Paradoxical exploitation of protected fishes as bait for anglers: evaluating the lamprey bait market in Europe and developing sustainable and ethical solutions

A reoccurring conservation problem is the resolution of consumptive use of threatened wildlife and is especially difficult to defend when it occurs for recreational practices. We explored the commercial capture and supply of threatened European river lamprey (Lampetra fluviatilis) to anglers, to determine the extent of exploitation and seek opportunities for improved conservation. The trade began in 1995 from England, but by 2012 involved sale of lamprey from England, The Netherlands and Estonia, including from protected populations. Lamprey are sold frozen for the capture of predatory fish, mostly in freshwater. In the year 2011/2012 9 tonnes (>90,000 lampreys) of river lamprey were supplied, almost exclusively to British anglers. Although annual catches in the main English lamprey fishery (River Ouse) have varied widely since 1995, catch per unit effort did not decline between 2000 and 2012. Conservation actions since 2011 have included a cap on fishing licenses, catch quotas and restricted fishing seasons. Now, 86% of lamprey bait is imported to Britain. Most bait sellers interviewed would not stock lamprey if they knew they were from threatened populations; many felt their trade would not be impacted if lamprey were not stocked. This facilitates opportunities to enter into dialogue with anglers over alternative baits to threatened lamprey. The study emphasises the need to inform stakeholders about conservation species subjected to market-driven exploitation

Multipartite entanglement measures via Bell basis measurements

We show how to estimate a broad class of multipartite entanglement measures from Bell basis measurement data. In addition to lowering the experimental requirements relative to previously known methods of estimating these measures, our proposed scheme also enables a simpler analysis of the number of measurement repetitions required to achieve an $\epsilon$-close approximation of the measures, which we provide for each. We focus our analysis on the recently introduced Concentratable Entanglements [Beckey et al. Phys. Rev. Lett. 127, 140501 (2021)] because many other well-known multipartite entanglement measures are recovered as special cases of this family of measures. We extend the definition of the Concentratable Entanglements to mixed states and show how to construct lower bounds on the mixed state Concentratable Entanglements that can also be estimated using only Bell basis measurement data. Finally, we demonstrate the feasibility of our methods by realistically simulating their implementation on a Rydberg atom quantum computer.Comment: 5+19 pages. 4+3 figure

Generalized Buneman pruning for inferring the most parsimonious multi-state phylogeny

Accurate reconstruction of phylogenies remains a key challenge in evolutionary biology. Most biologically plausible formulations of the problem are formally NP-hard, with no known efficient solution. The standard in practice are fast heuristic methods that are empirically known to work very well in general, but can yield results arbitrarily far from optimal. Practical exact methods, which yield exponential worst-case running times but generally much better times in practice, provide an important alternative. We report progress in this direction by introducing a provably optimal method for the weighted multi-state maximum parsimony phylogeny problem. The method is based on generalizing the notion of the Buneman graph, a construction key to efficient exact methods for binary sequences, so as to apply to sequences with arbitrary finite numbers of states with arbitrary state transition weights. We implement an integer linear programming (ILP) method for the multi-state problem using this generalized Buneman graph and demonstrate that the resulting method is able to solve data sets that are intractable by prior exact methods in run times comparable with popular heuristics. Our work provides the first method for provably optimal maximum parsimony phylogeny inference that is practical for multi-state data sets of more than a few characters.Comment: 15 page

Using Participatory Design to Develop a Menstrual Hygiene Management Intervention: Designing WASH UP! Girl Talk in Zimbabwe

Globally, as more girls transition from primary to secondary education, there is a new generation of girls who will have to manage their menses in school environments. Few schools are designed with girls’ menstrual hygiene management (MHM) needs in mind and many girls begin menstruating without knowing what is happening to them. This lack of knowledge about menstruation is associated with profound psychological and reproductive health issues. As such, school-based WASH interventions, especially those focused on MHM, can improve educational opportunities, promote lifelong health, and enhance the wellbeing of children and their families. In Zimbabwe, these global realities hold true, where menstruation is a taboo subject and girls find it difficult to access accurate information and are unable to manage their menstruation safely, hygienically, and with dignity and privacy. An effective solution to these challenges must address school infrastructure concerns and limitations in knowledge, attitudes, and practices around MHM. In response, Sesame Workshop, in collaboration with World Vision, launched WASH UP! Girl Talk in Zimbabwe, targeting students 10-14 years old. Girl Talk involved the development and implementation of an intervention aimed at improving students’ knowledge and practice of healthy hygiene behaviors. Girl Talk also focused on increasing girls’ confidence in their personal MHM. This article highlights the development of Girl Talk and its focus on participatory design to standardize a curriculum framework, implementation process, and research approach to contextualize education content. This process of program design, grounded in the intersections of best practices and local knowledge, provides both a conceptual and practical framework to inform future MHM interventions

Classifying the precancers: A metadata approach

BACKGROUND: During carcinogenesis, precancers are the morphologically identifiable lesions that precede invasive cancers. In theory, the successful treatment of precancers would result in the eradication of most human cancers. Despite the importance of these lesions, there has been no effort to list and classify all of the precancers. The purpose of this study is to describe the first comprehensive taxonomy and classification of the precancers. As a novel approach to disease classification, terms and classes were annotated with metadata (data that describes the data) so that the classification could be used to link precancer terms to data elements in other biological databases. METHODS: Terms in the UMLS (Unified Medical Language System) related to precancers were extracted. Extracted terms were reviewed and additional terms added. Each precancer was assigned one of six general classes. The entire classification was assembled as an XML (eXtensible Mark-up Language) file. A Perl script converted the XML file into a browser-viewable HTML (HyperText Mark-up Language) file. RESULTS: The classification contained 4700 precancer terms, 568 distinct precancer concepts and six precancer classes: 1) Acquired microscopic precancers; 2) acquired large lesions with microscopic atypia; 3) Precursor lesions occurring with inherited hyperplastic syndromes that progress to cancer; 4) Acquired diffuse hyperplasias and diffuse metaplasias; 5) Currently unclassified entities; and 6) Superclass and modifiers. CONCLUSION: This work represents the first attempt to create a comprehensive listing of the precancers, the first attempt to classify precancers by their biological properties and the first attempt to create a pathologic classification of precancers using standard metadata (XML). The classification is placed in the public domain, and comment is invited by the authors, who are prepared to curate and modify the classification