gebhart/patrepeval huggingface dataset:
Optical Interconnection Bidirectional Data Vortex Network: Architecture and Performance Analysis (2013)

Data Vortex architecture is a unidirectional, highly scalable, all optical multistage interconnection packet switching network. In the present paper we propose Data Vortex architecture with bidirectional links in which the packets are routed both in the forward as well as in the reverse directions. The feasibility of data flow in both the directions is simulated in C environment. The performance analysis of bidirectional network is carried out and presented in terms of injection rate, latency and latency distribution. Finally, the comparison of the proposed bidirectional architecture with two Data Vortex networks connected in parallel for bidirectional operation is also presented.
Very Deep Convolutional Networks for End-to-End Speech Recognition (2016)

Sequence-to-sequence models have shown success in end-to-end speech recognition. However these models have only used shallow acoustic encoder networks. In our work, we successively train very deep convolutional networks to add more expressive power and better generalization for end-to-end ASR models. We apply network-in-network principles, batch normalization, residual connections and convolutional LSTMs to build very deep recurrent and convolutional structures. Our models exploit the spectral structure in the feature space and add computational depth without overfitting issues. We experiment with the WSJ ASR task and achieve 10.5\% word error rate without any dictionary or language using a 15 layer deep network.
Real-world font recognition using deep network and domain adaptation (2015)

We address a challenging fine-grain classification problem: recognizing a font style from an image of text. In this task, it is very easy to generate lots of rendered font examples but very hard to obtain real-world labeled images. This realto-synthetic domain gap caused poor generalization to new real data in previous methods (Chen et al. (2014)). In this paper, we refer to Convolutional Neural Networks, and use an adaptation technique based on a Stacked Convolutional AutoEncoder that exploits unlabeled real-world images combined with synthetic data. The proposed method achieves an accuracy of higher than 80% (top-5) on a realworld dataset.
Estimation of Generative Force of Piezoelectric Actuator by Using Driving Current (2015)

This paper deals with a force estimation method by using driving current of a piezoelectric actuator. Because the size of sensors sometimes restricts the size of a whole device, a sensor-less control is preferable to build a device compactly. A mechanical clamp device including the actuator was represented as an equivalent electric circuit by applying Martin's model, and a force change is calculated from the driving current. Although only dynamic behavior generates the electric charge in the piezoelectric actuator, a static stress varies its piezoelectric constant. Then the stiffness of the piezoelectric actuator will change. The preload of the piezoelectric actuator can be estimated from the resonant frequency of residual vibration of the driving current, which coincided with the mechanical vibration of the device. Consequently, the generated force can be represented as a linear function of the applied voltage and resonance frequency of the current. The force containing the static preload was estimated with an error less than 12% for step response.
ChemInform Abstract: Novel, Potent Aldose Reductase Inhibitors: 3,4‐Dihydro‐4‐oxo‐3‐((5‐( trifluoromethyl)‐2‐benzothiazolyl)methyl)‐1‐phthalazineacetic Acid ( Zopolrestat) and Congeners. (1991)

Abstract ChemInform is a weekly Abstracting Service, delivering concise information at a glance that was extracted from about 100 leading journals. To access a ChemInform Abstract of an article which was published elsewhere, please select a “Full Text” option. The original article is trackable via the “References” option.
Molecular profiling predicts clinical outcome in patients with metastatic colorectal cancer treated with 5-FU/oxaliplatin (2004)

3519 Background: Genetic polymorphisms have been shown to predict clinical outcome to 5-Fluorouracil/Oxaliplatin chemotherapy in patients with colorectal cancer. We have shown in retrospective studies on patients with metastatic colorectal cancer that polymorphisms in the DNA repair pathway genes XPD751, ERCC1, metabolizing gene GSTP1, and target gene TS5', TS3'UTR are predictive to clinical outcome to 5-FU/Oxaliplatin. In a prospective study, we analyzed these polymorphisms along with XPD312, XPD156, and TS5'SNP to confirm identified patterns. We also analyzed the polymorphism in the COX-2 gene, which is associated with angiogenesis in colorectal cancer. Methods: 168 patients with stage IV metastatic colorectal cancer were enrolled and received 5-FU/Oxaliplatin after failing CTP-11. 130 patients (68 ♂,62 ♀) with median age 60 years (25 to 87) had sufficient follow up time for analysis. Median follow up time was 16.6 months. Genomic DNA was extracted and analyzed by a PCR-based RFLP technique. Results: A univariate analysis of the genotypes showed XPD156 was significant for response to chemotherapy (p=.04). Patients with the A/A genotype in XPD156 had greater response compared to patients with the C/C genotype. GSTP1 (p=.08), TS5' (p=.10), and TS3'UTR (p=.07) showed a trend for response. From the table below, GSTP1 and TS5'SNP were significant for survival and XPD312 showed a trend. Conclusion: The data confirms that genes identified retrospectively GSTP1, TS, and XDP may predict survival and response in patients with colorectal cancer who received 5-FU/Oxaliplatin. The data on the polymorphisms are in contrast to our retrospective study, indicating that further functional analysis is critical to understanding their role in chemosensitivity. Author Disclosure Employment or Leadership Consultant or Advisory Stock Ownership Honoraria Research Funding Expert Testimony Other Remuneration Chiron
Demonstration of an X-ray Fluorescence Sensor for the Cone Penetrometer (1995)

A feasibility test at the Naval Research Laboratory has shown that a miniature X-ray Fluorescence (XRF) sensor can be constructed for the cone penetrometer. Such a sensor would have detection limits for heavy metal contaminants in soils of a few parts per million. The next step is to demonstrate the capabilities of such a sensor in the cone penetrometer. A sensor for this purpose is being constructed and will be tested both in the laboratory and in the field. The XRF sensor will be capable of evaluating the in-situ detection limits and field screening (semi-quantitative) capabilities of x-ray fluorescence and can be transitioned to field activities for further evaluation and feedback. The sensor will consist of a miniature x-ray tube and an x-ray detector, together with appropriate apertures and x-ray filters, in a custom fabricated section of penetrometer pipe. The sensor will use commercially available components. High voltage and signal cables will couple the sensor to electronics in the truck. Boron carbide will be used for the x-ray windows which protect the sensor components from soil abrasion.
Low-power and high-sensitivity system-on-chip hall effect sensor (2017)

Low-cost, low-power, and high-sensitivity System-on-Chip (SoC) Hall Effect sensors for 0.18 μm and 0.13 μm technologies and beyond are developed in this work. A best-in-class current-related sensitivity S <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">I</sub> of 418 V/A*T is achieved by a Hall device with an area of 42 μm × 42 μm. Small offset voltage ranges within +/-1.05 mV, as well as excellent sensor reliability, are demonstrated. The Hall sensors are available for manufacturing.
A method for reduced-order modeling and simulation of large interconnect circuits and its application to PEEC models with retardation (2000)

The continuous improvement in the performance and the increases in the sizes of VLSI systems make electrical interconnect and package (EIP) design and modeling increasingly more important. Special software tools must be used for the design of high-performance VLSI systems. Furthermore, larger and faster systems require larger and more accurate circuit models. The partial element equivalent circuit (PEEC) technique is used for modeling such systems with three-dimensional full wave models. In this paper, we present a practical, readily parallelizable procedure for generating reduced-order frequency-domain models from general full wave PEEC systems. We use multiple expansion points, and piecemeal construction of pole-residue approximations to transfer functions of the PEEC systems, as was used in the complex frequency hopping algorithms. We consider general, multiple-input/multiple-output PEEC systems. Our block procedure consists of an outer loop of local approximations to the PEEC system, coupled with an inner loop where an iterative model-reduction method is applied to the local approximations. We systematically divide the complex frequency region of interest into small regions and construct local approximations to the PEEC system in each subregion. The local approximations are constructed so that the matrix factorizations associated with each of them are the size of the original system and independent of the order of the approximation. Results of computations on these local systems are combined to obtain a reduced-order model for the original PEEC system. We demonstrate the usefulness of our approach with three interesting examples.
Background-Free Observation of Cold Antihydrogen with Field-Ionization Analysis of Its States (2002)

A background-free observation of cold antihydrogen atoms is made using field ionization followed by antiproton storage, a detection method that provides the first experimental information about antihydrogen atomic states. More antihydrogen atoms can be field ionized in an hour than all the antimatter atoms that have been previously reported, and the production rate per incident high energy antiproton is higher than ever observed. The high rate and the high Rydberg states suggest that the antihydrogen is formed via three-body recombination.
Archaeal-type lysyl-tRNA synthetase in the Lyme disease spirochete <i>Borrelia burgdorferi</i> (1997)

Lysyl-tRNAs are essential for protein biosynthesis by ribosomal mRNA translation in all organisms. They are synthesized by lysyl-tRNA synthetases (EC 6.1.1.6), a group of enzymes composed of two unrelated families. In bacteria and eukarya, all known lysyl-tRNA synthetases are subclass IIc-type aminoacyl-tRNA synthetases, whereas some archaea have been shown to contain an unrelated class I-type lysyl-tRNA synthetase. Examination of the preliminary genomic sequence of the bacterial pathogen Borrelia burgdorferi, the causative agent of Lyme disease, indicated the presence of an open reading frame with over 55% similarity at the amino acid level to archaeal class I-type lysyl-tRNA synthetases. In contrast, no coding region with significant similarity to any class II-type lysyl-tRNA synthetase could be detected. Heterologous expression of this open reading frame in Escherichia coli led to the production of a protein with canonical lysyl-tRNA synthetase activity in vitro. Analysis of B. burgdorferi mRNA showed that the lysyl-tRNA synthetase-encoding gene is highly expressed, confirming that B. burgdorferi contains a functional class I-type lysyl-tRNA synthetase. The detection of an archaeal-type lysyl-tRNA synthetase in B. burgdorferi and other pathogenic spirochetes, but not to date elsewhere in bacteria or eukarya, indicates that the gene that encodes this enzyme has a common origin with its orthologue from the archaeal kingdom. This difference between the lysyl-tRNA synthetases of spirochetes and their hosts may be readily exploitable for the development of anti-spirochete therapeutics.
A brachytic dwarfism trait (<i>dw</i>) in peach trees is caused by a nonsense mutation within the gibberellic acid receptor<i>PpeGID1c</i> (2015)

Little is known about the genetic factors controlling tree size and shape. Here, we studied the genetic basis for a recessive brachytic dwarfism trait (dw) in peach (Prunus persica) that has little or no effect on fruit development. A sequencing-based mapping strategy positioned dw on the distal end of chromosome 6. Further sequence analysis and fine mapping identified a candidate gene for dw as a non-functional allele of the gibberellic acid receptor GID1c. Expression of the two GID1-like genes found in peach, PpeGID1c and PpeGID1b, was analyzed. GID1c was predominantly expressed in actively growing vegetative tissues, whereas GID1b was more highly expressed in reproductive tissues. Silencing of GID1c in plum via transgenic expression of a hairpin construct led to a dwarf phenotype similar to that of dw/dw peaches. In general, the degree of GID1c silencing corresponded to the degree of dwarfing. The results suggest that PpeGID1c serves a primary role in vegetative growth and elongation, whereas GID1b probably functions to regulate gibberellic acid perception in reproductive organs. Modification of GID1c expression could provide a rational approach to control tree size without impairing fruit development.
Crystal Structure of a Bacterial Type III Polyketide Synthase and Enzymatic Control of Reactive Polyketide Intermediates (2004)

In bacteria, a structurally simple type III polyketide synthase (PKS) known as 1,3,6,8-tetrahydroxynaphthlene synthase (THNS) catalyzes the iterative condensation of five CoA-linked malonyl units to form a pentaketide intermediate. THNS subsequently catalyzes dual intramolecular Claisen and aldol condensations of this linear intermediate to produce the fused ring tetrahydroxynaphthalene (THN) skeleton. The type III PKS-catalyzed polyketide extension mechanism, utilizing a conserved Cys-His-Asn catalytic triad in an internal active site cavity, is fairly well understood. However, the mechanistic basis for the unusual production of THN and dual cyclization of its malonyl-primed pentaketide is obscure. Here we present the first bacterial type III PKS crystal structure, that of Streptomyces coelicolor THNS, and identify by mutagenesis, structural modeling, and chemical analysis the unexpected catalytic participation of an additional THNS-conserved cysteine residue in facilitating malonyl-primed polyketide extension beyond the triketide stage. The resulting new mechanistic model, involving the use of additional cysteines to alter and steer polyketide reactivity, may generally apply to other PKS reaction mechanisms, including those catalyzed by iterative type I and II PKS enzymes. Our crystal structure also reveals an unanticipated novel cavity extending into the "floor" of the traditional active site cavity, providing the first plausible structural and mechanistic explanation for yet another unusual THNS catalytic activity: its previously inexplicable extra polyketide extension step when primed with a long acyl starter. This tunnel allows for selective expansion of available active site cavity volume by sequestration of aliphatic starter-derived polyketide tails, and further suggests another distinct protection mechanism involving maintenance of a linear polyketide conformation.
Surface imaging of focused ion-beam exposed resists (1991)

Silylation processes have previously been applied to optical lithography to overcome deleterious substrate effects and to achieve smaller linewidths. We have applied silylation to focused ion-beam (FIB) lithography, thereby eliminating the need for exposure throughout the entire resist thickness. This approach permits the use of Ga+ ions which have a limited range in the resist but are available from high brightness sources. Thus FIB lithography writing speed can be dramatically improved. Sensitivity of 8×1011 ions/cm2 was found with 30-keV Ga+ using SAL 601 resist, and linewidths below 100 nm have been demonstrated.
Knowledge Graph Embeddings and Explainable AI (2020)

Knowledge graph embeddings are now a widely adopted approach to knowledge representation in which entities and relationships are embedded in vector spaces. In this chapter, we introduce the reader to the concept of knowledge graph embeddings by explaining what they are, how they can be generated and how they can be evaluated. We summarize the state-of-the-art in this field by describing the approaches that have been introduced to represent knowledge in the vector space. In relation to knowledge representation, we consider the problem of explainability, and discuss models and methods for explaining predictions obtained via knowledge graph embeddings.
Development of Novel Method for Preparation of PEMFC Electrodes (2004)

A method based on pulse electrodeposition technique was developed for preparation of membrane electrode assemblies (MEAs). In this approach, platinum is deposited directly on the surface of the carbon electrode. The method ensures most of the platinum to be in close contact with the membrane. Using this method it is possible to increase the Pt/C ratio up to 75 wt % near the surface of the electrode resulting in a 5 μm thick catalyst layer. The MEA prepared by pulse electrodeposition exhibits a current density of at 0.8 V with platinum loading of 0.25 mg of The results indicate that pulse deposition may be an attractive technique to replace the conventional powder-type MEA preparation methods and help achieve industry goals of reducing catalyst cost and increasing efficiency in polymer electrode membrane fuel cells (PEMFCs). © 2004 The Electrochemical Society. All rights reserved.
Zombie memory: Extending memory lifetime by reviving dead blocks (2013)

Zombie is an endurance management framework that enables a variety of error correction mechanisms to extend the lifetimes of memories that suffer from bit failures caused by wearout, such as phase-change memory (PCM). Zombie supports both single-level cell (SLC) and multi-level cell (MLC) variants. It extends the lifetime of blocks in working memory pages (primary blocks) by pairing them with spare blocks, i.e., working blocks in pages that have been disabled due to exhaustion of a single block's error correction resources, which would be 'dead' otherwise. Spare blocks adaptively provide error correction resources to primary blocks as failures accumulate over time. This reduces the waste caused by early block failures, making working blocks in discarded pages a useful resource. Even though we use PCM as the target technology, Zombie applies to any memory technology that suffers stuck-at cell failures. This paper describes the Zombie framework, a combination of two new error correction mechanisms (ZombieXOR for SLC and ZombieMLC for MLC) and the extension of two previously proposed SLC mechanisms (ZombieECP and ZombieERC). The result is a 58% to 92% improvement in endurance for Zombie SLC memory and an even more impressive 11x to 17x improvement for ZombieMLC, both with performance overheads of only 0.1% when memories using prior error correction mechanisms reach end of life.
Schedule-Driven Coordination for Real-Time Traffic Network Control (2012)

Real-time optimization of the dynamic flow of vehicle traffic through a network of signalized intersections is an important practical problem. In this paper, we take a decentralized, schedule-driven coordination approach to address the challenge of achieving scalable network-wide optimization. To be locally effective, each intersection is controlled independently by an on-line scheduling agent. At each decision point, an agent constructs a schedule that optimizes movement of the observable traffic through the intersection, and uses this schedule to determine the best control action to take over the current look-ahead horizon. Decentralized coordination mechanisms, limited to interaction among direct neighbors to ensure scalability, are then layered on top of these asynchronously operating scheduling agents to promote overall performance. As a basic protocol, each agent queries for newly planned output flows from its upstream neighbors to obtain an optimistic projection of future demand. This projection may incorporate non-local influence from indirect neighbors depending on horizon length. Two additional mechanisms are then introduced to dampen ``nervousness'' and dynamic instability in the network, by adjusting locally determined schedules to better align with those of neighbors. We present simulation results on two traffic networks of tightly-coupled intersections that demonstrate the ability of our approach to establish traffic flows with lower average vehicle wait times than both a simple isolated control strategy and other contemporary coordinated control strategies that use moving average forecast or traditional offset calculation.
Plasma YKL‐40, as a prognostic tumor marker in recurrent ovarian cancer (2003)

High plasma YKL-40 is related to short survival in patients with recurrent ovarian cancer.
MicroRNA-200c modulates epithelial-to-mesenchymal transition (EMT) in human colorectal cancer metastasis (2012)

miR-200c plays an important role in mediating EMT and metastatic behaviour in the colon. Its expression is epigenetically regulated, and miR-200c may serve as a potential diagnostic marker and therapeutic target for patients with CRC.
Prototype Arabic Sign language recognition using multi-sensor data fusion of two leap motion controllers (2015)

Sign language is important for facilitating communication between hearing impaired and the rest of society. However, most vocal people do not understand sign language, hence, the need to develop system capable of translating sign language. Two approaches have traditionally been used in the literature: image-based and glove-based systems. Glove-based systems require the user to wear electronic gloves while performing the signs. The glove includes a number of sensors detecting different hand and finger articulations. Image-based systems use camera(s) to acquire a sequence of images of the hand. Each of the two approaches has its own disadvantages. The glove-based method is not natural as the user must wear a cumbersome instrument while the camera-based system requires specific background and environmental conditions to achieve high accuracy. In this paper, we propose a new approach for Arabic Sign Language Recognition (ArSLR) which involves the use of two Leap Motion Controllers (LMC) to prevent the case of one finger being occluded by another finger or hand. This device detects and tracks the hand and fingers to provide position and motion information. We propose to use the two LMCs as a backbone of the ArSLR system. In addition to data acquisition, the system includes a preprocessing stage, a feature extraction stage, and a classification stage. Fusion of evidences from the two LMCs at the feature extraction and classification stage was also investigated using Dempster-Shafer theory of evidence. Features fusion from the two LMCs gives 97.7% classification accuracy with Linear Discriminant Analysis (LDA) classifier and 97.1% with classifier level fusion. This gives better recognition over the use of a single LMC.
Engineering a DNAzyme-Based Operon System for the Production of DNA Nanoscaffolds in Living Bacteria (2020)

The ability to create nanoscaffolds within living cells using DNA has the potential to become a powerful tool in synthetic biology. However, to date, genetically encoded DNA nanostructures are limited to simple architecture due to the lack of genetic parts that can produce multiple ssDNAs in a single bacterium. Here, we develop a system that overcomes this challenge by using a single oligo gene mimicking operons. This was achieved by converting a noncoding RNA into a long ssDNA that self-cleaves into multiple ssDNAs using R3-DNAzymes (DNAzyme-based operon). We demonstrate the ability to apply the DNAzyme-based operon to produce a four-ssDNA crossover nanostructure (25 nm) that recruits split YFPs when properly assembled. This system enables the formation of more complex DNA nanostructures <i>in vivo</i> and thus paves the way to further integrate the field of DNA nanotechnology into living bacteria for basic biology, bioengineering, and medicine applications.