Combining column generation and Lagrangean relaxation : an application to a single-machine common due date scheduling problem

Column generation has proved to be an effective technique for solving the linear programming relaxation of huge set covering or set partitioning problems, and column generation approaches have led to state-of-the-art so-called branch-and-price algorithms for various archetypical combinatorial optimization problems. Usually, if Lagrangean relaxation is embedded at all in a column generation approach, then the Lagrangean bound serves only as a tool to fathom nodes of the branch-and-price tree. We show that the Lagrangean bound can be exploited in more sophisticated and effective ways for two purposes: to speed up convergence of the column generation algorithm and to speed up the pricing algorithm. Our vehicle to demonstrate the effectiveness of teaming up column generation with Lagrangean relaxation is an archetypical single-machine common due date scheduling problem. Our comprehensive computational study shows that the combined algorithm is by far superior to two existing purely column generation algorithms: it solves instances with up to 125 jobs to optimality, while purely column generation algorithm can solve instances with up to only 60 jobs

Learning emotions in virtual environments

A modular hybrid neural network architecture, called SHAME, for emotion learning is introduced. The system learns from annotated data how the emotional state is generated and changes due to internal and external stimuli. Part of the modular architecture is domain independent and part must be\ud adapted to the domain under consideration.\ud The generation and learning of emotions is based on the event appraisal model.\ud The architecture is implemented in a prototype consisting of agents trying to survive in a virtual world. An evaluation of this prototype shows that the architecture is capable of\ud generating natural emotions and furthermore that training of the neural network modules in the architecture is computationally feasible.\ud Keywords: hybrid neural systems, emotions, learning, agents

Elckerlyc goes mobile - Enabling natural interaction in mobile user interfaces

The fast growth of computational resources and speech technology available on mobile devices makes it possible to entertain users of these devices in having a natural dialogue with service systems. These systems are sometimes perceived as social agents and this can be supported by presenting them on the interface by means of an animated embodied conversational agent. To take the full advantage of the power of embodied conversational agents in service systems it is important to support real-time, online and responsive interaction with the system through the embodied conversational agent. The design of responsive animated conversational agents is a daunting task. Elckerlyc is a model-based platform for the speci﬿cation and animation of synchronised multi-modal responsive animated agents. This paper presents a new light-weight PictureEngine that allows to run this platform in mobile applications. We describe the integration of the PictureEngine in the user interface of two different coaching applications and discuss the ﬿ndings from user evaluations. We also conducted a study to evaluate an editing tool for the speci﬿cation of the agent’s communicative behaviour. Twenty one participants had to specify the behaviour of an embodied conversational agent using the PictureEngine. We may conclude that this new lightweight back-end engine for the Elckerlyc platform makes it easier to build embodied conversational interfaces for mobile devices

User preferences for multi-device context-aware feedback in a digital coaching system

We present the development of the user interfaces of a multi-device digital coaching service that provides tailored feedback to users concerning their physical activity level and medication intake. We present the outcomes of a survey study of user preferences regarding the situation, device and timing of feedback they receive from their personal attentive digital coach. There are clear preferences among the subjects for different types of messages on different devices. Results were implemented in a first prototype. We present the results of a user evaluations with a real version of the digital health coach and we compare them with the results of the survey study

Systematic evaluation of corticosteroid use in obese and non-obese individuals: A multi-cohort study

Background: Although the use of corticosteroids has been linked to high incidence of weight gain, no data are available concerning the differences in corticosteroid use between a diverse obese population and non-obese individuals. The main purpose of this study was to systematically explore t

Extensive Phenotyping for Potential Weight-Inducing Factors in an Outpatient Population with Obesity

Background: Obesity has been associated with miscellaneous weight-inducing determinants. A comprehensive assessment of known obesity-related factors other than diet and physical activity within one cohort is currently lacking. Objectives: To assess the prevalence of potential contributors to obesity and self-reported triggers for marked weight gain in an adult population with obesity and between obesity classes. Methods: In this observational cohort study, we assessed 408 persons with obesity (aged 41.3 ± 14.2 years, BMI 40.5 ± 6.2) visiting our obesity clinic. They were evaluated for use of weight-inducing drugs, hormonal abnormalities, menarcheal age, (high) birth weight, sleep deprivation, and obstructive sleep apnea syndrome (OSAS). We additionally assessed self-reported triggers for marked weight gain and performed genetic testing in patients suspected of genetic obesity. Results: Nearly half of the patients were using a potentially weight-inducing drug, which was also the most reported trigger for marked weight gain. For the assessed hormonal conditions, a relatively high prevalence was found for hypothyroidism (14.1%), polycystic ovary syndrome (12.0%), and male hypogonadism (41.7%). A relatively low average menarcheal age (12.6 ± 1.8 years) was reported, whereas there was a high prevalence of a high birth weight (19.5%). Sleep deprivation and OSAS were reported in, respectively, 14.5 and 13.7% of the examined patients. Obesity class appeared to have no influence on the majority of the assessed factors. Of the genetically analyzed patients, a definitive genetic diagnosis was made in 3 patients (1.9%). Conclusions: A thorough evaluation of patients with obesity yields a relatively high prevalence of various potentially weight-inducing factors. Diagnostic screening of patients with obesi

A γ-lactam siderophore antibiotic effective against multidrug-resistant Pseudomonas aeruginosa, Klebsiella pneumoniae, and Acinetobacter spp.

Serious infections caused by multidrug-resistant (MDR) organisms (Klebsiella pneumoniae, Pseudomonas aeruginosa, Acinetobacter baumannii) present a critical need for innovative drug development. Herein, we describe the preclinical evaluation of YU253911, 2, a novel γ-lactam siderophore antibiotic with potent antimicrobial activity against MDR Gram-negative pathogens. Penicillin-binding protein (PBP) 3 was shown to be a target of 2 using a binding assay with purified P. aeruginosa PBP3. The specific binding interactions with P. aeruginosa were further characterized with a high-resolution (2.0 Å) X-ray structure of the compound's acylation product in P. aeruginosa PBP3. Compound 2 was shown to have a concentration >1 μg/ml at the 6 h time point when administered intravenously or subcutaneously in mice. Employing a meropenem resistant strain of P. aeruginosa, 2 was shown to have dose-dependent efficacy at 50 and 100 mg/kg q6h dosing in a mouse thigh infection model. Lastly, we showed that a novel γ-lactam and β-lactamase inhibitor (BLI) combination can effectively lower minimum inhibitory concentrations (MICs) against carbapenem resistant Acinetobacter spp. that demonstrated decreased susceptibility to 2 alone

Identification of TGFβ-related genes regulated in murine osteoarthritis and chondrocyte hypertrophy by comparison of multiple microarray datasets

Objective: Osteoarthritis (OA) is a joint disease characterized by progressive degeneration of articular cartilage. Some features of OA, including chondrocyte hypertrophy and focal calcification of articular cartilage, resemble the endochondral ossification processes. Alterations in transforming growth factor β (TGFβ) signaling have been associated with OA as well as with chondrocyte hypertrophy. Our aim was to identify novel candidate genes implicated in chondrocyte hypertrophy during OA pathogenesis by determining which TGFβ-related genes are regulated during murine OA and endochondral ossification. Methods: A list of 580 TGFβ-related genes, including TGFβ signaling pathway components and TGFβ-target genes, was generated. Regulation of these TGFβ-related genes was a