Bjerringdavidsen9500

5μg ml-1againstE. coliand 655μg ml-1againstS. aureus. At the MIC, the inhibition rate of the GO/TCCA composite exceeded 99.46% againstE. coliand 99.17% againstS. aureus. The bactericidal kinetic curves indicate that the GO/TCCA composite has an excellent bactericidal effect againstE. coliandS. aureus.Digital light processing (DLP)-based three-dimensional (3D) printing technology has the advantages of speed and precision comparing with other 3D printing technologies like extrusion-based 3D printing. Therefore, it is a promising biomaterial fabrication technique for tissue engineering and regenerative medicine. When printing cell-laden biomaterials, one challenge of DLP-based bioprinting is the light scattering effect of the cells in the bioink, and therefore induce unpredictable effects on the photopolymerization process. In consequence, the DLP-based bioprinting requires extra trial-and-error efforts for parameters optimization for each specific printable structure to compensate the scattering effects induced by cells, which is often difficult and time-consuming for a machine operator. Such trial-and-error style optimization for each different structure is also very wasteful for those expensive biomaterials and cell lines. Here, we use machine learning to learn from a few trial sample printings and automatically provide printer the optimal parameters to compensate the cell-induced scattering effects. We employ a deep learning method with a learning-based data augmentation which only requires a small amount of training data. TGF-beta activation After learning from the data, the algorithm can automatically generate the printer parameters to compensate the scattering effects. Our method shows strong improvement in the intra-layer printing resolution for bioprinting, which can be further extended to solve the light scattering problems in multilayer 3D bioprinting processes.Microtia is a small, malformed external ear, which occurs at an incidence of 1-10 per 10 000 births. Autologous reconstruction using costal cartilage is the most widely accepted surgical microtia repair technique. Yet, the method involves donor-site pain and discomfort and relies on the artistic skill of the surgeon to create an aesthetic ear. This study employed novel tissue engineering techniques to overcome these limitations by developing a clinical-grade, 3D-printed biodegradable auricle scaffold that formed stable, custom-made neocartilage implants. The unique scaffold design combined strategically reinforced areas to maintain the complex topography of the outer ear and micropores to allow cell adhesion for the effective production of stable cartilage. The auricle construct was computed tomography (CT) scan-based composed of a 3D-printed clinical-grade polycaprolactone scaffold loaded with patient-derived chondrocytes produced from either auricular cartilage or costal cartilage biopsies combined with adipose-derived mesenchymal stem cells. Cartilage formation was measured within the constructin vitro, and cartilage maturation and stabilization were observed 12 weeks after its subcutaneous implantation into a murine model. The proposed technology is simple and effective and is expected to improve aesthetic outcomes and reduce patient discomfort.In the paper, the temperature dependence of magnetic nanoparticle (MNP) paramagnetic chemical shift (paraSHIFT) was studied by magnetic resonance (MR) spectroscopy. Based on it, iron oxide MNPs are considered as MR shifting probes for determining the temperature in liquids. With the increase in measurement temperature of the MNP reagent with MNPs, the decrease of MNP magnetization would make the peak of spectroscopy shift to the higher chemical shift area. The peak shift is related to the magnetic susceptibility of MNPs, which can be determined by MR frequency as a function of temperature and particle size. Experiments on temperature-dependent chemical shifts are performed for MNP samples with different core sizes and the estimated temperature accuracy can achieve 0.1 K. Combined with the contrast effect of magnetic nanoparticles in magnetic resonance imaging at 3 T, this technology can realize temperature imaging.Modeling system dynamics becomes challenging when the properties of individual system components cannot be directly measured, and often requires identification of properties from observed motion. In this paper, we show that systems whose movement is highly dissipative have features which provide an opportunity to more easily identify models and more quickly optimize motions than would be possible with general techniques. Geometric mechanics provides means for reduction of the dynamics by environmental homogeneity, while the dissipative nature minimizes the role of second order (inertial) features in the dynamics. Here we extend the tools of geometric system identification to 'shape-underactuated dissipative systems (SUDS)'-systems whose motions are more dissipative than inertial, but whose actuation is restricted to a subset of the body shape coordinates. Many animal motions are SUDS, including micro-swimmers such as nematodes and flagellated bacteria, and granular locomotors such as snakes and lizards. Many motion in friction dominated regimes.All-inorganic dual-phase CsPbBr3-Cs4PbBr6quantum dots (CPB QDs)-based polyacrylonitrile (PAN) fiber synthesized by supersaturated recrystallization and electrospinning technique possesses characteristics of homogeneous morphology, high crystallinity and solution sensitivity. Under 365 nm laser excitation, CPB@PAN fiber exhibits surprising trace-recording capability attributing to the splash-enhanced fluorescence (FL) performance with a narrow-band emission at 477-515 nm. In the process of ethanol anhydrous (EA) and water splashing, the CPB@PAN fiber presents conspicuous blue and green emission when contacting with EA and water, and maintains intense blue and green FL for more than 4 months. These experimental and theoretical findings provide a facile technology for the development of biological protection display, biotic detection and moisture-proof forewarning based on the trace-recording performance of CPB@PAN fiber.Investigation of structural, dynamical, mechanical, electronic and thermodynamic properties of RuYAs (Y= Cr and Fe) alloys have been performed from the first principle calculations. Among the three structural phases, 'α' phase is found to be energetically favorable for both the RuCrAs and RuFeAs compounds. The computed cohesive energies and phonon dispersion spectra indicate the structural and dynamical stabilities of both the compounds. Mechanical stability of these compounds are studied using elastic constants. The Pugh's ratio predicts RuFeAs to be more ductile than RuCrAs. The RuCrAs alloy, on the other hand, is found to be a stiffer, harder and highly rigid crystal with stronger bonding forces than the RuFeAs. Furthermore, the thermodynamical properties have also been estimated with respect to the temperature under different pressures using the quasi-harmonic Debye model. In order to account for the effect of the highly correlateddtransition elements in the system we incorporated the GGA +Uapproximations. Within the GGA +Uapproach, the electronic structure reveals the half-metallicity for both compounds, which follows the Slater-Pauling rule. The charge density and electron localized function reflect the covalent bonding among the constituent atoms. Bader analysis reveals that the charge transfer takes place from Cr/Fe to Ru and As atoms in both approximations. Both Raman and infrared active modes have been identified in the compounds.Objective.To develop a novel deep learning-based 3Din vivodose reconstruction framework with an electronic portal imaging device (EPID) for magnetic resonance-linear accelerators (MR-LINACs).Approach.The proposed method directly back-projected 2D portal dose into 3D patient coarse dose, which bypassed the complicated patient-to-EPID scatter estimation step used in conventional methods. A pre-trained convolutional neural network (CNN) was then employed to map the coarse dose to the final accurate dose. The electron return effect caused by the magnetic field was captured with the CNN model. Patient dose and portal dose datasets were synchronously generated with Monte Carlo simulation for 96 patients (78 cases for training and validation and 18 cases for testing) treated with fixed-beam intensity-modulated radiotherapy in four different tumor sites, including the brain, nasopharynx, lung, and rectum. Beam angles from the training dataset were further rotated 2-3 times, and doses were recalculated to augment the datasets.Results.The comparison between reconstructed doses and MC ground truth doses showed mean absolute errors less then 0.88% for all tumor sites. The averaged 3Dγ-passing rates (3%, 2 mm) were 97.42%±2.66% (brain), 98.53%±0.95% (nasopharynx), 99.41%±0.46% (lung), and 98.63%±1.01% (rectum). The dose volume histograms and indices also showed good consistency. The average dose reconstruction time, including back projection and CNN dose mapping, was less than 3 s for each individual beam.Significance.The proposed method can be potentially used for accurate and fast 3D dosimetric verification for online adaptive radiotherapy using MR-LINACs.Quantum interference (QI) in single molecular junctions shows a promising perspective for realizing conceptual nanoelectronics. However, controlling and modulating the QI remains a big challenge. Herein, two-type substituents at different positions ofmeta-linked benzene, namely electron-donating methoxy (-OMe) and electron-withdrawing nitryl (-NO2), are designed and synthesized to investigate the substituent effects on QI. The calculated transmission coefficientsT(E) indicates that -OMe and -NO2could remove the antiresonance and destructive quantum interference (DQI)-induced transmission dips at position 2. -OMe could raise the antiresonance energy at position 4 while -NO2groups removes the DQI features. For substituents at position 5, both of them are nonactive for tuning QI. The conductance measurements by scanning tunneling microscopy break junction show a good agreement with the theoretical prediction. More than two order of magnitude single-molecule conductance on/off ratio could be achieved at the different positions of -NO2substituent groups at room temperature. The present work proves chemical substituents can be used for tuning QI features in single molecular junctions, which provides a feasible way toward realization of high-performance molecular devices.The recently developed non-equilibrium self-consistent generalized Langevin equation theory of the dynamics of liquids of non-spherically interacting particles [2016J. Phys. Chem. B1207975] is applied to the description of the irreversible relaxation of a thermally and mechanically quenched dipolar fluid. Specifically, we consider a dipolar hard-sphere liquid quenched (attw= 0) from full equilibrium conditions towards different ergodic-non-ergodic transitions. Qualitatively different scenarios are predicted by the theory for the time evolution of the system after the quench (tw> 0), that depend on both the kind of transition approached and the specific features of the protocol of preparation. Each of these scenarios is characterized by the kinetics displayed by a set of structural correlations, and also by the development of two characteristic times describing the relaxation of the translational and rotational dynamics, allowing us to highlight the crossover from equilibration to aging in the system and leading to the prediction of different underlying mechanisms and relaxation laws for the dynamics at each of the glass transitions explored.