Combining active structural damping and active suspension control in flexible bodied railway vehicles

There is a desire to design lightweight railway vehicle bodies for future high speed trains. Previously, suppression of structural vibration of the flexible lightweight vehicle body was attempted via use of active suspensions (conventional actuators) or by structural damping via piezoelectric actuators, with the aim being to improve the ride quality. In a railway vehicle the typical active suspension setup comprises front and rear suspension conventional actuators, while adding more macro-actuator elements to minimise structural vibrations can substantially impact vehicle weight and location considerations. In this paper, we show that piezoelectric actuator control can provide complementary action to active suspensions. Decentralized control is adopted for combined active structural damping and active suspension design via Linear Quadratic Gaussian (LQG) method and modal control with skyhook damping respectively. The side-view model of a flexible-bodied railway vehicle integrated with piezoelectric actuators and appropriate sensor outputs is derived and the placement of the piezoelectric actuators and sensors is addressed via structural norms. It is shown that vibrations of both the flexible modes and rigid modes are suppressed effectively. This suggests that with the combined approach, control by both piezoelectric actuators and suspension actuators could be used in a more efficient way to address vibrations in light railway vehicle bodies

Does Employee Substance Abuse Predict Fraud?

Motivated by survey evidence, we examine the relation between worker substance abuse and workplace fraud. In our sample of white-collar professionals, nearly 10% of all frauds occur in the 0.01% of worker-years where the worker receives a professional sanction for substance abuse. Workers receiving such a sanction are between 40 and 50 times more likely to commit fraud in the current year relative to their peers. These results are consistent with prior research suggesting that substance abuse creates financial pressures and impairs neural functioning of self-regulatory mechanisms, both of which make fraud more appealing. We also find that there is no increased likelihood to commit fraud among workers with past or future substance abuse sanctions. This suggests that (1) workers with past but not current substance problems are not a fraud risk, and (2) the results we observe are driven by actual substance abuse, as opposed to stable personality traits predictive of both fraud and substance abuse. This study has implications for employers and policymakers as they consider both how to prevent fraud and how to reduce the negative impact of substance abuse in the workplace through internal control systems and practices like Employee Assistance Programs

Male Clients of Male Sex Workers in China: An Ignored High-Risk Population.

BackgroundThere is a high prevalence of HIV/syphilis among male sex workers, but no formal study has ever been conducted focusing on male clients of male sex workers (MCM). A detailed investigation was thus called for, to determine the burden and sociobehavioral determinants of HIV and syphilis among these MCM in China.MethodsAs part of a multicenter cross-sectional study, using respondent-driven and snowball sampling, 2958 consenting adult men who have sex with men (MSM) were recruited, interviewed, and tested for HIV and syphilis between 2008 and 2009. The distributions of sociodemographic characteristics, risk behaviors, and HIV/syphilis prevalence were determined and compared between MCM and other MSM.ResultsAmong recruited MSM, 5.0% (n = 148) were MCM. HIV prevalences for MCM and other MSM were 7.4% and 7.7%, whereas 18.9% and 14.0% were positive for syphilis, respectively. Condomless anal intercourse (CAI) was reported by 59.5% of MCM and 48.2% of MSM. Multiple logistic regression revealed that compared with other MSM, MCM were more likely to have less education [for ≤ elementary level, adjusted odds ratio (aOR) = 3.13, 95% confidence interval (95% CI): 1.42 to 6.90], higher income (for >500 US Dollars per month, aOR = 2.97, 95% CI: 1.53 to 5.77), more often found partners at parks/restrooms (aOR = 4.01, 95% CI: 2.34 to 6.85), reported CAI (aOR = 1.49, 95% CI: 1.05 to 2.10), reported a larger sexual network (for ≥ 10, aOR = 2.70, 95% CI: 1.44 to 5.07), and higher odds of syphilis (aOR = 1.54, 95% CI: 1.00 to 2.38).ConclusionsThe greater frequency of risk behaviors and high prevalence of HIV and syphilis indicated that HIV/syphilis prevention programs in China need to pay special attention to MCM as a distinct subgroup, which was completely ignored until date

Tris-Quarternary Ammonium Salts and Methods for Modulating Neuronal Nicotinic Acetylcholine Receptors

Provided are tris-quaternary ammonium compounds which are modulators of nicotinic acetylocholine receptors. Also provided are methods of using the compounds for modulating the function of a nicotinic acetylcholine receptor, and for the prevention and/or treatment of central nervous system disorders, substance use and/or abuse and or gastrointestinal tract disorders

A PropertyLed Approach to Cluster Development

This article assesses inter-company networks based on a type of urban area labelled as a 'creative industry cluster' (CCJQ) and explores the interaction between CCJQs and creative industry networks. With the use of questionnaire surveys and interviews, Shanghai's property-led clusters are found to contain inter-company networks; however, most linkages are part of companies' own inter-group networks. Thus, individual companies -not clusters -drive the evolution of creative industry networks. Accordingly, three problems are identified: the exclusion of network dynamics, weak institutional basis and inadequate local creativity. Finally, this article identifies the variables of CCJQs that affect company networks and offers advice for cluster improvement

Graph Neural Processes for Spatio-Temporal Extrapolation

We study the task of spatio-temporal extrapolation that generates data at target locations from surrounding contexts in a graph. This task is crucial as sensors that collect data are sparsely deployed, resulting in a lack of fine-grained information due to high deployment and maintenance costs. Existing methods either use learning-based models like Neural Networks or statistical approaches like Gaussian Processes for this task. However, the former lacks uncertainty estimates and the latter fails to capture complex spatial and temporal correlations effectively. To address these issues, we propose Spatio-Temporal Graph Neural Processes (STGNP), a neural latent variable model which commands these capabilities simultaneously. Specifically, we first learn deterministic spatio-temporal representations by stacking layers of causal convolutions and cross-set graph neural networks. Then, we learn latent variables for target locations through vertical latent state transitions along layers and obtain extrapolations. Importantly during the transitions, we propose Graph Bayesian Aggregation (GBA), a Bayesian graph aggregator that aggregates contexts considering uncertainties in context data and graph structure. Extensive experiments show that STGNP has desirable properties such as uncertainty estimates and strong learning capabilities, and achieves state-of-the-art results by a clear margin.Comment: SIGKDD 202

Characterization and Quantification of Isoprene-Derived Epoxydiols in Ambient Aerosol in the Southeastern United States

Isoprene-derived epoxydiols (IEPOX) are identified in ambient aerosol samples for the first time, together with other previously identified isoprene tracers (i.e., 2-methyltetrols, 2-methylglyceric acid, C5-alkenetriols, and organosulfate derivatives of 2-methyltetrols). Fine ambient aerosol collected in downtown Atlanta, GA and rural Yorkville, GA during the 2008 August Mini-Intensive Gas and Aerosol Study (AMIGAS) was analyzed using both gas chromatography/quadrupole mass spectrometry (GC/MS) and gas chromatography/time-of-flight mass spectrometry (GC/TOFMS) with prior trimethylsilylation. Mass concentrations of IEPOX ranged from ~1 to 24 ng m^(−3) in the aerosol collected from the two sites. Detection of particle-phase IEPOX in the AMIGAS samples supports recent laboratory results that gas-phase IEPOX produced from the photooxidation of isoprene under low-NO_x conditions is a key precursor of ambient isoprene secondary organic aerosol (SOA) formation. On average, the sum of the mass concentrations of IEPOX and the measured isoprene SOA tracers accounted for about 3% of the organic carbon, demonstrating the significance of isoprene oxidation to the formation of ambient aerosol in this region