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The optimization of the cutting path of the sample can effectively reduce the cutting time, thereby improving the production efficiency of numerical control processing. This paper comprehensively considers the impact of the cutting order and the position of the knife entry point on the cutting path, converts the cutting path problem into a type of traveling salesman problem (TSP), and proposes an improved genetic-particle swarm optimization algorithm. The selection mechanism of the algorithm combines the elitist retention strategy and roulette wheel selection method to accelerate the search for the optimal solution; the mutation strategy designs a linear decreasing mutation rate, which enhances the global search ability; at the same time, introduces the ant colony optimization algorithm to process the fitness function, adjusts the population evolution difference, and speeds up the optimization process. Through this hybrid algorithm, the cutting order of the sample can be quickly optimized, and the nearest neighbor algorithm is used to determine the position of the knife entry point. Tests are conducted on clothing patterning charts and standard examples. Compared with several commonly used algorithms, experimental results verify the feasibility and effectiveness of this algorithm. [ABSTRACT FROM AUTHOR]

To solve the problems of slow convergence and insufficient accuracy of traditional ant colony algorithms in solving large-scale problems, this paper proposes a multi-ant colony optimization algorithm based on game strategy and hierarchical temporal memory model (GHMACO). Firstly, the heterogeneous multi-ant colony model is constructed, and each colony collaborates to improve the performance of the algorithm. Secondly, in order to enhance the communication among the heterogeneous colonies, a non-cooperative game strategy is introduced. The heterogeneous ant colonies are divided into the propagating colony and the absorbing colonies, where the propagating colony propagates the optimal payoffs of the game, and the absorbing colonies choose optimal strategies for absorption to balance the convergence and diversity of the algorithm. Further, the hierarchical temporal memory model is adopted to perform hierarchical optimization strategies based on path memories which includes: local exploration strategy, pheromone redistribution strategy and path replacement strategy, thus improving the accuracy of the algorithm and helping the colonies to jump out of the local optimum. Experiments on the traveling salesman problem show that the improved algorithm is effective in improving the convergence and accuracy of the traditional ant colony algorithms, especially in large-scale problems. [ABSTRACT FROM AUTHOR]

Ant colony optimization is an intelligent evolutionary algorithm that has been widely used in the field of path planning, and the research on its improved methods is proliferating. In this paper, the improvement methods of single and hybrid ant colony optimization in path planning are reviewed in terms of initial pheromone concentration, heuristic function, state transition rule, pheromone update rule, and parameter optimization, respectively. The future research directions of ant colony optimization have been prospected in terms of theoretical aspects, parameter setting and optimization, integration with other algorithms, and multiobjectives. [ABSTRACT FROM AUTHOR]

Wireless sensor networks (WSNs) play a vital role in various fields, but ensuring optimal coverage poses a significant challenge due to the limited energy resources that constrain sensor nodes. To address this issue, this paper presents a novel approach that combines the binary ant colony algorithm (BACA), a variant of ant colony optimization (ACO), with other search optimization algorithms, such as hill climbing (HC) and simulated annealing (SA). The BACA is employed to generate an initial solution by emulating the foraging behavior of ants and the pheromone trails they leave behind in their search for food. However, we acknowledge that the BACA alone may not guarantee the most optimal solution. Subsequently, HC and SA are optimization search algorithms that refine the initial solution obtained by the BACA to find a more enhanced solution. Through extensive simulations and experiments, we demonstrate that our proposed approach results in enhanced coverage and energy-efficient coverage in a two-dimensional (2D) field. Interestingly, our findings reveal that HC consistently outperforms SA, particularly in less complex search spaces, leveraging its robust exploitation approach. Our research contributes valuable insights into optimizing WSN coverage, highlighting the superiority of HC in this context. Finally, we outline promising future research directions that can advance the optimization of WSN coverage. [ABSTRACT FROM AUTHOR]

In order to solve the problems of slow convergence and low accuracy of the traditional ant colony algorithm in solving the traveling salesman problem (TSP), this paper proposes a heterogeneous ant colony algorithm based on the selective evolution mechanism and game strategy (SGHACA). First, we propose a game mechanism. In each iteration, the best population and the worst population will play a game. At the end of the game, pheromone gains will be given to the participants according to the weight coefficients to motivate the populations to participate in the next round of the game, in order to promote cooperation among different populations and thus improve the diversity of the algorithm. Second, we introduce a selective evolution mechanism. The optimal paths of each iteration are compared with the historical optimal paths to evolve relatively better path fragments, thus improving the convergence speed of the algorithm. Finally, when the algorithm stagnates, we introduce a dynamic shaking mechanism, which is able to dynamically dither the pheromone on the current optimal path according to the number of iterations, increasing the probability that the algorithm chooses other paths, thus helping to jump out of the locally optimal solution. In order to verify the effectiveness of the improved algorithm in this paper, we experimentally verify through a large number of TSP instances that SGHACA is able to improve the convergence of the algorithm and the accuracy of the solution to a certain extent when solving large-scale TSP. Meanwhile, compared with the latest improved algorithms, the accuracy of the solution of SGHACA is better than most of the latest improved algorithms, which indicates that the improved algorithm of this paper has some competitiveness. [ABSTRACT FROM AUTHOR]

Distributed energy resources have demonstrated their potential to mitigate the limitations of large, centralized generation systems. This is achieved through the geographical distribution of generation sources that capitalize on the potential of their respective environments to satisfy local demand. In a microgrid, the control problem is inherently distributed, rendering traditional control techniques inefficient due to the impracticality of central governance. Instead, coordination among its components is essential. The challenge involves enabling these components to operate under optimal conditions, such as charging batteries with surplus solar energy or deactivating controllable loads when market prices rise. Consequently, there is a pressing need for innovative distributed strategies like emergent control. Inspired by phenomena such as the environmentally responsive behavior of ants, emergent control involves decentralized coordination schemes. This paper introduces an emergent control strategy for microgrids, grounded in the response threshold model, to establish an autonomous distributed control approach. The results, utilizing our methodology, demonstrate seamless coordination among the diverse components of a microgrid. For instance, system resilience is evident in scenarios where, upon the failure of certain components, others commence operation. Moreover, in dynamic conditions, such as varying weather and economic factors, the microgrid adeptly adapts to meet demand fluctuations. Our emergent control scheme enhances response times, performance, and on/off delay times. In various test scenarios, Integrated Absolute Error (IAE) metrics of approximately 0.01% were achieved, indicating a negligible difference between supplied and demanded energy. Furthermore, our approach prioritizes the utilization of renewable sources, increasing their usage from 59.7% to 86.1%. This shift not only reduces reliance on the public grid but also leads to significant energy cost savings. [ABSTRACT FROM AUTHOR]

The conflict between climate change and economic growth is one of the most significant dilemmas of our era. Under the prevalent discourse of sustainable development and green economy, many believe that market-based approaches can address environmental problems under the current capitalist economic regime. This article aims to analyse Ant Forest, a gamified green initiative launched by the biggest fintech company in China, to combat climate change through cultivating users' green lifestyles. Based on semi-structured interviews with the game-users, the paper argues that there is an inconsistency between the environmental value of Ant Forest and the real impact it has on the participants' consumption behaviour. As a capitalist green initiative based on consumption and market forces, Ant Forest reflects the basic logic of competition and expansion. In addition, it enhances the users' reliance on its related business entities and further alienates the users from the rest of nature by creating a knowledge gap that impedes its users from fully knowing the environmental implications of their consumption behaviour. [ABSTRACT FROM AUTHOR]

Several algorithms have been proposed in recent decades to solve optimization problems, some of which have been inspired by nature. The collective behavior of ants is an example of intelligence in the nature which has been a source of inspiration for optimization algorithms. Based on the concept of path integration, ants are able to continuously calculate their current location from their previous trajectory when exploring to find food. In the return journey, they go by calculating the outcome of the route, without returning exactly from their path, choosing a direct path to return to their original point. In this paper, the behavior of desert ants in finding their return path to the nest is the source of inspiration. By modeling the swarm intelligence of these ants based on the results of empirical scientific research, a new optimization algorithm is presented, termed Ant Path Integration. In this paper, the mathematical relationships governing the concept of path integration are presented. Simulation results on a variety of benchmark functions, including some of the CEC2019 benchmarks, show the superiority of this algorithm in finding the optimal solution in comparison to some well-known optimization algorithms. [ABSTRACT FROM AUTHOR]

Copyright of EMPIRIA: Revista de Metodología de Ciencias Sociales is the property of Editorial UNED 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.)

Remote sensing images can provide direct and accurate feedback on urban surface morphology and geographic conditions. They can be used as an auxiliary means to collect data for current geospatial information systems, which are also widely used in city public safety. Therefore, it is necessary to research remote sensing images. Therefore, we adopt the multi-threshold image segmentation method in this paper to segment the remote sensing images for research. We first introduce salp foraging behavior into the continuous ant colony optimization algorithm (ACOR) and construct a novel ACOR version based on salp foraging (SSACO). The original algorithm's convergence and ability to avoid hitting local optima are enhanced by salp foraging behavior. In order to illustrate this key benefit, SSACO is first tested against 14 fundamental algorithms using 30 benchmark test functions in IEEE CEC2017. Then, SSACO is compared with 14 other algorithms. The experimental results are examined from various angles, and the findings convincingly demonstrate the main power of SSACO. We performed segmentation comparison studies based on 12 remote sensing images between SSACO segmentation techniques and several peer segmentation approaches to demonstrate the benefits of SSACO in remote sensing image segmentation. Peak signal-to-noise ratio, structural similarity index, and feature similarity index evaluation of the segmentation results demonstrated the benefits of the SSACO-based segmentation approach. SSACO is an excellent optimizer since it seeks to serve as a guide and a point of reference for using remote sensing image algorithms in urban public safety. [ABSTRACT FROM AUTHOR]

Simple Summary: Ants fulfill an important ecological function, not only serving as one of the main decomposers but also playing a role in improving soil fertility. Ants may conflict with humans as a pest species in homes and living facilities (e.g., closets, wardrobes, cabinets, and tables), as well as in outdoor facilities (e.g., tables, chairs, and benches). In addition, ants and humans can come into conflict in green spaces (including parks, gardens, and tourist attractions) and can seriously interfere with outdoor leisure and the life and entertainment activities of people (especially children). Therefore, it is a matter of public health and environmental protection to ensure ant prevention by adopting green control technology and not merely by spraying pesticides to kill them. This review mainly focuses on the species and diversity of ants, especially in China, and the research progress of ant tropism regarding phototaxis, chromotaxis, and chemotaxis (i.e., 3-tropisms). Moreover, current research on repellent substances is also summarized, analyzed, and discussed in order to help the application of green prevention and control technology for ant diversity protection and conservation, especially in daily home life and entertainment activities. This field of research is related to ensuring the healthy life of the public and the protection of the ecological environment. Ants are one of the largest insect groups, with the most species and individuals in the world, and they have an important ecological function. Ants are not only an important part of the food chains but are also one of the main decomposers on the Earth; they can also improve soil fertility, etc. However, some species of ants are harmful to human beings, which leads to people's panic or worry about coming into contact with these insects during their daily home life or in their tourism or leisure activities. The presence of ants in indoor living facilities and in outdoor green spaces, parks, gardens, and tourist attractions seriously interferes with the leisure life and entertainment activities of all people (especially children). How can we control ants in these environments? Do we kill them by spraying insecticides, or do we adopt green prevention and control technology for the ecological management of ants? This topic is related to healthy life for the public and the protection of the ecological environment. In this paper, the species and diversity of ants are introduced, and research progress regarding ant tropism is introduced according to the three aspects of phototaxis, chromotaxis, and chemotaxis (i.e., "3-tropisms"). The research on repellent substances from plants and insects and the related ant attractants are also summarized, analyzed, and discussed, in order to help the research and application of green prevention and control technology for ant diversity protection and conservation. [ABSTRACT FROM AUTHOR]

Ant rescue behaviour belongs to the most interesting subcategories of prosocial and altruistic behaviour encountered in the animal world. Several studies suggested that ants are able to identify what exactly restrains the movements of another individual and to direct their rescue behaviour precisely to that object. To shed more light on the question of how precise the identification of the source of restraint of another ant is, we investigated rescue behaviour of red wood ant Formica polyctena workers, using a new version of an artificial snare bioassay in which a nestmate victim bore two wire loops on its body, one (acting as a snare) placed on its petiole and an additional one on its leg. The tested ants did not preferentially direct their rescue behaviour towards the snare. Moreover, the overall strategy adopted by the most active rescuers was not limited to precisely targeted rescue attempts directed towards the snare, but consisted of frequent switching between various subcategories of rescue behaviour. These findings highlight the importance of precise identification of cognitive processes and overall behavioural strategies for better understanding of causal factors underlying animal helping behaviour in light of new facts discovered by testing of various successive research hypotheses. [ABSTRACT FROM AUTHOR]

Simple Summary: Soldiers and workers collectively perform defensive behaviors in termite colonies. To determine the molecular mechanism driving the defensive behaviors of termite soldiers, we tested the effect of the juvenile hormone analogue pyriproxyfen (JHA) and the soldier caste-specific protein 1 (RaSsp1) on the defensive behaviors of Reticulitermes aculabialis soldiers when encountering an ant invasion. The results showed that JHA-feeding may affect defensive behaviors (i.e., bites and head-banging) of soldiers via downregulation of RaSsp1 expression. Feeding JHA may also affect the content of alarm pheromones in soldiers, including limonene, which also influenced the defensive behavior of soldiers. These results suggest that JH and RaSsp1 may play important roles in modulating social defense in termite colonies. Eusocial insects have evolved specific defensive strategies to protect their colonies. In termite colonies, soldiers perform a colony-level defense by displaying mechanical biting, head-banging and mandible opening–closing behaviors. However, few studies have been reported on the factors modulating defensive behaviors in termites. Owing to JH (juvenile hormone) being involved in soldier differentiation, JH was speculated to affect defensive behaviors in termite soldiers. To determine the effect of JH on the defensive behaviors of termite soldiers, we performed a JHA-feeding and RaSsp1-silencing experiment and then tested the changes in defense-related behaviors, alarm pheromones and key JH signaling genes. The observed result was that after feeding workers with JHA, soldiers displayed the following: (1) decreased biting events and increased head-banging events; (2) a reduced expression of RaSsp1 and increased expression of Met (methoprene-tolerant, the nuclear receptor of JH) and Kr-h1 (the JH-inducible transcription factor Krüppel homolog 1); and (3) a decreased concentration of alarm pheromones, including α-pinene, β-pinene and limonene (+, −). Further study showed that soldiers silenced for RaSsp1 also exhibited (1) decreased biting events and increased head-banging events and (2) increased expression of Met and Kr-h1. In addition, soldiers stimulated by the alarm pheromone limonene displayed an increase in the frequency of mandible opening–closing and biting behavior. All of these results show that JHA influenced the defensive behaviors of termite soldiers, possibly via downregulating RaSsp1 expression, up-regulating Met and Kr-h1 and stimulating the secretion of alarm pheromones, suggesting that the JH pathway plays important roles in modulating social behaviors in termite colonies. [ABSTRACT FROM AUTHOR]

This paper is concerned with the attracting set of an ant colonies model with bounded noisy perturbation. This perturbation is modeled by the well-known Ornstein–Uhlenbeck process and the arc tangent function. For the random model, we first verify the existence and uniqueness of the global positive solution, and then prove the existence of the deterministic attracting set. Furthermore, in order to reveal more detailed information about the long-time behavior of the ant colonies system, we analyze the internal structure of the attracting set and provide some conditions under which coexistence (or extinction) of the ant species exists in the ant colonies system. [ABSTRACT FROM AUTHOR]

The paper considers the modification and application of the ant colony method for the problem of directed enumeration of the values of system parameters when performing calculated multiple calculations. Interaction with the user makes it possible to stop the process of exhaustive enumeration of sets of parameter values, and the application of a modification of the ant colony method will allow us to consider rational sets at early iterations. If the user does not terminate the algorithm, then the proposed modifications allow one to enumerate all solutions using the ant colony method. To modify the ant colony method, a new probabilistic formula and various algorithms of the ant colony method are proposed, allowing for each agent to find a new set of parameter values. The optimal algorithm, according to the research results, is the use of repeated endless cyclic search for a new solution. This modification allows you to consider all solutions, and at the same time, find all the optimal solutions among the first 5% of the considered solutions. [ABSTRACT FROM AUTHOR]

The geogr aphy of paper is par t icul ar l y wel l capt ur ed in a chapt er on Al br echt Dür er (1471-1528), in which Fowl er discusses Dür er 's pr efer ence for bl ue paper dur ing his visit t o Venice and in his commissions for t he Venet o r egion (1505-07). Fr om t heir int r oduct ion in t he fift eent h cent ur y, pr int ing pr esses wer e t he cheapest, most effect ive way of pr oducing a l ar ge number of copies of t he same document and wer e onl y oust ed - in t er ms of simpl icit y and cost - by t he invent ion of cycl ost yl e st encil dupl icat or s in t he 1880s. In t he absence of copyr ight, it was al most impossibl e t o make a l iving as a wr it er, since pr ofit s accr ued most l y t o t he publ isher s, who al l t oo fr equent l y suffer ed fr om pir at e r epr int s, whil e t he best r ewar d an aut hor coul d hope for was a gener ous pr esent fr om a dedicat ee. Al beit bur densome, al so due t o t he accompanying par apher nal ia of l ead t ype, which was never l ight nor easy t o shift, t heir ut il it y meant t hat pr esses wer e oft en on t he move, which for ms t he subject of t he pr esent book (t he al t er nat ive, mor e evocat ive, t it l e - La stampa è mobile - unfor t unat el y had al r eady been t aken (p. 31)). [Extracted from the article]

This study addresses the challenges in large-scale unmanned aerial vehicle (UAV) clusters, specifically the scalability issues and limitations of using reactive routing protocols for inter-cluster routing. These traditional methods place an excessive burden on cluster heads and struggle to adapt to frequently changing topologies, leading to decreased network performance. To solve these problems, we propose an innovative inter-cluster routing protocol (ICRP), which is based on a hybrid ant colony algorithm. During the route establishment phase, ICRP uses this algorithm to identify the optimal relay node. This approach is inspired by the foraging behavior of Physarum polycephalum, combining factors such as the number of hops from the source node, the load condition of the node, and its weight in the pheromone calculation. In the route maintenance phase, ICRP uses a predictive repair and contraction mechanism to dynamically maintain routes, accommodating the high mobility of UAVs. Comparative simulations in OMNeT + + showed that this protocol surpasses ad-hoc on-demand distance vector (AODV), fuzzy-logic-assisted-AODV, and Enhanced-Ant-AODV routing protocols in packet delivery rate and end-to-end transmission delay. Furthermore, it showed superior adaptation to network environments with high-speed node mobility. [ABSTRACT FROM AUTHOR]

This essay examines a little-known but important installation entitled Insure the Life of an Ant, conceived by artist Mike Malloy and displayed at the O.K. Harris Gallery in New York in April of 1972. This provocative and idiosyncratic piece confronted gallery-goers, who became viewer–participants, with the option of killing or saving a live ant displayed like a sculpture on a pedestal, either by pushing a button or not. The artist made the piece, which can function almost like a psychology experiment, to engender a "moral dilemma". I explore the particular role of affect in a participatory art installation, distinct from response to inanimate art. I investigate the roles of emotion and reason in dealing with the work; whether ratiocination can be considered an "anti-affect"; and how the tension between competing thoughts and feelings helped create a psychological drama. The essay looks at how an art space can operate as a zone of moral exceptionalism to encourage questionable actions. It also locates the piece in relation to the emergence of a more behaviorist art in the early 1970s, as discussed by critic Gregory Battcock, and the larger notion of postmodernism. Other contexts investigated include art and animal rights and issues of sentience and speciesism; social and military violence, including capital punishment and the Vietnam War; the 1961 Milgram experiment; Hannah Arendt's concept of the "banality of evil" as a Nazi war criminal defense; and other works of art involving maltreatment or violence toward both human and non-human animals, including those by Marina Abramović, Marco Evaristti, and Edward and Nancy Reddin Kienholz. [ABSTRACT FROM AUTHOR]

The Asian weaver ant, Oecophylla smaragdina, indeed exhibits fascinating social behavior and a unique nesting strategy. The nesting behavior of weaver ants involves a "leaf-weaving," process where the worker ants use the silk produced by their larvae to bind leaves together, creating a complex and sturdy nest structure. Regarding their life stages and metabolic changes, Oecophylla smaragdina as a holometabolous species undergoes complete metamorphosis, involving distinct developmental stages such as egg, larva, pupa, and adult. Each stage is characterized by significant changes in the insect's physiology and appearance. It is essential to study the metabolic changes in these ants during their life stages to better understand their development, behavior, and adaptability to their environment. The main objective of the present study is a biochemical analysis of the life stages of the weaver ant. During this study, various ants were collected at various stages and analyzed for the estimation of protein, carbohydrate, RNA, and DNA. According to the findings, the concentration of proteins was observed to be highest during all life stages of weaver ants. Following proteins, the concentration of RNA was noted to be the highest, then the concentration of DNA and carbohydrates. It was also noted that the concentration of biomolecules increased from the egg stage to the pupal stage, reaching its maximum level at the pupal stage. However, after reaching the maximum level at the pupal stage, the concentration of biomolecules declines as the ant progresses from the white imago to the adult stage. [ABSTRACT FROM AUTHOR]

Copyright of People & Nature is the property of Wiley-Blackwell 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.)

With the rapid development of network technology, online recruitment and job hunting have become an important way of job hunting at present, but job seekers spend a lot of time looking for suitable positions in the face of massive job information. Traditional artificial selection of job information is difficult to solve the problem of job seekers finding suitable positions quickly and accurately. This article is based on ant colony algorithm for visual analysis and personalized recommendation of job information. Through visual analysis of massive job information on the network, personalized recommendations are made based on job seekers' professional, skill, behavior, and other information. A visual analysis and personalized recommendation system for job information is established, and recommendation accuracy, efficiency, and recall rate are evaluated and analyzed using recommendation theory, realize comprehensive evaluation of information visualization analysis and personalized recommendation quality of position information based on ant colony algorithm. Compared with artificial selection of position information, it is fast and highly matched. [ABSTRACT FROM AUTHOR]

Deep learning (DL) based detection models are powerful tools for large-scale analysis of dynamic biological behaviors in video data. Supervised training of a DL detection model often requires a large amount of manually-labeled training data which are time-consuming and labor-intensive to acquire. In this paper, we propose LFAGPA (Learn From Algorithm-Generated Pseudo-Annotations) that utilizes (noisy) annotations which are automatically generated by algorithms to train DL models for ant detection in videos. Our method consists of two main steps: (1) generate foreground objects using a (set of) state-of-the-art foreground extraction algorithm(s); (2) treat the results from step (1) as pseudo-annotations and use them to train deep neural networks for ant detection. We tackle several challenges on how to make use of automatically generated noisy annotations, how to learn from multiple annotation resources, and how to combine algorithm-generated annotations with human-labeled annotations (when available) for this learning framework. In experiments, we evaluate our method using 82 videos (totally 20,348 image frames) captured under natural conditions in a tropical rain-forest for dynamic ant behavior study. Without any manual annotation cost but only algorithm-generated annotations, our method can achieve a decent detection performance (77% in F 1 score). Moreover, when using only 10% manual annotations, our method can train a DL model to perform as well as using the full human annotations (81% in F 1 score). [ABSTRACT FROM AUTHOR]

In order to improve the efficiency and adaptability of cognitive radar jamming decision-making, a fusion algorithm (Ant-QL) based on ant colony and Q-Learning is proposed in this paper. The algorithm does not rely on a priori information and enhances adaptability through real-time interactions between the jammer and the target radar. At the same time, it can be applied to single jammer and multiple jammer countermeasure scenarios with high jamming effects. First, traditional Q-Learning and DQN algorithms are discussed, and a radar jamming decision-making model is built for the simulation verification of each algorithm. Then, an improved Q-Learning algorithm is proposed to address the shortcomings of both algorithms. By introducing the pheromone mechanism of ant colony algorithms in Q-Learning and using the ε -greedy algorithm to balance the contradictory relationship between exploration and exploitation, the algorithm greatly avoids falling into a local optimum, thus accelerating the convergence speed of the algorithm with good stability and robustness in the convergence process. In order to better adapt to the cluster countermeasure environment in future battlefields, the algorithm and model are extended to cluster cooperative jamming decision-making. We map each jammer in the cluster to an intelligent ant searching for the optimal path, and multiple jammers interact with each other to obtain information. During the process of confrontation, the method greatly improves the convergence speed and stability and reduces the need for hardware and power resources of the jammer. Assuming that the number of jammers is three, the experimental simulation results of the convergence speed of the Ant-QL algorithm improve by 85.4%, 80.56% and 72% compared with the Q-Learning, DQN and improved Q-Learning algorithms, respectively. During the convergence process, the Ant-QL algorithm is very stable and efficient, and the algorithm complexity is low. After the algorithms converge, the average response times of the four algorithms are 6.99 × 10−4 s, 2.234 × 10−3 s, 2.21 × 10−4 s and 1.7 × 10−4 s, respectively. The results show that the improved Q-Learning algorithm and Ant-QL algorithm also have more advantages in terms of average response time after convergence. [ABSTRACT FROM AUTHOR]

Simple Summary: Adhesive tapes are as effective as baits and pitfall traps in monitoring Solenopsis invicta and Tapinoma melanocephalum in urban areas in southern China. However, adhesive tapes detected less ants and fewer species of non-target ants than baits and pitfall traps. Our study demonstrated that tape-paving behavior can potentially be used in developing more specific monitoring methods for S. invicta and T. melanocephalum in urban areas in southern China. Our previous study discovered that two urban pest ants, red imported fire ants, Solenopsis invicta Buren (Formicidae: Myrmicinae), and ghost ants, Tapinoma melanocephalum (Fabricius) (Formicidae: Dolichoderinae), can pave viscose surfaces with particles to facilitate food search and transport. We hypothesize that this paving behavior can be applied to monitor S. invicta and T. melanocephalum. In the present study, 3998 adhesive tapes, each with a food source (sausage), were placed in 20 locations around Guangzhou, China (181–224 tapes per location), and their efficiency to detect S. invicta and T. melanocephalum was compared with two traditional ant-monitoring methods, baiting and pitfall trapping. Overall, S. invicta was detected by 45.6% and 46.4% of baits and adhesive tapes, respectively. In each location, the percentage of adhesive tapes detecting S. invicta and T. melanocephalum was similar when compared to baits and pitfall traps. However, significantly more non-target ant species showed up on bait and pitfall traps. Seven non-target ant species—Pheidole parva Mayr (Formicidae: Myrmicinae), Pheidole nodus Smith (Formicidae: Myrmicinae), Pheidole sinica Wu & Wang (Formicidae: Myrmicinae), Pheidole yeensis Forel (Formicidae: Myrmicinae), Carebara affinis (Jerdon) (Formicidae: Myrmicinae), Camponotus nicobarensis Mayr (Formicidae: Formicinae), and Odontoponera transversa (Smith) (Formicidae: Ponerinae)—also showed tape paving behavior, but they can be easily distinguished morphologically from S. invicta and T. melanocephalum. Our study showed that the paving behavior occurs in different subfamilies of ants (i.e., myrmicinae, dolichoderinae, formicinae, and ponerinae). In addition, paving behavior can potentially be used to develop more specific monitoring methods for S. invicta and T. melanocephalum in urban areas in southern China. [ABSTRACT FROM AUTHOR]

High current amounts, low voltage level and radial structure assign high percentage of active power loss in distribution system. There are many means in reducing the active power loss of distribution networks; this paper introduces an ant colony algorithm to solve the optimal network reconfiguration and capacitor placement problem for power loss reduction and voltage profile enhancement in distribution networks. The ant colony algorithm was inspired from natural behavior of the ant colonies on how they find the food source and bring them back to their nest by building the unique trial formation. Ants of artificial colony are able to search for the successively shorter feasible routes by using information accumulated in the form of a pheromone trial deposited on the edge of their traveling path. The proposed approach is demonstrated employing one distribution network. Computational results show that by taking into account feeder reconfiguration and capacitor placement simultaneously, one can be minimize losses more efficiently by considering them separately. [ABSTRACT FROM AUTHOR]

Artificial intelligence has recently been used in FANET-based routing strategies for decision-making, which is a unique paradigm. For effective communication in flying vehicles that use routing protocols to accomplish tasks collectively, aerial vehicles are used in both civic and military applications. Aerial ad hoc networks are wirelessly connected, and designing routing schemes is difficult due to the rapid mobility. Ground base stations and satellites are frequently used to interconnect UAV ad hoc networks. This paper developed a novel routing protocol with a focus on ant behavior routing, which assists in end-to-end security. For the first time in flying networks, the column mobility model is used to evaluate the performance of routing protocols. While merging with aerial ad hoc networks, AI-based networking is a relatively new field. In simulation results, AntHocNet shows better results in comparison with other contemporary routing algorithms. Pheromone update process is used for data encryption in AntHocNet. This research study is performed on network simulator-2. [ABSTRACT FROM AUTHOR]

Simple Summary: Florida carpenter ants (Camponotus floridanus) live in colonies comprised of thousands of workers. The smallest workers, known as minors, engage in routine tasks such as nursing and foraging while the largest workers, known as majors, are thought to be soldiers specialized for defending the nest. How ant colonies allocate their workforce to address the dynamic and ever-changing needs of the colonies remains an open question in the field, but current evidence suggests that ant social behavior likely results from a combination of genetic/epigenetic, physiological, and systems-level processes. Here, we extend these studies by investigating the role of olfactory sensitivity in regulating ant behavior. Minor workers exhibited significant shifts in olfactory sensitivity and odor coding as they aged and switched tasks. The olfactory sensitivity of majors, however, remained relatively stable as they aged. From these studies, we also identified a single compound, 3-methylindole, which elicited significantly higher olfactory responses and aversive behavior in nurses compared to foragers, suggesting that this chemical may have a role in brood care. Overall, these studies support the hypothesis that changes in olfactory sensitivity play an important role in regulating social behavior in ants. Age-related changes in behavior and sensory perception have been observed in a wide variety of animal species. In ants and other eusocial insects, workers often progress through an ordered sequence of olfactory-driven behavioral tasks. Notably, these behaviors are plastic, and workers adapt and rapidly switch tasks in response to changing environmental conditions. In the Florida carpenter ant, smaller minors typically perform most of the work needed to maintain the colony, while the larger majors are specialized for nest defense and rarely engage in these routine tasks. Here, we investigate the effects of age and task group on olfactory responses to a series of odorant blends in minor and major worker castes. Consistent with their respective roles within the colony, we observed significant age-associated shifts in the olfactory responses of minors as they transitioned between behavioral states, whereas the responses of majors remained consistently low regardless of age. Furthermore, we have identified a unitary compound, 3-methylindole, which elicited significantly higher responses and behavioral aversion in minor nurses than in similarly aged foragers suggesting that this compound may play an important role in brood care. Taken together, our results suggest that age- and task-associated shifts in olfactory physiology may play a critical role in the social organization of ant colonies. [ABSTRACT FROM AUTHOR]

Just like an army of ants caught in an ant mill, individuals, groups and even whole societies are sometimes caught up in a Death Spiral, a vicious cycle of self-reinforcing dysfunctional behavior characterized by continuous flawed decision making, myopic single-minded focus on one (set of) solution(s), denial, distrust, micromanagement, dogmatic thinking and learned helplessness. We propose the term Death Spiral Effect to describe this difficult-to-break downward spiral of societal decline. Specifically, in the current theory-building review we aim to: (a) more clearly define and describe the Death Spiral Effect; (b) model the downward spiral of societal decline as well as an upward spiral; (c) describe how and why individuals, groups and even society at large might be caught up in a Death Spiral; and (d) offer a positive way forward in terms of evidence-based solutions to escape the Death Spiral Effect. Management theory hints on the occurrence of this phenomenon and offers turn-around leadership as solution. On a societal level strengthening of democracy may be important. Prior research indicates that historically, two key factors trigger this type of societal decline: rising inequalities creating an upper layer of elites and a lower layer of masses; and dwindling (access to) resources. Historical key markers of societal decline are a steep increase in inequalities, government overreach, over-integration (interdependencies in networks) and a rapidly decreasing trust in institutions and resulting collapse of legitimacy. Important issues that we aim to shed light on are the behavioral underpinnings of decline, as well as the question if and how societal decline can be reversed. We explore the extension of these theories from the company/organization level to the society level, and make use of insights from both micro-, meso-, and macro-level theories (e.g., Complex Adaptive Systems and collapsology, the study of the risks of collapse of industrial civilization) to explain this process of societal demise. Our review furthermore draws on theories such as Social Safety Theory, Conservation of Resources Theory, and management theories that describe the decline and fall of groups, companies and societies, as well as offer ways to reverse this trend. [ABSTRACT FROM AUTHOR]

Collectively searching animals might be expected to coordinate with their groupmates to cover ground more evenly or efficiently than uncoordinated groups. Communication can lead to coordination in many ways. Previous work in ants suggests that chemical 'footprints', left behind by individuals as they walk, might serve this function by modulating the movement patterns of following ants. Here, we test this hypothesis by considering the two predictions that, first, ants may turn away from sites with higher footprint concentrations (klinotaxis), or, second, that they may change their turning patterns depending on the presence of footprints (klinokinesis). We tracked 5 whole colonies of Temnothorax rugatulus ants in a large arena over 5h. We approximated the footprint concentration by summing ant visitations for each point in the arena and calculated the speed and local path straightness for each point of the ant trajectories. We counterintuitively find that ants walk slightly faster and straighter in areas with fewer footprints. This is partially explained by the effect that ants who start out from the nest walking straighter move on average further away from the nest, where there are naturally fewer footprints, leading to an apparent relationship between footprint density and straightness However, ants walk slightly faster and straighter off footprints even when controlling for this effect. We tested for klinotaxis by calculating the footprint concentrations perceived by the left and right antennae of ants and found no evidence for a turning-away (nor turning-towards) behavior. Instead, we found noticeable effects of environmental idiosyncrasies on the behavior of ants which are likely to overpower any reactions to pheromones. Our results indicate that search density around an ant colony is affected by several independent processes, including individual differences in movement pattern, local spatial heterogeneities, and ants' reactions to chemical footprints. The multitude of effects illustrates that non-communicative coordination, individual biases and interactions with the environment might have a greater impact on group search efficiency and exploratory movements than pheromone communication. [ABSTRACT FROM AUTHOR]

In order to solve the problem of the low pickup efficiency of the robotic arm when harvesting safflower filaments, we established a pickup trajectory cycle and an improved velocity profile model for the harvest of safflower filaments according to the growth characteristics of safflower. Bezier curves were utilized to optimize the picking trajectory, mitigating the abrupt changes produced by the delta mechanism during operation. Furthermore, to overcome the slow convergence speed and the tendency of the ant colony algorithm to fall into local optima, a safflower harvesting trajectory planning method based on an ant colony genetic algorithm is proposed. This method includes enhancements through an adaptive adjustment mechanism, pheromone limitation, and the integration of optimized parameters from genetic algorithms. An optimization model with working time as the objective function was established in the MATLAB environment, and simulation experiments were conducted to optimize the trajectory using the designed ant colony genetic algorithm. The simulation results show that, compared to the basic ant colony algorithm, the path length with the ant colony genetic algorithm is reduced by 1.33% to 7.85%, and its convergence stability significantly surpasses that of the basic ant colony algorithm. Field tests demonstrate that, while maintaining an S-curve velocity, the ant colony genetic algorithm reduces the harvesting time by 28.25% to 35.18% compared to random harvesting and by 6.34% to 6.81% compared to the basic ant colony algorithm, significantly enhancing the picking efficiency of the safflower-harvesting robotic arm. [ABSTRACT FROM AUTHOR]

In ant-aphid interactions, various aphid species offer honeydew to the ant partner and increase their density by ant attendance, whilst others never attend ant species, in which case ants tend to treat them as prey. In this regard, ants should have the ability to distinguish myrmecophile aphid species from non-mutualistic species, so that mutualistic aphids will be accepted as partners rather than prey. Although ant-aphid interactions are now the focus of chemical ecology studies, the role of the different chemical stimuli in determining mutualistic interactions has not been completely clarified. Therefore, we have investigated the cuticular hydrocarbon profile of four myrmecophiles aphid species using GC-MS. We also investigated the behavior of the worker-ants (Lasius niger L., Hymenoptera: Formicidae) to different chemical stimuli derived from aphids. We applied four treatments and found that the behavior of the ant workers varied depending on the source of the different treatments. In particular, the real aphid Aphis pomi and the sugar solution proved to be the most attractive to the ants, while the presence of pure extract of the individuals is enough to disturb the behavior of the ants. We provide evidence that the key stimuli of the tending behavior could be the CHC patterns of the aphids and the CHC profile of the aphids tends to be genus specific. This research will promote further investigations to test the behavior of ant workers towards other species of aphids and treatment combinations. [ABSTRACT FROM AUTHOR]

Just like an army of ants caught in an ant mill, individuals, groups and even whole societies are sometimes caught up in a Death Spiral, a vicious cycle of self-reinforcing dysfunctional behavior characterized by continuous flawed decision making, myopic single-minded focus on one (set of) solution(s), denial, distrust, micromanagement, dogmatic thinking and learned helplessness. We propose the term Death Spiral Effect to describe this difficult-to-break downward spiral of societal decline. Specifically, in the current theory-building review we aim to: (a) more clearly define and describe the Death Spiral Effect; (b) model the downward spiral of societal decline as well as an upward spiral; (c) describe how and why individuals, groups and even society at large might be caught up in a Death Spiral; and (d) offer a positive way forward in terms of evidence-based solutions to escape the Death Spiral Effect. Management theory hints on the occurrence of this phenomenon and offers turn-around leadership as solution. On a societal level strengthening of democracy may be important. Prior research indicates that historically, two key factors trigger this type of societal decline: rising inequalities creating an upper layer of elites and a lower layer of masses; and dwindling (access to) resources. Historical key markers of societal decline are a steep increase in inequalities, government overreach, over-integration (interdependencies in networks) and a rapidly decreasing trust in institutions and resulting collapse of legitimacy. Important issues that we aim to shed light on are the behavioral underpinnings of decline, as well as the question if and how societal decline can be reversed. We explore the extension of these theories from the company/organization level to the society level, and make use of insights from both micro-, meso-, and macro-level theories (e.g., Complex Adaptive Systems and collapsology, the study of the risks of collapse of industrial civilization) to explain this process of societal demise. Our review furthermore draws on theories such as Social Safety Theory, Conservation of Resources Theory, and management theories that describe the decline and fall of groups, companies and societies, as well as offer ways to reverse this trend. [ABSTRACT FROM AUTHOR]

Since Tinbergen’s seminal contribution in 1963, ethology has blossomed as a multifaceted research field. Sixty years later, uncountable articles followed the four questions proposed as necessary for understanding animal behaviour, and they culminated in the segmentation of subareas which communicate little among themselves. Foraging in ants is one example where this division happened, despite the clear need to integrate results obtained from different approaches. We chose this research subject to revise the literature, relating the main results to the relevant level of explanation in Tinbergen’s four questions theoretical framework. Through such revision, we aim to foster the integration of different approaches and to bring to light how this can clarify how we understand foraging behaviour, sixty years after Tinbergen’s initial proposition. [ABSTRACT FROM AUTHOR]

Ant colony optimization (ACO) is a stochastic optimization algorithm inspired by the foraging behavior of ants. We investigate a simplified computational model of ACO, wherein ants sequentially engage in binary decision-making tasks, leaving pheromone trails contingent upon their choices. The quantity of pheromone left is the number of correct answers. We scrutinize the impact of a salient parameter in the ACO algorithm, specifically, the exponent α , which governs the pheromone levels in the stochastic choice function. In the absence of pheromone evaporation, the system is accurately modeled as a multivariate nonlinear Pólya urn, undergoing phase transition as α varies. The probability of selecting the correct answer for each question asymptotically approaches the stable fixed point of the nonlinear Pólya urn. The system exhibits dual stable fixed points for α ≥ α c and a singular stable fixed point for α < α c where α c is the critical value. When pheromone evaporates over a time scale τ , the phase transition does not occur and leads to a bimodal stationary distribution of probabilities for α ≥ α c and a monomodal distribution for α < α c . [ABSTRACT FROM AUTHOR]

Sol g 2 is the major protein in Solenopsis geminata fire ant venom. It shares the highest sequence identity with Sol i 2 (S. invicta) and shares high structural homology with LmaPBP (pheromone-binding protein (PBP) from the cockroach Leucophaea maderae). We examined the specific Sol g 2 protein ligands from fire ant venom. The results revealed that the protein naturally formed complexes with hydrocarbons, including decane, undecane, dodecane, and tridecane, in aqueous venom solutions. Decane showed the highest affinity binding (Kd) with the recombinant Sol g 2.1 protein (rSol g 2.1). Surprisingly, the mixture of alkanes exhibited a higher binding affinity with the rSol g 2.1 protein compared to a single one, which is related to molecular docking simulations, revealing allosteric binding sites in the Sol g 2.1 protein model. In the trail-following bioassay, we observed that a mixture of the protein sol g 2.1 and hydrocarbons elicited S. geminata worker ants to follow trails for a longer time and distance compared to a mixture containing only hydrocarbons. This suggests that Sol g 2.1 protein may delay the evaporation of the hydrocarbons. Interestingly, the piperidine alkaloids extracted have the highest attraction to the ants. Therefore, the mixture of hydrocarbons and piperidines had a synergistic effect on the trail-following of ants when both were added to the protein. [ABSTRACT FROM AUTHOR]

In the present study, we tested associative olfactory learning performance of the ant Formica clara in laboratory conditions based on their MaLER responses. Ants were harnessed with the help of a paper-made holder and conditioned in two groups by forward pairing either limonene or eugenol (conditioned stimuli – CS) with a reward (unconditioned stimulus – US). After conditioning, memory tests were performed for each CS 15, 60 and 90 minutes following the conditioning in the absence of US. A further test was performed for each group with the CS of the other group to see if the ants showed an odor generalization. The frequencies of MaLER-positive responses during tests were used as indication of learning performance. Ants learned the association between the CS and US during conditioning for both odors and showed initially significant and gradually decreasing MaLER-positive responses during tests. The results showed that conditioning to the odors was absolute and no generalization was observed. We conclude that associative learning is a universal strategy for ants to adjust their behaviors to environmental changes around them and the MaLER technique is a powerful and easy to apply technique to test learning and memory capacities in ants. [ABSTRACT FROM AUTHOR]

The discovery of the eusocial behavior of ants and bees in the 1960s fundamentally rewrote the decades of entomological research, biology, and ultimately human self-understanding. Understanding that these insect species organize themselves into social constellations similar to ours suggests that the sociability of homo sapiens sapiens will also be seen in a different light. But what made the insect world suitable for becoming a specific form of human self-understanding between the second half of the 19th century and the first third of the 20th century? My paper is limited to just a few situations when, in the course of my own literary studies, the early intersections of the insect world and human self-understanding flashed before me, drawing the possible contours of a pattern. [ABSTRACT FROM AUTHOR]

This paper proposes the use of Complex Network Theory to model the interactions between ants and analyze their social behavior. Specifically, the study focuses on six colonies of ants to investigate whether their behavior is community-oriented or individual-oriented. The research employs various nodes properties that define nodes' importance to quantify the existence of a social or individual-oriented behavior. The results aim to provide insights into the social behavior of ants and may have implications for understanding other complex social systems. [ABSTRACT FROM AUTHOR]

The optimal evacuation route in emergency evacuation can further reduce casualties. Therefore, path planning is of great significance to emergency evacuation. Aiming at the blindness and relatively slow convergence speed of ant colony algorithm path planning search, an improved ant colony algorithm is proposed by combining artificial potential field and quantum evolution theory. On the one hand, the evacuation environment of pedestrians is modeled by the grid method. Use the potential field force in the artificial potential field, the influence coefficient of the potential field force heuristic information, and the distance between the person and the target position in the ant colony algorithm to construct comprehensive heuristic information. On the other hand, the introduction of quantum evolutionary theory. The pheromone is represented by quantum bits, and the pheromone is updated by quantum revolving door feedback control. In this way, it can not only reflect the high efficiency of quantum parallel computing, but also have the better optimization ability of ant colony algorithm. A large number of simulation experiments show that the improved ant colony algorithm has a faster convergence rate and is more effective in evacuation path planning. [ABSTRACT FROM AUTHOR]

In this paper, we present a way to create an accurate trimap. Since the matting problem is a serious under-constrained problem, the user is required to provide additional constraint information to estimate the alpha value of the mixed pixels. The smaller the area of the unknown region of the user-provided trimap, the more accurate the alpha value of the estimated mixed pixels. But manually creating the trimap is a complicated and time-consuming task, and it is even impractical to manually create trimaps for some tasks. We use the ant colony algorithm to determine the boundary information of the foreground objects, and fuse different pheromone images at the superpixel level to create an accurate trimap. The trimap generated by our method also has higher precision when the edge of the foreground object has a lot of fine hair. Experiments show that the high-quality trimap can be generated by the method of this paper, which can effectively improve the performance of the matting algorithm and achieve accurate alpha mask estimation. [ABSTRACT FROM AUTHOR]

Ant workers are often specialized in specific tasks, and it is well‐established that the main task an ant performs in the colony can be used to predict its sensitivity and responses to task‐associated stimuli. An often‐overlooked aspect of ants' task specialization is that individuals often switch tasks throughout the day and are not always engaged in functional tasks. Furthermore, the tasks individuals engage in are often correlated with other context‐specific factors, such as worker density, which can independently influence individuals' behaviour. Given this intra‐individual variation in task engagement and its correlation with density, it is currently unknown how these two factors interact to modulate ants' sensitivity and responses to stimuli.To address this question, we built a robotic manipulation system that allowed us to teleoperate a dummy inside ant colonies and to provide simulated antennations to ants when performing different tasks in areas with different worker densities. We coupled this manipulation system with a custom‐built automated tracking system (FORT) that allowed us to track individual identities and locations as well as to record the ants' responses to the dummy stimulation.We found independent effects of task and worker density on ants' responsiveness and alarm towards the dummy. Ants were less likely to respond and be alarmed by the dummy when stimulated in areas with high worker density. Responsiveness but not alarm was further influenced by the task being performed, with ants doing broodcare being the least responsive. Our results suggest that ants' behaviour is density‐dependent and that ants experience a process of habituation to tactile stimulation. Additionally, ants' responsiveness is modulated by the task they are performing at a given time, showing that sensitivity to stimuli is context‐dependent.Our robotic set‐up constitutes a valuable tool to systematically investigate social insect behaviour under unprecedented experimental control to unravel the individual‐level behavioural rules that underpin the organization of social insect colonies. The integrated system presented here opens new research avenues to empirically investigate the effects of more complex stimuli on social insect behaviour and has the potential to significantly further our understanding of decentralized collective systems. [ABSTRACT FROM AUTHOR]

Simple Summary: Solenopsis invicta (Hymenoptera: Formicidae), also known as the red imported fire ant, is a social insect and a worldwide invasive pest. Biochar is a widely used soil amendment. In this work, we investigated the effects of varying soil biochar levels on irritability and contact toxicity as well as the behavioral and physiological changes in red fire ant behavior. High doses of biochar were toxic and repulsive to red fire ants, impairing their ability to walk, grasp, attack, and gather while also causing an increase in the activity of enzymes associated with oxidative stress. This study supports the prudent utilization of biochar as well as the prevention and management of red fire ants. Solenopsis invicta, often known as the red imported fire ants (RIFAs), is a well-known global invasive ant species that can be found in agricultural, urban, and natural environments worldwide. Simultaneously, it also inhabits the soil. Biochar is generated by the pyrolysis of organic matter under high-temperature anoxic environments and widely used in agricultural ecosystems and soil amendment. However, to date, it remains unknown as to whether soil application of biochar has a negative effect on RIFAs. In our study, we investigated the toxicity and irritability effects of different amounts of biochar (0%, 1%, 2%, 5%, 10%, and 20%) introduced into the soil on red fire ants; upon comparison with the control soil (0% biochar), the application of 1%, 2%, and 5% biochar did not result in significantly different results. But the utilization of biochar at a concentration over 10% effectively repelled the RIFAs, resulting in their departure from the treated soils. High doses of biochar were able to cause death of red fire ants; the mortality rate of red fire ants reached 55.56% after 11 days of 20% biochar treatment. We also evaluated the effects of biochar on four behaviors of red fire ants, namely aggregation, walking, grasping, and attacking; 20% of the biochar treatment group reduced aggregation by 64.22% and this value was 55.22%, 68.44%, and 62.36% for walking, grasping, and attacking. Finally, we measured the activities of superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT) enzyme activity and malondialdehyde (MDA) content in red fire ants; the results showed that the activities of the three enzymes increased with the increase in biochar addition, which indicated that a high dose of biochar induced oxidative stress in red fire ants. Our results indicate that biochar has the potential to cause toxicity and repel red imported fire ants (RIFAs) in a manner that is dependent on the concentration. We propose that biochar could be utilized in the control and manufacturing of baits for red fire ant management. This work establishes a foundation for the prevention and management of red fire ants and the logical utilization of biochar. [ABSTRACT FROM AUTHOR]

The common sand-dwelling Formica cinerea ants possess monomorphic workers, yet with considerable and easily identified size variation. Considering the importance of body size in polymorphic ants and other animals, we test whether size-dependent differences in behaviour occur in this species. We focus on the behaviour of large and small foragers in the context of rescue occurring between nestmates when one of them is entrapped and requires help. We show that workers of different sizes are characterized by a similar frequency of rescue activity and time delay to the first act of rescue. However, small workers rescue for longer than large workers. These results indicate that, although there is no size-related rescue specialization in F. cinerea foragers, small rescuers behave differently than large ones in terms of rescue persistence. Additionally, we show that small workers are more active when trapped. We suggest that variation in behavioural persistence of differently-sized workers may increase the efficiency of rescue actions. This study is the first to find a connection between body size and rescue behaviour in ants and the first to quantify and analyze the behaviour of individuals in need of rescue. These findings add substantially to our understanding of social insects and, more generally, highlight the need to study among-individual behavioural variation in social animals, including those in which body size is judged minute and irrelevant. [ABSTRACT FROM AUTHOR]

Ants store and recall views associated with foraging success, facilitating future foraging journeys. Negative views are also learned, but instead prompt avoidance behaviors such as turning away. However, little is known about the aversive view's role in navigation, the effect of cue conflict, or the contextual relationship between learning and recalling. In this study, we tested Myrmecia midas' capacity for aversive learning of views either independently of or in conflict with appetitive events. We either captured and released foragers when reaching a location or let them pass unhindered. After a few journeys, captured foragers exhibited aversive learning by circumventing the capture location and increasing both meandering and scanning. Ants that experienced foraging-appetitive and homing-aversive events on their journeys exhibited lower rates of avoidance behavior and scans than those experiencing aversive events in both outbound and homebound journeys. The foraging-aversive and homing-aversive ants exhibited similar levels of avoidance and scanning as those that experienced the foraging-aversive and homing-appetitive. We found that foragers showed evidence of context specificity in their scanning behavior, but not in other measures of aversive learning. The foragers did not increase their meandering and scans while approaching the views associated with aversive events. In addition to shedding light on the role of aversive views in navigation, our finding has important implications for understanding the learning mechanisms triggered by handling animals. [ABSTRACT FROM AUTHOR]

When foraging, internal needs for particular nutrients might affect food choice, and external constraints, such as predation risk, might impact trade-offs between foraging and risk avoidance. Examining both internal and external constraints simultaneously can provide important insights into how animals make decisions. We examined how internal nutritional needs and external cues of mortality risk jointly impact the foraging behavior of ants. Ant colonies require carbohydrates to support workers energetically and proteins to raise brood. Furthermore, colonies adjust their foraging activity in response to the environment, such as food availability and the presence of predators or heterospecifics. Here we examine the foraging decisions of groups of Argentine ants Linepithema humile , which differ in their nutritional needs in high-risk environments. We starved groups of ants for either proteins or carbohydrates and determined the foraging choices that ants made when cues of heterospecifics were present. We found that ants preferentially forage for carbohydrates in high-risk conditions. Furthermore, starvation for carbohydrates increased the ants' preference for carbohydrates, even when cues of heterospecifics were present at both carbohydrates and protein resources. Starvation for protein also resulted in preferential foraging for carbohydrates, but it increased visitation to a protein food source in high-risk environments compared to when ants were starved for carbohydrates or for both resources. Examining the effect of both nutrition and mortality risk on foraging simultaneously provides insights about state-dependent risk-taking behavior that may have important implications for predicting the invasion of species into novel habitats. [ABSTRACT FROM AUTHOR]

Hepatic encephalopathy (HE) implies high morbidity and mortality. The assessment of covert HE (CHE) [i.e. minimal HE (MHE) plus grade 1 HE] is often neglected in Taiwan. Therefore, the aim was to investigate the potential of the animal naming test (ANT1 and simplified ANT1 (S-ANT1)) for assessing CHE in Chinese-speaking regions, specifically Taiwan. A prospective cohort study was conducted, comprising 65 cirrhotic patients and 29 healthy controls (relatives of the patients). Patients were followed up every three months and censored after two years or until death. Hospitalization for overt HE (OHE) and mortality were considered. All subjects underwent ANT1, psychometric HE score (PHES), and mini-mental state examination (MMSE). The patients underwent an electroencephalogram (EEG) to detect slowing indicative of MHE. Cut-off values for ANT1 and S-ANT1 were assessed by ROC analysis and Youden's index, considering CHE as a reference. The prognostic values for OHE and OHE-free survival were assessed. Preliminary analysis confirmed that PHES ≤-4 is a good discriminant point for abnormal results. CHE was found in 29 patients: 9 had MHE (PHES ≤ -4 or altered EEG) and 20 had grade 1 HE. ANT1 and S-ANT1 were found to have diagnostic values for CHE: AUC = 0.807, 0.786; cut off: 18 and 19, respectively. ANT1 and S-ANT1 were found to have prognostic value for OHE, number of hospitalization episodes for OHE, and OHE recurrence-free survival. ANT1 shows promise as a tool for CHE detection, quantification, and follow-up in Taiwan and other Chinese-speaking regions. The animal naming test (ANT1) is a simple and valid semantic fluency test that can be easily performed in outpatient or bedside settings in one minute and can also be used as a tool for covert hepatic encephalopathy (CHE) detection, quantification, and follow-up in Taiwan, other Chinese-speaking regions, and many other countries. The diagnostic value of ANT1 and S-ANT1 for CHE were found to be significant, with area under the receiver operating characteristic curve (AUROC) values of 0.807 and 0.786 respectively, and cut-off scores of 18 and 19. ANT1 and S-ANT1 have prognostic value for the first breakthrough of overt hepatic encephalopathy (OHE), number of hospitalization episodes for OHE, and OHE recurrence-free survival, independent of the MELD score. [ABSTRACT FROM AUTHOR]

Ant colony optimization has insufficient convergence and tends to fall into the local optima when solving the traveling salesman problem. This paper proposes a co-evolutionary multi-colony ant colony optimization (MCGACO) to overcome this deficiency and applies it to the Robot Path Planning. First, a dynamic grouping cooperation algorithm, combined with Ant Colony System and Max-Min Ant System, is introduced to form a heterogeneous multi-population structure. Each population co-evolves and complements each other to improve the overall optimization performance. Second, an adaptive guidance mechanism is proposed to accelerate convergence speed. The mechanism includes two parts: One is a dynamic evaluation network, which is used to evaluate and divide all solutions by the evaluation function. The other is a positive-negative incentive strategy, which can enhance the guiding role of solutions with higher evaluation value. Besides, to jump out of the local optima, an inter-specific co-evolution mechanism based on the game model is proposed. By dynamically determining the optimal communication combination, the diversity among populations can be well balanced. Finally, the experimental results demonstrate that MCGACO outperforms in terms of solution accuracy and convergence. Meanwhile, the proposed algorithm is also feasible for application in Robot Path Planning. [ABSTRACT FROM AUTHOR]

Ant Colony Optimization (ACO) tends to fall into local optima and has insufficient convergence when solving the Traveling Salesman Problem (TSP). To overcome this problem, this paper proposes a multiple ant colony optimization (LDTACO) based on novel Long Short-Term Memory network and adaptive Tanimoto communication strategy. Firstly, we introduce an Artificial Bee Colony-based Ant Colony System (ABC-ACS), which along with the classic Ant Colony System (ACS) and Max-Min Ant System (MMAS), form the final proposed algorithm. These three types of subpopulations complement each other to improve overall optimization performance. Secondly, the evaluation reward mechanism is proposed to enhance the guiding role of the Recommended paths, which can effectively accelerate convergence speed. Besides, an adaptive Tanimoto communication strategy is put forward for interspecific communication. When the algorithm is stagnant, the homogenized information communication method is activated to help the algorithm jump out of the local optima, thus improving solution accuracy. Finally, the experimental results show that the proposed algorithm can lead to more accurate solution accuracy and faster convergence speed. [ABSTRACT FROM AUTHOR]

Leaf-cutting ants are insects of great economic importance which cause economic losses in numerous crops. Compounds that modulate behaviour, and among these natural repellents, show promise in integrated pest management strategies. Tea tree oil has been found to be repellent to certain insect pests, so this study aimed at identifying the effect of tea tree on foraging behaviour in Acromyrmex spp. ants in laboratory as well as in field trials. In laboratory bioassays, a repellent dose response effect of tea tree oil was observed, where concentrations of 0.0001 to 0.1% tea tree did not affect ant behaviour, but concentrations of 1 and 10% repelled ants. In the laboratory, the repellent effect of tea tree was lost after four days and its effect on ant behaviour was evident only at very short distances (less than 1 cm). In the field, ants avoided walking through filter papers treated with tea tree at 1% placed on the foraging trails, and food resources surrounded by tea tree at 1% were not collected. Tea tree is a potent short term leaf-cutting ant repellent and attractive food sources could be protected from leaf-cutting ants attack by this oil. [ABSTRACT FROM AUTHOR]