Miracle-dz/UniFAR-FTUs huggingface dataset:
Considerations for the design and analysis of experimental studies in physical activity and exercise promotion: advantages of the randomised controlled trial

A review of all published articles in the British Journal of Sports Medicine from 1991 to 19951 showed that a wide range of subjects had been covered, but that randomised controlled trials (RCTs) accounted for only 3% of the total number of articles. Common study designs for evaluating (exercise) interventions are “before and after” or “uncontrolled” trials. In these, outcomes of interest in subjects are measured before and after the intervention or exposure—for example, saliva tests before and after an exercise test, or the trials may be unmatched or matched case-control studies, in which subjects under exposure or measurement are compared with controls—for example, by comparison of a questionnaire survey completed by athletes and controls. These designs, though valid and important, are open to potential bias. The scientific outsider may be sceptical about the results and conclusions of such studies in the absence of the authors' detailed description of—for example, recruitment strategies, inclusion criteria, loss to follow up, and rules for interpretation of results of the intervention. Perhaps more importantly, interventions like exercise programmes or advice on physical activity may seem to produce positive results in research projects, but fail to deliver them in real life because of bias hidden in the original study. This can leave practitioners sceptical about research claims and prone to reject a rigorous approach to the evaluation of new ideas and techniques. Minimising bias is important in making sure that we really know what works. In this paper we try to indicate possible sources of bias in the design and analysis of experimental studies and remind sports scientists about the benefits of RCTs for reducing bias. Bias in statistical terms refers to the situation in which the statistical method does not estimate the quantity that is thought to be estimated, or does not test …
On Semi-Static Interference Coordination under Proportional Fair Scheduling in LTE Systems

In this paper we consider the design of semi-static inter-cell interference coordination schemes for LTE networks. In this approach, base stations coordinate the power settings per resource block over long time spans such as seconds. In order to optimize the power settings, one needs to employ models which predict the rate of terminals over the next coordination period under the usage of a given power setting. However, these models are typically quite simple and neglect the impact from fading as well as from dynamic resource allocation performed at the base stations on a millisecond basis. Ignoring such properties of OFDMA networks leads therefore to suboptimal transmit power settings. In this paper, we study the impact from a precise rate prediction model that accurately accounts for fading and dynamic resource allocation. On the down-side, this more precise model leads to a much more involved optimization problem to be solved once per coordination period. We propose two different heuristic methods to deal with this problem. Especially the usage of genetic algorithm results to be promising to counteract the complexity increase. We then study the overall system performance and find precise rate prediction models to be essential for semi-static interference coordination as they provide significant performance improvements in comparison to approaches with simpler models.
Error-Diffusion Kernel Estimation Using Least Squares

In this paper, we propose a method called the iterated estimation of kernel and error (KE estimation) to find the maximum-likelihood (ML) estimate of the error-diffusion (ED) kernel for halftones. The KE estimation consists mainly of iterated bound-constrained least squares (BLS). The KE-estimated kernel avoids the difficulty of regulating the control parameter in the previous least-mean-square (LMS) method. Most importantly, our method also guarantees the two characteristics of ED kernel: every kernel coefficient falls in the range [0,1] and the total of all coefficients must be one. The experimental results show that using the KE estimation to estimate kernel for the halftones generated from an ED process is very effective. The estimate progressively increases its accuracy as the number of iterations increases
A multi-scale approach to rapid transmission of vector river network data via the internet

Rapid transmission of vector map data over the Internet has become a hot issue in the field of spatial data delivery in web-based environment because of the conflict between huge quantity of map data amount and limited network bandwidth. A method of organizing and transmitting vector river data via the Internet is put forward in this paper. This approach considers two levels of importance of river data, i.e. the importance of river branches and the importance of the points belonging to each river branch, and forms data packages according to the two levels of importance. Our experiments have shown that the proposed approach can reduce 90% of original data as well as preserve the river structure well.
The research on uncertainty and information searching in service firms

The purpose of this study is to understand that the behavior behind information searching focuses on customer value within service firms when they faces uncertainty, and to refine the relationship among environmental uncertainty, task uncertainty, and the information search of customer value in service firms. We use an explanatory case study method and there are four service companies and 16 operation activities are in-depth interviewed in this study. The results of findings are: (1) the variety of information with high customer value leads to more frequency on information search; (2) the information on higher customer value leads to service firms organizing the routine process of information search; (3) the task outcome with higher uncertainty leads to information search through more sources; (4) the more intensive contact with suppliers leads to less effort for information search on tasks. This study expects the findings and implications could supplement the service organization management literatures.
Evolution Strategy with Covariance Matrix and decreasing step-size Adaptation (CMDSA-ES)

The Covariance Matrix Adaptation Evolution Strategy (CMA-ES) is state-of-the-art among evolution strategies. However, its adaptation process and parameters selection is rather complicated. The simplified version Covariance Matrix Adaptation and Step-size Self Adaptation Evolution Strategy (CMSA-ES) successfully reduces this complexity by turning to the well known step-size self-adaptation method. In the paper, we provide a new strategy to adapt the step size by analyzing the failure of fixed step-sizes and develop the CMDSA-ES, which is then compared with the CMA-ES and the CMSA-ES on different kinds of test functions and able to exhibit competitive performance.
The Generation of DAML+OIL

daml+oil is a new description logic developed for use within the DAML project and as a submission to the upcoming W3C semantic web ontology working group. It is closely based on the oil, but also has strong influences from the existing W3C efforts as well as input from DAML researchers. daml+oil pushes very close to the undecidability barrier. Developing effective reasoners for daml+oil will stress the capabilities of description logic researchers.
The Flow Analysis of Labour Markets

1. The Flow Approach to Labour and Market Analysis: Introduction, Ronald Schettkat, 2. Flows in Labor Market: Concepts and International Comparative Results, Ronald Schettkat, 3. Institutional Influences on Job and Labor Turnover, Johnathan S. Leonard, 4. Flow Analysis of Labor Markets: Orgins and Policy Relevance, Charles Holt, 5. Cyclical Patterns of Gross Job Flows and the Macroeconomic Relevance of Job Turnover, Tito Boeri, 6. Job Flows and Worker Flows: Issues, and Evidence from a Panel of US Firms, Simon Burgess, Julia Lane and David Stevens, 7. Is the U.S./Canada Unemployment Gap Truly Large? A Labor Flow Analysis, Pierre-Yves Cremieux and Marc Van Audenrode, 8. The Effects of Individual Characteristics and of Parametric and Non-parametric approaches on Job Duration in Japan, Toshiaki Tachibanaki and Atsuhiro Taki, 9. Aspects of Labor Force Dynamics in France, Denis Fougere, 10. Labor Turnover Flows by Type in France Panel Analysis of Large Firms, Gerard Ballot, 11. Job Creation and Destruction in Italy, Bruno Contini, Andrea Gavosto, Riccardo Revelli and Paolo Sestito, 12. The Flow Approach in the Netherlands an Empirical Analysis using Regional Information, Cees Gorter and Jan van Ours, 13. Searching and Job-to-Job Mobility over the Business Cycle, Joop Hartog and Hans van Ophem, 14. Labor Market Dynamics in Germany, Ronald Schettkat, 15. Migration and the Hiring Function: An Examination of Distance and Contiguity Effects in Great Britian, 1975 - 1992, Richard Jackman and Savvas Savouri
A graph model based author attribution technique for single-class e-mail classification

Electronic mails have increasingly replaced all written modes of communications for important correspondences including personal and business transactions. An e-mail is given equal significance as a signed document. Hence email impersonation through compromised accounts has become a major threat. In this paper, we have proposed an email style acquisition and classification model for authorship attribution that serves as an effective tool to prevent and detect email impersonation. The proposed model gains knowledge of the author's email style by being trained only with the sample email texts of the author and then identifies if a given email text is a legitimate email of the author or not. Extracting the significant features that represent an author's style from the available concise emails is a big challenge in email authorship attribution. We have proposed to use a graph-based model to precisely extract the unique feature set of the author. We have used one-class SVM classifier to deal with the single-class sample data that consists of only true positive samples. Two classification models have been designed and compared. The first one is a probability model which is based on the probability of occurrence of a feature in the specific email. The second technique is based on inclusive compound probability of a feature to appear in a sentence of an email. Both the models have been evaluated against the public Enron dataset.
Functional analysis of a novel Cys2/His2-type zinc finger protein involved in salt tolerance in rice

The Cys2/His2-type zinc finger proteins have been implicated in different cellular processes involved in plant development and stress responses. Through microarray analysis, a salt-responsive zinc finger protein gene ZFP179 was identified and subsequently cloned from rice seedlings. ZFP179 encodes a 17.95 kDa protein with two C2H2-type zinc finger motifs having transcriptional activation activity. The real-time RT-PCR analysis showed that ZFP179 was highly expressed in immature spikes, and markedly induced in the seedlings by NaCl, PEG 6000, and ABA treatments. Overexpression of ZFP179 in rice increased salt tolerance and the transgenic seedlings showed hypersensitivity to exogenous ABA. The increased levels of free proline and soluble sugars were observed in transgenic plants compared to wild-type plants under salt stress. The ZFP179 transgenic rice exhibited significantly increased tolerance to oxidative stress, the reactive oxygen species (ROS)-scavenging ability, and expression levels of a number of stress-related genes, including OsDREB2A, OsP5CS OsProT, and OsLea3 under salt stress. Our studies suggest that ZFP179 plays a crucial role in the plant response to salt stress, and is useful in developing transgenic crops with enhanced tolerance to salt stress.
Computational Analysis of Part of Speech Tagging

In order, to make text a suitable input to an automatic method of information extraction it is usually transformed from unstructured source of information into a structured format. Part of Speech Tagging is one of the preprocessing steps which assign one of the parts of speech to the given word. In this paper we had discussed various models of supervised and unsupervised technique shown the comparison of various techniques based on accuracy, and experimentally compared the results obtained in models of Condition Random Field and Maximum Entropy model. We had deployed a model of part of speech tagger for which we had compared the results with other models. The developed is based on HMM approach and had shown good results in terms of efficiency in comparison with other models.
The Open University ’ s repository of research publications and other research outputs Exploring unlikely errors using video games : An example in number entry research Conference Item

A common and important feature of many safety critical interactive devices is number entry. In hospitals, number entry takes the form of setting drug parameters such as doses, volumes, etc. There are several ways a number entry interface can be designed with different consequences for error and speed. Nurses and healthcare practitioners usually have to interact with different interfaces often under pressure and stress of taking care of patients with different health conditions. Error rates in practice are low, undetected error rates are even lower and obtaining the context in which the errors occur is often incredibly difficult due to poor logging systems in many medical devices and high cost of planning and conducting empirical studies. Laboratory based studies also suffer similar limitations in that, without interventions, error rates are also too low to study. This paper explores the benefits of using a gaming context to study safety critical systems. We argue that a game paradigm provides a way that overcomes many of the problems of studying low error rates in safety critical systems and specifically for number entry in medical contexts.
Event-driven Evaluation of Grammar Queries

We present a solution for answering queries on XML streams. Our approach extends the class of queries for which streamed solutions have been proposed to the class of queries expressible by monadic second order logic. We provide an algorithm which efficiently answers the queries despite their large expressiveness. We show that the algorithm reports matches at the earliest possible time during the scan of the input which implicitly leads to high adaptiveness in terms of memory consumption. The efficiency is documented with an experimental evaluation of our approach.
Impact of multi-query optimization in sensor networks

In this paper, we study the problem of processing multiple queries in a wireless sensor network. We focus on multi-query optimization at the base station level to minimize the number of radio messages in the sensor network. We adopt a cost-based approach, and develop a cost model to study the benefit of exploiting common subexpressions in queries. We also propose several optimization algorithms for both data acquisition queries and aggregation queries that intelligently rewrite multiple sensor data queries (at the base station) into "synthetic" queries to eliminate redundancy among them before they are injected into the wireless sensor network. The set of running synthetic queries is dynamically updated by the arrival of new queries as well as the termination of existing queries. We validate the effectiveness of our cost model and our experimental results indicate that our multi-query optimization strategy can provide significant performance improvements.
Health Status and Labour Force Participation in Sub-Saharan Africa: A Dynamic Panel Data Analysis

type="main" xml:lang="en"> Sub-Saharan African countries face significant health challenges, with several countries still far from reaching the health-related targets of the Millennium Development Goals (MDGs). The implication of this on economic growth and individual welfare is daunting. An important channel through which population health affects economic performance is labour supply and productivity. The objective of the study was to investigate a macro level relationship between population health status and labour force participation in sub-Saharan Africa. The study used panel data covering 46 countries from 1990 to 2011. A dynamic panel data model was estimated using the generalized method of moments. The results show that population health status (measured by life expectancy at birth) relates positively with labour force participation. The relationship was significant for total and female labour force participation. The findings call for improved population health status following the importance of labour force participation at the macro levels. Improved labour force contributes to the economic performance of a country at the macro level. Effective policy efforts should be directed towards providing facilities that will improve population health hence providing enough healthy time to participate in the labour force.
First optical detection of the supernova remnant G 15.1-1.6

Deep optical CCD images of the supernova remnant G 15.1−1.6 were obtained where filamentary and diffuse emission was discovered. The images, taken in the emission lines of Hα + [N ii], [S ii], and [O iii], reveal filamentary and diffuse structures all around the remnant. The radio emission at 4850 MHz in the same area is found to be strongly correlated with the brightest optical filaments. The IRAS 60 µm emission may also be correlated with the optical emission but to a lesser extent. The flux-calibrated images suggest that the optical emission originates from shock-heated gas ([S ii]/H α> 0.4), while there is a possible H ii region ([S ii]/Hα ∼ 0.3) contaminating the supernova remnant’s emission to the east. Furthermore, deep long-slit spectra were taken at two bright filaments and also show that the emission originates from shock-heated gas. An [O iii] filamentary structure is also detected farther to the west, but it lies outside the remnant’s boundaries and may not be associated to it. The [O iii] flux suggests shock velocities into the interstellar “clouds” ∼100 km s −1 , while the [S ii]λλ 6716/6731 ratio indicates electron densities up to ∼250 cm −3 . Finally, the Hα emission is measured to be between 2 to 7× 10 −16 erg s −1 cm −2 arcsec −2 , while the lower limit to the distance is estimated at 2.2 kpc.
KNOWLEDGE DISCOVERY FROM PEOPLE AND SEMANTIC NETWORKS-ANALYZING TEXTS IN LANGUAGES WE DO NOT UNDERSTAND

In this paper we present a methodology that makes it possible to mine a document collection from a domain without knowing the language in which the documents are written. This is a challenging problem for enterprises who want to analyze resources they cannot read. We describe in detail a method, tools and results that can be used within a digital library context for science watch and competitive intelligence. We consider a collection associated with the aquaculture domain written in Chinese and extracted from a digital library. Based on the original coding (UNICODE) of the data and the tag marking the structure of the documents, we extract key elements (authors, phrases, etc.) from within the domain and analyse them. The results are displayed in the form of graphs and networks. We extract people networks and semantic networks before examining their evolution over a period of several years. The principles developed in this paper can be applied to any language. ACM taxonomy: H.3. 1Content Analysis and Indexing; H.4. 2.aDecision support
Echo identification and cancellation techniques for antenna measurement in non-anechoic test sites

This paper focuses on the measurement of the antenna radiation patterns when fully anechoic conditions are not available and, as consequence, some undesirable echoes are initially present in the measure. Two techniques are analyzed and compared, which - starting from data measured in the frequency domain - allow the echo contributions to be identified and the antenna radiation pattern to be retrieved. The accuracy of both techniques is evaluated at the frequency of 22 GHz by comparison with measurements obtained in an anechoic chamber.
Microbiome Analysis Across a Natural Copper Gradient at a Proposed Northern Canadian Mine Site

Due to the environmental persistence, bioaccumulation, and toxicity of metals released by mining activities, mitigation methods are crucial to minimize impacts on aquatic environments. Bioremediation is one mitigation strategy used to reduce the potential for metal accumulation and toxicity in aquatic organisms. At a potential mine site in Yukon, Canada, elevated copper (Cu) concentrations and low pH are found in a water course near a naturally mineralized area; however, Cu concentrations and acidity are greatly reduced downstream. Physicochemical processes do not appear to explain this natural remediation and it is suggested that unique microbial communities may be responsible through Cu immobilization. To investigate the role of microbes in sequestering or transforming Cu in the water, biofilm samples were collected from 5 sites along a natural copper gradient: upstream of Cu introduction, on a Cu-rich tributary, 30 m downstream of Cu introduction where Cu levels were reduced, and 2 and 7 km further downstream where Cu concentrations were low. Taxonomic profiles of microbial communities (microbiomes) were compiled using DNA sequencing of 16S rRNA gene amplicons. Clear relationships between total Cu concentrations, pH and the microbiomes were evident. In the most Cu-affected samples, communities were dominated by bacteria from the Gallionellaceae family. Metagenomic sequencing profiled the genes present in microbiomes from the most Cu-contaminated sampling location and the area immediately upstream and showed that microbes in this area are well adapted to tolerate heavy metals. This study provides fundamental knowledge of microbial communities at a potential mine site and characterizes the genes likely involved in providing tolerance to an acidic and metals-rich environment. These results inform hypotheses for future experiments to support the development of bioremediation approaches that incorporate the use of native microorganisms at mining sites.
USING OF STATISTICAL SHAPE MODELS FOR PELVIS RECONSTRUCTION IN THE ONCOLOGIC SURGERY

The reconstruction of the osseous structures in the pelvic region after bone tumour resection is highl y complex and challenging. Up to now the reconstruction of the pe lvis defects by autologous or allogenous grafts (fo r instance the fibula transplants) are highly unsatisfied because of large shape diffe rences. Therefore there is a huge demand for patien t-specific and anatomically shaped implants. Our pelvis reconstruction planning approach is based on the statistical shape model. For generation of the statistical pelvis shape model a large data pool of CT datasets has been collected. The following CT data segmentati on and surface processing methods delivered the required pelvis geometries. V ia Procrustes analysis of the collected pelvis surf aces the parameterized pelvis shape mean model has been calculated and the princi pal component analysis (PCA) [3] applied for estimat ing the anatomically optimal graft or implant geometry. We will demonstrate on the clinical pelvis reconstruction case that the using of statistical shape models in the oncologic surgery planning is robust and very promising method.