A Risk-Based Sensor Management Method for Target Detection in the Presence of Suppressive Jamming

In this paper, a risk-based sensor management method for target detection in the presence of suppressive jamming is proposed, in which available sensors are dynamically scheduled to control the risk in the execution of target detection task. Firstly, the sensor detection models in the absence/ presence of jamming are established, and the calculation method of target detection risk is presented based on the target detection probability. Secondly, the sensor radiation model is established, and the calculation method of radiation risk is given by using hidden Markov filter. Then, a non-myopic objective function is constructed to minimize the sum of detection risk and radiation risk. Furthermore, in order to obtain the optimal solution of objective function quickly, a decision tree search algorithm combining with branch and bound theory and greedy search is proposed. Finally, simulations are conducted, and the results show that the proposed algorithm and sensor management method are effective and advanced compared with the existing algorithms and methods

NICE-SLAM with Adaptive Feature Grids

NICE-SLAM is a dense visual SLAM system that combines the advantages of neural implicit representations and hierarchical grid-based scene representation. However, the hierarchical grid features are densely stored, leading to memory explosion problems when adapting the framework to large scenes. In our project, we present sparse NICE-SLAM, a sparse SLAM system incorporating the idea of Voxel Hashing into NICE-SLAM framework. Instead of initializing feature grids in the whole space, voxel features near the surface are adaptively added and optimized. Experiments demonstrated that compared to NICE-SLAM algorithm, our approach takes much less memory and achieves comparable reconstruction quality on the same datasets. Our implementation is available at https://github.com/zhangganlin/NICE-SLAM-with-Adaptive-Feature-Grids.Comment: Course project of 3D Vision at ETH Zuric

Accessible Robot Control in Mixed Reality

A novel method to control the Spot robot of Boston Dynamics by Hololens 2 is proposed. This method is mainly designed for people with physical disabilities, users can control the robot's movement and robot arm without using their hands. The eye gaze tracking and head motion tracking technologies of Hololens 2 are utilized for sending control commands. The movement of the robot would follow the eye gaze and the robot arm would mimic the pose of the user's head. Through our experiment, our method is comparable with the traditional control method by joystick in both time efficiency and user experience. Demo can be found on our project webpage: https://zhangganlin.github.io/Holo-Spot-Page/index.htmlComment: Course Project of Mixed Reality at ETH Zuric

MRVM-NeRF: Mask-Based Pretraining for Neural Radiance Fields

Most Neural Radiance Fields (NeRFs) have poor generalization ability, limiting their application when representing multiple scenes by a single model. To ameliorate this problem, existing methods simply condition NeRF models on image features, lacking the global understanding and modeling of the entire 3D scene. Inspired by the significant success of mask-based modeling in other research fields, we propose a masked ray and view modeling method for generalizable NeRF (MRVM-NeRF), the first attempt to incorporate mask-based pretraining into 3D implicit representations. Specifically, considering that the core of NeRFs lies in modeling 3D representations along the rays and across the views, we randomly mask a proportion of sampled points along the ray at fine stage by discarding partial information obtained from multi-viewpoints, targeting at predicting the corresponding features produced in the coarse branch. In this way, the learned prior knowledge of 3D scenes during pretraining helps the model generalize better to novel scenarios after finetuning. Extensive experiments demonstrate the superiority of our proposed MRVM-NeRF under various synthetic and real-world settings, both qualitatively and quantitatively. Our empirical studies reveal the effectiveness of our proposed innovative MRVM which is specifically designed for NeRF models

Importance of short-term temporal variability in soil physical properties for soil water modelling under different tillage practices

Acknowledgements This study was part of the Red Soils CZO and MIDST-CZ projects funded by the National Environment Research Council (grants NE/N007611/1 and NE/S009167/1) and the National Sciences Foundation of China (NSFC: 41571130051, 41571130053, 41371235). The 596 experiments in Scotland had financial support from the Rural & Environment Science & Analytical Services Division of the Scottish Government.Peer reviewedPostprin

The paleoclimatic footprint in the soil carbon stock of the Tibetan permafrost region

Data and code availability The authors declare that the majority of the data supporting the findings of this study are available through the links given in the paper. The unpublished data are available from the corresponding author upon request. The new estimate of Tibetan soil carbon stock and R code are available in a persistent repository (https://figshare.com/s/4374f28d880f366eff6d). Acknowledgements This study was supported by the Strategic Priority Research Program (A) of the Chinese Academy of Sciences (XDA20050101), the National Natural Science Foundation of China (41871104), Key Research and Development Programs for Global Change and Adaptation (2017YFA0603604), International Partnership Program of the Chinese Academy of Sciences (131C11KYSB20160061) and the Thousand Youth Talents Plan project in China. Jinzhi Ding acknowledges the General (2017M620922) and the Special Grade (2018T110144) of the Financial Grant from the China Postdoctoral Science Foundation.Peer reviewedPublisher PD

A Simple Modelling Framework for Shallow Subsurface Water Storage and Flow

Water storage and flow in shallow subsurface drives runoff generation, vegetation water use and nutrient cycling. Modelling these processes under non-steady state conditions is challenging, particularly in regions like the subtropics that experience extreme wet and dry periods. At the catchment-scale, physically-based equations (e.g., Richards equation) are impractical due to their complexity, while conceptual models typically rely on steady state assumptions not found in daily hydrological dynamics. We addressed this by developing a simple modelling framework for shallow subsurface water dynamics based on physical relationships and a proxy parameter for the fluxes induced by non-unit hydraulic gradients. We demonstrate its applicability for six generic soil textures and for an Acrisol in subtropical China. Results showed that our new approach represents top soil daily fluxes and storage better than, and as fast as, standard conceptual approaches. Moreover, it was less complex and up to two orders of magnitude faster than simulating Richards equation, making it easy to include in existing hydrological models

Ideas and perspectives: strengthening the biogeosciences in environmental research networks

Many scientific approaches are improving our understanding and management of the rapidly changing environment. Long-term environmental research networks are one approach to advancing local, regional, and global environmental science and education. A remarkable number and wide variety of environmental research networks operate around the world today. These are diverse in funding, infrastructure, motivating questions, scientific strengths, and the sciences that birthed and maintained the networks. Some networks have individual sites that were selected because they had produced invaluable long-term data, while other networks have new sites selected to span ecological gradients. However, all long-term environmental networks share two challenges. Networks must keep pace with scientific advances and interact with both the scientific community and society at large. If networks fall short of successfully addressing these challenges, they risk becoming irrelevant. The objective of this paper is to assert that the biogeosciences offer environmental research networks a number of opportunities to expand scientific impact and public engagement. We explore some of these opportunities with four networks: the International Long Term Ecological Research programs (ILTERs), the Critical Zone Observatories (CZOs), the Earth and Ecological Observatory networks (EONs), and the FLUXNET program of eddy flux sites. While these networks were founded and grown by interdisciplinary scientists, the preponderance of expertise and funding have gravitated activities of ILTERs and EONs toward ecology and biology, CZOs toward the Earth sciences and geology, and FLUXNET toward ecophysiology and micrometeorology. Our point is not to homogenize networks, nor to diminish disciplinary science. Rather, we argue that by more fully incorporating the integration of biology and geology in long-term environmental research networks, scientists can better leverage network assets, keep pace with the ever-changing science of the environment, and engage with larger scientific and public audiences

Protéine Tau, stress oxydatif et mimétiques de glycosaminoglycannes. Des liens pour de nouvelles possibilités thérapeutiques pour la maladie d'Alzheimer.

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How Do Urban Parks Provide Bird Habitats and Birdwatching Service? Evidence from Beijing, China

Parks are an important green infrastructure. Besides other benefits for human and animals, parks provide important bird habitats and accommodate most human-bird interactions in cities. Understanding the complex dynamics among park characteristics, bird habitats and park attractiveness to birdwatchers will inform park designers and managers. However, previous studies often examined factors influencing bird habitats and birdwatching activities separately. To fill this gap, we aim to study the whole picture of “parks, birds and birdwatchers” in Beijing, China for its spatial patterns and possible factors which influence bird habitat areas and birdwatching services. We conducted a three-month bird census in at 159 sites and mapped bird habitat areas in parks of Beijing through the maximum entropy method based on results of the bird survey as well as high-resolution remote sensing data. We derived the number of birdwatching records to describe birdwatching activities from the China Birdwatching Record Center website. We used correlation analysis, regression and analysis of variance to investigate factors that may influence areas of bird habitats and the number of birdwatching records for each park. Our results showed that among the 102 parks, 61 provide habitats to breeding birds with an average of 17 ha, and 26 parks generated a total of 330 birdwatching records. Park size, age, proportion of pavement, landscape connectedness, pavement largest patch index and woodland patch density explained 95% of the variation in habitat areas altogether. Bird habitat area alone explained 65% of the variation in the number of birdwatching records. Furthermore, parks with birdwatching records are significantly larger, older, closer to the city center and more accessible than those have no reported birdwatching. These findings have important implications for park management. While park size or age cannot be easily changed, modifying landscape patterns can increase bird habitats in parks, and improving accessibility may attract more birdwatchers to parks that already have considerable bird habitats