Free-and open source software for a course on network management: authoring and enactment of scripts based on collaborative learning strategies

This paper describes a Computer-Supported Collaborative Learning (CSCL) case study in engineering education carried out within the context of a network management course. The case study shows that the use of two computing tools developed by the authors and based on Free- and Open-Source Software (FOSS) provide significant educational benefits over traditional engineering pedagogical approaches in terms of both concepts and engineering competencies acquisition. First, the Collage authoring tool guides and supports the course teacher in the process of authoring computer-interpretable representations (using the IMS Learning Design standard notation) of effective collaborative pedagogical designs. Besides, the Gridcole system supports the enactment of that design by guiding the students throughout the prescribed sequence of learning activities. The paper introduces the goals and context of the case study, elaborates onhow Collage and Gridcole were employed, describes the applied evaluation methodology, anddiscusses the most significant findings derived from the case study.

Time-resolved lanthanide luminescence for lab-on-a-chip detection of biomarkers on cancerous tissues.

PDMS-based microfluidic devices combined with lanthanide-based immunocomplexes have been successfully tested for the multiplex detection of biomarkers on cancerous tissues, revealing an enhanced sensitivity compared to classical organic dyes.

Audit report on the Iowa Communications Network (ICN) for the year ended June 30, 2007

Audit report on the Iowa Communications Network (ICN) for the year ended June 30, 2007

On bounds for network revenue management

The Network Revenue Management problem can be formulated as a stochastic dynamic programming problem (DP or the\optimal" solution V *) whose exact solution is computationally intractable. Consequently, a number of heuristics have been proposed in the literature, the most popular of which are the deterministic linear programming (DLP) model, and a simulation based method, the randomized linear programming (RLP) model. Both methods give upper bounds on the optimal solution value (DLP and PHLP respectively). These bounds are used to provide control values that can be used in practice to make accept/deny decisions for booking requests. Recently Adelman [1] and Topaloglu [18] have proposed alternate upper bounds, the affine relaxation (AR) bound and the Lagrangian relaxation (LR) bound respectively, and showed that their bounds are tighter than the DLP bound. Tight bounds are of great interest as it appears from empirical studies and practical experience that models that give tighter bounds also lead to better controls (better in the sense that they lead to more revenue). In this paper we give tightened versions of three bounds, calling themsAR (strong Affine Relaxation), sLR (strong Lagrangian Relaxation) and sPHLP (strong Perfect Hindsight LP), and show relations between them. Speciffically, we show that the sPHLP bound is tighter than sLR bound and sAR bound is tighter than the LR bound. The techniques for deriving the sLR and sPHLP bounds can potentially be applied to other instances of weakly-coupled dynamic programming.

Red meat and cancer risk in a network of case-control studies focusing on cooking practices.

BACKGROUND: Consumption of red meat has been related to increased risk of several cancers. Cooking methods could modify the magnitude of this association, as production of chemicals depends on the temperature and duration of cooking. METHODS: We analyzed data from a network of case-control studies conducted in Italy and Switzerland between 1991 and 2009. The studies included 1465 oral and pharyngeal, 198 nasopharyngeal, 851 laryngeal, 505 esophageal, 230 stomach, 1463 colon, 927 rectal, 326 pancreatic, 3034 breast, 454 endometrial, 1031 ovarian, 1294 prostate and 767 renal cancer cases. Controls included 11 656 patients admitted for acute, non-neoplastic conditions. Odds ratios (ORs) and confidence intervals (CIs) were estimated by multiple logistic regression models, adjusted for known confounding factors. RESULTS: Daily intake of red meat was significantly associated with the risk of cancer of the oral cavity and pharynx (OR for increase of 50 g/day = 1.38; 95% CI: 1.26-1.52), nasopharynx (OR = 1.29; 95% CI: 1.04-1.60), larynx (OR = 1.46; 95% CI: 1.30-1.64), esophagus (OR = 1.46; 95% CI: 1.23-1.72), colon (OR = 1.17; 95% CI: 1.08-1.26), rectum (OR = 1.22; 95% CI:1.11-1.33), pancreas (OR = 1.51; 95% CI: 1.25-1.82), breast (OR = 1.12; 95% CI: 1.04-1.19), endometrium (OR = 1.30; 95% CI: 1.10-1.55) and ovary (OR = 1.29; 95% CI: 1.16-1.43). Fried meat was associated with a higher risk of cancer of oral cavity and pharynx (OR = 2.80; 95% CI: 2.02-3.89) and esophagus (OR = 4.52; 95% CI: 2.50-8.18). Risk of prostate cancer increased for meat cooked by roasting/grilling (OR = 1.31; 95% CI: 1.12-1.54). No heterogeneity according to cooking methods emerged for other cancers. Nonetheless, significant associations with boiled/stewed meat also emerged for cancer of the nasopharynx (OR = 1.97; 95% CI: 1.30-3.00) and stomach (OR = 1.86; 95% CI: 1.20-2.87). CONCLUSIONS: Our analysis confirmed red meat consumption as a risk factor for several cancer sites, with a limited impact of cooking methods. These findings, thus, call for a limitation of its consumption in populations of Western countries.

Audit report on the Iowa Communications Network (ICN) for the year ended June 30, 2008

Audit report on the Iowa Communications Network (ICN) for the year ended June 30, 2008

The evolution of recent research on Catalan literature through the production of PhD theses: a bibliometric and social network analysis

Introduction. This paper studies the situation of research on Catalan literature between 1976 and 2003 by carrying out a bibliometric and social network analysis of PhD theses defended in Spain. It has a dual aim: to present interesting results for the discipline and to demonstrate the methodological efficacy of scientometric tools in the humanities, a field in which they are often neglected due to the difficulty of gathering data. Method. The analysis was performed on 151 records obtained from the TESEO database of PhD theses. The quantitative estimates include the use of the UCINET and Pajek software packages. Authority control was performed on the records. Analysis. Descriptive statistics were used to describe the sample and the distribution of responses to each question. Sex differences on key questions were analysed using the Chi-squared test. Results. The value of the figures obtained is demonstrated. The information obtained on the topic and the periods studied in the theses, and on the actors involved (doctoral students, thesis supervisors and members of defence committees), provide important insights into the mechanisms of humanities disciplines. The main research tendencies of Catalan literature are identified. It is observed that the composition of members of the thesis defence committees follows Lotka's Law. Conclusions. Bibliometric analysis and social network analysis may be especially useful in the humanities and in other fields which are lacking in scientometric data in comparison with the experimental sciences.

Audit report on the Iowa Communications Network (ICN) for the year ended June 30, 2009

Audit report on the Iowa Communications Network (ICN) for the year ended June 30, 2009

Report on the Iowa Communications Network (ICN) for the year ended June 30, 2010

Report on the Iowa Communications Network (ICN) for the year ended June 30, 2010

Candida species distribution and antifungal susceptibility testing according to European Committee on Antimicrobial Susceptibility Testing and new vs. old Clinical and Laboratory Standards Institute clinical breakpoints: a 6-year prospective candidaemia survey from the fungal infection network of Switzerland.

We analyzed the species distribution of Candida blood isolates (CBIs), prospectively collected between 2004 and 2009 within FUNGINOS, and compared their antifungal susceptibility according to clinical breakpoints defined by the European Committee on Antimicrobial Susceptibility Testing (EUCAST) in 2013, and the Clinical and Laboratory Standards Institute (CLSI) in 2008 (old CLSI breakpoints) and 2012 (new CLSI breakpoints). CBIs were tested for susceptiblity to fluconazole, voriconazole and caspofungin by microtitre broth dilution (Sensititre(®) YeastOne? test panel). Of 1090 CBIs, 675 (61.9%) were C. albicans, 191 (17.5%) C. glabrata, 64 (5.9%) C. tropicalis, 59 (5.4%) C. parapsilosis, 33 (3%) C. dubliniensis, 22 (2%) C. krusei and 46 (4.2%) rare Candida species. Independently of the breakpoints applied, C. albicans was almost uniformly (>98%) susceptible to all three antifungal agents. In contrast, the proportions of fluconazole- and voriconazole-susceptible C. tropicalis and F-susceptible C. parapsilosis were lower according to EUCAST/new CLSI breakpoints than to the old CLSI breakpoints. For caspofungin, non-susceptibility occurred mainly in C. krusei (63.3%) and C. glabrata (9.4%). Nine isolates (five C. tropicalis, three C. albicans and one C. parapsilosis) were cross-resistant to azoles according to EUCAST breakpoints, compared with three isolates (two C. albicans and one C. tropicalis) according to new and two (2 C. albicans) according to old CLSI breakpoints. Four species (C. albicans, C. glabrata, C. tropicalis and C. parapsilosis) represented >90% of all CBIs. In vitro resistance to fluconazole, voriconazole and caspofungin was rare among C. albicans, but an increase of non-susceptibile isolates was observed among C. tropicalis/C. parapsilosis for the azoles and C. glabrata/C. krusei for caspofungin according to EUCAST and new CLSI breakpoints compared with old CLSI breakpoints.

State-of-the-art of 3D cultures (organs-on-a-chip) in safety testing and pathophysiology.

Integrated approaches using different in vitro methods in combination with bioinformatics can (i) increase the success rate and speed of drug development; (ii) improve the accuracy of toxicological risk assessment; and (iii) increase our understanding of disease. Three-dimensional (3D) cell culture models are important building blocks of this strategy which has emerged during the last years. The majority of these models are organotypic, i.e., they aim to reproduce major functions of an organ or organ system. This implies in many cases that more than one cell type forms the 3D structure, and often matrix elements play an important role. This review summarizes the state of the art concerning commonalities of the different models. For instance, the theory of mass transport/metabolite exchange in 3D systems and the special analytical requirements for test endpoints in organotypic cultures are discussed in detail. In the next part, 3D model systems for selected organs--liver, lung, skin, brain--are presented and characterized in dedicated chapters. Also, 3D approaches to the modeling of tumors are presented and discussed. All chapters give a historical background, illustrate the large variety of approaches, and highlight up- and downsides as well as specific requirements. Moreover, they refer to the application in disease modeling, drug discovery and safety assessment. Finally, consensus recommendations indicate a roadmap for the successful implementation of 3D models in routine screening. It is expected that the use of such models will accelerate progress by reducing error rates and wrong predictions from compound testing.

Soil infiltration based on bp neural network and grey relational analysis

Soil infiltration is a key link of the natural water cycle process. Studies on soil permeability are conducive for water resources assessment and estimation, runoff regulation and management, soil erosion modeling, nonpoint and point source pollution of farmland, among other aspects. The unequal influence of rainfall duration, rainfall intensity, antecedent soil moisture, vegetation cover, vegetation type, and slope gradient on soil cumulative infiltration was studied under simulated rainfall and different underlying surfaces. We established a six factor-model of soil cumulative infiltration by the improved back propagation (BP)-based artificial neural network algorithm with a momentum term and self-adjusting learning rate. Compared to the multiple nonlinear regression method, the stability and accuracy of the improved BP algorithm was better. Based on the improved BP model, the sensitive index of these six factors on soil cumulative infiltration was investigated. Secondly, the grey relational analysis method was used to individually study grey correlations among these six factors and soil cumulative infiltration. The results of the two methods were very similar. Rainfall duration was the most influential factor, followed by vegetation cover, vegetation type, rainfall intensity and antecedent soil moisture. The effect of slope gradient on soil cumulative infiltration was not significant.

Report on the Iowa Communications Network (ICN) for the year ended June 30, 2011

Report on the Iowa Communications Network (ICN) for the year ended June 30, 2011