Multi-function based modeling of 3D heterogeneous wound scaffolds for improved wound healing

This paper presents a new multi-function based modeling of 3D heterogeneous porous wound scaffolds to improve wound healing process for complex deep acute or chronic wounds. An imaging-based approach is developed to extract 3D wound geometry and recognize wound features. Linear healing fashion of the wound margin towards the wound center is mimicked. Blending process is thus applied to the extracted geometry to partition the scaffold into a number of uniformly gradient healing regions. Computer models of 3D engineered porous wound scaffolds are then developed for solid freeform modeling and fabrication. Spatial variation over biomaterial and loaded bio-molecule concentration is developed based on wound healing requirements. Release of bio-molecules over the uniform healing regions is controlled by varying their amount and entrapping biomaterial concentration. Thus, localized controlled release is developed to improve wound healing. A prototype multi-syringe single nozzle deposition system is used to fabricate a sample scaffold. Proposed methodology is implemented and illustrative examples are presented in this paper

3D hybrid wound devices for spatiotemporally controlled release kinetics

This paper presents localized and temporal control of releasekinetics over 3-dimensional (3D) hybridwounddevices to improve wound-healing process. Imaging study is performed to extract wound bed geometry in 3D. Non-Uniform Rational B-Splines (NURBS) based surface lofting is applied to generate functionally graded regions. Diffusion-based releasekinetics model is developed to predict time-based release of loaded modifiers for functionally graded regions. Multi-chamber single nozzle solid freeform dispensing system is used to fabricate wounddevices with controlled dispensing concentration. Spatiotemporal control of biological modifiers thus enables a way to achieve target delivery to improve wound healing

Optimized normal and distance matching for heterogeneous object modeling

This paper presents a new optimization methodology of material blending for heterogeneous object modeling by matching the material governing features for designing a heterogeneous object. The proposed method establishes point-to-point correspondence represented by a set of connecting lines between two material directrices. To blend the material features between the directrices, a heuristic optimization method developed with the objective is to maximize the sum of the inner products of the unit normals at the end points of the connecting lines and minimize the sum of the lengths of connecting lines. The geometric features with material information are matched to generate non-self-intersecting and non-twisted connecting surfaces. By subdividing the connecting lines into equal number of segments, a series of intermediate piecewise curves are generated to represent the material metamorphosis between the governing material features. Alternatively, a dynamic programming approach developed in our earlier work is presented for comparison purposes. Result and computational efficiency of the proposed heuristic method is also compared with earlier techniques in the literature. Computer interface implementation and illustrative examples are also presented in this paper

Designing heterogeneous porous tissue scaffolds for additive manufacturing processes

A novel tissue scaffold design technique has been proposed with controllable heterogeneous architecture design suitable for additive manufacturing processes. The proposed layer-based design uses a bi-layer pattern of radial and spiral layers consecutively to generate functionally gradient porosity, which follows the geometry of the scaffold. The proposed approach constructs the medial region from the medial axis of each corresponding layer, which represents the geometric internal feature or the spine. The radial layers of the scaffold are then generated by connecting the boundaries of the medial region and the layer's outer contour. To avoid the twisting of the internal channels, reorientation and relaxation techniques are introduced to establish the point matching of ruling lines. An optimization algorithm is developed to construct sub-regions from these ruling lines. Gradient porosity is changed between the medial region and the layer's outer contour. Iso-porosity regions are determined by dividing the subregions peripherally into pore cells and consecutive iso-porosity curves are generated using the isopoints from those pore cells. The combination of consecutive layers generates the pore cells with desired pore sizes. To ensure the fabrication of the designed scaffolds, the generated contours are optimized for a continuous, interconnected, and smooth deposition path-planning. A continuous zig-zag pattern deposition path crossing through the medial region is used for the initial layer and a biarc fitted isoporosity curve is generated for the consecutive layer with C-1 continuity. The proposed methodologies can generate the structure with gradient (linear or non-linear), variational or constant porosity that can provide localized control of variational porosity along the scaffold architecture. The designed porous structures can be fabricated using additive manufacturing processes

Modeling of multifunctional porous tissue scaffolds with continuous deposition path plan

A novel modeling technique for porous tissue scaffolds with targeting the functionally gradient variational porosity with continuous material deposition planning has been proposed. To vary the porosity of the designed scaffold functionally, medial axis transformation is used. The medial axis of each layers of the scaffold is calculated and used as an internal feature. The medial axis is then used connected to the outer contour using an optimum matching. The desired pore size and hence the porosity have been achieved by discretizing the sub-regions along its peripheral direction based on the pore size while meeting the tissue scaffold design constraints. This would ensure the truly porous nature of the structure in every direction as well as controllable porosity with interconnected pores. Thus the desired controlled variational porosity along the scaffold architecture has been achieved with the combination of two geometrically oriented consecutive layers. A continuous, interconnected and optimized tool-path has been generated for successive layers for additive-manufacturing or solid free form fabrication process. The proposed methodology has been computationally implemented with illustrative examples. Furthermore, the designed example scaffolds with the desired pore size and porosity has been fabricated with an extrusion based bio-fabrication process

In silico EST-SSRs Analysis in UniGene of Quercus robur L.

Pedunculate oak (Quercus robur L.) is one of the most important tree componentsof Europe’s forest ecosystems, possessing both ecological and economical value. Development of genomic resources, such as genetic markers, is needed to support geneconservation and tree improvement activities. Experimental methods to develop SSR markers are laborious, time consuming and expensive, while in silico approaches havebecome a practicable and inexpensive alternative in genetic studies. The aim of this studywas to characterize simple sequence repeat (EST-SSR) markers and functional annotationof SSR containing sequences in Q. robur unigene sequences. 7170 unigene sequences(5147.315 kb) of Q. robur were downloaded from National Center for BiotechnologyInformation (NCBI). A total of 475 (6.62 %) unigene sequences containing 525 SSRs (microsatellites) were identified by using MISA software. The average frequency ofmicrosatellites was found, on average, one in every 9.8 kb of sequence. The analysisrevealed that tri-nucleotide repeats (42.6%) were most abundant followed by dinucleotide(36.9%), hexa-nucleotide (11.8%), penta-nucleotide (4.9%) and tetra-nucleotiderepeats (3.8%), respectively. Flanking sequences of the 525 SSRs generated 500 primers(95.2%) with forward and reverse strands by using Primer3 software. Gene based SSRmarkers can be used for studies of genetic diversity, population genetics, geneticmapping, gene tagging and more. Large numbers of unigenes containing SSRs (77.4%),annotations were available 46.75% of which were predicted, 23.91% were hypothetical,8.83% were putative and 20.51% belonged to other protein types. Only 22.5% sequencecould not assign to any specific protein class

A continues multi-material toolpath planning for tissue scaffolds with hollowed features

This paper presents a new multi-material based toolpath planning methodology for porous tissue scaffolds with multiple hollowed features. Ruled surface with hollowed features generated in our earlier work is used to develop toolpath planning. Ruling lines are reoriented to enable continuous and uniform size multi-material printing through them in two steps. Firstly, all ruling lines are matched and connected to eliminate start and stops during printing. Then, regions with high number of ruling lines are relaxed using a relaxation technique to eliminate over deposition. A novel layer-by-layer deposition process is progressed in two consecutive layers: The first layer with hollow shape based zigzag pattern and the next layer with spiral pattern deposition. Heterogeneous material properties are mapped based on the parametric distances from the hollow features

Blending Generative Adversarial Image Synthesis with Rendering for Computer Graphics

Conventional computer graphics pipelines require detailed 3D models, meshes, textures, and rendering engines to generate 2D images from 3D scenes. These processes are labor-intensive. We introduce Hybrid Neural Computer Graphics (HNCG) as an alternative. The contribution is a novel image formation strategy to reduce the 3D model and texture complexity of computer graphics pipelines. Our main idea is straightforward: Given a 3D scene, render only important objects of interest and use generative adversarial processes for synthesizing the rest of the image. To this end, we propose a novel image formation strategy to form 2D semantic images from 3D scenery consisting of simple object models without textures. These semantic images are then converted into photo-realistic RGB images with a state-of-the-art conditional Generative Adversarial Network (cGAN) based image synthesizer trained on real-world data. Meanwhile, objects of interest are rendered using a physics-based graphics engine. This is necessary as we want to have full control over the appearance of objects of interest. Finally, the partially-rendered and cGAN synthesized images are blended with a blending GAN. We show that the proposed framework outperforms conventional rendering with ablation and comparison studies. Semantic retention and Fr\'echet Inception Distance (FID) measurements were used as the main performance metrics

Cluster Index Modulation for Reconfigurable Intelligent Surface-Assisted mmWave Massive MIMO

In this paper, we propose a transmission mechanism for a reconfigurable intelligent surface (RIS)-assisted millimeter wave (mmWave) system based on cluster index modulation (CIM), named best-gain optimized cluster selection CIM (BGCS-CIM). The proposed BGCS-CIM scheme considers effective cluster power gain and spatial diversity gain obtained by the additional paths within the indexed cluster to construct an efficient codebook. We also integrate the proposed scheme into a practical system model to create a virtual path between transmitter and receiver where the direct link has been blocked. Thanks to the designed whitening filter, a closed-form expression for the upper bound on the average bit error rate (ABER) is derived and used to validate the simulation results. It has been shown that the proposed BGCS-CIM scheme outperforms the existing benchmarks thanks to its higher effective cluster gain, spatial diversity of indexed clusters, and lower inter-cluster interference.Comment: Submitted in IEE