Miracle-dz/UniFAR-FTUs huggingface dataset:
Advanced Practice Nursing Competency Assessment Instrument (APNCAI): clinimetric validation

Objective To describe the development and clinimetric validation of the Advanced Practice Nursing Competency Assessment Instrument (APNCAI) through several evidence sources about reliability and validity in the Spanish context. Design and setting APNCAI development was based on a multisequential and systematic process: literature review, instrument content consensus through qualitative Delphi method approach (a panel of 51 Advanced Practice in Nursing –APN– experts was selected) and the clinimetric validation process based on a sample of 600 nurses from the Balearic Islands public healthcare setting. Methods An initial step for tool's content development process based on Delphi method approach of expert consensus was implemented. A subsequent phase of tool validation started from the analysis of APN core competencies latent measurement model, including exploratory and confirmatory techniques. Reliability evidence for each latent factor was also obtained. Items' scores were submitted to descriptive analysis, plus univariate and multivariate normality tests. Results An eight-factor competency assessment latent model obtained adequate fit, and it was composed by ‘Research and Evidence-Based Practice’, ‘Clinical and Professional Leadership’, ‘Interprofessional Relationship and Mentoring’, ‘Professional Autonomy’, ‘Quality Management’, ‘Care Management’, ‘Professional Teaching and Education’ and ‘Health Promotion’. Conclusions Adequate empirical evidence of reliability and validity for APNCAI makes it useful for application in healthcare policy programmes for APN competency assessment in Spain.
Phenomenon of Higher Order Head-of-Line Blocking in Multistage Interconnection Networks under Nonuniform Traffic Patterns (Special Issue on Architectures, Algorithms and Networks for Massively Parallel Computing)

Nonuniform traff ic can degrade the overall performance of multistage interconnection networks substantially. In this paper, this performance degradation is traced back to blocking effects that are not present under uniform traff ic patterns within a network. This blocking phenomenon is not mentioned in the literature and is termed higher order Head-of-Line-blocking (HOLk-blocking) in this paper. Methods to determine the HOL-blocking order of multistage networks in order to classify the networks are presented. The performance of networks under hot-spot traff ic as a function of their HOL-blocking characteristics is studied by simulation. It is shown that network bandwidth and packet delay improve under nonuniform traffics with increasing HOL-blocking order of a network.
De Novo Reconstruction of Consensus Master Genomes of Plant RNA and DNA Viruses from siRNAs

Virus-infected plants accumulate abundant, 21–24 nucleotide viral siRNAs which are generated by the evolutionary conserved RNA interference (RNAi) machinery that regulates gene expression and defends against invasive nucleic acids. Here we show that, similar to RNA viruses, the entire genome sequences of DNA viruses are densely covered with siRNAs in both sense and antisense orientations. This implies pervasive transcription of both coding and non-coding viral DNA in the nucleus, which generates double-stranded RNA precursors of viral siRNAs. Consistent with our finding and hypothesis, we demonstrate that the complete genomes of DNA viruses from Caulimoviridae and Geminiviridae families can be reconstructed by deep sequencing and de novo assembly of viral siRNAs using bioinformatics tools. Furthermore, we prove that this ‘siRNA omics’ approach can be used for reliable identification of the consensus master genome and its microvariants in viral quasispecies. Finally, we utilized this approach to reconstruct an emerging DNA virus and two viroids associated with economically-important red blotch disease of grapevine, and to rapidly generate a biologically-active clone representing the wild type master genome of Oilseed rape mosaic virus. Our findings show that deep siRNA sequencing allows for de novo reconstruction of any DNA or RNA virus genome and its microvariants, making it suitable for universal characterization of evolving viral quasispecies as well as for studying the mechanisms of siRNA biogenesis and RNAi-based antiviral defense.
One Practical Range-Based Numbering Scheme for XML Document December 8 , 2003

It takes constant time to determine the ancestor relation between two nodes in an XML document when the document is indexed with range-based labeling scheme. This constant time procedure makes range-based labeling scheme very attractive. However, relabeling is unavoidable when arbitrary insertions are allowed, and relabeling can be very time-consuming. Relabeling problem limits the use of range-based labeling scheme in naive XML database management system, and document processing systems where insertions and deletions are frequent. In this paper, we present one practical algorithm to extend range labeling scheme (extended preorder) for indexing XML documents. Under this new scheme, arbitrary insertions can be accommodated without relabeling. The new method can be viewed as a combination of rangebased labeling and prefix-based labeling. Range allocation methods to improve the performance of the indexing method are also discussed in this paper.
Adaptive and reliable video transmission over UMTS for enhanced performance

This paper proposes a mechanism for the congestion control for video transmission over universal mobile telecommunications system (UMTS). Our scheme is applied when the mobile user experiences real‐time multimedia content and adopts the theory of a widely accepted rate control method in wired networks, namely equation‐based rate control. In this approach, the transmission rate of the multimedia data is determined as a function of the packet loss rate, the round trip time and the packet size and the server explicitly adjusts its sending rate as a function of these parameters. Furthermore, we examine the performance of the UMTS for real‐time video transmission using real‐time protocols. Through a number of experiments, we measure performance parameters such as end‐to‐end delay, delay in radio access network, delay jitter and throughput in the wireless link. Copyright © 2006 John Wiley & Sons, Ltd.
TREND in energy-aware adaptive routing solutions

Energy saving in telecommunications networks has become a well established topic in the research community. We look at the electrical and optical layers of IP-over-WDM networks, and present a list of evaluation criteria for energy- aware adaptive routing solutions (EA-ARSs) from the perspective of a network operator. Furthermore, we briefly explain the adaptive routing solutions originating from the European Union's TREND and the FP7 Network of Excellence, show saving of energy consumed by line cards in a reference scenario, and use the evaluation criteria to identify the next steps toward introduction of the EA-ARSs into real operation.
An innovative hybrid approach for extracting named entities from unstructured text data

Named entity recognition (NER) is the core part of information extraction that facilitates the automatic detection and classification of entities in natural language text into predefined categories, such as the names of persons, organizations, locations, and so on. The output of the NER task is crucial for many applications, including relation extraction, textual entailment, machine translation, information retrieval, etc. Literature shows that machine learning and deep learning approaches are the most widely used techniques for NER. However, for entity extraction, the abovementioned approaches demand the availability of a domain‐specific annotated data set. Our goal is to develop a hybrid NER system composed of rule‐based deep learning as well as clustering‐based approaches, which facilitates the extraction of generic entities (such as person, location, and organization) out of natural language texts of domains that lack generic named entities labeled domain data sets. The proposed approach takes the advantages of both deep learning and clustering approaches but separately, in combination with a knowledge‐based approach by using a postprocessing module. We evaluated the proposed methodology on court cases (judgments) as a use case since it contains generic named entities of different forms that are poorly or not present in open‐source NER data sets. We also evaluated our hybrid models on two benchmark data sets, namely, Computational Natural Language Learning (CoNLL) 2003 and Open Knowledge Extraction (OKE) 2016. The experimental results obtained from benchmark data sets show that our hybrid models achieved substantially better performance in terms of the F‐score in comparison to other competitive systems.
LEARNING TO COORDINATE IN TOPOLOGICAL NAVIGATION TASKS

Abstract In this paper we address multi-robot coordinated navigation from a topological perspective. The adopted topological representation of the environment leads naturally to a Markov game model to describe the interaction of the multiple robots in the environment. In this setting, we combine the Q-learning algorithm with a powerful coordination mechanism (biased adaptive play). We show that this combined algorithm, coordinated Q-learning, converges to an optimal, coordinated solution for the navigation problem. This implies that the team of robots is able to coordinate without using any communication protocol to enforce the coordination. We illustrate our method in some simple navigation tasks.
An efficient R-Mesh implementation of LDPC codes message-passing decoder

In this paper we propose a constant-time parallel algorithm for implementing the message-passing decoder of LDPC codes on a two dimensional R-Mesh, trying to keep the number of processors small. The R-Mesh provides dynamic reconfiguration, hardware reuse, and flexibility to problem changes. To decode a different code, we may simply set up the required connections between the bit-nodes and check-nodes by modifying the initialization phase of the R-Mesh algorithm. No extra wiring or hardware changes are required, as compared to other existing approaches. Moreover, the same hardware can implement the decoder in both probability and logarithm domains. We illustrate that the R-Mesh is an efficient model for parallel implementation of the decoder in terms of time complexity, flexibility to problem changes and simplicity of routing messages.
Impaired Axonal Regeneration in α7 Integrin-Deficient Mice

The interplay between growing axons and the extracellular substrate is pivotal for directing axonal outgrowth during development and regeneration. Here we show an important role for the neuronal cell adhesion molecule α7β1 integrin during peripheral nerve regeneration. Axotomy led to a strong increase of this integrin on regenerating motor and sensory neurons, but not on the normally nonregenerating CNS neurons. α7 and β1 subunits were present on the axons and their growth cones in the regenerating facial nerve. Transgenic deletion of the α7 subunit caused a significant reduction of axonal elongation. The associated delay in the reinnervation of the whiskerpad, a peripheral target of the facial motor neurons, points to an important role for this integrin in the successful execution of axonal regeneration.
Work in progress Do not site without author ’ s permission ANALYSING THE PROBLEM OF UNSUSTAINABLE HEALTH INFORMATION SYSTEMS IN LESS DEVELOPED ECONOMIES : CASE STUDIES FROM TANZANIA AND MOZAMBIQUE Honest

Most of donor supported information technology (IT) based projects developed or implemented in Less Developed Economies (LDEs) end up as a complete or partial failures or unsustainable. Notably, a number of intraorganizational and external factors are associated with this problem including inadequate infrastructure and human resource capacity, fragmented donor policy and lack of policies to manage the sustainability problem. Accordingly, IT initiatives are often donor driven, top down and hijacked by top managers who (normally) do not have adequate skills but have enormous power to enforce such initiatives across organizational hierarchies. In analysing the concepts from sustainability and institutionalization, the article develops key insights towards a better understanding of the problem of unsustainability. It is argued that Health Information Systems (HIS) become sustainable if they are institutionalized in the sense of being integrated into the everyday routine of the user organization. However, sustainable HIS need not only to be institutionalized, but also be flexible to allow changes as the user needs change. Moreover, introduction of new HIS is not only a technical change, but requires the cultivation and institutionalization of a new kind of culture. Through a comparative case analysis of the HIS development and implementation processes in Tanzania and Mozambique, we have identified two sets of relationships, between the Ministry of Health (MoH) and donor agencies and between the MoH and software development agencies as critical and contributing factors to the unsustainability of HIS. Given this setting, we highlight three key strategies for dealing with the problem of unsustainability in LDEs: (1) Integration of HIS, (2) local shaping of new cultures, and (3) cultivation approach to systems development.
Please Scroll down for Article the Quarterly Journal of Experimental Psychology Improved Intertask Coordination after Extensive Dual-task Practice

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Optimization of computer presented information for left-handed observers

An experiment was conducted to test the hypothesis that left- and right-handed people – due to differences in the cortical processing of the perceived information — will respond differently if a signal is presented in the left or right peripheral visual zone. Experiments showed small differences between left- and right-handed people that could be partially traced back to differences between their motoric skills. Differences could be observed depending on the task (identification of letters, numbers, seeing pictograms). For the lay-out of a display window, however, the differences seem to be too small to justify developing separate screen lay-outs designed for the use of left-handed or right-handed people.
Combinatorial properties of codes with w-identifiable parents property

In this paper, we study the combinatorial properties of wIPP (identifiable parents property) codes and give necessary and sufficient conditions for a code to be a w-IPP code. Furthermore, let R(C) = 1 n logq|C| denote the rate of the q-ary code C of length n, suppose q ≥ 3 is a prime power, we prove that there exists a sequence of linear q-ary 2-IPP codes Cn of length n with R(Cn) = 13 logq q3 4q2−6q+3 . MSC: 94A60, 05C65
Application of Information Technology: Translating Research into Practice: Organizational Issues in Implementing Automated Decision Support for Hypertension in Three Medical Centers

Information technology can support the implementation of clinical research findings in practice settings. Technology can address the quality gap in health care by providing automated decision support to clinicians that integrates guideline knowledge with electronic patient data to present real-time, patient-specific recommendations. However, technical success in implementing decision support systems may not translate directly into system use by clinicians. Successful technology integration into clinical work settings requires explicit attention to the organizational context. We describe the application of a "sociotechnical" approach to integration of ATHENA DSS, a decision support system for the treatment of hypertension, into geographically dispersed primary care clinics. We applied an iterative technical design in response to organizational input and obtained ongoing endorsements of the project by the organization's administrative and clinical leadership. Conscious attention to organizational context at the time of development, deployment, and maintenance of the system was associated with extensive clinician use of the system.
Random forest classification for p300 based brain computer interface applications

One of the most successful types of brain computer interfaces (BCI) is based on the P300 evoked potential (EP) elicited by oddball type of paradigms. Given a particular paradigm the main challenge is to obtain an efficient and robust classification. This paper proposes the use of Random Forest (RF), a tree based ensemble learning method providing state-of-the-art generalization performance, for P300 BCI classification. The performance of the proposed method is compared to both the most commonly used classifiers for this problem: the support vector machine (SVM), and the step-wise linear discriminant analysis (SWLDA); and to two state-of-the-art methods: the multiple convolutional neural networks (MCNN) and the ensemble support vector machine (ESVM). The proposed method has been evaluated on two public available BCI datasets: the BCI competition dataset II for healthy subjects and the image driven paradigm dataset for disabled subjects. The proposed method demonstrated a significant improvement in classification accuracy on both datasets.
Parametric piecewise linear subspace method for processing facial images with 3D pose variations

We propose a framework for learning a general, accurate and compact representation model of 3D objects from 2D images and demonstrate its application for analyzing and synthesizing facial images with head pose variation. The parametric piecewise linear subspace method accurately covers a wide range of pose variation in a continuous manner through a weighted linear combination of local linear models distributed in a 3D pose parameter space. Its parametric nature provides an explicit interface that permits clear interpretation of image variations and the connection to other functional modules. The linear design helps to avoid typical non-linear pitfalls such as over tting and time-consuming learning. When learned and tested for a speci c person, experimental results show sub-degree and sub-pixel accuracy within 55 degree full 3D rotations and good generalization capability over unknown head poses.
Comparison of passive radar detectors with noisy reference signal

Traditional passive radar systems with a noisy reference signal use the cross-correlation statistic for detection. However, owing to the composite nature of this hypothesis testing problem, no claims can be made about the optimality of this detector. Therefore, exploiting the low-rank structure of most passive radar illuminators, we recently proposed singular value decomposition based detectors that outperform the CC detector. In this paper, we derive the generalized likelihood ratio tests for this signal model and compare with our proposed SVD based detectors. We demonstrate the near CFAR behavior (highly desirable) of our SVD detectors. We show that on the other hand, the GLRT detectors have a varying probability of false alarm with changing reference channel characteristics making it impractical to use them in a passive radar system.
Stresses in Ytterbium Silicate Multilayer Environmental Barrier Coatings

The internal stresses of plasma-sprayed multilayer ytterbium disilicate environmental barrier coatings were measured using microfocused high-energy X-rays in a transmission geometry. Stresses were measured for as-sprayed and ex-situ heat-treated ytterbium disilicate topcoats at room temperature and during in-situ heating and cooling experiments. In-situ loading experiments were also performed on the topcoat in order to establish its elastic constants. The ytterbium disilicate was found to have a relatively low coefficient of thermal expansion resulting in compressive stresses of approximately 100 MPa throughout the topcoat. In-situ heating experiments revealed a statistically significant stress relaxation in the ytterbium disilicate topcoat upon thermal cycling to temperatures above 1300°C, indicating the onset of stress relaxation but no cracks were observed in SEM micrographs. The stress states were also modeled using a numerical solution; measured stresses were found to be very close to the predicted stresses in ytterbium dilisicate topcoats, while the experimentally determined stresses in the intermediate layers were of much smaller magnitude than the calculated stresses.
Low Latency Routing Algorithm for Unmanned Aerial Vehicles Ad-Hoc Networks

In this paper, we proposed a new routing protocol for Unmanned Aerial Vehicles (UAVs) that equipped with directional antenna. We named this protocol Directional Optimized Link State Routing Protocol (DOLSR). This protocol is based on the well known protocol that is called Optimized Link State Routing Protocol (OLSR). We focused in our protocol on the multipoint relay (MPR) concept which is the most important feature of this protocol. We developed a heuristic that allows DOLSR protocol to minimize the number of the multipoint relays. With this new protocol the number of overhead packets will be reduced and the End-to-End delay of the network will also be minimized. We showed through simulation that our protocol outperformed Optimized Link State Routing Protocol, Dynamic Source Routing (DSR) protocol and Ad- Hoc On demand Distance Vector (AODV) routing protocol in reducing the End-to-End delay and enhancing the overall throughput. Our evaluation of the previous protocols was based on the OPNET network simulation tool.