gebhart/patrepeval huggingface dataset:
CADRE: continuous analysis and discovery from relational evidence (2004)

CADRE (continuous analysis and discovery from relational evidence) is a link detection system that takes in a threat pattern and partial evidence about threat cases and outputs threat hypotheses with inferred actors and events. CADRE uses a Prolog-based frame system to represent threat patterns and enforce temporal and equality constraints among pattern slots. Based on rules involving uniquely identifying slots in the pattern, CADRE triggers an initial set of threat hypotheses, and then refines these hypotheses by generating queries for unknown slots from constraints involving known slots. To evaluate hypotheses, CADRE scores each local hypothesis using a probabilistic model in order to create a consistent, high-value global hypothesis by pruning conflicting lower scoring hypotheses. In a program-wide first year evaluation using simulated threats, CADRE performed best overall among five participating link detection systems.
Pict: A Programming Language Based on the Pi-Calculus (2000)

The &amp;pi;-calculus offers an attractive basis for concurrent programming. It is small, elegant, and well studied, and supports (via simple encodings) a wide range of high-level constructs including data structures, higher-order functional programming, concurrent control structures, and objects. Moreover, familiar type systems for the &amp;lambda;-calculus have direct counterparts in the &amp;pi;-calculus, yielding strong, static typing for a high-level language using the &amp;pi;-calculus as its core. This paper describes Pict, a strongly-typed concurrent programming language constructed in terms of an explicitly-typed &amp;pi;-calculus core language.
Ametryne and Prometryne as Sulfur Sources for Bacteria (1982)

Bacteria were isolated that could utilize quantitatively the s-triazine herbicide prometryne [N,N' -bis(1-methylethyl)-6-(methylthio)-1,3,5-triazine-2,4-diamine] or ametryne [N-ethyl-N'-(1-methylethyl)-6-(methylthio)-1,3,5-triazine- 2,4-diamine], or both, as a sole source of sulfur for growth. The success of enrichments depended on previous exposure of the soil inoculum to s-triazine herbicides. Deaminoethylametryne [4-(1-methylethyl)amino-6-(methylthio)-1,3,5-triazine-2-(1H)-one], methylsulfonic acid, and sodium sulfate could also be used as sulfur sources. Utilization of a compound was quantified as the growth yield per mole of sulfur supplied. Yields were about 6 kg of protein per mol of sulfur. The product of the desulfuration of an s-triazine was identified as the corresponding hydroxy-derivative. This is the first substantiated report of the utilization of these s-triazines as sulfur sources by bacteria.
Integration of OneM2M-based IoT Service Platform and Mixed Reality Device (2019)

To provide a more intuitive user experience, there have been studies to apply mixed reality to the Internet of Things. They have used a Mixed Reality device as a tailored user application only or proposed an early stage of the architecture without any considering the IoT service platform standard. In this paper, we introduce the architecture to integrate Mixed Reality Device to OneM2M, which is the most widely known IoT platform standard. For integration, we consider the three use cases of a Mixed Reality device in IoT service. Also, the demonstration showed the feasibility of the proposed idea with integrating Mobius platform, one of open source oneM2M IoT platform, and Hololens, MR device by Microsoft.
Erosion of metal cathodes by arcs and breakdowns in vacuum (1976)

The formation of erosion structures on metal cathodes by arcs and breakdown in UHV was studied experimentally by FEM and SEM and theoretically by a simple model. Nanosecond high-voltage breakdowns and quasi-stationary arcs had analogous effects on the production of surface craters. The existence of sharp micropoints could be proved directly by SEM. In accordance with the experiments the theory shows three distinct stages of crater formation on a nanosecond time scale: initially micropoints explode without strong erosion, then melting occurs with pronounced smoothing of the surface and finally craters are formed by the action of ion pressure. The latter process is connected with the production of a few sharp micropoints at crater boundaries, and of numerous droplets. The results presented here support the non-stationary model of arc cathode spots and the field-emission model of vacuum breakdown.
Synthesis, characterization, and photocatalytic activity of Au–ZnO nanopyramids (2015)

ZnO nanopyramids have been grown on top of Au nanoparticle seeds creating a unique heterostructured system for photocatalytic applications.
A Mixed Analog-Digital Hybrid for Speech Enhancement Purposes (2005)

The paper presents and evaluates a hybrid implementation of a low complexity algorithm for speech enhancement, the adaptive gain equalizer (AGE). The AGE is a subband based time domain method for instantaneous boosting of speech. By a combination of digital analysis and analog synthesis, the main advantages of the digital and analog domains are utilized. The hybrid solution is implemented on a printed circuit board and evaluated in real-time. The development time of the proposed solution was very short, the solution is flexible, robust, has high signal bandwidth in the signal chain and does not require a voice activity detector (VAD). Furthermore, the solution is not restricted by quantization errors in the signal chain and does not require a high speed digital signal processor (DSP) for analysis. Informal listening tests and signal-to-noise ratio (SNR) measures verify excellent speech enhancement performance and quality.
Oncostatin M Regulates Eotaxin Expression in Fibroblasts and Eosinophilic Inflammation in C57BL/6 Mice (2003)

Oncostatin M (OSM) is a member of the IL-6/LIF (or gp130) cytokine family, and its potential role in inflammation is supported by a number of activities identified in vitro. In this study, we investigate the action of murine OSM on expression of the CC chemokine eotaxin by fibroblasts in vitro and on mouse lung tissue in vivo. Recombinant murine OSM stimulated eotaxin protein production and mRNA levels in the NIH 3T3 fibroblast cell line. IL-6 could regulate a small induction of eotaxin in NIH 3T3 cells, but other IL-6/LIF cytokines (LIF, cardiotrophin-1 (CT-1)) had no effect. Cell signaling studies showed that murine OSM, LIF, IL-6, and CT-1 stimulated the tyrosine phosphorylation of STAT-3, suggesting STAT-3 activation is not sufficient for eotaxin induction in NIH 3T3 cells. OSM induced ERK-1,2 and p38 mitogen-activated protein kinase phosphorylation in NIH 3T3 cells, and inhibitors of ERK (PD98059) or p38 (SB203580) could partially reduce OSM-induced eotaxin production, suggesting partial dependence on mitogen-activated protein kinase signaling. OSM (but not LIF, IL-6, or CT-1) also induced eotaxin release by mouse lung fibroblast cultures derived from C57BL/6 mice. Overexpression of murine OSM in lungs of C57BL/6 mice using an adenovirus vector encoding murine OSM resulted in a vigorous inflammatory response by day 7 after intranasal administration, including marked extracellular matrix accumulation and eosinophil infiltration. Elevated levels of eotaxin mRNA in whole lung were detected at days 4 and 5. These data strongly support a role of OSM in lung inflammatory responses that involve eosinophil infiltration.
Purification and Characterization of Triacylglycerol Lipase from<i>Aspergillus oryzae</i> (1998)

Triacylglycerol lipase (L3) was purified from Aspergillus oryzae RIB128 by ammonium sulfate fractionation, acetone precipitation, anion-exchange chromatography, and gel filtration. The purified enzyme was formed from a glycoprotein and a monomeric protein with molecular masses of 25 and 29 kDa, by SDS-PAGE and gel filtration, respectively. The optimum pH at 40 degrees C was 5.5 and the optimum temperature at pH 5.5 was 40 degrees C. The enzyme was stable between a pH range of 4.0-7.5 at 30 degrees C for 24 h, and at up to 30 degrees C at pH 5.5 for 1 h. Heavy metal ions, detergents, DFP, and DEP strongly inhibited the enzyme activity. The lipase hydrolyzed not only triacylglycerols but also monoacylglycerols and diacylglycerols. The enzyme had higher specificity toward triacylglycerols of middle-chain saturated fatty acids than short-chain or long-chain fatty acids. The enzyme had 1,3-positional specificity. The N-terminal amino acid sequence of the enzyme was not significantly similar to that of other lipases with published sequences.
Logic design for printability using OPC methods (2006)

The steps that create physical shape data in a typical logic device design-to-reticle flow are cell layout, place and route, tapeout, OPC or RET, data fracture, and reticle build. Here, we define OPC as the transformation of reticle data to compensate for lithographic and process distortions so that the final wafer pattern is as close to the target pattern-the designed layout-as possible. We define RETs as the general class of transformations for reticle data that aim to improve the patterning process window; therefore, OPC is a subset of RET. DFM is traditionally considered to be implemented at the cell layout or routing stages of this flow. Examples include the optimization of a layout based on critical-defect area, the addition of redundant contacts and vias, wire spreading, upsizing of metal landing pads, and the addition of dummy metal tiles to improve the planarity after chemical-mechanical planarization (CMP). We presented a detailed analysis of these techniques in an earlier work. In contrast, this article analyzes the possibility of extending these traditional methods into the OPC stage and introduces new post-tapeout RET methods for improving printability.
Double lock-in concept for MORE glucose detection (2003)

We previously proposed a new approach to optical glucose sensing based on the fact that glucose solutions have a magnetic optical rotatory effect (MORE). The proportionality with the glucose concentration was found to be linear with single and double MORE at physiologic concentrations. Use of MORE has a number of potential advantages over the conventional optical rotatory effect including improved spatial resolution and sensitivity. We introduce the concept of using double lock-in amplifiers to separate a small, narrow band signal from interfering noise in this study.
Malignant lesion segmentation in contrast‐enhanced breast MR images based on the marker‐controlled watershed (2009)

Breast tumor volume measured on MRI has been used to assess response to neoadjuvant chemotherapy. However, accurate and reproducible delineation of breast lesions can be challenging, since the lesions may have complicated topological structures and heterogeneous intensity distributions. In this article, the authors present an advanced computerized method to semiautomatically segment tumor volumes on T1-weighted, contrast-enhanced breast MRI. The method starts with manual selection of a region of interest (ROI) that contains the lesion to be segmented in a single image, followed by automated separation of the lesion volume from its surrounding breast parenchyma by using a unique combination of the image processing techniques including Gaussian mixture modeling and a marker-controlled watershed transform. Explicitly, the Gaussian mixture modeling is applied to an intensity histogram of the pixels inside the ROI to distinguish the tumor class from other tissues. Based on the ROI and the intensity distribution of the tumor, internal and external markers are determined and the tumor contour is delineated using the marker-controlled watershed transform. To obtain the tumor volume, the segmented tumor in one slice is propagated to the adjacent slice to form an ROI in that slice. The marker-controlled watershed segmentation is then used again to obtain a tumor contour in the propagated slice. This procedure is terminated when there is no lesion in an adjacent slice. To reduce measurement variations possibly caused by the manual selection of the ROI, the segmentation result is refined based on an automatically determined ROI based on the segmented volume. The algorithm was applied to 13 patients with breast cancer, prospectively accrued prior to beginning neoadjuvant chemotherapy. Each patient had two MRI scans, a baseline MRI examination prior to commencing neoadjuvant chemotherapy and a 1 week follow-up after receiving the first dose of neoadjuvant chemotherapy. Blinded to the computer segmentation results, two experienced radiologists manually delineated all tumors independently. The computer results were then compared with the manually generated results using the volume overlap ratio, defined as the intersection of the computer- and radiologist-generated tumor volumes divided by the union of the two. The algorithm reached overall overlap ratios of 62.6% +/- 9.1% and 61.0% +/- 11.3% in comparison to the two manual segmentation results, respectively. The overall overlap ratio between the two radiologists' manual segmentations was 64.3% +/- 10.4%. Preliminary results suggest that the proposed algorithm is a promising method for assisting in tumor volume measurement in contrast-enhanced breast MRI.
Use of a simple symptom questionnaire to predict Barrett's esophagus in patients with symptoms of gastroesophageal reflux (2001)

Accurately predicting Barrett's esophagus (BE) in patients with gastroesophageal reflux disease (GERD) is difficult. Using logistic regression analysis of symptom questionnaire scores we created a model to predict the presence of BE.We conducted a logistic regression analysis of symptom data collected prospectively on 517 GERD patients and created a prediction model based on patient gender, age, ethnicity, and symptom severity.There were 337 (65%) males and 180 (35%) females, of whom 99 (19%) had Barrett's esophagus (BE). Multiple logistic regression analysis was performed to determine the predictive ability of gender, age, and ethnicity along with symptoms of heartburn, nocturnal pain, odynophagia, presence of belching, dysphagia, relief of symptoms with food, and nausea. The only significant predictors (at the 0.05 level) were male gender, heartburn, nocturnal pain, and odynophagia (all with positive effects on the presence of BE) and dysphagia (which had a negative effect). A nomogram was produced to show the effect of a given predictor on the probability of having BE in the context of the effects of the other predictors, and to estimate the probability of having BE for a given individual. The mean score (+/-SD) for the BE patients in our sample was 397.4+/-46.2 with a range of 292-530. For the patients without BE, the mean score (+/-SD) was 351.3+/-60.3 with a range of 190 - 528 (p < 0.001). If screening for BE is performed at a score of 375 or more, our model would have a specificity of 63% with a sensitivity of 77% (95% CI 61-86% given the 63% specificity).By asking seven questions about symptom severity, clinicians may be able to assign a probability to the presence of BE, and thus, determine the need for endoscopy in GERD patients.
Arbitrary Shape Scene Text Detection with Adaptive Text Region Representation (2019)

Scene text detection attracts much attention in computer vision, because it can be widely used in many applications such as real-time text translation, automatic information entry, blind person assistance, robot sensing and so on. Though many methods have been proposed for horizontal and oriented texts, detecting irregular shape texts such as curved texts is still a challenging problem. To solve the problem, we propose a robust scene text detection method with adaptive text region representation. Given an input image, a text region proposal network is first used for extracting text proposals. Then, these proposals are verified and refined with a refinement network. Here, recurrent neural network based adaptive text region representation is proposed for text region refinement, where a pair of boundary points are predicted each time step until no new points are found. In this way, text regions of arbitrary shapes are detected and represented with adaptive number of boundary points. This gives more accurate description of text regions. Experimental results on five benchmarks, namely, CTW1500, TotalText, ICDAR2013, ICDAR2015 and MSRATD500, show that the proposed method achieves state-of-the-art in scene text detection.
Prediction of Abnormal Behaviors for Intelligent Video Surveillance Systems (2007)

The OBSERVER is a video surveillance system that detects and predicts abnormal behaviors aiming at the intelligent surveillance concept. The system acquires color images from a stationary video camera and applies state of the art algorithms to segment, track and classify moving objects. In this paper we present the behavior analysis module of the system. A novel method, called Dynamic Oriented Graph (DOG) is used to detect and predict abnormal behaviors, using real-time unsupervised learning. The DOG method characterizes observed actions by means of a structure of unidirectional connected nodes, each one defining a region in the hyperspace of attributes measured from the observed moving objects and having assigned a probability to generate an abnormal behavior. An experimental evaluation with synthetic data was held, where the DOG method outperforms the previously used N-ary Trees classifier.
Bioengineered functional brain-like cortical tissue (2014)

The brain remains one of the most important but least understood tissues in our body, in part because of its complexity as well as the limitations associated with in vivo studies. Although simpler tissues have yielded to the emerging tools for in vitro 3D tissue cultures, functional brain-like tissues have not. We report the construction of complex functional 3D brain-like cortical tissue, maintained for months in vitro, formed from primary cortical neurons in modular 3D compartmentalized architectures with electrophysiological function. We show that, on injury, this brain-like tissue responds in vitro with biochemical and electrophysiological outcomes that mimic observations in vivo. This modular 3D brain-like tissue is capable of real-time nondestructive assessments, offering previously unidentified directions for studies of brain homeostasis and injury.
DSIP: A Scalable Inference Accelerator for Convolutional Neural Networks (2017)

This paper presents a scalable inference accelerator called a deep-learning specific instruction-set processor (DSIP) to support various convolutional neural networks (CNNs). For CNNs requiring a large amount of computations and memory accesses, a programmable inference system called master-slave instruction set architecture (ISA) is newly proposed to achieve high flexibility, processing speed, and energy efficiency. The master is responsible for sending and receiving feature maps in order to deal with neural networks in a scalable way, and the slave performs CNN operations, such as multiply accumulate, max pooling, and activation functions, on the features received from the master. The master-slave ISA maximizes computation speed by overlapping the off-chip data transmission and the CNN operations, and reduces power consumption by performing the convolution incrementally to reuse input and partial-sum data as maximally as possible. An inference system can be configured by connecting multiple DSIPs in a form of either 1-D or 2-D chain structure in order to enhance computation speed further. To evaluate the proposed accelerator, a prototype chip is implemented and evaluated for AlexNet. Compared to the state-of-the-art accelerator, the DSIP-based system enhances the energy efficiency by 2.17×.×.
Characterization of the FNR protein of <i>Escherichia coli</i> , an iron-binding transcriptional regulator (1991)

FNR is a transcriptional regulator mediating the activation or repression of a variety of Escherichia coli genes in response to anoxia. The FNR protein resembles CRP (the cyclic-AMP receptor protein) except for the presence of a cysteine-rich N-terminal segment which may form part of an iron-binding redoxsensing domain. The FNR protein was purified by a new procedure. It was monomeric (Mr = 30,000) and contained as much as 1.1 mol of iron per monomer when purified in the presence of added iron. This iron was associated with cysteine residues, because there was an inverse relation between iron content and titratable sulphydryl groups. Other physical and chemical properties are reported including evidence for a potential disulphide group or analogous modification. The interaction between FNR protein and target DNA appeared weak and non-specific in gel-retardation assays, but specific binding to the proposed DNA-binding site was shown for the first time in footprinting studies. A role for iron in FNR-mediated gene expression was confirmed by using cultures in which FNR was inactivated by growth in the presence of the specific chelator, ferrozine, but protected by ferrous iron.
Distributed transaction processing in the TUXEDO system (2002)

The TUXEDO system, a commercially proven transaction monitor, built on open industry standards, is described. It ensures data integrity in a distributed, heterogeneous environment with an optimized two-phase commit protocol. It offers an advanced client/server programming paradigm, increased throughput, network connectivity, and runtime system monitoring and management.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Dead Regions in the Cochlea: Diagnosis, Perceptual Consequences, and Implications for the Fitting of Hearing Aids (2001)

Hearing impairment is often associated with damage to the hair cells in the cochlea. Sometimes there may be complete loss of function of inner hair cells (IHCs) over a certain region of the cochlea; this is called a "dead region". The region can be defined in terms of the range of characteristic frequencies (CFs) of the IHCs and/or neurons immediately adjacent to the dead region. This paper reviews the following topics: the effect of dead regions on the audiogram; methods for the detection and delineation of dead regions based on psychophysical tuning curves (PTCs) and on the measurement of thresholds for pure tones in "threshold equalizing noise" (TEN); effects of dead regions on speech perception; effects of dead regions on the perception of tones; implications of dead regions for fitting hearing aids. The main conclusions are: (1) Dead regions may be relatively common in people with moderate-to-severe sensorineural hearing loss; (2) Dead regions cannot be reliably diagnosed from the audiogram; (3) PTCs provide a useful way of detecting dead regions and defining their boundaries. However, the determination of PTCs is probably too time-consuming to be used for routine diagnosis of dead regions in clinical practice; (4) The measurement of detection thresholds for pure tones in TEN provides a simple method for clinical diagnosis of dead regions; (5) Pure tones with frequencies falling in a dead region do not evoke clear pitch sensations (pitch matching is highly variable) and the perceived pitch is sometimes, but not always, different from "normal". However, ratings of pitch clarity cannot be used as a reliable indicator of a dead region; (6) Amplification of frequencies well inside a high-frequency dead region usually does not improve speech intelligibility, and may sometimes impair it. However, there may be some benefit in amplifying frequencies up to 50 to 100% above the estimated low-frequency edge of a high-frequency dead region; (7) The optimal form of amplification for people with low-frequency dead regions remains somewhat unclear. There may be some benefit from avoiding the amplification of frequencies well inside a dead region; (8) Patients with extensive dead regions are likely to get less benefit from hearing aids than patients without dead regions; (9) For patients with diagnosed dead regions at high frequencies, consideration should be given to use of a hearing aid incorporating frequency transposition and/or compression.