Miracle-dz/UniFAR-FTUs huggingface dataset:
Streptococcus pneumoniae Serotypes and Mortality in Adults and Adolescents in South Africa: Analysis of National Surveillance Data, 2003 - 2008

Background An association between pneumococcal serotypes and mortality has been suggested. We aimed to investigate this among individuals aged ≥15 years with invasive pneumococcal disease (IPD) in South Africa. Methods IPD cases were identified through national laboratory-based surveillance at 25 sites, pre-pneumococcal conjugate vaccine (PCV) introduction, from 2003–2008. We assessed the association between the 20 commonest serotypes and in-hospital mortality using logistic regression with serotype 4 (the third commonest serotype with intermediate case-fatality ratio (CFR)) as referent. Results Among 3953 IPD cases, CFR was 55% (641/1166) for meningitis and 23% (576/2484) for bacteremia (p<0.001). Serotype 19F had the highest CFR (48%, 100/207), followed by serotype 23F (39%, 99/252) and serotype 1 (38%, 246/651). On multivariable analysis, factors independently associated with mortality included serotype 1 (OR 1.9, 95%CI 1.1–3.5) and 19F (OR 2.9, 95%CI 1.4–6.1) vs. serotype 4; increasing age (25–44 years, OR 1.8, 95%CI 1.0–3.0; 45–64 years, OR 3.6, 95%CI 2.0–6.4; ≥65 years, OR 5.2, 95%CI 1.9–14.1; vs. 15–24 years); meningitis (OR 4.1, 95%CI 3.0–5.6) vs. bacteremic pneumonia; and HIV infection (OR1.7, 95%CI 1.0–2.8). On stratified multivariate analysis, serotype 19F was associated with increased mortality amongst bacteremic pneumococcal pneumonia cases, while no serotype was associated with increased mortality in meningitis cases. Conclusion Mortality was increased in HIV-infected individuals, which may be reduced by increased antiretroviral therapy availability. Serotypes associated with increased mortality are included in the 10-and-13-valent PCV and may become less common in adults due to indirect effects following routine infant immunization.
A Tale of Two Critics : Case Studies in Using Cognitive Walkthrough

Previous HCI-studies have compared usability evaluation methods quantitatively without supplementing these data with detailed qualitative data about how analysts actually learn and use methods. In contrast, we present two diary-based case studies that describe the processes of two novice analysts who learned about and applied the Cognitive Walkthrough (CW; Lewis, et al., 1990) to the specification of a multimedia authoring system. Results show that the two analysts easily learned to use CW but also that they found the technique tedious to use. Moreover, CW was neither reliable when comparing the two analysts’ processes and outcomes to each other, nor accurate when comparing the analysts’ problem predictions to results from usability tests applied to a running system. We examine these data in detail, searching for possible causes of the observed reliability and accuracy. Based on these analyses, we suggest three changes to CW method to improve its accuracy and two changes to improve its reliability. Further, we recommend developing a tool to reduce the tedium and integrate our suggested improvements to CW.
Antepartum risk factors for newborn encephalopathy : the Western Australian case-control study

Objective To ascertain antepartum predictors of newborn encephalopathy in term infants. Design Population based, unmatched case-control study. Setting Metropolitan area of Western Australia, June 1993 to September 1995. Subjects All 164 term infants with moderate or severe newborn encephalopathy; 400 randomly selected controls. Main outcome measures Adjusted odds ratio estimates. Results The birth prevalence of moderate or severe newborn encephalopathy was 3.8/1000 term live births. The neonatal fatality was 9.1%. The risk of newborn encephalopathy increased with increasing maternal age and decreased with increasing parity. There was an increased risk associated with having a mother who was unemployed (odds ratio 3.60), an unskilled manual worker (3.84), or a housewife (2.48). Other risk factors from before conception were not having private health insurance (3.46), a family history of seizures (2.55), a family history of neurological disease (2.73), and infertility treatment (4.43). Risk factors during pregnancy were maternal thyroid disease (9.7), severe pre-eclampsia (6.30), moderate or severe bleeding (3.57), a clinically diagnosed viral illness (2.97), not having drunk alcohol (2.91); and placenta described at delivery as abnormal (2.07). Factors related to the baby were birth weight adjusted for gestational age between the third and ninth centile (4.37) or below the third centile (38.23). The risk relation with gestational age was J shaped with 38 and 39 weeks having the lowest risk. Conclusions The causes of newborn encephalopathy are heterogeneous and many of the causal pathways start before birth.
Increased circulating cytokines in patients with myocarditis and cardiomyopathy.

OBJECTIVES--To elucidate the potential role of cytokines in the pathogenesis of cardiomyopathy and myocarditis. BACKGROUND--Experimental studies show that certain cytokines depress myocardial contractility and that tumour necrosis factor-alpha plays an important part in the pathogenesis of myocardial injury in animal models of viral and autoimmune myocarditis. METHODS--Plasma interleukin 1-alpha, interleukin 1-beta, interleukin-2, interleukin-6, tumour necrosis factor-alpha, tumour necrosis factor-beta, granulocyte-macrophage colony stimulating factor, granulocyte colony stimulating factor, macrophage colony stimulating factor, interferon-alpha and interferon-gamma were measured in 13 patients with acute myocarditis, 23 patients with dilated cardiomyopathy, 51 patients with hypertrophic cardiomyopathy, nine patients with acute myocardial infarction, 18 patients with angina pectoris, 12 patients with essential hypertension and 17 healthy controls. RESULTS--Increased concentrations of cytokines were not detected in the controls. In patients with acute myocarditis, interleukin 1-alpha was detected in 23% (mean (SD) 25 (11) pg/ml), tumour necrosis factor-alpha in 46% (61 (31) pg/ml), and macrophage colony stimulating factor was 2.5 (1.8) ng/ml (normal 1.9 (0.4)). In patients with dilated cardiomyopathy, tumour necrosis factor-alpha was detected in 35% (402 (555) pg/ml). In patients with hypertrophic cardiomyopathy, interleukin-2 was detectable in 14% (2318 (4738) pg/ml) and tumour necrosis factor-alpha ws detected in 20% (992 (1517) pg/ml). The concentration of macrophage colony stimulating factor was raised in patients with acute myocardial infarction. Granulocyte colony stimulating factor was often increased in myocarditis, cardiomyopathies, acute myocardial infarction, and angina pectoris--suggesting activation of macrophages and/or endothelial cells--but this increase was not specific to these diseases. Increased concentrations of cytokines were not found in patients with essential hypertension. CONCLUSION--These results suggest that cytokines may play a part in the pathogenesis of myocardial injury in myocarditis and cardiomyopathies and that further studies to explore the potential pathogenetic role of cytokines in myocardial diseases may be warranted.
Content-based information retrieval and analysis

131 132 Content-based information retrieval and analysis 7.1 Introduction Content-based image or information retrieval (CBIR) has been a subject of intensive research effort for more than a decade now. Content-based retrieval of images differs from many of its neighboring research disciplines in computer vision due to one notable fact: human subjectivity cannot totally be isolated from the use and evaluation of CBIR systems. In our PicSOM 1 CBIR system, parallel Self-Organizing Maps (SOMs) have been trained with separate data sets obtained from the multimodal object data with different feature extraction techniques. The different SOMs and their underlying feature extraction schemes impose different similarity functions on the images, videos, texts and other media objects. In the PicSOM approach, the system is able to discover those of the parallel SOMs that provide the most valuable information for retrieving relevant objects in each particular query. 7.2 Benchmark tasks of natural image content analysis In the course of previous years we have outlined and implemented our generic PicSOM system architecture for image and information retrieval tasks. The architecture is based on extraction of numerous different features from the feature descriptors from the information objects, performing inference separately based on each feature, and fusing the partial inferences. The architecture supports hierarchical organization of the information objects. In the case of image analysis, the hierarchy is used to describe the decomposition of images into segments. We have investigated how our architecture can be applied to various benchmark tasks concerning generic domain photographic images. While individual components of the architecture have been improved during the studies, the general architecture has proven to be successful. The improvements include the incorporation of new feature extraction methods, most notably the Scale-Invariant Feature Transform (SIFT) features calculated from interest points, the use of Support Vector Machines (SVMs) as an alternative to SOMs as the classification method, and alternative early and late feature feature fusion methods. Our group has participated in the annual PASCAL FP6 NoE Visual Object Classes (VOC) Challenges [1, 2]. The material of the Challenges consists of photographic images of natural scenes containing objects from predefined object classes. In 2006 there were approximately 5000 images and ten object classes, including objects such as " bicycle " , " bus " , " cat " and " cow ". For the 2007 Challenge the number of images and object classes were both doubled. The Challenge included the classification task, ie. …
ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions

Non-randomised studies of the effects of interventions are critical to many areas of healthcare evaluation, but their results may be biased. It is therefore important to understand and appraise their strengths and weaknesses. We developed ROBINS-I (“Risk Of Bias In Non-randomised Studies - of Interventions”), a new tool for evaluating risk of bias in estimates of the comparative effectiveness (harm or benefit) of interventions from studies that did not use randomisation to allocate units (individuals or clusters of individuals) to comparison groups. The tool will be particularly useful to those undertaking systematic reviews that include non-randomised studies.
Multicolumn Bidirectional Long Short-Term Memory for Mobile Devices-Based Human Activity Recognition

The ever-growing popularity of mobile devices equipped with accelerometers has provided the opportunity to capture the semantic aspects of human activity and improve user experiences with behavior-based recommendations. These functions depend heavily on the accuracy of human activity recognition, and thus real applications that use mobile devices-based human activity recognition systems (MARSs) need to seamlessly incorporate the information carried by newly labeled training samples. Motivated by the success of the weightlessness feature, we propose a new two-directional feature for bidirectional long short-term memory (BLSTM) for incremental learning in human activity recognition. To further improve the performance, we also present a new ensemble classifier termed multicolumn BLSTM (MBLSTM), which effectively combines different acceleration signal features to further improve activity recognition accuracy. Experiments on the naturalistic mobile devices-based human activity dataset suggest that MBLSTM is superior to other state-of-the-art MARS methods.
Desarrollo de habilidades para la vida en la prevención del consumo de sustancias psicoactivas: un enfoque crítico al modelo existente

The model offered by the World Health Organization and the Pan American Health Organization, from a health and productivity perspective, is insufficient for the development of these skills as a protective factor for the prevention of conducts, such as early consumption of psychoactive substances, every time that, according to the analysis of the accounts of the adolescents participating in this research, shows that there is a perception that this model is welfare oriented and limited to the teaching of the Concepts. Therefore, a critical approach is carried out and a look from Martha Nussbaum’s capabilities approach is proposed.
Constraint Adaptive Natural Gradient Algorithm (CANA) for Adaptive Array Processing

A novel Constraint Adaptive Natural Gradient Algorithm (CANA) is proposed based on the Natural Gradient technique, which is capable of rapidly adjusting the response of an array of sensors to a signal coming from Direction of Interest (DoI) and suppressing noises coming from other directions. Constrained optimization techniques have been extended to enhance the look direction signal in the presence of interference using adaptive natural gradient techniques. Mathematical analysis and realistic MATLAB simulations are developed to confirm the fast convergence of the adaptive weights, and the suitability of algorithm for operations in adverse environments.
1 Project Title & Acronym and Abstract DAESO : Detecting and Exploiting Semantic Overlap

The well-known fact that similar information can be expressed in many different ways is one of the major challenges in building robust NLP applications. It is commonly assumed that such applications can be improved with knowledge of how natural language expressions relate to each other, for instance in terms of paraphrases (same semantic content, different wording) or entailments (one expression implied by the other). DAESO investigates the detection of semantic overlap between Dutch sentences and the exploitation of this knowledge in a range of NLP applications. For this purpose, tools will be developed for the automatic alignment and classification of semantic relations (between words, phrases and sentences) for Dutch, as well as for a Dutch text-to-text generation application which fuses related sentences into a single grammatical sentence, which may be a generalization, a specification or a reformulation of the input sentences. To facilitate development and testing of these tools, an annotated monolingual Dutch parallel/comparable corpus of 1M words will be developed, consisting of pairs of texts that express comparable information. The utility of the resources and tools will be demonstrated in the context of three applications: (1) question-answering systems (improved recall, more complete answers), (2) information extraction (improved recall), and (3) summarization (beyond extraction: sentence compression, sentence fusion, anaphora resolution). There is a long-standing and successful collaboration between the language technology research groups in Antwerp and Tilburg in the field of machine learning for NLP. The various members of the research team have extensive experience with joint collaborations in language technology projects (e.g., the recent IMIX 1 and Prosit 2 NWO projects). For the current project proposal, the participants have complementary capabilities, all of which are needed. Tilburg has experience with phrasal alignment (Marsi and Krahmer, 2005b), natural language generation (Marsi, 1998, 2001; Theune et al., 2001), text-to-text generation techniques (Marsi and Krahmer, 2005a) and anaphora generation (Krahmer et al., 2003). Antwerp has experience with sentence alignment and summarization (Daelemans et al., 2004), anaphora resolution (Hoste, 2005), and question-answering (Buchholz and Daelemans, 2001). Amsterdam adds extensive research and know-how on Question Answering (Jijkoun et al., 2004), including experience with predicting textual entailment (Jijkoun and de Rijke, 2005). Textkernel is a company, specializing in text Mining and Information
SAVIE： An environment for identifying vulnerabilities in software

Software vulnerabilities are recognized as the major cause of system outages. This paper presents a SoftwAre Vulnerabilities Identifying Environment (SAVIE) which is a tool for identifying software weaknesses through profiling and conducting fault injection experiments on target software. SAVIE now supports the identification of two types of vulnerabilities, one is the weak part in software to resist environment perturbation (hardware faults); the other is the internal bugs in the source code of software (software faults). SAVIE also supports different injection methods (can be used on different platforms) and various error types (can be used to find different vulnerabilities), which can also be added by users easily. Experimental results are presented to demonstrate the potential of SAVIE in the identification of software vulnerabilities.
Design and development of an image processing based automatic library storage system

This paper describes the design and development of an image processing based automatic storage system for library. The prototype system comprises of a cartesian robot, two infrared sensors, a four channel motor interface board, a web camera and a PC. After the book has been detected by the infrared sensors, camera captures the image of front cover of the book. The title of the book is extracted and passed to the search engine of library database. The database returns the class and location of the book which is then placed automatically in the corresponding shelf with the help of a cartesian robot, a mechanical structure driven by three direct current (DC) motors. MATLAB® programming environment has been used in developing the system.
Validation of Ten Noninvasive Diagnostic Models for Prediction of Liver Fibrosis in Patients with Chronic Hepatitis B

Background and Aims Noninvasive models have been developed for fibrosis assessment in patients with chronic hepatitis B. However, the sensitivity, specificity and diagnostic accuracy in evaluating liver fibrosis of these methods have not been validated and compared in the same group of patients. The aim of this study was to verify the diagnostic performance and reproducibility of ten reported noninvasive models in a large cohort of Asian CHB patients. Methods The diagnostic performance of ten noninvasive models (HALF index, FibroScan, S index, Zeng model, Youyi model, Hui model, APAG, APRI, FIB-4 and FibroTest) was assessed against the liver histology by ROC curve analysis in CHB patients. The reproducibility of the ten models were evaluated by recalculating the diagnostic values at the given cut-off values defined by the original studies. Results Six models (HALF index, FibroScan, Zeng model, Youyi model, S index and FibroTest) had AUROCs higher than 0.70 in predicting any fibrosis stage and 2 of them had best diagnostic performance with AUROCs to predict F≥2, F≥3 and F4 being 0.83, 0.89 and 0.89 for HALF index, 0.82, 0.87 and 0.87 for FibroScan, respectively. Four models (HALF index, FibroScan, Zeng model and Youyi model) showed good diagnostic values at given cut-offs. Conclusions HALF index, FibroScan, Zeng model, Youyi model, S index and FibroTest show a good diagnostic performance and all of them, except S index and FibroTest, have good reproducibility for evaluating liver fibrosis in CHB patients. Registration Number ChiCTR-DCS-07000039.
Current Advances in Training Orthopaedic Patients to Comply with Partial Weight-Bearing Instructions

Partial weight-bearing instructions are commonly given to orthopaedic patients and are an important part of post-injury and/or post-operative care. However, the ability of patients to comply with these instructions is poorly defined. Training methods for instructing these patients vary widely among institutions. Traditional methods of training include verbal instruction and use of a bathroom scale. Recent technological advances have created biofeedback devices capable of offering feedback to partial weight-bearing patients. Biofeedback devices have shown great promise in training patients to better comply with partial weight-bearing instructions. This review examines the background and significance of partial weight bearing and offers insights into current advances in training methods for partial weight-bearing patients.
User Manual for Libra 0 . 5 . 0

A number of graphical model toolkits have been developed over the years, quite a few of which are open source. Libra is the first open source machine learning toolkit to directly support Bayesian networks (BNs) with decision tree conditional probability distributions (CPDs), dependency networks (DNs), Markov networks (MNs) with sparse factors, and arithmetic circuits (ACs) as an inference representation.1 Libra stands for Learning and I nference in Bayesian networks, Random fields and Arithmetic circuits. Libra’s strength is exploiting local structure such as context-specific independence and feature-based representations to allow richer structure, more compact models, and more efficient inference. The latest version of Libra can be obtained from http://libra.cs. uoregon.edu/. Libra is released under a modified BSD license. This user manual gives a brief overview of Libra’s functionality, describes the file formats used, and explains the operation of each command in the toolkit. See the tutorial for a step-by-step introduction to using Libra, and the developer’s guide for information on modifying and extending Libra.
A combination of different resource management policies in a multi-project environment

Multi-project problem environments are defined according to the way resources are managed in the problem environment which is called the resource management policy (RMP) in this study. Different resource management policies can be defined according to the characteristics of the projects and/or resources in the problem environment. The most common RMP encountered in the multi-project scheduling literature is the resource sharing policy (RSP) where resources can be shared among projects without any costs or limitations. This policy can be seen as an extreme case since there is a strong assumption of unconstrained resource sharing. Another RMP can be defined as the other extreme such that resources cannot be shared among projects which is called resource the dedication policy (RDP). The last RMP considered in this study is between these two policies where resources are dedicated but can be transferred among projects when a project finishes, the dedicated resources to this project can be transferred to another one starting after the finish of the corresponding project. This RPM is called the resource transfer policy (RTP). In this study we investigate a problem environment where all these three types of RPM are present. Additionally, the general resource capacities are taken as decision variables that are constrained by a given general budget. We call this multi-project environment as the Generalized Resource Portfolio Problem (GRPP). We have investigated this problem and proposed an iterative solution approach based on exact solution methods which determines the general resource capacities from the budget, resource dedications, resource sharing and resource transfer decisions and schedules the individual projects. Computational results for over forty test problems are reported.