Study on the Collaborative Design PN-PDDP Model for the Multi-component Coupling Rotor System Based on Petri Nets

AbstractBased on the analysis of the characteristics for the design process in the complex multi-component coupling rotor system, and considering the fact that the multi-components co-design is demanded in the design process of the performance-driven target coupled rotor system, a PN-PDDP (Petri Network for Performance Driven Design Process) model based on the extended Petri nets is presented. The model defines the libraries of the performance and structure characteristics, the traces Token and firing rules. With the model, the flow process of the various coupled information flow is described, and the conflict resolution mechanism for the conflict information is developed. The model also offers guidance on the construction of the related database and design platform, which will provide the important design tools and implementation means for the design of the multi-component coupling turbopump rotor system in the liquid rocket engine

Different forms of nitrogen contents and their vertical variations of transformation modes of the sediments of Lake Yuehu, Wuhan

Vertical distributions of nitrogen contents, net nitrification rates, net N-mineralization rates and nitrate reductase activities in sediments of Lake Yuehu in June, 2005, were described on basis of four samples from the lake. The results showed that there was a critical layer in which exchangeable nitrate contents were the highest. Exchangeable ammonium and available nitrogen contents were the lowest in the Subsurface sediment (5-10cm). Available nitrogen was stored mainly in the form of exchangeable ammonium in both surface (0-5cm deep) and deeper layers (>10cm deep) where their contents were higher. The pattern of this distribution can be explained by anaerobic conditions. The surface sediment not only showed higher contents of total nitrogen and organic nitrogen, rates of net nitrification, N-mineralization and nitrate reductase activities, but also displayed the highest ammonium and the lowest nitrate concentrations in interstitial water. Therefore, based on a nitrogen cycling mode, we proposed that organic nitrogen was re-mineralized to ammonium and nitrate with processes of the former being nitrified into the later, resulting in anaerobic conditions that contributed to ammonium accumulation by the production of its own and nitrate reduction in interstitial water of surface sediment. In general, the surface sediment in eutrophic lakes, enriched by organic nitrogen, is the most active dimension for the biogeochemical cycling of nitrogen with ammonium being the major and most effective forms

Evaluating the value of new metro lines using route diversity measures: the case of Hong Kong's Mass Transit Railway system

The Mass Transit Railway (MTR) serves as the backbone of the Hong Kong public transportation network and continues to be expanded in phases. Nevertheless, occasional but severe disruptions have raised concerns about whether the proposed MTR expansions will benefit the system resilience. To assess the value of each stage of MTR network expansion, it is key to identify the distributive effects of new metro lines on both accessibility and resilience. This paper applies the route diversity index, a relatively new accessibility indicator, to assess the effects of new lines and evaluate their spatial distribution, variation, and changes at nodal, dyadic, and network levels. The results indicate that the effects on accessibility and resilience will differ between each stage of MTR expansion. On the accessibility front, the benefits of reduced travel times and increased route diversity will be successively extended to more districts with each MTR expansion, and the spatial equity will also be improved gradually by the expansion, especially in isolated regions such as the northern and western New Territories. In contrast, on the resilience front, although the overall network vulnerability will be reduced, the vulnerability of certain parts of the network will be increased, which might necessitate additional resources to protect these stations. However, some new lines will reduce this vulnerability and provide a complementary solution to enhance network resilience. Overall, the insights from this study could assist in cost-effective resource allocation and informed decision-making for the prioritization of future railway investments and cost-effective resource allocation

Data-driven sea state estimation for vessels using multi-domain features from motion responses

Situation awareness is of great importance for autonomous ships. One key aspect is to estimate the sea state in a real-time manner. Considering the ship as a large wave buoy, the sea state can be estimated from motion responses without extra sensors installed. However, it is difficult to associate waves with ship motion through an explicit model since the hydrodynamic effect is hard to model. In this paper, a data-driven model is developed to estimate the sea state based on ship motion data. The ship motion response is analyzed through statistical, temporal, spectral, and wavelet analysis. Features from multi-domain are constructed and an ensemble machine learning model is established. Real-world data is collected from a research vessel operating on the west coast of Norway. Through the validation with the real-world data, the model shows promising performance in terms of significant wave height and peak period.acceptedVersio

Positive resources for combating depressive symptoms among Chinese male correctional officers: perceived organizational support and psychological capital

BACKGROUND: Although correctional officers (COs) clearly suffer from depression, positive resources for combating depression have been rarely studied in this population. The purpose of the study was to examine the associations of perceived organizational support (POS) and psychological capital (PsyCap) with depressive symptoms among Chinese COs. METHODS: A cross-sectional survey was conducted in a province of northeast China during March–April 2011. A self-administered questionnaire was distributed to 1900 male COs from four male prisons. Depressive symptoms, POS, and PsyCap (self efficacy, hope, resilience, and optimism) were measured anonymously. A total of 1428 effective respondents with 953 frontline COs (FL-COs) and 475 non-frontline COs (NFL-COs) became our final sample. Hierarchical linear regression was performed to explore the factors associated with depressive symptoms. Asymptotic and resampling strategies were used to examine the mediating roles of PsyCap and its four components. RESULTS: The level of depressive symptoms of FL-COs was significantly higher than that of NFL-COs (t = 2.28, p = 0.023). There were significant negative associations of POS, PsyCap, hope, resilience, and optimism with depressive symptoms among FL-COs. In NFL-COs, POS, PsyCap, and optimism were negatively associated with depressive symptoms. POS was positively associated with PsyCap and its four components among both FL-COs and NFL-COs. For FL-COs, PsyCap (a*b = −0.143, BCa 95% CI: –0.186, –0.103, p < 0.05), resilience (a*b = −0.052, BCa 95% CI: –0.090, –0.017, p < 0.05), and optimism (a*b = −0.053, BCa 95% CI: –0.090, –0.016, p < 0.05) significantly mediated the association between POS and depressive symptoms. For NFL-COs, PsyCap (a*b = −0.126, BCa 95% CI: –0.186, –0.065, p < 0.05) and optimism (a*b = −0.066, BCa 95% CI: –0.116, –0.008, p < 0.05) significantly mediated the association. CONCLUSIONS: Perceived organizational support and psychological capital could be positive resources for combating depressive symptoms in Chinese male COs. Psychological capital and its components (resilience and optimism) partially mediate the association between perceived organizational support and depressive symptoms. Therefore, organizational support and psychological capital investment (especially resilience and optimism) should be included in depression preventions and treatments targeting Chinese male COs

An Uncertainty-aware Hybrid Approach for Sea State Estimation Using Ship Motion Responses

Situation awareness is essential for autonomous ships. One key aspect is to estimate the sea state in a real-time manner. Considering the ship as a large wave buoy, the sea state can be estimated from motion responses without extra sensors installed. This task is challenging since the relationship between the wave and the ship motion is hard to model. Existing methods include a wave buoyanalogy (WBA) method, which assumes linearity between wave and ship motion, and a machine learning (ML) approach. Since the data collected from a vessel in the real world is typically limited to a small range of sea states, the ML method might suffer from catastrophic failure when the encountered sea state is not in the training dataset. This paper proposes a hybrid approach that combined the two methods above. The ML method is compensated by the WBA method based on the uncertainty of estimation results and, thus, the catastrophic failure can be avoided. Real-world historical data from the Research Vessel (RV) Gunnerus are applied to validate the approach. Results show that the hybrid approach improves estimation accuracy.acceptedVersio

Time-series stream temperature and dissolved oxygen modeling in the Lower Flint River Basin

In the Lower Flint River Basin (LFRB), ex- cessive groundwater withdrawals and possible water supply reservoirs threaten to exacerbate low ow conditions during summer droughts, possibly leading stream temperature and dissolved oxygen (DO) levels detrimental to aquatic biota. To evaluate possible effects of human modi cations to stream habitat, summer time-series of stream temperature and DO were monitored over the last three years along these streams. Continuously Stirred Tank Reactor (CSTR) models for tem- perature and DO were developed and calibrated with these data. The dominant drivers of stream temperature and DO were identi ed by this model. Simulations were conducted with assumed managed ow conditions to illustrate potential effects of various stream ow regimes on stream temperature and DO time-series. The goal of this research is to provide an accurate simulation tool to guide management decisions.Sponsored by: Georgia Environmental Protection Division U.S. Geological Survey, Georgia Water Science Center U.S. Department of Agriculture, Natural Resources Conservation Service Georgia Institute of Technology, Georgia Water Resources Institute The University of Georgia, Water Resources Facult

Towards Content-based Pixel Retrieval in Revisited Oxford and Paris

This paper introduces the first two pixel retrieval benchmarks. Pixel retrieval is segmented instance retrieval. Like semantic segmentation extends classification to the pixel level, pixel retrieval is an extension of image retrieval and offers information about which pixels are related to the query object. In addition to retrieving images for the given query, it helps users quickly identify the query object in true positive images and exclude false positive images by denoting the correlated pixels. Our user study results show pixel-level annotation can significantly improve the user experience. Compared with semantic and instance segmentation, pixel retrieval requires a fine-grained recognition capability for variable-granularity targets. To this end, we propose pixel retrieval benchmarks named PROxford and PRParis, which are based on the widely used image retrieval datasets, ROxford and RParis. Three professional annotators label 5,942 images with two rounds of double-checking and refinement. Furthermore, we conduct extensive experiments and analysis on the SOTA methods in image search, image matching, detection, segmentation, and dense matching using our pixel retrieval benchmarks. Results show that the pixel retrieval task is challenging to these approaches and distinctive from existing problems, suggesting that further research can advance the content-based pixel-retrieval and thus user search experience. The datasets can be downloaded from \href{https://github.com/anguoyuan/Pixel_retrieval-Segmented_instance_retrieval}{this link}