Fabrication and Characterization of AlₓCrCuFeNi₂ High-Entropy Alloys Coatings by Laser Metal Deposition

High-entropy alloys (HEAs) are becoming new hot spots in the metallic materials community, which are defined to contain equiatomic or close-to-equiatomic compositions. HEAs can possess many interesting mechanical properties, and in particular, they have the great potential to be used as coating materials requiring high hardness and wear resistance. In this study, the feasibility of fabrication AlₓCrCuFeNi₂ (x=0,0.75) HEAs was investigated via laser metal deposition from elemental powders. The microstructure, phase structure, and hardness were studied by an optical microscope, scanning electron microscopy with energy dispersive spectroscopy (SEM/EDS), electron backscatter diffraction (EBSD) and Vickers hardness tester. The bonding between the AlₓCrCuFeNi₂ (x = 0,0.75) HEAs and AISI 304 stainless steel were good combinations. The Al₀.₇₅CrCuFeNi₂ alloy consisted of columnar dendritic microstructure with Al/Ni enrichment in the dendritic regions. The phase structure of the AlₓCrCuFeNi₂ (x = 0,0.75) HEAs were face center cubic structure as identified by EBSD. Vickers hardness results indicate that the average hardness of CrCuFeNi₂ HEA was 175 HV. With the addition of aluminium, the Vickers hardness of Al0.75CrCuFeNi2 HEA increased to 285 HV

Predictive Model for Thermal and Stress Field in Selective Laser Melting Process -- Part II

Finite Element Analysis (FEA) is used to predict the transient thermal cycle and optimize process parameters to analyze these effects on deformation and residual stresses. However, the process of predicting the thermal history in this process with the FEA method is usually time-consuming, especially for large-scale parts. In this paper, an effective predictive model of part deformation and residual stress was developed for accurately predicting deformation and residual stresses in large-scale parts. An equivalent body heat flux proposed from the single layer laser scan model was imported as the thermal load to the layer by layer model. The hatched layer is then heated up by the equivalent body heat flux and used as a basic unit element to build up the macroscale part. The thermal history and residual stress fields of two solid parts with different support structures during the SLM process were simulated. Layer heat source method has the capability for fast temperature prediction in the SLM process, while sacrificing modeling details for the computational time-saving purpose. Thus numerical modeling in this work can be a very useful tool for the parametric study of process parameters, residual stresses and deformations

ChatCAD+: Towards a Universal and Reliable Interactive CAD using LLMs

The integration of Computer-Assisted Diagnosis (CAD) with Large Language Models (LLMs) holds great potential in clinical applications, specifically in the roles of digital family doctors and clinic assistants. However, current works in this field are plagued by limitations, specifically a restricted scope of applicable image domains and the provision of unreliable medical advice This restricts their overall processing capabilities. Furthermore, the mismatch in writing style between LLMs and radiologists undermines their practical usefulness. To tackle these challenges, we introduce ChatCAD+, which is designed to be universal and reliable. It is capable of handling medical images from diverse domains and leveraging up-to-date information from reputable medical websites to provide reliable medical advice. Additionally, it incorporates a template retrieval system that improves report generation performance via exemplar reports, enabling seamless integration into existing clinical workflows. The source code is available at https://github.com/zhaozh10/ChatCAD.Comment: Authors Zihao Zhao, Sheng Wang, Jinchen Gu, Yitao Zhu contributed equally to this work and should be considered co-first author

The First Case of Ischemia-Free Kidney Transplantation in Humans

Background: Ischemia-reperfusion injury (IRI) has been considered an inevitable event in organ transplantation since the first successful kidney transplant was performed in 1954. To avoid IRI, we have established a novel procedure called ischemia-free organ transplantation. Here, we describe the first case of ischemia-free kidney transplantation (IFKT). Materials and Methods: The kidney graft was donated by a 19-year-old brain-dead donor. The recipient was a 47-year-old man with end-stage diabetic nephropathy. The graft was procured, preserved, and implanted without cessation of blood supply using normothermic machine perfusion. Results: The graft appearance, perfusion flow, and urine production suggested that the kidney was functioning well-during the whole procedure. The creatinine dropped rapidly to normal range within 3 days post-transplantation. The levels of serum renal injury markers were low post-transplantation. No rejection or vascular or infectious complications occurred. The patient had an uneventful recovery. Conclusion: This paper marks the first case of IFKT in humans. This innovation may offer a unique solution to optimizing transplant outcomes in kidney transplantation

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Joining of Copper and Stainless Steel 304L using Direct Metal Deposition

In the current study, the feasibility of joining pure copper (Cu) and stainless steel 304L (SS304L) through direct metal deposition process was investigated by material characterization. Samples were analyzed in terms of microstructure, elemental distribution, and tensile testing. Direct depositing pure copper on SS304L shows copper was mechanically rather than metallurgical bonded with SS304L due to the poor dissolubility of iron in copper. Iron was diffused into copper with a diluted distance of 1.5 mm and above that, pure copper deposits were obtained. Columnar structure was observed at the copper region near the interface while the columnar grains became finer away from the interface and finally, equiaxed structure was observed. Tensile testing shows the yield strength and ultimate tensile strength of combined materials (copper and SS304L) are 123 MPa and 250 MPa and samples fractured at the copper section with a ductile fracture mechanism. The bi-material interface survived the tensile test. The yield strength and ultimate tensile strength of as-fabricated pure copper are 95.02 MPa and 186.66 MPa, respectively

Anti-cancer effects of Rhizoma Curcumae against doxorubicin-resistant breast cancer cells

Abstract Background Chemotherapy is a primary approach in cancer treatment after routine surgery. However, chemo-resistance tends to occur with chemotherapy in clinic, resulting in poor prognosis and recurrence. Nowadays, Chinese medicine may shed light on design of new therapeutic modes to overcome chemo-resistance. Although Rhizoma Curcumae possesses anti-cancer activities in various types of cancers, the effects and underlying mechanisms of its bioactive components against chemo-resistance are not clear. Therefore, the present study aims to explore the potential effects of Rhizoma Curcumae on doxorubicin-resistant breast cancer cells. Methods The expression and function of ABC transporters in doxorubicin-resistant MCF-7 breast cancer cells were measured by western blotting and flow cytometry. Cell viability was detected using MTT assay. The combination index was analyzed using the CalcuSyn program (Biosoft, Ferguson, MO), based on the Chou–Talalay method. Results In our present study, P-gp was overexpressed at protein level in doxorubicin-resistant MCF-7 cell line, but short of MRP1 and BCRP1. Essential oil of Rhizoma Curcumae and the main bioactive components were assessed on doxorubicin-resistant MCF-7 cell line. We found that the essential oil and furanodiene both display powerful inhibitory effects on cell viability, but neither of these is the specific inhibitor of ABC transporters. Moreover, furanodiene fails to enhance the efficacy of doxorubicin to improve multidrug resistance. Conclusion Overall, our findings fill the gaps of the researches on chemo-resistance improvement of Rhizoma Curcumae and are also beneficial for Rhizoma Curcumae being developed as a promising natural product for cancer adjuvant therapy in the future

Deformations and Stresses Prediction of Cantilever Structures Fabricated by Selective Laser Melting Process

Purpose: During the powder bed fusion process, thermal distortion is one big problem owing to the thermal stress caused by the high cooling rate and temperature gradient. For the purpose of avoiding distortion caused by internal residual stresses, support structures are used in most selective laser melting (SLM) process especially for cantilever beams because they can assist the heat dissipation. Support structures can also help to hold the work piece in its place and reduce volume of the printing materials. The mitigation of high thermal gradients during the manufacturing process helps to reduce thermal distortion and thus alleviate cracking, curling, delamination and shrinkage. Therefore, this paper aims to study the displacement and residual stress evolution of SLMed parts. Design/methodology/approach: The objective of this study was to examine and compare the distortion and residual stress properties of two cantilever structures, using both numerical and experimental methods. The part-scale finite element analysis modeling technique was applied to numerically analyze the overhang distortions, using the layer-by-layer model for predicting a part scale model. The validation experiments of these two samples were built in a SLM platform. Then average displacement of the four tip corners and residual stress on top surface of cantilever beams were tested to validate the model. Findings: The validation experiments results of average displacement of the four tip corners and residual stress on top surface of cantilever beams were tested to validate the model. It was found that they matched well with each other. From displacement and residual stress standpoint, by introducing two different support structure, two samples with the same cantilever beam can be successfully printed. In terms of reducing wasted support materials, print time and high surface quality, sample with less support will need less post-processing and waste energy. Originality/value: Numerical modeling in this work can be a very useful tool to parametrically study the feasibility of support structures of SLM parts in terms of residual stresses and deformations. It has the capability for fast prediction in the SLMed parts

Two-dimensional MXene-based materials for photothermal therapy

MXenes, a new family of two-dimensional materials, are also known as transition metal carbides and nitride, with a general formula of Mn+1XnTx (n = 1–3). Their inherent metallic conductivity and hydrophilic nature endow MXenes with fascinating physicochemical properties (optical, electronic, magnetic, light-to-heat conversion. etc.). The ultrathin layer structure and photothermal property attract many interests in biomedical applications, especially as phototherapeutic agents for cancer treatment. In this review, we summarize the recent progress of MXenes in the field of photothermal therapy and highlight the crucial biotic index for their preparation and evaluation. First, we introduce the main strategies for the preparation and surface modifications of biologically applied MXenes. Then, representative cases in the field of MXene-based photothermal application, such as photothermal therapy, synergistic therapy, and targeting treatments, are reviewed. Finally, the cytotoxicity and in vivo long-term biosafety are introduced. We also propose the underlying challenges and perspectives for MXene applications in terms of photothermal therapy