Hyper-heuristics comprise a set of approaches that are motivated (at least in part) by the goal of automating the design of heuristic methods to solve hard computational search problems. An underlying strategic research challenge is to develop more generally applicable search methodologies. The term hyper-heuristic is relatively new; it was first used in 2000 to describe heuristics to choose heuristics in the context of combinatorial optimisation. However, the idea of automating the design of heuristics is not new; it can be traced back to the 1960s. The definition of hyper-heuristics has been recently extended to refer to a search method or learning mechanism for selecting or generating heuristics to solve computational search problems. Two main hyper-heuristic categories can be considered: heuristic selection and heuristic generation. The distinguishing feature of hyper-heuristics is that they operate on a search space of heuristics (or heuristic components) rather than directly on the search space of solutions to the underlying problem that is being addressed. This paper presents a critical discussion of the scientific literature on hyper-heuristics including their origin and intellectual roots, a detailed account of the main types of approaches, and an overview of some related areas. Current research trends and directions for future research are also discussed.

Since December 2019, novel coronavirus infected pneumonia emerged in Wuhan city and rapidly spread throughout China. In severe novel coronavirus pneumonia cases, the number of platelets, their dynamic changes during the treatment, platelet-to-lymphocyte ratio (PLR) were a concern. We sought to describe the platelet feature of these cases. Single-center case series of the 30 hospitalized patients with confirmed coronavirus disease (COVID)-19 in Huizhou municipal central hospital from January 2020 to February 2020 were retrospectively analyzed.Demographic, clinical, blood routine results, other laboratory results, and treatment data were collected and analyzed. Outcomes of severe patients and nonsevere patients were compared. Univariate analysis showed that: age, platelet peaks, and PLR at peak platelet were the influencing factors in severe patients, multivariate analysis showed that the PLR value at peak platelet during treatment was an independent influencing factor in severe patients. The average hospitalization day of patients with platelet peaks during treatment was longer than those without platelet peaks (P < .05). The average age of patients with platelet peaks during treatment was older than those without platelet peaks (P < .05). The patients with significantly elevated platelets during treatment had longer average hospitalization days. And the higher PLR of patients during treatment had longer average hospitalization days.Single-center case series of the 30 hospitalized patients with confirmed in Huizhou Municipal Central Hospital, presumed that the number of platelets and their dynamic changes during the treatment may have a suggestion on the severity and prognosis of the disease. The patient with markedly elevated platelets and longer average hospitalization days may be related to the cytokine storm. The PLR Rong Qu, Yun Ling, and Yi-hui-zhi Zhang are the co-first authors.

Examination timetabling is one of the most important administrative activities that takes place in all academic institutions. In this paper, we present a critical discussion of the research on exam timetabling which has taken place in the last decade or so. This last ten years has seen a significantly increased level of research attention for this important area. There has been a range of insightful contributions to the scientific literature both in terms of theoretical issues and practical aspects. The main aim of this survey is to highlight the new trends and key research achievements that have been carried out in the last decade. We also aim to outline a range of relevant important research issues and challenges that have been generated by this body of work. We first define the problem and discuss previous survey papers. Within our presentation of the state-of-the-art methodologies, we highlight recent research trends including hybridisations of search methodologies and the development of techniques which are motivated by raising the level of generality at which search methodologies can operate. Summarising tables are presented to provide an overall view of these techniques. We also present and discuss some important issues which have come to light concerning the public benchmark exam timetabling data. Different versions of problem datasets with the same name have been circulating in the scientific community for the last ten years and this has generated a significant amount of confusion. We clarify the situation and present a re-naming of the widely studied datasets to avoid future confusion. We also highlight which research papers have dealt with which dataset. Finally, we draw upon our discussion of the literature to present a (non-exhaustive) range of potential future research directions and open issues in exam timetabling research

This paper presents an investigation of a simple generic hyper-heuristic approach upon a set of widely used constructive heuristics (graph coloring heuristics) in timetabling. Within the hyperheuristic framework, a Tabu Search approach is employed to search for permutations of graph heuristics which are used for constructing timetables in exam and course timetabling problems. This underpins a multi-stage hyper-heuristic where the Tabu Search employs permutations upon a different number of graph heuristics in two stages. We study this graph-based hyper-heuristic approach within the context of exploring fundamental issues concerning the search space of the hyper-heuristic (the heuristic space) and the solution space. Such issues have not been addressed in other hyper-heuristic research. These approaches are tested on both exam and course benchmark timetabling problems and are compared with the fine-tuned bespoke state-of-the-art approaches. The results are within the range of the best results reported in the literature. The approach described here represents a significantly more generally applicable approach than the current state of the art in the literature. Future work will extend this hyper-heuristic framework by employing methodologies which are applicable on a wider range of timetabling and scheduling problems.

TNF-alpha is present early in a model of large myocardial infarction and is sustained into the later stage within the myocardium. Expression of this cytokine is not only confined strictly to the infarct or peri-infarct zone but is expressed by cardiac myocytes within the myocardium contralateral to the infarct. Therefore TNF-alpha production forms a part of an important intrinsic myocardial stress response system to injury.