Motocross (Mx) is the off‐road mechanical sport most commonly practiced around the world. Riders practice training and competitions on motorcycles. It requires some specific physical and cognitive ...abilities. Mx racing is composed of successive heats. Whole‐body cryotherapy (WBC) appears to be an interesting way to recover faster between the successive heats which composes each race. The aim of this study is to determine whether WBC can be used between Mx heats to accelerate rider's muscular recovery. Eighteen riders performed a series of physical tests (isometric, concentric, and maximal strength, reaction time, and recovery perception); try to mimic Mx competition using a 25 minutes simulated Mx heat followed by a recovery condition (CONT or WBC); and repeated physical tests. WBC had better recovery in isometric strength for up/low limbs. CONT had better recovery in explosive strength for low limb. No difference in maximal strength or reaction time between the before exercise, the after exercise, and after recovery. The WBC group had a better recovery perception after recovery than the CONT group. WBC exposure seems to accelerate isometric muscle recovery after a simulated motocross exercise.
Hyperspectral remote sensing is now an established tool to determine shallow water properties over large areas, usually by inverting a semi-analytical model of water reflectance. However, various ...sources of error may make the observed subsurface remote-sensing reflectance deviate from the model, resulting in an increased retrieval error when inverting the model based on classical least-squares fitting. In this paper, we propose a probabilistic forward model of shallow water reflectance variability that describes two of the main sources of error, namely, (1) the environmental noise that includes every source of above-water variability (e.g., sensor noise and rough water surface), and (2) the potentially complex inherent spectral variability of each benthic class through their associated spectral covariance matrix. Based on this probabilistic model, we derive two inversion approaches, namely, MILE (MaxImum Likelihood estimation including Environmental noise) and MILEBI (MaxImum Likelihood estimation including Environmental noise and Bottom Intra-class variability) that utilize the information contained in the proposed covariance matrices to further constrain the inversion while allowing the observation to differ from the model in the less reliable wavebands. In this paper, MILE and MILEBI are compared with the widely used least-squares (LS) criterion in terms of depth, water clarity and benthic cover retrievals. For these three approaches, we also assess the influence of constraining bottom mixture coefficients to sum to one on estimation results.
The results show that the proposed probabilistic model is a valuable tool to investigate the influence of bottom intra-class variability on subsurface reflectance, e.g., as a function of optical depth or environmental noise. As expected, this influence is critical in very optically shallow waters, and decreases with increasing optical depth. The inversion results obtained from synthetic and airborne data of Quiberon Peninsula, France, show that MILE and MILEBI generally provide better performances than LS. For example, in the case of airborne data with depth ranging from 0.44 to 12.00m, the bathymetry estimation error decreases by about 32% when using MILE and MILEBI instead of LS. Estimated maps of bottom cover are also more consistent when derived using sum-to-one constrained versions of MILE and MILEBI. MILE is shown to be a simple but powerful method to map simple benthic habitats with negligible influence of intra-class variability. Alternatively, MILEBI is to be preferred if this variability cannot be neglected, since taking bottom covariance matrices into account concurrently with mean reflectance spectra may help the bottom discrimination, e.g., in the presence of overlapping classes. This study thus shows that taking potential sources of error into account through appropriate parameterizations of spectral covariance may be critical to improve the remote sensing of shallow waters, hence making MILE and MILEBI interesting alternatives to LS.
•Most shallow water remote-sensing methods are sensitive to model inaccuracies.•The latter can be due to the environmental noise and bottom intra-class variability.•Both are included in a probabilistic forward model of water reflectance variability.•Two maximum likelihood based inversion methods are derived from this modeling.•Both methods show better performances than the standard least-squares method.
In a previous paper, we introduced (i) a specific hyperspectral mixing model for the sea bottom, based on a detailed physical analysis that includes the adjacency effect, and (ii) an associated ...unmixing method that is supervised (i.e., not blind) in the sense that it requires a prior estimation of various parameters of the mixing model, which is constraining. We here proceed much further, by first analytically showing that the above model can be seen as a specific member of the general class of mixing models involving spectral variability. Therefore, we then process such data with the IP-NMF unsupervised (i.e., blind) unmixing method that we proposed in previous works to handle spectral variability. Such variability especially occurs when the sea depth significantly varies over the considered scene. We show that IP-NMF then yields significantly better pure spectra estimates than a classical method from the literature that was not designed to handle such variability. We present test results obtained with realistic synthetic data. These tests address several reference water depths, up to 7.5 m, and clear or standard water. For instance, they show that when the reference depth is set to 7.5 m and the water is clear, the proposed approach is able to distinguish various classes of pure materials when the water depth varies up to ±0.2 m around this reference depth, over all pixels of the analyzed scene or over a “subscene”: the overall scene may first be segmented, to obtain smaller depths variations over each subscene. The proposed approach is therefore effective and can be used as a building block in performing the subpixel classification of the sea bottom for shallow water.
Monitoring of coastal areas by remote sensing is an important issue. The interest of using an unmixing method to determine the seabed composition from hyperspectral aerial images of coastal areas is ...investigated. Unmixing provides both seabed abundances and endmember reflectances. A sub-surface mixing model is presented, based on a recently proposed oceanic radiative transfer model that accounts for seabed adjacency effects in the water column. Two original non-negative matrix factorization ( N M F )-based unmixing algorithms, referred to as W A D J U M (Water ADJacency UnMixing) and W U M (Water UnMixing, no adjacency effects) are developed, assuming as known the water column bio-optical properties. Simulations show that W A D J U M algorithm achieves performance close to that of the N M F -based unmixing of the seabed without any water column, up to 10 m depth. W U M performance is lower and decreases with the depth. The robustness of the algorithms when using erroneous information about the water column bio-optical properties is evaluated. The results show that the abundance estimation is more reliable using W A D J U M approach. W A D J U M is applied to real data acquired along the French coast; the derived abundance maps of the benthic habitats are discussed and compared to the maps obtained using a fixed spectral library and a least-square ( L S ) estimation of the seabed mixing coefficients. The results show the relevance of the W A D J U M algorithm for the local analysis of the benthic habitats.
The estimation of the bathymetry and the detection of targets located on the seabed of shallow waters using remote sensing techniques is of great interest for many environmental applications in ...coastal areas such as benthic habitat mapping, monitoring of seabed aquatic plants and the subsequent management of littoral zones. For that purpose, knowledge of the optical effects induced by the neighborhood of a given seabed target and by the water column itself is required to better interpret the subsurface upward radiance measured by satellite or shipborne radiometers. In this paper, the various sources of photons that contribute to the subsurface upward radiance are analyzed. In particular, the adjacency effects caused by the neighborhood of a given seabed target are quantified for three water turbidity conditions, namely clear, moderately turbid and turbid waters. Firstly, an analytical expression of the subsurface radiance is proposed in order to make explicit the radiance terms corresponding to these effects. Secondly, a sensitivity study is performed using radiative transfer modeling to determine the influence of the seabed adjacency effects on the upward signal with respect to various parameters such as the bathymetry or the bottom brightness. The results show that the highest contributions of the adjacency effects induced by the neighborhood of a seabed target to the subsurface radiance could reach 26%, 18% and 9% for clear, moderately turbid and turbid water conditions respectively. Therefore, the detection of a seabed target could be significantly biased if the seabed adjacency effects are ignored in the analysis of remote sensing measurements. Our results could be further used to improve the performance of inverse algorithms dedicated to the retrieval of bottom composition, water optical properties and/or bathymetry.
Objective
Determining whether to pursue or terminate resuscitation efforts remains one of the biggest challenges of cardiopulmonary resuscitation (CPR). No ideal cut-off duration has been recommended ...and the association between CPR duration and survival is still unclear for out-of-hospital cardiac arrest (OHCA). The aim of this study was to assess the association between CPR duration and 30-day survival after OHCA with favorable neurological outcomes according to initial rhythm.
Methods
This was an observational, retrospective analysis of the French national multicentric registry on cardiac arrest, RéAC. The primary endpoint was neurologically intact 30-day survival according to initial rhythm.
Results
20,628 patients were included. For non-shockable rhythms, the dynamic probability of 30-day survival with a Cerebral Performance Category (CPC) of 1 or 2 was less than 1% after 25 min of CPR. CPR duration over 10 min was not associated with 30-day survival with CPC of 1 or 2 (adjusted OR: 1.67; CI 95% 0.95–2.94). For shockable rhythms, the dynamic probability of 30-day survival with a CPC score of 1 or 2, was less than 1% after 54 min of CPR. CPR duration of 21–25 min was still associated with 30-day survival and 30-day survival with a CPC of 1 or 2 (adjusted OR: 2.77; CI 95% 2.16–3.57 and adjusted OR: 1.82; CI 95% 1.06–3.13, respectively).
Conclusions
Survival decreased rapidly with increasing CPR duration, especially for non-shockable rhythms. Pursuing CPR after 25 min may be futile for patients presenting a non-shockable rhythm. On the other hand, shockable rhythms might benefit from prolonged CPR.
We present an analytical approach based on Cramer-Rao Bounds (CRBs) to investigate the uncertainties in estimated ocean color parameters resulting from the propagation of uncertainties in the ...bio-optical reflectance modeling through the inversion process. Based on given bio-optical and noise probabilistic models, CRBs can be computed efficiently for any set of ocean color parameters and any sensor configuration, directly providing the minimum estimation variance that can be possibly attained by any unbiased estimator of any targeted parameter. Here, CRBs are explicitly developed using (1) two water reflectance models corresponding to deep and shallow waters, resp., and (2) four probabilistic models describing the environmental noises observed within four Sentinel-2 MSI, HICO, Sentinel-3 OLCI and MODIS images, resp. For both deep and shallow waters, CRBs are shown to be consistent with the experimental estimation variances obtained using two published remote-sensing methods, while not requiring one to perform any inversion. CRBs are also used to investigate to what extent perfect a priori knowledge on one or several geophysical parameters can improve the estimation of remaining unknown parameters. For example, using pre-existing knowledge of bathymetry (e.g., derived from LiDAR) within the inversion is shown to greatly improve the retrieval of bottom cover for shallow waters. Finally, CRBs are shown to provide valuable information on the best estimation performances that may be achieved with the MSI, HICO, OLCI and MODIS configurations for a variety of oceanic, coastal and inland waters. CRBs are thus demonstrated to be an informative and efficient tool to characterize minimum uncertainties in inverted ocean color geophysical parameters.
Instrumented single‐shot experiments provide crucial information of a material's response to impact events that can be used in shot‐peening modelling. However, no authors successfully used such test ...for constitutive model identification and validation as existing test rig generally cannot provide an accurate determination of the shot trajectory in three dimensions over a wide velocity range. In this work, a shot‐peening test rig that can propel single shot under the process conditions with a high aiming accuracy is presented. The test rig propels industrial shot by sudden pressurised gas release. A methodology to recover the propelled shot three‐dimensional trajectory within a 200‐μm accuracy using two high‐frequency cameras is developed in an open‐source in‐house code. The test rig can propel 0.5‐, 1.19‐ and 2.5‐mm‐diameter shot at velocity ranging from 0.8 to 143 m s−1 and can send several shots at the same position when using the largest shot diameter. Two potential applications of the set‐up are presented for (i) coefficient of restitution measurement with different shooting angles and velocities and (ii) crystal plasticity finite element model validation using the impact dent topology, the shot displacement curve and the crystal misorientation field under the dent.
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