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I have a folder or articles in my EBSCOhost account. On the left of each article, there are words like "export", "cite", and "notes". What do they do?
Please see the answers to your questions below about features in EBSCO's MyEBSCO folder. On the left of each article, there are words like "export", "cite", and "notes".
- These features allow you to manage the contents of the folder. For example, if you want to export the citation to a citation management (https://guides.lib.lsu.edu/c.php?g=279388&p=1862193) tool like Endnote or Zotero, you can do that. Or if you want to make notes about the citation and come back to them at a later date, the note for that citation will still be there. If you are interested in learning more about citation management and how it can help you organize your research, refer to our Citation LibGuide (https://guides.lib.lsu.edu/citation) as well as our workshop (https://www.youtube.com/watch?v=wRcFIlrWpDg&list=PL5ZtZe36ynPlutYgX4_x0…) about Zotero where you will learn how to set up Zotero to save and store sources and generate citations. To view upcoming workshops, please use our events calendar (https://lsu.libcal.com/calendar/eventsandprogramming) . What do these features actually do? How long does content remain in my folder?
- As long as you are logged into the MyEBSCOhost platform, the citations will stay there until you remove them. Here are some FAQs (https://connect.ebsco.com/s/article/EBSCOhost-Folder-Frequently-Asked-Q….) regarding how long content is kept in the folder. How do I delete an article from my folder if it is not relevant?
- To remove result(s) from your personalized folder, select the result by clicking on the appropriate check box, then click the Delete Items link. You may find this page (https://connect.ebsco.com/s/article/How-to-Use-the-My-EBSCOhost-Folder?…) useful in learning how to use the folder as well. Feel free to reach out to your subject librarian (https://www.lib.lsu.edu/staff?field_staff_type=2&search_api_staff=&fiel…) for more assistance. eResources Staff Answered by: Electronic Resources

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Catch fish optimization algorithm: a new human behavior algorithm for solving clustering problems
This paper is inspired by traditional rural fishing methods and proposes a new metaheuristic optimization algorithm based on human behavior: Catch Fish Optimization Algorithm (CFOA). This algorithm simulates the process of rural fishermen fishing in ponds, which is mainly divided into two phases: the exploration phase and the exploitation phase. In the exploration phase, there are two stages to search: first, the individual capture stage based on personal experience and intuition, and second, the group capture stage based on human proficiency in using tools and collaboration. Transition from independent search to group capture during the exploration phase. Exploitation phase: All fishermen will surround the shoal of fish and work together to salvage the remaining fish, a collective capture strategy. CFOA model is based on these two phases. This paper tested the optimization performance of CFOA using IEEE CEC 2014 and IEEE CEC 2020 test functions, and compared it with 11 other optimization algorithms. We employed the IEEE CEC2017 function to evaluate the overall performance of CFOA. The experimental results indicate that CFOA exhibits excellent and stable optimization capabilities overall. Additionally, we applied CFOA to data clustering problems, and the final results demonstrate that CFOA’s overall error rate in processing clustering problems is less than 20%, resulting in a better clustering effect. The comprehensive experimental results show that CFOA exhibits excellent optimization effects when facing different optimization problems. CFOA code is open at https://github.com/Meky-1210/CFOA.git.
Regulatory element in fibrin triggers tension-activated transition from catch to slip bonds
Fibrin formation and mechanical stability are essential in thrombosis and hemostasis. To reveal how mechanical load impacts fibrin, we carried out optical trap-based single-molecule forced unbinding experiments. The strength of noncovalent A:a knob-hole bond stabilizing fibrin polymers first increases with tensile force (catch bonds) and then decreases with force when the force exceeds a critical value (slip bonds). To provide the structural basis of catch–slip-bond behavior, we analyzed crystal structures and performed molecular modeling of A:a knob-hole complex. The movable flap (residues γ 295 to γ 305) containing the weak calcium-binding site γ 2 serves as a tension sensor. Flap dissociation from the B domain in the γ -nodule and translocation to knob ‘A’ triggers hole ‘a’ closure, resulting in the increase of binding affinity and prolonged bond lifetimes. The discovery of biphasic kinetics of knob-hole bond rupture is quantitatively explained by using a theory, formulated in terms of structural transitions in the binding pocket between the low-affinity (slip) and high-affinity (catch) states. We provide a general framework to understand the mechanical response of protein pairs capable of tension-induced remodeling of their association interface. Strengthening of the A:a knob-hole bonds at 30- to 40-pN forces might favor formation of nascent fibrin clots subject to hydrodynamic shear in vivo.