The effect of clamping sequence on dimensional variability in sheet metal assembly

Finite element (FE) modelling techniques have become a popular tool for exploring welding and clamping sequence dependence in sheet metal assemblies. In the current paper, the dimensional variability associated with different assembly clamping sequences is investigated with a FE contact modelling approach implemented in the commercial code Abaqus. A simplified channel section assembly consisting of a top hat and bottom plate is the case study investigated. Expected variation modes of bow and twist were used to simulate key variability sources in the main structural component under investigation; the top hat of the channel section. It was found that final assembly variability can change considerably depending on clamp sequence selection. It was also found that different clamp sequences can control particular modes of variation better than others, and that there is not one particular clamping sequence that is the best for containing all variation modes. An adaptable assembly process is therefore suggested, where given the shape of input components the best available clamping sequence is selected. Comparison of the performance of the proposed adaptable clamping sequence to traditional fixed clamping sequences shows improvements for the dimensional control of variability in non-rigid components. While introducing such a method in production would require inspection of each component being assembled and investigation of the alternative clamping sequences, given access to fast and detailed dimensional inspection technology such as optical coordinate measuring machines (OCMM's), the approach shows promise for future application.

A unified learning algorithm to extract principal and minor components

Recently, many unified learning algorithms have been developed to solve the task of principal component analysis (PCA) and minor component analysis (MCA). These unified algorithms can be used to extract principal component and if altered simply by the sign, it can also serve as a minor component extractor. This is of practical significance in the implementations of algorithms. Convergence of the existing unified algorithms is guaranteed only under the condition that the learning rates of algorithms approach zero, which is impractical in many practical applications. In this paper, we propose a unified PCA & MCA algorithm with a constant learning rate, and derive the sufficient conditions to guarantee convergence via analyzing the discrete-time dynamics of the proposed algorithm. The achieved theoretical results lay a solid foundation for the applications of our proposed algorithm.

Multi-envelope HIV-1 vaccine devoid of SIV components controls disease in macaques challenged with heterologous pathogenic SHIV

A central obstacle to the design of a global HIV-1 vaccine is virus diversity. Pathogen diversity is not unique to HIV-1, and has been successfully conquered in other fields by the creation of vaccine cocktails. Here we describe the testing of an HIV-1 envelope cocktail vaccine. Six macaques received the vaccine, delivered by successive immunizations with recombinant DNA, recombinant vaccinia virus and recombinant envelope proteins. Following vaccination, animals developed a diversity of anti-envelope antibody binding and neutralizing activities toward proteins and viruses that were not represented by sequence in the vaccine. T-cells were also elicited, as measured by gamma-interferon production assays with envelope-derived peptide pools. Vaccinated and control animals were then challenged with the heterologous pathogenic SHIV, 89.6P. Vaccinated monkeys experienced significantly lower virus titers and better maintenance of CD4+ T-cells than unvaccinated controls. The B- and T-cell immune responses were far superior post-challenge in the vaccinated group. Four of six vaccinated animals and only one of six control animals survived a 44-week observation period post-challenge. The present report is the first to describe pathogenic SHIV disease control mediated by a heterologous HIV-1 vaccine, devoid of 89.6 or SIV derivatives.

Rapid detection of SMARCB1 sequence variation using high resolution melting

Background : Rhabdoid tumors are rare cancers of early childhood arising in the kidney, central nervous system and other organs. The majority are caused by somatic inactivating mutations or deletions affecting the tumor suppressor locus SMARCB1 [OMIM 601607]. Germ-line SMARCB1 inactivation has been reported in association with rhabdoid tumor, epitheloid sarcoma and familial schwannomatosis, underscoring the importance of accurate mutation screening to ascertain recurrence and transmission risks. We describe a rapid and sensitive diagnostic screening method, using high resolution melting (HRM), for detecting sequence variations in SMARCB1. Methods : Amplicons, encompassing the nine coding exons of SMARCB1, flanking splice site sequences and the 5' and 3' UTR, were screened by both HRM and direct DNA sequencing to establish the reliability of HRM as a primary mutation screening tool. Reaction conditions were optimized with commercially available HRM mixes. Results : The false negative rate for detecting sequence variants by HRM in our sample series was zero. Nine amplicons out of a total of 140 (6.4%) showed variant melt profiles that were subsequently shown to be false positive. Overall nine distinct pathogenic SMARCB1 mutations were identified in a total of 19 possible rhabdoid tumors. Two tumors had two distinct mutations and two harbored SMARCB1 deletion. Other mutations were nonsense or frame-shifts. The detection sensitivity of the HRM screening method was influenced by both sequence context and specific nucleotide change and varied from 1: 4 to 1:1000 (variant to wild-type DNA). A novel method involving digital HRM, followed by re-sequencing, was used to confirm mutations in tumor specimens containing associated normal tissue. Conclusions : This is the first report describing SMARCB1 mutation screening using HRM. HRM is a rapid, sensitive and inexpensive screening technology that is likely to be widely adopted in diagnostic laboratories to facilitate whole gene mutation screening.

A sequence based dynamic SOM model for text clustering

Text clustering can be considered as a four step process consisting of feature extraction, text representation, document clustering and cluster interpretation. Most text clustering models consider text as an unordered collection of words. However the semantics of text would be better captured if word sequences are taken into account.

In this paper we propose a sequence based text clustering model where four novel sequence based components are introduced in each of the four steps in the text clustering process.

Experiments conducted on the Reuters dataset and Sydney Morning Herald (SMH) news archives demonstrate the advantage of the proposed sequence based model, in terms of capturing context with semantics, accuracy and speed, compared to clustering of documents based on single words and n-gram based models.

The metabolic syndrome and cancer: is the metabolic syndrome useful for predicting cancer risk above and beyond its individual components?

AIMS: The metabolic syndrome (MetS) is a risk factor for cancer. However, it is not known if the MetS confers a greater cancer risk than the sum of its individual components, which components drive the association, or if the MetS predicts future cancer risk. MATERIALS AND METHODS: We linked 20,648 participants from the Australian and New Zealand Diabetes and Cancer Collaboration with complete data on the MetS to national cancer registries and used Cox proportional hazards models to estimate associations of the MetS, the number of positive MetS components, and each of the five MetS components separately with the risk for overall, colorectal, prostate and breast cancer. Hazard ratios (HR) and 95% confidence intervals (95%CI) are reported. We assessed predictive ability of the MetS using Harrell's c-statistic. RESULTS: The MetS was inversely associated with prostate cancer (HR 0.85; 95% CI 0.72-0.99). We found no evidence of an association between the MetS overall, colorectal and breast cancers. For those with five positive MetS components the HR was 1.12 (1.02-1.48) and 2.07 (1.26-3.39) for overall, and colorectal cancer, respectively, compared with those with zero positive MetS components. Greater waist circumference (WC) (1.38; 1.13-1.70) and elevated blood pressure (1.29; 1.01-1.64) were associated with colorectal cancer. Elevated WC and triglycerides were (inversely) associated with prostate cancer. MetS models were only poor to moderate discriminators for all cancer outcomes. CONCLUSIONS: We show that the MetS is (inversely) associated with prostate cancer, but is not associated with overall, colorectal or breast cancer. Although, persons with five positive components of the MetS are at a 1.2 and 2.1 increased risk for overall and colorectal cancer, respectively, and these associations appear to be driven, largely, by elevated WC and BP. We also demonstrate that the MetS is only a moderate discriminator of cancer risk.