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Massive MIMO is one of the leading technologies for connecting very large numbers of energy-constrained nodes, as it offers both extensive spatial multiplexing and large array gain. A challenge resides in partitioning the many nodes into groups that can communicate simultaneously such that the mutual interference is minimized. Here we propose node partitioning strategies that do not require full c

The Petit Larousse illustré is a French dictionary first published in 1905. Its division in two main parts on language and on history and geography corresponds to a major milestone in French lexicography as well as a repository of general knowledge from this period. Although the value of many entries from 1905 remains intact, some descriptions now have a dimension that is more historical than cont

Efforts to develop effective climate strategies necessitate a better understanding of the relationship between terrestrial water and carbon cycles. Water use efficiency (WUE) has been often used to characterize this relationship, while the role of transpiration (T) in the variation of ecosystem WUE has been less investigated. Here, we partitioned WUEET (the ratio of gross primary productivity (GPP

Scarce water resources present a major hindrance to ensuring food security. Crop water productivity (WP), embraced as one of the Sustainable Development Goals (SDGs), is playing an integral role in the performance-based evaluation of agricultural systems and securing sustainable food production. This study aims at developing a cloud-based model within the Google Earth Engine (GEE) based on Landsat

Nonlinear group delay signals with frequency-varying characteristics are common in a wide variety of fields, for instance, structural health monitoring and fault diagnosis. For such applications, the signal is composed of multiple modes, where each mode may overlap in the frequency-domain. The resulting decomposition and forming of time-frequency representations of the nonlinear group delay modes

The CORDEX Flagship Pilot Study ELVIC (climate Extremes in the Lake VICtoria basin) was recently established to investigate how extreme weather events will evolve in this region of the world and to provide improved information for the climate impact community. Here we assess the added value of the convection-permitting scale simulations on the representation of moist convective systems over and ar

In this paper we address absolute camera pose estimation. An efficient (and standard) way to solve this problem, is to use sparse keypoint correspondences. In many cases point features are not available, or are unstable over time and viewing conditions. We propose a framework based on silhouettes of quadric surfaces, with special emphasis on cylinders. We provide mathematical analysis of the probl

In this work, we introduce a novel approach for determining a joint sparse spectrum from several non-uniformly sampled data sets, where each data set is assumed to have its own, and only partially known, sampling times. The problem originates in paleoclimatology, where each data point derives from a separate ice core measurement, resulting in that even though all measurements reflect the same peri

Interannual variability of the terrestrial ecosystem carbon sink is substantially regulated by various environmental variables and highly dominates the interannual variation of atmospheric carbon dioxide (CO2) concentrations. Thus, it is necessary to determine dominating factors affecting the interannual variability of the carbon sink to improve our capability of predicting future terrestrial carb

Remote sensing observations of variables related to vegetation at microwave and optical/infrared wavelengths are presented over three regions in Europe in the Iberian peninsula, northern Finland and central Europe. They include the instrumented sites of Las Majadas, Sodankyla and Reusel. The final goal is to better constrain land carbon cycle models using the complementarities of vegetation optica

Study region: Two hyper-arid regions (Atbara and Kassala stations) in Sudan. Study focus: The study aims to evaluate the potential of the D-vine Copula-based quantile regression (DVQR) model for estimating daily ETo during 2000–2015 based on various input structures. Further, the DVQR model was compared with Multivariate Linear quantile regression (MLQR), Bayesians Model Averaging quantile regress

Agroecosystem photosynthesis is key to coping with global climate change. In farmland where human activities are highly involved, the interaction between environmental factors and their influences on gross primary productivity (GPP) are insufficiently understood. Particularly, the irrigation and mulching in water-saving agriculture can alter the crop responses to environmental change. Based on edd

Efforts to develop effective climate mitigation strategies for agriculture require methods to estimate nitrous oxide (N2O) emissions from soil. Process-based biogeochemical models have been often used for field- and large-scale estimates, while the sensitivity and uncertainty of model applications to incubation experiments are less investigated. In this study, a process-oriented model (CoupModel)

In this work, we study self-supervised representation learning for 3D skeleton-based action recognition. We extend Bootstrap Your Own Latent (BYOL) for representation learning on skeleton sequence data and propose a new data augmentation strategy including two asymmetric transformation pipelines. We also introduce a multi-viewpoint sampling method that leverages multiple viewing angles of the same

Understanding influence of vegetation on past temperature changes in the Arctic region would help isolate uncertainty and build understanding of its broader climate system, with implications for paleoclimate reconstructions and future climate change. Using an Earth system model EC-Earth, we conduct a series of simulations to investigate the impact of vegetation-climate feedback on the Arctic clima

Variability on centennial to multi-centennial timescales is mentioned as a feature in reconstructions of the Holocene climate. As more long transient model simulations with complex climate models become available and efforts have been made to compile large proxy databases, there is now a unique opportunity to study multi-centennial variability with greater detail and a large amount of data than ea

The management and conservation of lakes should be conducted in the context of catchments because lakes collect water and materials from their upstream catchments. Thus, the datasets of catchment-level characteristics are essential for limnology studies. Lakes are widely spread on the Tibetan Plateau (TP), with a total lake area exceeding 50000km2, accounting for more than half of the total lake a

Crop production security is an essential guarantee for the prosperity of country and the well-being of people. In the context of frequent occurrence of extreme weather events, how to comprehensively evaluate the risk of multiple hazards and quantitatively describe spatial differences will be one of the significant topics in agricultural disaster mitigation. In this study, based on the gridded mete