Miracle-dz/UniFAR-FTUs huggingface dataset:
A geometric classification of some solvable groups of homeomorphisms

We investigate subgroups of the group PLo(I) of piecewise‐linear, orientation‐preserving homeomorphisms of the unit interval with finitely many breaks in slope, under the operation of composition, and also subgroups of generalized Thompson groups Fn. We find geometric criteria determining the derived length of any such group, and use these criteria to produce a geometric classification of the solvable and non‐solvable subgroups of PLo(I) and of the Fn. We also show that any standard restricted wreath product (of non‐trivial groups) that embeds in PLo(I) or Fn must have T≅ ℤ.
Combining Wavelets and Computational Intelligence Methods with Applications on Multi-class Classification Datasets

In this paper, we propose a novel algorithm for wavelet feature extraction as input to a supervised Multi-Class Classifier to improve classification performance. In particular, to select the best wavelets coefficient features, we first compute the energy-based variance distribution from wavelets coefficients at different subbands as well as the entropy-based fuzzy measures associated with the training instances. Once we get these entropy-based fuzzy measures associated with the different subsets of wavelets subbands, we apply the Mobius Transform to these entropy-based fuzzy measures to extract the Multivariate Mutual Information associated with the different subsets of wavelets subbands. The goal of these measures is twofold: assign weights (based on the wavelets information content) to all subsets of wavelets subbands and extract the independent (in terms of the multivariate mutual information) subsets of wavelets subbands. In our case, the optimal subsets of wavelets subbands as wavelets features vectors to train a Bayesian Network Model are those which provide a multivariate mutual information equal to zero. Experimental results with the multi-class SRBCT cancer dataset, show that our proposed approach achieves lower classification error in comparison with other methods proposed in the literature. Keywords— fuzzy measures, mutual information, wavelets.
Applying Superselective Conventional TACE

T ransarterial chemoembolization (TACE) is the most commonly performed therapy for inoperable hepatocellular carcinoma (HCC), and a complete response after the initial TACE or during the treatment course is the most robust predictor of a favorable outcome.1 TACE loads hypoxic and chemotherapeutic stress on HCC, and surviving tumors frequently change to a sarcomatous appearance2 or show a mixed hepatocholangiocellular phenotype3 and are usually more aggressive and TACE resistant. Hypoxia induced by TACE also stimulates vascular endothelial growth factor production by the residual tumor cells, which may be a potential cause of recurrent disease.4 Furthermore, some surviving tumors are fed by portal blood if the arterial branches, including extrahepatic collaterals, are severely damaged.5 This suggests that uncontrollable tumors may develop as a result of TACE, and “curative TACE” is necessary to realize a good prognosis.
How Do Differences in Treatment Impact Racial and Ethnic Disparities in Acute Myeloid Leukemia?

Background: We previously demonstrated disparate acute myelogenous leukemia (AML) survival for black and Hispanic patients; these differences persisted despite younger ages and higher prevalence of favorable cytogenetics in these groups. This study determined: (i) whether there are differences in treatment delivered to minorities, and (ii) how these differences affect outcomes in AML. We hypothesize that differences in treatment explain some proportion of survival disparities. Methods: We used California Cancer Registry data linked to hospital discharge abstracts for patients with AML (1998–2008). Logistic regression models estimated odds of treatment (chemotherapy and/or hematopoietic stem cell transplant) by race/ethnicity. Cox proportional hazard models estimated mortality by race after adjustment for treatment. Results: We analyzed 11,084 records. Black race was associated with lower odds of chemotherapy [OR, 0.74; 95% confidence interval (CI), 0.61–0.91]. Black and Hispanic patients had decreased odds of transplant [(OR, 0.64; 95% CI, 0.46–0.87); (OR, 0.74; 95% CI, 0.62–0.89), respectively]. Black patients had increased hazard of mortality (HR, 1.14; 95% CI, 1.04–1.25) compared with whites. Adjustment for receipt of any treatment resulted in decreased mortality (HR, 1.09; 95% CI, 1.00–1.20) for black patients. Conclusions: AML treatment differences for black patients explain some proportion of the disparity. Future AML disparities studies should investigate socioeconomic and other characteristics. Impact: Study findings may better elucidate drivers of disparities in AML. Cancer Epidemiol Biomarkers Prev; 24(2); 344–9. ©2015 AACR.
Geometric Layout Based Graphical Model for Multi-Part Object Tracking

This work puts forth a probabilistic graphical framework to track unoccluded objects undergoing large out of image plane rotations and/or presenting large scale variations in video sequences. The proposed scheme incorporates measurements from an ensemble of local patch trackers and inter-patch geometric layout to arrive at a sample based approximation of the state posterior. Following this, the geometric layout is updated online using the Iterative Conditional Estimation technique. These steps are iterated until convergence to arrive at the final state posterior. In contrast to offline training based schemes the proposed framework imposes no prior on the geometric layout and instead relies on online update of the geometric layout, thus broadening the scope of usage. Amongst other advantages, the scheme implicitly estimates the scale of the target and also adapts to varying target appearances to enable tracking under a fair degree of out of the image plane rotations. The tracking abilities of this scheme is put to test on several challenging videos with scale changes, out of the image plane rotations, illumination changes and motion jerks. Whereever possible qualitative comparisons are facilitated using videos from standard databases.
Physically consistent registration of extraocular muscle models from MRI

Building realistic subject-specific models of the orbit from medical images is important in biomechanical simulations to improve our understanding of extraocular muscle function and the mechanism of human eye movement. With advances in MRI techniques, configurations of orbital structures in different gazes can be captured. We propose to integrate estimated material properties of extraocular muscles in the surface reconstruction to achieve consistent parameterization across gazes. A constrained optimization problem is solved, which generates parametric surfaces satisfying material property constraints. The resultant anatomically accurate and physically meaningful models are discretized in the corresponding deformed material coordinates and consistent with the real tissue deformation. Material correspondences are provided directly. This will ease biomechanical simulation and inverse model parameter estimation.
Social Network and Click-through Prediction with Factorization Machines

The two tasks of KDDCup 2012 are to predict the followers of a microblogger (track 1) and to predict the click-through rate of ads (track 2). On rst glance, both tasks look dierent however they share two important challenges. First, the main variables in both problem settings are of large categorical domain. Estimating variable interactions between this type of variables is dicult with standard machine learning models and factorization models have become popular for such data. Secondly, many additional predictor variables are available which requires exible models based on feature engineering to facilitate model denition. In this work, it is shown how Factorization Machines (FM) can be used as a generic approach to solve both tracks. FMs combine the exibility of feature engineering with the advantages of factorization models. This paper shortly introduces FMs and presents for both tasks in detail the learning objectives and how features can be generated. For track 1, Bayesian inference with Markov Chain Monte Carlo (MCMC) is used whereas for track 2, stochastic gradient descent (SGD) and MCMC based solutions are combined.
Analysis of execution behavior for testing of multi-tasking real-time systems

An important issue in software testing is the ability to observe the execution of the software; this is especially true for real-time systems (RTS). RTS are difficult to observe, and the ability to test RTS is inherently low. Embedded RTS have few interfaces for observation and the execution of multi-tasking RTS is usually non-deterministic. As a consequence, testing of RTS cannot be exercised with existing tools for sequential programs. New tools and methods are necessary that enable observation of the system despite few interfaces while at the same time address the non-determinism issue. The contribution in this thesis is three-folded: (1) we present a tool suite that allows deterministic testing of multi-tasking RTS, in which synchronization of tasks is resolved off-line or on-line. (2) We show by building a test bed how to use the tool suite. (3) We present the design and functionality of Asterix the Real-Time Kernel. In (1) we propose an analysis tool that derives all possible system level control-flow paths of multi-tasking RTS in which synchronization between communicating tasks are resolved on-line by using the Priority Ceiling Emulation Protocol (PCEP; also know as the Immediate Inheritance Protocol). The analysis tool is an extension of an existing tool in which synchronization were resolved off-line by using release time offsets or priorities to separate the tasks in time. Based on the number of derived control-flow paths test coverage criteria are defined, and estimations of test effort can be done early in the development of a system. In (2) we show how the defined test coverage criteria relate to the number of traversed control-flow paths during test execution. We also show how the estimation of tasks’ execution times affects the analysis. The analysis tool is applied on multi-tasking RTS in which the tasks are synchronized offline. The real-time applications are then exercised on the test bed using Asterix as the operating system. In (3) we present a small-sized real-time kernel named Asterix that has support for software based instrumentation of kernel events as well as application usage of system calls. The major problem of software instrumentation is the change in execution behavior that occurs when a RTS is executed without or without the probes. In Asterix we avoid this probe-effect by leaving the probes in the kernel during normal operation. Also, we present a literature survey covering the state-of-the-art in the field real-time systems testing. To Andreas and Emelie
Graph matching through entropic manifold alignment

In this paper we cast the problem of graph matching as one of non-rigid manifold alignment. The low dimensional manifolds are from the commute time embedding and are matched though coherent point drift. Although there have been a number of attempts to realise graph matching in this way, in this paper we propose a novel information-theoretic measure of alignment, the so-called symmetrized normalized-entropy-square variation. We succesfully test this dissimilarity measure between manifolds on a a challenging database. The measure is estimated by means of the bypass Leonenko entropy functional. In addition we prove that the proposed measure induces a positive definite kernel between the probability density functions associated with the manifolds and hence between graphs after deformation. In our experiments we find that the optimal embedding is associated to the commute time distance and we also find that our approach, which is purely topological, outperforms several state-of-the-art graph-based algorithms for point matching.
Deformation mechanism of nylon 6/layered silicate nanocomposites: Role of the layered silicate

Polymer/layered silicate nanocomposites, depending on the molecular weight of nylon 6 as the matrix, were prepared through melt blending with a twin-screw extruder to study their morphology and the role of layered silicates (i.e., montmorillonite) on local deformation processes. A thermal analysis of the nanocomposites was performed with differential scanning calorimetry. The dispersion of the layered silicates and nanocomposite morphology were investigated with wide-angle X-ray scattering and transmission electron microscopy. The results showed that the layered-silicate surfaces predominantly induced γ-form crystals of nylon 6, whereas α-form crystals were nucleated far away from the clay surface. The fraction of γ-form crystals and the degree of exfoliation increased with the molecular weight of the nylon 6 matrix. In a high-molecular-weight nanocomposite, a well-defined exfoliated nanomorphology was observed, in which fine nylon 6 lamellae were most likely to be oriented with their planes perpendicular to the injection-molding direction, although to a great extent the layered silicates were arranged on planes parallel to the injection-molding direction. On the contrary, a mixed nanomorphology appeared in a low-molecular-weight nanocomposite, intercalated and exfoliated nanomorphologies coexisting; the layered silicates were randomly dispersed in the nylon 6 matrix, and the nylon 6 lamellae grew in no preferential direction with respect to the layered-silicate surface. The dispersion of the layered silicates and the orientation of the layered silicates as well as the lamellae were directly reflected in the mechanical deformation processes. The results of in situ deformation experiments under a high-voltage electron microscope (1000 kV) indicated that the main deformation mechanism was microvoid formation either within the intercalated tactoids or in the vicinity of layered silicates in the matrix for intercalated and exfoliated nanomorphology systems, respectively. In the exfoliated nanocomposite, that is, the high-molecular-weight nanocomposite, the external applied stresses were much more effectively transferred from the polymer matrix to the layered silicates; furthermore, microvoid formation took place more uniformly and homogeneously throughout the deformed specimen, and thus a well-improved stiffness/strength/ toughness balance was achieved in comparison with the mixed nanomorphology system (the low-molecular-weight nanocomposite). © 2007 Wiley Periodicals, Inc. JAppl Polym Sci 105: 38–48, 2007
New Human Papilloma Virus E2 Transcription Factor Mimics: A Tripyrrole-Peptide Conjugate with Tight and Specific DNA-Recognition

Background Human papillomavirus (HPV) is the main causative agent of cervical cancer, particularly high risk strains such us HPV-16, -18 and -31. The viral encoded E2 protein acts as a transcriptional modulator and exerts a key role in viral DNA replication. Thus, E2 constitutes an attractive target for developing antiviral agents. E2 is a homodimeric protein that interacts with the DNA target through an α-helix of each monomer. However, a peptide corresponding to the DNA recognition helix of HPV-16 E2 binds DNA with lower affinity than its full-length DNA binding domain. Therefore, in an attempt to promote the DNA binding of the isolated peptide, we have designed a conjugate compound of the E2 α-helix peptide and a derivative of the antibiotic distamycin, which involves simultaneous minor- and major-groove interactions. Methodology/Principal Findings An E2 α-helix peptide-distamycin conjugate was designed and synthesized. It was characterized by NMR and CD spectroscopy, and its DNA binding properties were investigated by CD, DNA melting and gel shift experiments. The coupling of E2 peptide with distamycin does not affect its structural properties. The conjugate improves significantly the affinity of the peptide for specific DNA. In addition, stoichiometric amounts of specific DNA increase meaningfully the helical population of the peptide. The conjugate enhances the DNA binding constant 50-fold, maintaining its specificity. Conclusions/Significance These results demonstrate that peptide-distamycin conjugates are a promising tool to obtain compounds that bind the E2 target DNA-sequences with remarkable affinity and suggest that a bipartite major/minor groove binding scaffold can be a useful approach for therapeutic treatment of HPV infection.
Sampled-data models and zero dynamics for nonlinear systems with relative degree two

This paper derives a more accurate sampled-data model than the Yuz and Goodwin type model for nonlinear systems in the case of the relative degree two, and analyzes the sampling zero dynamics of the sampled-data model to show a condition which assures the stability of the sampling zero dynamics of the proposed model. It is a nature extension of Ishitobi et al.'s result from a single-input single-output (SISO) nonlinear systems to a multi-input multi-output (MIMO) nonlinear systems.
Defense mechanisms and personality in depression

There is a longstanding belief that personality represents a structure that is stable over time, and changes, if at all, very slowly. Nonetheless, clinical and empirical evidence suggests that in patients with some Axis I disorders, the rate of personality disorders using DSM criteria decreases after treatment, suggesting that personality as assessed by phenomenological systems is state‐dependent. An alternative to the DSM phenomenological system of conceptualizing personality is the dynamic concept of character, that is, a predictable pattern of both adaptive and pathological defense mechanisms, and personality organization comprised of object relations, ego strengths, and superego development. Data from this study address the hypothesis that defense mechanisms and personality organization remain relatively stable in patients treated for Axis I disorders, irrespective of clinical improvement. Patients meeting DSM‐IV criteria for major depressive disorder (MDD) entered randomized, controlled medication trials. Defensive functioning was evaluated with the Defense Style Questionnaire (DSQ) [Bond et al., 1983: Arch Gen Psychiatry 40:333–338], and personality organization was assessed with the Inventory of Personality Organization (IPO; Clarkin et al., unpublished), both at baseline and at the completion of the clinical trial. Data were analyzed for whether an individual's pattern of defense mechanisms and personality organization were stable over time regardless of response to treatment of MDD. The question was also asked whether a predominant pattern of defense mechanisms or level of personality organization predicts response to treatment or dropout rate. Among treatment responders, nonresponders and drop‐outs, baseline DSQ scores were similar except for “image‐distorting” defenses, which were significantly more prevalent among drop‐outs compared to responders (P = .016). Post‐treatment DSQ values revealed a significant decrease in “maladaptive” defenses (P = .01) in the entire sample, while intermediate and “adaptive” defenses remained unchanged. This same pattern was found to hold true in treatment responders. When comparing treatment responders and nonresponders at the end of the trial, medication responders used significantly less “maladaptive” defenses than did nonresponders (P = .003), and had a significantly higher, or healthier level of “overall defensive functioning” (P = .04). Baseline and post‐treatment IPO values did not show significant differences. Results of the study address the question of whether there are personality characteristics that are enduring and that can be appreciated irrespective of an Axis I disorder. Depression and Anxiety 10:168–174, 1999. © 1999 Wiley‐Liss, Inc.
Stabilization of nonlinear systems using state-feedback periodic event-triggered controllers

We investigate the scenario where a controller communicates with a plant at discrete time instants generated by an event-triggering mechanism. In particular, the latter collects sampled data from the plant and the controller at each sampling instant, and then decides whether the control input needs to be updated, leading to periodic event-triggered control (PETC). In this paper, we propose a systematic design procedure for PETC that stabilize general nonlinear systems. The design is based on the existence of a continuous-time state-feedback controller, which stabilizes the system in the absence of communication constraints. We then take into account the sampling and we design an event-triggering condition, which is only updated at some of the sampling instants, to preserve stability. An explicit bound on the maximum sampling period with which the triggering rule is evaluated is provided. We show that there exists a trade-off between the latter and a parameter used to define the triggering condition. The results are applied to a van de Pol oscillator as an illustration.
Factor structure and use of the Hospital Anxiety and Depression Scale in the homeless and socially marginalized

Abstract The homeless have been identified as a group at risk of significant anxiety and depression and screening is therefore highly desirable to identify those needing psychological and psychiatric support. However, the psychometric properties of routine screening instruments have yet to be established in this group. This study sought to determine the psychometric properties of the widely used Hospital Anxiety and Depression Scale in this group. Using a cross-sectional design, 314 clients presenting at homelessness units (shelters) supported by The Salvation Army were administered the HADS. Confirmatory factor analysis revealed three-factor models offered the best fit to the data (best-fit model CFI = .98, RMSEA = .06, WRMR = .87). This investigation confirms contemporary research findings that the HADS comprises an underlying tri-dimensional factor structure. However, the internal consistency of the HADS anxiety (alpha = .81) and depression (alpha = .90) sub-scales was excellent. The findings of the current study suggest that the HADS is a suitable screening tool in this group.
High‐dose cefazolin on consecutive hemodialysis in anuric patients with Staphylococcal bacteremia

Methicillin‐sensitive Staphylococcus aureus (MSSA) bacteremia is a leading cause of infection in hemodialysis (HD) patients. Cloxacillin, cefazolin, and vancomycin are the mainstay antimicrobials. Cloxacillin administration leads to frequent drug dosing, longer length of stay (LOS), and higher cost, while resistance and poorer outcomes are associated with vancomycin use. Dosing cefazolin during HD allows for prolonged blood therapeutic levels. We assessed the outcomes and safety of a strategy of treating MSSA bacteremia with 2–3 g cefazolin on HD only. All HD patients with MSSA bacteremia admitted in June–December 2009 at our center and receiving this regime were compared with historical controls who received cloxacillin. Demographic characteristics and outcome measures like mortality, LOS, cost, recrudescence, and adverse drug reactions were assessed. Of 27 consecutive episodes reviewed, 14 and 13 patients received cefazolin and cloxacillin, respectively. Baseline demographics were comparable between the 2 treatment groups. More than one‐third of the bacteremia was related to tunneled catheter infection. The 30‐day mortality of cloxacillin‐ and cefazolin‐treated patients was 15% and 7%, respectively (P=0.14). Two of the 11 survivors treated with cloxacillin (18%) had recrudescent bacteremia while none was observed in cefazolin‐treated survivors. Cefazolin was associated with shorter LOS (10 vs. 20 days, P<0.05) and lower cost (US$8262.00 vs. US$15,367.00, P<0.05). Cefazolin use resulted in 3 idiosyncratic adverse drug reactions. Cefazolin dosed on each HD in MSSA bacteremia leads to earlier discharge and less cost. Larger prospective studies are, however, warranted to fully assess its safety and efficacy.