Search

IntroductionAssessing the influence of respiratory assistive devices on the diaphragm mobility is essential for advancing patient care and improving treatment outcomes. Existing respiratory assistive robots have not yet effectively assessed their impact on diaphragm mobility. In this study, we introduce for the first time a non-invasive, real-time clinically feasible ultrasound method to evaluate the impact of soft wearable robots on diaphragm displacement.MethodsWe measured and compared diaphragm displacement and lung volume in eight participants during both spontaneous and robotic-assisted respiration. Building on these measurements, we proposed a human-robot coupled two-compartment respiratory mechanics model that elucidates the underlying mechanism by which our extracorporeal wearable robots augments respiration. Specifically, the soft robot applies external compression to the abdominal wall muscles, inducing their inward movement, which consequently pushes the diaphragm upward and enhances respiratory function. Finally, we investigated the level and shape of various robotic assistive forces on diaphragm motion.ResultsThis robotic intervention leads to a significant increase in average diaphragm displacement by 1.95 times and in lung volume by 2.14 times compared to spontaneous respiration. Furthermore, the accuracy of the proposed respiratory mechanics model is confirmed by the experimental results, with less than 7% error in measurements of both diaphragm displacement and lung volume. Finally, the magnitude of robotic assistive forces positively correlates with diaphragm movement, while the shape of the forces shows no significant relationship with diaphragm activity.ConclusionOur experimental findings validate the effective assistance mechanism of the proposed robot, which enhances diaphragm mobility and assists in ventilation through extracorporeal robotic intervention. This robotic system can assist with ventilation while increasing diaphragm mobility, potentially resolving the issue of diaphragm atrophy. Additionally, this work paves the way for improved robotic designs and personalized assistance, tailored to the dynamics of the diaphragm in respiratory rehabilitation.

Abstract Target localization for distributed radars requires precise knowledge of the calibration errors in time, frequency, and space. Previous studies focus on the sensor location error and sensor directional error in space. This paper concentrates on the system errors in time and frequency which directly affect the targets estimation of range and velocity. Based on linear frequency modulation waveform, the impact of the system errors including sample interval, pulse repetition interval, and centre frequency are analysed. An alternating optimization algorithm is proposed to achieve the target localization, velocity estimation and system errors estimation simultaneously. Simulation shows the effectiveness of the algorithm and the influence on localization due to varying number of targets and radars.

Similar to the layout of an oscillating heat pipe (OHP), a quartz hybrid heat pipe (HHP) with an inner diameter of 5 mm, exceeding 59.7 % of the capillary threshold of OHP, was designed. The detailed thermal hydraulic behavior of fluid in the HHP has been revealed. It was found that the HHP undergoes a heat transfer mode transition from phase change to pulsating flow. It is also means that the liquid slugs can be dynamically and stably formed if the heat input is sufficient. The single bubble growth and the multi-bubble coalescence are two ways to form the intermittent flow. In addition, as the main flow pattern in low filling ratio (FR), the formation of annular flow is closely concerned in the behaviors of fluid. Moreover, the higher the FR is, the clearer the contour of slug flow is. At the same time, the oscillating motion can be formed easily at a high FR, resulting in a better performance of HHP in lower heat load. However, as the heat input increases, HHP with a 60 % filling ratio exhibits lower thermal resistance, achieving a minimum value of 0.08 °C/W at 100 W.

Objective: Trauma is a leading cause of death worldwide, with many incidents resulting in hemorrhage before the patient reaches the hospital. Despite advances in trauma care, the majority of deaths occur within the first three hours of hospital admission, offering a very limited window for effective intervention. Unfortunately, a significant increase in mortality from hemorrhagic trauma is primarily due to delays in hemorrhage control. Therefore, we propose a machine learning model to predict the need for urgent hemorrhage intervention. Methods: This study developed and validated an XGBoost-based machine learning model using data from the National Trauma Data Bank (NTDB) from 2017 to 2019. It focuses on demographic and clinical data from the initial hours following trauma for model training and validation, aiming to predict whether trauma patients require urgent hemorrhage intervention. Results: The XGBoost model demonstrated superior performance across multiple datasets, achieving an AUROC of 0.872 on the training set, 0.869 on the internal validation set, and 0.875 on the external validation set. The model also showed high sensitivity (77.8% on the external validation set) and specificity (82.1% on the external validation set), with an accuracy exceeding 81% across all datasets, highlighting its high reliability for clinical applications. Conclusions: Our study shows that the XGBoost model effectively predicts urgent hemorrhage interventions using data from the National Trauma Data Bank (NTDB). It outperforms other machine learning algorithms in accuracy and robustness across various datasets. These results highlight machine learning’s potential to improve emergency responses and decision-making in trauma care.

The perception of voluntary respiratory consciousness is quite important in some situations, such as respiratory assistance and respiratory rehabilitation training, and the key signatures about voluntary respiration control may lie in the neural signals from brain manifested as electroencephalography (EEG). The present work aims to explore whether there exists correlation between voluntary respiration and scalp EEG. Evoke voluntary respiration of different intensities, while collecting EEG and respiration signal synchronously. Data from 11 participants were analyzed. Spectrum characteristics at low-frequency band were studied. Computation of EEG-respiration phase lock value (PLV) and EEG sample entropy were conducted as well. When breathing voluntarily, the 0–2 Hz band EEG power is significantly enhanced in frontal and right-parietal area. The distance between main peaks belonging to the two signals in 0–2 Hz spectrum graph tends to get smaller, while EEG-respiration PLV increases in frontal area. Besides, the sample entropy of EEG shows a trend of decreasing during voluntary respiration in both areas. There’s a strong correlation between voluntary respiration and scalp EEG. Significance: The discoveries will provide guidelines for developing a voluntary respiratory consciousness identifying method and make it possible to monitor people’s intention of respiration by noninvasive BCI.

Two-dimensional molybdenum disulfide (MoS2) is considered as a highly promising anode material for lithium-ion batteries (LIBs) due to its unique layer structure, large plane spacing, and high theoretical specific capacity; however, the overlap of MoS2 nanosheets and inherently low electrical conductivity lead to rapid capacity decay, resulting in poor cycling stability and low multiplicative performance. This severely limits its practical application in LIBs. To overcome the above problems, composite fibers with a core//sheath structure have been designed and fabricated. The sheath moiety of MoS2 nanosheets is uniformly anchored by the hydrothermal treatment of the axial of carbon nanofibers derived from an electrospinning method (CNFs//MoS2). The quantity of the MoS2 nanosheets on the CNFs substrates can be tuned by controlling the amount of utilized thiourea precursor. The influence of the MoS2 nanosheets on the electrochemical properties of the composite fibers has been investigated. The synergistic effect between MoS2 and carbon nanofibers can enhance their electrical conductivity and ionic reversibility as an anode for LIBs. The composite fibers deliver a high reversible capacity of 866.5 mA h g−1 after 200 cycles at a current density of 0.5 A g−1 and maintain a capacity of 703.3 mA h g−1 after a long cycle of 500 charge–discharge processes at 1 A g−1.

This paper describes the design of a bionic soft exoskeleton and demonstrates its feasibility for assisting the expectoration function rehabilitation of patients with spinal cord injury (SCI). Methods: A human–robot coupling respiratory mechanic model is established to mimic human cough, and a synergic inspire–expire assistance strategy is proposed to maximize the peak expiratory flow (PEF), the key metric for promoting cough intensity. The negative pressure module of the exoskeleton is a soft “iron lung” using layer-jamming actuation. It assists inspiration by increasing insufflation to mimic diaphragm and intercostal muscle contraction. The positive pressure module exploits soft origami actuators for assistive expiration; it pressures human abdomen and bionically “pushes” the diaphragm upward. Results: The maximum increase in PEF ratios for mannequins, healthy participants, and patients with SCI with robotic assistance were 57.67%, 278.10%, and 124.47%, respectively. The soft exoskeleton assisted one tetraplegic SCI patient to cough up phlegm successfully. Conclusion: The experimental results suggest that the proposed soft exoskeleton is promising for assisting the expectoration ability of SCI patients in everyday life scenarios. Significance: The proposed soft exoskeleton is promising for advancing the application field of rehabilitation exoskeletons from motor functions to respiratory functions.

The patient was a male neonate, and a prenatal ultrasound had detected a right lung mass. He was born at term and after delivery had tachypnea and feeding difficulties. A chest x-ray and a computed tomography (CT) scan revealed a large mass in the right chest with compression on the right lung after birth. We initially considered congenital pulmonary airway malformation (CPAM). After conservative treatment, his respiratory symptoms worsened gradually, and he required continuous supplemental oxygen. The symptoms could not be relieved by puncturing due to a postnatal ultrasound having shown a mass with anechoic microcystic spaces. He therefore underwent an emergency thoracotomy and lobectomy at 14 days of age. The pathology was consistent with fetal lung interstitial tumor (FLIT). The patient remained healthy at the three-month follow-up. We reviewed the literature on FLIT and found that, to date, 23 cases have been reported worldwide.

Abstract Background Septic shock comprises a heterogeneous population, and individualized resuscitation strategy is of vital importance. The study aimed to identify subclasses of septic shock with non-supervised learning algorithms, so as to tailor resuscitation strategy for each class. Methods Patients with septic shock in 25 tertiary care teaching hospitals in China from January 2016 to December 2017 were enrolled in the study. Clinical and laboratory variables were collected on days 0, 1, 2, 3 and 7 after ICU admission. Subclasses of septic shock were identified by both finite mixture modeling and K-means clustering. Individualized fluid volume and norepinephrine dose were estimated using dynamic treatment regime (DTR) model to optimize the final mortality outcome. DTR models were validated in the eICU Collaborative Research Database (eICU-CRD) dataset. Results A total of 1437 patients with a mortality rate of 29% were included for analysis. The finite mixture modeling and K-means clustering robustly identified five classes of septic shock. Class 1 (baseline class) accounted for the majority of patients over all days; class 2 (critical class) had the highest severity of illness; class 3 (renal dysfunction) was characterized by renal dysfunction; class 4 (respiratory failure class) was characterized by respiratory failure; and class 5 (mild class) was characterized by the lowest mortality rate (21%). The optimal fluid infusion followed the resuscitation/de-resuscitation phases with initial large volume infusion and late restricted volume infusion. While class 1 transitioned to de-resuscitation phase on day 3, class 3 transitioned on day 1. Classes 1 and 3 might benefit from early use of norepinephrine, and class 2 can benefit from delayed use of norepinephrine while waiting for adequate fluid infusion. Conclusions Septic shock comprises a heterogeneous population that can be robustly classified into five phenotypes. These classes can be easily identified with routine clinical variables and can help to tailor resuscitation strategy in the context of precise medicine.

Abstract As the electronic technology becomes increasingly integrated and miniaturized, thermal management has become a major challenge for electronic device applications. A heat pipe is a highly efficient two-phase heat transfer device. Due to its simple structure, high thermal conductivity and good temperature uniformity, it has been used in many different industrial fields. A novel aluminum flat heat pipe, with micro-grooves, has in the present work been designed and fabricated by using a 3D printing technology. Aluminum powder was used as a raw material, which was selectively melted and solidified to form the shape of the heat pipe. The sintered aluminum powder increased the roughness of the inner surface of the heat pipe, and the designed micro-grooves further enhanced the capillary forces induced by the wick structure. The wettability, for the working fluid (acetone), was excellent and the capillary forces were sufficient for the working fluid to flow back in the pipe. The effects of working fluid filling ratio, on the heat transfer performance of the heat pipe, was also investigated. It was shown that a filling ratio of 10% gave the best heat transfer performance with the lowest thermal resistance. The 3D-printed flat heat pipe was, therefore, also tested for the thermal management of a LED. The temperature of the LED could be kept within 40 °C and its service life became prolonged.

Abstract Solar energy as an abundant renewable resource has been investigated for many years. Solar thermoelectric conversion technology, which converts solar energy into thermal energy and then into electricity, has been developed and implemented in many important fields. The operation of solar–thermal–electric conversion systems, however, is strongly affected by the intermittency of solar radiation, which requires installation of thermal storage subsystems. In this work, we demonstrated a new solar–thermal–electric conversion system that consists of a thermoelectric converter and a rapidly charging thermal storage subsystem. A magnetic-responsive solar–thermal mesh was used as the movable charging source to convert incident concentrated sunlight into high-temperature heat, which can induce solid-to-liquid phase transition of molten salts. Driven by the external magnetic field, the solar–thermal mesh can move together with the receding solid–liquid interface thus rapidly storing the harvested solar–thermal energy within the molten salts. By connecting with a thermoelectric generator, the harvested solar–thermal energy can be further converted into electricity with a solar–thermal–electric energy conversion efficiency up to 2.56%, and the converted electrical energy can simultaneously light up more than 40 orange-colored LEDs. In addition to stable operation under sunlight, the charged thermal storage subsystem can release the stored heat and thus enables the solar–thermal–electric system to continuously generate electricity after removal of solar illumination.

Exploring the health risks of diseases attributed to PM2.5 and SO2 exposure and analyzing the differences in their distribution over emissions can provide useful insights for decision-makers to reduce premature mortality due to PM2.5 and SO2 exposure. This study used exposure-response functions, health risk inequality curve (HRICU, based on Lorenz curve), and the health risk inequality coefficient (HRICO, based on Gini coefficient) to estimate population health risks of PM2.5 and SO2 exposure in China from 2013 to 2017 based on a full-coverage, high-precision PM2.5 and SO2 concentration and emission dataset. The inequality in the distribution of premature mortality was explored in terms of pollutant emissions. The results showed that (1) premature mortalities from cardiovascular disease (CVD) and respiratory disease (RD) due to PM2.5 and SO2 exposure decreased by 21% and 54%, respectively, from 2013 to 2017. (2) At a national scale, the HRICO value for the distribution of PM2.5 and SO2 health risks on emissions were lower than 0.10 and 0.20, respectively. (3) More than 20% of provinces had HRICO values above 0.1 for PM2.5 or SO2. The provinces near the national borders generally had higher HRICO for PM2.5, while the province with the most severe inequity in the distribution of SO2 health risks on emissions appeared in Xinjiang Uygur Autonomous Region, Ningxia Hui Autonomous Region, and Hainan Province.

Development of intelligent ships requires marine diesel engine simulation models of high accuracy and fast response. In addition, with advent of tighter shipping air emissions regulations, such models are required to have emission prediction capabilities. In this article, such a model was developed and validated for a 30,000-ton bulk carrier main engine using MATLAB/Simulink. The simulation is based on mean value model, which predicts both the steady-state and dynamic performance of the engine. The results show that the steady-state performance parameters of the main engine are predicted within 2.2% error, and the exhaust emissions parameters are predicted within 7% error as compared to the bench test data from the engine manufacturer. The Maximum Continuous Rating (MCR) points at 100%, 75%, 50% and 25% of the E3 duty cycle were investigated with emphasis according to the diesel propulsion characteristics. In dynamic simulation, it is found that the compressor pressure fluctuation is greater than that of the exhaust pressure with the load variation. Furthermore, the compressor and the exhaust pipe have a similar temperature drop value (about 60 K) when the engine load changes from 100% to 50% MCR, and the exhaust pipe temperature fluctuation is more significant when the load varies from 50% to 25% MCR. The above results show the model’s good transient capability in simulating the dynamic characteristics of the engine. This model can be used especially for the development and control of marine diesel engines in intelligent ships as well as training-oriented marine engine and ship simulators.

Freshwater scarcity, one of the most serious global challenges, has threatened the development of society in many regions. Solar-driven interfacial evaporation localizing solar-to-thermal energy conversion at the vapor–liquid interface provides a new approach for seawater desalination. In this work, we reported a high-efficiency porous TiNO solar absorber for a solar-driven interfacial evaporation system. The solar absorber was prepared by depositing a solar absorbing coating of TiNO on air-laid paper. Hydrophilicity and porosity of the absorber provide sufficient capillary force to absorb water to the evaporation region, thus resulting in rapid replenishment of water and simultaneously avoiding salt precipitation. Based on the TiNO solar absorber, the interfacial evaporation system achieves a high evaporation rate of 1.33 kg m−2 h−1 with an evaporation efficiency of 84.05% under 1 sun illumination and has good durability under long-time solar irradiation. Such a low-cost, high-efficiency solar-driven seawater desalination system holds the potential for rapid deployment in remote areas or isolated islands to collect freshwater.

In this paper, an experimental setup was established to study the influence of potassium chloride (KCL) solution as the ground electrode on the nitrogen oxides (NOx) removal efficiency in non-thermal plasma (NTP) generated by dielectric barrier discharging (DBD) reactor. The experimental results show that the KCL solution as the ground electrode has better stability and higher discharge intensity and it is a promising approach to improve NOx removal efficiency. The specific NOx removal efficiency is related to the power frequency, the concentration and temperature of the KCL solution. As the power frequency increases, the NOx removal efficiency first increases and then decreases, and a maximum value is reached at the power frequency of 8 kHz. The NO removal effect is improved as the concentration of the KCL solution increases, especially when the concentration is lower than 0.1 mol/L. Under the same KCL solution concentration and input energy density, the NOx removal efficiency is increased with the solution temperature. In particular, when the power discharge frequency is 8 kHz, the KCL solution concentration is 0.1 mol/L and the solution temperature is 60 °C, the NOx and NO removal efficiency reach 85.82% and 100%, respectively.

So far, most of the experimental researchers studying the removal of diesel exhaust pollutants have done so with simulated exhaust gas, which cannot demonstrate the ability of catalysts accurately. Because activated carbon (AC) has low price, no secondary pollution, good adsorption performance, and certain catalytic activity, it has good application prospects in the field of marine exhaust pollutant removal. In this paper, the removal of particulate matter (PM), carbon monoxide (CO), and NOx from real exhaust gas by AC was studied. The results show that PM removal efficiency reached up to 77%, while the pressure drop increased with running time. AC may degenerate to some extent with the increase of temperature, resulting in a negative removal efficiency of CO. The denitration efficiency of AC was up to 34.5% without urea, and further increased to 44.8% after spraying urea, still a distance from industrial applications. In the future, it may be necessary to install a fan to compensate the reactor or to backwash the reactor to avoid excessive pressure drop. The thermal stability of the AC also needs to be improved. To increase the denitration performance, it may be helpful to modify the AC or impregnate other metal oxides.

Vanadium-based catalysts are mainly used for marine diesel exhaust denitration. However, their poor catalytic ability at low temperature and poor sulfur tolerance, as well as high toxicity and cost, are big turnoffs. AC (Activated carbon) exhibits good adsorption capacity and catalytic ability in denitration because of its high specific surface area and chemical activity. In this paper, coal-based AC was used for simulating diesel exhaust denitration in different conditions. The results show that the NO removal ability of AC is poor in an NO/N2 system. The NO2 removal ability is excellent in an NO2/N2 system, where NO is desorbed. The NOx removal efficiency is 95% when the temperature is higher than 200 °C in an NO2/NH3/N2 system. When the temperature is lower than 100 °C, AC can catalytically oxidize NO to NO2 in an NO2/O2/N2 system. The near-stable catalytic efficiencies of AC for a slow SCR (Selective Catalytic Reduction) reaction, a standard SCR reaction, and a fast SCR reaction at 300 °C are 12.1%, 31.6%, and 70.8%, respectively. When ships use a high-sulfur fuel, AC can be used after wet scrubber desulfurization to catalytically oxidize NO to NO2 at a low temperature. When ships use a low-sulfur fuel, AC can be used as a denitration catalyst at high temperatures.