Miracle-dz/UniFAR-FTUs huggingface dataset:
Inhibition of the Notch-Hey1 Axis Blocks Embryonal Rhabdomyosarcoma Tumorigenesis

Purpose: Rhabdomyosarcoma (RMS) is the most common soft tissue sarcoma of childhood and remains refractory to combined-modality therapy in patients with high risk disease. In skeletal myogenesis, Notch signaling prevents muscle differentiation and promotes proliferation of satellite cell progeny. Given its physiologic role in myogenesis and oncogenic role in other human cancers, we hypothesized that aberrant Notch signaling may contribute to RMS tumorigenesis and present novel therapeutic opportunities. Experimental Design: Human RMS cell lines and tumors were evaluated by immunoblot, IHC, and RT-PCR to measure Notch ligand, receptor, and target gene expression. Manipulation of Notch signaling was accomplished using genetic and pharmacologic approaches. In vitro cell growth, proliferation, and differentiation were assessed using colorimetric MTT and BrdU assays, and biochemical/morphologic changes after incubation in differentiation-promoting media, respectively. In vivo tumorigenesis was assessed using xenograft formation in SCID/beige mice. Results: Notch signaling is upregulated in human RMS cell lines and tumors compared with primary skeletal muscle, especially in the embryonal (eRMS) subtype. Inhibition of Notch signaling using Notch1 RNAi or γ-secretase inhibitors reduced eRMS cell proliferation in vitro. Hey1 RNAi phenocopied Notch1 loss and permitted modest myogenic differentiation, while overexpression of an activated Notch moiety, ICN1, promoted eRMS cell proliferation and rescued pharmacologic inhibition. Finally, Notch inhibition using RNAi or γ-secretase inhibitors blocked tumorigenesis in vivo. Conclusions: Aberrant Notch-Hey1 signaling contributes to eRMS by impeding differentiation and promoting proliferation. The efficacy of Notch pathway inhibition in vivo supports the development of Notch-Hey1 axis inhibitors in the treatment of eRMS. Clin Cancer Res; 17(23); 7324–36. ©2011 AACR.
The Legitimacy of Police Among Young African-American Men

Introduction by Dean Joseph D. Kearney It is a privilege for me to introduce the George and Margaret Barrock Lecture. Permit me to begin by saying a few words about the individuals in whose memory this lecture stands. While I would do this in any event, it is especially appropriate to do so this year, for this is the inaugural Barrock Lecture. George Barrock was a Marquette lawyer, from our class of 1931. George’s parents were from Lebanon, coming over to the United States on a cattle boat. Like so many immigrants, they both modeled a strong work ethic and stressed to their children the importance of education. Upon George’s graduation from law school, he started his own firm in his native Milwaukee. He was primarily a family-law lawyer, although he is said to have always tried to help his client reconcile with his or her spouse rather than divorce, if possible. In all events, George Barrock was fortunate in his own marriage: his wife, Margaret, was not only his partner for life but also worked with him at the firm, on administrative matters. A bequest to support an occasional distinguished lecture in George and Margaret Barrock’s memory was provided by their daughter, Mary Bonfield. This is that lecture, which we have determined to associate with the area of criminal law. While this was not George Barrock’s specialty, it is consistent not only with his daughter’s bequest (to be sure) but with his own practice, which served individual citizens with their everyday legal problems. Moreover, criminal law is an
General equilibrium effects of price distortions on global markets, farm incomes and welfare

Earnings from farming in many developing countries have been depressed by a pro-urban bias in own-country policies as well as by Governments of richer countries favoring their farmers with import barriers and subsidies. Both sets of policies, which reduce national and global economic welfare and contribute to global inequality and poverty, have been undergoing reform since the 1980s. Using the linkage model of the global economy and modifications to the pre-release of version 7 of the Global Trade Analysis Project (GTAP) protection database for 2004, this paper seeks to compare the effect of those reforms to date with those that would come from removing remaining agricultural and trade policies. Two sets of results are thus presented: one showing the effects of policy reforms between 1980-84 and 2004, the other showing what the removal of remaining distortions as of 2004 could be. Both sets of results indicate improvements in the real value of agricultural output and exports, the real returns to farm land and unskilled labor, and real net farm incomes in most developing country regions despite the adverse effect on the international terms of trade for some developing countries that are net food importers or are enjoying preferential access to agricultural markets of high-income countries. Landowners in those high-income countries still offering their farmers price supports could readily afford to compensate them from the benefits of removing remaining agricultural protectionism.
Biological rhythms and mood disorders

Integration of several approaches concerning time and temporality can enhance the pathophysiological study of major mood disorders of unknown etiology. We propose that these conditions might be interpreted as disturbances of temporal profile of biological rhythms, as well as alterations of time-consciousness. Useful approaches to study time and temporality include philological suggestions, phenomenological and psychopathological conceptualizatíons, clinical descriptions, and research on circadian and ultradían rhythms, as well as nonlinear dynamics approaches to their analysis.
Intellectual Capital and Financial Performance in the Banking Sector

As a result of the contributions to science and technology made by humankind, intellectual ability has given rise to knowledge economy that increases the importance of intellectual capital. The development of intellectual capital in corporate dimension provides a competitive advantage and increases the market value of the firms. This study aims to examine whether or not the intellectual capital calculated according to the intangible assets method is reflected in the values that investors accord to firms in the ISE (Istanbul Stock Exchange) banking sector. A new model is developed in this study in order to overcome the limitations of the existing model in the literature. The results suggest that the intellectual capital is highly positively correlated with the market values. The correlation is even stronger for the new model developed in this study. As the importance of the intellectual capital in banking sector is relatively higher than other sectors, firms should give importance to the management of intellectual capital which is not reflected by the traditional accounting method. The intellectual capital should be calculated and reported to the concerned parties.
Market Power: How Does it Arise? How is it Measured?

Market power – how it arises, and how it is measured – is an important topic for the economics field of “industrial organization” (IO). It is also an important topic for managers and for managerial economics, since it can be related to sustainable advantage for a company and it is usually at the center of antitrust cases in which a company may be involved. This chapter defines market power, discusses how it arises, and describes the various methods that have been used for empirically detecting and measuring it. Attention is also given to the role and measurement of market power in important antitrust contexts.
High-Performance Volume Rendering on the Ubiquitous WebGL Platform

We have invented a high-performance GPU based volume rendering algorithm on the ubiquitous WebGL platform. As WebGL is emerging as a standard platform for web applications on mobile devices, a remarkable advantage of our approach is that the advanced volume rendering algorithms can run directly on mobile devices such as smart phones and tablets in which GPU is embedded, anywhere and anytime. Technically, we deployed a novel single-pass rendering pipeline, in contrast to the other WebGL volume rendering systems using the multi-pass approach. We extended the pseudo-color shading and ray function blending by using a custom transfer function widget in the web browser, which enables interactive feature enhancement in rendering. And lastly, to get rid of the limitation in the loop iteration for dynamic loops on the current mobile platforms, we devised a WebGL compliant 3D texture slicer as an alternative solution to rendering of large datasets. Extensive experimental results and performance assessments are reported in the paper.
Public governance in the age of globalization

Contents: Globalization and public governance - a contradiction? , Karl-Heinz Ladeur. Towards a General Theory of Globalization: Frontiers: national and transnational order, Lawrence M. Friedman De-nationalized State agendas and privatized norm-making, Saskia Sassen. The Transformation of the Relationship between Public and Private in a Globalizing Society: Global private regimes: neo-spontaneous law and dual constitution of autonomous sectors? , Gunther Teubner Globalization and the conversion of democracy to polycentric networks: can democracy survive the end of the Nation State? , Karl-Heinz Ladeur. The Change of Law and the State under the Pressure of Globalization: Global government networks, global information agencies and disaggregated democracy, Anne-Marie Slaughter Sovereignty and solidarity: EU and US, Joshua Cohen and Charles F. Sabel Legal orders between autonomy and intertwinement, Mark Van Hoecke. The New Forms of War in a Global Society: On globalization: the military dimension, Martin van Creveld. The Economy and Global Public Governance: The competitive State and the industrial organization of nations, Jean-Jacques Rosa The network economy as a challenge to create new public law (beyond the State), Thomas Vesting International trade as a vector in domestic regulatory reform: discrimination, cost-benefit analysis and negotiations, Joel P. Trachtman Public governance and the co-operative law of transnational markets: the case of financial regulation, Pedro Gustavo Teixeira Index.
The term structure as a predictor of real economic activity

A positive slope of the yield curve is associated with a future increase in real economic activity: consumption (nondurables plus services), consumer durables, and investment. It has extra predictive power over the index of leading indicators, real short-term interest rates, lagged growth in economic activity, and lagged rates of inflation. It outperforms survey forecasts, both in-sample and out-of-sample. Historically, the information in the slope reflected, inter alia, factors that were independent of monetary policy and, thus, the slope could have provided useful information both to private investors and to policymakers. Copyright 1991 by American Finance Association. (This abstract was borrowed from another version of this item.)
Excessive Activation of Poly(ADP-Ribose) Polymerase Contributes to Inherited Photoreceptor Degeneration in the Retinal Degeneration 1 Mouse

Retinitis pigmentosa (RP) is an inherited blinding disease for which there is no treatment available. It is characterized by a progressive and neurodegenerative loss of photoreceptors but the underlying mechanisms are poorly understood. Excessive activation of the enzyme poly(ADP-ribose) polymerase (PARP) has recently been shown to be involved in several neuropathologies. To investigate the possible role of PARP in retinal photoreceptor degeneration, we used the retinal degeneration 1 (rd1) mouse RP model to study PARP expression, PARP activity, and to test the effects of PARP inhibition on photoreceptor viability. PARP expression was found to be equal between rd1 and wild-type counterpart retinas. In contrast to this, a dramatic increase in both PARP activity per se and PARP product formation was detected by in situ assays in rd1 photoreceptors actively undergoing cell death. Furthermore, PARP activity colabeled with oxidatively damaged DNA and nuclear translocation of AIF (apoptosis-inducing factor), suggesting activation of PARP as a bridge between these events in the degenerating photoreceptors. The PARP-specific inhibitor PJ34 [N-(6-oxo-5,6-dihydrophenanthridin-2-yl)-N,N-dimethylacetamide·HCl[ reduced the number of cells exhibiting death markers in a short-term retinal culture paradigm, a protective effect that was translated into an increased number of surviving photoreceptors when the inhibitor was used in a long-term culture setting. Our results thus demonstrate an involvement of PARP activity in rd1 photoreceptor cell death, which could have a bearing on the understanding of neurodegenerations as such. The findings also suggest that the therapeutical possibilities of PARP inhibition should include retinal diseases like RP.
Fast Adaptation of Deep Neural Network Based on Discriminant Codes for Speech Recognition

Fast adaptation of deep neural networks (DNN) is an important research topic in deep learning. In this paper, we have proposed a general adaptation scheme for DNN based on discriminant condition codes, which are directly fed to various layers of a pre-trained DNN through a new set of connection weights. Moreover, we present several training methods to learn connection weights from training data as well as the corresponding adaptation methods to learn new condition code from adaptation data for each new test condition. In this work, the fast adaptation scheme is applied to supervised speaker adaptation in speech recognition based on either frame-level cross-entropy or sequence-level maximum mutual information training criterion. We have proposed three different ways to apply this adaptation scheme based on the so-called speaker codes: i) Nonlinear feature normalization in feature space; ii) Direct model adaptation of DNN based on speaker codes; iii) Joint speaker adaptive training with speaker codes. We have evaluated the proposed adaptation methods in two standard speech recognition tasks, namely TIMIT phone recognition and large vocabulary speech recognition in the Switchboard task. Experimental results have shown that all three methods are quite effective to adapt large DNN models using only a small amount of adaptation data. For example, the Switchboard results have shown that the proposed speaker-code-based adaptation methods may achieve up to 8-10% relative error reduction using only a few dozens of adaptation utterances per speaker. Finally, we have achieved very good performance in Switchboard (12.1% in WER) after speaker adaptation using sequence training criterion, which is very close to the best performance reported in this task (“Deep convolutional neural networks for LVCSR,” T. N. Sainath , Proc. IEEE Acoust., Speech, Signal Process., 2013).
Representation of Dynamical Stimuli in Populations of Threshold Neurons

Many sensory or cognitive events are associated with dynamic current modulations in cortical neurons. This raises an urgent demand for tractable model approaches addressing the merits and limits of potential encoding strategies. Yet, current theoretical approaches addressing the response to mean- and variance-encoded stimuli rarely provide complete response functions for both modes of encoding in the presence of correlated noise. Here, we investigate the neuronal population response to dynamical modifications of the mean or variance of the synaptic bombardment using an alternative threshold model framework. In the variance and mean channel, we provide explicit expressions for the linear and non-linear frequency response functions in the presence of correlated noise and use them to derive population rate response to step-like stimuli. For mean-encoded signals, we find that the complete response function depends only on the temporal width of the input correlation function, but not on other functional specifics. Furthermore, we show that both mean- and variance-encoded signals can relay high-frequency inputs, and in both schemes step-like changes can be detected instantaneously. Finally, we obtain the pairwise spike correlation function and the spike triggered average from the linear mean-evoked response function. These results provide a maximally tractable limiting case that complements and extends previous results obtained in the integrate and fire framework.
Calcitonin measurement in fine-needle aspirate washouts vs. cytologic examination for diagnosis of primary or metastatic medullary thyroid carcinoma

SUMMARY Ultrasound-guided fine-needle aspiration biopsy cytology (FNAB-C) is able to detect approximately 63% of medullary thyroid carcinoma (MTC). The measurement of calcitonin in the needle washout (FNAB-CT) could improve its accuracy. Sixty-two FNAB-C were performed in 38 patients. Serum calcitonin (sCT) was measured before performing FNAB-C. After obtaining a FNAB-C specimen, the needle was washed with 0.5 ml of saline solution to obtain the CT washouts. Receiver operating characteristic (RO C) analysis identified the cut-offs of FNAB-CT and FNAB-CT/sCT. Eighteen MTC were found at final histology. RO C analysis indicated FNAB-CT > 10.4 pg/ml and FNABCT/ sCT > 1.39 as more accurate cut-off values. Overall accuracy, positive (PPV) and negative predictive values (NPV) were 85%, 100 and 83%, respectively, for FNAB-C, 97%, 100%, 96% for FNAB-CT and 90%, 83% and 93% for FNAB-CT/sCT. The integration of FNAB-C and FNAB-CT resulted in 98% overall accuracy, 100% PPV and 98% NPV; the integration of FNAB-C and FNAB-CT/sCT in 90% overall accuracy, 80% PPV and 95% NPV. One of 2 false negative FNAB-CT and one of 3 false negative FNAB CT/sCT were correctly diagnosed by FNAB-C. Eight of 9 non-diagnostic FNAB-C were correctly classified by FNAB-CT and 7 by FNAB CT/sCT. FNAB-CT should integrate but not replace FNAB-C. FNAB-CT is particularly useful in the presence of non-diagnostic FNAB-C.
Automatic generation of analyzable failure propagation models from component-level failure annotations

Model-driven and component-based software engineering methodologies are currently key factors for the successful construction of complex software systems. To effectively apply these methodologies to mission- and safety-critical systems, component-based models should also support hazard analysis techniques and enable the automatic construction of safety cases. This paper outlines a technique, which annotates components with modular failure mode assumptions, described in the failure propagation transformation notation (FPTN) and generates an analyzable failure propagation model for the complete system. Based on this technique, a model-based safety evaluation is possible, which enables the automatic generation of safety cases based on system models. Consequently, a consistency between the safety case and the system model can be ensured, even if the system's architecture is changed.
Climate Change and Food Security to 2050: A Global Economy-wide Perspective

Recent analyses of the possible adverse effects of climate change on agriculture in developing countries have raised food security concerns, especially for farm households whose crop productivity is expected to fall. The present study uses the GTAP global economy-wide model to capture at the same time the expected positive effects on temperate zone crop productivity, which will more or less offset the upward pressure on farm product prices from yield falls in developing countries. Also modelled is an expected adverse effect of higher temperatures and humidity on the productivity of unskilled workers in the tropics, but since they work in nonfarm as well as farm activities the net effect of that shock on agriculture’s competitiveness is an empirical matter. The results suggest there may be less cause for concern over food security than some earlier studies indicated, but the degrees of uncertainty involved in such modelling are sufficient to warrant a precautionary approach.
A Virtual Emotional Freedom Therapy Practitioner: (Demonstration)

The role of virtual humans in a range of health scenarios, including therapy and counselling, are being explored. To help people in managing their emotional health this research project novelly investigates the value of a virtual practitioner to deliver the Emotional Freedom Technique (EFT). EFT, also known as Tapping Method, is a kind of psychological acupressure technique to optimize emotional and physical health. Significantly, we compare two different types of virtual EFT therapists, one that seeks to exhibit empathetic behaviour with another that delivers the therapy in a neutral manner. An initial online semi-interactive study with 37 participants reported benefits for both therapists from baseline emotion, and these improvements increased with a subsequent session, the empathic agent delivered slight but non-significant improvements but did not achieve a higher level of rapport with the human.
Stereotypical Motor Movement Detection in Dynamic Feature Space

Stereotypical Motor Movements (SMMs) are abnormal postural or motor behaviors that interfere with learning and social interaction in Autism Spectrum Disorder patients. An automatic SMM detection system, employing inertial sensing technology, provides a useful tool for real-time alert on the onset of these atypical behaviors, therefore facilitating personalized intervention therapies. To tackle critical issues with inter-subject variability, in this study, we propose to combine long short-term memory (LSTM) with convolutional neural network (CNN) to model the temporal patterns in the sequence of multi-axes IMU signals. Our results, on one simulated and two experimental datasets, show that transferring the raw feature space to a dynamic feature space via the proposed architecture enhances the performance of automatic SMM detection system especially for skewed training data. These findings facilitate the application of SMM detection system in real-time scenarios.
De novo SVM classification of precursor microRNAs from genomic pseudo hairpins using global and intrinsic folding measures

MOTIVATION MicroRNAs (miRNAs) are small ncRNAs participating in diverse cellular and physiological processes through the post-transcriptional gene regulatory pathway. Critically associated with the miRNAs biogenesis, the hairpin structure is a necessary feature for the computational classification of novel precursor miRNAs (pre-miRs). Though many of the abundant genomic inverted repeats (pseudo hairpins) can be filtered computationally, novel species-specific pre-miRs are likely to remain elusive. RESULTS miPred is a de novo Support Vector Machine (SVM) classifier for identifying pre-miRs without relying on phylogenetic conservation. To achieve significantly higher sensitivity and specificity than existing (quasi) de novo predictors, it employs a Gaussian Radial Basis Function kernel (RBF) as a similarity measure for 29 global and intrinsic hairpin folding attributes. They characterize a pre-miR at the dinucleotide sequence, hairpin folding, non-linear statistical thermodynamics and topological levels. Trained on 200 human pre-miRs and 400 pseudo hairpins, miPred achieves 93.50% (5-fold cross-validation accuracy) and 0.9833 (ROC score). Tested on the remaining 123 human pre-miRs and 246 pseudo hairpins, it reports 84.55% (sensitivity), 97.97% (specificity) and 93.50% (accuracy). Validated onto 1918 pre-miRs across 40 non-human species and 3836 pseudo hairpins, it yields 87.65% (92.08%), 97.75% (97.42%) and 94.38% (95.64%) for the mean (overall) sensitivity, specificity and accuracy. Notably, A.mellifera, A.geoffroyi, C.familiaris, E.Barr, H. Simplex virus, H.cytomegalovirus, O.aries, P.patens, R.lymphocryptovirus, Simian virus and Z.mays are unambiguously classified with 100.00% (sensitivity) and >93.75% (specificity). AVAILABILITY Data sets, raw statistical results and source codes are available at http://web.bii. a-star.edu. sg/~stanley/Publications