Detecting changes using bitemporal remote sensing imagery is vital to understand the dynamics of land surface. Existing change detection models based on deep learning suffer from problem scale variation and pseudochange due their insufficient multilevel aggregation inadequate capability feature representation, which limits accuracy. This study proposes a densely attentive refinement network (DARNet) improve very-high-resolution images. DARNet U-shape encoder–decoder architecture with...

To explore imaging biomarkers that can be used for diagnosis and prediction of pathologic stage in non-small cell lung cancer (NSCLC) using multiple machine learning algorithms based on CT image feature analysis.Patients with IA to IV NSCLC were included, the whole dataset was divided into training testing sets an external validation set. tackle imbalanced datasets NSCLC, we generated a new achieved equilibrium class distribution by SMOTE algorithm. The randomly split up training/testing We...

To explore the potential relationship between leading vehicle and following during car-following, we proposed a novel car-following model combining convolutional neural network (CNN) with long short-term memory (LSTM) network. Firstly, 400 periods were extracted from natural driving database OpenACC experiment database. Then, developed CNN-LSTM model, CNN is employed to analyze vehicle's dynamic parameters extract features of behavior generate feature vector. The LSTM adopted save vector...

Vegetation phenology is a sensitive indicator that reflects the vegetation–atmosphere interactions and vegetation processes under global atmospheric changes. Fast-developing remote sensing technologies monitor land surface at high spatial temporal resolutions have been widely used in retrieval analysis large scale. While researchers developed many retrieving methods based on data, relationships differences among are unclear, there lack of evaluation comparison with field recoding data. In...

Spiking neural P systems (SN systems) are a class of distributed parallel computing devices inspired from the way neurons communicate by means spikes. In most applications SN systems, synchronization plays key role which execution rule is completed in exactly one time unit (one step). However, such does not coincide with biological fact: nervous times spiking rules cannot be known exactly. Therefore, "realistic" system called time-free were proposed, where precise removed. this paper, we...

Counting the trees in a given area or city is meaningful when making decisions for government policies and administration, including international afforestation effort (i.e., Trillion Trees Campaign). Determining individual on large scale poses significant challenges, especially subtropical tropical areas, because of their diverse crown characteristics. Using very high-spatial-resolution images, we can see tree crowns clearly. In this study, counted population number mega Guangzhou, used an...

Both of the surface topographical features and distribution biochemical cues can influence cell-substrate interactions thereby tissue regeneration in vivo. However, they have not been combined simultaneously onto a biodegradable scaffold to demonstrate synergistic role so far. In this study, proof-of-concept study is performed prepare micropatterns peptide gradient on inner wall poly (D,L-lactide-co-caprolactone) (PLCL) guidance conduit its advantages peripheral nerve After linear...

Accurate building footprint polygons provide essential data for a wide range of urban applications. While deep learning models have been proposed to extract pixel-based areas from remote sensing imagery, the direct vectorization maps often leads with irregular shapes that are inconsistent real boundaries, making it difficult use them in geospatial analysis. In this study, we novel learning-based framework automated extraction (DLEBFP) very high-resolution aerial imagery by combining...

Abstract Background To further clarify the acne profile of Chinese adult women, we included 1,156,703 women. An artificial intelligence algorithm was used to analyze images taken by high‐resolution mobile phones explore levels in Method In this study, assessed severity evaluating patients' selfies through a smartphone application. Furthermore, gathered basic user information questionnaire, including details such as age, gender, skin sensitivity, and dietary habits. Results This study showed...

In this paper, three antibioadhering materials with quaternary phosphonium salt-modified polyamidoxime (PAO-QPS) for uranium extraction from seawater were prepared using commercial polyacrylonitrile fiber as the base material by ion-exchange method. Infrared spectroscopy and thermogravimetric analysis used to verify correctness of structure test thermal stability synthetic materials. Scanning electron microscopy was analyze microscopic appearance surface. X-ray photoelectron determine...

A widely adopted approach in the field of adsorbent preparation for uranium extraction involves grafting acrylonitrile onto inert polymer substrates, followed by amidoximation.

In the face of trend consumption downgrading, purchasing decisions middle class regarding real estate have undergone new changes. Existing literature on housing market and behavior under downgrading suggests that power has generally decreased, with many unable to bear costs mortgage loans other housing-related financial burdens. As a result, number people in future may decrease. Based existing research practical needs, this paper summarizes trends previous studies through review, pointing...

This study systematically explores the impact mechanism of social media platforms on construction networks among middle class, focusing how reshape path capital accumulation, strengthen class identity boundaries, and regulate cross-group interaction patterns. Based framework theory mediatization theory, proposes a "platform-mediated segmentation" model, revealing that dynamically reconstructs structure through synergy algorithmic logic user behavior. Using mixed research structural equation...

Abstract Atmospheric chemistry transport models have been extensively applied in aerosol forecasts over recent decades, whereas they are facing challenges from uncertainties emission rates, meteorological data, and over-simplified chemical parameterizations. Here, we developed a spatial-temporal deep learning framework, named PPN (Pollution-Predicting Net for PM 2.5 ), to accurately efficiently predict regional concentrations. It has an encoder-decoder architecture combines the preceding...

The combination therapy of platinum-based chemotherapy and PD-L1 inhibitors but not the single anti-PD-L1 has significantly improved prognosis patients with small-cell lung cancer (SCLC).However, synergistic mechanism been fully elucidated.In this work, we identified a positive correlation between expression pyroptosis-related proteins Gasdermin E (GSDME) survival rates SCLC.Importantly, it was shown that human SCLC cell lines high GSDME showed more sensitivity to cisplatin, as well...

Tissue P system is a class of parallel and distributed model; feature traditional tissue that the execution time certain biological processes very sensitive to environmental factors might be hard control. In this work, we construct family systems works independently from values associated with times rules. Furthermore, present time-free efficient solution multidimensional 0-1 knapsack problem by timed recognizer systems.

Abstract In the context of China's clean air policy, meteorological impacts on improved particulate matter (PM 2.5 ) quality during 2016–2019 are investigated based a four‐year high‐resolution atmospheric composition reanalysis data‐set, which has been produced by Joint Data Assimilation System to resolve long‐term fine‐scale variability over China. The assimilates surface observations using Weather Research and Forecasting model coupled with Chemistry an ensemble‐based assimilation...

Vegetation phenology plays a key role in influencing ecosystem processes and biosphere-atmosphere feedbacks. Digital cameras such as PhenoCam that monitor vegetation canopies near real-time provide continuous images record phenological environmental changes. There is need to develop methods for automated effective detection of dynamics from images. Here we developed method predict leaf deciduous broadleaf forests individual using deep learning approaches. We tested four convolutional neural...