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In computing eigenvalues for a large finite element system it has been observed that the eigenvalue extractors produce eigenvectors that are in some sense more accurate than their corresponding eigenvalues. From this observation the paper uses a patch type technique based on the eigenvector for one mesh quality to provide an eigenvalue error indicator. Tests show this indicator to be both accurate and reliable. This technique was first observed by Stephen and Steven for an error estimation for buckling and natural frequency of beams and two dimensional in-plane and out-of-plane structures. This paper produces and error indicator for the more difficult problem of three dimensional brick elements.
In a recent issue of the Journal of Cancer Prevention, Abdolmaleki and Sohrabi investigated the frequency of the JAK2 V617F mutation in patients with cervical cancer, proposing that polymorphisms in genes encoding elements of the intracellular JAK-STAT signalling pathway may contribute to oncogenesis through an immunomodulatory effect . Several aspects of this study require extensive explanation and clarification. Firstly, the authors have selected the JAK2 p.V617F (c.1849G>T; reference sequence NM_004972.3) which is not a polymorphism as continually stated, but the most common somatic, driver mutation of the classical myeloproliferative neoplasms (MPN) of polycythemia vera, essential thrombocythemia and primary myelofibrosis. This acquired mutation, located in exon 14 (not exon 12) of the JAK2 gene, causes constitutive activation of JAK-STAT signalling mediated by hematopoietic growth factors resulting in proliferation of various myeloid cell lineages . Selection of this acquired molecular marker to correlate with cervical cancer therefore appears highly erroneous and requires justification. Secondly, in order to detect the JAK2 V617F, the authors use a restriction fragment length polymorphism (RFLP) technique that detects the presence of the G>T transversion. This technique has been demonstrated to be highly inefficient due to incomplete restriction enzyme cleavage, particularly at low JAK2 V617F levels and therefore, assigning positivity and subsequent mutation zygosity would be extremely challenging . Numerous real-time PCR approaches exist for the detection of the JAK2 V617F and given the availability of this methodology to the authors, the selection of an RFLP approach appears somewhat confounding . Furthermore, the authors report the presence of a heterozygous JAK2 V617F in 68 (34.9%) of all study participants in Table 2, a strikingly disproportionate high number, lending further evidence for a largely false-positive identification of this mutation. Finally, if these study participants truly harbor the JAK2 V617F, did any possess other clinical, hematological or laboratory evidence of a co-existing MPN in addition to cervical cancer? If so, further information needs to be provided. While polymorphisms in immune mediators, including those of JAK2 such as rs10815144 and rs12349785, have been previously associated with the risk of cervical cancer , the rationale for examining the MPN-associated JAK2 V617F with such a problematic methodology in cervical cancer pathogenesis appears unconvincing.
The demand for beef as a protein source is increasing worldwide, although in most countries beef accounts for considerably less than half of total meat consumption. Beef also provides a highly desirable eating experience in developed countries and, increasingly, in developing countries. The sustainability of beef production has different meanings in the various geographical and socio-economic regions of the world. Natural resources including land mass and uses, rainfall and access to livestock feed, and the robustness of the economy are major determinants of the perception of beef sustainability. In this overview of the 2016 International Symposium on “Future Beef in Asia” and this subsequent Special Edition of the Asian-Australasian Journal of Animal Sciences on “Current Situation and Future Prospects for Global Beef Production”, the contributions have been grouped into the following categories: Countries in Southeast Asia; Europe; and Countries producing highly marbled beef for export and/or domestic consumption. They also include reference to Special Topics including marbled beef production, and use of “omics” technologies to enhance beef quality assurance. Among these broad categories, notable differences exist across countries in the production and marketing of beef. These reflect differences in factors including natural resource availability and climate, population size, traditional culture and degree of economic development including industrial and technological developments. We trust that the International Symposium and this Special Edition on Current Situation and Future Prospects for Global Beef Production, the contents of which that are briefly summarized in this paper, will serve as a valuable resource for the livestock industries, researchers and students with an interest in enhancing the prospects for sustainable, efficient beef production that satisfies the growing size and complexity of consumer demands and markets for beef.
How to study Southeast Asia (SEA)? The need to explore and identify methodologies for studying SEA are inherent in its multifaceted subject matter. At a minimum, the region’s rich cultural diversity inhibits both the articulation of decisive defining characteristics and the training of scholars who can write with confidence beyond their specialisms. Consequently, the challenges of understanding the region remain and a consensus regarding the most effective approaches to studying its history, identity and future seem quite unlikely. Furthermore, “Area Studies” more generally, has proved to be a less attractive frame of reference for burgeoning scholarly trends. This paper will propose a new tool to help address these challenges. Even though the science of artificial intelligence (AI) is in its infancy, it has already yielded new approaches to many commercial, scientific and humanistic questions. At this point, AI has been used to produce news, generate better smart phones, deliver more entertainment choices, analyze earthquakes and write fiction. The time has come to explore the possibility that AI can be put at the service of the study of SEA. The paper intends to lay out what would be required to develop SEABOT. This instrument might exist as a robot on the web which might be called upon to make the study of SEA both broader and more comprehensive. The discussion will explore the financial resources, ownership and timeline needed to make SEABOT go from an idea to a reality. SEABOT would draw upon artificial neural networks (ANNs) to mine the region’s “Big Data”, while synthesizing the information to form new and useful perspectives on SEA. Overcoming significant language issues, applying multidisciplinary methods and drawing upon new yields of information should produce new questions and ways to conceptualize SEA. SEABOT could lead to findings which might not otherwise be achieved. SEABOT’s work might well produce outcomes which could open up solutions to immediate regional problems, provide ASEAN planners with new resources and make it possible to eventually define and capitalize on SEA’s “soft power”. That is, new findings should provide the basis for ASEAN diplomats and policy-makers to develop new modalities of cultural diplomacy and improved governance. Last, SEABOT might also open up avenues to tell the SEA story in new distinctive ways. SEABOT is seen as a heuristic device to explore the results which this instrument might yield. More important the discussion will also raise the possibility that an AI-driven perspective on SEA may prove to be even more problematic than it is beneficial.