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Python for Natural Language Processing : Programming with NumPy, scikit-learn, Keras, and PyTorch: Third Edition

Since the last edition of this book (2014), progress has been astonishing in all areas of Natural Language Processing, with recent achievements in Text Generation that spurred a media interest going beyond the traditional academic circles. Text Processing has meanwhile become a mainstream industrial tool that is used, to various extents, by countless companies. As such, a revision of this book was

Spatial–Temporal Assessment of Eco-Environment Quality with a New Comprehensive Remote Sensing Ecological Index (CRSEI) Based on Quaternion Copula Function

The traditional remote sensing ecological index (RSEI), based on principal component analysis (PCA) to integrate four evaluation indexes: greenness (NDVI), humidity (WET), dryness (NDBSI), and heat (LST), is insufficient to comprehensively consider the influence of each eco-environment evaluation index on eco-environment quality (EEQ). In this research, a new comprehensive remote sensing ecologica

Detection of the 2022 extreme drought over the Yangtze River basin using two satellite-gauge precipitation products

In 2022, the Yangtze River Basin in China experienced an unprecedented extreme drought, induced by high temperatures and precipitation deficits. Accurate monitoring of such extreme drought events is vitally significant for disaster mitigation under global warming. This study evaluated the effectiveness of two satellite-based precipitation products: the latest Integrated Multi-satellitE Retrievals

Impacts of Spartina alterniflora invasion on coastal carbon cycling within a native Phragmites australis-dominated wetland

Despite its significance for climate adaptation, the impact of non-native Spartina alterniflora on coastal blue carbon cycling remains unclear. While it is generally reported that S. alterniflora invasion increases the soil organic carbon (SOC) stock along China's coastlines from tropical to subtropical climate zones, some cases, such as the Jiuduansha wetland in the Yangtze River estuary, show a

Improving crop yield prediction in Sweden using satellite remote sensing and the ecosystem model LPJ-GUESS

Meeting the food demand of a growing global population with limited agricultural resources is one of the greatest challenges of the 21st century. Crop yield is highly sensitive to weather variability and climate extremes, which are becoming more frequent due to climate change. Accurate regional yield prediction is essential for helping farmers adapt, ensuring food security, and strengthening the r

Hiking Trails Facilitate the Spread of a Native High-Arctic Species

High-Arctic environments are facing an elevated pace of warming and increasing human activities, making them more susceptible to the introduction and spread of alien species. We investigated the role of human disturbance in facilitating the spread of a native plant (Papaver dahlianum) in a high-Arctic natural environment close to Isfjord Radio station and along adjacent hiking trails at Kapp Linné

Advancing hydrological modeling through multivariate calibration of multi-layer soil moisture dynamics

Study region: The Meichuan Basin, China Study focus: Soil water processes are critical in hydrological modeling, yet most studies focus on surface moisture due to data limitations, which hampers accurate simulations of root zone soil moisture dynamics. To address this gap, we developed three calibration schemes: M1 and M2, two benchmarks that rely solely on traditional streamflow data and incorpor

Assessing recovery time of ecosystems in China : insights into flash drought impacts on gross primary productivity

Recovery time, referring to the duration that an ecosystem needs to return to its pre-drought condition, is a fundamental indicator of ecological resilience. Recently, flash droughts – characterised by rapid onset and development – have gained increasing attention. Nevertheless, the spatiotemporal patterns in gross primary productivity (GPP) recovery time and the factors influencing it remain larg

Intelligent Monitoring Applications of Landslide Disaster Knowledge Graphs Based on ChatGLM2

Over the years, the field of landslide disaster research has amassed a wealth of data and specialized knowledge. However, these resources originate from a wide array of sources and often feature complex data structures, highlighting a persistent lack of methods to integrate multi-source, heterogeneous data. Traditional landslide monitoring methods typically focus on singular monitoring targets and

Linking Named Entities in Diderot's Encyclopédie to Wikidata

Diderot's Encyclopédie is a reference work from XVIIIth century in Europe that aimed at collecting the knowledge of its era. Wikipedia has the same ambition with a much greater scope. However, the lack of digital connection between the two encyclopedias may hinder their comparison and the study of how knowledge has evolved. A key element of Wikipedia is Wikidata that backs the articles with a grap

The Importance of Impoundment interception in Simulating Riverine Dissolved Organic Carbon

Modeling of riverine dissolved organic carbon (DOC) dynamics is of great importance for the global carbon budget. Impoundment interception changes the travel time of water and DOC from upslope contributing areas, exerting substantial influence on riverine DOC dynamics in the catchments with many impoundments. However, the impact of impoundment interception representation on riverine DOC modeling h

The Impact of Urbanization-Induced Land Use Change on Land Surface Temperature

Rapid urbanization can change local climate by increasing land surface temperature (LST), particularly in metropolitan regions. This study uses two decades of remote sensing data to investigate how urbanization-induced changes in land use/land cover (LULC) affect LST in the Beijing Region, China. By focusing on the key issue of LST and its contributing variables through buffer zones, we determined

Warming response of peatland CO2 sink is sensitive to seasonality in warming trends

Peatlands have acted as net CO2 sinks over millennia, exerting a global climate cooling effect. Rapid warming at northern latitudes, where peatlands are abundant, can disturb their CO2 sink function. Here we show that sensitivity of peatland net CO2 exchange to warming changes in sign and magnitude across seasons, resulting in complex net CO2 sink responses. We use multiannual net CO2 exchange obs

Deep learning model for drought prediction based on large-scale spatial causal network in the Yangtze River Basin

Developing accurate large-scale drought prediction models is challenging due to the complex temporal and spatial correlation patterns that govern drought dynamics, as well as the compounding effects of anthropogenic activities and global climate change. Although recent advances in deep learning have yielded effective drought prediction models, many struggle to fully capture the heterogeneous spati

Non‐stationary forest responses to hotter droughts: a temporal perspective considering the role of past legacies

Global change is altering forests worldwide, with multiple consequences for ecosystem functioning. Temporal changes in climate, and extreme, compounded weather events like hotter droughts are affecting the demography, composition and function of forests, leading to a highly uncertain future. To accurately predict future forest responses to hotter droughts, we highlight the need for considering a b

Spatial Downscaling of Gridded Soil Moisture Products Using Optical and Thermal Satellite Data: Effect of Using Different Vegetation Indices

Satellite remote sensing offers global-scale soil moisture (SM) estimation to assess water and energy cycles. However, the coarse resolution of SM products from microwave remote sensing is unsuitable for fine-scale analysis. This study explored spatial downscaling methods to refine the 0.25° ESA CCI SM product to a 1-km resolution, utilizing optical and thermal remote sensing data, including the n

Discriminating Against Unrealistic Interpolations in Generative Adversarial Networks

Interpolations in the latent space of deep generative models is one of the standard tools to synthesize semantically meaningful mixtures of generated samples. As the generator function is non-linear, commonly used linear interpolations in the latent space do not yield the shortest paths in the sample space, resulting in non-smooth interpolations. Recent work has therefore equipped the latent space

Tipping point-induced abrupt shifts in East Asian hydroclimate since the Last Glacial Maximum

Multiple tipping points in the Earth system could be triggered when global warming exceeds specific thresholds. However, the degree of their impact on the East Asian hydroclimate remains uncertain due to the lack of quantitative rainfall records. Here we present an ensemble reconstruction of East Asian summer monsoon (EASM) rainfall since the Last Glacial Maximum (LGM) using nine statistical and m