Search

Domesticated honeybees and wild bees are some of the most important beneficial insects for human and environmental health, but infectious diseases pose a serious risk to these pollinators, particularly following the emergence of the ectoparasitic mite Varroa destructor as a viral vector. The acquisition of this novel viral vector from the Asian honeybee Apis ceranae has fundamentally changed viral epidemiology in its new host, the western honeybee A. mellifera. While the recently discovered Lake Sinai Viruses (LSV) have been associated with weak honeybee colonies, they have not been associated with vector-borne transmission. By combining a large-scale multi-year survey of LSV in Chinese A. mellifera and A. cerana honeybee colonies with globally available LSV-sequence data, we investigate the global epidemiology of this virus. We find that globally distributed LSV is a highly diverse multi-strain virus, which is predominantly associated with the western honeybee A. mellifera. In contrast to the vector-borne deformed wing virus, LSV is not an emerging disease. Instead, demographic reconstruction and strong global and local population structure indicates that it is a highly variable multi-strain virus in a stable association with its main host, the western honeybee. Prevalence patterns in China suggest a potential role for migratory beekeeping in the spread of this pathogen, demonstrating the potential for disease transmission with the man-made transport of beneficial insects., (© 2023 The Authors. Molecular Ecology published by John Wiley & Sons Ltd.)

Independent origins of sociality in bees and ants are associated with independent expansions of particular odorant receptor (OR) gene subfamilies. In ants, one clade within the OR gene family, the 9-exon subfamily, has dramatically expanded. These receptors detect cuticular hydrocarbons (CHCs), key social signaling molecules in insects. It is unclear to what extent 9-exon OR subfamily expansion is associated with the independent evolution of sociality across Hymenoptera, warranting studies of taxa with independently derived social behavior. Here, we describe OR gene family evolution in the northern paper wasp, Polistes fuscatus , and compare it to four additional paper wasp species spanning ∼40 million years of evolutionary divergence. We find 200 putatively functional OR genes in P. fuscatus , matching predictions from neuroanatomy, and more than half of these are in the 9-exon subfamily. Most OR gene expansions are tandemly arrayed at orthologous loci in Polistes genomes, and microsynteny analysis shows species-specific gain and loss of 9-exon ORs within tandem arrays. There is evidence of episodic positive diversifying selection shaping ORs in expanded subfamilies. Values of omega (d N/ d S) are higher among 9-exon ORs compared to other OR subfamilies. Within the Polistes OR gene tree, branches in the 9-exon OR clade experience relaxed negative (relaxed purifying) selection relative to other branches in the tree. Patterns of OR evolution within Polistes are consistent with 9-exon OR function in CHC perception by combinatorial coding, with both natural selection and neutral drift contributing to interspecies differences in gene copy number and sequence. [ABSTRACT FROM AUTHOR]

Individual heterogeneity within societies provides opportunities to test hypotheses about adaptive neural investment in the context of group cooperation. Here, we explore neural investment in defense specialist soldiers of the eusocial stingless bee (Tetragonisca angustula) which are age subspecialized on distinct defense tasks and have an overall higher lifetime task repertoire than other sterile workers within the colony. Consistent with predicted behavioral demands, soldiers had higher relative visual (optic lobe) investment than nonsoldiers but only during the period when they were performing the most visually demanding defense task (hovering guarding). As soldiers aged into the less visually demanding task of standing guarding this difference disappeared. Neural investment was otherwise similar across all colony members. Despite having larger task repertoires, soldiers had similar absolute brain size and the smaller relative brain size compared to other workers, meaning that lifetime task repertoire size was a poor predictor of brain size. Both high behavioral specialization in stable environmental conditions and reassignment across task groups during a crisis occur in T. angustula. The differences in neurobiology we report here are consistent with these specialized but flexible defense strategies. This work broadens our understanding of how neurobiology mediates age and morphological task specialization in highly cooperative societies., (© 2021 Wiley Periodicals LLC.)

Accusations have been made against high-profile papers documenting honeybee navigation, specifically regarding the existence of an internal "odometer" that relies on visual cues. Two scientists have raised concerns about possible miscalculations, image reuse, and data manipulation in 10 key papers. The author of these papers, Mandyam Veerambudi "Srini" Srinivasan, denies the allegations and states that his conclusions remain firm and have been independently replicated. While some researchers support Srinivasan, others believe that the claims need to be revisited. The journal Science is evaluating the concerns, and further investigation may be necessary. [Extracted from the article]

The "River Disease" (RD), a disorder impacting honeybee colonies located close to waterways with abundant riparian vegetation (including Sebastiania schottiana, Euphorbiaceae), kills newly hatched larvae. Forager bees from RD-affected colonies collect honeydew excretions from Epormenis cestri (Hemiptera: Flatidae), a planthopper feeding on trees of S. schottiana. First-instar honeybee larvae fed with this honeydew died. Thus, we postulated that the nectars of RD-affected colonies had a natural toxin coming from either E. cestri or S. schottiana. An untargeted metabolomics characterization of fresh nectars extracts from colonies with and without RD allowed to pinpoint xanthoxylin as one of the chemicals present in higher amounts in nectar from RD-affected colonies than in nectars from healthy colonies. Besides, xanthoxylin was also found in the aerial parts of S. schottiana and the honeydew excreted by E. cestri feeding on this tree. A larva feeding assay where xanthoxylin-enriched diets were offered to 1 st instar larvae showed that larvae died in the same proportion as larvae did when offered enriched diets with nectars from RD-colonies. These findings demonstrate that a xenobiotic can mimic the RD syndrome in honeybee larvae and provide evidence of an interspecific flow of xanthoxylin among three trophic levels. Further, our results give information that can be considered when implementing measures to control this honeybee disease., (© 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

The use of modern technology is becoming part of both industry and agriculture. These technologies can also be used in beekeeping, where they can help to monitor the operation of the hive remotely. Beekeepers can remotely monitor the weight of their hives, their temperature, humidity, and other parameters. The aim of this paper is to map the beekeepers in the use of products with monitoring system for remote bee detection in beekeeping in Czechia. To map the issue, qualitative research using semi-structured interviews was conducted with beekeepers, manufacturers/providers of smart devices in beekeeping, and other entities involved in beekeeping. The findings showed that the interest of manufacturers and sellers to offer these smart devices is significant, but the interest of beekeepers is rather less, due to e.g., the purchase price, weaker IT knowledge, traditional beekeeping practices, higher age of beekeepers and the joy of being personally with bees. The novelty of the paper is not to look at the provision of ICT in beekeeping from a technical perspective, but from the perspective of users (beekeepers) and manufacturers of these technologies. Through interviews with beekeepers as well as others in the apiculture sphere, a comprehensive view of the issue is developed. Moreover, this is the first piece of research on this area in Czechia. [ABSTRACT FROM AUTHOR]

The paper analyzed the evolution animal sector regarding livestock and production in Romania in the period 2007-2020. Two sub-periods: P1- 2007-2013 and P2 2014-2020 were compared for assessing if the achievements in P2 were superior. The data from the National Institute of statistics regarding livestock and production by species were processed using fixed basis index, structural index, regression equations, coefficient of determination, multi annual mean per decade, absolute and relative differences between P2 and P1, in order to emphasize the trends and changes during the studied period. The results emphasized the following: the number of bovines, pigs and poultry decreased, while the number of sheep and goats and bee families increased both in P2 and P1. The total animal live weight at slaughter diminished due to the lower and lower live weight of bovines and pigs. However, the increased live weight at slaughter of sheep, goats and poultry had a positive impact. Milk and egg production declined and continued in P2, while wool and honey production increased. Despite that agricultural production value in animal sector increased by +20,420 trillion Lei in 2020 versus 2007, it was by 68.61% smaller than the agricultural production value achieved in the vegetal sector. In consequence, the contribution of animal sector to agricultural output was just 31.39% in the year 2020. The gaps in domestic production have to be covered by imports to meet consumers' requirements and this will deepen the deficit in agro-food trade balance. The reduction of CO2 emissions in agriculture, where 50% come from animal sector, obliges farmers to set up strategies destined to promote animal products obtained from more environment friendly technologies. [ABSTRACT FROM AUTHOR]

This paper is intended to study the legal protection of the Maltese honey bee (Apis mellifera ruttneri) from the point of view of preserving Maltese biodiversity, and more specifically the honey bee's genetic status. The primary aim is to establish whether and how theMaltese honey bee can be protected, specifically through the banning of imports of foreign Apis mellifera subspecies. States are under the general legal obligation of protecting their biodiversity. Member States (MS) of the European Union (EU) EU MS have more specific obligations to do so under EU law. However, Yet conservation of biodiversity under EU law cannot be used to restrict the freedom of movement of goods unless this is done for very restrictive and specific reasons outlined under the EU treaties. This paper will be split into three broad sections. The first establishes whether there are legal obligations to protect the Maltese honey bee imposed on the Maltese government. The second considers whether such protection can be legally justified under EU law, including through banning imports of foreign subspecies of the Apis mellifera species. The third reviews the different methods available to protect the honey bee through the banning of imports of foreign bees. It also incorporates a comparative study of three EU MS that have protected, or are in the process of protecting, a bee native to their territories. [ABSTRACT FROM AUTHOR]

Solitary bees are in constant decline due to climate change, pesticide toxicity, and habitat loss. Provision of nesting sites is an important conservation strategy. Various factors affect bee nesting, including parasitism, entrance orientation, nesting substrate type, and diameter. This study explored the impact of nesting substrate, cavity diameter, and entrance orientation on solitary bee nesting preferences. Additionally, it investigated the influence of landscape type and seasonality on bee nesting efficiency which is the ability of a bee to successfully establish nest. Trap nests were placed at eight locations, representing five landscapes (forest, desert, agriculture, peri-urban, and urban). These trap nests had five different nesting substrates (bamboo reeds, wooden blocks, wooden logs, mud blocks, and paper tubes). At each location, four traps were set in all directions. The results showed maximum cavity occupation in south-facing nests. Peri-urban landscapes were the most favored for nesting, followed by forests. Solitary bees primarily preferred bamboo reeds for nesting, with peak occupation from April to June. Bees favored cavities with 6- and 8-mm entrance diameters, while wasps occupied smaller diameters (< 5 mm). Overall, bee species occupied fewer nests compared to parasitic wasps. Future research should explore brood chamber numbers and species-specific nesting preferences for bees, along with the impact of cavity microclimate on bee growth. [ABSTRACT FROM AUTHOR]

The artificial bee colony algorithm (ABC) is a promising metaheuristic algorithm for continuous optimization problems, but it performs poorly in solving discrete problems. To address this issue, this paper proposes a hybrid discrete artificial bee colony (HDABC) algorithm based on label similarity for the point-feature label placement (PFLP) problem. Firstly, to better adapt to PFLP, we have modified the update mechanism for employed bees and onlooker bees. Employed bees learn the label position of the better individuals, while onlooker bees perform dynamic probability searches using two neighborhood operators. Additionally, the onlooker bees' selection method selects the most promising solutions based on label similarity, which improves the algorithm's search capabilities. Finally, the Metropolis acceptance strategy is replaced by the original greedy acceptance strategy to avoid the premature convergence problem. Systematic experiments are conducted to verify the effectiveness of the neighborhood solution generation method, the selection operation based on label similarity, and the Metropolis acceptance strategy in this paper. In addition, experimental comparisons were made at different instances and label densities. The experimental results show that the algorithm proposed in this paper is better or more competitive with the compared algorithm. [ABSTRACT FROM AUTHOR]

In this paper, a novel Artificial Bee Colony algorithm is proposed to solve a variant of the Job Shop Scheduling Problem where only an interval of possible processing times is known for each operation. The solving method incorporates a diversification strategy based on the seasonal behaviour of bees. That is, the bees tend to explore more at the beginning of the search (spring) and be more conservative towards the end (summer to winter). This new strategy helps the algorithm avoid premature convergence, which appeared to be an issue in previous papers tackling the same problem. A thorough parametric analysis is conducted and a comparison of different seasonal models is performed on a set of benchmark instances from the literature. The results illustrate the benefit of using the new strategy, improving the performance of previous ABC-based methods for the same problem. An additional study is conducted to assess the robustness of the solutions obtained under different ranking operators, together with a sensitivity analysis to compare the effect that different levels of uncertainty have on the solutions' robustness. [ABSTRACT FROM AUTHOR]

Bee surveys bring valuable information regarding species distribution, phenology, and their interactions with host plants, and thus are important to bee conservation, especially in the present scenario of drastic declines reported worldwide. The Brazilian bee fauna has been surveyed intensively since the late 1960s, but the state-of-the-art of this research topic has not been explored in detail. Our main goal is to analyze the scientific literature through a systematic review of Brazilian bee surveys, describing (i) spatial sampling gaps; (ii) preferred sampling frequency and methods; (iii) species identification and vouchering practices; (iv) gender participation; and (v) how the studies are distributed among scientific journals. Our review includes 213 published studies, of which half targeted the entire bee fauna (Apoidea: Apidae sensu lato) while the other half targeted the orchid bees (Euglossini). Sampling sites are predominant in eastern Brazil, particularly within the Atlantic Forest. Hand netting bees for 1 year long was the most frequent sampling protocol to capture bees. Taxonomic identification and voucher deposition practices were mentioned in most of the papers. Men and women published almost the same number of papers, but women were less frequent as lead or senior authors and appeared less as prolific researchers. Most papers were published in a few Brazilian journals. We highlight that surveys in understudied areas are needed, especially in Amazon. Monitoring bees in previously surveyed locations is also encouraged to investigate temporal changes in bee assemblages, such as population declines, impacts of land-use changes, and effects of climate change. [ABSTRACT FROM AUTHOR]

Simple Summary: Bees are important pollinators that play a role in balancing ecosystems; however, their survival rates have decreased due to many factors, including pathogens and exposure to pesticides. Bees have native mechanisms to help them tackle such challenges, and yet, these may not be enough. To this end, gut symbionts are beneficial, as they can help stimulate bees' immune systems and detoxify ingested toxic chemicals. To enhance the efficiency of these mechanisms, genetic engineering is proposed in this work to further optimize the ability of bee gut symbionts, particularly in the dominant bacteria Snodgrassella alvi and Gilliamella apicola. Engineering strategies are discussed according to the gut symbiotic bacteria's main roles in digestion, essential nutrient provision, and pesticide detoxification. Bees play a crucial role as pollinators, contributing significantly to ecosystems. However, the honeybee population faces challenges such as global warming, pesticide use, and pathogenic microorganisms. Promoting bee growth using several approaches is therefore crucial for maintaining their roles. To this end, the bacterial microbiota is well-known for its native role in supporting bee growth in several respects. Maximizing the capabilities of these microorganisms holds the theoretical potential to promote the growth of bees. Recent advancements have made it feasible to achieve this enhancement through the application of genetic engineering. In this review, we present the roles of gut symbionts in promoting bee growth and collectively summarize the engineering approaches that would be needed for future applications. Particularly, as the engineering of bee gut symbionts has not been advanced, the dominant gut symbiotic bacteria Snodgrassella alvi and Gilliamella apicola are the main focus of the paper, along with other dominant species. Moreover, we propose engineering strategies that will allow for the improvement in bee growth with listed gene targets for modification to further encourage the use of engineered gut symbionts to promote bee growth. [ABSTRACT FROM AUTHOR]

With the colossal development that the multimedia applications have currently reached, it is possible to manipulate the data contents easily. Thus, a receiver may get incorrect data compared to what the sender transmits. As a result, it is required to come up with an effective solution that checks the integrity of the received data, mainly images. In this context, we attempt through this paper to present a semi-fragile blind watermarking method using ABC, BRISK features and DCT. The method works on embedding the watermark data into specific area. As for the extraction stage, an authentication key is used to decide if the watermarked image was changed during transferring or not. Our findings show the efficiency of the proposed technique in terms of imperceptibility, robustness against some attacks, and tamper detection accuracy. [ABSTRACT FROM AUTHOR]

Copyright of Historia Agraria is the property of Historia Agraria 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 paper questions design priorities in computational systems and proposes that social aspects of material practice are overlooked in existing computational design practices. An interactive fabrication system designed for this project: Digital Tufting Bee centres on machine tufting, an adaptation of the handcrafting technique for making voluminous folds of yarn. The word 'Bee' refers to a quilting tradition in which a group comes together to quilt; I use this term to emphasize communal effort, shared decision-making and collective meaning-making in computational design processes. Building on literature in Science and Technology Studies, I argue that collective material practice and social play deepen human engagement in making processes and further challenge existing orders of computational design processes. By collecting and analysing qualitative data from three tufting workshops, I observed that uncertainties of yarn, conversation during making, tendencies to leave space for others, and exchange of crafting skills brought valuable meaning to interactive tufting. This paper concludes that as long as researchers involve communal aspects of making to connect makers, tools, materials and their communities, computational making could challenge the dominant design paradigm. Based on these findings, promising areas of further study include rituals of gift giving and collective textile repair in material practices. [ABSTRACT FROM AUTHOR]

Target detection at the hive gate of a beehive can be used to effectively monitor invasive beehive species. However, in the natural environment, there is often a multi-target and multi-scale problem at the hive gate, making it difficult for beekeepers to accurately detect the internal state of the hive. (1) To solve the above problems, this paper proposes an improved RetinaNet target detection network, DY-RetinaNet, for the identification of common species at the hive doors of beehives in natural environments, i.e., Chinese bees, wasps, and cockroaches. (2) First, to solve the multi-target multi-scale problem presented in this paper, we propose replacing the FPN layer in the initial model RetinaNet with a symmetric structure BiFPN layer consisting of a feature pyramid, which allows the model to better balance the feature information of different scales. Then, for the loss function, using CIOU loss instead of smooth L1 loss makes the network more accurate for small target localization at multiple scales. Finally, the dynamic head framework is added after the model backbone network, due to the benefits of its multi-attention mechanism, which makes the model more concerned with multi-scale recognition in a multi-target scenario. (3) The experimental results of the homemade dataset show that DY-RetinaNet has the best network performance, compared to the initial model RetinaNet, when the backbone network is ResNet-101-BiFPN, and the mAP value of DY-RetinaNet is 97.38%. Compared with the initial model, the accuracy is improved by 6.77%. The experimental results from the public dataset MSCOCO 2017 show that DY-RetinaNet is better than the existing commonly used target-detection algorithms, such as SSD, YOLOV3, Faster R-CNN, Mask R-CNN, FCOS, and ExtremeNet. These results verify that the model has strong recognition accuracy and generalization ability for multi-target multi-scale detection. [ABSTRACT FROM AUTHOR]

The shuffled frog leaping algorithm (SFLA) is a promising metaheuristic bionics algorithm, which has been designed by the shuffled complex evolution and the particle swarm optimization (PSO) framework. However, it is easily trapped into local optimum and has the low optimization accuracy when it is used to optimize complex engineering problems. To overcome the shortcomings, a novel modified shuffled frog leaping algorithm (MSFLA) with inertia weight is proposed in this paper. To extend the scope of the direction and length of the updated worst frog (vector) of the original SFLA, the inertia weight α was introduced and its meaning and range of the new parameters are fully explained. Then the convergence of the MSFLA is deeply analyzed and proved theoretically by a new dynamic equation formed by Z-transform. Finally, we have compared the solution of the 7 benchmark functions with the original SFLA, other improved SFLAs, genetic algorithm, PSO, artificial bee colony algorithm, and the grasshopper optimization algorithm with invasive weed optimization. The testing results showed that the modified algorithms can effectively improve the solution accuracy and convergence property, and exhibited an excellent ability of global optimization in high-dimensional space and complex function problems. [ABSTRACT FROM AUTHOR]

The aim of this paper was to conduct a comparative analysis of rapeseed honeys enriched with various bee products: propolis (1%), bee bread (2%), and bee pollen (5%). The parameters examined included water content, electrical conductivity, pH, free acid content, brown pigment content, color analysis, total polyphenol content, sugar content, and antioxidant activity using the DPPH method. The results demonstrated compliance with Polish requirements for commercial honey quality, with one exception: honey containing 1% propolis, which had a water content of 21.15%. The analysis results indicated that the tested bee products exhibited strong antioxidant properties, with rapeseed honey enriched with 5% bee pollen showing the highest antioxidant activity and content. [ABSTRACT FROM AUTHOR]

In recent years, honey bee colony losses in the Republic of Kosovo remained largely unknown. From 2019 to 2021, 81 apiaries with different disease suspicions were investigated in the framework of honey bee disease passive surveillance. Fifty-nine of the eighty-one apiaries were tested for Vairimorpha ceranae, Vairimorpha apis, trypanosomatids Lotmaria passim, and Crithidia mellificae. All samples were positive for V. ceranae (100%) whereas L. passim was found with a lower frequency (11.9%). V. apis and C. mellificae were not found. Thirteen of the eighty-one apiaries were tested for seven viruses (ABPV, CBPV, DWV, BQCV, SBV, IAPV, KBV) and five of them were found (ABPV, CBPV, DWV, BQCV, SBV). The most frequently detected viruses in honey bees and Varroa mites were DWV (100%) followed by BQCV, ABPV, SBV, and CBPV (92.3%, 69.2%, 30.8%, and 7.7%, respectively). Varroa mite samples had different degrees of co-infection by viruses. Nine of the eighty-one apiaries consisted of brood combs with larvae, eight of them were AFB positive, ERIC I genotype, and one EFB positive. This paper represents the first molecular investigation (PCR) and detection of the honey bee viruses ABPV, CBPV, DWV, BQCV, and SBV as well as V. ceranae, L. passim, and M. plutonius in the Republic of Kosovo. [ABSTRACT FROM AUTHOR]

Featured Application: An automatic honey bee classification system based on audio signals for tracking the frequency of workers and drones entering and leaving a hive. The recent advances in smart beekeeping focus on remote solutions for bee colony monitoring and applying machine learning techniques for automatic decision making. One of the main applications is a swarming alarm, allowing beekeepers to prevent the bee colony from leaving their hive. Swarming is a naturally occurring phenomenon, mainly during late spring and early summer, but it is extremely hard to predict its exact time since it is highly dependent on many factors, including weather. Prevention from swarming is the most effective way to keep bee colonies; however, it requires constant monitoring by the beekeeper. Drone bees do not survive the winter and they occur in colonies seasonally with a peak in late spring, which is associated with the creation of drone congregation areas, where mating with young queens takes place. The paper presents a method of early swarming mood detection based on the observation of drone bee activity near the entrance to a hive. Audio recordings are represented by Mel Frequency Cepstral Coefficients and their first and second derivatives. The study investigates which MFCC coefficients, selected by the Least Absolute Shrinkage and Selection Operator, are significant for the worker bee and drone bee classification task. The classification results, obtained by an autoencoder neural network, allow to improve the detection performance, achieving accuracy slightly above 95% for the chosen set of signal features, selected by the proposed method, compared to the standard set of MFCC coefficients with only up to 90% accuracy. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) consists of complex and dynamically aggregated elements or smart entities that need decentralized supervision for data exchanging throughout different networks. The artificial bee colony (ABC) is utilized in optimization problems for the big data in IoT, cloud and central repositories. The main limitation during the searching mechanism is that every single food site is compared with every other food site to find the best solution in the neighboring regions. In this way, an extensive number of redundant comparisons are required, which results in a slower convergence rate, greater time consumption and increased delays. This paper presents a solution to optimize search operations with an enhanced ABC (E-ABC) approach. The proposed algorithm compares the best food sites with neighboring sites to exclude poor sources. It achieves an efficient mechanism, where the number of redundant comparisons is decreased during the searching mechanism of the employed bee phase and the onlooker bee phase. The proposed algorithm is implemented in a replication scenario to validate its performance in terms of the mean objective function values for different functions, as well as the probability of availability and the response time. The results prove the superiority of the E-ABC in contrast to its counterparts. [ABSTRACT FROM AUTHOR]

Background: Hymenoptera envenomation with honey bee (Apis mellifera) and paper wasp (Polistes spp.) may cause life‐threatening anaphylaxis in dogs. In human patients, clinical history, intradermal testing (IDT) and measurement of allergen‐specific serological immunoglobulin (Ig)E (sIgE) are used to support a diagnosis of Hymenoptera venom hypersensitivity. The utility of venom allergen‐specific sIgE has not yet been evaluated for this purpose in dogs. Objectives: The objective of the study was to investigate the sensitivity (sn), specificity (sp) and positive predictive value (PPV) of honey bee and paper wasp serological titres using a commercially available sIgE assay [VARL (Veterinary Allergen Reference Laboratory) Liquid Gold] against clinical history for a diagnosis of Hymenoptera hypersensitivity in dogs. Materials and Methods: Honeybee and paper wasp IgE serum titres were measured in 15 client‐owned dogs with a diagnosis of Hymenoptera venom hypersensitivity based on a history of anaphylaxis, owner observation of Hymenoptera, and positive IDT to bee and/or wasp; and in 10 client‐owned dogs with no known history of anaphylaxis or Hymenoptera exposure and a negative IDT to bee and wasp. Results: Analysis of receiver operating characteristic (ROC) curves demonstrate that a VARL score cut‐off of one of six for honeybee yields Sn, Sp and PPV of 40%, 60% and 60%, respectively, and two of six for wasp yields Sn, Sp and PPV of 25%, 78% and 60%, respectively. Conclusions and Clinical Relevance: Owing to the poor sensitivity and PPV of sIgE assays for both bee and wasp hypersensitivity in dogs with known envenomation and anaphylaxis, the use of sIgE cannot be recommended as a tool for venom identification. [ABSTRACT FROM AUTHOR]

Honey bees are eusocial insects which respond to warm weather, abundant food source by increasing their population through swarming to ensure the survival of the colony. To maintain a superior colony a queen must have a nutrient-rich diet and high egg production. Royal jelly is a high-quality food which has numerous beneficial properties required for proper growth, development, survival of the queen. Factors like congestion, lack of adequate queen pheromone, abnormal queen pheromone, pathogenic infections, exposure to pesticides influence the queen quality which further promotes non-reproductive swarming behaviour. Worker bees analyse the queen condition to prepare for supersedure or emergency queen rearing. This review paper highlights the influence of royal jelly composition on the queen quality, the impact of queen quality on swarming tendency, correlation between royal jelly composition and swarming tendency. [ABSTRACT FROM AUTHOR]

At present, the quality of material life and richness of the Chinese residents have been improved. Some people have high requirements for quality of their personal lives and put forward the problem of health preservation. Honey, as a nutritious food, is deeply loved by people. There are a large number of trace elements in honey, such as VC, VA, VD, VB1, and VB2. The honey from the Chinese honeybee has a very high nutritional value and plays an important role in the pollination and reproduction of some plants. Therefore, the Chinese honeybee plays a very significant role in the ecological environment. Moreover, it is protected as the main species resource of the country, which also fully proves the importance of the Chinese honeybee. Chinese bees can survive in various ecological and geographical environments in China and have strong heat as well as cold resistance. They can survive in the hot environment in the south and withstand the dynamics of severe cold in the north. At the same time, they can make full use of a small number of honey sources and have strong resistance to a variety of diseases and pests. In fact, there will be a variety of insect invasion problems in the beehive culture of Chinese bees, and it is necessary to accurately detect various diseases and pests during the breeding of Chinese bees. However, there are a large amount of insect invasion and various disease sources in the breeding stage of the Chinese bees. Therefore, in this paper, we use a deep learning algorithm to detect the insect invasion of the Chinese beehive culture and analyze the bee colonies in six bee farms in the province of Sichuan. In addition, we measure the common insect and disease indexes of the Chinese bee and analyze the parasitism rate, microsporidia infection rate, virus infection rate, and virus infection titer of bee colonies in overwintering and spring breeding. The experimental results show that the anti-insect invasion situation of bees in the six bee farms is significantly different; however, the antimite ability is basically the same. [ABSTRACT FROM AUTHOR]

Copyright of German Journal of Sports Medicine / Deutsche Zeitschrift fur Sportmedizin is the property of Verein zur Forderung der Sportmedizin Hannover e.V. 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.)

The original minimum exposure path (MEP) problem in WSNs (wireless sensor networks) requires the starting point and ending point of a moving target to be fixed, thus limiting the evaluation of coverage quality relative to the locations of these points. To resolve this issue, a minimum exposure path problem with various boundaries (VB-MEP) is proposed in this paper. Because the corresponding graph model cannot be established, the original classical methods (grid method and Voronoi diagram method) used to solve the minimum exposure path problem are no longer effective for the VB-MEP problem. This paper first transforms the problem into a hybrid optimization problem with constraint conditions and then considers the characteristics of the transformed mathematical optimization model with high dimensionality, unfixed dimensionality and high nonlinearity so that the deterministic optimization methods are no longer applicable. A hybrid artificial colony solution algorithm that incorporates the actual characteristics of the problem is designed, and a convergence analysis and a proof of the designed algorithm are given. Through simulation experiments based on large-scale node distribution scenarios, it is found that the designed hybrid optimization model with constraints and hybrid artificial bee colony solution algorithm can effectively solve the proposed VB-MEP problem. [ABSTRACT FROM AUTHOR]

Many countries including Ukraine use battle management systems (BMS) like Delta that enable command to share situation awareness information; this study focuses on the distribution of information across a warfighting network. Similar to natural systems, where autonomous agents, such as ants and bees, follow a set of simple rules, a BMS is a network of bases and electronic warfighting platforms that have military assets as agents within the network, guided by the defense doctrine. The rationale for the workability of such a system is based on each subsystem being reliable when multiple subsystems interact. However, the potential permutations and combinations of interactions can cause unpredictable negative or positive feedback loops, resulting in unpredictable and unwanted outcomes. The results of emergent behavior are unexpected and sometimes unwanted in areas such as intelligence, and wireless networks. Understanding emergent behavior is imperative in understanding complex engineering systems, and to present new insights, and take practical steps toward improving complex systems design and analysis. This paper presents the BMS and networks with examples of user-defined system integration of the network soldier concept. We believe that Ukrainian and other armies can directly benefit from utilising meta cybernetics, meta metasystem model analysis to control emergence. [ABSTRACT FROM AUTHOR]

Deep Learning (DL) is a type of machine learning used to model big data to extract complex relationship as it has the advantage of automatic feature extraction. This paper presents a review on DL showing all its network topologies along with their advantages, limitations, and applications. The most popular Deep Neural Network (DNN) is called a Convolutional Neural Network (CNN), the review found that the most important issue is designing better CNN topology, which needs to be addressed to improve CNN performance further. This paper addresses this problem by proposing a novel nature inspired hybrid algorithm that combines the Bees Algorithm (BA), which is known to mimic the behavior of honey bees, with Bayesian Optimization (BO) in order to increase the overall performance of CNN, which is referred to as BA-BO-CNN. Applying the hybrid algorithm on Cifar10DataDir benchmark image data yielded an increase in the validation accuracy from 80.72% to 82.22%, while applying it on digits datasets showed the same accuracy as the existing original CNN and BO-CNN, but with an improvement in the computational time by 3 min and 12 s reduction, and finally applying it on concrete cracks images produced almost similar results to existing algorithms. [ABSTRACT FROM AUTHOR]

The extreme conservation of mitochondrial genomes in metazoans poses a significant challenge to understanding mitogenome evolution. However, the presence of variation in gene order or genome structure, found in a small number of taxa, can provide unique insights into this evolution. Previous work on two stingless bees in the genus Tetragonula (T. carbonaria and T. hockingsi) revealed highly divergent CO1 regions between them and when compared to the bees from the same tribe (Meliponini), indicating rapid evolution. Using mtDNA isolation and Illumina sequencing, we elucidated the mitogenomes of both species. In both species, there has been a duplication of the whole mitogenome to give a total genome size of 30,666 bp in T. carbonaria; and 30,662 bp in T. hockingsi. These duplicated genomes present a circular structure with two identical and mirrored copies of all 13 protein coding genes and 22 tRNAs, with the exception of a few tRNAs that are present as single copies. In addition, the mitogenomes are characterized by rearrangements of two block of genes. We believe that rapid evolution is present in the whole Indo-Malay/Australasian group of Meliponini but is extraordinarily elevated in T. carbonaria and T. hockingsi, probably due to founder effect, low effective population size and the mitogenome duplication. All these features - rapid evolution, rearrangements, and duplication - deviate significantly from the vast majority of the mitogenomes described so far, making the mitogenomes of Tetragonula unique opportunities to address fundamental questions of mitogenome function and evolution., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Author(s). Published by Elsevier B.V. All rights reserved.)

Demodulation methods play a critical role in achieving high-performance interferometric fiber-optic temperature sensors. However, the conventional passive 3 × 3 coupler demodulation method overlooks certain issues, such as the non-1:1:1 splitting ratio of the coupler, resulting in a non-ideal phase difference in the three output interference signals. These problems significantly impact the measurement results of interferometric temperature sensors. In this paper, we propose a novel arc-tangent method based on a 3 × 3 coupler and a demodulation algorithm combining long short-term memory (LSTM) with an artificial bee colony (ABC). The arc-tangent method is employed to enhance the input phase signal of the ABC-LSTM network model and establish a nonlinear mapping between the phase signal and temperature, effectively preventing the influence of the spectral ratio and phase difference of the 3 × 3 coupler on temperature demodulation. The proposed ABC-LSTM method achieves high-resolution measurements with an interval of 0.10 °C, and the absolute error is below 0.0040 °C within the temperature range of 25.00–25.50 °C. To demonstrate the stability and adaptability of the proposed method under long-term constant temperature conditions, we conducted measurements for approximately three hours in a controlled temperature environment set at 25.00 °C. Experimental results indicate that the maximum error of LSTM-ABC method remains around 0.0040 °C, outperforming the conventional algorithm (0.0095 °C). Furthermore, when comparing the average error values of the conventional passive 3 × 3 coupler method (0.0023 °C), LSTM model (0.0019 °C), and ABC-LSTM model (0.0014 °C), it is evident that the demodulation results of the ABC-LSTM method exhibit the highest level of stability. Therefore, the ABC-LSTM method enhances the accuracy and reliability of interferometric fiber-optic temperature-sensing systems. [ABSTRACT FROM AUTHOR]

With the advancement of combat equipment technology and combat concepts, new requirements have been put forward for air defense operations during a group target attack. To achieve high-efficiency and lowloss defensive operations, a reasonable air defense weapon assignment strategy is a key step. In this paper, a multi-objective and multi-constraints weapon target assignment (WTA) model is established that aims to minimize the defensive resource loss, minimize total weapon consumption, and minimize the target residual effectiveness. An optimization framework of air defense weapon mission scheduling based on the multiobjective artificial bee colony (MOABC) algorithm is proposed. The solution for point-to-point saturated attack targets at different operational scales is achieved by encoding the nectar with real numbers. Simulations are performed for an imagined air defense scenario, where air defense weapons are saturated. The non-dominated solution sets are obtained by the MOABC algorithm to meet the operational demand. In the case where there are more weapons than targets, more diverse assignment schemes can be selected. According to the inverse generation distance (IGD) index, the convergence and diversity for the solutions of the non-dominated sorting genetic algorithm III (NSGA-III) algorithm and the MOABC algorithm are compared and analyzed. The results prove that the MOABC algorithm has better convergence and the solutions are more evenly distributed among the solution space. [ABSTRACT FROM AUTHOR]

The bee structure of an asphalt binder surface changes during the aging and rejuvenation process, and the effect of this microstructural change on the mechanical properties of the asphalt binder is not clear. Therefore, in this paper, a two-dimensional finite element model of an asphalt binder microstructure was constructed based on processed AFM images, and the contents of bee phases and bee casings were varied at the same time to analyze the stress and strain distribution law of the asphalt binder microstructure. The results of the study show that in the bee structure, the stress in the bee phase is obviously greater than that in the bee casing, and the stress in the interstitial phase is the lowest. With the simultaneous enhancement in the proportion of the bee phase and the bee casing, the stresses in the asphalt samples increased in all phase structures. Under the combined effect of the decrease in the content of the bee phase and the increase in the content of the bee casing, there is a certain degree of increase in the internal stresses and strains in the asphalt binder, the effect of the bee casing on the internal stresses in the asphalt binder is more pronounced, and the bee phase and the bee casing play better roles in resisting the external deformation due to the increase in the volume fraction. For a recycled asphalt binder, whether there is an increase in the dosage of the old asphalt binder or an enhancement in the interfacial diffusion and a fusion of new and old asphalt binders, the level of tensile strain within the recycled asphalt binder will increase to a certain extent, which, in turn, will put forward a higher requirement for its anti-cracking ability. [ABSTRACT FROM AUTHOR]

In the last decades, the availability constraint as well as learning and deteriorating effects were introduced into the production scheduling theory to simulate real-world case studies and to overcome the limitation of the classical models. To the best of our knowledge, this paper is the first in the literature to address the permutation flowshop scheduling problem (PFSP) with flexible maintenance under learning and deterioration effects to minimize the makespan. Firstly, we address the PFSP with flexible maintenance and learning effects. Then, the deteriorating effect is also considered. Adaptive artificial bee colony algorithms (ABC) enhanced with Q-learning are proposed, in which the Nawaz–Enscore–Ham (NEH) heuristic and modified NEH heuristics are hybridized with a maintenance insertion heuristic to construct potential integrated initial solutions. Furthermore, a Q-learning (QL)-based neighborhood selection is applied in the employed bees phase to improve the quality of the search space solutions. Computational experiments performed on Taillard's well-known benchmarks, augmented with both prognostic and health management (PHM) and maintenance data, demonstrate the effectiveness of the proposed QL-driven ABC algorithms. [ABSTRACT FROM AUTHOR]

Mobile network is a collection of devices with dynamic behavior where devices keep moving, which may lead to the network track to be connected or disconnected. This type of network is called Intermittently Connected Mobile Network (ICMN). The ICMN network is designed by splitting the region into 'n' regions, ensuring it is a disconnected network. This network holds the same topological structure with mobile devices in it. This type of network routing is a challenging task. Though research keeps deriving techniques to achieve efficient routing in ICMN such as Epidemic, Flooding, Spray, copy case, Probabilistic, andWait, these derived techniques for routing in ICMN are wise with higher packet delivery ratio, minimum latency, lesser overhead, and so on. A new routing schedule has been enacted comprising three optimization techniques such as Privacy-Preserving Ant Routing Protocol (PPARP), Privacy-Preserving Routing Protocol (PPRP), and Privacy-Preserving Bee Routing Protocol (PPBRP). In this paper, the enacted technique gives an optimal result following various network characteristics. Algorithms embedded with productive routing provide maximum security. Results are pointed out by analysis taken from spreading false devices into the network and its effectiveness at worst case. This paper also aids with the comparative results of enacted algorithms for secure routing in ICMN. [ABSTRACT FROM AUTHOR]

Sports video analysis has received much attention as it turned to be a hot research area in the field of image processing. This motivation offers opportunities that develop fascinating applications supported by analysis of different sports, especially soccer. Ball identification, in soccer images, is an essential task not only for goal‐scoring but also for performance evaluation. However, ball detection suffers from several hurdles such as occlusions, fast‐moving objects, shadows, poor lighting, color contrast, and other static background objects. Although several ball detection techniques have been introduced such as Frame Difference, Mixture of Gaussian (MoG), Optical Flow, and so forth; ball detection in soccer games is still an open research area. In this paper, a new Fuzzy Based Ball Detection (FB2D) strategy is proposed for identifying the ball through a set of image sequences extracted from a soccer match video. FB2D can accurately identify the ball even if it is attached to the white lines drawn on the playground or partially occluded behind players. FB2D is compared to recent ball detection techniques. Experimental results show that FB2D outperforms recent detection techniques as it introduces both the highest level of detection accuracy in the testing stage and the lowest possible error. [ABSTRACT FROM AUTHOR]

In this paper, molecular dynamics, full factorial experimental design and molecular docking were used to determine the toxic effects of pesticides on pests (Tetranychus telarius, Lygus lucorum and Helicoverpa armigera) and bees (North Chinese bee) in a cotton field, and an insecticide collocation scheme with the bi-directional selectivity was devised. Firstly, the main insecticides for three stages of cotton growth were identified under the lateral mixing condition. Insecticides for the first phase included abamectin (avermectin B1a and B1b), acetamiprid (N-(N-cyano-ethylimine)-N-methyl-2-chloropyridine-5-methylamine), dicofol (1,1-bis(p-Chlorophenyl)-2,2,2-trichloroethanol) and cypermethrin ((RS)-α-cyano-3-phenoxyebenzyl(SR)-3-(2,2-dichloroyl)-2,2-dimethyl cyclopropane carboxylic acid ester); the insecticides available in the second phase included cypermethrin ((RS)-α-cyano-3-phenoxyebenzyl(SR)-3-(2,2-dichloroyl)-2,2-dimethyl cyclopropane carboxylic acid ester), phoxim (O,O-diethyl-O-α-cyanophenylbenzylamine thiophosphate ester), deltamethrin ((R,cis)-2,2-dimethyl-3-(2,2-dibromovinylcyclopropane ester)-cyano-diphenyl ether) and abamectin (avermectin B1a and B1b). In third phase, cypermethrin ((RS)-α-cyano-3-phenoxyebenzyl(SR)-3-(2,2-dichloroyl)-2,2-dimethyl cyclopropane carboxylic acid ester), and deltamethrin ((R,cis)-2,2-dimethyl-3-(2,2-dibromovinylcyclopropane ester) -cyano-diphenyl ether) were included. Different insecticide application schemes were designed according to whether the application cycle and sequence were considered. The molecular dynamics simulation method was used to determine the effects of different insecticide application schemes on pests and bees. After the simulation, the simplified mixed-weighted model carried out each application scheme. In the case of lateral mixing, the combination of avermectin + acetamiprid + trichlorobacitol + cypermethrin + phoxim + deltamethrin was selected as the optimal application program, which reduced bee toxicity by 98.77% and increased insect toxicity by 55.84%. Whereas in the case of longitudinal residue, avermectin + cypermethrin + deltamethrin was selected. This combination reduced the harm to bees by 126.55% and increased the toxicity to target pests by 34.23%. Finally, by calculating the resultant force from different types of non-bonded forces, the mechanism of the effect of the optimal application scheme on bees and pests under two scenarios was analyzed. The optimally combined scheme prepared by screening could provide the bi-directional selectivity to bees and pests. This study provides an important reference for reducing the environmental problems caused by pesticide application in farmland. [ABSTRACT FROM AUTHOR]

Copyright of Przeglad Elektrotechniczny is the property of Przeglad Elektrotechniczny 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.)

The queen bee is the core member of a bee colony, and her loss will pose a great threat to the survival of the colony that may cause colony collapse. However, the process by which queen bee loss affects the internal social state of the bee colony remains unclear. In this paper, we used a multi-sensors system to continually monitor colonies with queen loss and regularly checked their biological status. Our results show that the queen loss initially caused a rapid decrease in brood rearing and changed the foraging strategy of the colony, leading to an increase in food storage. Also the population decline is difficult to reverse in a short time, even if the queen is naturally replaced. This study emphasises the impact of queen bee loss on the operation of the bee colony social system, and elucidates the interconnectedness of the bee colony social system. • Bee colony status was monitored using biology and multiple sensors. • Queen bee loss alters internal states as brooding, foraging, hive weight. • A new-born queen bee cannot improve the internal colony state in the short term. • A single indicator change can trigger chain reaction in the bee colony system. • Monitoring hive weight changes can effectively identify queen bee loss. [ABSTRACT FROM AUTHOR]

Wasps are understudied in their contribution to pollination services. In order to better understand the ecological contribution of wasp communities to plant pollination, we conducted three studies to compare bees and wasps by (1) the plant communities visited in agricultural and prairie environments, (2) body pollen composition as an indirect measure of pollination and (3) a single‐visit deposition study as a direct measure of pollination in the plant species complex Solidago canadensis.We found wasps visit a distinct early‐blooming exotic plant community from bees but have overlapping use of late‐blooming native plants and similar network interaction metrics. This suggests wasps may fill an ecological niche distinct from bees, while also serving as common native plant visitors. We also found that body pollen density and pollen fidelity in four and five (out of six) wasp families, respectively, were comparable to or greater than the bee family Colletidae. Three wasp families also showed comparable to or greater visit fidelity than two (out of five) bee families examined. These results suggest wasps may carry and potentially deliver substantial pollen to specific plants. In addition, controlled single‐visit deposition revealed the paper wasp Polistes fuscatus deposits a similar amount of pollen grains as the bumble bee Bombus impatiens, suggesting surprisingly high pollination efficiency that warrants further investigation.Our multi‐pronged study shows the importance of investigating the role of wasps as pollinators, especially by focusing on direct plant‐pollination metrics to determine wasp pollination efficacy. [ABSTRACT FROM AUTHOR]