Reinforcement of single-walled carbon nanotube bundles by intertube bridging

During their production, single-walled carbon nanotubes form bundles. Owing to the weak van der Waals interaction that holds them together in the bundle, the tubes can easily slide on each other, resulting in a shear modulus comparable to that of graphite. This low shear modulus is also a major obstacle in the fabrication of macroscopic fibres composed of carbon nanotubes. Here, we have introduced stable links between neighbouring carbon nanotubes within bundles, using moderate electron-beam irradiation inside a transmission electron microscope. Concurrent measurements of the mechanical properties using an atomic force microscope show a 30-fold increase of the bending modulus, due to the formation of stable crosslinks that effectively eliminate sliding between the nanotubes. Crosslinks were modelled using first-principles calculations, showing that interstitial carbon atoms formed during irradiation in addition to carboxyl groups, can independently lead to bridge formation between neighbouring nanotubes.     

Flexible active-matrix displays and shift registers based on solution-processed organic transistors

At present, flexible displays are an important focus of research. Further development of large, flexible displays requires a cost-effective manufacturing process for the active-matrix backplane, which contains one transistor per pixel. One way to further reduce costs is to integrate (part of) the display drive circuitry, such as row shift registers, directly on the display substrate. Here, we demonstrate flexible active-matrix monochrome electrophoretic displays based on solution-processed organic transistors on 25-microm-thick polyimide substrates. The displays can be bent to a radius of 1 cm without significant loss in performance. Using the same process flow we prepared row shift registers. With 1,888 transistors, these are the largest organic integrated circuits reported to date. More importantly, the operating frequency of 5 kHz is sufficiently high to allow integration with the display operating at video speed. This work therefore represents a major step towards 'system-on-plastic'.     

Do work technique and musculoskeletal symptoms differ between men and women performing the same type of work tasks?

Musculoskeletal disorders are more common among women than among men. When comparing the difference between men and women in the prevalence of musculoskeletal disorders, methodological problems arise as men and women seldom perform the same type of activities, neither at work nor at home.

The main objective of this cross-sectional case study was to compare work technique and self-reported musculoskeletal symptoms between men and women performing the same type of work tasks within a metal industry. Other factors, such as leisure activities, were also taken into consideration. Three data collection methods were used; questionnaire, interviews and systematic observations. The results from the observations revealed that women worked more frequently and during longer times with their hands above shoulder height than men. Working with hands above shoulder height is considered a risk factor for neck and shoulder disorders according to previous studies. Workplace design factors were probably a reason for differences in working technique between men and women. A higher proportion of women than men reported shoulder symptoms. Women spent more time on household activities than men, which indicates a higher total workload in paid and unpaid work.     

A randomized and controlled trial of a participative ergonomics intervention to reduce injuries associated with manual tasks: physical risk and legislative compliance

A participative ergonomics approach to reducing injuries associated with manual tasks is widely promoted; however only limited evidence from uncontrolled trials has been available to support the efficacy of such an approach. This paper reports on a randomized and controlled trial of PErforM, a participative ergonomics intervention designed to reduce the risks of injury associated with manual tasks. One hundred and seventeen small to medium sized food, construction, and health workplaces were audited by government inspectors using a manual tasks risk assessment tool (ManTRA). Forty-eight volunteer workplaces were then randomly assigned to Experimental and Control groups with the Experimental group receiving the PErforM program. Inspectors audited the workplaces again, 9 months following the intervention. The results showed a significant decrease in estimates of manual task risk and suggested better legal compliance in the Experimental group.     

Synchronization of traffic signals as a means of reducing red-light running

The goal of this study was to determine if traffic signals that are synchronized along a route are associated with fewer red-light violations than traffic signals that are not synchronized. A total 3600 cycles of traffic signals at 12 intersections along 2 major urban arteries were observed. Synchronized intersections were effective in reducing the likelihood of red-light running (RLR) by (a) providing fewer opportunities than nonsynchronized intersections for RLR and (b) having a lower rate of RLR relative to the number of opportunities. After adjustment for the number of opportunities, the odds of entering the intersections in red in synchronized intersections were nearly 1/7 the odds of RLR in nonsynchronized intersections. Congestion reduced the effectiveness of synchronized intersections relative to nonsynchronized intersections. Male drivers were slightly more likely to run red lights than female drivers, and the effects of synchronization were fairly constant across age, gender, and the presence or absence of passengers. Actual or potential applications of this research involve signal synchronization to reduce aggressive driving in general and RLR in particular.     

Application of the theory of optimal experiments to adaptive electromagnetic-induction sensing of buried targets

A mobile electromagnetic-induction (EM I) sensor is considered for detection and characterization of buried conducting and/or ferrous targets. The sensor maybe placed on a robot and, here, we consider design of an optimal adaptive-search strategy. A frequency-dependent magnetic-dipole model is used to characterize the target at EMI frequencies. The goal of the search is accurate characterization of the dipole-model parameters, denoted by the vector /spl Theta/; the target position and orientation are a subset of /spl Theta/. The sensor position and operating frequency are denoted by the parameter vector p and a measurement is represented by the pair (p, O), where O denotes the observed data. The parameters p are fixed for a given measurement, but, in the context of a sequence of measurements p may be changed adaptively. In a locally optimal sequence of measurements, we desire the optimal sensor parameters, p/sub N+1/ for estimation of /spl Theta/, based on the previous measurements (p/sub n/, O/sub n/)/sub n=1,N/. The search strategy is based on the theory of optimal experiments, as discussed in detail and demonstrated via several numerical examples.     

Skin color-based video segmentation under time-varying illumination

A novel approach for real-time skin segmentation in video sequences is described. The approach enables reliable skin segmentation despite wide variation in illumination during tracking. An explicit second order Markov model is used to predict evolution of the skin-color (HSV) histogram over time. Histograms are dynamically updated based on feedback from the current segmentation and predictions of the Markov model. The evolution of the skin-color distribution at each frame is parameterized by translation, scaling, and rotation in color space. Consequent changes in geometric parameterization of the distribution are propagated by warping and resampling the histogram. The parameters of the discrete-time dynamic Markov model are estimated using Maximum Likelihood Estimation and also evolve over time. The accuracy of the new dynamic skin color segmentation algorithm is compared to that obtained via a static color model. Segmentation accuracy is evaluated using labeled ground-truth video sequences taken from staged experiments and popular movies. An overall increase in segmentation accuracy of up to 24 percent is observed in 17 out of 21 test sequences. In all but one case, the skin-color classification rates for our system were higher, with background classification rates comparable to those of the static segmentation.     

Automatic writer identification using connected-component contours and edge-based features of uppercase Western script

In this paper, a new technique for offline writer identification is presented, using connected-component contours (COCOCOs or CO3s) in uppercase handwritten samples. In our model, the writer is considered to be characterized by a stochastic pattern generator, producing a family of connected components for the uppercase character set. Using a codebook of CO3s from an independent training set of 100 writers, the probability-density function (PDF) of CO3s was computed for an independent test set containing 150 unseen writers. Results revealed a high-sensitivity of the CO3 PDF for identifying individual writers on the basis of a single sentence of uppercase characters. The proposed automatic approach bridges the gap between image-statistics approaches on one end and manually measured allograph features of individual characters on the other end. Combining the CO3 PDF with an independent edge-based orientation and curvature PDF yielded very high correct identification rates.     

Error analysis of pure rotation-based self-calibration

Self-calibration using pure rotation is a well-known technique and has been shown to be a reliable means for recovering intrinsic camera parameters. However, in practice, it is virtually impossible to ensure that the camera motion for this type of self-calibration is a pure rotation. In this paper, we present an error analysis of recovered intrinsic camera parameters due to the presence of translation. We derived closed-form error expressions for a single pair of images with nondegenerate motion; for multiple rotations for which there are no closed-form solutions, analysis was done through repeated experiments. Among others, we show that translation-independent solutions do exist under certain practical conditions. Our analysis can be used to help choose the least error-prone approach (if multiple approaches exist) for a given set of conditions.     

High performance data compression method with pattern matching for biomedical ECG and arterial pulse waveforms

Biomedical waveforms, such as electrocardiogram (ECG) and arterial pulse, always possess a lot of important clinical information in medicine and are usually recorded in a long period of time in the application of telemedicine. Due to the huge amount of data, to compress the biomedical waveform data is vital. By recognizing the strong similarity and correlation between successive beat patterns in biomedical waveform sequences, an efficient data compression scheme mainly based on pattern matching is introduced in this paper. The waveform codec consists mainly of four units: beat segmentation, beat normalization, two-stage pattern matching and template updating and residual beat coding. Three different residual beat coding methods, such as Huffman/run-length coding, Huffman/run-length coding in discrete cosine transform domain, and vector quantization, are employed. The simulation results show that our compression algorithms achieve a very significant improvement in the performances of compression ratio and error measurement for both ECG and pulse, as compared with some other compression methods.