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We describe the iterative design and evaluation of a geometric interaction technique for bare-hand mid-air virtual pottery. We model the shaping of a pot as a gradual and progressive convergence of the pot-profile to the shape of the user׳s hand represented as a point-cloud (PCL). Our pottery-inspired application served as a platform for systematically revealing how users use their hands to express the intent of deformation during a pot shaping process. Our approach involved three stages: (a) clutching by proximal-attraction, (b) shaping by proximal-attraction, and (c) shaping by grasp+motion. The design and implementation of each stage was informed by user evaluations of the previous stage. Our work evidently demonstrates that it is possible to enable users to express their intent for shape deformation without the need for a fixed set of gestures for clutching and deforming a shape. We found that the expressive capability of hand articulation can be effectively harnessed for controllable shaping by organizing the deformation process in broad classes of intended operations such as pulling, pushing, and fairing. After minimal practice with the pottery application, users could figure out their own strategy for reaching, grasping, and deforming the pot. Users particularly enjoyed using day-to-day physical objects as tools for shaping pots. [ABSTRACT FROM AUTHOR]

Abstract: When existing parts are re-used for the development of a new product or business-to-business transactions, a method for searching parts from a database that best meet user’s requirements is essential. The core of a part search method is to measure the similarity between parts’ specifications and the user’s input data in an efficient manner. In this paper, the authors suggest a new method for part similarity measurement using ontology and multi-criteria decision making (MCDM) technique and discuss its technical details. This method ensures interoperability with existing engineering information management systems, represents part specifications in a formal manner, and has generality in search procedure. A case study with ejector pins has also been conducted for the demonstration of the proposed method. [Copyright &y& Elsevier]

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]

In this paper, we present a search method with multi-class probability estimates for sketch-based 3D engineering part retrieval. The purpose of using probabilistic output from classification is to support high-quality part retrieval by motivating user relevance feedback from a ranked list of top categorical choices. Given a free-hand user sketch, we use an ensemble of classifiers to estimate the likelihood of the sketch belonging to each predefined category by exploring the strengths of various individual classifiers. Complementary shape descriptors are used to generate classifiers with probabilistic output using support vector machines (SVM). A weighted linear combination rule, called adapted minimum classification error (AMCE), is developed to concurrently minimize the classification errors and the log likelihood errors. Experiments are conducted using our Engineering Shape Benchmark database to evaluate the proposed combination rule. User studies show that users can easily identify the desired classes and then the parts under the proposed method and algorithms. Compared with the best individual classifier, the classification accuracy using AMCE increased by 7% for 3D models, and the average best rank improved by 11.6% for sketches. [Copyright &y& Elsevier]

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 paper, we study the deep Ritz method for solving the linear elasticity equation from a numerical analysis perspective. A modified Ritz formulation using the H 1 / 2 (Γ D) norm is introduced and analyzed for linear elasticity equation in order to deal with the (essential) Dirichlet boundary condition. We show that the resulting deep Ritz method provides the best approximation among the set of deep neural network (DNN) functions with respect to the "energy" norm. Furthermore, we demonstrate that the total error of the deep Ritz simulation is bounded by the sum of the network approximation error and the numerical integration error, disregarding the algebraic error. To effectively control the numerical integration error, we propose an adaptive quadrature-based numerical integration technique with a residual-based local error indicator. This approach enables efficient approximation of the modified energy functional. Through numerical experiments involving smooth and singular problems, as well as problems with stress concentration, we validate the effectiveness and efficiency of the proposed deep Ritz method with adaptive quadrature. [ABSTRACT FROM AUTHOR]

A flattenable mesh surface is a polygonal mesh surface that can be unfolded into a planar patch without stretching any polygon. This paper presents a new method for computing a slightly stretched flattenable mesh surface M from a piecewise-linear surface patch P∈ R , where the shape approximation error between M and P is minimized and the strain of stretching on M is controlled. Prior approaches result in either a flattenable surface that could be quite different from the input shape or a (discrete) developable surface has relative simple shape. The techniques investigated in this paper overcome these difficulties. First, we introduce a new surface modeling method to conduct a sequence of nearly isometric deformations to morph a flattenable mesh surface to a new shape which has a better approximation of the input surface. Second, in order to get better initial surfaces for fitting and overcome topological obstacles, a shape perturbation scheme is investigated to obtain the optimal surface fitting result. Last, to improve the scalability of our optimal surface fitting algorithm, a coarse-to-fine fitting framework is exploited so that very dense flattenable mesh surfaces can be modeled and boundaries of the input surfaces can be interpolated. [ABSTRACT FROM AUTHOR]

A new visibility graph-based algorithm is presented for computing the inner distances of a 3D shape represented by a volumetric model. The inner distance is defined as the length of the shortest path between landmark points within the shape. The inner distance is robust to articulation and can reflect the deformation of a shape structure well without an explicit decomposition. Our method is based on the visibility graph approach. To check the visibility between pairwise points, we propose a novel, fast, and robust visibility checking algorithm based on a clustering technique which operates directly on the volumetric model without any surface reconstruction procedure, where an octree is used for accelerating the computation. The inner distance can be used as a replacement for other distance measures to build a more accurate description for complex shapes, especially for those with articulated parts. The binary executable program for the Windows platform is available from https://engineering.purdue.edu/PRECISE/VMID. [ABSTRACT FROM PUBLISHER]

This paper explores improving sketching skills and reducing the inhibition to sketch for student designers. In the first study, students were taught sketching skills through an in-class workshop. The effect was evaluated using a pre-mid-post test ( n = 40). In the second study, students were led through art activities to reduce their inhibition to sketch. The effect was tested using another pre-mid-post test ( n = 26). The first study found sketching skills increased, but declined with disuse. The second study found reduced inhibition immediately after the workshop, an increase after the sketch skills workshop, and a decrease over the semester. This suggests that sketch training and inhibition-reducing exercises are effective in the short term, but must be emphasized over time for a permanent change. [ABSTRACT FROM AUTHOR]

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]

Abstract: Customers often present certain preferences relative to the same product, such as function, shape, color, and cost. The ideas in the mind of the customer can be represented by higher level concepts. However, the actual shape, color, and cost embodied in the product can only be viewed as lower-level features. In this paper, a model of preference elicitation from customers is proposed to bridge the gap between low-level features and high-level concepts. First, the attributes of customer preferences are classified using preference taxonomies that we develop. These taxonomies are represented using unstructured documents that are directly collected from customer descriptions. Second, the documents or catalogs of design requirements, containing some textual descriptions and survey reports, are then normalized by using an ontology-based semantic representation. Some semantic rules are developed to describe the low-level features of customer preferences to build an ontological knowledge base. Third, customer preferences are mapped to domain ontologies for driving high-level concept generation. A customer preference modeling framework is developed to construct a vector space model to measure the similarity between two preference concept ontologies. Finally, an empirical study is implemented, and five different customer groups are surveyed about the cell phone preferences. The query results are analyzed to deeply understand the validity of concept generation from the customer preferences. [Copyright &y& Elsevier]

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]

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]

Abstract: The paper proposes a methodology to assist the designer at the initial stages of the design synthesis process by enabling him/her to employ knowledge and algorithms existing in graph network theory. The proposed method comprises three main stages: transforming the synthesis problem into a graph theoretic problem; devising the topology possessing special engineering properties corresponding to the system requirements; finding the geometric configuration of that topology that will possess the desired properties. To clarify the idea and to demonstrate its generality, the approach is presented through three synthesis case studies from different engineering domains: electrical networks, statics and kinematics. As is highlighted in the paper, the approach of employing graph theory in the synthesis process offers several unique advantages. Among these advantages are: gaining a general perspective on different synthesis problems from different engineering domains by transforming them into the same graph problem; employing the same graph algorithms for different synthesis problems; establishing the existence of configurations with special properties solely from the topology of the system; transferring knowledge and methods between different engineering disciplines for both the topology and the geometry generation steps. [Copyright &y& Elsevier]

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.

Design protocol analysis is a technique to understand designers’ cognitive processes by analyzing sequences of observations on their behavior. These observations typically use audio, video, and transcript data in order to gain insights into the designer's behavior and the design process. The recent availability of sophisticated sensing technology has made such data highly multimodal, requiring more flexible protocol analysis tools. To address this need, we present VizScribe, a visual analytics framework that employs multiple coordinated multiple views that enable the viewing of such data from different perspectives. VizScribe allows designers to create, customize, and extend interactive visualizations for design protocol data such as video, transcripts, sketches, sensor data, and user logs. User studies where design researchers used VizScribe for protocol analysis indicated that the linked views and interactive navigation offered by VizScribe afforded the researchers multiple, useful ways to approach and interpret such multimodal data. [ABSTRACT FROM AUTHOR]

Interaction in mid-air can be fatiguing. A model-based method to quantify cumulative subjective fatigue for such interaction was recently introduced in HCI research. This model separates muscle units into three states: active (M A) fatigued (M F) or rested (M R) and defines transition rules between states. This method demonstrated promising accuracy in predicting subjective fatigue accumulated in mid-air pointing tasks. In this paper, we introduce an improved model that additionally captures the variations of the maximum arm strength based on arm postures and adds linearly-varying model parameters based on current muscle strength. To validate the applicability and capabilities of the new model, we tested its performance in various mid-air interaction conditions, including mid-air pointing/docking tasks, with shorter and longer rest and task periods, and a long-term evaluation with individual participants. We present results from multiple cross-validations and comparisons against the previous model and identify that our new model predicts fatigue more accurately. Our modeling approach showed a 42.5% reduction in fatigue estimation error when the longitudinal experiment data is used for an individual participant's fatigue. Finally, we discuss the applicability and capabilities of our new approach. • Posture-based maximum strength representation is compatible with the TCM fatigue modeling method. • Subjective fatigue and muscle fatigue can be connected without contact-based measurement. • A reliable cumulative fatigue model is introduced based on brain effort (BE). • Designers can run our model in Kinect-based systems with a user's joint torque and Borg ratings. • A 42.5% reduction in fatigue estimation error for individualized modeling. [ABSTRACT FROM AUTHOR]

We present Sketcholution, a method for automatically creating visual histories of hand-drawn sketches. Such visual histories are useful for a designer to reflect on a sketch, communicate ideas to others, and fork from or revert to an earlier point in the creative process. Our approach uses a bottom-up agglomerative clustering mechanism that groups adjacent frames based on their perceptual similarity while maintaining the causality of how a sketch was constructed. The resulting aggregation dendrogram can be cut at any level depending on available display space, and can be used to create a visual history consisting of either a comic strip of highlights or a single annotated summary frame. We conducted a user study comparing the speed and accuracy of participants recovering causality in a sketch history using comic strips, summary frames, and simple animations. Although animations with interaction may seem better than static graphics, our results show that both comic strip and summary frame significantly outperform animation. [ABSTRACT FROM AUTHOR]

Laser direct deposition provides an attractive and cost effective means for repairing or remanufacturing high value engineering components. This study demonstrates the successful repair of defective voids in turbine airfoils based on a new semi-automated geometric reconstruction algorithm and a laser direct deposition process. A Boolean difference between the original defective model and the final reconstructed model yields a parameterized geometric representation of the repair volume. The experimental results of this method demonstrate the effectiveness of laser direct deposition in remanufacturing and its potential to adapt to a wide range of part defects. A Life Cycle Assessment (LCA) on the energy and environmental impacts by remanufacturing is also presented. [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]

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]

• Material context matters to perceptions of collaboration quality. • Spatial context matters to creative fluency in collaborative design. • Synchronous interaction has important roles in collaboration quality. • Reciprocal interaction has important roles in creative fluency. Engineering design typically occurs as a collaborative process situated in specific context such as computer-supported environments, however there is limited research examining the dynamics of design collaboration in specific contexts. In this study, drawing from situative learning theory, we developed two analytic lenses to broaden theoretical insights into collaborative design practices in computer-supported environments: (a) the role of spatial and material context, and (b) the role of social interactions. We randomly assigned participants to four conditions varying the material context (paper vs. tablet sketching tools) and spatial environment (private room vs commons area) as they worked collaboratively to generate ideas for a toy design task. We used wearable sociometric badges to automatically and unobtrusively collect social interaction data. Using partial least squares regression, we generated two predictive models for collaboration quality and creative fluency. We found that context matters materially to perceptions of collaboration, where those using collaboration-support tools perceived higher quality collaboration. But context matters spatially to creativity, and those situated in private spaces are more fluent in generating ideas than those in commons areas. We also found that interaction dynamics differ: synchronous interaction is important to quality collaboration, but reciprocal interaction is important to creative fluency. These findings provide important insights into the processual factors in collaborative design in computer-supported environments, and the predictive role of context and conversation dynamics. We discuss the theoretical contributions to computer-supported collaborative design, the methodological contributions of wearable sensor tools, and the practical contributions to structuring computer-supported environments for engineering design practice. [ABSTRACT FROM AUTHOR]