gebhart/patrepeval huggingface dataset:
The second-century Apologists (2022)

Click to increase image sizeClick to decrease image size Additional informationNotes on contributorsEarl CollinsEarl Collins is the Continuing Ministerial Development Officer in the Anglican Diocese of Chichester and the Vicar of St John’s Hove.
Local infiltration of high‐ and low‐molecular‐weight RNA from silenced sunflower (<i>Helianthus annuus</i> L.) plants triggers post‐transcriptional gene silencing in non‐silenced plants (2004)

Using grafting procedures, we have characterized post-transcriptional gene silencing (PTGS) in transgenic sunflower expressing beta-glucuronidase (GUS) activity. Silencing was observed as early as 2 weeks after grafting of non-silenced scions on to silenced rootstock. Transmission of the systemic signal occurs solely from stock to scion, is independent of the physiological age of the rootstock and is not heritable. Furthermore, we report, for the first time in plants, an easy and low-cost method of activating RNA silencing by infiltration of purified RNA from silenced plants. Local application of total RNA derived from silenced sunflower plants to leaves of non-silenced plants induces PTGS in newly developed leaves above the point of infiltration, as shown by reduced GUS activity and mRNA levels. Silenced plants contain 21-23-nucleotide RNAs hybridizing to transgene target sequences, in contrast with leaves of non-silenced plants. However, de novo production of GUS-specific short RNA in non-silenced plants can be activated by leaf infiltration of low-molecular-weight RNAs isolated from leaves of silenced plants. Significant levels were detected as early as 2 weeks after infiltration, peaked at 3 weeks and declined 5 weeks after infiltration. Our results provide evidence that RNA infiltration in sunflower induces transient silencing and is not transmitted to offspring. This approach could be of major use in dissecting the mechanisms involved in PTGS.
Random Neural Networks and Deep Learning for Attack Detection at the Edge (2019)

In this paper, we analyze the network attacks that can be launched against Internet of Things (IoT) gateways, identify the relevant metrics to detect them, and explain how they can be computed from packet captures. We then present the principles and design of a deep learning-based approach using dense random neural networks (RNN) for the online detection of network attacks. Empirical validation results on packet captures in which attacks are inserted show that the Dense RNN correctly detects attacks.
Three-Switch Active-Clamp Forward Converter With Low Switch Voltage Stress and Wide ZVS Range for High-Input-Voltage Applications (2009)

In low-to-medium power applications, an active-clamp forward (ACF) converter is popular for its simple structure and zero-voltage switching (ZVS) capability. However, the high voltage stress on switches can be a burden in high-input-voltage applications. To relieve this, a three-switch ACF (TS-ACF) converter, which employs two main switches for a forward converter and one auxiliary switch for an active-clamp circuit (ACC), is proposed in this paper. With a repositioned ACC, all the switches of TS-ACF converter have relatively low voltage stress compared to the conventional one. In addition, one of the main switches always ensures ZVS during the transformer reset. Consequently, the TS-ACF converter can be promising for high-input-voltage applications with high efficiency.
L‐8: <i>Late‐News Paper:</i> Highly Efficient Solution‐Processible Dendrimer LEDs (2002)

Abstract The recent progress in the development of organic light emitting diodes (OLEDs) has opened many avenues for the production of large area, full colour, flexible displays that are cheap to manufacture. Currently most research has focussed on two main classes of materials ‐ small organic molecules and conjugated polymers. An alternative approach is to use conjugated dendrimers. We show that conjugated dendrimers are a promising new class of solution‐processible materials for highly efficient organic LEDs.
Image display algorithms for high‐ and low‐dynamic‐range display devices (2007)

Abstract— With interest in high‐dynamic‐range imaging mounting, techniques for displaying such images on conventional display devices are gaining in importance. Conversely, high‐dynamic‐range display hardware is creating the need for display algorithms that prepare images for such displays. In this paper, the current state of the art in dynamic‐range reduction and expansion is reviewed, and in particular the theoretical and practical need to structure tone reproduction as a combination of a forward and a reverse pass is passed.
Tuberculosis drug discovery in the post‐post‐genomic era (2014)

The expectation that genomics would result in new therapeutic interventions for infectious diseases remains unfulfilled. In the post-genomic era, the decade immediately following the availability of the genome sequence of Mycobacterium tuberculosis, tuberculosis (TB) drug discovery relied heavily on the target-based approach but this proved unsuccessful leading to a return to whole cell screening. Genomics underpinned screening by providing knowledge and many enabling technologies, most importantly whole genome resequencing to find resistance mutations and targets, and this resulted in a selection of leads and new TB drug candidates that are reviewed here. Unexpectedly, many new targets were found to be 'promiscuous' as they were inhibited by a variety of different compounds. In the post-post-genomics era, more advanced technologies have been implemented and these include high-content screening, screening for inhibitors of latency, the use of conditional knock-down mutants for validated targets and siRNA screens. In addition, immunomodulation and pharmacological manipulation of host functions are being explored in an attempt to widen our therapeutic options.
Genetic diversity of influenza A viruses circulating in Bulgaria during the 2018–2019 winter season (2020)

<b>Introduction.</b> Influenza viruses evolve rapidly and change their antigenic characteristics, necessitating biannual updates of flu vaccines.<b>Aim.</b> The aim of this study was to characterize influenza viruses circulating in Bulgaria during the 2018/2019 season and to identify amino acid substitutions in them that might impact vaccine effectiveness.<b>Methodology.</b> Typing/subtyping of influenza viruses were performed using real-time Reverse Transcription-PCR (RT-PCR) and results of phylogenetic and amino acid sequence analyses of influenza strains are presented.<b>Results.</b> A(H1N1)pdm09 (66 %) predominated over A(H3N2) (34 %) viruses, with undetected circulation of B viruses in the 2018/2019 season. All A(H1N1)pdm09 viruses studied fell into the recently designated 6B.1A subclade with over 50 % falling in four subgroups: 6B.1A2, 6B.1A5, 6B.1A6 and 6B.1A7. Analysed A(H3N2) viruses belonged to subclades 3C.2a1b and 3C.2a2. Amino acid sequence analysis of 36 A(H1N1)pdm09 isolates revealed the presence of six-ten substitutions in haemagglutinin (HA), compared to the A/Michigan/45/2015 vaccine virus, three of which occurred in antigenic sites Sa and Cb, together with four-nine changes at positions in neuraminidase (NA), and a number of substitutions in internal proteins. HA1 D222N substitution, associated with increased virulence, was identified in two A(H1N1)pdm09 viruses. Despite the presence of several amino acid substitutions, A(H1N1)pdm09 viruses remained antigenically similar to the vaccine virus. The 28 A(H3N2) viruses characterized carried substitutions in HA, including some in antigenic sites A, B, C and E, in NA and internal protein sequences.<b>Conclusion.</b> The results of this study showed the genetic diversity of circulating influenza viruses and the need for continuous antigenic and molecular surveillance.
Optimized Mahalanobis–Taguchi System for High-Dimensional Small Sample Data Classification (2020)

The Mahalanobis-Taguchi system (MTS) is a multivariate data diagnosis and prediction technology, which is widely used to optimize large sample data or unbalanced data, but it is rarely used for high-dimensional small sample data. In this paper, the optimized MTS for the classification of high-dimensional small sample data is discussed from two aspects, namely, the inverse matrix instability of the covariance matrix and the instability of feature selection. Firstly, based on regularization and smoothing techniques, this paper proposes a modified Mahalanobis metric to calculate the Mahalanobis distance, which is aimed at reducing the influence of the inverse matrix instability under small sample conditions. Secondly, the minimum redundancy-maximum relevance (mRMR) algorithm is introduced into the MTS for the instability problem of feature selection. By using the mRMR algorithm and signal-to-noise ratio (SNR), a two-stage feature selection method is proposed: the mRMR algorithm is first used to remove noise and redundant variables; the orthogonal table and SNR are then used to screen the combination of variables that make great contribution to classification. Then, the feasibility and simplicity of the optimized MTS are shown in five datasets from the UCI database. The Mahalanobis distance based on regularization and smoothing techniques (RS-MD) is more robust than the traditional Mahalanobis distance. The two-stage feature selection method improves the effectiveness of feature selection for MTS. Finally, the optimized MTS is applied to email classification of the Spambase dataset. The results show that the optimized MTS outperforms the classical MTS and the other 3 machine learning algorithms.
EFFECTS OF SEED SIZE AND EMERGENCE TIME ON SUBSEQUENT GROWTH OF PERENNIAL RYEGRASS (1980)

SUMMARY The seed weight of individual perennial ryegrass seeds was measured prior to recording their date of emergence and subsequent growth in experimental populations raised in the glasshouse and sown at different initial densities. Seed size did not correlate with time to emergence although lighter individuals had a slightly lower probability of emergence. Seed size had no statistically significant effect on subsequent tillering up to 27 weeks, or on the dry wt attained by this time. The time from sowing to emergence was significantly related to subsequent tillering of the grass plants for a number of weeks in populations sown at different densities. After some 20 weeks the effect of emergence time became non‐significant. This coincided with the onset of tiller mortality in the population. Even after 27 weeks individual emergence time was inversely related to dry wt but was not related to mean tiller weight.
Design of Ultrathin LTCC Coupled Inductors for Compact DC/DC Converters (2011)

It is found out that using reverse coupled inductors could effectively improve power density and dynamic performance of multiphase interleaved point of load converters. Thus, it is of great significance to conduct a research about design and fabrication of ultrathin coupled inductors for system 3-D integration. The aim of this paper is to explore the structures, modeling, and fabrication of ultrathin coupled inductors based on low-temperature cofired ceramic (LTCC) technology. Four structures classified by shapes and relative positions of windings are introduced and compared. Simple but effective analytic models are set up to calculate self-inductance, leakage inductance, and coupling coefficient for quick design, and a design guideline is summarized according to the models. We made a 1.3-mm-thick LTCC coupled inductor and two competing coil coupled inductors, and compared their characteristics and performance. They are tested in a 12-V input and 1.2-V/40-A output two-phase interleaved buck converter at three different switching frequencies. Core loss and winding loss of the inductors are quantified by simulation. Compared with conventional coil coupled inductors, the LTCC coupled inductor has higher power density and light load efficiency. Besides, it could also help to improve the transient performance of converters for its higher coupling coefficient.
Effects of Unphysiological Factors on Cardiac Output Regulation During Artificial Heart Pumping (1975)

Several Factors affecting artificial heart output were studied employing two mathematical models of prosthetic hearts, i.e., sac and diaphragm heart models. The stroke volume sensitivity to changes in venous pressure was analyzed by numerical computations. Increased inflow valve resistance, increased pump vacuum pressure, decreased elasticity of the ventricular sac or diaphragm and decreased size of the ventricle were shown to depress artificial heart function. In total prosthetic heart replacement experiments in calves, the resistance at the junction of the right heart to the natural atrium was measured by varying the pump vacuum pressure. When the vacuum pressure exceeded -20 mmHg, the orifice resistance to flow increased approximately 4 times. Optimizing the above factors, a prosthetic heart should be designed that provides sufficient flow with a pump vacuum pressure not greater than -20 mmHg.
Copper(II) Tetrafluoroborate Catalyzed Ring-Opening Reaction of Epoxides with Alcohols at Room Temperature (2002)

[reaction: see text] Efficient ring opening of different epoxides by reaction with representative alcohols is presented. These processes were carried out at room temperature and rely on the usefulness of commercial copper tetrafluoroborate as catalyst.
Data protection on hadoop distributed file system by using encryption algorithms: a systematic literature review (2020)

Abstract Big data has capability to process huge amount of unstructured and structured data. Nowadays, technology is able to support business need by extracting massive amount of data and recognizing its pattern to predict future trends. It brings right insight in business strategy to gain tremendous benefit. Hadoop is a reliable technology which developed to distribute process and storage on big data efficiently. However, Hadoop doesn’t have any built-in provision to encrypt data by default. Hadoop additional feature in encryption zone has security issue which key management does outside of HDFS. Sensitive and confidential data in HDFS can be exposed against security attack. Information security is fundamental concern and new set challenge for the world of big data. The main purpose of this paper is to protect Hadoop Distributed File System data by using encryption algorithm. This is to ensure data is secured at storage level of HDFS. Dealing with big data, it is important to choose fast enough encryption algorithm that has great performance. Research methodology is SLR (System Literature Review) by using methodology of PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses).
High-quality Panorama Stitching based on Asymmetric Bidirectional Optical Flow (2020)

In this paper, we propose a panorama stitching algorithm based on asymmetric bidirectional optical flow. This algorithm expects multiple photos captured by fisheye lens cameras as input, and then, through the proposed algorithm, these photos can be merged into a high-quality 360-degree spherical panoramic image. For photos taken from a distant perspective, the parallax among them is relatively small, and the obtained panoramic image can be nearly seamless and undistorted. For photos taken from a close perspective or with a relatively large parallax, a seamless though partially distorted panoramic image can also be obtained. Besides, with the help of Graphics Processing Unit (GPU), this algorithm can complete the whole stitching process at a very fast speed: typically, it only takes less than 30s to obtain a panoramic image of 9000-by-4000 pixels, which means our panorama stitching algorithm is of high value in many real-time applications. Our code is available at https://github.com/MungoMeng/Panorama-OpticalFlow.
A Model Selection-Based Interval-Mapping Method for Autopolyploids (2005)

While extensive progress has been made in quantitative trait locus (QTL) mapping for diploid species, similar progress in QTL mapping for polyploids has been limited due to the complex genetic architecture of polyploids. To date, QTL mapping in polyploids has focused mainly on tetraploids with dominant and/or codominant markers. Here, we extend this view to include any even ploidy level under a dominant marker system. Our approach first selects the most likely chromosomal marker configurations using a Bayesian selection criterion and then fits an interval-mapping model to each candidate. Profiles of the likelihood-ratio test statistic and the maximum-likelihood estimates (MLEs) of parameters including QTL effects are obtained via the EM algorithm. Putative QTL are then detected using a resampling-based significance threshold, and the corresponding parental configuration is identified to be the underlying parental configuration from which the data are observed. Although presented via pseudo-doubled backcross experiments, this approach can be readily extended to other breeding systems. Our method is applied to single-dose restriction fragment autotetraploid alfalfa data, and the performance is investigated through simulation studies.
Legal regulation of electronic commerce (1998)

Electronic commerce is a new technology which is growing rapidly. It has the ability to create a truly global digital economy, but at present current legislation does not encourage the uptake of this technology. The nature of the Internet and the globalisation of the world economy mean that developments in electronic commerce create legal problems concerning security of transactions and legal jurisdiction of transactions. The growth of electronic commerce has made current and future legal requirements difficult to assess. In order for electronic commerce to develop these issues have to be addressed on an international level. This paper attempts to highlight the problems of legislating electronic commerce. The role of the United States, European Union and Organisation for Economic Co-operation and Development (OECD) in formulating legal policy is discussed. The legal position regarding digital signatures, certificate authorities and trusted third parties are addressed as, is the issue of data protection.
Equistatin, a New Inhibitor of Cysteine Proteinases fromActinia equina, Is Structurally Related to Thyroglobulin Type-1 Domain (1997)

It is well known that the activities of the lysosomal cysteine proteinases are tightly regulated by their endogenous inhibitors, cystatins. Here we report a new inhibitor of cysteine proteinases isolated from sea anemone Actinia equina. The inhibitor, equistatin, is an acidic protein with pI 4.7 and molecular weight of 14,129. It binds tightly and rapidly to cathepsin L (ka = 5.7 x 10(7) M-1 s-1, Ki = 0.051 nM) and papain (ka = 1.2 x 10(7) M-1 s-1, Ki = 0.57 nM). The lower affinity for cathepsin B (Ki = 1.4 nM) was shown to be due mainly to a lower second order association rate constant (ka = 0.04 x 10(6) M-1 s-1). The inhibitor is composed of 128 amino acids forming two repeated domains with 48% identity. Neither of the domains shows any sequence homology to cystatins, but they do show a significant homology to thyroglobulin type-1 domains. A highly conserved consensus sequence motif of Cys-Trp-Cys-Val together with conserved Cys, Pro, and Gly residues is present in major histocompatibility complex class II-associated p41 invariant chain, nidogen, insulin-like growth factor proteins, saxiphilin domain a, pancreatic carcinoma marker proteins (GA733), and chum salmon egg cysteine proteinase inhibitor. In each of the domains of the equistatin, the three residues are similarly conserved, and the sequences Val-Trp-Cys-Val and Cys-Trp-Cys-Val are present in domains a and b, respectively. We suggest that equistatin belongs to a new superfamily of protein inhibitors of cysteine proteinases named thyroglobulin type-1 domain inhibitors. This superfamily currently includes equistatin, major histocompatibility complex class II- associated p41 invariant chain fragment, and chum salmon egg cysteine proteinase inhibitor.
Summary for Policymakers (2007)

The Working Group I contribution to the IPCC Fourth Assessment Report describes progress in understanding of the human and natural drivers of climate change, observed climate change, climate processes and attribution, and estimates of projected future climate change. It builds upon past IPCC assessments and incorporates new findings from the past six years of research. Scientific progress since the TAR is based upon large amounts of new and more comprehensive data, more sophisticated analyses of\ndata, improvements in understanding of processes and their simulation in models, and more extensive exploration of uncertainty ranges.
Jitter reduction in ATM networks (2002)

Waiting time jitter is one of the main problems encountered in ATM (asynchronous transfer mode) networks, as its amplitude (after filtering) can exceed that permitted by current standards. A method for reducing jitter is presented which consists in transmitting the phase information from the plesiochronous source measured by a reference clock. This information is protected against transmission errors and cell loss. It is shown that it is possible to conform to CCITT recommendation G.823 for all plesiochronous rates of the 2-Mb/s hierarchy defined in recommendation G.702 by using as the reference clock either the 2-MHz synchronization network or the future 155-MHz network provided by the synchronous systems (synchronous digital hierarchy).< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Application of Nonlinear Filtering for SINS Initial Alignment (2006)

The paper derived the initial alignment error equation of the SINS (strapdown inertial navigation system) when the azimuth errors are considerably large. Because of including the nonlinear part in the equation, two methods of extended Kalman filter and scaled unscented Kalman filter are used to simulate the nonlinear system. The simulation results show that the accuracy of scaled unscented Kalman filter for the azimuth estimate is better than extended Kalman filter
Path Planning with Motion Optimization for Car Body-in-White Industrial Robot Applications (2012)

This paper discusses the problem of effective motion planning for industrial robots. The first part dealt with current method for off-line motion planning. In the second part the presented work is done by one of the simulation systems with automatic trajectory generation and off-line programming capability. A spot welding process is involved. The practical application of this step strongly depends on the method for robot path optimization with high accuracy, thus transform the path into a time and energy optimal robot program for the real world, which is discussed in the third step.