Wearable electronics, particularly electronic textiles, hold promise for significant advancements, yet their limited electrical conductivity hinders widespread application. This study examines the application of copper electrodeposition to enhance the electromechanical attributes of textronics. The conductive fabric undergoes copper electroplating for varying durations, assessing the increase in electrical conductivity relative to copper thickness. Experimental conditions span current densities from 0.2 to 20 A dm−2. Additionally, the research evaluates the mechanical resistance of the resulting interconnection with conventional electronic components. Voltammetric measurements, sheet resistance, and microscope observations establish optimal copper deposition conditions. As hypothesized, an inverse proportionality between the sheet resistance of the electrodeposited fabric and the thickness of the copper layer has been observed. This improvement raises a query: does the electromechanical reliability of e‐textiles improve with the addition of only a few micrometers of copper? The study reveals the significant enhancement of the mechanical resistance of soldered interconnections with rigid components after a few seconds of electrodeposition as well as an improvement of the quality factor of a textile antenna. In conclusion, electroplating significantly improves the electromechanical properties of textronics without compromising their wearability. This discovery paves the way for novel applications such as wireless fast charging with textile antennas.

This article describes an extensive study of the use of DSP48E2 Slices in Ultrascale FPGAs to design hardware versions of the Montgomery Multiplication algorithm for the hardware acceleration of modular multiplications. Our fully scalable systolic architectures result in parallelized, DSP48E2-optimized scheduling of operations analogous to the FIOS block variant of the Montgomery Multiplication. We explore the impacts of different pipelining strategies within DSP blocks, scheduling of operations, processing element configurations, global design structures and their tradeoffs in terms of performance and resource costs. We discuss the application of our methodology to multiple types of DSP primitives. We provide ready-to-use fast, efficient, and fully parametrizable designs, which can adapt to a wide range of requirements and applications. Implementations are scalable to any operand width. Our most efficient designs can perform 128, 256, 512, 1024, 2048, and 4096 bits Montgomery modular multiplications in 0.0992 μs, 0.2032 μs, 0.3952 μs, 0.7792μs, 1.550 μs, and 3.099 μs using 4, 6, 11, 21, 41, and 82 DSP blocks, respectively.

We assess the clinical and structural impact at two years of progressively spacing tocilizumab (TCZ) or abatacept (ABA) injections versus maintenance at full dose in patients with rheumatoid arthritis in sustained remission. This multicenter open-label noninferiority (NI) randomized clinical trial included patients with established rheumatoid arthritis in sustained remission receiving ABA or TCZ at a stable dose. Patients were randomized to treatment maintenance (M) at full dose (M-arm) or progressive injection spacing (S) driven by the Disease Activity Score in 28 joints every 3 months up to biologics discontinuation (S-arm). The primary end point was the evolution of disease activity according to the Disease Activity Score in 44 joints during the 2-year follow-up analyzed per protocol with a linear mixed-effects model, evaluated by an NI test based on the one-sided 95% confidence interval (95% CI) of the slope difference (NI margin 0.25). Other end points were flare incidence and structural damage progression. Overall, 202 of the 233 patients included were considered for per protocol analysis (90 in S-arm and 112 in M-arm). At the end of follow-up, 16.2% of the patients in the S-arm could discontinue their biologic disease-modifying antirheumatic drug, 46.9% tapered the dose and 36.9% returned to a full dose. NI was not demonstrated for the primary outcome, with a slope difference of 0.10 (95% CI 0.10-0.31) between the two arms. NI was not demonstrated for flare incidence (difference 42.6%, 95% CI 30.0-55.1) or rate of structural damage progression at two years (difference 13.9%, 95% CI -6.7 to 34.4). The Towards the Lowest Efficacious Dose trial failed to demonstrate NI for the proposed ABA or TCZ tapering strategy.

The sudden admission of many patients with similar needs caused by the COVID-19 (SARS-CoV-2) pandemic forced health care centers to temporarily transform units to respond to the crisis. This process greatly impacted the daily activities of the hospitals. In this paper, we propose a two-step approach based on process mining and discrete-event simulation for sizing a recovery unit dedicated to COVID-19 patients inside a hospital. A decision aid framework is proposed to help hospital managers make crucial decisions, such as hospitalization cancellation and resource sizing, taking into account all units of the hospital. Three sources of patients are considered: (i) planned admissions, (ii) emergent admissions representing day-to-day activities, and (iii) COVID-19 admissions. Hospitalization pathways have been modeled using process mining based on synthetic medico-administrative data, and a generic model of bed transfers between units is proposed as a basis to evaluate the impact of those moves using discrete-event simulation. A practical case study in collaboration with a local hospital is presented to assess the robustness of the approach. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —In this paper we develop and test a new decision-aid tool dedicated to bed management, taking into account exceptional hospitalization pathways such as COVID-19 patients. The tool enables the creation of a dedicated COVID-19 intensive care unit with specific management rules that are fine-tuned by considering the characteristics of the pandemic. Health practitioners can automatically use medico-administrative data extracted from the information system of the hospital to feed the model. Two execution modes are proposed: (i) fine-tuning of the staffed beds assignment policies through a design of experiment and (ii) simulation of user-defined scenarios. A practical case study in collaboration with a local hospital is presented. The results show that our model was able to find the strategy to minimize the number of transfers and the number of cancellations while maximizing the number of COVID-19 patients taken into care was to transfer beds to the COVID-19 ICU in batches of 12 and to cancel appointed patients using ICU when the department hit a 90% occupation rate.

To investigate potential correlations between human exposure to inhaled particles and pathological effects, the biological monitoring of nanoparticles in broncho-alveolar lavages (BAL) from patients has been proposed. To better understand the underlying mechanisms of toxicity, we propose to couple this biomonitoring of nanoparticles to their in vitro toxicity assessment. However, BAL obtained from regular clinical practice are conditioned with sodium hypochlorite solution (in a 50% v/v ratio), which is toxic to cells. The aim of this study was to develop a protocol to neutralize sodium hypochlorite, allowing to properly investigate the toxicity of the nanoparticles BAL contain. We first tried to neutralize chemically the sodium hypochlorite using H2O2, ascorbic acid or sodium ascorbate but this approach was unsuccessful. In addition, standard toxicology assays (MTT, LDH) could not be used because of interference with neutralizing solutions. We thus changed strategy and used ultracentrifugation to isolate nanoparticles from the sodium hypochlorite solution, with satisfactory extraction yields (88 to 100%). We then incubated the extracted nanoparticles with macrophages from the RAW264.7 cell line and assessed the cell viability and pro-inflammatory response. This study can be used as a proof-of-concept for further study of the biological impact of nanoparticles. This approach paves the way for studies aiming at a better understanding of the aetiology of some idiopathic diseases and underlying mechanisms.

Abstract Ensuring fault tolerance in Systems of Multiple-Sources of Energy (SMSE) is of paramount impor-tance for their reliable operation. Detecting, localizing, and characterizing faults are critical tasks toensure system integrity. One crucial element within SMSE, susceptible to faults, is the power convert-ers. This paper introduces an innovative approach leveraging Hierarchical Bayesian Belief Networks(HBBNs) for the identification and isolation of open circuit faults in DC-DC power converters com-monly employed in SMSE applications. Our proposed method addresses the challenge of fault detectionand localization, contributing to enhanced system reliability. The effectiveness of the approach isdemonstrated through extensive testing on simulated data generated via a developed state spacemodel. The results underscore the viability of our approach in bolstering the robustness of DC-DCpower converters against open circuit faults.

Inappropriate stent-graft (SG) flexibility has been frequently associated with endovascular aortic repair (EVAR) complications such as endoleaks, kinks, and SG migration, especially in tortuous arteries. Stents derived from auxetic unit cells have shown some potential to address these issues as they offer an optimum trade-off between radial stiffness and bending flexibility. In this study, we utilized an established finite element (FE)-based approach to replicate the mechanical response of a SG iliac limb derived from auxetic unit cells in a virtual tortuous iliac aneurysm using a combination of a 180° U-bend and intraluminal pressurization. This study aimed to compare the mechanical performance (flexibility and durability) of SG limbs derived from auxetic unit cells and two commercial SG limbs (Z-stented SG and circular-stented SG models) in a virtual tortuous iliac aneurysm. Maximal graft strain and maximum stress in stents were employed as criteria to estimate the durability of SGs, whereas the maximal luminal reduction rate and the bending stiffness were used to assess the flexibility of the SGs. SG limbs derived from auxetic unit cells demonstrated low luminal reduction (range 4-12%) with no kink, in contrast to Z-stented SG, which had a kink in its central area alongside a high luminal reduction (44%). SG limbs derived from auxetic unit cells show great promise for EVAR applications even at high angulations such as 180°, with acceptable levels of durability and flexibility.