The crystal structure of etrasimod has been solved and refined using synchrotron X-ray powder diffraction data and optimized using density functional theory techniques. Etrasimod crystallizes in space group P1 (#1) with a = 10.6131(5), b = 10.7003(5), c = 11.1219(8) Å, α = 72.756(2), β = 76.947(2), γ = 77.340(1)°, V = 1159.28(6) Å3, and Z = 2 at 298 K. The crystal structure contains O▬H⋯O hydrogen-bonded etrasimod dimers, which lie in layers approximately parallel to the (2,0,−1) plane. The amino group of each molecule forms an intramolecular N▬H⋯O hydrogen bond to the carbonyl group of the adjacent carboxylic acid group. The powder pattern has been submitted to ICDD for inclusion in the Powder Diffraction File™ (PDF®).

We present coherent beam combining of nanosecond pulses with 20-J energy and large beams using a Sagnac interferometer geometry based on Nd:glass rod-type amplifiers. In this study, we demonstrate that coherent beam combining is compatible with large-diameter energetic beams, presenting, therefore, an interesting and solid perspective towards the performance improvement of large-scale laser facilities, especially in terms of high-repetition-rate and high-energy operation. We demonstrate that for energy of 20 J, the coherent combination efficiency is around 92%, with high beam quality and long-term stability. A thorough temporal and spatial characterization of the system’s operation is provided to forecast the various potentialities available for large-scale facilities.

This paper presents for the first time the implementation of an Si/SiGe heterojunction bipolar phototransistor (HPT) into an STMicroelectronics BiCMOS technology together with the development of hydrodynamical model that fits in a trustable manner the measured opto-microwave performance. The developed hydrodynamical model relies on a precise topology analysis of the HPT and an efficient optical absorption coefficient model. It is key to predict the optimization required for the HPT. Simulation results with responsivities of 0.92 A/W and bandwidth of 1.55 GHz are obtained at low $V_{\scriptsize{\text{CE}}}=2$ V and for small devices with $2 \times 2\,\unicode{x00B5} \text{m}^{2}$ optical window. Simulation results are used to identify the best horizontal geometry that maximizes the gain–bandwidth product of the HPT. The behavior of the photo-generated carriers in the active region of the device is investigated.

The Water-Enhanced Turbofan is a promising aero engine propulsion concept that could reduce the climate impact of aviation significantly by combining the conventional Joule/Brayton cycle with a Clausius-Rankine steam cycle. One important component with a high impact on the overall performance is the condenser, a heat exchanger cooling the core exhaust for water recovery. The design conditions for the Water-Enhanced Turbofan condenser have not been analysed from a system perspective in previous studies. Therefore, these operating conditions, which can be decisive for the dimensioning of the condenser, are investigated in the present work. These operating conditions include ambient temperature variations, different cruise altitudes, maximum cruise thrust and contrail avoidance. A conceptual design engine model is set up in the Numerical Propulsion System Simulation (NPSS) framework, incorporating a multi-point design scheme. The heat exchangers are modelled using a neural network surrogate model. The results show a trade-off between engine fuel burn and the cold size frontal area of the condenser, the latter being an indication for the integrability. It is shown that high ambient temperatures pose a challenge to the condenser design, necessitating consideration of such operating conditions in new engine concepts based on heat exchange with the environment. The condenser designed for typical cruise at 15K above standard atmosphere at 35,000 ft cruise altitude, enables sustained water cycle operations down to 10,000 ft under standard day conditions. Additionally, the complete cruise segment of the design mission can be flown with sustained water cycle operations at 10K above standard atmosphere conditions. A positive side effect of the condenser sizing for hot day conditions is that the probability of contrail formation is reduced because the condenser design results in excess water recovery at colder ambient conditions.

A concept for a femtosecond pulse compressor based on underdense plasma prisms is presented. An analytical model is developed to calculate the spectral phase incurred and the expected pulse compression. A 2D particle-in-cell simulation verifies the analytical model. Simulated intensities (${\sim} {10}^{16}$ W/cm2) were orders of magnitude higher than the damage threshold for conventional gratings used in chirped pulse amplification. Theoretical geometries for compact (tens of cm scale) compressors for 1, 10 and 100 PW power levels are proposed.

Machine – human interaction systems have been proposed to improve motion learning efficiency. We developed a pneumatic-driven motion teaching system that provides feedback to the learner by simultaneously presenting visual and torque information. We achieved a lightweight, soft, and user-safety haptic system using a pneumatic artificial muscle (PAM). The PAM’s shrink force was estimated based on its characteristic model and the suit link system, and the suit generated external torque. However, accurate force control was challenging due to the time delay of the feedback control, the loosening of the soft suit, and modeling errors of the driving PAM caused by hysteresis. To improve the force control performance of the motion teaching suit, this article’s contributions are to develop a novel suit in which PAMs for drive and force estimation are connected in series and implement a 2-degree-of-freedom (DOF) force control system using force estimation values in this suit and to confirm the effectiveness of the proposed hardware and software. This article contains three topics: (a) the development of novel suit hardware, (b) force estimation using a sealed small PAM, and (c) a proposal of force control using a 2-DOF controller. The effect of loosening the soft suit is reduced in the novel-developed suit. A sealed small PAM with small deformation and little hysteresis is adopted for force estimation. The time delay in feedback control is decreased by adopting the proposed novel 2-DOF control. Finally, the proposed suit and its control system were evaluated in experiments and achieved the desired performance.

In this article, a qualitative work has been carried out based on airborne pulsed Doppler (PD) RF sensor consist of its operational requirements in terms of phase noise modeling and associated contributing factors. Precise and efficient theoretical modeling of phase noise requirement for airborne-PD radar or long-range RF sensor is presented. This work also emphasis on the limitation of conventional phase noise modeling practices used for PD RF sensor. An improved equation has been derived for accurate phase noise estimation considering the range correlation effect and inline flicker contribution on residual phase noise requirement. Random vibrations causes increase in phase noise level around low frequency offsets region in local oscillator. The proposed phase noise model is efficient enough to counter phase noise degradation at lower frequency offsets. The proposed model is also experimentally validated. Improved modeling offers benefit in reducing the stringent RF sensor phase noise specifications at close-in frequency offsets using range correlation effect and precise inclusion of inline flicker contribution. Present work can be used to mitigate random vibration effects at close-in phase noise offsets, which avoids complex stabilization practices and stringent oscillator design phase noise specification.

Elastic textiles play a critical role in passive wearable solutions for musculoskeletal load management in both passive exosuits and resistance clothing. These textiles, based on their ability to stretch and retract, can exhibit ambivalence in their load-modulating effects when used in occupational, rehabilitation, exercise, or everyday activity settings. While passive exosuits and resistance garments may appear similar in design, they have opposing goals: to reduce the musculoskeletal load in the case of exosuits and to increase it in the case of resistance clothing. Despite this intrinsic connection, these two approaches have not been extensively linked together. This review aims to fill this gap by examining the common and distinct principles of elastic textiles in passive exosuits and resistance clothing, shedding light on their interactions and the complex dynamics of musculoskeletal load systems. The effectiveness of different designs in passive exosuits that mimic musculoskeletal function and resistance clothing that increase the workload for strength training are critically reviewed. Current challenges in practical implementation and opportunities to improve critical issues, such as preload, thermal comfort, skin friction, and donning and doffing are also highlighted.

The wide adoption of occupational shoulder exoskeletons in industrial settings remains limited. Passive exoskeletons were proved effective in a limited amount of application scenarios, such as (quasi-)static overhead handling tasks. Quasi-active devices, albeit representing an improved version of their passive predecessors, do not allow full modulation of the amount of assistance delivered to the user, lacking versatility and adaptability in assisting various dynamic tasks. Active occupational shoulder exoskeletons could overcome these limitations by controlling the shape of the delivered torque profile according to the task they aim to assist. However, most existing active devices lack compactness and wearability. This prevents their implementation in working environments. In this work, we present a new active shoulder exoskeleton, named Active Exo4Work (AE4W). It features a new flexible shaft-driven remote actuation unit that allows the positioning of the motors close to the wearer’s center of mass while it maintains a kinematic structure that is compatible with the biological motion of the shoulder joint. in vitro and in vivo experiments have been conducted to investigate the performance of AE4W. Experimental results show that the exoskeleton is kinematically compatible with the user’s workspace since it does not constrain the natural range of motion of the shoulder joint. Moreover, this device can effectively provide different types of assistance while the user executes various dynamic tasks, without altering perceived comfort.

We present continuous Class-F (CCF) and continuous Class-F−1 (CCF−1) power amplifiers (PAs) with compact circuit sizes. The output matching network (OMN) of a continuously harmonic-tuned PA must accommodate varying load impedance conditions across a wide frequency range, spanning from the fundamental frequency up to the 2nd and 3rd harmonic frequencies. This requirement typically leads to LPF-type OMNs with a significant circuit area overhead, thereby limiting the applicability of the broadband PAs. In this paper, we propose utilizing a one-port composite right-/left-handed transmission line to control the harmonic loads, while the fundamental loads are managed by a moderately sized LPF. This resulted in a notable reduction in PA size by nearly an order of magnitude. We demonstrate the effectiveness of this design approach through the fabrication of 2-GHz-band GaN HEMT PAs operating in CCF and CCF−1 modes. While both PAs exhibited high-efficiency (>70%) operational bandwidths at a state-of-the-art level, we also elucidate key design considerations specific to each PA operation mode.

The propagation of multiple ultraintense femtosecond lasers in underdense plasmas is investigated theoretically and numerically. We find that the energy merging effect between two in-phase seed lasers can be improved by using two obliquely incident guiding lasers whose initial phase is $\pi$ and $\pi /2$ ahead of the seed laser. Particle-in-cell simulations show that due to the repulsion and energy transfer of the guiding laser, the peak intensity of the merged light is amplified by more than five times compared to the seed laser. The energy conversion efficiency from all incident lasers to the merged light is up to approximately 60$\%$. The results are useful for many applications, including plasma-based optical amplification, charged particle acceleration and extremely intense magnetic field generation.

State-of-the-art controllers for active back exosuits rely on body kinematics and state machines. These controllers do not continuously target the lumbosacral compression forces or adapt to unknown external loads. The use of additional contact or load detection could make such controllers more adaptive; however, it can be impractical for daily use. Here, we developed a novel neuro-mechanical model-based controller (NMBC) that uses a personalized electromyography (EMG)-driven musculoskeletal (MSK) model to estimate lumbosacral joint loading. NMBC provided adaptive, subject- and load-specific assistive forces proportional to estimates of the active part of biological joint moments through a soft back support exosuit. Without a priori information, the maximum assistive forces of the cable were modulated across weights. Simultaneously, we applied a non-adaptive, kinematic-dependent, trunk inclination-based controller (TIBC). Both NMBC and TIBC reduced the mean and peak biomechanical metrics, although not all reductions were significant. TIBC did not modulate assistance across weights. NMBC showed larger reductions of mean than peak values, significant reductions during the erect stance and the cumulative compressive loads by 21% over multiple cycles in a cohort of 10 participants. Overall, NMBC targeted mean lumbosacral compressive forces during lifting without a priori information of the load being carried. This may facilitate the adoption of non-hindering wearable robotics in real-life scenarios. As NMBC is informed by an EMG-driven MSK model, it is possible to tune the timing of NMBC-generated torque commands to the exosuit (delaying or anticipating commands with respect to biological torques) to target further reduction of peak or mean compressive forces and muscle fatigue.

Low-density polymer foams pre-ionized by a well-controlled nanosecond pulse are excellent plasma targets to trigger direct laser acceleration (DLA) of electrons by sub-picosecond relativistic laser pulses. In this work, the influence of the nanosecond pulse on the DLA process is investigated. The density profile of plasma generated after irradiating foam with a nanosecond pulse was simulated with a two-dimensional hydrodynamic code, which takes into account the high aspect ratio of interaction and the microstructure of polymer foams. The obtained plasma density profile was used as input to the three-dimensional particle-in-cell code to simulate energy, angular distributions and charge carried by the directional fraction of DLA electrons. The modelling shows good agreement with the experiment and in general a weak dependence of the electron spectra on the plasma profiles, which contain a density up-ramp and a region of near-critical electron density. This explains the high DLA stability in pre-ionized foams, which is important for applications.

Regression is a fundamental prediction task common in data-centric engineering applications that involves learning mappings between continuous variables. In many engineering applications (e.g., structural health monitoring), feature-label pairs used to learn such mappings are of limited availability, which hinders the effectiveness of traditional supervised machine learning approaches. This paper proposes a methodology for overcoming the issue of data scarcity by combining active learning (AL) for regression with hierarchical Bayesian modeling. AL is an approach for preferentially acquiring feature-label pairs in a resource-efficient manner. In particular, the current work adopts a risk-informed approach that leverages contextual information associated with regression-based engineering decision-making tasks (e.g., inspection and maintenance). Hierarchical Bayesian modeling allow multiple related regression tasks to be learned over a population, capturing local and global effects. The information sharing facilitated by this modeling approach means that information acquired for one engineering system can improve predictive performance across the population. The proposed methodology is demonstrated using an experimental case study. Specifically, multiple regressions are performed over a population of machining tools, where the quantity of interest is the surface roughness of the workpieces. An inspection and maintenance decision process is defined using these regression tasks, which is in turn used to construct the active-learning algorithm. The novel methodology proposed is benchmarked against an uninformed approach to label acquisition and independent modeling of the regression tasks. It is shown that the proposed approach has superior performance in terms of expected cost—maintaining predictive performance while reducing the number of inspections required.