Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of patient-specific surgical ventricular restoration: importance of an ellipsoidal left ventricular geometry for diastolic and systolic function.

Surgical ventricular restoration (SVR) is a procedure designed to treat heart failure by surgically excluding infarcted tissues from the dilated failing left ventricle. To elucidate and predict the effects of geometrical changes from SVR on cardiac function, we created patient-specific mathematical (finite-element) left ventricular models before and after surgery using untagged magnetic resonance images. Our results predict that the postsurgical improvement in systolic function was compromised by a decrease in diastolic distensibility in patients. These two conflicting effects typically manifested as a more depressed Starling relationship (stroke volume vs. end-diastolic pressure) after surgery. By simulating a restoration of the left ventricle back to its measured baseline sphericity, we show that both diastolic and systolic function improved. This result confirms that the increase in left ventricular sphericity commonly observed after SVR (endoventricular circular patch plasty) has a negative impact and contributes partly to the depressed Starling relationship. On the other hand, peak myofiber stress was reduced substantially (by 50%) after SVR, and the resultant left ventricular myofiber stress distribution became more uniform. This significant reduction in myofiber stress after SVR may help reduce adverse remodeling of the left ventricle. These results are consistent with the speculation proposed in the Surgical Treatment for Ischemic Heart Failure trial (20) for the neutral outcome, that "the lack of benefit seen with surgical ventricular reconstruction is that benefits anticipated from surgical reduction of left ventricular volume (reduced wall stress and improvement in systolic function) are counter-balanced by a reduction in diastolic distensibility. "
The development of strong career learning environments: the project ‘Career Orientation and Guidance’ in Dutch vocational education

Abstract Schools are increasingly acknowledging their responsibility to guide students in their career development. However, the guidance that is provided in the Netherlands, as well as in other Western countries, focuses for the most part on helping students towards their academic achievement, and not on helping them to develop competencies to manage their own career. In order to promote this type of career guidance, 37 secondary vocational schools in the Netherlands participated in a project that offered a training programme, aiming to teach teachers how to conduct career dialogues with students. The programme offers expert guidance to integrate a dialogical approach to career guidance and a more enquiry- and practice-based curriculum in the school’s vision and policy. In this article, the results of semi-structured interviews with 50 teachers who participated in the project are presented. These interviews were conducted right after the start of the project, to study how teachers perceive the initial situation regarding career development in their schools, as well as their perception of the initiated plans and ambitions for development, both in their own learning environment and the learning environment of their students.
Comparing feature matching for visual object categorization: MAX vs. bag-of-words

In this paper we address the comparison of two feature matching techniques which can be integrated in the HMAX framework. This comparison involves the originally proposed MAX technique and the histogram technique originating from Bag-of-Words literature. We have found that each of these techniques have their own field of operation. The histogram technique clearly outperforms the MAX technique with 5-15% for small dictionaries up to 500--1,000 features. A second investigation concentrates on comparing the often used hard vector quantization technique and a soft matching score technique for the histogram creation. It was found that the difference in performance is not significant and the scores are often within their standard deviations. Aiming at an embedded implementation such as in a surveillance system, computation power and memory (number of dictionary features) are intrinsically limited, so that the histogram technique is favored over the MAX technique.
BER Degradation of MC-CDMA at High SNR with MMSE Equalization and Residual Frequency Offset

Multicarrier Code Division Multiple Access (MC-CDMA) is an attractive technique for high speed wireless data transmission in view of its advantages over orthogonal frequency division multiplexing. In this paper, we analyze the performance of fully loaded downlink MC-CDMA systems with minimum mean square error (MMSE) equalizer in the presence of residual frequency offset (RFO) in multipath Rayleigh fading channels. We first show that as the SNR is increased beyond a value, referred as threshold SNR, the performance degrades. We then analyze the cause for this behavior and propose a remedy to prevent the degradation by regularizing the coefficient(s) of the equalizer, and use the regularized equalizer for SNRs beyond the threshold value. We suggest two methods for estimating this SNR, one gives close to the true value but requires the knowledge of RFO and the channel state information (CSI), while the other gives an approximate value but requires only CSI. We show that the regularization based on the approximate value also prevents the degradation, but the performance at higher SNRs is slightly poorer compared to that with the better estimate. Numerical and simulation results are provided to support the analysis.
Modelling Simultaneous Defaults: A Top-Down Approach

This article provides a new approach to modeling dependent defaults in a portfolio. Our top-down approach involves modeling the defaults of a set of firms and then allocating the aggregate default risk in each set to the individual firms in the set. The major advantage of our approach is that we can easily incorporate economic factors that lead to high correlations in default intensities. Once we obtain a measure of default risk for a set of firms we apply a process called random thinning to characterize the default intensity of a single firm that is a member of the set. Each firm is assigned a portion of its set9s default risk based on firm characteristics such as leverage, asset volatility, and asset correlation. This allows both pricing of portfolios and single name credits with the ease of a reduced form model and the economic motivation of a structural model. Furthermore, we do comparative static exercises to show how the model behaves and we conduct simulations to compare it to the reduced form and structural models9 predictions of single and multi-name credit derivative prices.
European Conference on Information Systems ( ECIS ) 5-15-2012 SENSING SOCIAL MEDIA FOR CORPORATE REPUTATION MANAGEMENT : A BUSINESS AGILITY PERSPECTIVE

The concept of business agility reflects an organization’s need to develop sensing capabilities for being able to respond to changes in the business environment rapidly. Therefore, intelligent information systems are needed to support decision makers with accurate and timely information. Since corporate reputation is among the most valuable assets, organizations need efficient measuring techniques for being able to manage it. Recently, due to the advent of social media new reputational challenges have emerged for firms, since such technologies significantly increase the risk for being associated with negative issues. Therefore, organizations should utilize there IT-systems for actively sensing social media content as a basis for a quick response to reputational threats. Accordingly, we provide an empirical example on how firms might improve corporate reputation management through sensing social media. Specifically, we analyze a dataset of 271,207 messages about a large American Bank collected from the public microblogging platform Twitter. For our empirical investigation, we applied automated sentiment analysis and manual content analysis. Our results demonstrate how social media might impact corporate reputation and what organizations can do to prepare themselves. Beyond corporate reputation management, analyzing social media content may be valuable for many other purposes to improve an organization’s sensing capabilities.
A Confluence of Traditions: Examining Teacher Practice in the Merging of Secondary Science and Environmental Education

Embedding environmental education within secondary science curriculum presents both philosophical and practical difficulties for teachers. This ethnographic/narrative study, with its methodology grounded in eco-feminism and realism/constructivism, examines the work of six secondary science teachers as they engage in an action research project focused on merging environmental education in their science lessons. Over the course of several months the teachers examine and discuss their views and their professional development related to the project. In the place of definitive conclusions, eight propositions relating the work of secondary science teachers to environmental education, form the basis for a discussion of the implications of the study. The implications are particularly relevant to secondary schools in Ontario, Canada, where the embedding of environmental education in science studies has been mandated.
The Internet of Bio-NanoThings

The Internet of Things (IoT) has become an important research topic in the last decade, where things refer to interconnected machines and objects with embedded computing capabilities employed to extend the Internet to many application domains. While research and development continue for general IoT devices, there are many application domains where very tiny, concealable, and non-intrusive Things are needed. The properties of recently studied nanomaterials, such as graphene, have inspired the concept of Internet of NanoThings (IoNT), based on the interconnection of nanoscale devices. Despite being an enabler for many applications, the artificial nature of IoNT devices can be detrimental where the deployment of NanoThings could result in unwanted effects on health, or pollution. The novel paradigm of the Internet of Bio-Nano Things (IoBNT) is introduced in this paper by stemming from synthetic biology and nanotechnology tools that allow the engineering of biological embedded computing devices. Based on biological cells, and their functionalities in the biochemical domain, Bio-NanoThings promise to enable applications such as intra-body sensing and actuation networks, and environmental control of toxic agents and pollution. The IoBNT stands as a paradigm-shifting concept for communication and network engineering, where novel challenges are faced to develop efficient and safe techniques for the exchange of information, interaction, and networking within the biochemical domain, while enabling an interface to the electrical domain of the Internet.
Evaluation of follow-up results of McBride operative treatment for hallux valgus deformity.

BACKGROUND Hallux valgus still remains a problem in orthopaedic surgery, a fact attested to by over a hundred operating procedures for the correction of this deformity that have been elaborated until now. The aim of the study was to evaluate the results of the McBride procedure for surgical correction of the hallux valgus deformity using an anatomic & functional foot scoring system and roentgenometric assessment. MATERIAL AND METHODS 121 feet in 65 women who underwent the McBride procedure for a hallux valgus deformity at the Orthopaedic Department of the Wrocław University of Medicine in the years 1995-2001 were analysed. The follow-up period varied from 4 to 11 years, for an average of 6.5+4.2 years. Foot function was assessed with a scoring system developed by the author. The roentgenometric examination comprised the following parameters: hallux valgus angle, intermetatarsal angle 1-2, metatarsal I varus angle, and medial sesamoid displacement. RESULTS After the operation the number of painless feet as well as walking ability increased. The number of bunions and the number of painful callosities beneath metatarsal heads also decreased in a statistically significant manner. The average hallux valgus angle on physical examination decreased by 17.2 o. The mean overall functional score increased from 31.2 to 74.1 points, i.e. it rose by two categories, from 'poor' to 'good'. The overall satisfaction rate (excellent and good results) was 76.9%. There were 4 cases (3.3%) of hypercorrection and 14% of the 121 patients experienced a recurrence of the valgus deformity. CONCLUSIONS The McBride procedure is still useful in the treatment of hallux valgus for selected groups of patients, on condition that the qualification criteria are very strictly adhered to.
Brief Intervention Impact on Truant Youth Attitudes to School and School Behavior Problems: A Longitudinal Study

Truancy continues to be a major problem, affecting most school districts in the U.S. Truancy is related to school dropout, with associated adverse consequences, including unemployment and delinquency. It is important to obtain a more complete picture of truants' educational experience. First, the present study sought to examine the longitudinal growth (increasing/decreasing trend) in truant youths' attitudes toward school and misbehavior in school (disobedience, inappropriate behavior, skipping school). Second, this study focused on examining the impact of a Brief Intervention (BI) targeting the youths’ substance use, as well as socio-demographic and background covariates, on their attitudes toward school and school behavior problems over time. A linear growth model was found to fit the attitudes toward school longitudinal data, suggesting the youths’ attitudes toward school are related across time. An auto-regressive lag model was estimated for each of the school misbehaviors, indicating that, once initiated, youth continued to engage in them. Several socio-demographic covariates effects were found on the youths’ attitudes towards school and school misbehaviors over time. However, no significant, overall BI effects were uncovered. Some statistically significant intervention effects were found at specific follow-up points for some school misbehaviors, but none were significant when applying the Holm procedure taking account of the number of follow-ups. The implications of these findings are discussed.
WorkItemExplorer: Visualizing software development tasks using an interactive exploration environment

This demo introduces WorkItemExplorer, an interactive environment to visually explore data from software development tasks. WorkItemExplorer enables developers and managers to investigate activity and correlations in their task management system by making data exploration flexible and interactive, and by utilizing multiple coordinated views. Our preliminary evaluation shows that WorkItemExplorer is able to answer questions that developers ask, while also enabling them to gain new insights through the free exploration of data.
SymMatch: Secure and privacy-preserving symptom matching for mobile healthcare social networks

Recently, mobile healthcare social networks (MHSN), serving as a promising platform for eHealthcare system, has attracted considerable interest. Profile matching is an effective method for medical users to find possible helpers in the mobile healthcare social networks while preserving privacy of the personal health information (PHI). This paper concerns the challenging problem of how to resist inside semi-honest-but-curious medical users from disclosing the PHI by altering their symptom matching results and joining the data transmission group. A new security threat arising from existing profile matching protocols, coined as inflation attack, is first formulated. Then, a new secure and privacy-preserving symptom matching scheme, called SymMatch, is proposed based on homomorphic encryption to thwart the inflation attack and other active attacks. The security analysis and simulation results show the effectiveness and efficiency of the proposed scheme.
The Conditional-Potts Clustering Model

This article presents a Bayesian kernel-based clustering method. The associated model arises as an embedding of the Potts density for class membership probabilities into an extended Bayesian model for joint data and class membership probabilities. The method may be seen as a principled extension of the super-paramagnetic clustering. The model depends on two parameters: the temperature and the kernel bandwidth. The clustering is obtained from the posterior marginal adjacency membership probabilities and does not depend on any particular value of the parameters. We elicit an informative prior based on random graph theory and kernel density estimation. A stochastic population Monte Carlo algorithm, based on parallel runs of the Wang–Landau algorithm, is developed to estimate the posterior adjacency membership probabilities and the parameter posterior. The convergence of the algorithm is also established. The method is applied to the whole human proteome to uncover human genes that share common evolutionary history. Our experiments and application show that good clustering results are obtained at many different values of the temperature and bandwidth parameters. Hence, instead of focusing on finding adequate values of the parameters, we advocate making clustering inference based on the study of the distribution of the posterior adjacency membership probabilities. This article has online supplementary material.
Interferon-g-Mediated Activation of STAT 1 a Regulates Growth Factor – Induced Mitogenesis

Immunomodulatory cytokines and growth factors act in a complex network to regulate diverse biologic processes. Pretreatment of two types of human vascular pericytes, liver fat–storing cells or glomerular mesangial cells, with IFNg dramatically enhanced DNA synthesis in response to PDGF or EGF. IFNg by itself had very little effect on DNA synthesis. At least 24-h exposure of the cells to IFNg is required for enhancement of growth factor–induced mitogenesis. IFNg pretreatment did not influence PDGF or EGF receptor autophosphorylation, activation of phospholipase C g 1, and phosphatidylinositol 3-kinase, or mitogen-activated protein kinase activity. However, IFNg pretreatment markedly potentiated the DNA binding activity of STAT1 a in response to PDGF or EGF. Incubation of cells with antisense oligonucleotides targeting STAT1 a mRNA resulted in inhibition of DNA synthesis induced by the combination of IFNg and PDGF or EGF. These data indicate that interaction between IFNg and growth factors at the level of STAT1 a results in increased DNA synthesis, and establish a role for STAT1 a in this important biologic function of growth factors. ( J. Clin. Invest. 1996. 98:1218–1230.)
Tumor Heterogeneity, Single-Cell Sequencing, and Drug Resistance

Tumor heterogeneity has been compared with Darwinian evolution and survival of the fittest. The evolutionary ecosystem of tumors consisting of heterogeneous tumor cell populations represents a considerable challenge to tumor therapy, since all genetically and phenotypically different subpopulations have to be efficiently killed by therapy. Otherwise, even small surviving subpopulations may cause repopulation and refractory tumors. Single-cell sequencing allows for a better understanding of the genomic principles of tumor heterogeneity and represents the basis for more successful tumor treatments. The isolation and sequencing of single tumor cells still represents a considerable technical challenge and consists of three major steps: (1) single cell isolation (e.g., by laser-capture microdissection), fluorescence-activated cell sorting, micromanipulation, whole genome amplification (e.g., with the help of Phi29 DNA polymerase), and transcriptome-wide next generation sequencing technologies (e.g., 454 pyrosequencing, Illumina sequencing, and other systems). Data demonstrating the feasibility of single-cell sequencing for monitoring the emergence of drug-resistant cell clones in patient samples are discussed herein. It is envisioned that single-cell sequencing will be a valuable asset to assist the design of regimens for personalized tumor therapies based on tumor subpopulation-specific genetic alterations in individual patients.
Contributions , Methods , and Unique Characteristics of Design Studies

Design studies describe and analyze the process of applied visualization research. They focus on describing the why and how of the development of a visualization system for a specific domain, with a secondary focus on the what. Although some design studies introduce novel visual encoding techniques and interaction mechanisms, they differ from other types of visualization papers in their focus on describing and characterizing a target domain [4]. The term design study was introduce in 2003 as one of five paper types in the then Symposium on Information Visualization. These application papers have gained traction in the visualization community ever since. Last year, three of the five papers awarded Best Paper and Honorable Mention at the InfoVis conference were arguably design studies[2, 3, 5]. This year design studies comprised 45 out of 135 papers submitted to the InfoVis conference and 48 out of 185 papers submitted to the Visualization conference1. There is still, however, open discussion in the visualization community about the research contributions and methodology of applied visualization work. My position on this work is two-fold: first, design studies offer a range of contributions to the visualization research community; and second, defining an effective methodology for applied visualization work is a wide-open, and active, research problem. In this workshop I am interested in discussing ideas that work towards clarifying the definition of design studies and their impact. I pose the following three questions:
Trading Project Costs and Benefits in Multi-Attribute Tradespace Exploration

Classical Cost-Benefit Analysis (CBA) is a preferred method for the evaluation of large-scale infrastructure investment projects in the private and government sector. This paper proposes the use of a method for tradespace exploration as an iterative to classical CBA to help overcome some of its shortcomings. Multi-Attribute Tradespace Exploration (MATE), a method for system decision making and design, allows the tradeoff of both desirable and undesirable system (and project) attributes. Undesirable attributes impose “costs” on stakeholders, which can be traded off in a similar manner to desirable attributes, which supply “benefits. ” This method possesses several advantages for the treatment of monetary and non-monetary attribute types compared to classical CBA. Utility for different stakeholders is kept separate, avoiding controversial interpersonal utility aggregation and comparison. Tradeoffs among different types of non-monetary attributes are made explicit. Large numbers of designs can be assessed rapidly, allowing for the exploration of patterns in the tradespaces that may help facilitate negotiations between stakeholders. In order to illustrate the proposed approach, this paper compares the evaluation of a project using classical CBA and MATE through application to an example case from the transportation domain, an airport express from downtown Chicago to O’Hare International Airport.