Miracle-dz/UniFAR-FTUs huggingface dataset:
Real-time principal direction line drawings of arbitrary 3D surfaces

Introduction and Related Work Computer-generated line drawings [4,7] are becoming an increasingly popular method of non-photorealistic rendering (NPR). While many factors contribute to an effective line drawing-quality of line, line placement and density-line direction is among the most critical for conveying surface shape. The principal directions hold particular promise in this respect [2]. In a human perceptual study, subjects displayed consistent biases toward perceiving surface contours (lines drawn on the surface) as being aligned with the principal directions [5]. Despite the potential for principal directions and their suggestion by previous authors [1,2,7], there are currently no available techniques for using them to render viewpoint-independent line drawings of arbitrary 3D surfaces. The line drawing algorithm of Markosian et al. [4] handled arbitrary 3D surfaces, but line direction was chosen in a viewpoint-dependent manner and lines tended to cluster on silhouette edges with little interior curvature information.
Performance Characterization of Hadoop Workloads on SR-IOV-Enabled Virtualized InfiniBand Clusters

Big Data Systems are becoming increasingly complex and generally have very high operational costs. Cloud computing offers attractive solutions for managing large scale systems. However, one of the major bottlenecks in VM performance is virtualized I/O. Since Big Data applications and middleware rely heavily on high performance interconnects such as InfiniBand, the performance of virtualized InfiniBand interfaces is vital. Single Root I/O Virtualization (SR-IOV) is a hardware based approach which offers significant performance benefits as compared to software based I/O virtualization. With the increasing adoption of InfiniBand network for cloud computing, it is important to evaluate the performance benefits of SR-IOV for InfiniBand networks, especially to see the performance characteristics of Big Data applications and middleware under different scenarios. We characterize the main performance factors for different workloads through this study (such as map task scheduling, I/O, data replication, etc.). Our experimental evaluations show that the performance difference for a wide set of Big Data benchmarks and applications over SR-IOV with InfiniBand using RDMA-enabled Hadoop as compared to native InfiniBand network is just 5 - 15%. In addition, with RDMA-enabled Hadoop, we see 20.9 - 81.6% performance improvement for RDMA as compared to IPoIB.
Ultrasonic Nanobubbles Carrying Anti-PSMA Nanobody: Construction and Application in Prostate Cancer-Targeted Imaging

To facilitate prostate cancer imaging using targeted molecules, we constructed ultrasonic nanobubbles coupled with specific anti-PSMA (prostate specific membrane antigen) nanobodies, and evaluated their in vitro binding capacity and in vivo imaging efficacy. The “targeted” nanobubbles, which were constructed via a biotin-streptavidin system, had an average diameter of 487.60 ± 33.55 nm and carried the anti-PSMA nanobody as demonstrated by immunofluorescence. Microscopy revealed targeted binding of nanobubbles in vitro to PSMA-positive cells. Additionally, ultrasonography indicators of nanobubble imaging (including arrival time, peak time, peak intensity and enhanced duration) were evaluated for the ultrasound imaging in three kinds of animal xenografts (LNCaP, C4-2 and MKN45), and showed that these four indicators of targeted nanobubbles exhibited significant differences from blank nanobubbles. Therefore, this study not only presents a novel approach to target prostate cancer ultrasonography, but also provides the basis and methods for constructing small-sized and high-efficient targeted ultrasound nanobubbles.
Capacitated minimum forest problem in wireless sensor networks

Due to wireless and decentralized nature, multi-hop wireless networks are attractive for variety of applications. These properties also pose significant challenges to their developers and so require new types of algorithms. In cases where traditional wired networks usually rely on some kind of centralized entity, in multihop wireless networks nodes have to cooperate in a distributed and self organizing manner. Additional side constraints, such as energy consumption, have to be taken into account as well. Therefore, the design of efficient network control mechanisms for optimizing the capabilities of complex networks is becoming an increasingly critical aspect in networking. This paper addresses constrained optimization problems. To utilize the critical WSN resources precisely, the development of approximation algorithms with quality guaranteed solutions in WSNs is desperately needed. In this paper it is shown that optimal approximation algorithms achieve highest optimization goal which minimize Cost of network resource consumption. This architecture helps to crystallize the Capacitated Minimum Forest (CMF) problem. The design progresses from for the decision version with NP completeness through devising approximation algorithms and providing upper bounds for their approximation ratios by evaluating the performance of the proposed algorithms through experimental simulation.Approximation ratio of the proposed algorithms is nearly equal to one.
Technology and Effect Matrix for Patent Clustering

Patents contain important technical, legal and economic information. Their annual publication accounts for a quarter of the books and journals in the world. Along with the growing number of patents, patent clustering analysis is becoming more and more important. We focus on two key issues in patent clustering, namely patent representation and data visualization. Firstly, patents are represented as technology and effect pairs, and then patents are clustered based on technology and effect matrix, finally a multi-layer patent map is generated. The experiments results show that our method has higher efficiency and better clustering effect than traditional vector space model and the visualization of clustering result is more practical and scalable.
Software Project Management Using Decision Networks

The Bayesian networks support resource allocation in software project and also help in analyzing trade-offs among resources. The model predicts the probability distribution of every variable given incomplete data. Even though the Bayesian networks conveniently facilitate scenario-based analysis, they do not support finding an optimal solution in multi-criteria decision making. This paper proposes extending the Bayesian networks into the decision networks to optimize an organizational target and to handle the multi-criteria environment of software project management. Specifically, the decision networks are used to find an optimal set of software activities under constraints of software cost and quality. The preliminary results demonstrate that the Bayesian networks can be easily extended into the decision networks, which then allow for optimization. The proposed methodology provides a flexible process for utilizing the encoded knowledge within the Bayesian networks to facilitate decision making, which could be applicable in other domains of problems
15(S)-HETE production in human retinal microvascular endothelial cells by hypoxia: Novel role for MEK1 in 15(S)-HETE induced angiogenesis.

PURPOSE To examine for the expression of 15-lipoxygenase 1 (15-LOX1) and 15-LOX2 in human retinal microvascular endothelial cells (HRMVECs) and study the role of arachidonic acid metabolites of these enzymes in angiogenesis. METHODS Quantitative RT-PCR and reverse-phase HPLC analyses were used to determine 15-LOX1/2 expression and their arachidonic acid metabolites in HRMVECs. The role of MEK1 in 15(S)-HETE-induced angiogenesis was studied using HRMVEC migration, tube formation, and basement membrane matrix plug angiogenesis. RESULTS HRMVECs expressed both 15-LOX1 and 15-LOX2. Hypoxia induced the expression of 15-LOX1 and the production of its arachidonic acid metabolites 15(S)-hydroxyeicosatetraenoic acid (15(S)-HETE) and 12(S)-hydroxyeicosatetraenoic acid (12(S)-HETE). 15(S)-HETE stimulated HRMVEC migration and tube formation as potently as 20 ng/mL fibroblast growth factor-2 (FGF-2). In addition, 15(S)-HETE stimulated the phosphorylation of ERK1/2, JNK1, p38 MAPK, and MEK1 in a time-dependent manner in these cells. Inhibition of MEK1 by pharmacologic and dominant-negative mutant approaches attenuated 15(S)-HETE-induced phosphorylation of ERK1/2 and JNK1 but not p38 MAPK. Blockade of ERK1/2 and JNK1 activation suppressed 15(S)-HETE-induced HRMVEC migration and tube formation and basement membrane matrix plug angiogenesis. Inhibition of p38 MAPK attenuated 15(S)-HETE-induced HRMVEC migration only. Inhibition of MEK1 also blocked 15(S)-HETE-induced HRMVEC migration and tube formation and basement membrane matrix plug angiogenesis. CONCLUSIONS These results suggest that hypoxia, through the induction of 15-LOX1 expression, leads to the production of 15(S)-HETE in HRMVECs. In addition, 15(S)-HETE, through MEK1-dependent activation of ERK1/2 and JNK1, stimulates the angiogenic differentiation of HRMVECs and basement membrane matrix plug angiogenesis.
Are mergers responsible for the surge in new bank charters

After stagnating for many years, the rate of new bank formation increased sharply in the second half of the 1990s. The financial press attributes this development to the high volume of bank mergers, which are said to have encouraged new entry by reducing service to some bank customers. It is commonly asserted, for example, that many new banks serve small businesses whose banks were taken over by larger banks uninterested in making small business loans. Most banking experts agree that such an increase in new banks in response to mergers would be healthy, helping maintain competition in local banking markets and offset reductions in service. > The view that mergers encourage new bank formation has recently come into question. Examining data on new bank charters and mergers in the 1990s, a study released early last year concluded that mergers have actually discouraged new bank formation. Shortly thereafter, another study came to the opposite conclusion, finding that mergers encourage new entry. Taken together, these studies raise two important questions. First, is merger activity positively or negatively related to new bank formation? Second, if mergers are positively related to new bank formation, which types of mergers account for the link? > Keeton reexamines the relationship between mergers and new bank charters, distinguishing more carefully than the other two studies between different types of mergers. The results, based on data for the second half of the 1990s, provide strong support for the view that mergers encourage the formation of new banks. Specifically, the author finds that markets with more merger activity experienced higher rates of new bank formation, and that the mergers with the strongest link to new bank formation were those in which small banks were taken over by large banks or local banks by distant banks.
CONTROL OF LAMINAR AND TURBULENT SHEAR FLOWS USING PLASMA ACTUATORS

The use of AC discharge plasma actuators in flow control applications is experimentally investigated using PIV. Experimental observations include actuators in quiescent flow, a flat plate boundary layer, and a low pressure turbine blade cascade. The actuators are shown to generate a high velocity region near the wall downstream of the interface with large fluctuating components. Even in cases where the velocity increase is small due to a fast free-stream flow, the actuator still produces velocity fluctuations of significant size. The displacement and momentum thicknesses decrease in the downstream region of the actuator, however. In the turbine cascade, separation is completely eliminated and cross-stream vortical structures are observed.
Validity range of some approximations involved in vegetation modelling through numerical approaches

Electromagnetic models of interaction with natural land media are extensively used to analyze and foresee the Synthetic Aperture Radar ob servables, and may be used to study the robustness of retrieval algorithms. However, usuall y, these models rely on approximations of various origins which may jeopardize the relevancy of some simulations, all the more so as retrieval algorithms rely more and more on complex sets of observables including polarimetry and interferometry, which makes the requirements toward these models still more demanding than for the mere radiometric outputs. In particular, the ne ed for deriving phase properties has led to the development of coherent codes (e.g. [8][9][10]), wh ich deliver greater range of outputs but may incorporate more approximations. Concerning these approximations, comparisons with experimental data are of course necessary but may be not sufficient. Indeed, since the land cover scenes are generally very complex, when a disagreement occur between simulated and experimental data it may be very difficult to attribute the discrepancy to a particular cause. Th en the use of numerical techniques for studying a particular point inside a complex continental land scene may be relevant. The goal of the present paper is to illustrate that Finite Differences in T ime Domain (FDTD) is well matched to treat such problems in their specificity and that it permits a nswering to lot of questions relative to these approximations. Section 1 deals with the numerical approach and section 2 illustrate its application to vegetation scattering.
Moving Object Detection in Video Streams Received from a Moving Camera

Detection of moving objects in a video stream received from a moving camera is difficult computer vision task, because the motion of the camera blends with the motion of the objects in the scene. In order to tackle this problem, we propose a method based on optical flow calculation and Delaunay triangulation. Given a sequence of frames, firstly, we extract the corner feature points using ORB algorithm and compute optical flow vectors at the extracted feature points. Secondly, we separate the optical flow vectors using K-Means clustering method. Third, we classify each cluster into camera and object motion using its mean scatter value. Finally, we represent the moving object using Delaunay triangulation.
Prostate cancer between prognosis and adequate/proper therapy

Knowing the indolent, non-invasive nature of most types of prostate cancer, as well as the simple fact that the disease seems more likely to be associated with age rather than with other factors (50% of men at the age of 50 and 80% at the age of 80 have it [1], with or without presenting any symptom), the big challenge of this clinical entity was to determine severity indicators (so far insufficient) to guide the physician towards an adequate attitude in the clinical setting. The risk of over-diagnosing and over-treating many prostate cancer cases (indicated by all the major European and American studies) is real and poses many question marks. The present paper was meant to deliver new research data and to reset the clinical approach in prostate cancer cases.
Multi-temporal RADARSA T-1 and ERS Backscattering Signatur es of Coastal Wetlands in Southeaster n Louisiana

Using multi-temporal European Remote-sensing Satellites (ERS-1/-2) and Canadian Radar Satellite (RADARSAT-1) synthetic aperture radar (SAR) data over the Louisiana coastal zone, we characterize seasonal variations of radar backscattering according to vegetation type. Our main findings are as follows. First, ERS-1/-2 and RADARSAT-1 require careful radiometric calibration to perform multi-temporal backscattering analysis for wetland mapping. We use SAR backscattering signals from cities for the relative calibration. Second, using seasonally averaged backscattering coefficients from ERS-1/-2 and RADARSAT-1, we can differentiate most forests (bottomland and swamp forests) and marshes (freshwater, intermediate, brackish, and saline marshes) in coastal wetlands. The student t-test results support the usefulness of season-averaged backscatter data for classification. Third, combining SAR backscattering coefficients and an opticalsensor-based normalized difference vegetation index can provide further insight into vegetation type and enhance the separation between forests and marshes. Our study demonstrates that SAR can provide necessary information to characterize coastal wetlands and monitor their changes.
Reduced-order observer and adaptive fuzzy-based dynamic surface control for induction motors with iron losses

In this paper, observer and adaptive fuzzy-based dynamic surface control is proposed for induction motors including iron losses systems with uncharted parameters and immeasurable state variable. Firstly, because of the uncharted and nonlinear functions, the fuzzy logic systems has been introduced. Secondly, an adaptive fuzzy reduced-order observer is proposed to approximate the immeasurable state variables. By means of first-order niters, the dynamic surface solves the trouble of “explosion of complexity”. The algorithm in this paper ensures that all the signals are bounded.
Modeling surface deformation observed with synthetic aperture radar interferometry at Campi Flegrei caldera

Satellite radar interferometry of Campi Flegrei caldera, Italy, reveals a pattern of subsidence during the period 1993–1998. Interferograms spanning the first half of the observation period (1993–1995) have a lower amplitude and average rate of subsidence than those spanning either the second half (1995–1998) or the entire period (1993–1998), consistent with observations of a slowing down or reversal of subsidence during the first half of the observation period. We calculate a time series of deformation images relative to a reference image on the basis of a least squares inversion. During the observation period the maximum subsidence progresses at a rate of roughly 38 ± 2 mm/yr, with periods of no apparent subsidence in late 1996 to early 1997. To understand the characteristics of the source, we jointly invert pairs of ascending and descending differential interferograms spanning similar time intervals (first half, second half, or entire interval) of the period 1993–1998. In each case the joint inversion fits the two unwrapped interferograms with a similar subhorizontal rectangular contracting tensile dislocation striking roughly N98°E with dimensions ? 4 × 2 km and located beneath the city of Pozzuoli at a depth of 2.5–3 km. Inversion for a spheroidal or Mogi point source also produced reasonable fits but with progressively poorer overall fits to the data, respectively. Our inversion assuming a simple source in an elastic half? space does not include the possible effects of local structure on the surface deformation, a factor that may also reduce the need for an asymmetric source. The solution we find is consistent with other studies that suggest subsidence due to hydrothermal diffusion as the primary deformation mechanism during this phase of caldera deflation.
Elliptical trajectories for non-holonomic vehicles

A manipulation device can be installed on a mobile robot. In this case, the robot should be able to approach the objects to be manipulated from a given direction, suitable for this purpose. If the kinematic structure of the robot is not holonomic, this problem can be very hard to solve. In this paper, it is described a navigation algorithm capable of driving a car-like robot (i.e. characterized by slow steering motion with a minimum radius of curvature) to a given point with a given orientation, whatever its initial position and orientation.
Parallelization Techniques for Sparse Matrix Applications 1

information to fetch data and to perform the computation. Such runtime preprocessing techniques have been fairly well-studied and successfully incorporated into compilers [14, 6]. The inspector/executor method incurs a runtime overhead for each inspector stage which are greatly increased when references use multiple levels of indirection. To reduce these overheads in sparse-matrix problems, the sparse-array rolling (SAR) technique was proposed in [15]. This method uses special representations for distributed sparse matrices which allows efficient access to the nonzero elements. Initial evaluations of the SAR method were promising and led to its integration into the Vienna Fortran compiler using language extensions. For a detailed description of the compilation issues, we refer the reader to [15]. In this paper, we focus on the SAR runtime support and describe how it allows efficient access to the distributed sparse matrix. The performance of SAR depends on a wide range of different parameters such as the data distribution, the locality characteristics of the algorithm, and the sparsity of the input matrix. We have evaluated its performance under many combinations of these choices, and we describe the impact that each choice has on preprocessing costs, executor efficiency, and memory overhead. The paper is structured as follows. Section 2 provides a general overview of sparse matrix parallelization. Section 3 provides an overview of the SAR technique and its runtime support. Section 4 introduces a sparse-matrix program and illustrates how it is parallelized using the SAR approach. We discuss the impact of distribution choices in Section 5. Section 6 provides a detailed performance evaluation. The last two sections discuss related work and the conclusions drawn from this work.
Perspectives on the role of business in social innovation

Purpose We conducted an integrative review of the representative literature on social innovation. The analysis focused on the key arguments made about the involvement of business actors in processes of social innovation and interweaved in this study to build a logically coherent definition of what social innovation in business means for the bulk of those who write and speak about it today. The scope of the literature review was expanded by integrating insights from the extant ‘business in society’ and social innovation literatures, thereby adding clarity to our conceptualisation. Design/methodology/approach This article examines the conceptual construct of social innovation in business as distinct from social innovation implemented by civil society and the state. The general absence of sustained research and analysis of this phenomenon, and the dominance of grey and policy-oriented literature, mean that a broadly accepted definition of how social innovation theorises the changing role of business in socie.
Biochemical and biophysical characterization of four EphB kinase domains reveals contrasting thermodynamic, kinetic and inhibition profiles

The Eph (erythropoietin-producing hepatocellular carcinoma) B receptors are important in a variety of cellular processes through their roles in cell-to-cell contact and signalling; their up-regulation and down-regulation has been shown to have implications in a variety of cancers. A greater understanding of the similarities and differences within this small, highly conserved family of tyrosine kinases will be essential to the identification of effective therapeutic opportunities for disease intervention. In this study, we have developed a route to production of multi-milligram quantities of highly purified, homogeneous, recombinant protein for the kinase domain of these human receptors in Escherichia coli. Analyses of these isolated catalytic fragments have revealed stark contrasts in their amenability to recombinant expression and their physical properties: e.g., a >16°C variance in thermal stability, a 3-fold difference in catalytic activity and disparities in their inhibitor binding profiles. We find EphB3 to be an outlier in terms of both its intrinsic stability, and more importantly its ligand-binding properties. Our findings have led us to speculate about both their biological significance and potential routes for generating EphB isozyme-selective small-molecule inhibitors. Our comprehensive methodologies provide a template for similar in-depth studies of other kinase superfamily members.