Optimization problems for general simple population with n-impulsive harvest

AbstractIn this paper, n-impulsive harvest problems of general simple population are discussed by models with Dirac function. The optimal impulsive harvest policies to protect the renewable resource better are obtained under conditions of fixed quantity per impulsive harvest. Then, a concept of the sequence for Ϝ-optimal harvest moments for general simple population is presented which is beneficial to protect resource better and sustainable development. Finally, we apply the conclusions to some special models

Where Did the President Visit Last Week? Detecting Celebrity Trips from News Articles

Celebrities' whereabouts are of pervasive importance. For instance, where politicians go, how often they visit, and who they meet, come with profound geopolitical and economic implications. Although news articles contain travel information of celebrities, it is not possible to perform large-scale and network-wise analysis due to the lack of automatic itinerary detection tools. To design such tools, we have to overcome difficulties from the heterogeneity among news articles: 1)One single article can be noisy, with irrelevant people and locations, especially when the articles are long. 2)Though it may be helpful if we consider multiple articles together to determine a particular trip, the key semantics are still scattered across different articles intertwined with various noises, making it hard to aggregate them effectively. 3)Over 20% of the articles refer to the celebrities' trips indirectly, instead of using the exact celebrity names or location names, leading to large portions of trips escaping regular detecting algorithms. We model text content across articles related to each candidate location as a graph to better associate essential information and cancel out the noises. Besides, we design a special pooling layer based on attention mechanism and node similarity, reducing irrelevant information from longer articles. To make up the missing information resulted from indirect mentions, we construct knowledge sub-graphs for named entities (person, organization, facility, etc.). Specifically, we dynamically update embeddings of event entities like the G7 summit from news descriptions since the properties (date and location) of the event change each time, which is not captured by the pre-trained event representations. The proposed CeleTrip jointly trains these modules, which outperforms all baseline models and achieves 82.53% in the F1 metric.Comment: Accepted to ICWSM 2024, 12 page

Modified cotton fabrics for improved ultraviolet protection performance and reactive dyeing property

Reactive quaternary ammonium cationic compound, [2,3-epoxypropyl-1-methy imidazole ammonium chloride (EPMI)] has been synthesized with 1-methylimidazole and epoxy chloropropane to improve the dyeing property of cotton fabrics and the cationic cotton fabrics combined Fe3+ to obtain UV protective property. The dye fixation (F%) of three reactive dyes is found to be 84.5-89.7% on modified cotton fabrics. Ultraviolet protection factor (UPF) value of modified cotton fabric is increased to 137.47 from 7.57 of untreated cotton fabric. The breaking strength of modified cotton fabrics is well retained. The hue (h) of dyed samples before and after modification shows a little change. The UPF of modified cotton fabric shows excellent durability. After 50 laundering cycles, the UPF values decrease to 12.47%. Scanning electron microscopy observations and XRD patterns show that the modified cotton fibres are left nearly undamaged by the modification. The FTIR spectra suggest that the EPMI and Fe3+ are combined on the cotton fibres