Abstract:The fast-growing wind power industry faces the challenge of reducing operation and maintenance (O&M) costs for wind power plants. Predictive maintenance is essential to improve wind turbine reliability and prolong operation time, thereby reducing the O&M cost for wind power plants. This study presents a solution for predictive maintenance of wind turbine generators. The proposed solution can: (1) predict the remaining useful life (RUL) of wind turbine generators before a fault occurs and (2) diagnose the state of the wind turbine generator when the fault occurs. Moreover, the proposed solution implies low-deployment costs because it relies solely on the information collected from the widely available supervisory control and data acquisition (SCADA) system. Extra sensing hardware is needless. The proposed solution has been deployed and evaluated in two real-world wind power plants located in China. The experimental study demonstrates that the RUL of the generators can be predicted 18 days ahead with about an 80% prediction accuracy. When faults occur, the specific type of generator fault can be diagnosed with an accuracy of 94%.

Several attempts have been made to demonstrate the accuracy of the iPhone pedometer function in laboratory test conditions. However, no studies have attempted to evaluate evidence of convergent validity of the iPhone step counts as a surveillance tool in the field. This study takes a pragmatic approach to evaluating Health application derived iPhone step counts by measuring accuracy of a standardized criterion iPhone SE and a heterogeneous sample of participant owned iPhones (6 or newer) in a laboratory condition, as well as comparing personal iPhones to accelerometer derived steps in a free-living test. During lab tests, criterion and personal iPhones differed from manually counted steps by a mean bias of less than ±5% when walking at 5km/h, 7.5km/h and 10km/h on a treadmill, which is generally considered acceptable for pedometers. In the free-living condition steps differed by a mean bias of 21.5% or 1340 steps/day when averaged across observation days. Researchers should be cautioned in considering the use of iPhone models as a research grade pedometer for physical activity surveillance or evaluation, likely due to the iPhone not being continually carried by participants; if compliance can be maximized then the iPhone might be suitable.

Background Although poppers are increasingly popular among MSM in China, little is known about the patterns of poppers use. The objectives of this study were to describe the patterns of poppers use and examine its association with sexual behaviors and HIV infection among MSM in Beijing, China. Methods As part of a multi-component HIV intervention trial, 3588 MSM were surveyed between March 2013 and March 2014 in Beijing, China. Blood samples were collected and tested for HIV and syphilis. The questionnaire collected information about socio-demographic and behavioral characteristics. Univariate and multivariable logistic regression analyses were performed to evaluate the correlates of poppers use. Results Over a quarter of men (27.5%) reported having used at least one type of drugs in the past three months. Poppers were the most popular one (26.8%). Poppers use was correlated with a higher HIV prevalence [odds ratio (OR): 1.38, 95% confidence interval (CI): 1.11–1.70]. Demographic and sexual behavioral factors associated with poppers use included: younger age [adjusted OR (AOR): 1.56, 95% CI: 1.25–1.94], higher education (AOR: 1.61, 95% CI: 1.33–1.96), alcohol use (AOR: 1.32, 95% CI: 1.10–1.60), seeking male partners mainly via the internet (AOR: 1.60, 95% CI: 1.28–2.00), multiple male sex partnership (AOR: 2.22, 95% CI: 1.90–2.60), and unprotected receptive anal intercourse (AOR: 1.52, 95% CI: 1.28–1.81). Conclusions In this study, poppers use was positively associated with HIV infection and unprotected anal intercourse. Intervention efforts should be devoted to promote safer sex and HIV testing and counseling among MSM who use poppers.

We used a three-dimensional coupled hydrodynamic–ecological model to investigate how lake currents can affect walleye ( Sander vitreus ) recruitment in western Lake Erie. Four years were selected based on a fall recruitment index: two high recruitment years (i.e., 1996 and 1999) and two low recruitment years (i.e., 1995 and 1998). During the low recruitment years, the model predicted that (i) walleye spawning grounds experienced destructive bottom currents capable of dislodging eggs from suitable habitats (reefs) to unsuitable habitats (i.e., muddy bottom), and (ii) the majority of newly hatched larvae were transported away from the known suitable nursery grounds at the start of their first feeding. Conversely, during two high recruitment years, predicted bottom currents at the spawning grounds were relatively weak, and the predicted movement of newly hatched larvae was toward suitable nursery grounds. Thus, low disturbance-based egg mortality and a temporal and spatial match between walleye first feeding larvae and their food resources were predicted for the two high recruitment years, and high egg mortality plus a mismatch of larvae with their food resources was predicted for the two low recruitment years. In general, mild westerly or southwesterly winds during the spawning–nursery period should favour walleye recruitment in the lake.