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Augmented reality (AR) is a unique, hands-on tool to deliver information. However, its educational value has been mainly demonstrated empirically so far. In this paper, we present a modeling approach to provide users with mastery of a skill, using AR learning content to implement an educational curriculum. We illustrate the potential of this approach by applying this to an important but pervasively misunderstood area of STEM learning, electrical circuitry. Unlike previous cognitive assessment models, we break down the area into microskills--the smallest segmentation of this knowledge--and concrete learning outcomes for each. This model empowers the user to perform a variety of tasks that are conducive to the acquisition of the skill. We also provide a classification of microskills and how to design them in an AR environment. Our results demonstrated that aligning the AR technology to specific learning objectives paves the way for high quality assessment, teaching, and learning.

BACKGROUND Compression Molding Jog (1) offers a good review of compression molding of neat thermoplastic resins. Polymeric powders are compression molded because melt flow polymer processing, like injection molding, does [...]

The processing of high temperature thermoplastic polymers as a hot melt adhesive is one means of joining thermoplastics to metals. The present study establishes the role of processing in thermoplastic joining of a titanium alloy (Ti-6A1-4V) using thin film poly(etherketoneetherketoneketone) (PEKEKK). A design of experiments (DOE) was performed to determine the effects of the soak above melt temperature ([T.sub.m] = 380 ° C), hold at the isothermal recrystallization temperature ([T.sub.iso] = [approximately] 340 ° C) and cooling rates on the joint strength. Extended soak times are required to remove the residual spherulitic crystallinity in the polymeric adhesive. With the elimination of the residual crystallinity, high-strength transcrystalline regions are enhanced at the polymer-metal interface during the hold time at [T.sub.iso] and during cooling to ambient temperature. Average tensile strengths of 137 MPa were achieved, exceeding the bulk polymer tensile strength of 118 MPa by 16%. X-ray photoelectron spectroscopy (XPS) and scanning electron microscopy (SEM) show that extended soak times above [T.sub.m] led to excessive polymer squeeze-out, resulting in the creation of strength-reducing shrink voids or unwetted regions. As a result, the failure mode of the joint, which was normally cohesive for high-strength joints, became a mix of cohesive and adhesive in parts with excessive polymer squeeze out., INTRODUCTION Many of the previous studies of joining have been directed toward thermoset-based adhesives such as epoxies. The thermoset-based adhesives generally require a time-consuming cure process. Hot-melt thermoplastic adhesives have [...]

Abstract Background Many molecules of interest are flexible and undergo significant shape deformation as part of their function, but most existing methods of molecular shape comparison treat them as rigid shapes, which may lead to incorrect measure of the shape similarity of flexible molecules. Currently, there still is a limited effort in retrieval and navigation for flexible molecular shape comparison, which would improve data retrieval by helping users locate the desirable molecule in a convenient way. Results To address this issue, we develop a web-based retrieval and navigation tool, named 3DMolNavi, for flexible molecular shape comparison. This tool is based on the histogram of Inner Distance Shape Signature (IDSS) for fast retrieving molecules that are similar to a query molecule, and uses dimensionality reduction to navigate the retrieved results in 2D and 3D spaces. We tested 3DMolNavi in the Database of Macromolecular Movements (MolMovDB) and CATH. Compared to other shape descriptors, it achieves good performance and retrieval results for different classes of flexible molecules. Conclusions The advantages of 3DMolNavi, over other existing softwares, are to integrate retrieval for flexible molecular shape comparison and enhance navigation for user’s interaction. 3DMolNavi can be accessed via https://engineering.purdue.edu/PRECISE/3dmolnavi/index.html.

Abstract Background Many molecules are flexible and undergo significant shape deformation as part of their function, and yet most existing molecular shape comparison (MSC) methods treat them as rigid bodies, which may lead to incorrect shape recognition. Results In this paper, we present a new shape descriptor, named Diffusion Distance Shape Descriptor (DDSD), for comparing 3D shapes of flexible molecules. The diffusion distance in our work is considered as an average length of paths connecting two landmark points on the molecular shape in a sense of inner distances. The diffusion distance is robust to flexible shape deformation, in particular to topological changes, and it reflects well the molecular structure and deformation without explicit decomposition. Our DDSD is stored as a histogram which is a probability distribution of diffusion distances between all sample point pairs on the molecular surface. Finally, the problem of flexible MSC is reduced to comparison of DDSD histograms. Conclusions We illustrate that DDSD is insensitive to shape deformation of flexible molecules and more effective at capturing molecular structures than traditional shape descriptors. The presented algorithm is robust and does not require any prior knowledge of the flexible regions.

Abstract Background During the past decade, the computed tomography has been successfully applied to various fields especially in medicine. The estimation of view angles for projections is necessary in some special applications of tomography, for example, the structuring of viruses using electron microscopy and the compensation of the patient's motion over long scanning period. Methods This work introduces a novel approach, based on the spherical multidimensional scaling (sMDS), which transforms the problem of the angle estimation to a sphere constrained embedding problem. The proposed approach views each projection as a high dimensional vector with dimensionality equal to the number of sampling points on the projection. By using SMDS, then each projection vector is embedded onto a 1D sphere which parameterizes the projection with respect to view angles in a globally consistent manner. The parameterized projections are used for the final reconstruction of the image through the inverse radon transform. The entire reconstruction process is non-iterative and computationally efficient. Results The effectiveness of the sMDS is verified with various experiments, including the evaluation of the reconstruction quality from different number of projections and resistance to different noise levels. The experimental results demonstrate the efficiency of the proposed method. Conclusion Our study provides an effective technique for the solution of 2D tomography with unknown acquisition view angles. The proposed method will be extended to three dimensional reconstructions in our future work. All materials, including source code and demos, are available on https://engineering.purdue.edu/PRECISE/SMDS.

Abstract Background Many molecules of interest are flexible and undergo significant shape deformation as part of their function, but most existing methods of molecular shape comparison (MSC) treat them as rigid bodies, which may lead to incorrect measure of the shape similarity of flexible molecules. Results To address the issue we introduce a new shape descriptor, called Inner Distance Shape Signature (IDSS), for describing the 3D shapes of flexible molecules. The inner distance is defined as the length of the shortest path between landmark points within the molecular shape, and it reflects well the molecular structure and deformation without explicit decomposition. Our IDSS is stored as a histogram which is a probability distribution of inner distances between all sample point pairs on the molecular surface. We show that IDSS is insensitive to shape deformation of flexible molecules and more effective at capturing molecular structures than traditional shape descriptors. Our approach reduces the 3D shape comparison problem of flexible molecules to the comparison of IDSS histograms. Conclusion The proposed algorithm is robust and does not require any prior knowledge of the flexible regions. We demonstrate the effectiveness of IDSS within a molecular search engine application for a benchmark containing abundant conformational changes of molecules. Such comparisons in several thousands per second can be carried out. The presented IDSS method can be considered as an alternative and complementary tool for the existing methods for rigid MSC. The binary executable program for Windows platform and database are available from https://engineering.purdue.edu/PRECISE/IDSS.

Abstract Background The conventional superposition methods use an ordinary least squares (LS) fit for structural comparison of two different conformations of the same protein. The main problem of the LS fit that it is sensitive to outliers, i.e. large displacements of the original structures superimposed. Results To overcome this problem, we present a new algorithm to overlap two protein conformations by their atomic coordinates using a robust statistics technique: least median of squares (LMS). In order to effectively approximate the LMS optimization, the forward search technique is utilized. Our algorithm can automatically detect and superimpose the rigid core regions of two conformations with small or large displacements. In contrast, most existing superposition techniques strongly depend on the initial LS estimating for the entire atom sets of proteins. They may fail on structural superposition of two conformations with large displacements. The presented LMS fit can be considered as an alternative and complementary tool for structural superposition. Conclusion The proposed algorithm is robust and does not require any prior knowledge of the flexible regions. Furthermore, we show that the LMS fit can be extended to multiple level superposition between two conformations with several rigid domains. Our fit tool has produced successful superpositions when applied to proteins for which two conformations are known. The binary executable program for Windows platform, tested examples, and database are available from https://engineering.purdue.edu/PRECISE/LMSfit.

Finite element analysis (FEA) has been widely adopted for deriving numerical solutions to complicated stress problems within a variety of materials. Compared to other computer-based solutions, FEA provides complete information [...]

Manufacturers rely heavily on computer-aided design (CAD) software to design parts and products. Although you can store CAD designs for future reference and use, it's not that easy to go [...]

Researchers are regularly interested in interpreting the multipartite structure of data entities according to their functional relationships. Data is often heterogeneous with intricately hidden inner structure. With limited prior knowledge, researchers are likely to confront the problem of transforming this data into knowledge. We develop a new framework, called heat-passing, which exploits intrinsic similarity relationships within noisy and incomplete raw data, and constructs a meaningful map of the data. The proposed framework is able to rank, cluster, and visualize the data all at once. The novelty of this framework is derived from an analogy between the process of data interpretation and that of heat transfer, in which all data points contribute simultaneously and globally to reveal intrinsic similarities between regions of data, meaningful coordinates for embedding the data, and exemplar data points that lie at optimal positions for heat transfer. We demonstrate the effectiveness of the heat-passing framework for robustly partitioning the complex networks, analyzing the globin family of proteins and determining conformational states of macromolecules in the presence of high levels of noise. The results indicate that the methodology is able to reveal functionally consistent relationships in a robust fashion with no reference to prior knowledge. The heat-passing framework is very general and has the potential for applications to a broad range of research fields, for example, biological networks, social networks and semantic analysis of documents. [ABSTRACT FROM AUTHOR]

Background: Many molecules of interest are flexible and undergo significant shape deformation as part of their function, but most existing methods of molecular shape comparison treat them as rigid shapes, which may lead to incorrect measure of the shape similarity of flexible molecules. Currently, there still is a limited effort in retrieval and navigation for flexible molecular shape comparison, which would improve data retrieval by helping users locate the desirable molecule in a convenient way. Results: To address this issue, we develop a web-based retrieval and navigation tool, named 3DMolNavi, for flexible molecular shape comparison. This tool is based on the histogram of Inner Distance Shape Signature (IDSS) for fast retrieving molecules that are similar to a query molecule, and uses dimensionality reduction to navigate the retrieved results in 2D and 3D spaces. We tested 3DMolNavi in the Database of Macromolecular Movements (MolMovDB) and CATH. Compared to other shape descriptors, it achieves good performance and retrieval results for different classes of flexible molecules. Conclusions: The advantages of 3DMolNavi, over other existing softwares, are to integrate retrieval for flexible molecular shape comparison and enhance navigation for user's interaction. 3DMolNavi can be accessed via https:// engineering.purdue.edu/PRECISE/3dmolnavi/index.html. [ABSTRACT FROM AUTHOR]

Protein-protein interaction (PPI) network analysis presents an essential role in understanding the functional relationship among proteins in a living biological system. Despite the success of current approaches for understanding the PPI network, the large fraction of missing and spurious PPIs and a low coverage of complete PPI network are the sources of major concern. In this paper, based on the diffusion process, we propose a new concept of global geometric affinity and an accompanying computational scheme to filter the uncertain PPIs, namely, reduce the spurious PPIs and recover the missing PPIs in the network. The main concept defines a diffusion process in which all proteins simultaneously participate to define a similarity metric (global geometric affinity (GGA)) to robustly reflect the internal connectivity among proteins. The robustness of the GGA is attributed to propagating the local connectivity to a global representation of similarity among proteins in a diffusion process. The propagation process is extremely fast as only simple matrix products are required in this computation process and thus our method is geared toward applications in high-throughput PPI networks. Furthermore, we proposed two new approaches that determine the optimal geometric scale of the PPI network and the optimal threshold for assigning the PPI from the GGA matrix. Our approach is tested with three protein-protein interaction networks and performs well with significant random noises of deletions and insertions in true PPIs. Our approach has the potential to benefit biological experiments, to better characterize network data sets, and to drive new discoveries. [ABSTRACT FROM AUTHOR]

Strain effects from stress liners on silicon-on-insulator MOSFETs with high-k dielectric and metal gate (HKMG) are reported. By thoroughly evaluating their impact on drive current, mobility, and threshold voltage, the intrinsic performance gain of stress liners is quantified at the 32-nm node with mobility enhancement identified as the major source. It is also experimentally demonstrated that advantageous stress liners can reduce gate leakage currents for MOSFETs with HKMG. [ABSTRACT FROM AUTHOR]

Background: During the past decade, the computed tomography has been successfully applied to various fields especially in medicine. The estimation of view angles for projections is necessary in some special applications of tomography, for example, the structuring of viruses using electron microscopy and the compensation of the patient's motion over long scanning period. Methods: This work introduces a novel approach, based on the spherical multidimensional scaling (sMDS), which transforms the problem of the angle estimation to a sphere constrained embedding problem. The proposed approach views each projection as a high dimensional vector with dimensionality equal to the number of sampling points on the projection. By using SMDS, then each projection vector is embedded onto a 1D sphere which parameterizes the projection with respect to view angles in a globally consistent manner. The parameterized projections are used for the final reconstruction of the image through the inverse radon transform. The entire reconstruction process is noniterative and computationally efficient. Results: The effectiveness of the sMDS is verified with various experiments, including the evaluation of the reconstruction quality from different number of projections and resistance to different noise levels. The experimental results demonstrate the efficiency of the proposed method. Conclusion: Our study provides an effective technique for the solution of 2D tomography with unknown acquisition view angles. The proposed method will be extended to three dimensional reconstructions in our future work. All materials, including source code and demos, are available on https://engineering.purdue.edu/PRECISE/SMDS. [ABSTRACT FROM AUTHOR]

Background: Many molecules are flexible and undergo significant shape deformation as part of their function, and yet most existing molecular shape comparison (MSC) methods treat them as rigid bodies, which may lead to incorrect shape recognition. Results: In this paper, we present a new shape descriptor, named Diffusion Distance Shape Descriptor (DDSD), for comparing 3D shapes of flexible molecules. The diffusion distance in our work is considered as an average length of paths connecting two landmark points on the molecular shape in a sense of inner distances. The diffusion distance is robust to flexible shape deformation, in particular to topological changes, and it reflects well the molecular structure and deformation without explicit decomposition. Our DDSD is stored as a histogram which is a probability distribution of diffusion distances between all sample point pairs on the molecular surface. Finally, the problem of flexible MSC is reduced to comparison of DDSD histograms. Conclusions: We illustrate that DDSD is insensitive to shape deformation of flexible molecules and more effective at capturing molecular structures than traditional shape descriptors. The presented algorithm is robust and does not require any prior knowledge of the flexible regions. [ABSTRACT FROM AUTHOR]

Background: The conventional superposition methods use an ordinary least squares (LS) fit for structural comparison of two different conformations of the same protein. The main problem of the LS fit that it is sensitive to outliers, i.e. large displacements of the original structures superimposed. Results: To overcome this problem, we present a new algorithm to overlap two protein conformations by their atomic coordinates using a robust statistics technique: least median of squares (LMS). In order to effectively approximate the LMS optimization, the forward search technique is utilized. Our algorithm can automatically detect and superimpose the rigid core regions of two conformations with small or large displacements. In contrast, most existing superposition techniques strongly depend on the initial LS estimating for the entire atom sets of proteins. They may fail on structural superposition of two conformations with large displacements. The presented LMS fit can be considered as an alternative and complementary tool for structural superposition. Conclusion: The proposed algorithm is robust and does not require any prior knowledge of the flexible regions. Furthermore, we show that the LMS fit can be extended to multiple level superposition between two conformations with several rigid domains. Our fit tool has produced successful superpositions when applied to proteins for which two conformations are known. The binary executable program for Windows platform, tested examples, and database are available from https://engineering.purdue.edu/PRECISE/LMSfit. [ABSTRACT FROM AUTHOR]

Background: Many molecules of interest are flexible and undergo significant shape deformation as part of their function, but most existing methods of molecular shape comparison (MSC) treat them as rigid bodies, which may lead to incorrect measure of the shape similarity of flexible molecules. Results: To address the issue we introduce a new shape descriptor, called Inner Distance Shape Signature (IDSS), for describing the 3D shapes of flexible molecules. The inner distance is defined as the length of the shortest path between landmark points within the molecular shape, and it reflects well the molecular structure and deformation without explicit decomposition. Our IDSS is stored as a histogram which is a probability distribution of inner distances between all sample point pairs on the molecular surface. We show that IDSS is insensitive to shape deformation of flexible molecules and more effective at capturing molecular structures than traditional shape descriptors. Our approach reduces the 3D shape comparison problem of flexible molecules to the comparison of IDSS histograms. Conclusion: The proposed algorithm is robust and does not require any prior knowledge of the flexible regions. We demonstrate the effectiveness of IDSS within a molecular search engine application for a benchmark containing abundant conformational changes of molecules. Such comparisons in several thousands per second can be carried out. The presented IDSS method can be considered as an alternative and complementary tool for the existing methods for rigid MSC. The binary executable program for Windows platform and database are available from https://engineering.purdue.edu/PRECISE/IDSS. [ABSTRACT FROM AUTHOR]

Background: Techniques for inferring the functions of the protein by comparing their shape similarity have been receiving a lot of attention. Proteins are functional units and their shape flexibility occupies an essential role in various biological processes. Several shape descriptors have demonstrated the capability of protein shape comparison by treating them as rigid bodies. But this may give rise to an incorrect comparison of flexible protein shapes. Results: We introduce an efficient approach for comparing flexible protein shapes by adapting a local diameter (LD) descriptor. The LD descriptor, developed recently to handle skeleton based shape deformations [1], is adapted in this work to capture the invariant properties of shape deformations caused by the motion of the protein backbone. Every sampled point on the protein surface is assigned a value measuring the diameter of the 3D shape in the neighborhood of that point. The LD descriptor is built in the form of a one dimensional histogram from the distribution of the diameter values. The histogram based shape representation reduces the shape comparison problem of the flexible protein to a simple distance calculation between 1D feature vectors. Experimental results indicate how the LD descriptor accurately treats the protein shape deformation. In addition, we use the LD descriptor for protein shape retrieval and compare it to the effectiveness of conventional shape descriptors. A sensitivity-specificity plot shows that the LD descriptor performs much better than the conventional shape descriptors in terms of consistency over a family of proteins and discernibility across families of different proteins. Conclusion: Our study provides an effective technique for comparing the shape of flexible proteins. The experimental results demonstrate the insensitivity of the LD descriptor to protein shape deformation. The proposed method will be potentially useful for molecule retrieval with similar shapes and rapid structure retrieval for proteins. The demos and supplemental materials are available on https://engineering.purdue.edu/PRECISE/LDD. [ABSTRACT FROM AUTHOR]

The authors reflect on the improvement on the speed of on-chip interconnects and communication fabrics through a heterogeneous interconnect layer of wires with differing characteristics. Various wire properties as well as the needs of data transfers should be considered for mapping activities to sets of wires. Due to the costs attached to a transmission line and optical modulators, architects must provide new ways to maximize resources and compete with regular resistance-capacitance-based wires.

Representation of the product/project information throughout the design life cycle is a critical aspect in engineering activities. The article begins with a discussion of the background research wherein the existing methodologies, which deal with product information representation, are reviewed. The article then proceeds to propose a new methodology for product management by presenting all the details of the system architecture. Product node (PN), which is introduced in this article, has a database-centric system at its core and an application built around it to support the various functions necessary to efficiently manage a distributed project environment. To aid the design life cycle, the system also enables distributed collaboration among people from different teams to support concurrent design activities. Effective management of product data using user-based control is also discussed. The detailed logic behind the system architecture and the practical implementation of the system are shown. [ABSTRACT FROM AUTHOR]

Factor VIII is a multidomain protein composed of Al, A2, B, A3, C1, and C2 domains. Deficiency or dysfunction of factor VIII causes hemophilia A, a bleeding disorder. Administration of exogenous recombinant factor VIII as a replacement leads to development of inhibitory antibodies against factor VIII in 15-30% of hemophilia A patients. Hence, less immunogenic preparations of factor VIII are highly desirable. Inhibitory antibodies against factor VIII are mainly directed against immunodominant epitopes in C2, A3, and A2 domains. Further, several universal epitopes for CD4+ T-cells have been identified within the C2 domain. The C2 domain is also known to interact specifically with phosphatidylserine-rich lipid vesicles. Here, we have investigated the hypothesis that complexation of O-phospho-L-serine, the head group of phosphatidylserine, with the C2 domain can reduce the overall immunogenicity of factor VIII. The biophysical (circular dichroism and fluorescence) and biochemical studies (ELISA and size exclusion chromatography) showed that O-phospho-L-serine binds to the phospholipid-binding region in the C2 domain, and this interaction causes subtle changes in the tertiary structure of the protein. O-Phospho-L-serine also prevented aggregation of the protein under thermal stress. The immunogenicity of the factor VIII-O-phospho-L-serine complex was evaluated in hemophilia A mice. The total and inhibitory antibody titers were lower for factor VIII-O-phospho-L-serine complex compared with factor VIII alone. Moreover, factor VIII administered as a complex with O-phospho-L-serine retained in vivo activity in hemophilia A mice. Our results suggest that factor VIII-O-phospho-L-serine complex may be beneficial to increase the physical stability and reduce immunogenicity of recombinant factor VIII preparations. [ABSTRACT FROM AUTHOR]

Cochleates are lipid-based delivery system that have found application in drug and gene delivery. They are precipitates, formed as a result of interaction between cations (e.g. Ca2+) and negatively charged phospholipids such as phosphatidylserine (PS). In the present study, we investigated the utility of fluorescent probe Laurdan (6-dodecanoyl-2-dimethylamino naphthalene) to monitor cochleate phase formation. Following addition of Ca2+ to Laurdan labeled lipid vesicles comprised of brain phosphatidylserine (BPS), a significant blue shift in the emission peak maximum of Laurdan was observed and the spectral features were distinct from those observed for the gel and liquid-crystalline (LC) phases. This is consistent with the formation of anhydrous cochleate cylinders that was further confirmed by electron microscopy studies. Due to dipolar relaxation, excitation and emission generalized polarization (GPEx and GPEm) indicate transition from a LC to a rigid and dehydrated (RD) cochleate phase. These spectral changes were utilized to monitor the influence of lipid composition, ionic strength and lamellarity on the formation of cochleate phase. The results indicated that the presence of phosphatidylcholine (PC) and bulk Na+ concentration influenced the formation of cochleate structures from small unilamellar vesicles (SUV) and multilamellar vesicles (MLV) composed of PS. The presence of PC and higher bulk Na+ concentration stabilized the PS vesicles against collapse and total loss of contents, intermediate molecular events in the formation of cochleate structures. From these studies, we conclude that Laurdan fluorescence is a sensitive and a rapid method to detect cochleate phase formation. [Copyright &y& Elsevier]

Factor VIII (FVIII), a plasma glycoprotein, is an essential cofactor in the blood coagulation cascade. It is a multidomain protein, known to bind to phosphatidylserine (PS)-containing membranes. Based on X-ray and electron crystallography data, binding of FVIII to PS-containing membranes has been proposed to occur only via the C2 domain. Based on these models, the molecular topology of membrane-bound FVIII can be envisioned as one in which only a small fraction of the protein interacts with the membrane, whereas the majority of the molecule is exposed to an aqueous milieu. We have investigated the topology of the membrane-bound FVIII using biophysical and biochemical techniques. Circular dichroism (CD) and fluorescence studies indicate no significant changes in the secondary and tertiary structure of FVIII associated with the membranes. Acrylamide quenching studies show that the protein is predominantly present on the surface of the membrane, exposed to the aqueous milieu. The light scattering and electron microscopy studies indicate the absence of vesicle aggregation and fusion. Binding studies with antibodies directed against specific epitopes in the A1, A2 and C2 domains suggest that FVIII binds to the membrane primarily via C2 domain including the specific phospholipid binding epitope (2303–2332) and may involve subtle conformational changes in this epitope region. [Copyright &y& Elsevier]

In this modern world, with the increase of complexity of many technologies, especially in the micro and nanoscale, the field of robotic manipulation has tremendously grown. Microrobots and other complex microscale systems are often to laborious to fabricate using standard microfabrication techniques, therefore there is a trend towards fabricating them in parts then assembling them together, mainly using micromanipulation tools. Here, a comprehensive and robust micromanipulation platform is presented, in which four micromanipulators can be used simultaneously to perform complex tasks, providing the user with an intuitive environment. The system utilizes a vision-based force sensor to aid with manipulation tasks and it provides a safe environment for biomanipulation. Lastly, virtual reality (VR) was incorporated into the system, allowing the user to control the probes from a more intuitive standpoint and providing an immersive platform for the future of micromanipulation. [ABSTRACT FROM AUTHOR]

Examines the use of an in-situ method for thermoplastic bonding by way of an injection molding technique for macro-composite manufacture. Methodology used to conduct the study; Results obtained from the study.