All Inequalities for the Relative Entropy

The relative entropy of two n-party quantum states is an important quantity exhibiting, for example, the extent to which the two states are different. The relative entropy of the states formed by reducing two n-party to a smaller number $m$ of parties is always less than or equal to the relative entropy of the two original n-party states. This is the monotonicity of relative entropy. Using techniques from convex geometry, we prove that monotonicity under restrictions is the only general inequality satisfied by relative entropies. In doing so we make a connection to secret sharing schemes with general access structures. A suprising outcome is that the structure of allowed relative entropy values of subsets of multiparty states is much simpler than the structure of allowed entropy values. And the structure of allowed relative entropy values (unlike that of entropies) is the same for classical probability distributions and quantum states.Comment: 15 pages, 3 embedded eps figure

Bilevel optimization approach to design of network of bike lanes

A bike lane is an effective way to improve cycling safety and to decrease greenhouse gas emissions with the promotion of cycling. Improvements include high-quality off-road facilities and on-road bike lanes. Whereas construction of off-road lanes is not always possible because of urban land constraints and construction costs, on-road lanes can be a cost-effective alternative. An optimization framework for the design of a network of bike lanes in an urban road network was proposed. This framework identified links on which a bike lane could be introduced. Allocation of a lane to cyclists would increase the use of cycling, although it could disadvantage auto traffic. The presented approach balances the effects of a bike lane for all stakeholders. A bilevel optimization was proposed to encompass the benefits of cyclists and car users at the upper level and a model for traffic and bike demand assignment at the lower level. The objective function was defined by a weighted sum of a measure for private car users (total travel time) versus a measure for bike users (total travel distance on bike lanes). A genetic algorithm was developed to solve the bilevel formulation, which included introduction of a special crossover technique and a mutation technique. The proposed optimization will help transport authorities at the planning stage to quantify the outcomes of various strategies for active transport

Reducing pain in children with cancer: Methodology for the development of a clinical practice guideline

Abstract Although pain is one of the most prevalent and bothersome symptoms children with cancer experience, evidence-based guidance regarding assessment and management is lacking. With 44 international, multidisciplinary healthcare professionals and nine patient representatives, we aimed to develop a clinical practice guideline (following GRADE methodology), addressing assessment and pharmacological, psychological, and physical management of tumor-, treatment-, and procedure-related pain in children with cancer. In this paper, we present our thorough methodology for this development, including the challenges we faced and how we approached these. This lays the foundation for our clinical practice guideline, for which there is a high clinical demand

Non-Adaptive Complex Group Testing with Multiple Positive Sets

Given n items with at most d of them having a particular property (referred as positive items), a test on a selected subset of them is positive if and only if the subset contains at least one positive item. The non-adaptive group testing problem is to design how to group the items to minimize the number of tests required to identify all positive items in which all tests are performed in parallel. This problem is well-studied and algorithms exist that match the lower bound with a small gap of log d asymptoticically. An important generalization of the problem is to consider the case that individual positive item cannot make a test positive, but a combination of them (referred as positive subsets) can do. The problem is referred as the non-adaptive complex group testing. Assume there are at most d positive subsets whose sizes are at most s, existing algorithms either require Ω(log s n) tests for general n or O ( () s+d log n) tests for some special values of n. However, the number d of items in each test cannot be very small or very large in real situation. The above algorithms cannot be applied because there is no control on the number of items in each test. In this paper, we provide a novel and practical derandomized algorithm to construct the tests with two important properties. (1) Our algorithm requires only O ( (d + s) d+s+1 /(ddss) log n) tests for all positive integers n which matches the upper bound on the number of tests when all positive subsets are singletons, i.e. s = 1. (2) All tests in our algorithm can have the same number of tested items k. Thus, our algorithm can solve the problem with additional constraints on the number of tested items in each test, such as maximum or minimum number of tested items

Retreat from Alma Ata?: the WHO's report on task shifting to community health workers for AIDS care in poor countries

This paper examines the potential of community health worker (CHW) programmes, as proposed by the 2008 World Health Organisation (WHO) document Task Shifting to tackle health worker shortages, to contribute to HIV/AIDS prevention and treatment and various Millennium Development Goals in low-income countries. It examines the WHO proposal through a literature review of factors that have facilitated the success of previous CHW experiences. The WHO has taken account of five key lessons learnt from past CHW programmes (the need for strong management, appropriate selection, suitable training, adequate retention structures and good relationships with other healthcare workers). It has, however, neglected to emphasise the importance of a sixth lesson, the 'community embeddedness' of CHWs, found to be of critical importance to the success of past CHW programmes. We have no doubt that the WHO plans will increase the number of workers able to perform medically oriented tasks. However, we argue that without community embeddedness, CHWs will be unable to successfully perform the socially oriented tasks assigned to them by the WHO, such as health education and counselling. We locate the WHO's neglect of community embeddedness within the context of a broader global public health trend away from community-focused primary healthcare towards biomedically focused selective healthcare