Design of a High Temperature Workstation for the Selective Laser Sintering Process

Mechanical Engineerin

An Evaluation of the Mechanical Behavior of Bronze-NI Composites Produced by Selective Laser Sintering

Mechanical properties of Bronze-Nickel composites produced by Selective Laser Sintering (SLS) were evaluated by constant displacement tension tests. These were studied as a function of SLS process parameters - laser power density, scan speed, scan spacing, scan direction and layer thickness. The strength data was then correlated to the microstructure and the part bulk density. To further enhance the part densities and the mechanical properties, post-SLS sintering was studied. The relationships between SLS process parameters, post-SLS sintering parameters and the resulting microstructures, part bulk density and the mechanical properties will be described.Mechanical Engineerin

Irreversible transformation of ferromagnetic ordered stripe domains in single-shot IR pump - resonant X-ray scattering probe experiments

The evolution of a magnetic domain structure upon excitation by an intense, femtosecond Infra-Red (IR) laser pulse has been investigated using single-shot based time-resolved resonant X-ray scattering at the X-ray Free Electron laser LCLS. A well-ordered stripe domain pattern as present in a thin CoPd alloy film has been used as prototype magnetic domain structure for this study. The fluence of the IR laser pump pulse was sufficient to lead to an almost complete quenching of the magnetization within the ultrafast demagnetization process taking place within the first few hundreds of femtoseconds following the IR laser pump pulse excitation. On longer time scales this excitation gave rise to subsequent irreversible transformations of the magnetic domain structure. Under our specific experimental conditions, it took about 2 nanoseconds before the magnetization started to recover. After about 5 nanoseconds the previously ordered stripe domain structure had evolved into a disordered labyrinth domain structure. Surprisingly, we observe after about 7 nanoseconds the occurrence of a partially ordered stripe domain structure reoriented into a novel direction. It is this domain structure in which the sample's magnetization stabilizes as revealed by scattering patterns recorded long after the initial pump-probe cycle. Using micro-magnetic simulations we can explain this observation based on changes of the magnetic anisotropy going along with heat dissipation in the film.Comment: 16 pages, 6 figure

Extracellular vesicles: pathogenic messengers and potential therapy for neonatal lung diseases

Extracellular vesicles (EVs) are a heterogeneous group of nano-sized membranous structures increasingly recognized as mediators of intercellular and inter-organ communication. EVs contain a cargo of proteins, lipids and nucleic acids, and their cargo composition is highly dependent on the biological function of the parental cells. Their cargo is protected from the extracellular environment by the phospholipid membrane, thus allowing for safe transport and delivery of their intact cargo to nearby or distant target cells, resulting in modification of the target cell's gene expression, signaling pathways and overall function. The highly selective, sophisticated network through which EVs facilitate cell signaling and modulate cellular processes make studying EVs a major focus of interest in understanding various biological functions and mechanisms of disease. Tracheal aspirate EV-miRNA profiling has been suggested as a potential biomarker for respiratory outcome in preterm infants and there is strong preclinical evidence showing that EVs released from stem cells protect the developing lung from the deleterious effects of hyperoxia and infection. This article will review the role of EVs as pathogenic messengers, biomarkers, and potential therapies for neonatal lung diseases

Large AI Models in Health Informatics: Applications, Challenges, and the Future

Large AI models, or foundation models, are models recently emerging with massive scales both parameter-wise and data-wise, the magnitudes of which can reach beyond billions. Once pretrained, large AI models demonstrate impressive performance in various downstream tasks. A prime example is ChatGPT, whose capability has compelled people's imagination about the far-reaching influence that large AI models can have and their potential to transform different domains of our lives. In health informatics, the advent of large AI models has brought new paradigms for the design of methodologies. The scale of multi-modal data in the biomedical and health domain has been ever-expanding especially since the community embraced the era of deep learning, which provides the ground to develop, validate, and advance large AI models for breakthroughs in health-related areas. This article presents a comprehensive review of large AI models, from background to their applications. We identify seven key sectors in which large AI models are applicable and might have substantial influence, including 1) bioinformatics; 2) medical diagnosis; 3) medical imaging; 4) medical informatics; 5) medical education; 6) public health; and 7) medical robotics. We examine their challenges, followed by a critical discussion about potential future directions and pitfalls of large AI models in transforming the field of health informatics.Comment: This article has been accepted for publication in IEEE Journal of Biomedical and Health Informatic

Ischemic and haemorrhagic stroke risk estimation using a machine-learning-based retinal image analysis

BackgroundStroke is the second leading cause of death worldwide, causing a considerable disease burden. Ischemic stroke is more frequent, but haemorrhagic stroke is responsible for more deaths. The clinical management and treatment are different, and it is advantageous to classify their risk as early as possible for disease prevention. Furthermore, retinal characteristics have been associated with stroke and can be used for stroke risk estimation. This study investigated machine learning approaches to retinal images for risk estimation and classification of ischemic and haemorrhagic stroke.Study designA case-control study was conducted in the Shenzhen Traditional Chinese Medicine Hospital. According to the computerized tomography scan (CT) or magnetic resonance imaging (MRI) results, stroke patients were classified as either ischemic or hemorrhage stroke. In addition, a control group was formed using non-stroke patients from the hospital and healthy individuals from the community. Baseline demographic and medical information was collected from participants' hospital medical records. Retinal images of both eyes of each participant were taken within 2 weeks of admission. Classification models using a machine-learning approach were developed. A 10-fold cross-validation method was used to validate the results.Results711 patients were included, with 145 ischemic stroke patients, 86 haemorrhagic stroke patients, and 480 controls. Based on 10-fold cross-validation, the ischemic stroke risk estimation has a sensitivity and a specificity of 91.0% and 94.8%, respectively. The area under the ROC curve for ischemic stroke is 0.929 (95% CI 0.900 to 0.958). The haemorrhagic stroke risk estimation has a sensitivity and a specificity of 93.0% and 97.1%, respectively. The area under the ROC curve is 0.951 (95% CI 0.918 to 0.983).ConclusionA fast and fully automatic method can be used for stroke subtype risk assessment and classification based on fundus photographs alone

Evaluation of Precision Livestock Technology and Human Scoring of Nursery Pigs in a Controlled Immune Challenge Experiment

The objectives were to determine the sensitivity, specificity, and cutoff values of a visual-based precision livestock technology (NUtrack), and determine the sensitivity and specificity of sickness score data collected with the live observation by trained human observers. At weaning, pigs (n = 192; gilts and barrows) were randomly assigned to one of twelve pens (16/pen) and treatments were randomly assigned to pens. Sham-pen pigs all received subcutaneous saline (3 mL). For LPS-pen pigs, all pigs received subcutaneous lipopolysaccharide (LPS; 300 µg/kg BW; E. coli O111:B4; in 3 mL of saline). For the last treatment, eight pigs were randomly assigned to receive LPS, and the other eight were sham (same methods as above; half-and-half pens). Human data from the day of the challenge presented high true positive and low false positive rates (88.5% sensitivity; 85.4% specificity; 0.871 Area Under Curve, AUC), however, these values declined when half-and-half pigs were scored (75% sensitivity; 65.5% specificity; 0.703 AUC). Precision technology measures had excellent AUC, sensitivity, and specificity for the first 72 h after treatment and AUC values were \u3e0.970, regardless of pen treatment. These results indicate that precision technology has a greater potential for identifying pigs during a natural infectious disease event than trained professionals using timepoint sampling

Shedding New Light on Weak Emission-Line Quasars in the CIV_{\rm IV}-Hβ\beta Parameter Space

Weak emission-line quasars (WLQs) are a subset of Type 1 quasars that exhibit extremely weak Ly$\alpha +$N V $\lambda$1240 and/or C IV $\lambda$1549 emission lines. We investigate the relationship between emission-line properties and accretion rate for a sample of 230 `ordinary' Type 1 quasars and 18 WLQs at $z < 0.5$ and $1.5 < z < 3.5$ that have rest-frame ultraviolet and optical spectral measurements. We apply a correction to the H$\beta$-based black-hole mass ($M_{\rm BH}$) estimates of these quasars using the strength of the optical Fe II emission. We confirm previous findings that WLQs' $M_{\rm BH}$ values are overestimated by up to an order of magnitude using the traditional broad emission-line region size-luminosity relation. With this $M_{\rm BH}$ correction, we find a significant correlation between H$\beta$-based Eddington luminosity ratios and a combination of the rest-frame C IV equivalent width and C IV blueshift with respect to the systemic redshift. This correlation holds for both ordinary quasars and WLQs, which suggests that the two-dimensional C IV parameter space can serve as an indicator of accretion rate in all Type 1 quasars across a wide range of spectral properties.Comment: 17 pages (AASTeX 6.3.1), 5 figures, accepted for publication in Ap