Investigation of the influence of a step change in surface roughness on turbulent heat transfer

The use is studied of smooth heat flux gages on the otherwise very rough SSME fuel pump turbine blades. To gain insights into behavior of such installations, fluid mechanics and heat transfer data were collected and are reported for a turbulent boundary layer over a surface with a step change from a rough surface to a smooth surface. The first 0.9 m length of the flat plate test surface was roughened with 1.27 mm hemispheres in a staggered, uniform array spaced 2 base diameters apart. The remaining 1.5 m length was smooth. The effect of the alignment of the smooth surface with respect to the rough surface was also studied by conducting experiments with the smooth surface aligned with the bases or alternatively with the crests of the roughness elements. Stanton number distributions, skin friction distributions, and boundary layer profiles of temperature and velocity are reported and are compared to previous data for both all rough and all smooth wall cases. The experiments show that the step change from rough to smooth has a dramatic effect on the convective heat transfer. It is concluded that use of smooth heat flux gages on otherwise rough surfaces could cause large errors

Formation of oligopeptides in high yield under simple programmable conditions

Many high-yielding reactions for forming peptide bonds have been developed but these are complex, requiring activated amino-acid precursors and heterogeneous supports. Herein we demonstrate the programmable one-pot dehydration–hydration condensation of amino acids forming oligopeptide chains in around 50% yield. A digital recursive reactor system was developed to investigate this process, performing these reactions with control over parameters such as temperature, number of cycles, cycle duration, initial monomer concentration and initial pH. Glycine oligopeptides up to 20 amino acids long were formed with very high monomer-to-oligomer conversion, and the majority of these products comprised three amino acid residues or more. Having established the formation of glycine homo-oligopeptides, we then demonstrated the co-condensation of glycine with eight other amino acids (Ala, Asp, Glu, His, Lys, Pro, Thr and Val), incorporating a range of side-chain functionality

Biomimetic strategies for fracture repair: engineering the cell microenvironment for directed tissue formation

Complications resulting from impaired fracture healing have major clinical implications on fracture management strategies. Novel concepts taken from developmental biology have driven research strategies towards the elaboration of regenerative approaches that can truly harness the complex cellular events involved in tissue formation and repair. Advances in polymer technology and a better understanding of naturally derived scaffolds have given rise to novel biomaterials with an increasing ability to recapitulate native tissue environments. This coupled with advances in the understanding of stem cell biology and technology has opened new avenues for regenerative strategies with true clinical translatability. These advances have provided the impetus to develop alternative approaches to enhance the fracture repair process. We provide an update on these advances, with a focus on the development of novel biomimetic approaches for bone regeneration and their translational potential

ActiveStereoNet: End-to-End Self-Supervised Learning for Active Stereo Systems

In this paper we present ActiveStereoNet, the first deep learning solution for active stereo systems. Due to the lack of ground truth, our method is fully self-supervised, yet it produces precise depth with a subpixel precision of $1/30th$ of a pixel; it does not suffer from the common over-smoothing issues; it preserves the edges; and it explicitly handles occlusions. We introduce a novel reconstruction loss that is more robust to noise and texture-less patches, and is invariant to illumination changes. The proposed loss is optimized using a window-based cost aggregation with an adaptive support weight scheme. This cost aggregation is edge-preserving and smooths the loss function, which is key to allow the network to reach compelling results. Finally we show how the task of predicting invalid regions, such as occlusions, can be trained end-to-end without ground-truth. This component is crucial to reduce blur and particularly improves predictions along depth discontinuities. Extensive quantitatively and qualitatively evaluations on real and synthetic data demonstrate state of the art results in many challenging scenes.Comment: Accepted by ECCV2018, Oral Presentation, Main paper + Supplementary Material

Tissue-Engineering the Fibrous Pancreatic Tumour Stroma Capsule in 3D Tumouroids to Demonstrate Paclitaxel Response

Pancreatic cancer is a unique cancer in that up to 90% of its tumour mass is composed of a hypovascular and fibrotic stroma. This makes it extremely difficult for chemotherapies to be delivered into the core of the cancer mass. We tissue-engineered a biomimetic 3D pancreatic cancer ("tumouroid") model comprised of a central artificial cancer mass (ACM), containing MIA Paca-2 cells, surrounded by a fibrotic stromal compartment. This stromal compartment had a higher concentration of collagen type I, fibronectin, laminin, and hyaluronic acid (HA) than the ACM. The incorporation of HA was validated with alcian blue staining. Response to paclitaxel was determined in 2D MIA Paca-2 cell cultures, the ACMs alone, and in simple and complex tumouroids, in order to demonstrate drug sensitivity within pancreatic tumouroids of increasing complexity. The results showed that MIA Paca-2 cells grew into the complex stroma and invaded as cell clusters with a maximum distance of 363.7 µm by day 21. In terms of drug response, the IC50 for paclitaxel for MIA Paca-2 cells increased from 0.819 nM in 2D to 3.02 nM in ACMs and to 5.87 nM and 3.803 nM in simple and complex tumouroids respectively, indicating that drug penetration may be significantly reduced in the latter. The results demonstrate the need for biomimetic models during initial drug testing and evaluation

Biophysical Parameters Can Induce Epithelial-to-Mesenchymal Phenotypic and Genotypic Changes in HT-29 Cells: A Preliminary Study

Epithelial to mesenchymal transition (EMT) in cancer is the process described where cancer epithelial cells acquire mesenchymal properties which can lead to enhanced invasiveness. Three-dimensional cancer models often lack the relevant and biomimetic microenvironment parameters appropriate to the native tumour microenvironment thought to drive EMT. In this study, HT-29 epithelial colorectal cells were cultivated in different oxygen and collagen concentrations to investigate how these biophysical parameters influenced invasion patterns and EMT. Colorectal HT-29 cells were grown in physiological hypoxia (5% O2) and normoxia (21% O2) in 2D, 3D soft (60 Pa), and 3D stiff (4 kPa) collagen matrices. Physiological hypoxia was sufficient to trigger expression of markers of EMT in the HT-29 cells in 2D by day 7. This is in contrast to a control breast cancer cell line, MDA-MB-231, which expresses a mesenchymal phenotype regardless of the oxygen concentration. In 3D, HT-29 cells invaded more extensively in a stiff matrix environment with corresponding increases in the invasive genes MMP2 and RAE1. This demonstrates that the physiological environment can directly impact HT-29 cells in terms of EMT marker expression and invasion, compared to an established cell line, MDA-MB-231, which has already undergone EMT. This study highlights the importance of the biophysical microenvironment to cancer epithelial cells and how these factors can direct cell behaviour. In particular, that stiffness of the 3D matrix drives greater invasion in HT-29 cells regardless of hypoxia. It is also pertinent that some cell lines (already having undergone EMT) are not as sensitive to the biophysical features of their microenvironment

Occlusion-Aware Depth Estimation with Adaptive Normal Constraints

We present a new learning-based method for multi-frame depth estimation from a color video, which is a fundamental problem in scene understanding, robot navigation or handheld 3D reconstruction. While recent learning-based methods estimate depth at high accuracy, 3D point clouds exported from their depth maps often fail to preserve important geometric feature (e.g., corners, edges, planes) of man-made scenes. Widely-used pixel-wise depth errors do not specifically penalize inconsistency on these features. These inaccuracies are particularly severe when subsequent depth reconstructions are accumulated in an attempt to scan a full environment with man-made objects with this kind of features. Our depth estimation algorithm therefore introduces a Combined Normal Map (CNM) constraint, which is designed to better preserve high-curvature features and global planar regions. In order to further improve the depth estimation accuracy, we introduce a new occlusion-aware strategy that aggregates initial depth predictions from multiple adjacent views into one final depth map and one occlusion probability map for the current reference view. Our method outperforms the state-of-the-art in terms of depth estimation accuracy, and preserves essential geometric features of man-made indoor scenes much better than other algorithms.Comment: ECCV 202

Mapping human serum induced gene networks as a basis for the creation of biomimetic periosteum for bone repair

The periosteum is a highly vascularised, collagen-rich tissue that plays a crucial role in directing bone repair. This is orchestrated primarily by its resident progenitor cell population. Indeed, preservation of periosteum integrity is critical for bone healing. Cells extracted from the periosteum retain their osteochondrogenic properties and as such are a promising basis for tissue engineering strategies for the repair of bone defects. However, the culture expansion conditions, and the way in which the cells are reintroduced to the defect site are critical aspects of successful translation. Indeed, expansion in human serum and implantation on biomimetic materials has previously been shown to improve in vivo bone formation. As such, this study aimed to develop a protocol to allow for the expansion of human periosteum derived cells (hPDCs) in a biomimetic periosteal-like environment. The expansion conditions were defined through the investigation of the bioactive cues involved in augmenting hPDC proliferative and multipotency characteristics, based on transcriptomic analysis of cells cultured in human serum. Master regulators of transcriptional networks were identified and an optimised periosteal derived-growth factor cocktail (PD-GFC; containing β-Estradiol, FGF2, TNFα, TGFβ, IGF-1 and PDGF-BB) was generated. Expansion of hPDCs in PD-GFC resulted in serum mimicry with regards to the cell morphology, proliferative capacity and chondrogenic differentiation. When incorporated into a 3D collagen-type-1 matrix and cultured in PD-GFC, the hPDCs migrated to the surface that represented the matrix topography of the periosteum cambium layer. Furthermore, gene expression analysis revealed a downregulated Wnt and TGFβ signature and an upregulation of CREB, which may indicate the hPDCs are recreating their progenitor cell signature. This study highlights the first stage in the development of a biomimetic periosteum which may have applications in bone repair

Custom-designed orthopedic implants evaluated using finite element analysis of patient-specific computed tomography data: femoral-component case study

<p>Abstract</p> <p>Background</p> <p>Conventional knee and hip implant systems have been in use for many years with good success. However, the custom design of implant components based on patient-specific anatomy has been attempted to overcome existing shortcomings of current designs. The longevity of cementless implant components is highly dependent on the initial fit between the bone surface and the implant. The bone-implant interface design has historically been limited by the surgical tools and cutting guides available; and the cost of fabricating custom-designed implant components has been prohibitive.</p> <p>Methods</p> <p>This paper describes an approach where the custom design is based on a Computed Tomography scan of the patient's joint. The proposed design will customize both the articulating surface and the bone-implant interface to address the most common problems found with conventional knee-implant components. Finite Element Analysis is used to evaluate and compare the proposed design of a custom femoral component with a conventional design.</p> <p>Results</p> <p>The proposed design shows a more even stress distribution on the bone-implant interface surface, which will reduce the uneven bone remodeling that can lead to premature loosening.</p> <p>Conclusion</p> <p>The proposed custom femoral component design has the following advantages compared with a conventional femoral component. (i) Since the articulating surface closely mimics the shape of the distal femur, there is no need for resurfacing of the patella or gait change. (ii) Owing to the resulting stress distribution, bone remodeling is even and the risk of premature loosening might be reduced. (iii) Because the bone-implant interface can accommodate anatomical abnormalities at the distal femur, the need for surgical interventions and fitting of filler components is reduced. (iv) Given that the bone-implant interface is customized, about 40% less bone must be removed. The primary disadvantages are the time and cost required for the design and the possible need for a surgical robot to perform the bone resection. Some of these disadvantages may be eliminated by the use of rapid prototyping technologies, especially the use of Electron Beam Melting technology for quick and economical fabrication of custom implant components.</p