gebhart/patrepeval huggingface dataset:
Augmented TV: An augmented reality system for TV programs beyond the TV screen (2014)

TV Service using a mobile device as a second screen has been increasing. We propose a new TV system which is able to augment representation of TV programs beyond the TV screen. In the system, which we named augmented TV, since animated 3DCG content interlocked with TV programs is overlaid on live video from the mobile device camera in the mobile device screen by augmented reality techniques, the representation of having a TV character coming out of the screen can be provided. To achieve the representation giving such surprise or reality to the viewer, synchronization accuracy of the overlay display is required. A conventional synchronization method for multi-device or a visible light communication method does not meet the requirement of the accuracy. Therefore, we developed an accurate synchronization method and authoring environment of augmented TV content. We implemented augmented TV, and confirmed frame-accurate synchronization (synchronization error time is about 0.03 seconds or less). And we confirmed that the authoring environment is easy to produce augmented TV content using a video clip using a 3DCG character with TV program quality.
Loss of Roquin induces early death and immune deregulation but not autoimmunity (2011)

The substitution of one amino acid in the Roquin protein by the sanroque mutation induces a dramatic autoimmune syndrome in mice. This is believed to occur through ectopic expression of inducible T cell co-stimulator (ICOS) and unrestrained differentiation of follicular T helper cells, which induce spontaneous germinal center reactions to self-antigens. In this study, we demonstrate that tissue-specific ablation of Roquin in T or B cells, in the entire hematopoietic system, or in epithelial cells of transplanted thymi did not cause autoimmunity. Loss of Roquin induced elevated expression of ICOS through T cell-intrinsic and -extrinsic mechanisms, which itself was not sufficient to break self-tolerance. Instead, ablation of Roquin in the hematopoietic system caused defined changes in immune homeostasis, including the expansion of macrophages, eosinophils, and T cell subsets, most dramatically CD8 effector-like T cells, through cell-autonomous and nonautonomous mechanisms. Germline Roquin deficiency led to perinatal lethality, which was partially rescued on the genetic background of an outbred strain. However, not even complete absence of Roquin resulted in overt self-reactivity, suggesting that the sanroque mutation induces autoimmunity through an as yet unknown mechanism.
Image Geo-Localization Based on MultipleNearest Neighbor Feature Matching UsingGeneralized Graphs (2014)

In this paper, we present a new framework for geo-locating an image utilizing a novel multiple nearest neighbor feature matching method using Generalized Minimum Clique Graphs (GMCP). First, we extract local features (e.g., SIFT) from the query image and retrieve a number of nearest neighbors for each query feature from the reference data set. Next, we apply our GMCP-based feature matching to select a single nearest neighbor for each query feature such that all matches are globally consistent. Our approach to feature matching is based on the proposition that the first nearest neighbors are not necessarily the best choices for finding correspondences in image matching. Therefore, the proposed method considers multiple reference nearest neighbors as potential matches and selects the correct ones by enforcing consistency among their global features (e.g., GIST) using GMCP. In this context, we argue that using a robust distance function for finding the similarity between the global features is essential for the cases where the query matches multiple reference images with dissimilar global features. Towards this end, we propose a robust distance function based on the Gaussian Radial Basis Function (G-RBF). We evaluated the proposed framework on a new data set of 102k street view images; the experiments show it outperforms the state of the art by 10 percent.
On the effect of parity-check weights in iterative decoding (2004)

It is well-established "folk knowledge" that in order to be iteratively decodable, a code should have a sparse parity-check matrix, as it has some qualitative and quantitative properties for finite-length codes.
Phase Analysis on Dual-Phase Steel Using Band Slope of Electron Backscatter Diffraction Pattern (2013)

A quantitative and automated phase analysis of dual-phase (DP) steel using electron backscatter diffraction (EBSD) was attempted. A ferrite-martensite DP microstructure was produced by intercritical annealing and quenching. An EBSD map of the microstructure was obtained and post-processed for phase discrimination. Band slope (BS), which was a measure of pattern quality, exhibited much stronger phase contrast than another conventional one, band contrast. Owing to high sensitivity to lattice defect and little orientation dependence, BS provided handiness in finding a threshold for phase discrimination. Its grain average gave a superior result on the discrimination and volume fraction measurement of the constituent phases in the DP steel.
Nanoscale simultaneous chemical and mechanical imaging via peak force infrared microscopy (2017)

Nondestructive chemical and mechanical measurements of materials with ~10-nm spatial resolution together with topography provide rich information on the compositions and organizations of heterogeneous materials and nanoscale objects. However, multimodal nanoscale correlations are difficult to achieve because of the limitation on spatial resolution of optical microscopy and constraints from instrumental complexities. We report a novel noninvasive spectroscopic scanning probe microscopy method-peak force infrared (PFIR) microscopy-that allows chemical imaging, collection of broadband infrared spectra, and mechanical mapping at a spatial resolution of 10 nm. In our technique, chemical absorption information is directly encoded in the withdraw curve of the peak force tapping cycle after illumination with synchronized infrared laser pulses in a simple apparatus. Nanoscale phase separation in block copolymers and inhomogeneity in CH<sub>3</sub>NH<sub>3</sub>PbBr<sub>3</sub> perovskite crystals are studied with correlative infrared/mechanical nanoimaging. Furthermore, we show that the PFIR method is sensitive to the presence of surface phonon polaritons in boron nitride nanotubes. PFIR microscopy will provide a powerful analytical tool for explorations at the nanoscale across wide disciplines.
Path Planning for Active SLAM Based on the D* Algorithm With Negative Edge Weights (2017)

In this paper, the problem of path planning for active simultaneous localization and mapping (SLAM) is addressed. In order to improve its localization accuracy while autonomously exploring an unknown environment the robot needs to revisit positions seen before. To that end, we propose a path planning algorithm for active SLAM that continuously improves robot's localization while moving smoothly, without stopping, toward a goal position. The algorithm is based on the D* shortest path graph search algorithm with negative edge weights for finding the shortest path taking into account localization uncertainty. The proposed path planning algorithm is suitable for exploration of highly dynamic environments with moving obstacles and dynamic changes in localization demands. While the algorithm operation is illustrated in simulation experiments, its effectiveness is verified experimentally in real-world scenarios.
A review of antimicrobial resistance in Canada (2000)

Antimicrobial resistance is a global concern. Over the past 10 years, considerable efforts and resources have been expended to detect, monitor, and understand at the basic level the many different facets of emerging and increasing resistance. This review summarizes our current understanding of bacterial antimicrobial resistance issues in Canada with particular emphasis given to the Enterobacteriaceae, Pseudomonas aeruginosa, Staphylococcus aureus, Enterococcus, Neisseria meningitidis, Haemophilus influenzae, Streptococcus pneumoniae, Moraxella catarrhalis, and Streptococcus pyogenes. In addition, future concerns and programs for ongoing surveillance are discussed.
Semi-Supervised Adapted HMMs for Unusual Event Detection (2005)

We address the problem of temporal unusual event detection. Unusual events are characterized by a number of features (rarity, unexpectedness, and relevance) that limit the application of traditional supervised model-based approaches. We propose a semi-supervised adapted hidden Markov model (HMM) framework, in which usual event models are first learned from a large amount of (commonly available) training data, while unusual event models are learned by Bayesian adaptation in an unsupervised manner. The proposed framework has an iterative structure, which adapts a new unusual event model at each iteration. We show that such a framework can address problems due to the scarcity of training data and the difficulty in pre-defining unusual events. Experiments on audio, visual, and audiovisual data streams illustrate its effectiveness, compared with both supervised and unsupervised baseline methods.
Becoming a mercury free facility: a priority to be achieved by the year 2000. (1997)

This Professional Development Series document outlines the public health and environmental impacts of mercury. It further explains the health care industry's extraordinary contribution of mercury pollution and outlines simple, cost effective strategies to better manage, minimize and ultimately eliminate the use of mercury and mercury based products in health care settings. Brief case studies of facilities that have been successful in this effort are described. A technical assistance resource guide is also included. Readers can expect to acquire the skills needed to make this important work a manageable task.
Structural Framing of Protocol for Secure Multiparty Cloud Computation (2011)

Secure Multi party Computation (SMC) is a paradigm that keeps data of individual parties as secret and provides the private data for computation to evaluate some function of their common interest. The outcome of the computation is made available to all the parties. Cloud Computing is a paradigm shift from the distributed computing where an organization uses resources "as service". With the"pay-as-you-go" model, an organization can improve efficiency while minimizing the expenditure and the operation overhead. However, users of the cloud are worrying about the privacy of their data that has been supplied to the cloud provider. The solutions to these problems can be provided by the protocols of the Secured Multi party Cloud Computing (SMCC). In this tutorial, we propose SMC solution techniques that can be embedded while designing architecture of cloud computing especially when multiple cloud users jointly compute some function of their private data inputs. With our experience of developing protocols and devising algorithms for SMC problem we anticipate a crucial role of SMC in cloud computing. In this tutorial, we explore such scenario while discussing various protocols of SMC and their applicability in cloud computing, with the design of SMCC Architecture.
Closed Access Colonoscopy (2005)

Purpose: Presently, patients referred for colonoscopy at our institution are required to have an initial encounter (closed access). Due to the clinic backlog for appointments, this initial visit may take up to three months. There is an additional wait time from the clinic visit to the colonoscopy. The concern was that the initial physician clinic visit might reveal a finding that would significantly impact the procedure preparation or performance. The aim of this study was to determine if the wait time, from consultation request to colonoscopy, could be reduced by eliminating the initial clinic visit. It was postulated that instead of a formal clinic visit, a medical provider could review the request for appropriateness, speak with the patient over the phone, and then schedule the colonoscopy. Methods: The records of all patients having colonoscopy for the calendar year, 2004, were reviewed. Inpatient colonoscopies, repeat colonoscopies, and inflammatory bowel patients were excluded. This left 786 patients who had consultations prior to their colonoscopy. The goal was to determine if any recommendations, other than a colonoscopy, were made during the initial consultation, and if such changes required physician input. The primary endpoint was the number of GI clinic patients whose treatment plan was simply “colonoscopy”. Secondary endpoints were the average wait time for a GI consultation and for a colonoscopy. Results: 529 of the 786 (67%) consultations did not result in any interventions during the clinic visit other than recommending colonoscopy. 197 (25%) patients had some type of intervention, other studies, labs, or adjustment of medications. The remaining 60 (8%) patients had their GERD addressed, in addition to ordering a colonoscopy during the consultation. The average wait from the request of the consultation to the clinic visit was 107 days. The time from clinic to colonoscopy was 109 days. Therefore, the total wait time from initial request to the actual colonoscopy was approximately 7 months. Conclusions: Our closed access system appears to be inefficient since more than 2/3 of the patients did not benefit from the mandatory consultation prior to scheduling the colonoscopy. The average wait time of 7 months for a colonoscopy is worrisome, especially for patients who subsequently had significant pathology diagnosed by their colonoscopies. Patients could be better served by having the consultation request reviewed by a medical provider and referred directly to colonoscopy when appropriate. This would immediately reduce wait time by half.
Improving MapReduce energy efficiency for computation intensive workloads (2011)

MapReduce is a programming model for data intensive computing on large-scale distributed systems. With its wide acceptance and deployment, improving the energy efficiency of MapReduce will lead to significant energy savings for data centers and computational grids. In this paper, we study the performance and energy efficiency of the Hadoop implementation of MapReduce under the context of energy-proportional computing. We consider how MapReduce efficiency varies with two runtime configurations: resource allocation that changes the number of available concurrent workers, and DVFS (Dynamic Voltage and Frequency Scaling) that adjusts the processor frequency based on the workloads' computational needs. Our experimental results indicate significant energy savings can be achieved from judicious resource allocation and intelligent DVFS scheduling for computation intensive applications, though the level of improvements depends on both workload characteristic of the MapReduce application and the policy of resource and DVFS scheduling.
Classification for DGA-Based Malicious Domain Names with Deep Learning Architectures (2017)

The preemptive defenses against various malware created by domain generation algorithms (DGAs) have traditionally been solved using manually-crafted domain features obtained by heuristic process. However, it is difficult to achieve real-world deployment with most research on detecting DGA-based malicious domain names due to poor performance and time consuming. Based on the recent overwhelming success of deep learning networks in a broad range of applications, this article transfers five advanced learned ImageNet models from Alex Net, VGG, Squeeze Net, Inception, Res Net to classify DGA domains and non-DGA domains, which: (i) is suited to automate feature extraction from raw inputs; (ii) has fast inference speed and good accuracy performance; and (iii) is capable of handling large-scale data. The results show that the proposed approach is effective and efficient.
Transfer of micro-optical structures into GaAs by use of inductively coupled plasma dry etching (2002)

The transfer of continuous-relief micro-optical structures from resist into GaAs by the use of direct-write electron-beam (e-beam) lithography followed by dry etching in an inductively coupled plasma is demonstrated. BCl3-Ar chemistry was found to give satisfactory results; N2 and Cl2 were added to change the selectivity between GaAs and e-beam resist. The transfer process generates smooth etched structures. Distortion of the diffractive structures in the transfer process was examined. Blazed gratings with a period of 10 microns were optically evaluated with a 940-nm VCSEL. This grating was a five-step approximation of a blazed profile. The diffraction efficiency was 67% in the first order, with a theoretical value of 87%. Also, simulations of the optical performance of the transferred diffractive elements were made by use of a Fourier transform of the grating profile. Our goal is to integrate micro-optical structures with VCSELs.
Solvothermal synthesis of carboxyl and amido functionalized mesoporous resins for water treatments (2009)

Carboxyl functionalized mesoporous resins have been successfully synthesized through solvothermal polymerization of divinylbenzene and methacrylic acid in the presence of tetrahydrofuran and water. A series of conjunct characterizations show that these materials have disordered mesopores with uniform pore sizes (3.8–12.5 nm) and high BET surface areas (383–547 m2 g−1). Furthermore, carboxyl groups on the samples could be covalently grafted by amido groups through chemical reactions, which imparts a promising property to these mesoporous resins in a broad range of applications. In the adsorption of various pollutants that usually exist in wastewater, the mesoporous resins exhibit superior performances, and thus have great potential in water treatments.
Human Milk K-Casein and Inhibition of Helicobacter pylori Adhesion to Human Gastric Mucosa (1995)

Readily digested caseins, which account for almost half of the protein content in human milk, are important as nutritional protein for breast-fed infants. It has also been advocated that part of the antimicrobial activity of human milk resides in the caseins, most likely the glycosyated K-casein. Top explore this possibility, we purified K-casein from human milk to homogeneity by a two-step size-exclusion chromatography procedure. Purified human K-casein, in contrast to K-casein purified from bovine milk, effectively inhibited the cell lineage-specific adhesion of fluoroisothiocyanate-labeled Helicobacter pylori to human gastric surface mucous cells. The inhibitory activity was abolished by metaperiodate oxidation and considerably reduced by preincubation with alpha-L-fucosidase but not with alpha-N-acetylneuraminidase or endo-beta-galactosidase. These results strongly support the view that fucose containing carbohydrate moieties of human K-casein are important for inhibition of H. pylori adhesion and, thus, infection. They also suggest that breastfeeding may protect from infection by H. pylori during early life and that species-specific glycosylation patterns, as illustrated by human bovine K-casein, partly determine both the narrow host spectrum of this human gastric pathogen and the capacity to resist infection.
A type system for regular expressions (2012)

Regular expressions are used to match and extract text. It is easy for developers to make syntactic mistakes when writing regular expressions, because regular expressions are often complex and different across programming languages. Such errors result in exceptions at run time, and there is currently no static support for preventing them.
Recent Advances in Amorphous Silicon Solar Cells (1982)

Abstract Current state of the art in the field of amorphous silicon solar cells and their technologies are reviewed. Progress of the amorphous silicon solar cell is briefly surveyed with their historical background. Unique advantages of amorphous silicon as a low cost solar cell material are pointed out in technological viewpoints. Some new approaches and key technologies to improve photovoltaic performances such as cell efficiency, sensitive area enlargement and stability of the cell performance are reviewed. Remaining problems to be solved are also discussed.
The glass-ceramic processing flowsheet for ICPP high-level waste: Status report (1991)

High-level liquid wastes (HLLW) are generated at the Idaho Chemical Processing Plant (ICPP) from the reprocessing of irradiated government nuclear fuels. The basic types of fuel reprocessed at the ICPP include those which are clad in aluminum, stainless steel, and zirconium. The HLLW is then solidified bed calciner at a temperature of 500{degrees}C in the New Waste Calcining Facility (NWCF). The calcined waste is stored near-surface in concrete encased stainless steel bins. A glass-ceramic waste form is being developed for immobilizing calcined high-level wastes (HLLW) prior to final disposal. Development work at the ICPP has included the formulation of experimental glass-ceramic waste forms to immobilize the calcined HLW, and the conceptualization of a process to produce the waste forms. Research has shown that a glass-ceramic waste form, with leaching properties comparable to a glass, could result in about 60% less immobilized waste volume as compared to a vitrified waste form. A conceptual process to produce a glass-ceramic waste form meeting the current preliminary regulatory durability requirements has been identified.
Secure Modular Smart Contract Platform for Multi-Tenant 5G Applications (2020)

Trusted decentralized applications based on distributed ledger technologies provide many potential opportunities to 5G applications and verticals, as well as in fifth generation mobile network (5G) enabling technologies, systems, and services. Apart from the tamper-proof exchange of transactions, distributed ledgers can provide a software environment for the trusted execution of smart contracts. In this article, we explore the security aspects of decentralized applications and, in particular, the security of smart contracts. Distributed ledger characteristics impose distinct requirements on smart contract design, implementation, deployment, and management. We briefly present the approach to the development of secure smart contracts, and highlight key smart contract vulnerabilities and the developer tools supporting smart contract security. We developed a secure, upgradeable modular multi-contract platform. It combines per-contract Smart Contract Tunnels and per-user-based access control to minimize vulnerabilities. The smart contract platform is comprised of service-agnostic, auxiliary, and service-specific smart contracts. It can be therefore easily adapted to different 5G application verticals. For illustration and evaluation, we elaborated on the proposed solution on a case of smart electric charging. During the design and development, state-of-the-art code analysis was applied. Finally, we propose an architecture for the integration of the secure multi-contract platform into a 5G architecture. The integration proposal utilizes hybrid private-public blockchain networks for possible security, scalability, performance, and transaction cost optimization.