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The forest floor provides an important interface of soil-atmosphere CO2 exchanges but their controls and contributions to the ecosystem-scale carbon budget are uncertain due to measurement limitations. In this study, we deployed eddy covariance systems below- and above-canopy to measure the spatially integrated net forest floor CO2 exchange (NFFE) and the entire net ecosystem CO2 exchange (NEE) at
The atmospheric boundary layer mediates the exchange of energy, matter, and momentum between the land surface and the free troposphere, integrating a range of physical, chemical, and biological processes and is defined as the lowest layer of the atmosphere (ranging from a few meters to 3 km). In this review, we investigate how continuous, automated observations of the atmospheric boundary layer ca
Age-related neurodegenerative diseases are a growing burden to society, and many are sporadic, meaning that the environment, diet and lifestyle play significant roles. Cerebrospinal fluid (CSF)-mediated clearing of brain waste products via perivascular pathways, named the glymphatic system, is receiving increasing interest, as it offers unexplored perspectives on understanding neurodegenerative di
Boreal forests have a large impact on the global greenhouse gas balance and their soils constitute an important carbon (C) reservoir. Mature boreal forests are typically a net CO2 sink, but there are also examples of boreal forests that are persistent CO2 sources. The reasons remain often unknown, presumably due to a lack of understanding of how biotic and abiotic drivers interact to determine the
Current literature show that frequency diverse arrays (FDAs) are able of producing range–angle-dependent and time-variant transmit beampatterns, but the resulting time and range dependencies and their characteristics are still not well understood. This paper examines the FDA transmission model with an emphasis on analyzing the beam auto-scanning characteristics and the equivalence with the MIMO be
Linking individual and stand-level dynamics during forest development reveals a scaling relationship between mean tree size and tree density in forest stands, which integrates forest structure and function. However, the nature of this so-called scaling law and its variation across broad spatial scales remain unquantified, and its linkage with forest demographic processes and carbon dynamics remain
The sparse iterative covariance-based estimation (SPICE) algorithm is promising for hyperparameter-free sparse source location for time-division-multiplexing multiple-input-multiple-output (TDM-MIMO) radar systems, with well-documented merits in resolution enhancement and sidelobe suppression. Regrettably, the method typically requires a large number of iterations to converge, each requiring high-
Globally, northern peatlands are major carbon deposits with important implications for the climate system. It is therefore crucial to understand their spatial occurrence, especially in the context of peatland degradation by land cover change and climate change. This study was aimed at mapping peatlands in the forested landscape of Sweden by modelling soil data against lidar-based terrain indices.
Soil organic matter decomposition and its interactions with climate depend on whether the organic matter is associated with soil minerals. However, data limitations have hindered global-scale analyses of mineral-associated and particulate soil organic carbon pools and their benchmarking in Earth system models used to estimate carbon cycle–climate feedbacks. Here we analyse observationally derived
Decentralized Cloud Storage (DCS) is considered to be the future for sustainable data storage within Web 3.0, in which we will move from a single cloud service provider to creating an ecosystem where anybody could be a cloud storage provider. Currently, the cloud storage market is highly dominated by centralized players like Amazon S3, Google Cloud, Box, etc. Decentralized projects like Storj, Fil
Research connecting text and images has recently seen several breakthroughs, with models like CLIP, DALL•E 2, and Stable Diffusion. However, the connection between text and other visual modalities, such as lidar data, has received less attention, prohibited by the lack of text-lidar datasets. In this work, we propose LidarCLIP, a mapping from automotive point clouds to a pre-existing CLIP embeddin
Acoustic testing is crucial in the aero-engine design process, providing valuable information about the sound field in terms of acoustic modes. The conventional use of a uniform sampling array limits the achievable resolution for a given number of sensors, necessitating the use of a large number of sensors to achieve high-resolution estimates. This limitation may be overcome using a non-uniform se
Childhood stunting is a serious public health concern in Rwanda. Although stunting causes have been documented, we still lack a more in-depth understanding of their local factors at a more detailed geographic level. We cross-sectionally examined 615 height-for-age prevalence observations in the Northern Province of Rwanda, linked with their related covariates, to explore the spatial heterogeneity
Many forms of small-size radars suffer from minor clock oscillations due to crystalline impurities in their internal clocks, causing time-varying clock offsets between the transmitter and the receivers. This offset causes a bias and an increased variance in the positioning of close-range targets, limiting the achievable accuracy well beyond the expected estimation limitations. This performance is
This paper develops an adaptive grid two-dimensional (2-D) direction-of-arrival (DOA) estimation technique employing an integrated dictionary framework. In contrast to using a traditional grid over distinct angles, combined angle information atoms are adopted to construct the dictionary, using a SPICE-based noise power estimate to select the active regions. To compensate for off-grid bias effects,
Post-marketing reports of suspected adverse drug reactions are important for establishing the safety profile of a medicinal product. However, a high influx of reports poses a challenge for regulatory authorities as a delay in identification of previously unknown adverse drug reactions can potentially be harmful to patients. In this study, we use natural language processing (NLP) to predict whether
This study spatially analyzes plant phenology and its variations over time in mainland Spain and the Balearic Islands. To conduct the analysis, a nearly 40-year span time series (1983-2020) was generated by merging NDVI vegetation index values from satellite images sourced from NOAA-AVHRR and MODIS sensors. The phenological variables were calculated using TIMESAT 3.3, which extracted 13 phenometri
Time-domain spectroscopy encompasses a wide range of techniques, such as Fourier-transform infrared, pump-probe, Fourier-transform Raman, and two-dimensional electronic spectroscopies. These methods enable various applications, such as molecule characterization, excited state dynamics studies, or spectral classification. Typically, these techniques rarely use sampling schemes that exploit the prio
Monitoring ecosystems at regional or continental scales is paramount for biodiversity conservation, climate change mitigation, and sustainable land management. Effective monitoring requires satellite imagery with both high spatial resolution and high temporal resolution. However, there is currently no single, freely available data source that fulfills these needs. A seamless fusion of data from th
