The Best-or-Worst and the Postdoc problems

We consider two variants of the secretary problem, the\emph{ Best-or-Worst} and the \emph{Postdoc} problems, which are closely related. First, we prove that both variants, in their standard form with binary payoff 1 or 0, share the same optimal stopping rule. We also consider additional cost/perquisites depending on the number of interviewed candidates. In these situations the optimal strategies are very different. Finally, we also focus on the Best-or-Worst variant with different payments depending on whether the selected candidate is the best or the worst

Well rounded Postdoctoral Researchers with initiative, who are not always “tied to the bench” are more successful academically

This article reports the development, application and results of a baseline investigation of contract research staff in 2007 in the Medical School at the University of Sheffield which was carried out in order to develop a specifically tailored training and career development programme and allow for future impact evaluation of the scheme. Postdoctoral researchers reported on their perceived skill levels, academic achievements, career motivations and the current research environment. Results indicated that transferable skills related to communication and awareness of the process of research (i.e. the process of acquisition of funding, commercialisation of research outputs) were lacking. Furthermore, these skills were associated with higher publication outputs, and improved with mobility between institutions at postdoctoral level. This paper also describes how the findings from the baseline evaluation were used to develop a programme to address the lower ranking skills and evaluate the impact of the programme

Novel Artificial Human Optimization Field Algorithms - The Beginning

New Artificial Human Optimization (AHO) Field Algorithms can be created from scratch or by adding the concept of Artificial Humans into other existing Optimization Algorithms. Particle Swarm Optimization (PSO) has been very popular for solving complex optimization problems due to its simplicity. In this work, new Artificial Human Optimization Field Algorithms are created by modifying existing PSO algorithms with AHO Field Concepts. These Hybrid PSO Algorithms comes under PSO Field as well as AHO Field. There are Hybrid PSO research articles based on Human Behavior, Human Cognition and Human Thinking etc. But there are no Hybrid PSO articles which based on concepts like Human Disease, Human Kindness and Human Relaxation. This paper proposes new AHO Field algorithms based on these research gaps. Some existing Hybrid PSO algorithms are given a new name in this work so that it will be easy for future AHO researchers to find these novel Artificial Human Optimization Field Algorithms. A total of 6 Artificial Human Optimization Field algorithms titled "Human Safety Particle Swarm Optimization (HuSaPSO)", "Human Kindness Particle Swarm Optimization (HKPSO)", "Human Relaxation Particle Swarm Optimization (HRPSO)", "Multiple Strategy Human Particle Swarm Optimization (MSHPSO)", "Human Thinking Particle Swarm Optimization (HTPSO)" and "Human Disease Particle Swarm Optimization (HDPSO)" are tested by applying these novel algorithms on Ackley, Beale, Bohachevsky, Booth and Three-Hump Camel Benchmark Functions. Results obtained are compared with PSO algorithm.Comment: 25 pages, 41 figure

University departments evaluation: a multivariate approach

Aim of the paper is to present a new model, based on multivariate statistic analyses, allowing to express a synthetic judgement on Departments activities by taking into consideration the whole set of indicators describing them both as aggregations of researchers and as University autonomous organs. The model, based on Principal Component Analysis and Cluster Analysis, allows both to explain the determinants of Departments performances, and to classify them into homogeneous groups. The paper shows the results obtained by testing the proposed model on University of Naples “L’Orientale” Departments, using data extracted by the 2007 assessment report to the Ministry of University and Research.Evaluation, Departments, Multivariate statistics

Shifting landscapes: from coalface to quick sand? Teaching geography, earth and environmental sciences in UK higher education

In this paper we examine contemporary academic working lives, with particular reference to teaching-only and teaching-focused academics. We argue that intensification in the neoliberal university has significantly shifted the structure of academic careers, while cultural stories about those careers have not changed. We call for academics to re-examine our collective stories about standard academic career paths. Challenging the stories and making visible the ways that they create and multiply disadvantage is a crucial step in expanding the possibilities for academic identities and careers. The paper begins by describing teaching-focused academics within the context of the wider workforce. We then draw on narratives of those in these roles to illustrate the processes that (re)inscribe their marginalisation. We uncover the gendering of the teaching-focused academic labour market. We end the paper by suggesting interventions that all academics can take and support to address the issues we highlight