QAPgrid: A Two Level QAP-Based Approach for Large-Scale Data Analysis and Visualization

Background: The visualization of large volumes of data is a computationally challenging task that often promises rewarding new insights. There is great potential in the application of new algorithms and models from combinatorial optimisation. Datasets often contain “hidden regularities” and a combined identification and visualization method should reveal these structures and present them in a way that helps analysis. While several methodologies exist, including those that use non-linear optimization algorithms, severe limitations exist even when working with only a few hundred objects. Methodology/Principal Findings: We present a new data visualization approach (QAPgrid) that reveals patterns of similarities and differences in large datasets of objects for which a similarity measure can be computed. Objects are assigned to positions on an underlying square grid in a two-dimensional space. We use the Quadratic Assignment Problem (QAP) as a mathematical model to provide an objective function for assignment of objects to positions on the grid. We employ a Memetic Algorithm (a powerful metaheuristic) to tackle the large instances of this NP-hard combinatorial optimization problem, and we show its performance on the visualization of real data sets. Conclusions/Significance: Overall, the results show that QAPgrid algorithm is able to produce a layout that represents the relationships between objects in the data set. Furthermore, it also represents the relationships between clusters that are feed into the algorithm. We apply the QAPgrid on the 84 Indo-European languages instance, producing a near-optimal layout. Next, we produce a layout of 470 world universities with an observed high degree of correlation with the score used by the Academic Ranking of World Universities compiled in the The Shanghai Jiao Tong University Academic Ranking of World Universities without the need of an ad hoc weighting of attributes. Finally, our Gene Ontology-based study on Saccharomyces cerevisiae fully demonstrates the scalability and precision of our method as a novel alternative tool for functional genomics

Transfer Synchronization of Public Transport Networks

Transfers in public transport, especially in bus operations, are used to create a more efficient network by the reduction of operational costs and the allowance of more flexible route planning. However, because of the stochastic nature of traffic, scheduled transfers do not always occur; this situation increases the total passenger travel time and reduces the attractiveness of the public transport service. The use of selected operational tactics in public transport networks for increasing the actual occurrence of scheduled transfers was analyzed. A model was developed to determine the impact that instructing vehicles to either hold at or skip certain stops had on total passenger travel time and the number of simultaneous transfers. The model consisted of two components. First, a simulation of a public transport network examined the two tactics for maximizing the number of transfers. Second, an ILOG optimization model was used for optimal determination of the combination of the two tactics to achieve the maximum number of simultaneous transfers. A bus network was created as a case study, in Auckland, New Zealand, to verify the impact of the model\u27s application. Results showed that applying online operational tactics dramatically improved the frequency of simultaneous transfers by more than 100%. The concept has great potential for increasing the efficiency and attractiveness of public transport networks that involve scheduled transfers

Novel Immunoblot Assay Using Four Recombinant Antigens for Diagnosis of Epstein-Barr Virus Primary Infection and Reactivation

ABSTRACT A new immunoblot assay, composed of four Epstein-Barr virus (EBV)-encoded recombinant proteins (virus capsid antigen [VCA] p23, early antigen [EA] p138, EA p54, and EBNA-1 p72), was compared with an immunofluorescence assay on a total of 291 sera. The test was accurate in 94.5% of cases of primary EBV infection, while an immunoglobulin G anti-VCA p23 band with strong intensity correlated with reactivation.</jats:p

New Order-Based Crossovers for the Graph Coloring Problem

Huge color class redundancy makes the graph coloring problem (GCP) very challenging for genetic algorithms (GAs), and designing effective crossover operators is notoriously difficult. Thus, despite the predominance of population based methods, crossover plays a minor role in many state-of-the-art approaches to solving the GCP. Two main encoding methods have been adopted for heuristic and GA methods: direct encoding, and order based encoding. Although more success has been achieved with direct approaches, algorithms using an order based representation have one powerful advantage: every chromosome decodes as a feasible solution. This paper introduces some new order based crossover variations and demonstrates that they are much more effective on the GCP than other order based crossovers taken from the literature

A Critical Element-Guided Perturbation Strategy for Iterated Local Search

Abstract. In this paper, we study the perturbation operator of Iterated Local Search. To guide more efficiently the search to move towards new promising regions of the search space, we introduce a Critical Element-Guided Perturbation strategy (CEGP). This perturbation approach consists of the identification of critical elements and then focusing on these critical elements within the perturbation operator. Computational experiments on two case studies—graph coloring and course timetabling—give evidence that this critical element-guided perturbation strategy helps reinforce the performance of Iterated Local Search

Towards a common definition of surgical prehabilitation: a scoping review of randomised trials

BACKGROUND: There is no universally accepted definition for surgical prehabilitation. The objectives of this scoping review were to (1) identify how surgical prehabilitation is defined across randomised controlled trials and (2) propose a common definition. METHODS: The final search was conducted in February 2023 using MEDLINE, Embase, PsycINFO, Web of Science, CINAHL, and Cochrane. We included randomised controlled trials (RCTs) of unimodal or multimodal prehabilitation interventions (nutrition, exercise, and psychological support) lasting at least 7 days in adults undergoing elective surgery. Qualitative data were analysed using summative content analysis. RESULTS: We identified 76 prehabilitation trials of patients undergoing abdominal (n=26, 34%), orthopaedic (n=20, 26%), thoracic (n=14, 18%), cardiac (n=7, 9%), spinal (n=4, 5%), and other (n=5, 7%) surgeries. Surgical prehabilitation was explicitly defined in more than half of these RCTs (n=42, 55%). Our findings consolidated the following definition: 'Prehabilitation is a process from diagnosis to surgery, consisting of one or more preoperative interventions of exercise, nutrition, psychological strategies and respiratory training, that aims to enhance functional capacity and physiological reserve to allow patients to withstand surgical stressors, improve postoperative outcomes, and facilitate recovery.' CONCLUSIONS: A common definition is the first step towards standardisation, which is needed to guide future high-quality research and advance the field of prehabilitation. The proposed definition should be further evaluated by international stakeholders to ensure that it is comprehensive and globally accepted