Willardpalm1649

Empty liquids represent a wide class of materials whose constituents arrange in a random network through reversible bonds. Many key insights on the physical properties of empty liquids have originated almost independently from the study of colloidal patchy particles on one side, and a large body of theoretical and experimental research on water on the other side. Patchy particles represent a family of coarse-grained potentials that allows for a precise control of both the geometric and the energetic aspects of bonding, while water has arguably the most complex phase diagram of any pure substance, and a puzzling amorphous phase behavior. It was only recently that the exchange of ideas from both fields has made it possible to solve long-standing problems and shed new light on the behavior of empty liquids. Here we highlight the connections between patchy particles and water, focusing on the modelling principles that make an empty liquid behave like water, including the factors that control the appearance of thermodynamic and dynamic anomalies, the possibility of liquid-liquid phase transitions, and the crystallization of open crystalline structures.Optical metamaterials are widely used in electromagnetic wave modulation due to their sub-wavelength feature sizes. In this paper, a method to plate an achiral nanopillar array with chiral coating by the secondary effect in focused ion beam induced deposition is proposed. Guided by the pattern defined in a bitmap with variable residence time, the beam scan strategy suppresses the interaction between adjacent nanostructures. A uniform chiral coating is formed on the target nanostructure without affecting the adjacent nanostructure, under carefully selected beam parameters and the rotation angle of the sample stage. Energy dispersive x-ray spectroscopy results show that the chiral film has high purity metal, which enables the generation of localized surface plasmon resonances and causes the circular dichroism (CD) under circularly polarized light illumination. Finally, the tailorable CD spectrum of the coated array is verified by the finite difference time domain method.In the past decade, cartilage tissue engineering has arisen as a promising therapeutic option for degenerative joint diseases, such as osteoarthritis, in the hope of restoring the structure and physiological functions. Hydrogels are promising biomaterials for developing engineered scaffolds for cartilage regeneration. However, hydrogel-delivered mesenchymal stem cells or chondrocytes could be exposed to elevated levels of reactive oxygen species (ROS) in the inflammatory microenvironment after being implanted into injured joints, which may affect their phenotype and normal functions and thereby hinder the regeneration efficacy. To attenuate ROS induced side effects, a multifunctional hydrogel with an innate anti-oxidative ability was produced in this study. The hydrogel was rapidly formed through a dynamic covalent bond between phenylboronic acid grafted hyaluronic acid (HA-PBA) and poly(vinyl alcohol) and was further stabilized through a secondary crosslinking between the acrylate moiety on HA-PBA and the fron with H2O2. Furthermore, intra-articular injection of the hydrogel in mice revealed adequate stability and good biocompatibilityin vivo. These results demonstrate that this hydrogel can be used as a novel bioink for the generation of 3D bioprinted constructs with anti-ROS ability to potentially enhance cartilage tissue regeneration in a chronic inflammatory and elevated ROS microenvironment.Thermoelectric materials are considered promising candidates for thermal energy conversion. This study presents the fabrication of Zn- and Ce-alloyed In2O3with a porous structure. The electrical conductivity was improved by the alloying effect and an ultra-low thermal conductivity was observed owing to the porous structure, which concomitantly provide a distinct enhancement ofZT. However, SiO2nanoparticle additives react with the matrix to form a third-phase impurity, which weakens the electrical conductivity and increases the thermal conductivity. A thermoelectric module was constructed for the purpose of thermal heat energy conversion. Our experimental results proved that both an enhancement in electrical conductivity and a suppression in thermal conductivity could be achieved through nano-engineering. This approach presents a feasible route to synthesize porous thermoelectric oxides, and provides insight into the effect of additives; moreover, this approach is a cost-effective method for the fabrication of thermoelectric oxides without traditional hot-pressing and spark-plasma-sintering processes.L-3,4-dihydroxy-phenylalanine (L-dopa) is the most widely used drug in Parkinson's disease treatment. However, development of cost-effective and high-throughput sensors to accurate enantioselective discrimination of L-dopa and D-dopa remains challenging to date. Herein, on the basis of the peroxidase-mimic activity of chiral FexCuySe nanoparticles, we demonstrated a novel colorimetric sensor for determination of chiral dopa. The surface chiral ligand, L/D-histidine (L/D-His), endowed the nanozymes with enantioselectivity in catalyzing the oxidation of dopa enantiomers. According to the values ofkcat/Km, the efficiency of L-His modified nanoparticles (L-FexCuySe NPs) towards L-dopa was 1.56 times higher than that of D-dopa. While, D-His can facilely reverse the preference of the nanozyme to D-dopa. On the basis of high catalytic activity and enantioselectivity of L-FexCuySe NPs in oxidation of L-dopa, the L-FexCuySe NPs-based system can be utilized for detection of L-dopa. The linear ranges for L-dopa determination were 5μM-0.125 mM and 0.125 mM-1 mM with a detection limit of 1.02μM. Critically, the developed sensor has been successfully applied in the quality control of clinical used L-dopa tablets. Our work sheds light on developing simple and sensitive chiral nanomaterials-based sensors for drug analysis.The variation behaviors of the morphology, transmission, and sheet resistance of the surface Ag/AgO nano-network (NNW) structures fabricated under different illumination conditions and with different Ag deposition thicknesses and thermal annealing temperatures in forming initial Ag nanoparticles (NPs) are studied. Generally, an NNW structure with a smaller mesh size or a denser branch distribution has a lower transmission and a lower sheet resistance level. Under the fabrication condition of a broader illumination spectrum, a lower thermal annealing temperature, or a thicker Ag deposition, we can obtain an NNW structure of a smaller mesh size. The mesh size of an NNW structure is basically controlled by the seed density of Brownian tree (BT) at the beginning of light illumination. A BT seed can be formed through a stronger local localized surface plasmon resonance for accelerating Ag oxidation in a certain region. Once an Ag/AgO BT seed is formed, the surrounding Ag NPs are reorganized to form the branches of a BT. Multiple BTs are connected to form a large-area NNW structure, which can serve as a transparent conductor. Under the fabrication conditions of a broader illumination spectrum, 3 nm Ag deposition, and 100 °C thermal annealing, we can implement an NNW structure to achieve ∼1.15μm in mesh size, ∼90 Ω sq-1in sheet resistance, and 93%-77% in transmittance within the wavelength range between 370 and 700 nm.Objective.Lesions of COVID-19 can be clearly visualized using chest CT images, and hence provide valuable evidence for clinicians when making a diagnosis. However, due to the variety of COVID-19 lesions and the complexity of the manual delineation procedure, automatic analysis of lesions with unknown and diverse types from a CT image remains a challenging task. In this paper we propose a weakly-supervised framework for this task requiring only a series of normal and abnormal CT images without the need for annotations of the specific locations and types of lesions.Approach.A deep learning-based diagnosis branch is employed for classification of the CT image and then a lesion identification branch is leveraged to capture multiple types of lesions.Main Results.Our framework is verified on publicly available datasets and CT data collected from 13 patients of the First Affiliated Hospital of Shantou University Medical College, China. The results show that the proposed framework can achieve state-of-the-art diagnosis prediction, and the extracted lesion features are capable of distinguishing between lesions showing ground glass opacity and consolidation.Significance.The proposed approach integrates COVID-19 positive diagnosis and lesion analysis into a unified framework without extra pixel-wise supervision. Further exploration also demonstrates that this framework has the potential to discover lesion types that have not been reported and can potentially be generalized to lesion detection of other chest-based diseases.Objective. We proposed an experimental approach to build a precise machine-specific beam delivery time (BDT) prediction and delivery sequence model for standard, volumetric, and layer repainting delivery based on a cyclotron accelerator system.Approach. Test fields and clinical treatment plans' log files were used to experimentally derive three main beam delivery parameters that impacted BDT energy layer switching time (ELST), spot switching time, and spot drill time. This derived machine-specific model includes standard, volumetric, and layer repainting delivery sequences. A total of 103 clinical treatment fields were used to validate the model.Main results. The study found that ELST is not stochastic in this specific machine. Instead, it is actually the data transmission time or energy selection time, whichever takes longer. The validation showed that the accuracy of each component of the BDT matches well between machine log files and the model's prediction. VY-3-135 solubility dmso The average total BDT was about (-0.74 ± 3.33)% difference compared to the actual treatment log files, which is improved from the current commercial proton therapy system's prediction (67.22%±26.19%).Significance. An accurate BDT prediction and delivery sequence model was established for an cyclotron-based proton therapy system IBA ProteusPLUS®. Most institutions could adopt this method to build a machine-specific model for their own proton system.Blood reperfusion of ischemic cerebral tissue may cause cerebral ischemia-reperfusion (CIR) injury. Necroptosis and inflammation have been demonstrated to be involved in the disease-related process of CIR injury. The E3 ubiquitin ligase carboxyl terminus of Hsp70-interacting protein (CHIP) can modulate multiple cellular signaling processes, including necroptosis and inflammation. Numerous studies have demonstrated the neuroprotective effects of CHIP on multiple central nervous system (CNS) diseases. However, the effects of CHIP on CIR injury have not been fully explored. We hypothesize that CHIP can exert neuroprotective effects by attenuating necroptosis and inflammation during CIR injury. In the present study, adult wild-type (WT) C57BL/6 mice and CHIP knock-in (KI) mice with a C57BL/6 background and CHIP overexpression in neural tissue underwent middle cerebral artery occlusion (MCAO) surgery to simulate CIR onset. Our data indicated that CHIP expression in the peri-infarct tissue was markedly increased after MCAO surgery.