Traditional Float Charges: are They Suited to Stationary Antimony-free Lead Acid Batteries?

International audienc

Multi-UAV trajectory planning problem using the difference of convex function programming

The trajectory planning problem for a swarm of multiple UAVs is known as a challenging nonconvex optimization problem, particularly due to a large number of collision avoidance constraints required for individual pairs of UAVs in the swarm. In this paper, we tackle this nonconvexity by leveraging the difference of convex function (DC) programming. We introduce the slack variables to relax and reformulate the collision avoidance conditions and employ the penalty function term to equivalently convert the problem into a DC form. Consequently, we construct a penalty DC algorithm in which we sequentially solve a set of convex optimization problems obtained by linearizing the collision avoidance constraint. The algorithm iteratively tightens the safety condition and reduces the objective cost of the planning problem and the additional penalty term. Numerical results demonstrate the effectiveness of the proposed approach in planning a large number of UAVs in congested space.Comment: This paper has been accepted for presentation at the 62nd IEEE Conference on Decision and Control (CDC 2023

Childhood hospitalisation and related deaths in Hanoi, Vietnam: a tertiary hospital database analysis from 2007 to 2014

To describe hospital admission and emergency visit rates and potential risk factors of prolonged hospitalisation and death among children in Hanoi.; A retrospective study reviewed 212 216 hospitalisation records of children (aged 0-17) who attended the Vietnam National Children's Hospital in Hanoi between 2007 and 2014. Four indicators were analysed and reported: (1) rate of emergency hospital visits, (2) rate of hospitalisation, (3) length of hospital stay and (4) number of deaths. The risk of prolonged hospitalisation was investigated using Cox proportion hazard, and the risk of death was investigated through logistic regressions.; During 2007-2014, the average annual rate of emergency visits was 2.2 per 1000 children and the rate of hospital admissions was 13.8 per 1000 children. The annual rates for infants increased significantly by 3.9 per 1000 children during 2012-2014 for emergency visits and 25.1 per 1000 children during 2009-2014 for hospital admissions. Digestive diseases (32.0%) and injuries (30.2%) were common causes of emergency visits, whereas respiratory diseases (37.7%) and bacterial and parasitic infections (19.8%) accounted for most hospital admissions. Patients with mental and behavioural disorders remained in the hospital the longest (median=12 days). Morbidities related to the perinatal period dominated mortality causes (32.5% of deaths among those admitted to the hospital. Among the respiratory diseases, pneumonia was the leading cause of both prolonged hospitalisation and death.; Preventable health problems, such as common bacterial infections and respiratory diseases, were the primary causes of hospital admissions in Vietnam

Exercise-based cardiac rehabilitation in heart transplant recipients

This is a protocol for a Cochrane Review (Intervention). The objectives are as follows: To determine the effectiveness and safety of exercise‐based rehabilitation on the mortality, hospital admissions, morbidity, exercise capacity, health‐related quality of life, and return to work of people after heart transplantation

Scalable Focused Ion Beam Creation of Nearly Lifetime-Limited Single Quantum Emitters in Diamond Nanostructures

The controlled creation of defect center---nanocavity systems is one of the outstanding challenges for efficiently interfacing spin quantum memories with photons for photon-based entanglement operations in a quantum network. Here, we demonstrate direct, maskless creation of atom-like single silicon-vacancy (SiV) centers in diamond nanostructures via focused ion beam implantation with $\sim 32$ nm lateral precision and $< 50$ nm positioning accuracy relative to a nanocavity. Moreover, we determine the Si+ ion to SiV center conversion yield to $\sim 2.5\%$ and observe a 10-fold conversion yield increase by additional electron irradiation. We extract inhomogeneously broadened ensemble emission linewidths of $\sim 51$ GHz, and close to lifetime-limited single-emitter transition linewidths down to $126 \pm13$ MHz corresponding to $\sim 1.4$-times the natural linewidth. This demonstration of deterministic creation of optically coherent solid-state single quantum systems is an important step towards development of scalable quantum optical devices

imageseg: An R package for deep learning-based image segmentation

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2022 The Authors. Methods in Ecology and Evolution published by John Wiley & Sons Ltd on behalf of British Ecological SocietyConvolutional neural networks (CNNs) and deep learning are powerful and robust tools for ecological applications and are particularly suited for image data. Image segmentation (the classification of all pixels in images) is one such application and can, for example, be used to assess forest structural metrics. While CNN-based image segmentation methods for such applications have been suggested, widespread adoption in ecological research has been slow, likely due to technical difficulties in implementation of CNNs and lack of toolboxes for ecologists. Here, we present R package imageseg which implements a CNN-based workflow for general purpose image segmentation using the U-Net and U-Net++ architectures in R. The workflow covers data (pre)processing, model training and predictions. We illustrate the utility of the package with image recognition models for two forest structural metrics: tree canopy density and understorey vegetation density. We trained the models using large and diverse training datasets from a variety of forest types and biomes, consisting of 2877 canopy images (both canopy cover and hemispherical canopy closure photographs) and 1285 understorey vegetation images. Overall segmentation accuracy of the models was high with a Dice score of 0.91 for the canopy model and 0.89 for the understorey vegetation model (assessed with 821 and 367 images respectively). The image segmentation models performed significantly better than commonly used thresholding methods and generalized well to data from study areas not included in training. This indicates robustness to variation in input images and good generalization strength across forest types and biomes. The package and its workflow allow simple yet powerful assessments of forest structural metrics using pretrained models. Furthermore, the package facilitates custom image segmentation with single or multiple classes and based on colour or grayscale images, for example, for applications in cell biology or for medical images. Our package is free, open source and available from CRAN. It will enable easier and faster implementation of deep learning-based image segmentation within R for ecological applications and beyond.publishedVersio

Experimental Determination of the Uncertainty of the Absorption Coefficient of Crystalline Silicon

Based on a combined analysis of spectroscopic ellipsometry, reflectance and transmittance measurements as well as spectrally resolved luminescence measurements and spectral responsivity measurements, we present data of the coefficient of band-to-band absorption of crystalline silicon at 295 K in the wavelength range 250 - 1450 nm. A systematic measurement uncertainty analysis according to the "Guide to the Expression of Uncertainty in Measurements" (GUM) is carried out for each method, showing that the relative uncertainty of the absorption coefficient data so determined is of the order of 0.3% at 300 nm, 1% at 900 nm, 10% at 1200 nm and 180% at 1450 nm. The data are consolidated by comparison of measurements carried out independently at different institutions. The uncertainty of solar cell energy conversion predictions by means of simulations due to the uncertainty of the absorption coefficient data is shown to be of the order of 0.1% relative.Deutsche Bundesstiftung UmweltState of Lower Saxon

Evaluation of Arctic Sea Ice Thickness Simulated by AOMIP Models

We compare results from six AOMIP model simulations with estimates of sea ice thickness obtained from ICESat, moored and submarine-based upward looking sensors, airborne electromagnetic measurements and drill holes. Our goal is to find patterns of model performance to guide model improvement. The satellite data is pan-arctic from 2004-2008, ice-draft data is from moored instruments in Fram Strait, the Greenland Sea and the Beaufort Sea from 1992-2008 and from submarines from 1975-2000. The drill hole data are from the Laptev and East Siberian marginal seas from 1982-1986 and from coastal stations from 1998-2009. While there are important caveats when comparing modeled results with measurements from different platforms and time periods such as these, the models agree well with moored ULS data. In general, the AOMIP models underestimate the thickness of measured ice thicker than about 2 m and overestimate thickness of ice thinner than 2 m. The simulated results are poor over the fast ice and marginal seas of the Siberian shelves. Averaging over all observational data sets, the better correlations and smaller differences from observed thickness are from the ECCO2 and UW models