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Does the library offer a book delivery service?
Yes, LSU Library offers book deliveries to faculty and staff only . We will deliver LSU Library books and interlibrary loan books to your departmental mailbox. Reserve and Government Document materials will not be included. To use the service, request the item through your interlibrary loan account. On the request form under "Delivery Options" select "Deliver to Departmental Mailbox." The request will arrive 1-2 business days from the date we receive the item. Heres how to get your materials delivered:
- You will need an ILLiad account to make the request.
- Once logged in, you will need to select "Deliver to Departmental Mailbox" for your Delivery Method. Books will be delivered to the departmental mailbox of the requestors within 1-2 business days. A second attempt will be made if the delivery is not successful the first time, but if the department office is inaccessible again, patrons will receive an e-mail stating the problem and asking them to come pick up their materials.
- The materials will be placed on hold and kept at the checkout desk for 7 days. If they are not picked up in this time frame, they will be returned to the collection. Be aware of the following:
- Users are responsible for returning materials back to the library.
- Materials will be checked out to the patrons library account prior to being delivered.
- The user is responsible for the items requested through this service.
- Any LSU Library books not returned or renewed within 40 days of the due date will be considered lost and the usual penalties will apply.
- A limit of eight physical material format items can be requested per day. LSU Libraries | Book Delivery Answered by: Access Services Staff

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2058654
Assessing the indicated impact of cantrang (boat Danish seine) based on catch characteristics in Java Sea, Indonesia
Cantrang (boat Danish seine) has been illegal since 2015 but remains prevalent in Indonesia’s Java Sea. Despite known negative impacts, no comprehensive ecological assessment of cantrang fishing exists. This study evaluates its effects by analyzing catch data based on taxa, trophic level, habitat, and fishing vulnerability by a multivariate approach. In this study, the size of 60 cantrang vessel samples were grouped into 4, namely 20–30, 31–50, 51–100, and 101–200 gross tons (GT), representing the spatial distribution of the fishing grounds. Larger vessels catch more diverse and abundant fish, primarily reef-associated and demersal species groups. There was a significant difference in the fishing vessel’s size on the catch’s composition (analysis of similarities, ANOSIM R = 0.114, p = 0.024). The dominant catches were families of Loliginidae (Loligo sp., 24.38%) and Nemipteridae (Nemipterus nematophorus, 19.29%), trophic level 2.7 (34.41–43.18%), reef-associated and demersal fish (37.06–46.09%), and low vulnerability group of fish (58.01–64.56%). Additionally, 2.69–8.56% of the endangered, threatened, and protected species of wedgefish (Rhyncobatus sp.) were also caught by the cantrang. This study confirms the impacts of cantrang on fish resources in the Java Sea, Indonesia’s Fisheries Management Area 712. The findings emphasize the need to improve management strategies to achieve sustainable fish resources and marine biodiversity in the region.
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.
Does soak time influence the effect of artificial light on catch efficiency in snow crab (Chionoecetes opilio) pot fishery?
In the Barents Sea commercial snow crab (Chionoecetes opilio) fishery, an increase in catch efficiency of the conical pots is important for the profitability of the industry. Light emitting diodes (LEDs) have previously been tested for increasing catch efficiency of the snow crab pots. These earlier experiments have shown varying results ranging from large increase in snow crab catches to no significant effect. These experiments have used different pot soaking times; however, the soaking time might affect the impact of LEDs on catch efficiency. In commercial snow crab fishery, the pot soak time is varying which has not been considered in earlier experiments testing the effect of LEDs. Therefore, this study examined whether pot soaking time can explain the observed differences in relative catch efficiency of snow crab pots with and without LEDs with soak times ranging from 2 to 14 days in the Barents Sea snow crab fishery. For target sizes of snow crab (≥95 mm carapace width), results indicated an increase in catch efficiency between 10 and 30% for pots with LEDs with exception of one experiment using six days soak time. However, experimental results were subjected to large uncertainties and, except from one experiment with five days soak time, the estimated increases were nonsignificant. Furthermore, the pot soak time was not found to impact the effect of white LEDs on capture efficiency.
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.
A new method for predicting wind-driven rain catch ratios on building facades in urban residential areas using machine learning models
The distribution of wind-driven rain on building facades significantly affects their thermal performance and durability. Accurately and efficiently predicting the wind-driven rain catch ratio on wall surfaces is crucial for building performance evaluation. This study proposes a novel computational approach to rapidly predict the wind-driven rain catch ratio on urban building facades. A predictive model was developed using extensive numerical simulations combined with machine learning algorithms. Specifically, the model replaces traditional numerical simulations by learning the influence of wind field characteristics and building geometry on raindrop catch ratios across different sizes. The research results indicate that the machine learning models can effectively substitute conventional simulation methods for wind-driven rain predictions. Notably, the Artificial Neural Network model achieved a prediction accuracy comparable to numerical simulations (RMSE: 0.009, MAE: 0.006) while being over 300 times faster. The inlet wind speed at roof height emerged as the most influential feature, and the model exhibited strong generalization performance across varying wind directions. This method is simple, efficient, and well-suited to support wind-driven rain analysis, experimental measurements, and urban energy consumption studies in residential building contexts.
Knowledge and awareness of human papillomavirus (HPV) influence HPV vaccination uptake among the catch-up generation in Japan
Introduction Despite its importance for young women, the human papillomavirus (HPV) vaccination coverage remains low in Japan. Previous studies have examined behaviors related to HPV catch-up vaccination. Uniquely, this study aimed to investigate perceptions and factors influencing vaccination coverage among female university students in the catch-up program, focusing on both medical and non-medical undergraduates.Methods A web-based survey was conducted at Kochi University from January 16 to February 13, 2023, targeting female students born between April 2, 1997, and April 1, 2006. The survey collected demographic data and assessed knowledge of HPV infection, cervical cancer, and preventive measures. Chi-square tests and logistic regression analyses were used to identify differences between vaccinated and unvaccinated groups as well as factors related to HPV vaccination.Results Of the 310 participants, 39.0 % were vaccinated against HPV, 35.2 % were freshmen, and 75.2 % were in medical science programs. HPV vaccination was significantly associated with being in upper years of university (OR = 3.78–42.83), studying medical sciences (OR = 1.93), undergoing cervical cancer screening (OR = 4.04), and receiving free vaccination vouchers (OR = 2.03).Conclusion Knowledge and awareness of HPV and cervical cancer significantly contribute to higher vaccination uptake in the generation receiving catch-up vaccinations. Tailoring information and distributing free vaccination vouchers could enhance HPV vaccination rates and awareness in this group.