There has been no subsequent meta-analysis examining the effects of long working hours on health or occupational health since 1997. Therefore, this paper aims to conduct a meta-analysis covering studies after 1997 for a comparison. A total of 243 published records were extracted from electronic databases. The effects were measured by five conditions, namely, physiological health (PH), mental health (MH), health behaviours (HB), related health (RH), and nonspecified health (NH). The overall odds ratio between long working hours and occupational health was 1.245 (95% confidence interval (CI): 1.195–1.298). The condition of related health constituted the highest odds ratio value (1.465, 95% CI: 1.332–1.611). The potential moderators were study method, cut-point for long weekly working hours, and country of origin. Long working hours were shown to adversely affect the occupational health of workers. The management on safeguarding the occupational health of workers working long hours should be reinforced.

We describe new algorithms and modules for protein structure prediction available as part of the PROTINFO web server. The modules, comparative and de novo modelling, have significantly improved back-end algorithms that were rigorously evaluated at the sixth meeting on the Critical Assessment of Protein Structure Prediction methods. We were one of four server groups invited to make an oral presentation (only the best performing groups are asked to do so). These two modules allow a user to submit a protein sequence and return atomic coordinates representing the tertiary structure of that protein. The PROTINFO server is available at .

Commonly used methods in analyzing functional magnetic resonance imaging (fMRI) data, such as the Student's t-test and cross-correlation analysis, are model-based approaches. Although these methods are easy to implement and are effective in analyzing data obtained with simple paradigms, they are not applicable in situations in which patterns of neuronal response are complicated and when fMRI response is unknown. In this work, Kohonen's self-organizing mapping (SOM), which is a model-free approach, is adapted for analyzing fMRI data. Because spatial connectivity is an important function in the identification of activation sites in functional brain imaging, it is incorporated into the SOM algorithm. Receiver operating characteristic analysis on simulated data shows that the new algorithm achieves measurable improvement over the standard algorithm. The applicability of the new algorithm is demonstrated on experimental data. Magn Reson Med 41:939

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In spite of recent progress in our understanding of the absolute stability of elastic phases under loads, the generic presence of metastable configurations and the possibility of their dynamic breakdown remains a major problem in the mechanical theory of phase transitions in solids. In this paper, by considering the simplest one-dimensional model, we study the interplay between inertial and thermal effects associated with nucleation of a new phase, and address the crucial question concerning the size of a perturbation breaking metastability. We begin by reformulating the nucleation problem as a degenerate Riemann problem. By choosing a specific kinetic relation, originating from thermo-visco-capillary (TVC) regularization, we solve a self-similar problem analytically and demonstrate the existence of two types of solutions: with nucleation and without it. We then show that in the presence of a nonzero latent heat, solution with nucleation may by itself be non-unique. To understand the domain of attraction of different self-similar solutions with and without nucleation, we regularize the model and study numerically the full scale initial value problem with locally perturbed data. Through numerical experiments we present evidence that the TVC regularization is successful in removing deficiencies of the classical thermo-elastic model and is sufficient in specifying the limits of metastability.