gebhart/patrepeval huggingface dataset:
Sparse Recovery of Streaming Signals Using <formula formulatype="inline"><tex Notation="TeX">$\ell_1$</tex></formula>-Homotopy (2014)

Most of the existing sparse-recovery methods assume a static system: the signal is a finite-length vector for which a fixed set of measurements and sparse representation are available and an l1 problem is solved for the reconstruction. However, the same representation and reconstruction framework is not readily applicable in a streaming system: the signal changes over time, and it is measured and reconstructed sequentially over small intervals. This is particularly desired when dividing signals into disjoint blocks and processing each block separately is infeasible or inefficient. In this paper, we discuss two streaming systems and a new homotopy algorithm for quickly solving the associated l1 problems: 1) recovery of smooth, time-varying signals for which, instead of using block transforms, we use lapped orthogonal transforms for sparse representation and 2) recovery of sparse, time-varying signals that follows a linear dynamic model. For both systems, we iteratively process measurements over a sliding interval and solve a weighted l1-norm minimization problem for estimating sparse coefficients. Since we estimate overlapping portions of the signal while adding and removing measurements, instead of solving a new l1 program as the system changes, we use available signal estimates as starting point in a homotopy formulation and update the solution in a few simple steps. We demonstrate with numerical experiments that our proposed streaming recovery framework provides better reconstruction compared to the methods that represent and reconstruct signals as independent, disjoint blocks, and that our proposed homotopy algorithm updates the solution faster than the current state-of-the-art solvers.
Noisin: Unbiased Regularization for Recurrent Neural Networks (2018)

Recurrent neural networks (RNNs) are powerful models of sequential data. They have been successfully used in domains such as text and speech. However, RNNs are susceptible to overfitting; regularization is important. In this paper we develop Noisin, a new method for regularizing RNNs. Noisin injects random noise into the hidden states of the RNN and then maximizes the corresponding marginal likelihood of the data. We show how Noisin applies to any RNN and we study many different types of noise. Noisin is unbiased--it preserves the underlying RNN on average. We characterize how Noisin regularizes its RNN both theoretically and empirically. On language modeling benchmarks, Noisin improves over dropout by as much as 12.2% on the Penn Treebank and 9.4% on the Wikitext-2 dataset. We also compared the state-of-the-art language model of Yang et al. 2017, both with and without Noisin. On the Penn Treebank, the method with Noisin more quickly reaches state-of-the-art performance.
Front Matter and Table of Contents (1978)

This entry contains the front cover, front matter and back cover.
Singularity-treated quadrature-evaluated method of moments solver for 3-D capacitance extraction (2000)

While research work on fast integral equation solver has resulted in several algorithms of similar linear equation solving performance, it has been well observed that the convergence of capacitance versus discretization is rather slow due to the most commonly used first-order collocation or Galerkin methods. This paper reports a new high-order scheme, Quadrature-evaluated Method of Moments Solver (QMMS), that uses high-order weighting and Gaussian quadrature to optimally handle the singularities at the edges and corners. For practical interconnect extraction problems, singularities at edges are analytically known and the corresponding Gaussian nodes allocation affords a near optimal discretization scheme. The new formulation avoids the special position-dependent quadrature rules, and surprisingly, provides a well-behaved matrix that converges rapidly without any pre-conditioning. Combining the high-order scheme with a kernel-independent fast solver yields an efficient algorithm for 3-D capacitance extraction.
<i>Candida albicans</i>and cancer: Can this yeast induce cancer development or progression? (2014)

There is currently increasing concern about the relation between microbial infections and cancer. More and more studies support the view that there is an association, above all, when the causal agents are bacteria or viruses. This review adds to this, summarizing evidence that the opportunistic fungus Candida albicans increases the risk of carcinogenesis and metastasis. Until recent years, Candida spp. had fundamentally been linked to cancerous processes as it is an opportunist pathogen that takes advantage of the immunosuppressed state of patients particularly due to chemotherapy. In contrast, the most recent findings demonstrate that C. albicans is capable of promoting cancer by several mechanisms, as described in the review: production of carcinogenic byproducts, triggering of inflammation, induction of Th17 response and molecular mimicry. We underline the need not only to control this type of infection during cancer treatment, especially given the major role of this yeast species in nosocomial infections, but also to find new therapeutic approaches to avoid the pro-tumor effect of this fungal species.
A scalable architecture for discrete wavelet transform (2002)

We present the design and prototyping of an efficient systolic architecture which performs both forward and inverse discrete wavelet transform. The proposed architecture consists of a linear array of processing elements, each of which has an adder and a multiplier and fixed number of I/O channels. The wavelet transform is computed by convolution and by mapping the computation on to a linear array of systolic processing elements. The design of the architecture has been shown to be simple, scalable and has the advantage of low I/O bandwidth. The number of processing elements is independent of the size of the input. The architecture has been prototyped using 2/spl mu/m p-well CMOS technology and has been developed in the CADENCE Edge Design Framework environment.
Protocol Reconfiguration Schemes for Policy-Based Equipment Management (2006)

The continuous proliferation in modern communication technologies towards a pervasive composite environment prescribes a profound shift in telecommunication management and poses new challenges, in terms of proposing key solutions for the management and support of legacy as well as emerging systems. Driven by these advances, a direct requirement lies in providing an advanced configuration system that will embrace the demands for optimal and adaptive configuration and reconfiguration of the underlying layers. This objective can be achieved by upgrading the capabilities of mobile equipment with the introduction of a configuration system that incorporates advanced features such as policy-based decision making mechanisms and protocol layer adaptation and reconfiguration procedures. This contribution exploits protocol reconfiguration schemes for policy-based equipment management as addressed in the E <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> R environment.
Direct spectrum sensing from compressed measurements (2010)

Because current Cognitive Radios are limited in their operational bandwidth by existing hardware devices, much of the extensive theoretical work on spectrum sensing is impossible to realize in practice over a wide frequency band. To solve this problem, many have used Compressive Sensing (CS) in sequence with CRs: first acquiring compressed samples, then reconstructing the Nyquist Rate signal, and lastly performing spectrum sensing on the reconstructed signal. While CS alleviates the bandwidth constraints imposed by front-end ADCs, the resulting increase in computation/complexity is non-trivial, especially in a power-constrained mobile CR. This motivates us to look at different ways to reduce computational complexity while achieving the same goals. In this paper, we will demonstrate how directly performing spectrum sensing from the compressed measurements can achieve the sampling reduction advantage of Compressive Sensing with significantly less computational complexity. Our key observation is that the CR does not have to reconstruct the entire signal because it is only interested in detecting the presence of Primary Users. Our algorithm takes advantage of this observation by estimating signal parameters directly from the compressed signal, thereby eliminating the reconstruction stage and reducing the computational complexity. In addition, our framework provides a measure of the quality of estimation allowing the system to optimize its data acquisition process to always acquire the minimum number of compressed measurements, even in a dynamic spectral environment.
PenSight: Enhanced Interaction with a Pen-Top Camera (2020)

We propose mounting a downward-facing camera above the top end of a digital tablet pen. This creates a unique and practical viewing angle for capturing the pen-holding hand and the immediate surroundings which can include the other hand. The fabrication of a prototype device is described and the enabled interaction design space is explored, including dominant and non-dominant hand pose recognition, tablet grip detection, hand gestures, capturing physical content in the environment, and detecting users and pens. A deep learning computer vision pipeline is developed for classification, regression, and keypoint detection to enable these interactions. Example applications demonstrate usage scenarios and a qualitative user evaluation confirms the potential of the approach.
Snorkeling of lysine side chains in transmembrane helices: how easy can it get? (2003)

Transmembrane segments of proteins are often flanked by lysine residues. The side chains of these residues may snorkel, i.e. they may bury themselves with their aliphatic part in the hydrophobic region of the lipid bilayer, while positioning the charged amino group in the more polar interface. Here we estimate the free energy cost of snorkeling from thermodynamical calculations based on studies with synthetic transmembrane peptides [Strandberg et al. (2002) Biochemistry 41, 7190-7198]. The value is estimated to be between 0.07 and 0.7 kcal mol(-1) for a lysine side chain. This very low value indicates that snorkeling may be a common process, which should be taken into consideration both in experimental and in theoretical studies on protein-lipid interactions.
A Parallel Implementation of the Message-Passing Decoder of LDPC Codes Using a Reconfigurable Optical Model (2005)

In this paper we propose a constant-time algorithm for parallel implementation of the message-passing decoder of low density parity check (LDPC) codes on the linear array with a reconfigurable pipelined bus system (LARPBS), achieving the minimum number of processors required for a fully parallel implementation. Dynamic reconfiguration provides flexibility to code changes and efficient message routing. To decode a different code, we may simply set up the required connections between the bit-nodes and check-nodes by modifying the initialization phase of the LARPBS algorithm. No extra wiring or hardware changes are required, as compared to other existing approaches. Moreover, the same hardware can implement the decoder in both probability and logarithm domains. The LARPBS also allows reducing the number of the bus cycles required for processor communications to a small constant, regardless of the code length. We illustrate that the LARPBS is an efficient and fast model for implementing the decoder.
(Invited) High Power Normally-Off GaN MOSFET (2011)

The enhancement mode n-channel GaN-based MOSFETs on Si substrates have been demonstrated. We achieved a low interface state density between SiO2 and GaN, a high breakdown field, and a high reliability of SiO2 by annealing after SiO2 deposition on GaN. The SiO2 was applied for the gate oxide of GaN MOSFET. The fabricated GaN MOSFETs using an ion implantation technique showed good normally-off operation with threshold voltage of 2.7 V, the maximum output current of over 3.5 A, and a high-temperature operation up to 300oC. Furthermore, AlGaN/GaN hybrid MOS-HFETs were fabricated. The MOS-HFET has the merits of both a MOS channel and an AlGaN/GaN heterostructure with high mobility two dimensional electron gases. The maximum drain current of over 100 A was performed. The specific on-state resistance was 9.3 mΩ-cm2. The fabricated device also exhibited good normally-off operation and the breakdown voltage of over 600 V.
Antioxidant System for the Preservation of Vitamin A in Ultra Rice (2009)

The best antioxidant system, composed of generally accepted food additives, improved vitamin A stability while reducing the price, thus greatly improving the commercial viability of Ultra Rice grains for use as a ricefortificant.
Binary and ternary crystal structure analyses of a novel inhibitor with 17β-HSD type 1: a lead compound for breast cancer therapy (2009)

Oestradiol is a well-characterized sex hormone that stimulates breast cancer and other oestrogen-related diseases. 17beta-hydroxysteroid dehydrogenase type 1 (17beta-HSD1) catalyses the last step in the synthesis of oestradiol and androstenediol in breast tumour tissue. The enzyme's high expression and activity after simultaneous blockade of oestrogen receptors and inhibition of aromatase in the tumour shows the necessity for its inhibition as a requirement for breast cancer therapy. In the present paper, we report structures of the binary and ternary complexes of 17beta-HSD1 with a new inhibitor E2B {3-[3',17'beta-dihydroxyestra-1',3',5'(10')-trien-16'beta-methyl]benzamide}, and the enzyme inhibition by the later. The IC50 value for E2B was determined to be 42 nM in T47D cells. Multiple interactions between E2B and the enzyme include hydrogen bonds and hydrophobic interactions, as well as pi-pi interactions. A kinetic study demonstrated that E2B inhibits the enzyme's reduction forming oestradiol from oestrone, with a Ki of 0.9+/-0.15 nM. Such strong inhibition is in agreement with its extensive interaction with the enzyme, suggesting its potential as a lead compound for breast cancer therapy. In fact, this possibility is enhanced by its capacity for cell penetration similar to natural steroids. Such inhibitors that block oestrogen synthesis to suppress the sulfatase pathway producing oestradiol can be used in adjuvant therapies with oestrogen receptor blockade, opening a new orientation of breast cancer treatment.
Intraoperative Imaging Platform (2011)

A thorough review of past and current projects involving intraoperative imaging is conducted.A general purpose intraoperative imaging tool was designed and its application was tested on tissue-mimic phantom and in-vitro tissue.The results show improved efficiency in the detection of disease margins by using the intraoperative imaging tool.Two methods for fabricating contrast agents with dual-mode image enhancement were discussed and evaluated.With ink-encapsulated microbubbles, we were able to get enhanced image for both ultrasound and photo acoustic modalities.With ICGencapsulated microbubbles, both fluorescence and ultrasound images can be taken simultaneously.Finally, an integrated dual-mode intraoperative imaging system for wound is discussed.Wound perfusion and oxygenation can be simultaneously assessed by this dual-mode imaging system.
FeatureMatch: A General ANNF Estimation Technique and its Applications (2014)

In this paper, we propose FeatureMatch, a generalised approximate nearest-neighbour field (ANNF) computation framework, between a source and target image. The proposed algorithm can estimate ANNF maps between any image pairs, not necessarily related. This generalisation is achieved through appropriate spatial-range transforms. To compute ANNF maps, global colour adaptation is applied as a range transform on the source image. Image patches from the pair of images are approximated using low-dimensional features, which are used along with KD-tree to estimate the ANNF map. This ANNF map is further improved based on image coherency and spatial transforms. The proposed generalisation, enables us to handle a wider range of vision applications, which have not been tackled using the ANNF framework. We illustrate two such applications namely: 1) optic disk detection and 2) super resolution. The first application deals with medical imaging, where we locate optic disks in retinal images using a healthy optic disk image as common target image. The second application deals with super resolution of synthetic images using a common source image as dictionary. We make use of ANNF mappings in both these applications and show experimentally that our proposed approaches are faster and accurate, compared with the state-ofthe-art techniques.
The Atom-Cavity Microscope: Single Atoms Bound in Orbit by Single Photons (2000)

The motion of individual cesium atoms trapped inside an optical resonator is revealed with the atom-cavity microscope (ACM). A single atom moving within the resonator generates large variations in the transmission of a weak probe laser, which are recorded in real time. An inversion algorithm then allows individual atom trajectories to be reconstructed from the record of cavity transmission and reveals single atoms bound in orbit by the mechanical forces associated with single photons. In these initial experiments, the ACM yields 2-micrometer spatial resolution in a 10-microsecond time interval. Over the duration of the observation, the sensitivity is near the standard quantum limit for sensing the motion of a cesium atom.
Placement de tâches dynamique et flexible sur processeur multicoeur asymétrique en fonctionnalités (2015)

To meet the increasingly heterogeneous needs of applications (in terms of power and efficiency), this thesis focus on the emerging functionally asymmetric multi-core processor (FAMP) architectures. These architectures are characterized by non-uniform implementation of hardware extensions in the cores (ex. Floating Point Unit (FPU)). The area savings are apparent, but what about the impact in software, energy and performance?To answer these questions, the thesis investigates the nature of the use of extensions in state-of-the-art's applications and compares various existing methods. To optimize the tasks mapping and increase efficiency, the thesis proposes a dynamic solution at scheduler level, called relaxed scheduler.Hardware extensions are valuable because they speed up part of code where the parallelization on multi-core isn't efficient. However, the hardware extensions are under-exploited by applications and their cost in terms of area and power consumption are important.Based on these observations, the following contributions have been proposed:We present a detailed study on the use of vector and FPU extensions in state-of-the-art's applicationsWe compare multiple extension management solutions at different levels of temporal granularity of action, to understand the limitations of these solutions and thus define at which level we must act. Few studies address the issue of the granularity of action to manage extensions.We offer a solution for estimating online performance degradation to run a task on a core without a given extension. To allow the scalability of multi-core, the operating system must have flexibility in the placement of tasks. Placing a task on a core with no extension can have important consequences for energy and performance. But to date, there is no way to estimate this potential degradation.We offer a relaxed scheduler, based on our degradation estimation model, which maps the tasks on a set of heterogeneous cores effectively. We study the flexibility gained and the implications for performance and energy levels. Existing solutions propose methods to map tasks on a heterogeneous set of cores, but they do not study the tradeoff between quality of service and consumption gain for FAMP architectures.Our experiments with simulators have shown that the scheduler can achieve a significantly higher mapping flexibility with a performance degradation of less than 2 %. Compared to a symmetrical multi-core, our solution enables an average energy gain at core level of 11 %. These results are very encouraging and contribute to the development of a comprehensive FAMP platform . This thesis has been the subject of a patent application, three international scientific communications (plus one submission), and contributes to two active european projects.
“H-Bar Lift-Out” and “Plan-View Lift-Out”: Robust, Re-thinnable FIB-TEM Preparation for Ex-Situ Cross-Sectional and Plan-View FIB Specimen Preparation (2002)

Journal Article "H-Bar Lift-Out" and "Plan-View Lift-Out": Robust, Re-thinnable FIB-TEM Preparation for Ex-Situ Cross-Sectional and Plan-View FIB Specimen Preparation Get access R J Patterson, R J Patterson Fibics Incorporated, 556 Booth St. Ottawa, Ontario, Canada K1A 0G1 (info@fibics.com) Search for other works by this author on: Oxford Academic Google Scholar D Mayer, D Mayer Fibics Incorporated, 556 Booth St. Ottawa, Ontario, Canada K1A 0G1 (info@fibics.com) Search for other works by this author on: Oxford Academic Google Scholar L Weaver, L Weaver Fibics Incorporated, 556 Booth St. Ottawa, Ontario, Canada K1A 0G1 (info@fibics.com) Search for other works by this author on: Oxford Academic Google Scholar MW Phaneuf MW Phaneuf Fibics Incorporated, 556 Booth St. Ottawa, Ontario, Canada K1A 0G1 (info@fibics.com) Search for other works by this author on: Oxford Academic Google Scholar Microscopy and Microanalysis, Volume 8, Issue S02, 1 August 2002, Pages 566–567, https://doi.org/10.1017/S1431927602105502 Published: 01 August 2002
Research on modeling and optimization of overtaking rules under intelligent system (2015)

Right-lane driving rule is common in most countries in the world. Nonetheless people supported this rule while fail to be aware that it may not have perfect performance in certain aspects. This paper modeled driving rules and discussed performances. We construct an overtaking model and a non-changing lane driving model to illustrate the right-lane driving rule. Computer simulations are employed respectively in light and heavy traffic to show the traffic procedure under these rules. An evaluation model is constructed to measure the traffic flow and safety based on the vehicle number, time of brakes, overtaking and car accident from the simulation data. The evaluation results demonstrated that traffic flow and safety are existence of contradictions. High traffic flow inevitably leads to low safety and vice versa. In order to address the problem, an alternative called free-lane driving rule in intelligence system is built. Under the intelligent system, all the distance and speed are automatic control. Additionally we set up fast traffic lane and slow traffic lane. Computer simulation indicates that performance under intelligence system has a significant progress.
The Affordable Care Act and the Need for Public Health Leadership (2014)

The fourth of five commentaries on “Bloomberg's Health Legacy: Urban Innovator or Meddling Nanny?” from the September-October 2013.
Optimization of Solvent Extraction and Direct Transmethylation Methods for the Analysis of Egg Yolk Lipids (2006)

The composition of egg yolk lipids differs greatly from most other food lipids, as it combines high contents of triglycerides and phospholipids, as well as a high proportion of cholesterol. The lipids are organized in lipoproteins and are dispersed in aqueous phase. Classical extraction methods using chloroform and methanol have not been optimized for such a matrix, therefore quantitative extraction yields of egg lipids can be inaccurate. In this study, the original method of Bligh and Dyer is evaluated and adapted for egg lipids. Furthermore, a direct extraction/derivatization method is presented. Solvent extraction resulted in a lipid yield of 31.8 ± 0.89% and total fatty acid yield was 257 ± 2 mg/g yolk whereas the direct method yielded 250 ± 7 mg/g yolk. Gas chromatographic analyses confirmed that lipid recovery was complete for triglycerides and phospholipids as well.