gebhart/patrepeval huggingface dataset:
Ultrasound Classification of Breast Masses Using a Comprehensive Nakagami Imaging and Machine Learning Framework (2021)

In this study we investigate the potential of parametric images formed from ultrasound B-mode scans using the Nakagami distribution for non-invasive classification of breast lesions. Through a sliding window technique, we generated seven types of parametric images from each patient scan in our dataset using basic and as well as derived parameters of the Nakagami distribution. To determine the most suitable window size for image generation, we conducted an empirical analysis using three windows, and selected the best one for our study. From the parametric images formed for each patient, we extracted a total of 72 features. Feature selection was performed to find the optimum subset of features for the best classification performance. Incorporating the selected subset of features with the Support Vector Machine (SVM) classifier, and by tuning the decision threshold, we obtained a maximum classification accuracy of 93.08%, an Area under the ROC Curve (AUC) of 0.9712, a False Negative Rate of 0%, and a very low False Positive Rate of 8.65%. Our results indicate that the high accuracy of such a procedure may assist in the diagnostic process associated with detection of breast cancer, as well as help to reduce false positive diagnosis.
Immune transgene-dependent myocarditis in macaques after systemic administration of adeno-associated virus expressing human acid alpha-glucosidase (2023)

Immune responses to human non-self transgenes can present challenges in preclinical studies of adeno-associated virus (AAV) gene therapy candidates in nonhuman primates. Although anti-transgene immune responses are usually mild and non-adverse, they can confound pharmacological readouts and complicate translation of results between species. We developed a gene therapy candidate for Pompe disease consisting of AAVhu68, a clade F AAV closely related to AAV9, that expresses an engineered human acid-alpha glucosidase (hGAA) tagged with an insulin-like growth factor 2 variant (vIGF2) peptide for enhanced cell uptake. Rhesus macaques were administered an intravenous dose of 1x10<sup>13</sup> genome copies (GC)/kg, 5x10<sup>13</sup> GC/kg, or 1 x 10<sup>14</sup> GC/kg of AAVhu68.vIGF2.hGAA. Some unusually severe adaptive immune responses to hGAA presented, albeit with a high degree of variability between animals. Anti-hGAA responses ranged from absent to severe cytotoxic T-cell-mediated myocarditis with elevated troponin I levels. Cardiac toxicity was not dose dependent and affected five out of eleven animals. Upon further investigation, we identified an association between toxicity and a major histocompatibility complex class I haplotype (Mamu-A002.01) in three of these animals. An immunodominant peptide located in the C-terminal region of hGAA was subsequently identified <i>via</i> enzyme-linked immunospot epitope mapping. Another notable observation in this preclinical safety study cohort pertained to the achievement of robust and safe gene transfer upon intravenous administration of 5x10<sup>13</sup> GC/kg in one animal with a low pre-existing neutralizing anti-capsid antibodies titer (1:20). Collectively, these findings may have significant implications for gene therapy inclusion criteria.
Integration of photonic functions in and with silicon (2004)

Silicon is gaining importance in photonic systems on a chip, either because of the importance of integrating photonic functions with electronic functions or because of the potential of silicon-based technology for photonics as such. In this paper, we discuss two distinct developments. The first is the development of nano-photonic integrated circuits based on photonic crystals or photonic wires. The second is the development of heterogeneously integrated active photonic components on top of silicon by means of wafer bonding.
Industrial byproducts valorization through energy saving processes. Alkaline extraction of polyphenols from vine shoots (2014)

Vine shoots are viticulture byproducts recently valorized as important sources of polyphenols. These are powerful natural antioxidants used in several industrial applications. The aim of this work is to intensify polyphenol extraction from vine shoots (Syrah variety) using energy saving techniques. In this study, we chose to work with green solvent and in absence of organic solutions. The effect of NaOH concentrations (0, 1, 10, 100 and 1000 mM) on polyphenol extraction was studied. Polyphenol concentrations (Folin-Ciocalteu) and diffusion coefficients (Fick's second law) were calculated. The radical scavenging activity (DPPH assay) of extracts was determined. Polyphenol identification and quantification were conducted by High Performance Liquid Chromatography (HPLC). The maximal polyphenol yield (5 mg GAE/g of dry matter (DM)), diffusion coefficient (9 × 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-12</sup> m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> /s), radical scavenging activity (62 %) and the maximum molecular diversity were obtained using 1000 mM NaOH solution. We hereby propose an environmentally friendly procedure to valorize industrial waste using green technology, leading to the recovery of target compounds and their recycling inside food chain.
Influence of Kinetics of Gastric Emptying on Hepatic IGF1 Production in Young Calves (1990)

Five preruminant calves, fitted with chronically indwelling catheters in the hepatic and portal veins and hepatic artery, were fed two kinds of diet (a conventional clotting milk diet and an incurdled milk diet) or fasted for 24 h. The statistical analysis of the plasma growth hormone (GH; nmol/l) or IGF1 (nmol/l) daily secretory profiles indicated that hormonal levels were very high in fed calves (GH mean values: 0.40 +/- 0.11 and 0.36 +/- 0.10, respectively; IGF1 mean values: 6.65 +/- 0.57 and 7.54 +/- 0.33, respectively). The GH secretory profile observed over a 24-hour period showed 7 secretory spikes without periodicity in both diets. In fasting animals, plasma GH and IGF1 concentrations were very low (0.17 +/- 0.08 and 3.08 +/- 0.36, respectively) and stable, they increased with refeeding (1.51 +/- 0.05 and 7.36 +/- 0.55, respectively). Hepatic IGF1 production (micrograms/kg body weight/day) was 195 +/- 7 in standard milk fed calves and -255 +/- 30 in others. Our results demonstrated that nutritional factors, such as different kinetics of gastric emptying or fasting, may influence hepatic IGF1 production in the conscious newborn calf.
Single-column ion chromatography for the determination of chloride and sulfate in steam condensate and boiler feed water (1981)

ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTSingle-column ion chromatography for the determination of chloride and sulfate in steam condensate and boiler feed waterK. M. Roberts, D. T. Gjerde, and J. S. FritzCite this: Anal. Chem. 1981, 53, 11, 1691–1695Publication Date (Print):September 1, 1981Publication History Published online1 May 2002Published inissue 1 September 1981https://pubs.acs.org/doi/10.1021/ac00234a032https://doi.org/10.1021/ac00234a032research-articleACS PublicationsRequest reuse permissionsArticle Views269Altmetric-Citations39LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail Other access optionsGet e-Alertsclose Get e-Alerts
Gibbs sampling MIMO detection with maximum ratio combining (2017)

In this paper, Gibbs sampling multi-input multi-output (MIMO) detection with maximum ratio combining (MRC) is proposed and it is applied to the uplink with a massive MIMO receiver. In conventional Gibbs sampling schemes, the Gibbs sampling algorithm is directly applied to received signals. When it is applied to signals with higher order modulation symbols, a stalling problem occurs. Though a random restart scheme is proposed to solve the stalling problem, it needs adaptive restart criteria that makes hard to estimate the total amount of computational complexity. In the proposed scheme, each candidate symbol is updated with a metric calculated by multiplying corresponding MRC coefficients to the received signal vector. In this case, the convergence speed of the metric for the received signals even with higher order modulation symbols improves and the complexity of metric calculation for the update of a transmit candidate symbol vector can be reduced. Numerical results obtained through computer simulation have shown that the proposed scheme reduces the number of multiplication operations by a factor of 1/6.7 when it is applied to signals modulated with QPSK. It is also shown that the proposed scheme improves the convergence speed of the metric for E <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">b</sub> /N <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sub> ≥ 10dB when 16QAM symbols are transmitted. Furthermore, the proposed mixed Gibbs sampling achieves the same BER performance with smaller complexity as compared to that of a QR decomposition with M-algorithm (QRM)-maximum likelihood detection (MLD) when the number of transmit signals is more than 32.
ChemInform Abstract: STRUCTURE OF AN IRON(II) COMPLEX WITH A NOVEL SEXADENTATE LIGAND DERIVED FROM A TETRAAZA MACROCYCLE (1978)

Abstract Ein durch Kondensation von Acetonitril mit dem Makrocyclus (I) in Gegenwart von Fe‐Ionen dargestellter neuer Komplex (II) kristallisiert in der orthorhombischen Raumgruppe P2 1 2 1 2 1 mit Z=4.
Pharmacology and toxicity of a potent "nonclassical" 2,4-diamino quinazoline folate antagonist, trimetrexate, in normal dogs. (1982)

The pharmacology of trimetrexate (JB-11, NSC 249008, 2,4-diamino-5-methyl-5-[(3,4,5-trimethoxyanilino)methyl]quinazoline), an antitumor agent effective against several mouse tumors, was studied in normal dogs. A high-performance liquid chromatographic technique with electrochemical detection, dihydrofolate reductase inhibition assay, and 14C-labeled drug were used to measure plasma disappearance, tissue distribution, excretion, and metabolism of the drug at doses from 0.5 to 6 mg/kg. Doses of 2 mg/kg were well tolerated without toxicity. Higher doses (3 to 6 mg/kg) produced mainly intestinal toxicity without significant hematological or liver abnormalities. The 6-mg/kg dose caused severe bloody diarrhea. After administration of 3 mg/kg, plasma concentrations of trimetrexate were 1 microM and were equal to or greater than 0.1 microM at 1 and 24 hr, respectively. The predominant pharmacokinetics of trimetrexate plasma disappearance was an elimination phase with a t1/2 of 3.5 hr. Concentrations in the cerebrospinal fluid were 2 to 5% of that in plasma and were maximum within 1 to 2 hr after i.v. administration. Highest tissue concentrations of drug were measured in liver and kidney; lowest were found in brain and lung. A dose equivalent to 3 mg/kg in humans (on a sq m basis) should produce adequate plasma concentrations (greater than 0.1 microM) for therapeutic effects.
Why All Tibial Polyethylene Bearings are Not the Same? (2018)

Important differences exist in both the materials and geometric forms of tibial bearings across total knee implant systems on the market. The extent of crosslinking, sterilization methods, mechanical/thermal treatment methods used for management of free radicals, the amount of incorporated antioxidants, and the methods for incorporation of antioxidants, are some of the material variables, which may affect bearing clinical performance. Despite initial concerns about increased fatigue damage and failure with crosslinked ultra high molecular weight polyethylene developed to reduce the incidence of osteolysis, their utilization now constitutes close to 50% of tibial bearings in primary operations. This is based on long-term clinical data, which show equivalent or better performance in revisions due to aseptic loosening compared with conventional materials. Similarly, bearing conformity, modularity and mobility, are important geometric elements influencing polyethylene wear and failure. With regard to conformity, conventional wisdom has favored more conforming designs. However, growing body of evidence suggests potential for improved wear performance with less conforming designs enabled by modern polyethylene processing techniques. Long-term clinical data show excellent outcomes for all-polyethylene bearings, which may assume an enhanced role in total knee replacement in the future. In contrast, modern fixed-bearing designs seem to outperform mobile-bearing designs in the long run. Consequently, the use of the mobile bearings has declined over time, and currently they account for about 7% of primary knee replacements.
Pangenome Flux Balance Analysis Toward Panphenomes (2020)

Abstract Studies of the pangenome have been empowered by an exponentially increasing amount of strain-specific genome sequencing data. With this data deluge comes a need for new tools to contextualize, analyze, and interpret such a vast amount of information. Network reconstructions, genome-scale metabolic models (GEMs), and the corresponding computational analysis frameworks such as flux balance analysis (FBA) have been proven useful toward this end. Network reconstructions can be used to interpret genomic variation not just from a single strain but for an entire species. By applying these approaches at the pangenome scale, it becomes possible to systematically evaluate phenotypic properties for an entire species thus enabling the study of a panphenome directly from a pangenome. Applying insights gained from analysis of the panphenome has diverse implications with applications ranging from human health to metabolic engineering. The future of pangenomics will include panphenomic analyses, thus supplementing traditional pangenomic analyses and helping to address the Big-data-to-knowledge grand challenge of analyzing thousands of genomic sequences.
Experimental investigation of resonance curves in dynamic force microscopy (2003)

A precise experimental investigation of the amplitude and phase resonance curves of a driven dynamic force microscope (DFM) cantilever interacting with an Al2O3(0001) surface in ultra-high vacuum is reported. The large amplitude (a few tens of nanometres), high cantilever stiffness (25 N m−1) and high quality factor (a few 104) characterizing these experiments are typical of the frequency modulation (FM) mode of DFM. The whole range of tip–substrate distances where a stationary oscillation of the cantilever can be maintained is explored. It covers two different regimes: a large distance regime where only long range conservative van der Waals interactions contribute and a small distance regime where short range interactions play a significant role. A comparison is made with frequency shift and excitation amplitude curves as a function of the distance acquired in the FM mode. It is also shown that approach–retract amplitude and phase curves usually obtained in the amplitude modulation mode can be extracted from these data. These experimental results are compared with analytical predictions reported in the literature. An excellent agreement is found in the van der Waals domain, allowing us to evaluate the Hamaker constant for the alumina–vacuum–silicon system.
Causal Transfer Random Forest: Leveraging Observational and Randomization Studies (2019)

It is often critical for prediction models to be robust to distributional shifts. Online advertisement platforms, for example, evaluate systems and policy changes using models that predict whether users will click on shown advertisements. Click prediction models built using conventional machine learning methods, however, become unreliable when the new systems or policy significantly shifts the feature distributions away from the available training data—usually large-scale observational data from the online system. In this paper, we describe a causal transfer random forest (CTRF) which combines existing training data with a small amount of data from randomized experiments to make robust predictions under distributional shifts. We learn the CTRF tree structure from randomized data—which breaks spurious correlations between input features and prediction targets—and then calibrate each node with both existing large-scale training data and randomized data. We evaluate the proposed method using data from radical exploration flights in an online ad platform and find that the CTRF outperforms other approaches.
Telomerase as an Important Target of Androgen Signaling Blockade for Prostate Cancer Treatment (2010)

As the mainstay treatment for advanced prostate cancer, androgen deprivation therapy (ADT) targets the action of androgen receptor (AR) by reducing androgen level and/or by using anti-androgen to compete with androgens for binding to AR. Albeit effective in extending survival, ADT is associated with dose-limiting toxicity and the development of castration-resistant prostate cancer (CRPC) after prolonged use. Because CRPC is lethal and incurable, developing effective strategies to enhance the efficacy of ADT and circumvent resistance becomes an urgent task. Continuous AR signaling constitutes one major mechanism underlying the development of CRPC. The present study showed that methylseleninic acid (MSA), an agent that effectively reduces AR abundance, could enhance the cancer-killing efficacy of the anti-androgen bicalutamide in androgen-dependent and CRPC cells. We found that the combination of MSA and bicalutamide produced a robust downregulation of prostate-specific antigen and a recently identified AR target, telomerase, and its catalytic subunit, human telomerase reverse transcriptase. The downregulation of hTERT occurs mainly at the transcriptional level, and reduced AR occupancy of the promoter contributes to downregulation. Furthermore, apoptosis induction by the two agents is significantly mitigated by the restoration of hTERT. Our findings thus indicate that MSA in combination with anti-androgen could represent a viable approach to improve the therapeutic outcome of ADT. Given the critical role of hTERT/telomerase downregulation in mediating the combination effect and the fact that hTERT/telomerase could be measured in blood and urine, hTERT/telomerase could serve as an ideal tumor-specific biomarker to monitor the efficacy of the combination therapy noninvasively.
Parallel Hardware Architectures for the Cryptographic Tate Pairing (2006)

Identity-based cryptography uses pairing functions, which are sophisticated bilinear maps defined on elliptic curves. Computing pairings efficiently in software is presently a relevant research topic. Since such functions are very complex and slow in software, dedicated hardware (HW) implementations are worthy of being studied, but presently only very preliminary research is available. This work affords the problem of designing parallel dedicated HW architectures, i.e., co-processors, for the Tate pairing, in the case of the Duursma-Lee algorithm in characteristic 3. Formal scheduling methodologies are applied to carry out an extensive exploration of the architectural solution space, evaluating the obtained structures by means of different figures of merit such as computation time, circuit area and combinations thereof. Comparisons with the (few) existing proposals are carried out, showing that a large space exists for the efficient parallel HW computation of pairings
Structure and Relative Stability of Dirhodium Tetracamphanate Adducts with 5-Pyrido- 1,4-benzodiazepines and Their 4,5-Dihydro Congeners; First Representatives of Non-Symmetric Bidentate 1,4-Bisnitrogen Ligands (1996)

1H-NMR Spectra of dirhodium tetracamphanate adducts with 5-pyrido-1, 4-benzodiazepin-2-ones 3-5 reveal different modes of complexation. Depending on the structure of the chelating pyridobenzodiazepine, two types of kinetic and dynamic profiles are observed. Ligands 3 and 4, possessing a 1, 4-bisnitrogen subunit with 4p electrons, behave as bidentate ligands and form the kinetically stable 1:1 adducts, non-symmetric diastereomers 6A, 7A, which undergo fast isomerization into the thermodynamically more stable 6A, 7B. Ligand 5 (4, 5-dihydro derivatative of 4) behaves as a pyridine derivative, forming kinetically stable, symmetric 2:1 adduct 8, which very slowly isomerizes into non-symmetric 1:1 adduct 9. The relative stability of 8 is attributed to the hydrogen bonding N(4)-H-O(camphanyl), as well as to the low coordinating ability of the non-conjugated, pyramidal N(4) atom.
Complete mitochondrial genomes of living and extinct pigeons revise the timing of the columbiform radiation (2016)

Our analyses indicate that the earliest radiation of the Columbidae crown group most likely occurred during the Oligocene, with continued divergence of major clades into the Miocene, suggesting that diversification within the Columbidae occurred more recently than has been reported previously.
Populating Web Scale Knowledge Graphs using Distantly Supervised\n Relation Extraction and Validation (2019)

In this paper, we propose a fully automated system to extend knowledge graphs\nusing external information from web-scale corpora. The designed system\nleverages a deep learning based technology for relation extraction that can be\ntrained by a distantly supervised approach. In addition to that, the system\nuses a deep learning approach for knowledge base completion by utilizing the\nglobal structure information of the induced KG to further refine the confidence\nof the newly discovered relations. The designed system does not require any\neffort for adaptation to new languages and domains as it does not use any\nhand-labeled data, NLP analytics and inference rules. Our experiments,\nperformed on a popular academic benchmark demonstrate that the suggested system\nboosts the performance of relation extraction by a wide margin, reporting error\nreductions of 50%, resulting in relative improvement of up to 100%. Also, a\nweb-scale experiment conducted to extend DBPedia with knowledge from Common\nCrawl shows that our system is not only scalable but also does not require any\nadaptation cost, while yielding substantial accuracy gain.\n
Traction control oriented torque-to-slip identification for powered two-wheelers (2015)

In this paper a torque-to-slip model, oriented to the development of a traction control system based on wheel slip control for powered two-wheelers, is identified. A black-box identification approach is employed to find model parameters, using I/O experimentally measured data. Different tests are employed to analyse different features of the inquired dynamics. In particular, a PRBS based identification unearths an average model; step responses are employed to study the effect of the vehicle lean angle and narrow band sine sweeps better quantify the features of an underdamped mode. The resulting model is thus a family of linear models with lean angle and velocity as scheduling parameters. The identified model is proven accurate and suitable for control system design, thanks to a closed-loop experimental validation.