gebhart/patrepeval huggingface dataset:
Static knee alignment is associated with the risk of unicompartmental knee cartilage defects (2007)

Although knee malalignment is a risk factor for the progression of unicompartmental knee osteoarthritis (OA), it is unclear how this relationship is mediated. Cartilage defects are known to predate cartilage loss and the onset of knee OA, and it may be that knee malalignment increases the risk of unicompartmental knee cartilage defects. Knee radiographs and MRI were performed on a total of 202 subjects, 36.6% of whom had radiographic knee OA, to determine the relationship between static knee alignment and knee cartilage defects. Analyses were performed for the entire cohort, as well as for healthy and OA subgroups. For every 1 degrees increase in a valgus direction, there was an associated reduced risk of the presence of cartilage defects in the medial compartment of subjects with knee OA (p = 0.02), healthy subjects (p = 0.002), and the combined (p < 0.001) group. Moreover, for every 1 degrees increase in a valgus direction, there was an associated increased risk of the presence of lateral cartilage defects in the OA group (p = 0.006), although the relationship between change toward genu valgum and lateral compartment cartilage defects did not persist for the healthy group (p = 0.16). This cross-sectional study has demonstrated that knee alignment is associated with the risk for compartment specific knee cartilage defects in both healthy and arthritic people. Given that the natural history of cartilage volume reduction appears to be predated by the presence of cartilage defects, whether knee alignment affects the longitudinal progression from cartilage defects to cartilage loss requires further examination.
SOURCES OF ERROR IN OXIMETRY (1949)

Elam, James O. M.D.; Neville, John F. Jr. M.D.; Sleator, William Ph.D.; Elam, William N. Jr. B.A. Author Information
Recognition of low-pass-filtered consonants in noise with normal and impaired high-frequency hearing (2002)

People with high-frequency hearing loss often complain of difficulty understanding speech, particularly in noisy environments. The reduction in audible high-frequency speech information provides one explanation. In addition, high-frequency hearing loss may reduce the contribution from the "tails" of high-frequency auditory nerve fibers, resulting in diminished availability of lower frequency speech cues. This study was designed to determine if high-frequency hearing loss results in speech-understanding deficits beyond those accounted for by reduced high-frequency speech information. Recognition of speech, both low-pass filtered and unfiltered, was measured for subjects with normal hearing and those with hearing loss limited to high frequencies. Nonsense syllables were presented in three levels of noise that was spectrally shaped to match the long-term spectrum of the speech. Scores for subjects with impaired high-frequency hearing were significantly poorer than scores for subjects with normal hearing. In the case of the low-pass-filtered speech, performance differences between groups could not be attributed to differences in speech audibility, as high-frequency speech cues were absent for all subjects. These results are consistent with the hypothesis that high-frequency fibers encode useful low-frequency speech information.
A multiresolution neural network classifier for machine vision (1991)

The authors discuss the first subcomponent of a vision system being developed to combine the benefit of the flexible approach offered by using neural networks as classifiers and some traditional image classification techniques which have failed to produce the expected results due to the inadequacies of the classification system hitherto used. By using a multiresolution pyramid to focus the attention of the system on areas that are likely to contain the features being sought, the performance of the system in terms of its accuracy and speed of location is improved. Furthermore, by breaking the problem of locating an object into subgoals, the construction and operation of the detectors is reduced in complexity.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Lectern II: a multimedia lecture capturing and editing system (2003)

Deployment of asynchronous learning systems is still very limited mainly because of the use of expensive video to record and play back classroom lectures. The key advantage of the Lectern II approach is that all important lecture components can be effectively captured without video. Lectern II employs the touch-sensitive screen technology to build a "digital desk," which is shown to be able to effectively support and transparently capture the standard classroom lecturing activity. Recorded lectures can be edited and automatically uploaded to a Web server, and than viewed by students via a standard streaming player. As the total cost of a complete Lectern II system is under $4,000, Lectern II represents the first course lecture recording system that has the potential to be widely deployed in the classrooms of universities and K-12 schools.
Comprehensive Privacy Analysis of Deep Learning: Stand-alone and Federated Learning under Passive and Active White-box Inference Attacks. (2018)

Deep neural networks are susceptible to various inference attacks as they
remember information about their training data. We perform a comprehensive
analysis of white-box privacy inference attacks on deep learning models. We
measure the privacy leakage by leveraging the final model parameters as well as
the parameter updates during the training and fine-tuning processes. We design
the attacks in the stand-alone and federated settings, with respect to passive
and active inference attackers, and assuming different adversary prior
knowledge. We design and evaluate our novel white-box membership inference attacks
against deep learning algorithms to measure their training data membership
leakage. We show that a straightforward extension of the known black-box
attacks to the white-box setting (through analyzing the outputs of activation
functions) is ineffective. We therefore design new algorithms tailored to the
white-box setting by exploiting the privacy vulnerabilities of the stochastic
gradient descent algorithm, widely used to train deep neural networks. We show
that even well-generalized models are significantly susceptible to white-box
membership inference attacks, by analyzing state-of-the-art pre-trained and
publicly available models for the CIFAR dataset. We also show how adversarial
participants of a federated learning setting can run active membership
inference attacks against other participants, even when the global model
achieves high prediction accuracies.
Editorial (1988)

As the table of contents indicates, this volume of QAR is dedicated to archaeological research in the extreme S. E. corner of Queensland. All but two of the papers fall under the umbrella of the Moreton Region Archaeological Project (MRAP) and represent a statement about the current aims of this long-term regional research program. By way of this editorial I have taken the opportunity to provide an historical backdrop to MRAP so as to inform the QAR readership of its development.
Power distribution system reliability planning using a fuzzy knowledge-based approach (2000)

Electric power distribution system reliability is defined as the ability to deliver uninterrupted service to customers. Deregulation of the electric power industry has forced utilities to face new challenges and to evaluate the cost-benefit implications of providing an acceptable level of service. This paper presents a fuzzy knowledge-based approach for reliability planning purposes. This approach makes a direct assessment of the circuit configuration and hazards and assigns each section and feeder a relative risk index by expressing the configuration variables mathematically using fuzzy logic. Results obtained using the fuzzy model on actual utility feeder data are presented and the correlation between the fuzzy model results and actual feeder performance is obtained. Determination of the highest risk feeders and of the feeders which benefit the most from a given reliability improvement project are the major goals of the paper.
Tomographic Reconstruction of 2-D Vector Fields: Application to Flow Imaging (1989)

Summary

We examine the problem of reconstructing a 2-D vector field v(x,y) throughout a bounded region D from the line integrals of v(x, y) through D. This problem arises in the 2-D mapping of fluid-flow in a region D from acoustic travel-time measurements through D. For an arbitrary vector field, the reconstruction problem is in general underdetermined since v(x, y) has two independent components, vx(x, y) and vy(x, y). However, under the constraint that v is divergenceless (▿ v = 0) in D, we show that the vector reconstruction problem can be solved uniquely. For incompressible fluid flow, a divergenceless velocity field follows under the assumption of no sources or sinks in D.



A vector central-slice theorem is derived, which is a generalization of the well-known ‘scalar’ central-slice theorem that plays a fundamental role in conventional tomography. the key to the solution to the vector tomography problem is the decomposition of the field v(x, y) into its irrotational and solenoidal components: v =▿φ+▿×ψ, where φ(x, y) and ψ(x, y) are scalar and vector potentials. We show that the solenoidal component ▿ x ψ can be uniquely reconstructed from the line integrals of v through D, whereas the irrotational component ▿φ cannot. However, when the field is divergenceless in D, the scalar potential φ solves Laplace's equation in D and can be determined by the values of v on the boundary of D. an explicit formula for φ from the boundary values of v is derived. Consequently, v(x, y) can be uniquely recovered throughout the region of reconstruction from the following information: line-integral measurements of v through this region and v measured on the boundary of this region.
Visualizing Graphs - A Generalized View (2006)

The visualization of graphs has proven to be very useful for exploring structures in different application domains. However, in certain fields of computer science, graph visualization is understood and focused quite differently. While "graph drawing" focuses on optimized layouts for node-link-representations of networks, "information visualization" prefers to work on hierarchies focusing on very large structures, different views and interactivity. This paper gives a systematic view of the problem of graph visualization by combining both approaches. We introduce a general view of different visualization methods as well as describe occurring problems and discuss basic constraints. These are used to propose a visualization framework for graphs, whose development motivated this paper
Impact of distribution system reconfiguration on optimal placement of phasor measurement units (2014)

Phasor measurement units (PMUs) become a necessity in the modern distribution system especially with the direction towards smart grid. The PMUs should be placed appropriately in the distribution network. The problem of optimal PMU placement for full observability is analyzed in literature. Distribution network reconfiguration for loss reduction is also analyzed in literature. This paper studies the placement problem of PMUs in distribution system considering the system reconfiguration. System reconfiguration is achieved using the ant colony optimization (ACO) algorithm to solve the minimum losses problem. Greedy algorithm is used as an optimization tool to obtain the minimal number of PMUs and their corresponding locations. The 33-node distribution system is tested for optimally locating the PMUs with different network reconfiguration.
Assessment of <i>Clostridium difficile</i> Infections by Quantitative Detection of <i>tcdB</i> Toxin by Use of a Real-Time Cell Analysis System (2010)

We explored the use of a real-time cell analysis (RTCA) system for the assessment of Clostridium difficile toxins in human stool specimens by monitoring the dynamic responses of the HS27 cells to tcdB toxins. The C. difficile toxin caused cytotoxic effects on the cells, which resulted in a dose-dependent and time-dependent decrease in cell impedance. The RTCA assay possessed an analytical sensitivity of 0.2 ng/ml for C. difficile toxin B with no cross-reactions with other enterotoxins, nontoxigenic C. difficile, or other Clostridum species. Clinical validation was performed on 300 consecutively collected stool specimens from patients with suspected C. difficile infection (CDI). Each stool specimen was tested in parallel by a real-time PCR assay (PCR), a dual glutamate dehydrogenase and toxin A/B enzyme immunoassay (EIA), and the RTCA assay. In comparison to a reference standard in a combination of the three assays, the RTCA had a specificity of 99.6% and a sensitivity of 87.5% (28 of 32), which was higher than the EIA result (P = 0.005) but lower than the PCR result (P = 0.057). In addition, the RTCA assay allowed for quantification of toxin protein concentration in a given specimen. Among RTCA-positive specimens collected prior to treatment with metronidazole and/or vancomycin, a significant correlation between toxin protein concentrations and clinical CDI severities was observed (R(2) = 0.732, P = 0.0004). Toxin concentrations after treatment (0.89 ng/ml) were significantly lower than those prior to the treatment (15.68 ng/ml, Wilcoxon P = 0.01). The study demonstrates that the RTCA assay provides a functional tool for the potential assessment of C. difficile infections.
Manhattan scene understanding using monocular, stereo, and 3D features (2011)

This paper addresses scene understanding in the context of a moving camera, integrating semantic reasoning ideas from monocular vision with 3D information available through structure-from-motion. We combine geometric and photometric cues in a Bayesian framework, building on recent successes leveraging the indoor Manhattan assumption in monocular vision. We focus on indoor environments and show how to extract key boundaries while ignoring clutter and decorations. To achieve this we present a graphical model that relates photometric cues learned from labeled data, stereo photo-consistency across multiple views, and depth cues derived from structure-from-motion point clouds. We show how to solve MAP inference using dynamic programming, allowing exact, global inference in ~100 ms (in addition to feature computation of under one second) without using specialized hardware. Experiments show our system out-performing the state-of-the-art.
Realizing Optical Magnetism from Dielectric Metamaterials (2012)

We demonstrate, for the first time, an all-dielectric metamaterial composite in the midinfrared based on micron-sized, high-index tellurium dielectric resonators. Dielectric resonators are desirable compared to conventional metallodielectric metamaterials at optical frequencies as they are largely angular invariant, free of Ohmic loss, and easily integrated into three-dimensional volumes. Measurements and simulation provide evidence of optical magnetism, which could be used for infrared magnetic mirrors, hard or soft surfaces, and subwavelength cavities.
Chemistry of Crystalline Aluminosilicates. II. The Synthesis and Properties of Zeolite ZK-4 (1966)

ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTChemistry of Crystalline Aluminosilicates. II. The Synthesis and Properties of Zeolite ZK-4George T. KerrCite this: Inorg. Chem. 1966, 5, 9, 1537–1539Publication Date (Print):September 1, 1966Publication History Published online1 May 2002Published inissue 1 September 1966https://pubs.acs.org/doi/10.1021/ic50043a015https://doi.org/10.1021/ic50043a015research-articleACS PublicationsRequest reuse permissionsArticle Views807Altmetric-Citations112LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail Other access optionsGet e-Alertsclose Get e-Alerts
An Applicatin of Micro-Ball Wafer Bumping to Double Ball Bump for Flip Chip Interconnection (2005)

Microball wafer bumping method was applied to forming double ball bumps, which increased the bump height to improve the reliability of the flip chip interconnection. The micro solder balls of 100mum in diameter were transferred and connected to the whole electrode-pads covered with UBMs (under bump metals) of an 8 inch wafer in one stroke using a fully automated micro ball mounter, which was originally developed. The balls were held on fluxed pads and melted in a reflow furnace. After cleaning the flux residue, the wafer bumped with microballs was then encapsulated with epoxy resin containing silica fillers by using Apic Yamada's wafer level molding system. The molding resin was spread to the whole wafer by compressing with a heated flat plate, where the top of the solder bumps were covered with an elastic parting film. The supplied resin volume was previously adjusted to the desired molding thickness. The exposed top of the ball bumps was cleaned and then second microball bumping was processed on the top of the first bumps. The first and second balls were connected by reflowing to form the double ball bumps. The height variation and shear strength of double ball bumps were evaluated. To compare the reliability for the different type of bumps the TCTs and FEM analysis were performed for the chips connected with PCBs
Gas Sensors Fabricated from Ceramic Suspensions by Micromolding in Capillaries (2001)

Micromolding in capillaries has been used to fabricate an array of SnO2 gas sensors (see Figure) using colloidal suspensions. The micromolding procedure was integrated in a sequence of conventional photolithography steps. Miniaturized gas sensors on sapphire single crystal substrates showed responses of 100 ppm for H2 and 600 ppm for CO, the active sensing area being only 10 by 40 μm2.
Ballistic analysis of a two-cavity finite beam klystron (1958)

Bunching in a two-cavity klystron in the presence of space charge is computed using a disk model of the electron stream. This digital computer study shows that space charge can actually enhance bunching under proper conditions. Optimum bunching distance is discussed along with the details of the effect of space charge on the velocity spread within the beam. The results are synthesized to provide a qualitative picture of the manner in which bunching, velocity spread, and circuit efficiency contribute to efficiency of energy conversion at an output gap.
Optimized Thermal and Electrical Scheduling of a Large Scale Virtual Power Plant in the Presence of Energy Storages (2013)

Smart grids are often analyzed using a top-down approach, i.e., starting from communication and control technologies evolution, to then focus on their effects on active and passive users, in terms of new services, higher efficiency and quality of supply. However, with their bottom-up approach, virtual power plants (VPP) are very promising instruments for promoting an effective integration of distributed generation (DG) and energy storage devices as well as valid means for enabling consumers to respond to load management signals, when operated under the supervision of a scheduling coordinator. These aggregation factors can be very profitable for the distributed energy resources (DERs) economy and for the energy network itself. This paper presents a new algorithm to optimize the day-ahead thermal and electrical scheduling of a large scale VPP (LSVPP) which contains: a) many small-scale producers and consumers (“prosumers”) distributed over a large territory and b) energy storage and cogeneration processes. The algorithm also takes into account the actual location of each DER in the public network and their specific capability. Thermal and electrical generator models, load and storage devices are very detailed and flexible, as are the rates and incentives framework. Several novelties, with respect to the previous literature, are proposed. Case study results are also described and discussed.
Understanding the Genetics of Gene Regulation Using Multi-Omics Profiling (2019)

Type 2 diabetes (T2D) is a complex disease that affects an estimated 415 million people worldwide. Genome wide association studies (GWAS) have identified >240 genetic signals that encode predisposition to this disease and related traits. However, the underlying biological mechanisms driving this predisposition are largely unknown, which is a serious impediment in designing precision therapeutic strategies. The focus of my research is to untangle the genetic complexity of T2D to better understand the biological mechanisms of how disease predisposition is encoded in our DNA. Specifically, I aim to understand how T2D genetic risk variants modulate gene expression in orchestrating disease mechanisms. I utilize high throughput molecular profiling data in human pancreatic islets and other diverse tissues along with human and rodent cell line model systems and employ computational and experimental approaches to map functional signatures of genetic variants associated with T2D. First, I compared gene regulatory annotations defined using diverse epigenomic data across 4 cell types to compare their cell specificities and genetics of gene expression regulation. I observed that genetic variants in genomic regions with more cell type-specific enhancer chromatin have lower effects on gene expression than variants in genomic regions with more ubiquitous promoter chromatin. However, genetic variants in cell type-specific enhancer regions have higher effects in chromatin accessibility than those in less cell type-specific promoter regions. Second, I integrated GWAS data with various -omics data in islets to nominate biological mechanisms. I observed that T2D risk variants confluently disrupt DNA binding motifs of the transcription factor (TF) regulatory factor X (RFX) in accessible regions. Third, I describe large scale expression quantitative trait locus (eQTL) mapping efforts along with integration of epigenomic data to describe molecular regulatory mechanisms. Utilizing such large eQTL and integrating information such as chromatin accessibility and TF binding predictions helped elucidate in vivo TF activity preferences. Fourth, I describe profiling and analysis of the enhancer transcriptome in islets, which I then integrate with other available epigenomic data to better understand the characteristics of gene regulation.