Microstructure and mechanical properties of ductile aluminium alloy manufactured by recycled materials

The present paper introduces the microstructure and mechanical properties of the Al-Mg- Si-Mn alloy made by recycled materials, in which the impurity levels of iron are mainly concerned. It is found that the increased Fe content reduces the ductility and yield strength but slightly increases the UTS of the diecast alloy. The tolerable Fe content is 0.45wt.%, at which the recycled alloys are still able to produce castings with the mechanical properties of yield strength over 140MPa, UTS over 280MPa and elongation over 15%.The Fe content is steadily accumulated in the alloy with the increase of recycle times. However, after 13 cycles, the recycled alloys are still able to produce ductile alloys with satisfied mechanical properties.The TSB (UK

Reaching the End-Game for GWAS: Machine Learning Approaches for the Prioritization of Complex Disease Loci.

Genome-wide association studies (GWAS) have revealed thousands of genetic loci that underpin the complex biology of many human traits. However, the strength of GWAS - the ability to detect genetic association by linkage disequilibrium (LD) - is also its limitation. Whilst the ever-increasing study size and improved design have augmented the power of GWAS to detect effects, differentiation of causal variants or genes from other highly correlated genes associated by LD remains the real challenge. This has severely hindered the biological insights and clinical translation of GWAS findings. Although thousands of disease susceptibility loci have been reported, causal genes at these loci remain elusive. Machine learning (ML) techniques offer an opportunity to dissect the heterogeneity of variant and gene signals in the post-GWAS analysis phase. ML models for GWAS prioritization vary greatly in their complexity, ranging from relatively simple logistic regression approaches to more complex ensemble models such as random forests and gradient boosting, as well as deep learning models, i.e., neural networks. Paired with functional validation, these methods show important promise for clinical translation, providing a strong evidence-based approach to direct post-GWAS research. However, as ML approaches continue to evolve to meet the challenge of causal gene identification, a critical assessment of the underlying methodologies and their applicability to the GWAS prioritization problem is needed. This review investigates the landscape of ML applications in three parts: selected models, input features, and output model performance, with a focus on prioritizations of complex disease associated loci. Overall, we explore the contributions ML has made towards reaching the GWAS end-game with consequent wide-ranging translational impact

lp-Recovery of the Most Significant Subspace among Multiple Subspaces with Outliers

We assume data sampled from a mixture of d-dimensional linear subspaces with spherically symmetric distributions within each subspace and an additional outlier component with spherically symmetric distribution within the ambient space (for simplicity we may assume that all distributions are uniform on their corresponding unit spheres). We also assume mixture weights for the different components. We say that one of the underlying subspaces of the model is most significant if its mixture weight is higher than the sum of the mixture weights of all other subspaces. We study the recovery of the most significant subspace by minimizing the lp-averaged distances of data points from d-dimensional subspaces, where p>0. Unlike other lp minimization problems, this minimization is non-convex for all p>0 and thus requires different methods for its analysis. We show that if 0<p<=1, then for any fraction of outliers the most significant subspace can be recovered by lp minimization with overwhelming probability (which depends on the generating distribution and its parameters). We show that when adding small noise around the underlying subspaces the most significant subspace can be nearly recovered by lp minimization for any 0<p<=1 with an error proportional to the noise level. On the other hand, if p>1 and there is more than one underlying subspace, then with overwhelming probability the most significant subspace cannot be recovered or nearly recovered. This last result does not require spherically symmetric outliers.Comment: This is a revised version of the part of 1002.1994 that deals with single subspace recovery. V3: Improved estimates (in particular for Lemma 3.1 and for estimates relying on it), asymptotic dependence of probabilities and constants on D and d and further clarifications; for simplicity it assumes uniform distributions on spheres. V4: minor revision for the published versio

Winter wheat roots grow twice as deep as spring wheat roots, is this important for N uptake and N leaching losses?

Cropping systems comprising winter catch crops followed by spring wheat could reduce N leaching risks compared to traditional winter wheat systems in humid climates. We studied the soil mineral N (Ninorg) and root growth of winter- and spring wheat to 2.5 m depth during three years. Root depth of winter wheat (2.2 m) was twice that of spring wheat, and this was related to much lower amounts of Ninorg in the 1 to 2.5 m layer after winter wheat (81 kg Ninorg ha-1 less). When growing winter catch crops before spring wheat, N content in the 1 to 2.5 m layer after spring wheat was not different from that after winter wheat. The results suggest that by virtue of its deep rooting, winter wheat may not lead to high levels of leaching as it is often assumed in humid climates. Deep soil and root measurements (below 1 m) in this experiment were essential to answer the questions we posed

Optimal measurement of visual motion across spatial and temporal scales

Sensory systems use limited resources to mediate the perception of a great variety of objects and events. Here a normative framework is presented for exploring how the problem of efficient allocation of resources can be solved in visual perception. Starting with a basic property of every measurement, captured by Gabor's uncertainty relation about the location and frequency content of signals, prescriptions are developed for optimal allocation of sensors for reliable perception of visual motion. This study reveals that a large-scale characteristic of human vision (the spatiotemporal contrast sensitivity function) is similar to the optimal prescription, and it suggests that some previously puzzling phenomena of visual sensitivity, adaptation, and perceptual organization have simple principled explanations.Comment: 28 pages, 10 figures, 2 appendices; in press in Favorskaya MN and Jain LC (Eds), Computer Vision in Advanced Control Systems using Conventional and Intelligent Paradigms, Intelligent Systems Reference Library, Springer-Verlag, Berli

Cancer pharmacogenetics

The large number of active combination chemotherapy regimens for most cancers has led to the need for better information to guide the \u27standard\u27 treatment for each patient. In an attempt to individualise therapy, pharmacogenetics and pharmacogenomics (a polygenic approach to pharmacogenetic studies) encompass the search for answers to the hereditary basis for interindividual differences in drug response. This review will focus on the results of studies assessing the effects of polymorphisms in drug-metabolising enzymes and drug targets on the toxicity and response to commonly used chemotherapy drugs. In addition, the need for polygenic pharmacogenomic strategies to identify patients at risk for adverse drug reactions will be highlighted

Organisational participation and women - an attitude problem?

Employee participation is a dynamic and contested area of organisational behaviour, attracting continuing academic, practitioner and policy interest and debate. This chapter focuses on organisational participation and women

Regulation of cell survival by sphingosine-1-phosphate receptor S1P1 via reciprocal ERK-dependent suppression of bim and PI-3-kinase/protein kinase C-mediated upregulation of Mcl-1

Although the ability of bioactive lipid sphingosine-1-phosphate (S1P) to positively regulate anti-apoptotic/pro-survival responses by binding to S1P1 is well known, the molecular mechanisms remain unclear. Here we demonstrate that expression of S1P1 renders CCL39 lung fibroblasts resistant to apoptosis following growth factor withdrawal. Resistance to apoptosis was associated with attenuated accumulation of pro-apoptotic BH3-only protein Bim. However, although blockade of extracellular signal-regulated kinase (ERK) activation could reverse S1P1-mediated suppression of Bim accumulation, inhibition of caspase-3 cleavage was unaffected. Instead S1P1-mediated inhibition of caspase-3 cleavage was reversed by inhibition of phosphatidylinositol-3-kinase (PI3K) and protein kinase C (PKC), which had no effect on S1P1 regulation of Bim. However, S1P1 suppression of caspase-3 was associated with increased expression of anti-apoptotic protein Mcl-1, the expression of which was also reduced by inhibition of PI3K and PKC. A role for the induction of Mcl-1 in regulating endogenous S1P receptor-dependent pro-survival responses in human umbilical vein endothelial cells was confirmed using S1P receptor agonist FTY720-phosphate (FTY720P). FTY720P induced a transient accumulation of Mcl-1 that was associated with a delayed onset of caspase-3 cleavage following growth factor withdrawal, whereas Mcl-1 knockdown was sufficient to enhance caspase-3 cleavage even in the presence of FTY720P. Consistent with a pro-survival role of S1P1 in disease, analysis of tissue microarrays from ER+ breast cancer patients revealed a significant correlation between S1P1 expression and tumour cell survival. In these tumours, S1P1 expression and cancer cell survival were correlated with increased activation of ERK, but not the PI3K/PKB pathway. In summary, pro-survival/anti-apoptotic signalling from S1P1 is intimately linked to its ability to promote the accumulation of pro-survival protein Mcl-1 and downregulation of pro-apoptotic BH3-only protein Bim via distinct signalling pathways. However, the functional importance of each pathway is dependent on the specific cellular context

Perinatal mental ill health - the experiences of women from ethnic minority groups

This study aimed to investigate ethnic minority women’s experiences and opinions of perinatal mental health problems and the provision of perinatal mental health support services. An exploratory survey was undertaken using a questionnaire. Quantitative data were analysed using descriptive statistics and a simple thematic analysis was used for the qualitative data. A total of 51 responses from women of 14 different ethnic minority backgrounds were analysed. Women from minority ethnic groups face barriers to seeking help for perinatal mental ill health as a result of ongoing stigma and the poor attitudes and behaviours of health professionals and inappropriately designed services. Future interventions should focus on providing adequate cultural competency for health care professionals and ensure that all women are able to access culturally appropriate spaces to talk and be listened to within community settings and wider services