Towards Sustainable Co-Management of Mekong River Inland Aquatic Resources, Including Fisheries, in Southern Lao PDR

This paper presents historical information regarding the development of the aquatic resource co-management system in Khong District, Champasak Province, Southern Lao PDF. Between 1993 and 1998, 63 villages in Khong District established co-management regulations to sustainably manage and conserve inland aquatic resources, including fisheries, in the Mekong River, streams, backwater wetlands, and rice paddy fields. Local government has endorsed these regulations, but villages have been given the mandate to choose what regulations to adopt based on local conditions and community consensus. Communities are also empowered to alter regulations in response to changing circumstances. Villagers have widely reported increased fish catches since the adoption of aquatic resource co-management regulations. Improved solidarity and coordination within and between rural fishing and farming villages has also been observed. While many of the lessons learned from the co-management experience in Khong are applicable to other parts of Laos and the region, unique conditions in different areas will require inventive approaches to meet local needs. Common property regimes can break down in crisis, but experience in Khong indicates that they can also be strengthened in response to resource management crisis

Chao Fa Movies: The Transnational Production of Hmong American History and Identity

Films made by and for particular social and ethnic peoples can reveal a great deal about identity issues. Here, I examine the cultural production, the content, and the socio-cultural and political significance of three Chao Fa-inspired Hmong films produced at Khek Noi, Thailand by Hmong American producers working with largely Hmong Thai actors. The first two, Chao Fa 1 and 2, were directed in 2009 by Kou Thao. The third, Vaj Tuam Thawj – The Legend of Chao Fa, was put together by Jimmy Vang, in 2010. Even though these Chao Fa films are fictional, they attempt to depict events and circumstances that are familiar to many first generation Hmong Americans, and they can muster strong emotions from people who see them as depicting factual history. In addition, just like many other American youth, many 1.5 generation Hmong are tied together by shared media experiences, including Hmong movies. Thus, the Chao Fa movies are important for producing and reproducing, reinforcing and dispersing ideas related to Hmong American identity and culture. They tell stories of the Hmong being oppressed by many different groups, and this history suggests why many Hmong—not only the Chao Fa—have long desired the type of independence and freedom from prejudice and discrimination that they imagine would come if the Hmong only had their own nation state

Supervision and culture: Meetings at thresholds

Counsellors are required to engage in supervision in order to reflect on, reflexively review, and extend their practice. Supervision, then, might be understood as a partnership in which the focus of practitioners and supervisors is on ethical and effective practice with all clients. In Aotearoa/New Zealand, there has recently been interest in the implications for supervision of cultural difference, particularly in terms of the Treaty of Waitangi as a practice metaphor, and when non-Māori practitioners counsel Māori clients. This article offers an account of a qualitative investigation by a group of counsellors/supervisors into their experiences of supervision as cultural partnership. Based on interviews and then using writing-as-research, the article explores the playing out of supervision’s contribution to practitioners’ effective and ethical practice in the context of Aotearoa/New Zealand, showing a range of possible accounts and strategies and discussing their effects. Employing the metaphor of threshold, the article includes a series of reflections and considerations for supervision practice when attention is drawn to difference

No Exit? Withdrawal Rights and the Law of Corporate Reorganizations

Bankruptcy scholarship is largely a debate about the comparative merits of a mandatory regime on one hand and bankruptcy by free design on the other. By the standard account, the current law of corporate reorganization is mandatory. Various rules that cannot be avoided ensure that investors’ actions are limited and they do not exercise their rights against specialized assets in a way that destroys the value of a business as a whole. These rules solve collective action problems and reduce the risk of bargaining failure. But there are costs to a mandatory regime. In particular, investors cannot design their rights to achieve optimal monitoring as they could in a system of bankruptcy by free design. This Article suggests that the academic debate has missed a fundamental feature of the law. Bankruptcy operates on legal entities, not on firms in the economic sense. For this reason, sophisticated investors do not face a mandatory regime at all. The ability of investors to place assets in separate entities gives them the ability to create specific withdrawal rights in the event the firm encounters financial distress. There is nothing mandatory about rules like the automatic stay when assets can be partitioned off into legal entities that are beyond the reach of the bankruptcy judge. Thus, by partitioning assets of one economic enterprise into different legal entities, investors can create a tailored bankruptcy regime. In this way, legal entities serve as building blocks that can be combined to create specific and varied but transparent investor withdrawal rights. This regime of tailored bankruptcy has been unrecognized and underappreciated and may be preferable to both mandatory and free design regimes. By allowing a limited number of investors to opt out of bankruptcy in a particular, discrete, and visible way, investors as a group may be able to both limit the risk of bargaining failure and at the same time enjoy the disciplining effect that a withdrawal right brings with it

Logical Analysis of Data (LAD) model for the early diagnosis of acute ischemic stroke

<p>Abstract</p> <p>Background</p> <p>Strokes are a leading cause of morbidity and the first cause of adult disability in the United States. Currently, no biomarkers are being used clinically to diagnose acute ischemic stroke. A diagnostic test using a blood sample from a patient would potentially be beneficial in treating the disease.</p> <p>Results</p> <p>A classification approach is described for differentiating between proteomic samples of stroke patients and controls, and a second novel predictive model is developed for predicting the severity of stroke as measured by the National Institutes of Health Stroke Scale (NIHSS). The models were constructed by applying the Logical Analysis of Data (LAD) methodology to the mass peak profiles of 48 stroke patients and 32 controls. The classification model was shown to have an accuracy of 75% when tested on an independent validation set of 35 stroke patients and 25 controls, while the predictive model exhibited superior performance when compared to alternative algorithms. In spite of their high accuracy, both models are extremely simple and were developed using a common set consisting of only 3 peaks.</p> <p>Conclusion</p> <p>We have successfully identified 3 biomarkers that can detect ischemic stroke with an accuracy of 75%. The performance of the classification model on the validation set and on cross-validation does not deteriorate significantly when compared to that on the training set, indicating the robustness of the model. As in the case of the LAD classification model, the results of the predictive model validate the function constructed on our support-set for approximating the severity scores of stroke patients. The correlation and root mean absolute error of the LAD predictive model are consistently superior to those of the other algorithms used (Support vector machines, C4.5 decision trees, Logistic regression and Multilayer perceptron).</p

Identifying Highly Penetrant Disease Causal Mutations Using Next Generation Sequencing: Guide to Whole Process

Recent technological advances have created challenges for geneticists and a need to adapt to a wide range of new bioinformatics tools and an expanding wealth of publicly available data (e.g., mutation databases, and software). This wide range of methods and a diversity of file formats used in sequence analysis is a significant issue, with a considerable amount of time spent before anyone can even attempt to analyse the genetic basis of human disorders. Another point to consider that is although many possess “just enough” knowledge to analyse their data, they do not make full use of the tools and databases that are available and also do not fully understand how their data was created. The primary aim of this review is to document some of the key approaches and provide an analysis schema to make the analysis process more efficient and reliable in the context of discovering highly penetrant causal mutations/genes. This review will also compare the methods used to identify highly penetrant variants when data is obtained from consanguineous individuals as opposed to nonconsanguineous; and when Mendelian disorders are analysed as opposed to common-complex disorders

What is missing in autonomous discovery: Open challenges for the community

Self-driving labs (SDLs) leverage combinations of artificial intelligence, automation, and advanced computing to accelerate scientific discovery. The promise of this field has given rise to a rich community of passionate scientists, engineers, and social scientists, as evidenced by the development of the Acceleration Consortium and recent Accelerate Conference. Despite its strengths, this rapidly developing field presents numerous opportunities for growth, challenges to overcome, and potential risks of which to remain aware. This community perspective builds on a discourse instantiated during the first Accelerate Conference, and looks to the future of self-driving labs with a tempered optimism. Incorporating input from academia, government, and industry, we briefly describe the current status of self-driving labs, then turn our attention to barriers, opportunities, and a vision for what is possible. Our field is delivering solutions in technology and infrastructure, artificial intelligence and knowledge generation, and education and workforce development. In the spirit of community, we intend for this work to foster discussion and drive best practices as our field grows