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The large-scale detection of greenhouses and rural buildings is important for natural resource surveys and farmland protection. However, in rural and mountainous areas, the resolution and accessibility of remote sensing satellite images from a single source are poor, making it difficult to detect greenhouses and rural buildings effectively and automatically. In this paper, a wide-area greenhouse and rural building (GH-RB) detection dataset is constructed as a benchmark by using high-resolution remote sensing images of Hebei Province, China, collected from the image platform. Then, Efficient Weighted YOLOv8 (EW-YOLOv8) is proposed by using the dataset with unbalanced and small samples of greenhouse and rural buildings, in which the improvement measures are introduced. These include the following: (1) replacing the traditional up-sampler with DySample in the up-sampling part of the neck of the model to recover the lost details after multiple down-sampling operations; (2) replacing the calculation loss function with NWD loss to compensate for the sensitivity of the IoU to the position deviation of small objects; and (3) introducing a weight function named Slide to resolve the data imbalance between easy and difficult samples. The experimental results show that the proposed method can achieve excellent object detection performance on the RSOD dataset compared with state-of-the-art methods, proving the effectiveness of the proposed EW-YOLOv8. The results on the constructed GH-RB dataset show that the proposed method can detect greenhouse and rural buildings quickly and accurately, which could help improve the efficiency of investigating farmland usage and performing natural resource surveys.

Deep learning-based landslide detection in optical remote sensing images has been extensively studied. However, several challenges remain. Over time, factors such as vegetation cover and surface weathering can weaken the distinct characteristics of landslides, leading to blurred boundaries and diminished texture features. Furthermore, obtaining landslide samples is challenging in regions with low landslide frequency. Expanding the acquisition range introduces greater variability in the optical characteristics of the samples. As a result, deep learning models often struggle to achieve accurate landslide identification in these regions. To address these challenges, we propose a multi-scale target attention YOLO model (MSTA-YOLO). First, we introduced a receptive field attention (RFA) module, which initially applies channel attention to emphasize the primary features and then simulates the human visual receptive field using convolutions of varying sizes. This design enhances the model’s feature extraction capability, particularly for complex and multi-scale features. Next, we incorporated the normalized Wasserstein distance (NWD) to refine the loss function, thereby enhancing the model’s learning capacity for detecting small-scale landslides. Finally, we streamlined the model by removing redundant structures, achieving a more efficient architecture compared to state-of-the-art YOLO models. Experimental results demonstrated that our proposed MSTA-YOLO outperformed other compared methods in landslide detection and is particularly suitable for wide-area landslide monitoring.

The upper tropospheric water vapor is a key component of Earth's climate. Understanding variations in upper tropospheric water vapor and identifying its influencing factors is crucial for enhancing our comprehension of global climate change. While many studies have shown the impact of El Niño-Southern Oscillation (ENSO) and global warming on water vapor, how they affect the upper tropospheric water vapor remains unclear. Long-term, high-precision ERA5 specific humidity data from the European Centre for Medium-Range Weather Forecasts (ECMWF) provided the data foundation for this study. On this basis, we successfully obtained the patterns of global warming (Independent Component 1, IC1) and ENSO (Independent Component 2, IC2) by employing the strategy of independent component analysis (ICA) combined with non-parametric optimal dimension selection to investigate the upper tropospheric water vapor variations and responses to ENSO and global warming. The results indicate that global warming and ENSO are the primary factors contributing to water vapor variations in the upper troposphere, achieving the significant correlations of 0.87 and 0.61 with water vapor anomalies respectively. Together, they account for 86% of the global interannual variations in water vapor. Consistent with previous studies, our findings also find positive anomalies in upper tropospheric water vapor during El Niño years and negative anomalies during La Niña years. Moreover, the influence extent of ENSO on upper tropospheric water vapor varies with the changing seasons.

Introduction Gastrointestinal (GI) cancers account for over a quarter of all cancer-related deaths in the United States; however, the latest trends in their prevalence remain unclear. Methods Data on GI cancers were obtained from the Global Burden of Disease Study 2021. Age-standardized incidence rates (ASIR) and age-standardized mortality rates (ASMR) were estimated across various states, sexes, ages, and risk factors, and annual percentage changes were calculated. Results From 2000 to 2021, liver cancer exhibited the greatest increase in both the ASIR and the ASMR, followed by pancreatic cancer. In contrast, stomach cancer showed the greatest decline, followed by colorectal cancer, esophageal cancer, and biliary tract cancer. Most GI cancers predominantly affect men and tend toward a younger age of onset. Geographic disparities exist in the burden of GI cancers and their risk factors. For esophageal, stomach, and colorectal cancers, mortality rates linked to diet and smoking decreased, whereas alcohol-related mortality increased in several states, especially West Virginia. Hepatitis C remains the leading cause of liver cancer, with intravenous drug use as the primary risk factor. Non-alcoholic steatohepatitis (NASH) is the fastest-growing cause of liver cancer, followed by excessive alcohol use. Mortality rates for pancreatic cancer due to high body-mass index and high fasting plasma glucose have increased across states and age groups. Discussion The epidemiological trends of GI cancers in the U.S. have shifted substantially. States need to implement targeted policies that address specific populations and risk factors for each cancer type.

For large cross-section tunnel in horizontal layered rock mass, blasting excavation often causes serious overbreak and underbreak. In this study, blasting excavation tests of tunnel upper face were conducted, blast-induced excavation damage and the influence mechanisms of weak beddings and joints were analyzed based on the Panlongshan tunnel. In order to achieve fine excavation, the cut mode of “center holes and four-wedge cutting holes”, the blasthole pattern of “empty holes, long holes, short holes and additional relief holes”, the maximum single-hole charge and the air-deck charge structure were proposed. Compared with the damage characteristics, overbreak and underbreak, and deformations of surrounding rock before and after optimization, the latter was better in tunnel contour formation and surrounding rock stability. The results show that after optimization, the large-area separation of vault rock mass is solved, the step-like overbreak of spandrel rock mass is reduced and the large-size rock block and underbreak are avoided. The maximum linear overbreak of vault, spandrel, and haunch surrounding rock is decreased by 42.3%, 53.7% and 45.1%, respectively. The underbreak at the bottom of the upper face is reduced from − 111.5 to − 16.5 cm. The average overbreak area is decreased by 61.1%. The surrounding rock displacement after optimization finally converges to the smaller value. The arch crown settlement and the horizontal convergence of haunch are reduced by about 21.6% and 18.3%, respectively. Furthermore, from the completion of blasting excavation to the stabilization of surrounding rock, it takes less time by using the optimized blasting scheme.

Heterosigma akashiwo is one of the main toxin-producing species that is globally known for frequently forming fish-killing harmful algal blooms. In this study, a novel technique referred to as recombinase polymerase amplification (RPA) combined with lateral flow dipstick (LFD) (RPA-LFD) was established for detection of H. akashiwo. RPA primers and an LFD probe were designed based on the sequence of the large ribosomal subunit (LSU rDNA) D1-D2 region of H. akashiwo. RAP/RPA-LFD was experimentally verified to be specific, displaying no cross-reaction with other control microalgae. It was demonstrated that the optimal amplification temperature and time for RPA were 41 °C and 40 min. The LFD assay was completed in only 5–10 min to analyze RPA products, and RPA results could be visualized directly. RPA-LFD was 100 times more sensitive than PCR, displaying a detection limit of 3.37 × 10−4 ng µL−1 for genomic DNA of H. akashiwo and 1.28 × 102 copies µL−1 for the recombinant plasmid containing the inserted LSU rDNA D1-D2 region of H. akashiwo. In this study, RPA-LFD’s detection limit was 1 cell mL−1, which is feasible to apply in the field test. Thus, the established RPA-LFD targeting the detection of H. akashiwo is characterized by simplicity, rapidity, sensitivity, specificity, and visualization.

Quantum random number generators (QRNGs) produce true random numbers with significant applications in quantum communication and numerical computation, where high-rate random number generation is critical. Photon detection-based quantum random-number generation methods have been widely studied. However, the generation rate is constrained by the count rate of single-photon detectors. This study proposes an efficient method that enhances random number generation by simultaneously detecting photons in temporal and spatial dimensions. We achieved simultaneous detection of photon arrival time and spatial position by employing a laboratory-developed 5 × 5 single-photon detector array and a high-saturation count rate multichannel time-to-digital converter. The maximum efficiency of the method was 21.1 bits per event and it maintained a consistent efficiency of 17.6 bits per event while achieving a random number generation rate of 2.1 Gbps. The proposed QRNG approach offers a promising pathway for significantly increasing random number generation rates, benefiting applications that require secure and high-speed random number sequences.

The deep-sea mining hose is a crucial component of the underwater lifting and transport system utilized in deep-sea mining operations. The marine environmental loading and the dynamic coupling between the hose, the subsea mining vehicle, and the relay bin have a complex effect on the mechanical properties of the hose. This study employs the vector form intrinsic finite element method to develop a MATLAB-based three-dimensional dynamic response simulation program for analyzing the hose’s dynamic response characteristics under varying current velocities, buoyancy module quantities, relay bin resonance conditions, and mining vehicle motions with double-hose systems, etc. The findings demonstrate that the vector form intrinsic finite element method effectively simulates the dynamic behavior of the hose structure. It is necessary to analyze the dynamic response of the hose’s multiple factors.

Circular RNAs (circRNAs) have been implicated in tumorigenesis and progression of various cancers. However, the underlying mechanisms of circRNAs in hepatocellular carcinoma (HCC) have not been fully elucidated. Herein, a new oncogenic circRNA, hsa_circ_0070039 (circNUP54), was identified to be significantly upregulated in HCC through circRNA sequencing. As verified in 68 HCC samples, circNUP54 overexpression was correlated with aggressive cancerous behaviors and poor outcomes. Moreover, the function experiments showed that knockdown of circNUP54 inhibited the malignant progression of HCC in vitro and in vivo, whereas overexpression of circNUP54 had the opposite role. Mechanistic investigations carried out by RNA pull-down, RNA immunoprecipitation, and immunofluorescence revealed that circNUP54 interacted with the RNA-binding protein Hu-antigen R (HuR) and promoted its cytoplasmic export. The cytoplasmic accumulation of HuR stabilized the downstream BIRC3 mRNA through its binding to the 3′ UTR region. Consequently, the encoded protein of BIRC3, cellular inhibitor of apoptosis 2 (cIAP2), proceeded to activate the NF-κB signal pathway and ultimately contributed to HCC progression. In addition, depletion of BIRC3 rescued the pro-tumorigenic effect of circNUP54 on HCC cells. Overall, this study demonstrated that circNUP54 facilitates HCC progression via regulating the HuR/BIRC3/NF-κB axis, which may serve as a promising therapeutic target for HCC treatment.

Background Forkhead-box protein P1 (FOXP1) has been proposed to have both oncogenic and tumor-suppressive properties, depending on tumor heterogeneity. However, the role of FOXP1 in intrahepatic cholangiocarcinoma (ICC) has not been previously reported. Methods Immunohistochemistry was performed to detect FOXP1 expression in ICC and normal liver tissues. The relationship between FOXP1 levels and the clinicopathological characteristics of patients with ICC was evaluated. Finally, in vitro and in vivo experiments were conducted to examine the regulatory role of FOXP1 in ICC cells. Results FOXP1 was significantly downregulated in the ICC compared to their peritumoral tissues ( p  < 0.01). The positive rates of FOXP1 were significantly lower in patients with poor differentiation, lymph node metastasis, invasion into surrounding organs, and advanced stages ( p  < 0.05). Notably, patients with FOXP1 positivity had better outcomes (overall survival) than those with FOXP1 negativity ( p  < 0.05), as revealed by Kaplan–Meier survival analysis. Moreover, Cox multivariate analysis showed that negative FOXP1 expression, advanced TNM stages, invasion, and lymph node metastasis were independent prognostic risk factors in patients with ICC. Lastly, overexpression of FOXP1 inhibited the proliferation, migration, and invasion of ICC cells and promoted apoptosis, whereas knockdown of FOXP1 had the opposite role. Conclusion Our findings suggest that FOXP1 may serve as a novel outcome predictor for ICC as well as a tumor suppressor that may contribute to cancer treatment.