TDF (France)

Background: Embolization is a key therapeutic option in interventional radiology for the management of acute arterial bleeding and solid organ injuries. While various embolic agents exist, there is a persistent clinical need for materials that are not only highly effective but also biocompatible, easy to deliver, and cost-effective. We aim to evaluate a new eco-friendly dry foam agar-based embolization agent (ABEA) in an uncontrolled solid organ hemorrhage model. Material and Methods: Ten pigs underwent a controlled splenic injury. After a 5 min free-bleeding period, five pigs were treated with splenic artery ABEA embolization, while the remaining five received no treatment and served as the control group. Follow-up angiography was performed immediately after embolization and at 5 and 15 min in the treated pigs. Mean arterial pressures and average blood loss volumes were evaluated for 120 min. Results: The control group showed continuous blood loss, leading to a significantly higher total blood loss than the ABEA-treated group (1451 mL vs. 611 mL at 120 min, p < 0.05). Mean arterial pressure (MAP) remained below the hemorrhagic shock threshold throughout the procedure in the control group, validating the model of uncontrolled hemorrhage. In addition, a significant stabilization of MAP was observed in treated pigs, remaining above the critical level of hemorrhagic shock and differed significantly from control group values. Conclusions: Embolization with ABEA maintained MAP above critical levels and significantly reduced blood loss volume in a hemorrhagic model. These results support the technical feasibility and short-term hemostatic performance of ABEA in an acute setting. While preliminary, this proof-of-concept has provided the basis for a validated clinical study currently underway to evaluate its effectiveness and safety in human patients.

Abstract Rationale High treatment quality, defined by mean adherence &amp;gt;4 hours per day, unintentional leaks &amp;lt;24 L/min, and residual apnea-hypopnea index &amp;lt;5 events per hour, is associated with better outcomes. Adherence variance may reflect behaviour linked to better treatment quality. This study aimed to assess whether monthly adherence variance is associated with improved treatment quality in patients treated with non-invasive ventilation (NIV) for more than 4 months. Methods EqualiNIV is a retrospective study evaluating treatment quality in 511 telemonitored patients with chronic respiratory failure treated with non-invasive ventilation (using a Resmed Lumis 150 VPAP ST device) for at least 4 months before the beginning of the study, observed from April 15th to October 31st 2023. The study followed three steps: (1) hierarchical clustering based on individual adherence variance; (2) assessing whether monthly adherence variance in the preceding month predicted the proportion of alerts in the subsequent month; (3) evaluating treatment quality based on the number of months with low adherence variance. Results The population was predominantly male (60.7%), with a median age 71.4 years) and a median treatment duration of 6.2 years. The population showed good adherence, with few leaks and residual respiratory events reported by the device software. Almost half of the patients were also receiving oxygen therapy. The full-face mask was the most commonly used, and half of the patients used a humidifier. Cluster 1, consisting of patients with adherence variance below 3, had a significantly higher proportion (57.93%) of patients achieving high-quality treatment compared to other clusters. The IPTW-adjusted analysis indicated that patients with a monthly adherence variance below 3 had a significantly higher probability of achieving high-quality treatment (coefficient: 0.2695, p-value: 0.017) compared to those with variances between 3 and 13 or above 13. Patients with a monthly adherence variance below 3 had a significantly higher probability of achieving high-quality treatment in the subsequent month compared to those with variances between 3 and 13 or above 13. The IPTW-adjusted analysis showed that patients with an adherence variance below 3 for six months or more had a significantly higher probability of having high-quality treatment in October and over the entire period (coefficient: 0.2649, p-value: 0.028; and coefficient: 0.2649, p-value: 0.0028, respectively) compared to those who did not (non-significant). Conclusion The EqualiNIV study demonstrates that low adherence variance is associated with high-quality treatment and serves as a prognostic indicator of treatment stability and alert occurrence in the subsequent month.

Abstract In the beginning, a presentation of the international TS63111 Technical Specification on hydraulic transient phenomena of hydro turbines, storage pumps and pump-turbines will be done. The Specification has been submitted for comments to the IEC TC4 Countries Committees and it deals with the factors that affect the hydraulic transients, the recommend modelling, design, and the best practice for site measurement and guarantee evaluation. With respect to the pressure measurement during transient testing and the calibration of the transient modeling following the site measurement, sometimes the dynamic pressure fluctuations are not considered and only the average value is indicated. During the testing, a full attention should be given not only to the measurements conditions but also to the equipment used and not least the sampling rate used for the acquisition. The paper presents the findings of EDF-DTG during the testing performed in some power plants and the mechanical impact of high frequency pressure fluctuations on the penstock liner. During the testing, the penstock has been equipped with classic pressure transducers and with strain gauges in order to demonstrate that the high frequency pressure fluctuations have also a mechanical impact on the liner and should be considered in the evaluation of the guarantee. A comparison between the stress calculated as an effect of the pressure and the stress given by the strain gauges have been performed on the signals together with the classical Spectral analysis.

The safety of nuclear power plants in France is assessed based on 1000-year flood estimates, with a safety factor accounting for uncertainty. Previous studies on the Garonne River near Agen, France, used threshold exceedance values from a continuous 85&amp;#160;year-long series at two hydrometric stations: Malause (1915-1966) and Lamagist&amp;#232;re (1967-2000), and historical data at Agen since 1770. The estimate of the design flood was very sensitive to the choice of an Exponential or of a Generalized Pareto distribution, yielding 12&amp;#160;600 and 16&amp;#160;000 m3/s, respectively. This communication presents a more comprehensive study based on a GEV distribution fitted from the annual maximum values of a continuous series since 1852 (adding Agen 1852-1914) and historical data at Agen since 1435. The statistical framework accounts for both discharge and sampling uncertainty components. The first uncertainty component is about 3% for the recent years and 35% for the oldest years. The statistical framework is able to account for a multiplicative error on rating curves. This leads to corrections in peak discharge values, with better agreement between historical data at Agen and hydrometric data at Malause-Lamagist&amp;#232;re. The final estimate of the design flood is around 10 500-11 600 m3/s, without or with the largest known historical flood of 1435. It confirms the safety of the nuclear plant, based on extensive historical information.

In this paper, we evaluate the performance of a newly developed spatial domain zero-forcing (ZF) based selfinterference cancellation (SIC) method in a generic multiple-input multiple-output (MIMO) full-duplex (FD) system. To this end, we theoretically evaluate the influence of channel state information (CSI) error on the SIC performance of our considered approach, and we validate our results through simulations. In particular, we show that the additional received self-interference (SI) power due to the CSI errors is quadratically proportional to a particular parameter α, quantifying the level of CSI errors. Furthermore, simulations results show that the increase of SI power has a negligible impact on the overall system performance in terms of spectral efficiency (SE), which proves the robustness of our considered SIC method.

&lt;p&gt;This paper deals with a massive multiple-input multiple- output (mMIMO) full-duplex (FD) communication system. We propose new spatial domain self-interference cancellation (SIC) techniques. The main idea is to treat the self-interference (SI) signal emitted from the FD node as another spatial stream that needs to be precoded in the null space of the MIMO channel that includes that node as an output. To this end, an additional RF chain is needed at the transmitter to cancel the SI signal. On this basis, we derive the expressions of the spatial precoders with respect to the conventional zero forcing (ZF) and minimum mean square error precoding (MMSE) criteria. Furthermore, the originality of the analysis lies in the consideration of SWM for modeling the SI channel, which is justified by the close proximity of the transmit and receive antenna panels in the FD node. Simulations show the relevance of the study. We verify the SIC efficiency in the spatial domain using the derived ZF and MMSE precoders by analyzing their relative performance in terms of spectral efficiency. We also highlight the robustness of our SWM-based SI channel compared to classic planar wave model (PWM) and therefore the need for using it.&lt;/p&gt;

&lt;p&gt;This paper deals with a new spatial domain-based self-interference cancellation (SIC) method called constrained minimum mean square error (C-MMSE) for massive multiple-input multiple-output (mMIMO) full-duplex (FD) communication systems. The main idea is to treat the self-interference (SI) signal emitted from an FD node as a particular spatial stream arriving at the receiver part of that same FD node which needs to be spatially postcoded along with other useful signals coming from other transmitters, so that it falls into the null space of the MIMO channel that includes the FD node transmitter part as an input. On this basis, we first adapt the expressions of the spatial combiners with respect to the conventional zero forcing (ZF) and minimum mean square error combining (MMSE) criteria and show that the latter is not capable to efficiently cancel the SI signal unless an additional constraint is added to properly perform SIC. We hence design the new so-called C-MMSE combiner and derive its expression. In addition to our proposal, the originality of our work lies in the consideration of spherical wave model (SWM) for modeling the SI channel, which is justified by the close proximity of the transmit and receive antenna panels in the FD node.&lt;/p&gt; &lt;p&gt;We examine and compare the SIC performance of the adapted ZF combiner, the adapted MMSE combiner and the newly introduced C-MMSE combiner by evaluating the obtained spectral efficiency (SE). We also highlight the robustness of the SWM-based SI channel modelling compared to conventional planar wave modelling (PWM) and therefore the relevance of using it.&lt;/p&gt;

Modern communication systems rely on accurate channel estimation to achieve efficient and reliable transmission of information. As the communication channel response is highly related to the user's location, one can use a neural network to map the user's spatial coordinates to the channel coefficients. However, these latter are rapidly varying as a function of the location, on the order of the wavelength. Classical neural architectures being biased towards learning low frequency functions (spectral bias), such mapping is therefore notably difficult to learn. In order to overcome this limitation, this paper presents a frugal, model-based network that separates the low frequency from the high frequency components of the target mapping function. This yields an hypernetwork architecture where the neural network only learns low frequency sparse coefficients in a dictionary of high frequency components. Simulation results show that the proposed neural network outperforms standard approaches on realistic synthetic data.

<strong class="journal-contentHeaderColor">Abstract.</strong> Hydrological modelling of small mountainous catchments is particularly challenging because of the high spatio-temporal resolution required for the meteorological forcings. In-situ measurements of precipitation are typically scarce in these remote areas, particularly at high elevations. Precipitation reanalyses propose different alternative forcings for the simulation of streamflow using hydrological models. In this paper, we evaluate the performances of two hydrological models representing some of the key processes for small mountainous catchments, using different meteorological products with a fine spatial and temporal resolution. The evaluation is performed on 55 small catchments of the Northern French Alps. While the simulated streamflows are adequately reproduced for most of the configurations, these evaluations emphasize the added value of radar measurements, in particular for the reproduction of flood events. However, these better performances are only obtained because the hydrological models correct the underestimations of accumulated amounts (e.g. annual) from the radar data in high-elevation areas.