $dc$ measurements. In this paper, we analyze relaxation phenomena in electrolytes with linear electrohydrodynamics in terms of dopant density $n_d$. It is shown that the requirement of linearity on $n_d$ of the electrohydrodynamics of dilute solutions cannot be satisfied by the Debye–Huckel–Onsager theory of electrolyte conductivity. A linear alternative based on the fundamental principles of the theory of transport in finely dispersed two-phase systems is proposed. This alternative is referred to in the literature as Maxwell’s formalism. It is noted that, in this case, there is a consistent possibility of treating the observed relaxation time, ${\tau }_c$, as impedance time ${\tau }_{rc}({\tau }_c\to {\tau }_{rc}=RC)$. Here, R is the resistance of the dilute electrolyte part of the cell, and C is the electrolytic capacitance of the same cell. This capacitance does not coincide with the traditional geometric one, $C_0<<C$, and has to be calculated self-consistently. Examples of the successful application of $RC$-consistent $ac$ diagnostics are discussed. This refers to the numerous instances in which the effective conductivity of various colloidal media deviates from the predictions of Maxwell’s well-known theory and to the correct interpretation of these anomalies in the RC representation. Full article

Timely and accurate crop yield estimation is vital for food security and management decision-making. Integrating remote sensing with machine learning provides an effective solution. In this study, based on canopy hyperspectral data collected by an ASD FieldSpec 3 handheld spectrometer during the critical growth stages of winter wheat, 18 vegetation indices (VIs) were systematically calculated, and their correlation with yield was analyzed. At the same time, a continuous projection algorithm, Successive Projections Algorithm (SPA), was used to screen the characteristic bands. Recursive Feature Elimination (RFE) was employed to select optimal features from VIs and characteristic spectral bands, facilitating the construction of a multi-temporal fusion feature set. To identify the superior yield estimation approach, a comparative analysis was conducted among four machine learning models: Deep Forest (DF), Support Vector Regression (SVR), Random Forest (RF), and Gaussian Process Regression (GPR). Performance was evaluated using the coefficient of determination (R²), root mean square error (RMSE), and relative root mean square error (rRMSE). Results indicate that the highest correlations between VIs and grain yield were observed during the flowering and grain-filling stages. Independent analysis showed that VIs reached absolute correlations of 0.713 and 0.730 with winter wheat yield during the flowering and grain-filling stages, respectively, while the SPA further identified key bands primarily in the near-infrared and short-wave infrared regions. On this basis, integrating multi-temporal features through RFE significantly improved the accuracy of yield estimation. Among them, the DF model with the fusion of flowering and filling stage features performed best (R² = 0.786, RMSE = 641.470 kg·hm⁻², rRMSE = 15.67%). This study demonstrates that combining hyperspectral data and VIs from different growth stages provides complementary information. These findings provide an effective method for crop yield estimation in precision agriculture. Full article

Background: Pancreatic cancer (PC) has a very poor 5-year survival and prognosis. Even when CT or MRI shows no metastasis, staging laparoscopy(SL) still detects tiny peritoneal deposits in 20–30% of patients, making them ineligible for surgery. SL is invasive, requiring general anesthesia and substantial resources. Endoscopic ultrasound (EUS) allows the observation of the bile ducts, pancreas, and abdominal cavity, and EUS-guided fine-needle aspiration (EUS-FNA) is essential for pathological diagnosis. Reports on using EUS to perform peritoneal lavage cytology are currently not available. We hypothesized that combining EUS-FNA with peritoneal lavage (EUS-lavage technique; EUS-LT) could enhance staging accuracy and avoid unnecessary surgical procedures. Methods: Ten ex vivo porcine models underwent EUS-LT. Using a 19G FNA needle, 800 mL saline was instilled into the intraperitoneal cavity and then recovered. Two refinements were introduced sequentially: an ENBD catheter with additional side holes and, subsequently, a side-hole introducer (EndoSheather) that eliminated balloon dilation. The primary endpoint was procedural success. Secondary endpoints included safety, complications, recovered volume, duration of endoscopic procedure, and time required to instill 800 mL. Nonparametric tests compared outcomes across iterations. Results: Ten-model porcine ex vivo model series were included, and all procedures were successful. No device malfunctions or unanticipated technical failures; one minor mucosal injury during saline injection resolved after re-puncture. The average procedure time was 31.1 min. Stepwise refinements shortened procedure and infusion times and increased recovered volume. Recovered volume approached the instilled amount in later cases, indicating efficient performance. Conclusions: In this ten-model ex vivo series, EUS-LT demonstrated technical feasibility and short-term safety. Full article

In citrus cultivation practice, regular monitoring of leaf leaf relative water content (RWC) can effectively guide water management, thereby improving fruit quality and yield. When applying hyperspectral technology to citrus leaf moisture monitoring, the precise quantification of RWC still needs to address issues such as data noise and algorithm adaptability. The noise interference and spectral aliasing in RWC sensitive bands lead to a decrease in the accuracy of moisture inversion in hyperspectral data, and the combined sensitive bands of chlorophyll (LCC) in citrus leaves can affect its estimation accuracy. In order to explore the optimal prediction model for RWC of citrus leaves and accurately control irrigation to improve citrus quality and yield, this study is based on 401–2400 nm spectral data and extracts noise robust features through continuous wavelet transform (CWT) multi-scale decomposition. A high-precision estimation model for citrus leaf RWC is established, and the potential of CWT in RWC quantitative inversion is systematically evaluated. This study is based on the multi-scale analysis characteristics of CWT to probe the time–frequency characteristic patterns associated with RWC and LCC in citrus leaf spectra. Pearson correlation analysis is used to evaluate the effectiveness of features at different decomposition scales, and the successive projections algorithm (SPA) is further used to eliminate band collinearity and extract the optimal sensitive band combination. Finally, based on the selected RWC and LCC-sensitive bands, a high-precision predictive model for citrus leaf RWC was established using partial least squares regression (PLSR). The results revealed that (1) CWT preprocessing markedly boosts the estimation accuracy of RWC and LCC relative to the original spectrum (max improvements: 6% and 3%), proving it enhances spectral sensitivity to these two indices in citrus leaves. (2) Combining CWT and SPA, the resulting predictive model showed higher inversion accuracy than the original spectra. (3) Integrating RWC Scale7 and LCC Scale5-2224/2308 features, the CWT-SPA fusion model showed optimal predictive performance (R² = 0.756, RMSE = 0.0214), confirming the value of multi-scale feature joint modeling. Overall, CWT-SPA coupled with LCC spectral traits can boost the spectral response signal of citrus leaf RWC, enhancing its prediction capability and stability. Full article

Nestmate recognition is the primary defense mechanism maintaining the integrity of eusocial insect colonies. While social parasitism is widespread in Hymenoptera, it is rarely documented in termites, and the behavioral boundaries preventing interspecific infiltration remain poorly understood. Here, we investigated the potential for interspecific integration between two closely related termite species under laboratory conditions. We introduced Reticulitermes labralis workers and reproductives (queens and kings) into orphaned groups of R. aculabialis. We found that host workers exhibited caste-dependent aggression: introduced workers were immediately attacked and eliminated, whereas alien reproductives were partially tolerated. Surviving alien reproductives successfully integrated into host group, receiving allogrooming and trophallactic care from host workers. Crucially, these integrated pairs produced viable eggs and larvae. Molecular analysis confirmed that the brood reared by the host workers were the genetic offspring of the introduced R. labralis pair, demonstrating successful “cuckoo-like” reproduction. These findings reveal that termite colony recognition is sufficiently flexible to permit the acceptance of heterospecific reproductives when native royals are absent. While field evidence remains to be discovered, our results demonstrate that the behavioral and physiological prerequisites for social parasitism exist in termites, supporting the hypothesis that close phylogenetic relatedness (Emery’s rule) facilitates the breach of social barriers. Full article

Cervical cancer remains a significant global health burden, with chemoradioresistance representing a major obstacle to successful treatment. To elucidate the mechanisms underlying this resistance, we established a unique pair of isogenic primary cervical cancer cell lines, AdMer35 and AdMer43, obtained from a patient with squamous cell carcinoma of the cervix before and after radiation therapy. The aim of our study was to characterize the transcriptomic and cellular heterogeneity of these cells. We conducted an in-depth comparative analysis using single-cell RNA sequencing. Analysis of this paired, patient-derived isogenic model suggests that chemoradioresistance can arise through coordinated multilevel cellular adaptations. Resistant AdMer43 cells demonstrated transcriptional reprogramming, with the upregulation of embryonic stemness factors (HOX, POU5F1, SOX2), a shift in extracellular matrix from fibrillar to non-fibrillar collagens, and activation of inflammatory pathways. We identified and characterized critical cell-state dynamics: resistant cells exhibited a remodeled ecosystem with a metabolically reprogrammed senescent-like cell population showing an enhanced pro-tumorigenic communication via EREG, SEMA3C, BMP, and WNT pathways. Furthermore, we identified a progenitor-like cell population with a minimal CNV burden, potentially serving as a reservoir for tumor persistence. These findings offer novel insights for developing targeted strategies to eliminate resistant cell pools and improve cervical cancer outcomes. Full article

Immunotherapy has revolutionized the management of patients with cancer. Immune checkpoint inhibition (ICI) is a promising treatment option that targets the molecular mechanisms that cancer cells exploit to prevent immune-mediated elimination. ICI therapy can cause exceptional long-term tumor remissions, in some cases, even after treatment discontinuation. Despite its success, many patients acquire resistance or fail to respond due to immune escape mechanisms mediated by the tumor and its microenvironment. Pre-existing immunity status of individuals seems to play a fundamental role in immunotherapy response and eventually tumor progression, as it orchestrates tumor-immune interactions. Different immune cell subsets, both in the tumor microenvironment and the peripheral blood, are established mediators that contribute to immune escape in various tumor types. Based on these findings, the elucidation of the mechanisms implicated in the regulation of these immune cells has become a priority for investigators focused on improving the efficacy of ICI. This will be essential for identifying responders as well as for developing novel therapeutic modalities to improve clinical outcomes. Herein, we summarize preclinical and clinical evidence proposing a predictive role of pre-existing immunity for clinical responses to immunotherapies. Full article