nPoint (United States)

The process of centrifugal casting of AMg5 and AMg6 alloys was tested under gravitational load coefficients (GLC) of 300g and 500g. It was found that the positive effect of increased GLC on melt crystallization is more pronounced when casting alloys with higher alloying element content. This promotes not only grain refinement and melt purification from brittle iron‑silicon compounds but also enhances the solubility of alloying elements in α(Al). Thus, castings from AMg6 obtained at 500g, compared to those at 300g, showed 1.1 and 1.3 times higher strength and ductility, respectively. Compared to the best samples of cast AMg6 alloy produced according to GOST 1583–93, centrifugal casting at 500g yielded an AMg6 alloy with strength, ductility, and hard‑ ness increased by 15–25, 10–50, and 40 %, respectively. Moreover, the alloy exhibits a structure equivalent to that obtained through solution heat treatment. Using the rolling method, the process of plastic deformation of AMg5 and AMg6 aluminum‑ magnesium alloys with structures obtained via casting at 500g was studied. As a result of developing various rolling routes, the AMg6 cast alloy obtained at 500g was strengthened, achieving a 1.6‑fold increase in strength and hardness at a total deformation of 60 %. The resulting AMg6 material had a strength ranging from 411 to 435 MPa and an elongation of 10 to 13 %, de‑ pending on the tensile direction. The results demonstrate the promise and necessity of further research into producing AMg alloys via centrifugal casting under GLCs of 300–500g followed by plastic deformation.

In the UK, the majority of cancers are diagnosed following referral from the GP after presenting with symptoms, signs, or test results associated with undiagnosed cancer.1 In England and Wales, an urgent referral pathway for patients presenting to GPs with 'red flag' symptoms was introduced in 2000, whereby all patients should be seen by a specialist within 2 weeks of referral (known as the Two Week Wait [TWW] pathway). These guidelines were updated in 2015 by incorporating more non-specific symptoms and lowering the threshold of risk of cancer from 5% to 3%.2 The TWW pathway is a high-volume referral pathway and the number of referrals has increased substantially over the last decade; in 2019/2020, 2.4 million patients were referred via this pathway.3 In addition to monitoring TWW referral rates, other key outcome indicators are the conversion rate (percentage of TWW referrals resulting in a cancer diagnosis) and the detection rate (percentage of new cancer cases treated resulting from a TWW referral) (Box 1). Improving the detection rate is a key priority as this means that patients may be diagnosed more promptly rather than by other routes such as emergency presentations, which have poorer survival.1 However, obtaining the right balance between high detection rate and low conversion rate is difficult and complex, involving many stakeholders.4 The full impact of increasing referrals on conversion and detection rates, as well as the wider impact on patients and the health system, is not well understood.4 There is a growing body of published data on cancer diagnostics publicly available including data by cancer pathway. | | ||

IO: UBC meshes contributions from: @thast, @micmitch, review from @lheagy from pr #54 discretize.TensorMesh.readUBC is now a wrapper for loading either 2D or 3D mesh discretize.TensorMesh.readUBC can take care of recognizing if the file is a 2D or 3D UBC mesh, or it can be an input given by the user (arg: <em>meshdim</em>) the original functions are now <em>hidden</em> class function under discretize.TensorMesh._readUBC_3DMesh and discretize.TensorMesh._readUBC_2DMesh comments in UBC files are assumed to be marked with "!" in front utils.Zero: Numpy upgrades contributions from: @lheagy, review and comments from @rowanc1, @jcapriot<br> from pr #61 Updates to <code>Identity()</code> and <code>Zero()</code> so that they are consistent with numpy upgrades in numpy=1.13.0 (https://github.com/charris/numpy/blob/master/doc/source/reference/arrays.classes.rst) use scipy.sparse.dia_matrix for spzeros (closed #60)

The complexities of today’s organizations have made it increasingly challenging for leaders to encourage and sustain a culture of cooperation. As organizations become flatter and leaner and people are required to do “more with less,” the key to success is the ability to coordinate decisions and actions across organizational boundaries and gain the support of people who often have competing priorities or conflicting goals. Further, the increasing prevalence of virtual teamwork and widespread use of e-collaboration tools have additional implications for how leaders encourage cooperation and coordinate work. This article explores the critical organizational factors and leadership skills that are required to build a culture of cooperation in today’s highly matrix, and often virtual, organizations.