Miracle-dz/UniFAR-FTUs huggingface dataset:
Role of the Laboratory in Ensuring Global Access to ARV Treatment for HIV-Infected Children: Consensus Statement on the Performance of Laboratory Assays for Early Infant Diagnosis

A two day meeting hosted by the World Health Organization (WHO) and the U.S. Centers for Disease Control and Prevention (CDC) was held in May 2006 in Entebbe, Uganda to review the laboratory performance of virologic molecular methods, particularly the Roche Amplicor DNA PCR version 1.5 assay, in the diagnosis of HIV-1 infection in infants. The meeting was attended by approximately 60 participants from 17 countries. Data on the performance and limitations of the HIV-1 DNA PCR assay from 9 African countries with high-burdens of HIV/AIDS were shared with respect to different settings and HIV- subtypes. A consensus statement on the use of the assay for early infant diagnosis was developed and areas of needed operational research were identified. In addition, consensus was reached on the usefulness of dried blood spot (DBS) specimens in childhood as a means for ensuring greater accessibility to serologic and virologic HIV testing for the paediatric population.
Creating Shared Value: Ett nytt fenomen eller en naturlig utveckling av Corporate Social Responsibility?

Date: Juny 15th 2011 Level: Master thesis in business administration, 15 ECTS Institution: School of Sustainable development of society and technology, Malardalens University. Authors: Thom Sundberg Philippe Viel Lamare 5th April 1987 30th June 1983 Title: Creating Shared Value: A new phenomenon or a natural development of Corporate Social Responsibility? – A case study of Lansforsakringar Bergslagen Tutor: Finn Wiedersheim-Paul
OAEditor - A FRAMEWORK FOR EDITING ADAPTIVE LEARNING OBJECTS

Distance Learning supported by the WEB is a reality which is growing fast and, like any technological or empirical innovation, it reveals positive and negative aspects. An important aspect is in relation to the monitoring of the activities done by the students since an accurate online assessment of the knowledge acquired is an open and, therefore, worrying subject. A way of minimizing such situation is by using technology to monitor the general performance of the student in the virtual learning environment. This work invests on the construction of the OAEditor framework which allows teachers to create learning objects in the form of educational hyper documents representing conceptual graphs that can adapt to the interaction of the students according to their performance, besides enabling a pedagogical monitoring based on self-evaluative questionnaires which are automatically generated, pondering the navigation and performance obtained.
Identification of the motility-related protein (MRP-1), recognized by monoclonal antibody M31-15, which inhibits cell motility

A murine monoclonal antibody (M31-15) was identified using the penetration-inhibiting assay of a human lung adenocarcinoma cell line (MAC10) and remarkably inhibited the phagokinetic tract motility of various cancer cell lines. The antigen, motility-related protein (MRP- 1), recognized by M31-15, was 25- and 28-kD proteins, and M31-15 was used to isolate a cDNA clone from a human breast carcinoma cDNA library. Sequence analysis revealed that MRP-1 had strong similarity with a B cell surface antigen (CD37), a melanoma-associated antigen (ME491), the target of an antiproliferative antibody (TAPA-1), a human tumor-associated antigen (CO-029), and the Sm23 antigen of the trematode parasite Schistosoma mansoni.
QuestVis and MDSteer : the visualization of high-dimensional environmental sustainability data

The visualization of large high-dimensional datasets is an active topic within the research area of information visualization (infovis), a research area that studies the visual representations of complex abstract datasets. My thesis presents two infovis systems that were motivated by the desire to explore a 294-dimensional environmental sustainability dataset. Our collaborators developed the environmental dataset from expert knowledge on ecological, economical, and social systems which were used to model future scenarios consisting of 294 measures of environmental sustainability such as urban population, water supply levels, or tonnes of waste. Since these complex systems and large datasets are difficult for a non-expert user to comprehend, we developed QuestVis, a tool that applies infovis theories and techniques to improve the comprehensibility during exploration of the environmental dataset. The tool consists of three components: the input panel, the Multiscale Dimension Visualizer (MDV), and the Scenario Space Explorer (SSE). The M D V presents up to ten 294-dimensional future scenarios simultaneously on the screen to enable users to get a quick overview of the data. The simultaneous presentation also enables users to compare multiple future scenarios side-by-side. The SSE presents the space of all 120 000 future scenarios in an interactive two-dimensional layout which provides the user an overview of the possibilities. The SSE is tightly coupled with the M D V to provide context to the specific future scenarios that are presented in the MDV. These tightly linked components together provide an overview-hdetails framework within which users can effectively explore the dataset and immediately see the consequences of their choices. The creation of the dimensionality reduced overview in QuestVis led to a second research direction. We realized that current implementations of Multidimensional Scaling (MDS), a technique that attempts to best represent data point similarity in a low-dimensional embedding, are not suited for many of today's largescale datasets. This realization motivated us to develop MDSteer, a steerable MDS computation engine and visualization tool that progressively computes an MDS layout and handles datasets of over one million points. Our technique employs hierarchical data structures and progressive layouts that allow the user to steer the computation of the algorithm to the interesting areas of the dataset. The algorithm
Maximal frequent sequence mining for finding software clones

Software clones are introduced to source code by copying and slightly modifying code fragments for reuse. Thus, the problem of finding software clones is essentially the detection of strings that partially match. This paper describes a software clone detection technique using a sequential pattern-mining algorithm. After outlining a code normalization technique that extracts code-matching statements of interest from a specific programming language, viz., Java, we discuss how to extract a set of frequent sequences with gaps from a set of sequences that correspond to methods. The proposed algorithm also deals with maximal frequent sequences to find the most compact representation of sequential patterns. We define the maximal frequent sequence in the context of a partial match of sequences or gapped sequences. The novelty of our approach includes modified longest-common-subsequence (LCS) and backtrace algorithms for handling partial matches of sequences systematically. The paper also reports on the results of a case study using Apache Struts 2.5. 2 Core. The results demonstrate the ability of the proposed algorithm to find clones of Types 1, 2, and 3.
The Structure of Mandarin Comparatives 1 mitcho (

In this talk we will explore the syntactic structure of the " phrasal " Mandarin bi comparative. We aim to: • motivate the Mandarin comparative morpheme bi as a v head; • argue against Liu's (1996) PP analysis and Xiang's (2005) DegP analysis on syntactic grounds; • explore a neo-Davidsonian event-based conceptualization of comparison. A comparative generally involves two things to be compared, the target and standard, and a gradable predicate which introduces a scale over which they are compared (predicate of comparison). There are broadly two widely-accepted analyses of the syntax of English adjectival comparatives: Here, the English comparative morpheme "-er " is a Degree node which selects a standard (than-phrase). This Degree phrase is an adjunct of the adjective. AP DegP Deg-er ThanP than standard AP predicate of comparison 1.2 The DegP analysis (Kennedy, 1997) Kennedy (1997) argues for the comparative morpheme (again a Degree) selecting the adjective , with the than-phrase introduced as an adjunct.
Improving the Spatial Prediction of Soil Organic Carbon Stocks in a Complex Tropical Mountain Landscape by Methodological Specifications in Machine Learning Approaches

Tropical forests are significant carbon sinks and their soils’ carbon storage potential is immense. However, little is known about the soil organic carbon (SOC) stocks of tropical mountain areas whose complex soil-landscape and difficult accessibility pose a challenge to spatial analysis. The choice of methodology for spatial prediction is of high importance to improve the expected poor model results in case of low predictor-response correlations. Four aspects were considered to improve model performance in predicting SOC stocks of the organic layer of a tropical mountain forest landscape: Different spatial predictor settings, predictor selection strategies, various machine learning algorithms and model tuning. Five machine learning algorithms: random forests, artificial neural networks, multivariate adaptive regression splines, boosted regression trees and support vector machines were trained and tuned to predict SOC stocks from predictors derived from a digital elevation model and satellite image. Topographical predictors were calculated with a GIS search radius of 45 to 615 m. Finally, three predictor selection strategies were applied to the total set of 236 predictors. All machine learning algorithms—including the model tuning and predictor selection—were compared via five repetitions of a tenfold cross-validation. The boosted regression tree algorithm resulted in the overall best model. SOC stocks ranged between 0.2 to 17.7 kg m-2, displaying a huge variability with diffuse insolation and curvatures of different scale guiding the spatial pattern. Predictor selection and model tuning improved the models’ predictive performance in all five machine learning algorithms. The rather low number of selected predictors favours forward compared to backward selection procedures. Choosing predictors due to their indiviual performance was vanquished by the two procedures which accounted for predictor interaction.
Calibration of SCIAMACHY In-Flight Measured Irradiances and Radiances First Results of Level 1 Validation

SCIAMACHY is part of the payload of ESA’s new Environmental Satellite ENVISAT which was launched into a sunsynchronous polar orbit on 2002-02-28. As a prerequisite for high quality data products an in-flight radiometric and spectral calibration and validation of SCIAMACHY (ir)radiance measurements has to be performed. This paper covers part of the validation efforts during the first nine months of SCIAMACHY in orbit with special emphasis on the application of the internal light sources for radiometric and spectral calibration. Presented is the comparison of the solar irradiance spectrum contained in SCIAMACHY level 1b data products with a solar spectrum derived by R. L. Kurucz, solar irradiances measured by the UARS instruments SOLSTICE and SUSIM, and with the SCIAMACHY solar irradiance derived with independent implemented calibration routines.
Comparison of Temporal Masking Models for Audio Quality Assessment

This paper investigates the use and performance of some recently proposed models for temporal masking in wideband audio quality assessment algorithms. Three published temporal masking models are incorporated into the ITU-standardised PEAQ (Perceptual Evaluation of Audio Quality) algorithm, to assess the accuracy of such models in predicting subjective audio quality. The PEAQ algorithm already includes a temporal masking model, however, the paper shows that the performance of PEAQ may be improved for certain distortions by using a different temporal masking model. Furthermore, a novel temporal masking model is presented in this paper, that appears to further improve the perceptual accuracy of the PEAQ algorithm for most distortions examined.
Saliency Extraction for Gaze-Contingent Displays

Organic Computing is beginning to provide computer systems with organic and biological properties. We believe these systems will benefit from user interfaces that integrate the user more tightly with the system and optimize the way the user absorbs information. To this end, we propose gaze-contingent interactive displays that monitor and guide the user's gaze to make interaction with the system more effective and enjoyable. A vital prerequisite for such a system is the ability to predict one or several salient locations that the user is likely to attend to in a dynamic display, with the goal of then modifying the display to influence the user's direction of gaze. In this paper, we present a structure-tensor-based saliency measure and a novel algorithm for extracting salient locations from saliency maps by using the mechanism of selective lateral inhibition. We assess the quality of the extracted locations by comparing them to the locations actually attended by test subjects.
Speculative Dynamics and the Role of Feedback Traders

This paper summarizes our earlier research documenting the characteristic speculative dynamics of many asset markets and suggests a framework for understanding them. Our model incorporates "feedback traders," traders whose demand is based on the history of past returns rather than the expectation of future fundamentals. We use this framework to describe ways in which the characteristic return patterns might be generated, and also to address the long-standing question of whether profitable speculation stabilizes asset markets.
Making Expert Knowledge of Adaptations of E-Learning Material Available with Patterns

Adapting E-Learning material allows re-using existing material even in changed usage scenarios. But this adaptation is a complex task. To achieve a perfect result expert knowledge is needed. Often adaptations have to be performed by persons who are not experts in performing these tasks. To enable those persons to achieve a satisfying result they need to be supported. Patterns are one possibility to make expert knowledge on certain tasks available to other persons. In this paper an approach is presented how expert knowledge of performing adaptations of existing E-Learning material can be collected and made available with patterns. This approach can also be used to collect knowledge of other processes, e.g. in companies.
Is IP-10 an Accurate Marker for Detecting M. tuberculosis-Specific Response in HIV-Infected Persons?

Background The suboptimal sensitivity of Interferon (IFN)-γ-based in-vitro assays, especially in immunocompromised individuals, emphasizes the need for alternative markers for diagnosing tuberculosis (TB). The objective of this study was to evaluate whether interferon-inducible protein (IP)-10, monocyte chemotactic protein (MCP)-2 and interleukin (IL)-2 can be useful biomarkers for evaluating a specific response to RD1 antigens associated to active TB disease in HIV-infected individuals. Methodology/Principal Findings The study was carried out in India, the country with the highest TB burden in the world. Sixty-six HIV-infected individuals were prospectively enrolled, 28 with active-pulmonary-TB and 38 without. The whole blood assay based on RD1-selected peptides (experimental test) and QuantiFERON-TB Gold In tube (QFT-IT) was performed. Plasma was harvested at day-1-post-culture and soluble factors were evaluated by ELISA. The results indicate that by detecting IP-10, the sensitivity of the experimental test and QFT-antigen (75% and 85.7% respectively) for active TB was higher compared to the same assays based on IFN-γ (42.9% and 60.7% respectively) and was not influenced by the ability to respond to the mitogen. By detecting IP-10, the specificity of the experimental test and QFT-antigen (57.9% and 13.2% respectively) for active TB was lower than what was reported for the same assays using IFN-γ-detection (78.9% and 68.4% respectively). On the other side, in vitro IL-2 and MCP-2 responses were not significantly associated with active TB. Conclusions HIV infection does not impair RD1-specific response detected by IP-10, while it significantly decreases IFN-γ-mediated responses. At the moment it is unclear whether higher detection is related to higher sensitivity or lower specificity of the assay. Further studies in high and low TB endemic countries are needed to elucidate this.
Clinical Interventions in Aging Dovepress a Case of Possibly Pathogenic Psen2 R62c Mutation in a Patient with Probable Early-onset Alzheimer's Dementia Supported by Structure Prediction

hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms Abstract: A 49-year-old Korean male patient with dementia was diagnosed with probable early-onset Alzheimer's disease (AD). He presented with memory problems, personality changes, and disorientation. His family history of dementia was probably negative, since no family member with dementia was found or mentioned. Mild cortical atrophy was observed upon magnetic resonance imaging analyses of his brain, and the single-photon emission computed tomography analysis revealed hypoperfusion in the frontal, temporal, and limbic lobes. The patient was tested for mutations in APP, PSEN1, PSEN2, PGRN, MAPT, and PRNP genes. Genetic analysis revealed R62C mutation in PSEN2 gene. PSEN2 R62C mutation was previously reported in European populations, including Dutch and Belgian families with AD. Herein, we present the first case report of PSEN2 R62C mutation in Asia. PolyPhen-2 and SIFT software analyses predicted this mutation as " possibly damaging " , suggesting its potential involvement with AD. In silico protein structural prediction analyses of PSEN2 R62 and C62 revealed two divergent structures, suggesting that large perturbations of R62C mutation might cause dysfunctions of PSEN2, which may alter the normal amyloid production.
Improving efficiency with surface trajectory-based operations and conformance monitoring

Surface Trajectory-Based Operations (STBO) is a concept of operations for enhancing surface operations in the mid- and far-term by better managing surface traffic and airport resources to enable surface trajectory-based operations. STBO, which is expected to be implemented as part of the Next Generation Air Transportation System (NextGen), proposes the use of automation systems in the tower and better data exchange with users to enhance the efficiency and safety of surface operations. STBO relies on automated tools to assist air traffic controllers and managers with planning for airport configuration changes, sequencing aircraft, assigning runways and taxi routes, and monitoring performance against those taxi routes. This paper focuses on the surface conformance monitoring aspect of STBO and describes a human-in-the-loop simulation designed to test the feasibility and benefits of this concept. This paper will describe at a high level the surface conformance monitoring concept and the conformance monitoring software that was developed by Mosaic ATM. This paper outlines how the software was used and tested in the human-in-the-loop simulation performed at The MITRE Corporation. Results of human-in-the-loop simulation suggest this automation may increase deviation detection accuracy and reduce controller workload. Finally, conclusions will be drawn about the utility of the surface conformance monitoring technologies in enhancing the efficiency of surface operations and reducing controller workload.
Distribution of Human Virus Contamination in Shellfish from Different Growing Areas in Greece, Spain, Sweden, and the United Kingdom

ABSTRACT Viral pollution in shellfish has been analyzed simultaneously across a wide range of geographical regions, with emphasis on the concomitant variations in physicochemical characteristics and social features. The methods for sample treatment and for the detection of human enteric viruses were optimized by the participating laboratories. The second part of this study involves the selection of a protocol for virus detection, which was validated by analyzing the distribution and concentration of human viral pathogens under diverse conditions during an 18-month period in four European countries. Shellfish-growing areas from diverse countries in the north and south of Europe were defined and studied, and the microbiological quality of the shellfish was analyzed. Human adenovirus, Norwalk-like virus, and enterovirus were identified as contaminants of shellfish in all the participating countries. Hepatitis A virus was also isolated in all areas except Sweden. The seasonal distribution of viral contamination was also described. Norwalk-like virus appeared to be the only group of viruses that demonstrated seasonal variation, with lower concentrations occurring during warm months. The depuration treatments currently applied were shown to be adequate for reducing Escherichia coli levels but ineffective for the elimination of viral particles. The human adenoviruses detected by PCR correlate with the presence of other human viruses and could be useful as a molecular index of viral contamination in shellfish.
Playlist generation based on user perception of songs

Large online music collections often frustrate users and have increased the importance of recommender systems. This has led to interesting problem of automated playlist generation. Most of the existing playlist's compare a pair songs based on low-level/mid-level features and calculate the similarity. These systems lack user perception of music. This work supplements such existing systems by providing user perception of songs conveyed in Twitter messages. The proposed system combines audio based features and sentiment associated with the song. This unique fusion not only yields better results but also better user satisfaction. Further a validation on 200 users who used our playlist showed that atleast 67% of the songs in the playlist were liked by the user.
In Silico Identification of Potent Pancreatic Triacylglycerol Lipase Inhibitors from Traditional Chinese Medicine

Pancreatic triacylglycerol lipase (PNLIP) are primary lipases that are critical for triacylglyceride digestion in human. Since reduced metabolism of triacylglyceride might be a plausible concept for weight loss, we screened for potential PNLIP inhibitors from traditional Chinese medicine (TCM) with the aim to identify weight loss candidate compounds. TCM candidates Aurantiamide, Cnidiadin, and 2-hexadecenoic acid exhibited higher Dock Scores than the commercial drug Orlistat, and were also predicted to have inhibitory characteristics against PNLIP using constructed MLR (R2 = 0.8664) and SVM (R2 = 0.9030) models. Molecular dynamics indicated that the TCM-PNLIP complexes formed were stable. We identified that the PNLIP binding site has several residues that can serve as anchors, and a hydrophobic corridor that provides additional stability to the complex. Aurantiamide, Cnidiadin, and 2-hexadecenoic acid all have features that correspond to these binding site features, indicating their potential as candidates for PNLIP inhibitors. The information presented in this study may provide helpful insights to designing novel weight-control drugs.