Miracle-dz/UniFAR-FTUs huggingface dataset:
Wild-Type NRas and KRas Perform Distinct Functions during Transformation

ABSTRACT The ras proto-oncogenes, of which there are four isoforms, are molecular switches that function in signal transduction pathways to control cell differentiation, proliferation, and survival. How the Ras isoforms orchestrate cellular processes that affect behavior is poorly understood. Further, why cells express two or more Ras isoforms is unknown. Here, using a genetically defined system, we show that the presence of both wild-type KRas and NRas isoforms is required for transformation because they perform distinct nonoverlapping functions: wild-type NRas regulates adhesion, and KRas coordinates motility. Remarkably, we find that Ras isoforms achieve functional specificity by engaging different signaling pathways to affect the same cellular processes, thereby coordinating cellular outcome. Although we find that signaling from both isoforms intersects in actin and microtubule cytoskeletons, our results suggest that KRas signals through Akt and Cdc42 while NRas signals through Raf and RhoA. Our analyses suggest a previously unappreciated convergence of different Ras isoforms on the dynamics of the processes involved in transformation.
Estimation of Market Information Shares: A Comparison

This note investigates via Monte Carlo simulation the finite‐sample performance of two identification schemes that provide unique measures of Hasbrouck‐type information share in price discovery. The Lien and Shrestha (2009) method is based on factorization of the full correlation matrix and the Grammig and Peter (2013) method is based on different correlations of price innovations in the tails and in the center of the distributions. We find that the GP method performs poorly under the chosen data generation processes. The LS method provides at most marginal improvement over the method based upon the upper/lower bound midpoint of the Hasbrouck measure. The results, therefore, support the common practice of the midpoint approach. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 36:1108–1124, 2016
A novel antibody–drug conjugate anti-CD19(Fab)-LDM in the treatment of B-cell non-Hodgkin lymphoma xenografts with enhanced anticancer activity

Abstract Background: Rituximab is widely used in clinical setting for the treatment of B malignant lymphoma and has achieved remarkable success. However, in most patients, the disease ultimately relapses and become resistant to rituximab. To overcome the limitation, there is still a need to find novel strategy for improving therapeutic efficacy. Objective: To construct genetically engineered antibody anti-CD19(Fab)-LDM, and verify the anticancer activity targeted toward B-lymphoma. Methods: The anticancer activity of anti-CD19(Fab)-LDM in vitro and in vivo was examined. In vitro, the binding activity and internalization of anti-CD19(Fab)-LDP were measured. Using comet assay and apoptosis, the cytotoxicity of energized fusion proteins was observed. From in vivo experiments, targeting of therapeutic effect and anticancer efficacy bythe fusion protein was verified. Results: Data showed that anti-CD19(Fab)-LDM does not only binding the cell surface but is also internalized into the cell. The energized fusion proteins anti-CD19(Fab)-LDM can induce DNA damage. Furthermore, significant in vivo therapeutic efficacy was observed. Conclusion: The present study demonstrated that the genetically engineered antibody anti-CD19(Fab)-LDM exhibited enhanced cytotoxicity compared to LDM alone. One of the most powerful advantages of anti-CD19(Fab)-LDM, however, is that it can be internalized within the cells and carry out cytotoxic effects. Therefore, anti-CD19(Fab)-LDM may be as a useful targeted therapy for B-cell lymphoma.
Kinetic Curve Type Assessment for Classification of Breast Lesions Using Dynamic Contrast-Enhanced MR Imaging

Objective The aim of this study was to employ a kinetic model with dynamic contrast enhancement-magnetic resonance imaging to develop an approach that can efficiently distinguish malignant from benign lesions. Materials and Methods A total of 43 patients with 46 lesions who underwent breast dynamic contrast enhancement-magnetic resonance imaging were included in this retrospective study. The distribution of malignant to benign lesions was 31/15 based on histological results. This study integrated a single-compartment kinetic model and dynamic contrast enhancement-magnetic resonance imaging to generate a kinetic modeling curve for improving the accuracy of diagnosis of breast lesions. Kinetic modeling curves of all different lesions were analyzed by three experienced radiologists and classified into one of three given types. Receiver operating characteristic and Kappa statistics were used for the qualitative method. The findings of the three radiologists based on the time-signal intensity curve and the kinetic curve were compared. Results An average sensitivity of 82%, a specificity of 65%, an area under the receiver operating characteristic curve of 0.76, and a positive predictive value of 82% and negative predictive value of 63% was shown with the kinetic model (p = 0.017, 0.052, 0.068), as compared to an average sensitivity of 80%, a specificity of 55%, an area under the receiver operating characteristic of 0.69, and a positive predictive value of 79% and negative predictive value of 57% with the time-signal intensity curve method (p = 0.003, 0.004, 0.008). The diagnostic consistency of the three radiologists was shown by the κ-value, 0.857 (p<0.001) with the method based on the time-signal intensity curve and 0.826 (p<0.001) with the method of the kinetic model. Conclusions According to the statistic results based on the 46 lesions, the kinetic modeling curve method showed higher sensitivity, specificity, positive and negative predictive values as compared with the time-signal intensity curve method in lesion classification.
Seemingly Unrelated Regression and Regional Price Response Functions: A Study of U. S. Apple Production

Enke problem [3:5]. This familiar problem may be stated as follows: given two or more spatially separated markets for a single commodity, with supply and demand functions specified in each market, and constant unit transport costs between regions, what are the final competitive equilibrium prices in all markets, the equilibrium quantities supplied and demanded in each market, and the level of exports and imports from and to each market? While the equilibrium conditions of these models are interesting because of the extension of economic theory they provide, it is the comparative statics of these interregional trade systems that is more valuable to the applied economist and policy maker. ' The particular problem addressed in this paper is the effect that a change in regional supply configuration has on prices in each region within an interregional trade system. However, the analytical tool used here is not a programming model.2 An alternative method of obtaining this information through the direct estimation of regional price response functions is developed, and the procedure is applied to the study of interregional competition in the U.S. apple industry. The following section contains a review of contributions to the solution of the aforementioned Cournot-Enke problem. A simple interregional trade model is developed for apple production, and the comparative statics of the model are examined. Regional price equations that lend themselves to empirical analysis are derived and estimated. Since there is a high probability that regression residuals are contemporaneously correlated, Zellner's seemingly unrelated regression procedure is applied. A final section of the paper contains a discussion of policy implications.
Large eddy simulation of compressible turbulent jets

Increasing noise regulation at urban airports force jet engine manufactures to develop and build quieter engines. Over the last 10-15 years, a significant reduction in fan and mechanical noise has been achieved. However, the reduction in jet noise over the same time period is fairly small and a major reduction in acoustic emissions of jet engines has to come from a reduction in jet noise. Traditional jet mixing-noise predictions are based on a statistical description of the jet turbulence; space-time correlations of the Lighthill quadruples (Lighthill 1952, Lighthill 1954) are specified in the jet. Further refinements are, however, needed to obtain a reasonable prediction of the directivity and spectral distribution of the radiated noise (Goldstein 1976). Significant improvements are achieved by modeling the effects of source-convection (Lighthill 1954, Ffowcs Williams & Hawkins 1969) and mean-flow refraction (Mani 1976). Reynolds-averaged mean flow calculations can be used to provide the source-strength distribution and the length and time-scale estimates needed in the source models (Bechara et al. 1994). The empirical input needed in such an approach places limits on the range of applicability of this method. It is, therefore, desirable to develop methods which obtain the unsteady flow data with much less empirical input. Due to the inherently high Reynolds numbers of the jet formed by a jet engine, LES seems to be the only feasible candidate to obtain the necessary unsteady data for the jet. Some attempts for round jets have been made by Choi et al. (1999) and Boersma & Lele (1999). For simpler geometries like plane mixing layers, various simulations have also been performed by Vreman et al. (1996). In this paper we will describe an LES method which uses the standard compressible LES filtered variables (no Favre averaging). The LES equation are discretized with accurate numerical schemes with very little artificial diffusion. So the LES models have to supply all the damping of the non-linear terms. In LES models which use low order numerics, damping can come from the LES subgrid model or from the numerics, and it is often very difficult to separate those two effects. This makes the physical interpretation of the results, especially those related to subgrid motions, difficult.
Trio Learning: A New Strategy for Building Hybrid Neural Trees

Neural trees are constructive algorithms which build decision trees whose nodes are binary neurons. We propose a new learning scheme, "trio-learning," which leads to a significant reduction in the tree complexity. In this strategy, each node of the tree is optimized by taking into account the knowledge that it will be followed by two son nodes. Moreover, trio-learning can be used to build hybrid trees, with internal nodes and terminal nodes of different nature, for solving any standard tasks (e.g. classification, regression, density estimation). Significant results on a handwritten character classification are presented.
Can echocardiographically estimated pulmonary arterial elastance be a non-invasive predictor of pulmonary vascular resistance?

Introduction Measurement of pulmonary vascular resistance (PVR) is essential in evaluating a patient with pulmonary hypertension. Material and methods Data from right heart catheterization (RHC) and echocardiograms performed within 90 days of each other on 45 non-consecutive adult patients were reviewed in this retrospective study. Patients were recruited using an assortment of strategies to ensure the presence of patients with a wide range of PVR. Results The linear regression equation between RHC-derived PVR and echocardiographic pulmonary arterial elastance (PAE) was: PVR = (562.6 × PAE) – 38.9 (R = 0.56, p < 0.0001). An adjustment for echocardiographic PAE was made by multiplying it by hemoglobin (in g/dl) and (right atrial area)1.5 (in cm3). As RHC-derived PVR varies with blood hemoglobin, an adjustment for PVR was made for hemoglobin of 12 g/dl. Visualization of the XY scatter plot of adjusted PVR and adjusted PAE isolated a subset of patients with PVR higher than 8.8 Wood units, where a strong linear relationship existed (adjusted PVR = (0.89 × adjusted PAE) + 137.4, R = 0.89, p = 0.008). Conclusions The correlation coefficient of the regression equation connecting echocardiographic PAE and RHC-derived PVR was moderate. In a subset of patients with very high PVR and after appropriate adjustment, a strong linear relationship existed with an excellent correlation coefficient.
Smoothed state estimation for nonlinear Markovian switching systems

The contributions of the work presented here are twofold. First we introduce a computationally efficient refinement of the unscented transformation (UT) which is applicable to nonlinear systems with a linear substructure. The resulting UT is referred to as the marginalised UT and is derived in two forms: the conventional UT marginalised form and the simplex sigma point marginalised form. The second contribution is the application of the proposed marginalised UT to smoothed state estimation in Markovian switching systems with nonlinear dynamic and measurement equations. Three algorithms for smoothing are proposed in this context. The first two algorithms are based on the well-known interacting multiple model (IMM) and hypothesis pruning techniques. The third algorithm uses maximum a posteriori (MAP) estimates of the switching parameter to generate a stochastic dynamic system within which smoothed state estimation is performed. The performances of the smoothing algorithms are analysed and compared in two scenarios involving a target which undergoes coordinated turn maneuvers.
Early Administration of Sivelestat, the Neutrophil Elastase Inhibitor, in Adults for Acute Lung Injury Following Gastric Aspiration

Gastric aspiration is the major cause of acute lung injury (ALI) and acute respiratory distress syndrome. Aspiration-induced ALI is believed to be, at least in part, facilitated by neutrophil-derived mediators and toxic molecules. We conducted a prospective cohort study based on the hypothesis that sivelestat, a specific neutrophil elastase inhibitor, is effective for treating ALI following gastric aspiration. Forty-four ALI patients who showed evidence of aspiration were observed within 12 h before intensive care unit admission and who had been mechanically ventilated within 12 h after admission were included in this study. Lung injury score (LIS) and PAO2/FiO2 (P/F) ratio on day 7 were defined as the primary outcomes of the study. Twenty-three patients were assigned to the sivelestat group and 21 to the control group. In univariate analyses, the proportions of patients with LIS lower than 1.0 on day 7 and a P/F greater than 300 on day 7 were significantly higher in the sivelestat group than in the control group (60.9% vs. 26.3%, P = 0.03; 87.0% vs. 36.8%, P = 0.001). In the logistic regression model, the use of sivelestat was an independent predictor for LIS lower than 1.0 on day 7 (relative risk, 7.4; 95% confidence interval [CI], 1.51-36.48) and for a P/F ratio higher than 300 on day 7 (relative risk, 18.5; 95% CI, 2.72-126.46). In the Cox proportional hazards model, the use of sivelestat was associated with a lower cumulative proportion of patients who received mechanical ventilation during the initial 14 days (hazard ratio, 2.6; 95% CI, 1.17-5.55).
Identification of Haplotypes in Promoter of Prolactin Gene and Their Effect on Egg Production and Quality Traits in Layer Chicken

Expression of prolactin hormone is a crucial event in regulating egg production in chickens for which promoter plays the vital role in expressing the prolactin gene. The objective of the present study was to identify haplotypes in the prolactin promoter and their effects on egg production and egg quality traits in White Leghorn chicken. Single stranded conformation polymorphism followed by sequencing was conducted to explore polymorphism at 561 bp promoter of prolactin gene. The effect of haplotype combinations on egg production and quality traits were estimated following general linear model technique. The expression of prolactin by different haplogroups was quantified by qPCR. Total 28 haplotypes were found in White Leghorn chicken of which h1 haplotype possessed the highest frequency of 0.46 and h8, h14, h16, h25, h26, and h28 haplotypes had the lowest frequency (0.1%). The egg production up to 52 and 64 weeks of age were found to be significantly (p < 0.05) associated with haplotype combinations where the highest 52-w (52 weeks) egg production was found in animals with h1/h22 combination and the lowest production was observed in the birds with h1/h2 haplogroup. The haplotype combinations had the significant effect (p < 0.05) on Haugh Unit, yolk index and albumen weight at 40 weeks of age; Haugh Unit and albumen weight at 52 weeks of age and Haugh unit, yolk weight and yolk percentage at 64 weeks of age. The prolactin expression in h1/h22 birds was found to be the lowest and in h1/h5 birds to be the highest. The prolactin expression showed significant effect on 52-w egg production and albumin weight at 52 weeks age. In conclusion, it may be stated that the prolactin promoter was highly polymorphic and had the significant association with egg production and quality traits in White Leghorn chicken.
Unbalance, flicker, harmonic, voltage and reactive power compensation of the distribution grid using a universal STATOM

Power electronic converters are actively involved in many parts of the power grid as active power filters and FACTs devices. They are employed to actively control the absorbed/injected reactive power of the fixed capacitor banks. These devices have the ability to regulate the voltage of distribution systems. In this paper, some novel features are added to the controller of the compensator without adding any hardware to make the device a universal tool. Having said that, the unbalance of the grid is compensated using the proposed dq0 transformation developed for both positive sequence and negative sequence components. A 5 Hz flicker produced by the dynamic load can be perfectly compensated by the converter. This makes the converter a universal tool that is able to correct the power quality indices of the grid. The MATLAB DSTACOM model is used for the implementation of the proposed features. The simulation results are presented to show the effectiveness of the proposed controller.
The Supply of Stock Returns: Adding Back Buybacks

The shift in corporate payout policy from dividends to buybacks creates the need for a new supply model of stock returns. Our study provides theoretical and empirical evidence for a total payout (dividends plus buybacks) model of stock returns. First, we show that long-run stock returns between 1871 and 2014 can almost entirely be attributed to the supply of total payouts. Second, we provide evidence that total payouts per-share (adjusted for the share decrease from buybacks) grow in line with economic productivity, and that aggregate total payouts grow in line with GDP. Third, we demonstrate that the dividend discount model (DDM), based on current yields and historical growth rates, significantly underestimates forward-looking equity return compared to a total payout model that includes both dividends and buybacks. Fourth, we show that the cyclically-adjusted total yield (CATY) is at least as good of a predictor of changes in expected returns as the cyclically-adjusted price-to-earnings ratio (CAPE).
WHY STRONG COORDINATION AT ONE LEVEL OF GOVERNMENT IS INCOMPATIBLE WITH STRONG COORDINATION ACROSS LEVELS (AND HOW TO LIVE WITH IT): THE CASE OF THE EUROPEAN UNION

The European Union (EU) inherited ‘indirect administration’ from classical international organizations: policies adopted by the international organization are subsequently to be implemented nationally by member states themselves, and not by bodies owned by the international organization. This arrangement has often led to legislation being incorporated and applied rather differently across countries. In order to harmonize implementation practices within the EU, we have witnessed a development from ‘indirect administration’ to more ‘direct administration’ in the sense that national agencies work closely with the European Commission, EU agencies and sister agencies in other member states, partly bypassing national ministries. Thus, stronger coordination across levels may counteract strong coordination at the national level. This ‘coordination dilemma’ seems to have been largely ignored in the literatures on EU network governance and national ‘joined-up government’, respectively. The ambition of this article is twofold: first, the coordination dilemma is theoretically and empirically illustrated by the seeming incompatibility between a more direct implementation structure in the multilevel EU administrative system and trends towards strengthening coordination and control within nation states. Second, the article discusses organizational arrangements that may enable systems to live with the coordination dilemma in practice.
Reducing unwelcome surprises in project management

Unknown unknowns - often called unk-unks - are lurking in every project, just waiting to emerge, surprise and derail plans. Project knowledge comes from learning about the project its overall context, its goals and objectives, the process for achieving them, the people, tools and other resources to be deployed, and how all of these affect one another. Many so-called unk-unks aren't really unkunks at all. Rather, they are things no one has bothered to find out. Indeed, there are two kinds of unknowns: unknown unknowns (things we don't know we don't know) and known unknowns (things we know we don't know). (See Converting Knowable Unk-Unks to Known Unknowns.) Every project has some of both. The techniques of conventional risk management apply only to the known unknowns. Yet some unk-unks are knowable and can be converted to known unknowns through a process of directed recognition. This article provides an overview of the targets, methods and tools the where, why and how of directed recognition. Several characteristics of a project's subsystems and context make surprises more likely.
The ADiWa Project - On the Way to Just-in-time Process Dynamics based on Events from the Internet of Things

In this paper, we introduce a concept, which focuses on innovative commercial system implementations reflecting process-embedded events from the Internet of Things. The developed concepts are derived from experiences applying recent research advances to industry scenarios. The rationale behind the overall concept is twofold: while transparency is increased by event-based methodologies in the context of the Internet of Things, the agility of business processes is fostered by enhanced business process models, orchestration support, execution control, and user assistance.
Emotion Regulation in Achievement Situations: An Integrated Model

Achievement emotions are critical because of their impact on success and failure in important domains such as learning. These emotions may be modified via emotion regulation (ER). The dominant process model of ER (PMER) proposed by J. Gross, however, provides a domain-general account of ER strategies and has not had substantial contact with theories of achievement emotions such as R. Pekrun’s control-value theory (CVT) and the academic achievement literature. Moreover, ER has not been a focal point of major theories related to achievement emotions, such as CVT. We propose an integrated model of ER in achievement situations (ERAS) that integrates propositions about the generation of emotions from CVT with propositions about how emotions are regulated and types of ER strategies from PMER. The ERAS model also offers new propositions regarding how different achievement situations, object foci, and time frames, as well as discrete emotions with different appraisal patterns, impact ER strategies.