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Copyright of Phegea is the property of Vlaamse Vereniging voor Entomologie and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This article introduces WingSegment, a MATLAB app‐designed tool employing a hybrid approach of computer vision and graph theory for precise insect wing image segmentation. WingSegment detects cells, junctions, Pterostigma, and venation patterns, measuring geometric features and generating Voronoi patterns. The tool utilizes region‐growing, thinning, and Dijkstra's algorithms for boundary detection, junction identification, and vein path extraction. It provides histograms and box plots of geometric features, facilitating comprehensive wing analysis. WingSegment's efficiency is validated through comparisons with established tools and manual measurements, demonstrating accurate results. The tool further enables exporting detected boundaries as FreeCAD macro files for 3D modeling and printing, supporting finite element analysis. Beyond advancing insect wing morphology understanding, WingSegment holds broader implications for diverse planar structures, including leaves and geocells. This tool not only enhances automated geometric analysis and 3D model generation in insect wing studies but also contributes to the broader advancement of analysis, 3D printing, and modeling technologies across various planar structures. [ABSTRACT FROM AUTHOR]

Insect diversity monitoring is crucial for biological pest control in agriculture and forestry. Modern monitoring of insect species relies heavily on fine-grained image classification models. Fine-grained image classification faces challenges such as small inter-class differences and large intra-class variances, which are even more pronounced in insect scenes where insect species often exhibit significant morphological differences across multiple life stages. To address these challenges, we introduce segmentation and clustering operations into the image classification task and design a novel network model training framework for fine-grained classification of insect images using multi-modality clustering and approximate mask methods, named PCAM-Frame. In the first stage of the framework, we adopt the Polymorphic Clustering Module, and segmentation and clustering operations are employed to distinguish various morphologies of insects at different life stages, allowing the model to differentiate between samples at different life stages during training. The second stage consists of a feature extraction network, called Basenet, which can be any mainstream network that performs well in fine-grained image classification tasks, aiming to provide pre-classification confidence for the next stage. In the third stage, we apply the Approximate Masking Module to mask the common attention regions of the most likely classes and continuously adjust the convergence direction of the model during training using a Deviation Loss function. We apply PCAM-Frame with multiple classification networks as the Basenet in the second stage and conduct extensive experiments on the Insecta dataset of iNaturalist 2017 and IP102 dataset, achieving improvements of 2.2% and 1.4%, respectively. Generalization experiments on other fine-grained image classification datasets such as CUB200-2011 and Stanford Dogs also demonstrate positive effects. These experiments validate the pertinence and effectiveness of our framework PCAM-Frame in fine-grained image classification tasks under complex conditions, particularly in insect scenes. [ABSTRACT FROM AUTHOR]

Background: Lysiteles Simon, 1895 contains 64 nominal species distributed in East, South and South Asia. It possesses very high species diversity in China (with 46 and 32 endemics), Bhutan (with 9 and 1 endemic) and Nepal (with 8 and 4 endemics). In June 2023, a spider survey of Cibagou National Nature Reserve, Xizang, China was carried out. After examination and morphological comparison, two Lysiteles species were recognised as new to science. New information: Two new species of Lysiteles Simon, 1895 collected from Cibagou National Nature Reserve, Xizang, China are described: L. cibagou sp. nov. (♂♀) and L. tangi sp. nov. (♂♀). Diagnostic photos of habitus and copulatory organs and a distributional map are provided. [ABSTRACT FROM AUTHOR]

Background: The genus Clavicornaltica Scherer 1974 consists of very small, soil-dwelling flea beetles in South, Southeast and East Asia. Due to their diminutive size and morphological similarities, very little is known about their ecology and taxonomical diversity. It is likely that further studies will reveal this genus to be much more speciose than the 30 species currently recognised. New information: A new species of Clavicornaltica from Brunei Darussalam is described, C. mataikanensis Otani et al., sp. nov. This is the second species of this genus recorded from Ulu Temburong National Park. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Insect Biodiversity & Systematics is the property of Tarbiat Modares University Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Males of Leptogenys (Lobopelta) borneensis Wheeler, 1919 are described, including their genital morphology, which is important for diagnostics and morphological phylogeny of the genus Leptogenys Roger, 1861. The mtDNA COI barcoding sequence of 607 bp obtained and uploaded to GenBank and BOLD. The species was previously known from Borneo (Malaysia: Sarawak — type locality), Thailand and Vietnam and is recorded for the first time from Sumatra (Indonesia). [ABSTRACT FROM AUTHOR]

Scorpions and spiders belong to the class Arachnida in phylum Arthropoda. Scorpions are easily distinguished by median eyes on obvious the center of the carapace and have one pair, and lateral eyes have 2-8 in some species. Scorpions do not have good eyesight so the median eyes have always been simple and they are more sensitive than the lateral pairs. They have anterior median eyes (AME) with narrow field of view and pairs of lateral eyes (LE) with more sensitivity and response to light. Family Buthidae have 2-6 lateral eyes in Compsobuthus Mesobuthus, Hottentotta, while Vaejovidae, Chactidae and Chaerilidae have 2 pairs of lateral eyes. In addition, 3 pairs are found in Orthochirus and Androctonus. Spiders have six eyes in family Pholicidae, Sicariidae, Araneidae, Salticidae, while eight eyes in Theridiidae, Lycosidae and some with two eyes or four in the carapace of the prosoma. Spider have anterior median eyes, anterior lateral eyes, posterior median eyes, or posterior lateral eyes. Scorpions and Spider eyes are not compound but simple. There is one lens for each eye. Spiders have poor vision, not able to see light and darkness. Scorpion and spider taxonomy is based on the forms and number of eyes. So, the reasons to study these organisms are important in studies of medical, ecology, morphology and taxonomy. and it is a little known about their biology and fauna. [ABSTRACT FROM AUTHOR]

Selymbria amazonensis sp. nov. is described and illustrated from Brazil. An illustrated taxonomic key for males and females is provided. We include distribution maps and comments on their morphology, geographical distribution, and life history. [ABSTRACT FROM AUTHOR]