Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimizing outpatient phlebotomy staffing: tools to assess staffing needs and monitor effectiveness.

CONTEXT Short patient wait times are critical for patient satisfaction with outpatient phlebotomy services. Although increasing phlebotomy staffing is a direct way to improve wait times, it may not be feasible or appropriate in many settings, particularly in the context of current economic pressures in health care. OBJECTIVE To effect sustainable reductions in patient wait times, we created a simple, data-driven tool to systematically optimize staffing across our 14 phlebotomy sites with varying patient populations, scope of service, capacity, and process workflows. DESIGN We used staffing levels and patient venipuncture volumes to derive the estimated capacity, a parameter that helps predict the number of patients a location can accommodate per unit of time. We then used this parameter to determine whether a particular phlebotomy site was overstaffed, adequately staffed, or understaffed. Patient wait-time and satisfaction data were collected to assess the efficacy and accuracy of the staffing tool after implementing the staffing changes. RESULTS In this article, we present the applications of our approach in 1 overstaffed and 2 understaffed phlebotomy sites. After staffing changes at previously understaffed sites, the percentage of patients waiting less than 10 minutes ranged from 88% to 100%. At our previously overstaffed site, we maintained our goal of 90% of patients waiting less than 10 minutes despite staffing reductions. All staffing changes were made using existing resources. CONCLUSIONS Used in conjunction with patient wait-time and satisfaction data, our outpatient phlebotomy staffing tool is an accurate and flexible way to assess capacity and to improve patient wait times.
An Integrating Text Retrieval Framework for Digital Ecosystems Paradigm

The purpose of the research is to provide effective information retrieval services for digital 'organisms' in a digital ecosystem by leveraging the power of Web searching technology. A novel integrating digital ecosystem search framework (a new digital organism) is proposed which employs the Web search technology and traditional database searching techniques to provide economic organisms with comprehensive, dynamic, and organization-oriented information retrieval ranging from the Internet to personal (semantic) desktop.
Blurred Palmprint Recognition Based on Stable-Feature Extraction Using a Vese–Osher Decomposition Model

As palmprints are captured using non-contact devices, image blur is inevitably generated because of the defocused status. This degrades the recognition performance of the system. To solve this problem, we propose a stable-feature extraction method based on a Vese–Osher (VO) decomposition model to recognize blurred palmprints effectively. A Gaussian defocus degradation model is first established to simulate image blur. With different degrees of blurring, stable features are found to exist in the image which can be investigated by analyzing the blur theoretically. Then, a VO decomposition model is used to obtain structure and texture layers of the blurred palmprint images. The structure layer is stable for different degrees of blurring (this is a theoretical conclusion that needs to be further proved via experiment). Next, an algorithm based on weighted robustness histogram of oriented gradients (WRHOG) is designed to extract the stable features from the structure layer of the blurred palmprint image. Finally, a normalized correlation coefficient is introduced to measure the similarity in the palmprint features. We also designed and performed a series of experiments to show the benefits of the proposed method. The experimental results are used to demonstrate the theoretical conclusion that the structure layer is stable for different blurring scales. The WRHOG method also proves to be an advanced and robust method of distinguishing blurred palmprints. The recognition results obtained using the proposed method and data from two palmprint databases (PolyU and Blurred–PolyU) are stable and superior in comparison to previous high-performance methods (the equal error rate is only 0.132%). In addition, the authentication time is less than 1.3 s, which is fast enough to meet real-time demands. Therefore, the proposed method is a feasible way of implementing blurred palmprint recognition.
Applying TOGAF to Define and Govern a Service-oriented Architecture in a Large-scale Research Project

ABSTRACT The Service-oriented Architecture paradigm has become a widely adopted solution for enterprise application landscapes. SOA promises system integration improvement, business and IT alignment, applications reusability, and fast adaptability to changing requirements. Yet, the advantages that SOA offers lead to its main management challenges. An SOA consists not only of services. Business requirements, processes, models, rules, policies, and different stakeholders play also an important role. To manage this increased complexity and heterogeneity in SOA landscapes enterprises apply architecture frameworks and governance approaches. An essential enabler for SOA Governance is the traceable documentation of the service-oriented application landscape. This paper shows how the TOGAF Architecture Development Method was applied in a large-scale SOA-based research project to support the governance proposes in the context of a service marketplace. Supplementary templates were defined to guide the description of services, data models, and architectural components. Some of the models and decisions proposed by TOGAF were shifted to other phases to fit the innovative nature of research projects.
Leucine‐rich repeat kinase 2 and alternative splicing in Parkinson's disease

Mutations of the leucine‐rich repeat kinase 2 (LRRK2) gene are the most common genetic cause of Parkinson's disease (PD) and are associated with pleiomorphic neuropathology. We hypothesize that LRRK2 mediates its pathogenic effect through alternative splicing of neurodegeneration genes. Methods used in this study included western blotting analysis of subcellular protein fractions, exon‐array analysis of RNA from cultured neuroblastoma cells transfected with LRRK2 expression vectors, and reverse‐transcription polymerase chain reaction (RT‐PCR) of RNA from cultured cells and postmortem tissue. Overexpression of the LRRK2 G2019S mutant resulted in a significant (2.6‐fold; P = 0.020) decrease in nuclear transactive response DNA‐binding protein 43 levels. Exon‐array analyses revealed that wild‐type LRRK2 had a significant effect on the expression of genes with nuclear (P < 10−22) and cell‐cycle functions (P < 10−15). We replicated changes in gene expression in 30% of selected genes by quantitative RT‐PCR. Overexpression of LRRK2 resulted in the altered splicing of two genes associated with PD, with an increased inclusion of exon 10 of microtubule‐associated protein tau (1.7‐fold; P = 0.001) and exon 5 of the alpha‐synuclein (SNCA) gene (1.6‐fold; P =0.005). Moreover, overexpression of LRRK2 (G2019S) and two mutant genes associated with neurodegeneration, TARDBP (M337V) and FUS (R521H), were associated with decreased inclusion out of the dystonin (DST) 1e precursor exons in SK‐N‐MC cells. Altered splicing of SNCA (1.9‐fold; P < 0.001) and DST genes (log2 2.3‐fold; P = 0.005) was observed in a cohort of PD, compared with neurologically healthy, brains. This suggests that aberrant RNA metabolism is an important contributor to idiopathic PD. © 2012 Movement Disorder Society
Who Leaves Science? The First Year Experience at York University.

This study examined student departure rates from the Faculty of Pure and Applied Science at York University in Ontario (Canada) using Tinto's (1987) model of student departure. Student records from 1992-93 were used to obtain data on grades in the final year of high school, sex, language status, and amount of student financial awards received; first-year grade point average and enrollment status after the first year were obtained from 1993-94 records. A total of 141 students also completed surveys regarding academic goals and attitudes. It was found that 78 percent of the students re-enrolled in the sciences for their second year, 5 percent enrolled in other faculties at the university, and 17 percent left the university for destinations unknown. In general, those who remained in the sciences had higher grade 13 and first year marks than those leaving the university; however, students leaving the sciences for other university faculties had higher grade 13 and first-year marks than those remaining in the sciences. Enrollment status in the second year could not be related to pre-entry characteristics or initial goals and commitments of students. An appendix explains the model of student departure. (Contains 28 references.) (MDM) *********************************************************************** Reproductions supplied by EDRS are the best that can be made from the original document. *********************************************************************** Who Leaves Science? The First Year Experience at York University
An Overview of Cuckoo Hashing

Cuckoo Hashing is a technique for resolving collisions in hash tables that produces a dictionary with constant-time worst-case lookup and deletion operations as well as amortized constant-time insertion operations. First introduced by Pagh in 2001 [3] as an extension of a previous static dictionary data structure, Cuckoo Hashing was the first such hash table with practically small constant factors [4]. Here, we first outline existing hash table collision policies and go on to analyze the Cuckoo Hashing scheme in detail. Next, we give an overview of (c, k)-universal hash families, and finally, we summarize some selected experimental results comparing the varied collision policies.
Title a Probabilistic Memetic Framework Promotional Purposes or for Creating New Collective Works for Resale or a Probabilistic Memetic Framework

component of this work in other works must be obtained from the IEEE. reposted without the explicit permission of the copyright holder. timely dissemination of scholarly and technical work. Abstract— Memetic algorithms (MAs) represent one of the recent growing areas in evolutionary algorithm (EA) research. The term MAs is now widely used as a synergy of evolutionary or any population-based approach with separate individual learning or local improvement procedures for problem search. Quite often, MAs are also referred to in the literature as Baldwinian EAs, Lamarckian EAs, cultural algorithms, or genetic local searches. In the last decade, MAs have been demonstrated to converge to high-quality solutions more efficiently than their conventional counterparts on a wide range of real-world problems. Despite the success and surge in interests on MAs, many of the successful MAs reported have been crafted to suit problems in very specific domains. Given the restricted theoretical knowledge available in the field of MAs and the limited progress made on formal MA frameworks, we present a novel probabilistic memetic framework that models MAs as a process involving the decision of embracing the separate actions of evolution or individual learning and analyzing the probability of each process in locating the global optimum. Further, the framework balances evolution and individual learning by governing the learning intensity of each individual according to the theoretical upper bound derived while the search progresses. Theoretical and empirical studies on representative benchmark problems commonly used in the literature are presented to demonstrate the characteristics and efficacies of the probabilistic memetic framework. Further, comparisons to recent state-of-the-art evolutionary algorithms, memetic algorithms, and hybrid evolutionary-local search demonstrate that the proposed framework yields robust and improved search performance.
Self-Dual Stochastic Production Frontiers and Decomposition of Output Growth: The Case of Olive-Growing Farms in Greece

This paper provides a decomposition of output growth among olive-growing farms in Greece during the period 1987–1993 by integrating Bauer's (1990) and Bravo-Ureta and Rieger's (1991) approaches. The proposed methodology is based on the use of self-dual production frontier functions. Output growth is attributed to the size effect, technical change, changes in technical and input allocative inefficiency, and the scale effect. Empirical results indicate that the scale and the input allocative inefficiency effects, which were not taken into account in previous studies on output growth decomposition analysis, have caused a 7.3% slowdown and a 11.0% increase in output growth, respectively. Technical change was found to be the main source of TFP growth while both technical and input allocative inefficiency decreased over time. Still though, a 56.5% of output growth is attributed to input growth.
Interoperable subject retrieval in a distributed multi-scheme environment: new developments in the HILT project

The HILT (HIgh-Level Thesaurus) project (http://hilt.cdlr.strath.ac.uk/), based primarily at the Centre for Digital Library Research (CDLR) (http://cdlr.strath.ac.uk/) at Strathclyde University in Glasgow is entering its fourth stage following the completion of Phases I (http://hilt.cdlr.strath.ac.uk/index1.html) and II (http://hilt.cdlr.strath.ac.uk/index2.html) and the Machine to Machine (M2M) Feasibility Study (http://hilt.cdlr.strath.ac.uk/hiltm2mfs/). HILT is funded by the Joint Information Systems Committee (JISC) in the United Kingdom (UK) to examine an issue of global significance - facilitating interoperability of subject descriptions in a distributed, cross-service retrieval environment where different services use different subject and classification schemes to describe content, making cross-searching by subject difficult. HILT Phase I determined that there was a community consensus in the UK in favour of using inter-scheme mapping to achieve interoperability between services using different schemes, an approach followed by several recent projects (Heery et al, 2001; Koch et al, 2001; MACS, 2005; Saeed and Chaudhury 2002). HILT Phase II chose a spine-based approach to mapping and chose the Dewey Decimal Classification (DDC) as the central scheme to which all other schemes would be mapped. It also built an illustrative pilot mapping service, based on an adaptation of the Wordmap (http://www.wordmap.com/) terminology-handling software and made a range of recommendations on issues requiring further research and ongoing development requirements.
Principles of QTL Mapping

To date, most genetic progress for quantitative traits in livestock has been made by selection on phenotype or on estimates of breeding values (EBV) derived from phenotype, without knowledge of the number of genes that affect the trait or the effects of each gene. In this quantitative genetic approach to genetic improvement, the genetic architecture of traits of interest has essentially been treated as a ‘black box’ (Figure 1). Despite this, the substantial rates of genetic improvement that have been and continue to be achieved in the main livestock species is clear evidence of the power of quantitative genetic approaches to selection.
Use of Weather Radar Data for Site Diversity Predictions and Impact of Rain Field Advection

This paper presents the analysis on two weather radar datasets, collected at Spino d'Adda (Italy) and Bordeaux (France), for the simulation and the performance evaluation of a site diversity system. Results from the two locations are compared and the impact of different factors such as baseline and link orientation is assessed and related to the local climatologic and topographic characteristics. A link is then established between the preferable baseline orientation and the predominant direction of the rain field advection. The rain field displacement is finally shown to be well approximated by the wind speed and direction at the 700 hPa pressure level extracted from the ECMWF ERA-40 meteorological database.
Learning distance metric for regression by semidefinite programming with application to human age estimation

A good distance metric for the input data is crucial in many pattern recognition and machine learning applications. Past studies have demonstrated that learning a metric from labeled samples can significantly improve the performance of classification and clustering algorithms. In this paper, we investigate the problem of learning a distance metric that measures the semantic similarity of input data for regression problems. The particular application we consider is human age estimation. Our guiding principle for learning the distance metric is to preserve the local neighborhoods based on a specially designed distance as well as to maximize the distances between data that are not in the same neighborhood in the semantic space.Without any assumption about the structure and the distribution of the input data, we show that this can be done by using semidefinite programming. Furthermore, the low-level feature space can be mapped to the high-level semantic space by a linear transformation with very low computational cost. Experimental results on the publicly available FG-NET database show that 1) the learned metric correctly discovers the semantic structure of the data even when the amount of training data is small and 2) significant improvement over the traditional Euclidean metric for regression can be obtained using the learned metric. Most importantly, simple regression methods such as k nearest neighbors (kNN), combined with our learned metric, become quite competitive (and sometimes even superior) in terms of accuracy when compared with the state-of-the-art human age estimation approaches.
Fair Pricing of Weather Derivatives

This paper proposes a consistent approach to the pricing of weather derivatives. Since weather derivatives are traded in an incomplete market setting, standard hedging based pricing methods cannot be applied. The growth optimal portfolio, which is interpreted as a world stock index, is used as a benchmark or numeraire such that all benchmarked derivative price processes are martingales. No measure transformation is needed for the proposed fair pricing. For weather derivative payofis that are independent of the value of the growth optimal portfolio, it is shown that the classical actuarial pricing methodology is a particular case of the fair pricing concept. A discrete time model is constructed to approximate historical weather characteristics. The fair prices of some particular weather derivatives are derived using historical and Gaussian residuals. The question of weather risk as diversiflable risk is also discussed.
Full-range affinities for graph-based segmentation

Graph-based segmentation has become a major trend in image segmentation. A key issue in graph-based segmentation is how to build the affinity matrix. Among the previous methods, many successful ones only compute the pairwise affinities between adjacent pixels and superpixels without considering the nonadjacent ones. Thus, they often obtain unsatisfactory results when foreground is cut into several nonadjacent parts by background or shadows. In this paper, we propose a full-range affinities learning method for graph-based segmentation. Our method computes the affinities both between adjacent pixels and nonadjacent pixels, which are inversely proportional to the shortest connectivity paths. The experimental results demonstrate the superiority of the proposed approach comparing with existing popular methods.
Synergic prodegradative activity of Bicalutamide and trehalose on the mutant androgen receptor responsible for spinal and bulbar muscular atrophy

Spinal and bulbar muscular atrophy (SBMA) is an X-linked motoneuron disease due to a CAG triplet-repeat expansion in the androgen receptor (AR) gene, which is translated into an elongated polyglutamine (polyQ) tract in AR protein (ARpolyQ). ARpolyQ toxicity is activated by the AR ligand testosterone (or dihydrotestosterone), and the polyQ triggers ARpolyQ misfolding and aggregation in spinal cord motoneurons and muscle cells. In motoneurons, testosterone triggers nuclear toxicity by inducing AR nuclear translocation. Thus, (i) prevention of ARpolyQ nuclear localization, combined with (ii) an increased ARpolyQ cytoplasmic clearance, should reduce its detrimental activity. Using the antiandrogen Bicalutamide (Casodex®), which slows down AR activation and nuclear translocation, and the disaccharide trehalose, an autophagy activator, we found that, in motoneurons, the two compounds together reduced ARpolyQ insoluble forms with higher efficiency than that obtained with single treatments. The ARpolyQ clearance was mediated by trehalose-induced autophagy combined with the longer cytoplasmic retention of ARpolyQ bound to Bicalutamide. This allows an increased recognition of misfolded species by the autophagic system prior to their migration into the nucleus. Interestingly, the combinatory use of trehalose and Bicalutamide was also efficient in the removal of insoluble species of AR with a very long polyQ (Q112) tract, which typically aggregates into the cell nuclei. Collectively, these data suggest that the combinatory use of Bicalutamide and trehalose is a novel approach to facilitate ARpolyQ clearance that has to be tested in other cell types target of SBMA (i.e. muscle cells) and in vivo in animal models of SBMA.
ASEAN economic cooperation and integration : progress, challenges and future directions

General editors' preface 1. Introduction 2. ASEAN diversity, economic growth and internationalisation 3. ASEAN's international trade and foreign direct investment, commercial policy reforms and production networks 4. ASEAN's FTA-led economic integration 5. The AEC and its economic effects 6. Future directions: moving beyond AEC 2015 Executive summary Bibliography Index.
ARCHITECTURE DEGREE PROJECT: USE OF 3D TECHNOLOGY, MODELS AND AUGMENTED REALITY EXPERIENCE WITH VISUALLY IMPAIRED USERS

Web 3.0 technologies provide effective tools for interpreting architecture and culture in general. Thus, a project may have an emotional impact on people while also having a more widespread effect in society as a whole. This project defines a methodology for evaluating accessibility of architecture for people with visual disabilities and the application of this to visiting emblematic buildings such as the Basilica of the Holly Family in Barcelona, designed by the architect, Antoni Gaudi.
Mothers and Daughters

The interpretive study reported in this article focused on the process by which mothers and daughters interact about body and dieting. In-depth interviews were conducted with 20 mothers and their adolescent daughters. Constant comparison analysis of data revealed four patterns of mother-daughter interaction about body and dieting: (a) the direct verbal approach, including encouragement/facilitation, dissuasion, and fault-finding messages; (b) the avoidance/guardedness approach; (c) the modeling approach; and (d) the laissez-faire approach. These four patterns of communication varied in terms of content and were used in different contexts and combinations. These mother-daughter interactions (a) were shaped by mothers’ and daughters’ thoughts about the self, the other, and the mother-daughter relationship; (b) were used by mothers and daughters to plan future interactions with one another; and (c) served to guide lines of personal action with respect to dieting, especially in the case of daughters.