Constraint Programming for Multi-criteria Conceptual Clustering

International audienceA conceptual clustering is a set of formal concepts (i.e., closed itemsets) that defines a partition of a set of transactions. Finding a conceptual clustering is an N P-complete problem for which Constraint Programming (CP) and Integer Linear Programming (ILP) approaches have been recently proposed. We introduce new CP models to solve this problem: a pure CP model that uses set constraints, and an hybrid model that uses a data mining tool to extract formal concepts in a preprocessing step and then uses CP to select a subset of formal concepts that defines a partition. We compare our new models with recent CP and ILP approaches on classical machine learning instances. We also introduce a new set of instances coming from a real application case, which aims at extracting setting concepts from an Enterprise Resource Planning (ERP) software. We consider two classic criteria to optimize, i.e., the frequency and the size. We show that these criteria lead to extreme solutions with either very few small formal concepts or many large formal concepts, and that compromise clusterings may be obtained by computing the Pareto front of non dominated clusterings

Plasma sTNFR1 and IL8 for prognostic enrichment in sepsis trials: a prospective cohort study.

BackgroundEnrichment strategies improve therapeutic targeting and trial efficiency, but enrichment factors for sepsis trials are lacking. We determined whether concentrations of soluble tumor necrosis factor receptor-1 (sTNFR1), interleukin-8 (IL8), and angiopoietin-2 (Ang2) could identify sepsis patients at higher mortality risk and serve as prognostic enrichment factors.MethodsIn a multicenter prospective cohort study of 400 critically ill septic patients, we derived and validated thresholds for each marker and expressed prognostic enrichment using risk differences (RD) of 30-day mortality as predictive values. We then used decision curve analysis to simulate the prognostic enrichment of each marker and compare different prognostic enrichment strategies.Measurements and main resultsAn admission sTNFR1 concentration > 8861 pg/ml identified patients with increased mortality in both the derivation (RD 21.6%) and validation (RD 17.8%) populations. Among immunocompetent patients, an IL8 concentration > 94 pg/ml identified patients with increased mortality in both the derivation (RD 17.7%) and validation (RD 27.0%) populations. An Ang2 level > 9761 pg/ml identified patients at 21.3% and 12.3% increased risk of mortality in the derivation and validation populations, respectively. Using sTNFR1 or IL8 to select high-risk patients improved clinical trial power and efficiency compared to selecting patients with septic shock. Ang2 did not outperform septic shock as an enrichment factor.ConclusionsThresholds for sTNFR1 and IL8 consistently identified sepsis patients with higher mortality risk and may have utility for prognostic enrichment in sepsis trials

A Constraint Solver based on Abstract Domains

International audienceIn this article, we apply techniques from Abstract Interpretation (a general theory of semantic abstractions) to Constraint Programming (which aims at solving hard combinatorial problems with a generic framework based on first-order logics). We highlight some links and differences between these fields: both compute fixpoints by iteration but employ different extrapolation and refinement strategies; moreover, consistencies in Constraint Programming can be mapped to non-relational abstract domains. We then use these correspondences to build an abstract constraint solver that leverages abstract interpretation techniques (such as relational domains) to go beyond classic solvers. We present encouraging experimental results obtained with our prototype implementation

The nutrition-based comprehensive intervention study on childhood obesity in China (NISCOC): a randomised cluster controlled trial

<p>Abstract</p> <p>Background</p> <p>Childhood obesity and its related metabolic and psychological abnormalities are becoming serious health problems in China. Effective, feasible and practical interventions should be developed in order to prevent the childhood obesity and its related early onset of clinical cardiovascular diseases. The objective of this paper is to describe the design of a multi-centred random controlled school-based clinical intervention for childhood obesity in China. The secondary objective is to compare the cost-effectiveness of the comprehensive intervention strategy with two other interventions, one only focuses on nutrition education, the other only focuses on physical activity.</p> <p>Methods/Design</p> <p>The study is designed as a multi-centred randomised controlled trial, which included 6 centres located in Beijing, Shanghai, Chongqing, Shandong province, Heilongjiang province and Guangdong province. Both nutrition education (special developed carton style nutrition education handbook) and physical activity intervention (Happy 10 program) will be applied in all intervention schools of 5 cities except Beijing. In Beijing, nutrition education intervention will be applied in 3 schools and physical activity intervention among another 3 schools. A total of 9750 primary students (grade 1 to grade 5, aged 7-13 years) will participate in baseline and intervention measurements, including weight, height, waist circumference, body composition (bioelectrical impendence device), physical fitness, 3 days dietary record, physical activity questionnaire, blood pressure, plasma glucose and plasma lipid profiles. Data concerning investments will be collected in our study, including costs in staff training, intervention materials, teachers and school input and supervising related expenditure.</p> <p>Discussion</p> <p>Present study is the first and biggest multi-center comprehensive childhood obesity intervention study in China. Should the study produce comprehensive results, the intervention strategies would justify a national school-based program to prevent childhood obesity in China.</p> <p>Trial Registration</p> <p>Chinese clinical trial registry (Primary registry in the WHO registry network) Identifier: ChiCTR-TRC-00000402</p

"Dreaming in colour’: disabled higher education students’ perspectives on improving design practices that would enable them to benefit from their use of technologies"

The focus of this paper is the design of technology products and services for disabled students in higher education. It analyses the perspectives of disabled students studying in the US, the UK, Germany, Israel and Canada, regarding their experiences of using technologies to support their learning. The students shared how the functionality of the technologies supported them to study and enabled them to achieve their academic potential. Despite these positive outcomes, the students also reported difficulties associated with: i) the design of the technologies, ii) a lack of technology know-how and iii) a lack of social capital. When identifying potential solutions to these difficulties the disabled students imagined both preferable and possible futures where faculty, higher education institutions, researchers and technology companies are challenged to push the boundaries of their current design practices

High-Intensity Interval Training Interventions in Children and Adolescents: A Systematic Review

BackgroundWhilst there is increasing interest in the efficacy of high-intensity interval training in children and adolescents as a time-effective method of eliciting health benefits, there remains little consensus within the literature regarding the most effective means for delivering a high-intensity interval training intervention. Given the global health issues surrounding childhood obesity and associated health implications, the identification of effective intervention strategies is imperative.ObjectivesThe aim of this review was to examine high-intensity interval training as a means of influencing key health parameters and to elucidate the most effective high-intensity interval training protocol.MethodsStudies were included if they: (1) studied healthy children and/or adolescents (aged 5–18 years); (2) prescribed an intervention that was deemed high intensity; and (3) reported health-related outcome measures.ResultsA total of 2092 studies were initially retrieved from four databases. Studies that were deemed to meet the criteria were downloaded in their entirety and independently assessed for relevance by two authors using the pre-determined criteria. From this, 13 studies were deemed suitable. This review found that high-intensity interval training in children and adolescents is a time-effective method of improving cardiovascular disease biomarkers, but evidence regarding other health-related measures is more equivocal. Running-based sessions, at an intensity of >90% heart rate maximum/100–130% maximal aerobic velocity, two to three times a week and with a minimum intervention duration of 7 weeks, elicit the greatest improvements in participant health.ConclusionWhile high-intensity interval training improves cardiovascular disease biomarkers, and the evidence supports the effectiveness of running-based sessions, as outlined above, further recommendations as to optimal exercise duration and rest intervals remain ambiguous owing to the paucity of literature and the methodological limitations of studies presently available

Comparaison pratique de quelques méthodes d'analyse discriminante

peer reviewedDans cette étude, on compare les performances des trois méthodes d'analyse discriminante suivantes : analyse discriminante linéaire, analyse discriminante quadratique et analyse discriminante logistique. Les performances sont étudiées dans le cas de données réelles, en envisageant diverses transformations de variables destinées à modifier les conditions de normalité et d'égalité des variances entre populations. Aucune différence significative de performances entre méthodes n'a pu être mise en évidence au niveau de signification de 0,05. Par contre, les performances des trois méthodes diminuent quand les distributions des variables sont nettement non normales ou de variances très inégales. Différentes estimations des taux d'erreur ont également été comparées : resubstitutin, extraction-insertion et utilisation d'un échantillon-test. Les résultats ont montré que, par rapport à l'utilisation d'échantillons-tests, la méthode de resubstitution sous-estime le taux d'erreur. Cette sous-estimation est de l'ordre de 13 % du taux d'erreur réel. La méthode d'extraction-insertion donne par contre des résultats très semblables à la méthode utilisant un échantillon-test