Adherence rates to ferric citrate as compared to active control in patients with end stage kidney disease on dialysis

Introduction: Oral phosphate binders are the main stay of treatment of hyperphosphatemia. Adherence rates to ferric citrate, a recently approved phosphate binder, are unknown. Methods: We conducted a post‐hoc analysis to evaluate whether adherence rates were different for ferric citrate vs. active control in 412 subjects with end stage kidney disease (ESKD) who were randomized to ferric citrate vs. active control (sevelamer carbonate and/or calcium acetate). Adherence was defined as percent of actual number of pills taken to total number of pills prescribed. Findings: There were no significant differences in baseline characteristics including gender, race/ethnicity, and age between the ferric citrate and active control groups. Baseline phosphorus, calcium, and parathyroid hormone levels were similar. Mean (SD) adherence was 81.4% (17.4) and 81.7% (15.9) in the ferric citrate and active control groups, respectively (P = 0.88). Adherence remained similar between both groups after adjusting for gender, race/ethnicity, age, cardiovascular disease (CVD), and diabetic nephropathy (mean [95% CI]: 81.4% [78.2, 84.6] and 81.5% [77.7, 85.2] for ferric citrate and active control, respectively). Gender, race/ethnicity, age, and diagnosis of diabetic nephropathy did not influence adherence to the prescribed phosphate binder. Subjects with CVD had lower adherence rates to phosphate binder; this was significant only in the active control group. Discussion: Adherence rates to the phosphate binder, ferric citrate, were similar to adherence rates to active control. Similar adherence rates to ferric citrate are notable since tolerance to active control was an entry criteria and the study was open label. Gender, race/ethnicity, nor age influenced adherence.     

Hybridized electronic states between CdSe nanoparticles and conjugated organic ligands: A theoretical and ultrafast photo-excited carrier dynamics study

Formation of densely packed thin films of semiconductor nanocrystals is advantageous for the exploitation of their unique optoelectronic properties for real-world applications. Here we investigate the fundamental role of the structure of the bridging ligand on the optoelectronic properties of the resulting hybrid film. In particular, we considered hybrid films formed using the same CdSe nanocrystals and two organic ligands that have the same bidentate dithiocarbamate binding moiety, but differ in their bridging structures, one bridged by ethylene, the other by phenylene that exhibits conjugation. Based on the results of photo-excited carrier dynamics experiments combined with theoretical calculations on the electronic states of bridged CdSe layers, we show that only the phenylene-based ligand presents a strong hybridization of the molecular HOMO state with CdSe layers, that is a marker of formation of an effective bridge. We argue that this hybridization spread favors the hopping of photo-excited carriers between nanocrystals, which may explain the reported larger photo-currents in phenylene-based hybrid films than those observed in ethylene-based ones.

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Agent decision-making in open mixed networks

Computer systems increasingly carry out tasks in mixed networks, that is in group settings in which they interact both with other computer systems and with people. Participants in these heterogeneous human-computer groups vary in their capabilities, goals, and strategies; they may cooperate, collaborate, or compete. The presence of people in mixed networks raises challenges for the design and the evaluation of decision-making strategies for computer agents. This paper describes several new decision-making models that represent, learn and adapt to various social attributes that influence people's decision-making and presents a novel approach to evaluating such models. It identifies a range of social attributes in an open-network setting that influence people's decision-making and thus affect the performance of computer-agent strategies, and establishes the importance of learning and adaptation to the success of such strategies. The settings vary in the capabilities, goals, and strategies that people bring into their interactions. The studies deploy a configurable system called Colored Trails (CT) that generates a family of games. CT is an abstract, conceptually simple but highly versatile game in which players negotiate and exchange resources to enable them to achieve their individual or group goals. It provides a realistic analogue to multi-agent task domains, while not requiring extensive domain modeling. It is less abstract than payoff matrices, and people exhibit less strategic and more helpful behavior in CT than in the identical payoff matrix decision-making context. By not requiring extensive domain modeling, CT enables agent researchers to focus their attention on strategy design, and it provides an environment in which the influence of social factors can be better isolated and studied.     

Reporting computing projects through structured abstracts: a quasi-experiment

Previous work has demonstrated that the use of structured abstracts can lead to greater completeness and clarity of information, making it easier for researchers to extract information about a study. In academic year 2007/08, Durham University’s Computer Science Department revised the format of the project report that final year students were required to write, from a ‘traditional dissertation’ format, using a conventional abstract, to that of a 20-page technical paper, together with a structured abstract. This study set out to determine whether inexperienced authors (students writing their final project reports for computing topics) find it easier to produce good abstracts, in terms of completeness and clarity, when using a structured form rather than a conventional form. We performed a controlled quasi-experiment in which a set of ‘judges’ each assessed one conventional and one structured abstract for its completeness and clarity. These abstracts were drawn from those produced by four cohorts of final year students: two preceding the change, and the two following. The assessments were performed using a form of checklist that is similar to those used for previous experimental studies. We used 40 abstracts (10 per cohort) and 20 student ‘judges’ to perform the evaluation. Scored on a scale of 0.1–1.0, the mean for completeness increased from 0.37 to 0.61 when using a structured form. For clarity, using a scale of 1–10, the mean score increased from 5.1 to 7.2. For a minimum goal of scoring 50% for both completeness and clarity, only 3 from 19 conventional abstracts achieved this level, while only 3 from 20 structured abstracts failed to reach it. We conclude that the use of a structured form for organising the material of an abstract can assist inexperienced authors with writing technical abstracts that are clearer and more complete than those produced without the framework provided by such a mechanism.     

Handling Movement Epenthesis and Hand Segmentation Ambiguities in Continuous Sign Language Recognition Using Nested Dynamic Programming

We consider two crucial problems in continuous sign language recognition from unaided video sequences. At the sentence level, we consider the movement epenthesis (me) problem and at the feature level, we consider the problem of hand segmentation and grouping. We construct a framework that can handle both of these problems based on an enhanced, nested version of the dynamic programming approach. To address movement epenthesis, a dynamic programming (DP) process employs a virtual me option that does not need explicit models. We call this the enhanced level building (eLB) algorithm. This formulation also allows the incorporation of grammar models. Nested within this eLB is another DP that handles the problem of selecting among multiple hand candidates. We demonstrate our ideas on four American Sign Language data sets with simple background, with the signer wearing short sleeves, with complex background, and across signers. We compared the performance with Conditional Random Fields (CRF) and Latent Dynamic-CRF-based approaches. The experiments show more than 40 percent improvement over CRF or LDCRF approaches in terms of the frame labeling rate. We show the flexibility of our approach when handling a changing context. We also find a 70 percent improvement in sign recognition rate over the unenhanced DP matching algorithm that does not accommodate the me effect.     

Evolving trees for the retrieval of mass spectrometry-based bacteria fingerprints

In this paper, we investigate the application of Evolving Trees (ET) for the analysis of mass spectrometric data of bacteria. Evolving Trees are extensions of self-organizing maps (SOMs) developed for hierarchical classification systems. Therefore, they are well suited for taxonomic problems such as the identification of bacteria. Here, we focus on three topics, an appropriate pre-processing and encoding of the spectra, an adequate data model by means of a hierarchical Evolving Tree and an interpretable visualization. First, the high dimensionality of the data is reduced by a compact representation. Here, we employ sparse coding, specifically tailored for the processing of mass spectra. In the second step, the topographic information which is expected in the fingerprints is used for advanced tree evaluation and analysis. We adapted the original topographic product for SOMs for ET to achieve a judgment of topography. Additionally we transferred the concept of U-matrix for evaluation of the separability of SOMs to their analog in ET. We demonstrate these extensions for two mass spectrometric data sets of bacteria fingerprints and show their classification and evaluation capabilities in comparison to state of the art techniques.     

A web-based formative assessment tool for Masters students: A pilot study

The use of web-based learning and assessment tools is growing in tertiary institutions around the world. To date, very few papers have reported the development and evaluation of a web-based formative assessment tool for postgraduate students. The aim of the present paper was to report on the development and evaluation of an online formative assessment tool for this student group. The web-based formative assessment tool was evaluated by a sample of undergraduate students, postgraduate students and academic staff within a psychology department in order to determine the suitability and sensitivity of the tool. The results of this pilot test suggest that the development of such a tool is both appropriate and feasible for Masters students studying psychology.     

Exploring the relationship of a file’s history and its fault-proneness: An empirical method and its application to open source programs

ContextThe knowledge about particular characteristics of software that are indicators for defects is very valuable for testers because it helps them to focus the testing effort and to allocate their limited resources appropriately.ObjectiveIn this paper, we explore the relationship between several historical characteristics of files and their defect count.MethodFor this purpose, we propose an empirical approach that uses statistical procedures and visual representations of the data in order to determine indicators for a file’s defect count. We apply this approach to nine open source Java projects across different versions.ResultsOnly 4 of 9 programs show moderate correlations between a file’s defects in previous and in current releases in more than half of the analysed releases. In contrast to our expectations, the oldest files represent the most fault-prone files. Additionally, late changes correlate with a file’s defect count only partly. The number of changes, the number of distinct authors performing changes to a file as well as the file’s age are good indicators for a file’s defect count in all projects.ConclusionOur results show that a software’s history is a good indicator for ist quality. We did not find one indicator that persists across all projects in an equal manner. Nevertheless, there are several indicators that show significant strong correlations in nearly all projects: DA (number of distinct authors) and FC (frequency of change). In practice, for each software, statistical analyses have to be performed in order to evaluate the best indicator(s) for a file’s defect count.     

A Case-Based Micro Interactive Genetic Algorithm (CBMIGA) for interactive learning and search: Methodology and application to groundwater monitoring design

Interactive optimization algorithms use real–time interaction to include decision maker preferences based on the subjective quality of evolving solutions. In water resources management problems where numerous qualitative criteria exist, use of such interactive optimization methods can facilitate in the search for comprehensive and meaningful solutions for the decision maker. The decision makers using such a system are, however, likely to go through their own learning process as they view new solutions and gain knowledge about the design space. This leads to temporal changes (nonstationarity) in their preferences that can impair the performance of interactive optimization algorithms. This paper proposes a new interactive optimization algorithm – Case-Based Micro Interactive Genetic Algorithm – that uses a case-based memory and case-based reasoning to manage the effects of nonstationarity in decision maker’s preferences within the search process without impairing the performance of the search algorithm. This paper focuses on exploring the advantages of such an approach within the domain of groundwater monitoring design, though it is applicable to many other problems. The methodology is tested under non-stationary preference conditions using simulated and real human decision makers, and it is also compared with a non-interactive genetic algorithm and a previous version of the interactive genetic algorithm.     

Refining the systematic literature review process—two participant-observer case studies

Systematic literature reviews (SLRs) are a major tool for supporting evidence-based software engineering. Adapting the procedures involved in such a review to meet the needs of software engineering and its literature remains an ongoing process. As part of this process of refinement, we undertook two case studies which aimed 1) to compare the use of targeted manual searches with broad automated searches and 2) to compare different methods of reaching a consensus on quality. For Case 1, we compared a tertiary study of systematic literature reviews published between January 1, 2004 and June 30, 2007 which used a manual search of selected journals and conferences and a replication of that study based on a broad automated search. We found that broad automated searches find more studies than manual restricted searches, but they may be of poor quality. Researchers undertaking SLRs may be justified in using targeted manual searches if they intend to omit low quality papers, or they are assessing research trends in research methodologies. For Case 2, we analyzed the process used to evaluate the quality of SLRs. We conclude that if quality evaluation of primary studies is a critical component of a specific SLR, assessments should be based on three independent evaluators incorporating at least two rounds of discussion.