Miracle-dz/UniFAR-FTUs huggingface dataset:
Treatment-induced pathologic necrosis: a predictor of local recurrence and survival in patients receiving neoadjuvant therapy for high-grade extremity soft tissue sarcomas.

PURPOSE To determine whether treatment-induced pathologic necrosis correlates with local recurrence and overall survival in patients who receive neoadjuvant therapy for high-grade extremity soft tissue sarcomas. PATIENTS AND METHODS Four hundred ninety-six patients with intermediate- to high-grade extremity soft tissue sarcomas received protocol neoadjuvant therapy. All patients underwent surgical resection after neoadjuvant therapy and had pathologic assessment of tumor necrosis in the resected specimens. RESULTS The 5- and 10-year local recurrence rates for patients with > or = 95% pathologic necrosis were significantly lower (6% and 11%, respectively) than the local recurrence rates for patients with less than 95% pathologic necrosis (17% and 23%, respectively). The 5- and 10-year survival rates for the patients with > or = 95% pathologic necrosis were significantly higher (80% and 71%, respectively) than the survival rates for the patients with less than 95% pathologic necrosis (62% and 55%, respectively). Patients with less than 95% pathologic necrosis were 2.51 times more likely to develop a local recurrence and 1.86 times more likely to die of their disease as compared with patients with > or = 95% pathologic necrosis. The percentage of patients who achieved > or /= 95% pathologic necrosis increased to 48% with the addition of ifosfamide as compared with 13% of the patients in all the other protocols combined. CONCLUSION Treatment-induced pathologic necrosis is an independent predictor of both local recurrence and overall survival in patients who receive neoadjuvant therapy for high-grade extremity soft tissue sarcomas. A complete pathologic response (> or = 95% pathologic necrosis) correlated with a significantly lower rate of local recurrence and improved overall survival.
Partial rupture of the proximal Achilles tendon: a differential diagnostic problem in ultrasound imaging

Objectives: The aim of this study was to determine whether ultrasound can correctly visualise partial ruptures of the proximal Achilles tendon. Method: This was a prospective study in which all chronic Achilles tendon injury patients seen at three centres in Germany from 1998 to 2003 were screened. All patients with clinical and/or sonographic signs of abnormalities in the region of the proximal third of the Achilles tendon and tendomuscular junction were included in the analysis. Each of these cases was evaluated by ultrasound following an assessment protocol. Patients with ambiguous ultrasound findings and/or clinical signs were additionally assessed by magnetic resonance imaging (MRI). Results: Sonomorphologic changes suggestive of an abnormality in the proximal third of the Achilles tendon were detected in 13 out of 320 patients (4.2%) with recurring Achilles tendon complaints. Thirteen patients had clinical signs but no sonographic changes in the tendon. The sonographic diagnosis was correct in 19 cases. In six of the 26 cases studied, MRI was needed to establish the correct diagnosis of partial intratendinous rupture of the proximal Achilles tendon. Sensitivity was 0.5, specificity was 0.81, and the overall agreement of the ultrasound examination was 61.5%. All patients were asymptomatic at follow up at a mean of 14 months (range 12–17 months) after surgery. Conclusions: Ultrasound is a useful tool for evaluation of proximal Achilles tendon complaints. However, ultrasound is not sufficiently reliable for diagnosis of all pathologies, especially partial ruptures of the Achilles tendon. Thus, the definitive diagnosis must be established by MRI.
Motion in action : optical flow estimation and action localization in videos. (Le mouvement en action : estimation du flot optique et localisation d'actions dans les vidéos)

With the recent overwhelming growth of digital video content, automatic video understanding has become an increasingly important issue.This thesis introduces several contributions on two automatic video understanding tasks: optical flow estimation and human action localization.Optical flow estimation consists in computing the displacement of every pixel in a video andfaces several challenges including large non-rigid displacements, occlusions and motion boundaries.We first introduce an optical flow approach based on a variational model that incorporates a new matching method.The proposed matching algorithm is built upon a hierarchical multi-layer correlational architecture and effectively handles non-rigid deformations and repetitive textures.It improves the flow estimation in the presence of significant appearance changes and large displacements.We also introduce a novel scheme for estimating optical flow based on a sparse-to-dense interpolation of matches while respecting edges.This method leverages an edge-aware geodesic distance tailored to respect motion boundaries and to handle occlusions.Furthermore, we propose a learning-based approach for detecting motion boundaries.Motion boundary patterns are predicted at the patch level using structured random forests.We experimentally show that our approach outperforms the flow gradient baseline on both synthetic data and real-world videos,including an introduced dataset with consumer videos.Human action localization consists in recognizing the actions that occur in a video, such as `drinking' or `phoning', as well as their temporal and spatial extent.We first propose a novel approach based on Deep Convolutional Neural Network.The method extracts class-specific tubes leveraging recent advances in detection and tracking.Tube description is enhanced by spatio-temporal local features.Temporal detection is performed using a sliding window scheme inside each tube.Our approach outperforms the state of the art on challenging action localization benchmarks.Second, we introduce a weakly-supervised action localization method, ie, which does not require bounding box annotation.Action proposals are computed by extracting tubes around the humans.This is performed using a human detector robust to unusual poses and occlusions, which is learned on a human pose benchmark.A high recall is reached with only several human tubes, allowing to effectively apply Multiple Instance Learning.Furthermore, we introduce a new dataset for human action localization.It overcomes the limitations of existing benchmarks, such as the diversity and the duration of the videos.Our weakly-supervised approach obtains results close to fully-supervised ones while significantly reducing the required amount of annotations.
Apolipoprotein A-I conformation in discoidal particles: evidence for alternate structures.

To define the conformation of apolipoprotein A-I in discoidal particles, the immunoreactivity of a series of epitopes distributed along the apoA-I sequence has been evaluated in lipid-free apoA-I and in lipid-bound form. To this end, reconstituted discoidal lipoproteins, here called LpA-I, and defined by number of apoA-I per particle (e.g., Lp2A-I), have been prepared with palmitoyloleoylphosphatidylcholine, cholesterol, and apoA-I. Four LpA-I have been obtained and studied: two in the Lp2A-I class, 7.8 and 9.6 nm in diameter, and two in the Lp3A-I class, 10.8 and 13.4 nm. The immunoreactivity of all the epitopes tested was significantly different in LpA-I particles compared to lipid-free apoA-I, demonstrating that binding to lipids produces a drastic change in apoA-I conformation. Specific domains in the primary sequence become highly exposed while others are masked. Although the variation in immunoreactivity of the epitopes between various LpA-I was not drastic, significant differences in the calculated ED50 values were observed for a number of antibodies in small versus large particles within each class (Lp2A-I or Lp3A-I), indicating that particle size can modulate apoA-I conformation. In addition, when the competition between pairs of mAbs was analyzed in order to understand the relative position of epitopes, highly significant differences were observed as a function of particle size within each class. In particular, the competition between mAbs recognizing epitopes in the central region of apoA-I was greater in the larger particles than in their small counterparts. (ABSTRACT TRUNCATED AT 250 WORDS)
New Directions in Vector Space Models of Meaning

Symbolic approaches have dominated NLP as a means to model syntactic and semantic aspects of natural language. While powerful inferential tools exist for such models, they suffer from an inability to capture correlation between words and to provide a continuous model for word, phrase, and document similarity. Distributed representations are one mechanism to overcome these constraints. This tutorial will supply NLP researchers with the mathematical and conceptual background to make use of vector-based models of meaning in their own research. We will begin by motivating the need for a transition from symbolic representations to distributed ones. We will briefly cover how collocational (distributional) vectors can be used and manipulated to model word meaning. We will discuss the progress from distributional to distributed representations, and how neural networks allow us to learn word vectors and condition them on metadata such as parallel texts, topic labels, or sentiment labels. Finally, we will present various forms of semantic vector composition, and discuss their relative strengths and weaknesses, and their application to problems such as language modelling, paraphrasing, machine translation and document classification. This tutorial aims to bring researchers up to speed with recent developments in this fastmoving field. It aims to strike a balance between providing a general introduction to vectorbased models of meaning, an analysis of diverging strands of research in the field, and also being a hands-on tutorial to equip NLP researchers with the necessary tools and background knowledge to start working on such models. Attendees should be comfortable with basic probability, linear algebra, and continuous mathematics. No substantial knowledge of machine learning is required.
- 1-An Exploratory Model of Antecedents and Consequences of Public Trust in Government

This paper presents an integrative theoretical model of public trust in government by distinguishing the factors directly related to government activities and contextual factors. Especially, new variables that reflect the current discussions on trusting-relationships with government are introduced – such as process-oriented performance, bureaucratic politics in citizens’ perspective, and constantly – influencing contextual factors. With regard to consequences of trust, in addition to behavioral responses like political participation and public compliance, citizens’ attitudes toward expansion of government roles and governance structure are included. Introduction Public trust in government is considered essential to good governance. High level of public trust leads to reduced administrative costs and citizens’ greater compliance with laws and regulations (Levi 1998; Tyler 1998; Fard & Rostamy 2007). Public trust in government also helps reconcile the need for political accountability and the demand for the discretionary power needed to create a flexible administration by encouraging citizens to accept expanded government authority (Ruscio 1997; Kim 2005). Over the past few decades, however, public trust in government has been declining in the developed world. Reversing this decline in public trust in government has become an important goal of modern government in countries the world over. Reversing such decline in public trust in government has become an important goal of modern government in countries around the world. Numerous studies have been conducted to identify and examine the factors that contribute to the decline in public trust in government. For example, studies have argued that the economic situation, administrative performance of government institutions and programs, irresponsiveness and dishonesty have been found to influence public trust in government; others have suggested that social capital, political scandals, and media intervention can explain declining levels of trust in government (i.e., Nye 1997; Orren 1997; Thomas 1998; Putnam 2000; Mishler & Rose 2001; Vigoda 2002). Most studies, however, show particular aspects of trust or have not developed an integrative framework which includes most of important factors affecting the level of trust. Nye (1997) points out that each of these studies offers only a partial explanation because the causes of trust are complex. Kim (2005) also claims that scholars of public administration have largely failed to develop an appropriate model of public trust that both explores the concept of trust and appropriately addresses its antecedents and implications. In particular, trust is affected by not only government-related variables but also environmental factors, so it is critical to take all of such relevant factors into account. Furthermore, with respect to the consequences of trust in government, public attitudes towards
Testing Toxicity of Intravitreal Bevacizumab (Avastin) used for the Treatment of Choroidal Neovascularization Associated with Age-Related Macular Degeneration: A Full Field ERG Study

Purpose: To evaluate the toxic retinal effects of intravitreal bevacizumab used for the treatment of exudative age-related macular degeneration (AMD) using Ganzfeld Electroretinography (G-ERG) Methods: In this prospective comparative interventional study, 23 patients with active choroidal neovascularization (CNV) associated with AMD were enrolled. Patients were received intravitreal injections of either 2.5 (12 patients) or 1.25 mg (11 patients) of intravitreal bevacizumab. Patients underwent complete ophthalmic examination including visual acuity testing, and G-ERG, at baseline, at one week, at one month, and at three months after intravitreal bevacizumab. Results: Best corrected visual acuity (BCVA) significantly increased from 1.34±0.59 (logMAR) in preinjection examination to 1.07±0.47 (logMAR) at one month (P=0.01), and 1.03±0.46 (logMAR) at three months (P=0.001). G-ERG did not show any significant change in the waveform parameters following intravitreal injection of bevacizumab. No significant difference was found between the two groups in the amount of change in visual acuity and G-ERG recordings of postinjection measurements. Conclusion: Intravitreal bevacizumab did not appear toxic to the retina based on G-ERG recordings.
The Uptick Rule and Short-Selling Strategies

The Security and Exchange Commission revoked the uptick rule in July 2007. The revocation of the uptick rule provides us with a unique setting to investigate the impact of short-sale constraints on various short-selling strategies in a controlled environment. Comparing short-selling behaviors for uptick-rule restricted and unrestricted stocks during the pre- and post-revocation periods, we find that contrarian short selling and voluntary-liquidity short selling are more profound in uptick-rule-restricted stocks than in unrestricted stock and that market trend chasing short selling is less profound in uptick-rule-restricted stocks than in unrestricted stocks. Our results also show that the uptick rule has no impact on risk-bearing short-selling strategies.
An evaluation of open source software adoption by UK SMEs in the IT industry

This study evaluates the adoption of Open Source Software (OSS) by IT Small to Medium­ sized Enterprises (SMEs) in the UK. The growing popularity and acceptance of OSS continues to draw much attention in research and practice. However, researchers and IT practitioners within the UK SME sector still face challenges in understanding the issues that influence the acceptance, adoption, and diffusion of OSS. While previous research studies have focused mainly on the software development model and the unique characteristics of OSS, the area of OSS adoption by UK SMEs has largely been ignored. Furthermore, there is a lack of widely­ acceptable theories that explain the adoption of OSS, implying that there is limited understanding of OSS adoption by UK SMEs. This gap in research has led this thesis to evaluate existing adoption theories and then apply the 'Decomposed Theory of Planned Behaviour' to model the adoption of OSS by SMEs. Based on the emerged conceptual model, an innovative and structured qualitative research design that uses a case study strategy was developed to evaluate the adoption of OSS across 10 UK SMEs in the IT industry. The analysis of the standardised data from the case study interviews led to the definition of the 16 factors of an emergent theory of OSS adoption by IT SMEs. The analysis of that empirical model has led to important conclusions including the following five issues, summarily. (1) The participant IT SMEs were drawn to different benefits, and experienced different challenges, in using OSS, suggesting that there is subjectivity and complexity in the factors influencing OSS adoption. (2) As in most Information and Communication Technology (ICT) adoption, IT­ capability was identified to be essential for successful adoption of OSS, and therefore, it presents potential for important cooperative and collaborative support with OSS communities. (3) The emergent theory from this research study provide researchers and practitioners with variables for surveying critical­success­factors and a reference model for understanding the adoption of OSS. (4) The emergent theory and other general findings from this study are likely to have relevance in other areas of Information Systems research and practice, owing to the factors and theoretical framework that are common to OSS and general ICT acceptance, adoption, and diffusion. (5) This study appears to be the first that has focused on developing a widely­acceptable theory of OSS adoption by IT SMEs in the UK, suggesting that this innovative research study is a novel contribution that has important implications for theory and practice in OSS and general ICT acceptance, adoption, and diffusion.
Stock returns, earnings management, and discretionary accruals : an examination of the accrual anomaly

The purpose of this dissertation is to examine earnings management as it relates to the accrual anomaly. In this examination, three primary research questions arise. First, I address the question as to whether or not accrual decomposition models can, in actuality, be used to identify earnings management firms in the general population of firms. Second, I address the question as to whether or not earnings management firms drive the accrual anomaly. Third, I address the question as to whether or not the accrual anomaly results from a reversal of an overreaction to the earnings announcements of earnings management firms. With respect to the first question, although I am unable to conclude that extreme decile firms, in general, manage earnings, I find that the firms in the highest and lowest discretionary accrual deciles are more likely to contain firms with incentives to manage earnings upwards and downwards, respectively. Results relating to the second question are mixed. While regression analysis does not support the contention that earnings management firms drive the anomaly, hedge portfolio analysis reveals that earnings management firms produce signifcantly higher returns. With regards to the final question, although I find some evidence of positive abnormal returns accruing to high accrual firms and negative abnormal returns to low accrual firms around their announcement dates, the magnitudes of these returns are far too small to explain the long-run returns that have been documented. Additional contributions of this research include 1. ) evidence that the KLW Jones model is most effective at identifying earnings management firms when analyzing the general population of firms and 2. ) evidence that the abnormal returns of the accrual anomaly should be measured from firms’ actual earnings announcement dates, rather than from four months following fiscal year-ends.
Prediction of Treatment Response and the Effect of Independent Component Neurofeedback in Obsessive-Compulsive Disorder: A Randomized, Sham-Controlled, Double-Blind Study

Aims: The goal of this study was to assess the effect of independent component neurofeedback (NFB) on EEG and clinical symptoms in patients with obsessive-compulsive disorder (OCD). Subsequently, we explored predictors of treatment response and EEG correlates of clinical symptoms. Methods: In a randomized, double-blind, parallel design, 20 inpatients with OCD underwent 25 sessions of NFB or sham feedback (SFB). NFB aimed at reducing EEG activity in an independent component previously reported abnormal in this diagnosis. Resting-state EEG recorded before and after the treatment was analyzed to assess its posttreatment changes, relationships with clinical symptoms and treatment response. Results: Overall, clinical improvement in OCD patients was not accompanied by EEG change as assessed by standardized low-resolution electromagnetic tomography and normative independent component analysis. Pre- to posttreatment comparison of the trained component and frequency did not yield significant results; however, in the NFB group, the nominal values at the downtrained frequency were lower after treatment. The NFB group showed significantly higher percentage reduction of compulsions compared to the SFB group (p = 0.015). Pretreatment higher amount of delta (1-6 Hz) and low alpha oscillations as well as a lower amount of high beta activity predicted a worse treatment outcome. Source localization of these delta and high beta oscillations corresponded with previous EEG resting-state findings in OCD patients compared to healthy controls. Conclusion: Independent component NFB in OCD proved useful in percentage improvement of compulsions. Based on our correlation analyses, we hypothesize that we targeted a network related to treatment resistance.
Construction and characterization of multiple human colon cancer cell lines for inducibly regulated gene expression

Validation of targets for cancer drug discovery requires robust experimental models. Systems based on inducible gene expression are well suited to this purpose but are difficult to establish in several epithelial cell types. Using the recently discovered transcriptional transactivator (rtTA2S‐M2), we developed a strategy for fast and efficient generation of Tet On cells. Multiple clones of HCT116, SW480, and HT29 human colon cancer cells for doxycycline‐regulated gene expression were constructed that constitutively express green fluorescent protein (GFP) for selection/maintenance purposes. The cell lines displayed good fold inducibility (49–124× HCT116; 178–621× SW480; 261–787× HT29) and minimal leakiness after transient transfection with a luciferase reporter or with vectors driving inducible expression of red fluorescent protein (dsRed2), constitutively active c‐Src or dominant negative K‐Ras4B. The clones preserved their transformed phenotype as demonstrated by comparing their properties to respective wild type cells, in terms of growth in vitro and in vivo (as tumor xenografts), cell cycle traverse, and sensitivity to drugs used in chemotherapy. These engineered cell lines enabled tightly controlled inducible gene expression both in vitro and in vivo, and proved well suited for construction of double‐stable cell lines inducibly expressing a protein of interest. As such they represent a useful research tool for example, to dissect oncogene function(s) in colon cancer. Supplementary material for this article be found at http://www.mrw. interscience.wiley. com/suppmat/0730‐2312/suppmat/94/suppmat_welman. doc. © 2005 Wiley‐Liss, Inc.