gebhart/patrepeval huggingface dataset:
Protein Kinase C Receptor Binding Assay for the Detection of Chemopreventive Agents from Natural Products (1997)

Protein Kinase C (PKC) is generally believed to play a central role in signal transduction, cellular growth control, gene expression, and tumor promotion. And it has been suggested that inhibitors of PKC might play important roles for the prevention and treatment of cancer. In order to investigate the possible inhibitors of PKC from natural products, PKC receptor binding assay was performed using bovine brain particulate as a source of PKC and the amount of 12,13-dibutyrate (PDBu) bound to PKC was measured in the presence of test materials. Total methanol extracts from 100 kinds of natural products were partitioned into 3 fractions (n-hexane, ethyl acetate and aqueous layer) and their binding ability to the regulatory domain of PKC was evaluated. The ethyl acetate fractions of Morus alba , Rehmannia glutinosa , Lysimachia foenum-graecum , Polygonum cuspidata , Cnidium officinale , and the hexane and the EtOAc fraction of Symplocarpus nipponicus showed inhibitory activity of binding to PKC.
Power consumption estimation of CPU and peripheral components in virtual machines (2013)

Energy consumption of IT increased continuously during the last decades. Numerous works have been accomplished for improving energy efficiency of hardware whereas software energy efficiency has been ignored for a long time. This contribution presents a novel approach for estimating energy consumption of computer systems in dependency of software-caused workloads in different execution environments. The system is the basis for automatic optimization of software execution in an energy-efficient way by finding the best-suiting host computer (and best-suiting peripheral devices). Thus, it opens novel ways to further improve energy-efficiency of IT systems by migrating software-caused load to an energy-efficient target. Exemplary, the approach is tested in a virtualized data center environment, where virtual machines are the applications. The presented approach is a vehicle for automatically computing an energy-efficient virtual machine placement. The paper presents a new algorithm for estimating virtual machine power consumption, which consists of CPU power consumption estimation as well as power usage estimation of peripheral components like hard disk drive and network interface controller. The accuracy of the presented approach is proved by means of measurements.
MUSEFood: Multi-sensor-based Food Volume Estimation on Smartphones (2019)

Researches have shown that diet recording can help people increase awareness of food intake and improve nutrition management, and thereby maintain a healthier life. Recently, researchers have been working on smartphone-based diet recording methods and applications that help users accomplish two tasks: record what they eat and how much they eat. Although the former task has made great progress through adopting image recognition technology, it is still a challenge to estimate the volume of foods accurately and conveniently. In this paper, we propose a novel method, named MUSEFood, for food volume estimation. MUSEFood uses the camera to capture photos of the food, but unlike existing volume measurement methods, MUSEFood requires neither training images with volume information nor placing a reference object of known size while taking photos. In addition, considering the impact of different containers on the contour shape of foods, MUSEFood uses a multi-task learning framework to improve the accuracy of food segmentation, and uses a differential model applicable for various containers to further reduce the negative impact of container differences on volume estimation accuracy. Furthermore, MUSEFood uses the microphone and the speaker to accurately measure the vertical distance from the camera to the food in a noisy environment, thus scaling the size of food in the image to its actual size. The experiments on real foods indicate that MUSEFood outperforms state-of-the-art approaches, and highly improves the speed of food volume estimation.
Role of prostaglandin E2 in zinc absorption in the rat. (1978)

The supernatant of cytoplasmic extract of rat small intestine was mixed with 65Zn and subjected to Sephadex G-75 column chromatography. The activity of 65Zn was detected in four peaks with estimated 800, 10,000, 50,000-75,000 mol wt, and larger than 100,000 daltons. The zinc-binding ligand from the 800 mol wt peak was prostaglandin or prostaglandin-like as indicated by ultra-violet absorption spectrum, by absorption spectrum shift in alcoholic potassium hydroxide, by its effects on pulmonary vascular resistance, and by radioimmunoassay. Addition of prostaglandin E2 or prostaglandin extracted from rat small intestine with ethyl acetate into the lumen of intestinal sacs resulted in a two to threefold increase in the activity of 65Zn in the external medium after 15-20 min incubation. The absorption and tissue distribution of orally administered 65Zn were decreased by 60% in indomethacin-treated rats and increased 70% when ethyl acetate-extracted prostaglandin and radioactive zinc were given simultaneously. These data suggest that prostaglandin not only binds zinc, but also facilitates its transport across the intestinal mucosa.
Correlates of farmers' variables with productivity in dryland crops. (2010)

Dryland farming is way of life for a majority of Indian farmers. It is characterized by the resource poor, small and marginal farmers, a poor infrastructure and low investments in technology and inputs. Dryland farming means cultivation of crops purely under rainfed conditions where soil moisture is limited for crop growth. It is not possible to have any practical control over the occurrence of rainfall and drought. The best way is to live with the situation and find out ways and means of sustainable dryland farming. Dryland farming involves the use of low-cost, on-farm resource, simple and manageable technologies that are ecologically compatible, environmentally friendly and economically profitable. For achieving sustainability under dryland farming production, each and every aspect of crop production (nutrient and water management, soil and water conservation, pest and disease management, etc.) has to be taken care of. It is inevitable that the second green-revolution has to come from the dryland farming and accordingly the application of technology, inputs and investments has to be tailored to converts these so-called “grey areas into green”. The South-West zone of Haryana offers ample scope for the development of dryland areas for production of dry land crops. This study highlights that the utilization of inputs, adoption of recommended crop production technologies and adoption of recommended resource conserving technologies had significant positive relationship with productivity of rapeseed & mustard and bajra. The variables such as farming experience and mass media use had the significant positive relationship with productivity of rapeseed & mustard and bajra. The technological variables, viz; adoption of recommended resource conserving technologies and personal variable like farming experience in cultivation of gram had significant positive relationship with productivity of gram.
In Vitro and In Vivo Induction of Antiangiogenic Activity by Plasminogen Activators and Captopril (2003)

Treatment with rt-PA and captopril induced antiangiogenic activity in vitro and in vivo that appears to be independent of angiostatin.
Recombinant interleukin 4 suppresses the production of interferon gamma by human mononuclear cells. (1989)

rIL-4 inhibits the production of IFN-gamma by PBMC stimulated with mitogens or allogeneic cells. The suppression is observed at the protein and at the mRNA level; it is dose and time dependent, and it is abolished by a neutralizing mAb to IL-4. It is suggested that the balance between the production of IL-4 and IFN-gamma may be significantly influenced by the chronological order of activation of their respective gene.
Experimental and Theoretical Studies on the Thermal Decomposition of Heterocyclic Nitrosimines<sup>1</sup> (2001)

A series of substituted 2-nitrosiminobenzothiazolines (2) were synthesized by the nitrosation of the corresponding 2-iminobenzothiazolines (6). Thermal decomposition of 2a--f and of the seleno analogue 7 in methanol and of 3-methyl-2-nitrosobenzothiazoline (2a) in acetonitrile, 1,4-dioxane, and cyclohexane followed first-order kinetics. The activation parameters for thermal deazetization of 2a were measured in cyclohexane (Delta H(++) = 25.3 +/- 0.5 kcal/mol, Delta S(++) = 1.3 +/- 1.5 eu) and in methanol (Delta H(++) = 22.5 +/- 0.7 kcal/mol, Delta S(++) = -12.9 +/- 2.1 eu). These results indicate a unimolecular decomposition and are consistent with a proposed stepwise mechanism involving cyclization of the nitrosimine followed by loss of N(2). The ground-state conformations of the parent nitrosiminothiazoline (9a) and transition states for rotation around the exocyclic C==N bond, electrocyclic ring closure, and loss of N(2) were calculated using ab initio molecular orbital theory at the MP2/6-31G* level. The calculated gas-phase barrier height for the loss of N(2) from 9a (25.2 kcal/mol, MP4(SDQ, FC)/6-31G*//MP2/6-31G* + ZPE) compares favorably with the experimental barrier for 2a of 25.3 kcal/mol in cyclohexane. The potential energy surface is unusual; the rotational transition state 9a-rot-ts connects directly to the orthogonal transition state for ring-closure 9aTS. The decoupling of rotational and pseudopericyclic bond-forming transition states is contrasted with the single pericyclic transition state (15TS) for the electrocyclic ring-opening of oxetene (15) to acrolein (16). For comparison, the calculated homolytic strength of the N--NO bond is 40.0 kcal/mol (MP4(SDQ, FC)/6-31G*//MP2/6-31G* + ZPE).
Signal processing design for an ADSL high speed equalizer (2002)

An asymmetric digital subscriber line (ADSL) is an emerging technology for the transport of video services or other asymmetric high bit-rate services over the copper local loop plant. This paper describes the design and implementation of a high speed equalizer for an ADSL research prototype. This equalizer contains two complex adaptive 32-tap equalizers, and is capable of processing QAM or carrierless amplitude/phase (CAP) modulation signals up to 1 MBaud in speed. Implementation is via off-the-shelf fixed and programmable DSPs, with a resulting throughput in excess of 300 MIPS. Experimental results are presented indicating a reach of 18 kft of twisted copper pair for the system.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Chiral Phosphine Lewis Bases Catalyzed Asymmetric aza-Baylis−Hillman Reaction of N-Sulfonated Imines with Activated Olefins (2005)

In the aza-Baylis-Hillman reaction of N-sulfonated imines (N-arylmethylidene-4-methylbenzenesulfonamides and others) with methyl vinyl ketone, ethyl vinyl ketone, and acrolein, we found that, in the presence of a catalytic amount of chiral phosphine Lewis base such as (R)-2'-diphenylphosphanyl-[1,1']binaphthalenyl-2-ol LB1 (10 mol %) and molecular sieve 4A, the corresponding aza-Baylis-Hillman adducts could be obtained in good yields with good to high ee (70-95% ee) at low temperature (approximately -30 to -20 degrees C) or at room temperature in THF, respectively. In CH2Cl2 upon heating at 40 degrees C, the aza-Baylis-Hillman reaction of N-sulfonated imines with phenyl acrylate or naphthyl acrylate gave the adducts in good to high yields (60-97%) with moderate ee (52-77%). The mechanistic insight has been investigated by 31P and 1H NMR spectroscopic measurements. The key enolate intermediate, which has been stabilized by intramolecular hydrogen bonding, has been observed by 31P and 1H NMR spectroscopy. An effective bifunctional Lewis base and Bronsted acid phosphine Lewis base system has been disclosed in this catalytic, asymmetric aza-Baylis-Hillman reaction.
Enhanced nondestructive holographic readout in strontium barium niobate (1988)

We describe a novel procedure for obtaining enhanced nondestructive holographic readout in SBN, where the key new ingredient is utilization of degrees of freedom in polarization of the reconstruction beam. The effect also involves spatial frequency and the applied voltage during both the recording and the reconstruction. The reconstructed beam first drops in intensity but subsequently grows in strength above the starting value, approaching 100% efficiency in some cases. More than 6 h of continuous readout has been achieved, with efficiency remaining strong enough to give more than 10(9) 10-microsec readouts with signal-to-noise ratios exceeding 20 dB.
Agreement with the disulfide stretching frequency-conformation correlation of Sugeta, Go, and Miyazawa. (1986)

Two hypotheses have been advanced to explain the conformational dependence of the disulfide stretching frequency of the CCSSCC moiety in unstrained disulfides. Such compounds can adopt conformations that exhibit disulfide stretching bands near 510, 525, and 540 cm-1. Sugeta et al. [Sugeta, H., Go, A. & Miyazawa, T. (1973) Bull. Chem. Soc. Jpn. 46, 3407-3411] have attributed these three bands to conformations having none, one, and two trans conformations, respectively, about the C-S bonds. In apparent contradiction to this correlation, Van Wart and Scheraga [Van Wart, H. E. & Scheraga, H. A. (1976) J. Phys. Chem. 80, 1812-1823] found that dithioglycolic acid crystals, believed at the time to exist only in the trans conformation about both C-S bonds, exhibited the S-S stretching band near 510 cm-1. On the basis of this observation, it was suggested instead that the 510, 525, and 540 cm-1 bands arose from CCSSCC moieties having none, one, and two A conformations (i.e., those with CC-SS dihedral angles close to 30 degrees), respectively, about the C-S bonds. It has recently been shown by Nash et al. [Nash, C. P., Olmstead, M. M., Weiss-Lopez, B., Musker, W. K., Ramasubbu, M. & Parthasarathy, R. (1985) J. Am. Chem. Soc. 107, 7194-7195] that dithioglycolic acid can crystallize in two different forms, one with trans and the other with gauche conformations about both C-S bonds, and that these have S-S stretching bands at 536 and 510 cm-1, respectively. These results are confirmed here and it is shown that our earlier data were collected on the all-gauche (rather than the all-trans) form. Thus, the correlation proposed by Sugeta et al. is correct.
Page Stream Segmentation with Convolutional Neural Nets Combining Textual and Visual Features (2017)

In recent years, (retro-)digitizing paper-based files became a major undertaking for private and public archives as well as an important task in electronic mailroom applications. As a first step, the workflow involves scanning and Optical Character Recognition (OCR) of documents. Preservation of document contexts of single page scans is a major requirement in this context. To facilitate workflows involving very large amounts of paper scans, page stream segmentation (PSS) is the task to automatically separate a stream of scanned images into multi-page documents. In a digitization project together with a German federal archive, we developed a novel approach based on convolutional neural networks (CNN) combining image and text features to achieve optimal document separation results. Evaluation shows that our PSS architecture achieves an accuracy up to 93 % which can be regarded as a new state-of-the-art for this task.
Dichlorocarbene modification of styrene–butadiene rubber (1998)

Dichlorocarbene-modified styrene–butadiene rubber (SBR) prepared by the alkaline hydrolysis of chloroform using cetyltrimethylammonium bromide as a phase-transfer agent resulted in a product that showed good mechanical properties, excellent flame resistance, solvent resistance, and good thermal stability. The activation energy for this chemical reaction calculated from the time–temperature data on the chemical reaction by the measurement of the percentage of chlorine indicated that the reaction proceeded according to first-order kinetics. The molecular weight of the polymers, determined by gel permeation chromatography, showed that chemical modification was accompanied by an increase in molecular weight. The chemical modification was characterized by proton NMR, FTIR studies, thermogravimetric analysis, and flammability measurement. Proton NMR and FTIR studies revealed the attachment of chlorine through cyclopropyl rings to the double bond of butadiene. © 1998 John Wiley & Sons, Inc. J Appl Polym Sci 68: 153–160, 1998
Imaging artifacts in magnetic induction tomography caused by the structural incorrectness of the sensor model (2010)

Magnetic induction tomography (MIT) is a noninvasive imaging modality that aims to reconstruct the interior electrical conductivity distribution of the human body. It uses magnetic induction to excite eddy currents in the body and an array of sensor coils to detect the perturbations in the magnetic field. Image reconstruction in MIT is usually carried out by minimizing the residuals between the estimated and measured quantities assuming a structurally correct model. Thus, any mismatch between the simulated and the true experimental coil setup alters the data and may cause artifacts in the images. In this paper, a simulation study was performed to investigate the effect of modeling mismatches on measurements and corresponding reconstructed images. It was found that slight distortions of the receivers may cause up to 20% deviations in the data considering a local and small perturbation in conductivity. Unless the geometry is modeled correctly, these artifacts may spoil the images particularly for the case of flexible systems that have many degrees of freedom and systems that require different adjustments for different imaging sessions. If the system does not need calibration, for instance as in the case of head applications, then a rigid mechanical support appears to be an important design issue to achieve a better image quality.
Automatic product feature extraction from online product reviews using maximum entropy with lexical and syntactic features (2008)

The task of product feature extraction is to find product features that customers refer to their topic reviews. It would be useful to characterize the opinions about the products. We propose an approach for product feature extraction by combining lexical and syntactic features with a maximum entropy model. For the underlying principle of maximum entropy, it prefers the uniform distributions if there is no external knowledge. Using a maximum entropy approach, firstly we extract the learning features from the annotated corpus, secondly we train the maximum entropy model, thirdly we use trained model to extract product features, and finally we apply a natural language processing technique in postprocessing step to discover the remaining product features. Our experimental results show that this approach is suitable for automatic product feature extraction.
Pharmakologisches über Luminal oder Phenyläthylbarbitursäure (1912)

Drug Prescribing for Patients with Chronic Kidney Disease in General Practice: a Cross-Sectional Study
Supporting Control-Flow-Dependent Execution Times on WCET Calculation (2000)

Embedded computer systems commonly interact with the environment. There may be some realtime constraints imposed on this interaction. To guaranteesuchconstraints the knowledge about the worst case execution time (WCET) of the system components is mandatory. In the last years several concepts have been developed to obtain the WCET statically by code analysis or dynamically by measurements. In this paper we describe a method for static WCET analysis. This methodisbased on analysis with implicit path enumeration by the use of linear programming. This is a quite efficient approach with respect to the analysis time. We present a graph based formalism to analyze programs. This formalism handles in a smart way the different execution times of conditional instructions whether the branch is taken or not. This approach enables the calculation of tight WCET result with small effort.
A Scaled Conjugate Gradient Algorithm for Fast Supervised Learning (1990)

<p>A supervised learning algorithm (Scaled Conjugate Gradient, SCG) with superlinear convergence rate is introduced. The algorithm is based upon a class of optimization techniques well known in numerical analysis as the Conjugate Gradient Methods. SCG uses second order information from the neural network but requires only O(N) memory usage, where N is the number of weights in the network. The performance of SCG is benchmarked against the performance of the standard backpropagation algorithm (BP), the conjugate gradient backpropagation (CGB) and the one-step Broyden-Fletcher-Goldfarb-Shanno memoryless quasi-Newton algorithm (BFGS). SCG yields a speed-up of at least an order of magnitude relative to BP. The speed-up depends on the convergence criterion, i.e., the bigger demand for reduction in error the bigger the speed-up. SCG is fully automated including no user dependent parameters and avoids a time consuming line-search, which CGB and BFGS use in each iteration in order to determine an appropriate step size.</p><p> </p><p>Incorporating problem dependent structural information in the architecture of a neural network often lowers the overall complexity. The smaller the complexity of the neural network relative to the problem domain, the bigger the possibility that the weight space contains long ravines characterized by sharp curvature. While BP is inefficient on these ravine phenomena, it is shown that SCG handles them effectively.</p>
Ensemble-Based Closed-Loop Optimization Applied to Brugge Field (2009)

Abstract In closed-loop reservoir management, geologic properties are updated sequentially using available data, and model-based optimization is used to search for the optimal operating strategy. Ensemble-based methods can be used to solve both data assimilation and production optimization with the gradient approximated from an ensemble. This ensemble-based closed-loop optimization method is flexible and has been illustrated using a small scale problem in Chen et al. (2008). The dimensionality of the model parameter and control parameter space are high in large scale problems. Approximating the gradient using small ensembles might result in unsatisfactory solution of the ensemble-based closed-loop optimization. In this paper the ensemble-based closed-loop optimization is applied to a large scale SPE Benchmark study. Brugge field, a synthetic reservoir, is designed as a common platform to test different methods for closed-loop reservoir management. The problem was designed to mimic real field scenarios, and as a result is by far the largest and most complex test case on closed-loop optimization. The Brugge field model consists of nine layers and the number of active cells is 44550. It has one internal fault and seven rock regions with different relative permeability and capillary pressure functions. There are 20 producers and 10 injectors in the field. Noise corrupted production data are provided monthly. Additionally, time-lapse seismic data are available at year ten. Each well has three different completions that can be controlled independently. The producing life of the reservoir is 30 years and the objective of optimization is to maximize the net present value at the end of 30 years. Due to the complexity of this test case, several advanced techniques are used in order to improve the solution of the ensemble-based closed-loop optimization. Saturation normalization is used to account for the presence of difference rock regions. Localization is used in the assimilation of production and seismic data to increase the effective size of the ensemble and to alleviate the effect of spurious correlations resulted from the small ensemble. Relative permeability curves and initial oil water contact are estimated together with the gridblock properties. Covariance inflation is used to maintain the desired variability in the ensemble. We expect that these techniques will also be critical in real field application of the ensemble-based closed-loop optimization.