Two new species of the genus Kingdonella Uvarov, 1933 (Orthoptera, Acridoidea) and the first reported male of Kingdonellaqinghaiensis Zheng, 1990.

Two new species of the genus Kingdonella and the first report of a male K.qinghaiensis Zheng, 1990 are presented. The new species K.gandensis sp. nov. has similar morphological features to K.wardi Uvarov, 1933, but it differs from the latter in having 1) the hind tibia black; 2) the epiproct, in males, with a median groove in the basal 1/2 and in the apical 1/4; 3) the denticles of the male epiproct black; 4) the outside of the hind femur reddish-brown on the basal 1/4 and black on the apical 3/4; and 5) the ventral face of the hind femur black on the outer side. The second new species, K.biruensis sp. nov., is morphologically close to K.pienbaensis Zheng, 1980 but differs from the latter in having 1) the length of the middle segment (12th segment) of antennae 1.2 times longer than its width; 2) the subgenital plate sharp-cornered in males; 3) the ovipositor smooth; 4) the upper half of hind femur outside surface with two black spots; and 5) the ventral face of the hind femur black on its outer side, red on the basal 2/3, and black on the apical 1/3 of its inner side. Finally, we provide a key to all known species of Kingdonella.

Acceptance of Muffins (Sweet and Savory) with the Addition of T. molitor, A. diaperinus, A. domesticus, R. differens, Considering Psychological Factors (Food Neophobia Scale, Consumer Attitude).

The aim of the study was to analyze the acceptance of muffins containing a 15% addition of powder from four edible insect species (Alphitobius diaperinus, Tenebrio molitor, Acheta domesticus, Ruspolia differens) in both savory and sweet versions, focusing on the psychological factors influencing their consumption. The study involved 106 adult consumers. Initially, the level of food neophobia (FNS) among participants was determined. Over 80% displayed low to medium levels of neophobia. Similar results were obtained when assessing attitudes towards insects, with most participants showing positive and ambivalent attitudes. Based on these findings, the acceptance of insect-based muffins was evaluated. The level of acceptance of insects varied and depended mainly on taste, smell, and texture. Participants with lower levels of neophobia and positive attitudes towards consuming insects generally rated the insect muffins higher compared to those with higher levels of neophobia and negative attitudes. The sweet versions of insect powder muffins were rated higher, which also indicates preferences and dietary habits. Products with grasshopper powder (GS, GCL) were rated the lowest for both taste versions. Conversely, products based on buffalo worms (BS, BCL) were seen as having the greatest potential for acceptance. Understanding consumer attitudes, neophobia, and levels of acceptance provides valuable insights for designing new insect-based foods.

Changes in the Range of Four Advantageous Grasshopper Habitats in the Hexi Corridor under Future Climate Conditions.

Angaracris rhodopa (Fischer et Walheim), Calliptamus abbreviatus (Ikonnikov), Myrmeleotettix palpalis (Zubowsky), and Oedaleus decorus asiaticus (Bey-Bienko) are the main grasshoppers that harm the natural grassland in the Hexi Corridor in Gansu, northwest China. In this study, the MaxEnt model was employed to identify the key environmental factors affecting the distribution of the four grasshoppers' habitats and to assess their distribution under current and future climate conditions. The aim was to provide a basis for grasshopper monitoring, prediction, and precise control. In this study, distribution of suitable habitats for A. rhodopa, C. abbreviates, M. palpalis, O. decorus asiaticus were predicted under current and future climatic scenarios using the Maxent model. The average AUC (area under the ROC curve) and TSS (true skill statistic) values of the four grasshoppers were greater than 0.9, and the simulation results were excellent and highly reliable. The mean annual precipitation was the main factor limiting the current range of suitable areas for these four species. Under the current climate, A. rhodopa, C. abbreviatus, and O. decorus asiaticus were mainly distributed in the central and eastern parts of the Hexi Corridor, and M. palpalis was distributed throughout the Hexi Corridor, with a suitable area of 1.29 × 104, 1.43 × 104, 1.44 × 104, and 2.12 × 104 km2, accounting for 13.7%, 15.2%, 15.3%, and 22.5% of the total area of the grasslands in the Hexi Corridor, respectively. The highly suitable areas of A. rhodopa, C. abbreviatus, and O. decorus asiaticus were mainly distributed in the eastern-central part of Zhangye City, the western part of Wuwei City, and the western and southern parts of Jinchang City, with areas of 0.20 × 104, 0.29 × 104, and 0.35 × 104 km2, accounting for 2.2%, 3%, and 3.7% of the grassland area, respectively. The high habitat of M. palpalis was mainly distributed in the southeast of Jiuquan City, the west, middle, and east of Zhangye City, the west of Wuwei City, and the west and south of Jinchang City, with an area of 0.32 × 104 km2, accounting for 3.4% of the grassland area. In the 2030s, the range of A. rhodopa, C. abbreviatus, and O. decorus asiaticus was predicted to increase; the range of M. palpalis will decrease. The results of this study could provide a theoretical basis for the precise monitoring and control of key areas of grasshoppers in the Hexi Corridor.

Brain tumor recognition by an optimized deep network utilizing ammended grasshopper optimization.

Brain tumors are abnormal cell masses that can get originated in the brain spread from other organs. They can be categorized as either malignant (cancerous) or benign (noncancerous), and their growth rates and locations can impact the functioning of the nerve system. The timely detection of brain tumors is crucial for effective treatment and prognosis. In this study, a new approach has been proposed for diagnosing brain tumors using deep learning and a meta-heuristic algorithm. The method involves three main steps: (1) extracting features from brain MRI images using AlexNet, (2) reducing the complexity of AlexNet by employing an Extreme Learning Machine (ELM) network as a classification layer, and (3) fine-tuning the parameters of the ELM network using an Amended Grasshopper Optimization Algorithm (AGOA). The performance of the method has been evaluated on a publicly available dataset consisting of 20 patients with newly diagnosed glioblastoma that is compared with several state-of-the-art techniques. Experimental results demonstrate that the method achieves the highest accuracy, precision, specificity, F1-score, sensitivity, and MCC with values of 0.96, 0.94, 0.96, 0.96, 0.94, and 0.90, respectively. Furthermore, the robustness and stability of the method have been illustrated when subjected to different levels of noise and image resolutions. The proposed approach offers a rapid, accurate, and dependable diagnosis of brain tumors and holds potential for application in other medical image analysis tasks.

Dynamic simulation and projection of ESV changes in arid regions caused by urban growth under climate change scenarios.

Spatial simulation and projection of ecosystem services value (ESV) changes caused by urban growth are important for sustainable development in arid regions. We developed a new model of cellular automata based grasshopper optimization algorithm (named GOA-CA) for simulating urban growth patterns and assessing the impacts of urban growth on ESV changes under climate change scenarios. The results show that GOA-CA yielded overall accuracy exceeding 98%, and FOM for 2010 and 2020 were 43.2% and 38.1%, respectively, indicating the effectiveness of the model. The prairie lost the highest economic ESVs (192 million USD) and the coniferous yielded the largest economic ESV increase (292 million USD) during 2000-2020. Using climate change scenarios as urban future land use demands, we projected three scenarios of the urban growth of Urumqi for 2050 and their impacts on ESV. Our model can be easily applied to simulating urban development, analyzing its impact on ESV and projecting future scenarios in global arid regions.

BGOA-TVG: Binary Grasshopper Optimization Algorithm with Time-Varying Gaussian Transfer Functions for Feature Selection.

Feature selection aims to select crucial features to improve classification accuracy in machine learning and data mining. In this paper, a new binary grasshopper optimization algorithm using time-varying Gaussian transfer functions (BGOA-TVG) is proposed for feature selection. Compared with the traditional S-shaped and V-shaped transfer functions, the proposed Gaussian time-varying transfer functions have the characteristics of a fast convergence speed and a strong global search capability to convert a continuous search space to a binary one. The BGOA-TVG is tested and compared to S-shaped and V-shaped binary grasshopper optimization algorithms and five state-of-the-art swarm intelligence algorithms for feature selection. The experimental results show that the BGOA-TVG has better performance in UCI, DEAP, and EPILEPSY datasets for feature selection.

The Survival and Physiological Response of Calliptamus abbreviatus Ikonn (Orthoptera: Acrididae) to Flavonoids Rutin and Quercetin.

Insect-resistant substances from plants are important natural resources that human beings can potentially develop and use to control pests. In this study, we explored the adverse effects of rutin and quercetin on grasshopper (Calliptamus abbreviatus), as well as the insect's physiological response to these substances in laboratory and field experiments. These two plant compounds exhibited toxic effects on C. abbreviatus, with quercetin showing a stronger toxicity, indicated by a lower survival, slower development, and higher induced gene expression and activities of UDP-glucuronosyltransferase, cytochrome P450s, superoxide dismutase, peroxidase and catalase, compared to rutin. These compounds, especially quercetin, have the potential to be developed as biopesticides to control grasshoppers.

Value chain hygiene practices and microbial contamination of street and market vended ready-to-eat grasshopper, Ruspolia differens in Uganda: Implications for food safety and public health.

Food safety is a major public health issue particularly in developing countries. Ready-to-eat street-vended foods contribute significantly to dietary intake in urban and peri-urban areas, but with elevated public health risk. In this study, hygiene and food safety practices as well as the microbial contamination in Uganda's edible grasshopper value chain were evaluated."A total of 29 grasshopper-processing households participated, and grasshopper samples collected. Indicator pathogens were analyzed using standard microbiological methods. In Kampala 50% and in Masaka 12% households had earth floors. All households in Kampala were one or two-roomed dwellings with no separate room as a kitchen, and shared a toilet. In contrast, 59% of households in Masaka had three or more rooms, 35% had a separate room for a kitchen and 47% did not share a toilet. 83% households in Kampala and 56% in Masaka obtained drinking water from public taps. Handwashing was inadequate and none of the actors was observed to wash their hands after taking a break or handling waste. For vendors, wearing protective clothing was not common, with only 28.5% in Kampala and 30.8% in Masaka wearing an apron. Containers for vending grasshoppers were largely uncovered and the utensils for measuring the grasshoppers were left mainly uncovered. Indicator organisms, Escherichia coli and Salmonella typhimurium, were detected. E. coli was the most common contaminant, but with lower levels in Masaka compared to Kampala. S. typhimurium was mainly a burden in Kampala. Our findings demonstrate that there are enormous contributors to poor hygiene and sanitation along the edible grasshopper value chain. The existence of pathogenic bacteria such as E. coli in ready-to-eat foods imply that their consumption poses a health risk.

Improved chaos grasshopper optimizer and its application to HRES techno-economic evaluation.

Current political and economic trends are moving more and more toward the use of renewable and clean energy as a result of rising energy use and diminishing fossil fuel supplies. In this paper, an improved chaos-based grasshopper optimizer used for techno-economic evaluation in integrated green power systems is investigated. The integrated system consists of a fuel cell system, a wind farm, and solar energy. The integrated solar, wind, and hydrogen fuel cell architectures increase the effectiveness and electrical output of the system while needing less energy storage in structures that are unconnected from the grid. The grasshopper optimization technique and chaos theory have been combined to create the suggested chaotic grasshopper optimizer in this study. The performance, precision, and robustness of this optimization were then assessed, using four benchmark tasks. The ICGO model is utilized to assign suitable ratings to all system devices, thereby guaranteeing the attainment of optimal performance and efficiency. The Net Present Cost (NPC) analysis revealed that the ICGO algorithm attained the lowest minimum NPC value of 274.541E4 USD and the highest maximum NPC value of 311.94E4 USD. The average NPC value of the ICGO algorithm (289.176E4 USD) was found to be comparable to the other algorithms examined in the study. These findings indicate that the ICGO algorithm outperformed other optimization algorithms in minimizing the cost of the renewable energy system. The chaotic grasshopper optimizer can handle several targets, restrictions, and variables with ease, and the results demonstrate that it is substantially more efficient and precise than standard optimization techniques. It is also quite durable, with minimal performance degradation as compared to the benchmark solutions. This study demonstrates the effectiveness of the chaos grasshopper optimizer as an HRES technique.

Preliminary Study on Hourly Dynamics of a Ground-Dwelling Invertebrate Community in a Farmland Vineyard.

We evaluated the hourly dynamics of ground-dwelling invertebrate communities in farmland using infrared camera traps between August and September 2022. No significant variations within 24 h nor between any two time points of each day were observed in the taxonomic richness and abundance of the entire community. However, the periods from 4:00 to 7:00 and 13:00 to 20:00 showed relatively high taxonomic richness, while those from 2:00 to 6:00 and 16:00 to 21:00 showed relatively high abundance. Millipede abundance varied significantly in a 24 h period, with higher abundance from 3:00 to 4:00 and 1:00 to 2:00. Additionally, slug, beetle, and grasshopper abundances were significantly higher from 22:00 to 23:00, 17:00 to 18:00, and 23:00 to 24:00, respectively. The abundance of other taxa did not show significant variations between any two time points of a day. Predominant generalist predators showed positive correlation in their activity times. These results suggest that significant variations within each 24 h period are uncommon at either community or taxa (except for millipedes) levels in farmland ground-dwelling invertebrates. Further, while most taxa had significantly preferred active hours, the total community did not. Therefore, hourly dynamics should be considered to understand biodiversity maintenance.

How Nutrients Mediate the Impacts of Global Change on Locust Outbreaks.

Locusts are grasshoppers that can migrate en masse and devastate food security. Plant nutrient content is a key variable influencing population dynamics, but the relationship is not straightforward. For an herbivore, plant quality depends not only on the balance of nutrients and antinutrients in plant tissues, which is influenced by land use and climate change, but also on the nutritional state and demands of the herbivore, as well as its capacity to extract nutrients from host plants. In contrast to the concept of a positive relationship between nitrogen or protein concentration and herbivore performance, a five-decade review of lab and field studies indicates that equating plant N to plant quality is misleading because grasshoppers respond negatively or neutrally to increasing plant N just as often as they respond positively. For locusts specifically, low-N environments are actually beneficial because they supply high energy rates that support migration. Therefore, intensive land use, such as continuous grazing or cropping, and elevated ambient CO2 levels that decrease the protein:carbohydrate ratios of plants are predicted to broadly promote locust outbreaks.

Air-soil cycling of oxygenated, nitrated and parent polycyclic aromatic hydrocarbons in source and receptor areas.

Polycyclic aromatic hydrocarbons (PAHs) and their oxygenated and nitrated derivatives, OPAHs and NPAHs, are semivolatile air pollutants which are distributed and cycling regionally. Subsequent to atmospheric deposition to and accumulation in soils they may re-volatilise, a secondary source which is understudied. We studied the direction of air-soil mass exchange fluxes of 12 OPAHs, 17 NPAHs, 25 PAHs and one alkylated PAH in two rural environments being influenced by the pollutant concentrations in soil and air, by season, and by land cover. The OPAHs and NPAHs in samples of topsoil, of ambient air particulate and gas phases and in the gas-phase equilibrated with soil were analysed by GC-APCI-MS/MS. The pollutants soil burdens show a pronounced seasonality, a winter maximum for NPAHs and PAHs and a summer maximum for OPAHs. One order of magnitude more OPAH and parent PAH are found stored in forest soil than in nearby grassland soil. Among a number of 3-4 ring PAHs, the OPAHs benzanthrone and 6H-benzo(c,d)pyren-6-one, and the NPAHs 1- and 2-nitronaphthalene, 9-nitrophenanthrene and 7-nitrobenz(a)anthracene are found to re-volatilise from soils at a rural background site in central Europe in summer. At a receptor site in northern Europe, net deposition of polycyclic aromatic compounds (PACs) prevails and re-volatilisation occurs only sporadic. Re-volatilisation of a number of PACs, including strong mutagens, from soils in summer and even in winter indicates that long-range atmospheric transport of primary PAC emissions from central Europe to receptor areas might be enhanced by secondary emissions from soils.

Maximizing micro-grid energy output with modified chaos grasshopper algorithms.

This study presents a Modified version of Chaos Grasshopper Algorithm (MCGA) as a solution to the Techno-Economic Energy Management Strategy (TEMS) problem in microgrids. Our main contribution is the optimization of parameters to minimize the overall daily electricity price in an integrated clean energy micro-grid, incorporating fuel cell, battery storage, and photovoltaic systems. Through comparative simulations with established methods (HOMER, GAMS, GWO, and MILPA), we demonstrate the superiority of our proposed strategy. The results reveal that MCGA surpasses these methods, yielding significantly improved optimal solutions for the overall daily electricity price. Notably, the MCGA approach exhibits high precision, flexibility, and adaptability to power prices and environmental constraints, leading to accurate and flexible solutions. Thus, our proposed approach offers a promising and effective solution for the TEMS problem in microgrids, with the potential to greatly enhance microgrid performance.

On the specific status of Scelimenaspicupennis and a new record of S.discalis from China with mitochondrial genome characterization (Orthoptera, Tetrigidae).

The genus Scelimena Serville (Orthoptera: Tetrigidae) from China is reviewed. One species, Scelimenaspicupennis Zheng & Ou, 2003 (China: Yunnan) is redescribed, and a new record of Scelimenadiscalis (Hancock, 1915) from China is given. An annotated identification key for Chinese species of the genus Scelimena is provided. Mitochondrial genes of S.spicupennis and S.discalis were sequenced and annotated. The sizes of the two sequenced mitogenomes are 17,552 bp (S.discalis), and 16,069 bp (S.spicupennis), respectively. All of the PCGs started with the typical ATN (ATT, ATC or ATG) or TTG codon and most ended with complete TAA or TAG codon, with the exception of the ND5 gene, which terminated with an incomplete T. The mitochondrial genomes for these two recorded species are provided, and the constructed phylogenetic tree supports their morphological taxonomic classification. The topology of the phylogenetic tree showed that three species of Scelimena were clustered into one branch and formed a monophyletic and a holophyletic group.

The Acceptance of Cream Soups with the Addition of Edible Insects (Mealworm, T. molitor; House Cricket, A. domesticus; Buffalo Worm, A. diaperinus; Grasshopper, R. differens) among Young People and Seniors in Poland.

Research on the acceptance of consuming insects in one's diet shows the increasing importance of this issue in the context of a sustainable food chain and ecology. Insects represent a promising food source due to their high nutritional value, efficiency in production, and minimal environmental impact, as well as the growing awareness of ecological issues. Despite these benefits, cultural and psychological barriers hinder the acceptance of consuming insects in Western countries. In this study, an assessment was made of the acceptance level of cream-type soups made from tomatoes and white vegetables with the addition of 20% flour from four insect species: mealworm (T. molitor); house cricket (A. domesticus); buffalo worm (A. diaperinus); and grasshopper (R. differens), compared to a control sample. One hundred and four subjects (55 seniors and 49 young adults) participated in this study. The acceptance level of various soups with insect flour was evaluated, considering different sensory parameters such as appearance, smell, taste, and texture. The research showed that older people have a lower acceptance for dishes containing insects compared to young adults, but the differences in the responses given were not statistically significant (p = 0.05), rejecting the assumption that insect-based products should be mainly targeted at young people. Of all the proposed test samples, the mealworm (T. molitor) was the most acceptable insect species in the tests in both taste versions for both age groups. The average score was 6.63 points on a 10-point scale. The products with the addition of grasshopper (R. differens) were rated the lowest. The acceptance level ranged between 4.23 and 4.38 points. A multiple regression analysis showed that taste and texture had the strongest influence on the overall acceptance of these dishes, and the results obtained were highly correlated with the general opinion of the testers. The increasing acceptance level and growing interest in this type of food can be a positive step towards sustainable and efficient food production.

Comparative analysis of mitogenomes among three species of grasshoppers (Orthoptera: Acridoidea: Gomphocerinae) and their phylogenetic implications.

Whole mitochondrial genomes have been widely used in phylogenetic analysis, population genetics and biogeography studies. This study sequenced and characterized three complete mitochondrial genomes (Dasyhippus peipingensis, Myrmeleotettix palpalis, Aeropedellus prominemarginis) and determined their phylogenetic position in Acrididae. The length of the mitochondrial genomes ranged from 15,621-15,629 bp and composed of 13 PCGs, 2 rRNA, 22 tRNA genes and an AT control region. The arrangement and structure of the mitochondrial genomes were similar to those of other invertebrates. Comparative genomics revealed that the three mitochondrial genomes were highly conserved in terms of gene size, structure, and codon usage, all PCGs were purified selections with an ATN start codon and a TAN stop codon. All tRNAs could be folded into the typical clover-leaf structure, except tRNA Ser (AGN) that lacked a dihydrouridine (DHU) arm. Phylogenetic analysis based on 13 PCGs of 34 Acrididae species and seven outgroup species revealed that differences in the shape of antennae within the family Acrididae should be given less weight as a taxonomic character for higher-level classification. Moreover, the divergence time estimates indicates that in Gomphocerinae, the species with clubbed antennae were formed within the nearest 18 Mya, and Pacris xizangensis is more ancient.

Isolation and characterization of intestinal bacteria associated with cellulose degradation in grasshoppers (Orthoptera).

Insect gut bacteria play an essential role in the nutritional metabolism, growth, and development of insects. Grasshoppers (Orthoptera) are cellulose-rich plant-feeding pests. Although the biological potential of grasshopper gut microorganisms to assist cellulose decomposition is well established, microbial resources for efficient degradation of cellulose biomass are still scarce and need to be developed. In this study, we used selective media to isolate cellulose-degrading bacteria from the intestines of Atractomorpha sinensis, Trilophidia annulata, Sphingonotus mongolicus, and Calliptamus abbreviatus. Phylogenetic analysis based on the maximum likelihood method using 16S rDNA sequencing sequences to identify bacteria revealed the isolation of 11 strains belonging to 3 genera, including Klebsiella, Aeromonas, and Bacillus. The degradability of the isolates to cellulose was then determined by the DNS colorimetric method, and the results showed that Bacillus had the highest degradation rate. The elucidation of microbial cellulose degradation capacity in grasshoppers not only contributes to the understanding of multiple plant-insect-microbe interactions, but also provides a valuable microbial resource for solving the biomass conversion of cellulose species problem.

The neglect of nonnative orthopterans as potential invaders: A call for awareness.

Despite the potential ecological and economic impacts of invasive species, there is a dearth of data on the presence, impacts, and management implications of potentially invasive Orthoptera species. This lack of research and inconsistent data, including risk screenings and impact assessments, is especially evident in Europe. Consequently, assessing the status, distribution, and potential threats of nonnative Orthoptera in Europe remains challenging, impeding the development of effective management strategies. To address this gap, we call for increased efforts to collect and curate data on non-native and possibly invasive Orthoptera in Europe. Such efforts will improve our understanding of this order's invasion dynamics, facilitate the identification of priority areas for conservation, and support the development of effective management policies and preventive measures.

New hybrid segmentation algorithm: UNet-GOA.

The U-Net architecture is a prominent technique for image segmentation. However, a significant challenge in utilizing this algorithm is the selection of appropriate hyperparameters. In this study, we aimed to address this issue using an evolutionary approach. We conducted experiments on four different geometric datasets (triangle, kite, parallelogram, and square), with 1,000 training samples and 200 test samples. Initially, we performed image segmentation without the evolutionary approach, manually adjusting the U-Net hyperparameters. The average accuracy rates for the geometric images were 0.94463, 0.96289, 0.96962, and 0.93971, respectively. Subsequently, we proposed a hybrid version of the U-Net architecture, incorporating the Grasshopper Optimization Algorithm (GOA) for an evolutionary approach. This method automatically discovered the optimal hyperparameters, resulting in improved image segmentation performance. The average accuracy rates achieved by the proposed method were 0.99418, 0.99673, 0.99143, and 0.99946, respectively, for the geometric images. Comparative analysis revealed that the proposed UNet-GOA approach outperformed the traditional U-Net architecture, yielding higher accuracy rates.

Mechanomyography Signal Pattern Recognition of Knee and Ankle Movements Using Swarm Intelligence Algorithm-Based Feature Selection Methods.

Pattern recognition of lower-limb movements based on mechanomyography (MMG) signals has a certain application value in the study of wearable rehabilitation-training devices. In this paper, MMG feature selection methods based on a chameleon swarm algorithm (CSA) and a grasshopper optimization algorithm (GOA) are proposed for the pattern recognition of knee and ankle movements in the sitting and standing positions. Wireless multichannel MMG acquisition systems were designed and used to collect MMG movements from four sites on the subjects thighs. The relationship between the threshold values and classification accuracy was analyzed, and comparatively high recognition rates were obtained after redundant information was eliminated. When the threshold value rose, the recognition rates from the CSA fluctuated within a small range: up to 88.17% (sitting position) and 90.07% (standing position). However, the recognition rates from the GOA drop dramatically when increasing the threshold value. The comparison results demonstrated that using a GOA consumes less time and selects fewer features, while a CSA gives higher recognition rates of knee and ankle movements.