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Despite the successes in the use of artificial intelligence systems for image analysis, in certain critical applications, the final decision-making should remain with the human operator. To facilitate the working conditions of an unmanned aerial vehicle (UAV) pilot during prolonged missions, an auxiliary narrow-angle video camera is installed on board the UAV. This camera can be positioned indepen
We prove the first hardness results against efficient proof search by quantum algorithms. We show that under Learning with Errors (LWE), the standard lattice-based cryptographic assumption, no quantum algorithm can weakly automate TC0-Frege. This extends the line of results of Krajíček and Pudlák (Information and Computation, 1998), Bonet, Pitassi, and Raz (FOCS, 1997), and Bonet, Domingo, Gavaldà
Atmospheric trace gas measurements can be used to independently assess national greenhouse gas inventories through inverse modeling. Atmospheric nitrous oxide (N2O) measurements made in the United Kingdom (UK) and Republic of Ireland are used to derive monthly N2O emissions for 2013–2022 using two different inverse methods. We find mean UK emissions of 90.5 ± 23.0 (1σ) and 111.7 ± 32.1 (1σ) Gg N2O
This paper is concerned with the feasibility of the power flow in DC power grids with constant power loads. We introduce the notion of distance to infeasibility as a voltage stability index and robustness measure for power flow feasibility. In particular, we study the p-norm distance to infeasibility in the domain of the constant power loads, and show how this distance may be expressed as a mathem
The CryoGrid community model is a flexible toolbox for simulating the ground thermal regime and the ice-water balance for permafrost and glaciers, extending a well-established suite of permafrost models (CryoGrid 1, 2, and 3). The CryoGrid community model can accommodate a wide variety of application scenarios, which is achieved by fully modular structures through object-oriented programming. Diff
Ground-level fine particulate matter (PM2.5) and ozone (O3) are air pollutants that can pose severe health risks. Surface PM2.5 and O3 concentrations can be monitored from satellites, but most retrieval methods retrieve PM2.5 or O3 separately and disregard the shared information between the two air pollutants, for example due to common emission sources. Using surface observations across China span
Accurate and timely mapping of inundation extents during flood periods is essential for disaster evaluation and development of rescue strategies. With unique advantages over the optical sensors (e.g., little effect of clouds, and observations at day and night), Synthetic aperture radar (SAR) sensors provide an important data source for mapping inundation, particularly during flood periods. Freely
In this paper we investigate simultaneous radial distortion calibration and motion estimation for vehicles travelling parallel to planar surfaces. This is done by estimating the inter-image homography between two poses, as well as the distortion parameter. Radial distortion correction is often performed as a pre-calibration step; however, accurately estimating the distortion profile without specia
We apply the statistical sparse jump model, a recently developed, interpretable and robust regime-switching model, to infer key features that drive the return dynamics of the largest cryptocurrencies. The algorithm jointly performs feature selection, parameter estimation, and state classification. Our large set of candidate features are based on cryptocurrency, sentiment and financial market-based
Tropical cloud forests are characterized by abundant and biodiverse mosses which grow epiphytically as well as on the ground. Nitrogen (N)-fixing cyanobacteria live in association with most mosses, and contribute greatly to the N pool via biological nitrogen fixation (BNF). However, the availability of nutrients, especially N and phosphorus (P), can influence BNF rates drastically. To evaluate the
Remote sensing is an effective means for lake water level monitoring on the Tibetan Plateau (TP). The purpose of this study is to estimate water levels of lakes on the TP using the Global Ecosystem Dynamics Investigation (GEDI) and Cloud and Land Elevation Satellite-2 (ICESat-2), evaluate the performance of ICESat-2 and GEDI in estimating water levels, and analyze the differences of water level ob
Selection of the number and which of multisource precipitation datasets is crucially important for precipitation fusion. Considering the effects of different inputs, this study proposes a new framework based on the Bayesian model averaging (BMA) algorithm to integrate precipitation information from gauge-based analysis CPC, reanalysis-derived dataset ERA5, and satellite-retrieval products IMERG-E
Clouds are essential elements within Earth's atmosphere, posing a challenge for cloud-resolving models in understanding the creation of new cloud ice particles from existing ice and liquid phases. Such ice initiation determines cloud microphysical and radiative properties, influencing cloud phase, precipitation and cloud extent/properties. To address this challenge effectively, it proves beneficia
Glacio-hydrological modeling is a key task for assessing the influence of snow and glaciers on water resources, essential for water resources management. The present study aims to enhance a conceptual hydrological model (namely Glacial Snow Melt (GSM)) by data-driven and swarm computing for enhancing the accuracy of rainfall runoff prediction. The proposed framework combines the conceptual hydrolo
We investigate the problem of risk averse robot path planning using the deep reinforcement learning and distributionally robust optimization perspectives. Our problem formulation involves modelling the robot as a stochastic linear dynamical system, assuming that a collection of process noise samples is available. We cast the risk averse motion planning problem as a Markov decision process and prop
Despite the fact that the response of tropical hydroclimate to North Atlantic cooling events during the Heinrich Stadial 1 (HS1) has been extensively studied in African, South American and Indonesia, the nature of such responses remains debated. Here we investigate the tropical hydroclimate pattern over the Indo-Asian-Australian monsoon region during the HS1 by integrating hydroclimatic records, a
Modern embedded software includes complex functionalities and routines, often implemented by splitting the code across different tasks. Such tasks communicate their partial computations to their successors, forming a task chain. Traditionally, this architecture relies on the assumption of hard deadlines and timely communication. However, in actual implementations, tasks may miss their deadlines, t
The tropical Pacific Ocean plays a significant role in climate change, and the El Niño-Southern Oscillation (ENSO) is considered to be closely related to extreme climate phenomenon worldwide. However, the evolution of the ENSO-like patterns in the tropical Pacific during the Pleistocene glacial cycles remains controversial. In this study, we present geochemical indices and a transient model simula
Vegetation gross primary production (GPP) is the largest terrestrial carbon flux and plays an important role in regulating the carbon sink. Current terrestrial ecosystem models (TEMs) are indispensable tools for evaluating and predicting GPP. However, to which degree the TEMs can capture the interannual variability (IAV) of GPP remains unclear. With large data sets of remote sensing, in situ obser
