gebhart/patrepeval huggingface dataset:
Microbial production of abscisic acid by Botrytis cinerea. (1982)

Botrytis cinerea, a phytopathogenic fungus causing serious gray mold disease of many kinds of cultivated plants, produces a plant growth inhibitory substance. The active substance was isolated and identified as abscisic acid (ABA), a wellknown plant hormone. This report described a microbial production of ABA, emphasizing that ABAproduction by this fungus was remarkably enahnced by irradiating the fungus with blue light during the culture.
An In Vitro Diagnostic for Multiple Sclerosis Based on C-peptide Binding to Erythrocytes (2016)

Exogenous C-peptide binding to erythrocytes has potential value in distinguishing MS subjects from non-MS neurologic diseases and healthy controls.
Utility-Based Subchannel Allocation for OFDMA Femtocell Networks (2011)

In femtocell networks, due to their small cell size, we can achieve higher spatial diversity from the channel reuse between multiple femtocells. In addition, if femtocells are operated on OFDMA systems, each subchannel can be reused separately among femtocells by carefully treating inter-cell interferences. However, due to a large number of femtocells and their uncoordinated and irregular deployment, we need to treat intercell interferences very carefully in OFDMA-based fmetocell networks, which make developing efficient resource allocation schemes more difficult. In this paper, we study a subchannel allocation problem that aims at maximizing the sum utility of the OFDMA-based femtocell network. Since the problem is formulated as a nonlinear integer programming, which is inherently difficult to solve, we propose a suboptimal subchannel allocation algorithm. The proposed subchannel allocation algorithm consists of two steps: calculating the number of subchannels that should be granted to each femtocell to maximize the sum utility and finding actual subchannel allocation that achieves the granted number of subchannels for each femtocell. Numerical results show that the proposed subchannel allocation algorithm provides near-optimal performance.
Bacterial strain typing in the genomic era (2009)

Bacterial strain typing, or identifying bacteria at the strain level, is particularly important for diagnosis, treatment, and epidemiological surveillance of bacterial infections. This is especially the case for bacteria exhibiting high levels of antibiotic resistance or virulence, and those involved in nosocomial or pandemic infections. Strain typing also has applications in studying bacterial population dynamics. Over the last two decades, molecular methods have progressively replaced phenotypic assays to type bacterial strains. In this article, we review the current bacterial genotyping methods and classify them into three main categories: (1) DNA banding pattern-based methods, which classify bacteria according to the size of fragments generated by amplification and/or enzymatic digestion of genomic DNA, (2) DNA sequencing-based methods, which study the polymorphism of DNA sequences, and (3) DNA hybridization-based methods using nucleotidic probes. We described and compared the applications of genotyping methods to the study of bacterial strain diversity. We also discussed the selection of appropriate genotyping methods and the challenges of bacterial strain typing, described the current trends of genotyping methods, and investigated the progresses allowed by the availability of genomic sequences.
Type I β‐turn conformation is important for biological activity of the melanocyte‐stimulating hormone analogues (1999)

In order to define which structure of alpha-melanocyte-stimulating hormone (MSH) analogues plays a critical role for ligand-receptor interaction and selectivity, we analysed receptor-binding and cAMP-generating activity in Chinese hamster ovary cell lines stably transfected with rMC3R and hMC4R, as well as the NMR structures of chemically synthesized alpha-MSH analogues. Compared with [Ahx4]alpha-MSH, the linear MTII designated as alpha-MSH-ND revealed a preference for the MC4R, whereas its IC50 and EC50 values were comparable to those of MTII reported previously. Truncation of Ahx4 and Asp5 of alpha-MSH-ND remarkably decreased the receptor-binding and cAMP-generating activity. Meanwhile, maximum cAMP-generating activity was observed at a higher concentration (10(-5) M) of alpha-MSH-ND(6-10), and MC4R preference was changed into MC3R preference. In contrast, [Gln6]alpha-MSH-ND(6-10) lost its cAMP-generating activity almost completely, even though it bound to both receptors. Whereas the solution conformation of alpha-MSH-ND revealed a stable type I beta-turn structure, [Gln6]alpha-MSH-ND(6-10) revealed a tight gamma-turn composed of Gln6-D-Phe7-Arg8. Replacement of the His6 residue of alpha-MSH-ND by Gln, Asn, Arg or Lys decreased not only the receptor binding, but also the cAMP-generating activity in both the MC3R and the MC4R. The structure of [Gln6]alpha-MSH-ND exhibited a stable type I' beta-turn comprising Asp5, Gln6, D-Phe7 and Arg8. [Lys6]alpha-MSH-ND showed a greatly reduced binding affinity and cAMP-generating activity with the loss of MC4R selectivity. In NMR studies, [Lys6]alpha-MSH-ND also demonstrated a gamma-turn conformation around Lys6-DPhe7-Arg8. From the above results, we conclude that a type I beta-turn conformation comprising the residues Asp5-His6-(D-Phe7)-Arg8 was important for receptor binding and activation, as well as the selectivity of MSH analogues.
ChemInform Abstract: HALOACETYL GROUPS AS REVERSIBLE PROTECTION OF THE AMINO FUNCTION: CLEAVAGE WITH 2‐AMINOTHIOPHENOL (1979)

Abstract Der Chloracetylrest stellt ein Schutzgruppe für die Aminogruppe in Aminosäuren dar.
Noise margin and leakage in ultra-low leakage SRAM cell design (2002)

Various aspects of ultra-low leakage static random-access memories (SRAM) cell design are considered. It is shown that the high threshold voltage relative to the power supply so improves the stability of the cell that the beta ratio of the design may be made very small for improved performance. Also, the ramifications of threshold uncertainty due to random dopant fluctuations are investigated, and it is shown that chip performance will be adversely affected by this phenomenon.
Clinical Inquiry: Does qHPV vaccine prevent anal intraepithelial neoplasia and condylomata in men? (2015)

Yes. Quadrivalent human papillomavirus (qHPV) vaccine reduces rates of anal intraepithelial neoplasia (AIN) by 50% to 54%, and persistent anal infection by 59%, associated with the 4 types of HPV in the vaccine (6, 11, 16, and 18) in young men who have sex with men (MSM); it also reduces external genital lesions by 66%, and persistent HPV infection associated with the same 4 HPV types by 48 to 59% in all young men, heterosexual men, and MSM.
Wnt pathway is involved in pleomorphic adenomas induced by overexpression of <i>PLAG1</i> in transgenic mice (2005)

Pleomorphic adenoma gene 1 (PLAG1) was found frequently rearranged and activated in human salivary gland pleomorphic adenomas. It encodes a developmentally regulated transcription factor. Ectopic overexpression of PLAG1 has been proposed to play a crucial role in tumorigenesis of salivary gland pleomorphic adenomas. It was reported that PLAG1 can activate the transcription of insulin-like growth factor 2 (IGF2), functioning as a protooncogene. In this report, we show that the salivary gland tumors developed in PLAG1 transgenic mice share major histopathologic features with human pleomorphic adenomas. It was found that beta-catenin, the key component of Wnt signaling pathway, was upregulated at transcriptional level in tumors developed in 3 independent transgenic mouse lines. Immunohistochemical staining revealed that expression of beta-catenin as well as c-myc, downstream of beta-catenin in Wnt signaling pathway, was highly upregulated with overexpression of PLAG1 transgene in tumor and normal transgenic salivary gland tissues. Moreover, we found that PLAG1 can activate the transcription of mouse but not human beta-catenin in the 3T3 cells cotransfected with reporter constructs. Sequence analysis shows there are 4 PLAG1 consensus binding sites in mouse beta-catenin promoter region but not in human. Our findings provide the first in vivo evidence for the oncogenic activity of PLAG1 in pleomorphic adenoma tumorigenesis, reveal a valued animal model for human salivary gland tumors and suggest that Wnt signaling pathway may also contribute to the development of pleomorphic adenomas in transgenic mice.
Easy and direct method for calibrating atomic force microscopy lateral force measurements (2007)

We have designed and tested a new, inexpensive, easy-to-make and easy-to-use calibration standard for atomic force microscopy (AFM) lateral force measurements. This new standard simply consists of a small glass fiber of known dimensions and Young's modulus, which is fixed at one end to a substrate and which can be bent laterally with the AFM tip at the other end. This standard has equal or less error than the commonly used method of using beam mechanics to determine a cantilever's lateral force constant. It is transferable, thus providing a universal tool for comparing the calibrations of different instruments. It does not require knowledge of the cantilever dimensions and composition or its tip height. This standard also allows direct conversion of the photodiode signal to force and, thus, circumvents the requirement for a sensor response (sensitivity) measurement.
A REAL OPTIONS DESIGN FOR QUALITY CONTROL CHARTS (2002)

Abstract We develop a financial model for a manufacturing process where quality can be affected by an assignable cause. We value the real options associated with applying a statistical process control chart using the Black-Scholes equation, binomial and pentanomial lattices, and Monte Carlo simulation methods. This valuation gives decision makers a way to choose the appropriate quality control strategy based on an integrated view of the market dynamics with the manufacturing operational aspects. An industry case is used to demonstrate the application of real options to value control chart decisions. Web based programs are given to value the alternatives in the case study, making the valuation task accessible to other users.
A Survey on an Emerging Area: Deep Learning for Smart City Data (2019)

Rapid urbanization has brought about great challenges to our daily lives, such as traffic congestion, environmental pollution, energy consumption, public safety, and so on. Research on smart cities aims to address these issues with various technologies developed for the Internet of Things. Very recently, the research focus has shifted toward processing of massive amount of data continuously generated within a city environment, e.g., physical and participatory sensing data on traffic flow, air quality, and health care. Techniques from computational intelligence have been applied to process and analyze such data, and to extract useful knowledge that helps citizens better understand their surroundings and informs city authorities to provide better and more efficient public services. Deep learning, as a relatively new paradigm in computational intelligence, has attracted substantial attention of the research community and demonstrated greater potential over traditional techniques. This paper provides a survey of the latest research on the convergence of deep learning and smart city from two perspectives: while the technique-oriented review pays attention to the popular and extended deep learning models, the application-oriented review emphasises the representative application domains in smart cities. Our study showed that there are still many challenges ahead for this emerging area owing to the complex nature of deep learning and wide coverage of smart city applications. We pointed out a number of future directions related to deep learning efficiency, emergent deep learning paradigms, knowledge fusion and privacy preservation, and hope these would move the relevant research one step further in creating truly distributed intelligence for smart cities.
Studies on apple and blueberry fruit constituents: Do the polyphenols reach the colon after ingestion? (2006)

The aim of our studies was to determine the amount of polyphenols reaching the colon after oral intake of apple juice and blueberries. After a polyphenol-free diet healthy ileostomy volunteers consumed a polyphenol-rich cloudy apple juice while others consumed anthocyanin-rich blueberries. Ileostomy effluent was collected and polyphenols were identified using HPLC-DAD as well as HPLC-ESI-MS/MS; quantification was performed with HPLC-DAD. Most of the orally administered apple polyphenols were absorbed from or metabolized in the small intestine. Between 0 and 33% of the oral dose was recovered in the ileostomy bags with a maximum of excretion after 2 h. A higher amount of the blueberry anthocyanins under study (up to 85%, depending on the sugar moiety) were determined in the ileostomy bags and therefore would reach the colon under physiological circumstances. Such structure-related availability has to be considered when polyphenols are used in model systems to study potential preventive effects in colorectal diseases.
Fast Synthesis of ZnO Nanostructures by Laser-Induced Decomposition of Zinc Acetylacetonate (2007)

A CO2 laser (lambda = 10.6 microm) was used to heat a solution of water and alcohol saturated by Zn(AcAc)2 on a fused quartz substrate in open air. After only a few seconds of irradiation, various zinc oxide (ZnO) nanostructures including nanorods and nanowires are formed near the center of the irradiated zone, surrounded by a porous thin film of ZnO nanoparticles. The type of structures produced and their localization on the substrate can be varied by selecting adequate irradiation time and laser power ranges. The deposits have been analyzed using SEM, TEM, EDS, XRD, and Raman spectroscopy, revealing that the nanorods (aspect ratio ~6) and nanowires (aspect ratio ~94) are single-crystalline structures which grow along the c axis of wurtzite ZnO. The nanoparticles are also single-crystalline and have an average diameter of 16 nm. A qualitative model for nanostructure growth is proposed, based on previous studies of aqueous solution and hydrothermal processing.
Leaching and Selective Recovery of Cu from Printed Circuit Boards (2019)

Printed circuit boards (PCBs), a typical end-of-life electronic waste, were collected from an E-waste recycling company located in the Netherlands. Cu and precious metal concentration analyses of the powdered PCBs confirm that the PCBs are multimetallic in nature, rich, but contain high concentrations of Cu, Au, Ag, Pd, and Pt. Ferric sulfate concentration (100 mM), agitation speed (300 rpm), temperature (20 °C), and solid-to-liquid ratio (10 g·L−1) were found to be the optimum conditions for the maximum leaching of Cu from PCBs. The ferric sulfate leachates were further examined for selective recovery of Cu as copper sulfides. The important process variables of sulfide precipitation, such as lixiviant concentration and sulfide dosage were investigated and optimized 100 ppm of ferric sulfate and (copper:sulfide) 1:3 molar ratio, respectively. Over 95% of the dissolved Cu (from the multimetallic leachates) was selectively precipitated as copper sulfide under optimum conditions. The characterization of the copper sulfide precipitates by SEM-EDS analyses showed that the precipitates mainly consist of Cu and S. PCBs can thus be seen as a potential secondary resource for copper.
Making trust explicit in distributed commerce transactions (2002)

In a distributed environment where nodes are independently motivated, many transactions or commercial exchanges may be stymied due to a lack of trust between the participants. The addition of trusted intermediaries may facilitate some exchanges, but others are still problematic. We introduce a language for specifying these commercial exchange problems, and sequencing graphs, a formalism for determining whether a given exchange may occur We also present an algorithm for generating a feasible execution sequence of pairwise exchanges between parties (when it exists). Indemnities may be offered to facilitate previously infeasible transactions. We show when and how they enable commercial transactions.
Effects of sildenafil, a type‐5 cGMP phosphodiesterase inhibitor, and papaverine on cyclic GMP and cyclic AMP levels in the rabbit corpus cavernosum <i>in vitro</i> (1997)

Sildenafil specifically increases cGMP levels in rabbit corpora cavernosa; the increase is greater in the presence of SNP indicating that, in vivo, sildenafil may enhance erection by the augmentation of nitric oxide-mediated relaxation pathways. The erectogenic effect of sildenafil is mediated by a specific enhancement of cGMP accumulation in the corpus cavernosum, consistent with the known activity of sildenafil as a potent and highly selective inhibitor of cGMP-specific PDE.
Attack Type Agnostic Perceptual Enhancement of Adversarial Images (2019)

Adversarial images are samples that are intentionally modified to deceive machine learning systems. They are widely used in applications such as CAPTHAs to help distinguish legitimate human users from bots. However, the noise introduced during the adversarial image generation process degrades the perceptual quality and introduces artificial colours; making it also difficult for humans to classify images and recognise objects. In this letter, we propose a method to enhance the perceptual quality of these adversarial images. The proposed method is attack type agnostic and could be used in association with the existing attacks in the literature. Our experiments show that the generated adversarial images have lower Euclidean distance values while maintaining the same adversarial attack performance. Distances are reduced by 5.88% to 41.27% with an average reduction of 22% over the different attack and network types.
LAMP-2C Inhibits MHC Class II Presentation of Cytoplasmic Antigens by Disrupting Chaperone-Mediated Autophagy (2016)

Cells use multiple autophagy pathways to sequester macromolecules, senescent organelles, and pathogens. Several conserved isoforms of the lysosome-associated membrane protein-2 (LAMP-2) regulate these pathways influencing immune recognition and responses. LAMP-2A is required for chaperone-mediated autophagy (CMA), which promotes Ag capture and MHC class II (MHCII) presentation in B cells and signaling in T cells. LAMP-2B regulates lysosome maturation to impact macroautophagy and phagocytosis. Yet, far less is known about LAMP-2C function. Whereas LAMP2A and LAMP2B mRNA were broadly detected in human tissues, LAMP2C expression was more limited. Transcripts for the three LAMP2 isoforms increased with B cell activation, although specific gene induction varied depending on TLR versus BCR engagement. To examine LAMP-2C function in human B cells and specifically its role in Ag presentation, we used ectopic gene expression. Increased LAMP-2C expression in B cells did not alter MHCII expression or invariant chain processing, but did perturb cytoplasmic Ag presentation via CMA. MHCII presentation of epitopes from exogenous and membrane Ags was not affected by LAMP-2C expression in B cells. Similarly, changes in B cell LAMP-2C expression did not impact macroautophagy. The gene expression of other LAMP2 isoforms and proteasome and lysosomal proteases activities were unperturbed by LAMP-2C ectopic expression. LAMP-2C levels modulated the steady-state expression of several cytoplasmic proteins that are targeted for degradation by CMA and diminished peptide translocation via this pathway. Thus, LAMP-2C serves as a natural inhibitor of CMA that can selectively skew MHCII presentation of cytoplasmic Ags.
Survival prediction of liver cancer patients from CT images using deep learning and radiomic feature-based regression (2020)

Prediction of survival period for patients with hepatocellular carcinoma (HCC) provides important information for treatment planning such as radiotherapy. However, the task is known to be challenging due to the similarity of tumor imaging characteristics from patients with different survival periods. In this paper, we propose a survival prediction method using deep learning and radiomic features from CT images with support vector machine (SVM) regression. First, to extract the deep features, the convolutional neural network (CNN) is trained for the task of classifying the patients for 24-month survival. Second, the radiomic features including texture and shape are extracted from the patient images. After concatenating the radiomic features and the deep features, the SVM regressor is trained to predict the survival period of the patients. The experiment was performed on the CT scans of 171 HCC patients with 5-fold cross validation. In the experiments, the proposed method showed an accuracy of 86.5%, a root-mean-squared-error (RMSE) of 11.6, and a Spearman rank coefficient of 0.11. In comparisons with the deep feature-only- and radiomic feature-only regression results, the proposed method showed improved accuracy and RMSE than both, but lower rank coefficient than the radiomic feature-only regression. It can be observed that (1) the deep learning of CT images has a promising potential for predicting the survival period of HCC patients, and (2) the radiomic feature analysis provides useful information to strengthen the power of deep learning-based survival prediction.
Polarimetric Analysis of Backscatter From the Deepwater Horizon Oil Spill Using L-Band Synthetic Aperture Radar (2012)

We analyze the fully-polarimetric Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) data acquired on June 23, 2010, from two adjacent, overlapping flight tracks that imaged the main oil slick near the Deepwater Horizon (DWH) rig site in the Gulf of Mexico. Our results show that radar backscatter from both clean water and oil in the slick is predominantly from a single surface scatterer, consistent with the tilted Bragg scattering mechanism, across the range of incidence angles from 26° to 60°. We show that the change of backscatter over the main slick is due both to a damping of the ocean wave spectral components by the oil and an effective reduction of the dielectric constant resulting from a mixture of 65-90% oil with water in the surface layer. This shows that synthetic aperture radar can be used to measure the oil volumetric concentration in a thick slick. Using the H/A/α parameters, we show that surface scattering is dominant for oil and water whenever the data are above the noise floor and that the entropy (H) and α parameters for the DWH slick are comparable to those from the clean water. The anisotropy, A, parameter shows substantial variation across the oil slick and a significant range-dependent signal whenever the backscatter in all channels is above the instrument noise floor. For slick detection, we find the most reliable indicator to be the major eigenvalue of the coherency matrix, which is approximately equal to the total backscatter power for both oil in the slick and clean sea water.