Feasibility study of experimental methods for joint damping analysis

Feasibility of damping test apparatus using bolted join

A new numerical approach to Anderson (de)localization

We develop a new approach for the Anderson localization problem. The implementation of this method yields strong numerical evidence leading to a (surprising to many) conjecture: The two dimensional discrete random Schroedinger operator with small disorder allows states that are dynamically delocalized with positive probability. This approach is based on a recent result by Abakumov-Liaw-Poltoratski which is rooted in the study of spectral behavior under rank-one perturbations, and states that every non-zero vector is almost surely cyclic for the singular part of the operator. The numerical work presented is rather simplistic compared to other numerical approaches in the field. Further, this method eliminates effects due to boundary conditions. While we carried out the numerical experiment almost exclusively in the case of the two dimensional discrete random Schroedinger operator, we include the setup for the general class of Anderson models called Anderson-type Hamiltonians. We track the location of the energy when a wave packet initially located at the origin is evolved according to the discrete random Schroedinger operator. This method does not provide new insight on the energy regimes for which diffusion occurs.Comment: 15 pages, 8 figure

Status of ENDF/B-V fission yields

The features of ENDF/B-V with respect to fission yields are described. Yields for approximately 1100 nuclides are given for each of 11 fissioning nuclides at one or more fission-neutron energies, plus the yield uncertainties. Selected chain yields and uncertainties are illustrated. Aspects of the evaluation process are discussed. 4 figures, 3 tables. (RWR

Parental experience of an early developmental surveillance programme for autism within Australian general practice: A qualitative study

Objectives Implementing support and services early in the life course has been shown to promote positive developmental outcomes for children at high likelihood of developmental conditions including autism. This study examined parents'/caregivers' experiences and perceptions about a digital developmental surveillance pathway for autism, the autism surveillance pathway (ASP), and usual care, the surveillance as usual (SaU) pathway, in the primary healthcare general practice setting. Design This qualitative study involves using a convenience selection process of the full sample of parents/caregivers that participated in the main programme, 'General Practice Surveillance for Autism', a cluster-randomised controlled trial study. All interviews were audio-recorded, transcribed and coded using NVivo V.12 software. An inductive thematic interpretive approach was adopted and data were analysed thematically. Participants Twelve parents/caregivers of children with or without a developmental condition/autism (who participated in the main programme) in South Western Sydney and Melbourne were interviewed. Settings All interviews were completed over the phone. Results There were seven major themes and 20 subthemes that included positive experiences, such as pre-existing patient-doctor relationships and their perceptions on the importance of knowing and accessing early support/services. Barriers or challenges experienced while using the SaU pathway included long waiting periods, poor communication and lack of action plans, complexity associated with navigating the healthcare system and lack of understanding by general practitioners (GPs). Common suggestions for improvement included greater awareness/education for parents/carers and the availability of accessible resources on child development for parents/caregivers. Conclusion The findings support the use of digital screening tools for developmental surveillance, including for autism, using opportunistic contacts in the general practice setting. Trial registration number ANZCTR (ACTRN12619001200178)

Critical Review of Theoretical Models for Anomalous Effects (Cold Fusion) in Deuterated Metals

We briefly summarize the reported anomalous effects in deuterated metals at ambient temperature, commonly known as "Cold Fusion" (CF), with an emphasis on important experiments as well as the theoretical basis for the opposition to interpreting them as cold fusion. Then we critically examine more than 25 theoretical models for CF, including unusual nuclear and exotic chemical hypotheses. We conclude that they do not explain the data.Comment: 51 pages, 4 Figure

Mapping pervasive selective logging in the south-west Brazilian Amazon 2000–2019

Tropical forests harbour the highest biodiversity on the planet and are essential to human livelihoods and the global economy. However, continued loss and degradation of forested landscapes, coupled with a rapidly rising global population is placing incredible pressure on forests globally. The United Nations has developed the Reducing Emissions from Deforestation and forest Degradation (REDD+) programme in response to the challenges facing tropical forests and in recognition of the role they can play in climate mitigation. REDD+ requires consistent and reliable monitoring of forests, however, national-level methodologies for measuring degradation are often bespoke and, because of an inability to track degradation effectively, the majority of countries combine reporting for deforestation and forest degradation into a single value. Here, we extend a recent analysis that enabled the detection of selective logging at the scale of a logging concession to a regional-scale estimation of selective logging activities. We utilized logging records from across Brazil to train a supervised classification algorithm for detecting logged pixels in Landsat imagery then predicted the extent of logging over a 20 year period throughout Rondônia, Brazil. Approximately one-quarter of the forested lands in Rondônia were cleared between 2000 and 2019. We estimate that 11.0% of the forest area present in 2000 had been selectively logged by 2019, comprising >11,500 km2 of forest. In general, rates of selective logging were twice as high in the first decade relative to the last decade of the period. Our approach is a considerable advance in developing an operationalized selective logging monitoring system capable of detecting subtle forest disturbances over large spatial scales

Internet-based medical education: a realist review of what works, for whom and in what circumstances

http://creativecommons.org/licenses/by/2.0

Asian-Pacific consensus statement on the management of chronic hepatitis B: a 2008 update

Large amounts of new data on the natural history and treatment of chronic hepatitis B virus (HBV) infection have become available since 2005. These include long-term follow-up studies in large community-based cohorts or asymptomatic subjects with chronic HBV infection, further studies on the role of HBV genotype/naturally occurring HBV mutations, treatment of drug resistance and new therapies. In addition, Pegylated interferon α2a, entecavir and telbivudine have been approved globally. To update HBV management guidelines, relevant new data were reviewed and assessed by experts from the region, and the significance of the reported findings were discussed and debated. The earlier “Asian-Pacific consensus statement on the management of chronic hepatitis B” was revised accordingly. The key terms used in the statement were also defined. The new guidelines include general management, special indications for liver biopsy in patients with persistently normal alanine aminotransferase, time to start or stop drug therapy, choice of drug to initiate therapy, when and how to monitor the patients during and after stopping drug therapy. Recommendations on the therapy of patients in special circumstances, including women in childbearing age, patients with antiviral drug resistance, concurrent viral infection, hepatic decompensation, patients receiving immune-suppressive medications or chemotherapy and patients in the setting of liver transplantation, are also included

Supervised machine learning algorithms can classify open-text feedback of doctor performance with human-level accuracy

Background: Machine learning techniques may be an effective and efficient way to classify open-text reports on doctor’s activity for the purposes of quality assurance, safety, and continuing professional development. Objective: The objective of the study was to evaluate the accuracy of machine learning algorithms trained to classify open-text reports of doctor performance and to assess the potential for classifications to identify significant differences in doctors’ professional performance in the United Kingdom. Methods: We used 1636 open-text comments (34,283 words) relating to the performance of 548 doctors collected from a survey of clinicians’ colleagues using the General Medical Council Colleague Questionnaire (GMC-CQ). We coded 77.75% (1272/1636) of the comments into 5 global themes (innovation, interpersonal skills, popularity, professionalism, and respect) using a qualitative framework. We trained 8 machine learning algorithms to classify comments and assessed their performance using several training samples. We evaluated doctor performance using the GMC-CQ and compared scores between doctors with different classifications using t tests. Results: Individual algorithm performance was high (range F score=.68 to .83). Interrater agreement between the algorithms and the human coder was highest for codes relating to “popular” (recall=.97), “innovator” (recall=.98), and “respected” (recall=.87) codes and was lower for the “interpersonal” (recall=.80) and “professional” (recall=.82) codes. A 10-fold cross-validation demonstrated similar performance in each analysis. When combined together into an ensemble of multiple algorithms, mean human-computer interrater agreement was .88. Comments that were classified as “respected,” “professional,” and “interpersonal” related to higher doctor scores on the GMC-CQ compared with comments that were not classified (P.05). Conclusions: Machine learning algorithms can classify open-text feedback of doctor performance into multiple themes derived by human raters with high performance. Colleague open-text comments that signal respect, professionalism, and being interpersonal may be key indicators of doctor’s performance