Miracle-dz/UniFAR-FTUs huggingface dataset:
Higher Risk Myelodysplastic Syndromes in Patients with Well-Controlled HIV Infection: Clinical Features, Treatment, and Outcome

Introduction. In advanced HIV prior to combination antiretroviral therapy (ART), dysplastic marrow changes occurred and resolved with ART. Few reports of myelodysplastic syndromes (MDS) in well-controlled HIV exist and management is undefined. Methods. Patients with well-controlled HIV and higher risk MDS were identified; characteristics, treatment, and outcomes were reviewed. Results. Of 292 MDS patients since 1996, 1 (0.3%) was HIV-positive. A 56-year-old woman presented with cytopenias. CD4 was 1310 cells/mL and HIV viral load <40 copies/mL. Bone marrow biopsy showed RCMD and karyotype included del(5q) and del(7q); IPSS was intermediate-2 risk. She received azacitidine at 75% dose. Cycle 2, at full dose, was complicated by marrow aplasia and possible AML; she elected palliation. Three additional HIV patients with higher risk MDS, aged 56–64, were identified from the literature. All had deletions involving chromosomes 5 and 7. MDS treatment of 2 was not reported and one received palliation; all died of AML. Conclusion. Four higher risk MDS in well-controlled HIV were below the median age of diagnosis for HIV-negative patients; all had adverse karyotype. This is the first report of an HIV patient receiving MDS treatment with azacitidine. Cytopenias were profound and dosing in HIV patients should be considered with caution.
Dynamic Contrast-Enhanced Magnetic Resonance Imaging Identifies a Subgroup of Patients with Asymptomatic Monoclonal Plasma Cell Disease and Pathologic Microcirculation

Purpose: The aim of our study was to investigate whether dynamic contrast–enhanced magnetic resonance imaging (DCE-MRI) allows visualization of changes in microcirculation between healthy controls on the one side and early/advanced stages of plasma cell disease on the other. Experimental Design: We examined a group of 222 individuals consisting of 60 patients with monoclonal gammopathy of undetermined significance (MGUS), 65 patients with asymptomatic multiple myeloma (aMM), 75 patients with newly diagnosed symptomatic MM (sMM), and 22 healthy controls with DCE-MRI of the lumbar spine. Results: A continuous increase in microcirculation parameters amplitude A and exchange rate constant kep reflecting vascular volume and permeability, respectively, was detected from normal controls over MGUS and aMM to sMM. For A and kep, significant differences were found between controls and aMM (P = 0.03 and P = 0.004, respectively) as well as controls and sMM (P = 0.001 and P < 0.001, respectively). Although diffuse microcirculation patterns were found in healthy controls as well as MGUS and MM, a pattern with focal hotspots was exclusively detected in 42.6% of sMM and in 3 MGUS and 3 aMM patients. MGUS and aMM patients with increased microcirculation patterns showed significantly higher bone marrow plasmocytosis compared with patients with a low microcirculation pattern. Conclusions: Our investigations substantiate the concept of an angiogenic switch from early plasma cell disorders to sMM. Pathologic DCE-MRI findings correlate with adverse prognostic factors and DCE-MRI identifies a distinct group of patients with increased microcirculation parameters in aMM and MGUS patients.
An iterative, dynamically stabilized method of data unfolding

We propose a new iterative unfolding method for experimental data, making use of a regularization function. The use of this function allows one to build an improved normalization procedure for Monte Carlo spectra, unbiased by the presence of possible new structures in data. We are able to unfold, in a dynamically stable way, data spectra which can be strongly affected by fluctuations in the background subtraction and simultaneously reconstruct structures which were not initially simulated. This method also allows one to control the amount of correlations introduced between the bins of the unfolded spectrum, when the transfers of events correcting the systematic detector effects are performed.
Essential role of CIB1 in regulating PAK1 activation and cell migration

p21-activated kinases (PAKs) regulate many cellular processes, including cytoskeletal rearrangement and cell migration. In this study, we report a direct and specific interaction of PAK1 with a 22-kD Ca2+-binding protein, CIB1, which results in PAK1 activation both in vitro and in vivo. CIB1 binds to PAK1 within discrete regions surrounding the inhibitory switch domain in a calcium-dependent manner, providing a potential mechanism of CIB1-induced PAK1 activation. CIB1 overexpression significantly decreases cell migration on fibronectin as a result of a PAK1-and LIM kinase–dependent increase in cofilin phosphorylation. Conversely, the RNA interference–mediated depletion of CIB1 increases cell migration and reduces normal adhesion-induced PAK1 activation and cofilin phosphorylation. Together, these results demonstrate that endogenous CIB1 is required for regulated adhesion-induced PAK1 activation and preferentially induces a PAK1-dependent pathway that can negatively regulate cell migration. These results point to CIB1 as a key regulator of PAK1 activation and signaling.
Hybrid Silhouette and Key-Point Driven 3D-2D Registration

This paper proposes a 3D-2D registration method to determine the pose of a camera from an uncalibrated image of a given 3D model. Through the combined use of global silhouette comparison and local feature point matching, the camera pose of a 2D photograph can be accurately determined by minimising a hybird objective function. The registered photos can be used to stitch textures or refine the geometry of 3D models. This method can be used independently or collaboratively in image-based modeling systems to effectively treat restrictive camera-model position configurations. The experiment shows that our method is more flexible than the methods using only geometrical or local feature information.
SoC Test: Trends and Recent Standards

The well-known approaching test cost crisis, where semiconductor test costs begin to approach or exceed manufacturing costs has led test engineers to apply new solutions to the problem of testing System-On-Chip (SoC) designs containing multiple IP (Intellectual Property) cores. While it is not yet possible to apply generic test architectures to an IP core within a SoC, the emergence of a number of similar approaches, and the release of new industry standards, such as IEEE 1500 and IEEE 1450.6, may begin to change this situation. This paper looks at these standards and at some techniques currently used by SoC test engineers. An extensive reference list is included, reflecting the purpose of this publication as a review paper.
Spatially related image mining on very large image collections

Collections of images of ever growing sizes are becoming common. Structuring and browsing large image databases is a challenging problem. Access to images based on the 3D acquisition location or on the spatial overlap of the scenes they depict is intuitive and has high user acceptability. Commonly, the sets of relevant spatially related images are obtained using manual annotations. A method for discovering spatial overlaps using image content only via image retrieval techniques was proposed. The objective of the proposed approach is to provide a randomized data mining method for finding clusters of images with spatial overlap. Instead of trying to match each image, in turn, the method relies on the min- Hash algorithm for fast detection of random pairs of images with spatial overlap, the so-called cluster seeds. The seeds are then used as visual queries and clusters are obtained as transitive closures of sets of partially overlapping images that include the seed. This approach shows that the probability of finding a seed for an image cluster rapidly increases with the size of the cluster and approaches one fast. For practical database sizes, the running time of the seed generation process is close to linear in the size of the database. The cluster completion process requires a number of visual queries proportional to the number of images in all clusters. The proposed method discovers the spatially related images in large-scale image databases.
Ambidextrous Enterprise Architecting: Betting on the Future and Hacking Path-dependencies

Much existing research on IS and enterprise architecture focuses on suggesting different representations describing a ‘target architecture’ for processes, information and information systems at different levels across the organization. Less emphasis has been put on the actual evolution of the current enterprise architecture towards this envisioned ‘target architecture’. In this paper we look at enterprise architecture from a process perspective and explore how actual practices of architecting enfold and how they are mutually shaped by context. In doing so, we offer two contributions. First, we contribute empirically showing how enterprise architecting in practice is an ambidextrous activity focusing on both fixing the limitations of historically entrenched architectures and establishing new architecture by betting on what needs are going to give the most flexibility and value in the future. Secondly, we contribute by conceptualizing how enterprise architecture evolves over time, and propose the concepts of ‘architectural path-dependency’ and ‘enterprise architecting’. Architectural path-dependencies is the effect of existing architectures that become economically, technically and organizationally hard to change ‐ at least in a radical manner. Enterprise architecting, on the other hand, is the intentional acts to circumvent path-dependencies and evolve towards an envisioned architecture. Henceforth, we argue that enterprise architecture transition is shaped by multiple architectural path-dependencies as well as various acts of enterprise architecting to establish new paths. The paper discusses theses concepts in relation to existing literature on software and enterprise architecture.
On the energy savings of network coding in wireless networks

The energy consumption of a wireless device is modeled by including not only the energy emitted while transmitting, but also energy consumed by supporting circuitry. In particular also receiver energy consumption is taken into account. It is shown that under this model, compared to traditional routing, the energy reduction oﬀered by network coding is signiﬁcantly diﬀerent from results reported in the literature based on an energy consumption model that includes the energy emitted while transmitting only. Moreover, it is illustrated that energy can be saved by increasing the transmission power. Whereas this causes individual transmissions to consume more energy, overall energy consumption can be reduced since more coding opportunities arise.
Costly Public Disclosure and the Choice Between Private and Public Debt

This paper examines the implications of costly public disclosure within the context of a firm’s financing choice between private and public debt. Because private debt avoids costly public disclosure, extant theory posits that firms who discern disadvantages in disclosing firm-specific information publicly will find it cost efficient to raise funds in private debt markets. Using a sample of new debt issues, we find that firms are more likely to issue private debt when disclosure costs are high. We complement these results by also examining the relation between the mix of private and public debt claims in firms’ capital structure and disclosure costs. Consistent with theory, we find the level of private debt claims outstanding increases with the level of disclosure costs. Overall, our results hold after controlling for the endogeneity of firms’ disclosure policy. Our results are also robust to the inclusion of firm characteristics that have been posited by theory to influence the choice between private and public debt. Costly Public Disclosure and the Choice between Private and Public Debt
Real-Time Hand Tracking for Natural and Direct Interaction

Copyright is held by the author/owner(s). CHI 2010, April 10–15, 2010. Atlanta, Georia, USA ACM 978-1-60558-930-5/10/04. Abstract Hand tracking is a useful technique for interaction in many applications, for example for navigation in virtual environments, virtual assembly simulation, gesture recognition, and motion capture. Therefore, our goal is to track the global position and all finger joint angles of a human hand in real-time. Due to measurement noise, occlusion, cluttered background, inappropriate illumination, high dimensionality, and real-time constraints, hand-tracking is a very important and interesting scientific challenge. We capture images of the hand from different directions with multiple cameras. We use a model based approach to track the hand. As matching features, we use skin segmentation combined with a silhouette area comparison and an edgegradient based similarity measure. We utilize dimension reduction techniques to cope with the high complexity of the tracking problem (the hand has about 20 local DOFs and 6 global DOFs).
An Outer Approximation Method for the Variational Inequality Problem

We study two outer approximation schemes, applied to the variational inequality problem in reflexive Banach spaces. First we propose a generic outer approximation scheme, and its convergence analysis unifies a wide class of outer approximation methods applied to the constrained optimization problem. As is standard in this setting, boundedness and optimality of weak limit points are proved to hold under two alternative conditions: (i) boundedness of the feasible set, or (ii) coerciveness of the operator. To develop a convergence analysis where (i) and (ii) do not hold, we consider a second scheme in which the approximated subproblems use a coercive approximation of the original operator. Under conditions alternative to both (i) and (ii), we obtain standard convergence results. Furthermore, when the space is uniformly convex, we establish full strong convergence of the second scheme to a solution.
Basics of tumor development and importance of human papilloma virus (HPV) for head and neck cancer

Head and Neck Squamous Cell Carcinomas (HNSCC) are the 6th most common cancers worldwide. While incidence rates for cancer of the hypopharynx and larynx are decreasing, a significant increase in cancer of the oropharynx (OSCC) is observed. Classical risk factors for HNSCC are smoking and alcohol. It has been shown for 25 to 60% of OSCC to be associated with an infection by oncogenic human papilloma viruses (HPV). The development of “common” cancer of the head and neck is substantially enhanced by an accumulation of genetic changes, which lead to an inactivation of tumor suppressor genes or activation of proto-oncogenes. A more or less uniform sequence of different DNA-damages leads to genetic instability. In this context, an early and frequent event is deletion on the short arm of chromosome 9, which results in inactivation of the p16-gene. In contrast, for HPV-induced carcinogenesis, expression of the viral proteins E6 and E7 is most important, since they lead to inactivation of the cellular tumor-suppressor-proteins p53 and Rb. The natural route of transoral infection is a matter of debate; peroral HPV-infections might be frequent and disappear uneventfully in most cases. Smoking seems to increase the probability for developing an HPV-associated OSCC. The association of HNSCC with HPV can be proven with established methods in clinical diagnostics. In addition to classical prognostic factors, diagnosis of HPV-association may become important for selection of future therapies. Prognostic relevance of HPV probably surmounts many known risk-factors, for example regional metastasis. Until now, no other molecular markers are established in clinical routine. Future therapy concepts may vary for the two subgroups of patients, particularly patients with HPV-associated OSCC may take advantage of less aggressive treatments. Finally, an outlook will be given on possible targeted therapies.
C OMPUTATION BASED ON V ARIABLE SUPPORT WINDOW

We propose in this paper a real-time dense stereo matching algorithm using variable support window for disparity map computing. Basic real-time local algorithms relying on a fixed and rectangular correlation window suffer from the difficulty for window-based methods lies in determining the best window shape and size for each pixel. This work proposes a novel local approach using a combination of the DSI (Disparity Space Image) structure and gradient information. Two improvements are introduced so that an accurate and fast result will be reached. The first one concerns the proposition of a new strategy in order to optimize the computation time of the initial disparity map. The second one, concerns the pixel similarity measure for matching score computation and it consists to use in addition to the traditional pixel intensities, the magnitude and orientation of the gradients providing more accuracy. Experimental results on real data sets are conducted and a comparative evaluation of the obtained results relatively to the state-of-art methods is presented.
Analog circuit state identification by means of diffferential evolution

An evolutionary technique for a linear analog circuit state recognition is presented in this paper. Transfer function zeros, poles and its amplification coefficient are determined by means of differential evolution. Time responses to a unit step stimulus for the circuit under test and for the evaluated phenotype are compared during the fitness calculation. Absolute response error of phenotype is minimized during evolution cycles to achieve the desired transfer function. The proposed method can be used for a linear analog circuit diagnosis, especially during the design stage when accurateness of diagnose is more critical than computations time.
Learning language with technology in a hybrid university EAP course

Today’s college campuses are offering increased alternatives to the traditional face-to-face classroom, including hybrid or blended courses that combine online and face-to-face elements. Language learning is no exception. This instrumental case study examines the affordances and constraints of integrating technology into a hybrid language classroom, following one teacher’s construction of an undergraduate, hybrid English for Academic Purpose (EAP) grammar class for ten international students in their first year of study at an American university. Drawing on data from this single classroom case, findings address both the instructor’s and students’ perceptions of course content and delivery, knowledge expression activities, and classroom assessments. An understanding of multivoiced interpretations of hybrid learning illuminates the benefits and challenges of technology integration. Data sources include teacher, student, and focus group interviews, student pre-, mid-, and post-class surveys, document analysis of instructor lessons and course design, classroom observations, and reflective journaling over the course of the semester. Data analysis drew deeply from the phenomenological approach to data organization and interpretation. Findings were presented using textural, structural, and composite phenomenological elements. Through active collaboration with the language instructor, I document one teacher’s experience in purposeful hybrid course development and design, carefully recording and describing the essence of integrating technology tools to teach and the meanings that students articulate as they engage in new learning modalities. The research found that not only did the international students display a typical range of course success, they also articulated a value for Learning language in a hybrid university EAP course 5 learning how to use the technology in a new and unfamiliar learning environment. While there was some confusion on the students’ part about the distinction between learning independently and completing online activities/homework, the students reported that the self-reliant nature of the hybrid format better prepared them for their future studies. This dissertation yielded empirically-based, practical implications to support the implementation of knowledge-driven, pedagogically sound hybrid learning environments. Learning language in a hybrid university EAP course 6 Table of
Nonparametric Estimation of State-Price Densities Implicit in Interest Rate Cap Prices

Based on a multivariate extension of the constrained locally polynomial estimator of Ait-Sahalia and Duarte (2003), we provide one of the first nonparametric estimates of probability densities of LIBOR rates under forward martingale measures and state-price densities (SPDs) implicit in interest rate cap prices. The forward densities and SPDs depend significantly on the slope and volatility of LIBOR rates, and mortgage markets activities have strong impacts on the shape of the forward densities. The SPDs exhibit a pronounced U-shape as a function of future LIBOR rates, suggesting that the state prices are high at both extremely low and high interest rates, which tend to be associated with recessions and periods of high inflation, respectively. Our results provide nonparametric evidence of unspanned stochastic volatility and suggest that the unspanned factors could be partly driven by activities in the mortgage markets. The Author 2009. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please e-mail: journals.permissions@oxfordjournals.org. , Oxford University Press.
MIMO channel estimation with dimension reduction

The number of channel estimates that have to be estimated in multiple-input multiple-output (MIMO) system is in general much larger, than in a single antenna communication scheme. This leads to lower signal to noise ratios (SNR) of the channel estimates if a constant pilot power independent from the number of transmit antennas is assumed. The use of long-term spatial channel characteristics can improve channel estimation for MIMO wireless systems. Separating the signal and the noise subspace followed by a dimension reduction can significantly reduce additive noise on channel estimates. This leads to improved channel estimation, especially for MIMO systems with high numbers of antennas, and to lower pilot power requirements.
A discriminative spatial bag-of-word scheme with distinct patch

In the past few years, Bag of Word (BOW) plays an important role in the field of image retrieval and automatic annotation especially in large scale image databases. However, in practice, the spatial location information of visual word is often ignored. Despite much previous work, it remains a challenging task to extract the spatial location information of visual word. Recently, salient object detection has been attracting lots of interest and obtains a series of satisfactory results. In this paper, the novel approach can encode spatial location information into standard BOW representation which utilize salient object in the image. The proposed approach is so simple, yet useful and efficient enough to be applied in large-scale databases. The main properties of this approach are: (1) the potential strength of visual word's spatial location information is extracted and a novel BOW scheme is proposed. (2) the advantage of standard BOW scheme is still retained such as rotational invariance, translational invariance and scaling invariance. (3) The new BOW scheme could significantly enhance the discriminative power. We evaluate our new framework on the standard dataset and the results have shown a significant improvement over the state-of-the-art methods.