Thermomechanical analyses of ultrasonic welding process using thermal and acoustic softening effects

Ultrasonic welding process is a rapid manufacturing process used to weld thin layers of metal at low temperatures and low energy consumption. Experimental results have shown that ultrasonic welding is a combination of both surface (friction) and volume (plasticity) softening effects. In the presented work, a very first attempt has been made to simulate the ultrasonic welding of metals by taking into account both of these effects (surface and volume). A phenomenological material model has been proposed which incorporates these two effects (i.e. surface and volume). The thermal softening due to friction and ultrasonic (acoustic) softening has been included in the proposed material model. For surface effects a friction law with variable coefficient of friction dependent upon contact pressure, slip, temperature and number of cycles has been derived from experimental friction tests. Thermomechanical analyses of ultrasonic welding of aluminium alloy have been performed. The effects of ultrasonic welding process parameters, such as applied load, amplitude of ultrasonic vibration, and velocity of welding sonotrode on the friction work at the weld interface are being analyzed. The change in the friction work at the weld interface has been explained on the basis of softening (thermal and acoustic) of the specimen during the ultrasonic welding process. In the end, a comparison between experimental and simulated results has been presented showing a good agreement. © 2008 Elsevier Ltd. All rights reserved.

Fibre embedding in aluminium alloy 3003 using ultrasonic consolidation process-thermo-mechanical analyses

This work presents a computational framework based on finite element methods to simulate the fibre-embedding process using ultrasonic consolidation process. The computational approach comprises of a material model which takes into account thermal and acoustic softening effects and a friction model which indicates the realistic friction behaviour at the interfaces. The derived material model and developed friction model have been incorporated in finite element model. Using the implemented material and friction model, thermo-mechanical analyses of embedding of fibre in aluminium alloy 3003 has been performed. Effect of different process parameters, such as velocity of sonotrode, displacement amplitude of ultrasonic vibration and applied loads, is studied and compared with the experimental results. The presented work has specially focused on the quality of the developed weld which could be evaluated by the friction work and the coverage of the fibre which is estimated by the plastic flow around the fibre. The computed friction work obtained from the thermomechanial analyses performed in this study show a similar trend as that of the experimentally found fracture energies. © Springer-Verlag London Limited 2010.

JPEG Image Steganalysis Using Multivariate PDF Estimates With MRF Cliques

Blind steganalysis of JPEG images is addressed by modeling the correlations among the DCT coefficients using K -variate (K = 2) p.d.f. estimates (p.d.f.s) constructed by means of Markov random field (MRF) cliques. The reasoning of using high variate p.d.f.s together with MRF cliques for image steganalysis is explained via a classical detection problem. Although our approach has many improvements over the current state-of-the-art, it suffers from the high dimensionality and the sparseness of the high variate p.d.f.s. The dimensionality problem as well as the sparseness problem are solved heuristically by means of dimensionality reduction and feature selection algorithms. The detection accuracy of the proposed method(s) is evaluated over Memon's (30.000 images) and Goljan's (1912 images) image sets. It is shown that practically applicable steganalysis systems are possible with a suitable dimensionality reduction technique and these systems can provide, in general, improved detection accuracy over the current state-of-the-art. Experimental results also justify this assertion.

Chemometric techniques in multivariate statistical modelling of process plant

The techniques of principal component analysis (PCA) and partial least squares (PLS) are introduced from the point of view of providing a multivariate statistical method for modelling process plants. The advantages and limitations of PCA and PLS are discussed from the perspective of the type of data and problems that might be encountered in this application area. These concepts are exemplified by two case studies dealing first with data from a continuous stirred tank reactor (CSTR) simulation and second a literature source describing a low-density polyethylene (LDPE) reactor simulation.

Molecular comparison of Scytalidium thermophilum isolates using RAPD and ITS nucleotide sequence analyses

Scytalidium thermophilum plays an important role in determining selectivity of compost produced for growing Agaricus bisporus. The objective of this study was to characterise S. thermophilum isolates by random amplified polymorphic DNA (RAPD) analysis and sequence analysis of internally transcribed spacer (ITS) regions of the rDNA, to assess the genetic variation exhibited by this species complex and to compare this with existing morphological and thermogravimetric data. RAPD analysis of 34 isolates from various parts of the world revealed two distinct groups, which could be separated on the basis of the differences in the banding patterns produced with five random primers. Nucleotide sequence analysis of the ITS region, which was ca 536 bp in length, revealed only very minor variation among S. thermophilum isolates examined. Several nucleotide base changes within this region demonstrated variation. Genetic distance values among type 1 and 2 S. thermophilum isolates, as determined by ITS sequence analysis, varied by a value of 0.005 %. Molecular analyses carried out in the present study would suggest that isolates within this species complex exhibit genetic differences which correlate well with morphological variation and thermogravimetric data previously determined.

Structural damage diagnosis of steel truss bridges by outlier detection

This study discusses structural damage diagnosis of real steel truss bridges by measuring trafficinduced vibration of bridges and utilizing a damage indicator derived from linear system parameters of a time series model. On-site damage experiments were carried out on real steel truss bridges. Artificial damage was applied to the bridge by severing a truss member with a cutting machine.Vehicle-induced vibrations of the bridges before and after applying damagewere measured and used in structural damage diagnosis of the bridges. Changes in the damage indicator are detected by Mahalanobis-Taguchi system (MTS) which is one of multivariate outlier analyses. The damage indicator and outlier detection was successfully applied to detect anomalies in the steel truss bridges utilizing vehicle-induced vibrations. Observations through this study demonstrate feasibility of the proposed approach for real world applications.

'Sorry I meant the patient's left side': impact of distraction on right/left discrimination

Context Medical students can have difficulty in distinguishing left from right. Many infamous medical errors have occurred when a procedure has been performed on the wrong side, such as in the removal of the wrong kidney. Clinicians encounter many distractions during their work. There is limited information on how these affect performance. 
Objectives Using a neuropsychological paradigm, we aim to elucidate the impacts of different types of distraction on left–right (LR) discrimination ability. 
Methods Medical students were recruited to a study with four arms: (i) control arm (no distraction); (ii) auditory distraction arm (continuous ambient ward noise); (iii) cognitive distraction arm (interruptions with clinical cognitive tasks), and (iv) auditory and cognitive distraction arm. Participants’ LR discrimination ability was measured using the validated Bergen Left–Right Discrimination Test (BLRDT). Multivariate analysis of variance was used to analyse the impacts of the different forms of distraction on participants’ performance on the BLRDT. Additional analyses looked at effects of demographics on performance and correlated participants’ self-perceived LR discrimination ability and their actual performance. 
Results A total of 234 students were recruited. Cognitive distraction had a greater negative impact on BLRDT performance than auditory distraction. Combined auditory and cognitive distraction had a negative impact on performance, but only in the most difficult LR task was this negative impact found to be significantly greater than that of cognitive distraction alone. There was a significant medium-sized correlation between perceived LR discrimination ability and actual overall BLRDT performance. 
Conclusions
Distraction has a significant impact on performance and multifaceted approaches are required to reduce LR errors. Educationally, greater emphasis on the linking of theory and clinical application is required to support patient safety and human factor training in medical school curricula. Distraction has the potential to impair an individual's ability to make accurate LR decisions and students should be trained from undergraduate level to be mindful of this.

Repeated measures of body mass index and C-reactive protein in relation to all-cause mortality and cardiovascular disease: Results from the consortium on health and ageing network of cohorts in Europe and the United States (CHANCES)

Obesity has been linked with elevated levels of C-reactive protein (CRP), and both have been associated with increased risk of mortality and cardiovascular disease (CVD). Previous studies have used a single ‘baseline’ measurement and such analyses cannot account for possible changes in these which may lead to a biased estimation of risk. Using four cohorts from CHANCES which had repeated measures in participants 50 years and older, multivariate time-dependent Cox proportional hazards was used to estimate hazard ratios (HR) and 95 % confidence intervals (CI) to examine the relationship between body mass index (BMI) and CRP with all-cause mortality and CVD. Being overweight (≥25–<30 kg/m2) or moderately obese (≥30–<35) tended to be associated with a lower risk of mortality compared to normal (≥18.5–<25): ESTHER, HR (95 % CI) 0.69 (0.58–0.82) and 0.78 (0.63–0.97); Rotterdam, 0.86 (0.79–0.94) and 0.80 (0.72–0.89). A similar relationship was found, but only for overweight in Glostrup, HR (95 % CI) 0.88 (0.76–1.02); and moderately obese in Tromsø, HR (95 % CI) 0.79 (0.62–1.01). Associations were not evident between repeated measures of BMI and CVD. Conversely, increasing CRP concentrations, measured on more than one occasion, were associated with an increasing risk of mortality and CVD. Being overweight or moderately obese is associated with a lower risk of mortality, while CRP, independent of BMI, is positively associated with mortality and CVD risk. If inflammation links CRP and BMI, they may participate in distinct/independent pathways. Accounting for independent changes in risk factors over time may be crucial for unveiling their effects on mortality and disease morbidity.

CCAAT/enhancer binding protein α predicts poorer prognosis and prevents energy starvation-induced cell death in hepatocellular carcinoma

CCAAT enhancer binding protein α (C/EBPα) plays an essential role in cellular differentiation, growth, and energy metabolism. Here, we investigate the correlation between C/EBPα and hepatocellular carcinoma (HCC) patient outcomes and how C/EBPα protects cells against energy starvation. Expression of C/EBPα protein was increased in the majority of HCCs examined (191 pairs) compared with adjacent nontumor liver tissues in HCC tissue microarrays. Its upregulation was correlated significantly with poorer overall patient survival in both Kaplan-Meier survival (P = 0.017) and multivariate Cox regression (P = 0.028) analyses. Stable C/EBPα-silenced cells failed to establish xenograft tumors in nude mice due to extensive necrosis, consistent with increased necrosis in human C/EBPα-deficient HCC nodules. Expression of C/EBPα protected HCC cells in vitro from glucose and glutamine starvation-induced cell death through autophagy-involved lipid catabolism. Firstly, C/EBPα promoted lipid catabolism during starvation, while inhibition of fatty acid beta-oxidation significantly sensitized cell death. Secondly, autophagy was activated in C/EBPα-expressing cells, and the inhibition of autophagy by ATG7 knockdown or chloroquine treatment attenuated lipid catabolism and subsequently sensitized cell death. Finally, we identified TMEM166 as a key player in C/EBPα-mediated autophagy induction and protection against starvation.

CONCLUSION: The C/EBPα gene is important in that it links HCC carcinogenesis to autophagy-mediated lipid metabolism and resistance to energy starvation; its expression in HCC predicts poorer patient prognosis.

Neural basis of language switching in the brain: fMRI evidence from Korean-Chinese early bilinguals

Using fMRI, we conducted two types of property generation task that involved language switching, with early bilingual speakers of Korean and Chinese. The first is a more conventional task in which a single language (L1 or L2) was used within each trial, but switched randomly from trial to trial. The other consists of a novel experimental design where language switching happens within each trial, alternating in the direction of the L1/L2 translation required. Our findings support a recently introduced cognitive model, the 'hodological' view of language switching proposed by Moritz-Gasser and Duffau. The nodes of a distributed neural network that this model proposes are consistent with the informative regions that we extracted in this study, using both GLM methods and Multivariate Pattern Analyses: the supplementary motor area, caudate, supramarginal gyrus and fusiform gyrus and other cortical areas.