Miracle-dz/UniFAR-FTUs huggingface dataset:
Arachidonic acid metabolites alter G protein-mediated signal transduction in heart. Effects on muscarinic K+ channels

The muscarinic acetylcholine receptor (mAChR)-stimulated, inwardly rectifying K+ current (IK [ACh]) was examined in single bullfrog atrial cells using the whole-cell patch clamp technique. IK[ACh] was activated either by bath addition of 1 microM ACh or via activation of the G protein, Gk, with guanosine-gamma-thiotriphosphate (GTP gamma S). Arachidonic acid (AA) modulated IK[ACh] under both conditions. AA decreased mAChR-stimulated IK[ACh] and increased the rate of decay from the peak current (desensitization). In addition, AA affected GTP gamma S-activated IK[ACh] by modulation of Gk. The effects of AA and its metabolites on Gk were assessed by examining their effects on both the basal rate of Gk activation by GTP gamma S, and the mAChR-mediated increase in activation rate produced by nanomolar ACh. AA increased the basal rate of GTP gamma S-mediated IK[ACh] activation, but reduced the ACh-induced augmentation of this rate. All of the effects of AA on GTP gamma S-mediated IK[ACh] activation were produced by metabolites. A lipoxygenase inhibitor, nordihydroguaiaretic acid (NDGA), decreased the basal and ACh-enhanced rate of IK[ACh] activation in both the presence and absence of exogenous AA. In contrast, indomethacin (INDO), a cyclooxygenase inhibitor, increased the basal rate of IK[ACh] activation by GTP gamma S in both the presence and absence of exogenous AA, and reversed the effects of AA on the ACh-augmented basal rate. AA metabolites produced via lipoxygenase and cyclooxygenase pathways thus have opposing effects on the signal transduction pathway from mAChR to IK[ACh]. We directly tested a lipoxygenase pathway metabolite, LTC4, on GTP gamma S-mediated IK[ACh] activation and found that it not only overcame the inhibitory effects of NDGA, but also increased both the basal and ACh-augmented rate of IK[ACh] activation. From these data, we propose that AA metabolites modulate the function of Gk by altering its kinetic properties.
Brief announcement: on the quest of optimal service ordering in decentralized queries

This paper deals with pipelined queries over services. The execution plan of such queries defines an order in which the services are called. We present the theoretical underpinnings of a newly proposed algorithm that produces the optimal linear ordering corresponding to a query being executed in a decentralized manner, i.e., when the services communicate directly with each other. The optimality is defined in terms of query response time, which is determined by the bottleneck service in the plan. The properties discussed in this work allow a branch-and-bound approach to be very efficient.
Towards a Framework for Managing Evolving Information Resources on the Data Web

The web of data has brought forth the need to preserve and sustain evolving information within linked datasets; however, a basic requirement of data preservation is the maintenance of the datasets' structural characteristics as well. As open data are often found using different and/or heterogeneous data models and schemata from one source to another, there is a need to reconcile these mismatches and provide common denominations of interpretation on a multitude of levels, in order to be able to preserve and manage the evolution of the generated resources. In this paper, we present a linked data approach for the preservation and archiving of open heterogeneous datasets that evolve through time, at both the structural and the semantic layer. We first propose a set of re-quirements for modelling evolving linked datasets. We then proceed on concep-tualizing a modelling framework for evolving entities and place these in a 2x2 model space that consists of the semantic and the temporal dimensions.
Long-Term Effects of Ionizing Radiation on Gene Expression in a Zebrafish Model

Understanding how initial radiation injury translates into long-term effects is an important problem in radiation biology. Here, we define a set of changes in the transcription profile that are associated with the long-term response to radiation exposure. The study was performed in vivo using zebrafish, an established radiobiological model organism. To study the long-term response, 24 hour post-fertilization embryos were exposed to 0.1 Gy (low dose) or 1.0 Gy (moderate dose) of whole-body gamma radiation and allowed to develop for 16 weeks. Liver mRNA profiles were then analyzed using the Affymetrix microarray platform, with validation by quantitative PCR. As a basis for comparison, 16-week old adults were exposed at the same doses and analyzed after 4 hours. Statistical analysis was performed in a way to minimize the effects of multiple comparisons. The responses to these two treatment regimes differed greatly: 360 probe sets were associated primarily with the long-term response, whereas a different 2062 probe sets were associated primarily with the response when adults of the same age were irradiated 4 hours before exposure. Surprisingly, a ten-fold difference in radiation dose (0.1 versus 1.0 Gy) had little effect. Analysis at the gene and pathway level indicated that the long-term response includes the induction of cytokine and inflammatory regulators and transcription and growth factors. The acute response includes the induction of p53 target genes and modulation of the hypoxia-induced transcription factor-C/EBP axis. Results help define genes and pathways affected in the long-term, low and moderate dose radiation response and differentiate them from those affected in an acute response in the same tissue.
Frame-based method for customizing generic software architectures

One way to support development and maintenance of a software system family is to design a generic software architecture for a family. A generic architecture captures requirements common to all (or most of) the family members. Then, we develop specific software systems, members of a family, by customizing a generic architecture. During customization, we address variant requirements to be met by a specific system we wish to implement. In this paper, we describe how we applied frame technology an advanced form of pre-processing to design a mechanism for customizing generic software architectures. Customization of a generic architecture involves selecting architecture components, customization of connectors and customization of components’ code. We turn architecture components and connectors into frames and map variant requirements into sequences of customization activities. The frame processor and Perl scripts automate the customization process. Our customization method can be applied to a wide range of generic architectures. It can be used together with other customization techniques such as inheritance (in Object-Oriented frameworks), table-driven techniques (in compiler-compilers) or parameterization. The overall objective of the work described in this paper is to create formal links between requirements for system families and the process of customizing a generic architecture during architecture-based system engineering. Ideally, a system engineer would define only novel requirements for a specific system (based on a domain model) and an automated engineering environment would actively guide him/her in obtaining the architecture and code for the specific system. This paper describes some of the techniques that lead towards this objective.
Synthesizing bidirectional texture functions for real-world surfaces

In this paper, we present a novel approach to synthetically generating bidirectional texture functions (BTFs) of real-world surfaces. Unlike a conventional two-dimensional texture, a BTF is a six-dimensional function that describes the appearance of texture as a function of illumination and viewing directions. The BTF captures the appearance change caused by visible small-scale geometric details on surfaces. From a sparse set of images under different viewing/lighting settings, our approach generates BTFs in three steps. First, it recovers approximate 3D geometry of surface details using a shape-from-shading method. Then, it generates a novel version of the geometric details that has the same statistical properties as the sample surface with a non-parametric sampling method. Finally, it employs an appearance preserving procedure to synthesize novel images for the recovered or generated geometric details under various viewing/lighting settings, which then define a BTF. Our experimental results demonstrate the effectiveness of our approach.
EXPLORING THE IMPACT OF HIGH PERFORMANCE WORK SYSTEMS IN PROFESSIONAL SERVICE FIRMS : A PRACTICES-RESOURCES-USES-PERFORMANCE

This article aims to explore how a system of human resource management (HRM) practices influence firm performance in a professional service context. It integrates multidisciplinary theory and research findings. The system of HRM practices are labeled as high performance work systems (HPWS). In this article, it is proposed that HPWS influence firm performance through two steps: (1) by creating resources of human, social and organizational capital; and (2) by efficient uses of these resources. It indicates that firms using higher level of HPWS will experience better performance. The underlying mechanism is that HPWS first promote employees’ ability, relationships, and opportunities; that is, the resources. These resources then facilitate the uses process, which is represented by 4 means: (1) sensing the changes in the external environment; (2) team formation and utilization; (3) leveraging knowledge from seniors to juniors; and (4) combining and exchanging knowledge. Uses finally lead to higher organizational performance. This approach is called the practices-resources-uses-performance linkage model. Employing this linkage process tool, managers are able to diagnose the requirements for organizational development. They can effectively adopt and implement HPWS. This article introduces a novel perspective for investigating the underlying mediating mechanisms that explain the link between HPWS and Professional Service Firm (PSF) performance.
CTCV: A protocol for Coordinated Transport of Correlated Video in Smart Camera Networks

Smart camera networks (SCNs) are increasingly used in applications such as homeland security, border control and traffic monitoring. The cameras are often wireless with an organically growing structure, to reduce the overhead of deployment. We frame a new and important problem in SCNs: how to transmit videos from multiple cameras with overlapping coverage given the limited available wireless bandwidth to maximize the quality of the received videos. We call this problem Coordinated Transport of Correlated Videos (CTCV). CTCV is a more general version of 3D video transport: in that problem, highly correlated videos from two cameras (that provide the 3D perspective) are jointly encoded exploiting their pre-defined and known overlap. In contrast, in CTCV there is an arbitrary number of cameras whose overlap is not known apriori and that require transmission as multiple video streams. To effectively support CTCV, we propose a video delivery protocol that consists of two primary components: (1) Consolidation of correlated videos from multiple cameras which removes spatially redundant fields-of-view; and (2) Network and coverage aware bandwidth allocation to optimize coverage quality cooperatively among the different video streams to match the available bandwidth. We formulate the problem of optimal bandwidth allocation for maximizing coverage. We propose and investigate different heuristic policies for bandwidth allocation. We evaluate CTCV using data from a small camera testbed as well as topologies from realistic deployments. Experiments show that CTCV achieves around 10 dB gains in video quality in the scenarios we consider.
Conflict detection tradeoffs for replicated data

Many concurrency control algorithms have been proposed for use in distributed database systems. Despite the large number of available algorithms and the fact that distributed database systems are becoming a commercial reality, distributed concurrency control performance trade-offs are still not well understood. In this paper we examine some of these trade-offs by using a detailed model of a distributed DBMS to study a set of representative algorithms, including several derivatives of the two-phase locking, timestamp ordering, and optimistic approaches to distributed concurrency control. In particular, we examine the performance of these algorithms for update transactions as a function of data contention for various levels of data replication and “distributedness” of accesses to replicated data. The results provide some interesting insights into how the trade-offs between early and late conflict detection vary as a function of message cost, and should prove useful to distributed database system designers.
Teaching critical appraisal skills in healthcare settings.

BACKGROUND Critical appraisal is the process of assessing and interpreting evidence by systematically considering its validity, results and relevance to an individual's work. Within the last decade critical appraisal has been added as a topic to many medical school and UK Royal College curricula, and several continuing professional development ventures have been funded to provide further training. This is an update of a Cochrane review first published in 2001. OBJECTIVES To assess the effects of teaching critical appraisal skills to health professionals on the process of care, patient outcomes and knowledge of health professionals. SEARCH METHODS. We updated the search (see Appendix 1 for search strategies by database) and used those search strategies to search the Cochrane Central Register of Controlled Trials (1997 to June 2011) and MEDLINE (from 1997 to June 2011). We also searched EMBASE, CINAHL and PsycINFO (up to January 2010). We searched LISA (up to January 2010), ERIC (up to January 2010), SIGLE (up to January 2010) and Web of Knowledge (up to January 2010). We also searched the Cochrane Database of Systematic Reviews (CDSR), Database of Abstracts of Reviews of Effects (DARE) and the Cochrane Effective Practice and Organisation of Care (EPOC) Group Specialised Register up to January 2010. SELECTION CRITERIA Randomised trials, controlled clinical trials, controlled before and after studies and interrupted time series analyses that examined the effectiveness of educational interventions teaching critical appraisal to health professionals. The outcomes included process of care, patient mortality, morbidity, quality of life and satisfaction. We included studies reporting on health professional knowledge/awareness only when based upon objective, standardised, validated instruments. We did not consider studies involving students. DATA COLLECTION AND ANALYSIS Two review authors independently extracted data and assessed risk of bias. We contacted authors of included studies to obtain missing data. MAIN RESULTS In total, we reviewed a total of 11,057 titles and abstracts, of which 148 appeared potentially relevant to the review. We included three studies involving 272 people in this review. None of the included studies evaluated process of care or patient outcomes. Statistically significant improvements in participants' knowledge were reported in domains of critical appraisal (variable approaches across studies) in two of the three studies. We determined risk of bias to be 'unclear' and as such considered this to be 'plausible bias that raises some doubt about the results'. AUTHORS' CONCLUSIONS Low-intensity critical appraisal teaching interventions in healthcare populations may result in modest gains. Improvements to research examining the effectiveness of interventions in healthcare populations are required; specifically rigorous randomised trials employing interventions using appropriate adult learning theories.
Semi-Supervised Support Vector Machines for Unlabeled Data Classiﬁcation

A concave minimization approach is proposed for classifying unlabeled data based on the following ideas: (i) A small representative percentage (5% to 10%) of the unlabeled data is chosen by a clustering algorithm and given to an expert or oracle to label. (ii) A linear support vector machine is trained using the small labeled sample while simultaneously assigning the remaining bulk of the unlabeled dataset to one of two classes so as to maximize the margin (distance) between the two bounding planes that determine the separating plane midway between them. This latter problem is formulated as a concave minimization problem on a polyhedral set for which a stationary point is quickly obtained by solving a few (5 to 7) linear programs. Such stationary points turn out to be very eﬀective as evidenced by our computational results which show that clustered concave minimization yields: (a) Test set improvement as high as 20.4% over a linear support vector machine trained on a correspondingly small but randomly chosen subset that is labeled by an expert. (b) Test set correctness averaged to within 5.1% when compared to that of a completely supervised linear support vector machine trained on the entire dataset which has been labeled by an expert.
pH Triggered In-situ Gelling Ophthalmic Drug Delivery System

Eyes are delicate and most vital organs of the body whose defence mechanism restricts entry of exogenous substance. Conventional drug delivery systems get washed off within a short period of time that usually cause poor bioavailability and therapeutic responses because high tear fluid turnover and dynamics cause rapid elimination of the drug from the eye. In-situ gelling ophthalmic drug delivery system is one of the new methods that is developed to overcome this bioavailability problems. In-situ gelling systems are viscous polymerbased liquids that exhibit sol-to-gel phase transition on the ocular surface due to a change in a specific physicochemical parameter like temperature, ionic strength, or pH triggered in-situ systems. Using this formulation of pH triggered in-situ gel systems, the release of drug can be sustained for longer periods of time, therapeutically more efficacious, non-irritant and stable than conventional eye drops.
Immune genetic algorithm for solving nonlinear equations

A steam conversion of hydrocarbon mass balance of the nonlinear equations of the immune genetic algorithm method is researched in this paper. The nonlinear equations is transformed into nonlinear optimization problems; Tthe transformation process and implementation are discussed, this method is used to quickly and easily obtain the effective solution of the production technology. The production process used to solve practical problems, optimize production, increase economic efficiency.
Longitudinal Data Analysis in Medical Device Clinical Studies

Several statistical approaches are discussed for analysis of longitudinal clinical data from a two independent groups, randomized, prospective, multicenter study of patients with benign prostate hyperplasia (BPH) who are treated with either a new transurethral microwave thermotherapy device (TUMT, n = 147) or sham control (n = 73) at baseline and at 1, 3, and 6 months follow up. The primary clinical endpoint, based on the American Urological Association (AUA) symptom score from 7 questions (each scored 0–5) with 35 as the worst total score, is illustrated in this paper. The primary effectiveness null hypothesis is no treatment effect at any follow-up time against the alternative hypothesis of a favorable treatment effect at one or more follow-up times. Based on the prespecified clinical input of TUMT improvement in AUA mean score as a possible early effect, the expected change of slope between baseline to month 1 (baseline slope) and from month 1 to the end of month 6 (longitudinal slope), with knot at one month, were analyzed. The primary effectiveness endpoint was analyzed by a piecewise linear spline regression model with knot at month 1. Statistically significant lower mean AUA score was found in the TUMT group compared to the sham group at month 3 (P = 0.01) and at month 6 (P < 0.0001) follow-up; no significant difference in mean AUA score was found at baseline or at month 1 follow-up, after an overall statistically significant difference in mean AUA score (P = 0.004) was found between the TUMT and sham groups.
New knowledge extraction technique using probability for case‐based reasoning: application to medical diagnosis

Abstract: Case‐based reasoning (CBR) has been used in various problem‐solving areas such as financial forecasting, credit analysis and medical diagnosis. However, conventional CBR has the limitation that it has no criterion for choosing the nearest cases based on the probabilistic similarity of cases. It uses a fixed number of neighbors without considering an optimal number for each target case, so it does not guarantee optimal similar neighbors for various target cases. This leads to the weakness of lowering predictability due to deviation from desired similar neighbors. In this paper we suggest a new case extraction technique called statistical case‐based reasoning. The main idea involves a dynamic adaptation of the optimal number of neighbors by considering the distribution of distances between potential similar neighbors for each target case. In order to do this, our technique finds the optimal distance threshold and selects similar neighbors satisfying the distance threshold criterion. We apply this new method to five real‐life medical data sets and compare the results with those of the statistical method, logistic regression; we also compare the results with the learning methods C5.0, CART, neural networks and conventional CBR. The results of this paper show that the proposed technique outperforms those of many other methods, it overcomes the limitation of conventional CBR, and it provides improved classification accuracy.
Radio Resource Management for a Two-hop OFDMA Relay System in Downlink

In this paper, we propose two radio resource control (RRC) schemes where both base station (BS) and relay station (RS) perform dynamic resource allocation. The target system is a two-hop mobile communication system employing OFDMA technique. These schemes operate in such a distributed manner that both BS and RS control the mobile stations directly connected to each of them. However, the mobile station (MS) connected to RS is influenced by BS-RS and RS-RS links as well in addition to RS-MS link. To solve this problem, a BS-RS link control mechanism based on the information from RS should be supplemented into the system. The proposed mechanism, a semi-distributed method, is that BS allocates resources to the directly connected mobile stations and relay stations, first. Then RS allocates resources to the connected mobile stations in two ways; RS uses the assigned subcarriers from BS or all system subcategories independently. The former method is called the 'separate and sequential allocation (SSA)' and the latter the 'separate and reuse allocation (SRA)'. The SSA method yields a superior quality without regard to the location of RS, but the SRA method reveals performance results depending on the location of RS. Computer simulations show that the two proposed methods have almost the same performance as the existing centralized method but lower complexity and higher flexibility compared to the centralized method.