Constructing computer virus phylogenies

There has been much recent algorithmic work on the problem of reconstructing the evolutionary history of biological species. Computer virus specialists are interested in finding the evolutionary history of computer viruses - a virus is often written using code fragments from one or more other viruses, which are its immediate ancestors. A phylogeny for a collection of computer viruses is a directed acyclic graph whose nodes are the viruses and whose edges map ancestors to descendants and satisfy the property that each code fragment is "invented" only once. To provide a simple explanation for the data, we consider the problem of constructing such a phylogeny with a minimum number of edges. In general this optimization problem is NP-complete; some associated approximation problems are also hard, but others are easy. When tree solutions exist, they can be constructed and randomly sampled in polynomial time

Tolerating the Community Detection Resolution Limit with Edge Weighting

Communities of vertices within a giant network such as the World-Wide Web are likely to be vastly smaller than the network itself. However, Fortunato and Barth\'{e}lemy have proved that modularity maximization algorithms for community detection may fail to resolve communities with fewer than $\sqrt{L/2}$ edges, where $L$ is the number of edges in the entire network. This resolution limit leads modularity maximization algorithms to have notoriously poor accuracy on many real networks. Fortunato and Barth\'{e}lemy's argument can be extended to networks with weighted edges as well, and we derive this corollary argument. We conclude that weighted modularity algorithms may fail to resolve communities with fewer than $\sqrt{W \epsilon/2}$ total edge weight, where $W$ is the total edge weight in the network and $\epsilon$ is the maximum weight of an inter-community edge. If $\epsilon$ is small, then small communities can be resolved. Given a weighted or unweighted network, we describe how to derive new edge weights in order to achieve a low $\epsilon$, we modify the ``CNM'' community detection algorithm to maximize weighted modularity, and show that the resulting algorithm has greatly improved accuracy. In experiments with an emerging community standard benchmark, we find that our simple CNM variant is competitive with the most accurate community detection methods yet proposed.Comment: revision with 8 pages 3 figures 2 table

Water, sanitation and hygiene at sex work venues to support menstrual needs

Introduction: Adequate menstrual health and hygiene (MHH) is necessary for women’s health and equity of all menstruators. Female sex workers (FSW) require good MHH to prevent discomfort and exposure to pathogens. No studies have evaluated water, sanitation, and hygiene (WASH) conditions of FSW. We report on a cross-sectional WASH assessment at FSW venues in Kisumu, western Kenya. Methods: Stakeholders identified 77 FSW venues in Kisumu, of which 47 were randomly sampled and visited between April-May 2023. A standardized structured survey of WASH conditions was deployed by trained research staff using Android tablets after proprietor’s consent. WASH scores ranging 0 – 3 were computed based on point each for direct observation of water available, soap available, and acceptable latrine. MHH scores ranging between 0-4 were computed (one point each) for direct observation of: currently available soap and water, locking door on a usable latrine, functional lighting, and a private area for changing clothes or menstrual materials, separate from the latrine(s). WASH and MHH scores were compared by venue type using non-parametric Kruskal-Wallis tests, and non-parametric Spearman rank tests. Results: Full WASH criteria was met by 29.8% of venues; 34.0% had no adequate WASH facilities; 46.8% had no female latrine, and 25.5% provided soap and water in private spaces for women. While 76.6% had menstrual waste disposal only 14 (29.8%) had covered bins. One in 10 venues provided adequate MHM facilities. Poorest WASH facilities were in brothels and in bars, and three-quarters of bars with accommodation had no MHH facilities. Discussion: WASH and MHH services were sub-optimal in the majority of FSW venues, preventing menstrual management safely, effectively, with dignity and privacy. This study highlights the unmet need for MHH support for this population. Poor MHH can deleteriously impact FSW health and wellbeing and compound the stigma and shame associated with their work and ability to stay clean. Acceptable and cost-effective solutions to sustainably improve WASH facilities for these populations are needed