Evaluation of the effectiveness of active and passive safety measures in preventing ship–bridge collision

The risk of ship–bridge collisions should be evaluated using advanced models to consider different anti-collision and bridge-protection measures. This study aimed to propose a method to evaluate the effectiveness of active and passive safety measures in preventing ship–bridge collision. A novel ship–bridge collision probability formulation taking into consideration different safety measures was proposed. The model was applied at Jintang Bridge in China where the surrounding vessel traffic is ultra-crowded. We calculated the collision probability between the bridge and passing traffic using automatic identification system (AIS) data, Monte Carlo simulation, and Bayesian networks. Results under four different safety measures (i.e., active measures, passive measures, both measures and none) were analyzed and compared. The analysis concluded that both active and passive safety measures are effective in reducing the ship–bridge collision probability. Active measures, if deployed properly, can provide protection at an equivalent level than passive measures against collision risks. However, passive measures, such as setting arresting cables, are necessary in cases where the response time of the active measures is long. The proposed method and the results obtained from the case study may be useful for robust and systematic effectiveness evaluation of safety measures in other cases worldwide.Postprint (published version

Predicting the response of three common subtropical tree species in China to climate change

IntroductionClimate is crucial factor influencing species distribution, and with global climate change, the potential geographic distribution of species will also alter. In this study, three subtropical tree species (Cunninghamia lanceolata, Pinus taiwanensis, and Quercus glauca) of great ecological values were selected as research objects.MethodsWe applied a maximum entropy (MaxEnt) to predict their potential distributions under different climate scenarios in both present and future conditions based on 37 environmental factors. Jackknife test was used in key factors affecting species distribution. In addition, we explored the key environmental variables that affect their distributions and revealed the evolutionary patterns and migration trends of these tree species under future climate.ResultsThe main findings are as follows: (1) Winter temperature, winter precipitation, and annual temperature range are identified as the key environmental variables affecting the potential geographic distribution of the three tree species; moreover, precipitation-related factors have a greater impact than temperature-related factors; (2) Currently suitable habitats for these three tree species are primarily located in subtropical China with decreasing suitability from south to north; (3) Under future climate conditions, the area of potentially suitable habitat for C. lanceolata continues to expand, while P. taiwanensis and Q. glauca tend to experience a reduction due to increasing greenhouse gas emissions over time; and (4) The centroid of suitable habitat for C. lanceolata shifts northward under future climate change, while the centroid of P. taiwanensis and Q. glauca move southward along with shrinking suitable habitat area.DiscussionOur predictions highlight a high risk of habitat loss of Q. glauca under climate change, recommending management and conservation references for these three commonly used afforestation species under current and future climate change scenarios in China

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

Teach and Tell: Access Services’ Frontline Rolein Patron-Centered Activities

Presented at the 2016 Access Services Conference, Georgia Tech Global Learning Center and the Georgia Tech Hotel and Conference Center, November 16-18, 2016, Atlanta, Georgia.Yini Zhu is a Managing Librarian and Head of Access Services at George F. Smith Library of the Health Sciences at Rutgers, the State University of New Jersey. Her responsibilities include the development of public services policies, library technology, and faculty research support. She manages and coordinates the planning of all operational activities and outreach programs of Media/Computer Center, Circulation Department, and Interlibrary Loan Department. In addition, she oversees the internal planning and operation of all technology functions within the library, as well as the design, development and maintenance of the George F. Smith Library’s website and the Health Sciences Distance Learning website. After earning a Bachelor of Art in English Language and Literature from Yangzhou University in China, Yini Zhu pursued her graduate degree in the Information and Libraries Sciences from Rutgers University where she earned her MLS in 1994. Her passion in the medical information technology and informatics research led her to her second Masters degree in Medical Informatics from Rutgers University and New Jersey Institute of Technology. She was named a NLM Medical Informatics Fellow for which she attended a week-long medical informatics study at Augusta University, Georgia, in April 2016. Yini Zhu is actively involved in scholarly activities including research data management, graduate level teaching, presentations, grant writing, and applied information research.Within the library, the Access Services staff stand at the convergence of users and services and are armed with core functional skills. Yet despite this advantage, they have traditionally played a passive role in patron-centered outreach. Our objective was to see if Access Services could play an active role in promoting library services to enhance academic learning and research. The “Teach and Tell” project began with identifying each Access Services Department’s (Circulation, ILL, and Media/Computer) unique services and expertise. Potential outreach activities were then identified for different target library patron populations. Through these outreach activities, the Access Services staff contributed significantly to raising awareness of library services and promoting a positive library image. This project demonstrated that Access Services can go far beyond its traditional, passive desk function and succeed in building confidence and motivation among staff to take on active roles in patron-centered activities

Consumer’s Waste Classification Intention in China: An Extended Theory of Planned Behavior Model

Although there have been a variety of studies on waste classification management, there are few studies on how governments can effectively publicize waste classification knowledge in order to enhance citizen participation. Government publicity may be the key to the effective implementation of waste classification management in China. The purpose of this study is to examine the effects of government publicity, consumer attitudes, subjective norms, perceived behavioral control and consumer knowledge on consumers’ willingness to classify waste in the process of waste management in China. The methodology used for the study included data collected from a survey conducted among citizens from four cities in China, the extended theory of planned behavior model and a moderating effect analyses using the statistical software Amos17.0 and SPSS 22.0, utilizing structural equation modeling, hierarchical regression, and the interpretation of the results. The results show that government publicity has a significant positive impact on consumer attitudes, subjective norms, and perceived behavioral control. The positive effect of consumer attitudes and perceived behavioral control on waste classification intentions are significant. Consumer knowledge plays a significant role in moderating the effect of perceived behavioral control on waste classification intentions. The findings of this study are of great significance to government and public decision-making. The results strongly suggest that the government should vigorously publicize the knowledge of waste classification at the initial stage of implementation of waste classification. Furthermore, a detailed distinction between types of consumers and the role of personal values in the implementation of waste classification is considered as a direction of future research

Effects of Preparedness on Successful Emergency Response to Ship Accident Pollution Using a Bayesian Network

With the rapid development of international trade and the fast growth of port freight volumes, the risk of ship pollution in marine areas has significantly increased. Frequent ship pollution accidents seriously endanger marine ecosystems and are extremely unfavorable to economic development and marine environmental protection. In this study, we investigate the results of emergency responses after ship pollution accidents and analyze the factors affecting a successful emergency response. A Bayesian network model of the emergency response results of ship pollution is established, and the emergency response results of ship pollution accidents in the example of Zhoushan Port are analyzed. Based on the analysis, suggestions for strengthening the emergency preparedness of Zhoushan Port are proposed. We believe that the results of this are beneficial for improving ship pollution risk management and decision making, and that they have practical significance for marine environmental protection

Evaluation of the Effectiveness of Active and Passive Safety Measures in Preventing Ship–Bridge Collision

The risk of ship–bridge collisions should be evaluated using advanced models to consider different anti-collision and bridge-protection measures. This study aimed to propose a method to evaluate the effectiveness of active and passive safety measures in preventing ship–bridge collision. A novel ship–bridge collision probability formulation taking into consideration different safety measures was proposed. The model was applied at Jintang Bridge in China where the surrounding vessel traffic is ultra-crowded. We calculated the collision probability between the bridge and passing traffic using automatic identification system (AIS) data, Monte Carlo simulation, and Bayesian networks. Results under four different safety measures (i.e., active measures, passive measures, both measures and none) were analyzed and compared. The analysis concluded that both active and passive safety measures are effective in reducing the ship–bridge collision probability. Active measures, if deployed properly, can provide protection at an equivalent level than passive measures against collision risks. However, passive measures, such as setting arresting cables, are necessary in cases where the response time of the active measures is long. The proposed method and the results obtained from the case study may be useful for robust and systematic effectiveness evaluation of safety measures in other cases worldwide