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\"Scientists say they are one of most abundant animals on the planet. But when pressed, few people can accurately describe krill or explain their ecological importance. Antarctic krill have used their extraordinary adaptive skills to survive and thrive for millions of years in a dark, icy world far from human interference. But with climate change melting ice caps at the top and bottom of the world, and increased human activity and pollution, their evolutionary flexibility to withstand these new pressures may not be enough. Eminent krill scientist Stephen Nicol wants us to know more about this enigmatic creature of the sea. He argues that it's critical to understand krill's complex biology in order to protect them as the krill fishing industry expands. Ocean enthusiasts will come away with a newfound appreciation for the complex ecology of a species we have much to learn from, and many reasons to protect\"--Provided by publisher.

In the Southern Ocean, the at‐sea distributions of most predators of Antarctic krill are poorly known, primarily because tracking studies have only been undertaken on a restricted set of species, and then only at a limited number of sites. For chinstrap penguins, one of the most abundant krill predators breeding across the Antarctic Peninsula, we show that habitat models developed utilizing the distance from the colony and the bearing to the shelf‐edge, adjusting for the at‐sea density of Pygoscelis penguins from other colonies, can be used to predict, with a high level of confidence, the at‐sea distribution of chinstrap penguins from untracked colonies during the breeding season. Comparison of predicted penguin distributions with outputs from a high‐resolution oceanographic model shows that chinstrap penguins prefer nearshore habitats, over shallow bathymetry, with slow‐flowing waters, but that they sometimes also travel to areas beyond the edge of the continental shelf where the faster‐flowing waters of the Coastal Current or the fronts of the Antarctic Circumpolar Current occur. In the slow‐moving shelf waters, large penguin colonies may lead to krill depletion during incubation and chick‐rearing periods when penguins are acting as central place foragers. The habitats used by chinstrap penguins are also locations preferentially used by the commercial krill fishery, one of the last under‐developed marine capture fisheries anywhere on the planet. As it develops, this fishery has the potential to compete with chinstrap penguins and other natural krill predators. Scaling our habitat models by chinstrap penguin population data demonstrates where overlap with the fishery is likely to be most important. Our results suggest that a better understanding of krill retention and krill depletion in areas used by natural predators and by the krill fishery are needed, and that risk management strategies for the fishery should include assessment of how krill movement can satisfy the demands of both natural predators and the fishery across a range of spatial and temporal scales. Such information will help regional management authorities better understand how plausible ecosystem‐based management frameworks could be developed to ensure sustainable co‐existence of the fishery and competing natural predators.

In this paper, a novel text clustering method, improved krill herd algorithm with a hybrid function, called MMKHA, is proposed as an efficient clustering way to obtain promising and precise results in this domain. Krill herd is a new swarm-based optimization algorithm that imitates the behavior of a group of live krill. The potential of this algorithm is high because it performs better than other optimization methods; it balances the process of exploration and exploitation by complementing the strength of local nearby searching and global wide-range searching. Text clustering is the process of grouping significant amounts of text documents into coherent clusters in which documents in the same cluster are relevant. For the purpose of the experiments, six versions are thoroughly investigated to determine the best version for solving the text clustering. Eight benchmark text datasets are used for the evaluation process available at the Laboratory of Computational Intelligence (LABIC). Seven evaluation measures are utilized to validate the proposed algorithms, namely, ASDC, accuracy, precision, recall, F-measure, purity, and entropy. The proposed algorithms are compared with the other successful algorithms published in the literature. The results proved that the proposed improved krill herd algorithm with hybrid function achieved almost all the best results for all datasets in comparison with the other comparative algorithms.

Following the cessation of whaling, South Atlantic populations of humpback Megaptera novaeangliae and some other baleen whale species are recovering, but there has been limited monitoring of their recovery in the Scotia Arc, a former whaling epicentre and a hotspot for Antarctic krill Euphausia superba. To inform the management of krill fisheries, up-to-date assessment of whale biomass and prey consumption is essential. Using a model-based approach, we provide the first estimates of whale abundance and krill consumption for South Georgia and the South Sandwich Islands and total abundance of humpback whales across their southwestern Atlantic feeding grounds, using data collected in 2019. Humpback whale abundance was estimated at 24 543 (coefficient of variation, CV = 0.26; 95% CI = 14 863–40 528), similar to that measured in Brazil on the main wintering ground for this population. The abundance of baleen whales in South Georgia and the South Sandwich Islands, including those not identified to species level, was estimated at 43 824 (CV = 0.15, 95% CI = 33 509–59 077). Based on the proportion of humpback whales identified during the surveys (83%), the majority of these are likely to be humpback whales. Annual krill consumption by baleen whales was estimated to be in the range 4.8 to 7.2 million tons, representing 7 to 10% of the estimated krill biomass in the region. However, there is a need to better understand feeding rates in baleen whales, and further research into this field should be a priority to improve the accuracy and precision of prey consumption rate estimation.

The fatty acid content and composition of the Antarctic krill Euphausia superba Dana, 1850 were investigated using samples collected by a commercial fishing vessel. This dataset allowed comparison between seasons, years (2013–2016), and different fishing locations. Quantities of omega 3 fatty acids 20:5n-3 and 22:6n-3 (mg/g dry mass; DM) were highest in autumn and decreased through winter to reach a spring low. Quantities of the flagellate marker 18:4n-3 and diatom marker 16:1n-7c were variable and did not display the same seasonal fluctuations. In summer, krill had high percentages (% total fatty acids) of 20:5n-3 and 22:6n-3, total PUFA, and low 18:1n-9c/18:1n-7c ratios, indicating a more herbivorous diet. Krill became more omnivorous from autumn to spring, indicated by increasing ratios of 18:1n-9c/18:1n-7c and percentages of Σ 20:1 + 22:1 isomers. Bacterial fatty acids (Σ C₁₅ + C₁₇ + C₁₉ isomers) were minor components year-round (0.9–1.8 %). Seasonal levels of herbivory and omnivory differed between years, and levels of specific fatty acid ratios differed between fishing locations. The fatty acid 18:4n-3 was a major driver of variability in krill fatty acid composition, with no obvious seasonal driver. This is the first study to report krill fatty acid data during all four seasons over consecutive years. This large-scale study highlights the value of using fisheries samples to examine seasonal and annual fluctuations in krill diet and condition.

Industry 4.0 enable novel business cases, such as client-specific production, real-time monitoring of process condition and progress, independent decision making and remote maintenance, to name a few. However, they are more susceptible to a broad range of cyber threats because of limited resources and heterogeneous nature. Such risks cause financial and reputational damages for businesses, well as the theft of sensitive information. The higher level of diversity in industrial network prevents the attackers from such attacks. Therefore, to efficiently detect the intrusions, a novel intrusion detection system known as Bidirectional Long Short-Term Memory based Explainable Artificial Intelligence framework (BiLSTM-XAI) is developed. Initially, the preprocessing task using data cleaning and normalization is performed to enhance the data quality for detecting network intrusions. Subsequently, the significant features are selected from the databases using the Krill herd optimization (KHO) algorithm. The proposed BiLSTM-XAI approach provides better security and privacy inside the industry networking system by detecting intrusions very precisely. In this, we utilized SHAP and LIME explainable AI algorithms to improve interpretation of prediction results. The experimental setup is made by MATLAB 2016 software using Honeypot and NSL-KDD datasets as input. The analysis result reveals that the proposed method achieves superior performance in detecting intrusions with a classification accuracy of 98.2%.

This study investigates the effects of incorporating Spirulina, krill meal, and corn gluten meal as dietary additives on the growth performance and body coloration of shrimp ( Litopenaeus vannamei ). Experimental diets containing varying percentages of Spirulina (1% and 3%), krill meal (2% and 5%), and corn gluten meal (3% and 6%) were formulated by replacing fish meal at different inclusion levels and compared to a Control diet with higher levels of fish meal. Results indicated that shrimp fed with 3% Spirulina exhibited the highest final weight and best feed conversion ratio (FCR), significantly outperforming the Control and the corn gluten meal treatments. Color analysis revealed that shrimp fed 3% Spirulina had significantly lower L* values (darker color) and higher b* values (yellow hue) suggesting improved pigmentation. Despite containing xanthophylls, corn gluten meal did not produce significant changes to the yellowish tone of the shrimp when raw, with less efficiency than other pigments. After cooking, all treatments showed increased L*, a* and b* values, with shrimp fed with 3% Spirulina and 6% corn gluten meal showing the most intense red‐orange coloration. These findings highlight the potential of krill meal, spirulina, and corn gluten as natural dietary pigments and growth stimulators in shrimp aquaculture, providing valuable information to improve shrimp quality to meet market demands.

Krill herd (KH) is a novel swarm-based metaheuristic optimization algorithm inspired by the krill herding behavior. The objective function in the KH optimization process is based on the least distance between the food location and position of a krill. The KH method has been proven to outperform several state-of-the-art metaheuristic algorithms on many benchmarks and engineering cases. This paper presents a comprehensive review of different versions of the KH algorithm and their engineering applications. The study is divided into the following general parts: KH variants, engineering optimization/application, and theoretical analysis. In addition, specific features of KH and future directions are discussed.

This study analyzes the structure of North Pacific krill Euphausia pacifica fisheries in Japan and the value chain from producer to consumer. Krill fishery is conducted along the Pacific coast of Japan, and the catch is mainly used as frozen bait for recreational fisheries and partly for dry food. Semi-structured interviews were conducted with stakeholders of the krill industry in the Iwate and Miyagi prefectures to analyze the industrial structure from production to distribution and retail. Based on the information obtained from interviews, storefront surveys, and the available statistics, we analyzed the value chain of the krill industry, which was found to be similar to that of other seafood industries. Overall, a market mechanism is functional at each distribution stage based on the demand of anglers (consumers) and the krill market is competitive. Together with the survey results, we found that the production adjustment may benefit the producers in the short run, but create market inefficiencies and may reduce the market share and increase inexpensive substitutes. Instead, market expansion strategy by developing new krill products, or by increasing dried krill may benefit them in the long run.

Antarctic krill (Euphausia superba) is the world’s largest resource of animal proteins and is thought to be a high-quality resource for future marine healthy foods and functional products. Therefore, Antarctic krill was degreased and separately hydrolyzed using flavourzyme, pepsin, papain, and alcalase. Protein hydrolysate (AKH) of Antarctic krill prepared by trypsin showed the highest Ca-chelating rate under the optimized chelating conditions: a pH of 8.0, reaction time of 50 min, temperature of 50 °C, and material/calcium ratio of 1:15. Subsequently, fourteen Ca-chelating peptides were isolated from APK by ultrafiltration and a series of chromatographic methods and identified as AK, EAR, AEA, VERG, VAS, GPK, SP, GPKG, APRGH, GVPG, LEPGP, LEKGA, FPPGR, and GEPG with molecular weights of 217.27, 374.40, 289.29, 459.50, 275.30, 300.36, 202.21, 357.41, 536.59, 328.37, 511.58, 516.60, 572.66, and 358.35 Da, respectively. Among fourteen Ca-chelating peptides, VERG presented the highest Ca-chelating ability. Ultraviolet spectrum (UV), Fourier Transform Infrared (FTIR), and scanning electron microscope (SEM) analysis indicated that the VERG-Ca chelate had a dense granular structure because the N-H, C=O and -COOH groups of VERG combined with Ca2+. Moreover, the VERG-Ca chelate is stable in gastrointestinal digestion and can significantly improve Ca transport in Caco-2 cell monolayer experiments, but phytate could significantly reduce the absorption of Ca derived from the VERG-Ca chelate. Therefore, Ca-chelating peptides from protein hydrolysate of Antarctic krill possess the potential to serve as a Ca supplement in developing healthy foods.