114 research outputs found
DynamicLight: Dynamically Tuning Traffic Signal Duration with DRL
Deep reinforcement learning (DRL) is becoming increasingly popular in
implementing traffic signal control (TSC). However, most existing DRL methods
employ fixed control strategies, making traffic signal phase duration less
flexible. Additionally, the trend of using more complex DRL models makes
real-life deployment more challenging. To address these two challenges, we
firstly propose a two-stage DRL framework, named DynamicLight, which uses Max
Queue-Length to select the proper phase and employs a deep Q-learning network
to determine the duration of the corresponding phase. Based on the design of
DynamicLight, we also introduce two variants: (1) DynamicLight-Lite, which
addresses the first challenge by using only 19 parameters to achieve dynamic
phase duration settings; and (2) DynamicLight-Cycle, which tackles the second
challenge by actuating a set of phases in a fixed cyclical order to implement
flexible phase duration in the respective cyclical phase structure. Numerical
experiments are conducted using both real-world and synthetic datasets,
covering four most commonly adopted traffic signal intersections in real life.
Experimental results show that: (1) DynamicLight can learn satisfactorily on
determining the phase duration and achieve a new state-of-the-art, with
improvement up to 6% compared to the baselines in terms of adjusted average
travel time; (2) DynamicLight-Lite matches or outperforms most baseline methods
with only 19 parameters; and (3) DynamicLight-Cycle demonstrates high
performance for current TSC systems without remarkable modification in an
actual deployment. Our code is released at Github.Comment: 9 pages, 5figure
Selenite benefits embryonic stem cells therapy in the animal models of Parkinson’s disease through inhibiting inflammation
B vitamins supplementation induced shifts in phytoplankton dynamics and copepod populations in a subtropical coastal area
IntroductionB vitamins play a crucial role in shaping phytoplankton and zooplankton communities in marine ecosystems, yet their impact on community dynamics remains poorly understood.MethodsWe carried out in situ incubation experiments of B vitamins supplementation to explore the response pattern of phytoplankton and zooplankton community compositions.ResultsThe results showed that vitamins B1, B2, B6 and B12 promoted the growth of phytoplankton, and the total Chl α in 87.5% of the supplemented B vitamin treatments showed a significant positive response (p < 0.05). Supplementation with these B vitamins significantly altered the community composition of phytoplankton, and 75% of the B vitamin-supplemented treatments showed an increase in the relative abundance of Minutocellus, Thalassiosirales, Odontella, Prymnesiales and Ditylum, considered mainly to be the result of B vitamin auxotrophy. In contrast, a significant decrease in Copepoda, including Calanoida and Cyclopoida, was observed in 87.5% of treatments. The observed shifts in community composition were attributed to the auxotrophy of certain diatoms and Prymnesiales for B vitamins. These shifts subsequently led to negative correlations (Spearman Rho < -0.8) between the abundance of these phytoplankton species and Copepoda populations.DiscussionThese findings advance our understanding of the complex interactions between micronutrient availability and plankton community dynamics
Boosting Heterosubtypic Neutralization Antibodies in Recipients of 2009 Pandemic H1N1 Influenza Vaccine
Our data demonstrated that the inoculation with vaccine derived from the 2009 pandemic influenza raised vigorous neutralization antibodies against both cognate H1N1 and heterotypic influenza viruses. This observation has important implication for vaccine development
Better or worse food: Nutrition value of the prey fishes and the potential health implications for Indo-Pacific humpback dolphins
IntroductionOverfishing and climate change have combined to cause fishery stocks to decline and fish community composition to change, further threatening the predation and nutritional health of marine mammals.MethodsIn this study, we collected potential prey fishes catched by fishermen in six habitats of Indo-Pacific humpback dolphins and analyzed their proximate composition (moisture, water, fat and protein), the fatty acid composition and the amino acid composition to evaluate the possible health effect on humpback dolphins.ResultsThe results showed that the nutritional composition varied significantly with species and locations. Fishes in the families Sciaenidae and Engraulidae displayed richer fatty acid composition, while those in the family Clupeidae had the highest value of amino acid quality index. In Zhuhai, home to the largest Indo-Pacific humpback dolphin population, pelagic/neritic prey fishes possessed lower energy density, PUFA content, PUFA/SFA ratio, DHA content, and EAA content compared to demersal fish, suggesting nutritional stress when there is a dietary switch from demersal to pelagic/neritic fishes in Zhuhai population.DiscussionOur study provided a framework, with energy density and fatty acid composition as its most important indicator, for assessment of the marine top predators based on the nutritional composition of their prey fishes and revealed the potential threats. Data here is expected to facilitate the development of scientific programs for successful conservation of not only the Indo-Pacific humpback dolphins, but also other marine top predators, possibly through reconstructing their prey fish’s quantity and quality
A Parallel Disjointed Multi-path Routing Algorithm based on OLSR and Energy in Ad Hoc Networks
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