gebhart/patrepeval huggingface dataset:
Storage Allocation in Unreliable Peer-to-Peer Systems (2006)

Peer-to-peer systems provide the opportunity to pool large amounts of distributed resources to enable Internet-scale applications. However, the participant nodes are highly dynamic and unreliable. Thus, any shared resource such as file objects must incorporate redundancy to be useful. While many studies have proposed heuristics to determine redundancy levels based on object popularity, there has been little work in determining optimal or near-optimal resource allocation based on node reliability. In this paper, we present a strategy for the allocation of objects in the presence of dynamic and unreliable peers. We have built an availability model of peer-to-peer storage systems based on the bimodal and time-dependent availability characteristics of a P2P node. Using this model, we can select the size of a candidate node set for storage allocation and assign storage objects to maximize availability while still maintaining a balanced distribution of objects
Comparison of various surface textured layer in InGaN LEDs for high light extraction efficiency (2011)

The various surface texturing effects of InGaN light emitting diodes (LEDs) have been investigated by comparison of experimented data and simulated data. The single-layer and double-layer texturing were performed with the help of ITO nanospheres using wet etching, where the ITO ohmic contact layer and the p-GaN layer are textured using ITO nanospheres as an etch mask. In case of single-layer texturing, p-type GaN layer texturing was more effective than ITO ohmic contact layer texturing. The maximum enhancement of wall-plug efficiency of double-layered textured LEDs is 40% more than conventional LEDs, after packaging at an injected current of 20 mA. The increase of light scattering at the textured GaN surfaces is a major reason for increasing the light extraction efficiency of LEDs.
An FPGA Implementation of Hough Transform using DSP blocks and block RAMs (2013)

Since FPGA chips maintain relatively low price and its programmable features, it is widely used in those fields which need to update architecture or functions frequently such as communication and education areas. Especially, in mobile devices that recently require the ability to perform computation such as real-time image processing, FPGAs are promising devices. The main contribution of this paper is to present a new FPGA architecture for the Hough transform that identifies straight lines in a binary image. Recent FPGAs have hundreds of embedded DSP blocks and block RAMs. For example, Xilinx Virtex-6 Family FPGAs have a DSP48E1 block, which is a configurable logic block equipped with fast multipliers, adders, pipeline registers, and so on. They also have a dual-port memory with 18Kbits as a block RAM. One of the most important key techniques for accelerating computation using FPGAs is an efficient usage of DSP blocks and block RAMs. Our new architecture for the Hough transform uses 178 DSP48E1 blocks and 180 block RAMs with 18Kbits that work in parallel. As far as we know, there is no previously published work that fully utilizes DSP blocks and block RAMs for the Hough transform. Roughly speaking, a conventional sequential implementation performs 180 m voting operations for m edge points. Our architecture performs voting operations in parallel, and outputs identified straight lines in m +97 clock cycles. Since 180 m voting operations are performed using 178 DSP48E1 blocks, the lower bound of the computing time is m clock cycles. Hence our implementation is close to optimal. The implementation results show that the Hough transform for a 512×512 image with 33232 edge points can be done in only 135.75µs.
Temperature measurements of polymer melts in the heating barrel during injection molding. Part 3: Effects of screw geometry (1990)

Abstract We have developed a new method to measure the true temperature of the polymer melt and its three‐dimensional distribution of a shot stored in the reservoir during injection. By means of this method, it is demonstrated that the temperature distribution of the polymer melt stored in the reservoir is strongly dependent on the setup molding conditions, the polymer investigated, and the geometry of the screw used. Further, it is noted qualitatively that there are two major effects of screw geometry on the temperature distribution of polymer melts. One, which governs strongly the temperature in the high temperature zone, is shear heat generated within the polymer itself in the metering zone of the screw during the transporting process. The second is the ability to preheat and plasticate the polymer in the compression zone, which is indispensable for uniform plastication.
Memristor-Based Neural Logic Blocks for Nonlinearly Separable Functions (2013)

Neural logic blocks (NLBs) enable the realization of biologically inspired reconfigurable hardware. Networks of NLBs can be trained to perform complex computations such as multilevel Boolean logic and optical character recognition (OCR) in an area- and energy-efficient manner. Recently, several groups have proposed perceptron-based NLB designs with thin-film memristor synapses. These designs are implemented using a static threshold activation function, limiting the set of learnable functions to be linearly separable. In this work, we propose two NLB designs-robust adaptive NLB (RANLB) and multithreshold NLB (MTNLB)-which overcome this limitation by allowing the effective activation function to be adapted during the training process. Consequently, both designs enable any logic function to be implemented in a single-layer NLB network. The proposed NLBs are designed, simulated, and trained to implement ISCAS-85 benchmark circuits, as well as OCR. The MTNLB achieves 90 percent improvement in the energy delay product (EDP) over lookup table (LUT)-based implementations of the ISCAS-85 benchmarks and up to a 99 percent improvement over a previous NLB implementation. As a compromise, the RANLB provides a smaller EDP improvement, but has an average training time of only ≈ 4 cycles for 4-input logic functions, compared to the MTNLBs ≈ 8-cycle average training time.
miR-205 Exerts Tumor-Suppressive Functions in Human Prostate through Down-regulation of Protein Kinase Cε (2009)

Limited information is available concerning the expression and role of microRNAs in prostate cancer. In this study, we investigated the involvement of miR-205 in prostate carcinogenesis. Significantly lower miR-205 expression levels were found in cancer than in normal prostate cell lines as well as in tumor compared with matched normal prostate tissues, with a particularly pronounced reduction in carcinomas from patients with local-regionally disseminated disease. Restoring the expression of miR-205 in prostate cancer cells resulted in cell rearrangements consistent with a mesenchymal-to-epithelial transition, such as up-regulation of E-cadherin and reduction of cell locomotion and invasion, and in the down-regulation of several oncogenes known to be involved in disease progression (i.e., interleukin 6, caveolin-1, EZH2). Our evidence suggests that these events are driven by the concurrent repression of specific predicted miR-205 targets, namely N-chimaerin, ErbB3, E2F1, E2F5, ZEB2, and protein kinase Cepsilon. Strikingly, the latter seemed to play a direct role in regulating epithelial-to-mesenchymal transition. In fact, its down-regulation led to a cell phenotype largely reminiscent of that of cells ectopically expressing miR-205. Overall, we showed for the first time that miR-205 exerts a tumor-suppressive effect in human prostate by counteracting epithelial-to-mesenchymal transition and reducing cell migration/invasion, at least in part through the down-regulation of protein kinase Cepsilon.
Source Expertise and Persuasion (2011)

Compared to nonexperts, expert sources have been considered to elicit more processing of persuasive messages because of expectations that the information is likely to be valid or accurate. However, depending on the position of an advocacy, source expertise could activate other motives that may produce a very different relation from that found in past research. When messages are counterattitudinal (disagreeable), experts should motivate greater processing than nonexpert sources because of expectations that they will likely provide robust opposition to one's existing views. In contrast, when advocacies are proattitudinal (agreeable), nonexpert rather than expert sources should elicit more scrutiny because of perceptions that they will likely provide inadequate support to recipients' current views. Two studies offer evidence consistent with these predictions. Manipulations of source expertise created different expectations regarding the strength of opposition or support, and these perceptions accounted for effects of source expertise on the amount of message scrutiny.
Reconstruction of dynamic 3-D structures of biological objects using stereo microscopy (2002)

The authors address the analysis of three dimensional shape and shape change in nonrigid biological objects imaged via a stereo light microscope (SLM). Most existing stereo or motion analysis techniques cannot be applied to microscopic biological images because they usually lack salient features. The authors propose an integrated approach for the reconstruction of 3D structures and motion analysis for scenes where only a few informative features are available. The key components of this framework are: (1) image registration, (2) region-of-interest extraction, and (3) stereo and motion analysis using a cooperative spatial and temporal matching process. The authors describe these three stages of processing and illustrate the efficacy of the proposed approach using real images of a live frog's ventricle. The reconstructed dynamic 3-D structures of the ventricle are demonstrated in the authors' experimental results.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Distributed Data Mining: The JAM system architecture (2001)

This paper describes the system architecture of JAM (Java Agents for Meta-learning), a distributed data mining system that scales up to large and physically separated data sets. An earlyversion of the JAM system was described in Stolfo-et-al-97-KDD-JAM. Since then, JAM has evolved both architecturally and functionally and here we present the final design and implementation details of this system architecture. JAM is an extensible agent-based distributed data mining system that supports the remote dispatch and exchange of agents among participating datasites and employs meta-learning techniques to combine the multiple models that are learned. One of JAM's target applications is fraud and intrusion detection in financial information systems. A brief description of this learning task and JAM's applicability and summary results are also discussed.
Dysbaric Osteonecrosis (Caisson Disease of Bone): are Active Oxygen Species and the Endocrine System Responsible, and Can Control of the Production of Free Radicals and Their Reaction Products Confer Protection? (1987)

The development of osteonecrosis after exposure to altered air pressures is consistent with cellular injury brought about by active oxygen species. The syndrome is considered to arise as a result of an unusual combination of circumstances in which hyperoxia itself, together with the additive responses of the endocrine system to hyperoxia, hypothermia and exertion, each appear to play a part; the net result is thought to increase the mitochondrial generation of superoxide. It is suggested that effective prophylaxis may be possible primarily by establishing a nutritional status that is adequate to ensure that the functional activities of radical-scavenging systems are not hampered by deficiencies either of essential trace elements or of vitamin E. Pharmacological pretreatments designed both to decrease excessive levels of superoxide through increased catalysis of anionic dismutation and to attenuate enzyme-dependent peroxidation may provide an additional line of defence.
Shape control of large lightweight mirrors with dielectric elastomer actuation (2003)

Space-based astronomy and remote sensing systems would benefit from extremely large aperture mirrors that can permit greater-resolution images. To be cost effective and practical, such optical systems must be lightweight and capable of deployment from highly compacted stowed configurations. Such gossamer mirror structures are likely to be very flexible and therefore present challenges in achieving and maintaining the required optically precise shape. Active control based on dielectric elastomers was evaluated in order to address these challenges. Dielectric elastomers offer potential advantages over other candidate actuation technologies including high elastic strain, low power dissipation, tolerance of the space environment, and ease of commercial fabrication into large sheets. The basic functional element of dielectric elastomer actuation is a thin polymer film coated on both sides by a compliant electrode material. When voltage is applied between electrodes, a compressive force squeezes the film, causing it to expand in area. We have explored both material survivability issues and candidate designs of adaptive structures that incorporate dielectric elastomer actuation. Experimental testing has shown the operation of silicone-based actuator layers over a temperature range of -100 °C to 260 °C, suitable for most earth orbits. Analytical (finite element) and experimental methods suggested that dielectric elastomers can produce the necessary shape change when laminated to the back of a flexible mirror or incorporated into an inflatable mirror. Interferometric measurements verified the ability to effect controllable shape changes less than the wavelength of light. In an alternative design, discrete polymer actuators were shown to be able to control the position of a rigid mirror segment with a sensitivity of 1800 nm/V, suggesting that sub-wavelength position control is feasible. While initial results are promising, numerous technical challenges remain to be addressed, including the development of shape control algorithms, the fabrication of optically smooth reflective coatings, consideration of dynamic effects such as vibration, methods of addressing large-numbers of active areas, and stowability and deployment schemes.
Assessment of ear length and low set ears in newborn infants. (1983)

In order to define normal values for ear length and position in the newborn infant, 198 (87 term and 111 preterm) infants were examined. In every case gestational age was determined chronologically and clinically. Ear length was measured from the superior to the inferior aspects of the ear. Using a horizontal line passing through the inner canthi of the eyes the portion of the ear above this line was measured, determining the position of the ear by its relation to total ear length. Normal values are presented by plotting the mean +/- 2 SD versus the gestational age. Small ears and low set ears are defined as values less than the mean -2 SD.
SyntaxSQLNet: Syntax Tree Networks for Complex and Cross-DomainText-to-SQL Task (2018)

Most existing studies in text-to-SQL tasks do not require generating complex SQL queries with multiple clauses or sub-queries, and generalizing to new, unseen databases. In this paper we propose SyntaxSQLNet, a syntax tree network to address the complex and cross-domain text-to-SQL generation task. SyntaxSQLNet employs a SQL specific syntax tree-based decoder with SQL generation path history and table-aware column attention encoders. We evaluate SyntaxSQLNet on the Spider text-to-SQL task, which contains databases with multiple tables and complex SQL queries with multiple SQL clauses and nested queries. We use a database split setting where databases in the test set are unseen during training. Experimental results show that SyntaxSQLNet can handle a significantly greater number of complex SQL examples than prior work, outperforming the previous state-of-the-art model by 7.3% in exact matching accuracy. We also show that SyntaxSQLNet can further improve the performance by an additional 7.5% using a cross-domain augmentation method, resulting in a 14.8% improvement in total. To our knowledge, we are the first to study this complex and cross-domain text-to-SQL task.
Cyclisations of ortho-substituted N-arylbenzimidoyl nitrenes. Part 1. Cyclisations with ortho-alkyl substituents: skeletal rearrangements and [1,9]alkyl migrations (1979)

Photolysis of the N-(N-arylbenzimidoyl)sulphimides (2a)–(2c) and (2e), in which the ortho-positions of the N-aryl group carry alkyl substituents, gives the cyclopenta[d]pyrimidines (8), together with the carbodi-imides (6). Photolysis of the corresponding tetrazoles (3) gives the same products. The cyclopenta[d]pyrimidines and carbodi-imides are also produced when the tetrazoles (3), and the oxadiazolone (5), are subjected to flash vacuum pyrolysis. It is proposed that the cyclopenta[d]pyrimidines are formed by cyclisation of N-arylbenzimidoyl nitrene intermediates to give 3aH-benzimidazoles, which then undergo skeletal rearrangement by successive [1,5]-vinyl and -imidoyl shifts. 1-(2-Methyl-1-naphthyl)-5-phenyltetrazole (4) undergoes an analogous reaction when photolysed, giving the pyrimidine (13).In the flash pyrolysis of the tetrazoles (3) and the oxadiazolone (5), benzimidazoles are also isolated in low yields. These products can also be accounted for by postulating the intermediacy of 3aH -benzimidazoles, which subsequently undergo [1,9] methyl shifts, or, with tetrazole (3c), elimination of formaldehyde.
Phytate and phytase: consequences for protein utilisation (2000)

The excretion of large amounts of P in effluent from intensive pig and poultry units is indicative of the poor availability of phytate-bound P in plant-derived feed ingredients. This environmental problem prompted the development and acceptance of microbial phytase feed enzymes for single-stomached animals. Their introduction led to an increasing recognition that phytate may have adverse effects on protein utilisation in addition to P. Consequently, the nutritional relevance of protein-phytate interactions for pigs and poultry is considered in the present review. Since the current understanding of the effects of protein-phytate interactions comes mainly from responses obtained to added phytase, literature on the influence of microbial phytases on amino acid digestibility and utilisation is summarised, followed by a discussion of possible mechanisms contributing to the negative effects of phytate. However, the rationale for the protein responses to added phytase remains largely speculative, and several modes of action are probably involved. It may be that the release of protein from protein-phytate complexes occurring naturally in feed ingredients, the prevention of formation of binary and ternary protein-phytate complexes within the gut, the alleviation of the negative impact of phytate on digestive enzymes and the reduction in endogenous amino acid losses are all contributing factors. A better understanding of the mechanisms of protein-phytate interactions and the modes of action of exogenous phytase enzymes is clearly desirable. Studies are also needed to identify and quantify the factors that contribute to the variable amino acid responses to added phytase. It appears that the relative solubilities of phytate salts and proteins from different feed ingredients and their effects on the extent of protein-phytate complex formation, coupled with variations in the effectiveness of phytase in different dietary contexts, may be the major factors responsible.
CGARS: cancer genome analysis by rank sums (2014)

We applied our approach to recently published datasets of small-cell lung cancer and squamous cell lung cancer and validated its performance by comparing the results to an orthogonal approach. In addition, we found a new deletion peak containing the HLA-A gene in squamous cell lung cancer.
A model-based registration approach of preoperative MRI with 3D ultrasound of the liver for Interventional guidance procedures (2012)

In this paper, we present a novel approach to rigidly register intraoperative electromagnetically tracked ultrasound (US) with pre-operative contrast-enhanced magnetic resonance (MR) images. The clinical rationale for this work is to allow accurate needle placement during thermal ablations of liver metastases using multimodal imaging. We adopt a model-based approach that rigidly matches segmented liver surface shapes obtained from the multimodal image volumes. Towards this end, a shape-constrained deformable surface model combining the strengths of both deformable and active shape models is used to segment the liver surface from the MR scan. It incorporates a priori shape information while external forces guide the deformation and adapts the model to a target structure. The liver boundary is extracted from US by merging a dynamic region-growing method with a graph-based segmentation framework anchored on adaptive priors of neighboring surface points. Registration is performed with a weighted ICP algorithm with a physiological penalizing term. The MR segmentation model was trained with 30 datasets and validated on a separate cohort of 10 patients with corresponding ground truth. The accuracy and robustness of the method were assessed by registering four US/MR datasets, yielding accurate landmark registration errors (3.7 ± 0.69mm) and high robustness, and is thus acceptable for radiofrequency clinical applications.
Blockchain-Based Mobile Edge Computing Framework for Secure Therapy Applications (2018)

Mobile edge computing (MEC) is being introduced and leveraged in many domains, but few studies have addressed MEC for secure in-home therapy management. To this end, this paper presents an in-home therapy management framework, which leverages the IoT nodes and the blockchain-based decentralized MEC paradigm to support low-latency, secure, anonymous, and always-available spatiotemporal multimedia therapeutic data communication within an on-demand data-sharing scenario. To the best of our knowledge, this non-invasive, MEC-based IoT therapy platform is first done by our group. This platform can provide a full-body joint range of motion data for physically challenged individuals in a decentralized manner. With MEC, the framework can provide therapy diagnostic and analytical data on demand to a large portion of humanity who are either born with disabilities or became disabled due to accidents, war-time injuries, or old age. For security, the framework uses blockchain–Tor-based distributed transactions to preserve the therapeutic data privacy, ownership, generation, storage, and sharing. Our initial test results from a complete implementation of the framework show that it can support a sufficiently large number of users without considerable increase in mean processing time.