Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparison of 24-h Urinary Aldosterone Level and Random Urinary Aldosterone-to-Creatinine Ratio in the Diagnosis of Primary Aldosteronism

Background Historically, urinary aldosterone level measurement was a commonly employed confirmatory test to detect primary aldosteronism (PA). However, 24-h urine collection is inconvenient and cumbersome. We hypothesized that random urinary aldosterone measurements with correction for creatinine concentration might be comparable to 24-h urinary aldosterone levels (Uald-24 h) in the diagnosis of PA. Methods The non-concurrent prospective study was conducted between June 2006 and March 2008 in patients admitted for confirmation of aldosteronism by salt loading test. A 24-h urine sample, which was collected during hospitalization on the day before saline infusion testing after restoration of serum hypokalemia, was collected from all subjects. Moreover, participants were asked to collect a first bladder voiding random urine sample during clinic visits. Uald-24 h and the random urinary aldosterone-to-creatinine ratio (UACR) were calculated accordingly. Results A total of 102 PA patients (71 patients diagnosed of aldosterone-producing adenoma, 31 with idiopathic hyperaldosteronism) and 65 patients with EH were enrolled. The receiver operating characteristic curve showed comparable areas under the curves of UACR and Uald-24 h. The Bland-Altman plot showed mean bias but no obvious heteroscedasticity between the two tests. When using random UACR >3.0 ng/mg creatinine as the cutoff value, we obtained a specificity of 90.6% to confirm PA from essential hypertension. Conclusions Our study reinforce that the diagnostic accuracy of random UACR was comparable to that of Uald-24 h in PA patients. With the quickness and simplicity of the UACR method and its equivalence to Uald-24 h, this assay could be a good alternative diagnostic tool for PA confirmation.
GRADE PERFORMANCE IN STATISTICS : A BAYESIAN FRAMEWORK

In this paper, we investigate questions involving the impact of a multitude of covariates and their interactions on the scores of a comprehensive exit exam from 121 undergraduate students in Texas State University via a hierarchical Bayesian mixture model. The model uses a mixture of Beta distributions, inflated for the purposes of modeling the behavior of students who are no-shows for the exam. We formulate the predictive probability distribution of letter grade test scores as well as the probability that a student will belong to a particular grade cluster given a set of covariate values.
Measuring the Impact of a Moving Target: Towards a Dynamic Framework for Evaluating Collaborative Adaptive Interactive Technologies

Background Website evaluation is a key issue for researchers, organizations, and others responsible for designing, maintaining, endorsing, approving, and/or assessing the use and impact of interventions designed to influence health and health services. Traditionally, these evaluations have included elements such as content credibility, interface usability, and overall design aesthetics. With the emergence of collaborative, adaptive, and interactive ("Web 2.0") technologies such as wikis and other forms of social networking applications, these metrics may no longer be sufficient to adequately assess the quality, use or impact of a health website. Collaborative, adaptive, interactive applications support different ways for people to interact with health information on the Web, including the potential for increased user participation in the design, creation, and maintenance of such sites. Objective We propose a framework that addresses how to evaluate collaborative, adaptive, and interactive applications. Methods In this paper, we conducted a comprehensive review of a variety of databases using terminology related to this area. Results We present a review of evaluation frameworks and also propose a framework that incorporates collaborative, adaptive, and interactive technologies, grounded in evaluation theory. Conclusion This framework can be applied by researchers who wish to compare Web-based interventions, non-profit organizations, and clinical groups who aim to provide health information and support about a particular health concern via the Web, and decisions about funding grants by agencies interested in the role of social networks and collaborative, adaptive, and interactive technologies technologies to improve health and the health system.
Efficient Adaptations of the Non-Blocking Buffer for Event Message Communication between Real-Time Threads

Enabling message communication among concurrent computing threads without relying on mutual exclusion (i.e., locking) is highly desirable in real-time computing systems. This paper presents a refined version of the Non-Blocking Buffer (NBB), which is a lock-free interaction mechanism that enables efficient event-message communication between a single producer thread and a single consumer thread. The NBB scheme presented here contains improvements over the previous version in two aspects. First, application designers now have the flexibility of choosing the consumer's retry strategy for the case when the buffer is empty but the producer is in the middle of inserting an item. Second, in the refined version the producer inserts pointers to data items into the buffer whereas the consumer obtains copies of the items. This design is consistent with the fact that shared heap management must be avoided to enable fully lock-free interaction between the producer and the consumer. This paper also discusses the approaches based on the NBB mechanism for supporting all conceivable producer-consumer scenarios.
XtremWeb & Condor : sharing resources between Internet connected Condor pool

Grid computing presents two major challenges for deploying large scale applications across wide area networks gathering volunteers PC and clusters/parallel computers as computational resources: security and fault tolerance. This paper presents a lightweight Grid solution for the deployment of multi-parameters applications on a set of clusters protected by firewalls. The system uses a hierarchical design based on Condor for managing each cluster locally and XtremWeb for enabling resource sharing among the clusters. We discuss the security and fault tolerance mechanisms used for this design and demonstrate the usefulness of the approach measuring the performances of a multi-parameters bio-chemistry application deployed on two sites: University of Wisconsin/Madison and Paris South University. This experiment shows that we can efficiently and safely harness the computational power of about 200 PC distributed on two geographic sites.
A simple noninvasive index can predict both significant fibrosis and cirrhosis in patients with chronic hepatitis C

Information on the stage of liver fibrosis is essential in managing chronic hepatitis C (CHC) patients. However, most models for predicting liver fibrosis are complicated and separate formulas are needed to predict significant fibrosis and cirrhosis. The aim of our study was to construct one simple model consisting of routine laboratory data to predict both significant fibrosis and cirrhosis among patients with CHC. Consecutive treatment‐naive CHC patients who underwent liver biopsy over a 25‐month period were divided into 2 sequential cohorts: training set (n = 192) and validation set (n = 78). The best model for predicting both significant fibrosis (Ishak score ≥ 3) and cirrhosis in the training set included platelets, aspartate aminotransferase (AST), and alkaline phosphatase with an area under ROC curves (AUC) of 0.82 and 0.92, respectively. A novel index, AST to platelet ratio index (APRI), was developed to amplify the opposing effects of liver fibrosis on AST and platelet count. The AUC of APRI for predicting significant fibrosis and cirrhosis were 0.80 and 0.89, respectively, in the training set. Using optimized cut‐off values, significant fibrosis could be predicted accurately in 51% and cirrhosis in 81% of patients. The AUC of APRI for predicting significant fibrosis and cirrhosis in the validation set were 0.88 and 0.94, respectively. In conclusion, our study showed that a simple index using readily available laboratory results can identify CHC patients with significant fibrosis and cirrhosis with a high degree of accuracy. Application of this index may decrease the need for staging liver biopsy specimens among CHC patients.
Modelling Relational Statistics With Bayes Nets ( Poster Presentation SRL Workshop )

Class-level dependencies model general relational statistics over attributes of linked objects and links. Class-level relationships are important in themselves, and they support applications like policy making, strategic planning, and query optimization. An example of a class-level query is “what is the percentage of friendship pairs where both friends are women? ”. To represent class-level statistics, we utilize Parametrized Bayes nets (PBNs), a 1st-order logic extension of Bayes nets. The standard grounding semantics for PBNs is appropriate for answering queries about specific ground facts but not appropriate for answering queries about classes of individuals. We propose a novel random selection semantics for PBNs, based on Halpern’s classic semantics for probabilistic 1st-order logic (Halpern, 1990), that supports classlevel queries. For parameter learning we use the empirical frequencies in the relational data. A naive computation of the empirical frequencies of the relations is intractable due to the complexity imposed by negated relations. We render the computation tractable by using the Möbius transform. Evaluation on four benchmark datasets indicates that maximum pseudo-likelihood provides accurate estimates at different sample sizes.
Lessons from an evaluation of a domestic well-being indicator system

The objective of this study was to find out whether a domestic well-being indicator system might support the dialogue of care between the older person and his or her carer. Ten evaluation sessions, each one with three parts, were run with ten older people and ten carers. Peoples' attitudes and feelings, perceptions, and preferences were compared. Both qualitative and quantitative data were collected. In conclusion the prototype could be used as a tool to improve the dialogue of care between the older person and the carer.
An algorithm for computing the shortest path of three spheres

Computing the Euclidean shortest path among a plural number of spherical balls is an interesting problem in 3D computer graphics. Finding the Euclidean shortest path of three spheres is fundamental to the more general n-sphere problem. In this paper, we develop an exact algorithm for computing the shortest path of three spheres in 3D space. The problem is firstly reduced to a corresponding problem of computing the shortest path of three coplanar circles, and turns out to a two points and one circle path planning problem. After applying the general root formula of the shortest path of two points and one circle together with the method of axis rotation, the algorithm is build. Empirical results accompany a brute force method for comparison have shown the correctness and effectiveness of the proposed algorithm. This result can be applied in 3D computer graphics, computer-aided design and the molecular geometry.
Data Warehouse and Master Data Management Evolution – A Meta-Data-Vault Approach

The paper presents a: a) brief overview and analysis of existing approaches to the data warehouse (DW) evolution problem, and b) detailed description of the research idea for the DW evolution problem (primarily intended for structured data sources and realizations with relational database engines). We observe the DW evolution problem as a double issue - from the DW perspective, and from the master data management (MDM) perspective. The proposed general solution will include a Data Vault (DV) model based metadata repository that will integrate the DW data and metadata with the MDM data and metadata. This historicized metadata repository will manage schema versions and support schema changes. We believe this integration will: a) increase the quality of data in the Enterprise Data Warehouse (EDW), b) increase the quality of the metadata in the EDW, and c) increase the simplicity and efficiency of the DW and the MDM schema evolution.
Design methodologies for 3D mixed signal integrated circuits: A practical 12-bit SAR ADC design case

Three-dimensional (3D) integration technology has been proposed as a promising technology to provide small footprint, reduced wire-length, and the capability of heterogeneous integration. In particular, 3D IC is a good candidate to address the design issues in conventional analog/digital mixed-signal IC designs. In this work, we focus on modeling and analyzing the impacts of through silicon vias (TSVs) on mixed-signal ICs. Based on the analysis, a set of design methodologies for 3D mixed-signal ICs are proposed. The design methodologies are verified with a case study, in which a 12-bit successive approximation register analog-to-digital converter (SAR ADC) is re-designed by partitioning it into three stacked layers for 3D integration. The experimental results show that, compared to the traditional 2D counterpart, our 3D SAR ADC with optimized TSV placement can achieve significant area and power reduction, and performance improvement. Specifically, due to the isolation of substrate noise disturbance in our 3D design, the signal-to-noise-plus-distortion ratio (SNDR) is improved from 68.74 dB to 74.12 dB.
Actions of Agonists and Antagonists of the ghrelin/GHS-R Pathway on GH Secretion, Appetite, and cFos Activity

The stimulatory effects of ghrelin, a 28-AA acylated peptide originally isolated from stomach, on growth hormone (GH) secretion and feeding are exclusively mediated through the growth hormone secretagogue 1a receptor (GHS-R1a), the only ghrelin receptor described so far. Several GHS-R1a agonists and antagonists have been developed to treat metabolic or nutritional disorders but their mechanisms of action in the central nervous system remain poorly understood. In the present study, we compared the activity of BIM-28163, a GHS-R1a antagonist, and of several agonists, including native ghrelin and the potent synthetic agonist, BIM-28131, to modulate food intake, GH secretion, and cFos activity in arcuate nucleus (ArcN), nucleus tractus solitarius (NTS), and area postrema (AP) in wild-type and NPY-GFP mice. BIM-28131 was as effective as ghrelin in stimulating GH secretion, but more active than ghrelin in inducing feeding. It stimulated cFos activity similarly to ghrelin in the NTS and AP but was more powerful in the ArcN, suggesting that the super-agonist activity of BIM-28131 is mostly mediated in the ArcN. BIM-28163 antagonized ghrelin-induced GH secretion but not ghrelin-induced food consumption and cFos activation, rather it stimulated food intake and cFos activity without affecting GH secretion. The level of cFos activation was dependent on the region considered: BIM-28163 was as active as ghrelin in the NTS, but less active in the ArcN and AP. All compounds also induced cFos immunoreactivity in ArcN NPY neurons but BIM-28131 was the most active. In conclusion, these data demonstrate that two peptide analogs of ghrelin, BIM-28163, and BIM-28131, are powerful stimulators of appetite in mice, acting through pathways and key brain regions involved in the control of appetite that are only partially superimposable from those activated by ghrelin. A better understanding of the molecular pathways activated by these compounds could be useful in devising future therapeutic applications, such as for cachexia and anorexia.
From PropBank to EngValLex: Adapting the PropBank-Lexicon to the Valency Theory of the Functional Generative Description

EngValLex is the name of an FGD-compliant valency lexicon of English verbs, built from the PropBank-Lexicon and following the structure of Vallex, the FGD-based lexicon of Czech verbs. EngValLex is interlinked with the PropBank-Lexicon, thus preserving the original links between the PropBank-Lexicon and the PropBank-Corpus. Therefore it is also supposed to be part of corpus annotation. This paper describes the automatic conversion of the PropBank-Lexicon into Pre-EngValLex, as well as the progress of its subsequent manual refinement (EngValLex). At the start, the Propbank-arguments were automatically re-labeled with functors (semantic labels of FGD) and the PropBank-rolesets were split into the respective example sentences, which became FGD-valency frames of Pre-EngValLex. Human annotators check and correct the labels and make the preliminary valency frames FGD-compliant. The most essential theoretical difference between the original and EngValLex is the syntactic alternations used by the PropBank-Lexicon, not yet employed within the Czech framework. The alternation-based approach substantially affects the conception of the frame, making in very different from the one applied within the FGD-framework. Preserving the valuable alternation information required special linguistic rules for keeping, altering and re-merging the automatically generated preliminary valency frames.
An Approach to Improve Accuracy in Probabilistic Models using State Refinement

Probabilistic models are useful in the analysis of system behaviour and non-functional properties. Reliable estimates and measurements of probabilities are needed to annotate behaviour models in order to generate accurate predictions. However, this may not be sufficient, and may still lead to inaccurate results when the system model does not properly reflect the probabilistic choices made by the environment. Thus, not only should the probabilities be accurate in properly reflecting reality, but also the model that is being used. In this paper we propose state refinement as a technique to mitigate this problem, showing that it is guaranteed to preserve or increase the accuracy of the initial model. We present a framework for iteratively improving the accuracy of a probabilistically annotated behaviour model with respect to a set of benchmark properties through iterative state refinements.
CORL: A Continuous-state Offset-dynamics Reinforcement Learner

Continuous state spaces and stochastic, switching dynamics characterize a number of rich, real-world domains, such as robot navigation across varying terrain. We describe a reinforcement-learning algorithm for learning in these domains and prove for certain environments the algorithm is probably approximately correct with a sample complexity that scales polynomially with the state-space dimension. Unfortunately, no optimal planning techniques exist in general for such problems; instead we use fitted value iteration to solve the learned MDP, and include the error due to approximate planning in our bounds. Finally, we report an experiment using a robotic car driving over varying terrain to demonstrate that these dynamics representations adequately capture real-world dynamics and that our algorithm can be used to efficiently solve such problems.
Manna from Heaven or Forbidden Fruit? the (Ab) Use of Control Variables in Research on International Conflict

Model specification is a ubiquitous challenge in the social sciences. While this issue of Conflict Management and Peace Science is dedicated to addressing this topic in the context of research on international conflict, the discussion among the contributors also contains general lessons and debates relevant to statistical analyses of political, economic, and social phenomena. The reader might suspect that when Glenn Palmer first approached us with the idea of putting together a roundtable and special issue on using control variables, we yawned. Nothing could be further from the truth. Not only did we think the topic warranted some good debate and dialogue, but we already had in mind some lively, articulate, and bright scholars who would offer clever insight.1 We apparently were not alone in our estimation: a record-breaking, spirited audience attended a roundtable featuring these individuals at the 2004 Peace Science Meeting in Houston, Texas. We are confident that the readers of this volume will similarly be engaged and will find the dialogue on the contributions and weakness of control variables useful for their own research. The origins of this special issue can be traced to James Lee Ray’s 2002 Presidential Address to the Peace Science Society (published in 2003). In that address, Ray argued that international conflict scholars had become obsessed with control variables. He warned us of the perils of interpreting results from models with too many independent variables and set down five guidelines for assessing whether to use controls and how to do so if one must. Returning to that theme, Ray leads off this issue with a paper demonstrating what he would consider the pitfalls of multivariate analysis by examining a particular research program, namely a series of dyadic democratic peace papers. John Oneal and Bruce Russett take Ray to task in the next paper, arguing that their own democratic peace research would not have progressed, especially in terms of being able to evaluate alternative theories, without the use of control variables. In our own contribution to this issue, we make a leap of faith and submit some of our own research on the systemic democratic peace to Ray’s five guidelines,
A Laserscanner-Vision Fusion System Implemented on the TerraMax Autonomous Vehicle

This paper presents a sensor fusion model developed for the 2005 Grand Challenge competition, an autonomous ground vehicle race across the Mojave desert organized by DARPA. The two sensors used in this work are a stereo vision camera pair and an ALASCA laserscanner. An algorithm to filter laserscanner's raw scan data and to remove ground reflections is also presented. Several tests were made to prove the reliability of this method, that has proved to be useful to extract the information required by the race. Fusion was performed both at a low and medium level: terrain slope, detected with stereo vision, was used to correct pitch information of laserscanner raw data. Object segmentation is applied on a bird view bitmap where each pixel represents a square area of the world in front of the vehicle; this bitmap is obtained from the fusion of the ones generated by each sensor
Molecular Characterization and Growth Association of Two Apolipoprotein A-Ib Genes in Common Carp (Cyprinus carpio)

Apolipoprotein A-I (ApoA-I) is functionally involved in the transportation and metabolism of lipids in vertebrates. In this study, two isoforms of apoA-Ib in common carp (Cyprinus carpio L.) were characterized. Sequence comparison and phylogenetic analysis showed that C. carpio ApoA-Ib is relatively conserved within cyprinid fishes. During embryonic development, C. carpio apoA-Ib was first expressed at the stage of multi-cells, and the highest mRNA level was observed at the stage of optic vesicle. A ubiquitous expression pattern was detected in various tissues with extreme predominance in the liver. Significantly different expression levels were observed between light and heavy body weight groups and also in the compensatory growth test. Seventeen and eight single-nucleotide polymorphisms (SNPs) were identified in matured mRNA of the C. carpio apoA-Ib.1 and apoA-Ib.2, respectively. Two of these SNPs (apoA-Ib.2-g.183A>T and apoA-Ib.2-g.1753C>T) were significantly associated with body weight and body length in two populations of common carp. These results indicate that apoA-Ib may play an important role in the modulation of growth and development in common carp.