Linking process, structure, and property in additive manufacturing applications through advanced materials modelling

Additive manufacturing (AM) processes have the ability to build complex geometries from a wide variety of materials. A popular approach for metal-based AM processes involves the deposition of material particles on a substrate followed by fusion of those particles together using a high intensity heat source, e.g.a laser or an electron beam, in order to fabricate a solid part. These methods are of high priority in engineering research, especially in applications for the energy, health, and defense sectors. The primary reasons behind the rapid growth in interest for AM include: (1) the ability to create complex geometries thatare otherwise cost-prohibitive or difficult to manufacture, (2) increased freedom of material composition design through the adjustment of the elemental ratios of the composing powders, (3) a reduction in wasted materials, and (4) fast, low-volume, production of prototypeand functional parts without the additional tooling and die requirements of conventional manufacturing methods. However, the highly localized and intense nature of these processes elicits many experimental and computational challenges. These challenges motivate a strong need for computational investigation, as does the need to more accurately characterize the response of parts built using AM. The present work will discuss these challenges and methods for creating multiscale material models that account forthe complex phenomena observed in additively manufacturedproducts. The linkage between process, structure, and property of AM components, e.g., anisotropic plastic behavior combined with anisotropic microstructural descriptors afforded through enhanced data compression techniques, will also be discussed

Metformin Uniquely Prevents Thrombosis by Inhibiting Platelet Activation and mtDNA Release

Thrombosis and its complications are the leading cause of death in patients with diabetes. Metformin, a first-line therapy for type 2 diabetes, is the only drug demonstrated to reduce cardiovascular complications in diabetic patients. However, whether metformin can effectively prevent thrombosis and its potential mechanism of action is unknown. Here we show, metformin prevents both venous and arterial thrombosis with no significant prolonged bleeding time by inhibiting platelet activation and extracellular mitochondrial DNA (mtDNA) release. Specifically, metformin inhibits mitochondrial complex I and thereby protects mitochondrial function, reduces activated platelet-induced mitochondrial hyperpolarization, reactive oxygen species overload and associated membrane damage. In mitochondrial function assays designed to detect amounts of extracellular mtDNA, we found that metformin prevents mtDNA release. This study also demonstrated that mtDNA induces platelet activation through a DC-SIGN dependent pathway. Metformin exemplifies a promising new class of antiplatelet agents that are highly effective at inhibiting platelet activation by decreasing the release of free mtDNA, which induces platelet activation in a DC-SIGN-dependent manner. This study has established a novel therapeutic strategy and molecular target for thrombotic diseases, especially for thrombotic complications of diabetes mellitus

Construction of a Medical Micro-Object Cascade Network for Automated Segmentation of Cerebral Microbleeds in Susceptibility Weighted Imaging

Aim: The detection and segmentation of cerebral microbleeds (CMBs) images are the focus of clinical diagnosis and treatment. However, segmentation is difficult in clinical practice, and missed diagnosis may occur. Few related studies on the automated segmentation of CMB images have been performed, and we provide the most effective CMB segmentation to date using an automated segmentation system.Materials and Methods: From a research perspective, we focused on the automated segmentation of CMB targets in susceptibility weighted imaging (SWI) for the first time and then constructed a deep learning network focused on the segmentation of micro-objects. We collected and marked clinical datasets and proposed a new medical micro-object cascade network (MMOC-Net). In the first stage, U-Net was utilized to select the region of interest (ROI). In the second stage, we utilized a full-resolution network (FRN) to complete fine segmentation. We also incorporated residual atrous spatial pyramid pooling (R-ASPP) and a new joint loss function.Results: The most suitable segmentation result was achieved with a ROI size of 32 × 32. To verify the validity of each part of the method, ablation studies were performed, which showed that the best segmentation results were obtained when FRN, R-ASPP and the combined loss function were used simultaneously. Under these conditions, the obtained Dice similarity coefficient (DSC) value was 87.93% and the F2-score (F2) value was 90.69%. We also innovatively developed a visual clinical diagnosis system that can provide effective support for clinical diagnosis and treatment decisions.Conclusions: We created the MMOC-Net method to perform the automated segmentation task of CMBs in an SWI and obtained better segmentation performance; hence, this pioneering method has research significance

Xanthohumol alleviates oxidative stress and impaired autophagy in experimental severe acute pancreatitis through inhibition of AKT/mTOR

Severe acute pancreatitis (SAP) is a lethal gastrointestinal disorder, yet no specific and effective treatment is available. Its pathogenesis involves inflammatory cascade, oxidative stress, and autophagy dysfunction. Xanthohumol (Xn) displays various medicinal properties,including anti-inflammation, antioxidative, and enhancing autophagic flux. However, it is unclear whether Xn inhibits SAP. This study investigated the efficacy of Xn on sodium taurocholate (NaT)-induced SAP (NaT-SAP) in vitro and in vivo. First, Xn attenuated biochemical and histopathological responses in NaT-SAP mice. And Xn reduced NaT-induced necrosis, inflammation, oxidative stress, and autophagy impairment. The mTOR activator MHY1485 and the AKT activator SC79 partly reversed the treatment effect of Xn. Overall, this is an innovative study to identify that Xn improved pancreatic injury by enhancing autophagic flux via inhibition of AKT/mTOR. Xn is expected to become a novel SAP therapeutic agent

Quadruple perovskite CaCu3Fe2Re2O12 : A potential actuator based on a multiscale model

In this study, the magnetic structure of CaCu3Fe2Re2O12 is analyzed combined on a macro to micro-scale. To combine first-principles calculations and finite element methods, the magnetic properties, Young's modulus and Poisson's ratio are used as input parameters in the finite element methods calculations. As a function of applied magnetic field and actuator structure, the energy loss and magnetostrictive coefficient of an magnetostrictive actuator are identified. When the voltage and frequency are specified, a small bar radius and narrow air gap are preferred for a high magnetostrictive coefficient. The total range of simulation parameters results in a large magnetostrictive coefficient of 2700 ppm, which is higher than the one for Tb-Dy-Fe alloys. According to our results, CaCu3Fe2Re2O12 can be designed to be used as actuators by controlling the structures and applying magnetic fields.Title in Web of Science: Quadruple perovskite CaCu3Fe2Re2O12: A potential actuator based on a multiscale model</p

Phenytoin regulates osteogenic differentiation of human bone marrow stem cells by PI3K/Akt pathway

Background: We mainly studied the mechanism by which phenytoin promotes osteogenic differentiation of human jawbone marrow stem cells. Methods: Bone marrow stem cells were extracted from jaw bone tissue debris obtained from 5 subjects undergoing implant restoration. Osteogenic and adipogenic experiments proved cells stemness, and the expression of ALP, RUNX2, and OSX were detected by qPCR and Western blot. High-throughput sequencing was used to extract differentially expressed genes, the network database predicted phenytoin drug targets, GO and KEGG enrichment combined with PPI network diagram to analyze the osteogenesis mechanism. Results: Calcium nodules and lipid droplet formation were observed in osteogenic and adipogenic experiments. The concentration of phenytoin within 100 mg/L does not produce cytotoxicity. The results of PCR and WB indicated that 50 mg/L phenytoin significantly promoted the expression of ALP and RUNX2, and 25 mg/L phenytoin significantly promoted the expression of OSX. The results of network pharmacology suggest that phenytoin promotes bone formation by up-regulating FGFR2, S1PR1, TGFB3, VCAN core proteins and activating PI3K/Akt pathway. Conclusions: Phenytoin activated the PI3K/Akt pathway to regulate the osteogenic differentiation of human jawbone marrow stem cells. https://data.mendeley.com/datasets/t3xstktt93/1

Mechanical and electronic properties of van der Waals layered hcp PdH2

Mechanical and electronic properties of palladium dihydrides (PdH2) as a function of pressure were studied by ab initio calculations based on density functional theory (DFT). The ab initio random structure searching technique was employed for screening potential PdH2 crystal structures under high pressure. A hexagonal close packed (hcp) phase of PdH2 with space group P63mc was reported. The structure geometry and elastic constants were calculated as a function of pressure. It was found that H atoms are in the interstitial position of Pd atoms layer at 0 GPa. There is an electronic topology transition of hcp PdH2 at 15 GPa. When pressure exceeds above 15 GPa, one hydrogen atom occupies the tetrahedral site and another hydrogen atom locates in the interstitial position. When the c/a ratio is between 1.765 to 1.875, the hcp PdH2 is mechanically stable, and the Pd-H-2b bond is the major factor that limits the mechanical stability. The elastic constant C-44 is the first one that cannot satisfy the mechanical stability criteria under pressure. The anisotropy parameters are far from 1(one) shows that the hcp PdH2 is a highly anisotropic structure. The electronic structure study indicates that the bonding force between Pd and H atoms along the z-axis direction increases with the increasing pressure. Also, the phonon dispersion study shows that PdH2 is dynamic stability under pressure. The results suggest that hcp PdH2 can be metastable in van der Waals layered structure

Audio-Visual Fusion using Multiscale Temporal Convolutional Attention for Time-Domain Speech Separation

Audio-only speech separation methods cannot fully exploit audio-visual correlation information of speaker, which limits separation performance. Additionally, audio-visual separation methods usually adopt traditional idea of feature splicing and linear mapping to fuse audio-visual features, this approach requires us to think more about fusion process. Therefore, in this paper, combining with the changes of speaker mouth landmarks, we propose a time-domain audio-visual temporal convolution attention speech separation method (AVTA). In AVTA, we design a multiscale temporal convolutional attention (MTCA) to better focus on contextual dependencies of time sequences. We then use sequence learning and fusion network composed of MTCA to build a separation model for speech separation task. On different datasets, AVTA achieves competitive performance, and compared to baseline methods, AVTA is better balanced in training cost, computational complexity and separation performance.</p