Deformation Prediction of Foundation Pit Based on Exponential Power Product Model of Improved Algorithm by Chuankui Jing, Hao Wang, Hongsong Li

“…Through six standard test functions and three application examples, the optimization ability of the ISDO algorithm is verified, and the optimization results are compared with those of basic supply demand optimization algorithm (SDO), whale optimization algorithm (WOA), grey wolf optimization algorithm (GWO), moth swarm algorithm (MSA), and particle swarm optimization algorithm (PSO). …”
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Image Recognition Method of Agricultural Pests Based on Multisensor Image Fusion Technology by Xianfeng Zeng, Changjiang Huang, Liuchun Zhan

“…And through experimental data, it is finally verified that the image recognition method used in this paper improves the recognition rate and effectiveness by nearly 65% in the detection of soybean leaf moth pests.…”
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Reinforced colour preference of parasitoid wasps in the presence of floral scent: a case study of a cross-modal effect by Soichi Kugimiya, Takeshi Shimoda, Junji Takabayashi

“…Abstract We examined the possibility of a cross-modal effect in naïve Cotesia vestalis, a parasitoid wasp of diamondback moth larvae, by using artificial flower models of four colours (blue, green, yellow, and red) in the absence or presence of floral scent collected from Brassica rapa inflorescences. …”
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Chevroned Water Hyacinth weevil Neochetina bruchi Hustache (Insecta: Coleoptera: Curculionidae) by Eutychus Kariuki, Carey Minteer

“…The other three species include a weevil, Neochetina eichhorniae; a moth, Niphograptaalbiguttalis; and a planthopper, Megamelus scutellaris, which were introduced into the United States in 1972, 1977, and 2010, respectively (Tipping et al. 2014). …”
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Chevroned Water Hyacinth weevil Neochetina bruchi Hustache (Insecta: Coleoptera: Curculionidae) by Eutychus Kariuki, Carey Minteer

“…The other three species include a weevil, Neochetina eichhorniae; a moth, Niphograptaalbiguttalis; and a planthopper, Megamelus scutellaris, which were introduced into the United States in 1972, 1977, and 2010, respectively (Tipping et al. 2014). …”
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Design and optimal tuning of fractional order PID controller for paper machine headbox using jellyfish search optimizer algorithm by Divya Nataraj, Manoharan Subramanian

“…Furthermore, comparative analyses with other optimization techniques, including Moth Flame Optimization (MFO), Ant Lion Optimization (ALO), and Elephant Herding Optimization (EHO), reveal that the JSO algorithm provides higher accuracy and stability in diverse operating conditions. …”
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Zinc finger proteins facilitate adaptation of a global insect pest to climate change by Tianpu Li, Jiao Guo, Guilei Hu, Fang Cao, Haiyin Su, Mengdi Shen, Huimin Wang, Minsheng You, Yuanyuan Liu, Geoff M. Gurr, Shijun You

“…As poikilotherms, insect pests such as the globally devastating diamondback moth (DBM), Plutella xylostella, are especially vulnerable to rising temperatures and extreme heat events, necessitating effective adaptive mechanisms. …”
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Comparative Morphology and Ultrastructure of Antennal Sensilla in <em>Dendrolimus superans</em> (Lepidoptera: Lasiocampidae) and <em>Lymantria dispar</em> (Lepidoptera: Lymantriida... by Qi Wang, Longzheng Wang, Qing Wang, Shanchun Yan

“…Potential functionalities of these sensilla were discussed with reference to moth feeding habits, and their morphology, distribution, and ultrastructures on both species.…”
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Leptin Deficiency and Its Effects on Tibial and Vertebral Bone Mechanical Properties in Mature Genetically Lean and Obese JCR:LA-Corpulent Rats by Raylene A. Reimer, Jeremy M. LaMothe, Ronald F. Zernicke

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Pharmacological inhibition of key metabolic pathways attenuates Leishmania spp infection in macrophages. by Elaine Carvalho de Oliveira, Rafael Tibúrcio, Gabriela Duarte, Amanda Lago, Léon de Melo, Sara Nunes, Gustavo Gastão Davanzo, Ana Júlia Martins, Bruno Vinagre Ribeiro, Deborah Mothé, Juliana B P Menezes, Patrícia Veras, Natalia Tavares, Pedro M Moraes-Vieira, Cláudia Ida Brodskyn

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Natural history of the hyperdominant tree, Pentaclethra macroloba (Willd.) Kuntze, in the Amazon River estuary by A. R. Dantas, C. C. Vasconcelos, M. C. Guedes, A. C. Lira-Guedes, M. T. F. Piedade

“…The seed predation rate was 5%, mainly caused by Carmenta surinamensis moth larva. The flood gradient established different phenological responses in the species, directing trees to have a better reproductive performance. …”
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Agroforestry systems favor bat conservation but only when old and grazed by Manon Edo, Martin H. Entling, Felix Herzog, Kira Noe, João HN Palma, Ayla Seithe, Will Simonson, Jo Smith, Anja Weiler, Verena Rösch

“…In this study, bat activity was recorded with autonomous sound recorders (AudioMoth) in sixty-five agroforestry and reference sites across western Europe. …”
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Insect Pests and Diseases in Stored Sorghum (Sorghum bicolor L.) and Maize (Zea mays L.) in West Hararghe, Ethiopia by Gelana Keno Beyene, Amin Mohammed Yones, Ahmed Beyan Heji, Mukaddes Kayim

“…The results revealed that maize and sorghum grains stored in sacks, ground pits, markets, and hanging (maize cob) storage containers were infested with insect species: maize weevil (S. zeamais), Angoumois grain moth (S. cerealella), rice weevil (S. oryzae), Red flour beetle (T. castaneum), confused flour beetle (T. confusum), and Lesser grain borer (R. dominica). …”
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A Review of CNN Applications in Smart Agriculture Using Multimodal Data by Mohammad El Sakka, Mihai Ivanovici, Lotfi Chaari, Josiane Mothe

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Refined methodology for quantifying Pseudomonas aeruginosa virulence using Galleria mellonella by Christopher M. R. Axline, Travis J. Kochan, Sophie Nozick, Timothy Ward, Tania Afzal, Issay Niki, Sumitra D. Mitra, Ethan VanGosen, Julia Nelson, Aliki Valdes, David Hynes, William Cheng, Joanne Lee, Prarthana Prashanth, Timothy L. Turner, Nathan B. Pincus, Marc H. Scheetz, Kelly E. R. Bachta, Alan R. Hauser

“…ABSTRACT Larvae of Galleria mellonella (the greater wax moth) are being increasingly used as a model to study microbial pathogenesis. …”
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Characterization of a Novel Male Pheromone Compound in <i>Leucoptera sinuella</i> (Lepidoptera: Lyonetiidae) and Its Role in Courtship Behavior by Laura Sánchez-Aros, Abel F. O. Queiroz, Jorge Guajardo, Wilson Barros-Parada, Glenn P. Svensson, Jan Bergmann

“…The poplar moth, <i>Leucoptera sinuella</i> (Lepidoptera: Lyonetiidae), is widely distributed across Europe, Asia, and parts of Africa. …”
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Polymorphous Adenocarcinoma: A Rare Case Report with Unique Radiographic Appearance on CBCT by Jagadish Chandra, Junaid Ahmed, K. M. Veena, M. Vijayakumar, Nandita Shenoy, Nanditha Sujir

“…The CBCT scan revealed evidence of moth-eaten appearance of maxilla with destruction of medial and lateral walls and floor of maxillary sinus. …”
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Two novel entomopathogenic fungal species of Lecanicillium isolated from soil in China by Tongyi Liu, Wei Chen, Yanhong Tang, Fen Liu, Liyan Yao, Qiongbo Hu, Ke Zhang, Qunfang Weng

“…Bioassays conducted on the greater wax moth, Galleria mellonella and crucifer aphid, Lipaphis erysimi showed that both fungal strains exhibit virulence. …”
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Multijunction solar cell parameter estimation based on metaheuristic algorithms by Marwa M. Elzalabani, Doaa M. Atia, Aref Y. Eliwa, Belal A. Abou Zalam, Mahmoud S. AbouOmar

“…The study compared the performance of five optimization algorithms: Grey Wolf Optimizer (GWO), Artificial Hummingbird Algorithm (AHA), Tunicate Swarm Algorithm (TSA), War Strategy Algorithm (WSA), and Moth flam optimizer (MFO). The results demonstrate the superior performance of the AHA algorithm, which has the lowest RMSE value (0.0582) in the SDM and DDM cases, while WSA has the lowest RMSE value (0.0488) in the TDM instance. …”
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Enhancing Residential Electricity Consumption Forecasting with Meta-Heuristic Algorithms by Milad Mohebbi, Behnam Sobhani

“…The meta-heuristic algorithms employed for fine-tuning the ANN's weight and bias parameters include the Genetic Algorithm (GA), Multi-Verse Optimizer (MVO), Moth Flame Optimization (MFO), Particle Swarm Optimization (PSO), Grey Wolf Optimizer (GWO), Advanced Grey Wolf Optimizer (AGWO), Biogeography-Based Optimization (BBO), and Particle Swarm Optimization with Grey Wolf Optimizer (PSOGWO). …”
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