The Effect Of Different Generations Psychosocial Work Climate On The Employees’ Work Performance

The main objective of this paper is to examine the psychosocial work environment factors that influence the employee’s work performance at difference generation

Modeling of Traffic Excitation for System Identification of Bridge Structures

In long-term health monitoring of bridge structures, system identification is often performed based only on the system output (bridge vibration responses) because the system input (traffic excitation) is difficult to measure. To facilitate the identification of the bridge properties, traffic excitation is commonly modeled as spatially uncorrelated white noise. A physical model of a stationary stream of vehicles (moving loads) arriving in accordance with a Poisson process, traversing an elastic beam, shows that the traffic excitation is spatially correlated. Employing the dynamic nodal loading approach, this spatial correlation results in a frequency-dependent excitation spectrum density matrix, and shifts the response spectra obtained from those excited by spatially uncorrelated white noise. It is shown that the application of system identification techniques based on the conventional excitation model may result in misleading structural properties. Hence, this study further proposes an output-only gray-box identification technique for bridge structures, in which knowledge about the nature of the traffic excitation, such as its spatial correlation, is implanted into an autoregressive-moving-average (ARMA) model. The identifiability of the ARMA model so constructed is assured and the feasibility of the proposed identification technique is demonstrated by a numerical example

Modeling of Traffic Excitation for System Identification of Bridge Structures

In long-term health monitoring of bridge structures, system identification is often performed based only on the system output (bridge vibration responses) because the system input (traffic excitation) is difficult to measure. To facilitate the identification of the bridge properties, traffic excitation is commonly modeled as spatially uncorrelated white noise. A physical model of a stationary stream of vehicles (moving loads) arriving in accordance with a Poisson process, traversing an elastic beam, shows that the traffic excitation is spatially correlated. Employing the dynamic nodal loading approach, this spatial correlation results in a frequency-dependent excitation spectrum density matrix, and shifts the response spectra obtained from those excited by spatially uncorrelated white noise. It is shown that the application of system identification techniques based on the conventional excitation model may result in misleading structural properties. Hence, this study further proposes an output-only gray-box identification technique for bridge structures, in which knowledge about the nature of the traffic excitation, such as its spatial correlation, is implanted into an autoregressive-moving-average (ARMA) model. The identifiability of the ARMA model so constructed is assured and the feasibility of the proposed identification technique is demonstrated by a numerical example

APPLICATION OF INDEPENDENT COMPONENT ANALYSIS FOR SOUND SOURCE SEPARATION

ABSTRACT In this paper, experiments on the application of the independent component analysis (ICA) technique to separate unknown source signals are reported. ICA is one of the fastest growing fields in signal processing with applications to speech recognition systems, telecommunications, and biomedical signal processing. It is a data-transformation technique that finds independent sources of activity from linear mixtures of unknown independent sources. The statistical method to measure independence is to find a linear representation of the non-Gaussian data so that the components are as independent as possible and the mutual information between them is minimum. Although extensive simulations have been performed to demonstrate the power of the learning algorithm for the problems of instantaneous mixing and un-mixing of sources, its application to the noise diagnosis and separation in an industrial setting has not been considered. Noise separation in machinery has a strong basis in the "cocktail problem" in which it is difficult to separate/isolate the voice of a person in a room filled with competing voices and noises. The experiments conducted consist of separating several artificially generated sources of noise. Our results demonstrate that ICA can be effectively employed for such kinds of applications. The underdetermined problem in which there are fewer sensors than sources in the ICA formulation is also examined by applying a time-invariant linear transformation of the acquired signals to identify a single source

The LRRK2 Arg1628Pro variant is a risk factor for Parkinson's disease in the Chinese population

The c.G4883C variant in the leucine-rich repeat kinase 2 (LRRK2) gene (protein effect: Arg1628Pro) has been recently proposed as a second risk factor for sporadic Parkinson's disease in the Han Chinese population (after the Gly2385Arg variant). In this paper, we analyze the Arg1628Pro variant and the associated haplotype in a large sample of 1,337 Han subjects (834 patients and 543 controls) ascertained from a single referral center in Taiwan. In our sample, the Arg1628Pro allele was more frequent among patients (3.8%) than among controls (1.8%; p = 0.004, OR 2.13, 95% CI 1.29-3.52). Sixty heterozygous and two homozygous carriers of the Arg1628Pro variant were identified among the patients, of which only one was also a carrier of the LRRK2 Gly2385Arg variant. We also show that carriers of the Arg1628Pro variant share a common, extended haplotype, suggesting a founder effect. Parkinson's disease onset age was similar in patients who carried the Arg1628Pro variant and in those who did not carry it. Our data support the contention that the Arg1628Pro variant is a second risk factor for Parkinson's disease in the Han Chinese population. Adding the estimated effects of Arg1628Pro (population attributable risk [PAR] ∼4%) and Gly2385Arg variants (PAR ∼6%) yields a total PAR of ∼10%

Important prognostic factors for the long-term survival of lung cancer subjects in Taiwan

<p>Abstract</p> <p>Background</p> <p>This study used a large-scale cancer database in determination of prognostic factors for the survival of lung cancer subjects in Taiwan.</p> <p>Methods</p> <p>Total of 24,910 subjects diagnosed with lung cancer was analysed. Survival estimates by Kaplan-Meier methods. Cox proportional-hazards model estimated the death risk (hazard ratio (HR)) for various prognostic factors.</p> <p>Results</p> <p>The prognostic indicators associated with a higher risk of lung cancer deaths are male gender (males versus females; HR = 1.07, 95% confidence intervals (CI): 1.03–1.11), males diagnosed in later periods (shown in 1991–1994 versus 1987–1990; HR = 1.13), older age at diagnosis, large cell carcinoma (LCC)/small cell carcinoma (SCC), and supportive care therapy over chemotherapy. The overall 5-year survival rate for lung cancer death was significantly poorer for males (21.3%) than females (23.6%). Subjects with squamous cell carcinoma (SQCC) and treatment by surgical resection alone had better prognosis. We find surgical resections to markedly increase 5-year survival rate from LCC, decreased risk of death from LCC, and no improved survival from SCC.</p> <p>Conclusion</p> <p>Gender and clinical characteristics (i.e. diagnostic period, diagnostic age, histological type and treatment modality) play important roles in determining lung cancer survival.</p

Phase I study of pegylated liposomal doxorubicin and the multidrug-resistance modulator, valspodar

Valspodar, a P-glycoprotein modulator, affects pharmacokinetics of doxorubicin when administered in combination, resulting in doxorubicin dose reduction. In animal models, valspodar has minimal interaction with pegylated liposomal doxorubicin (PEG-LD). To determine any pharmacokinetic interaction in humans, we designed a study to determine maximum tolerated dose, dose-limiting toxicity (DLT), and pharmacokinetics of total doxorubicin, in PEG-LD and valspodar combination therapy in patients with advanced malignancies. Patients received PEG-LD 20–25 mg m−2 intravenously over 1 h for cycle one. In subsequent 2-week cycles, valspodar was administered as 72 h continuous intravenous infusion with PEG-LD beginning at 8 mg m−2 and escalated in an accelerated titration design to 25 mg m−2. Pharmacokinetic data were collected with and without valspodar. A total of 14 patients completed at least two cycles of therapy. No DLTs were observed in six patients treated at the highest level of PEG-LD 25 mg m−2. The most common toxicities were fatigue, nausea, vomiting, mucositis, palmar plantar erythrodysesthesia, diarrhoea, and ataxia. Partial responses were observed in patients with breast and ovarian carcinoma. The mean (range) total doxorubicin clearance decreased from 27 (10–73) ml h−1 m−2 in cycle 1 to 18 (3–37) ml h−1 m−2 with the addition of valspodar in cycle 2 (P=0.009). Treatment with PEG-LD 25 mg m−2 in combination with valspodar results in a moderate prolongation of total doxorubicin clearance and half-life but did not increase the toxicity of this agent

STIM2 regulates PKA-dependent phosphorylation and trafficking of AMPARs

STIMs (STIM1 and STIM2 in mammals) are transmembrane proteins that reside in the endoplasmic reticulum (ER) and regulate store-operated Ca2+ entry (SOCE). The function of STIMs in the brain is only beginning to be explored, and the relevance of SOCE in nerve cells is being debated. Here we identify STIM2 as a central organizer of excitatory synapses. STIM2, but not its paralogue STIM1, influences the formation of dendritic spines and shapes basal synaptic transmission in excitatory neurons. We further demonstrate that STIM2 is essential for cAMP/PKA-dependent phosphorylation of the AMPA receptor (AMPAR) subunit GluA1. cAMP triggers rapid migration of STIM2 to ER–plasma membrane (PM) contact sites, enhances recruitment of GluA1 to these ER-PM junctions, and promotes localization of STIM2 in dendritic spines. Both biochemical and imaging data suggest that STIM2 regulates GluA1 phosphorylation by coupling PKA to the AMPAR in a SOCE-independent manner. Consistent with a central role of STIM2 in regulating AMPAR phosphorylation, STIM2 promotes cAMP-dependent surface delivery of GluA1 through combined effects on exocytosis and endocytosis. Collectively our results point to a unique mechanism of synaptic plasticity driven by dynamic assembly of a STIM2 signaling complex at ER-PM contact sites

Breast cancer prognostic classification in the molecular era: the role of histological grade

Breast cancer is a heterogeneous disease with varied morphological appearances, molecular features, behavior, and response to therapy. Current routine clinical management of breast cancer relies on the availability of robust clinical and pathological prognostic and predictive factors to support clinical and patient decision making in which potentially suitable treatment options are increasingly available. One of the best-established prognostic factors in breast cancer is histological grade, which represents the morphological assessment of tumor biological characteristics and has been shown to be able to generate important information related to the clinical behavior of breast cancers. Genome-wide microarray-based expression profiling studies have unraveled several characteristics of breast cancer biology and have provided further evidence that the biological features captured by histological grade are important in determining tumor behavior. Also, expression profiling studies have generated clinically useful data that have significantly improved our understanding of the biology of breast cancer, and these studies are undergoing evaluation as improved prognostic and predictive tools in clinical practice. Clinical acceptance of these molecular assays will require them to be more than expensive surrogates of established traditional factors such as histological grade. It is essential that they provide additional prognostic or predictive information above and beyond that offered by current parameters. Here, we present an analysis of the validity of histological grade as a prognostic factor and a consensus view on the significance of histological grade and its role in breast cancer classification and staging systems in this era of emerging clinical use of molecular classifiers. © 2010 BioMed Central Lt