Miracle-dz/UniFAR-FTUs huggingface dataset:
Adverse drug reactions and drug–drug interactions with over-the-counter NSAIDs

Nonsteroidal anti-inflammatory drugs (NSAIDs) such as ibuprofen have a long history of safe and effective use as both prescription and over-the-counter (OTC) analgesics/antipyretics. The mechanism of action of all NSAIDs is through reversible inhibition of cyclooxygenase enzymes. Adverse drug reactions (ADRs) including gastrointestinal bleeding as well as cardiovascular and renal effects have been reported with NSAID use. In many cases, ADRs may occur because of drug–drug interactions (DDIs) between the NSAID and a concomitant medication. For example, DDIs have been reported when NSAIDs are coadministered with aspirin, alcohol, some antihypertensives, antidepressants, and other commonly used medications. Because of the pharmacologic nature of these interactions, there is a continuum of risk in that the potential for an ADR is dependent on total drug exposure. Therefore, consideration of dose and duration of NSAID use, as well as the type or class of comedication administered, is important when assessing potential risk for ADRs. Safety findings from clinical studies evaluating prescription-strength NSAIDs may not be directly applicable to OTC dosing. Health care providers can be instrumental in educating patients that using OTC NSAIDs at the lowest effective dose for the shortest required duration is vital to balancing efficacy and safety. This review discusses some of the most clinically relevant DDIs reported with NSAIDs based on major sites of ADRs and classes of medication, with a focus on OTC ibuprofen, for which the most data are available.
The Overlapped Microstrip for MICs and MMICs

The overlapped microstrip-like lines and their applications feasible by means of MIC and MMIC technology have been presented. Several 3dB coupler designs and a microstrip representation of the Marchand balun are suggested as good alternatives to the well known devices. The coupler results are used to prove the balun feasibility. The brief discussion on the quasi-TEM analysis results is stressing the significance of asymmetric structures. The experimental results are limited to the MIC technology using alumina substrate.
Weakly Supervised PLDA Training

PLDA is a popular normalization approach for the i-vector model, and it has delivered state-of-the-art performance in speaker verification. However, PLDA training requires a large amount of labelled development data, which is highly expensive in most cases. We present a cheap PLDA training approach, which assumes that speakers in the same session can be easily separated, and speakers in different sessions are simply different. This results in `weak labels' which are not fully accurate but cheap, leading to a weak PLDA training. Our experimental results on real-life large-scale telephony customer service achieves demonstrated that the weak training can offer good performance when human-labelled data are limited. More interestingly, the weak training can be employed as a discriminative adaptation approach, which is more efficient than the prevailing unsupervised method when human-labelled data are insufficient.
Test case prioritization techniques “an empirical study”

Regression testing is an expensive process. A number of methodologies of regression testing are used to improve its effectiveness. These are retest all, test case selection, test case reduction and test case prioritization. Retest all technique involves re-execution of all available test suites, which are critical moreover cost effective. In order to increase efficiency, test case prioritization is being utilized for rearranging the test cases. A number of algorithms has been stated in the literature survey such as Greedy Algorithms and Metaheuristic search algorithms. A simple greedy algorithm focuses on test case prioritization but results in less efficient manner, due to which researches moved towards the additional greedy and 2-Optimal algorithms. Forthcoming metaheuristic search technique (Hill climbing and Genetic Algorithm) produces a much better solution to the test case prioritization problem. It implements stochastic optimization while dealing with problem concern. The genetic algorithm is an evolutionary algorithm which gives an exact mathematical fitness value for the test cases on which prioritization is done. This paper focuses on the comparison of metaheuristic genetic algorithm with other algorithms and proves the efficiency of genetic algorithm over the remaining ones.
Infrared Absorption at 300 K in InGaN/GaN Disk-in-Nanowire Arrays Grown on (001) Silicon

In<sub>0.34</sub>Ga<sub>0.66</sub>N/GaN disk-in-nanowire arrays have been grown on (001) Si substrates by molecular beam epitaxy and their infrared absorption spectra have been measured at room temperature. The average diameter and area density of the nanowires are 60 nm and <inline-formula> <tex-math notation="LaTeX">$2\times 10^{10}$ </tex-math></inline-formula>cm<inline-formula> <tex-math notation="LaTeX">$^{-2}$ </tex-math></inline-formula>, respectively. The room temperature photoluminescence spectrum is characterized by peak emission at 540 nm. The absorption spectra measured with a Fourier transform infrared spectrometer in transmission and reflection modes exhibit multiple absorption peaks ranging from 1.6 to <inline-formula> <tex-math notation="LaTeX">$20~\mu \text{m}$ </tex-math></inline-formula>. The peak energies have been compared with those for intersubband transitions calculated with a simple model and there is agreement in some cases.
Projective Methods for Stiff Differential Equations: Problems with Gaps in Their Eigenvalue Spectrum

We show that there exist classes of explicit numerical integration methods that can handle very stiff problems if the eigenvalues are separated into two clusters, one containing the "stiff," or fast, components, and one containing the slow components. These methods have large average step sizes relative to the fast components. Conventional implicit methods involve the solution of nonlinear equations at each step, which for large problems requires significant communication between processors on a multiprocessor machine. For such problems the methods proposed here have significant potential for speed improvement.
Two-level Data Staging ETL for Transaction Data

In data warehousing, Extract-Transform-Load (ETL) extracts the data from data sources into a central data warehouse regularly for the support of business decision-makings. The data from transaction processing systems are featured with the high frequent changes of insertion, update, and deletion. It is challenging for ETL to propagate the changes to the data warehouse, and maintain the change history. Moreover, ETL jobs typically run in a sequential order when processing the data with dependencies, which is not optimal, e.g., when processing early-arriving data. In this paper, we propose a two-level data staging ETL for handling transaction data. The proposed method detects the changes of the data from transactional processing systems, identifies the corresponding operation codes for the changes, and uses two staging databases to facilitate the data processing in an ETL process. The proposed ETL provides the “onestop" method for fast-changing, slowly-changing and early-arriving data processing.
The Effects of a Feedback Package on the Facial Orientation of a Young Girl with Autism During Restricted and Free Operant Conditions

A multiple baseline design across activities and people was used to assess the effectiveness of a feedback package on the facial orientation of a young girl with autism. During baseline, observations indicated low rates of facial orientation and high rates of gaze avoidance during conversation (restricted operant) and play (free operant) conditions. After treatment, facial orientation rates increased and gaze avoidance rates decreased to levels similar to typically-developing peers and maintained at one month follow up. These results suggest that the feedback package was effective in producing durable facial orientation across different environments and people. Possible interpretations, strengths, and limitations are discussed.
Numerical stability properties of a QR-based fast least squares algorithm

The numerical stability of a recent QR-based fast least-squares algorithm is established from a backward stability perspective. A stability domain approach applicable to any least-squares algorithm, constructed from the set of reachable states in exact arithmetic, is presented. The error propagation question is shown to be subordinate to a backward consistency constraint, which requires that the set of numerically reachable variables be contained within the stability domain associated to the algorithm. This leads to a conceptually lucid approach to the numerical stability question which frees the analysis of stationary assumptions on the filtered sequences and obviates the tedious linearization methods of previous approaches. Moreover, initialization phenomena and considerations related to poorly exciting inputs admit clear interpretations from this perspective. The algorithm under study is proved, in contrast to many fast algorithms, to be minimal. >
A Solution of Two-Dimensional Magnetohydrodynamic Flow Using the Finite Volume Method

This paper presents the two dimensional numerical modeling of the coupling electromagnetic-hydrodynamic phenomena in a conduction MHD pump using the Finite volume Method. Magnetohydrodynamic problems are, thus, interdisciplinary and coupled, since the effect of the velocity field appears in the magnetic transport equations, and the interaction between the electric current and the magnetic field appears in the momentum transport equations. The resolution of the Maxwell's and Navier Stokes equations is obtained by introducing the magnetic vector potential A, the vorticity  and the stream function  . The flux density, the electromagnetic force, and the velocity are graphically presented. Also, the simulation results agree with those obtained by Ansys Workbench Fluent software.
The Implications of Daylight Saving Time: A Field Experiment on Cognitive Performance and Risk Taking

To explore the effects of daylights saving time (DST) transition on cognitive performance and risk-taking behaviour immediately before and one week after the shift to DST, this study examines two Australian populations living in similar geographic surroundings who experience either no DST transition (Queensland) or a one-hour DST desynchronization (New South Wales). This exogenous variation creates natural control (QLD) and treatment (NSW) groups that enable isolation and identification of the DST transition’s effect on the two outcome variables. Proximity to the border ensures similar socio-demographic and socio-economic conditions and thus permits comparison of the cognitive performance and risk-taking behaviour of affected versus unaffected individuals. The results suggest that exposure to the DST transition has no significant impact on either cognitive performance or risk-taking behaviour.
Using mobilize power management IP for dynamic and static power reduction in SoC at 130 nm

At 130 nm and 90 nm, power consumption (both dynamic and static) has become a barrier in the roadmap for SoC designs targeting battery powered, mobile applications. This paper presents the results of dynamic and static power reduction achieved implementing Tensilica's 32-bit Xtensa microprocessor core, using Virtual Silicon's Power Management IP. Independent voltage islands are created using Virtual Silicon's VIP PowerSaver standard cells by using voltage level shifting cells and voltage isolation cells to implement power islands. The VIP PowerSaver standard cells are characterized at 1.2V, 1.0V and 0.8V, to accommodate voltage scaling. Power islands can also be turned off completely. Designers can significantly lower both the dynamic power and the quiescent or leakage power of their SoC designs, with very little impact on speed or area using Virtual Silicon's VIP Gate Bias standard cells.
ABCB1 polymorphisms and the concentrations of lopinavir and ritonavir in blood, semen and saliva of HIV-infected men under antiretroviral therapy.

INTRODUCTION Lopinavir and ritonavir are frequently included in highly active antiretroviral therapy (HAART) regimens for HIV infection. These drugs are substrates, and may also inhibit and/or induce the P-glycoprotein (ABCB1) transporter, encoded by the polymorphic ABCB1 gene. We investigated the impact of three common exonic ABCB1 polymorphisms on the concentrations of lopinavir and ritonavir in blood, semen and saliva of HIV-infected men under stable HAART containing ritonavir-boosted lopinavir. MATERIALS & METHODS Blood, semen and saliva samples were collected from 113 subjects, 30-35 minutes before the scheduled morning dose of lopinavir/ritonavir, and trough drug concentrations were measured using LC/MS/MS. The 1236C>T, 2677G>T/A and 3435C>T polymorphisms were genotyped using the single base extension-termination method and ABCB1 haplotypes were statistically inferred. RESULTS Median (25th-75th percentile) trough concentrations (ng/ml) of lopinavir in plasma, semen and saliva were 6326 (4070-8617), 286.0 (128.4-475.5) and 72.7 (38.0-119.6), respectively. The corresponding concentrations (ng/ml) for ritonavir were 261.8 (172.2-398.6), 17.7 (9.2-27.6) and 5.3 (3.2-9.0), respectively. Univariate and multivariate regression analysis revealed no influence of ABCB1 genotypes or haplotypes on the concentrations of lopinavir and ritonavir in plasma, semen and saliva of HIV-infected men under stable HAART treatment. CONCLUSION The ABCB1 1236C>T, 2667G>T/A and 3435C>T genotypes and haplotypes are not predictors of lopinavir and ritonavir concentrations in blood plasma, semen or saliva of HIV-infected men under stable HAART treatment. The concentrations of lopinavir and ritonavir in saliva are not reliable predictors of the concentration of these drugs in semen.
The Transaction Costs of Semi-Public Institutions: Railway History as a Challenge for Coase

In the social sciences, there are two things one can do with a theory and the aspect of reality it is meant to explain: one can use the theory to improve reality2, or one can use reality to improve the theory. The purpose of the present thesis is very much to do the latter. The empirical problem concerns the proper scope of government3, which we will use to examine the new institutional economics (hereafter: NIE) as it was developed starting with the work of Ronald Coase.4 For reasons that will be explained below, we will focus particularly on the history of the railway industry in Western Europe.
Rethinking College Student Retention by John M. Braxton et al. (review)

to see the path toward a more egalitarian future just described. However, we agree with Audre Lorde (2007) who suggested that, “the master’s tools will never dismantle the master’s house” (p. 110). It could not have been easy for Dr. Kimmel, for example, to interview men with whom he so fundamentally disagreed. We, therefore, honor Kimmel’s modeling the behavior of treating those with whom we disagree with openness, love, and compassion. This in no way excuses angry White men from responsibility, nor does it delegitimize our own anger and frustration in working with those who have caused tremendous pain. We believe, however, that history has taught us that tools of love and compassion are both powerful and more appropriate for dismantling oppression.
Economic models of advertising have conflicting predictions for the effects of

Advertising bans can increase or decrease alcohol consumption due to effects on beverage choice, price competition, and substitution by producers toward non-banned media. We study bans on broadcast advertising in seventeen OECD countries for the years 1977-95, in relation to per capita alcohol consumption, liver cirrhosis mortality, and motor vehicle fatalities. The results indicate that advertising bans in OECD countries have not decreased alcohol consumption or alcohol abuse. Final version published in International Review of Advertising, 20(3), 2001
Neural-network-based adaptive baseband predistortion method for RF power amplifiers

An adaptive baseband predistortion method for RF power amplifier (PA) linearization is proposed and experimentally demonstrated. The predistortion component is implemented by a single-input dual-output multilayer perceptron (MLP). Both amplitude-to-amplitude and amplitude-to-phase distortion products are compensated by backpropagation training of the neural network including the response of the PA. Effects of modulator and demodulator imperfections on system performance are examined. Measurements on a system prototype reveal a significant linearity improvement that reaches 25 dB.
Ieee Transactions on Software Engineering 1 Modular Pluggable Analyses for Data Structure Consistency

— Hob is a program analysis system that enables the focused application of multiple analyses to different modules in the same program. In our approach, each module encapsulates one or more data structures and uses membership in abstract sets to characterize how objects participate in data structures. Each analysis verifies that the implementation of the module 1) preserves important internal data structure consistency properties and 2) correctly implements a set algebra interface that characterizes the effects of operations on the data structure. Collectively, the analyses use the set algebra to 1) characterize how objects participate in multiple data structures and to 2) enable the inter-analysis communication required to verify properties that depend on multiple modules analyzed by different analyses. We implemented our system and deployed several pluggable analyses, including a flag analysis for modules in which abstract set membership is determined by a flag field in each object, a PALE shape analysis plugin, and a theorem proving plugin for analyzing arbitrarily complicated data structures. Our experience shows that our system can effectively 1) verify the consistency of data structures encapsulated within a single module and 2) combine analysis results from different analysis plugins to verify properties involving objects shared by multiple modules analyzed by different analyses.
Tell me Dave: Context-sensitive grounding of natural language to manipulation instructions

It is important for a robot to be able to interpret natural language commands given by a human. In this paper, we consider performing a sequence of mobile manipulation tasks with instructions described in natural language. Given a new environment, even a simple task such as boiling water would be performed quite differently depending on the presence, location and state of the objects. We start by collecting a dataset of task descriptions in free-form natural language and the corresponding grounded task-logs of the tasks performed in an online robot simulator. We then build a library of verb–environment instructions that represents the possible instructions for each verb in that environment, these may or may not be valid for a different environment and task context. We present a model that takes into account the variations in natural language and ambiguities in grounding them to robotic instructions with appropriate environment context and task constraints. Our model also handles incomplete or noisy natural language instructions. It is based on an energy function that encodes such properties in a form isomorphic to a conditional random field. We evaluate our model on tasks given in a robotic simulator and show that it successfully outperforms the state of the art with 61.8% accuracy. We also demonstrate a grounded robotic instruction sequence on a PR2 robot using the Learning from Demonstration approach.
Chinese Novelty Mining

Automated mining of novel documents or sentences from chronologically ordered documents or sentences is an open challenge in text mining. In this paper, we describe the preprocessing techniques for detecting novel Chinese text and discuss the influence of different Part of Speech (POS) filtering rules on the detection performance. Experimental results on APWSJ and TREC 2004 Novelty Track data show that the Chinese novelty mining performance is quite different when choosing two dissimilar POS filtering rules. Thus, the selection of words to represent Chinese text is of vital importance to the success of the Chinese novelty mining. Moreover, we compare the Chinese novelty mining performance with that of English and investigate the impact of preprocessing steps on detecting novel Chinese text, which will be very helpful for developing a Chinese novelty mining system.
[PSI+] Prion Transmission Barriers Protect Saccharomyces cerevisiae from Infection: Intraspecies 'Species Barriers'

[PSI+] is a prion of Sup35p, an essential translation termination and mRNA turnover factor. The existence of lethal [PSI+] variants, the absence of [PSI+] in wild strains, the mRNA turnover function of the Sup35p prion domain, and the stress reaction to prion infection suggest that [PSI+] is a disease. Nonetheless, others have proposed that [PSI+] and other yeast prions benefit their hosts. We find that wild Saccharomyces cerevisiae strains are polymorphic for the sequence of the prion domain and particularly in the adjacent M domain. Here we establish that these variations within the species produce barriers to prion transmission. The barriers are partially asymmetric in some cases, and evidence for variant specificity in barriers is presented. We propose that, as the PrP 129M/V polymorphism protects people from Creutzfeldt–Jakob disease, the Sup35p polymorphisms were selected to protect yeast cells from prion infection. In one prion incompatibility group, the barrier is due to N109S in the Sup35 prion domain and several changes in the middle (M) domain, with either the single N109S mutation or the group of M changes (without the N109S) producing a barrier. In another, the barrier is due to a large deletion in the repeat domain. All are outside the region previously believed to determine transmission compatibility. [SWI+], a prion of the chromatin remodeling factor Swi1p, was also proposed to benefit its host. We find that none of 70 wild strains carry this prion, suggesting that it is not beneficial.
Inhibition of Influenza A Virus (H1N1) Fusion by Benzenesulfonamide Derivatives Targeting Viral Hemagglutinin

Hemagglutinin (HA) of the influenza virus plays a crucial role in the early stage of the viral life cycle by binding to sialic acid on the surface of host epithelial cells and mediating fusion between virus envelope and endosome membrane for the release of viral genomes into the cytoplasm. To initiate virus fusion, endosome pH is lowered by acidification causing an irreversible conformational change of HA, which in turn results in a fusogenic HA. In this study, we describe characterization of an HA inhibitor of influenza H1N1 viruses, RO5464466. One-cycle time course study in MDCK cells showed that this compound acted at an early step of influenza virus replication. Results from HA-mediated hemolysis of chicken red blood cells and trypsin sensitivity assay of isolated HA clearly showed that RO5464466 targeted HA. In cell-based assays involving multiple rounds of virus infection and replication, RO5464466 inhibited an established influenza infection. The overall production of progeny viruses, as a result of the compound's inhibitory effect on fusion, was dramatically reduced by 8 log units when compared with a negative control. Furthermore, RO5487624, a close analogue of RO5464466, with pharmacokinetic properties suitable for in vivo efficacy studies displayed a protective effect on mice that were lethally challenged with influenza H1N1 virus. These results might benefit further characterization and development of novel anti-influenza agents by targeting viral hemagglutinin.