Systématique, adaptation, évolution

Capillary electrophoresis (CE) often provides superior separation of macromolecules such as monoclonal antibodies (mAbs), a major biopharmaceutical class, compared with liquid chromatography. However, electropherograms frequently exhibit complex baselines and peak shapes that are not reliably handled by integration algorithms designed for chromatographic data, and manual integration is often required. Many concepts have been proposed to improve peak integration, ranging from incremental algorithmic refinements and signal-to-noise (S/N)-based approaches to artificial intelligence (AI)-driven strategies, but objective performance comparisons are not possible without shared reference data sets and agreed peak limits. To address this gap, we initiated a multinational collaboration involving industrial and academic laboratories to create a comprehensive reference data set for CE peak integration. A total of 227 challenging and practically relevant electropherograms were collected from diverse applications, converted to a standardized format, and independently integrated by multiple experts. Using dedicated software tools and a structured consensus process, mutually accepted reference integration limits were established for each data set. These reference electropherograms, together with the underlying integration rules, are now made available to the scientific community. Analysis of the reference data set identified general principles for reliable peak integration, including the importance of standardized zoom levels and consistent handling of small peaks near the noise level. The data set provides a common foundation for benchmarking commercial chromatography data systems (CDS) and for developing and validating new algorithmic and AI-based integration methods. We expect this work to speed up the development of practical, automated integration strategies for CE and that these core concepts can be applied to other separation techniques.

ABSTRACT Three classes of mid‐infrared metasurfaces operating in the 12–24 µm spectral range are produced solely through the structuration of a single‐crystal silicon surface. By controlling surface topography, we achieve tailorable spectral responses, including resonant, broadband, and anti‐resonant absorptance. Two metasurfaces use smooth gratings, while the third employs a hierarchical topography involving further nanostructuration, leading to a rough grating. Simulations and experiments reveal distinct spectral behaviors: (i) narrow‐band absorptance with mid‐quality factor and angle‐tunable resonant wavelength, also enabling precise control over the photon lifetime, (ii) broadband absorptance, and (iii) broadband absorptance with narrow‐band anti‐resonant absorption dip. Compared to flat silicon surfaces, these metasurfaces enable significantly enhanced light‐matter interactions, achieving a two‐fold increase in the absorptance with only 10% increase in effective surface area. The observed effects are attributed to different expressions of Wood anomalies, driven by the high carrier concentration in heavily doped silicon, which critically shape the metasurfaces’ optical behavior.

The rapid adoption of electric vehicles (EVs) has heightened the need for advanced diagnostic frameworks to ensure the safety, reliability, and longevity of battery systems. Batteries, as the cornerstone of EV performance, are susceptible to capacity degradation, thermal instability, and anomalies that compromise efficiency and safety. Traditional diagnostic approaches, relying on physics-based models and heuristic thresholds, often fail to address the complexity and variability of real-world EV operations, necessitating scalable, efficient, and privacy-preserving solutions. This paper presents a Split Multi-Task Federated Learning (SMTFL) framework that leverages a Transformer-based architecture to address the dual challenges of battery health anomaly detection and capacity estimation. By combining the efficiency of split learning with the collaborative benefits of federated learning, the proposed system enables EVs to train and share partial model updates while retaining sensitive data locally. Experimental results on a recent large-scale EV dataset demonstrate the superior performance of the SMTFL framework, achieving an accuracy of 98.9% for battery health anomaly detection and a mean absolute error (MAE) of 0.32 Ah for capacity estimation, corresponding to a relative error of approximately 1.80%, significantly outperforming state-of-the-art approaches. By training a single model for both tasks and performing computations during charging sessions, the framework minimizes energy consumption and computational overhead, ensuring practicality for large-scale deployment in real-world EV systems.

The micro-structure, residual stresses, and micro-distortions generated near the surface in the AA6061-B4C metal matrix composite by glass-bead blasting are investigated and compared with those of the bulk. In contrast to the bulk, the sublayer is under compression and contains an extremely low density of B4C and a high density of dislocations. Corrosion behaviour was studied in H3BO3 after immersion at the OCP and after accelerated tests. In the sublayer, initial rapid oxidation (formation of a homogeneous oxide film) is followed by slow oxidation (average corrosion rate: 2 µm/year); the oxidation front moves parallel to the surface. In the bulk, oxidation takes place along preferential paths defined by the distribution of B4C. The driving force is the galvanic coupling between B4C and the matrix. Once corrosion proceeds, corrosion products (oxidation of the sublayer) become weakly adherent, peeling off locally. The bulk is then directly exposed to the solution, promoting corrosion.

While physiological predictors like maximal oxygen uptake and lactate threshold are well established in cycling, psychological factors such as affective load and effort perception remain less studied. The aim of this study was to explore the possible differences in psychophysiological responses between professional and national-level cyclists during a race simulation. Twenty-four male cyclists (12 professionals and 12 national level) matched for V˙O2max (75.2 [5.9] vs 74.3 [7.1]mL·min-1·kg-1) performed a 60-minute treadmill cycling test simulating race-end conditions. Power output (PO), heart rate, respiratory frequency, electroencephalographic-derived neural efficiency, perceptual responses (effort, pain, pleasure), and motivation were recorded. Professionals trained 795 (120)h·y-1, compared with 388 (202)h·y-1 for nationals. Exercise intensities were determined using individualized PO values, with participants' self-regulating treadmill velocity via real-time feedback. Compared to national-level cyclists, professionals sustained higher relative PO (5.3 [1.9] vs 4.8 [1.6]W·kg-1, P < .001, d = -0.97) and affective load (2.8 [4.3] vs. 0.6 [3.7], P = .047, d = -0.75). The professionals also reported a greater perceived effort (6.0 [2.7] vs 5.1 [2.3], P = .023, d = -0.67). No significant differences were found for heart rate, respiratory frequency, or neural efficiency. Professional cyclists exhibited superior PO and effort tolerance despite lower pleasure, underscoring the importance of psychological resilience in professional races. These results suggest that tailored training programs aimed at improving tolerance to high-intensity efforts may benefit national-level cyclists seeking to transition to the professional level.

This study examined the experiences, perceptions, and satisfaction of registered dietitian nutritionists (RDNs) working in primary care in the United States. Close-ended survey data were analyzed using descriptive and bivariate analysis, whereas open-ended survey data were studied through content analysis to identify themes. Satisfaction was significantly associated with working with older adults (P = .01), multidisciplinary care teams (P &lt; .001), and opportunities for patient education (P = .004). Dissatisfaction focused on reimbursement limitations, high administrative burden, and perceived lack of respect by patients and physicians. Future research utilizing qualitative approaches to further examine this under-researched area of dietetics practice in the United States may be warranted.

Most active filters for electromagnetic compatibility (EMC) are designed as Single-Input Single-Output (SISO) systems. This work proposes an innovative approach with a control strategy for a Two-Inputs Two-Outputs (TITO) active filter. This model employs two detection points and two injection points, optimizing noise attenuation on power lines. Integrated into the regulation loop, it allows precise control of line currents without relying on the traditional separation of modes (common mode and differential mode), while inherently accounting for mode conversion phenomena. This approach offers a different method for active filter design.

HighlightsWhat are the main findings?REEV SENSE IMUs provide accurate knee kinematics during post-stroke gait.The system adapts to various assistive device conditions, with robust knee measurements.What are the implications of the main findings?Enable reliable wearable-based gait monitoring outside the laboratory settings.Support the broader use of wearable sensors in stroke rehabilitation.Human gait analysis is essential for clinical evaluation and rehabilitation monitoring, particularly in post-stroke individuals, where joint kinematics provide valuable insights into motor recovery. While optical motion capture (OMC) is the gold standard, its high cost and restricted use in laboratory settings limit its accessibility. This study aimed to evaluate the accuracy of REEV SENSE, a novel magnetometer-free inertial measurement unit (IMU), in capturing knee and ankle joint angles during overground walking in post-stroke individuals using assistive devices. Twenty participants with chronic stroke walked along a 10-m walkway with their usual assistive device (cane or walker), while joint kinematics were simultaneously recorded using OMC and IMUs. Agreement between the systems was assessed using the mean absolute error, root mean square error, 95% confidence intervals, and Pearson’s correlation coefficient. Knee angles measured with the IMUs showed a strong correlation with the OMC (r > 0.9) and low errors (MAE < 5°), consistent with clinical acceptability. Ankle angle accuracy was lower for participants using walkers, while knee measurements remained stable regardless of the assistive device. These findings demonstrate that REEV SENSE IMUs provide clinically relevant kinematic data and support their use as a practical wearable tool for gait analysis in real-world or remote clinical settings.

Aulacus is a genus of parasitic wasps in the superfamily Evanioidea. We re-examine the Australian fauna, assessing both generic and species boundaries. In doing so, we provide diagnostic descriptions for 41 previously described species, two new species A. elongaticeps Parslow & Hill sp. nov. and A. gromiti Parslow & Hill sp. nov., and synonymise 19 speciesA. anici Jennings & Austin, 2018, A. aroueti (Girault, 1926), A. bashfordi Jennings & Austin, 2018, and A. simsoni Jennings & Austin, 2018 are all synonymised with A. albimanus (Kieffer, 1911); A. wrightae Jennings & Austin, 2018, is synonymised with A. aquilus Jennings & Austin, 2018; A. pallidus Jennings & Austin, 2018 and A. warraensis Jennings & Austin, 2018 are both synonymised with A. atriceps (Kieffer, 1911); A. kittelae Jennings & Austin, 2018 is synonymised with A. bamagensis Jennings & Austin, 2018; A. deansi Jennings & Austin 2018 is synonymised with A. belairensis Jennings, Austin & Stevens, 2004; A. brabyi Jennings & Austin, 2018 is synonomised with A. flavicornis (Kieffer, 1911); A. pallidicaudis (Cameron, 1911) is synonomised with A. flavimanus (Kieffer, 1911); A. nebo Jennings & Austin, 2018 and A. mareebaensis Jennings & Austin, 2018 are both synonymised with A. flindersbaudini Jennings, Austin & Stevens, 2004; A. mcmillani Jennings Austin & Stevens, 2004 is synonomised with A. fuscicornis Cameron, 1911; A. naumanni Jennings & Austin, 2018 is synonomised with A. jamberoo Jennings & Parslow, 2018; A. williamsi Jennings & Austin, 2018 is synonymised with A. kiwarrakensis Jennings & Austin, 2018; A. scitulus Jennings & Parslow, 2018 is synonymised with A. obcordellus Jennings & Parslow, 2018; A. hackeri Jennings & Austin, 2018 is synonymised with A. planiceps (Szepligeti, 1903); and A. tasmanicus Jennings & Austin, 2018 is synonymised with A. rieki Jennings & Austin, 2018. As well, A. biroi (Szpligeti, 1903) remains incertae sedis. Diagnostic figure plates for all valid 43 species and an updated key to the Australian species are also provided.