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Intravital microscopy (IVM) is a valuable method for biomedical characterization of dynamic processes, which has been applied to many fields such as neuroscience, oncology, and immunology. During IVM, vibration suppression is a major challenge due to the inevitable respiration and heartbeat from live animals. In this study, taking liver IVM as an example, we have unraveled the vibration inhibition effect of liquid bridges by studying the friction characteristics of a moist surface on the mouse liver. We confirmed the presence of liquid bridges on the liver through fluorescence imaging, which can provide microscale and nondestructive liquid connections between adjacent surfaces. Liquid bridges were constructed to sufficiently stabilize the liver after abdominal dissection by covering it with a polymer film, taking advantage of the high adhesion properties of liquid bridges. We further prototyped a microscope-integrated vibration-damping device with adjustable film tension to simplify the sample preparation procedure, which remarkably decreased the liver vibration. In practical application scenarios, we observed the process of liposome phagocytosis by liver Kupffer cells with significantly improved image and video quality. Collectively, our method not only provided a feasible solution to vibration suppression in the field of IVM, but also has the potential to be applied to vibration damping of precision instruments or other fields that require nondestructive ″soft″ vibration damping.

The exploration of a new conceptual strategy for improving the oxygen evolution reaction (OER) of earth-abundant electrocatalysts is critical. In this study, chiral copper oxide nanoflower is explored by a self-assembly method. The characterization suggests the chiral structure originates from the crystal plane-level helical stack of the secondary nanosheets. Of note, the assembly illustrates a record-high degree of spin polarization of 96%, indicating the ideal alignment of electron spin. Moreover, density function theory calculations show the chiral structure reducing the reaction energy barrier (REB) while switching the potential-determining step from *O→*OOH to *OH→*O. Together with the enhanced electrochemical active surface area and accelerated charge transfer, the production of ground-state triplet O 2 is improved via a spin-forbidden route that involves the singlet H 2 O/OH•. Consequently, the chiral nanoflower shows a overpotential of 308 mV at 10 mA cm -2 and a Tafel slope of 93.5 mV dec -1 , which is even superior to the commercial RuO 2 (310 mV, 101 mV dec -1 ). This study presents a new strategy for improving the OER activity by simultaneously enhancing electronic properties and lowering the REB of an non-noble electrocatalyst via chirality engineering., (© 2024 Wiley‐VCH GmbH.)

Energy harvesting from ubiquitous natural water vapor based on moisture electric generator (MEG) technology holds great potential to power portable electronics, the Internet of Things, and wireless transmission. However, most devices still encounter challenges of low output, and a single MEG complemented with another form of energy harvesting for achieving high power has seldom been demonstrated. Herein, we report a flexible and efficient hybrid generator capable of harvesting moisture and tribo energies simultaneously, both from the source of water droplets. The moisture electric and triboelectric layers are based on a water-absorbent citric acid (CA)-mediated polyglutamic acid (PGA) hydrogel and porous electret expanded polytetrafluoroethylene (E-PTFE), respectively. Such a waterproof E-PTFE film not only enables efficient triboelectrification with water droplets' contact but also facilitates water vapor to be transferred into the hydrogel layer for moisture electricity generation. A single hybrid generator under water droplets' impact delivers a DC voltage of 0.55 V and a peak current density of 120 μA cm -2 from the MEG, together with a simultaneous AC output voltage of 300 V and a current of 400 μA from the complementary water-based triboelectric generator (TEG) side. Such a hybrid generator can work even under harsh wild environments with 5 °C cold and saltwater impacts. Significantly, an optical alarm and wireless communication system for wild, complex, and emergency scenarios is demonstrated with power from the hybrid generators. This work expands the applications of water-based electricity generation technologies and provides insight into harvesting multiple potential energies in the natural environment with high output.

Designing catalysts with desirable oxygen evolution reaction (OER) performance under pH-universal conditions is of great significance to promote the development of hydrogen production. Herein, we successfully synthesized a crystalline-amorphous IrO x supported on perovskite oxide nanotubes to obtain IrO x @La 0.6 Ca 0.4 Fe 0.8 Ni 0.2 O 3 with superior OER performance in whole pH media. The overpotential of the IrO x @La 0.6 Ca 0.4 Fe 0.8 Ni 0.2 O 3 catalyst in media of pH 14, 7.2, and 1 has been demonstrated to be 120, 400, and 143 mV, respectively, with no significant element dissolution as well as double-layer capacitance decay after the durability test. Through comparative experiments with IrO x @CNT and the physical mixture of IrO x and La 0.6 Ca 0.4 Fe 0.8 Ni 0.2 O 3 , it is found that the strong metal-support interaction (SMSI) in IrO x @La 0.6 Ca 0.4 Fe 0.8 Ni 0.2 O 3 makes IrO x exist in an amorphous state rich in Ir 3+ , which is closely associated with the surface-active species Ir-OH. Through the regulation of Ir by a perovskite oxide support at the heterointerface, the reaction breaks through the limitation of the adsorbate evolution mechanism (AEM) and converts to a lattice-oxygen-mediated mechanism (LOM), which was fully demonstrated by the addition of the probe tetramethylammonium cation (TMA + ), a LOM reaction intermediate, to the electrolyte. This work fills the research gap of perovskite oxide supported Ir-based catalysts with heterogeneous structures, providing an excellent strategy for the structural design of efficient pH-universal OER catalysts for hydrogen production systems.

Avian feather intricate adaptable architecture to wing deformations has catalyzed interest in feathered flapping-wing aircraft with high maneuverability, agility, and stealth. Yet, to mimic avian integrated somatic sensation within stringent weight constraints, remains challenging. Here, we propose an avian-inspired embodied perception approach for biohybrid flapping-wing robots. Our feather-piezoelectric mechanoreceptor leverages feather-based vibration structures and flexible piezoelectric materials to refine and augment mechanoreception via coupled oscillator interactions and robust microstructure adhesion. Utilizing convolutional neural networks with the grey wolf optimizer, we develop tactile perception of airflow velocity and wing flapping frequency proprioception. This method also senses pitch angle via airflow direction and detects wing morphology through feather collisions. Our low-weight, accurate perception of flapping-wing robot flight states is validated by motion capture. This investigation constructs a biomechanically integrated embodied perception system in flapping-wing robots, which holds significant promise in reflex-based control of complex flight maneuvers and natural bird flight surveillance., (© 2024. The Author(s).)

Multiscale parameter optimization for laser peen forming (LPF) on 6005A-T6 aluminum alloy plates was conducted through a combination of simulation and experimentation. By obtaining the optimal parameter, this study aims to explore the constrained deformation and forming laws of the integral stiffened plates. Detailed descriptions were provided regarding the dynamic response process and transient behavior of aluminum alloy plates under ultrahigh strain rates, along with an in-depth analysis of the stress evolution. The results reveal that laser beam diameter and laser beam energy can achieve large range forming, while the number of tracks facilitates the precise deformation adjustment. During the 12-track LPF process, there is an overall upward trend in deformation values accompanied by a dynamic increase in the bend curvature. After static relaxation, the deformation value recovers to 55.2% of the final bending curvature. The chord direction scanning of stiffened plates exhibits a larger bending curvature, indicating its greater forming capacity for large-sized single unfolding direction formation; whereas, the unfolding direction scanning of stiffened plates excels in achieving efficient integrated two-way forming.

Future humanoid robots will be widely deployed in our daily lives. Motion planning and control in an unstructured, confined, and human-centered environment utilizing dexterity and a cooperative ability of dual-arm robots is still an open issue. We propose a globally guided dual-arm reactive motion controller (GGDRC) that combines the strengths of global planning and reactive methods. In this framework, a global planner module with a prospective task horizon provides feasible guidance in a Cartesian space, and a local reactive controller module addresses real-time collision avoidance and coordinated task constraints through the exploitation of dual-arm redundancy. GGDRC extends the start-of-the-art optimization-based reactive method for motion-restricted dynamic scenarios requiring dual-arm cooperation. We design a pick-handover-place task to compare the performances of these two methods. Results demonstrate that GGDRC exhibits accurate collision avoidance precision (5 mm) and a high success rate (84.5%).

Monitoring minuscule mechanical signals, both in magnitude and direction, is imperative in many application scenarios, e.g., structural health monitoring and robotic sensing systems. However, the piezoelectric sensor struggles to satisfy the requirements for directional recognition due to the limited piezoelectric coefficient matrix, and achieving sensitivity for detecting micrometer-scale deformations is also challenging. Herein, we develop a vector sensor composed of lead zirconate titanate-electronic grade glass fiber composite filaments with oriented arrangement, capable of detecting minute anisotropic deformations. The as-prepared vector sensor can identify the deformation directions even when subjected to an unprecedented nominal strain of 0.06%, thereby enabling its utility in accurately discerning the 5 μm-height wrinkles in thin films and in monitoring human pulse waves. The ultra-high sensitivity is attributed to the formation of porous ferroelectret and the efficient load transfer efficiency of continuous lead zirconate titanate phase. Additionally, when integrated with machine learning techniques, the sensor's capability to recognize multi-signals enables it to differentiate between 10 types of fine textures with 100% accuracy. The structural design in piezoelectric devices enables a more comprehensive perception of mechanical stimuli, offering a novel perspective for enhancing recognition accuracy., (© 2024. The Author(s).)

Background and Objectives: Image-based 2D/3D registration is a crucial technology for fluoroscopy-guided surgical interventions. However, traditional registration methods relying on a single X-ray image into surgical navigation systems. This study proposes a novel 2D/3D registration approach utilizing biplanar X-ray images combined with computed tomography (CT) to significantly reduce registration and navigation errors. The method is successfully implemented in a surgical navigation system, enhancing its precision and reliability., Methods: First, we simultaneously register the frontal and lateral X-ray images with the CT image, enabling mutual complementation and more precise localization. Additionally, we introduce a novel similarity measure for image comparison, providing a more robust cost function for the optimization algorithm. Furthermore, a multi-resolution strategy is employed to enhance registration efficiency. Lastly, we propose a more accurate coordinate transformation method, based on projection and 3D reconstruction, to improve the precision of surgical navigation systems., Results: We conducted registration and navigation experiments using pelvic, spinal, and femur phantoms. The navigation results demonstrated that the feature registration errors (FREs) in the three experiments were 0.505±0.063 mm, 0.515±0.055 mm, and 0.577±0.056 mm, respectively. Compared to the point-to-point (PTP) registration method based on anatomical landmarks, our method reduced registration errors by 31.3%, 23.9%, and 26.3%, respectively., Conclusion: The results demonstrate that our method significantly reduces registration and navigation errors, highlighting its potential for application across various anatomical sites. Our code is available at: https://github.com/SJTUdemon/2D-3D-Registration., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Due to the complexity of determining the initial rotor flux and detecting errors, conventional rotor flux observation methods are easily affected by direct current (DC) components and harmonics. To address this issue, this paper proposes an in-phase filter (IPF)-based rotor flux observation strategy for sensorless control of permanent magnet synchronous machines (PMSMs). The core components of the IPF consist of a double second-order generalized integrator (DSOGI) and a phase angle compensation transfer function (PACTF). The DSOGI provides a accurate electrical angular frequency, while the PACTF implements a phase correction to the v q signals. By employing IPF structure, accurate observations for rotor flux, electronic speed, and rotor position are achieved, which can be effectively used in the sensorless control of PMSMs, eliminating the need for magnitude and phase compensations. Finally, the proposed observation strategy is applied to an experimental bench of a PMSM, and its effectiveness is illustrated by experimental results. From experimental results, it can be concluded that the IPF is significantly better than the LPF, and 5% more accurate than the observer based on cascade second-order generalized integral(CSOGI) overall.' signals. By employing IPF structure, accurate observations for rotor flux, electronic speed, and rotor position are achieved, which can be effectively used in the sensorless control of PMSMs, eliminating the need for magnitude and phase compensations. Finally, the proposed observation strategy is applied to an experimental bench of a PMSM, and its effectiveness is illustrated by experimental results. From experimental results, it can be concluded that the IPF is significantly better than the LPF, and 5% more accurate than the observer based on cascade second-order generalized integral(CSOGI) overall., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

This study investigates the sound absorption mechanisms of a finite flexible perforated panel absorber. Different from existing work where the mechanisms were often investigated by comparing the sound absorption coefficient curves of different absorber configurations, a numerical approach, called virtual impedance tube (VIT) technique, is developed and used for the analysis. One advantage of this technique is the vast dataset generated can be used to investigate the sound absorption mechanisms from an energy standpoint. The developed VIT technique is first validated using the impedance tube test, where a proportion-integration-differentiation control algorithm is developed to maintain the incident sound at a desired sound pressure level. Then, the sound absorption mechanisms at three absorption peaks, i.e., hole-cavity controlled, panel-cavity controlled, and panel controlled, are investigated and the dominant energy dissipation mechanism at different sound pressure levels (SPLs) is revealed. Finally, an impedance model that takes account of the panel vibration and is applicable to various SPLs is proposed and validated., (© 2024 Acoustical Society of America.)

Ultrafast stimuli can stabilize metastable states of matter inaccessible by equilibrium means. Establishing the spatiotemporal link between ultrafast excitation and metastability is crucial to understand these phenomena. Here we utilize single-shot optical pump-X-ray probe measurements to capture snapshots of the emergence of a persistent polar vortex supercrystal in a heterostructure that hosts a fine balance between built-in electrostatic and elastic frustrations by design. By perturbing this balance with photoinduced charges, an initially heterogeneous mixture of polar phase disorders within a few picoseconds, leading to a state composed of disordered ferroelectric and suppressed vortex orders. On the picosecond-nanosecond timescales, transient labyrinthine fluctuations develop, accompanied by the recovery of the vortex order. On longer timescales, these fluctuations are progressively quenched by dynamical strain modulations, which drive the collective emergence of a single vortex supercrystal phase. Our results, corroborated by dynamical phase-field modelling, reveal non-equilibrium pathways following the ultrafast excitation of designer systems to persistent metastability., (© 2024. UChicago Argonne, LLC, Operator of Argonne National Laboratory, and the Authors, under exclusive licence to Springer Nature Limited.)

Pelvic fracture is a severe trauma with life-threatening implications. Surgical reduction is essential for restoring the anatomical structure and functional integrity of the pelvis, requiring accurate preoperative planning. However, the complexity of pelvic fractures and limited data availability necessitate labor-intensive manual corrections in a clinical setting. We describe in this paper a novel bidirectional framework for automatic pelvic fracture surgical planning based on fracture simulation and structure restoration. Our fracture simulation method accounts for patient-specific pelvic structures, bone density information, and the randomness of fractures, enabling the generation of various types of fracture cases from healthy pelvises. Based on these features and on adversarial learning, we develop a novel structure restoration network to predict the deformation mapping in CT images before and after a fracture for the precise structural reconstruction of any fracture. Furthermore, a self-supervised strategy based on pelvic anatomical symmetry priors is developed to optimize the details of the restored pelvic structure. Finally, the restored pelvis is used as a template to generate a surgical reduction plan in which the fragments are repositioned in an efficient jigsaw puzzle registration manner. Extensive experiments on simulated and clinical datasets, including scans with metal artifacts, show that our method achieves good accuracy and robustness: a mean SSIM of 90.7% for restorations, with translational errors of 2.88 mm and rotational errors of 3.18°for reductions in real datasets. Our method takes 52.9 s to complete the surgical planning in the phantom study, representing a significant acceleration compared to standard clinical workflows. Our method may facilitate effective surgical planning for pelvic fractures tailored to individual patients in clinical settings., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Objective: College students experience intense anxiety, for which biofeedback mindfulness techniques show effectiveness in relief. However, typical biofeedback products often lead to user fatigue and boredom because of a single or fixed feedback and lack of focus on mindfulness enhancement. Materials and Methods: In this research, we developed Mindjourney, a VR-based respiratory feedback mindfulness system, designed to enhance mindfulness and alleviate anxiety through continuous/noncontinuous feedback and nonjudgmental reward/punishment for self-perception and attention management. A randomized controlled trial involved 72 college students, split equally into short-term ( n = 34, age: 23.11 ± 1.729) and 4-week long-term ( n = 38, age: 24.12 ± 1.408) groups, with equal randomization for intervention and control groups. Pre/postintervention tests were measured by using Trait Anxiety Inventory (TAI) and Five Facet Mindfulness Questionnaire (FFMQ) for long-term groups and Galvanic Skin Response and State Anxiety Inventory (SAI) for short-term groups. Results: Results showed that the long-term intervention group showed a significant increase in mindfulness ( P = 0.001 for FFMQ total score). Furthermore, observe and act with awareness subscales showed significant increase after intervention ( P = 0.034 for observe , P < 0.001 for act with awareness ) compared with the control group. Both intervention groups demonstrated a significant decrease in anxiety levels compared with the control groups ( P = 0.049 for SAI, P = 0.01 for TAI). Moreover, participants expressed high interest in this biofeedback mindfulness system and willingness for long-term usage. Conclusion: The proposed biofeedback mindfulness practice system could potentially facilitate mindfulness practice and serve as a convenient tool for anxiety relief in campus college students.

Ubiquitous moisture is of particular interest for sustainable power generation and self-powered electronics. However, current moisture electric generators (MEGs) can only harvest moisture energy in the air, which tremendously limits the energy harvesting efficiency and practical application scenarios. Herein, the operationality of MEG from air to underwater environment, through a sandwiched engineered-hydrogel device with an additional waterproof breathable membrane layer allowing water vapor exchange while preventing liquid water penetration, is expanded. Underwater environment, the device can spontaneously deliver a voltage of 0.55 V and a current density of 130 µA cm -2 due to the efficient ion separation assisted by negative ions confinement in hydrogel networks. The output can be maintained even under harsh underwater environment with 10% salt concentration, 1 m s -1 disturbing flow, as well as >40 kPa hydraulic pressure. The engineered hydrogel used for MEG also exhibits excellent self-healing ability, flexibility, and biocompatibility. As the first demonstration of practical applications in self-powered underwater electronics, the MEG device is successfully powering a wireless emitter for remote communication in water. This new type of MEG offers an innovative route for harvesting moisture energy underwater and holds promise in the creation of a new range of innovative electronic devices for marine Internet-of-Things., (© 2024 The Author(s). Advanced Science published by Wiley‐VCH GmbH.)

Place recognition is widely used to re-localize robots in pre-built point cloud maps for navigation. However, current place recognition methods can only be used to recognize previously visited places. Moreover, these methods are limited by the requirement of using the same types of sensors in the re-localization process and the process is time consuming. In this paper, a template-matching-based global re-localization framework is proposed to address these challenges. The proposed framework includes an offline building stage and an online matching stage. In the offline stage, virtual LiDAR scans are densely resampled in the map and rotation-invariant descriptors can be extracted as templates. These templates are hierarchically clustered to build a template library. The map used to collect virtual LiDAR scans can be built either by the robot itself previously, or by other heterogeneous sensors. So, an important feature of the proposed framework is that it can be used in environments that have never been visited by the robot before. In the online stage, a cascade coarse-to-fine template matching method is proposed for efficient matching, considering both computational efficiency and accuracy. In the simulation with 100 K templates, the proposed framework achieves a 99% success rate and around 11 Hz matching speed when the re-localization error threshold is 1.0 m. In the validation on The Newer College Dataset with 40 K templates, it achieves a 94.67% success rate and around 7 Hz matching speed when the re-localization error threshold is 1.0 m. All the results show that the proposed framework has high accuracy, excellent efficiency, and the capability to achieve global re-localization in heterogeneous maps.

Archwire bending is the key to orthodontic treatment, and multi-time bendings are inevitable during manual and robotic automated bending. The purpose of this paper is to quantitatively evaluate the mechanical effects of the different preparation modes and to compare the mechanical properties of the orthodontic loops in one and multiple bends. Three types of typical stainless steel orthodontic loops (vertical loop, T-loop, and L-loop) were used to quantify the mechanical effect of patterns for preparation by experimental comparison between loops with different bending times by using an orthodontic force tester (OFT). The results were statistically analyzed by t-test. The fracture test of the stainless steel archwire was also carried out, and the bending times at fracture were recorded. Results of the tests indicate that one-time and multi-time bending have a significant mechanical effect on orthodontic appliances. Multi-time bending causes significant mechanical decreases and can damage the appliances.

The present study focuses on a middle-arch dual-channel municipal solid waste (MSW) incinerator facing issues of high NO x emission and overheating. To address these problems and optimize the incinerator, an advanced numerical simulation method was employed to comprehensively assess its bed combustion, freeboard combustion, and NO x emission characteristics. A multiphase fuel bed model considering large-particle characteristics of MSW was developed, coupled with a three-dimensional (3D) model for combustion in freeboard. The analysis revealed that the observed issues stem from multiple factors, including primary-to-secondary air ratio, flame propagation in bed, release of volatiles from bed, and distribution and mixing of components in freeboard. Reducing the proportion of primary air and correspondingly increasing secondary air effectively alleviated the localized overheating in the furnace and reduced NO x emission. Further adjustments to the distribution of primary air in three stages delaying air supply toward the burnout stage, together with the decrease in the grate movement speed, can better control the amount and speciation of N released from the bed. Implementing a counterflow mixing strategy with NH 3 in the front channel and NO in the rear channel can greatly reduce the original NO x emission concentration to 95.94 mg/(N·m 3 ), as predicted by a numerical simulation. Subsequent practical adjustments to an actual incinerator led to notable improvements, clearly optimizing the localized high-temperature issues at various locations, especially the front channel suffering severe slagging problems, with the temperature reduced from 1118 to 957 °C. Meanwhile, NO x emission concentration decreased from 200 mg/(N·m 3 ) to around 50 mg/(N·m 3 ), with no negative effect on the boiler load., Competing Interests: The authors declare no competing financial interest., (© 2024 The Authors. Published by American Chemical Society.)

Transformation of lignin to syngas can turn waste into treasure yet remains a tremendous challenge because of its naturally evolved stubborn structure. In this work, light-driven reforming of natural lignin in water for green syngas production is explored using Pt-decorated InGaN nanowires. The spectroscopic characterizations, isotope, and model compound experiments, as well as density function theory calculation, disclose that among a variety of groups including aromatic ring, -OH, -OCH 3 , -C 3 H 7 with complex chemical bonds of O-H, C-H, C-C, C-O, etc., InGaN nanowires are cooperative with Pt for preferably breaking the C-O bond of the rich O-CH 3 group in lignin to liberating ⋅CH 3 by photogenerated holes with a minimum dissociation energy of 2.33 eV. Syngas are subsequently yielded from the continuous evolution of ⋅CH 3 and ⋅OH from photocatalytic reforming of lignin in water. Together with the superior optoelectronic attributes of Pt-decorated InGaN nanowires, the evolution rate of syngas approaches 43.4 mol ⋅ g -1  ⋅ h -1 with tunable H 2 /CO ratios and a remarkable turnover number (TON) of 150, 543 mol syngas per mol Pt. Notably, the architecture demonstrates a high light efficiency of 12.1 % for syngas generation under focused light without any extra thermal input. Outdoor test ascertains the viability of producing syngas with the only inputs of natural lignin, water, and sunlight, thus presenting a low-carbon route for synthesizing transportation fuels and value-added chemicals., (© 2024 Wiley-VCH GmbH.)

Solid Oxide Electrolysis Cells (SOECs) can electro-reduce carbon dioxide to carbon monoxide, which not only effectively utilizes greenhouse gases, but also converts excess electrical energy into chemical energy. Perovskite-based oxides with exsolved metal nanoparticles are promising cathode materials for direct electrocatalytic reduction of CO 2 through SOECs, and have thus received increasing attention. In this work, we doped Pr 0.7 Ba 0.3 MnO 3-δ at the B site, and after reduction treatment, metal nanoparticles exsolved and precipitated on the surface of the cathode material, thereby establishing a stable metal-oxide interface structure and significantly improving the electrocatalytic activity of the SOEC cathode materials. Through research, among the Pr 0.7 Ba 0.3 Mn 1-x Ni x O 3-δ (PBMN x = 0-1) cathode materials, it has been found that the Pr 0.7 Ba 0.3 Mn 0.9 Ni 0.1 O 3-δ (PBMN 0.1 ) electrode material exhibits greater catalytic activity, with a CO yield of 5.36 mL min -1 cm -2 and a Faraday current efficiency of ~99%. After 100 h of long-term testing, the current can still remain stable and there is no significant change in performance. Therefore, the design of this interface has increasing potential for development.

Legged soccer robots present a significant challenge in robotics owing to the need for seamless integration of perception, manipulation, and dynamic movement. While existing models often depend on external perception or static techniques, our study aims to develop a robot with dynamic and untethered capabilities. We have introduced a motion planner that allows the robot to excel in dynamic shooting and dribbling. Initially, it identifies and predicts the position of the ball using a rolling model. The robot then pursues the ball, using a novel optimization-based cycle planner, continuously adjusting its gait cycle. This enables the robot to kick without stopping its forward motion near the ball. Each leg is assigned a specific role (stance, swing, pre-kick, or kick), as determined by a gait scheduler. Different leg controllers were used for tailored tiptoe trajectory planning and control. We validated our approach using real-world penalty shot experiments (5 out of 12 successful), cycle adjustment tests (11 out of 12 successful), and dynamic dribbling assessments. The results demonstrate that legged robots can overcome onboard capability limitations and achieve dynamic mobility and manipulation., Competing Interests: Author Jiangwei Zhong was employed by the company Lenovo. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

In situ bioprinting enables precise 3D printing inside the human body using modified bioprinters with thermosensitive bioinks such as gelatin methacrylate (GelMA). However, these devices lack refined temperature-regulated mechanisms essential for ensuring bioink viscosity, as compared to traditional bio-3D printers. Addressing this challenge, this study presents a temperature-regulated printhead designed to improve the fabrication of thermosensitive bioink scaffolds in in situ bioprinting, integrated into a UR5 robotic arm. Featuring a closed-loop system, it achieves a temperature steady error of 1 °C and a response time of approximately 1 min. The effectiveness of the printer was validated by bioprinting multilayer lattice 3D bioscaffolds. Comparisons were made with or without temperature control using different concentrations of GelMA + LAP. The deformation of the bioscaffolds under both conditions was analyzed, and cell culture tests were conducted to verify viability. Additionally, the rheology and mechanical properties of GelMA were tested. A final preliminary in situ bioprinting experiment was conducted on a model of a damaged femur to demonstrate practical application. The fabrication of this printhead is entirely open source, facilitating easy modifications to accommodate various robotic arms. We encourage readers to advance this prototype for application in increasingly complex in situ bioprinting situations, especially those utilizing thermosensitive bioinks., Competing Interests: The authors declare no competing financial interest., (© 2024 The Authors. Published by American Chemical Society.)

At the Worldwide Developers Conference in June 2023, Apple introduced the Vision Pro. The Apple Vision Pro (AVP) is a mixed reality headset; more specifically, it is a virtual reality device with an additional video see-through capability. The video see-through capability turns the AVP into an augmented reality (AR) device. The AR feature is enabled by streaming the real world via cameras on the (virtual reality) screens in front of the user's eyes. This is, of course, not unique and is similar to other devices, such as the Varjo XR-3 (Varjo Technologies Oy). Nevertheless, the AVP has some interesting features, such as an inside-out screen that can show the headset wearer's eyes to "outsiders," and a button on the top, called the "digital crown," that allows a seamless blend of digital content with the user's physical space by turning it. In addition, it is untethered, except for the cable to the battery, which makes the headset more agile, compared to the Varjo XR-3. This could actually come closer to "The Ultimate Display," which Ivan Sutherland had already sketched in 1965. After a great response from the media and social networks to the release, we were able to test and review the new AVP ourselves in March 2024. Including an expert survey with 13 of our colleagues after testing the AVP in our institute, this Viewpoint explores whether the AVP can overcome clinical challenges that AR especially still faces in the medical domain; we also go beyond this and discuss whether the AVP could support clinicians in essential tasks to allow them to spend more time with their patients., (©Jan Egger, Christina Gsaxner, Gijs Luijten, Jianxu Chen, Xiaojun Chen, Jiang Bian, Jens Kleesiek, Behrus Puladi. Originally published in JMIR Serious Games (https://games.jmir.org), 18.09.2024.)

Sweat contains abundant physiological and metabolic data to evaluate an individual's physical health. Since the non-exercise sweat secretion rate is low, with an average value of 1-10 μl h -1 cm -2 , sweat is generally collected during exercise for existing wearable sweat sensors. To expand their applications to include daily scenarios, these sensors developed for sports and fitness are challenged by the difficulty of collecting trace amounts of sweat. This study proposes a wearable patch inspired by the hierarchical structure of Sarracenia trichomes, allowing for the spontaneous and fast collection of a small amount of secreted sweat. The patch contains microfluidic channels featuring a 20 μm-wide rib structure, fully utilizing the capillary force, thereby eliminating the issue of sweat hysteresis. Furthermore, with only 0.5 μl of the sweat secreted at the collection site, it can converge on the detection medium located within the center reservoir. Volunteer verification demonstrated a twofold increase in sweat collection efficiency compared to traditional wearable patches. This patch serves as an efficient sweat-collection configuration, promising potential for diverse in situ sweat colorimetric analyses., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Zhinan Zhang reports financial support was provided by State Key Laboratory of Mechanical System and Vibration. Zhinan Zhang reports financial support was provided by the open project of National Research Center for Translational Medicine, Shanghai. Zhinan Zhang reports financial support was provided by High-end Foreign Experts Recruitment Plan. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Metal hydrides are crucial intermediates in numerous catalytic reactions. Intensive efforts have been dedicated to constructing molecular metal hydrides, where toxic precursors and delicate mediators are usually involved. Herein, we demonstrate a facile pressure-induced methodology to generate a cost-effective heterogeneous electrocatalytic metal hydride surface for sustainable hydrogen transfer. Taking carbon dioxide (CO 2 ) electroreduction as a model system and zinc (Zn), a well-known carbon monoxide (CO)-selective catalyst, as a model catalyst, we showcase a homogeneous-type hydrogen atom transfer process induced by heterogeneous hydride surfaces, enabling direct hydrogenation pathways traditionally considered "prohibited". Specifically, the maximal Faradaic efficiency for formate is enhanced by ~fivefold to 83% under ambient conditions. Experimental and theoretical analyses reveal that unlike the distal hydrogenation route for CO 2 to CO over pristine Zn, the Zn hydride surface enables direct hydrogenation at the carbon site of CO 2 to form formate. This work provides a promising material platform for sustainable synthesis., (© 2024. The Author(s).)

Orbital blowout fracture (OBF) is a disease that can result in herniation of orbital soft tissue, enophthalmos, and even severe visual dysfunction. Given the complex and diverse types of orbital wall fractures, reconstructing the orbital wall presents a significant challenge in OBF repair surgery. Accurate surgical planning is crucial in addressing this issue. However, there is currently a lack of efficient and precise surgical planning methods. Therefore, we propose an intelligent surgical planning method for automatic OBF reconstruction based on a prior adversarial generative network (GAN). Firstly, an automatic generation method of symmetric prior anatomical knowledge (SPAK) based on spatial transformation is proposed to guide the reconstruction of fractured orbital wall. Secondly, a reconstruction network based on SPAK-guided GAN is proposed to achieve accurate and automatic reconstruction of fractured orbital wall. Building upon this, a new surgical planning workflow based on the proposed reconstruction network and 3D Slicer software is developed to simplify the operational steps. Finally, the proposed surgical planning method is successfully applied in OBF repair surgery, verifying its reliability. Experimental results demonstrate that the proposed reconstruction network achieves relatively accurate automatic reconstruction of the orbital wall, with an average DSC of 92.35 ± 2.13% and a 95% Hausdorff distance of 0.59 ± 0.23 mm, markedly outperforming the compared state-of-the-art networks. Additionally, the proposed surgical planning workflow reduces the traditional planning time from an average of 25 min and 17.8 s to just 1 min and 35.1 s, greatly enhancing planning efficiency. In the future, the proposed surgical planning method will have good application prospects in OBF repair surgery., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Materials with electromechanical coupling are essential for transducers and acoustic devices as reversible converters between mechanical and electrical energy 1-6 . High electromechanical responses are typically found in materials with strong structural instabilities, conventionally achieved by two strategies-morphotropic phase boundaries 7 and nanoscale structural heterogeneity 8 . Here we demonstrate a different strategy to accomplish ultrahigh electromechanical response by inducing extreme structural instability from competing antiferroelectric and ferroelectric orders. Guided by the phase diagram and theoretical calculations, we designed the coexistence of antiferroelectric orthorhombic and ferroelectric rhombohedral phases in sodium niobate thin films. These films show effective piezoelectric coefficients above 5,000 pm V -1 because of electric-field-induced antiferroelectric-ferroelectric phase transitions. Our results provide a general approach to design and exploit antiferroelectric materials for electromechanical devices., (© 2024. The Author(s).)

The dense mechanoreceptors in human fingertips enable texture discrimination. Recent advances in flexible electronics have created tactile sensors that effectively replicate slowly adapting (SA) and rapidly adapting (RA) mechanoreceptors. However, the influence of dermatoglyphic structures on tactile signal transmission, such as the effect of fingerprint ridge filtering on friction-induced vibration frequencies, remains unexplored. A novel multi-layer flexible sensor with an artificially synthesized skin surface capable of replicating arbitrary fingerprints is developed. This sensor simultaneously detects pressure (SA response) and vibration (RA response), enabling texture recognition. Fingerprint ridge patterns from notable historical figures - Rosa Parks, Richard Nixon, Martin Luther King Jr., and Ronald Reagan - are fabricated on the sensor surface. Vibration frequency responses to assorted fabric textures are measured and compared between fingerprint replicas. Results demonstrate that fingerprint topography substantially impacts skin-surface vibrational transmission. Specifically, Parks' fingerprint structure conveyed higher frequencies more clearly than those of Nixon, King, or Reagan. This work suggests individual fingerprint ridge morphological variation influences tactile perception and can confer adaptive advantages for fine texture discrimination. The flexible bioinspired sensor provides new insights into human vibrotactile processing by modeling fingerprint-filtered mechanical signals at the finger-object interface., (© 2024 The Author(s). Advanced Science published by Wiley‐VCH GmbH.)

This paper proposes a differential privacy decentralized zeroth-order gradient tracking optimization (DP-DZOGT) algorithm for solving optimization problems of decentralized systems, where the gradient information of the function is unknown. To address the challenge of unknown gradient information, a one-point zeroth-order gradient estimator (OPZOGE) is constructed, which can estimate the gradient based on the function value and guide the update of decision variables. Additionally, to prevent privacy leakage of agents, random noise is introduced into both the state and the gradient of the agents, which effectively enhances the level of privacy protection. The linear convergence of the proposed DP-DZOGT under a fixed step size can be guaranteed. Moreover, it has been applied to the fields of smart grid (SG) and decentralized federated learning (DFL). Finally, the effectiveness of the algorithm is validated through three numerical simulations., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

Compared to lithium (Li) anode, the alloy/Li-alloy anodes show more compatible with sulfide solid electrolytes (SSEs), and are promising candidates for practical SSE-based all-solid-state Li batteries (ASSLBs). In this work, a porous Li-Al alloy (LiAl-p) anode is crafted using a straightforward mechanical pressing method. Various characterizations confirm the porous nature of such anode, as well as rich oxygen species on its surface. To the best knowledge, such LiAl-p anode demonstrates the best room temperature cell performance in comparison with reported Li and alloy/Li-alloy anodes in SSE-based ASSLBs. For example, the LiAl-p symmetric cells deliver a record critical current density of 6.0 mA cm -2 and an ultralong cycling of 5000 h; the LiAl-p|LiNi 0.8 Co 0.1 Mn 0.1 O 2 full cells achieve a high areal capacity of 11.9 mAh cm -2 and excellent durability of 1800 cycles. Further in situ and ex situ experiments reveal that the porous structure can accommodate volume changes of LiAl-p and ensure its integrity during cycling; and moreover, a robust Li inorganics-rich solid electrolyte interphase can be formed originated from the reaction between SSE and surface oxygen species of LiAl-p. This study offers inspiration for designing high-performance alloy anodes by focusing on designing special architecture to alleviate volume change and constructing stable interphase., (© 2024 Wiley‐VCH GmbH.)

Purpose: Preoperative planning of maxillary anterior dental implant is a prerequisite to ensuring that the implant achieves the proper three-dimensional (3D) pose, which is essential for its long-term stability. However, the current planning process is labor-intensive and subjective, relying heavily on the surgeon's experience. Consequently, this paper proposes an automatic method for computing the optimal pose of the dental implant., Methods: The method adopts the principle of prosthetically guided dental implant placement. Initially, the prosthesis coordinate system is established to determine the implant candidate orientations. Subsequently, virtual slices of the maxilla in the buccal-palatal direction are generated according to the prosthesis position. By extracting feature points from the virtual slices, the implant candidate starting points are acquired. Then, a candidate pose set is obtained by combining these candidate starting points and orientations. Finally, a pose evaluation indicator is introduced to determine the optimal implant pose from this set., Results: Twenty-two cases were utilized to validate the method. The results show that the method could determine an ideal pose for the dental implant, with the average minimum distance between the implant and the left tooth root, the right tooth root, the palatal side, and the buccal side being 2.57 ± 0.53 mm, 2.59 ± 0.65 mm, 0.74 ± 0.19 mm, 1.83 ± 0.16 mm, respectively. The planning time was less than 9 s., Conclusion: Unlike manual planning, the proposed method can efficiently and accurately complete maxillary anterior dental implant planning, providing a theoretical analysis of the success rate of the implant. Thus, it has great potential for future clinical application., (© 2024. CARS.)

Purpose: Reverse shoulder arthroplasty has demonstrated excellent clinical efficacy for patients with shoulder joint diseases and is increasingly in demand. Traditional surgery faces challenges such as limited exposed surfaces and a narrow field of vision, leading to a shorter prosthesis lifespan and a higher risk of complications. In this study, an optical navigation system was proposed to assist surgeons in real-time tracking of the surgical scene., Methods: Our optical navigation system was developed using the NDI Polaris Spectra device and several open-source platforms. The first step involved using the preoperative medical image to plan screw implantation paths. Real-time tracking of the patient phantom or cadaver and the surgical instrument was achieved through registration and calibration algorithms. Surgeons were guided on drilling through visualization methods. Postoperative results were compared with the planned implantation paths, and an algorithm was introduced to correct errors caused by the incorrect beginning points., Results: Experiments involved three scapula cadavers and their corresponding phantoms with identical anatomy. For each experiment, three holes were completed with drills with diameters of 3.2 mm and 8.0 mm, respectively. Comparisons between the postoperative actual screw implantation paths and the preoperative planned implantation paths revealed an entry error of 1.05 ± 0.15 mm and an angle error of 2.47 ± 0.55° for phantom experiments. For cadaver experiments, the entry error was 1.53 ± 0.22 mm, and the angle error was 4.91 ± 0.78°., Conclusion: Our proposed optical navigation system successfully achieved real-time tracking of the surgical site, encompassing the patient phantom or cadaver and surgical instrument, thereby aiding surgeons in achieving precise surgical outcomes. Future study will explore the integration of robots to further enhance surgical efficiency and effectiveness., (© 2024. CARS.)

Objectives: To assess the performance of deep learning (DL) in the detection, classification, and segmentation of maxillary sinus diseases., Methods: An electronic search was conducted by two reviewers on databases including PubMed, Scopus, Cochrane, and IEEE. All English papers published no later than February 7, 2024, were evaluated. Studies related to DL for diagnosing maxillary sinus diseases were also searched in journals manually., Results: Fourteen of 1167 studies were eligible according to the inclusion criteria. All studies trained DL models based on radiographic images. Six studies applied to detection tasks, one focused on classification, two segmented lesions, and five studies made a combination of two types of DL models. The accuracy of the DL algorithms ranged from 75.7% to 99.7%, and the area under curves (AUC) varied between 0.7 and 0.997., Conclusion: DL can accurately deal with the tasks of diagnosing maxillary sinus diseases. Students, residents, and dentists could be assisted by DL algorithms to diagnose and make rational decisions on implant treatment related to maxillary sinuses., (© The Author(s) 2024. Published by Oxford University Press on behalf of the British Institute of Radiology and the International Association of Dentomaxillofacial Radiology. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Pelvic fracture is a complex and severe injury. Accurate diagnosis and treatment planning require the segmentation of the pelvic structure and the fractured fragments from preoperative CT scans. However, this segmentation is a challenging task, as the fragments from a pelvic fracture typically exhibit considerable variability and irregularity in the morphologies, locations, and quantities. In this study, we propose a novel dual-stream learning framework for the automatic segmentation and category labeling of pelvic fractures. Our method uniquely identifies pelvic fracture fragments in various quantities and locations using a dual-branch architecture that leverages distance learning from bone fragments. Moreover, we develop a multi-size feature fusion module that adaptively aggregates features from diverse receptive fields tailored to targets of different sizes and shapes, thus boosting segmentation performance. Extensive experiments on three pelvic fracture datasets from different medical centers demonstrated the accuracy and generalizability of the proposed method. It achieves a mean Dice coefficient and mean Sensitivity of 0.935±0.068 and 0.929±0.058 in the dataset FracCLINIC, and 0.955±0.072 and 0.912±0.125 in the dataset FracSegData, which are superior than other comparing methods. Our method optimizes the process of pelvic fracture segmentation, potentially serving as an effective tool for preoperative planning in the clinical management of pelvic fractures., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Heterogeneous thermocatalysis of formic acid dehydrogenation by metals in solution is of great importance for chemical storage and production of hydrogen. Insightful understanding of the complicated formic acid dehydrogenation kinetics at the metal-solution interface is challenging and yet essential for the design of efficient heterogeneous formic acid dehydrogenation systems. In this work, formic acid dehydrogenation kinetics is initially studied from a perspective of electrochemistry by decoupling this reaction on Pd catalyst into two short-circuit half reactions, formic acid oxidation reaction and hydrogen evolution reaction and manipulating the electrical double layer impact from the solution side. The pH-dependences of formic acid dehydrogenation kinetics and the associated cation effect are attributed to the induced change of electric double layer structure and potential by means of electrochemical measurements involving kinetic isotope effect, in situ infrared spectroscopy as well as grand canonical quantum mechanics calculations. This work showcases how kinetic puzzles on some important heterogeneous catalytic reactions can be tackled by electrochemical theories and methodologies., (© 2024. The Author(s).)

The study of energy correlations in catalytic reactions plays a pivotal role in guiding catalyst development. This paper focuses on the investigation of energy linear relationships in methanol synthesis from CO 2 hydrogenation on copper surfaces, systematically exploring energy parameters including activation energy, reaction energy and adsorption energy. A comparative analysis of the adsorption characteristics and reaction parameters in the formate, formic acid and reverse water-gas shift pathways is conducted, laying the data foundation for subsequent linear studies. Then, descriptors are extracted from electronic, energetic and structural information and further integrated using the sure independence screening and sparsifying operator (SISSO) method to establish an energy description paradigm characterized by interpretability and accuracy. Additionally, reactions are further categorized based on hydrogenation types to mitigate the adverse effects of redundant data points. Finally, the summarized reaction descriptors are extended to Cu-based alloy systems to highlight the rationality and transferability of the developed descriptors.

Photo-thermal-coupling ammonia decomposition presents a promising strategy for utilizing the full-spectrum to address the H 2 storage and transportation issues. Herein, we exhibit a photo-thermal-catalytic architecture by assembling gallium nitride nanowires-supported ruthenium nanoparticles on a silicon for extracting hydrogen from ammonia aqueous solution in a batch reactor with only sunlight input. The photoexcited charge carriers make a predomination contribution on H 2 activity with the assistance of the photothermal effect. Upon concentrated light illumination, the architecture significantly reduces the activation energy barrier from 1.08 to 0.22 eV. As a result, a high turnover number of 3,400,750 is reported during 400 h of continuous light illumination, and the H 2 activity per hour  is nearly 1000 times higher than that under the pure thermo-catalytic conditions. The reaction mechanism is extensively studied by coordinating experiments, spectroscopic characterizations, and density functional theory calculation. Outdoor tests validate the viability of such a multifunctional architecture for ammonia decomposition toward H 2 under natural sunlight., (© 2024. The Author(s).)

In this study, a new-generation tissue-engineered bone capable of temporally regulating the immune response, balancing proinflammatory and anti-inflammatory activities, and facilitating bone regeneration and repair to address the challenges of delayed healing and nonunion in large-sized bone defects, is innovatively developed. Using the innovative techniques including multiphysics-assisted combined decellularization, side-chain biochemical modification, and sterile freeze-drying, a novel photocurable extracellular matrix hydrogel, methacrylated bone-derived decellularized extracellular matrix (bdECM-MA), is synthesized. After incorporating the bdECM-MA with silicon-substituted calcium phosphate and bone marrow mesenchymal stem cells, the tissue-engineered bone is fabricated through digital light processing 3D bioprinting. This study provides in vitro confirmation that the engineered bone maintains high cellular viability while achieving MPa-level mechanical strength. Moreover, this engineered bone exhibits excellent osteogenesis, angiogenesis, and immunomodulatory functions. One of the molecular mechanisms of the immunomodulatory function involves the inhibition of the p38-MAPK pathway. A pioneering in vivo discovery is that the natural biomaterial-based tissue-engineered bone demonstrates sequential immunomodulatory properties that activate proinflammatory and anti-inflammatory responses in succession, significantly accelerating the repair of bone defects. This study provides a new research basis and an effective method for developing autogenous bone substitute materials and treating large-sized bone defects., (© 2024 Wiley‐VCH GmbH.)

Microplastics (MPs), omnipresent contaminants in the ocean, could be carried by seawater intrusion into coastal aquifers, which might affect the fate of heavy metals existing in aquifers. Herein, we investigated the release behavior of arsenic (As) in coastal aquifers during MPs-containing seawater intrusion by applying laboratory experiment and numerical simulation. We found that seawater with marine MPs enhanced the release of As in aquifers, especially for dissolved As(V) and colloidal As. Negatively charged MPs competed with As(V) for the adsorption sites on iron (hydr)oxides in aquifers, resulting in the desorption of As(V). In addition, MPs could promote the release of Fe-rich colloids by imparting negative charge to its surface and providing it with sufficient repulsive force to detach from the matrix, thereby leading to the release of As associated with Fe-rich colloid. We also developed a modeling approach that well described the transport of As in coastal aquifer under the impact of MPs, which coupled variable density flow and kinetically controlled colloids transport with multicomponent reactive transport model. Our findings elucidated the enhancement of MPs on the release of As in aquifers during seawater intrusion, which provides new insights into the risk assessment of MPs in coastal zones., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Objective: Electronic medical records (EMRs) contain patients' medical and health information. The Utilization of EMRs for assisted diagnosis is of significant importance for the rehabilitation of spinal cord injury (SCI) patients. Therefore, this study proposes a decision-making model for rehabilitation programs of SCI patients based on EMRs., Methods: First, an Electronic Medical Records (EMR) dataset comprising 1252 Spinal Cord Injury (SCI) patients was constructed, and data preprocessing was completed. Second, the Random Forest (RF) feature extraction algorithm was utilized to select case features with high contribution levels. Then, to address the imbalance issue in EMRs, a multi-label learning framework based on the improved MLSMOTE was adopted. Finally, seven multi-label classification models were employed to predict patients' physical therapy (PT) prescriptions., Results: The proposed improved MLSMOTE multi-label learning framework can solve the problem of class imbalance. Compared with the other six models, the CC model has improved significantly in many metrics. Its hamming loss and ranking loss were 0.1388 and 0.2467, and precision, recall, and F1-score were 83.33 %, 81.20 %, and 79.82 % respectively., Conclusions: The improved MLSMOTE multi-label learning framework proposed in this study can make full use of the information in EMRs and effectively improve the decision-making accuracy of rehabilitation treatment programs., Competing Interests: The authors declare that they have no conflict of interest., (© 2024 The Authors. Published by Elsevier Ltd.)

Mixed potential ammonia (NH 3 ) sensors with the Fe- and Mo-codoped BiVO 4 sensing electrode and Ag reference electrode based on the yttria-stabilized zirconia solid electrolyte were developed. Fe- and Mo-doped BiVO 4 sensing materials were prepared using solution combustion synthesis and then characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), energy-dispersive spectroscopy (EDS), and X-ray photoelectron spectroscopy (XPS). It was observed that Fe doping could greatly improve the response rate, while Mo doping could enhance the response signal (Δ U ) and sensitivity. Based on the optimal doping ratio of Fe and Mo each, the synergistic enhancement of the performance by Fe and Mo codoping was investigated. The sensor coated by BiV 0.75 Fe 0.2 Mo 0.05 O δ materials exhibited a prominent sensing performance to a low concentration of 10-50 ppm of NH 3 at 525 °C with the outstanding sensitivity of -148.988 mV/decade. Fe and Mo doping also improved the selectivity of the sensor to NH 3 , with the relative deviations less than ±8% of other typical gases' interference including NO, NO 2 , CO, CO 2 , and CH 4 . Besides, the sensor showed good resistance to fluctuations in the oxygen concentration and favorable stability against changes in the water vapor concentration. In addition, the sensor also exhibited good long-term stability. The mixed potential response mechanism was further discussed and analyzed through polarization curves as well as through gas chromatography and infrared absorption spectroscopy.

Emerging task-agnostic control methods offer a promising avenue for versatile assistance in powered exoskeletons without explicit task detection, but typically come with a performance trade-off for specific tasks and/or users. One such approach employs data-driven optimization of an energy shaping controller to provide naturalistic assistance across essential daily tasks with passivity/stability guarantees. This study introduces a novel control method that merges energy shaping with a machine learning-based classifier to deliver optimal support accommodating diverse individual tasks and users. The classifier detects transitions between multiple tasks and gait patterns in order to employ a more optimal, task-agnostic controller based on the weighted sum of multiple optimized energy-shaping controllers. To demonstrate the efficacy of this integrated control strategy, an in-silico assessment is conducted over a range of gait patterns and tasks, including incline walking, stairs ascent/descent, and stand-to-sit transitions. The proposed method surpasses benchmark approaches in 5-fold cross-validation ( p < 0.05 ), yielding 93.17 ± 7.39% cosine similarity and 77.92 ± 19.76% variance-accounted-for across tasks and users. These findings highlight the control approach's adaptability in aligning with human joint moments across various tasks.

Virtual reality (VR) technology has experienced a steady rise and has been widely applied in the field of rehabilitation. The integration of VR technology in rehabilitation has shown promising results in enhancing their motivation for treatment, thereby enabling patients to actively engage in rehab training. Despite the advancement, there is a dearth of comprehensive summary and analysis on the use of VR technology to enhance patient motivation in rehabilitation. Thus, this narrative review aims to evaluate the potential of VR technology in enhancing patient motivation during motor rehabilitation training. This review commences with an explanation of how enhancing motivation through the VR rehabilitation system could improve the efficiency and effectiveness of rehabilitation training. Then, the technology was analyzed to improve patient motivation in the present VR rehabilitation system in detail. Furthermore, these technologies are classified and summarized to provide a comprehensive overview of the state-of-the-art approaches for enhancing patient motivation in VR rehabilitation. Findings showed VR rehabilitation training utilizes game-like exercises to enhance the engagement and enjoyment of rehabilitation training. By immersing patients in a simulated environment with multisensory feedback, VR systems offer a unique approach to rehabilitation that can lead to improved patient motivation. Both ultimately lead to improved patient outcomes, which is not typically achievable with traditional rehabilitation methods. The review concludes that VR rehabilitation presents an opportunity to improve patient motivation and adherence to long-term rehabilitation training. However, to further enhance patient self-efficacy, VR rehabilitation should integrate psychology and incorporate methods. Moreover, it is necessary to build a game design theory for rehabilitation games, and the latest VR feedback technology should also be introduced.

As the number of patients with cardiovascular diseases (CVDs) increases annually, a reliable and automated system for detecting electrocardiogram (ECG) abnormalities is becoming increasingly essential. Scholars have developed numerous methods of arrhythmia classification using machine learning or deep learning. However, the issue of low classification rates of individual classes in inter-patient heartbeat classification remains a challenge. This study proposes a method for inter-patient heartbeat classification by fusing dual-channel squeeze-and-excitation residual neural networks (SE-ResNet) and expert features. In the preprocessing stage, ECG heartbeats extracted from both leads of ECG signals are filtered and normalized. Additionally, nine features representing waveform morphology and heartbeat contextual information are selected to be fused with the deep neural networks. Using different filter and kernel sizes for each block, the SE-residual block-based model can effectively learn long-term features between heartbeats. The divided ECG heartbeats and extracted features are then input to the improved SE-ResNet for training and testing according to the inter-patient scheme. The focal loss is utilized to handle the heartbeat of the imbalance category. The proposed arrhythmia classification method is evaluated on three open-source databases, and it achieved an overall F1-score of 83.39 % in the MIT-BIH database. This system can be applied in the scenario of daily monitoring of ECG and plays a significant role in diagnosing arrhythmias., Competing Interests: Declaration of competing interest The authors declared that they have no conflicts of interest to this work., (Copyright © 2024. Published by Elsevier Ltd.)

Water is the source of life and civilization, but water icing causes catastrophic damage to human life and diverse industrial processes. Currently, superhydrophobic surfaces (inspired by the lotus effect) aided anti-icing attracts intensive attention due to their energy-free property. Here, recent advances in anti-icing by design and functionalization of superhydrophobic surfaces are reviewed. The mechanisms and advantages of conventional, macrostructured, and photothermal superhydrophobic surfaces are introduced in turn. Conventional superhydrophobic surfaces, as well as macrostructured ones, easily lose the icephobic property under extreme conditions, while photothermal superhydrophobic surfaces strongly rely on solar illumination. To address the above issues, a potentially smart strategy is found by developing macrostructured photothermal storage superhydrophobic (MPSS) surfaces, which integrate the functions of macrostructured superhydrophobic materials, photothermal materials, and phase change materials (PCMs), and are expected to achieve all-day anti-icing in various fields. Finally, the latest achievements in developing MPSS surfaces, showcasing their immense potential, are highlighted. Besides, the perspectives on the future development of MPSS surfaces are provided and the problems that need to be solved in their practical applications are proposed., (© 2024 Wiley‐VCH GmbH.)