Effects of the deformation and size of the upper airway on the deposition of aerosols.

Aerosol drug delivery in the human airway is significantly affected by the morphology and size of the airway. This work developed a CFD-DEM model to simulate and analyze air flow and powder dynamics in combined inhaler-airway systems with different degrees of airway deformation (non-deformed, 50%, and 75% deformed) and sizes (adult, 0.80, and 0.62 scaled). The airways were generated based on a regular airway constructed from the MRI images through finite element method (for deformed airways) or scaling-down (for smaller airways). The airways were connected to Turbuhaler® through a connector. The results showed that under the same flow rate, the variation in the airway geometry and size had a minimum impact on the flow field and powder deposition in the device and the connector. However, deformation caused more particle deposition in the deformed region. Notably, the airway with 50% deformation had the most particles passing through the airway with the largest particle sizes due to its lower air velocity in the deformed area. Reducing airway size resulted in more powder deposition on the airway, particularly at the pharynx and mouth regions. This was because, with the same flow rate, the flow velocity in the smaller airway was higher, causing more particle-wall collisions in the mouth and pharynx regions. More importantly, the deposition efficiency in the 0.62-scaled airway was significantly higher than the other two airways, highlighting the importance of the different administration of aerosol drugs for young children.

Scalable Manufacturing of Large-Area Pressure Sensor Array for Sitting Posture Recognition in Real Time.

Pressure sensors are considered the key technology for potential applications in real-time health monitoring, artificial electronic skins, and human-machine interfaces. Despite the significant progress in developing novel sensitive materials and constructing unique sensor structures, it remains challenging to fabricate large-area pressure sensor arrays due to the involvement of complex procedures including photolithography, laser writing, or coating. Herein, a scalable manufacturing approach for the realization of pressure sensor arrays with substantially enlarged sensitive areas is proposed using a versatile screen-printing technique. A compensation mechanism is introduced into the printing process to ensure the precise alignment of conductive electrodes, insulation layers, and sensitive microstructures with an alignment error of less than 4 µm. The fully screen-printed sensors exhibit excellent collective sensing performance, such as a reasonable pressure sensitivity of -2.2 kPa-1, a fast response time of 40 ms, and superior durability over 3000 consecutive pressures. Additionally, an integrated 16 × 32 pressure sensor array with a sensing area of 190 × 380 mm2 is demonstrated to precisely recognize the sitting postures and the body weights, showing great potential in continuous and real-time health status monitoring.

Macromolecular Engineered Multifunctional Room-Temperature Phosphorescent Polymers through Reversible Deactivation Radical Polymerization.

Despite the intensive research in room-temperature phosphorescent (RTP) polymers, the synthesis of RTP polymers with well-defined macromolecular structures and multiple functions remains a challenge. Herein, reversible deactivation radical polymerization was demonstrated to offer a gradient copolymer (GCP) architecture with controlled heterogeneities, which combines hard segment and flexible segment. The GCPs would self-assemble into a multiphase nanostructure, featuring tunable stretchability, excellent RTP performance, and intrinsic healability without compromising light emission under stretching. The mechanical performance is tunable on demand with elongation at break ranging from 5.0% to 221.7% and Young's modulus ranging from 0.5 to 225.0 MPa.

Multifrequency matched-field source localization based on Wasserstein metric for probability measures.

Matched-field processing (MFP) for underwater source localization serves as a generalized beamforming approach that assesses the correlation between the received array data and a dictionary of replica vectors. In this study, the processing scheme of MFP is reformulated by computing a statistical metric between two Gaussian probability measures with the cross-spectral density matrices (CSDMs). To achieve this, the Wasserstein metric, a widely used notion of metric in the space of probability measures, is employed for developing the processor to attach the intrinsic properties of CSDMs, expressing the underlying optimal value of the statistic. The Wasserstein processor uses the embedded metric structure to suppress ambiguities, resulting in the ability to distinguish between multiple sources. In this foundation, a multifrequency processor that combines the information at different frequencies is derived, providing improved localization statistics with deficient snapshots. The effectiveness and robustness of the Wasserstein processor are demonstrated using acoustic simulation and the event S5 of the SWellEx-96 experiment data, exhibiting correct localization statistics and a notable reduction in ambiguity. Additionally, this paper presents an approach to derive the averaged Bartlett processor by evaluating the Wasserstein metric between two Dirac measures, providing an innovative perspective for MFP.

CFD-DEM investigation of the effects of aperture size for a capsule-based dry powder inhaler.

Capsule based dry powder inhalers (DPIs) often require piercing of the capsule before inhalation, and the characteristics of the apertures (punctured holes) affect air flow and the release of powders from the capsule. This work develops a numerical model based on the two-way coupling of computational fluid dynamics and discrete element method (CFD-DEM) to investigate the effect of aperture size on powder dispersion in the Aerolizer® device loaded with only carrier particles (lactose). Powders (carrier particles) in the size range 60-140 µm (d50: 90 µm and span: 0.66) were initialized in a capsule which had a circular aperture at each end. Boundary conditions corresponding to an air flow rate of 45 L/min were specified at each inlet to the mixing chamber (i.e., a total flow rate 90 L/min), and a capsule spin speed of âˆ¼ 4050 rpm. The velocity magnitudes inside the capsule were considerably lower than those in the mixing chamber in the vicinity of the rotating capsule, with the exception of the capsules featuring 2.5 mm and 4 mm apertures. Larger apertures reduced the capsule emptying time and increased the particle evacuation velocity; the fluid drag force on the particles issuing from the capsule peaked for an aperture of 1.3 mm. Inside the capsule, particle-particle (PP) collisions were more frequent than particle-wall (PW) collisions due to high concentration of powder, but PP collisions had smaller (median) impact energy than PW collisions. Larger apertures resulted in fewer collisions in the capsule with higher PW and virtually unchanged PP collision energies. Outside the capsule (i.e., in the inhaler mixing chamber), PW collisions occurred more frequently than PP collisions with median collision energies typically two orders of magnitude higher than inside the capsule. Larger apertures resulted in more collisions with slightly reduced collision energy, but this effect plateaued for aperture sizes larger than 1.3 mm. Powder dispersion, expressed as the fine particle fraction (FPF) of the powder, was predicted using an empirical equation based on carrier PW collisions. Therefore, consistent with the model prediction of the effect of aperture sizes on the chamber collision frequency, FPF increased with aperture size but plateaued beyond 1.3 mm.

Research on AGV path tracking method based on global vision and reinforcement learning.

As the key to the movement of automated guided vehicle (AGV), the design of control algorithm directly affects whether AGV can follow the preset path. Aiming at the difficulty of AGV control, an AGV path tracking control method based on global vision and reinforcement learning is proposed. Firstly, the global view is obtained by the visual sensor, and the position information of obstacles and AGV is obtained by the target detection algorithm. Secondly, the path planning algorithm is used to obtain the driving path information which is used to establish a virtual environment. Thirdly, the position and pose of the physical AGV are introduced into the virtual environment by the visual sensor, and the virtual AGV is reset. Finally, the image obtained by virtual vehicle camera is input into the reinforcement learning model and the output action is sent to the physical AGV for execution. In the experimental part, this method can not only plan the driving path in different environments but also well control AGV to drive along the specified path, which proves that this method has strong robustness and feasibility.

Electrospun cellulose acetate nanofibrous composites for multi-responsive shape memory actuators and self-powered pressure sensors.

Soft actuators and sensors have attracted extensive scientific interest attributed to their great potential applications in various fields, but the integration of actuating and sensing functions in one material is still a big challenge. Here, we developed an electrospun cellulose acetate (CA)/carbon nanotube nanofiborous composite with both functional applications as multi-responsive shape memory actuators and triboelectric nanogenerator (TENG) based sensors. Attributed to excellent thermo- and light-induced shape memory performance, the CA nanofiborous composites showed high heavy-lift capability as light driven actuators, able to lift burdens 1050 times heavier than their own weight. The CA nanofiborous membranes based TENG exhibited high output performance with open-circuit voltage, short-circuit density, and instantaneous power density about 103.2 V, 7.93 mA m-2 and 0.74 W m-2, respectively. The fabricated TENG based pressure sensor exhibited a high sensitivity of 3.03 V kPa-1 below 6.8 kPa and 0.11 V kPa-1 in the pressure range from 6.8 to 65 kPa, which can be effectively used to monitor human motion state and measure wind velocity. It is expected that the electrospun composites with actuating and sensing functions will show prosperous applications prospects in soft robotics.

Effects of the mouthpiece and chamber of Turbuhaler® on the aerosolization of API-only powder formulations.

Powder dispersion in dry powder inhalers (DPIs) is affected by powder formulations as well as the design of a device. This paper conducted a numerical investigation based on the coupled computational fluid dynamics (CFD) and discrete element method (DEM) to evaluate the changes of the design of a commercial DPI device Turbuhaler® on the aerosolization of an API-only formulation. Six different designs were proposed by modifying the mouthpiece and chamber of the original geometry which was reconstructed from a CT-scan of the Turbuhaler, and their performances in terms of powder deposition in the device and fine powder fraction (FPF) were evaluated. The resistance of the device was observed to vary with different designs. For the change of the mouthpiece, the device with a cylindrical mouthpiece had the least resistance and the lowest FPF emitted among all the devices, confirming the important role of the spiral mouthpiece on powder dispersion. Reducing the mouthpiece size caused more powder deposition in the inhaler due to higher airflow velocity, but FPF emitted increased compared to the original design as more powder dispersion occurred inside the mouthpiece. The half-length mouthpiece design reduced device resistance to increase airflow velocity and average collision energy, resulting in an increase in FPF loaded but a decrease in the number of collisions. For the change of the chamber, the domed chamber design increased the powder dispersion time and thus enhanced the frequency and energy of particle collisions, which eventually led to an increase in FPF loaded. At fixed flow rates, the powder dispersion efficiency was a function of the device resistance with higher device resistance causing an increase in the FPF loaded. However, it is important for the patient's attainable pressure drop to be considered in this context. Correlations between the aerosolization efficiency and the ratio of the average collision energy and cohesion energy were established based on model-predicted quantities.

Accurate mechanical-optical theoretical model of cross-axis sensitivity of an interferometric micro-optomechanical accelerometer.

An interferometric micro-optomechanical accelerometer usually has ultrahigh sensitivity and accuracy. However, cross-axis interference inevitably degrades the performance, including its detection accuracy and output signal contrast. To accurately clarify the influence of cross-axis interference, a modified mechanical-optical theoretical model is established. The rotation of the proof mass and the detected light intensity are quantitatively investigated with a load of cross-axis acceleration. A simulation and experiment are performed to verify the correctness of the theoretical model when the cross-axis acceleration is from 0 to 0.175 g. The results demonstrate that this model has a more than fivefold accuracy increase compared with conventional theoretical models when the cross-axis acceleration is from 0.06 to 0.175 g. In addition, we provide a suppression method to diminish the rotation of the proof mass based on squeeze film air damping, which significantly suppresses the contrast reduction caused by cross-axis interference.

Role of CFD based in silico modelling in establishing an in vitro-in vivo correlation of aerosol deposition in the respiratory tract.

Effective evaluation and prediction of aerosol transport deposition in the human respiratory tracts are critical to aerosol drug delivery and evaluation of inhalation products. Establishment of an in vitro-in vivo correlation (IVIVC) requires the understanding of flow and aerosol behaviour and underlying mechanisms at the microscopic scale. The achievement of the aim can be facilitated via computational fluid dynamics (CFD) based in silico modelling which treats the aerosol delivery as a two-phase flow. CFD modelling research, in particular coupling with discrete phase model (DPM) and discrete element method (DEM) approaches, has been rapidly developed in the past two decades. This paper reviews the recent development in this area. The paper covers the following aspects: geometric models of the respiratory tract, CFD turbulence models for gas phase and its coupling with DPM/DEM for aerosols, and CFD investigation of the effects of key factors associated with geometric variations, flow and powder characteristics. The review showed that in silico study based on CFD models can effectively evaluate and predict aerosol deposition pattern in human respiratory tracts. The review concludes with recommendations on future research to improve in silico prediction to achieve better IVIVC.

Development and in-use evaluation of a novel Luminex MicroPlex microsphere-based (TRIOL) assay for simultaneous identification of Mycobacterium tuberculosis and detection of first-line and second-line anti-tuberculous drug resistance in China.

AIMS: Rapid and accurate diagnostic assays with simultaneous microbial identification and drug resistance detection are essential for optimising treatment and control of tuberculosis. METHODS: We developed a novel multiplex (TRIOL, Tuberculosis-Rifampicin-Isoniazid-Ofloxacin-Luminex) assay using the Luminex xMAP system that simultaneously identifies Mycobacterium tuberculosis and detects resistance to first-line and second-line anti-tuberculous drugs, and compared its performance with that by PCR sequencing, using phenotypic drug susceptibility testing as the gold standard. RESULTS: Identification of M. tuberculosis by the TRIOL assay was highly sensitive (100%) and specific (100%). The overall drug-specific specificities were excellent (100%). The overall sensitivity of the TRIOL assay was lower than that of the PCR-sequencing assays (72.4% vs 82.8%) because of a lower sensitivity of detecting rifampicin resistance (71.4% vs 92.9%). The sensitivity of detecting isoniazid and ofloxacin resistance was as good as the PCR-sequencing assays. Importantly, the TRIOL assay did not miss any mutations that were included in the assay. All of the resistant isolates that were missed had uncommon mutations or unknown resistance mechanisms that were not included in the assay. CONCLUSIONS: The TRIOL assay has higher throughput, lower cost and is less labour intensive than the PCR-sequencing assays. The TRIOL assay is advantageous in having the capability to detect resistance to multiple drugs and an open-architecture system that allows addition of more specific primers to detect uncommon mutations. Inclusion of additional primers for the identification of non-tuberculous mycobacteria, spoligotyping and improvement of rifampicin resistance detection would enhance the use of the TRIOL assay in future clinical and epidemiological studies.