Miracle-dz/UniFAR-FTUs huggingface dataset:
Bench to Bed Evidences for Pharmacokinetic and Pharmacodynamic Interactions Involving Oseltamivir and Chinese Medicine

Oseltamivir (OA), an ethyl ester prodrug of oseltamivir carboxylate (OC), is clinically used as a potent and selective inhibitor of neuraminidase. Chinese medicines have been advocated to combine with conventional drug for avian influenza. The current study aims to investigate the potential pharmacokinetic and pharmacodynamic interactions of a Chinese medicine formula, namely, Yin Qiao San and Sang Ju Yin (CMF1), commonly used for anti-influenza in combination with OA in both rat and human, and to reveal the underlined mechanisms. It was found that although C max, AUC and urinary recovery of OC, as well as metabolic ratio (AUCOC/AUCOA), were significantly decreased in a dose-dependent manner following combination use of CMF1 and OA in rat studies (P < 0.01), such coadministration in 14 healthy volunteers only resulted in a trend of minor decrease in the related parameters. Further mechanistic studies found that although CMF1 could reduce absorption and metabolism of OA, it appears to enhance viral inhibition of OA (P < 0.01). In summary, although there was potential interaction between OA and CMF1 found in rat studies, its clinical impact was expected to be minimal. The coadministration of OA and CMF1 at the clinical recommended dosages is, therefore, considered to be safe.
Altered Extracellular Signal-regulated Kinase Signal Transduction by the Muscarinic Acetylcholine and Metabotropic Glutamate Receptors after Cerebral Ischemia*

To determine whether muscarinic acetylcholine receptors (mAChR) in the post-ischemic hippocampus may be involved in altered extracellular signal-regulated kinases (ERK) signal transduction, we have investigated changes in the activity of ERK1/2 induced by a muscarinic agonist, carbachol. Cerebral ischemia was produced in the rat by injecting 900 microspheres (48 μm in diameter) into the right internal carotid artery. Applying carbachol to the contralateral hippocampal slices from ischemic rats increased the phosphorylation of ERK1/2 but did not increase phosphorylation in the ipsilateral hippocampus. Analysis of M1 mAChR binding showed that there was no significant difference in the number and Kd values between the hippocampi from naı̈ve and ischemic rats. Immunoblotting analysis showed no significant difference in the amount of M1 mAChR in both hemispheres. In contrast to carbachol stimulation, the protein kinase C activator induced an activation of ERK1/2 in the ipsilateral hippocampus. This increase was shown to occur in neurons by immunofluorescence colocalization study. Carbachol-stimulated tyrosine phosphorylation of the Gαq/11, inositol 1,4,5-trisphosphate formation, and association of Gαq/11with phospholipase Cβ1 were attenuated in the ipsilateral hippocampus. We also found that stimulation of group I metabotropic glutamate receptors, which are linked to Gαq/11, failed to increase in phosphorylation of ERK1/2 in the ipsilateral hippocampus. These results suggest that failure in receptor-mediated tyrosine phosphorylation of the Gαq/11 subunit and a defect in receptor-Gαq/11-effector coupling in the ischemic hippocampus may be involved in alterations of ERK signal transduction.
Recent Trends in Analysis of Algorithms and Complexity Theory Analysis Two Stage Feature Selection for Classification of Microarray Databases

Classification of microarray data with high dimension and small sample size is a complex task. This work explores the optimal search space appropriate for classification. Here the crush of dimensionality is handled with a two stages feature selection technique. At the first stage, statistical measures are used to remove genes that do not contribute for classification. In the second stage, attributes are arranged in a non-increasing order of signal to noise ratio (SNR). The number of attributes to be considered from this stage is a challenging task. Selection of very few numbers of genes may not help representing the properties of each class properly, while selection of a large numbers of genes also leads to diminishing classifier performance. A set of four classifiers such as artificial neural network, naïve Bayes, k-nearest neighbor, multiple linear regression classifier and ten microarray databases are considered for this experimentation. For each microarray data and for each classifier, selection for different set of genes improves the performance. However, the analysis shows that a favorable set of genes can be suggested to improve performance and another set of genes can be suggested to avoid which degrades the performance.
Automated feature discovery via sentence selection and source code summarization

Programs are, in essence, a collection of implemented features. Feature discovery in software engineering is the task of identifying key functionalities that a program implements. Manual feature discovery can be time consuming and expensive, leading to automatic feature discovery tools being developed. However, these approaches typically only describe features using lists of keywords, which can be difficult for readers who are not already familiar with the source code. An alternative to keyword lists is sentence selection, in which one sentence is chosen from among the sentences in a text document to describe that document. Sentence selection has been widely studied in the context of natural language summarization but is only beginning to be explored as a solution to feature discovery. In this paper, we compare four sentence selection strategies for the purpose of feature discovery. Two are off‐the‐shelf approaches, while two are adaptations we propose. We present our findings as guidelines and recommendations to designers of feature discovery tools. Copyright © 2016 John Wiley & Sons, Ltd.
Leveraging Inflection Tables for Stemming and Lemmatization.

We present several methods for stemming and lemmatization based on discriminative string transduction. We exploit the paradigmatic regularity of semi-structured inflection tables to identify stems in an unsupervised manner with over 85% accuracy. Experiments on English, Dutch and German show that our stemmers substantially outperform Snowball and Morfessor, and approach the accuracy of a supervised model. Furthermore, the generated stems are more consistent than those annotated by experts. Our direct lemmatization model is more accurate than Morfette and Lemming on most datasets. Finally, we test our methods on the data from the shared task on morphological reinflection.
A Novel Role of Peripheral Corticotropin-Releasing Hormone (CRH) on Dermal Fibroblasts

Corticotropin-releasing hormone, or factor, (CRH or CRF) exerts important biological effects in multiple peripheral tissues via paracrine/autocrine actions. The aim of our study was to assess the effects of endogenous CRH in the biology of mouse and human skin fibroblasts, the primary cell type involved in wound healing. We show expression of CRH and its receptors in primary fibroblasts, and we demonstrate the functionality of fibroblast CRH receptors by induction of cAMP. Fibroblasts genetically deficient in Crh (Crh−/−) had higher proliferation and migration rates and compromised production of IL-6 and TGF-β1 compared to the wildtype (Crh+/+) cells. Human primary cultures of foreskin fibroblasts exposed to the CRF1 antagonist antalarmin recapitulated the findings in the Crh−/− cells, exhibiting altered proliferative and migratory behavior and suppressed production of IL-6. In conclusion, our findings show an important role of fibroblast-expressed CRH in the proliferation, migration, and cytokine production of these cells, processes associated with the skin response to injury. Our data suggest that the immunomodulatory effects of CRH may include an important, albeit not explored yet, role in epidermal tissue remodeling and regeneration and maintenance of tissue homeostasis.
A Post Keynesian Theory of Asset Price Inflation with Endogenous Money

A fundamental building block of Post Keynesian economics recognizes that a modem economy's stock of money is endogenous, since the banking system is able to supply any quantity of credit money on demand (Davidson, 1968; Robinson, 1970; Weintraub and Davidson, 1973; Kaldor, 1980; Moore, 1988; Wray, 1990). This means that inflation cannot be caused by nominal money supply growth but is due to nonmonetary factors such as income distribution conflict in the labor market (Wallich and Weintraub, 1971; Eichner and Kregel, 1975; Rowthorn, 1977; Davidson, 1978, pp. 347-52; Cornwall, 1984; Kregel, 1989; Dalziel, 1990; Arestis and Skott, 1993). Over the last decade or longer, high unemployment and antiunion legislation in the English-language OECD countries have weakened the ability of organized labor to press for higher wages. As Post Keynesian theory predicts, this has suppressed consumer price inflation at the expense of greater income disparities. Throughout this period, however, there have been several episodes around the world in which property prices or the value of sharemarket equities have risen significantly, even while consumer prices and workers' wages remained relatively stable. Such asset price inflations require close attention, for at least two reasons. First, an increase in sharemarket or property values can itself contribute to more general inflationary pressures (through wealth effects on consumer expenditure,
Defined types of cortical interneurone structure space and spike timing in the hippocampus

The cerebral cortex encodes, stores and combines information about the internal and external environment in rhythmic activity of multiple frequency ranges. Neurones of the cortex can be defined, recognized and compared on the comprehensive application of the following measures: (i) brain area‐ and cell domain‐specific distribution of input and output synapses, (ii) expression of molecules involved in cell signalling, (iii) membrane and synaptic properties reflecting the expression of membrane proteins, (iv) temporal structure of firing in vivo, resulting from (i)–(iii). Spatial and temporal measures of neurones in the network reflect an indivisible unity of evolutionary design, i.e. neurones do not have separate structure or function. The blueprint of this design is most easily accessible in the CA1 area of the hippocampus, where a relatively uniform population of pyramidal cells and their inputs follow an instantly recognizable laminated pattern and act within stereotyped network activity patterns. Reviewing the cell types and their spatio‐temporal interactions, we suggest that CA1 pyramidal cells are supported by at least 16 distinct types of GABAergic neurone. During a given behaviour‐contingent network oscillation, interneurones of a given type exhibit similar firing patterns. During different network oscillations representing two distinct brain states, interneurones of the same class show different firing patterns modulating their postsynaptic target‐domain in a brain‐state‐dependent manner. These results suggest roles for specific interneurone types in structuring the activity of pyramidal cells via their respective target domains, and accurately timing and synchronizing pyramidal cell discharge, rather than providing generalized inhibition. Finally, interneurones belonging to different classes may fire preferentially at distinct time points during a given oscillation. As different interneurones innervate distinct domains of the pyramidal cells, the different compartments will receive GABAergic input differentiated in time. Such a dynamic, spatio‐temporal, GABAergic control, which evolves distinct patterns during different brain states, is ideally suited to regulating the input integration of individual pyramidal cells contributing to the formation of cell assemblies and representations in the hippocampus and, probably, throughout the cerebral cortex.
An analysis of patterns of debugging among novice computer science students

The process by which students learn to program is a major issue in computer science educational research. Programming is a fundamental part of the computer science curriculum, but one which is often problematic. It seems to be difficult to find an effective method of teaching that is suitable for all students. In this research we tried to gain insights into ways of improving our teaching by a careful examination of students' mistakes. The compiler errors that were generated by their programs together with the pattern that was observed in their debugging activities formed the basis of this research. We discovered that many students with a good understanding of programming do not acquire the skills to debug programs effectively, and this is a major impediment to their producing working code of any complexity. Skill at debugging seems to increase a programmer's confidence and we suggest that more emphasis be placed on debugging skills in the teaching of programming.
Dependence of radio halo properties on star formation activity and galaxy mass

We investigate the relation between the existence and size of radio halos, which are believed to be created by star formation (SF) related energy input into the interstellar medium, and other galaxy properties, most importantly star formation activity and galaxy mass. Based on radio continuum and Hobservations of a sample of seven late-type spiral galaxies we find a direct, linear correlation of the radial extent of gaseous halos on the size of the actively star-forming parts of the galaxy disks. Data of a larger sample of 22 galaxies indicate that the threshold energy input rate into the disk ISM per unit surface area for the creation of a gaseous halo depends on the mass surface density of the galaxy, in the sense that a higher threshold must be surpassed for galaxies with a higher surface density. Because of the good prediction of the existence of a radio halo from these two parameters, we conclude that they are important, albeit not the only contributors. The compactness of the SF-related energy input is also found to be a relevant factor. Galaxies with relatively compact SF distributions are more likely to have gaseous halos than others with more widespread SF activity. These results quantify the so-called "break-out" condition for matter to escape from galaxy disks, as used in all current models of the interstellar medium and first defined by Norman & Ikeuchi (1989).
The Mediating Role of Early Maladaptive Schemas in the Relation between Co-Rumination and Depression in Young Adults

Research on co-rumination has investigated its relationship with internalizing symptoms, but few studies have addressed underlying maladaptive cognitive-affective processes that may play an important role in the maintenance of this relation. This study examines if Young’s schema domains mediate the relation between co-rumination and depression in a community sample of non-clinical young adults. Participants completed the Co-Rumination Questionnaire, Young Schema Questionnaire-L3, and Teate Depression Inventory. Correlations and path analysis were calculated for the full sample and separately by gender. The schema domains of Overvigilance/Inhibition and Other-Directedness fully mediated the relation between co-rumination and depression. When analyses were performed separately for males and females, mediation persisted only for females. Findings suggest that among young women, co-rumination with a friend may be associated with depressive symptoms because of its activation of specific maladaptive cognitive schemas. Better understanding of the content and processes underpinning co-rumination may have important implications for the prevention and treatment of depression.
Wavelet Frame Based Multiphase Image Segmentation

Wavelet frames have been successfully applied to various image restoration problems, such as denoising, inpainting, and deblurring. However, they are rarely used in geometric applications, except for the recent work of [B. Dong, A. Chien, and Z. Shen, Commun. Math. Sci., 9 (2011), pp. 551--559; B. Dong and Z. Shen, in Proceedings of the SPIE, Vol. 8401, 2012, 840102]. Motivated by the theoretical connection between wavelet frame based and total variation based image restoration models recently established in [J.-F. Cai, B. Dong, S. Osher, and Z. Shen, J. Amer. Math. Soc. , 25 (2012), pp. 1033--1089], we propose here a convex multiphase segmentation model based on wavelet frame transform. The proposed model allows us to automatically identify complex tubular structures, including blood vessels, leaf vein systems, etc. Numerical results show that our method can extract more details than existing variational methods especially when the image contains different scales of structures. The proposed method is para.
Perceiving the GUISE : Graphical User Interface Specification Extraction

We present a dynamic control-flow analysis and state classifier for graphical user interfaces. Search engines, end-user programming interfaces, and automated testers exploit such information, but are challenged by clientside and serverside scripts obscuring it: our analysis succeeds on popular web applications that contain both. We further motivate such analyses. First, we introduce a new type of browser extension: a natural-language interface to third-party applications. Second, we begin to address the problem of updates to a website changing how a third-party application must use it: by extending our analysis to yield change-impact information, meta-applications can automatically repair their broken interactions.
Validation of National Genomic Evaluations

Several countries enrolled in Interbull services have developed national genomic models for computation of genomic breeding values. For international trade, these models should be validated. A new validation method was developed and tested on 13 different populations for protein yield. This new method is described in this paper. Because of selective genotyping of young bulls, the slopes of the linear regressions and their expected values differed from one. Comparing these slopes to their expected values, 11 of the 13 populations passed the genomic validation test successfully. Using information on direct genomic values in addition to parent averages doubled the accuracy of predicting future breeding values.
Actor Identification and Relevance Filtering in Movie Reviews

With a large amount of data it is not always useful to run analyses on the entire corpus. Sometimes, it is helpful to previously preprocess data by filtering relevant information in order to form a fitting basis for the examination of particular aspects such as sentiment analysis. As a result, the amount of data that needs to be explored is reduced and concentrated, and thus the performance is enhanced. For example, a correct recognition of the rating of acting performances in movie reviews assumes that only judgements on the movie’s actors are used as a basis. In this paper, we discuss different approaches for a rulebased selection of sentences from movie reviews. Our aim is the filtering of sentences in order to facilitate analyses about single actors. Thereby actor identification is used to preselect a set of sentences that mention a specific actor. This is done individually for every actor involved in the movie. Furthermore, filtering is used to identify sentences that not only mention an actor but also state facts about him. To evaluate the developed methods, a test corpus consisting of ten movies with 30 reviews each, taken from the online movie platform IMDb, was built. Based on this data and the presented feature selection rules, an average F1 score of 77.9% is achieved as best result.
Accurate photometric redshifts for the CFHT legacy survey calibrated using the VIMOS VLT deep survey

We present photometric redshifts for an uniquely large and deep sample of 522286 objects with i'_{AB}<25 in the Canada-France Legacy Survey ``Deep Survey'' fields, which cover a total effective area of 3.2 deg^2. We use 3241 spectroscopic redshifts with 0
Optimal Fiscal Policy

This paper derives and estimates rules for fiscal policy that prescribe the optimal response to changes in unemployment and debt. We combine the reduced-form model of the economy from a linear VAR with a non-linear welfare function and obtain analytic solutions for optimal policy. The variables in our reduced-form model – growth, unemployment, primary surplus – have a natural rate that cannot be affected by policy. Policy can only reduce fluctuations around these natural rates. Our welfare function contains future GDP and unemployment, the relative weights of which determine the optimal response. The optimal policy rule demands an immediate and large policy response that is procyclical to growth shocks and countercyclical to unemployment shocks. This result holds true when the weight of unemployment in the welfare function is reduced to zero. The rule currently followed by policy makers responds procyclically to both growth and unemployment shocks, and does so much slower than the optimal rule, leading to significant welfare losses.
Dynamic programming formulation of periodic event-triggered control: Performance Guarantees and co-design

While potential benefits of choosing the transmissions times in a networked control system based on state or event information have been advocated in the literature, few general methods are available that guarantee closed-loop improvements over traditional periodic transmission strategies. In this paper, we propose event-triggered controllers that guarantee better quadratic discounted cost performance than periodic control strategies using the same average transmission rate. Moreover, we show that the performance of a method in the line of previous Lyapunov based approaches is within a multiplicative factor of periodic control performance, while using less transmissions. Our approach is based on a dynamic programming formulation for the co-design problem of choosing both transmission decisions and control inputs in the context of periodic event-triggered control for linear systems. A numerical example illustrates the advantages of the proposed method over traditional periodic control.
Interactive multimodal music transcription

Automatic music transcription has usually been performed as an autonomous task and its evaluation has been made in terms of precision, recall, accuracy, etc. Nevertheless, in this work, assuming that the state of the art is far from being perfect, it is considered as an interactive one, where an expert user is assisted in its work by a transcription tool. In this context, the performance evaluation of the system turns into an assessment of how many user interactions are needed to complete the work. The strategy is that the user interactions can be used by the system to improve its performance in an adaptive way, thus minimizing the workload. Also, a multimodal approach has been implemented, in such a way that different sources of information, like onsets, beats, and meter, are used to detect notes in a musical audio excerpt. The system is focused on monotimbral polyphonic transcription.
Immigration and the Pension System in Spain

In this paper we use a large overlapping generations model with individuals that differ across age, productivity and native status to assess the effects on the pension system of different immigration quotas in the context of an aging population by computing how much should social security taxes be rised in order to pay for the pension burden in two model economies. The first one is the standard model pioneered by Auerbach and Kotlikoff (1987) where skilled and unskilled workers are perfect substitutes in the production process. In the second model economy, individuals with different skill levels are imperfect substitutes as in Canova and Ravn (1998). The main result of the paper is that half of the reduction of the social security tax rate associated with immigration in the standard model is lost when skilled and unskilled individual are imperfect substitutes. Consequently, the standard model with perfect substitution overestimates the ability of immigration inflows to sustain the pension system in Spain.