A major advance in powder metallurgy

Ultramet has developed a process which promises to significantly increase the mechanical properties of powder metallurgy (PM) parts. Current PM technology uses mixed powders of various constituents prior to compaction. The homogeneity and flaw distribution in PM parts depends on the uniformity of mixing and the maintenance of uniformity during compaction. Conventional PM fabrication processes typically result in non-uniform distribution of the matrix, flaw generation due to particle-particle contact when one of the constituents is a brittle material, and grain growth caused by high temperature, long duration compaction processes. Additionally, a significant amount of matrix material is usually necessary to fill voids and create 100 percent dense parts. In Ultramet's process, each individual particle is coated with the matrix material, and compaction is performed by solid state processing. In this program, Ultramet coated 12-micron tungsten particles with approximately 5 wt percent nickel/iron. After compaction, flexure strengths were measured 50 percent higher than those achieved in conventional liquid phase sintered parts (10 wt percent Ni/Fe). Further results and other material combinations are discussed

Metformin and cancer in type 2 diabetes: a systematic review and comprehensive bias evaluation.

Background: Existing observational studies provide conflicting evidence for the causal effect of metformin use on cancer risk in patients with type-2 diabetes, and there are concerns about bias affecting a number of studies. Methods: MEDLINE was used to identify observational studies investigating the association between metformin and overall or site-specific cancer in people with type-2 diabetes. A systematic data extraction and bias assessment was conducted, in which risk of eight bias domains (outcome, exposure, control selection, baseline confounding, time-dependent confounding, immortal time, missing data, censoring methods) were assessed against pre-defined criteria, and rated as unlikely, low, medium or high. Results: Of 46 studies identified, 21 assessed the effect of metformin on all cancer. Reported relative risks ranged from 0.23 to 1.22, with 12/21 reporting a statistically significant protective effect and none a harmful effect. The range of estimates was similar for site-specific cancers; 3/46 studies were rated as low or unlikely risk of bias in all domains. Two of these had results consistent with no effect of metformin; one observed a moderate protective effect overall, but presented further analyses that the authors concluded were inconsistent with causality. However, 28/46 studies were at risk from bias through exposure definition, 22 through insufficient baseline adjustment and 35 from possible time-dependent confounding. Conclusions: Observational studies on metformin and cancer varied in design, and the majority were at risk of a range of biases. The studies least likely to be affected by bias did not support a causal effect of metformin on cancer risk

Anomalous nonadditive dispersion interactions in systems of three one-dimensional wires

10 pages, 8 figures, 1 tableFinancial support was provided by the U. K. Engineering and Physical Sciences Research Council (EPSRC). Part of the computations have been performed using the K computer at Advanced Institute for Computational Science, RIKEN. R.M. is grateful for financial support from KAKENHI Grants No. 23104714, No. 22104011, and No. 25600156, and from the Tokuyama Science Foundation

Neurobiologic Features of Fibromyalgia Are Also Present Among Rheumatoid Arthritis Patients

Funding: The study recieved support from Pfizer. The funder had no role in study design, data collection, analysis, decision to publish or preparation of the manuscript. The content is solely the responsibility of the authors. Funding Information Pfizer Aptinyx Cerephex ACKNOWLEDGEMENTS: The authors wish to thank all of the patient volunteers. We also thank Mariella D’Allesandro for supporting recruitment and data collection.Peer reviewedPostprin

Generation of unpredictable time series by a Neural Network

A perceptron that learns the opposite of its own output is used to generate a time series. We analyse properties of the weight vector and the generated sequence, like the cycle length and the probability distribution of generated sequences. A remarkable suppression of the autocorrelation function is explained, and connections to the Bernasconi model are discussed. If a continuous transfer function is used, the system displays chaotic and intermittent behaviour, with the product of the learning rate and amplification as a control parameter.Comment: 11 pages, 14 figures; slightly expanded and clarified, mistakes corrected; accepted for publication in PR

Editors' Note

Editors' Note for the Proceedings of the 2020 Annual Meeting on Phonology (AMP 2020), held at the University of California, Santa Cruz in September 2020