gebhart/patrepeval huggingface dataset:
Exploration of a Heterogeneous Concentrated-Sparse On-Chip Interconnect for Energy Efficient Multicore Architecture (2014)

We present a novel heterogeneous on-chip interconnect, concentrated-sparse mesh, suitable for high efficiency multicore architectures. The topology is implemented by taking the advantages of both concentrated mesh and sparse mesh networks. The object of the proposed heterogeneous network is to improve performance of the system when running real applications with self-similar, hot-spot and bursty traffic. While regular mesh network has been used widely in on-chip interconnect, concentrated mesh improves average network latency by reducing the number of intermediate network resources. However with high traffic requirements, the limited network bandwidth leads to congestion and performance bottleneck. On the other hand, sparse mesh improves network bandwidth by increasing the number of routers and links, therefore the network can process more hot-spot and bursty traffic than regular and concentrated mesh networks. The weakness of sparse mesh is that, with low traffic injection, the network latency of packets can be higher than other networks. Furthermore the size of the interconnect can become unrealistic for large systems. The proposed heterogeneous interconnect utilizes two networks for processing different traffic. We explore and discuss traffic injection behaviour of several applications. The heterogeneous network is analyzed in details. We investigate a routing algorithm and a mapping algorithm designed for the proposed network. Comparative results are provided by using a full system simulation environment. Results demonstrate that the proposed interconnect improves the average network latency and energy delay product by 15.7% and 44.7%, respectively, compared with regular mesh network.
Phase 1 First‐in‐Human, Single‐ and Multiple‐Ascending Dose, and Food Effect Studies to Assess the Safety, Tolerability, and Pharmacokinetics of Presatovir for the Treatment of Respiratory Syncytial Virus Infection (2018)

Respiratory syncytial virus (RSV)-associated respiratory tract infection is a leading cause of hospitalizations in infants for which no effective treatment exists. RSV infection is also an important cause of respiratory disease in adults and immunocompromised patients. Presatovir (GS-5806) is an orally bioavailable antiviral agent that inhibits fusion of RSV with host cell membranes. Here, results from 2 phase 1 studies that evaluated safety, tolerability, and pharmacokinetics of presatovir in healthy adults following administration of single and multiple (7 days) once- or twice-daily ascending doses (first-in-human study) and in the presence or absence of food (food effect study) are described. Presatovir exhibited favorable safety and pharmacokinetic profiles that supported once-daily dosing. Presatovir exposure increased in an approximately dose-proportional manner across the evaluated dose range (single doses 25-300 mg; multiple doses 10-75 mg once daily for 7 days). Administration of presatovir with a high-fat meal did not alter exposure, supporting administration without regard to a meal in further clinical studies. These data were subsequently used to inform presatovir dosing regimens in a phase 2a challenge study of adults experimentally infected with RSV. Collectively, results from phase 1 evaluations and a phase 2a challenge study support further clinical investigation of presatovir for the treatment of RSV infection.
Valuating service transformation alternatives using real options (2008)

Firms that grow through mergers and acquisitions often need to deal with duplicate and disparate business functions. Recently, 'shared services' is emerging as an innovative approach for addressing this challenge. Shared services is a business model in which a centralized workforce, either created in-house or provided by external vendors, performs common functions for multiple business units of a firm. To implement shared services, firms need to transform their IT and business processes through simplification, standardization, consolidation, insourcing, and/or outsourcing. In order to decide whether and how to implement shared services, firms need to estimate the value of different transformation alternatives. Conventional valuation approaches tend to focus on foreseeable cost savings and cannot adequately capture critical aspects such as managerial flexibility that may be embedded in certain types of transformation. In this work, we draw upon existing research in IT service, finance, and strategy, and introduce a novel valuation methodology that can help firms evaluate different transformation alternatives. The methodology is centered on a conceptual map for identifying transformation alternatives and a real-option based model that quantifies the value of managerial flexibility. We illustrate the methodology using a real-life based case study.
Anneal-less domain wall displacement detection of 15-Gbit/in2land-groove recording using a deep groove substrate and a red laser (2003)

Domain Wall Displacement Detection (DWDD) medium with no annealing method, which we call "anneal-less" DWDD medium, has been improved for practical use. The key technologies of our progress are not only an optimum design of the magnetic film structure but also a deep groove substrate for land-groove recording with a quite unique groove form. The substrate was prepared by using the mastering process with a reactive ion etching (RIE) method. We achieved 15 Gbit/in<sup>2</sup>-areal density with wide system tolerances using the anneal-less DWDD medium, a 660nm-laser and a 0.60 NA objective lens. The areal density corresponds to 4.7 GB-capacity on a disc like MiniDisc (MD) wiht a 64 mm-diameter.
Dependency-Aware Named Entity Recognition with Relative and Global Attentions (2019)

Named entity recognition is one of the core tasks in NLP. Although many improvements have been made on this task during the last years, the state-of-the-art systems do not explicitly take into account the recursive nature of language. Instead of only treating the text as a plain sequence of words, we incorporate a linguistically-inspired way to recognize entities based on syntax and tree structures. Our model exploits syntactic relationships among words using a Tree-LSTM guided by dependency trees. Then, we enhance these features by applying relative and global attention mechanisms. On the one hand, the relative attention detects the most informative words in the sentence with respect to the word being evaluated. On the other hand, the global attention spots the most relevant words in the sequence. Lastly, we linearly project the weighted vectors into the tagging space so that a conditional random field classifier predicts the entity labels. Our findings show that the model detects words that disclose the entity types based on their syntactic roles in a sentence (e.g., verbs such as speak and write are attended when the entity type is PERSON, whereas meet and travel strongly relate to LOCATION). We confirm our findings and establish a new state of the art on two datasets.
Application sensitive energy management framework for storage systems (2016)

Rapidly escalating energy and cooling costs of storage systems have become a concern for data centers. In response, a multitude of energy saving approaches that take into account storage-device-level input/output (I/O) behaviors has been proposed. The trouble is that critical applications are in constant operation at data centers, and the conventional approaches do not produce sufficient energy savings. It may be possible to dramatically reduce storage energy consumption without degrading application performance levels by utilizing application level I/O behaviors. However, such behaviors differ from one application to another, and it would be too expensive to tailor methods to individual applications. We propose a universal storage energy management framework for runtime storage energy savings that can be applied to any type of application. The results of evaluations show that the use of this framework results in substantive energy savings compared with the traditional approaches.
A 3mm2 Programmable Bayesian Inference Accelerator for Unsupervised Machine Perception using Parallel Gibbs Sampling in 16nm (2020)

This paper describes a 16nm programmable accelerator for unsupervised probabilistic machine perception tasks that performs Bayesian inference on probabilistic models mapped onto a 2D Markov Random Field, using MCMC. Exploiting two degrees of parallelism, it performs Gibbs sampling inference at up to 1380× faster with 1965× less energy than an Arm Cortex-A53 on the same SoC, and 1.5× faster with 6.3× less energy than an embedded FPGA in the same technology. At 0.8V, it runs at 450MHz, producing 44.6 MSamples/s at 0.88 nJ/sample.
Ultra-Short High-Efficiency Power-Function Waveguide Tapers for Micro-Photonic Applications (2008)

A series of power-function shaped tapers are analyzed. Optimized design can achieve 99% transmission for 4μm to 0.3 μm mode conversion with 9.95 μm taper, which saves 85% of the length compared with conventional straight tapers.
Preparation and characterization of bioadhesive grafted starch copolymers as platforms for controlled drug delivery (2002)

Abstract 60 Co‐gamma‐radiation and ceric ammonium nitrate (CAN) redox‐induced graft polymerization of acrylic monomers (acrylonitrile, acrylic acid, and methyl acrylate) to starch was performed to produce drug‐delivery systems. The grafted starches obtained mainly by redox‐induced polymerization were characterized by chemical and physicochemical methods, and the nature and size of the polyacrylic moiety grafted to the starch were determined. Although the choice of grafting method depended in part on the particular monomer, only copolymers obtained by gamma radiation proved to be satisfactory drug delivery systems. Changes of parameters in the gamma radiation–induced polymerization, such as radiation times and changes in the amount of starch and/or acrylic monomers, were tested in terms of the release rate of model drug compounds. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 86: 1157–1162, 2002
(Iodomethyl)trimethylsilane (2014)

[4206-67-1] C4H11ISi (MW 214.12) 1S/C4H11ISi/c1-6(2,3)4-5/h4H2,1-3H3 InChIKey = VZNYXGQMDSRJAL-UHFFFAOYSA-N (electrophile for the preparation of allylsilanes2 and propargylsilanes;3 forms carbon alkylation adducts useful for alkene synthesis;4 alkylation adducts are frequently a source of fluoride-induced reactive intermediates, forming nitrogen5 and sulfur6 alkylation adducts that function as ylide precursors; readily undergoes metal–halogen exchange to generate a reagent for Peterson methylenation7) Alternate Name: trimethylsilylmethyl iodide. Physical Data: bp 140–142 °C; d 1.442 g cm−3. Form Supplied in: colorless liquid; widely available. Handling, Storage, and Precautions: highly flammable liquid; corrosive; irritant; should be stored cold, protected from light, and stabilized with copper metal. Handle in a fume hood.
Mask parameter variation in the context of the overall variation budget of an advanced logic wafer fab (2009)

Within our paper we are going to discuss the variation within the patterning process in the context of the overall electrical parameter variation in an advanced logic Fab. The evaluation is based on both the variation of ring oscillators that are distributed across the chip as well as on local variation of matched transistor pairs. Starting with a view back to the 130nm technology, we will show how things and requirements changed over time. In particular we focus on the gate layer where we do a detailed ACLV-comparison from the 130nm technology node down to today's 45nm node. Within the patterning variation we keep special attention on the mask performance. Within that section, we do a detailed wafer-mask correlation analysis. Additionally to the low-MEEF gate layer we show the importance of the mask CD-performance for a typical high MEEF-layer. Finally, we discuss the mask contribution to the overall overlay error for the most critical contact to gate overlay. In all of the cases, we will show that the mask performance is not the limiter within today's most advanced technology, as long as we get access to a world class mask shop.
Phenyl Hydrazine as Initiator for Direct Arene C–H Arylation via Base Promoted Homolytic Aromatic Substitution (2013)

A simple and efficient direct radical arylation of unactivated arenes is described which uses cheap and commercially available phenyl hydrazine as an initiator. The reaction occurs through a base promoted homolytic aromatic substitution (BHAS) mechanism involving aryl radicals and aryl radical anions as intermediates and offers a practical approach for preparation of an array of substituted biaryls.
ChemInform Abstract: Targeted Cancer Therapy: Conferring Specificity to Cytotoxic Drugs (2008)

Abstract ChemInform is a weekly Abstracting Service, delivering concise information at a glance that was extracted from about 200 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.
The PARIS Ocean Altimeter In-Orbit Demonstrator (2011)

Mesoscale ocean altimetry remains a challenge in satellite remote sensing. Conventional nadir-looking radar altimeters can make observations only along the satellite ground track, and many of them are needed to sample the sea surface at the required spatial and temporal resolutions. The Passive Reflectometry and Interferometry System (PARIS) using Global Navigation Satellite Systems (GNSS) reflected signals was proposed as a means to perform ocean altimetry along several tracks simultaneously spread over a wide swath. The bandwidth limitation of the GNSS signals and the large ionospheric delay at L-band are however issues which deserve careful attention in the design and performance of a PARIS ocean altimeter. This paper describes such an instrument specially conceived to fully exploit the GNSS signals for best altimetric performance and to provide multifrequency observations to correct for the ionospheric delay. Furthermore, an in-orbit demonstration mission that would prove the expected altimetric accuracy suited for mesoscale ocean science is proposed.
ChemInform Abstract: Reaction of 2‐(6‐Hydroxyspiro(4.5)dec‐6‐yl)alkanoic Acids with Aldehydes. (1987)

Abstract The reaction of the title acid (Ia) with trioxane (II) or the aldehydes (IV) at 25 °C yields the tricyclic compounds (III) and (V).
Effectiveness of augmented-reality visualization versus cognitive mediation for learning actions in near space (2008)

The present study examined the impact of augmented-reality visualization, in comparison to conventional ultrasound (CUS), on the learning of ultrasound-guided needle insertion. Whereas CUS requires cognitive processes for localizing targets, our augmented-reality device, called the “sonic flashlight” (SF) enables direct perceptual guidance. Participants guided a needle to an ultrasound-localized target within opaque fluid. In three experiments, the SF showed higher accuracy and lower variability in aiming and endpoint placements than did CUS. The SF, but not CUS, readily transferred to new targets and starting points for action. These effects were evident in visually guided action (needle and target continuously visible) and visually directed action (target alone visible). The results have application to learning to visualize surgical targets through ultrasound.
Single R-Group Polymorphisms (SRPs) and R-Cliffs: An Intuitive Framework for Analyzing and Visualizing Activity Cliffs in a Single Analog Series (2011)

We introduce Single R-Group Polymorphisms (SRPs, pronounced 'sharps'), an intuitive framework for analyzing substituent effects and activity cliffs in a single congeneric series. A SRP is a pair of compounds that differ only in a single R-group position. Because the same substituent pair may occur in multiple SRPs in the series (i.e., with different combinations of substituents at the other R-group positions), SRP analysis makes it easy to identify systematic substituent effects and activity cliffs at each point of variation (R-cliffs). SRPs can be visualized as a symmetric heatmap where each cell represents a particular pair of substituents color-coded by the average difference in activity between the compounds that contain that particular SRP. SRP maps offer several advantages over existing techniques for visualizing activity cliffs: 1) the chemical structures of all the substituents are displayed simultaneously on a single map, thus directly engaging the pattern recognition abilities of the medicinal chemist; 2) it is based on R-group decomposition, a natural paradigm for generating and rationalizing SAR; 3) it uses a heatmap representation that makes it easy to identify systematic trends in the data; 4) it generalizes the concept of activity cliffs beyond similarity by allowing the analyst to sort the substituents according to any property of interest or place them manually in any desired order.
Use of dielectrophoresis for directing T cells to microwells before nanostraw transfection: modelling and experiments (2022)

Nanostraw substrates have great potential for achieving minimally invasive cell transfection. Cells located on the nanostraw substrate are subjected to mild DC electric pulses applied across the nanostraw substrate, which open pores in the cell membrane on top of the nanostraws and drives charged cargo through these pores <i>via</i> electrophoresis. However, with this method, the current may leak through uncovered nanostraws, thereby decreasing the desired effect in the cell-covered nanostraws. A minimization of the number of uncovered nanostraws could be achieved by high cell coverage, but this is challenging when working with small cell populations. Nanostraw substrates of smaller area could be covered by smaller cell populations but are hard to integrate into fluidics systems. Here, we use simulations and experiments to show that this issue can be addressed by covering the nanostraw substrate with an insulating layer containing pores of similar size to cells. The pores act as traps into which cells can be guided using dielectrophoresis, ensuring a high degree of occupancy while maintaining a high cell viability, even if the total number of cells is low.
A combined structural dynamics approach identifies a putative switch in factor VIIa employed by tissue factor to initiate blood coagulation (2007)

Coagulation factor VIIa (FVIIa) requires tissue factor (TF) to attain full catalytic competency and to initiate blood coagulation. In this study, the mechanism by which TF allosterically activates FVIIa is investigated by a structural dynamics approach that combines molecular dynamics (MD) simulations and hydrogen/deuterium exchange (HX) mass spectrometry on free and TF-bound FVIIa. The differences in conformational dynamics from MD simulations are shown to be confined to regions of FVIIa observed to undergo structural stabilization as judged by HX experiments, especially implicating activation loop 3 (residues 365-374{216-225}) of the so-called activation domain and the 170-loop (residues 313-322{170A-175}) succeeding the TF-binding helix. The latter finding is corroborated by experiments demonstrating rapid deglycosylation of Asn322 in free FVIIa by PNGase F but almost complete protection in the presence of TF or an active-site inhibitor. Based on MD simulations, a key switch of the TF-induced structural changes is identified as the interacting pair Leu305{163} and Phe374{225} in FVIIa, whose mutual conformations are guided by the presence of TF and observed to be closely linked to the structural stability of activation loop 3. Altogether, our findings strongly support an allosteric activation mechanism initiated by the stabilization of the Leu305{163}/Phe374{225} pair, which, in turn, stabilizes activation loop 3 and the S(1) and S(3) substrate pockets, the activation pocket, and N-terminal insertion.
Titanium Dioxide-Based Hybrid Ion-Exchange Media for Simultaneous Removal of Arsenic and Nitrate (2013)

The goal of this study was to develop an inexpensive and easy to fabricate titanium dioxide-based hybrid ion-exchange media (Ti-HIX) and assess its potential to remove arsenic and nitrate from water. Different Ti-HIX media were fabricated via in-situ formation of TiO2 nanoparticles within the pores of three different commercially IX resins; the Ti-HIX media were characterized; and the arsenic and nitrate removal potential of the most economically feasible Ti-HIX media was assessed in model water under batch pseudo-equilibrium conditions. The Ti-HIX media were characterized with content ranging between 11% and 21% TiO2 per media dry mass. The TiO2 exhibited form of anatase nanoparticles. The Freundlich adsorption intensity parameters (1/n) for all the Ti-HIX media were < 1 implying favorable adsorption for arsenic. The estimated maximum adsorption capacity for arsenic expressed per mass of titanium ranged between 16.6 mgAs g–1 Ti, 24.9 mgAs g–1Ti, and 27.3 for different types of tested Ti-HIX media, and was several fold higher than similar reported values in the literature. Nitrate removal performance of the base ion-exchange resins used in synthesis of the Ti-HIX media was not adversely impacted by the synthesis process.
Learning-Based Adaptive Imputation Methodwith kNN Algorithm for Missing Power Data (2017)

This paper proposes a learning-based adaptive imputation method (LAI) for imputing missing power data in an energy system. This method estimates the missing power data by using the pattern that appears in the collected data. Here, in order to capture the patterns from past power data, we newly model a feature vector by using past data and its variations. The proposed LAI then learns the optimal length of the feature vector and the optimal historical length, which are significant hyper parameters of the proposed method, by utilizing intentional missing data. Based on a weighted distance between feature vectors representing a missing situation and past situation, missing power data are estimated by referring to the k most similar past situations in the optimal historical length. We further extend the proposed LAI to alleviate the effect of unexpected variation in power data and refer to this new approach as the extended LAI method (eLAI). The eLAI selects a method between linear interpolation (LI) and the proposed LAI to improve accuracy under unexpected variations. Finally, from a simulation under various energy consumption profiles, we verify that the proposed eLAI achieves about a 74% reduction of the average imputation error in an energy system, compared to the existing imputation methods.
Method for Detecting Nanoparticles on Cuttings Recovered from a Gas Reservoir (2021)

Mud logging is frequently performed during oil and gas operations for determining the position of hydrocarbons and accurately assessing the geophysical properties of the formation based on the study of returned drill cuttings. The successful application of an advanced mud logging analysis depends on an accurate determination of the depth where the drill cuttings were generated. We have envisioned an improved accuracy of cuttings’ depth assignment via labeling the drill cuttings with barcoded polymeric nanoparticles (NPs) when they are generated at the drill bit. However, the detection of NPs at sub-ppm levels in very complex and viscous drilling muds is a challenge. This paper reports a unique workflow comprising cleaning, solvent extraction, thermal separation, and pyrolysis-gas chromatography–mass spectrometry (Py-GCMS) detection of polymeric NPs in the drilling mud and on the collected drill cuttings. Applying this workflow to the drill cuttings successfully removes most GCMS matrix interferences generated from the drilling mud. Our method has unambiguously detected and quantified nanograms of NPs on the cuttings recovered from a field test that probed the injection of ppm levels of the NPs into the drilling fluid while drilling a carbonate gas well.