CAD Domain Research Articles

Spin-It Faster: Quadrics Solve All Topology Optimization Problems That Depend Only On Mass Moments

The behavior of a rigid body primarily depends on its mass moments, which consist of the mass, center of mass, and moments of inertia. It is possible to manipulate these quantities without altering the geometric appearance of an object by introducing cavities in its interior. Algorithms that find cavities of suitable shapes and sizes have enabled the computational design of spinning tops, yo-yos, wheels, buoys, and statically balanced objects. Previous work is based, for example, on topology optimization on voxel grids, which introduces a large number of optimization variables and box constraints, or offset surface computation, which cannot guarantee that solutions to a feasible problem will always be found. In this work, we provide a mathematical analysis of constrained topology optimization problems that depend only on mass moments. This class of problems covers, among others, all applications mentioned above. Our main result is to show that no matter the outer shape of the rigid body to be optimized or the optimization objective and constraints considered, the optimal solution always features a quadric-shaped interface between material and cavities. This proves that optimal interfaces are always ellipsoids, hyperboloids, paraboloids, or one of a few degenerate cases, such as planes. This insight lets us replace a difficult topology optimization problem with a provably equivalent non-linear equation system in a small number (<10) of variables, which represent the coefficients of the quadric. This system can be solved in a few seconds for most examples, provides insights into the geometric structure of many specific applications, and lets us describe their solution properties. Finally, our method integrates seamlessly into modern fabrication workflows because our solutions are analytical surfaces that are native to the CAD domain.

Allosteric regulation of the inactive to active state conformational transition in CDPK1 protein of Plasmodium falciparum

The aim of the current study is to investigate the role of the CAD domain in the activation mechanism of calcium dependent protein kinase-1 of Plasmodium falciparum (PfCDPK1) and explore the possibility of allosteric inhibition of this kinase. PfCDPK1 belongs to CDPK family of apicomplexan kinases which have a C-terminal CAD domain. Microsecond scale MD simulations were performed on modeled structures of complete PfCDPK1 and its kinase domain alone. The simulations revealed that in absence of CAD the salt bridge between Glu116 in αC-helix and Lys85 in β3-sheet of kinase breaks after 200 ns resulting in inactive conformation of the kinase, but the salt bridge stays intact in the complete protein stabilizing it in active conformation. These results highlight the novel CAD mediated allosteric stabilization of the crucial salt bridge which is a hallmark of active conformation of kinase domains. The mechanistic details of the allosteric activation revealed by our study, opens up the possibility for design of allosteric inhibitors of PfCDPK1 kinase by disrupting the kinase:CAD interactions. Using a combination of machine learning and structure-based in silico screening, we have identified novel PPI modulators for allosteric inactivation of PfCDPK1 kinase.

Deep learning-based framework for Shape Instance Registration on 3D CAD models

3D CAD models play an important role in large-scale engineering projects. The increasing demand for highly-detailed datasets presents a challenge for efficient storage, transmission, and rendering. To reduce dataset size, 3D shape matching techniques have been proposed to find repeated triangle meshes, but are strongly dependent on surface triangulation. Meanwhile, existing shape registration techniques are not well suited for the 3D CAD domain. In this paper, we present a deep learning-based framework that uses point clouds to identify repeated instances of triangle meshes (a single 3D CAD model component) overcoming the limitations of previous work and guaranteeing an upper bound on any geometric errors. The framework combines PointNet++ for shape classification with a registration procedure based on Principal Component Analysis and the Adam optimizer. The resulting affine transformation can be used to efficiently instantiate repeated CAD geometries. Using the proposed framework, we were able to reduce a real-world 3D CAD model to 2.61% of its original size, while preserving its geometric accuracy and improving rendering performance.

The early temperamental correlates of antisocial propensity

•The three CAD domains are likely dimensional, not categorical.•More concerning temperament profiles can be identified by at least 3 years of age.•Negative emotionality may be important to the development of impulsive and sensation-seeking behaviors during childhood.•Negative emotionality may be important to the development of prosocial values during childhood.

Persistent Naming Based on Graph Transformation Rules to Reevaluate Parametric Specification

The ability of 3D modeling tools to generate automatically various versions of a similar model is an increasing need in several and diferent domains such as Archaeology, Architecture or Geology. To address this issue, we propose to use both the Jerboa library designed to assist the development of application-specific modelers and the reevaluation methods used for parametric systems in the CAD domain. Unlike most approaches, Jerboa is independent from any application domain and allows rapid development of new operations using graph transformation rules to automatically check the consistency of different objects properties. But it do es not support any reevaluation mechanism and especially not a persistent naming system , that is used to identify entities of the initial model and match them with entities of the reevaluated model. Using the capacity of graph transformation rules, we address naming problems through a very precise characterization of the basic elements forming the model.

Utilities of Virtual 3D City Models Based on CityGML: Various Use Cases

Virtual 3D city models are increasingly being used to model the realms of the real world for utilization in a number of applications related to environmental simulations including, urban planning, mapping the energy characteristics of buildings, noise mapping, flood modelling, etc. Apart from geometric and appearance/textural information, these applications have a requirement for complex urban semantics. Currently, a number of 3D standards are available in CAD, BIM and GIS related domains for the storage, visualization and transfer of 3D geospatial datasets. Initially, the 3D data models (such as COLLADA, VRML, X3D, etc.) were purely graphical/geometrical in nature and mainly used for visualization purposes. With the inclusion of thematic modules in OGC CityGML, the integration of geometry and semantics in a single data model paved the way for better sharing of virtual 3D city models. In spite of the availability of a wide range of 3D data standards, there are certain differences with respect to geometry, topology, semantics, LODs, etc., which complicates the integration of 3D geodata from heterogeneous sources. This paper serves to highlights the need for the innovative solutions with respect to the urban environmental related simulations primarily based on the use of virtual 3D city models. Four use cases are studied in this context namely, (1) urban solar potential estimation using CityGML models, (2) simulation of traffic noise level mapped on building walls from the urban road segments, (3) CityGML based 3D data models interoperability, and (4) 3D indoor logistics and subsurface utilities. However, for modelling majority of use cases, CityGML does not provide explicit thematic representations but provides support for extending the CityGML schema using Application Domain Extensions. In a nutshell, the study explores the semantic modelling capabilities of the CityGML for the transformation of native 3D virtual city models to one satisfying capabilities like semantic information and support towards interoperability.

Isogeometric Schwarz preconditioners for the biharmonic problem

A scalable overlapping Schwarz preconditioner for the biharmonic Dirichlet problem discretized by isogeometric analysis is constructed, and its convergence rate is analyzed. The proposed preconditioner is based on solving local biharmonic problems on overlapping subdomains that form a partition of the CAD domain of the problem and on solving an additional coarse biharmonic problem associated with the subdomain coarse mesh. An h-analysis of the preconditioner shows an optimal convergence rate bound that is scalable in the number of subdomains and is cubic in the ratio between subdomain and overlap sizes. Numerical results in 2D and 3D confirm this analysis and also illustrate the good convergence properties of the preconditioner with respect to the isogeometric polynomial degree p and regularity k.

Structural Insight into the Core of CAD, the Multifunctional Protein Leading De Novo Pyrimidine Biosynthesis

CAD, the multifunctional protein initiating and controlling de novo biosynthesis of pyrimidines in animals, self-assembles into ∼1.5 MDa hexamers. The structures of the dihydroorotase (DHO) and aspartate transcarbamoylase (ATC) domains of human CAD have been previously determined, but we lack information on how these domains associate and interact with the rest of CAD forming a multienzymatic unit. Here, we prove that a construct covering human DHO and ATC oligomerizes as a dimer of trimers and that this arrangement is conserved in CAD-like from fungi, which holds an inactive DHO-like domain. The crystal structures of the ATC trimer and DHO-like dimer from the fungus Chaetomium thermophilum confirm the similarity with the human CAD homologs. These results demonstrate that, despite being inactive, the fungal DHO-like domain has a conserved structural function. We propose a model that sets the DHO and ATC complex as the central element in the architecture of CAD.

On solving partition driven standard cell placement problem using firefly-based metaheuristic approach

The standard-cell placement problem has drawn great attention in the VLSI CAD domain. Being an NP complete problem, a spacious range of heuristic approaches exist in the literature for expeditiously organising the circuit elements on a VLSI chip design. The advancement in the partitioning algorithms has made the recursive bisection-based placement more attractive. The paper presents a metaheuristic approach based on firefly algorithm for partition-driven global standard cell placement. The algorithm is tested against circuits from the MCNC and IBM benchmark circuits and gives promising results in comparison to meta genetic approach.

Purifying Properly Folded Cysteine-rich, Zinc Finger Containing Recombinant Proteins for Structural Drug Targeting Studies: the CH1 Domain of p300 as a Case Example.

The transcription factor Hypoxia-Inducible Factor (HIF) complexes with the coactivator p300, activating the hypoxia response pathway and allowing tumors to grow. The CH1 and CAD domains of each respective protein form the interface between p300 and HIF. Small molecule compounds are in development that target and inhibit HIF/p300 complex formation, with the goal of reducing tumor growth. High resolution NMR spectroscopy is necessary to study ligand interaction with p300-CH1, and purifying high quantities of properly folded p300-CH1 is needed for pursuing structural and biophysical studies. p300-CH1 has 3 zinc fingers and 9 cysteine residues, posing challenges associated with reagent compatibility and protein oxidation. A protocol has been developed to overcome such issues by incorporating zinc during expression and streamlining the purification time, resulting in a high yield of optimally folded protein (120 mg per 4 L expression media) that is suitable for structural NMR studies. The structural integrity of the final recombinant p300-CH1 has been verified to be optimal using onedimensional 1H NMR spectroscopy and circular dichroism. This protocol is applicable for the purification of other zinc finger containing proteins.

4D CAD Based Method for Supporting Coordination of Urban Subsurface Utility Projects

Coordinators of inner city utility construction works face increasing difficulty in managing their projects due to tight physical restrictions, strict deadlines and growing stakeholder fragmentation. This paper therefore presents a 4D CAD based coordination method that supports project plan scoping, formalizing and synchronizing. We developed and implemented the method by conducting ethnographic action research in four project cases. In these projects, we observed that 4D-models generated with the method allowed practitioners to identify project interfaces and conflicts, to identify schedule shortcomings and to evaluate delays. By introducing the method and reporting on its empirical evaluation we extend 4D CAD's domain of applicability with mid and small-sized utility projects and address a need for 4D implementation studies.

Smoothness driven frame field generation for hexahedral meshing

For many years, providing an algorithm to generate hexahedral meshes that fulfill minimal geometric criteria (boundary-alignment, minimum of singularity vertices) and that is not limited to a category of geometries has been an open issue. In the past couple of years, techniques using 3D frame fields have emerged to design such meshes (Huang et al., 2011; Li et al., 2012). Those methods are based on a two-step process where a 3D frame field is built by assigning a frame to each cell of a tetrahedral mesh, then a parametrization algorithm is applied to generate a hexahedral mesh. In this work, we propose a novel algorithm to generate block-structured hexahedral meshes for any CAD domain Ω. This work differs from previous ones in many points: (1) the proposed approach does not need to start from a pre-meshed quad boundary; (2) The frame field initialization does not put singularity lines around the medial object of Ω; (3) Conceptually, frames are assigned to the vertices and not to the cells of the tetrahedral mesh; (4) The parametrization process is replaced by a constructive algorithm that generates a block structure, which partitions Ω in meshable regions.

STIM1 Is a Novel Component of ER-Chlamydia trachomatis Inclusion Membrane Contact Sites.

Productive developmental cycle of the obligate intracellular bacterial pathogen Chlamydia trachomatis depends on the interaction of the replicative vacuole, named the inclusion, with cellular organelles. We have recently reported the formation of ER-Inclusion membrane contact sites (MCSs), where the endoplasmic reticulum (ER) is in apposition to the inclusion membrane. These platforms contain the C. trachomatis inclusion membrane protein IncD, the mammalian ceramide transfer protein CERT and the ER resident proteins VAPA/B and were proposed to play a role in the non-vesicular trafficking of lipids to the inclusion. Here, we identify STIM1 as a novel component of ER-Inclusion MCSs. STIM1, an ER calcium (Ca2+) sensor that relocate to ER-Plasma Membrane (PM) MCSs upon Ca2+ store depletion, associated with C. trachomatis inclusion. STIM1, but not the general ER markers Rtn3C and Sec61ß, was enriched at the inclusion membrane. Ultra-structural studies demonstrated that STIM1 localized to ER-Inclusion MCSs. Time-course experiments showed that STIM1, CERT and VAPB co-localized throughout the developmental cycle. By contrast, Orai1, the PM Ca2+ channel that interacts with STIM1 at ER-PM MCSs, did not associate with C. trachomatis inclusion. Upon ER Ca2+ store depletion, a pool of STIM1 relocated to ER-PM MCSs, while the existing ER-Inclusion MCSs remained enriched in STIM1. Finally, we have identified the CAD domain, which mediates STIM1-Orai1 interaction, as the minimal domain required for STIM1 enrichment at ER-Inclusion MCSs. Altogether this study identifies STIM1 as a novel component of ER-C. trachomatis inclusion MCSs. We discuss the potential role(s) of STIM1 during the infection process.

Cloning and characterization of an apoptosis-related DNA fragmentation factor (DFF) from oyster, Crassostrea hongkongensis

Apoptosis plays an important pathophysiological role in the homeostasis of immune systems. DNA fragmentation factors (DFFs) have been shown to be essential for DNA fragmentation, and the resultant DNA fragments follow a laddering pattern during apoptosis in vertebrates. In invertebrates, the functions of the DFF orthologs are not well characterized; therefore, we cloned and characterized a bivalve DFFA ortholog from the Hong Kong oyster Crassostrea hongkongensis (designated ChDFFA). The full-length cDNA of ChDFFA is 1186 bp in length and encodes a putative protein of 200 amino acids that contains an N-terminal CAD domain and a DFF-C domain at its C-terminus. Real-time RT-PCR results showed that ChDFFA is ubiquitously expressed in several tissues, and its highest expression is in gill. Following a 3- to 48-h challenge by microbial infection, the expression of ChDFFA increased in hemocytes. Using fluorescence microscopy, ChDFFA was localized in nuclei when exogenously expressed in HeLa cells. In addition, over-expression of ChDFFA inhibited the transcriptional activities of p53/p21-Luc reporter genes in HEK293T cells. These results suggest that ChDFFA may be involved in immune response reactions in the Hong Kong oyster C. hongkongensis.

A deep learning approach to the classification of 3D CAD models

Model classification is essential to the management and reuse of 3D CAD models. Manual model classification is laborious and error prone. At the same time, the automatic classification methods are scarce due to the intrinsic complexity of 3D CAD models. In this paper, we propose an automatic 3D CAD model classification approach based on deep neural networks. According to prior knowledge of the CAD domain, features are selected and extracted from 3D CAD models first, and then preprocessed as high dimensional input vectors for category recognition. By analogy with the thinking process of engineers, a deep neural network classifier for 3D CAD models is constructed with the aid of deep learning techniques. To obtain an optimal solution, multiple strategies are appropriately chosen and applied in the training phase, which makes our classifier achieve better performance. We demonstrate the efficiency and effectiveness of our approach through experiments on 3D CAD model datasets.

A Review on Approaches for Handling Bezier Curves in CAD for Manufacturing

Ever since aesthetics have emerged in modern design, parametric curve like Bezier is widely used in CAD design. Various techniques and methodologies like curve fitting, curve manipulation, blending and merging of curves have been proposed over the years for better handling and enhancing Bezier curve use with every possible application in CAD domain such as image extraction, modelization, profile approximation, fairing and smoothing, etc. These techniques have found its applications in manufacturing as well. A review is done on various approaches for handling Bezier curve in Computer Aided Design for the purpose of manufacturing for example tool path optimization, profile design, reverse engineering, etc.

Block-structured Hexahedral Meshes for CAD Models Using 3D Frame Fields

In the past couple of years, techniques using 3D frame fields have emerged to design hexahedral meshes[1,2]. Those methods are based on a two-step process where a 3D frame field is built by assigning a frame to each cell of a tetrahedral mesh, then a parametrization algorithm is applied to generate a hexahedral mesh. In this paper, we propose a novel algorithm to generate block-structured hexahedral meshes for any CAD domain Ω. This work differs from previous ones in several points: (1) the proposed approach does not start from a pre-meshed boundary; (2) The frame field initialization does not put singularity lines around the medial object of Ω; (3) Frames are assigned to the vertices and not to the cells of the tetrahedral mesh; (4) We do not perform a parametrization process but we generate a block structure that partition Ω in meshable regions.

Characterization of Bombyx embryo segmentation process: expression profiles of engrailed, even‐skipped, caudal, and wnt1/wingless homologues

To gain insight into segmentation processes, the expression at embryonic stages of the silkmoth Bombyx mori homologues of even-skipped (eve), engrailed (en), caudal (cad), and wnt1/wingless (wg) transcripts were examined by whole mount in situ hybridization. Pair-rule eve stripes and segmental en and wnt1/wg stripes were generated sequentially from anterior to posterior, confirming the previous results that showed that Bombyx belongs to short-germ insects. However, unlike in previously described short germ insects, the segmentation of Bombyx occurred without marked germ band elongation: the putative growth zone was expanded compared with previously described short germ insects. This may indicate that Bombyx represents an evolutionarily intermediate state in a transition from short to long germ type. The expressions of cad and wnt1/wg, which are known to be present in the growth zone in short germ insects, initially showed a large median expression domain that, as segmentation proceeded, later retracted to the posterior pole. This is also unique to this insect. Detailed analysis of their relative expressions indicated that wnt1/wg domain retracted faster than the cad domain, and double stain in situ hybridization suggested that the eve stripe appears from cells that have ceased to express wnt1/wg. Another unique aspect of Bombyx embryogenesis is that gastrulation began at later embryonic stage compared with other insects and proceeded slowly from anterior to posterior. On the basis of these results, conserved and divergent aspects of the evolution of insect segmentation mechanisms and germ cell formation are discussed.

Stim1 Binds to and Inhibits CaV1.2 Voltage Gated Calcium Channels

CaV1.2 and other L-type voltage gated calcium channels play a key role in regulating cardiac contraction, synaptic plasticity, insulin secretion and a variety of other cellular events. Phospho-inositide linked receptors like the muscarinic acetylcholine receptor, inhibit L-type calcium channels and this inhibition is important for parasympathetic regulation of heart contraction as well as for learning and memory in the brain. The mechanisms by which PLC coupled receptors inhibit L-type channels are still controversial though several hypotheses including reduction of cAMP and depletion of PIP2 from the cell membrane have been proposed. We report a new and unexpected mechanism by which PLC-coupled receptors inhibit L-type calcium channels in cells. We have found that depletion of ER calcium stores either down stream of muscarinic receptors or following application of the ER calcium ATPase inhibitor, thapsigargin, inhibits CaV1.2 channels. CaV1.2 inhibition depends on binding to Stim1, an ER calcium sensor protein that activates the Orai family of store operated calcium channels. In cells expressing CaV1.2, Stim1 translocates to ER-plasma membrane junctions and co-localizes with clusters of CaV1.2. In vitro and in vivo studies indicate that the CAD domain of Stim1 binds to a coiled coil in the II-III loop of CaV1.2. Stim1 lacking the CAD domain is unable to bind to CaV1.2 and fails to inhibit CaV1.2 currents following depletion of ER calcium stores. These studies support a new mechanism by which phosphoinositide-linked receptors inhibit L-type calcium channels and suggest that Stim1 dynamically regulates the relative contributions of Orai and CaV1.2 channels to calcium influx in excitable cells.

ADVERSE IVF/ICSI OUTCOMES ASSOCIATED WITH HIGHER LEVELS OF SPERM DNA FRAGMENTATION

Apoptosis plays an important pathophysiological role in the homeostasis of immune systems. DNA fragmentation factors (DFFs) have been shown to be essential for DNA fragmentation, and the resultant DNA fragments follow a laddering pattern during apoptosis in vertebrates. In invertebrates, the functions of the DFF orthologs are not well characterized; therefore, we cloned and characterized a bivalve DFFA ortholog from the Hong Kong oyster Crassostrea hongkongensis (designated ChDFFA). The full-length cDNA of ChDFFA is 1186 bp in length and encodes a putative protein of 200 amino acids that contains an N-terminal CAD domain and a DFF-C domain at its C-terminus. Real-time RT-PCR results showed that ChDFFA is ubiquitously expressed in several tissues, and its highest expression is in gill. Following a 3- to 48-h challenge by microbial infection, the expression of ChDFFA increased in hemocytes. Using fluorescence microscopy, ChDFFA was localized in nuclei when exogenously expressed in HeLa cells. In addition, over-expression of ChDFFA inhibited the transcriptional activities of p53/p21-Luc reporter genes in HEK293T cells. These results suggest that ChDFFA may be involved in immune response reactions in the Hong Kong oyster C. hongkongensis.