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Based on a comprehensive review of existing literature and examining the specimens, including 11 types that were housed in the Coleoptera Section of the Zoological Survey of India, Kolkata, 154 species of tortoise beetles (Coleoptera: Chrysomelidae: Cassidinae) from India are identified. This represents approximately 5.4% of the species diversity of the known tortoise beetles. Photographs of the examined specimens (including type specimens) are also provided. The details of the distribution of all the species across Indian states (including districts and micro-locations) and biogeographic zones are presented. Studying the distribution data of the species reveals that the Western Ghats harbours the highest number of tortoise beetle species (84), followed by the Northeast (58), Deccan Peninsula (51), Himalayas (49), Gangetic plains (34), Islands (12), and Semi-Arid regions (12).

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The paper presents a compilation of the documented occurrence of the date stone beetle Coccotrypes dactyliperda across the globe. The data presented here have been compiled based on an exhaustive search of academic journal databases, collections presented in research portals and digitised holdings of national libraries. A visualisation of the global distribution shows that the presence of Coccotrypes dactyliperda is circumscribed by climatic factors.

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In July 2022 several grasshoppers of the genus Miramella Dovnar-Zapolskij, 1932 were encountered on two localities in Montenegro. Voucher specimens were sampled. It became clear that these did not belong to the species Miramella albanica Mistshenko, 1952. They also deviated in morphology and habitat from Miramella irena (Fruhstorfer, 1921). After further investigation of external morphology and the male genitalia, confirmation was derived about its undescribed status of the specimens and the species is here formally described and illustrated as Miramella demissa sp. nov. The new species is known from a restricted area in southern Montenegro. It is adapted to particularly low elevations, quite aberrant for the genus. A key to both sexes is given for the species in the region.

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An updated checklist of the hoverflies including distribution and seasonal occurence data of known species in Nepal is presented. The list is based on all available published literature on taxonomy, biodiversity, ecology, and biological aspects of the syrphid fauna of Nepal up to 2023. A total of 205 species from three subfamilies and 63 genera are known to occur in Nepal. Among the three subfamilies, Eristalinae shares maximum species (111 species, 54%), followed by Syrphinae (90 species, 44%), and Microdontinae (four species, 2%). is presented. Among these, 48 (23%) species are recorded in Nepal only. The distribution of known hoverfly species in the country is not uniform, with the Bagmati (82 species) and Koshi (75 species) provinces having the greatest number of species, while the Madhesh (four species) and Lumbini (one species) provinces having the lowest records. The highest number of species are recorded in May (51 species), followed by July (50 species) and June (48 species). Winter season records are relatively low, and distribution data are still incomplete for some sites. Based on the present review, comprehensive and systematic sampling across the entire country is necessary for further exploration of Nepal's hoverfly fauna.

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In this paper, a new type of iterative learning control systems with fractional order known as iterative learning control with fractional order derivative and iterative learning control with fractional proportional–derivative for linearized systems of single-link robot arm is introduced. First order derivative of classic Arimoto is used for tracking error in updating law of derivative iterative learning control. Suggested method in this paper implement tracking error for updating control law of iterative learning of fractional order. For the first time, nonlinear robot system is linearized by input feedback linearization. Then, convergence analysis of iterative learning control law of type PD^alpha is studied.In the next step, we define a criteria for parameters optimization of proposed controller by using Biogeography-based optimization algorithm. Both updating law of fractional order iterative learning control (D^alpha-type ILC and PD^alpha-type ILC) is applied on linearized robot arm and performance of both controller for different value of alpha is presented. For improving the performance of closed loop system, coefficient of fractional order iterative learning control (proportional and derivative coefficients) is optimized by BBO algorithm. Proposed iterative learning control is compared with common type of system.