Sets Of Libraries Research Articles

Californium-252 production at the High Flux Isotope Reactor − I: Validation study using campaign data

This paper presents a series of 252Cf production validation and code-to-code comparison studies performed based on data from the production campaigns at the High Flux Isotope Reactor (HFIR). These studies support efforts to convert HFIR from using highly enriched uranium (HEU) fuel to low-enriched uranium (LEU) fuel. HFIR must maintain its world-class performance and missions following this conversion, and because 252Cf is a vital neutron-emitting radioisotope used for a variety of high-impact applications (e.g., reactor startup, cancer treatment), the ability to efficiently produce 252Cf must be preserved. In this work, the HFIRCON, Shift, ORIGEN, and TCOMP codes were deployed, and several sets of data libraries were investigated to better understand the calculation codes and the data biases. As-loaded target composition data, as-run irradiation history data, and post-irradiation measurements from recent multi-cycle irradiation campaigns of the HEU core were used to validate and determine methodology biases. The findings demonstrated a good agreement, with results falling within 3 standard deviations of measurements. This paper lays the ground work for the second paper, which evaluates and compares 252Cf production and safety metrics with the HEU core and a proposed LEU core.

Improved Discrimination of Mass Spectral Isomers Using the High-Dimensional Consensus Mass Spectral Similarity Algorithm.

This study employs a high-dimensional consensus mass spectral (HDCMS) similarity scoring technique to discriminate isomers collected using an electron ionization mass spectrometer. The HDCMS method was previously introduced and applied to the discrimination of mass spectra of constitutional isomers, methamphetamine and phentermine, collected with direct analysis real-time mass spectrometry (DART-MS). The method formulates the problem of discriminating mass spectra in a mathematical Hilbert space and is hence called "high dimensional." It requires replicate mass spectra to build a Gaussian model and evaluate the inner products between these functions. The resulting measurement variability is used as a signature by which to discriminate spectra. In this work, HDCMS is tested on electron impact ionization (EI) mass spectra of 7 terpene and terpene-related (C10H16 and C10H14) isomers with experimental retention indices that differ by less than 30 and with traditional cosine similarity scores greater than 0.9, on a scale of 0 to 1, when compared with at least one other compound in the test set. Using identical instrument parameters, 15 replicate gas chromatography-electron ionization-mass spectrometry (GC-EI-MS) spectra of each isomer were collected and separated into distinct library and query sets. The HDCMS algorithm discriminated each isomer, indicating the method's potential. Because the method requires replicate measurements, observations from a simple heuristic study of the number of replicates required to discriminate these isomers is presented. The paper concludes with a discussion of compound discrimination using HDCMS and the benefits and drawbacks of applying the method to EI-MS data.

Nkoda

nkoda is a robust digital sheet music library and sophisticated user interface for interacting with scores. The resource will be beneficial to students to professional artists, creating efficiencies in ensembles, studios, and personal practice. The vast content library sets nkoda apart from other digital score apps, as does the ability to engage an institutional license.

Authentication of edible oils using an infrared spectral library and digital sample sets: A feasibility study

AbstractA potential method to determine whether two varieties of edible oils can be differentiated by Fourier transform infrared (FTIR) spectroscopy is proposed using digitally generated data of adulterated edible oils from an infrared (IR) spectral library. The first step is the evaluation of digitally blended data sets. Specifically, IR spectra of adulterated edible oils are computed from digitally blending experimental data of the IR spectra of an edible oil and the corresponding adulterant using the appropriate mixing coefficients to achieve the desired level of adulteration. To determine whether two edible oils can be differentiated by FTIR spectroscopy, pure IR spectra of the two edible oils are compared with IR spectra of two edible oils digitally mixed using a genetic algorithm for pattern recognition to solve a ternary classification problem. If the IR spectra of the two edible oils and their binary mixtures are differentiable from principal component plots of the spectral data, then differences between the IR spectra of these two edible oils are of sufficient magnitude to ensure that a reliable classification by FTIR spectroscopy can be obtained. Using this approach, the feasibility of authenticating edible oils such as extra virgin olive oil (EVOO) directly from library spectra is demonstrated. For this study, both digital and experimental data are combined to generate training and validation data sets to assess detection limits in FTIR spectroscopy for the adulterants.

Machine Learning Prediction for Design and System Technology Co-Optimization Sensitivity Analysis

As technology nodes continue to advance relentlessly, geometric pitch scaling starts to slow down. In order to retain the trend of Moore’s law, design technology co-optimization (DTCO) and system technology co-optimization (STCO) are introduced together to continue scaling beyond 5 nm using pitch scaling, patterning, and novel 3-D cell structures [i.e., complementary-FET (CFET)]. However, numerous DTCO and STCO iterations are needed to continue block-level area scaling with considerations of physical layout factors: 1) various standard cell (SDC) library sets (i.e., different cell heights and conventional FET); 2) design rules (DRs); 3) back end of line (BEOL) settings; and 4) power delivery network (PDN) configurations. The growing turnaround time (TAT) among SDC design, DR optimization, and block-level area evaluation becomes one of the major bottlenecks in DTCO and STCO explorations. In this work, we develop a machine learning model that combines bootstrap aggregation and gradient boosting techniques to predict the sensitivity of minimum valid block-level area of various physical layout factors. We first demonstrate that the proposed model achieves 16.3% less mean absolute error (MAE) than the previous work for testing sets. Then, we show that the proposed model successfully captures the block-level area sensitivity of new SDC library sets, new BEOL settings, and new PDN settings with 0.013, 0.004, and 0.027 MAE, respectively. Finally, compared to the previous work, the proposed approach improves the robustness of predicting new circuit designs by up to 6.76%. The proposed framework provides more than <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$100\times $ </tex-math></inline-formula> speedup compared to conventional DTCO and STCO exploration flows.

High-throughput sequencing of faeces provides evidence for dispersal of parasites and pathogens by migratory waterbirds.

Examination of faecal material has demonstrated how a broad range of organisms are distributed by bird movements. Such research has largely focused on dispersal of plant seeds by frugivores and of freshwater organisms by waterbirds. However, with few exceptions (e.g. avian influenza, Ebola virus), there is a dearth of evidence for transport of parasites and pathogens. High-throughput sequencing methods now provide a powerful means of addressing this knowledge gap by elucidating faecal contents in unprecedented detail. We collected faeces excreted by a range of migratory waterbirds in south-west Spain and pooled faecal DNA to create libraries reflective of feeding behavior. We created sets of libraries using high-throughput metagenomic and amplicon sequencing. For the latter we employed two sets of primers to broadly target the V4 region of the 18S rRNA gene (one set amplifying the region across all eukaryotes, the other excluding amplification of metazoans). Libraries revealed a wide diversity of eukaryotes, including parasites of the faecal producers themselves, parasites of food items, or those incidentally ingested. We also detected novel microbial eukaryotic taxa and found that parasite assemblage profiles were relatively distinct. Comparing the performance of the methods used supports their joint use for future studies of diversity and abundance. Because viable stages of many parasites are likely to be present in faeces, our results suggest significant levels of bird-mediated dispersal of parasites (both from avian and other hosts). Our methods revealed much hidden biodiversity, and allowed identification of the individuals who produced the faecal samples to species level, facilitating the study of interaction networks.

Library Information Construction and Service Trend under Big Data

With the rapid development of knowledge economy and the rapid progress of science and technology, in order to adapt to the pace of the times, university libraries have also undergone tremendous changes, especially in the context of information technology. The traditional service mode of library cannot meet the demand of teachers and students for cultural knowledge information. Is not a single demand for knowledge, but more pursuit of personalization, specialization and diversification? Therefore, it is urgent for the library to change the old service mode. Under this background, the university library has been greatly challenged in the service concept and service mode. Only through the application of personalized service mode through innovative service mode, the university library sets up individualized information service channel according to the user’s information demand behavior. And through the analysis of user’s habits and personal characteristics to meet the user’s potential information needs. Through the investigation and investigation of a university in our province, the number of people who do not understand the personalized recommendation service is up to 115, accounting for 40.35% of the total.

Face recognition using viola-jones depending on python

&lt;p&gt;In this paper, the proposed software system based on face recognition the proposed system can be implemented in the smart building or any VIP building need security interring in general, The human face will be recognized from a stream of pictures or video feed, this technology recognizes the person according to the specific algorithm, the algorithm that employed in this paper is the Viola–Jones object detection framework by using Python. The task of the proposed facial recognition system consists of two steps, the first one was detected the human face from live video using the webcamera in the computer, and the second step recognizes if this face allowed to enter the building or not by comparing it with the existing database, the two steps depending on the OpenCV python by importing cv2 method for detecting the human face, the frames can be read or written to file with the cv2.imread and cv2.imwrite functions respectively Finally, this proposed software system can be used to control access in smart buildings as a rule and the advancement of techniques connected around there, Providing a security system is one of the most important features must be achieved in the smart buildings, this proposed system can be used as an application in a smart building as a security system. Face recognition is one of the most important applications using today for practical facial recognition, The proposed software system, depending on using OpenCV (Open Source Computer Vision) is a popular computer vision library, in 1999 this library started by Intel. The platform library sets its focus on real-time image processing and includes patent-free implementations of the latest computer vision algorithms. OpenCV 2.3.1 now comes with a programming interface to C, C++, Python, and Android. OpenCV library of python, the three algorithms that will be used in this proposed system. The currently available algorithms are:&lt;/p&gt;&lt;p&gt;Eigenfaces → createEigenFaceRecognizer()&lt;/p&gt;&lt;p&gt;Fisherfaces → createFisherFaceRecognizer()&lt;/p&gt;&lt;p&gt;Local Binary Patterns Histograms → createLBPHFaceRecognizer()&lt;/p&gt;Finally the proposed system provide entering to the building just for the authorized person according to face recognition algorithem.&lt;p&gt; &lt;/p&gt;

An end-to-end model for chinese calligraphy generation

A Chinese calligraphy copybook usually has a limited number of Chinese characters, far from a whole set of characters needed for typesetting. Therefore, there is a need to develop complete sets of Chinese calligraphy libraries for well-known calligrapher styles. This paper proposes an end-to-end network for character generation based on specific calligraphy styles. Specifically, a style transfer network is designed to transfer the style of characters, and a content supplement network is designed to capture the details of stylish strokes. Our model can generate high-quality calligraphy images without manually annotating data. To verify the generated calligraphy styles, a new dataset is constructed for experimental comparison between our method and two other baseline methods. Moreover, a user study is conducted to evaluate our generated calligraphy from a visual perspective. When the experiment participants are asked to distinguish the real calligraphy from generated samples, the correct rate was 53.5%. The results show that the calligraphy styles generated by our model are almost indistinguishable from the original works.

A Comprehensive Online Database for Exploring ∼20,000 Public Arabidopsis RNA-Seq Libraries

A Comprehensive Online Database for Exploring ∼20,000 Public Arabidopsis RNA-Seq Libraries

Genome Wide Analysis for Growth at Two Growth Stages in A New Fast-Growing Common Carp Strain (Cyprinus carpio L.)

In order to identify candidate genes or loci associated with growth performance of the newly established common carp strain, Xinlong, we conducted a genome-wide association analysis using 2b-RAD technology on 123 individuals. We constructed two sets of libraries associated with growth-related parameters (weight, length, width and depth) measured at two different grow-out stages. Among the 413,059 SNPs identified using SOAP SNP calling, 147,131 were tested for GWAS after quality filtering. Finally, 39 overlapping SNPs, assigned to four genomic locations, were associated with growth traits in two stages. These loci were assigned to functional classes related to immune response, response to stress, neurogenesis, cholesterol metabolism and development, and proliferation and differentiation of cells. By overlapping results of Plink and EMMAX analyses, we identified three genes: TOX, PLK2 and CD163 (both methods P < 0.05). Our study results could be used for marker-assisted selection to further improve the growth of the Xinlong strain, and illustrate that largely different sets of genes drive the growth of carp in the early and late grow-out stages.

Exploratory Data Analysis using Python

Data need to be analyzed so as to produce good result. Using the result decision can be taken. For example recommendation system, ranking of the page, demand fore casting, prediction of purchase of the product. There are some leading companies where the review of the customer plays a great role to analyze the factor which influences the review rating. We have used exploratory data analysis (EDA) where data interpretations can be done in row and column format. We have used python for data analysis. it is object oriented ,interpreted and interactive programming language. it is open source with rich sets of libraries like pandas, MATplotlib, seaborn etc. We have used different types of charts and various types of parameter to analyze Amazon review data sets which contains the reviews of electronic data items. We have used python programming for the data analysis.

New pharmacological effect of fulvestrant to prevent oxaliplatin-induced neurodegeneration and mechanical allodynia in rats.

Oxaliplatin, which is widely used as chemotherapy for certain solid cancers, frequently causes peripheral neuropathy. Commonly described neuropathic symptoms include aberrant sensations such as mechanical allodynia (hypersensitivity to normally innocuous stimuli). Although oxaliplatin neuropathy is a dose-limiting toxicity, there are no established preventive strategies available at present. By screening several sets of small-molecule chemical libraries (more than 3,000 compounds in total) using a newly established in vitro high-throughput phenotypic assay, we identified fulvestrant, a clinically approved drug for the treatment of breast cancer in postmenopausal women, as having a protective effect on oxaliplatin-induced neuronal damage. Furthermore, histological and behavioural analyses using a rat model of oxaliplatin neuropathy demonstrated the in vivo efficacy of fulvestrant to prevent oxaliplatin-induced axonal degeneration of the sciatic nerve and mechanical allodynia. Furthermore, fulvestrant did not interfere with oxaliplatin-induced cytotoxicity against cancer cells. Thus, our findings reveal a previously unrecognised pharmacological effect of fulvestrant to prevent oxaliplatin-induced painful peripheral neuropathy without impairing its cytotoxicity against cancer cells and may represent a novel prophylactic option for patients receiving oxaliplatin chemotherapy.

An Analysis of Different Components of a High-Throughput Screening Library.

Since many projects at pharmaceutical organizations get their start from a high-throughput screening (HTS) campaign, improving the quality of the HTS deck can improve the likelihood of discovering a high-quality lead molecule that can be progressed to a drug candidate. Over the past decade, Janssen has implemented several strategies for external compound acquisition to augment the screening deck beyond the chemical space and number of molecules synthesized for internal projects. In this report, we analyzed the performance of each of those compound collections in the screening campaigns performed internally within Janssen during the last five years. We classified the screening library into two broad categories: Internal and External. The comparison of the performance of these sets of libraries was done by considering the primary, confirmation, and dose response hit rates. Our analysis revealed that Internal compounds (resulting from numerous medicinal chemistry efforts against diverse protein targets) have higher average confirmation hit rates than External ones; however, actives from both categories show similar probabilities of hitting multiple distinct targets. We also investigated the property landscape of both sets of libraries to identify the key elements which make a difference in these categories of compounds. From this analysis, Janssen aims to understand the descriptor landscape of the compounds with the highest hit rates and to use them for improving its future acquisition strategies as well as to inform our plating strategy.

Fast and Flexible Synthesis of Combinatorial Libraries for Directed Evolution.

Directed evolution (DE) is a powerful tool for optimizing an enzyme's properties toward a particular objective, such as broader substrate scope, greater thermostability, or increased kcat. A successful DE project requires the generation of genetic diversity and subsequent screening or selection to identify variants with improved fitness. In contrast to random methods (error-prone PCR or DNA shuffling), site-directed mutagenesis enables the rational design of variant libraries and provides control over the nature and frequency of the encoded mutations. Knowledge of protein structure, dynamics, enzyme mechanisms, and natural evolution demonstrates that multiple (combinatorial) mutations are required to discover the most improved variants. To this end, we describe an experimentally straightforward and low-cost method for the preparation of combinatorial variant libraries. Our approach employs a two-step PCR protocol, first producing mutagenic megaprimers, which can then be combined in a "mix-and-match" fashion to generate diverse sets of combinatorial variant libraries both quickly and accurately.

RNA-seq reveals distinctive RNA profiles of small extracellular vesicles from different human liver cancer cell lines.

Liver cancer (LC) is one of the most common cancers and represents the third highest cause of cancer-related deaths worldwide. Extracellular vesicle (EVs) cargoes, which are selectively enriched in RNA, offer great promise for the diagnosis, prognosis and treatment of LC. Our study analyzed the RNA cargoes of EVs derived from 4 liver-cancer cell lines: HuH7, Hep3B, HepG2 (hepato-cellular carcinoma) and HuH6 (hepatoblastoma), generating two different sets of sequencing libraries for each. One library was size-selected for small RNAs and the other targeted the whole transcriptome. Here are reported genome wide data of the expression level of coding and non-coding transcripts, microRNAs, isomiRs and snoRNAs providing the first comprehensive overview of the extracellular-vesicle RNA cargo released from LC cell lines. The EV-RNA expression profiles of the four liver cancer cell lines share a similar background, but cell-specific features clearly emerge showing the marked heterogeneity of the EV-cargo among the individual cell lines, evident both for the coding and non-coding RNA species.

Transfer of microRNA-486-5p from human endothelial colony forming cell–derived exosomes reduces ischemic kidney injury

Administration of human cord blood endothelial colony-forming cells (ECFCs) or their exosomes protects mice against kidney ischemia/reperfusion injury. Here we studied the microRNA (miRNA) content of ECFC exosomes and the role of miRNA transfer in kidney and endothelial cell protection. ECFC exosomes were enriched in miR-486-5p, which targets the phosphatase and tensin homolog (PTEN) and the Akt pathway. In cultured endothelial cells exposed to hypoxia, incubation with ECFC exosomes increased miR-486-5p, decreased PTEN, and stimulated Aktphosphorylation. Exposure of hypoxic endothelial cellsto conditioned medium from ECFCs pretreated with anti-miR-486-5p blocked increases in miR-486-5p and phosphorylated Akt, restored expression of PTEN, and enhanced apoptosis. Coculture of endothelial cells with ECFCs enhanced endothelial miR-486-5p levels. Targeting of PTEN by miR-486-5p was observed in endothelial cells, and PTEN knockdown blocked apoptosis. In mice with ischemic kidney injury, infusion of ECFC exosomes induced potent functional and histologic protection, associated with increased kidney miR-486-5p levels, decreased PTEN, and activation of Akt. Infusion of exosomes from ECFCs transfected with anti-miR-486-5p had no protective effect. Thus, delivery of ECFC exosomes reduces ischemic kidney injury via transfer of miR-486-5p targeting PTEN. Exosomes enriched in miR-486-5p could represent a therapeutic tool in acute kidney injury.

Concordance and reproducibility of a next generation mtGenome sequencing method for high-quality samples using the Illumina MiSeq

Sanger-type sequencing (STS) of mitochondrial DNA (mtDNA), specifically the control region (CR), is routinely employed in forensics in human identification and missing persons scenarios. Yet next-generation sequencing (NGS) has the potential to overcome some of the major limitations of STS processing, permitting reasonable paths forward for full mitochondrial genome (mtGenome) sequencing, while also offering higher-throughput and higher sensitivity capabilities. To establish the accuracy and reproducibility of NGS for the development of mtDNA data, 90 DNA extracts that were previously used to generate forensic quality full mtGenomes using STS were sequenced using Nextera XT library preparation and the Illumina MiSeq. Using the same amplicon product, replicate library sets were generated and sequenced at different laboratories, and analysis was performed in replicate using the CLC Genomics Workbench. Both sequencing sets resulted in 99.998% of positions with greater than 10X coverage when 96 samples (including controls) were multiplexed. Overall, 99.9996% concordance was observed between the NGS data and the STS data for the full mtGenome. The only “discordant” calls involved low level point heteroplasmies, with the differences resulting from stochastic variation and/or the increased sensitivity of NGS. Higher sensitivity also allowed for the detection of a mixed sample previously not detected with STS. Additionally, variant calls were reproducible between sequencing sets and between software analysis versions with the variant frequency only differing by 0.23% and 0.01%, respectively. Further validation studies and specialized software functionality tailored to forensic practice should facilitate the incorporation of NGS processing into standard casework applications. The data herein comprise the largest, and likely most thoroughly examined, complete mtGenome STS-NGS concordance dataset available.

Sound production and associated behaviours of benthic invertebrates from a coastal habitat in the north-east Atlantic

Maerl beds are among the most endangered habitats in coastal temperate waters and a priority for conservation. Passive acoustics is a potential non-intrusive approach for surveying this fragile ecosystem with minor disturbances. Invertebrate sounds can be major contributors to natural coastal soundscapes but are not well studied. We conducted controlled tank-based experiments to identify sound-producing invertebrates inhabiting north-east Atlantic maerl beds and to characterise their sounds in terms of frequency features and source levels. We also determined which sound types are able to be detected above natural maerl ambient noise and suitable for in situ monitoring. Tank recording sessions of 20 abundant and potentially soniferous invertebrates from maerl beds revealed eight soniferous species and 15 different sound types. Two new sound-producing families were identified, Calyptraeidae and Majidae. Six sound types had properties consistent with detectability and identification for in situ acoustic studies: the feeding sound of sea urchins Echinus esculentus, Paracentrotus lividus and Psammechinus miliaris, snapping sound of the snapping shrimp Athanas nitescens, and feeding and other sounds of the spider crab Maja brachydactyla. Estimated detection distances ranged from a few metres for sea urchin feeding sounds up to about 40 m for A. nitescens snaps and spider crab feeding sounds. These invertebrates, particularly A. nitescens, probably make a substantial contribution to the maerl ambient noise. This invertebrate sound library sets a basis for in situ acoustic studies.

Assessment of pin-by-pin fission rate distribution within MOX/UO2 fuel assembly using MCNPX code

Abstract The aim of the present paper is to assess the calculations of pin-by-pin group integrated fission rates within MOX/UO2 Fuel assemblies using the Monte Carlo code MCNPX2.7c with two sets of the available latest nuclear data libraries used for calculating MOX-fueled systems. The data that are used in this paper are based on the benchmark by the NEA Nuclear Science Committee (NSC). The k ∞ and absorption/fission reaction rates per isotope, keff and pin-by-pin group integrated fission rates on 1/8 fraction of the geometry are determined. To assess the overall pin-by-pin fission rate distribution, the collective per cent error measures were investigated. The results of AVG, MRE and RMS error measures were less than 1 % error. The present results are compared with other participants using other Monte Carlo codes and with CEA results that were taken in the benchmark as reference. The results with ENDF/B-VI.6 are close to the results received by MVP (JENDL3.2) and SCALE 4.2 (JEF2.2). The results with ENDF/BVII.1 give higher values of k∞ reflecting the changes in the newer evaluations. In almost all results presented here, the MCNP calculated results with ENDF/B VII.1 should be considered more than those obtained by using other Monte Carlo codes and nuclear data libraries. The present calculations may be consider a reference for evaluating the numerical schemes in production code systems, as well as the global performance including cross-section data reduction methods as the calculations used continuous energy and no geometrical approximations.