Chappellgordon6658

In this review, we present the most recent works on UHF-SAWs for microfluidics and biosensing, with a particular focus on the LoC application. We derive the relevant scale laws, useful formulas, fabrication guidelines, current limitations of the technology, and future developments.In-vivoviscoelastic properties have been estimated in human subcutaneous adipose tissue (SAT) by integration of poroviscoelastic-mass transport model (pve-MTM) into wearable electrical impedance tomography (w-EIT) under the influence of external compressive pressure-P.Thepve-MTM predicts the ion concentration distributioncmod(t)by coupling the poroviscoelastic and mass transport model to describe the hydrodynamics, rheology, and transport phenomena inside SAT. Thew-EIT measures the time-difference conductivity distribution∆γ(t)in SAT resulted from the ion transport. Based on the integration, the two viscoelastic properties which are viscoelastic shear modulus of SATGvand relaxation time of SATτvare estimated by applying an iterative curve-fitting between the normalized average ion concentration distributioncˆmod(t)predicted frompve-MTM and the experimental normalized average ion concentration distributioncˆexp(t)derived fromw-EIT. Thein-vivoexperiments were conducted by applying external compressive pressure-Pon human calf boundary to induce interstitial fluid flow and ion movement in SAT. As a result, the value ofGvwas range from 4.9-6.3 kPa and the value ofτvwas range from 27.50-38.5 s with the value of average goodness-of-fit curve fittingR2 > 0.76. These values ofGvandτvwere compared to the human and animal tissue from the literature in order to verify this method. The results frompve-MTM provide evidence thatGvandτvplay a role in the predicted value ofcˆmod.In this study, Bi-particle-functionalized tungsten trioxide-bismuth oxide (WO3-Bi2O3) composite nanorods were prepared by integrating sputtering and hydrothermal syntheses with an appropriate postannealing procedure to induce Bi particle precipitation. Unlike other routes in which metal particle decoration is achieved externally, in this study, photoresponsive one-dimensional WO3-Bi2O3composite nanorods were decorated with Bi particles by using the internal precipitation method. Structural analysis revealed that the Bi-metal-particle-functionalized WO3-Bi2O3composite nanorods with particle size ranging from 5 to 10 nm were formed through hydrogen gas annealing at an optimal annealing temperature of 350 °C. Compared with the pristine WO3nanorod template, the Bi-WO3-Bi2O3composite nanorods exhibited higher photoresponsive performance, substantial photogenerated charge transfer ability, and efficient separation of photogenerated electron-hole pairs. The study results indicated that the Bi-WO3-Bi2O3composite nanorods had superior decontamination ability and excellent stability toward RhB dye as compared with pristine WO3. Moreover, the photogenerated charge separation and migration efficiencies of the WO3-Bi2O3nanorods could be tuned through appropriate reduction of the surface oxide layer; this is a promising approach to designing WO3-Bi2O3nanorods with high photoactive performance.In this research, the potential application of borophene as gas sensor device is explored. The first-principles theory is employed to investigate the sensing performance of pristine and Li-doped borophene for SO2and five main atmospheric gases (including CH4, CO2, N2, CO and H2). All gases are found to be adsorbed weakly on pristine borophene, which shows weak physical interaction between the pristine borophene and gases. The gas adsorption performance of borophene is improved by the doping of Li atom. The results of adsorption energy suggest that Li-borophene exhibits high selectivity to SO2molecule. Moreover, analyses of the charge transfer, density of states and work function also confirm the introduction of Li adatom on borophene significantly enhances the selectivity and sensitivity to SO2. In addition, desorption time of gas from pristine and Li doped borophene indicates the Li-borophene has good desorption characteristics for SO2molecule at high temperatures. This research would be helpful for understanding the influence of Li doping on borophene and presents the potential application of Li-borophene as a SO2gas sensor or scavenger.Purpose O-(2-[18F]fluoroethyl)-L-tyrosine (FET), a PET radiotracer of amino acid uptake, has shown potential for diagnosis and treatment planning in patients with glioblastoma (GBM). To improve quantitative assessment of FET PET imaging, we evaluated the repeatability of uptake of this tracer in patients with GBM.Methods Test-retest FET PET imaging was performed on 8 patients with histologically confirmed GBM, who previously underwent surgical resection of the tumour. Data were acquired according to the protocol of a prospective clinical trial validating FET PET as a clinical tool in GBM. SUVmean, SUVmaxand SUV98%metrics were extracted for both test and retest images and used to calculate 95% Bland-Altman limits of agreement (LoA) on lesion-level, as well as on volumes of varying sizes. Impact of healthy brain normalization on repeatability of lesion SUV metrics was evaluated.Results Tumour LoA were [0.72, 1.46] for SUVmeanand SUVtotal, [0.79,1.23] for SUVmax, and [0.80,1.18] for SUV98%. Healthy brain LoA were [0.80,1.25] for SUVmean, [0.80,1.25] for SUVmax, and [0.81,1.23] for SUV98%. Voxel-level SUV LoA were [0.76, 1.32] for tumour volumes and [0.80, 1.25] for healthy brain. When sampled over maximum volume, SUV LoA were [0.90,1.12] for tumour and [0.92,1.08] for healthy brain. Normalization of uptake using healthy brain volumes was found to improve repeatability, but not after normalization volume size of about 15 cm3.Conclusions Advances in Knowledge and Implications for Patient Care Repeatability of FET PET is comparable to existing tracers such as FDG and FLT. Healthy brain uptake is slightly more repeatable than uptake of tumour volumes. Repeatability was found to increase with sampled volume. SUV normalization between scans using healthy brain uptake should be performed using volumes at least 15 cm3in size to ensure best imaging repeatability.

Disease may cause changes in the individual's respiratory pattern, which can be measured as parameters for evaluating disease, usually through manually annotated polysomnographic recordings. In this study, a machine learning model based on nasal airflow and respiratory effort of chest and abdomen is proposed to automatically identify respiratory events, including normal breathing event, hypopnea event and apnea event.

The nasal airflow and chest-abdominal respiratory effort signals were collected from Polysomnography (PSG). Time/frequency domain features, fractional fourier transform features and sample entropy were calculated to obtain feature sets. And selected features through statistical analysis were used as input variables of the machine learning model. The performance of different input combinations on different models was studied and cross-validated.

The dataset included PSG sleep records of 60 patients provided by the Chinese People's Liberation Army General Hospital. The eXtreme Gradient Boostbdomen contain the characteristics of respiratory events, their combined use can improve the classification performance in identifying respiratory events. With this method, respiratory events can be automatically detected and labeled from the PSG records, which can be used to screen for patients with Sleep Apnea Hypopnea Syndrome (SAHS).Transforming levulinic acid (LA) to γ-valerolactone (GVL) is a significant route for converting biomass into valuable chemicals. The development of an efficient and robust heterogeneous catalyst for this reaction has aroused great interest. In this work, nitrogen-doped graphene (NG) supported nickel (Ni) based heterogeneous catalyst with excellent activities was successfully synthesized. The Ni/NG catalyst shows outstanding performance for hydrogenation of LA to GVL at a relatively low temperature of 140 °C, which is superior then most of the present reported heterogeneous catalyst. Further investigation indicated the Ni nanoparticles were the active sites and the NG also plays an indispensable role. The catalytic performance was highly depended on the crystallinity, particles sizes and electronic structure of Ni in Ni/NG catalyst, which can be optimized by nitrogen doping. This work affords a new route for designing robust and excellent heterogeneous catalysts by doping method to optimize the support.Binary III-N nitride semiconductors with wurtzite crystal structure such as GaN and AlN have been long used in many practical applications ranging from optoelectronics to telecommunication. The structurally related ZnGeN2or ZnSnN2derived from the parent binary compounds by cation mutation (elemental substitution) have recently attracted attention, but such ternary nitride materials are mostly limited to II-IV-N2compositions. This paper demonstrates synthesis and characterization of zinc niobium nitride (Zn2NbN3)-a previously unreported II2-V-N3ternary nitride semiconductor. The Zn2NbN3thin films are synthesized using a one-step adsorption-controlled growth that locks in the targeted stoichiometry, and a two-step deposition/annealing method that suppresses the loss of Zn and N. Measurements indicate that this sputtered Zn2NbN3crystalizes in cation-disordered wurtzite-derived structure, in contrast to chemically related rocksalt-derived Mg2NbN3compound, also synthesized here for comparison using the two-step method. The estimated wurtzite lattice parameter ratio of Zn2NbN3is 1.55, and the optical absorption onset is at 2.1 eV. Both of these values are lower compared to published Zn2NbN3computational values ofc/a= 1.62 andEg= 3.5-3.6 eV. Additional theoretical calculations indicate that this difference is due to cation disorder in experimental samples, suggesting a way to tune the structural parameters and the resulting properties of heterovalent ternary nitride materials. Overall, this work expands the wurtzite family of nitride semiconductors to include Zn2NbN3, and suggests that related II2-V-N3and other ternary nitrides should be possible to synthesize.Purpose. Accurate tumor localization for image-guided liver stereotactic body radiation therapy (SBRT) is challenging due to respiratory motion and poor tumor visibility on conventional x-ray based images. Novel integrated MRI and radiotherapy systems enable direct in-room tumor visualization, potentially increasing treatment accuracy. As these systems currently do not provide a 4D image-guided radiotherapy strategy, we developed a 4D-MRI guided liver SBRT workflow and validated all steps for implementation on the Unity MR-linac.Materials and Methods. selleck inhibitor The proposed workflow consists of five steps (1) acquisition of a daily 4D-MRI scan, (2) 4D-MRI to mid-position planning-CT rigid tumor registration, (3) calculation of daily tumor midP misalignment, (4) plan adaptation using adapt-to-position (ATP) with segment-weights optimization and (5) adapted plan delivery. The workflow was first validated in a motion phantom, performing regular motion at different baselines (±5 to ±10 mm) and patient-derived respiratory signals with varying degrees of irregularity.