gebhart/patrepeval huggingface dataset:
Characterization of vanY, a DD-carboxypeptidase from vancomycin-resistant Enterococcus faecium BM4147 (1992)

VanY is a protein with a molecular mass of 34.8 kDa encoded by vanY, a member of the high-level vancomycin resistance gene cluster found on plasmid pIP816 in Enterococcus faecium BM4147. Extracts from Escherichia coli JM83 bearing plasmid pAT383, which contains the vanY gene, were examined for enzymatic hydrolysis of peptidoglycan precursors. VanY was associated with the cell membranes and cleaved the C-terminal D-alanine residue of UDP-muramyl-pentapeptide but did not display transpeptidase or beta-lactamase activities. The DD-carboxypeptidase activity was not inhibited by beta-lactam antibiotics. VanY released the C-terminal D-hydroxy acid from depsipeptides produced by the vancomycin resistance protein VanA. These results demonstrate that VanY should contribute in vivo to the hydrolysis of both the D-alanyl-D-alanine- and the depsipeptide-containing peptidoglycan precursors.
Small Molecules Dorsomorphin and LDN-193189 Inhibit Myostatin/GDF8 Signaling and Promote Functional Myoblast Differentiation (2014)

GDF8, or myostatin, is a member of the TGF-β superfamily of secreted polypeptide growth factors. GDF8 is a potent negative regulator of myogenesis both in vivo and in vitro. We found that GDF8 signaling was inhibited by the small molecule ATP competitive inhibitors dorsomorphin and LDN-193189. These compounds were previously shown to be potent inhibitors of BMP signaling by binding to the BMP type I receptors ALK1/2/3/6. We present the crystal structure of the type II receptor ActRIIA with dorsomorphin and demonstrate that dorsomorphin or LDN-193189 target GDF8 induced Smad2/3 signaling and repression of myogenic transcription factors. As a result, both inhibitors rescued myogenesis in myoblasts treated with GDF8. As revealed by quantitative live cell microscopy, treatment with dorsomorphin or LDN-193189 promoted the contractile activity of myotubular networks in vitro. We therefore suggest these inhibitors as suitable tools to promote functional myogenesis.
Scaling Challenges for Advanced CMOS Devices (2017)

The economic health of the semiconductor industry requires substantial scaling of chip power, performance, and area with every new technology node that is ramped into manufacturing in two year intervals. With no direct physical link to any particular design dimensions, industry wide the technology node names are chosen to reflect the roughly 70% scaling of linear dimensions necessary to enable the doubling of transistor density predicted by Moore’s law and typically progress as 22nm, 14nm, 10nm, 7nm, 5nm, 3nm etc. At the time of this writing, the most advanced technology node in volume manufacturing is the 14nm node with the 7nm node in advanced development and 5nm in early exploration. The technology challenges to reach thus far have not been trivial. This review addresses the past innovation in response to the device challenges and discusses in-depth the integration challenges associated with the sub-22nm non-planar finFET technologies that are either in advanced technology development or in manufacturing. It discusses the integration challenges in patterning for both the front-end-of-line and back-end-of-line elements in the CMOS transistor. In addition, this article also gives a brief review of integrating an alternate channel material into the finFET technology, as well as next generation device architectures such as nanowire and vertical FETs. Lastly, it also discusses challenges dictated by the need to interconnect the ever-increasing density of transistors.
Inferring Insertion Times and Optimizing Error Penalties in Time-decaying Bloom Filters (2019)

Current Bloom Filters tend to ignore Bayesian priors as well as a great deal of useful information they hold, compromising the accuracy of their responses. Incorrect responses cause users to incur penalties that are both application- and item-specific, but current Bloom Filters are typically tuned only for static penalties. Such shortcomings are problematic for all Bloom Filter variants, but especially so for Time-decaying Bloom Filters, in which the memory of older items decays over time, causing both false positives and false negatives. We address these issues by introducing inferential filters, which integrate Bayesian priors and information latent in filters to make penalty-optimal, query-specific decisions. We also show how to properly infer insertion times in such filters. Our methods are general, but here we illustrate their application to inferential time-decaying filters to support novel query types and sliding window queries with dynamic error penalties. We present inferential versions of the Timing Bloom Filter and Generalized Bloom Filter. Our experiments on real and synthetic datasets show that our methods reduce penalties for incorrect responses to sliding-window queries in these filters by up to 70% when penalties are dynamic.
<i>In vitro</i>characterization of<i>Trichophyton rubrum</i>and<i>T. mentagrophytes</i>biofilms (2014)

Dermatophytes are fungi responsible for a disease known as dermatophytosis. Biofilms are sessile microbial communities surrounded by extracellular polymeric substances (EPS) with increased resistance to antimicrobial agents and host defenses. This paper describes, for the first time, the characteristics of Trichophyton rubrum and T. mentagrophytes biofilms. Biofilm formation was analyzed by light microscopy, scanning electron microscopy (SEM) and confocal laser scanning microscopy (CLSM) as well as by staining with crystal violet and safranin. Metabolic activity was determined using the XTT reduction assay. Both species were able to form mature biofilms in 72 h. T. rubrum biofilm produced more biomass and EPS and was denser than T. mentagrophytes biofilm. The SEM results demonstrated a coordinated network of hyphae in all directions, embedded within EPS in some areas. Research and characterization of biofilms formed by dermatophytes may contribute to the search of new drugs for the treatment of these mycoses and might inform future revisions with respect to the dose and duration of treatment of currently available antifungals.
Opportunistic Feedback Reduction for Multiuser MIMO Broadcast Channel with Orthogonal Beamforming (2014)

For the multiuser multiple-input multiple-output downlink channel, users feedback their channel state information to help base station schedule users and improve system sum rate. This incurs a large aggregate feedback bandwidth which grows linearly with the number of users. In this paper, we propose a novel scheme to reduce feedback load in a scheduled downlink orthogonal beamforming system by allowing users to opportunistically determine the number of feedback bits to use according to multiple decision thresholds. Through theoretical analysis, we show that, while keeping the aggregate feedback load of the entire system constant regardless of the number of users, the proposed scheme almost achieves the optimal asymptotic sum rate scaling with respect to the number of users (i.e., the multiuser diversity). Specifically, given the number of thresholds, the proposed scheme can achieve a constant portion of the optimal sum rate achievable by the system in which all the users always feedback, and the remaining portion (i.e., the sum rate loss) decreases exponentially to zero as the number of thresholds increases. We further consider feedback design by minimizing the number of thresholds and allocating quantization bits. Simulation shows that the proposed scheme can reduce feedback load and utilize limited feedback bandwidth more effectively than the existing feedback methods.
A fuzzy variant of k-member clustering for collaborative filtering with data anonymization (2012)

Privacy preserving data mining is a promising approach for encouraging users to exploit the IT supports without fear of information leaks. k-member clustering is a basic technique for achieving k-anonymization, in which data samples are summarized so that any sample is indistinguishable from at least k - 1 other samples. This paper proposes a fuzzy variant of k-member clustering with the goal of improving the quality of data summarization with k-anonymity. Each k-member cluster is extracted considering the fuzzy membership degrees of samples, which are estimated based on the distance from clusters. The proposed anonymization method is also applied to collaborative filtering, in which the main task is estimation of the applicability of unevaluated items. Several experimental results demonstrate the characteristic features of the proposed anonymization method.
Deep Reinforcement Learning for Cybersecurity Assessment of Wind Integrated Power Systems (2020)

The integration of renewable energy sources (RES) is rapidly increasing in electric power systems (EPS). While the inclusion of intermittent RES coupled with the wide-scale deployment of communication and sensing devices is important towards a fully smart grid, it has also expanded the cyber-threat landscape, effectively making power systems vulnerable to cyberattacks. This article proposes a cybersecurity assessment approach designed to assess the cyberphysical security of EPS. The work takes into consideration the intermittent generation of RES, vulnerabilities introduced by microprocessor-based electronic information and operational technology (IT/OT) devices, and contingency analysis results. The proposed approach utilizes deep reinforcement learning (DRL) and an adapted Common Vulnerability Scoring System (CVSS) score tailored to assess vulnerabilities in EPS in order to identify the optimal attack transition policy based on $N-2$ contingency results, i.e., the simultaneous failure of two system elements. The effectiveness of the work is validated via numerical and real-time simulation experiments performed on literature-based power grid test cases. The results demonstrate how the proposed method based on deep $Q$ -network ($\text{D}Q\text{N}$ ) performs closely to a graph-search approach in terms of the number of transitions needed to find the optimal attack policy, without the need for full observation of the system. In addition, the experiments present the method's scalability by showcasing the number of transitions needed to find the optimal attack transition policy in a large system such as the Polish 2383 bus test system. The results exhibit how the proposed approach requires one order of magnitude fewer transitions when compared to a random transition policy.
THE PHYSIOLOGY AND EMERGING ROLES OF ANTIDIURETIC HORMONE (2002)

The antidiuretic hormone (ADH) vasopressin is a simple peptide hormone with a number of complex, essential physiological actions. It is becoming clear that this hormone is developing an important therapeutic role in a number of different conditions. These include vasodilatory shock due to sepsis or cardiac surgery, cardiac arrest, and prolonged/excessive bleeding caused by, for example, variceal haemorrhage. This article reviews the physiology of ADH relevant to these actions and scrutinises the evidence for its therapeutic applications.
Discontinuation of Dapoxetine Treatment in Patients With Premature Ejaculation: A 2-Year Prospective Observational Study (2017)

The treatment discontinuation rate of dapoxetine was very high. The main reasons for discontinuation were the cost and disappointment that treatment was required every time adequate sexual function was required. Park HJ, Park NC, Kim TN, et al. Discontinuation of Dapoxetine Treatment in Patients With Premature Ejaculation: A 2-Year Prospective Observational Study. Sex Med 2017;5:e99-e105.
Software for the analysis of DNA sequence elements of transcription (1997)

The detection of transcription control elements in DNA sequences became both more important and more complicated by the completion of the first full genome sequencing projects. Rapid evaluation of potential regulatory elements in large amounts of sequence data requires specific methods preferably available as user-friendly computer programs. However, many more algorithms and methods have been published than programs are available, creating problems for scientists who try to select an appropriate method for their needs from the literature. The Internet provides a worldwide and relatively easy access to computer software if the user knows where to look. One of the major problems remaining is how to find the appropriate software. We have compiled a guide detailing where software is available and what is to be expected in terms of interface and data compatibility with other programs. We also show results obtained with each program for several examples. The summarized features of each program should allow scientists to select quickly the method of their choice and inform them where to download the software.
Silicon high-resistivity-substrate millimeter-wave technology (1986)

The application of molecular beam epitaxy (MBE) and X-ray lithography for the fabrication of monolithic integrated millimeter-wave devices on high-resistivity silicon has been investigated. Process compatibility and the retention of high-resistivity characteristics were measured using the spreading resistance method and Hall measurements after various process steps. Microstrip resonators of ring and linear geometry were fabricated on 10 000 Ω.cm silicon substrates. For linear microstrip resonators, the attenuation was found to be less than 0.6 dB/cm at 90 GHz. A 95-GHz IMPATT oscillator circuit and a planar microstrip antenna array have been fabricated on highly insulating silicon substrates. For the oscillator, a combined monolithic-hybrid integration technique was used to attach the discrete IMPATT diode to the resonator circuit. The oscillator does not require tuning elements. Preliminary experimental results are 8 mW of output power with 0.2 percent efficiency at 95 GHz.
A containerized analytics framework for data and compute-intensive pipeline applications (2017)

The joint effort of scientific collaborations and the expanding data market creates demand for high-performance and data-intensive analytics infrastructures that can exploit the potential of heterogeneous multi-core architectures with dynamic and scalable execution environments. Contemporary approaches focus on developing efficient parallel application models, but lack the flexibility of efficiently integrating and utilizing native or accelerator-based code. In this work, we illustrate a novel approach on mending this shortcoming and offering seamless application integration into a highly versatile execution infrastructure. The centerpiece is a framework of containerized execution units and management thereof for satisfying the diverse requirements of data analytics pipelines and its stages. Containers not only ease distribution and deployment of applications, but, more importantly enable an efficient synthesis of different stage implementation variants aimed towards exploiting heterogeneous computing resources. Consequently, this approach allows the infrastructure to utilize mainstream data and compute-intensive techniques and paradigms to achieve the goal of efficient pipeline execution. We present our approach in form of a requirement analysis, a multi-tier architecture description, and deployment scenarios based on our current prototype implementation.
Chemical genomics: Functional analysis of orphan nuclear receptors in the regulation of bile acid metabolism (2001)

Chemical genomics is the name we have given to the analysis of gene function through use of small molecule chemical tools. Orphan nuclear receptors are ideally suited to this technique of functional analysis, since their activity as transcription factors is regulated by small hydrophobic ligands. GW4064 is a potent and selective nonsteroidal ligand for the nuclear bile acid receptor FXR (NR1H4). Using GW4064 as a chemical tool, we have identified genes regulated by FXR in the liver, including those involved in bile acid synthesis and transport. We have also discovered that PXR (NR1I2) is a lithocholic acid receptor that controls the biosynthesis and metabolism of bile acids. Together FXR and PXR cooperate to control biliary and urinary bile acid excretion. These functions suggest that potent PXR and FXR ligands may offer a new approach to the treatment of cholestatic liver disease.
SAMS Teach Yourself Microsoft Word 2000 in 10 Minutes (1999)

From the Publisher:
Sams Teach Yourself Microsoft Word 2000 in 10 Minutes is the book to help users get more productivity from Microsoft Word focusing on the 25% of Word features users use 95% of the time. For users that need to write reports or memos, letters or resumes, this book gets them up and running quickly. It gives them idea of what the application can do, and what features might be different from the last version. To accomplish this, the book presents the most fundamental Word tasks such as entering text, saving and loading documents, basic formatting, printer, etc. in a manner that be quickly absorbed and used. Improvements to this edition will also include adding and ensuring all examples use real-world material the reader can relate to and better using figures and notes to make the book as informative as possible.
GHz High-$Q$ Lateral Overmoded Bulk Acoustic-Wave Resonators Using Epitaxial SiC Thin Film (2012)

This letter presents the development of a lateral overmoded bulk acoustic-wave resonator (LOBAR) made out of epitaxial silicon carbide and piezoelectrically driven by an aluminum nitride transducer at radio frequencies. The 1.75-GHz SiC LOBAR constitutes a new class of resonant devices formed by a very small volume piezoelectric transducer on a high quality factor (Q) acoustic cavity. In operation, the AIN-based transducer excites multiple longitudinal vibrations in the SiC resonant cavity. A high Q of 4250 is obtained for a LOBAR with series resonances around 1.75 GHz. The impact of the AIN transducer coverage of the SiC cavity on device Q and impedance is also experimentally studied. Characterization of the LOBAR over temperature is performed to extrapolate the intrinsic loss limits in the epitaxial SiC. The integration of two materials, capable of offering high Q and high transduction efficiency in conjunction with their ability of sustaining operations at high temperature and in harsh environments, will enable the development of radio frequency microelectromechanical system components for a new realm of applications.
Stabilization of Cascaded DC/DC Converters via Adaptive Series-Virtual-Impedance Control of the Load Converter (2016)

It has been shown recently that a cascaded dc/dc converter system can be stabilized via amplitude compensation (SAC) or phase compensation (SPC) for the input impedance of the load converter. In this letter, it is shown that the cascaded system when adopting the SAC is unconditionally stable but conditionally stable when adopting the SPC, that is, SAC is more stable than SPC. Then, the comparison is carried out for the parallel-virtual-impedance (PVI) and series-virtual-impedance (SVI) control strategies that are adopted to implement the SAC, and it is found that only the SVI control strategy can achieve the SAC for the whole load and input voltage range of the load converter without limitation. Therefore, SVI is in general better than PVI when realizing SAC. Following on this, an adaptive mechanism is introduced to improve the traditional SVI control strategy so that the load converter can be stably connected to different source converters such as <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$LC$</tex-math></inline-formula> input filters and traditional dc/dc converters. Finally, a load converter cascaded with three different source converters is fabricated to validate the effectiveness of the proposed adaptive SVI control strategy.
The chemical physics of sequential infiltration synthesis—A thermodynamic and kinetic perspective (2019)

Sequential infiltration synthesis (SIS) is an emerging materials growth method by which inorganic metal oxides are nucleated and grown within the free volume of polymers in association with chemical functional groups in the polymer. SIS enables the growth of novel polymer-inorganic hybrid materials, porous inorganic materials, and spatially templated nanoscale devices of relevance to a host of technological applications. Although SIS borrows from the precursors and equipment of atomic layer deposition (ALD), the chemistry and physics of SIS differ in important ways. These differences arise from the permeable three-dimensional distribution of functional groups in polymers in SIS, which contrast to the typically impermeable two-dimensional distribution of active sites on solid surfaces in ALD. In SIS, metal-organic vapor-phase precursors dissolve and diffuse into polymers and interact with these functional groups through reversible complex formation and/or irreversible chemical reactions. In this perspective, we describe the thermodynamics and kinetics of SIS and attempt to disentangle the tightly coupled physical and chemical processes that underlie this method. We discuss the various experimental, computational, and theoretical efforts that provide insight into SIS mechanisms and identify approaches that may fill out current gaps in knowledge and expand the utilization of SIS.
Granuloma anular disseminado em paciente com diabetes mellitus tipo II: tratamento bem sucedido com dapsona (2010)

O granuloma anular e uma doenca granulomatosa de etiologia desconhecida, que acomete preferencialmente mulheres. A forma disseminada dessa
dermatose pode estar associada a desordens sistemicas imunosupressoras. Algumas medidas terapeuticas vem sendo empregadas, tais como: corticosteroides,
psoralenicos com radiacao ultravioleta A, retinoides sistemicos, pentoxifilina, antimicrobianos e a dapsona. Relataremos um caso de granuloma
anular disseminado, em paciente portadora de diabetes mellitus tipo II, que obteve excelente resposta terapeutica com o uso de dapsona.
Golo, a dynamic, light and efficient language for post-invokedynamic JVM (2013)

This paper introduces Golo, a simple dynamic programming language for the Java Virtual Machine (JVM) that has been designed to leverage the capabilities of the new Java 7 invokedynamic instruction and API (JSR 292). Golo has its own language constructs being designed with invokedynamic in mind, whereas existing dynamic languages for the JVM such as Groovy, JRuby or Nashorn have to adapt language constructions which are sometimes hard to optimize. Coupled with a minimal runtime that directly uses the Java SE API, Golo is an interesting language for rapid prototyping, polyglot application embedding, research (e.g., runtime extensions, language prototyping) and teaching (e.g., programming, dynamic language runtime implementation). We show that the language design around invokedynamic allows for a very concise runtime code base with performance figures that compare favorably against Java and other dynamic JVM languages. We also discuss its future directions, either as part of Golo or through language and runtime research extensions.